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</a></div></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Iwao Kanno</h3></div><div class="js-work-strip profile--work_container" data-work-id="124733919"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/124733919/Verb_Generation_in_Japanese_A_Multicenter_PET_Activation_Study"><img alt="Research paper thumbnail of Verb Generation in Japanese—A Multicenter PET Activation Study" class="work-thumbnail" src="https://attachments.academia-assets.com/118904784/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733919/Verb_Generation_in_Japanese_A_Multicenter_PET_Activation_Study">Verb Generation in Japanese—A Multicenter PET Activation Study</a></div><div class="wp-workCard_item"><span>NeuroImage</span><span>, 1999</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1c1cbdbf8be4cf37cf8ef3741a2e84ef" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":118904784,"asset_id":124733919,"asset_type":"Work","button_location":"profile"}" 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Blood Flow","url":"https://www.academia.edu/Documents/in/Cerebral_Blood_Flow"},{"id":1000427,"name":"Reference Values","url":"https://www.academia.edu/Documents/in/Reference_Values"},{"id":1257483,"name":"Frontal Lobe","url":"https://www.academia.edu/Documents/in/Frontal_Lobe"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"},{"id":3922190,"name":"Activity pattern","url":"https://www.academia.edu/Documents/in/Activity_pattern"}],"urls":[{"id":45156267,"url":"https://doi.org/10.1006/nimg.1998.0382"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="124733918"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/124733918/Anatomic_validation_of_spatial_normalization_methods_for_PET"><img alt="Research paper thumbnail of Anatomic validation of spatial normalization methods for PET" class="work-thumbnail" src="https://attachments.academia-assets.com/118904778/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733918/Anatomic_validation_of_spatial_normalization_methods_for_PET">Anatomic validation of spatial normalization methods for PET</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, Feb 1, 1999</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Spatial normalization methods, which are indispensable for intersubject analysis in current PET s...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Spatial normalization methods, which are indispensable for intersubject analysis in current PET studies, have been improved in many aspects. These methods have not necessarily been evaluated as anatomic normalization methods because PET images are functional images. However, in view of the close relation between brain function and morphology, it is very intriguing how precisely normalized brains coincide with each other. In this report, the anatomic precision of spatial normalization is validated with three different methods. Methods: Four PET centers in Japan participated in this study. In each center, six normal subjects were recruited for both H2(15)O-PET and high-resolution MRI studies. Variations in the location of the anterior commissure (AC) and size and contours of the brain and the courses of major sulci were measured in spatially normalized MR images for each method. Spatial normalization was performed as follows. (a) Linear: The AC-posterior commissure and midsagittal plane were identified on MRI and the size of the brain was adjusted to the Talairach space in each axis using linear parameters. (b) Human brain atlas (HBA): Atlas structures were manually adjusted to MRI to determine linear and nonlinear transformation parameters and then MRI was transformed with the inverse of these parameters. (c) Statistical parametric mapping (SPM) 95: PET images were transformed into the template PET image with linear and nonlinear parameters in a least-squares manner. Then, coregistered MR images were transformed with the same parameters used for the PET transformation. Results: The AC was well registered in all methods. The size of the brain normalized with SPM95 varied to a greater extent than with other approaches. Larger variance in contours was observed with the linear method. Only SPM95 showed significant superiority to the linear method when the courses of major sulci were compared. Conclusion: The results of this study indicate that SPM95 is as effective a spatial normalization as HBA, although it does not use anatomic images. Large variance in structures other than the AC and size of the brain in the linear method suggests the necessity of nonlinear transformations for effective spatial normalization. Operator dependency of HBA also must be considered.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="04ba7f2f0d49603689ab0b99278a9e7e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":118904778,"asset_id":124733918,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/118904778/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="124733918"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="124733918"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 124733918; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=124733918]").text(description); $(".js-view-count[data-work-id=124733918]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 124733918; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='124733918']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 124733918, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "04ba7f2f0d49603689ab0b99278a9e7e" } } $('.js-work-strip[data-work-id=124733918]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":124733918,"title":"Anatomic validation of spatial normalization methods for PET","translated_title":"","metadata":{"abstract":"Spatial normalization methods, which are indispensable for intersubject analysis in current PET studies, have been improved in many aspects. These methods have not necessarily been evaluated as anatomic normalization methods because PET images are functional images. However, in view of the close relation between brain function and morphology, it is very intriguing how precisely normalized brains coincide with each other. In this report, the anatomic precision of spatial normalization is validated with three different methods. Methods: Four PET centers in Japan participated in this study. In each center, six normal subjects were recruited for both H2(15)O-PET and high-resolution MRI studies. Variations in the location of the anterior commissure (AC) and size and contours of the brain and the courses of major sulci were measured in spatially normalized MR images for each method. Spatial normalization was performed as follows. (a) Linear: The AC-posterior commissure and midsagittal plane were identified on MRI and the size of the brain was adjusted to the Talairach space in each axis using linear parameters. (b) Human brain atlas (HBA): Atlas structures were manually adjusted to MRI to determine linear and nonlinear transformation parameters and then MRI was transformed with the inverse of these parameters. (c) Statistical parametric mapping (SPM) 95: PET images were transformed into the template PET image with linear and nonlinear parameters in a least-squares manner. Then, coregistered MR images were transformed with the same parameters used for the PET transformation. Results: The AC was well registered in all methods. The size of the brain normalized with SPM95 varied to a greater extent than with other approaches. Larger variance in contours was observed with the linear method. Only SPM95 showed significant superiority to the linear method when the courses of major sulci were compared. Conclusion: The results of this study indicate that SPM95 is as effective a spatial normalization as HBA, although it does not use anatomic images. Large variance in structures other than the AC and size of the brain in the linear method suggests the necessity of nonlinear transformations for effective spatial normalization. Operator dependency of HBA also must be considered.","publication_date":{"day":1,"month":2,"year":1999,"errors":{}},"publication_name":"PubMed"},"translated_abstract":"Spatial normalization methods, which are indispensable for intersubject analysis in current PET studies, have been improved in many aspects. These methods have not necessarily been evaluated as anatomic normalization methods because PET images are functional images. However, in view of the close relation between brain function and morphology, it is very intriguing how precisely normalized brains coincide with each other. In this report, the anatomic precision of spatial normalization is validated with three different methods. Methods: Four PET centers in Japan participated in this study. In each center, six normal subjects were recruited for both H2(15)O-PET and high-resolution MRI studies. Variations in the location of the anterior commissure (AC) and size and contours of the brain and the courses of major sulci were measured in spatially normalized MR images for each method. Spatial normalization was performed as follows. (a) Linear: The AC-posterior commissure and midsagittal plane were identified on MRI and the size of the brain was adjusted to the Talairach space in each axis using linear parameters. (b) Human brain atlas (HBA): Atlas structures were manually adjusted to MRI to determine linear and nonlinear transformation parameters and then MRI was transformed with the inverse of these parameters. (c) Statistical parametric mapping (SPM) 95: PET images were transformed into the template PET image with linear and nonlinear parameters in a least-squares manner. Then, coregistered MR images were transformed with the same parameters used for the PET transformation. Results: The AC was well registered in all methods. The size of the brain normalized with SPM95 varied to a greater extent than with other approaches. Larger variance in contours was observed with the linear method. Only SPM95 showed significant superiority to the linear method when the courses of major sulci were compared. Conclusion: The results of this study indicate that SPM95 is as effective a spatial normalization as HBA, although it does not use anatomic images. Large variance in structures other than the AC and size of the brain in the linear method suggests the necessity of nonlinear transformations for effective spatial normalization. Operator dependency of HBA also must be considered.","internal_url":"https://www.academia.edu/124733918/Anatomic_validation_of_spatial_normalization_methods_for_PET","translated_internal_url":"","created_at":"2024-10-14T22:03:56.322-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":118904778,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/118904778/thumbnails/1.jpg","file_name":"317.pdf","download_url":"https://www.academia.edu/attachments/118904778/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Anatomic_validation_of_spatial_normaliza.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/118904778/317-libre.pdf?1729041039=\u0026response-content-disposition=attachment%3B+filename%3DAnatomic_validation_of_spatial_normaliza.pdf\u0026Expires=1732412448\u0026Signature=Kx2wqJBl9UqcMutniAn6p5V0LfRT1YyAMdimJ9koaCNqCtMIv5EfMHp6CijLrrM54oSJQkW40Wd0jgCYopwadNoczdCcq6HI0EOgilFpbNBtnDIa5kmRllR2lpgXRcGCrZOQH~hI5mF8d8h-Z0ZiYmEkCFUzPA7g7ZgO8T9Qw2zf4~ZPURzBR5sMQKrKJkY2NNbKt9XEyR7fGDjCiCyifv6CO5DGcoTYW3tqkjCIORK4KGgifRL98ajvK6x8pJiTM33hE0HFsz858Cjlszudj4iaZCKa8ixEFfLiNqOiMvNsouwJglv9yo~ucFrhI1IiXczOqzmP78njo3eCXSJfGQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Anatomic_validation_of_spatial_normalization_methods_for_PET","translated_slug":"","page_count":7,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao 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Circuit Based on Digital Signal Processor for Beta Camera" class="work-thumbnail" src="https://attachments.academia-assets.com/118904776/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733917/Artifacts_Suppression_Using_Real_time_Position_Calculation_Circuit_Based_on_Digital_Signal_Processor_for_Beta_Camera">Artifacts Suppression Using Real-time Position Calculation Circuit Based on Digital Signal Processor for Beta Camera</a></div><div class="wp-workCard_item"><span>RADIOISOTOPES</span><span>, 1998</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7c5b2363bf9127427df321109b8c913f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" 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require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "7c5b2363bf9127427df321109b8c913f" } } $('.js-work-strip[data-work-id=124733917]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":124733917,"title":"Artifacts Suppression Using Real-time Position Calculation Circuit Based on Digital Signal Processor for Beta Camera","translated_title":"","metadata":{"publisher":"Japan Radioisotope 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Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":523,"name":"Chemistry","url":"https://www.academia.edu/Documents/in/Chemistry"},{"id":464357,"name":"Digital Signal Processor","url":"https://www.academia.edu/Documents/in/Digital_Signal_Processor"},{"id":967378,"name":"Radioisotopes","url":"https://www.academia.edu/Documents/in/Radioisotopes"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="124733916"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/124733916/Analysis_of_Collimator_System_for_Radionuclide_Computed_Tomography"><img alt="Research paper thumbnail of Analysis of Collimator System for Radionuclide Computed Tomography" class="work-thumbnail" src="https://attachments.academia-assets.com/118904777/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733916/Analysis_of_Collimator_System_for_Radionuclide_Computed_Tomography">Analysis of Collimator System for Radionuclide Computed Tomography</a></div><div class="wp-workCard_item"><span>RADIOISOTOPES</span><span>, 1977</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="78a1111ed50a6c0d71e45c8d9b083e0e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":118904777,"asset_id":124733916,"asset_type":"Work","button_location":"profile"}" 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wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733914/Auditory_visual_speech_perception_examined_by_functional_MRI_and_reaction_time">Auditory-visual speech perception examined by functional MRI and reaction time</a></div><div class="wp-workCard_item"><span>The Journal of the Acoustical Society of America</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In face-to-face communication, auditory and visual speech cues are easily integrated as demonstra...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In face-to-face communication, auditory and visual speech cues are easily integrated as demonstrated by the McGurk effect. The integration processes are investigated by measuring brain activity (fMRI) and reaction time. The subjects were 10 native speakers of Japanese. The stimuli were /ba/, /da/, and /ga/ uttered by three female talkers. The audiovisual stimuli were the McGurk type stimuli consisting of discrepant auditory and visual syllables (e.g., audio /ba/ was combined with video /da/ or /ga/). We compared brain activity during audiovisual speech perception for two sets of conditions differing in the intelligibility of auditory component of speech. In each condition, the subjects were asked to identify spoken syllables. When the auditory speech was intelligible, a brain area for visual motion processing was quiet, whereas the same visual area was active when speech was harder to hear. 