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Patients with ovarian cancer have a high risk of developing thrombosis. We aimed to investigate pre and post operative biomarkers associated with thrombosis including deep vein thrombosis and pulmonary thromboembolism in patients treated for ovarian cancer. We collected pre and post operative blood samples from 133 patients undergoing surgery for ovarian cancer between December 2021 and August 2022. The measured parameters were white blood cell count, hemoglobin, platelets, monocytes, serum glucose, CA125, D-dimer, fibrinogen, prothrombin time, activated partial thromboplastin time, fibrinogen degradation products, antithrombin III, protein C, protein S, plasminogen, plasminogen activator inhibitor 1, homocysteine, N-terminal pro-brain natriuretic peptide, interleukin 6, thrombopoietin, soluble P-selectin and granulocyte stimulating factor. Body mass index of patients were collected. Differences between patients who developed thrombosis and those without were compared with Wilcoxon rank-sum test and we analyzed the continuous variables using logistic regression. Twenty-one (15.8%) patients developed thrombosis ranging from 6 to 146 days (median 15 days) after surgery. Pre operative values of homocysteine (p = 0.033) and IL-6 (p = 0.043) were significantly increased and post operative aPTT (p = 0.022) was prolonged and plasminogen (p = 0.041) was decreased in patients with thrombosis. It is important to find novel biomarkers for thrombosis to carefully manage patients who are prone to develop thrombosis despite preventive measures were applied. [ABSTRACT FROM AUTHOR]

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Purpose: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods. Methods: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established "no-new-Net" framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test. Results: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10–7, 3 × 10–4, 4 × 10–2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10–3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions. Conclusion: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions. Relevance statement: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines. Key points: • The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented. • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists. • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study is to describe the radiological spectrum of appearances of ovarian lymphoma (OL). The manuscript describes the radiological aspects of OL to assist the radiologist in achieving correct orientation of the diagnosis. Methods: We conducted a retrospective evaluation of imaging studies of 98 cases of non-Hodgkin's lymphoma, with extra-nodal localisation (ovaries) in three cases (1 primary, 2 secondary). A literature review was also performed. Results: Of the three evaluated women, one had a primary ovarian involvement and two had a secondary ovarian involvement. The most common lesion characteristics were a well-defined, solid homogeneous and hypoechoic mass at US. CT depicts OL as a well-defined, non-infiltrating, homogeneous hypodense solid mass, with mild contrast enhancement. On T1-weight MRI, OL appears as a homogeneous mass of low signal intensity, which enhances avidly following intravenous gadolinium. Conclusion: Clinical and serological presentation of OL can be similar to that of primary ovarian cancer. As imaging plays a central role in the diagnosis of OL, the radiologist should be familiar with US, CT and MRI appearances of this condition to correctly orient the diagnosis and so avoid unnecessary adnexectomy. [ABSTRACT FROM AUTHOR]

Copyright of Die Gynäkologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High-grade serous ovarian cancer is the most lethal gynaecological malignancy. Detailed molecular studies have revealed marked intra-patient heterogeneity at the tumour microenvironment level, likely contributing to poor prognosis. Despite large quantities of clinical, molecular and imaging data on ovarian cancer being accumulated worldwide and the rise of high-throughput computing, data frequently remain siloed and are thus inaccessible for integrated analyses. Only a minority of studies on ovarian cancer have set out to harness artificial intelligence (AI) for the integration of multiomics data and for developing powerful algorithms that capture the characteristics of ovarian cancer at multiple scales and levels. Clinical data, serum markers, and imaging data were most frequently used, followed by genomics and transcriptomics. The current literature proves that integrative multiomics approaches outperform models based on single data types and indicates that imaging can be used for the longitudinal tracking of tumour heterogeneity in space and potentially over time. This review presents an overview of studies that integrated two or more data types to develop AI-based classifiers or prediction models. Relevance statement Integrative multiomics models for ovarian cancer outperform models using single data types for classification, prognostication, and predictive tasks. Key points • This review presents studies using multiomics and artificial intelligence in ovarian cancer. • Current literature proves that integrative multiomics outperform models using single data types. • Around 60% of studies used a combination of imaging with clinical data. • The combination of genomics and transcriptomics with imaging data was infrequently used. [ABSTRACT FROM AUTHOR]

