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international ovarian tumor analysis classification</title> <meta name="description" content="Search results for: international ovarian tumor analysis classification"> <meta name="keywords" content="international ovarian tumor analysis classification"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science 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class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="international ovarian tumor analysis classification"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 32120</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: international ovarian tumor analysis classification</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32120</span> Metastatic Ovarian Tumor Discovered Accidentally during Cesarean Section in a 34 Year Old Woman: A Case Report</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghada%20E.%20Esheba">Ghada E. Esheba</a>, <a href="https://publications.waset.org/abstracts/search?q=Ghufran%20Kheshaifaty"> Ghufran Kheshaifaty</a>, <a href="https://publications.waset.org/abstracts/search?q=Kholoud%20%20Al-Harbi"> Kholoud Al-Harbi</a>, <a href="https://publications.waset.org/abstracts/search?q=Wafa%27a%20Al-Harbi"> Wafa'a Al-Harbi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ala%27a%20Al-Orabi"> Ala'a Al-Orabi</a>, <a href="https://publications.waset.org/abstracts/search?q=Moayad%20Turkistani"> Moayad Turkistani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Krukenberg tumor is a rare metastatic ovarian carcinoma that usually occurs in female between 30 - 40 year old and rarely seen after menopause. Stomach is the most common primary site. Histopathological features of krukenberg tumors appear as diffuse stromal proliferation, mucus-production, and numerous signet-cells and these tumors spread mostly by lymphatic route. Treatment and prognostic factors are not well established. This study describes a 34 year old female with a unilateral ovarian mass discovered accidentally during cesarean section delivery and it was misdiagnosed as luteoma of pregnancy, but histopathological examination showed a diffuse infiltration of the ovary and omentum by signet ring cells. These findings were not correlated with luteoma of pregnancy or any other types of primary ovarian tumors like surface epithelial tumor, sex cord stromal tumor or germ cell tumor. However, after the analysis of immunohistochemical results (negative CK7, positive CK20 and CDX-2), the finding was the diagnostic of metastatic krukenberg tumor. Two weeks later, the patient was evaluated and a large gastric tumor was found in her stomach and she underwent gastrectomy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CK7" title="CK7">CK7</a>, <a href="https://publications.waset.org/abstracts/search?q=CK20" title=" CK20"> CK20</a>, <a href="https://publications.waset.org/abstracts/search?q=CDX-2" title=" CDX-2"> CDX-2</a>, <a href="https://publications.waset.org/abstracts/search?q=Krukenburg%20tumor" title=" Krukenburg tumor"> Krukenburg tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=metastatic%20ovarian%20tumor" title=" metastatic ovarian tumor"> metastatic ovarian tumor</a> </p> <a href="https://publications.waset.org/abstracts/59354/metastatic-ovarian-tumor-discovered-accidentally-during-cesarean-section-in-a-34-year-old-woman-a-case-report" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59354.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">315</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32119</span> WT1 Expression in Ovarian Malignant Surface Epithelial Tumors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahmoodreza%20Tahamtan">Mahmoodreza Tahamtan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Malignant surface epithelial ovarian tumors(SEOT) account for approximately 90% of primary ovarian cancer. We evaluate the immunohistochemical expression of WT1 protein among different histologic subtypes of SEOT. Immunohistochemistry for WT1 was done on 35 serous cystadenocarcinomas, 9 borderline serous tumors. A tumor was considered negative if < 1% of tumor cells were stained.Positive reactions were graded as follows:1+,1%-24%; 2+,25%-49%; 3+,50%-74%; 4+,75%-100%. Of the 35 cases of ovarian serous cystadenocarcinoma 30(85.7%)were diffusely positive(3+,4+),4 showed reactivity of < 50% of the tumor cells(1+,2+) and one were negative. All 9 borderline serous tumors showed immunoreactivity with WT1. WT1 is a good marker to distinguish primary ovarian serous carcinomas from other surface epithelial tumors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=WT1" title="WT1">WT1</a>, <a href="https://publications.waset.org/abstracts/search?q=ovary" title=" ovary"> ovary</a>, <a href="https://publications.waset.org/abstracts/search?q=malignant" title=" malignant"> malignant</a>, <a href="https://publications.waset.org/abstracts/search?q=epithelial%20tumors" title=" epithelial tumors"> epithelial tumors</a> </p> <a href="https://publications.waset.org/abstracts/160272/wt1-expression-in-ovarian-malignant-surface-epithelial-tumors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160272.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">102</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32118</span> Correlation of Clinical and Sonographic Findings with Cytohistology for Diagnosis of Ovarian Tumours</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Meenakshi%20Barsaul%20Chauhan">Meenakshi Barsaul Chauhan</a>, <a href="https://publications.waset.org/abstracts/search?q=Aastha%20Chauhan"> Aastha Chauhan</a>, <a href="https://publications.waset.org/abstracts/search?q=Shilpa%20Hurmade"> Shilpa Hurmade</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajeev%20Sen"> Rajeev Sen</a>, <a href="https://publications.waset.org/abstracts/search?q=Jyotsna%20Sen"> Jyotsna Sen</a>, <a href="https://publications.waset.org/abstracts/search?q=Monika%20Dalal"> Monika Dalal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Ovarian masses are common forms of neoplasm in women and represent 2/3rd of gynaecological malignancies. A pre-operative suggestion of malignancy can guide the gynecologist to refer women with suspected pelvic mass to a gynecological oncologist for appropriate therapy and optimized treatment, which can improve survival. In the younger age group preoperative differentiation into benign or malignant pathology can decide for conservative or radical surgery. Imaging modalities have a definite role in establishing the diagnosis. By using International Ovarian Tumor Analysis (IOTA) classification with sonography, costly radiological methods like Magnetic Resonance Imaging (MRI) / computed tomography (CT) scan can be reduced, especially in developing countries like India. Thus, this study is being undertaken to evaluate the role of clinical methods and sonography for diagnosis of the nature of the ovarian tumor. Material And Methods: This prospective observational study was conducted on 40 patients presenting with ovarian masses, in the Department of Obstetrics and Gynaecology, at a tertiary care center in northern India. Functional cysts were excluded. Ultrasonography and color Doppler were performed on all the cases.IOTA rules were applied, which take into account locularity, size, presence of solid components, acoustic shadow, dopper flow etc . Magnetic Resonance Imaging (MRI) / computed tomography (CT) scans abdomen and pelvis were done in cases where sonography was inconclusive. In inoperable cases, Fine needle aspiration cytology (FNAC) was done. The histopathology report after surgery and cytology report after FNAC was correlated statistically with the pre-operative diagnosis made clinically and sonographically using IOTA rules. Statistical Analysis: Descriptive measures were analyzed by using mean and standard deviation and the Student t-test was applied and the proportion was analyzed by applying the chi-square test. Inferential measures were analyzed by sensitivity, specificity, negative predictive value, and positive predictive value. Results: Provisional diagnosis of the benign tumor was made in 16(42.5%) and of the malignant tumor was made in 24(57.5%) patients on the basis of clinical findings. With IOTA simple rules on sonography, 15(37.5%) were found to be benign, while 23 (57.5%) were found to be malignant and findings were inconclusive in 2 patients (5%). FNAC/Histopathology reported that benign ovarian tumors were 14 (35%) and 26(65%) were malignant, which was taken as the gold standard. The clinical finding alone was found to have a sensitivity of 66.6% and a specificity of 90.9%. USG alone had a sensitivity of 86% and a specificity of 80%. When clinical findings and IOTA simple rules of sonography were combined (excluding inconclusive masses), the sensitivity and specificity were 83.3% and 92.3%, respectively. While including inconclusive masses, sensitivity came out to be 91.6% and specificity was 89.2. Conclusion: IOTA's simple sonography rules are highly sensitive and specific in the prediction of ovarian malignancy and also easy to use and easily reproducible. Thus, combining clinical examination with USG will help in the better management of patients in terms of time, cost and better prognosis. This will also avoid the need for costlier modalities like CT, and MRI. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=benign" title="benign">benign</a>, <a href="https://publications.waset.org/abstracts/search?q=international%20ovarian%20tumor%20analysis%20classification" title=" international ovarian tumor analysis classification"> international ovarian tumor analysis classification</a>, <a href="https://publications.waset.org/abstracts/search?q=malignant" title=" malignant"> malignant</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20tumours" title=" ovarian tumours"> ovarian tumours</a>, <a href="https://publications.waset.org/abstracts/search?q=sonography" title=" sonography"> sonography</a> </p> <a href="https://publications.waset.org/abstracts/160067/correlation-of-clinical-and-sonographic-findings-with-cytohistology-for-diagnosis-of-ovarian-tumours" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160067.