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class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Most read</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/aaf26a" class="art-list-item-title event_main-link">The linear quadratic model: usage, interpretation and challenges</a> <p class="small art-list-item-meta"> Stephen Joseph McMahon 2019 <em>Phys. Med. Biol.</em> <b>64</b> 01TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="The linear quadratic model: usage, interpretation and challenges" data-link-purpose-append-open="The linear quadratic model: usage, interpretation and challenges">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/aaf26a/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, The linear quadratic model: usage, interpretation and challenges</span></a> <a href="/article/10.1088/1361-6560/aaf26a/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, The linear quadratic model: usage, interpretation and challenges</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The linear-quadratic model is one of the key tools in radiation biology and physics. It provides a simple relationship between cell survival and delivered dose: <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/64/1/01TR01/revision2/pmbaaf26aieqn001.gif" style="max-width: 100%;" alt="" align="top"></img></span>, and has been used extensively to analyse and predict responses to ionising radiation both <i>in vitro</i> and <i>in vivo</i>. Despite its ubiquity, there remain questions about its interpretation and wider applicability—Is it a convenient empirical fit or representative of some deeper mechanistic behaviour? Does a model of single-cell survival <i>in vitro</i> really correspond to clinical tissue responses? Is it applicable at very high and very low doses? Here, we review these issues, discussing current usage of the LQ model, its historical context, what we now know about its mechanistic underpinnings, and the potential challenges and confounding factors that arise when trying to apply it across a range of systems.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/aaf26a">https://doi.org/10.1088/1361-6560/aaf26a</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/abbd17" class="art-list-item-title event_main-link">Tissue mimicking materials for imaging and therapy phantoms: a review</a> <p class="small art-list-item-meta"> Conor K McGarry <em>et al</em> 2020 <em>Phys. Med. Biol.</em> <b>65</b> 23TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Tissue mimicking materials for imaging and therapy phantoms: a review" data-link-purpose-append-open="Tissue mimicking materials for imaging and therapy phantoms: a review">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/abbd17/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Tissue mimicking materials for imaging and therapy phantoms: a review</span></a> <a href="/article/10.1088/1361-6560/abbd17/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Tissue mimicking materials for imaging and therapy phantoms: a review</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Tissue mimicking materials (TMMs), typically contained within phantoms, have been used for many decades in both imaging and therapeutic applications. This review investigates the specifications that are typically being used in development of the latest TMMs. The imaging modalities that have been investigated focus around CT, mammography, SPECT, PET, MRI and ultrasound. Therapeutic applications discussed within the review include radiotherapy, thermal therapy and surgical applications. A number of modalities were not reviewed including optical spectroscopy, optical imaging and planar x-rays. The emergence of image guided interventions and multimodality imaging have placed an increasing demand on the number of specifications on the latest TMMs. Material specification standards are available in some imaging areas such as ultrasound. It is recommended that this should be replicated for other imaging and therapeutic modalities. Materials used within phantoms have been reviewed for a series of imaging and therapeutic applications with the potential to become a testbed for cross-fertilization of materials across modalities. Deformation, texture, multimodality imaging and perfusion are common themes that are currently under development.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/abbd17">https://doi.org/10.1088/1361-6560/abbd17</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/0031-9155/60/8/R155" class="art-list-item-title event_main-link">The physics of proton therapy</a> <p class="small art-list-item-meta"> Wayne D Newhauser and Rui Zhang 2015 <em>Phys. Med. Biol.</em> <b>60</b> R155 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="The physics of proton therapy" data-link-purpose-append-open="The physics of proton therapy">Open abstract</span> </button> <a href="/article/10.1088/0031-9155/60/8/R155/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, The physics of proton therapy</span></a> <a href="/article/10.1088/0031-9155/60/8/R155/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, The physics of proton therapy</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The physics of proton therapy has advanced considerably since it was proposed in 1946. Today analytical equations and numerical simulation methods are available to predict and characterize many aspects of proton therapy. This article reviews the basic aspects of the physics of proton therapy, including proton interaction mechanisms, proton transport calculations, the determination of dose from therapeutic and stray radiations, and shielding design. The article discusses underlying processes as well as selected practical experimental and theoretical methods. We conclude by briefly speculating on possible future areas of research of relevance to the physics of proton therapy.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/0031-9155/60/8/R155">https://doi.org/10.1088/0031-9155/60/8/R155</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad7d5c" class="art-list-item-title event_main-link">RayStation/GATE Monte Carlo simulation framework for verification of proton therapy based on the <sup>12</sup>N imaging</a> <p class="small art-list-item-meta"> Zahra Ahmadi Ganjeh <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 195007 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="RayStation/GATE Monte Carlo simulation framework for verification of proton therapy based on the 12N imaging" data-link-purpose-append-open="RayStation/GATE Monte Carlo simulation framework for verification of proton therapy based on the 12N imaging">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad7d5c/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, RayStation/GATE Monte Carlo simulation framework for verification of proton therapy based on the 12N imaging</span></a> <a href="/article/10.1088/1361-6560/ad7d5c/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, RayStation/GATE Monte Carlo simulation framework for verification of proton therapy based on the 12N imaging</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. <sup>12</sup>N, having a half-life of 11 ms, is a highly effective positron emitter that can potentially provide near real-time feedback in proton therapy. There is currently no framework for comparing and validating positron emission imaging of <sup>12</sup>N. This work describes the development and validation of a Monte Carlo (MC) framework to calculate the images of <sup>12</sup>N, as well as long-lived isotopes, originating from activation by protons. <i>Approach</i>. The available dual-panel Biograph mCT PET scanner was modeled in GATE and validated by comparing the simulated sensitivity map with the measured one. The distributions of <sup>12</sup>N and long-lived isotopes were calculated by RayStation and used as the input of GATE simulations. The RayStation/GATE combination was verified using proton beam irradiations of homogeneous phantoms. A 120 MeV pulsed pencil beam with 10<sup>8</sup> protons per pulse was used. Two-dimensional images were created from the GATE output and compared with the images based on the measurements and the 1D longitudinal projection of the full 2D image was used to calculate the <sup>12</sup>N activity range. <i>Main results</i>. The simulated sensitivity in the center of the FoV (5.44%) agrees well with the measured one (5.41%). The simulated and measured 2D sensitivity maps agree in good detail. The relative difference between the measured and simulated positron activity range for both <sup>12</sup>N and long-lived isotopes is less than 1%. The broadening of the <sup>12</sup>N images relative to those of the longer-lived isotopes can be understood in terms of the large positron range of <sup>12</sup>N. <i>Significance</i>. We developed and validated a MC framework based on RayStation/GATE to support the in-beam PET method for quality assurance of proton therapy. The inclusion of the very short-lived isotope <sup>12</sup>N makes the framework useful for developing near real-time verification. This represents a significant step towards translating <sup>12</sup>N real-time in vivo verification to the clinic.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad7d5c">https://doi.org/10.1088/1361-6560/ad7d5c</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/acca5c" class="art-list-item-title event_main-link">2D medical image synthesis using transformer-based denoising diffusion probabilistic model</a> <p class="small art-list-item-meta"> Shaoyan Pan <em>et al</em> 2023 <em>Phys. Med. Biol.</em> <b>68</b> 105004 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="2D medical image synthesis using transformer-based denoising diffusion probabilistic model" data-link-purpose-append-open="2D medical image synthesis using transformer-based denoising diffusion probabilistic model">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/acca5c/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, 2D medical image synthesis using transformer-based denoising diffusion probabilistic model</span></a> <a href="/article/10.1088/1361-6560/acca5c/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, 2D medical image synthesis using transformer-based denoising diffusion probabilistic model</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. Artificial intelligence (AI) methods have gained popularity in medical imaging research. The size and scope of the training image datasets needed for successful AI model deployment does not always have the desired scale. In this paper, we introduce a medical image synthesis framework aimed at addressing the challenge of limited training datasets for AI models. <i>Approach</i>. The proposed 2D image synthesis framework is based on a diffusion model using a Swin-transformer-based network. This model consists of a forward Gaussian noise process and a reverse process using the transformer-based diffusion model for denoising. Training data includes four image datasets: chest x-rays, heart MRI, pelvic CT, and abdomen CT. We evaluated the authenticity, quality, and diversity of the synthetic images using visual Turing assessments conducted by three medical physicists, and four quantitative evaluations: the Inception score (IS), Fréchet Inception Distance score (FID), feature similarity and diversity score (DS, indicating diversity similarity) between the synthetic and true images. To leverage the framework value for training AI models, we conducted COVID-19 classification tasks using real images, synthetic images, and mixtures of both images. <i>Main results</i>. Visual Turing assessments showed an average accuracy of 0.64 (accuracy converging to <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/68/10/105004/revision2/pmbacca5cieqn1.gif" style="max-width: 100%;" alt="$50 \% $" align="top"></img></span><script type="math/tex">50 \%</script></span></span> indicates a better realistic visual appearance of the synthetic images), sensitivity of 0.79, and specificity of 0.50. Average quantitative accuracy obtained from all datasets were IS = 2.28, FID = 37.27, FDS = 0.20, and DS = 0.86. For the COVID-19 classification task, the baseline network obtained an accuracy of 0.88 using a pure real dataset, 0.89 using a pure synthetic dataset, and 0.93 using a dataset mixed of real and synthetic data. <i>Significance</i>. A image synthesis framework was demonstrated for medical image synthesis, which can generate high-quality medical images of different imaging modalities with the purpose of supplementing existing training sets for AI model deployment. This method has potential applications in many data-driven medical imaging research.