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Thus visual information of the mouth movements was processed more intensively when speech was...","publisher":"Acoustical Society of America (ASA)","publication_date":{"day":null,"month":null,"year":2001,"errors":{}},"publication_name":"The Journal of the Acoustical Society of America"},"translated_abstract":"In face-to-face communication, auditory and visual speech cues are easily integrated as demonstrated by the McGurk effect. The integration processes are investigated by measuring brain activity (fMRI) and reaction time. The subjects were 10 native speakers of Japanese. The stimuli were /ba/, /da/, and /ga/ uttered by three female talkers. The audiovisual stimuli were the McGurk type stimuli consisting of discrepant auditory and visual syllables (e.g., audio /ba/ was combined with video /da/ or /ga/). We compared brain activity during audiovisual speech perception for two sets of conditions differing in the intelligibility of auditory component of speech. In each condition, the subjects were asked to identify spoken syllables. When the auditory speech was intelligible, a brain area for visual motion processing was quiet, whereas the same visual area was active when speech was harder to hear. Thus visual information of the mouth movements was processed more intensively when speech was...","internal_url":"https://www.academia.edu/124733914/Auditory_visual_speech_perception_examined_by_functional_MRI_and_reaction_time","translated_internal_url":"","created_at":"2024-10-14T22:03:55.458-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Auditory_visual_speech_perception_examined_by_functional_MRI_and_reaction_time","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":422,"name":"Computer 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href="https://www.academia.edu/124733789/Acute_effects_of_cigarette_smoking_on_global_cerebral_blood_flow_in_overnight_abstinent_tobacco_smokers"><img alt="Research paper thumbnail of Acute effects of cigarette smoking on global cerebral blood flow in overnight abstinent tobacco smokers" class="work-thumbnail" src="https://attachments.academia-assets.com/118904855/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733789/Acute_effects_of_cigarette_smoking_on_global_cerebral_blood_flow_in_overnight_abstinent_tobacco_smokers">Acute effects of cigarette smoking on global cerebral blood flow in overnight abstinent tobacco smokers</a></div><div class="wp-workCard_item"><span>Nicotine & Tobacco Research</span><span>, Feb 1, 2006</span></div><div class="wp-workCard_item 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pharmaceutical sciences","url":"https://www.academia.edu/Documents/in/Pharmacology_and_pharmaceutical_sciences"}],"urls":[{"id":45156198,"url":"https://doi.org/10.1080/14622200500431759"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="121394671"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/121394671/Blood_sampling_devices_and_measurements"><img alt="Research paper thumbnail of Blood sampling devices and measurements" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/121394671/Blood_sampling_devices_and_measurements">Blood sampling devices and measurements</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, 1991</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Quantitative positron emission tomography requires the determination of the tracer concentration ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. By imaging the neck region the time-activity curve of the carotid arteries can be obtained. The PET time-activity curves of the carotid arteries are in good agreement with a conventional experimental input function determined from the radial artery with an automated blood sampling system. However, PET time-activity curves of the radial arteries can not be used without a deconvolution since the resistance in the intact radial artery causes dispersion compared to the input function obtained by invasive methods.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="121394671"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="121394671"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 121394671; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=121394671]").text(description); $(".js-view-count[data-work-id=121394671]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 121394671; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='121394671']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 121394671, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=121394671]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":121394671,"title":"Blood sampling devices and measurements","translated_title":"","metadata":{"abstract":"Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. By imaging the neck region the time-activity curve of the carotid arteries can be obtained. The PET time-activity curves of the carotid arteries are in good agreement with a conventional experimental input function determined from the radial artery with an automated blood sampling system. However, PET time-activity curves of the radial arteries can not be used without a deconvolution since the resistance in the intact radial artery causes dispersion compared to the input function obtained by invasive methods.","publication_date":{"day":null,"month":null,"year":1991,"errors":{}},"publication_name":"PubMed"},"translated_abstract":"Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. By imaging the neck region the time-activity curve of the carotid arteries can be obtained. The PET time-activity curves of the carotid arteries are in good agreement with a conventional experimental input function determined from the radial artery with an automated blood sampling system. However, PET time-activity curves of the radial arteries can not be used without a deconvolution since the resistance in the intact radial artery causes dispersion compared to the input function obtained by invasive methods.","internal_url":"https://www.academia.edu/121394671/Blood_sampling_devices_and_measurements","translated_internal_url":"","created_at":"2024-06-22T23:57:59.885-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Blood_sampling_devices_and_measurements","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":23518,"name":"Positron Emission Tomography","url":"https://www.academia.edu/Documents/in/Positron_Emission_Tomography"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":88383,"name":"Deconvolution","url":"https://www.academia.edu/Documents/in/Deconvolution"},{"id":98939,"name":"Pubmed","url":"https://www.academia.edu/Documents/in/Pubmed"},{"id":103298,"name":"Blood sampling","url":"https://www.academia.edu/Documents/in/Blood_sampling"},{"id":311341,"name":"Radioactive Tracers","url":"https://www.academia.edu/Documents/in/Radioactive_Tracers"},{"id":343667,"name":"Theoretical Models","url":"https://www.academia.edu/Documents/in/Theoretical_Models"},{"id":375439,"name":"Single Photon Emission Computed Tomography","url":"https://www.academia.edu/Documents/in/Single_Photon_Emission_Computed_Tomography"},{"id":413195,"name":"Time Factors","url":"https://www.academia.edu/Documents/in/Time_Factors"},{"id":847988,"name":"Neck","url":"https://www.academia.edu/Documents/in/Neck"},{"id":954130,"name":"Liquid Scintillation Counting","url":"https://www.academia.edu/Documents/in/Liquid_Scintillation_Counting"},{"id":1145520,"name":"Equipment Design","url":"https://www.academia.edu/Documents/in/Equipment_Design"},{"id":1311193,"name":"Wrist","url":"https://www.academia.edu/Documents/in/Wrist"},{"id":2579149,"name":"Carotid Arteries","url":"https://www.academia.edu/Documents/in/Carotid_Arteries"},{"id":3189424,"name":"Blood Specimen Collection","url":"https://www.academia.edu/Documents/in/Blood_Specimen_Collection"}],"urls":[{"id":43164179,"url":"https://pubmed.ncbi.nlm.nih.gov/1839858"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="121394670"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/121394670/Blood_sampling_devices_and_measurements"><img alt="Research paper thumbnail of Blood sampling devices and measurements" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/121394670/Blood_sampling_devices_and_measurements">Blood sampling devices and measurements</a></div><div class="wp-workCard_item"><span>Medical progress through technology</span><span>, 1991</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Quantitative positron emission tomography requires the determination of the tracer concentration ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570580"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570580/Noninvasive_quantitation_of_cerebral_blood_flow_using_oxygen_15_water_and_a_dual_PET_system"><img alt="Research paper thumbnail of Noninvasive quantitation of cerebral blood flow using oxygen-15-water and a dual-PET system" class="work-thumbnail" src="https://attachments.academia-assets.com/114954521/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570580/Noninvasive_quantitation_of_cerebral_blood_flow_using_oxygen_15_water_and_a_dual_PET_system">Noninvasive quantitation of cerebral blood flow using oxygen-15-water and a dual-PET system</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, Oct 1, 1998</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Measurement of the arterial input function is essential for quantitative assessment of physiologi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Measurement of the arterial input function is essential for quantitative assessment of physiological function in vivo using PET. However, frequent arterial blood sampling is invasive and labor intensive. Recently, a PET system has been developed that consists of two independent PET tomographs for simultaneously scanning the brain and heart, which should avoid the need for arterial blood sampling. The aim of this study was to validate noninvasive quantitation with this system for 15O-labeled compounds. Methods: Twelve healthy volunteers underwent a series of PET studies after C15O inhalation and intravenous H2(15)O administration using a Headtome-V-Dual tomograph (Shimadzu Corp., Kyoto, Japan). The C15O study provided gated blood-pool images of the heart simultaneously with quantitative static blood-volume images of both the brain and heart. Weighted-integrated H2(15)O sinograms were acquired for estimating rate constant (K1) and distribution-volume (Vd) images in the brain, in addition to single-frame sinograms for estimating autoradiographic cerebral blood flow images. Noninvasive arterial input functions were determined from the heart scanner (left ventricular chamber) according to a previously developed model and compared directly to invasive input functions measured with an on-line beta probe in six subjects. Results: The noninvasive input functions derived from this PET system were in good agreement with those obtained by continuous arterial blood sampling in all six subjects. There was good agreement between quantitative values obtained noninvasively and those using the invasive input function: average autoradiographic regional cerebral blood flow was 0.412 +/- 0.058 and 0.426 +/- 0.062 ml/min/g, K1 of H2(15)O was 0.416 +/- 0.073 and 0.420 +/- 0.067 ml/min/ml and Vd of H2(15)O was 0.800 +/- 0.080 and 0.830 +/- 0.070 ml/ml for the noninvasive and invasive input functions, respectively. In addition to the brain functional parameters, the system also simultaneously provided cardiac function such as regional myocardial blood flow (0.84 +/- 0.19 ml/min/g), left ventricular volume (132 +/- 22 mm at end diastole and 45 +/- 14 ml at end systole) and ejection fraction (66% +/- 5%). Conclusion: This PET system allows noninvasive quantitation in both the brain and heart simultaneously without arterial cannulation, and may prove useful in clinical research.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ccf4b7694bbcbbac5b072238e9596cc9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954521,"asset_id":119570580,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114954521/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570580"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570580"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570580; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570580]").text(description); $(".js-view-count[data-work-id=119570580]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570580; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570580']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570580, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ccf4b7694bbcbbac5b072238e9596cc9" } } $('.js-work-strip[data-work-id=119570580]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570580,"title":"Noninvasive quantitation of cerebral blood flow using oxygen-15-water and a dual-PET system","translated_title":"","metadata":{"abstract":"Measurement of the arterial input function is essential for quantitative assessment of physiological function in vivo using PET. However, frequent arterial blood sampling is invasive and labor intensive. Recently, a PET system has been developed that consists of two independent PET tomographs for simultaneously scanning the brain and heart, which should avoid the need for arterial blood sampling. The aim of this study was to validate noninvasive quantitation with this system for 15O-labeled compounds. Methods: Twelve healthy volunteers underwent a series of PET studies after C15O inhalation and intravenous H2(15)O administration using a Headtome-V-Dual tomograph (Shimadzu Corp., Kyoto, Japan). The C15O study provided gated blood-pool images of the heart simultaneously with quantitative static blood-volume images of both the brain and heart. Weighted-integrated H2(15)O sinograms were acquired for estimating rate constant (K1) and distribution-volume (Vd) images in the brain, in addition to single-frame sinograms for estimating autoradiographic cerebral blood flow images. Noninvasive arterial input functions were determined from the heart scanner (left ventricular chamber) according to a previously developed model and compared directly to invasive input functions measured with an on-line beta probe in six subjects. Results: The noninvasive input functions derived from this PET system were in good agreement with those obtained by continuous arterial blood sampling in all six subjects. There was good agreement between quantitative values obtained noninvasively and those using the invasive input function: average autoradiographic regional cerebral blood flow was 0.412 +/- 0.058 and 0.426 +/- 0.062 ml/min/g, K1 of H2(15)O was 0.416 +/- 0.073 and 0.420 +/- 0.067 ml/min/ml and Vd of H2(15)O was 0.800 +/- 0.080 and 0.830 +/- 0.070 ml/ml for the noninvasive and invasive input functions, respectively. In addition to the brain functional parameters, the system also simultaneously provided cardiac function such as regional myocardial blood flow (0.84 +/- 0.19 ml/min/g), left ventricular volume (132 +/- 22 mm at end diastole and 45 +/- 14 ml at end systole) and ejection fraction (66% +/- 5%). Conclusion: This PET system allows noninvasive quantitation in both the brain and heart simultaneously without arterial cannulation, and may prove useful in clinical research.","publication_date":{"day":1,"month":10,"year":1998,"errors":{}},"publication_name":"PubMed"},"translated_abstract":"Measurement of the arterial input function is essential for quantitative assessment of physiological function in vivo using PET. However, frequent arterial blood sampling is invasive and labor intensive. Recently, a PET system has been developed that consists of two independent PET tomographs for simultaneously scanning the brain and heart, which should avoid the need for arterial blood sampling. The aim of this study was to validate noninvasive quantitation with this system for 15O-labeled compounds. Methods: Twelve healthy volunteers underwent a series of PET studies after C15O inhalation and intravenous H2(15)O administration using a Headtome-V-Dual tomograph (Shimadzu Corp., Kyoto, Japan). The C15O study provided gated blood-pool images of the heart simultaneously with quantitative static blood-volume images of both the brain and heart. Weighted-integrated H2(15)O sinograms were acquired for estimating rate constant (K1) and distribution-volume (Vd) images in the brain, in addition to single-frame sinograms for estimating autoradiographic cerebral blood flow images. Noninvasive arterial input functions were determined from the heart scanner (left ventricular chamber) according to a previously developed model and compared directly to invasive input functions measured with an on-line beta probe in six subjects. Results: The noninvasive input functions derived from this PET system were in good agreement with those obtained by continuous arterial blood sampling in all six subjects. There was good agreement between quantitative values obtained noninvasively and those using the invasive input function: average autoradiographic regional cerebral blood flow was 0.412 +/- 0.058 and 0.426 +/- 0.062 ml/min/g, K1 of H2(15)O was 0.416 +/- 0.073 and 0.420 +/- 0.067 ml/min/ml and Vd of H2(15)O was 0.800 +/- 0.080 and 0.830 +/- 0.070 ml/ml for the noninvasive and invasive input functions, respectively. In addition to the brain functional parameters, the system also simultaneously provided cardiac function such as regional myocardial blood flow (0.84 +/- 0.19 ml/min/g), left ventricular volume (132 +/- 22 mm at end diastole and 45 +/- 14 ml at end systole) and ejection fraction (66% +/- 5%). Conclusion: This PET system allows noninvasive quantitation in both the brain and heart simultaneously without arterial cannulation, and may prove useful in clinical 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true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570579"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570579/Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation"><img alt="Research paper thumbnail of Influence of ANOVA Design and Anatomical Standardization on Statistical Mapping for PET Activation" class="work-thumbnail" src="https://attachments.academia-assets.com/114954551/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570579/Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation">Influence of ANOVA Design and Anatomical Standardization on Statistical Mapping for PET Activation</a></div><div class="wp-workCard_item"><span>NeuroImage</span><span>, Oct 1, 1998</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="96065421944e9cc8fc4789034065a0b6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954551,"asset_id":119570579,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114954551/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span 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Data were acquired in four PET centers. In each center, CBF was measured on six normal male subjects under resting and covert verb generation, three times for each. The images were anatomically standardized with LINEAR transformation, SPM (Ver. 95), HBA (Karolinska/Tohoku), or MICHIGAN (Minoshima). ANOVA was performed pixel by pixel to compute t (and z) for the task main effect (Verb vs Rest) in four different designs: (i) two way (subject and task) (2W), (ii) two-way with interaction (2WI), (iii) subject considered a random factor (2WI-MX), and (iv) threeway (subject, task, and replication) (3W). A large area extending from the Broca to the left premotor cortex was activated. The localization of the highest peak depended both on the anatomical standardization and on the ANOVA design, the variation ranging 3-4 cm. Smoothing reduced the variation while erasing possible subfoci. The z images of 2W, 2WI, and 3W looked alike, whereas 2WI-MX presented lower peak z values. SPM tended to present higher z values than the other methods. The error was high in the gray and low in the white matter. The root mean square for the subject effect was high on the border of gray matter especially in LINEAR and HBA, revealing intersubject mismatch in the gray matter distribution. The root mean square for the subject-by-task interaction effect revealed individual variation in activation. 