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">80</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32117</span> Role of Human Epididymis Protein 4 as a Biomarker in the Diagnosis of Ovarian Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amar%20Ranjan">Amar Ranjan</a>, <a href="https://publications.waset.org/abstracts/search?q=Julieana%20Durai"> Julieana Durai</a>, <a href="https://publications.waset.org/abstracts/search?q=Pranay%20Tanwar"> Pranay Tanwar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background &Introduction: Ovarian cancer is one of the most common malignant tumor in the female. 70% of the cases of ovarian cancer are diagnosed at an advanced stage. The five-year survival rate associated with ovarian cancer is less than 30%. The early diagnosis of ovarian cancer becomes a key factor in improving the survival rate of patients. Presently, CAl25 (carbohydrate antigen125) is used for the diagnosis and therapeutic monitoring of ovarian cancer, but its sensitivity and specificity is not ideal. The introduction of HE4, human epididymis protein 4 has attracted much attention. HE4 has a sensitivity and specificity of 72.9% and 95% for differentiating between benign and malignant adnexal masses, which is better than CA125 detection. Methods: Serum HE4 and CA -125 were estimated using the chemiluminescence method. Our cases were 40 epithelial ovarian cancer, 9 benign ovarian tumor, 29 benign gynaecological diseases and 13 healthy individuals. This group include healthy woman those who have undergoing family planning and menopause-related medical consultations and they are negative for ovarian mass. Optimal cut off values for HE4 and CA125 were 55.89pmol/L and 40.25U/L respectively (determined by statistical analysis). Results: The level of HE4 was raised in all ovarian cancer patients (n=40) whereas CA125 levels were normal in 6/40 ovarian cancer patients, which were the cases of OC confirmed by histopathology. There is a significant decrease in the level of HE4 with comparison to CA125 in benign ovarian tumor cases. Both the levels of HE4 and CA125 were raised in the nonovarian cancer group, which includes cancer of endometrium and cervix. In the healthy group, HE4 was normal in all patients except in one case of the rudimentary horn, and the reason for this raised HE4 level is due to the incomplete development of uterus whereas CA125 was raised in 3 cases. Conclusions: Findings showed that the serum level of HE4 is an important indicator in the diagnosis of ovarian cancer, and it also distinguishes between benign and malignant pelvic masses. However, a combination of HE4 and CA125 panel will be extremely valuable in improving the diagnostic efficiency of ovarian cancer. These findings of our study need to be validated in the larger cohort of patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=human%20epididymis%20protein%204" title="human epididymis protein 4">human epididymis protein 4</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title=" ovarian cancer"> ovarian cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title=" diagnosis"> diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=benign%20lesions" title=" benign lesions"> benign lesions</a> </p> <a href="https://publications.waset.org/abstracts/108113/role-of-human-epididymis-protein-4-as-a-biomarker-in-the-diagnosis-of-ovarian-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108113.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">131</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32116</span> WT1 Exprassion in Malignant Surface Epithelial Ovarian Tumors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahmoodreza%20Tahamtan">Mahmoodreza Tahamtan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Malignant surface epithelial ovarian tumors (SEOT) account for approximately 90% of primary ovarian cancer. Wilms tumor gene (WT1) product was defined as a tumor suppressor gene, but today it is considered capable of performing oncogenic functions. There seems to be differences in WT1 expression patterns among SEOT subtypes. We evaluate the immunohistochemical expression of WT1 protein among different histologic subtypes of SEOT. Materials and Methods: Immunohistochemistry for WT1 was done on 35 serous cystadenocarcinomas, 9 borderline serous tumors, 3 mucinous cystadenocarcinomas, 10 borderline mucinous tumors, 7 endometrioid ovarian carcinomas, 3 clear cell carcinomas, 1 malignant Brenner tumor, 2 metastatic adenocarcinomas, and 6 endometrial adenocarcinomas. A tumor was considered negative if < 1% of tumor cells were stained.Positive reactions were graded as follows:1+,1%-24%; 2+,25%-49%; 3+,50%-74%; 4+,75%-100%. Results: Of the 35 cases of ovarian serous cystadenocarcinoma, 30(85.7%) were diffusely positive (3+,4+),4 showed reactivity of < 50% of the tumor cells (1+,2+), and one were negative. All 9 borderline serous tumors showed immunoreactivity with WT1. All the mucinous tumors(n:13), endometrioid carcinomas (n: 7), clear cell carcinomas (n: 3), metastatic adenocarcinomas (n: 2) and primary endometrial carcinomas (n:6) were negative. The single malignant Brenner tumor showed a positive reaction for WT1(4+) Conclusion: WT1 is a good marker to distinguish primary ovarian serous carcinomas from other surface epithelial tumors (especially endometrioid subtype) and metastatic carcinomas (especially endometrial serous carcinoma), other than malignant mesothelioma. We cannot rely to the degree of expression inorder to separate high grade borderline serous tumors from low grade ones. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=WT1" title="WT1">WT1</a>, <a href="https://publications.waset.org/abstracts/search?q=ovary" title=" ovary"> ovary</a>, <a href="https://publications.waset.org/abstracts/search?q=epithelial%20tumors" title=" epithelial tumors"> epithelial tumors</a>, <a href="https://publications.waset.org/abstracts/search?q=malignant" title=" malignant"> malignant</a> </p> <a href="https://publications.waset.org/abstracts/159905/wt1-exprassion-in-malignant-surface-epithelial-ovarian-tumors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159905.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">103</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32115</span> Automated 3D Segmentation System for Detecting Tumor and Its Heterogeneity in Patients with High Grade Ovarian Epithelial Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dimitrios%20Binas">Dimitrios Binas</a>, <a href="https://publications.waset.org/abstracts/search?q=Marianna%20Konidari"> Marianna Konidari</a>, <a href="https://publications.waset.org/abstracts/search?q=Charis%20Bourgioti"> Charis Bourgioti</a>, <a href="https://publications.waset.org/abstracts/search?q=Lia%20Angela%20Moulopoulou"> Lia Angela Moulopoulou</a>, <a href="https://publications.waset.org/abstracts/search?q=Theodore%20Economopoulos"> Theodore Economopoulos</a>, <a href="https://publications.waset.org/abstracts/search?q=George%20Matsopoulos"> George Matsopoulos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> High grade ovarian epithelial cancer (OEC) is fatal gynecological cancer and the poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study proposes a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20segmentation" title="image segmentation">image segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20epithelial%20cancer" title=" ovarian epithelial cancer"> ovarian epithelial cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=quantitative%20characteristics" title=" quantitative characteristics"> quantitative characteristics</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20registration" title=" image registration"> image registration</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20visualization" title=" tumor visualization"> tumor visualization</a> </p> <a href="https://publications.waset.org/abstracts/139039/automated-3d-segmentation-system-for-detecting-tumor-and-its-heterogeneity-in-patients-with-high-grade-ovarian-epithelial-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139039.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">211</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32114</span> Borderline Ovarian Tumor: Management of Recurrence After Conservative Surgical Treatment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghorbeli%20Eya">Ghorbeli Eya</a>, <a href="https://publications.waset.org/abstracts/search?q=Naija%20Lamia"> Naija Lamia</a>, <a href="https://publications.waset.org/abstracts/search?q=Khessairi%20Nayssem"> Khessairi Nayssem</a>, <a href="https://publications.waset.org/abstracts/search?q=Saadallah%20Fatma"> Saadallah Fatma</a>, <a href="https://publications.waset.org/abstracts/search?q=Slimane%20Maher"> Slimane Maher</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarek%20Ben%20Dhiab"> Tarek Ben Dhiab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> INTRODUCTION: Borderline ovarian tumors account for 15 to 20% of ovarian tumors. Prognostic factors of recurrence include the stage of the disease, presence of peritoneal implants, micropapillary pattern, microinvasion and intra-epithelial carcinoma. Fertility sparing constitutes a major therapeutic issue in young patients that leads to conservative surgical treatment in specific cases. METHODS: We conducted a retrospective descriptive study including patients treated at the Salah Azaiez Institute for Borderline Ovarian Tumor who underwent conservative surgical treatment from 2003 to 2018. RESULTS: Nine patients were included in our study. The median age was 33 years. Three patients were nulliparous. Given the age, conservative treatment was indicated in all these patients. Cystectomy without ovariectomy was indicated in 5 of the 9 women, which was within the margin of tumor resection on definitive anatomopathic examination in 3 of the 5 women. In contrast, given the impossibility of ovarian conservation, total annexectomy was carried out in 4 of all these women. All of the patients were followed regularly postoperatively; three had a carcinomatous transformation as an ovarian adenocarcinoma at an average interval of 18 months. Among these three patients, a single one presented intra-peritoneal metastases, requiring radical surgical treatment and adjuvant chemotherapy with 6 cures of Carbo-Taxol, with a good tolerance and a complete response. Moreover, one patient had a recurrence on the contralateral ovary as a Borderline mucinous ovarian tumor. For the remaining four women, after a median follow-up of 35 months, one patient fell spontaneously pregnant during follow-up, and three patients were in complete remission at 16 months. CONCLUSION: Borderline tumors of the ovary usually occur in young patients, which makes conservative treatment advisable if possible, but this always comes with a risk of recurrence and/or carcinomatous transformation, especially if the conservative surgical procedure was a cystectomy instead of a total annexectomy, and even more so if the resection margins were tumoral. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ovarian%20tumor" title="ovarian tumor">ovarian tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=conservative%20treatment" title=" conservative treatment"> conservative treatment</a>, <a href="https://publications.waset.org/abstracts/search?q=surgical%20management" title=" surgical management"> surgical management</a>, <a href="https://publications.waset.org/abstracts/search?q=borderline%20ovarian%20tumor" title=" borderline ovarian tumor"> borderline ovarian tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=recurrence%20management" title=" recurrence management"> recurrence management</a> </p> <a href="https://publications.waset.org/abstracts/190122/borderline-ovarian-tumor-management-of-recurrence-after-conservative-surgical-treatment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190122.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">28</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32113</span> Expression of Hypoxia-Inducible Transmembrane Carbonic Anhydrases IX, Ca XII and Glut 1 in Ovarian Cancer </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Sunitha">M. Sunitha</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Nithyavani"> B. Nithyavani</a>, <a href="https://publications.waset.org/abstracts/search?q=Mathew%20Yohannan"> Mathew Yohannan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Thiruvieni%20Balajji"> S. Thiruvieni Balajji</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Rathi"> M. A. Rathi</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Arul%20Raj"> C. Arul Raj</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Ragavendran"> P. Ragavendran</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20K.%20Gopalkrishnan"> V. K. Gopalkrishnan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Establishment of an early and reliable biomarker for ovarian carcinogenesis whose expression can be monitored through noninvasive techniques will enable early diagnosis of cancer. Carbonic anhydrases (CA) isozymes IX and XII have been suggested to play a role in oncogenic processes. In von Hippel-Lindau (VHL)-defective tumors, the cell surface transmembrane carbonic anhydrase (CA) CA XI and CA XII genes are overexpressed because of the absence of pVHL. These enzymes are involved in causing a hypoxia condition, thereby providing an environment for metastasis. Aberrant expression of the facilitative glucose transporter GLUT I is found in a wide spectrum of epithelial malignancies. Studying the mRNA expression of CA IX, CA XII and Glut I isozymes in ovarian cancer cell lines (OAW-42 and PA-1) revealed the expression of these hypoxia genes. Immunohistochemical staining of carbonic anhydrases was also performed in 40 ovarian cancer tissues. CA IX and CA XII were expressed at 540 bp and 520 bp in OAW42, PA1 in ovarian cancer cell lines. GLUT-1 was expressed at 325bp in OAW 42, PA1 genes in ovarian cancer cell lines. Immunohistochemistry revealed high to moderate levels of expression of these enzymes. The immuostaining was seen predominantly on the cell surface membrane. The study concluded that these genes CA IX, CA XII and Glut I are expressed under hypoxic condition in tumor cells. From the present results expression of CA IX, XII and Glut I may represent potential targets in ovarian cancer therapy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title="ovarian cancer">ovarian cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=carbonic%20anhydrase%20IX" title=" carbonic anhydrase IX"> carbonic anhydrase IX</a>, <a href="https://publications.waset.org/abstracts/search?q=XII" title=" XII"> XII</a>, <a href="https://publications.waset.org/abstracts/search?q=Glut%20I" title=" Glut I"> Glut I</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20markers" title=" tumor markers "> tumor markers </a> </p> <a href="https://publications.waset.org/abstracts/9998/expression-of-hypoxia-inducible-transmembrane-carbonic-anhydrases-ix-ca-xii-and-glut-1-in-ovarian-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9998.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">369</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32112</span> Predictive Value of ¹⁸F-Fluorodeoxyglucose Accumulation in Visceral Fat Activity to Detect Epithelial Ovarian Cancer Metastases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20F.%20Suleimanov">A. F. Suleimanov</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20B.%20Saduakassova"> A. B. Saduakassova</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20S.%20Pokrovsky"> V. S. Pokrovsky</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20V.%20Vinnikov"> D. V. Vinnikov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Relevance: Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, with relapse occurring in about 70% of advanced cases with poor prognoses. The aim of the study was to evaluate functional visceral fat activity (VAT) evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in epithelial ovarian cancer (EOC). Materials and methods: We assessed 53 patients with histologically confirmed EOC who underwent ¹⁸F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVₘₐₓ) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also identified the best areas under the curve (AUC) for SUVₘₐₓ with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted-for regression models and ROC analysis, ¹⁸F-FDG accumulation in RE (cut-off SUVₘₐₓ 1.18; Se 64%; Sp 64%; AUC 0.669; p = 0.035) could predict later metastases in EOC patients, as opposed to age, sex, primary tumor location, tumor grade, and histology. Conclusions: VAT SUVₘₐₓ is significantly associated with later metastases in EOC patients and can be used as their predictor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=%C2%B9%E2%81%B8F-FDG" title="¹⁸F-FDG">¹⁸F-FDG</a>, <a href="https://publications.waset.org/abstracts/search?q=PET%2FCT" title=" PET/CT"> PET/CT</a>, <a href="https://publications.waset.org/abstracts/search?q=EOC" title=" EOC"> EOC</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20value" title=" predictive value"> predictive value</a> </p> <a href="https://publications.waset.org/abstracts/150624/predictive-value-of-18f-fluorodeoxyglucose-accumulation-in-visceral-fat-activity-to-detect-epithelial-ovarian-cancer-metastases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150624.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">64</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32111</span> Targeted Photodynamic Therapy for Intraperitoneal Ovarian Cancer, A Way to Stimulate Anti-Tumoral Immune Response</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lea%20Boidin">Lea Boidin</a>, <a href="https://publications.waset.org/abstracts/search?q=Martha%20Baydoun"> Martha Baydoun</a>, <a href="https://publications.waset.org/abstracts/search?q=Bertrand%20Leroux"> Bertrand Leroux</a>, <a href="https://publications.waset.org/abstracts/search?q=Olivier%20Morales"> Olivier Morales</a>, <a href="https://publications.waset.org/abstracts/search?q=Samir%20Acherar"> Samir Acherar</a>, <a href="https://publications.waset.org/abstracts/search?q=Celine%20Frochot"> Celine Frochot</a>, <a href="https://publications.waset.org/abstracts/search?q=Nadira%20Delhem"> Nadira Delhem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ovarian cancer (OC) is one of the most defying diseases in gynecologic oncology. Even though surgery remains crucial in the therapy of patients with primary ovarian cancer, recurrent recidivism calls for the development of new therapy protocols to propose for patients dealing with this cancer. FRα is described as a tumor‐associated antigen in OC, where FRα expression is usually linked with more poorly differentiated, aggressive tumors. The Photodynamic treatment (PDT) available data have shown improvements in the uptake of small tumors and in the induction of a proper anti-tumoral immune response. In order to target specifically peritoneal metastatis, which overexpress FRα, a new-patented PS coupled with folic acid has been developed in our team. Herein we propose PDT using this new patented PS for PDT applied in an in vivo mice model. The efficacy of the treatment was evaluated in mice without and with PBMC reconstitution. Mice were divided into four groups: Non-Treated, PS, Light Only, and PDT Treated and subjected to illumination by laser set at 668nm with a duration of illumination of 45 minutes (or 1 min of illumination followed by 2 minutes of pause repeated 45 times). When mice were not reconstituted and after fractionized PDT protocol, a significant decrease in the tumor volume was noticed. An induction in the anti-tumoral cytokine IFNγ chaperoned this decrease while a subsequent inhibition in the cytokine TGFβ. Even more crucial, when mice were reconstituted and upon PDT, the fold of tumor decrease was even higher. An immune response was activated decoded with an increase in NK, CD3 +, LT helper and Cytotoxic T cells. Thereafter, an increase in the expression of the cytokines IFNγ and TNFα were noticed while an inhibition in TGFβ, IL8 and IL10 accompanied this immune response activation. Therefore, our work has shown for the first time that a fractionized PDT protocol using a folate-targeted PDT is effective for treatment of ovarian cancer. The interest in using PDT in this case, goes beyond the local induction of tumor apoptosis only, but can promote subsequent anti-tumor response. Most of the therapies currently used to treat ovarian cancer, have an uncooperative outcomes on the host immune response. The readiness of a tumor adjuvant treatment like PDT adequate in eliminating the tumor and in concert stimulating anti-tumor immunity would be weighty. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=folate%20receptor" title="folate receptor">folate receptor</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title=" ovarian cancer"> ovarian cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=photodynamic%20therapy" title=" photodynamic therapy"> photodynamic therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=humanized%20mice%20model" title=" humanized mice model"> humanized mice model</a> </p> <a href="https://publications.waset.org/abstracts/151346/targeted-photodynamic-therapy-for-intraperitoneal-ovarian-cancer-a-way-to-stimulate-anti-tumoral-immune-response" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151346.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">110</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32110</span> Blood Thicker Than Water: A Case Report on Familial Ovarian Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Joanna%20Marie%20A.%20Paulino-Morente">Joanna Marie A. Paulino-Morente</a>, <a href="https://publications.waset.org/abstracts/search?q=Vaneza%20Valentina%20L.%20Penolio"> Vaneza Valentina L. Penolio</a>, <a href="https://publications.waset.org/abstracts/search?q=Grace%20Sabado"> Grace Sabado</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ovarian cancer is extremely hard to diagnose in its early stages, and those afflicted at the time of diagnosis are typically asymptomatic and in the late stages of the disease, with metastasis to other organs. Ovarian cancers often occur sporadically, with only 5% associated with hereditary mutations. Mutations in the BRCA1 and BRCA2 tumor suppressor genes have been found to be responsible for the majority of hereditary ovarian cancers. One type of ovarian tumor is Malignant Mixed Mullerian Tumor (MMMT), which is a very rare and aggressive type, accounting for only 1% of all ovarian cancers. Reported is a case of a 43-year-old G3P3 (3003), who came into our institution due to a 2-month history of difficulty of breathing. Family history reveals that her eldest and younger sisters both died of ovarian malignancy, with her younger sister having a histopathology report of endometrioid ovarian carcinoma, left ovary stage IIIb. She still has 2 asymptomatic sisters. Physical examination pointed to pleural effusion of right lung, and presence of bilateral ovarian new growth, which had a Sassone score of 13. Admitting Diagnosis was G3P3 (3003), Ovarian New Growth, bilateral, Malignant; Pleural effusion secondary to malignancy. BRCA was requested to establish a hereditary mutation; however, the patient had no funds. Once the patient was stabilized, TAHBSO with surgical staging was performed. Intraoperatively, the pelvic cavity was occupied by firm, irregularly shaped ovaries, with a colorectal metastasis. Microscopic sections from both ovaries and the colorectal metastasis had pleomorphic tumor cells lined by cuboidal to columnar epithelium exhibiting glandular complexity, displaying nuclear atypia and increased nuclear-cytoplasmic ratio, which are infiltrating the stroma, consistent with the features of Malignant Mixed Mullerian Tumor, since MMMT is composed histologically of malignant epithelial and sarcomatous elements. In conclusion, discussed is the clinic-pathological feature of a patient with primary ovarian Malignant Mixed Mullerian Tumor, a rare malignancy comprising only 1% of all ovarian neoplasms. Also, by understanding the hereditary ovarian cancer syndromes and its relation to this patient, it cannot be overemphasized that a comprehensive family history is really fundamental for early diagnosis. The familial association of the disease, given that the patient has two sisters who were diagnosed with an advanced stage of ovarian cancer and succumbed to the disease at a much earlier age than what is reported in the general population, points to a possible hereditary syndrome which occurs in only 5% of ovarian neoplasms. In a low-resource setting, being in a third world country, the following will be recommended for monitoring and/or screening women who are at high risk for developing ovarian cancer, such as the remaining sisters of the patient: 1) Physical examination focusing on the breast, abdomen, and rectal area every 6 months. 2) Transvaginal sonography every 6 months. 3) Mammography annually. 4) CA125 for postmenopausal women. 5) Genetic testing for BRCA1 and BRCA2 will be reserved for those who are financially capable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BRCA" title="BRCA">BRCA</a>, <a href="https://publications.waset.org/abstracts/search?q=hereditary%20breast-ovarian%20cancer%20syndrome" title=" hereditary breast-ovarian cancer syndrome"> hereditary breast-ovarian cancer syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=malignant%20mixed%20mullerian%20tumor" title=" malignant mixed mullerian tumor"> malignant mixed mullerian tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title=" ovarian cancer"> ovarian cancer</a> </p> <a href="https://publications.waset.org/abstracts/33478/blood-thicker-than-water-a-case-report-on-familial-ovarian-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33478.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">289</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32109</span> Evaluation of Tumor-Infiltrating Lymphocytes in Breast Carcinoma: Correlation with Molecular Subtypes and Clinicopathological Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arundhathi%20S.">Arundhathi S.</a>, <a href="https://publications.waset.org/abstracts/search?q=Poongodi%20R."> Poongodi R.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tumor-infiltrating lymphocytes (TILs) are indicative of the local immune response against tumor proliferation and metastasis. Emerging as a significant marker of immune reactivity, TILs are utilized to evaluate prognostic outcomes across various malignancies, including colon, ovarian, lung, bladder, and breast cancers. In breast cancer (BC), TILs are particularly relevant for assessing tumor response to therapy in both adjuvant and neoadjuvant settings, with a prominent role in triple-negative breast cancer (TNBC), where they have been associated with improved outcomes. As such, TILs are recognized as an independent marker of favorable prognosis in several tumor types, underscoring their potential as a tool in personalized cancer therapy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title="breast cancer">breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=intratumoral%20TIL" title=" intratumoral TIL"> intratumoral TIL</a>, <a href="https://publications.waset.org/abstracts/search?q=stromal%20TIL" title=" stromal TIL"> stromal TIL</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20infiltrating%20lymphocytes" title=" tumor infiltrating lymphocytes"> tumor infiltrating lymphocytes</a> </p> <a href="https://publications.waset.org/abstracts/194529/evaluation-of-tumor-infiltrating-lymphocytes-in-breast-carcinoma-correlation-with-molecular-subtypes-and-clinicopathological-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194529.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">8</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32108</span> Utility of CK7, CK20 and CDX-2 as a Potential Panel in Differentiating Primary Ovarian Surface Epithelial Tumors from Metastatic Adenocarcinoma to the Ovary</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghada%20Esheba">Ghada Esheba</a>, <a href="https://publications.waset.org/abstracts/search?q=Ghadeer%20Aldoobi"> Ghadeer Aldoobi</a>, <a href="https://publications.waset.org/abstracts/search?q=Salwa%20Almalk"> Salwa Almalk</a>, <a href="https://publications.waset.org/abstracts/search?q=Abrar%20Alshareef"> Abrar Alshareef</a>, <a href="https://publications.waset.org/abstracts/search?q=Eman%20Al-khairi"> Eman Al-khairi</a>, <a href="https://publications.waset.org/abstracts/search?q=Eman%20Yaseen"> Eman Yaseen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: In Saudi Arabia, ovarian cancer ranked seventh among female population and is the most common female genital tract malignancy after endometrial cancer. A slight increase in the incidence of ovarian cancer was observed from 2001–2008. Makkah, Riyadh, and the eastern region of Saudi Arabia had the highest incidence rate ratio for the number of ovarian cancer cases (1). Differentiating metastatic adenocarcinomas from primary ovarian carcinomas, especially those of endometrioid and mucinous type is clinically signiﬁcant and a challenge for clinicians and pathologists, yet the distinction has important therapeutic and prognostic implications. Aim: To clarify the most important histopathological criteria to differentiate between primary ovarian surface epithelial tumors especially mucinous and endometrioid subtypes, and metastatic adenocarcinoma and to evaluate the value of a panel of antibodies consisting of CK7, CK20, and CDX-2 in the distinction between primary ovarian surface epithelial tumors and metastatic adenocarcinoma. Material and methods: This study was carried out on 26 cases of primary ovarian surface epithelial neoplasms and 14 cases of metastatic ovarian adenocarcinoma. All cases were studied immunohistochemically using CK7, CK20, and CDX-2. Results: All cases of primary ovarian adenocarcinoma were positive for CK7. 25% and 58% of mucinous borderline mucinous tumor and mucinous carcinoma respectively were positive for CK20. Only 42% of mucinous carcinoma were positive for CDX-2. All cases of endometrioid carcinomas were negative for both CK20 and CDX-2. All cases of metastatic adenocarcinoma from the colon were negative for CK7 and positive for CK20 and CDX-2. Conclusions: CK7 is an important positive marker for primary ovarian tumors, while CK20 and CDX-2 are useful markers for colorectal carcinoma metastatic to the ovary. Caution should be taken as primary ovarian mucinous tumors may stain positive for CK20, CDX-2, or both, however, they usually exhibit a focal pattern of reactivity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adenoma" title="adenoma">adenoma</a>, <a href="https://publications.waset.org/abstracts/search?q=endometrioid" title=" endometrioid"> endometrioid</a>, <a href="https://publications.waset.org/abstracts/search?q=malignancy" title=" malignancy"> malignancy</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian" title=" ovarian"> ovarian</a> </p> <a href="https://publications.waset.org/abstracts/43930/utility-of-ck7-ck20-and-cdx-2-as-a-potential-panel-in-differentiating-primary-ovarian-surface-epithelial-tumors-from-metastatic-adenocarcinoma-to-the-ovary" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43930.