Objectives: The study aim was to conduct a systematic review of the literature reporting the application of radiomics to imaging techniques in patients with ovarian lesions. Methods: MEDLINE/PubMed, Web of Science, Scopus, EMBASE, Ovid and ClinicalTrials.gov were searched for relevant articles. Using PRISMA criteria, data were extracted from short-listed studies. Validity and bias were assessed independently by 2 researchers in consensus using the Quality in Prognosis Studies (QUIPS) tool. Radiomic Quality Score (RQS) was utilised to assess radiomic methodology. Results: After duplicate removal, 63 articles were identified, of which 33 were eligible. Fifteen assessed lesion classifications, 10 treatment outcomes, 5 outcome predictions, 2 metastatic disease predictions and 1 classification/outcome prediction. The sample size ranged from 28 to 501 patients. Twelve studies investigated CT, 11 MRI, 4 ultrasound and 1 FDG PET-CT. Twenty-three studies (70%) incorporated 3D segmentation. Various modelling methods were used, most commonly LASSO (least absolute shrinkage and selection operator) (10/33). Five studies (15%) compared radiomic models to radiologist interpretation, all demonstrating superior performance. Only 6 studies (18%) included external validation. Five studies (15%) had a low overall risk of bias, 9 (27%) moderate, and 19 (58%) high risk of bias. The highest RQS achieved was 61.1%, and the lowest was − 16.7%. Conclusion: Radiomics has the potential as a clinical diagnostic tool in patients with ovarian masses and may allow better lesion stratification, guiding more personalised patient care in the future. Standardisation of the feature extraction methodology, larger and more diverse patient cohorts and real-world evaluation is required before clinical translation. Clinical relevance statement: Radiomics shows promising results in improving lesion stratification, treatment selection and outcome prediction. Modelling with larger cohorts and real-world evaluation is required before clinical translation. Key points: • Radiomics is emerging as a tool for enhancing clinical decisions in patients with ovarian masses. • Radiomics shows promising results in improving lesion stratification, treatment selection and outcome prediction. • Modelling with larger cohorts and real-world evaluation is required before clinical translation. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the value of a radiomics nomogram to identify platinum resistance and predict the progression-free survival (PFS) of patients with advanced high-grade serous ovarian carcinoma (HGSOC). Materials and methods: In this multicenter retrospective study, 301 patients with advanced HGSOC underwent radiomics features extraction from the whole primary tumor on contrast-enhanced T1WI and T2WI. The radiomics features were selected by the support vector machine–based recursive feature elimination method, and then the radiomics signature was generated. Furthermore, a radiomics nomogram was developed using the radiomics signature and clinical characteristics by multivariable logistic regression. The predictive performance was evaluated using receiver operating characteristic analysis. The net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) were used to compare the clinical utility and benefits of different models. Results: Five features significantly correlated with platinum resistance were selected to construct the radiomics model. The radiomics nomogram, combining radiomics signatures with three clinical characteristics (FIGO stage, CA-125, and residual tumor), had a higher area under the curve (AUC) compared with the clinical model alone (AUC: 0.799 vs 0.747), with positive NRI and IDI. The net benefit of the radiomics nomogram is typically higher than clinical-only and radiomics-only models. Kaplan–Meier survival analysis showed that the radiomics nomogram–defined high-risk groups had shorter PFS compared with the low-risk groups in patients with advanced HGSOC. Conclusions: The radiomics nomogram can identify platinum resistance and predict PFS. It helps make the personalized management of advanced HGSOC. Key Points: • The radiomics-based approach has the potential to identify platinum resistance and can help make the personalized management of advanced HGSOC. • The radiomics–clinical nomogram showed improved performance compared with either of them alone for predicting platinum-resistant HGSOC. • The proposed nomogram performed well in predicting the PFS time of patients with low-risk and high-risk HGSOC in both training and testing cohorts. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to present the state of the art of CT- and MRI-based radiomics in the context of ovarian cancer (OC), with a focus on the methodological quality of these studies and the clinical utility of these proposed radiomics models. Methods: Original articles investigating radiomics in OC published in PubMed, Embase, Web of Science, and the Cochrane Library between January 1, 2002, and January 6, 2023, were extracted. The methodological quality was evaluated using the radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pairwise correlation analyses were performed to compare the methodological quality, baseline information, and performance metrics. Additional meta-analyses of studies exploring differential diagnoses and prognostic prediction in patients with OC were performed separately. Results: Fifty-seven studies encompassing 11,693 patients were included. The mean RQS was 30.7% (range − 4 to 22); less than 25% of studies had a high risk of bias and applicability concerns in each domain of QUADAS-2. A high RQS was significantly associated with a low QUADAS-2 risk and recent publication year. Significantly higher performance metrics were observed in studies examining differential diagnosis; 16 such studies as well as 13 exploring prognostic prediction were included in a separate meta-analysis, which revealed diagnostic odds ratios of 25.76 (95% confidence interval (CI) 13.50–49.13) and 12.55 (95% CI 8.38–18.77), respectively. Conclusion: Current evidence suggests that the methodological quality of OC-related radiomics studies is unsatisfactory. Radiomics analysis based on CT and MRI showed promising results in terms of differential diagnosis and prognostic prediction. Critical relevance statement: Radiomics analysis has potential clinical utility; however, shortcomings persist in existing studies in terms of reproducibility. We suggest that future radiomics studies should be more standardized to better bridge the gap between concepts and clinical applications. Key points: The methodological quality of current radiomics studies concerning ovarian cancer was unsatisfactory. Meta-analyses showed high diagnostic odds ratios regarding differential diagnosis and prognostic prediction. Radiomics analysis in ovarian cancer holds promise for clinical applications. More standardization should be required for radiomics studies. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the association between alcohol intake over the lifetime and the risk of overall, borderline, and invasive ovarian cancer. Methods: In a population-based case–control study of 495 cases and 902 controls, conducted in Montreal, Canada, average alcohol intake over the lifetime and during specific age periods were computed from a detailed assessment of the intake of beer, red wine, white wine and spirits. Multivariable logistic regression was used to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for the association between alcohol intake and ovarian cancer risk. Results: For each one drink/week increment in average alcohol intake over the lifetime, the adjusted OR (95% CI) was 1.06 (1.01–1.10) for ovarian cancer overall, 1.13 (1.06–1.20) for borderline ovarian cancers and 1.02 (0.97–1.08) for invasive ovarian cancers. This pattern of association was similarly observed for alcohol intake in early (15– < 25 years), mid (25– < 40 years) and late adulthood (≥ 40 years), as well as for the intake of specific alcohol beverages over the lifetime. Conclusions: Our results support the hypothesis that a higher alcohol intake modestly increases the risk of overall ovarian cancer, and more specifically, borderline tumours. [ABSTRACT FROM AUTHOR]

Adnexal masses during pregnancy are a relatively uncommon entity. Their clinical management is challenging given the overlapping features of certain entities on imaging and histopathology, which can mimic malignancy, and the potential side effects to the mother and fetus, whether expectant management versus surgery is pursued. Ultrasonography with Doppler evaluation is the modality of choice for evaluating adnexal masses during pregnancy. Magnetic resonance imaging is the second-line modality useful when US findings are inconclusive/indeterminate. Most adnexal masses in pregnant patients are benign in origin (e.g., functional cysts, mature cystic teratoma, decidualization of endometrioma), but a few are malignant in origin (e.g., dysgerminoma, granulosa cell tumor). Most cases of adnexal masses are asymptomatic, but complications such as ovarian torsion can occur. This review aims to familiarize the radiologist with the imaging of adnexal lesions during pregnancy so that the radiologist can identify ovarian cancer. Specifically, the review will detail the most common benign and malignant adnexal masses in pregnancy, mimickers, and their corresponding imaging findings on US and MRI. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate computed tomography (CT) findings in patients with ovarian cancer presenting to a comprehensive cancer center's urgent care unit with acute abdominal symptoms.Methods: This retrospective study included consecutive patients with ovarian cancer who underwent abdominal CT at a comprehensive cancer center's urgent care unit between January 1, 2018, and January 14, 2020, due to acute abdominal symptoms. Two abdominal radiologists reviewed the abdominal CT reports, categorizing imaging findings as follows: (a) no new or acute finding, (b) new or increased bowel or gastric obstruction, (c) new or increased ascites, (d) new or increased peritoneal carcinomatosis, (e) new or increased nonperitoneal metastases, (f) new inflammatory or infectious changes, (g) new or increased hydronephrosis, (h) new or increased biliary dilatation, (i) new vascular complications, or (j) new bowel perforation.Results: A total of 200 patients (mean age, 59 years; range, 22-87) underwent a total of 259 abdominal CT scans, of which 217/259 (83.8%) scans were found to have new or increased findings. A total of 115/259 (44.4%) scans had only one finding while 102/259 (39.4%) scans had 2 or more findings. Altogether, 382 new or increased findings were detected: findings were most commonly related to bowel or gastric obstruction (92/382, 24.1%) with small bowel obstruction being the most common finding (80/382, 20.9%); ascites (78/382, 20.4%); peritoneal carcinomatosis (62/382, 16.2%); and nonperitoneal metastases (62/382, 16.2%). Inflammatory or infectious findings accounted for 30/382 (7.9%) findings.Conclusion: Most patients with ovarian cancer presenting with acute abdominal had relevant positive findings on abdominal CT, with small bowel obstruction being the most common finding. [ABSTRACT FROM AUTHOR]