1998 Academic Press","publication_date":{"day":1,"month":10,"year":1998,"errors":{}},"publication_name":"NeuroImage","grobid_abstract_attachment_id":114954551},"translated_abstract":null,"internal_url":"https://www.academia.edu/119570579/Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation","translated_internal_url":"","created_at":"2024-05-19T17:59:30.770-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":114954551,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/114954551/thumbnails/1.jpg","file_name":"nimg.1998.037020240520-1-3ej8.pdf","download_url":"https://www.academia.edu/attachments/114954551/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Influence_of_ANOVA_Design_and_Anatomical.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/114954551/nimg.1998.037020240520-1-3ej8-libre.pdf?1716167436=\u0026response-content-disposition=attachment%3B+filename%3DInfluence_of_ANOVA_Design_and_Anatomical.pdf\u0026Expires=1732412448\u0026Signature=M-fAO9NZAC3kmgKtNe6-g0ZUblvr5hNqL07pC4mNk0hd0LioUzFAU9SgqUk9HRHjdIIdFIkQD3yURSOSvkX5dliP2R32KGuIIPoaVfG4Qcvgzgl9HfRot1dbBTajTkqmtbjQxh6o9q8ixIWws4EqISZwo8ZBGlCkagUJfiI6WsP4~cfIDuYJ9j6XwPKJvpZJJGw~WaTjPpsgU5Bw48tXUo7cIlbH2b9ruGN~t~SZPJa1PJMoT5djC5SYjVigH-lYu9qAV687CT9SKOKyH~OGJxik046Y~7QuorwMVfZ8FoGCdmZQfGGmCIHOGXTJd~XePoxZk84BbuLriHlEU9~MAw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation","translated_slug":"","page_count":19,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570578"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570578/Quantitative_analysis_of_dopamine_transporters_in_human_brain_using_11C_PE2I_and_positron_emission_tomography_evaluation_of_reference_tissue_models"><img alt="Research paper thumbnail of Quantitative analysis of dopamine transporters in human brain using [11C]PE2I and positron emission tomography: evaluation of reference tissue models" class="work-thumbnail" src="https://attachments.academia-assets.com/114954630/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570578/Quantitative_analysis_of_dopamine_transporters_in_human_brain_using_11C_PE2I_and_positron_emission_tomography_evaluation_of_reference_tissue_models">Quantitative analysis of dopamine transporters in human brain using [11C]PE2I and positron emission tomography: evaluation of reference tissue models</a></div><div class="wp-workCard_item"><span>Annals of Nuclear Medicine</span><span>, Apr 3, 2010</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c8b787ee26fd5d2bba65e708309638cb" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954630,"asset_id":119570578,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114954630/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa 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})(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "c8b787ee26fd5d2bba65e708309638cb" } } $('.js-work-strip[data-work-id=119570578]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570578,"title":"Quantitative analysis of dopamine transporters in human brain using [11C]PE2I and positron emission tomography: evaluation of reference tissue models","translated_title":"","metadata":{"publisher":"Springer Nature","grobid_abstract":"Objective Dopamine transporter (DAT) is a reuptake carrier of dopamine at presynapse that regulates dopaminergic neural transmission. [ 11 C]PE2I is a cocaine analog developed as a potent positron emission tomography (PET) ligand for DAT with high selectivity. The aim of this study was to evaluate the applicability of quantification methods using reference tissue models for [ 11 C]PE2I. Methods Dynamic PET scans were performed in 6 young healthy male volunteers after an intravenous bolus injection of [ 11 C]PE2I. Metabolite-corrected arterial plasma-input functions were obtained. Compartment model analysis and plasma-input Logan analysis were performed to determine the kinetic parameters and distribution volume (V T). The distribution volume ratio (DVR) was calculated as the ratio of V T in the cerebral region to that in the cerebellum. DVRs were also determined by the original multilinear reference tissue model method (MRTMo) and the simplified reference tissue model method (SRTM), comparing the results with those obtained from graphical analysis using arterial input function. To estimate errors in DVR calculated using the reference tissue model, a simulation study that focused on cerebellar kinetics and scan duration was performed. Results The highest [ 11 C]PE2I binding was observed in the striatum, followed by the midbrain and thalamus. The 2-tissue model was preferable to the 1-tissue model for describing the [ 11 C]PE2I kinetics in the cerebellum. Both the measured and 90-min simulated data showed that reference tissue models caused an underestimation of DVR in the striatum. The simulation showed that 90-min scan duration was insufficient when cerebellar kinetics was described as a 1-tissue model. Nevertheless, DVR values determined by MRTMo and SRTM were in good agreement with those by the graphical approach in other lower binding regions. Conclusion Due to the [ 11 C]PE2I kinetics in the cerebellum and limited scan duration for 11 C, MRTMo and SRTM underestimated the striatal DVR. Despite this limitation, the present study demonstrated the applicability of reference tissue models. Since DAT in the midbrain and thalamus is of interest in the pathophysiology of neuropsychiatric disease, this noninvasive quantitative analysis will be useful for clinical investigations.","publication_date":{"day":3,"month":4,"year":2010,"errors":{}},"publication_name":"Annals of Nuclear 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metabolic rate of oxygen measured by positron emission tomography with 15 O-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in Japan" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570577/Database_of_normal_human_cerebral_blood_flow_cerebral_blood_volume_cerebral_oxygen_extraction_fraction_and_cerebral_metabolic_rate_of_oxygen_measured_by_positron_emission_tomography_with_15_O_labelled_carbon_dioxide_or_water_carbon_monoxide_and_oxygen_a_multicentre_study_in_Japan">Database of normal human cerebral blood flow, cerebral blood volume, cerebral oxygen extraction fraction and cerebral metabolic rate of oxygen measured by positron emission tomography with 15 O-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in Japan</a></div><div class="wp-workCard_item"><span>European Journal of Nuclear Medicine and Molecular Imaging</span><span>, May 1, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO(2)) by positron emission tomography (PET) with oxygen-15 labelled carbon dioxide (C(15)O(2)) or (15)O-labelled water (H(2)(15)O), (15)O-labelled carbon monoxide (C(15)O) and (15)O-labelled oxygen ((15)O(2)) is useful for diagnosis and treatment planning in cases of cerebrovascular disease. The measured values theoretically depend on various factors, which may differ between PET centres. This study explored the applicability of a database of (15)O-PET by examining between-centre and within-centre variation in values. Eleven PET centres participated in this multicentre study; seven used the steady-state inhalation method, one used build-up inhalation and three used bolus administration of C(15)O(2) (or H(2)(15)O) and (15)O(2). All used C(15)O for measurement of CBV. Subjects comprised 70 healthy volunteers (43 men and 27 women; mean age 51.8+/-15.1 years). Overall mean+/-SD values for cerebral cortical regions were: CBF=44.4+/-6.5 ml 100 ml(-1) min(-1); CBV=3.8+/-0.7 ml 100 ml(-1); OEF=0.44+/-0.06; CMRO(2)=3.3+/-0.5 ml 100 ml(-1) min(-1). Significant between-centre variation was observed in CBV, OEF and CMRO(2) by one-way analysis of variance. However, the overall inter-individual variation in CBF, CBV, OEF and CMRO(2) was acceptably small. Building a database of normal cerebral haemodynamics obtained by the(15)O-PET methods may be practicable.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570577"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570577"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570577; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570577]").text(description); $(".js-view-count[data-work-id=119570577]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570577; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570577']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570577, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=119570577]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570577,"title":"Database of normal human cerebral blood flow, cerebral blood volume, cerebral oxygen extraction fraction and cerebral metabolic rate of oxygen measured by positron emission tomography with 15 O-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in Japan","translated_title":"","metadata":{"abstract":"Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO(2)) by positron emission tomography (PET) with oxygen-15 labelled carbon dioxide (C(15)O(2)) or (15)O-labelled water (H(2)(15)O), (15)O-labelled carbon monoxide (C(15)O) and (15)O-labelled oxygen ((15)O(2)) is useful for diagnosis and treatment planning in cases of cerebrovascular disease. The measured values theoretically depend on various factors, which may differ between PET centres. This study explored the applicability of a database of (15)O-PET by examining between-centre and within-centre variation in values. Eleven PET centres participated in this multicentre study; seven used the steady-state inhalation method, one used build-up inhalation and three used bolus administration of C(15)O(2) (or H(2)(15)O) and (15)O(2). All used C(15)O for measurement of CBV. Subjects comprised 70 healthy volunteers (43 men and 27 women; mean age 51.8+/-15.1 years). Overall mean+/-SD values for cerebral cortical regions were: CBF=44.4+/-6.5 ml 100 ml(-1) min(-1); CBV=3.8+/-0.7 ml 100 ml(-1); OEF=0.44+/-0.06; CMRO(2)=3.3+/-0.5 ml 100 ml(-1) min(-1). Significant between-centre variation was observed in CBV, OEF and CMRO(2) by one-way analysis of variance. However, the overall inter-individual variation in CBF, CBV, OEF and CMRO(2) was acceptably small. Building a database of normal cerebral haemodynamics obtained by the(15)O-PET methods may be practicable.","publisher":"Springer Science+Business Media","publication_date":{"day":1,"month":5,"year":2004,"errors":{}},"publication_name":"European Journal of Nuclear Medicine and Molecular Imaging"},"translated_abstract":"Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO(2)) by positron emission tomography (PET) with oxygen-15 labelled carbon dioxide (C(15)O(2)) or (15)O-labelled water (H(2)(15)O), (15)O-labelled carbon monoxide (C(15)O) and (15)O-labelled oxygen ((15)O(2)) is useful for diagnosis and treatment planning in cases of cerebrovascular disease. The measured values theoretically depend on various factors, which may differ between PET centres. This study explored the applicability of a database of (15)O-PET by examining between-centre and within-centre variation in values. Eleven PET centres participated in this multicentre study; seven used the steady-state inhalation method, one used build-up inhalation and three used bolus administration of C(15)O(2) (or H(2)(15)O) and (15)O(2). All used C(15)O for measurement of CBV. Subjects comprised 70 healthy volunteers (43 men and 27 women; mean age 51.8+/-15.1 years). Overall mean+/-SD values for cerebral cortical regions were: CBF=44.4+/-6.5 ml 100 ml(-1) min(-1); CBV=3.8+/-0.7 ml 100 ml(-1); OEF=0.44+/-0.06; CMRO(2)=3.3+/-0.5 ml 100 ml(-1) min(-1). Significant between-centre variation was observed in CBV, OEF and CMRO(2) by one-way analysis of variance. However, the overall inter-individual variation in CBF, CBV, OEF and CMRO(2) was acceptably small. Building a database of normal cerebral haemodynamics obtained by the(15)O-PET methods may be practicable.","internal_url":"https://www.academia.edu/119570577/Database_of_normal_human_cerebral_blood_flow_cerebral_blood_volume_cerebral_oxygen_extraction_fraction_and_cerebral_metabolic_rate_of_oxygen_measured_by_positron_emission_tomography_with_15_O_labelled_carbon_dioxide_or_water_carbon_monoxide_and_oxygen_a_multicentre_study_in_Japan","translated_internal_url":"","created_at":"2024-05-19T17:59:30.357-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Database_of_normal_human_cerebral_blood_flow_cerebral_blood_volume_cerebral_oxygen_extraction_fraction_and_cerebral_metabolic_rate_of_oxygen_measured_by_positron_emission_tomography_with_15_O_labelled_carbon_dioxide_or_water_carbon_monoxide_and_oxygen_a_multicentre_study_in_Japan","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":4594,"name":"Carbon Dioxide","url":"https://www.academia.edu/Documents/in/Carbon_Dioxide"},{"id":10035,"name":"Nuclear medicine","url":"https://www.academia.edu/Documents/in/Nuclear_medicine"},{"id":17158,"name":"Japan","url":"https://www.academia.edu/Documents/in/Japan"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":61474,"name":"Brain","url":"https://www.academia.edu/Documents/in/Brain"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":71905,"name":"Carbon Monoxide","url":"https://www.academia.edu/Documents/in/Carbon_Monoxide"},{"id":91905,"name":"Cerebrovascular Disease","url":"https://www.academia.edu/Documents/in/Cerebrovascular_Disease"},{"id":98925,"name":"Female","url":"https://www.academia.edu/Documents/in/Female"},{"id":111545,"name":"Male","url":"https://www.academia.edu/Documents/in/Male"},{"id":198377,"name":"Individual variation","url":"https://www.academia.edu/Documents/in/Individual_variation"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences"},{"id":295155,"name":"Middle Aged","url":"https://www.academia.edu/Documents/in/Middle_Aged"},{"id":296766,"name":"Metabolic rate","url":"https://www.academia.edu/Documents/in/Metabolic_rate"},{"id":380825,"name":"Oxygen","url":"https://www.academia.edu/Documents/in/Oxygen"},{"id":394395,"name":"Inhalation","url":"https://www.academia.edu/Documents/in/Inhalation"},{"id":413194,"name":"Analysis of Variance","url":"https://www.academia.edu/Documents/in/Analysis_of_Variance"},{"id":970066,"name":"Cerebral Blood Flow","url":"https://www.academia.edu/Documents/in/Cerebral_Blood_Flow"},{"id":1193624,"name":"Oxygen Consumption","url":"https://www.academia.edu/Documents/in/Oxygen_Consumption"},{"id":2763984,"name":"Cerebral Blood Volume","url":"https://www.academia.edu/Documents/in/Cerebral_Blood_Volume"}],"urls":[{"id":42118151,"url":"https://doi.org/10.1007/s00259-003-1430-8"}]}, dispatcherData: dispatcherData }); 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and &lt;sup&gt;15&lt;/sup&gt;O&lt;sub&gt;2&lt;/sub&gt</a></div><div class="wp-workCard_item"><span>Japanese Journal of Radiological Technology</span><span>, 1998</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4226220f87a8b74cb5a4d006abf2f0cd" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954519,"asset_id":119570576,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114954519/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570576"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570576"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570576; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570574"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570574/Uncoupling_of_Absolute_CBF_to_Neural_Activity"><img alt="Research paper thumbnail of Uncoupling of Absolute CBF to Neural Activity" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570574/Uncoupling_of_Absolute_CBF_to_Neural_Activity">Uncoupling of Absolute CBF to Neural Activity</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 1997</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Since Roy and Sherrington (1890) described that neural activity would regulate blood supply to th...