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">232</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32107</span> MSIpred: A Python 2 Package for the Classification of Tumor Microsatellite Instability from Tumor Mutation Annotation Data Using a Support Vector Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chen%20Wang">Chen Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chun%20Liang"> Chun Liang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Microsatellite instability (MSI) is characterized by high degree of polymorphism in microsatellite (MS) length due to a deficiency in mismatch repair (MMR) system. MSI is associated with several tumor types and its status can be considered as an important indicator for tumor prognostic. Conventional clinical diagnosis of MSI examines PCR products of a panel of MS markers using electrophoresis (MSI-PCR) which is laborious, time consuming, and less reliable. MSIpred, a python 2 package for automatic classification of MSI was released by this study. It computes important somatic mutation features from files in mutation annotation format (MAF) generated from paired tumor-normal exome sequencing data, subsequently using these to predict tumor MSI status with a support vector machine (SVM) classifier trained by MAF files of 1074 tumors belonging to four types. Evaluation of MSIpred on an independent 358-tumor test set achieved overall accuracy of over 98% and area under receiver operating characteristic (ROC) curve of 0.967. These results indicated that MSIpred is a robust pan-cancer MSI classification tool and can serve as a complementary diagnostic to MSI-PCR in MSI diagnosis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microsatellite%20instability" title="microsatellite instability">microsatellite instability</a>, <a href="https://publications.waset.org/abstracts/search?q=pan-cancer%20classification" title=" pan-cancer classification"> pan-cancer classification</a>, <a href="https://publications.waset.org/abstracts/search?q=somatic%20mutation" title=" somatic mutation"> somatic mutation</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/93236/msipred-a-python-2-package-for-the-classification-of-tumor-microsatellite-instability-from-tumor-mutation-annotation-data-using-a-support-vector-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93236.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">173</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32106</span> Automatic Staging and Subtype Determination for Non-Small Cell Lung Carcinoma Using PET Image Texture Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seyhan%20Kara%C3%A7avu%C5%9F">Seyhan Karaçavuş</a>, <a href="https://publications.waset.org/abstracts/search?q=B%C3%BClent%20Y%C4%B1lmaz"> Bülent Yılmaz</a>, <a href="https://publications.waset.org/abstracts/search?q=%C3%96mer%20Kayaalt%C4%B1"> Ömer Kayaaltı</a>, <a href="https://publications.waset.org/abstracts/search?q=Semra%20%C4%B0%C3%A7er"> Semra İçer</a>, <a href="https://publications.waset.org/abstracts/search?q=Arzu%20Ta%C5%9Fdemir"> Arzu Taşdemir</a>, <a href="https://publications.waset.org/abstracts/search?q=O%C4%9Fuzhan%20Ayy%C4%B1ld%C4%B1z"> Oğuzhan Ayyıldız</a>, <a href="https://publications.waset.org/abstracts/search?q=K%C3%BCbra%20Eset"> Kübra Eset</a>, <a href="https://publications.waset.org/abstracts/search?q=Eser%20Kaya"> Eser Kaya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by <em>k</em>-nearest neighbors (<em>k</em>-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with <em>k</em>-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cancer%20stage" title="cancer stage">cancer stage</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer%20cell%20type" title=" cancer cell type"> cancer cell type</a>, <a href="https://publications.waset.org/abstracts/search?q=non-small%20cell%20lung%20carcinoma" title=" non-small cell lung carcinoma"> non-small cell lung carcinoma</a>, <a href="https://publications.waset.org/abstracts/search?q=PET" title=" PET"> PET</a>, <a href="https://publications.waset.org/abstracts/search?q=texture%20analysis" title=" texture analysis"> texture analysis</a> </p> <a href="https://publications.waset.org/abstracts/43698/automatic-staging-and-subtype-determination-for-non-small-cell-lung-carcinoma-using-pet-image-texture-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43698.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">326</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32105</span> Update on Epithelial Ovarian Cancer (EOC), Types, Origin, Molecular Pathogenesis, and Biomarkers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salina%20Yahya%20Saddick">Salina Yahya Saddick</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=epithelial%20ovarian%20cancers" title="epithelial ovarian cancers">epithelial ovarian cancers</a>, <a href="https://publications.waset.org/abstracts/search?q=somatic%20sequence%20mutations" title=" somatic sequence mutations"> somatic sequence mutations</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer%20stem%20cell%20%28CSC%29" title=" cancer stem cell (CSC)"> cancer stem cell (CSC)</a>, <a href="https://publications.waset.org/abstracts/search?q=potential%20protein" title=" potential protein"> potential protein</a>, <a href="https://publications.waset.org/abstracts/search?q=biomarker" title=" biomarker"> biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=genomic%20analysis" title=" genomic analysis"> genomic analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=FGF18%20biomarker" title=" FGF18 biomarker"> FGF18 biomarker</a> </p> <a href="https://publications.waset.org/abstracts/25939/update-on-epithelial-ovarian-cancer-eoc-types-origin-molecular-pathogenesis-and-biomarkers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25939.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">380</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32104</span> Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Atanu%20K%20Samanta">Atanu K Samanta</a>, <a href="https://publications.waset.org/abstracts/search?q=Asim%20Ali%20Khan"> Asim Ali Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain%20tumor" title="brain tumor">brain tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=computer-aided%20diagnostic%20%28CAD%29%20system" title=" computer-aided diagnostic (CAD) system"> computer-aided diagnostic (CAD) system</a>, <a href="https://publications.waset.org/abstracts/search?q=gray-level%20co-occurrence%20matrix%20%28GLCM%29" title=" gray-level co-occurrence matrix (GLCM)"> gray-level co-occurrence matrix (GLCM)</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20segmentation" title=" tumor segmentation"> tumor segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=level%20set%20method" title=" level set method"> level set method</a> </p> <a href="https://publications.waset.org/abstracts/61237/computer-aided-diagnostic-system-for-detection-and-classification-of-a-brain-tumor-through-mri-using-level-set-based-segmentation-technique-and-ann-classifier" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61237.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">512</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32103</span> Liver Tumor Detection by Classification through FD Enhancement of CT Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Ghatwary">N. Ghatwary</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ahmed"> A. Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Jalab"> H. Jalab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20differential%20%28FD%29" title="fractional differential (FD)">fractional differential (FD)</a>, <a href="https://publications.waset.org/abstracts/search?q=computed%20tomography%20%28CT%29" title=" computed tomography (CT)"> computed tomography (CT)</a>, <a href="https://publications.waset.org/abstracts/search?q=fusion" title=" fusion"> fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=aplha" title=" aplha"> aplha</a>, <a href="https://publications.waset.org/abstracts/search?q=texture%20features." title=" texture features."> texture features.</a> </p> <a href="https://publications.waset.org/abstracts/39719/liver-tumor-detection-by-classification-through-fd-enhancement-of-ct-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39719.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">358</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32102</span> Diagnosis and Analysis of Automated Liver and Tumor Segmentation on CT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20R.%20Ramsheeja">R. R. Ramsheeja</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Sreeraj"> R. Sreeraj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computed%20tomography%20%28CT%29" title="computed tomography (CT)">computed tomography (CT)</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20region%20of%20interest%28ROI%29" title=" multiple region of interest(ROI)"> multiple region of interest(ROI)</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20values" title=" feature values"> feature values</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation" title=" segmentation"> segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM%20classification" title=" SVM classification"> SVM classification</a> </p> <a href="https://publications.waset.org/abstracts/18207/diagnosis-and-analysis-of-automated-liver-and-tumor-segmentation-on-ct" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18207.