Ovarian tumors are one of the most common gynecological neoplasms worldwide affecting women of all ages. As preoperative diagnosis is often inaccurate, intraoperative diagnostic modalities play indispensable role in management of ovarian tumors to avoid unnecessary extensive surgery. Although reliable, frozen section is highly expensive for resource-poor developing countries. Intraoperative cytological methods can help to overcome these limitations. The aim of this study was to evaluate the accuracy of scrape cytology in diagnosis of ovarian tumors. The freshly removed specimens of ovarian tumors sent without any fixative during the study period were included in this observational prospective cross-sectional study. Scraping was done from the most representative area of the cut surface of the tumor. Cytological smears were stained by hematoxylin–eosin method. All the cytological smears and corresponding histological sections were evaluated separately. Cytological interpretation was then compared with histological diagnosis to assess the diagnostic accuracy of scrape cytology. On histology, 66 cases were diagnosed as benign (60%), 5 cases as borderline (4.55%), and 39 as malignant (35.45%). Of these, 64 cases (58%) were of epithelial origin, 25 cases (22.7%) were of germ cell origin and 6 (5.45%) cases were categorized as sex cord-stromal tumor. Accuracy of scrape cytology in diagnosis of benign, borderline, and malignant ovarian tumors was found to be 95.45%, 40%, and 89.74%, respectively. Overall accuracy rate was 90.91%. Scrape cytology is a rapid, inexpensive yet effective tool to diagnose benign and malignant ovarian tumors with high diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Introduction: We aimed to demonstrate the sensitivity of frozen section for patients with adult granulosa cell tumor (AGCT) and analyze the clinico-pathological factors that may be associated with sensitivity.This is a multicenter study including data of 10 Gynecological Oncology Departments. Frozen-section results of patients who had ovarian AGCT at the final pathology report were retrospectively analyzed. The relation between clinico-pathological characteristics such as age, tumor size, Ca-125 level, presence of ascites, omental metastasis, menopausal status and peritoneal cytology, and the sensitivity of frozen section in patients with AGCT were evaluated. The sensitivity of frozen section diagnosis was determined by comparing the frozen section result with the final pathological diagnosis.Frozen section results of 274 patients with AGCT were obtained. The median age of the patients was 52 years (range, 17–82 years). Totally, 144 (52.7%, n = 273) patients were postmenopausal. The median tumour size was 90 mm (range, 9–700 mm). The median preoperative Ca-125 level was 23 IU/mL (range, 2–995 IU/mL). The sensitivity of frozen section for detecting AGCT was 76.3%. Any association between the sensitivity of frozen section and menopausal status, presence of ascites, positive cytology, omental metastasis, tumor size, Ca-125 level, age could not be shown.It is important to know the diagnosis of AGCT intraoperatively, and we demonstrated the sensitivity of frozen-section for these tumors as 76.3%.Material methods: We aimed to demonstrate the sensitivity of frozen section for patients with adult granulosa cell tumor (AGCT) and analyze the clinico-pathological factors that may be associated with sensitivity.This is a multicenter study including data of 10 Gynecological Oncology Departments. Frozen-section results of patients who had ovarian AGCT at the final pathology report were retrospectively analyzed. The relation between clinico-pathological characteristics such as age, tumor size, Ca-125 level, presence of ascites, omental metastasis, menopausal status and peritoneal cytology, and the sensitivity of frozen section in patients with AGCT were evaluated. The sensitivity of frozen section diagnosis was determined by comparing the frozen section result with the final pathological diagnosis.Frozen section results of 274 patients with AGCT were obtained. The median age of the patients was 52 years (range, 17–82 years). Totally, 144 (52.7%, n = 273) patients were postmenopausal. The median tumour size was 90 mm (range, 9–700 mm). The median preoperative Ca-125 level was 23 IU/mL (range, 2–995 IU/mL). The sensitivity of frozen section for detecting AGCT was 76.3%. Any association between the sensitivity of frozen section and menopausal status, presence of ascites, positive cytology, omental metastasis, tumor size, Ca-125 level, age could not be shown.It is important to know the diagnosis of AGCT intraoperatively, and we demonstrated the sensitivity of frozen-section for these tumors as 76.3%.Results: We aimed to demonstrate the sensitivity of frozen section for patients with adult granulosa cell tumor (AGCT) and analyze the clinico-pathological factors that may be associated with sensitivity.This is a multicenter study including data of 10 Gynecological Oncology Departments. Frozen-section results of patients who had ovarian AGCT at the final pathology report were retrospectively analyzed. The relation between clinico-pathological characteristics such as age, tumor size, Ca-125 level, presence of ascites, omental metastasis, menopausal status and peritoneal cytology, and the sensitivity of frozen section in patients with AGCT were evaluated. The sensitivity of frozen section diagnosis was determined by comparing the frozen section result with the final pathological diagnosis.Frozen section results of 274 patients with AGCT were obtained. The median age of the patients was 52 years (range, 17–82 years). Totally, 144 (52.7%, n = 273) patients were postmenopausal. The median tumour size was 90 mm (range, 9–700 mm). The median preoperative Ca-125 level was 23 IU/mL (range, 2–995 IU/mL). The sensitivity of frozen section for detecting AGCT was 76.3%. Any association between the sensitivity of frozen section and menopausal status, presence of ascites, positive cytology, omental metastasis, tumor size, Ca-125 level, age could not be shown.It is important to know the diagnosis of AGCT intraoperatively, and we demonstrated the sensitivity of frozen-section for these tumors as 76.3%.Conclusion: We aimed to demonstrate the sensitivity of frozen section for patients with adult granulosa cell tumor (AGCT) and analyze the clinico-pathological factors that may be associated with sensitivity.This is a multicenter study including data of 10 Gynecological Oncology Departments. Frozen-section results of patients who had ovarian AGCT at the final pathology report were retrospectively analyzed. The relation between clinico-pathological characteristics such as age, tumor size, Ca-125 level, presence of ascites, omental metastasis, menopausal status and peritoneal cytology, and the sensitivity of frozen section in patients with AGCT were evaluated. The sensitivity of frozen section diagnosis was determined by comparing the frozen section result with the final pathological diagnosis.Frozen section results of 274 patients with AGCT were obtained. The median age of the patients was 52 years (range, 17–82 years). Totally, 144 (52.7%, n = 273) patients were postmenopausal. The median tumour size was 90 mm (range, 9–700 mm). The median preoperative Ca-125 level was 23 IU/mL (range, 2–995 IU/mL). The sensitivity of frozen section for detecting AGCT was 76.3%. Any association between the sensitivity of frozen section and menopausal status, presence of ascites, positive cytology, omental metastasis, tumor size, Ca-125 level, age could not be shown.It is important to know the diagnosis of AGCT intraoperatively, and we demonstrated the sensitivity of frozen-section for these tumors as 76.3%. [ABSTRACT FROM AUTHOR]

Copyright of Best Practice Onkologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: We used real-world claims data to assess the utility of the relatively novel therapeutic bevacizumab in patients with newly diagnosed ovarian cancer in the United States after release of clinical data but prior to FDA approval. Methods: We used the IQVIA Pharmetrics Plus commercial claims database to identify women with a new diagnosis of ovarian cancer who underwent primary surgery or neoadjuvant chemotherapy followed by interval surgery from 2006 to 2018. We calculated the rate of use of bevacizumab, and the relative frequency of hospital and emergency department (ED) admissions. Treatment-related toxicities, and time to second line chemotherapy were calculated. Results: Among 8923 women who met study parameters, 533 (6.0%) received bevacizumab. The rate of use increased over time from 1.5% in 2006 to 7.0% in 2017 (P < 0.001), with a peak of 8.6% in 2011. The use was lowest in those ≥ 70 years old (2.8%), and in the West (4.5%), and was unaffected by number of comorbidities. Over one third (35.1%) received bevacizumab for less than 3 months, and 15.9% remained on it for greater than 13 months. Bevacizumab use was not associated with hospitalization or ED admission. Toxicities included hypertension (15.0%), kidney damage (6.8%), bleeding (3.8%), venous thrombo-embolism (2.3%) and fistula (1.1%). Time from initiation of first line chemotherapy to initiation of second line therapy was 19.9 months without bevacizumab and 22.6 months with bevacizumab use. Conclusions: Real-world patterns of upfront bevacizumab use prior to FDA approval in 2018 differed significantly from trial data. [ABSTRACT FROM AUTHOR]