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/acca5c">https://doi.org/10.1088/1361-6560/acca5c</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/abc5a5" class="art-list-item-title event_main-link">Photon-counting x-ray detectors for CT</a> <p class="small art-list-item-meta"> Mats Danielsson <em>et al</em> 2021 <em>Phys. Med. Biol.</em> <b>66</b> 03TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Photon-counting x-ray detectors for CT" data-link-purpose-append-open="Photon-counting x-ray detectors for CT">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/abc5a5/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Photon-counting x-ray detectors for CT</span></a> <a href="/article/10.1088/1361-6560/abc5a5/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Photon-counting x-ray detectors for CT</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The introduction of photon-counting detectors is expected to be the next major breakthrough in clinical x-ray computed tomography (CT). During the last decade, there has been considerable research activity in the field of photon-counting CT, in terms of both hardware development and theoretical understanding of the factors affecting image quality. In this article, we review the recent progress in this field with the intent of highlighting the relationship between detector design considerations and the resulting image quality. We discuss detector design choices such as converter material, pixel size, and readout electronics design, and then elucidate their impact on detector performance in terms of dose efficiency, spatial resolution, and energy resolution. Furthermore, we give an overview of data processing, reconstruction methods and metrics of imaging performance; outline clinical applications; and discuss potential future developments.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/abc5a5">https://doi.org/10.1088/1361-6560/abc5a5</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ab7b2d" class="art-list-item-title event_main-link">The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector</a> <p class="small art-list-item-meta"> Stefan Gundacker and Arjan Heering 2020 <em>Phys. Med. Biol.</em> <b>65</b> 17TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector" data-link-purpose-append-open="The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ab7b2d/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector</span></a> <a href="/article/10.1088/1361-6560/ab7b2d/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The silicon photomultiplier (SiPM) is an established device of choice for a variety of applications, e.g. in time of flight positron emission tomography (TOF-PET), lifetime fluorescence spectroscopy, distance measurements in LIDAR applications, astrophysics, quantum-cryptography and related applications as well as in high energy physics (HEP).</p><p>To fully utilize the exceptional performances of the SiPM, in particular its sensitivity down to single photon detection, the dynamic range and its intrinsically fast timing properties, a qualitative description and understanding of the main SiPM parameters and properties is necessary. These analyses consider the structure and the electrical model of a single photon avalanche diode (SPAD) and the integration in an array of SPADs, i.e. the SiPM. The discussion will include the front-end readout and the comparison between analog-SiPMs, where the array of SPADs is connected in parallel, and the digital SiPM, where each SPAD is read out and digitized by its own electronic channel.</p><p>For several applications a further complete phenomenological view on SiPMs is necessary, defining several SiPM intrinsic parameters, i.e. gain fluctuation, afterpulsing, excess noise, dark count rate, prompt and delayed optical crosstalk, single photon time resolution (SPTR), photon detection effieciency (PDE) etc. These qualities of SiPMs influence directly and indirectly the time and energy resolution, for example in PET and HEP. This complete overview of all parameters allows one to draw solid conclusions on how best performances can be achieved for the various needs of the different applications.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ab7b2d">https://doi.org/10.1088/1361-6560/ab7b2d</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad8c93" class="art-list-item-title event_main-link">Noise & mottle suppression methods for cumulative Cherenkov images of radiation therapy delivery</a> <p class="small art-list-item-meta"> Jeremy E Hallett <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 225015 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Noise & mottle suppression methods for cumulative Cherenkov images of radiation therapy delivery" data-link-purpose-append-open="Noise & mottle suppression methods for cumulative Cherenkov images of radiation therapy delivery">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8c93/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Noise & mottle suppression methods for cumulative Cherenkov images of radiation therapy delivery</span></a> <a href="/article/10.1088/1361-6560/ad8c93/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Noise & mottle suppression methods for cumulative Cherenkov images of radiation therapy delivery</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Purpose.</i> Cherenkov imaging during radiotherapy provides a real time visualization of beam delivery on patient tissue, which can be used dynamically for incident detection or to review a summary of the delivered surface signal for treatment verification. Very few photons form the images, and one limitation is that the noise level per frame can be quite high, and mottle in the cumulative processed images can cause mild overall noise. This work focused on removing or suppressing noise via image postprocessing. <i>Approach.</i> Images were analyzed for peak-signal-to-noise and spatial frequencies present, and several established noise/mottle reduction algorithms were chosen based upon these observations. These included total variation minimization (TV-L1), non-local means filter (NLM), block-matching 3D (BM3D), alpha (adaptive) trimmed mean (ATM), and bilateral filtering. Each were applied to images acquired using a BeamSite camera (DoseOptics) imaged signal from 6x photons from a TrueBeam linac delivering dose at 600 MU min<sup>−1</sup> incident on an anthropomorphic phantom and tissue slab phantom in various configurations and beam angles. The standard denoised images were tested for PSNR, noise power spectrum (NPS) and image sharpness. <i>Results.</i> The average peak-signal-to-noise ratio (PSNR) increase was 17.4% for TV-L1. NLM denoising increased the average PSNR by 19.1%, BM3D processing increased it by12.1% and the bilateral filter increased the average PSNR by 19.0%. Lastly, the ATM filter resulted in the lowest average PSNR increase of 10.9%. Of all of these, the NLM and bilateral filters produced improved edge sharpness with, generally, the lowest NPS curve. <i>Conclusion.</i> For cumulative image Cherenkov data, NLM and the bilateral filter yielded optimal denoising with the TV-L1 algorithm giving comparable results. Single video frame Cherenkov images exhibit much higher noise levels compared to cumulative images. Noise suppression algorithms for these frame rates will likely be a different processing pipeline involving these filters incorporated with machine learning.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8c93">https://doi.org/10.1088/1361-6560/ad8c93</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad8d9f" class="art-list-item-title event_main-link">Treatment envelope of transcranial histotripsy: challenges and strategies to maximize the treatment location profile</a> <p class="small art-list-item-meta"> Ning Lu <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 225006 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Treatment envelope of transcranial histotripsy: challenges and strategies to maximize the treatment location profile" data-link-purpose-append-open="Treatment envelope of transcranial histotripsy: challenges and strategies to maximize the treatment location profile">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8d9f/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Treatment envelope of transcranial histotripsy: challenges and strategies to maximize the treatment location profile</span></a> <a href="/article/10.1088/1361-6560/ad8d9f/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Treatment envelope of transcranial histotripsy: challenges and strategies to maximize the treatment location profile</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>A 750 kHz, 360-element ultrasound array has been built for transcranial histotripsy applications. This study aims to evaluate its performance to determine whether this array is adequate for treating a wide range of brain locations through a human skull. Treatment location profiles in 2 excised human skulls were experimentally characterized based on passive cavitation mapping. Full-wave acoustic simulations were performed in 8 human skulls to analyze the ultrasound propagation at shallow targets in skulls with different properties. Results showed that histotripsy successfully generated cavitation from deep to shallow targets within 5 mm from the skull surface in the skull with high SDR and small thickness, whereas in the skull with low SDR and large thickness, the treatment envelope was limited up to 16 mm from the skull surface. Simulation results demonstrated that the treatment envelope was highly dependent on the skull acoustic properties. Pre-focal pressure hotspots were observed in both simulation and experiments when targeting near the skull. For each skull, the acoustic pressure loss increases significantly for shallow targets compared to central targets due to high attenuation, large incident angles, and pre-focal pressure hotspots. Strategies including array design optimization, pose optimization, and amplitude correction, are proposed to broaden the treatment envelope. This study identifies the capabilities and limitations of the 360-element transcranial histotripsy array and suggests strategies for designing the next-generation transcranial histotripsy array to expand the treatment location profile for a future clinical trial.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8d9f">https://doi.org/10.1088/1361-6560/ad8d9f</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/0031-9155/58/11/R37" class="art-list-item-title event_main-link">Optical properties of biological tissues: a review</a> <p class="small art-list-item-meta"> Steven L Jacques 2013 <em>Phys. Med. Biol.</em> <b>58</b> R37 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Optical properties of biological tissues: a review" data-link-purpose-append-open="Optical properties of biological tissues: a review">Open abstract</span> </button> <a href="/article/10.1088/0031-9155/58/11/R37/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Optical properties of biological tissues: a review</span></a> <a href="/article/10.1088/0031-9155/58/11/R37/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Optical properties of biological tissues: a review</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>A review of reported tissue optical properties summarizes the wavelength-dependent behavior of scattering and absorption. Formulae are presented for generating the optical properties of a generic tissue with variable amounts of absorbing chromophores (blood, water, melanin, fat, yellow pigments) and a variable balance between small-scale scatterers and large-scale scatterers in the ultrastructures of cells and tissues.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/0031-9155/58/11/R37">https://doi.org/10.1088/0031-9155/58/11/R37</a> </div> </div> </div> </div> </div>  </div> </div> </div>   <div tabindex="0" role="tabpanel" id="latest-articles-tab" aria-labelledby="latest-articles"> <div class=" reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Latest articles</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6560/ad8fec" class="art-list-item-title event_main-link">Verification of linear energy transfer optimized carbon-ion radiotherapy</a> <p class="small art-list-item-meta"> Hideyuki Mizuno <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 23NT01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Verification of linear energy transfer optimized carbon-ion radiotherapy" data-link-purpose-append-open="Verification of linear energy transfer optimized carbon-ion radiotherapy">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8fec/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Verification of linear energy transfer optimized carbon-ion radiotherapy</span></a> <a href="/article/10.1088/1361-6560/ad8fec/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Verification of linear energy transfer optimized carbon-ion radiotherapy</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Linear energy transfer (LET) verification was conducted using a silicon-on-insulator (SOI) microdosimeter during the commissioning of LET-optimized carbon-ion radiotherapy (CIRT). This advanced treatment technique is expected to improve local control rates, especially in hypoxic tumors. <i>Approach.