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Since Roy and Sherrington (1890) described that neural activity would regulate blood supply to the brain, it has been widely accepted that neural activation will increase cerebral blood flow (CBF). Lassen and Munck (1955) first demonstrated the regional change of CBF at the cortical areas using radioisotopes. The recent development of technology, e.g. positron emission tomography (PET), has allowed us to measure quantitative CBF at every cubic centimeter of the brain. 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Lassen and Munck (1955) first demonstrated the regional change of CBF at the cortical areas using radioisotopes. The recent development of technology, e.g. positron emission tomography (PET), has allowed us to measure quantitative CBF at every cubic centimeter of the brain. However, most of psychophysiological brain mapping studies mainly utilize the topographic information to delineate CBF change by canceling out quantitative information of CBF in the process of the statistical analysis to evaluate regional CBF change relating to the neural activity (Friston et al. 1990).","publisher":"Springer Nature","publication_date":{"day":null,"month":null,"year":1997,"errors":{}},"publication_name":"Springer eBooks"},"translated_abstract":"Since Roy and Sherrington (1890) described that neural activity would regulate blood supply to the brain, it has been widely accepted that neural activation will increase cerebral blood flow (CBF). 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However, most of psychophysiological brain mapping studies mainly utilize the topographic information to delineate CBF change by canceling out quantitative information of CBF in the process of the statistical analysis to evaluate regional CBF change relating to the neural activity (Friston et al. 1990).","internal_url":"https://www.academia.edu/119570574/Uncoupling_of_Absolute_CBF_to_Neural_Activity","translated_internal_url":"","created_at":"2024-05-19T17:59:29.045-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Uncoupling_of_Absolute_CBF_to_Neural_Activity","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":4594,"name":"Carbon Dioxide","url":"https://www.academia.edu/Documents/in/Carbon_Dioxide"},{"id":7710,"name":"Biology","url":"https://www.academia.edu/Documents/in/Biology"},{"id":23518,"name":"Positron Emission Tomography","url":"https://www.academia.edu/Documents/in/Positron_Emission_Tomography"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":52176,"name":"Brain Mapping","url":"https://www.academia.edu/Documents/in/Brain_Mapping"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":154388,"name":"Hyperventilation","url":"https://www.academia.edu/Documents/in/Hyperventilation"},{"id":292405,"name":"Neural Activity","url":"https://www.academia.edu/Documents/in/Neural_Activity"},{"id":375439,"name":"Single Photon Emission Computed Tomography","url":"https://www.academia.edu/Documents/in/Single_Photon_Emission_Computed_Tomography"},{"id":469105,"name":"Retrospective Studies","url":"https://www.academia.edu/Documents/in/Retrospective_Studies"},{"id":970066,"name":"Cerebral Blood Flow","url":"https://www.academia.edu/Documents/in/Cerebral_Blood_Flow"},{"id":1000427,"name":"Reference Values","url":"https://www.academia.edu/Documents/in/Reference_Values"},{"id":2849038,"name":"photic stimulation","url":"https://www.academia.edu/Documents/in/photic_stimulation"},{"id":3647879,"name":"Springer Ebooks","url":"https://www.academia.edu/Documents/in/Springer_Ebooks"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":42118148,"url":"https://doi.org/10.1007/978-1-4899-0056-2_23"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570573"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570573/Regional_correlations_between_the_EEG_and_oxygen_metabolism_in_dementia_of_Alzheimers_type"><img alt="Research paper thumbnail of Regional correlations between the EEG and oxygen metabolism in dementia of Alzheimer's type" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570573/Regional_correlations_between_the_EEG_and_oxygen_metabolism_in_dementia_of_Alzheimers_type">Regional correlations between the EEG and oxygen metabolism in dementia of Alzheimer's type</a></div><div class="wp-workCard_item"><span>Electroencephalography and Clinical Neurophysiology</span><span>, Sep 1, 1997</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">To determine the relationship between EEG slowing and cerebral hypometabolism in dementia, 10 pat...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">To determine the relationship between EEG slowing and cerebral hypometabolism in dementia, 10 patients with dementia of Alzheimer&amp;#39;s type (DAT) were evaluated with quantitative topographic EEG and positron emission tomography (PET). Power in each 1-Hz frequency band from 2-20 Hz, power ratio index, and normalised PET data from corresponding cortical sites were compared to data obtained from 20 normal volunteers. PET revealed significant parieto-temporal hypometabolism, and topographic EEG mapping and power spectrum analysis revealed a slowing of the background EEG that was most pronounced in the parietal-temporal areas. Correlation analysis between EEG power spectrum data and CMRO2 revealed significant negative correlations for frequencies below 8 Hz and significant positive correlations above 8 Hz in the parieto-temporal regions, which have previously been identified as the areas most severely affected by pathological changes associated with DAT. Correlation coefficients plotted as functions of frequency illustrated the relationships between EEG changes and reduced CMRO2, supporting previous views that EEG slowing in DAT may be related to hypometabolism in cortical regions most affected by the disease.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570573"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570573"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570573; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570573]").text(description); $(".js-view-count[data-work-id=119570573]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570573; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570573']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570573, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=119570573]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570573,"title":"Regional correlations between the EEG and oxygen metabolism in dementia of Alzheimer's type","translated_title":"","metadata":{"abstract":"To determine the relationship between EEG slowing and cerebral hypometabolism in dementia, 10 patients with dementia of Alzheimer\u0026amp;#39;s type (DAT) were evaluated with quantitative topographic EEG and positron emission tomography (PET). Power in each 1-Hz frequency band from 2-20 Hz, power ratio index, and normalised PET data from corresponding cortical sites were compared to data obtained from 20 normal volunteers. PET revealed significant parieto-temporal hypometabolism, and topographic EEG mapping and power spectrum analysis revealed a slowing of the background EEG that was most pronounced in the parietal-temporal areas. Correlation analysis between EEG power spectrum data and CMRO2 revealed significant negative correlations for frequencies below 8 Hz and significant positive correlations above 8 Hz in the parieto-temporal regions, which have previously been identified as the areas most severely affected by pathological changes associated with DAT. Correlation coefficients plotted as functions of frequency illustrated the relationships between EEG changes and reduced CMRO2, supporting previous views that EEG slowing in DAT may be related to hypometabolism in cortical regions most affected by the disease.","publisher":"Elsevier BV","publication_date":{"day":1,"month":9,"year":1997,"errors":{}},"publication_name":"Electroencephalography and Clinical Neurophysiology"},"translated_abstract":"To determine the relationship between EEG slowing and cerebral hypometabolism in dementia, 10 patients with dementia of Alzheimer\u0026amp;#39;s type (DAT) were evaluated with quantitative topographic EEG and positron emission tomography (PET). Power in each 1-Hz frequency band from 2-20 Hz, power ratio index, and normalised PET data from corresponding cortical sites were compared to data obtained from 20 normal volunteers. PET revealed significant parieto-temporal hypometabolism, and topographic EEG mapping and power spectrum analysis revealed a slowing of the background EEG that was most pronounced in the parietal-temporal areas. Correlation analysis between EEG power spectrum data and CMRO2 revealed significant negative correlations for frequencies below 8 Hz and significant positive correlations above 8 Hz in the parieto-temporal regions, which have previously been identified as the areas most severely affected by pathological changes associated with DAT. Correlation coefficients plotted as functions of frequency illustrated the relationships between EEG changes and reduced CMRO2, supporting previous views that EEG slowing in DAT may be related to hypometabolism in cortical regions most affected by the disease.","internal_url":"https://www.academia.edu/119570573/Regional_correlations_between_the_EEG_and_oxygen_metabolism_in_dementia_of_Alzheimers_type","translated_internal_url":"","created_at":"2024-05-19T17:59:28.692-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Regional_correlations_between_the_EEG_and_oxygen_metabolism_in_dementia_of_Alzheimers_type","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":3662,"name":"Dementia","url":"https://www.academia.edu/Documents/in/Dementia"},{"id":10904,"name":"Electroencephalography","url":"https://www.academia.edu/Documents/in/Electroencephalography"},{"id":23518,"name":"Positron Emission Tomography","url":"https://www.academia.edu/Documents/in/Positron_Emission_Tomography"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":36213,"name":"Energy Metabolism","url":"https://www.academia.edu/Documents/in/Energy_Metabolism"},{"id":52176,"name":"Brain Mapping","url":"https://www.academia.edu/Documents/in/Brain_Mapping"},{"id":61474,"name":"Brain","url":"https://www.academia.edu/Documents/in/Brain"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":81504,"name":"Correlation","url":"https://www.academia.edu/Documents/in/Correlation"},{"id":98925,"name":"Female","url":"https://www.academia.edu/Documents/in/Female"},{"id":111545,"name":"Male","url":"https://www.academia.edu/Documents/in/Male"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged"},{"id":295155,"name":"Middle Aged","url":"https://www.academia.edu/Documents/in/Middle_Aged"},{"id":380825,"name":"Oxygen","url":"https://www.academia.edu/Documents/in/Oxygen"},{"id":386999,"name":"Power Spectrum","url":"https://www.academia.edu/Documents/in/Power_Spectrum"},{"id":410595,"name":"Correlation Analysis","url":"https://www.academia.edu/Documents/in/Correlation_Analysis"},{"id":611814,"name":"Correlation coefficient","url":"https://www.academia.edu/Documents/in/Correlation_coefficient"},{"id":1120234,"name":"Alzheimer Disease","url":"https://www.academia.edu/Documents/in/Alzheimer_Disease"},{"id":2736308,"name":"Frequency spectrum","url":"https://www.academia.edu/Documents/in/Frequency_spectrum"}],"urls":[{"id":42118147,"url":"https://doi.org/10.1016/s0013-4694(97)00015-5"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570571"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570571/Error_and_t_Images_Depend_on_ANOVA_Design_and_Anatomical_Standardization_in_PET_Activation_Analysis_1_1Transcripts_of_the_BRAINPET97_discussion_of_this_chapter_can_be_found_in_Section_VIII"><img alt="Research paper thumbnail of Error and t Images Depend on ANOVA Design and Anatomical Standardization in PET Activation Analysis 1 1Transcripts of the BRAINPET97 discussion of this chapter can be found in Section VIII" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570571/Error_and_t_Images_Depend_on_ANOVA_Design_and_Anatomical_Standardization_in_PET_Activation_Analysis_1_1Transcripts_of_the_BRAINPET97_discussion_of_this_chapter_can_be_found_in_Section_VIII">Error and t Images Depend on ANOVA Design and Anatomical Standardization in PET Activation Analysis 1 1Transcripts of the BRAINPET97 discussion of this chapter can be found in Section VIII</a></div><div class="wp-workCard_item"><span>Elsevier eBooks</span><span>, 1998</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In a positron emission tomography activation analysis with task replications within subject, a nu...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In a positron emission tomography activation analysis with task replications within subject, a number of analysis of variance (ANOVA) designs are applicable with different definitions of t and error. The characteristics of t (and z) maps and error images and how they depend on the ANOVA design and on the anatomical standardization method have been investigated. Six subjects underwent measurement of regional cerebral blood flow with [15O]water under resting and while thinking of verbs associated with auditorily presented nouns, three times for each. The images were anatomically standardized with LINear, SPM95, or HBA. ANOVA was performed pixel by pixel to compute t statistics for the task main effect (verb vs rest) in four different ANOVA designs: (i) two way (subject and task) (2W), (ii) two way with interaction (2WI), (iii) two way with interaction, except that the “subject” was considered a random factor (2WI-RF), and (iv) three way (subject, task, and replication). The left frontal cortex extending from Broca&#39;s area to the premotor cortex was activated by the verb generation. The foci localization in the z images depended both on the anatomical standardization method and on the ANOVA design, and the variation ranged from 1 to 3 cm. SPM tended to present a higher peak z than LIN and HBA. The z images of 2W and 2WI looked alike, but 2WI-RF and 3W each presented a different z map within the activated area. The peak z score by 2WI-RF was lower than the others. The error images for 2W, 2WI, and 3W were heterogeneous, being high in gray and low in white.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570571"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570571"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570571; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570571]").text(description); $(".js-view-count[data-work-id=119570571]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570571; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570571']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570571, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=119570571]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570571,"title":"Error and t Images Depend on ANOVA Design and Anatomical Standardization in PET Activation Analysis 1 1Transcripts of the BRAINPET97 discussion of this chapter can be found in Section VIII","translated_title":"","metadata":{"abstract":"In a positron emission tomography activation analysis with task replications within subject, a number of analysis of variance (ANOVA) designs are applicable with different definitions of t and error. The characteristics of t (and z) maps and error images and how they depend on the ANOVA design and on the anatomical standardization method have been investigated. Six subjects underwent measurement of regional cerebral blood flow with [15O]water under resting and while thinking of verbs associated with auditorily presented nouns, three times for each. The images were anatomically standardized with LINear, SPM95, or HBA. ANOVA was performed pixel by pixel to compute t statistics for the task main effect (verb vs rest) in four different ANOVA designs: (i) two way (subject and task) (2W), (ii) two way with interaction (2WI), (iii) two way with interaction, except that the “subject” was considered a random factor (2WI-RF), and (iv) three way (subject, task, and replication). The left frontal cortex extending from Broca\u0026#39;s area to the premotor cortex was activated by the verb generation. The foci localization in the z images depended both on the anatomical standardization method and on the ANOVA design, and the variation ranged from 1 to 3 cm. SPM tended to present a higher peak z than LIN and HBA. The z images of 2W and 2WI looked alike, but 2WI-RF and 3W each presented a different z map within the activated area. The peak z score by 2WI-RF was lower than the others. The error images for 2W, 2WI, and 3W were heterogeneous, being high in gray and low in white.","publisher":"Elsevier BV","publication_date":{"day":null,"month":null,"year":1998,"errors":{}},"publication_name":"Elsevier eBooks"},"translated_abstract":"In a positron emission tomography activation analysis with task replications within subject, a number of analysis of variance (ANOVA) designs are applicable with different definitions of t and error. The characteristics of t (and z) maps and error images and how they depend on the ANOVA design and on the anatomical standardization method have been investigated. Six subjects underwent measurement of regional cerebral blood flow with [15O]water under resting and while thinking of verbs associated with auditorily presented nouns, three times for each. The images were anatomically standardized with LINear, SPM95, or HBA. ANOVA was performed pixel by pixel to compute t statistics for the task main effect (verb vs rest) in four different ANOVA designs: (i) two way (subject and task) (2W), (ii) two way with interaction (2WI), (iii) two way with interaction, except that the “subject” was considered a random factor (2WI-RF), and (iv) three way (subject, task, and replication). The left frontal cortex extending from Broca\u0026#39;s area to the premotor cortex was activated by the verb generation. 