Ovarian masses encompass various conditions, from benign to highly malignant, and imaging plays a vital role in their diagnosis and management. Ultrasound, particularly transvaginal ultrasound, is the foremost diagnostic method for adnexal masses. Magnetic Resonance Imaging (MRI) is advised for more precise characterisation if ultrasound results are inconclusive. The ovarian-adnexal reporting and data system (O-RADS) MRI lexicon and scoring system provides a standardised method for describing, assessing, and categorising the risk of each ovarian mass. Determining a histological differential diagnosis of the mass may influence treatment decision-making and treatment planning. When ultrasound or MRI suggests the possibility of cancer, computed tomography (CT) is the preferred imaging technique for staging. It is essential to outline the extent of the malignancy, guide treatment decisions, and evaluate the feasibility of cytoreductive surgery.This article provides a comprehensive overview of the key imaging processes in evaluating and managing ovarian masses, from initial diagnosis to initial treatment. It also includes pertinent recommendations for properly performing and interpreting various imaging modalities.MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians.CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery.Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians.CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery.Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.Key Points: Ovarian masses encompass various conditions, from benign to highly malignant, and imaging plays a vital role in their diagnosis and management. Ultrasound, particularly transvaginal ultrasound, is the foremost diagnostic method for adnexal masses. Magnetic Resonance Imaging (MRI) is advised for more precise characterisation if ultrasound results are inconclusive. The ovarian-adnexal reporting and data system (O-RADS) MRI lexicon and scoring system provides a standardised method for describing, assessing, and categorising the risk of each ovarian mass. Determining a histological differential diagnosis of the mass may influence treatment decision-making and treatment planning. When ultrasound or MRI suggests the possibility of cancer, computed tomography (CT) is the preferred imaging technique for staging. It is essential to outline the extent of the malignancy, guide treatment decisions, and evaluate the feasibility of cytoreductive surgery.This article provides a comprehensive overview of the key imaging processes in evaluating and managing ovarian masses, from initial diagnosis to initial treatment. It also includes pertinent recommendations for properly performing and interpreting various imaging modalities.MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians.CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery.Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians.CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery.Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to evaluate the utility of uterine extension determined via MRI for the differentiation of large subserosal leiomyomas from ovarian tumors. Methods: In total, 55 patients with subserosal leiomyomas and 127 patients with ovarian tumors were included in this study. These patients were selected from a cohort of female patients whose pelvic masses were larger than 10 cm and who underwent preoperative MRI. We retrospectively reviewed the MRI and compared the diagnostic ability of uterine extension measurements and bridging vascular signs for differentiating subserosal leiomyomas from ovarian tumors. Results: The vertical height of the uterus (107.2 ± 36.4 mm vs. 59.9 ± 24.9 mm, p < 0.01), the uterine length (114.4 ± 34.9 mm vs. 80.4 ± 23.8 mm, p < 0.01), and the frequency of the bridging vascular sign (78% vs. 6%, p < 0.01) were significantly higher in subserosal leiomyomas than in ovarian tumors. For diagnosing subserosal leiomyoma, the area under the curve, sensitivity, and specificity of vertical height of the uterus, using cutoff threshold > 81 mm, were 0.89, 89%, and 80% and those of the uterine length, using cutoff threshold > 84 mm, were 0.85, 69%, and 93%, respectively. Alternatively, the sensitivity and specificity of bridging vascular sign were 78% and 94%, respectively. Conclusion: Uterine extension determined via MRI is a useful parameter for differentiating large subserosal leiomyomas from ovarian tumors. [ABSTRACT FROM AUTHOR]

In a sample of individuals with ovarian cancer, we aimed to (a) identify factors associated with the psychosocial impact of genetic counseling and multigene panel testing, (b) identify factors associated with cancer genetics knowledge, and (c) summarize patient-reported recommendations to improve the genetic counseling and multigene panel testing process. Eligible participants in this secondary analysis of quantitative and qualitative survey data were English-speaking adults with ovarian cancer. Psychosocial impact was assessed using the Multidimensional Impact of Cancer Risk Assessment (MICRA) questionnaire. Knowledge of cancer genetics was assessed using the KnowGene scale. Significant predictors of MICRA and KnowGene scores were identified using multiple regression. Open-ended survey item responses were analyzed using conventional content analysis. Eighty-seven participants met eligibility criteria. A positive genetic test result was associated with greater adverse psychosocial impact (B = 1.13, p = 0.002). Older age (B = − 0.07, p = 0.044) and being a member of a minority racial or ethnic group (B = − 3.075, p = 0.033) were associated with lower knowledge, while a personal history of at least one other type of cancer (B = 1.975, p = 0.015) was associated with higher knowledge. In open-ended item responses, participants wanted clinicians to assist with family communication, improve result disclosure, and enhance patient and family understanding of results. A subset of individuals with ovarian cancer who receive a positive genetic test result may be at risk for adverse psychosocial outcomes. Tailored cancer genetics education is necessary to promote the equitable uptake of targeted ovarian cancer treatment and risk-reducing therapies. Interventions to enhance patient-clinician communication in this setting are a research priority. [ABSTRACT FROM AUTHOR]

Copyright of Der Gynäkologe is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Despite being widely used, to date (June 2021), the regimen of bevacizumab 10 mg/kg every 2 weeks (Q2W) combined with chemotherapy is not approved in Japan for patients with platinum-resistant recurrent ovarian cancer. In this retrospective analysis, we evaluated the usage patterns of bevacizumab administered for platinum-resistant recurrent ovarian cancer. Methods: We obtained clinical data from 155 Japanese medical facilities between November 2013 and December 2018 via a survey. Items included the number of cases of platinum-resistant recurrent ovarian cancer treated with bevacizumab according to dosage. For regimens including bevacizumab 10 mg/kg Q2W, additional information was requested relating to concomitantly administered agents, and the efficacy and safety of the regimen. Results: Of 1739 bevacizumab-containing regimens reported in 1633 patients with recurrent ovarian cancer, 264 used 10 mg/kg Q2W. The overall response rate (ORR) with this regimen was 26.1%. Response rates varied according to regimen and were particularly favorable when bevacizumab 10 mg/kg Q2W was administered with paclitaxel (ORR, 53.0%) versus liposomal doxorubicin (15.0%; P < 0.0001) and irinotecan (7.7%; P < 0.028). The most frequent Grade ≥ 3 adverse events associated with bevacizumab 10 mg/kg Q2W were neutropenia (11.7%) and hypertension (11.7%). The most frequent bevacizumab-associated Grade ≥ 3 adverse events with bevacizumab plus paclitaxel versus bevacizumab plus liposomal doxorubicin were hypertension (9.0% versus 13.9%) and proteinuria (3.0% versus 8.4%). Conclusions: Bevacizumab 10 mg/kg Q2W appears efficacious for patients with recurrent ovarian cancer, with a manageable toxicity profile. Approval of this regimen is clinically desirable for Japanese patients with ovarian cancer. [ABSTRACT FROM AUTHOR]