</i> An SOI microdosimeter with a cylindrical sensitive volume of 30 <i>μ</i>m diameter and 5 <i>μ</i>m thickness was used. Simple cubic plans and patient plans using the carbon-ion beams were created by treatment planning system, and the calculated LET<sub>d</sub> values were compared with the measured LET<sub>d</sub> values obtained by the SOI microdosimeter. <i>Main results.</i> Reasonable agreement between the measured and calculated LET<sub>d</sub> was seen in the plateau region of depth LET<sub>d</sub> profile, whereas the measured LET<sub>d</sub> were below the calculated LET<sub>d</sub> in the peak region, specifically where LET<sub>d</sub> exceeds 75 keV <i>μ</i>m<sup>−1</sup>. The discrepancy in the peak region may arise from the uncertainties in the calibration process of the SOI microdosimeter. Excluding the peak region, the average ratio and standard deviation between measured and calculated LET<sub>d</sub> values were 0.996 and 7%, respectively. <i>Significance.</i> This verification results in the initiation of clinical trials for LET-optimized CIRT at QST Hospital, National Institutes for Quantum Science and Technology.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8fec">https://doi.org/10.1088/1361-6560/ad8fec</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad8b08" class="art-list-item-title event_main-link">Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy</a> <p class="small art-list-item-meta"> Robin Straathof <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235007 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy" data-link-purpose-append-open="Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8b08/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy</span></a> <a href="/article/10.1088/1361-6560/ad8b08/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Purpose.</i> Patient-tailored intracavitary/interstitial (IC/IS) brachytherapy (BT) applicators may increase dose conformity in cervical cancer patients. Current configuration planning methods in these custom applicators rely on manual specification or a small set of (straight) needles. This work introduces and validates a two-stage approach for establishing channel configurations in the 3D printed patient-tailored ARCHITECT applicator. <i>Methods.</i> For each patient, the patient-tailored applicator shape was based on the first BT application with a commercial applicator and integrated connectors to a commercial (Geneva) intrauterine tube and two lunar ring channels. First, a large candidate set was generated of channels that steer the needle to desired poses in the target region and are contained in the applicator. The channels' centrelines were represented by Bézier curves. Channels running between straight target segments and entry points were optimised and refined to ensure (dynamic) feasibility. Second, channel configurations were selected using geometric coverage optimisation. This workflow was applied to establish patient-tailored geometries for twenty-two patients previously treated using the Venezia applicator. Treatment plans were automatically generated using the in-house developed algorithm BiCycle. Plans for the clinically used configuration, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn1.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{clin}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{clin}}}}</script></span></span>, and patient-tailored configuration, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn2.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{arch}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{arch}}}}</script></span></span>, were compared. <i>Results.</i> Channel configurations could be generated in clinically feasible time (median: 2651 s, range 1826–3812 s). All <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn3.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{arch}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{arch}}}}</script></span></span> and <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn4.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{clin}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{clin}}}}</script></span></span> plans were acceptable, but planning aims were more frequently attained with patient-tailored configurations (115/132 versus 100/132 instances). Median CTV<sub>IR</sub><span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn5.gif" style="max-width: 100%;" alt="${D_{98}}$" align="top"></img></span><script type="math/tex">{D_{98}}</script></span></span> and bladder <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn6.gif" style="max-width: 100%;" alt="${D_{2{\text{c}}{{\text{m}}^3}}}$" align="top"></img></span><script type="math/tex">{D_{2{\text{c}}{{\text{m}}^3}}}</script></span></span> doses significantly improved (<span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn7.gif" style="max-width: 100%;" alt="$p\, < $" align="top"></img></span><script type="math/tex">p\, <</script></span></span> 0.001 and <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn8.gif" style="max-width: 100%;" alt="$p\, < $" align="top"></img></span><script type="math/tex">p\, <</script></span></span> 0.01 respectively) in <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn9.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{arch}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{arch}}}}</script></span></span> plans in comparison with <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn10.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{clin}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{clin}}}}</script></span></span> plans, and in approximately half of the patients dosimetric indices improved. <i>Conclusion.</i> Automated patient-tailored BT channel configuration planning for 3D printed applicators is clinically feasible. A treatment planning study showed that all plans met planning limits for the patient-tailored configurations, and in selected cases improved the plan quality in comparison with commercial applicator configurations.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8b08">https://doi.org/10.1088/1361-6560/ad8b08</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad9231" class="art-list-item-title event_main-link">Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study</a> <p class="small art-list-item-meta"> Lachlan J M B Arthur <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235006 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study" data-link-purpose-append-open="Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad9231/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study</span></a> <a href="/article/10.1088/1361-6560/ad9231/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The study of microcirculation can reveal important information related to pathology. Focusing on alterations that are represented by an obstruction of blood flow in microcirculatory regions may provide an insight into vascular biomarkers. The current in silico study assesses the capability of contrast enhanced ultrasound (CEUS) and super-resolution ultrasound imaging (SRU) flow-quantification to study occlusive actions in a microvascular bed, particularly the ability to characterise known and model induced flow behaviours. The aim is to investigate theoretical limits with the use of CEUS and SRU in order to propose realistic biomarker targets relevant for clinical diagnosis. Results from CEUS flow parameters display limitations congruent with prior investigations. Conventional resolution limits lead to signals dominated by large vessels, making discrimination of microvasculature specific signals difficult. Additionally, some occlusions lead to weakened parametric correlation against flow rate in the remainder of the network. Loss of correlation is dependent on the degree to which flow is redistributed, with comparatively minor redistribution correlating in accordance with ground truth measurements for change in mean transit time, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235006/revision2/pmbad9231ieqn1.gif" style="max-width: 100%;" alt="$\textrm{dMTT}$" align="top"></img></span><script type="math/tex">\textrm{dMTT}</script></span></span> (CEUS, <i>R</i> = 0.85; GT, <i>R</i> = 0.82) and change in peak intensity, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235006/revision2/pmbad9231ieqn2.gif" style="max-width: 100%;" alt="$dI\textrm{p}$" align="top"></img></span><script type="math/tex">dI\textrm{p}</script></span></span> (CEUS, <i>R</i> = 0.87; GT, <i>R</i> = 0.96). Major redistributions, however, result in a loss of correlation, demonstrating that the effectiveness of time-intensity curve parameters is influenced by the site of occlusion. Conversely, results from SRU processing provides accurate depiction of the anatomy and dynamics present in the vascular bed, that extends to individual microvessels. Correspondence between model vessel structure displayed in SRU maps with the ground truth was <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235006/revision2/pmbad9231ieqn3.gif" style="max-width: 100%;" alt="$ \gt 91\%$" align="top"></img></span><script type="math/tex">\gt 91\%</script></span></span> for cases of minor and major flow redistributions. In conclusion, SRU appears to be a highly promising technology in the quantification of subtle flow phenomena due ischaemia induced vascular flow redistribution.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad9231">https://doi.org/10.1088/1361-6560/ad9231</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6560/ad9076" class="art-list-item-title event_main-link">Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning</a> <p class="small art-list-item-meta"> Dagnachew Tessema Ambaye <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235005 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning" data-link-purpose-append-open="Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad9076/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning</span></a> <a href="/article/10.1088/1361-6560/ad9076/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> This study aims to investigate the feasibility of utilizing generative adversarial networks (GANs) to synthesize high-fidelity computed tomography (CT) images from lower-resolution MR images. The goal is to reduce patient exposure to ionizing radiation while maintaining treatment accuracy and accelerating MR image acquisition. The primary focus is to determine the extent to which low-resolution MR images can be utilized to generate high-quality CT images through a systematic study of spatial resolution-dependent magnetic resonance imaging (MRI)-to-CT image conversion. <i>Approach.</i> Paired MRI-CT images were acquired from healthy control and tumor models, generated by injecting MDA-MB-231 and 4T1 tumor cells into the mammary fat pad of nude and BALB/c mice to ensure model diversification. To explore various MRI resolutions, we downscaled the highest-resolution MR image into three lower resolutions. Using a customized U-Net model, we automated region of interest masking for both MRI and CT modalities with precise alignment, achieved through three-dimensional affine paired MRI-CT registrations. Then our customized models, Nested U-Net GAN and Attention U-Net GAN, were employed to translate low-resolution MR images into high-resolution CT images, followed by evaluation with separate testing datasets. <i>Main Results.</i> Our approach successfully generated high-quality CT images (0.14<sup>2</sup> mm<sup>2</sup>) from both lower-resolution (0.28<sup>2</sup> mm<sup>2</sup>) and higher-resolution (0.14<sup>2</sup> mm<sup>2</sup>) MR images, with no statistically significant differences between them, effectively doubling the speed of MR image acquisition. Our customized GANs successfully preserved anatomical details, addressing the typical loss issue seen in other MRI-CT translation techniques across all resolutions of MR image inputs. <i>Significance.</i> This study demonstrates the potential of using low-resolution MR images to generate high-quality CT images, thereby reducing radiation exposure and expediting MRI acquisition while maintaining accuracy for radiotherapy.