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">509</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32101</span> Clinicopathological and Immunohistochemical Study of Ovarian Sex Cord-Stromal Tumors and Their Histological Mimics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghada%20Esheba">Ghada Esheba</a>, <a href="https://publications.waset.org/abstracts/search?q=Ebtisam%20Aljerayan"> Ebtisam Aljerayan</a>, <a href="https://publications.waset.org/abstracts/search?q=Afnan%20Al-Ghamdi"> Afnan Al-Ghamdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Atheer%20Alsharif"> Atheer Alsharif</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanan%20alzahrani"> Hanan alzahrani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Primary ovarian neoplasms comprise a heterogeneous group of tumors of three main subtypes: surface epithelial, germ cell, and sex cord-stromal. The wide morphological variation within and between these groups can result in diagnostic difficulties. Gonadal sex cord-stromal tumors (SCST) represent one of the most heterogeneous categories of human neoplasms, because they may contain various combinations of different gonadal sex cord and stromal element. Aim: The aim of this work is to highlight the clinicopathological characteristics of SCST and to assess the value of alpha-inhibin and calretinin in the distinction between SCST and their mimics. Material and methods: This study was carried out on 100 cases using full tissue sections; 70 cases were SCST and 30 cases were histological mimics of SCST. The cases were studied using immunohistochemically using alpha-inhibin. In addition, an ovarian tissue microarray containing 170 benign and malignant ovarian neoplasms was also studied immunohistochemically for calretinin expression. The ovarian microarray included 14 SCST, 59 ovarian serous borderline tumors, 17 mucinous borderline tumors, 10 mucinous adenocarcinomas, 32 endometrioid adenocarcinomas, 34 clear cell carcinomas, and 4 germ cell tumors. Results: 99% of SCST examined using full tissue sections exhibited positive cytoplasmic staining for inhibin. On the contrary, only 7% of the histological mimics (P value < 0.0001). 86% of SCST in the tissue microarray were positive for calretinin with nuclear and/or cytoplasmic staining compared to only 7% of the other tumor types (P value < 0.0001). Conclusions: SCST have characteristic clinicopathological and immunohistochemical features and their recognition is crucial for proper diagnosis and treatment. Alpha-inhibin and calretinin are of great help in the diagnosis of sex cord-stromal tumors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=calretinin" title="calretinin">calretinin</a>, <a href="https://publications.waset.org/abstracts/search?q=granulosa%20cell%20tumor" title=" granulosa cell tumor"> granulosa cell tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=inhibin" title=" inhibin"> inhibin</a>, <a href="https://publications.waset.org/abstracts/search?q=sex%20cord-stromal%20tumors" title=" sex cord-stromal tumors "> sex cord-stromal tumors </a> </p> <a href="https://publications.waset.org/abstracts/40762/clinicopathological-and-immunohistochemical-study-of-ovarian-sex-cord-stromal-tumors-and-their-histological-mimics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40762.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">208</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32100</span> Development of a Computer Aided Diagnosis Tool for Brain Tumor Extraction and Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fathi%20Kallel">Fathi Kallel</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulelah%20Alabd%20Uljabbar"> Abdulelah Alabd Uljabbar</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulrahman%20Aldukhail"> Abdulrahman Aldukhail</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulaziz%20Alomran"> Abdulaziz Alomran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MRI" title="MRI">MRI</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20tumor" title=" brain tumor"> brain tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=CAD" title=" CAD"> CAD</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=DWT" title=" DWT"> DWT</a>, <a href="https://publications.waset.org/abstracts/search?q=PCA" title=" PCA"> PCA</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/81523/development-of-a-computer-aided-diagnosis-tool-for-brain-tumor-extraction-and-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81523.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">249</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32099</span> Endometriosis-Associated Ovarian Cancer: Clinical and Pathological Pattern</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=I.%20Ramalho">I. Ramalho</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Campos"> S. Campos</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Dias"> M. Dias</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Endometriosis may play a role in the pathogenesis of ovarian cancer (OC), however, the risk and prognosis have not been well established. The association between these two pathologies could have an important impact on prevention and early diagnosis of OC. Objective: To analyze the prevalence of endometriosis associated ovarian cancer and related clinical, epidemiological and histopathological issues. Design: We conducted a retrospective case series analysis of patients diagnosed with endometriosis and ovarian cancer in the Gynecology Department of Coimbra University Hospital Center since 2006 to 2015. Methods: We collected data from women diagnosed with ovarian cancer, with anatomopathology records reporting findings of endometriosis in ovarian cancer patients. Patients were retrieved from the pathological records and appropriate medical records were retrospectively reviewed. Statistical analysis was performed using SPSS 22.0. Results: Histological evidence of endometriosis was found in 17 out of 261 patients diagnosed with ovarian cancer (OC) (6.51%). The most usual symptoms were pelvic pain, abdominal distension, asthenia, ascites, weight loss and nausea. Mean age at diagnosis was 61.2 ± 15.1, 41-86 years old, 33.3% were pre-menopausal patients and cancer stage distribution was predominantly stage I (31.3%) and stage III (56.3%). OC occurred unilaterally in 14 patients and 2 patients were diagnosed with a synchronous ovarian and endometrial cancer. Regarding histological type, 10 OC were classified as clear cell carcinoma (CCC), 4 endometrioid carcinomas (EC) and 3 mixed type (clear cell and endometrioid). Four ovarian carcinomas presumably arose from endometriomas: 3 CCC and 1 EC. Conclusions: In accordance with previous studies, clear cell was the most common pathological type in endometriotic patients, followed by endometrioid carcinomas, and two rare synchronous ovarian and endometrial carcinomas were registered. Although endometriosis association to OC is uncommon, endometriosis should be managed with special care in order to early diagnosis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=endometriosis" title="endometriosis">endometriosis</a>, <a href="https://publications.waset.org/abstracts/search?q=histology" title=" histology"> histology</a>, <a href="https://publications.waset.org/abstracts/search?q=observational%20study" title=" observational study"> observational study</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title=" ovarian cancer"> ovarian cancer</a> </p> <a href="https://publications.waset.org/abstracts/71642/endometriosis-associated-ovarian-cancer-clinical-and-pathological-pattern" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71642.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">229</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32098</span> Malignant Ovarian Cancer Ascites Confers Platinum Chemoresistance to Ovarian Cancer Cells: A Combination Treatment with Crizotinib and 2 Hydroxyestradiol Restore Platinum Sensitivity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yifat%20Koren%20Carmi">Yifat Koren Carmi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abed%20Agbarya"> Abed Agbarya</a>, <a href="https://publications.waset.org/abstracts/search?q=Hazem%20Khamaisi"> Hazem Khamaisi</a>, <a href="https://publications.waset.org/abstracts/search?q=Raymond%20Farah"> Raymond Farah</a>, <a href="https://publications.waset.org/abstracts/search?q=Yelena%20Shechtman"> Yelena Shechtman</a>, <a href="https://publications.waset.org/abstracts/search?q=Roman%20Korobochka"> Roman Korobochka</a>, <a href="https://publications.waset.org/abstracts/search?q=Jacob%20Gopas"> Jacob Gopas</a>, <a href="https://publications.waset.org/abstracts/search?q=Jamal%20Mahajna"> Jamal Mahajna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ovarian cancer (OC), the second most common form of gynecological malignancy, has a poor prognosis and is frequently identified in its late stages. The recommended treatment for OC typically includes a platinum-based chemotherapy, like carboplatin. Nonetheless, OC treatment has proven challenging due to toxicity and development of acquired resistance to therapy. Chemoresistance is a significant obstacle to a long-lasting response in OC patients, believed to arise from alterations within the cancer cells as well as within the tumor microenvironments (TME). Malignant ascites is a presenting feature in more than one-third of OC patients. It serves as a reservoir for a complex mixture of soluble factors, metabolites, and cellular components, providing a pro-inflammatory and tumor-promoting microenvironment for the OC cells. Malignant ascites is also associated with metastasis and chemoresistance. In an attempt to elucidate the role of TME in chemoresistance of OC, we monitored the ability of soluble factors derived from ascites fluids to affect platinum sensitivity of OC cells. This research, compared ascites fluids from non-malignant cirrhotic patients to those from OC patients in terms of their ability to alter the platinum sensitivity of OC cells. Our findings indicated that exposure to OC ascites induces platinum chemoresistance on OC cells in 11 out of 13 cases (85%). In contrast, 75% of cirrhosis ascites (3 out of 4) failed to confer platinum chemoresistance to OC cells. Cytokine array analysis revealed that IL-6, and to a lesser extent HGF were enriched in OC ascites, whereas IL-22 was enriched in cirrhosis ascites. Pharmaceutical inhibitors that target the IL-6/JAK signaling pathway were mildly effective in overcoming the platinum chemoresistance induced by malignant ascites. In contrast, Crizotinib an HGF/c-MET inhibitor, and 2-hydroxyestradiol (2HE2) were effective in restoring platinum chemoresistance to OC. Our findings demonstrate the importance of OC ascites in supporting platinum chemoresistance as well as the potential of a combination therapy with Crizotinib and the estradiol metabolite 2HE2 to regain OC cells chemosensitivity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title="ovarian cancer">ovarian cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=platinum%20chemoresistance" title=" platinum chemoresistance"> platinum chemoresistance</a>, <a href="https://publications.waset.org/abstracts/search?q=malignant%20ascites" title=" malignant ascites"> malignant ascites</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20microenvironment" title=" tumor microenvironment"> tumor microenvironment</a>, <a href="https://publications.waset.org/abstracts/search?q=IL-6" title=" IL-6"> IL-6</a>, <a href="https://publications.waset.org/abstracts/search?q=2-hydroxyestradiol" title=" 2-hydroxyestradiol"> 2-hydroxyestradiol</a>, <a href="https://publications.waset.org/abstracts/search?q=HGF" title=" HGF"> HGF</a>, <a href="https://publications.waset.org/abstracts/search?q=crizotinib" title=" crizotinib"> crizotinib</a> </p> <a href="https://publications.waset.org/abstracts/170418/malignant-ovarian-cancer-ascites-confers-platinum-chemoresistance-to-ovarian-cancer-cells-a-combination-treatment-with-crizotinib-and-2-hydroxyestradiol-restore-platinum-sensitivity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170418.