Objectives: To develop a radiomics signature based on multisequence magnetic resonance imaging (MRI) to preoperatively predict peritoneal metastasis (PM) in ovarian cancer (OC). Methods: Eighty-nine patients with OC were divided into a training cohort including patients (n = 54) with a single lesion and a validation cohort including patients (n = 35) with bilateral lesions. Radiomics features were extracted from the T2-weighted images (T2WIs), fat-suppressed T2WIs, multi-b-value diffusion-weighted images (DWIs), and corresponding parametric maps. A radiomics signature and nomogram incorporating the radiomics signature and clinical predictors were developed and validated on the training and validation cohorts, respectively. Results: The radiomics signature generated by 6 selected features showed a favorable discriminatory ability to predict PM in OC with an area under the curve (AUC) of 0.963 in the training cohort and an AUC of 0.928 in the validation cohort. The nomogram, comprising the radiomics signature, pelvic fluid, and CA-125 level, showed more favorable discrimination with an AUC of 0.969 in the training cohort and 0.944 in the validation cohort. Net reclassification index with values of 0.548 in the training cohort and 0.500 in the validation cohort. Conclusion: Radiomics signature based on multisequence MRI serves as an effective quantitative approach to predict PM in OC patients. A nomogram of radiomics signature and clinical predictors could further improve the prediction ability of PM in patients with OC. Key Points: • Multisequence MRI-based radiomics showed a favorable discriminatory ability to predict PM in OC. • The nomogram incorporating the radiomics signature and clinical predictors was clinically useful to preoperatively predict PM in patients with OC. [ABSTRACT FROM AUTHOR]

Objectives: To develop a preoperative MRI-based radiomic-clinical nomogram for prediction of residual disease (RD) in patients with advanced high-grade serous ovarian carcinoma (HGSOC). Methods: In total, 217 patients with advanced HGSOC were enrolled from January 2014 to June 2019 and randomly divided into a training set (n = 160) and a validation set (n = 57). Finally, 841 radiomic features were extracted from each tumor on T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) sequence, respectively. We used two fusion methods, the maximal volume of interest (MV) and the maximal feature value (MF), to fuse the radiomic features of bilateral tumors, so that patients with bilateral tumors have the same kind of radiomic features as patients with unilateral tumors. The radiomic signatures were constructed by using mRMR method and LASSO classifier. Multivariable logistic regression analysis was used to develop a radiomic-clinical nomogram incorporating radiomic signature and conventional clinico-radiological features. The performance of the nomogram was evaluated on the validation set. Results: In total, 342 tumors from 217 patients were analyzed in this study. The MF-based radiomic signature showed significantly better prediction performance than the MV-based radiomic signature (AUC = 0.744 vs. 0.650, p = 0.047). By incorporating clinico-radiological features and MF-based radiomic signature, radiomic-clinical nomogram showed favorable prediction ability with an AUC of 0.803 in the validation set, which was significantly higher than that of clinico-radiological signature and MF-based radiomic signature (AUC = 0.623, 0.744, respectively). Conclusions: The proposed MRI-based radiomic-clinical nomogram provides a promising way to noninvasively predict the RD status. Key Points: • MRI-based radiomic-clinical nomogram is feasible to noninvasively predict residual disease in patients with advanced HGSOC. • The radiomic signature based on MF showed significantly better prediction performance than that based on MV. • The radiomic-clinical nomogram showed a favorable prediction ability with an AUC of 0.803. [ABSTRACT FROM AUTHOR]

Background: To evaluate the performance of a decision support system (DSS) based on radiomics and machine learning in predicting the risk of malignancy of ovarian masses (OMs) from transvaginal ultrasonography (TUS) and serum CA-125. Methods: A total of 274 consecutive patients who underwent TUS (by different examiners and with different ultrasound machines) and surgery, with suspicious OMs and known CA-125 serum level were used to train and test a DSS. The DSS was used to predict the risk of malignancy of these masses (very low versus medium-high risk), based on the US appearance (solid, liquid, or mixed) and radiomic features (morphometry and regional texture features) within the masses, on the shadow presence (yes/no), and on the level of serum CA-125. Reproducibility of results among the examiners, and performance accuracy, sensitivity, specificity, and area under the curve were tested in a real-world clinical setting. Results: The DSS showed a mean 88% accuracy, 99% sensitivity, and 77% specificity for the 239 patients used for training, cross-validation, and testing, and a mean 91% accuracy, 100% sensitivity, and 80% specificity for the 35 patients used for independent testing. Conclusions: This DSS is a promising tool in women diagnosed with OMs at TUS, allowing to predict the individual risk of malignancy, supporting clinical decision making. [ABSTRACT FROM AUTHOR]

Objectives: There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study developed a deep learning algorithm that distinguishes benign from malignant ovarian lesion by applying a convolutional neural network on routine MR imaging. Methods: Five hundred forty-five lesions (379 benign and 166 malignant) from 451 patients from a single institution were divided into training, validation, and testing set in a 7:2:1 ratio. Model performance was compared with four junior and three senior radiologists on the test set. Results: Compared with junior radiologists averaged, the final ensemble model combining MR imaging and clinical variables had a higher test accuracy (0.87 vs 0.64, p < 0.001) and specificity (0.92 vs 0.64, p < 0.001) with comparable sensitivity (0.75 vs 0.63, p = 0.407). Against the senior radiologists averaged, the final ensemble model also had a higher test accuracy (0.87 vs 0.74, p = 0.033) and specificity (0.92 vs 0.70, p < 0.001) with comparable sensitivity (0.75 vs 0.83, p = 0.557). Assisted by the model's probabilities, the junior radiologists achieved a higher average test accuracy (0.77 vs 0.64, Δ = 0.13, p < 0.001) and specificity (0.81 vs 0.64, Δ = 0.17, p < 0.001) with unchanged sensitivity (0.69 vs 0.63, Δ = 0.06, p = 0.302). With the AI probabilities, the junior radiologists had higher specificity (0.81 vs 0.70, Δ = 0.11, p = 0.005) but similar accuracy (0.77 vs 0.74, Δ = 0.03, p = 0.409) and sensitivity (0.69 vs 0.83, Δ = -0.146, p = 0.097) when compared with the senior radiologists. Conclusions: These results demonstrate that artificial intelligence based on deep learning can assist radiologists in assessing the nature of ovarian lesions and improve their performance. Key Points: • Artificial Intelligence based on deep learning can assess the nature of ovarian lesions on routine MRI with higher accuracy and specificity than radiologists. • Assisted by the deep learning model's probabilities, junior radiologists achieved better performance that matched those of senior radiologists. [ABSTRACT FROM AUTHOR]

Epithelial ovarian cancer (EOC) represents the most frequently occurring gynecological malignancy, accounting for more than 70% of ovarian cancer deaths. Preoperative imaging plays an important role in assessing the extent of disease and guides the next step in surgical decision-making and operative planning. In this article, we will review the multimodality imaging features of various subtypes of EOC. We will also discuss the role of imaging in the staging, management, and surveillance of EOC. [ABSTRACT FROM AUTHOR]