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The error images for 2W, 2WI, and 3W were heterogeneous, being high in gray and low in white.","internal_url":"https://www.academia.edu/119570571/Error_and_t_Images_Depend_on_ANOVA_Design_and_Anatomical_Standardization_in_PET_Activation_Analysis_1_1Transcripts_of_the_BRAINPET97_discussion_of_this_chapter_can_be_found_in_Section_VIII","translated_internal_url":"","created_at":"2024-05-19T17:59:28.067-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Error_and_t_Images_Depend_on_ANOVA_Design_and_Anatomical_Standardization_in_PET_Activation_Analysis_1_1Transcripts_of_the_BRAINPET97_discussion_of_this_chapter_can_be_found_in_Section_VIII","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao 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class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/124733919/Verb_Generation_in_Japanese_A_Multicenter_PET_Activation_Study"><img alt="Research paper thumbnail of Verb Generation in Japanese—A Multicenter PET Activation Study" class="work-thumbnail" src="https://attachments.academia-assets.com/118904784/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733919/Verb_Generation_in_Japanese_A_Multicenter_PET_Activation_Study">Verb Generation in Japanese—A Multicenter PET Activation Study</a></div><div class="wp-workCard_item"><span>NeuroImage</span><span>, 1999</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1c1cbdbf8be4cf37cf8ef3741a2e84ef" 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hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/124733918/Anatomic_validation_of_spatial_normalization_methods_for_PET"><img alt="Research paper thumbnail of Anatomic validation of spatial normalization methods for PET" class="work-thumbnail" src="https://attachments.academia-assets.com/118904778/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733918/Anatomic_validation_of_spatial_normalization_methods_for_PET">Anatomic validation of spatial normalization methods for PET</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, Feb 1, 1999</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Spatial normalization methods, which are indispensable for intersubject analysis in current PET s...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Spatial normalization methods, which are indispensable for intersubject analysis in current PET studies, have been improved in many aspects. These methods have not necessarily been evaluated as anatomic normalization methods because PET images are functional images. However, in view of the close relation between brain function and morphology, it is very intriguing how precisely normalized brains coincide with each other. In this report, the anatomic precision of spatial normalization is validated with three different methods. Methods: Four PET centers in Japan participated in this study. In each center, six normal subjects were recruited for both H2(15)O-PET and high-resolution MRI studies. Variations in the location of the anterior commissure (AC) and size and contours of the brain and the courses of major sulci were measured in spatially normalized MR images for each method. Spatial normalization was performed as follows. (a) Linear: The AC-posterior commissure and midsagittal plane were identified on MRI and the size of the brain was adjusted to the Talairach space in each axis using linear parameters. (b) Human brain atlas (HBA): Atlas structures were manually adjusted to MRI to determine linear and nonlinear transformation parameters and then MRI was transformed with the inverse of these parameters. (c) Statistical parametric mapping (SPM) 95: PET images were transformed into the template PET image with linear and nonlinear parameters in a least-squares manner. Then, coregistered MR images were transformed with the same parameters used for the PET transformation. Results: The AC was well registered in all methods. The size of the brain normalized with SPM95 varied to a greater extent than with other approaches. Larger variance in contours was observed with the linear method. Only SPM95 showed significant superiority to the linear method when the courses of major sulci were compared. Conclusion: The results of this study indicate that SPM95 is as effective a spatial normalization as HBA, although it does not use anatomic images. Large variance in structures other than the AC and size of the brain in the linear method suggests the necessity of nonlinear transformations for effective spatial normalization. Operator dependency of HBA also must be considered.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="04ba7f2f0d49603689ab0b99278a9e7e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":118904778,"asset_id":124733918,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/118904778/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="124733918"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="124733918"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 124733918; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=124733918]").text(description); $(".js-view-count[data-work-id=124733918]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 124733918; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='124733918']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 124733918, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "04ba7f2f0d49603689ab0b99278a9e7e" } } $('.js-work-strip[data-work-id=124733918]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":124733918,"title":"Anatomic validation of spatial normalization methods for PET","translated_title":"","metadata":{"abstract":"Spatial normalization methods, which are indispensable for intersubject analysis in current PET studies, have been improved in many aspects. 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(b) Human brain atlas (HBA): Atlas structures were manually adjusted to MRI to determine linear and nonlinear transformation parameters and then MRI was transformed with the inverse of these parameters. (c) Statistical parametric mapping (SPM) 95: PET images were transformed into the template PET image with linear and nonlinear parameters in a least-squares manner. Then, coregistered MR images were transformed with the same parameters used for the PET transformation. Results: The AC was well registered in all methods. The size of the brain normalized with SPM95 varied to a greater extent than with other approaches. Larger variance in contours was observed with the linear method. Only SPM95 showed significant superiority to the linear method when the courses of major sulci were compared. Conclusion: The results of this study indicate that SPM95 is as effective a spatial normalization as HBA, although it does not use anatomic images. Large variance in structures other than the AC and size of the brain in the linear method suggests the necessity of nonlinear transformations for effective spatial normalization. Operator dependency of HBA also must be considered.","publication_date":{"day":1,"month":2,"year":1999,"errors":{}},"publication_name":"PubMed"},"translated_abstract":"Spatial normalization methods, which are indispensable for intersubject analysis in current PET studies, have been improved in many aspects. These methods have not necessarily been evaluated as anatomic normalization methods because PET images are functional images. However, in view of the close relation between brain function and morphology, it is very intriguing how precisely normalized brains coincide with each other. In this report, the anatomic precision of spatial normalization is validated with three different methods. Methods: Four PET centers in Japan participated in this study. In each center, six normal subjects were recruited for both H2(15)O-PET and high-resolution MRI studies. Variations in the location of the anterior commissure (AC) and size and contours of the brain and the courses of major sulci were measured in spatially normalized MR images for each method. Spatial normalization was performed as follows. (a) Linear: The AC-posterior commissure and midsagittal plane were identified on MRI and the size of the brain was adjusted to the Talairach space in each axis using linear parameters. (b) Human brain atlas (HBA): Atlas structures were manually adjusted to MRI to determine linear and nonlinear transformation parameters and then MRI was transformed with the inverse of these parameters. (c) Statistical parametric mapping (SPM) 95: PET images were transformed into the template PET image with linear and nonlinear parameters in a least-squares manner. Then, coregistered MR images were transformed with the same parameters used for the PET transformation. 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wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/124733914/Auditory_visual_speech_perception_examined_by_functional_MRI_and_reaction_time">Auditory-visual speech perception examined by functional MRI and reaction time</a></div><div class="wp-workCard_item"><span>The Journal of the Acoustical Society of America</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In face-to-face communication, auditory and visual speech cues are easily integrated as demonstra...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In face-to-face communication, auditory and visual speech cues are easily integrated as demonstrated by the McGurk effect. The integration processes are investigated by measuring brain activity (fMRI) and reaction time. The subjects were 10 native speakers of Japanese. The stimuli were /ba/, /da/, and /ga/ uttered by three female talkers. The audiovisual stimuli were the McGurk type stimuli consisting of discrepant auditory and visual syllables (e.g., audio /ba/ was combined with video /da/ or /ga/). We compared brain activity during audiovisual speech perception for two sets of conditions differing in the intelligibility of auditory component of speech. In each condition, the subjects were asked to identify spoken syllables. When the auditory speech was intelligible, a brain area for visual motion processing was quiet, whereas the same visual area was active when speech was harder to hear. 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data-click-track="profile-work-strip-title" href="https://www.academia.edu/121394671/Blood_sampling_devices_and_measurements">Blood sampling devices and measurements</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, 1991</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Quantitative positron emission tomography requires the determination of the tracer concentration ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. By imaging the neck region the time-activity curve of the carotid arteries can be obtained. The PET time-activity curves of the carotid arteries are in good agreement with a conventional experimental input function determined from the radial artery with an automated blood sampling system. However, PET time-activity curves of the radial arteries can not be used without a deconvolution since the resistance in the intact radial artery causes dispersion compared to the input function obtained by invasive methods.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="121394671"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="121394671"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 121394671; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=121394671]").text(description); $(".js-view-count[data-work-id=121394671]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 121394671; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='121394671']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 121394671, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=121394671]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":121394671,"title":"Blood sampling devices and measurements","translated_title":"","metadata":{"abstract":"Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. By imaging the neck region the time-activity curve of the carotid arteries can be obtained. The PET time-activity curves of the carotid arteries are in good agreement with a conventional experimental input function determined from the radial artery with an automated blood sampling system. However, PET time-activity curves of the radial arteries can not be used without a deconvolution since the resistance in the intact radial artery causes dispersion compared to the input function obtained by invasive methods.","publication_date":{"day":null,"month":null,"year":1991,"errors":{}},"publication_name":"PubMed"},"translated_abstract":"Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. 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However, PET time-activity curves of the radial arteries can not be used without a deconvolution since the resistance in the intact radial artery causes dispersion compared to the input function obtained by invasive methods.","internal_url":"https://www.academia.edu/121394671/Blood_sampling_devices_and_measurements","translated_internal_url":"","created_at":"2024-06-22T23:57:59.885-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Blood_sampling_devices_and_measurements","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":23518,"name":"Positron Emission Tomography","url":"https://www.academia.edu/Documents/in/Positron_Emission_Tomography"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":88383,"name":"Deconvolution","url":"https://www.academia.edu/Documents/in/Deconvolution"},{"id":98939,"name":"Pubmed","url":"https://www.academia.edu/Documents/in/Pubmed"},{"id":103298,"name":"Blood sampling","url":"https://www.academia.edu/Documents/in/Blood_sampling"},{"id":311341,"name":"Radioactive Tracers","url":"https://www.academia.edu/Documents/in/Radioactive_Tracers"},{"id":343667,"name":"Theoretical Models","url":"https://www.academia.edu/Documents/in/Theoretical_Models"},{"id":375439,"name":"Single Photon Emission Computed Tomography","url":"https://www.academia.edu/Documents/in/Single_Photon_Emission_Computed_Tomography"},{"id":413195,"name":"Time Factors","url":"https://www.academia.edu/Documents/in/Time_Factors"},{"id":847988,"name":"Neck","url":"https://www.academia.edu/Documents/in/Neck"},{"id":954130,"name":"Liquid Scintillation Counting","url":"https://www.academia.edu/Documents/in/Liquid_Scintillation_Counting"},{"id":1145520,"name":"Equipment Design","url":"https://www.academia.edu/Documents/in/Equipment_Design"},{"id":1311193,"name":"Wrist","url":"https://www.academia.edu/Documents/in/Wrist"},{"id":2579149,"name":"Carotid Arteries","url":"https://www.academia.edu/Documents/in/Carotid_Arteries"},{"id":3189424,"name":"Blood Specimen Collection","url":"https://www.academia.edu/Documents/in/Blood_Specimen_Collection"}],"urls":[{"id":43164179,"url":"https://pubmed.ncbi.nlm.nih.gov/1839858"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="121394670"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/121394670/Blood_sampling_devices_and_measurements"><img alt="Research paper thumbnail of Blood sampling devices and measurements" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/121394670/Blood_sampling_devices_and_measurements">Blood sampling devices and measurements</a></div><div class="wp-workCard_item"><span>Medical progress through technology</span><span>, 1991</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Quantitative positron emission tomography requires the determination of the tracer concentration ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. By imaging the neck region the time-activity curve of the carotid arteries can be...