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad9076">https://doi.org/10.1088/1361-6560/ad9076</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6560/ad8c98" class="art-list-item-title event_main-link">Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors</a> <p class="small art-list-item-meta"> Chunyan Liu <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235004 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors" data-link-purpose-append-open="Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8c98/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors</span></a> <a href="/article/10.1088/1361-6560/ad8c98/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. Low-dose computed tomography (LDCT) is an imaging technique that can effectively help patients reduce radiation dose, which has attracted increasing interest from researchers in the field of medical imaging. Nevertheless, LDCT imaging is often affected by a large amount of noise, making it difficult to clearly display subtle abnormalities or lesions. Therefore, this paper proposes a multiple complementary priors CT image reconstruction method by simultaneously considering both the internal prior and external image information of CT images, thereby enhancing the reconstruction quality of CT images. <i>Approach</i>. Specifically, we propose a CT image reconstruction method based on weighted nonconvex low-rank regularized group sparse and deep image priors under hybrid plug-and-play framework by utilizing the weighted nonconvex low rankness and group sparsity of dictionary domain coefficients of each group of similar patches, and a convolutional neural network denoiser. To make the proposed reconstruction problem easier to tackle, we utilize the alternate direction method of multipliers for optimization. <i>Main results</i>. To verify the performance of the proposed method, we conduct detailed simulation experiments on the images of the abdominal, pelvic, and thoracic at projection views of 45, 65, and 85, and at noise levels of <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235004/revision2/pmbad8c98ieqn1.gif" style="max-width: 100%;" alt="$1\times10^{5}$" align="top"></img></span><script type="math/tex">1\times10^{5}</script></span></span> and <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235004/revision2/pmbad8c98ieqn2.gif" style="max-width: 100%;" alt="$1\times10^{6}$" align="top"></img></span><script type="math/tex">1\times10^{6}</script></span></span>, respectively. A large number of qualitative and quantitative experimental results indicate that the proposed method has achieved better results in texture preservation and noise suppression compared to several existing iterative reconstruction methods. <i>Significance</i>. The proposed method fully considers the internal nonlocal low rankness and sparsity, as well as the external local information of CT images, providing a more effective solution for CT image reconstruction. Consequently, this method enables doctors to diagnose and treat diseases more accurately by reconstructing high-quality CT images.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8c98">https://doi.org/10.1088/1361-6560/ad8c98</a> </div> </div> </div> </div> </div>  </div> </div> </div>     <div tabindex="0" role="tabpanel" id="review-articles-tab" aria-labelledby="review-articles" hidden="hidden"> <div class=" reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Review articles</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6560/ad6951" class="art-list-item-title event_main-link">Research and application of omics and artificial intelligence in cancer</a> <p class="small art-list-item-meta"> Ye Zhang <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 21TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Research and application of omics and artificial intelligence in cancer" data-link-purpose-append-open="Research and application of omics and artificial intelligence in cancer">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad6951/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Research and application of omics and artificial intelligence in cancer</span></a> <a href="/article/10.1088/1361-6560/ad6951/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Research and application of omics and artificial intelligence in cancer</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Cancer has a high incidence and lethality rate, which is a significant threat to human health. With the development of high-throughput technologies, different types of cancer genomics data have been accumulated, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. A comprehensive analysis of various omics data is needed to understand the underlying mechanisms of tumor development. However, integrating such a massive amount of data is one of the main challenges today. Artificial intelligence (AI) techniques such as machine learning are now becoming practical tools for analyzing and understanding multi-omics data on diseases. Enabling great optimization of existing research paradigms for cancer screening, diagnosis, and treatment. In addition, intelligent healthcare has received widespread attention with the development of healthcare informatization. As an essential part of innovative healthcare, practical, intelligent prognosis analysis and personalized treatment for cancer patients are also necessary. This paper introduces the advanced multi-omics data analysis technology in recent years, presents the cases and advantages of the combination of both omics data and AI applied to cancer diseases, and finally briefly describes the challenges faced by multi-omics analysis and AI at the current stage, aiming to provide new perspectives for oncology research and the possibility of personalized cancer treatment.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad6951">https://doi.org/10.1088/1361-6560/ad6951</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad70ee" class="art-list-item-title event_main-link">Opportunities and challenges of upright patient positioning in radiotherapy</a> <p class="small art-list-item-meta"> Lennart Volz <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 18TR02 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Opportunities and challenges of upright patient positioning in radiotherapy" data-link-purpose-append-open="Opportunities and challenges of upright patient positioning in radiotherapy">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad70ee/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Opportunities and challenges of upright patient positioning in radiotherapy</span></a> <a href="/article/10.1088/1361-6560/ad70ee/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Opportunities and challenges of upright patient positioning in radiotherapy</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Upright positioning has seen a surge in interest as a means to reduce radiotherapy (RT) cost, improve patient comfort, and, in selected cases, benefit treatment quality. In particle therapy (PT) in particular, eliminating the need for a gantry can present massive cost and facility footprint reduction. This review discusses the opportunities of upright RT in perspective of the open challenges. <i>Approach.</i> The clinical, technical, and workflow challenges that come with the upright posture have been extracted from an extensive literature review, and the current state of the art was collected in a synergistic perspective from photon and particle therapy. Considerations on future developments and opportunities are provided. <i>Main results.</i> Modern image guidance is paramount to upright RT, but it is not clear which modalities are essential to acquire in upright posture. Using upright MRI or upright CT, anatomical differences between upright/recumbent postures have been observed for nearly all body sites. Patient alignment similar to recumbent positioning was achieved in small patient/volunteer cohorts with prototype upright positioning systems. Possible clinical advantages, such as reduced breathing motion in upright position, have been reported, but limited cohort sizes prevent resilient conclusions on the treatment impact. Redesign of RT equipment for upright positioning, such as immobilization accessories for various body regions, is necessary, where several innovations were recently presented. Few clinical studies in upright PT have already reported promising outcomes for head&neck patients. <i>Significance.</i> With more evidence for benefits of upright RT emerging, several centers worldwide, particularly in PT, are installing upright positioning devices or have commenced upright treatment. Still, many challenges and open questions remain to be addressed to embed upright positioning firmly in the modern RT landscape. Guidelines, professionals trained in upright patient positioning, and large-scale clinical studies are required to bring upright RT to fruition.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad70ee">https://doi.org/10.1088/1361-6560/ad70ee</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad70f0" class="art-list-item-title event_main-link">Modelling radiobiology</a> <p class="small art-list-item-meta"> Lydia L Gardner <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 18TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Modelling radiobiology" data-link-purpose-append-open="Modelling radiobiology">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad70f0/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Modelling radiobiology</span></a> <a href="/article/10.1088/1361-6560/ad70f0/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Modelling radiobiology</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Radiotherapy has played an essential role in cancer treatment for over a century, and remains one of the best-studied methods of cancer treatment. Because of its close links with the physical sciences, it has been the subject of extensive quantitative mathematical modelling, but a complete understanding of the mechanisms of radiotherapy has remained elusive. In part this is because of the complexity and range of scales involved in radiotherapy—from physical radiation interactions occurring over nanometres to evolution of patient responses over months and years. This review presents the current status and ongoing research in modelling radiotherapy responses across these scales, including basic physical mechanisms of DNA damage, the immediate biological responses this triggers, and genetic- and patient-level determinants of response. Finally, some of the major challenges in this field and potential avenues for future improvements are also discussed.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad70f0">https://doi.org/10.1088/1361-6560/ad70f0</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6560/ad66a9" class="art-list-item-title event_main-link">A survey on integral equations for bioelectric modeling</a> <p class="small art-list-item-meta"> Guillermo Nuñez Ponasso 2024 <em>Phys. Med. Biol.</em> <b>69</b> 17TR02 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="A survey on integral equations for bioelectric modeling" data-link-purpose-append-open="A survey on integral equations for bioelectric modeling">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad66a9/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, A survey on integral equations for bioelectric modeling</span></a> <a href="/article/10.1088/1361-6560/ad66a9/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, A survey on integral equations for bioelectric modeling</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Bioelectric modeling problems, such as electroencephalography, magnetoencephalography, transcranial electrical stimulation, deep brain stimulation, and transcranial magnetic stimulation, among others, can be approached through the formulation and resolution of integral equations of the <i>boundary element method</i> (BEM). Recently, it has been realized that the <i>charge-based formulation</i> of the BEM is naturally well-suited for the application of the <i>fast multipole method</i> (FMM). The FMM is a powerful algorithm for the computation of many-body interactions and is widely applied in electromagnetic modeling problems. With the introduction of BEM-FMM in the context of bioelectromagnetism, the BEM can now compete with the <i>finite element method</i> (FEM) in a number of application cases. This survey has two goals: first, to give a modern account of the main BEM formulations in the literature and their integration with FMM, directed to general researchers involved in development of BEM software for bioelectromagnetic applications. Second, to survey different techniques and available software, and to contrast different BEM and FEM approaches. As a new contribution, we showcase that the charge-based formulation is dual to the more common surface potential formulation.