Purpose: To develop a precision tissue sampling technique that uses computed tomography (CT)–based radiomic tumour habitats for ultrasound (US)-guided targeted biopsies that can be integrated in the clinical workflow of patients with high-grade serous ovarian cancer (HGSOC). Methods: Six patients with suspected HGSOC scheduled for US-guided biopsy before starting neoadjuvant chemotherapy were included in this prospective study from September 2019 to February 2020. The tumour segmentation was performed manually on the pre-biopsy contrast-enhanced CT scan. Spatial radiomic maps were used to identify tumour areas with similar or distinct radiomic patterns, and tumour habitats were identified using the Gaussian mixture modelling. CT images with superimposed habitat maps were co-registered with US images by means of a landmark-based rigid registration method for US-guided targeted biopsies. The dice similarity coefficient (DSC) was used to assess the tumour-specific CT/US fusion accuracy. Results: We successfully co-registered CT-based radiomic tumour habitats with US images in all patients. The median time between CT scan and biopsy was 21 days (range 7–30 days). The median DSC for tumour-specific CT/US fusion accuracy was 0.53 (range 0.79 to 0.37). The CT/US fusion accuracy was high for the larger pelvic tumours (DSC: 0.76–0.79) while it was lower for the smaller omental metastases (DSC: 0.37–0.53). Conclusion: We developed a precision tissue sampling technique that uses radiomic habitats to guide in vivo biopsies using CT/US fusion and that can be seamlessly integrated in the clinical routine for patients with HGSOC. Key Points: • We developed a prevision tissue sampling technique that co-registers CT-based radiomics–based tumour habitats with US images. • The CT/US fusion accuracy was high for the larger pelvic tumours (DSC: 0.76–0.79) while it was lower for the smaller omental metastases (DSC: 0.37–0.53). [ABSTRACT FROM AUTHOR]

Homologous recombination (HR) is one of the important mechanisms in repairing double-strand breaks to maintain genomic integrity and DNA stability from the cytotoxic effects and mutations. Various studies have reported that single nucleotide polymorphisms (SNPs) in the HR-associated genes may have a significant association with ovarian cancer (OCa) risk but the results were inconclusive. In the present study, five polymorphisms of HR-associated genes (RAD51, XRCC2 and XRCC3) were genotyped by allelic discrimination assay in 200 OCa cases and 200 healthy individuals. The association with OCa risk was evaluated by unconditional logistic regression analyses. The results revealed that the mutant allele in both rs1801320 (CC) and rs1801321 (TT) of RAD51 gene was associated with increased risk of OCa (odds ratio [OR] 3.79, 95% confidence interval [CI] 1.21–11.78, p = 0.014 and OR 1.61, 95% CI 1.06–2.45, p = 0.025, respectively). Moreover, a significant association of TT allele (OR 4.68, 95% CI 1.27–17.15, p = 0.011) of rs3218536 of XRCC2 gene with OCa was observed. Stratified analysis results showed that patients with early menarche and stages 3 and 4 were found to be associated with rs1801321 of RAD51 gene and rs1799794 of XRCC3 gene. In silico analysis predicted that the two missense SNPs (rs3218536 and rs1799794) were found to have an impact on the protein structure, stability and function. The present study suggested that RAD51 and XRCC2 gene polymorphisms might have an impact on the OCa risk in the South Indian population. However, studies with a larger sample and on different populations are needed to support the conclusions. [ABSTRACT FROM AUTHOR]

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Purpose: To define and weight the preoperative CT findings for ovarian torsion and to develop an integrated nomogram for estimating the probability of ovarian torsion in women with ovarian lesion and pelvic pain. Methods: This retrospective study included 218 women with surgically resected ovarian lesions who underwent preoperative contrast-enhanced CT for pelvic pain from January 2014 to February 2019. Significant imaging findings for torsion were extracted using regression analyses and a regression coefficient-based nomogram was constructed. The diagnostic performance with sensitivity, specificity, and accuracy of the significant imaging findings and the nomogram were assessed. Results: A total of 255 ovarian lesions (123 lesions with torsion and 132 lesions without torsion) were evaluated. Multivariable regression analysis showed that whirl sign (odds ratio [OR] 11.000; p < 0.001), tubal thickening (OR 4.621; p = 0.001), unusual location of ovarian lesion (OR 2.712; p = 0.020), and hemorrhagic component within adnexal lesion (OR 2.537; p = 0.028) were independent significant parameters predicting ovarian torsion. Tubal thickening showed the highest sensitivity (91.1%) and whirl sign showed the highest specificity (94.7%). When probabilities of ovarian torsion of 0.5 or more in the nomogram were diagnosed as ovarian torsion, sensitivity, specificity, and accuracy of the nomogram were 78.1%, 91.7%, and 85.1%, respectively. Conclusion: The whirl sign, tubal thickening, unusual location of ovarian lesion, and hemorrhagic component within adnexal lesion, and an integrated nomogram derived from these significant findings can be useful for predicting ovarian torsion. [ABSTRACT FROM AUTHOR]

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Copyright of Gynäkologische Endokrinologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Der Gynäkologe is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: To investigate the predictive value of peritoneal carcinomatosis (PC) quantification by DWI in determining incomplete tumour debulking in ovarian carcinoma (OC). Methods: Prospective patients with suspected stage III–IV or recurrent OC were recruited for DWI before surgery. PC on DWI was segmented semi-automatically by k-means clustering, retaining voxels with intermediate apparent diffusion coefficient (ADC) to quantify PC burden. A scoring system, functional peritoneal cancer index (fPCI), was proposed based on the segmentation of tumour volume in 13 abdominopelvic regions with additional point given to involvement of critical sites. ADC of the largest PC was recorded. The surgical complexity and outcomes (complete vs. incomplete tumour debulking) were documented. fPCI was correlated with surgical PCI (sPCI), surgical complexity, and its ability to predict incomplete tumour debulking. Results: Fifty-three patients with stage III–IV or recurrent OC were included with a mean age of 56.1 ± 11.8 years old. Complete tumour debulking was achieved in 38/53 patients (71.7%). Significant correlation was found between fPCI and sPCI (r > 0.757, p < 0.001). Patients with high-fPCI (fPCI ≥ 6) had a high surgical complexity score (p = 0.043) with 84.2% received radical or supra-radical surgery. The mean fPCI was significantly higher in patients with incomplete tumour debulking than in those with complete debulking (10.27 vs. 4.71, p < 0.001). fPCI/ADC combined with The International Federation of Gynecology and Obstetrics stage achieved 92.5% accuracy in predicting incomplete tumour debulking (AUC 0.947). Conclusions: DWI-derived fPCI offered a semi-automated estimation of PC burden. fPCI/ADC could predict the likelihood of incomplete tumour debulking with high accuracy. Key Points: • Functional peritoneal cancer index (fPCI) derived from DWI offered a semi-automated estimation of tumour burden in ovarian carcinoma. • fPCI was highly correlated with surgical PCI (sPCI). • fPCI/ADC could predict the likelihood of incomplete tumour debulking with high accuracy. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the association between CT imaging traits and texture metrics with proteomic data in patients with high-grade serous ovarian cancer (HGSOC). Methods: This retrospective, hypothesis-generating study included 20 patients with HGSOC prior to primary cytoreductive surgery. Two readers independently assessed the contrast-enhanced computed tomography (CT) images and extracted 33 imaging traits, with a third reader adjudicating in the event of a disagreement. In addition, all sites of suspected HGSOC were manually segmented texture features which were computed from each tumor site. Three texture features that represented intra- and inter-site tumor heterogeneity were used for analysis. An integrated analysis of transcriptomic and proteomic data identified proteins with conserved expression between primary tumor sites and metastasis. Correlations between protein abundance and various CT imaging traits and texture features were assessed using the Kendall tau rank correlation coefficient and the Mann-Whitney U test, whereas the area under the receiver operating characteristic curve (AUC) was reported as a metric of the strength and the direction of the association. P values < 0.05 were considered significant. Results: Four proteins were associated with CT-based imaging traits, with the strongest correlation observed between the CRIP2 protein and disease in the mesentery (p < 0.001, AUC = 0.05). The abundance of three proteins was associated with texture features that represented intra-and inter-site tumor heterogeneity, with the strongest negative correlation between the CKB protein and cluster dissimilarity (p = 0.047, τ = 0.326). Conclusion: This study provides the first insights into the potential associations between standard-of-care CT imaging traits and texture measures of intra- and inter-site heterogeneity, and the abundance of several proteins. Key Points: • CT-based texture features of intra- and inter-site tumor heterogeneity correlate with the abundance of several proteins in patients with HGSOC. • CT imaging traits correlate with protein abundance in patients with HGSOC. [ABSTRACT FROM AUTHOR]