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="121394670"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="121394670"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 121394670; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=121394670]").text(description); $(".js-view-count[data-work-id=121394670]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 121394670; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='121394670']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 121394670, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=121394670]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":121394670,"title":"Blood sampling devices and measurements","translated_title":"","metadata":{"abstract":"Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. 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By imaging the neck region the time-activity curve of the carotid arteries can be...","publication_date":{"day":null,"month":null,"year":1991,"errors":{}},"publication_name":"Medical progress through technology"},"translated_abstract":"Quantitative positron emission tomography requires the determination of the tracer concentration in arterial plasma or full blood as a function of time. This defines the experimental input function. The model prediction, with which the positron camera regional time-activity curves are compared, is given by the experimental input function convoluted with the model. This paper reviews different strategies for determining the input function, invasive techniques, such as manual blood sampling and the use of automated blood sampling systems, and non-invasive techniques. The importance of corrections is discussed, such as accurate cross-calibrations of the different detectors used in quantitative PET and corrections for differences in time phase between the regional PET time-activity curves and the input function. We also report on the use of a PET system in non-invasive determinations of the input function. By imaging the neck region the time-activity curve of the carotid arteries can be...","internal_url":"https://www.academia.edu/121394670/Blood_sampling_devices_and_measurements","translated_internal_url":"","created_at":"2024-06-22T23:57:59.757-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Blood_sampling_devices_and_measurements","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":23518,"name":"Positron Emission Tomography","url":"https://www.academia.edu/Documents/in/Positron_Emission_Tomography"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":88383,"name":"Deconvolution","url":"https://www.academia.edu/Documents/in/Deconvolution"},{"id":98939,"name":"Pubmed","url":"https://www.academia.edu/Documents/in/Pubmed"},{"id":103298,"name":"Blood sampling","url":"https://www.academia.edu/Documents/in/Blood_sampling"},{"id":311341,"name":"Radioactive Tracers","url":"https://www.academia.edu/Documents/in/Radioactive_Tracers"},{"id":343667,"name":"Theoretical Models","url":"https://www.academia.edu/Documents/in/Theoretical_Models"},{"id":375439,"name":"Single Photon Emission Computed Tomography","url":"https://www.academia.edu/Documents/in/Single_Photon_Emission_Computed_Tomography"},{"id":413195,"name":"Time Factors","url":"https://www.academia.edu/Documents/in/Time_Factors"},{"id":847988,"name":"Neck","url":"https://www.academia.edu/Documents/in/Neck"},{"id":954130,"name":"Liquid Scintillation Counting","url":"https://www.academia.edu/Documents/in/Liquid_Scintillation_Counting"},{"id":1145520,"name":"Equipment Design","url":"https://www.academia.edu/Documents/in/Equipment_Design"},{"id":1311193,"name":"Wrist","url":"https://www.academia.edu/Documents/in/Wrist"},{"id":2579149,"name":"Carotid Arteries","url":"https://www.academia.edu/Documents/in/Carotid_Arteries"},{"id":3189424,"name":"Blood Specimen Collection","url":"https://www.academia.edu/Documents/in/Blood_Specimen_Collection"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="121394669"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/121394669/Pet_activation_study_Methodology"><img alt="Research paper thumbnail of Pet activation study: Methodology" class="work-thumbnail" src="https://attachments.academia-assets.com/116283518/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/121394669/Pet_activation_study_Methodology">Pet activation study: Methodology</a></div><div class="wp-workCard_item"><span>Neuroscience Research Supplements</span><span>, 1994</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6a21cbbb0cdd4549f8d0ea9276b59890" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":116283518,"asset_id":121394669,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/116283518/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="121394669"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="121394669"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 121394669; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="121394668"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/121394668/Quantitative_aspects_of_neurovascular_interaction"><img alt="Research paper thumbnail of Quantitative aspects of neurovascular interaction" class="work-thumbnail" src="https://attachments.academia-assets.com/116283517/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/121394668/Quantitative_aspects_of_neurovascular_interaction">Quantitative aspects of neurovascular interaction</a></div><div class="wp-workCard_item"><span>International Congress Series</span><span>, 2003</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="058c8fe341ef272f51d7fe6635636940" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":116283517,"asset_id":121394668,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/116283517/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="121394668"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="121394668"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 121394668; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570580"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570580/Noninvasive_quantitation_of_cerebral_blood_flow_using_oxygen_15_water_and_a_dual_PET_system"><img alt="Research paper thumbnail of Noninvasive quantitation of cerebral blood flow using oxygen-15-water and a dual-PET system" class="work-thumbnail" src="https://attachments.academia-assets.com/114954521/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570580/Noninvasive_quantitation_of_cerebral_blood_flow_using_oxygen_15_water_and_a_dual_PET_system">Noninvasive quantitation of cerebral blood flow using oxygen-15-water and a dual-PET system</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, Oct 1, 1998</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Measurement of the arterial input function is essential for quantitative assessment of physiologi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Measurement of the arterial input function is essential for quantitative assessment of physiological function in vivo using PET. However, frequent arterial blood sampling is invasive and labor intensive. Recently, a PET system has been developed that consists of two independent PET tomographs for simultaneously scanning the brain and heart, which should avoid the need for arterial blood sampling. The aim of this study was to validate noninvasive quantitation with this system for 15O-labeled compounds. Methods: Twelve healthy volunteers underwent a series of PET studies after C15O inhalation and intravenous H2(15)O administration using a Headtome-V-Dual tomograph (Shimadzu Corp., Kyoto, Japan). The C15O study provided gated blood-pool images of the heart simultaneously with quantitative static blood-volume images of both the brain and heart. Weighted-integrated H2(15)O sinograms were acquired for estimating rate constant (K1) and distribution-volume (Vd) images in the brain, in addition to single-frame sinograms for estimating autoradiographic cerebral blood flow images. Noninvasive arterial input functions were determined from the heart scanner (left ventricular chamber) according to a previously developed model and compared directly to invasive input functions measured with an on-line beta probe in six subjects. Results: The noninvasive input functions derived from this PET system were in good agreement with those obtained by continuous arterial blood sampling in all six subjects. There was good agreement between quantitative values obtained noninvasively and those using the invasive input function: average autoradiographic regional cerebral blood flow was 0.412 +/- 0.058 and 0.426 +/- 0.062 ml/min/g, K1 of H2(15)O was 0.416 +/- 0.073 and 0.420 +/- 0.067 ml/min/ml and Vd of H2(15)O was 0.800 +/- 0.080 and 0.830 +/- 0.070 ml/ml for the noninvasive and invasive input functions, respectively. In addition to the brain functional parameters, the system also simultaneously provided cardiac function such as regional myocardial blood flow (0.84 +/- 0.19 ml/min/g), left ventricular volume (132 +/- 22 mm at end diastole and 45 +/- 14 ml at end systole) and ejection fraction (66% +/- 5%). Conclusion: This PET system allows noninvasive quantitation in both the brain and heart simultaneously without arterial cannulation, and may prove useful in clinical research.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ccf4b7694bbcbbac5b072238e9596cc9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954521,"asset_id":119570580,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114954521/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570580"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570580"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570580; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570580]").text(description); $(".js-view-count[data-work-id=119570580]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570580; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570580']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570580, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ccf4b7694bbcbbac5b072238e9596cc9" } } $('.js-work-strip[data-work-id=119570580]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570580,"title":"Noninvasive quantitation of cerebral blood flow using oxygen-15-water and a dual-PET system","translated_title":"","metadata":{"abstract":"Measurement of the arterial input function is essential for quantitative assessment of physiological function in vivo using PET. However, frequent arterial blood sampling is invasive and labor intensive. Recently, a PET system has been developed that consists of two independent PET tomographs for simultaneously scanning the brain and heart, which should avoid the need for arterial blood sampling. The aim of this study was to validate noninvasive quantitation with this system for 15O-labeled compounds. Methods: Twelve healthy volunteers underwent a series of PET studies after C15O inhalation and intravenous H2(15)O administration using a Headtome-V-Dual tomograph (Shimadzu Corp., Kyoto, Japan). The C15O study provided gated blood-pool images of the heart simultaneously with quantitative static blood-volume images of both the brain and heart. Weighted-integrated H2(15)O sinograms were acquired for estimating rate constant (K1) and distribution-volume (Vd) images in the brain, in addition to single-frame sinograms for estimating autoradiographic cerebral blood flow images. Noninvasive arterial input functions were determined from the heart scanner (left ventricular chamber) according to a previously developed model and compared directly to invasive input functions measured with an on-line beta probe in six subjects. Results: The noninvasive input functions derived from this PET system were in good agreement with those obtained by continuous arterial blood sampling in all six subjects. There was good agreement between quantitative values obtained noninvasively and those using the invasive input function: average autoradiographic regional cerebral blood flow was 0.412 +/- 0.058 and 0.426 +/- 0.062 ml/min/g, K1 of H2(15)O was 0.416 +/- 0.073 and 0.420 +/- 0.067 ml/min/ml and Vd of H2(15)O was 0.800 +/- 0.080 and 0.830 +/- 0.070 ml/ml for the noninvasive and invasive input functions, respectively. In addition to the brain functional parameters, the system also simultaneously provided cardiac function such as regional myocardial blood flow (0.84 +/- 0.19 ml/min/g), left ventricular volume (132 +/- 22 mm at end diastole and 45 +/- 14 ml at end systole) and ejection fraction (66% +/- 5%). Conclusion: This PET system allows noninvasive quantitation in both the brain and heart simultaneously without arterial cannulation, and may prove useful in clinical research.","publication_date":{"day":1,"month":10,"year":1998,"errors":{}},"publication_name":"PubMed"},"translated_abstract":"Measurement of the arterial input function is essential for quantitative assessment of physiological function in vivo using PET. However, frequent arterial blood sampling is invasive and labor intensive. Recently, a PET system has been developed that consists of two independent PET tomographs for simultaneously scanning the brain and heart, which should avoid the need for arterial blood sampling. The aim of this study was to validate noninvasive quantitation with this system for 15O-labeled compounds. Methods: Twelve healthy volunteers underwent a series of PET studies after C15O inhalation and intravenous H2(15)O administration using a Headtome-V-Dual tomograph (Shimadzu Corp., Kyoto, Japan). The C15O study provided gated blood-pool images of the heart simultaneously with quantitative static blood-volume images of both the brain and heart. Weighted-integrated H2(15)O sinograms were acquired for estimating rate constant (K1) and distribution-volume (Vd) images in the brain, in addition to single-frame sinograms for estimating autoradiographic cerebral blood flow images. Noninvasive arterial input functions were determined from the heart scanner (left ventricular chamber) according to a previously developed model and compared directly to invasive input functions measured with an on-line beta probe in six subjects. Results: The noninvasive input functions derived from this PET system were in good agreement with those obtained by continuous arterial blood sampling in all six subjects. There was good agreement between quantitative values obtained noninvasively and those using the invasive input function: average autoradiographic regional cerebral blood flow was 0.412 +/- 0.058 and 0.426 +/- 0.062 ml/min/g, K1 of H2(15)O was 0.416 +/- 0.073 and 0.420 +/- 0.067 ml/min/ml and Vd of H2(15)O was 0.800 +/- 0.080 and 0.830 +/- 0.070 ml/ml for the noninvasive and invasive input functions, respectively. In addition to the brain functional parameters, the system also simultaneously provided cardiac function such as regional myocardial blood flow (0.84 +/- 0.19 ml/min/g), left ventricular volume (132 +/- 22 mm at end diastole and 45 +/- 14 ml at end systole) and ejection fraction (66% +/- 5%). Conclusion: This PET system allows noninvasive quantitation in both the brain and heart simultaneously without arterial cannulation, and may prove useful in clinical research.","internal_url":"https://www.academia.edu/119570580/Noninvasive_quantitation_of_cerebral_blood_flow_using_oxygen_15_water_and_a_dual_PET_system","translated_internal_url":"","created_at":"2024-05-19T17:59:30.985-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":114954521,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/114954521/thumbnails/1.jpg","file_name":"1789.full.pdf","download_url":"https://www.academia.edu/attachments/114954521/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Noninvasive_quantitation_of_cerebral_blo.