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad66a9">https://doi.org/10.1088/1361-6560/ad66a9</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6560/ad67a7" class="art-list-item-title event_main-link">Fast Monte Carlo dose calculation in proton therapy</a> <p class="small art-list-item-meta"> Jason Holmes <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 17TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Fast Monte Carlo dose calculation in proton therapy" data-link-purpose-append-open="Fast Monte Carlo dose calculation in proton therapy">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad67a7/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Fast Monte Carlo dose calculation in proton therapy</span></a> <a href="/article/10.1088/1361-6560/ad67a7/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Fast Monte Carlo dose calculation in proton therapy</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>This article examines the critical role of fast Monte Carlo (MC) dose calculations in advancing proton therapy techniques, particularly in the context of increasing treatment customization and precision. As adaptive radiotherapy and other patient-specific approaches evolve, the need for accurate and precise dose calculations, essential for techniques like proton-based stereotactic radiosurgery, becomes more prominent. These calculations, however, are time-intensive, with the treatment planning/optimization process constrained by the achievable speed of dose computations. Thus, enhancing the speed of MC methods is vital, as it not only facilitates the implementation of novel treatment modalities but also leads to more optimal treatment plans. Today, the state-of-the-art in MC dose calculation speeds is 10<sup>6</sup>–10<sup>7</sup> protons per second. This review highlights the latest advancements in fast MC dose calculations that have led to such speeds, including emerging artificial intelligence-based techniques, and discusses their application in both current and emerging proton therapy strategies.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad67a7">https://doi.org/10.1088/1361-6560/ad67a7</a> </div> </div> </div> </div> </div>  </div> </div> </div>       <div tabindex="0" role="tabpanel" id="accepted-manuscripts-tab" aria-labelledby="accepted-manuscripts" hidden="hidden"> <div class="reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Accepted manuscripts</button> </h2> <div class="reveal-content tabpanel__content" style="display: none;">  <p id="jnl-issue-disp-links" class="cf"> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab">Open all abstracts<span class="offscreen-hidden">, in this tab</span></button> </p>  <div class="art-list" id="wd-jnl-issue-art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965b" class="art-list-item-title event_main-link">Novel frequency selective B<sub>1</sub> focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification</a> <p class="small art-list-item-meta"> Hodgson et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification" data-link-purpose-append-open="Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965b/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification</span></a> <a href="/article/10.1088/1361-6560/ad965b/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Objective. The need for increased sensitivity in magnetic resonance imaging (MRI) is crucial for its advancement as an imaging modality. The development of passive Lenz Resonators for effective RF magnetic field focusing will improve MRI sensitivity via local amplification of MRI signal, thereby leading to more efficient diagnosis and patient treatment. Approach. While there are methods for amplifying the signal from specific nuclei in MRI, such as hyperpolarization, a general solution will be more advantageous and would work in combination with these preexisting methods. While the Lenz Lens proposed such a general solution based on Lenz's law and the reciprocity principle, it came at the cost of limited signal enhancement. In this work, the first-in-kind prototype Lenz Resonator was conceived and examined as a general frequency-selective passive flux-focusing element for significant MRI signal enhancement. A 3.0 T Philips Achieva MRI was used to compare the signal from a phantom in the presence of Lenz Lenses, Lenz Resonators, and control trials with neither component. Main results. An MRI investigation demonstrated an experimental amplification of the signal-to-noise ratio up to 80% using an MRI insert of two coaxial Lenz Resonators due to superior B1 magnetic field focusing. The resonators displayed consistent amplification, nearly independent of their x-position within the MRI bore. Significance. This behavior demonstrates the feasibility of imaging large objects of varying shapes without penalties for signal amplification using Lenz Resonators. The Lenz Resonators versatility in geometrical design and consistent signal amplifying abilities between pulse sequences should allow for the development of Lenz Resonators suitable for most commonly used MRI setups.</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965b">https://doi.org/10.1088/1361-6560/ad965b</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965c" class="art-list-item-title event_main-link">Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images</a> <p class="small art-list-item-meta"> Anetai et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images" data-link-purpose-append-open="Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965c/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images</span></a> <a href="/article/10.1088/1361-6560/ad965c/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Objective. Diffusion equation imaging processing is promising to enhance images showing lesions of bone metastasis (LBM). The Perona–Malik diffusion (PMD) model, which has been widely used and studied, is an anisotropic diffusion processing method to denoise or extract objects from an image effectively. However, the smoothing characteristics of PMD or its related method hinder extraction and enhancement of soft tissue regions of medical image such as computed tomography (CT), typically leaving an indistinct region with ambient tissues. Moreover, PMD expands the border region of the objects. A novel diffusion methodology must be used to enhance the LBM region effectively.&#xD;Approach. For this study, we originally developed a diffusion equation quantification (DEQ) method that uses a filter function to selectively provide modulated diffusion according to the original locations of objects in an image. The structural similarity index measure (SSIM) and Lie derivative image analysis (LDIA) L-value map were used to evaluate image quality and processing.&#xD;Main results. We determined superellipse function with its order n=4 for the LBM region. DEQ was found to be more effective at contrasting LBM for various LBM CT images than PMD or its improved models. DEQ yields enhancement agreeing with the indications of positron emission tomography despite complex lesions of bone metastasis comprising osteoblastic, osteoclastic, mixed tissues, and metal artifacts, which is innovative. Moreover, DEQ retained high quality of image (SSIM > 0.95), and achieved a low mean value of the L-value (< 0.001), indicative of our intended selective diffusion compared to other PMD models.&#xD;Significance. Our method improved the visibility of mixed tissue lesions, which can assist computer visional framework and can help radiologists to produce accurate diagnose of LBM regions which are frequently overlooked in radiology findings because of the various degrees of visibility in CT images.</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965c">https://doi.org/10.1088/1361-6560/ad965c</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6560/ad965d" class="art-list-item-title event_main-link">Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT)</a> <p class="small art-list-item-meta"> Yang et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT)" data-link-purpose-append-open="Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT)">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965d/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT)</span></a> <a href="/article/10.1088/1361-6560/ad965d/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT)</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Purpose:&#xD;To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system (TPS) to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-risk (OAR) sparing performance.&#xD;Methods:&#xD;With IRB approval, one hundred and twenty HN patients receiving IMRT were included. The DRL agent was trained with 20 patients. During each inverse optimization process, the intermediate dosimetric endpoints' value, dose volume constraints value and structure objective function loss were collected as the DRL states. By adjusting the objective constraints as actions, the agent learned to seek optimal rewards by balancing OAR sparing and planning target volume (PTV) coverage. Reward computed from current dose-volume-histogram (DVH) endpoints and clinical objectives were sent back to the agent to update action policy during model training. The trained agent was evaluated with the rest 100 patients. &#xD;Results:&#xD;The DRL agent was able to generate a clinically acceptable IMRT plan within 12.4±3.1 minutes without human intervention. DRL plans showed lower PTV maximum dose (109.2%) compared to clinical plans (112.4%) (p<.05). Average median dose of left parotid, right parotid, oral cavity, larynx, pharynx of DRL plans were 15.6Gy, 12.2Gy, 25.7Gy, 27.3Gy and 32.1Gy respectively, comparable to 17.1 Gy,15.7Gy, 24.4Gy, 23.7Gy and 35.5Gy of corresponding clinical plans. The maximum dose of cord+5mm, brainstem and mandible were also comparable between the two groups. In addition, DRL plans demonstrated reduced variability, as evidenced by smaller 95% confidence intervals. The total MU of the DRL plans was 1611 vs 1870 (p<.05) of clinical plans. The results signaled the DRL's consistent planning strategy compared to the planners' occasional back-and-forth decision-making during planning.&#xD;Conclusion:&#xD;The proposed deep reinforcement learning (DRL) agent is capable of efficiently generating HN IMRT plans with consistent quality. &#xD;</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965d">https://doi.org/10.1088/1361-6560/ad965d</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965e" class="art-list-item-title event_main-link">On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness</a> <p class="small art-list-item-meta"> Parisi et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness" data-link-purpose-append-open="On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965e/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness</span></a> <a href="/article/10.1088/1361-6560/ad965e/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Objective - Microdosimetry is gaining increasing interest in particle therapy. Thanks to the advancements in microdosimeter technologies and the increasing number of experimental studies carried out in hadron therapy frameworks, it is proving to be a reliable experimental technique for radiation quality characterisation, quality assurance, and radiobiology studies. However, considering the variety of detectors used for microdosimetry, it is important to ensure the consistency of microdosimetric results measured with different types of microdosimeters.&#xD;Approach - This work presents a novel multi-thickness microdosimeter and a methodology to characterise the radiation quality of a clinical carbon-ion beam. The novel device is a diamond detector made of three sensitive volumes (SV) of different thicknesses: 2, 6 and 12 μm. The SVs, which operate simultaneously, were accurately aligned and laterally positioned within 3mm. This allignement allowed for a comparison of the results with a negligible impact of the SVs alignment and their lateral positioning, ensuring the homogeneity of the measured radiation quality. An experimental campaign was carried out at MedAustron using a carbon-ion beam of typical clinical energy (284.7MeV/u).&#xD;Main results - The measurement results allowed for a meticulous interpretation of its radiation quality, highlighting the effect of the SV thickness. The consistency of the microdosimetric spectra measured by detectors of different thicknesses is discussed by critically analysing the spectra and the differences observed.