Background/objective: Elderly patients with cancer are often at risk for undertreatment because of frailty, an aging-specific problem. However, current real-world conditions of recurrent ovarian cancer treatment in elderly patients remain unclear. This study aimed to clarify treatment patterns in elderly patients with recurrent ovarian cancer. Patients and methods: We used an ovarian cancer database containing the diagnosis and initial therapy of all patients at the National Cancer Center Hospital in Japan from 2007 to 2014. Patients were stratified into the platinum-sensitive group and the platinum-resistant group. We retrospectively assessed chemotherapy use in patients aged ≤ 64, 65–69, 70–74, 75–79, and ≥ 80 years. Results: Among 253 patients (sensitive group: 135; resistant group: 118), by age group 91%, 95%, 100%, 100%, and 100% received chemotherapy in the sensitive group, and 79%, 67%, 50%, 29%, 0% received chemotherapy in the resistant group, respectively. In the resistant group, the percentage of patients aged 70–74 or 75–79 years who received chemotherapy was significantly lower than the percentage among patients aged ≤ 64 years, respectively (p = 0.01, p = 0.01). In multivariate analysis, age ≥ 70 years (odds ratio [OR], 4.412; 95% confidence interval (CI), 1.628–11.959; p = 0.004) and platinum-free interval < 3 months (OR, 3.434; 95% CI, 1.401–8.399; p = 0.007) were inversely associated with chemotherapy use. Conclusions: Doctors and patients did not consider chemotherapy in patients aged ≥ 70 years with platinum-resistant disease. Older age was independently and inversely associated with chemotherapy use in platinum-resistant ovarian cancer. Our results highlight the importance of demographic information in clinical decision-making for elderly patients. [ABSTRACT FROM AUTHOR]

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Objective: The purpose of this article is to review the imaging findings and genomics of granulosa cell tumors (GCTs) in order to aid in diagnosis and management of GCTs. GCTs are the most common type of sex cord-stromal tumors of the ovary. They are usually diagnosed initially with ultrasound and are subsequently further characterized with CT and MRI. PET/CT is often ordered as well to measure the extent of disease and for follow-up, but its usefulness is in question as some GCTs lack FDG avidity. There is significant variability in imaging phenotypes of GCTs, ranging from mostly cystic to almost solid. More resources have recently been dedicated to understanding the genetics and molecular mechanisms of GCT development. Current research shows that the main cause of GCT carcinogenesis is the FOXL2 mutation, but there are several other noteworthy mutations that contribute to the pathogenesis of this disease. Certain mutations, like GATA4, are known to be associated with more aggressive disease and higher rates of recurrence. Conclusion: Using this information, imaging protocols can be altered depending on the genotype of the tumor. Further understanding of the genetic alterations that underpin the development of GCTs is indicated as genotypic knowledge could be used to guide optimal imaging and management strategies. [ABSTRACT FROM AUTHOR]

Our knowledge of ovarian teratomas in children is still far from complete, and much remains to be discovered. Here, we conduct a scoping review of the primary research related to ovarian teratomas in pediatric age. To our knowledge, there is no published synthesis of the literature surrounding ovarian teratomas in children using scoping review methodology. We identified 24 studies from 11 countries; 18 studies were retrospective, 3 were prospective, and 3 were experimental. There were 6 studies concerning mature teratomas, 5 concerning immature teratomas, and 13 that included both tumor types. Overall, 9 out of all the studies concerned more than 50 patients. We revealed 7 major branches of research within the topic of ovarian teratoma in pediatric population: recurrence rate/relapse and follow-up strategy, malignant potential, prognostic factors, use of sparing surgery, differences between the use of laparoscopy and laparotomy, use of chemotherapy, and additional examinations to test the character of the lesion (immature vs. mature). This scoping review has revealed a number of knowledge gaps in the evidence base for pediatric ovarian teratomas. Overall, this topic has not been extensively explored, and more research dedicated exclusively to this tumor and patient population is required. [ABSTRACT FROM AUTHOR]

Objectives: The use of magnetic resonance (MR) imaging in differentiation between benign and malignant adnexal masses in children and adolescents might be of great value in the diagnostic workup of sonographically indeterminate masses, since preserving fertility is of particular importance in this population. This systematic review evaluates the diagnostic value of MR imaging in children with an ovarian mass.Methods: The review was made according to the PRISMA Statement. PubMed and EMBASE were systematically searched for studies on the use of MR imaging in differential diagnosis of ovarian masses in both adult women and children from 2008 to 2018.Results: Sixteen paediatric and 18 adult studies were included. In the included studies, MR imaging has shown good diagnostic performance in differentiating between benign and malignant ovarian masses. MR imaging techniques including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging seem to further improve the diagnostic performance.Conclusion: The addition of DWI with apparent diffusion coefficient (ADC) values measured in enhancing components of solid lesions and DCE imaging may further increase the good diagnostic performance of MR imaging in the pre-operative differentiation between benign and malignant ovarian masses by increasing specificity. Prospective age-specific studies are needed to confirm the high diagnostic performance of MR imaging in children and adolescents with a sonographically indeterminate ovarian mass.Key Points: • MR imaging, based on several morphological features, is of good diagnostic performance in differentiating between benign and malignant ovarian masses. Sensitivity and specificity varied between 84.8 to 100% and 20.0 to 98.4%, respectively. • MR imaging techniques like diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging seem to improve the diagnostic performance. • Specific studies in children and adolescents with ovarian masses are required to confirm the suggested increased diagnostic performance of DWI and DCE in this population. [ABSTRACT FROM AUTHOR]