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/114954521/1789.full-libre.pdf?1716167451=\u0026response-content-disposition=attachment%3B+filename%3DNoninvasive_quantitation_of_cerebral_blo.pdf\u0026Expires=1732362037\u0026Signature=LJ1cLZD6yj0OMn8nmRipxDA3Um7SwbWWfgwMePxW7z790s36xDNyj1YoGsfoDEr~yPJQ7uM0asD83rUWKlwq51WdxNZ0e~QPqi7ZTfgjBVO3lQDIj3OGCQjSHzZtKH-b82PND1Kyut3LhDL0RePpn3yzR7DJBX-wwmrVXf8Hh59o3q4sT~zZzzENWR5AOijeUYxnmAOnnXrem~s~Y9hGrS1CpOxqINq46w8YJNNiTD-vQbq5w3XvjsVhKDvBhmxpVyDHReQYD4yMibD7FQf5sDI4PeXI5Ekvw2bvsrxsXaDrQyKqcvtsOX3lteXrPJxUGiczmFq2GK2Dg9WtIx6PIw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Noninvasive_quantitation_of_cerebral_blood_flow_using_oxygen_15_water_and_a_dual_PET_system","translated_slug":"","page_count":10,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao 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true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570579"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570579/Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation"><img alt="Research paper thumbnail of Influence of ANOVA Design and Anatomical Standardization on Statistical Mapping for PET Activation" class="work-thumbnail" src="https://attachments.academia-assets.com/114954551/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570579/Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation">Influence of ANOVA Design and Anatomical Standardization on Statistical Mapping for PET Activation</a></div><div class="wp-workCard_item"><span>NeuroImage</span><span>, Oct 1, 1998</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="96065421944e9cc8fc4789034065a0b6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954551,"asset_id":119570579,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114954551/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: 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{ var workId = 119570579; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570579']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570579, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = 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Data were acquired in four PET centers. In each center, CBF was measured on six normal male subjects under resting and covert verb generation, three times for each. The images were anatomically standardized with LINEAR transformation, SPM (Ver. 95), HBA (Karolinska/Tohoku), or MICHIGAN (Minoshima). ANOVA was performed pixel by pixel to compute t (and z) for the task main effect (Verb vs Rest) in four different designs: (i) two way (subject and task) (2W), (ii) two-way with interaction (2WI), (iii) subject considered a random factor (2WI-MX), and (iv) threeway (subject, task, and replication) (3W). A large area extending from the Broca to the left premotor cortex was activated. The localization of the highest peak depended both on the anatomical standardization and on the ANOVA design, the variation ranging 3-4 cm. Smoothing reduced the variation while erasing possible subfoci. The z images of 2W, 2WI, and 3W looked alike, whereas 2WI-MX presented lower peak z values. SPM tended to present higher z values than the other methods. The error was high in the gray and low in the white matter. The root mean square for the subject effect was high on the border of gray matter especially in LINEAR and HBA, revealing intersubject mismatch in the gray matter distribution. The root mean square for the subject-by-task interaction effect revealed individual variation in activation. 1998 Academic Press","publication_date":{"day":1,"month":10,"year":1998,"errors":{}},"publication_name":"NeuroImage","grobid_abstract_attachment_id":114954551},"translated_abstract":null,"internal_url":"https://www.academia.edu/119570579/Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation","translated_internal_url":"","created_at":"2024-05-19T17:59:30.770-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":114954551,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/114954551/thumbnails/1.jpg","file_name":"nimg.1998.037020240520-1-3ej8.pdf","download_url":"https://www.academia.edu/attachments/114954551/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Influence_of_ANOVA_Design_and_Anatomical.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/114954551/nimg.1998.037020240520-1-3ej8-libre.pdf?1716167436=\u0026response-content-disposition=attachment%3B+filename%3DInfluence_of_ANOVA_Design_and_Anatomical.pdf\u0026Expires=1732412448\u0026Signature=M-fAO9NZAC3kmgKtNe6-g0ZUblvr5hNqL07pC4mNk0hd0LioUzFAU9SgqUk9HRHjdIIdFIkQD3yURSOSvkX5dliP2R32KGuIIPoaVfG4Qcvgzgl9HfRot1dbBTajTkqmtbjQxh6o9q8ixIWws4EqISZwo8ZBGlCkagUJfiI6WsP4~cfIDuYJ9j6XwPKJvpZJJGw~WaTjPpsgU5Bw48tXUo7cIlbH2b9ruGN~t~SZPJa1PJMoT5djC5SYjVigH-lYu9qAV687CT9SKOKyH~OGJxik046Y~7QuorwMVfZ8FoGCdmZQfGGmCIHOGXTJd~XePoxZk84BbuLriHlEU9~MAw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Influence_of_ANOVA_Design_and_Anatomical_Standardization_on_Statistical_Mapping_for_PET_Activation","translated_slug":"","page_count":19,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570578"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570578/Quantitative_analysis_of_dopamine_transporters_in_human_brain_using_11C_PE2I_and_positron_emission_tomography_evaluation_of_reference_tissue_models"><img alt="Research paper thumbnail of Quantitative analysis of dopamine transporters in human brain using [11C]PE2I and positron emission tomography: evaluation of reference tissue models" class="work-thumbnail" src="https://attachments.academia-assets.com/114954630/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570578/Quantitative_analysis_of_dopamine_transporters_in_human_brain_using_11C_PE2I_and_positron_emission_tomography_evaluation_of_reference_tissue_models">Quantitative analysis of dopamine transporters in human brain using [11C]PE2I and positron emission tomography: evaluation of reference tissue models</a></div><div class="wp-workCard_item"><span>Annals of Nuclear Medicine</span><span>, Apr 3, 2010</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c8b787ee26fd5d2bba65e708309638cb" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954630,"asset_id":119570578,"asset_type":"Work","button_location":"profile"}" 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})(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "c8b787ee26fd5d2bba65e708309638cb" } } $('.js-work-strip[data-work-id=119570578]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570578,"title":"Quantitative analysis of dopamine transporters in human brain using [11C]PE2I and positron emission tomography: evaluation of reference tissue models","translated_title":"","metadata":{"publisher":"Springer Nature","grobid_abstract":"Objective Dopamine transporter (DAT) is a reuptake carrier of dopamine at presynapse that regulates dopaminergic neural transmission. [ 11 C]PE2I is a cocaine analog developed as a potent positron emission tomography (PET) ligand for DAT with high selectivity. The aim of this study was to evaluate the applicability of quantification methods using reference tissue models for [ 11 C]PE2I. Methods Dynamic PET scans were performed in 6 young healthy male volunteers after an intravenous bolus injection of [ 11 C]PE2I. Metabolite-corrected arterial plasma-input functions were obtained. Compartment model analysis and plasma-input Logan analysis were performed to determine the kinetic parameters and distribution volume (V T). The distribution volume ratio (DVR) was calculated as the ratio of V T in the cerebral region to that in the cerebellum. DVRs were also determined by the original multilinear reference tissue model method (MRTMo) and the simplified reference tissue model method (SRTM), comparing the results with those obtained from graphical analysis using arterial input function. To estimate errors in DVR calculated using the reference tissue model, a simulation study that focused on cerebellar kinetics and scan duration was performed. Results The highest [ 11 C]PE2I binding was observed in the striatum, followed by the midbrain and thalamus. The 2-tissue model was preferable to the 1-tissue model for describing the [ 11 C]PE2I kinetics in the cerebellum. Both the measured and 90-min simulated data showed that reference tissue models caused an underestimation of DVR in the striatum. The simulation showed that 90-min scan duration was insufficient when cerebellar kinetics was described as a 1-tissue model. Nevertheless, DVR values determined by MRTMo and SRTM were in good agreement with those by the graphical approach in other lower binding regions. Conclusion Due to the [ 11 C]PE2I kinetics in the cerebellum and limited scan duration for 11 C, MRTMo and SRTM underestimated the striatal DVR. Despite this limitation, the present study demonstrated the applicability of reference tissue models. Since DAT in the midbrain and thalamus is of interest in the pathophysiology of neuropsychiatric disease, this noninvasive quantitative analysis will be useful for clinical investigations.","publication_date":{"day":3,"month":4,"year":2010,"errors":{}},"publication_name":"Annals of Nuclear 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medicine","url":"https://www.academia.edu/Documents/in/Nuclear_medicine"},{"id":23518,"name":"Positron Emission Tomography","url":"https://www.academia.edu/Documents/in/Positron_Emission_Tomography"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":37434,"name":"Quantitative analysis","url":"https://www.academia.edu/Documents/in/Quantitative_analysis"},{"id":51566,"name":"Dopamine","url":"https://www.academia.edu/Documents/in/Dopamine"},{"id":61474,"name":"Brain","url":"https://www.academia.edu/Documents/in/Brain"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":111545,"name":"Male","url":"https://www.academia.edu/Documents/in/Male"},{"id":203010,"name":"Human Brain","url":"https://www.academia.edu/Documents/in/Human_Brain"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences"},{"id":382075,"name":"Adult","url":"https://www.academia.edu/Documents/in/Adult"},{"id":429223,"name":"Dopamine Transporter","url":"https://www.academia.edu/Documents/in/Dopamine_Transporter"},{"id":509785,"name":"Simulation Study","url":"https://www.academia.edu/Documents/in/Simulation_Study"},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results"},{"id":641216,"name":"Quantitative Analysis","url":"https://www.academia.edu/Documents/in/Quantitative_Analysis-1"},{"id":1000427,"name":"Reference Values","url":"https://www.academia.edu/Documents/in/Reference_Values"},{"id":1167882,"name":"Kinetic Parameter","url":"https://www.academia.edu/Documents/in/Kinetic_Parameter"},{"id":2562018,"name":"Arteries","url":"https://www.academia.edu/Documents/in/Arteries"},{"id":3476481,"name":"Compartment Model","url":"https://www.academia.edu/Documents/in/Compartment_Model"}],"urls":[{"id":42118152,"url":"https://doi.org/10.1007/s12149-010-0364-z"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570577"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570577/Database_of_normal_human_cerebral_blood_flow_cerebral_blood_volume_cerebral_oxygen_extraction_fraction_and_cerebral_metabolic_rate_of_oxygen_measured_by_positron_emission_tomography_with_15_O_labelled_carbon_dioxide_or_water_carbon_monoxide_and_oxygen_a_multicentre_study_in_Japan"><img alt="Research paper thumbnail of Database of normal human cerebral blood flow, cerebral blood volume, cerebral oxygen extraction fraction and cerebral metabolic rate of oxygen measured by positron emission tomography with 15 O-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in Japan" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570577/Database_of_normal_human_cerebral_blood_flow_cerebral_blood_volume_cerebral_oxygen_extraction_fraction_and_cerebral_metabolic_rate_of_oxygen_measured_by_positron_emission_tomography_with_15_O_labelled_carbon_dioxide_or_water_carbon_monoxide_and_oxygen_a_multicentre_study_in_Japan">Database of normal human cerebral blood flow, cerebral blood volume, cerebral oxygen extraction fraction and cerebral metabolic rate of oxygen measured by positron emission tomography with 15 O-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in Japan</a></div><div class="wp-workCard_item"><span>European Journal of Nuclear Medicine and Molecular Imaging</span><span>, May 1, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO(2)) by positron emission tomography (PET) with oxygen-15 labelled carbon dioxide (C(15)O(2)) or (15)O-labelled water (H(2)(15)O), (15)O-labelled carbon monoxide (C(15)O) and (15)O-labelled oxygen ((15)O(2)) is useful for diagnosis and treatment planning in cases of cerebrovascular disease. The measured values theoretically depend on various factors, which may differ between PET centres. This study explored the applicability of a database of (15)O-PET by examining between-centre and within-centre variation in values. Eleven PET centres participated in this multicentre study; seven used the steady-state inhalation method, one used build-up inhalation and three used bolus administration of C(15)O(2) (or H(2)(15)O) and (15)O(2). All used C(15)O for measurement of CBV. Subjects comprised 70 healthy volunteers (43 men and 27 women; mean age 51.8+/-15.1 years). Overall mean+/-SD values for cerebral cortical regions were: CBF=44.4+/-6.5 ml 100 ml(-1) min(-1); CBV=3.8+/-0.7 ml 100 ml(-1); OEF=0.44+/-0.06; CMRO(2)=3.3+/-0.5 ml 100 ml(-1) min(-1). Significant between-centre variation was observed in CBV, OEF and CMRO(2) by one-way analysis of variance. However, the overall inter-individual variation in CBF, CBV, OEF and CMRO(2) was acceptably small. Building a database of normal cerebral haemodynamics obtained by the(15)O-PET methods may be practicable.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570577"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570577"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570577; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570577]").text(description); $(".js-view-count[data-work-id=119570577]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570577; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570577']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570577, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=119570577]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570577,"title":"Database of normal human cerebral blood flow, cerebral blood volume, cerebral oxygen extraction fraction and cerebral metabolic rate of oxygen measured by positron emission tomography with 15 O-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in Japan","translated_title":"","metadata":{"abstract":"Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO(2)) by positron emission tomography (PET) with oxygen-15 labelled carbon dioxide (C(15)O(2)) or (15)O-labelled water (H(2)(15)O), (15)O-labelled carbon monoxide (C(15)O) and (15)O-labelled oxygen ((15)O(2)) is useful for diagnosis and treatment planning in cases of cerebrovascular disease. The measured values theoretically depend on various factors, which may differ between PET centres. This study explored the applicability of a database of (15)O-PET by examining between-centre and within-centre variation in values. Eleven PET centres participated in this multicentre study; seven used the steady-state inhalation method, one used build-up inhalation and three used bolus administration of C(15)O(2) (or H(2)(15)O) and (15)O(2). All used C(15)O for measurement of CBV. Subjects comprised 70 healthy volunteers (43 men and 27 women; mean age 51.8+/-15.1 years). Overall mean+/-SD values for cerebral cortical regions were: CBF=44.4+/-6.5 ml 100 ml(-1) min(-1); CBV=3.8+/-0.7 ml 100 ml(-1); OEF=0.44+/-0.06; CMRO(2)=3.3+/-0.5 ml 100 ml(-1) min(-1). Significant between-centre variation was observed in CBV, OEF and CMRO(2) by one-way analysis of variance. However, the overall inter-individual variation in CBF, CBV, OEF and CMRO(2) was acceptably small. Building a database of normal cerebral haemodynamics obtained by the(15)O-PET methods may be practicable.","publisher":"Springer Science+Business Media","publication_date":{"day":1,"month":5,"year":2004,"errors":{}},"publication_name":"European Journal of Nuclear Medicine and Molecular Imaging"},"translated_abstract":"Measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO(2)) by positron emission tomography (PET) with oxygen-15 labelled carbon dioxide (C(15)O(2)) or (15)O-labelled water (H(2)(15)O), (15)O-labelled carbon monoxide (C(15)O) and (15)O-labelled oxygen ((15)O(2)) is useful for diagnosis and treatment planning in cases of cerebrovascular disease. The measured values theoretically depend on various factors, which may differ between PET centres. This study explored the applicability of a database of (15)O-PET by examining between-centre and within-centre variation in values. Eleven PET centres participated in this multicentre study; seven used the steady-state inhalation method, one used build-up inhalation and three used bolus administration of C(15)O(2) (or H(2)(15)O) and (15)O(2). All used C(15)O for measurement of CBV. Subjects comprised 70 healthy volunteers (43 men and 27 women; mean age 51.8+/-15.1 years). Overall mean+/-SD values for cerebral cortical regions were: CBF=44.4+/-6.5 ml 100 ml(-1) min(-1); CBV=3.8+/-0.7 ml 100 ml(-1); OEF=0.44+/-0.06; CMRO(2)=3.3+/-0.5 ml 100 ml(-1) min(-1). Significant between-centre variation was observed in CBV, OEF and CMRO(2) by one-way analysis of variance. However, the overall inter-individual variation in CBF, CBV, OEF and CMRO(2) was acceptably small. Building a database of normal cerebral haemodynamics obtained by the(15)O-PET methods may be