&#xD;Significance - The methodology presented will be highly valuable for future experiments investigating the effects of the target volume size in radiobiology and could be easily adapted to the other particles employed in hadron therapy for clinical (i.e. protons) and for research purposes (e.g. helium, lithium and oxygen ions).</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965e">https://doi.org/10.1088/1361-6560/ad965e</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965f" class="art-list-item-title event_main-link">Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images</a> <p class="small art-list-item-meta"> Beikali Soltani et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images" data-link-purpose-append-open="Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965f/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images</span></a> <a href="/article/10.1088/1361-6560/ad965f/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Objective: Contrast agents in CT scans can compromise the accuracy of dose calculations in radiation therapy planning, especially for particle therapy. This often requires an additional non-contrast CT scan, increasing radiation exposure and introducing potential registration errors. Our goal is to resolve these issues by accurately estimating radiotherapy parameters from dual virtual non-contrast (dual-VNC) images generated by contrast-enhanced dual-energy CT (DECT) scans, while accounting for noise and variability in tissue composition.&#xD;Approach: A new Bayesian model is introduced to estimate dual-VNC Hounsfield units from contrast-enhanced DECT data. The model defines a prior distribution that describes tissue variations in terms of elemental compositions and mass densities. Multiple reference tissues are used to estimate variations across human tissues. A likelihood distribution is also defined to model the noise contained in CT data. The model is thoroughly validated in a simulated environment including 12 virtual patients under low and high iodine uptake scenarios, while incorporating noise and beam hardening effects. The eigentissue decomposition (ETD) technique is used to derive elemental compositions and parameters critical for radiotherapy from the dual-VNC images, such as electron density (ρ<sub>e</sub>), particle stopping power (SPR), and photon energy absorption coefficient (EAC)&#xD;Main results: The proposed method yields accurate voxelwise estimations for ρ<sub>e</sub>, SPR, and EAC, with root mean square errors of 3.09%, 3.14%, and 1.34% for highly-enhanced tissues, compared to 5.93%, 6.39%, and 17.11% when the presence of contrast agent is ignored. It also demonstrates robustness to systematic shifts in tissue composition and bandwidth variations in the prior distribution, resulting in overall uncertainties down to 1.13%, 1.33%, and 0.86% for ρ<sub>e</sub>, SPR, and EAC in soft tissues; 1.17%, 1.32%, and 1.34% in enhanced soft tissues; and 4.34%, 4.00%, and 2.50% in bone.&#xD;Significance: The proposed method accurately derives radiotherapy parameters from contrast-enhanced DECT data and demonstrates robustness against systematic errors in reference data, highlighting its potential for clinical use.</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965f">https://doi.org/10.1088/1361-6560/ad965f</a> </div> </div> </div> </div> </div>  <p> <a href="/journal/0031-9155/acceptedmanuscripts/1">More Accepted manuscripts</a> </p>  </div> </div> </div>   <div tabindex="0" role="tabpanel" id="trending-altmetrics-tab" aria-labelledby="trending-altmetrics" hidden="hidden"> <div class="reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Trending</button> </h2> <div class="reveal-content tabpanel__content" style="display: none;">  <div class="trending-altmetric-results-list" id="https://api.altmetric.com/v1/citations/1y?num_results=5&issns=0031-9155"> <h2>Trending on Altmetric</h2> <div class="art-list"> </div> </div>  </div> </div> </div>   <div tabindex="0" role="tabpanel" id="open-access-articles-tab" aria-labelledby="open-access-articles" hidden="hidden"> <div class=" reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Open access</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad8b08" class="art-list-item-title event_main-link">Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy</a> <p class="small art-list-item-meta"> Robin Straathof <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235007 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy" data-link-purpose-append-open="Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8b08/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy</span></a> <a href="/article/10.1088/1361-6560/ad8b08/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Purpose.</i> Patient-tailored intracavitary/interstitial (IC/IS) brachytherapy (BT) applicators may increase dose conformity in cervical cancer patients. Current configuration planning methods in these custom applicators rely on manual specification or a small set of (straight) needles. This work introduces and validates a two-stage approach for establishing channel configurations in the 3D printed patient-tailored ARCHITECT applicator. <i>Methods.</i> For each patient, the patient-tailored applicator shape was based on the first BT application with a commercial applicator and integrated connectors to a commercial (Geneva) intrauterine tube and two lunar ring channels. First, a large candidate set was generated of channels that steer the needle to desired poses in the target region and are contained in the applicator. The channels' centrelines were represented by Bézier curves. Channels running between straight target segments and entry points were optimised and refined to ensure (dynamic) feasibility. Second, channel configurations were selected using geometric coverage optimisation. This workflow was applied to establish patient-tailored geometries for twenty-two patients previously treated using the Venezia applicator. Treatment plans were automatically generated using the in-house developed algorithm BiCycle. Plans for the clinically used configuration, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn1.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{clin}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{clin}}}}</script></span></span>, and patient-tailored configuration, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn2.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{arch}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{arch}}}}</script></span></span>, were compared. <i>Results.</i> Channel configurations could be generated in clinically feasible time (median: 2651 s, range 1826–3812 s). All <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn3.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{arch}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{arch}}}}</script></span></span> and <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn4.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{clin}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{clin}}}}</script></span></span> plans were acceptable, but planning aims were more frequently attained with patient-tailored configurations (115/132 versus 100/132 instances). Median CTV<sub>IR</sub><span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn5.gif" style="max-width: 100%;" alt="${D_{98}}$" align="top"></img></span><script type="math/tex">{D_{98}}</script></span></span> and bladder <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn6.gif" style="max-width: 100%;" alt="${D_{2{\text{c}}{{\text{m}}^3}}}$" align="top"></img></span><script type="math/tex">{D_{2{\text{c}}{{\text{m}}^3}}}</script></span></span> doses significantly improved (<span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn7.gif" style="max-width: 100%;" alt="$p\, < $" align="top"></img></span><script type="math/tex">p\, <</script></span></span> 0.001 and <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn8.gif" style="max-width: 100%;" alt="$p\, < $" align="top"></img></span><script type="math/tex">p\, <</script></span></span> 0.01 respectively) in <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn9.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{arch}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{arch}}}}</script></span></span> plans in comparison with <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235007/revision2/pmbad8b08ieqn10.gif" style="max-width: 100%;" alt="${\text{T}}{{\text{P}}_{{\text{clin}}}}$" align="top"></img></span><script type="math/tex">{\text{T}}{{\text{P}}_{{\text{clin}}}}</script></span></span> plans, and in approximately half of the patients dosimetric indices improved. <i>Conclusion.</i> Automated patient-tailored BT channel configuration planning for 3D printed applicators is clinically feasible. A treatment planning study showed that all plans met planning limits for the patient-tailored configurations, and in selected cases improved the plan quality in comparison with commercial applicator configurations.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8b08">https://doi.org/10.1088/1361-6560/ad8b08</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad9231" class="art-list-item-title event_main-link">Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study</a> <p class="small art-list-item-meta"> Lachlan J M B Arthur <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235006 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study" data-link-purpose-append-open="Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad9231/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study</span></a> <a href="/article/10.1088/1361-6560/ad9231/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: a theoretical study</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The study of microcirculation can reveal important information related to pathology. Focusing on alterations that are represented by an obstruction of blood flow in microcirculatory regions may provide an insight into vascular biomarkers. The current in silico study assesses the capability of contrast enhanced ultrasound (CEUS) and super-resolution ultrasound imaging (SRU) flow-quantification to study occlusive actions in a microvascular bed, particularly the ability to characterise known and model induced flow behaviours. The aim is to investigate theoretical limits with the use of CEUS and SRU in order to propose realistic biomarker targets relevant for clinical diagnosis. Results from CEUS flow parameters display limitations congruent with prior investigations. Conventional resolution limits lead to signals dominated by large vessels, making discrimination of microvasculature specific signals difficult. Additionally, some occlusions lead to weakened parametric correlation against flow rate in the remainder of the network. Loss of correlation is dependent on the degree to which flow is redistributed, with comparatively minor redistribution correlating in accordance with ground truth measurements for change in mean transit time, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235006/revision2/pmbad9231ieqn1.gif" style="max-width: 100%;" alt="$\textrm{dMTT}$" align="top"></img></span><script type="math/tex">\textrm{dMTT}</script></span></span> (CEUS, <i>R</i> = 0.85; GT, <i>R</i> = 0.82) and change in peak intensity, <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235006/revision2/pmbad9231ieqn2.gif" style="max-width: 100%;" alt="$dI\textrm{p}$" align="top"></img></span><script type="math/tex">dI\textrm{p}</script></span></span> (CEUS, <i>R</i> = 0.87; GT, <i>R</i> = 0.96). Major redistributions, however, result in a loss of correlation, demonstrating that the effectiveness of time-intensity curve parameters is influenced by the site of occlusion. Conversely, results from SRU processing provides accurate depiction of the anatomy and dynamics present in the vascular bed, that extends to individual microvessels. Correspondence between model vessel structure displayed in SRU maps with the ground truth was <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0031-9155/69/23/235006/revision2/pmbad9231ieqn3.gif" style="max-width: 100%;" alt="$ \gt 91\%$" align="top"></img></span><script type="math/tex">\gt 91\%</script></span></span> for cases of minor and major flow redistributions. In conclusion, SRU appears to be a highly promising technology in the quantification of subtle flow phenomena due ischaemia induced vascular flow redistribution.