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">68</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32097</span> Cytology Is a Promising Tool for the Diagnosis of High-Grade Serous Ovarian Carcinoma from Ascites</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Miceska%20Simona">Miceska Simona</a>, <a href="https://publications.waset.org/abstracts/search?q=%C5%A0kof%20Erik"> Škof Erik</a>, <a href="https://publications.waset.org/abstracts/search?q=Frkovi%C4%87%20Grazio%20Snje%C5%BEana"> Frković Grazio Snježana</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeri%C4%8Devi%C4%87%20Anja"> Jeričević Anja</a>, <a href="https://publications.waset.org/abstracts/search?q=Smrkolj%20%C5%A0pela"> Smrkolj Špela</a>, <a href="https://publications.waset.org/abstracts/search?q=Cvjeti%C4%87anin%20Branko"> Cvjetićanin Branko</a>, <a href="https://publications.waset.org/abstracts/search?q=Novakovi%C4%87%20Srdjan"> Novaković Srdjan</a>, <a href="https://publications.waset.org/abstracts/search?q=Gr%C4%8Dar%20Kuzmanov%20Biljana"> Grčar Kuzmanov Biljana</a>, <a href="https://publications.waset.org/abstracts/search?q=Kloboves-Prevodnik%20Veronika"> Kloboves-Prevodnik Veronika</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objectives: High-grade serous ovarian cancer (HGSOC) is characterized by the dissemination of the tumor cells (TC) in the peritoneal cavity forming malignant ascites at the time of diagnosis or recurrence. Still, cytology itself has been underutilized as a modality for the diagnosis of HGSOC from ascites, and histological examination from the tumor tissue is yet the only validated method used. The objective of this study was to evaluate the reliability of cytology in the diagnosis of HGSOC in relation to the histopathological examination. Methods: The study included 42 patients with histologically confirmed HGSOC, accompanied by malignant ascites. To confirm the malignancy of the TC in the ascites and to define their immunophenotype, immunohistochemical reaction (IHC) of the following antigens: Calretinin, MOC, WT1, PAX8, p53, p16 & Ki-67 was evaluated on ascites cytospins and tissue blocks. For complete cytological determination of HGSOC, BRCA 1/2 gene mutation was determined from ascites, tissue block, and blood. BRCA1/2 mutation from blood was performed to define the type of mutation, somatic vs germline. Results: Among 42 patients, the immunophenotype of HGSOC from ascites was confirmed in 36 cases (86%). For more profound analysis, the patients were divided in 3 groups regarding the number of TC present in the ascites: patients with less than 10% TC, 10% TC, and more than 10% TC. From all included patients, in the group with less than 10% TC, there were 10 cases, and only 5 of them(50%) showed HGSOC phenotype; 12 cases had equally 10% of TC, and 11 cases (92%) showed HGSOC phenotype; 20 cases had more than 10% TC and all of them (100%) confirmed the HGSOC immunophenotype from ascites. Only 33 patients were eligible for further BRCA1/2 analysis. Eleven BRCA1/2 mutations were detected from thetissue block: 6 germline and 5 somatic. In 2 cases with less than 10% TC, BRCA1/2 mutation was not detected; 4 cases had 10% TC, and 2 of them (50%) confirmed the mutation; 4 cases had more than 10% TC, and all showed 100% reliability with the tumor tissue. Conclusions: Cytology is a highly reliable method for determining the immunophenotype of HGSOC and BRCA1/2 mutation if more than 10% of tumor cells are present in the ascites. This may present an additional non-invasive clinical approach for fast and effective diagnose in the future, especially in inoperable conditions or relapses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cytology" title="cytology">cytology</a>, <a href="https://publications.waset.org/abstracts/search?q=ascites" title=" ascites"> ascites</a>, <a href="https://publications.waset.org/abstracts/search?q=high-grade%20serous%20ovarian%20cancer" title=" high-grade serous ovarian cancer"> high-grade serous ovarian cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=immunophenotype" title=" immunophenotype"> immunophenotype</a>, <a href="https://publications.waset.org/abstracts/search?q=BRCA1%2F2" title=" BRCA1/2"> BRCA1/2</a> </p> <a href="https://publications.waset.org/abstracts/144274/cytology-is-a-promising-tool-for-the-diagnosis-of-high-grade-serous-ovarian-carcinoma-from-ascites" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144274.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">188</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32096</span> An Advanced Automated Brain Tumor Diagnostics Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Berkan%20Ural">Berkan Ural</a>, <a href="https://publications.waset.org/abstracts/search?q=Arif%20Eser"> Arif Eser</a>, <a href="https://publications.waset.org/abstracts/search?q=Sinan%20Apaydin"> Sinan Apaydin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20processing%20algorithms" title="image processing algorithms">image processing algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetic%20resonance%20imaging" title=" magnetic resonance imaging"> magnetic resonance imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=pattern%20recognition" title=" pattern recognition"> pattern recognition</a> </p> <a href="https://publications.waset.org/abstracts/69471/an-advanced-automated-brain-tumor-diagnostics-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69471.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">418</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32095</span> PCR Based DNA Analysis in Detecting P53 Mutation in Human Breast Cancer (MDA-468)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Debbarma%20Asis">Debbarma Asis</a>, <a href="https://publications.waset.org/abstracts/search?q=Guha%20Chandan"> Guha Chandan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tumor Protein-53 (P53) is one of the tumor suppressor proteins. P53 regulates the cell cycle that conserves stability by preventing genome mutation. It is named so as it runs as 53-kilodalton (kDa) protein on Polyacrylamide gel electrophoresis although the actual mass is 43.7 kDa. Experimental evidence has indicated that P53 cancer mutants loses tumor suppression activity and subsequently gain oncogenic activities to promote tumourigenesis. Tumor-specific DNA has recently been detected in the plasma of breast cancer patients. Detection of tumor-specific genetic materials in cancer patients may provide a unique and valuable tumor marker for diagnosis and prognosis. Commercially available MDA-468 breast cancer cell line was used for the proposed study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=tumor%20protein%20%28P53%29" title="tumor protein (P53)">tumor protein (P53)</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer%20mutants" title=" cancer mutants"> cancer mutants</a>, <a href="https://publications.waset.org/abstracts/search?q=MDA-468" title=" MDA-468"> MDA-468</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20suppressor%20gene" title=" tumor suppressor gene"> tumor suppressor gene</a> </p> <a href="https://publications.waset.org/abstracts/43690/pcr-based-dna-analysis-in-detecting-p53-mutation-in-human-breast-cancer-mda-468" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43690.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">478</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32094</span> Effects of New Anthraquinone Derivatives on Resistance Ovarian Cancer Cells and The Mechanism Investigation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hui-Hsin%20Huang">Hui-Hsin Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sheng-Tung%20Huang"> Sheng-Tung Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chi-Ming%20Lee"> Chi-Ming Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Chiao-Han%20Yen"> Chiao-Han Yen</a>, <a href="https://publications.waset.org/abstracts/search?q=Chun-Mao%20Lin"> Chun-Mao Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> At initiation stage, there are no symptoms at initiation stage; however, at late stage, patients suffer symptoms as soon as ovarian cancer metastasis. Moreover, ovarian cancer cells are resistant to some anti-ovarian cancer drugs in clinical. Thus, it is very important to find an effective treatment for resistant ovarian cancer. Anthraquinone derivatives are able to induce DNA damage and lead to cell apoptosis, so several derivatives have been used for clinical application. Therefore, to explore more effective anti-ovarian cancer drugs, this study investigates the mechanism of three new anthraquinone compounds bearing different functional groups to camptothecin-resistance ovarian cell line A2780R2000. Cell viability was determined by MTT assay after treating A2780R2000 with the three new anthraquinone compounds. The results indicated that IC50 values are 33.44μM (Compound I), 25.77μM (Compound II) and 24.59μM (Compound III). Next, through cell cycle analysis, the results demonstrated that three new anthraquinone compounds not only induced A2780R2000 cell cycle arrest at early stage but also apoptosis at late stage. Besides, through apoptosis assay, the results indicated new anthraquinone compound induced apoptosis at late stage. Furthermore, the results of western blot show that the three new anthraquinone compounds lead to A2780R2000 apoptosis through intrinsic pathway. Theses results suggested that three new anthraquinone compounds may be potential new drugs for clinical cancer treatment in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anthraquinone" title="anthraquinone">anthraquinone</a>, <a href="https://publications.waset.org/abstracts/search?q=camptothecin" title=" camptothecin"> camptothecin</a>, <a href="https://publications.waset.org/abstracts/search?q=resistance" title=" resistance"> resistance</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title=" ovarian cancer"> ovarian cancer</a> </p> <a href="https://publications.waset.org/abstracts/44883/effects-of-new-anthraquinone-derivatives-on-resistance-ovarian-cancer-cells-and-the-mechanism-investigation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44883.