practicable.","internal_url":"https://www.academia.edu/119570577/Database_of_normal_human_cerebral_blood_flow_cerebral_blood_volume_cerebral_oxygen_extraction_fraction_and_cerebral_metabolic_rate_of_oxygen_measured_by_positron_emission_tomography_with_15_O_labelled_carbon_dioxide_or_water_carbon_monoxide_and_oxygen_a_multicentre_study_in_Japan","translated_internal_url":"","created_at":"2024-05-19T17:59:30.357-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Database_of_normal_human_cerebral_blood_flow_cerebral_blood_volume_cerebral_oxygen_extraction_fraction_and_cerebral_metabolic_rate_of_oxygen_measured_by_positron_emission_tomography_with_15_O_labelled_carbon_dioxide_or_water_carbon_monoxide_and_oxygen_a_multicentre_study_in_Japan","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[],"research_interests":[{"id":4594,"name":"Carbon Dioxide","url":"https://www.academia.edu/Documents/in/Carbon_Dioxide"},{"id":10035,"name":"Nuclear medicine","url":"https://www.academia.edu/Documents/in/Nuclear_medicine"},{"id":17158,"name":"Japan","url":"https://www.academia.edu/Documents/in/Japan"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":61474,"name":"Brain","url":"https://www.academia.edu/Documents/in/Brain"},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans"},{"id":71905,"name":"Carbon Monoxide","url":"https://www.academia.edu/Documents/in/Carbon_Monoxide"},{"id":91905,"name":"Cerebrovascular Disease","url":"https://www.academia.edu/Documents/in/Cerebrovascular_Disease"},{"id":98925,"name":"Female","url":"https://www.academia.edu/Documents/in/Female"},{"id":111545,"name":"Male","url":"https://www.academia.edu/Documents/in/Male"},{"id":198377,"name":"Individual variation","url":"https://www.academia.edu/Documents/in/Individual_variation"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences"},{"id":295155,"name":"Middle Aged","url":"https://www.academia.edu/Documents/in/Middle_Aged"},{"id":296766,"name":"Metabolic rate","url":"https://www.academia.edu/Documents/in/Metabolic_rate"},{"id":380825,"name":"Oxygen","url":"https://www.academia.edu/Documents/in/Oxygen"},{"id":394395,"name":"Inhalation","url":"https://www.academia.edu/Documents/in/Inhalation"},{"id":413194,"name":"Analysis of Variance","url":"https://www.academia.edu/Documents/in/Analysis_of_Variance"},{"id":970066,"name":"Cerebral Blood Flow","url":"https://www.academia.edu/Documents/in/Cerebral_Blood_Flow"},{"id":1193624,"name":"Oxygen Consumption","url":"https://www.academia.edu/Documents/in/Oxygen_Consumption"},{"id":2763984,"name":"Cerebral Blood Volume","url":"https://www.academia.edu/Documents/in/Cerebral_Blood_Volume"}],"urls":[{"id":42118151,"url":"https://doi.org/10.1007/s00259-003-1430-8"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570576"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570576/Estimation_of_Absorbed_Dese_Using_Activity_Measured_by_PET_for_Continuous_Inhalation_of_C_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt_and_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt"><img alt="Research paper thumbnail of Estimation of Absorbed Dese Using Activity Measured by PET for Continuous Inhalation of C&lt;sup&gt;15&lt;/sup&gt;O&lt;sub&gt;2&lt;/sub&gt; and &lt;sup&gt;15&lt;/sup&gt;O&lt;sub&gt;2&lt;/sub&gt" class="work-thumbnail" src="https://attachments.academia-assets.com/114954519/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570576/Estimation_of_Absorbed_Dese_Using_Activity_Measured_by_PET_for_Continuous_Inhalation_of_C_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt_and_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt">Estimation of Absorbed Dese Using Activity Measured by PET for Continuous Inhalation of C&lt;sup&gt;15&lt;/sup&gt;O&lt;sub&gt;2&lt;/sub&gt; and &lt;sup&gt;15&lt;/sup&gt;O&lt;sub&gt;2&lt;/sub&gt</a></div><div class="wp-workCard_item"><span>Japanese Journal of Radiological Technology</span><span>, 1998</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4226220f87a8b74cb5a4d006abf2f0cd" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":114954519,"asset_id":119570576,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/114954519/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570576"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570576"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570576; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570576]").text(description); $(".js-view-count[data-work-id=119570576]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570576; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570576']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570576, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "4226220f87a8b74cb5a4d006abf2f0cd" } } $('.js-work-strip[data-work-id=119570576]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570576,"title":"Estimation of Absorbed Dese Using Activity Measured by PET for Continuous Inhalation of C\u0026lt;sup\u0026gt;15\u0026lt;/sup\u0026gt;O\u0026lt;sub\u0026gt;2\u0026lt;/sub\u0026gt; and \u0026lt;sup\u0026gt;15\u0026lt;/sup\u0026gt;O\u0026lt;sub\u0026gt;2\u0026lt;/sub\u0026gt","translated_title":"","metadata":{"publisher":"Japan Radiological Society","grobid_abstract":"JapaneseSociety ofRadiologicalTechnology-4stimatigp. gf Absorbed Dose..U. sing ActMty Measureg. .P.y PET for Continu.ous lnh.g!gt-ion .`o-f 9.l502 andp m '02 \u003cHACHIYA et al)-Z7.1","publication_date":{"day":null,"month":null,"year":1998,"errors":{}},"publication_name":"Japanese Journal of Radiological Technology","grobid_abstract_attachment_id":114954519},"translated_abstract":null,"internal_url":"https://www.academia.edu/119570576/Estimation_of_Absorbed_Dese_Using_Activity_Measured_by_PET_for_Continuous_Inhalation_of_C_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt_and_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt","translated_internal_url":"","created_at":"2024-05-19T17:59:29.470-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":34797888,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":114954519,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/114954519/thumbnails/1.jpg","file_name":"_pdf.pdf","download_url":"https://www.academia.edu/attachments/114954519/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Estimation_of_Absorbed_Dese_Using_Activi.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/114954519/_pdf-libre.pdf?1716167450=\u0026response-content-disposition=attachment%3B+filename%3DEstimation_of_Absorbed_Dese_Using_Activi.pdf\u0026Expires=1732412448\u0026Signature=IJfas4V8DphhP9f5kFoBRTLCKQPqE25Jqj0SJw15cWbD4XywH1aRGlctz3iJkfjOfrcahIoN8xV-~QB~ACdWbElGKtQYok-DRRX3DstuAgSD49YPbRj0dB~IKPsvQbHdibUOkw5O3KQOHY5Ul6lx18zCkQ3-Ngk~JdK5Ru4HIV-GyPOgzWIWJIAkMvmQBDQRqB4dIq0VapL-QCnKui5DxvQ2W7E1zJBc8fIIF0zs51MMXSUWCgFCCk-5mDP9NVco~BMyMGBG8~2ZLIBG9UloSym6tvPR7nWm5WnW2Md79zzK6an9s-g7vFOcyLX0A~P4AbEbLQoKMLV2dajsHTNS1Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Estimation_of_Absorbed_Dese_Using_Activity_Measured_by_PET_for_Continuous_Inhalation_of_C_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt_and_and_lt_sup_and_gt_15_and_lt_sup_and_gt_O_and_lt_sub_and_gt_2_and_lt_sub_and_gt","translated_slug":"","page_count":7,"language":"en","content_type":"Work","owner":{"id":34797888,"first_name":"Iwao","middle_initials":null,"last_name":"Kanno","page_name":"IwaoKanno","domain_name":"independent","created_at":"2015-09-12T02:59:08.602-07:00","display_name":"Iwao Kanno","url":"https://independent.academia.edu/IwaoKanno"},"attachments":[{"id":114954519,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/114954519/thumbnails/1.jpg","file_name":"_pdf.pdf","download_url":"https://www.academia.edu/attachments/114954519/download_file?st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&st=MTczMjQwODg0OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Estimation_of_Absorbed_Dese_Using_Activi.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/114954519/_pdf-libre.pdf?1716167450=\u0026response-content-disposition=attachment%3B+filename%3DEstimation_of_Absorbed_Dese_Using_Activi.pdf\u0026Expires=1732412448\u0026Signature=IJfas4V8DphhP9f5kFoBRTLCKQPqE25Jqj0SJw15cWbD4XywH1aRGlctz3iJkfjOfrcahIoN8xV-~QB~ACdWbElGKtQYok-DRRX3DstuAgSD49YPbRj0dB~IKPsvQbHdibUOkw5O3KQOHY5Ul6lx18zCkQ3-Ngk~JdK5Ru4HIV-GyPOgzWIWJIAkMvmQBDQRqB4dIq0VapL-QCnKui5DxvQ2W7E1zJBc8fIIF0zs51MMXSUWCgFCCk-5mDP9NVco~BMyMGBG8~2ZLIBG9UloSym6tvPR7nWm5WnW2Md79zzK6an9s-g7vFOcyLX0A~P4AbEbLQoKMLV2dajsHTNS1Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":511,"name":"Materials Science","url":"https://www.academia.edu/Documents/in/Materials_Science"},{"id":2413,"name":"Radiochemistry","url":"https://www.academia.edu/Documents/in/Radiochemistry"},{"id":394395,"name":"Inhalation","url":"https://www.academia.edu/Documents/in/Inhalation"}],"urls":[{"id":42118150,"url":"https://doi.org/10.6009/jjrt.kj00003110165"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570575"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/119570575/Relative_CBF_estimation_from_the_kinetics_of_hyperpolarized_Xe_129_NMR_spectroscopy"><img alt="Research paper thumbnail of Relative CBF estimation from the kinetics of hyperpolarized Xe-129 NMR spectroscopy" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/119570575/Relative_CBF_estimation_from_the_kinetics_of_hyperpolarized_Xe_129_NMR_spectroscopy">Relative CBF estimation from the kinetics of hyperpolarized Xe-129 NMR spectroscopy</a></div><div class="wp-workCard_item"><span>Journal of Cerebral Blood Flow and Metabolism</span><span>, Aug 1, 2005</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570575"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570575"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570575; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570574"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570574/Uncoupling_of_Absolute_CBF_to_Neural_Activity"><img alt="Research paper thumbnail of Uncoupling of Absolute CBF to Neural Activity" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570574/Uncoupling_of_Absolute_CBF_to_Neural_Activity">Uncoupling of Absolute CBF to Neural Activity</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 1997</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Since Roy and Sherrington (1890) described that neural activity would regulate blood supply to th...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Since Roy and Sherrington (1890) described that neural activity would regulate blood supply to the brain, it has been widely accepted that neural activation will increase cerebral blood flow (CBF). Lassen and Munck (1955) first demonstrated the regional change of CBF at the cortical areas using radioisotopes. The recent development of technology, e.g. positron emission tomography (PET), has allowed us to measure quantitative CBF at every cubic centimeter of the brain. 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Power in each 1-Hz frequency band from 2-20 Hz, power ratio index, and normalised PET data from corresponding cortical sites were compared to data obtained from 20 normal volunteers. PET revealed significant parieto-temporal hypometabolism, and topographic EEG mapping and power spectrum analysis revealed a slowing of the background EEG that was most pronounced in the parietal-temporal areas. Correlation analysis between EEG power spectrum data and CMRO2 revealed significant negative correlations for frequencies below 8 Hz and significant positive correlations above 8 Hz in the parieto-temporal regions, which have previously been identified as the areas most severely affected by pathological changes associated with DAT. 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PET revealed significant parieto-temporal hypometabolism, and topographic EEG mapping and power spectrum analysis revealed a slowing of the background EEG that was most pronounced in the parietal-temporal areas. Correlation analysis between EEG power spectrum data and CMRO2 revealed significant negative correlations for frequencies below 8 Hz and significant positive correlations above 8 Hz in the parieto-temporal regions, which have previously been identified as the areas most severely affected by pathological changes associated with DAT. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="119570571"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/119570571/Error_and_t_Images_Depend_on_ANOVA_Design_and_Anatomical_Standardization_in_PET_Activation_Analysis_1_1Transcripts_of_the_BRAINPET97_discussion_of_this_chapter_can_be_found_in_Section_VIII"><img alt="Research paper thumbnail of Error and t Images Depend on ANOVA Design and Anatomical Standardization in PET Activation Analysis 1 1Transcripts of the BRAINPET97 discussion of this chapter can be found in Section VIII" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/119570571/Error_and_t_Images_Depend_on_ANOVA_Design_and_Anatomical_Standardization_in_PET_Activation_Analysis_1_1Transcripts_of_the_BRAINPET97_discussion_of_this_chapter_can_be_found_in_Section_VIII">Error and t Images Depend on ANOVA Design and Anatomical Standardization in PET Activation Analysis 1 1Transcripts of the BRAINPET97 discussion of this chapter can be found in Section VIII</a></div><div class="wp-workCard_item"><span>Elsevier eBooks</span><span>, 1998</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In a positron emission tomography activation analysis with task replications within subject, a nu...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In a positron emission tomography activation analysis with task replications within subject, a number of analysis of variance (ANOVA) designs are applicable with different definitions of t and error. The characteristics of t (and z) maps and error images and how they depend on the ANOVA design and on the anatomical standardization method have been investigated. Six subjects underwent measurement of regional cerebral blood flow with [15O]water under resting and while thinking of verbs associated with auditorily presented nouns, three times for each. The images were anatomically standardized with LINear, SPM95, or HBA. ANOVA was performed pixel by pixel to compute t statistics for the task main effect (verb vs rest) in four different ANOVA designs: (i) two way (subject and task) (2W), (ii) two way with interaction (2WI), (iii) two way with interaction, except that the “subject” was considered a random factor (2WI-RF), and (iv) three way (subject, task, and replication). The left frontal cortex extending from Broca&#39;s area to the premotor cortex was activated by the verb generation. The foci localization in the z images depended both on the anatomical standardization method and on the ANOVA design, and the variation ranged from 1 to 3 cm. SPM tended to present a higher peak z than LIN and HBA. The z images of 2W and 2WI looked alike, but 2WI-RF and 3W each presented a different z map within the activated area. The peak z score by 2WI-RF was lower than the others. The error images for 2W, 2WI, and 3W were heterogeneous, being high in gray and low in white.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="119570571"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="119570571"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 119570571; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=119570571]").text(description); $(".js-view-count[data-work-id=119570571]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 119570571; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='119570571']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 119570571, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=119570571]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":119570571,"title":"Error and t Images Depend on ANOVA Design and Anatomical Standardization in PET Activation Analysis 1 1Transcripts of the BRAINPET97 discussion of this chapter can be found in Section VIII","translated_title":"","metadata":{"abstract":"In a positron emission tomography activation analysis with task replications within subject, a number of analysis of variance (ANOVA) designs are applicable with different definitions of t and error. The characteristics of t (and z) maps and error images and how they depend on the ANOVA design and on the anatomical standardization method have been investigated. Six subjects underwent measurement of regional cerebral blood flow with [15O]water under resting and while thinking of verbs associated with auditorily presented nouns, three times for each. The images were anatomically standardized with LINear, SPM95, or HBA. ANOVA was performed pixel by pixel to compute t statistics for the task main effect (verb vs rest) in four different ANOVA designs: (i) two way (subject and task) (2W), (ii) two way with interaction (2WI), (iii) two way with interaction, except that the “subject” was considered a random factor (2WI-RF), and (iv) three way (subject, task, and replication). The left frontal cortex extending from Broca\u0026#39;s area to the premotor cortex was activated by the verb generation. 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