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad9231">https://doi.org/10.1088/1361-6560/ad9231</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965b" class="art-list-item-title event_main-link">Novel frequency selective B<sub>1</sub> focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification</a> <p class="small art-list-item-meta"> Aaron Earl Hodgson <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification" data-link-purpose-append-open="Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965b/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification</span></a> <a href="/article/10.1088/1361-6560/ad965b/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Novel frequency selective B1 focusing passive Lenz resonators for substantial MRI signal-to-noise ratio amplification</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective. The need for increased sensitivity in magnetic resonance imaging (MRI) is crucial for its advancement as an imaging modality. The development of passive Lenz Resonators for effective RF magnetic field focusing will improve MRI sensitivity via local amplification of MRI signal, thereby leading to more efficient diagnosis and patient treatment. Approach. While there are methods for amplifying the signal from specific nuclei in MRI, such as hyperpolarization, a general solution will be more advantageous and would work in combination with these preexisting methods. While the Lenz Lens proposed such a general solution based on Lenz's law and the reciprocity principle, it came at the cost of limited signal enhancement. In this work, the first-in-kind prototype Lenz Resonator was conceived and examined as a general frequency-selective passive flux-focusing element for significant MRI signal enhancement. A 3.0 T Philips Achieva MRI was used to compare the signal from a phantom in the presence of Lenz Lenses, Lenz Resonators, and control trials with neither component. Main results. An MRI investigation demonstrated an experimental amplification of the signal-to-noise ratio up to 80% using an MRI insert of two coaxial Lenz Resonators due to superior B1 magnetic field focusing. The resonators displayed consistent amplification, nearly independent of their x-position within the MRI bore. Significance. This behavior demonstrates the feasibility of imaging large objects of varying shapes without penalties for signal amplification using Lenz Resonators. The Lenz Resonators versatility in geometrical design and consistent signal amplifying abilities between pulse sequences should allow for the development of Lenz Resonators suitable for most commonly used MRI setups.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965b">https://doi.org/10.1088/1361-6560/ad965b</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965c" class="art-list-item-title event_main-link">Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images</a> <p class="small art-list-item-meta"> Yusuke Anetai <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images" data-link-purpose-append-open="Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965c/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images</span></a> <a href="/article/10.1088/1361-6560/ad965c/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective. Diffusion equation imaging processing is promising to enhance images showing lesions of bone metastasis (LBM). The Perona–Malik diffusion (PMD) model, which has been widely used and studied, is an anisotropic diffusion processing method to denoise or extract objects from an image effectively. However, the smoothing characteristics of PMD or its related method hinder extraction and enhancement of soft tissue regions of medical image such as computed tomography (CT), typically leaving an indistinct region with ambient tissues. Moreover, PMD expands the border region of the objects. A novel diffusion methodology must be used to enhance the LBM region effectively.&#xD;Approach. For this study, we originally developed a diffusion equation quantification (DEQ) method that uses a filter function to selectively provide modulated diffusion according to the original locations of objects in an image. The structural similarity index measure (SSIM) and Lie derivative image analysis (LDIA) L-value map were used to evaluate image quality and processing.&#xD;Main results. We determined superellipse function with its order n=4 for the LBM region. DEQ was found to be more effective at contrasting LBM for various LBM CT images than PMD or its improved models. DEQ yields enhancement agreeing with the indications of positron emission tomography despite complex lesions of bone metastasis comprising osteoblastic, osteoclastic, mixed tissues, and metal artifacts, which is innovative. Moreover, DEQ retained high quality of image (SSIM > 0.95), and achieved a low mean value of the L-value (< 0.001), indicative of our intended selective diffusion compared to other PMD models.&#xD;Significance. Our method improved the visibility of mixed tissue lesions, which can assist computer visional framework and can help radiologists to produce accurate diagnose of LBM regions which are frequently overlooked in radiology findings because of the various degrees of visibility in CT images.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965c">https://doi.org/10.1088/1361-6560/ad965c</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965e" class="art-list-item-title event_main-link">On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness</a> <p class="small art-list-item-meta"> Gabriele Parisi <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness" data-link-purpose-append-open="On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965e/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness</span></a> <a href="/article/10.1088/1361-6560/ad965e/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, On the microdosimetric characterisation of the radiation quality of a carbon-ion beam and the effect of the target volume thickness</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective - Microdosimetry is gaining increasing interest in particle therapy. Thanks to the advancements in microdosimeter technologies and the increasing number of experimental studies carried out in hadron therapy frameworks, it is proving to be a reliable experimental technique for radiation quality characterisation, quality assurance, and radiobiology studies. However, considering the variety of detectors used for microdosimetry, it is important to ensure the consistency of microdosimetric results measured with different types of microdosimeters.&#xD;Approach - This work presents a novel multi-thickness microdosimeter and a methodology to characterise the radiation quality of a clinical carbon-ion beam. The novel device is a diamond detector made of three sensitive volumes (SV) of different thicknesses: 2, 6 and 12 μm. The SVs, which operate simultaneously, were accurately aligned and laterally positioned within 3mm. This allignement allowed for a comparison of the results with a negligible impact of the SVs alignment and their lateral positioning, ensuring the homogeneity of the measured radiation quality. An experimental campaign was carried out at MedAustron using a carbon-ion beam of typical clinical energy (284.7MeV/u).&#xD;Main results - The measurement results allowed for a meticulous interpretation of its radiation quality, highlighting the effect of the SV thickness. The consistency of the microdosimetric spectra measured by detectors of different thicknesses is discussed by critically analysing the spectra and the differences observed.&#xD;Significance - The methodology presented will be highly valuable for future experiments investigating the effects of the target volume size in radiobiology and could be easily adapted to the other particles employed in hadron therapy for clinical (i.e. protons) and for research purposes (e.g. helium, lithium and oxygen ions).</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965e">https://doi.org/10.1088/1361-6560/ad965e</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad965f" class="art-list-item-title event_main-link">Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images</a> <p class="small art-list-item-meta"> Mohsen Beikali Soltani and Hugo Bouchard 2024 <em>Phys. Med. Biol.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images" data-link-purpose-append-open="Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad965f/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images</span></a> <a href="/article/10.1088/1361-6560/ad965f/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Dual virtual non-contrast imaging: a Bayesian quantitative approach to determine radiotherapy quantities from contrast-enhanced DECT images</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective: Contrast agents in CT scans can compromise the accuracy of dose calculations in radiation therapy planning, especially for particle therapy. This often requires an additional non-contrast CT scan, increasing radiation exposure and introducing potential registration errors. Our goal is to resolve these issues by accurately estimating radiotherapy parameters from dual virtual non-contrast (dual-VNC) images generated by contrast-enhanced dual-energy CT (DECT) scans, while accounting for noise and variability in tissue composition.&#xD;Approach: A new Bayesian model is introduced to estimate dual-VNC Hounsfield units from contrast-enhanced DECT data. The model defines a prior distribution that describes tissue variations in terms of elemental compositions and mass densities. Multiple reference tissues are used to estimate variations across human tissues. A likelihood distribution is also defined to model the noise contained in CT data. The model is thoroughly validated in a simulated environment including 12 virtual patients under low and high iodine uptake scenarios, while incorporating noise and beam hardening effects. The eigentissue decomposition (ETD) technique is used to derive elemental compositions and parameters critical for radiotherapy from the dual-VNC images, such as electron density (ρ<sub>e</sub>), particle stopping power (SPR), and photon energy absorption coefficient (EAC)&#xD;Main results: The proposed method yields accurate voxelwise estimations for ρ<sub>e</sub>, SPR, and EAC, with root mean square errors of 3.09%, 3.14%, and 1.34% for highly-enhanced tissues, compared to 5.93%, 6.39%, and 17.11% when the presence of contrast agent is ignored. It also demonstrates robustness to systematic shifts in tissue composition and bandwidth variations in the prior distribution, resulting in overall uncertainties down to 1.13%, 1.33%, and 0.86% for ρ<sub>e</sub>, SPR, and EAC in soft tissues; 1.17%, 1.32%, and 1.34% in enhanced soft tissues; and 4.34%, 4.00%, and 2.50% in bone.&#xD;Significance: The proposed method accurately derives radiotherapy parameters from contrast-enhanced DECT data and demonstrates robustness against systematic errors in reference data, highlighting its potential for clinical use.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad965f">https://doi.org/10.1088/1361-6560/ad965f</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad9660" class="art-list-item-title event_main-link">ML-EM based dual tracer PET image reconstruction with inclusion of prompt gamma attenuation</a> <p class="small art-list-item-meta"> Elisabeth Pfaehler <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="ML-EM based dual tracer PET image reconstruction with inclusion of prompt gamma attenuation" data-link-purpose-append-open="ML-EM based dual tracer PET image reconstruction with inclusion of prompt gamma attenuation">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad9660/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, ML-EM based dual tracer PET image reconstruction with inclusion of prompt gamma attenuation</span></a> <a href="/article/10.1088/1361-6560/ad9660/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, ML-EM based dual tracer PET image reconstruction with inclusion of prompt gamma attenuation</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective: Conventionally, if two metabolic processes are of interest for image analysis, two separate, sequential PET scans are performed. However, sequential PET scans cannot simultaneously display the metabolic targets. The concurrent study of two simultaneous PET scans could provide new insights into the causes of diseases.