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">394</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32093</span> Application of Raman Spectroscopy for Ovarian Cancer Detection: Comparative Analysis of Fresh, Formalin-Fixed, and Paraffin-Embedded Samples</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zeinab%20Farhat">Zeinab Farhat</a>, <a href="https://publications.waset.org/abstracts/search?q=Nicolas%20Errien"> Nicolas Errien</a>, <a href="https://publications.waset.org/abstracts/search?q=Romuald%20Wernert"> Romuald Wernert</a>, <a href="https://publications.waset.org/abstracts/search?q=V%C3%A9ronique%20Verriele"> Véronique Verriele</a>, <a href="https://publications.waset.org/abstracts/search?q=Fr%C3%A9d%C3%A9ric%20Amiard"> Frédéric Amiard</a>, <a href="https://publications.waset.org/abstracts/search?q=Philippe%20Daniel"> Philippe Daniel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ovarian cancer, also known as the silent killer, is the fifth most common cancer among women worldwide, and its death rate is higher than that of other gynecological cancers. The low survival rate of women with high-grade serous ovarian carcinoma highlights the critical need for the development of new methods for early detection and diagnosis of the disease. The aim of this study was to evaluate if Raman spectroscopy combined with chemometric methods such as Principal Component Analysis (PCA) could differentiate between cancerous and normal tissues from different types of samples, such as paraffin embedding, chemical deparaffinized, formalin-fixed and fresh samples of the same normal and malignant ovarian tissue. The method was applied specifically to two critical spectral regions: the signature region (860-1000 〖cm〗^(-1)) and the high-frequency region (2800-3100 〖cm〗^(-1) ). The mean spectra of paraffin-embedded in normal and malignant tissues showed almost similar intensity. On the other hand, the mean spectra of normal and cancer tissues from chemical deparaffinized, formalin-fixed, and fresh samples show significant intensity differences. These spectral differences reflect variations in the molecular composition of the tissues, particularly lipids and proteins. PCA, which was applied to distinguish between cancer and normal tissues, was performed on whole spectra and on selected regions—the PCA score plot of paraffin-embedded shows considerable overlap between the two groups. However, the PCA score of chemicals deparaffinized, formalin-fixed, and fresh samples showed a good discrimination of tissue types. Our findings were validated by analyses of a set of samples whose status (normal and cancerous) was not previously known. The results of this study suggest that Raman Spectroscopy associated with PCA methods has the capacity to provide clinically significant differentiation between normal and cancerous ovarian tissues. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Raman%20spectroscopy" title="Raman spectroscopy">Raman spectroscopy</a>, <a href="https://publications.waset.org/abstracts/search?q=ovarian%20cancer" title=" ovarian cancer"> ovarian cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=Principal%20Component%20Analysis" title=" Principal Component Analysis"> Principal Component Analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/190210/application-of-raman-spectroscopy-for-ovarian-cancer-detection-comparative-analysis-of-fresh-formalin-fixed-and-paraffin-embedded-samples" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190210.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">25</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32092</span> Performance Evaluation of the HE4 as a Serum Tumor Marker for Ovarian Carcinoma</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hyun-jin%20Kim">Hyun-jin Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Gumgyung%20Gu"> Gumgyung Gu</a>, <a href="https://publications.waset.org/abstracts/search?q=Dae-Hyun%20Ko"> Dae-Hyun Ko</a>, <a href="https://publications.waset.org/abstracts/search?q=Woochang%20Lee"> Woochang Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sail%20Chun"> Sail Chun</a>, <a href="https://publications.waset.org/abstracts/search?q=Won-Ki%20Min"> Won-Ki Min</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Ovarian carcinoma is the fourth most common cause of cancer-related death in women worldwide. HE4, a novel marker for ovarian cancer could be used for monitoring recurrence or progression of disease in patients with invasive epithelial ovarian carcinoma. It is further intended to be used in conjunction with CA 125 to estimate the risk of epithelial ovarian cancer in women presenting with an adnexal mass. In this study, we aim to evaluate the analytical performance and clinical utility of HE4 assay using Architect i 2000SR(Abbott Diagnostics, USA). Methods: The precision was evaluated according to Clinical and Laboratory Standards Institute(CLSI) EP5 guideline. Three levels of control materials were analyzed twice a day in duplicate manner over 20 days. We calculated within run and total coefficient of variation (CV) at each level of control materials. The linearity was evaluated based on CLSI EP6 guideline. Five levels of calibrator were prepared by mixing high and low level of calibrators. For 43 women with adnexal masses, HE4 and CA 125 were measured and Risk of ovarian malignancy (ROMA) scores were calculated. The patients’ medical records were reviewed to determine the clinical utility of HE4 and ROMA score. Results: In a precision study, the within-run and total CV were 2.0 % and 2.3% for low level of control material, 1.9% and 2.4% for medium level and 0.5 % and 1.1% for high level, respectively. The linear range of HE4 was 14.63 to 1475.15pmol/L. Of the 43 patients, two patients in pre-menopausal group showed the ROMA score above the cut-off level (7.3%). One of them showed CA 125 level within the reference range, while the HE4 was higher than the cut-off. Conclusion: The overall analytical performance of HE4 assay using Architect showed high precision and good linearity within clinically important range. HE4 could be an useful marker for managing patients with adnexal masses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HE4" title="HE4">HE4</a>, <a href="https://publications.waset.org/abstracts/search?q=CA125" title=" CA125"> CA125</a>, <a href="https://publications.waset.org/abstracts/search?q=ROMA" title=" ROMA"> ROMA</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation" title=" evaluation"> evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a> </p> <a href="https://publications.waset.org/abstracts/21188/performance-evaluation-of-the-he4-as-a-serum-tumor-marker-for-ovarian-carcinoma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21188.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32091</span> lncRNA Gene Expression Profiling Analysis by TCGA RNA-Seq Data of Breast Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiaoping%20Su">Xiaoping Su</a>, <a href="https://publications.waset.org/abstracts/search?q=Gabriel%20G.%20Malouf"> Gabriel G. Malouf</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Breast cancer is a heterogeneous disease that can be classified in 4 subgroups using transcriptional profiling. The role of lncRNA expression in human breast cancer biology, prognosis, and molecular classification remains unknown. Methods and results: Using an integrative comprehensive analysis of lncRNA, mRNA and DNA methylation in 900 breast cancer patients from The Cancer Genome Atlas (TCGA) project, we unraveled the molecular portraits of 1,700 expressed lncRNA. Some of those lncRNAs (i.e, HOTAIR) are previously reported and others are novel (i.e, HOTAIRM1, MAPT-AS1). The lncRNA classification correlated well with the PAM50 classification for basal-like, Her-2 enriched and luminal B subgroups, in contrast to the luminal A subgroup which behaved differently. Importantly, estrogen receptor (ESR1) expression was associated with distinct lncRNA networks in lncRNA clusters III and IV. Gene set enrichment analysis for cis- and trans-acting lncRNA showed enrichment for breast cancer signatures driven by breast cancer master regulators. Almost two third of those lncRNA were marked by enhancer chromatin modifications (i.e., H3K27ac), suggesting that lncRNA expression may result in increased activity of neighboring genes. Differential analysis of gene expression profiling data showed that lncRNA HOTAIRM1 was significantly down-regulated in basal-like subtype, and DNA methylation profiling data showed that lncRNA HOTAIRM1 was highly methylated in basal-like subtype. Thus, our integrative analysis of gene expression and DNA methylation strongly suggested that lncRNA HOTAIRM1 should be a tumor suppressor in basal-like subtype. Conclusion and significance: Our study depicts the first lncRNA molecular portrait of breast cancer and shows that lncRNA HOTAIRM1 might be a novel tumor suppressor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=lncRNA%20profiling" title="lncRNA profiling">lncRNA profiling</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title=" breast cancer"> breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=HOTAIRM1" title=" HOTAIRM1"> HOTAIRM1</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor%20suppressor" title=" tumor suppressor"> tumor suppressor</a> </p> <a href="https://publications.waset.org/abstracts/104472/lncrna-gene-expression-profiling-analysis-by-tcga-rna-seq-data-of-breast-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/104472.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">105</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=international%20ovarian%20tumor%20analysis%20classification&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=international%20ovarian%20tumor%20analysis%20classification&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=international%20ovarian%20tumor%20analysis%20classification&page=4">4</a></li> <li class="page-item"><a class="page-link" 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