&#xD;Approach: In this work, we propose a reconstruction algorithm for the simultaneous injection of a β+-emitter emitting only annihilation photons and a β+-γ-emitter emitting annihilation photons and an additional prompt γ-photon. As in previous works, the γ-photon is used to identify events originating from the β+-γ-emitter. However, due to e.g. attenuation, the γ-photon is often not&#xD;detected and not all events can correctly be associated with the β+-γ-emitter as they are detected as double coincidences. In contrast to previous works, we estimate this number of double coincidences with origin in the β+-γ, emitter including the attenuation of the prompt γ, and incorporate this estimation in the forward-projection of the ML-EM algorithm. For evaluation, we simulate different scenarios with&#xD;varying objects and attenuation maps. The nuclide 18F serves as β+-emitter, while 44Sc functions as β+-γ emitter. The performance of the algorithm is assessed by calculating the residual error of the β+-γ-emitter in the reconstructed β+-emitter image. Additionally, the intensity values in the simulated cylinders of the ground truth (GT) and the reconstructed images are compared. &#xD;Main Results: The remaining activity in the β+-emitter image varied from 0.4% to 3.7%. The absolute percentage difference between GT and reconstructed intensity for the pure β+ emitter images was found to be between 3.0 and 7.4% for all cases. The absolute percentage difference between GT and reconstructed intensity for the β+-γ emitter images ranged from 8.7 to 10.4% for all simulated cases. &#xD;Significance: These results demonstrate that our approach can reconstruct two separate images with a good quantitation accurac</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad9660">https://doi.org/10.1088/1361-6560/ad9660</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad8e2a" class="art-list-item-title event_main-link">Prompt gamma emission prediction using a long short-term memory network</a> <p class="small art-list-item-meta"> Fan Xiao <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235003 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Prompt gamma emission prediction using a long short-term memory network" data-link-purpose-append-open="Prompt gamma emission prediction using a long short-term memory network">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8e2a/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Prompt gamma emission prediction using a long short-term memory network</span></a> <a href="/article/10.1088/1361-6560/ad8e2a/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Prompt gamma emission prediction using a long short-term memory network</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>: To present a long short-term memory (LSTM)-based prompt gamma (PG) emission prediction method for proton therapy. <i>Approach</i>: Computed tomography (CT) scans of 33 patients with a prostate tumor were included in the dataset. A set of 10<sup>7</sup> histories proton pencil beam (PB)s was generated for Monte Carlo (MC) dose and PG simulation. For training (20 patients) and validation (3 patients), over 6000 PBs at 150, 175 and 200 MeV were simulated. 3D relative stopping power (RSP), PG and dose cuboids that included the PB were extracted. Three models were trained, validated and tested based on an LSTM-based network: (1) input RSP and output PG, (2) input RSP with dose and output PG (single-energy), and (3) input RSP/dose and output PG (multi-energy). 540 PBs at each of the four energy levels (150, 175, 200, and 125–210 MeV) were simulated across 10 patients to test the three models. The gamma passing rate (2%/2 mm) and PG range shift were evaluated and compared among the three models. <i>Results</i>: The model with input RSP/dose and output PG (multi-energy) showed the best performance in terms of gamma passing rate and range shift metrics. Its mean gamma passing rate of testing PBs of 125–210 MeV was 98.5% and the worst case was 92.8%. Its mean absolute range shift between predicted and MC PGs was 0.15 mm, where the maximum shift was 1.1 mm. The prediction time of our models was within 130 ms per PB. <i>Significance</i>: We developed a sub-second LSTM-based PG emission prediction method. Its accuracy in prostate patients has been confirmed across an extensive range of proton energies.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8e2a">https://doi.org/10.1088/1361-6560/ad8e2a</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad9544" class="art-list-item-title event_main-link">An improved calibration procedure for accurate plastic scintillation dosimetry on an MR-linac</a> <p class="small art-list-item-meta"> Madelon van den Dobbelsteen <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="An improved calibration procedure for accurate plastic scintillation dosimetry on an MR-linac" data-link-purpose-append-open="An improved calibration procedure for accurate plastic scintillation dosimetry on an MR-linac">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad9544/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, An improved calibration procedure for accurate plastic scintillation dosimetry on an MR-linac</span></a> <a href="/article/10.1088/1361-6560/ad9544/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, An improved calibration procedure for accurate plastic scintillation dosimetry on an MR-linac</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective: Plastic scintillation dosimeters (PSDs) are highly suitable for real-time dosimetry on the MR-linac. For optimal performance, the primary signal (scintillation) needs to be separated from secondary optical effects (Cerenkov, fluorescence and optical fiber attenuation). This requires a spectral separation approach and careful calibration. Currently, the 'classic' calibration is a multi-step procedure using both kV and MV X-ray sources, requiring an uninterrupted optical connection between the dosimeter and read-out system, complicating efficient use of PSDs. Therefore, we present a more time-efficient and more practical novel calibration technique for PSDs suitable for MR-linac dosimetry.&#xD;Approach: The novel calibration relies on prior spectral information combined with two 10x10 cm<sup>2</sup> field irradiations on the 1.5 T MR-linac. Performance of the novel calibration technique was evaluated focusing on its reproducibility, performance characteristics (repeatability, linearity, dose rate dependency, output factors, angular response and detector angle dependency) and IMRT deliveries. To investigate the calibration stability over time, prior spectral information up to 315 days old was used. To quantify the time efficiency, each step of the novel and classic calibration was timed.&#xD;Main results: The novel calibration showed a high reproducibility with a maximum relative standard deviation of 0.3%. The novel method showed maximum differences of 1.2% compared to the gold-standard calibration, while reusing old classic calibrations after reconnecting fibers showed differences up to 3.0%. The novel calibration improved time efficiency from 105 to 30 minutes compared to the classic method.&#xD;Significance: The novel calibration method showed a gain in time efficiency and practicality while preserving the dosimetric accuracy. Therefore, this method can replace the traditional method for PSDs suitable for MR-linac dosimetry, using prior spectral information of up to a year. This novel calibration facilitates reconnecting the detector to the read-out system which would lead to unacceptable dosimetric results with the classic calibration method.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad9544">https://doi.org/10.1088/1361-6560/ad9544</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6560/ad8fed" class="art-list-item-title event_main-link"><i>Ex vivo</i> validation of non-invasive phase correction for transspine focused ultrasound: model performance and target feasibility</a> <p class="small art-list-item-meta"> David Martin <em>et al</em> 2024 <em>Phys. Med. Biol.</em> <b>69</b> 235001 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Ex vivo validation of non-invasive phase correction for transspine focused ultrasound: model performance and target feasibility" data-link-purpose-append-open="Ex vivo validation of non-invasive phase correction for transspine focused ultrasound: model performance and target feasibility">Open abstract</span> </button> <a href="/article/10.1088/1361-6560/ad8fed/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Ex vivo validation of non-invasive phase correction for transspine focused ultrasound: model performance and target feasibility</span></a> <a href="/article/10.1088/1361-6560/ad8fed/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Ex vivo validation of non-invasive phase correction for transspine focused ultrasound: model performance and target feasibility</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> To evaluate the feasibility of transspine focused ultrasound using simulation-based phase corrections from a CT-derived ray acoustics model. <i>Approach.</i> Bilateral transspine focusing was performed in <i>ex vivo</i> human vertebrae with a spine-specific ultrasound array. Ray acoustics-derived phase correction was compared to geometric focusing and a hydrophone-corrected gold standard. Planar hydrophone scans were recorded in the spinal canal and three metrics were calculated: target pressure, coronal and sagittal focal shift, and coronal and sagittal Sørensen–Dice similarity to the free-field. <i>Post hoc</i> analysis was performed <i>in silico</i> to assess the impact of windows between vertebrae on focal shift. <i>Main results.</i> Hydrophone correction reduced mean sagittal plane shift from 1.74 ± 0.82 mm to 1.40 ± 0.82 mm and mean coronal plane shift from 1.07 ± 0.63 mm to 0.54 ± 0.49 mm. Ray acoustics correction reduced mean sagittal plane and coronal plane shift to 1.63 ± 0.83 mm and 0.83 ± 0.60 mm, respectively. Hydrophone correction increased mean sagittal similarity from 0.48 ± 0.22 to 0.68 ± 0.19 and mean coronal similarity from 0.48 ± 0.23 to 0.70 ± 0.19. Ray acoustics correction increased mean sagittal and coronal similarity to 0.53 ± 0.25 and 0.55 ± 0.26, respectively. Target pressure was relatively unchanged across beamforming methods. <i>In silico</i> analysis found that, for some targets, unoccluded paths may have increased focal shift. <i>Significance</i>. Gold standard phase correction significantly reduced coronal shift and significantly increased sagittal and coronal Sørensen–Dice similarity (<i>p</i> < 0.05). Ray acoustics-derived phase correction reduced sagittal and coronal shift and increased sagittal and coronal similarity but did not achieve statistical significance. Across beamforming methods, mean focal shift was comparable to MRI resolution, suggesting that transspine focusing is possible with minimal correction in favourable targets. Future work will explore the mitigation of acoustic windows with anti-focus control points.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6560/ad8fed">https://doi.org/10.1088/1361-6560/ad8fed</a> </div> </div> </div> </div> </div>  <p> <a href="/nsearch?currentPage=1&terms=&nextPage=2&previousPage=-1&searchDatePeriod=anytime&journals=0031-9155&accessType=open-access&orderBy=newest&pageLength=20">More Open Access articles</a> </p> </div> </div> </div>    </div>    <aside aria-label="Main column advert"> <div id='div-gpt-ad-1562594774007-0' style='width: 728px; height: 90px; display: block;'> <script> googletag.cmd.push(function () { googletag.display('div-gpt-ad-1562594774007-0'); }); </script> </div> </aside>   </div>  </div> </main> <div class="db2 tb2"> <div class="side-and-below">  <div class="sidebar-list" id="wd-jnl-links"> <h2 class="sidebar-list__heading">Journal links</h2> <ul class="sidebar-list__list"><li><a href="http://mc04.manuscriptcentral.com/pmb-ipem" target="_blank"><strong>Submit an article</strong></a></li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physics-in-medicine-biology/about-physics-medicine-biology/">About the journal</a></li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physics-in-medicine-biology/editorial-board/">Editorial board</a></li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physics-in-medicine-biology/">Author guidelines</a></li> <li><a href="https://publishingsupport.iopscience.iop.org/questions/volunteering-to-be-a-journal-reviewer">Review for this journal</li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physics-in-medicine-biology/about-physics-medicine-biology/#publication-charges">Publication charges</a></li> <li><a href="/0031-9155/page/Awards">Awards</a></p> <li><a href="/0031-9155/page/Journal_Collections">Journal collections</a></li> <li><a href="https://ioppublishing.org/librarians/">Pricing and ordering</a></li> <li><a href="/0031-9155/page/Contact_us">Contact us</a></li> </ul> </div>    <aside role="complementary" aria-label="Right sidebar adverts"> <div id='div-gpt-ad-1669279847892-0' style='min-width: 160px; 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