This systematic review evaluated the effectiveness of strategies to identify and manage patients with familial risk of breast, ovarian, colorectal and prostate cancer in primary care to improve clinical outcomes. MEDLINE, EMBASE, CINAHL and Cochrane library were searched from January 1980 to October 2017. We included randomised controlled trials (RCT) and non-randomised studies of interventions (NRSI). Primary outcomes were cancer incidence, cancer-related clinical outcomes or the identification of cancer predisposition; secondary outcomes were the appropriateness of referral, uptake of preventive strategies and cognitive and psychological effect. From 11,842 abstracts, 111 full texts were reviewed and three eligible studies (nine articles) identified. Two were cluster RCTs and one NRSI; all used risk assessment software. No studies identified our primary outcomes, with no consistent outcome across the three studies. In one RCT, intervention improved the proportion of genetic referrals meeting referral guidelines for breast cancer (OR 4.5, 95% CI 1.6 to 13.1). In the other RCT, there was no difference in screening adherence between the intervention and control group. However, there was borderline increased risk perception (OR 1.89, 95% CI 0.99 to 3.59) in the subgroup that under-estimated their colon cancer risk. In the NRSI, there was no change in psychological distress in patients at increased familial breast cancer risk, but population risk patients had reduced anxiety after intervention (state anxiety mean change − 3, 95% CI − 5 to − 2). Future studies should have better-defined comparator groups and longer follow-up and assess outcomes using validated tools. [ABSTRACT FROM AUTHOR]

Recent studies have shown that re-expression of stem cell factors contribute to pathogenesis, therapy resistance, and recurrent disease in ovarian carcinomas. In this study, we compare the expression and co-expression of stem cell markers ALDH1 and SOX2 in different types of serous ovarian tumors. A total of 215 serous ovarian tumors (161 high-grade serous carcinomas (HGSC), 17 low-grade serous carcinomas (LGSC), 37 atypical proliferative serous tumors (APST)), and 10 cases of serous tubal intraepithelial carcinoma (STIC) were analyzed. Double immunostaining experiments addressed the association of cell proliferation (Ki67) with ALDH1 and the potential co-expression of SOX2 and ALDH1. The prognostic effect was analyzed in the cohort of HGSC. Expression of ALDH1and/or SOX2 was detected with increased frequency in HGSC (88.8%), compared with LGSC (70.5%) and APST (36.4%), while ALDH1 alone was significantly more frequently expressed in LGSC. The majority of all tumor types showed expression of ALDH1 and SOX2 in different cells. Only a minority of HGSC (4.6%) and STIC (20%) showed SOX2/ALDH1 co-expression in > 10% of tumor cells. Double staining also revealed that ALDH1 is associated with the non-proliferating Ki67-negative fraction consistent with a stem cell phenotype. Co-expression of ALDH1 and SOX2 or ALDH1 and Ki67 has no effect on survival. Expression of stem cell factors ALDH1 and/or SOX2 shows increased frequency in high-grade serous ovarian carcinomas compared to low-grade carcinomas and borderline tumors, supporting the concept that stem cell markers play different biological roles in low-grade versus high-grade serous neoplasia of the ovary. [ABSTRACT FROM AUTHOR]

Objective: To examine the effectiveness of pegylated liposomal doxorubicin (PLD) maintenance therapy (intravenous administration at dose 40 mg/m2 on day 1, repeated every 4 weeks) after first-line salvage chemotherapy for platinum-sensitive recurrent epithelial ovarian cancer. Methods: This retrospective cohort study examined women with a first recurrence of platinum-sensitive epithelial ovarian cancer diagnosed between 2005 and 2015. Eligible cases had PLD maintenance following the first-line salvage chemotherapy (n = 28). Outcomes of interest included adverse events related to PLD maintenance therapy and survival outcome after the first recurrence. Results: The median number of PLD maintenance cycles was 7.5 (range 2–26), and 11 (40%) women received ≥ 12 cycles. The median cumulative dose of PLD was 432.5 mg/m2 (range 120–1200 mg/m2). No women developed cardiotoxicity or secondary malignancies. There were 16 (57%) women who developed any grade of adverse events, including 3 (11%) women who developed grade 3 adverse events. There were no grade 4 adverse events. The most common adverse event was mucositis (n = 7, 25%). Dose reduction due to adverse events occurred in 14 (50%) women including 3 (11%) women with discontinuation due to toxicity. Median progression-free survival and overall survival after the initiation of PLD maintenance was 14.5 months (2-year rate 21.1%) and 51.2 months (5-year rate 43.4%), respectively. Conclusion: Our study suggests that PLD maintenance therapy for platinum-sensitive recurrent ovarian cancer is relatively well tolerated with the use of dose reduction to manage toxicity. Our study suggests that PLD maintenance therapy may be effective for women with platinum-sensitive recurrent epithelial ovarian cancer. [ABSTRACT FROM AUTHOR]

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Copyright of Der Onkologe is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To investigate changes in estrogen receptor alpha (ERα) signaling during progression of endometriosis to endometriosis-associated ovarian cancer (EAOC) as a driver of malignant transformation. We procured tissue samples of normal endometrium, endometriosis (benign, atypical, concurrent with EAOC), and EAOC. We evaluated expression of a 236-gene signature of estrogen signaling. ANOVA and unsupervised clustering were used to identify gene expression profiles across disease states. These profiles were compared to profiles of estrogen regulation in cancer models from the Gene Expression Omnibus (GEO). Gene Set Enrichment Analysis (GSEA) was performed to determine whether gene expression in EAOC was consistent with ERα activity. ANOVA revealed 158 differentially expressed genes (q < 0.05) and unsupervised clustering identified five distinct gene clusters. The estrogen signaling profile of EAOC was not consistent with activated ERα in pre-clinical models. Gene set enrichment analysis did not identify signatures of activated ERα in EAOC but instead identified expression patterns consistent with loss of ERα function and development of endocrine resistance. Gene expression data suggest that ERα signaling becomes inactivated throughout the progression of endometriosis to EAOC. The gene expression pattern in EAOC is more consistent with profiles of endocrine resistance. [ABSTRACT FROM AUTHOR]

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In the tumor microenvironment, adipocytes function as an alternate fuel source for cancer cells. However, whether adipocytes influence macromolecular biosynthesis in cancer cells is unknown. Here we systematically characterized the bidirectional interaction between primary human adipocytes and ovarian cancer (OvCa) cells using multi-platform metabolomics, imaging mass spectrometry, isotope tracing and gene expression analysis. We report that, in OvCa cells co-cultured with adipocytes and in metastatic tumors, a part of the glucose from glycolysis is utilized for the biosynthesis of glycerol-3-phosphate (G3P). Normoxic HIF1α protein regulates the altered flow of glucose-derived carbons in cancer cells, resulting in increased glycerophospholipids and triacylglycerol synthesis. The knockdown of HIF1α or G3P acyltransferase 3 (a regulatory enzyme of glycerophospholipid synthesis) reduced metastasis in xenograft models of OvCa. In summary, we show that, in an adipose-rich tumor microenvironment, cancer cells generate G3P as a precursor for critical membrane and signaling components, thereby promoting metastasis. Targeting biosynthetic processes specific to adipose-rich tumor microenvironments might be an effective strategy against metastasis., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: To build and validate a radiomics nomogram based on preoperative CT scans and clinical data for detecting synchronous ovarian metastasis (SOM) in female gastric cancer (GC) cases., Methods: Pathologically confirmed GC cases in 2 cohorts were retrospectively enrolled. All cases had presurgical abdominal contrast-enhanced CT and pelvis contrast-enhanced MRI and pathological examinations for any suspicious ovarian lesions detected by MRI. Cohort 1 cases (n = 101) were included as the training set. Radiomics features were obtained to develop a radscore. A nomogram combining the radscore and clinical factors was built to detect SOM. The bootstrap method was carried out in cohort 1 as internal validation. External validation was carried out in cohort 2 (n = 46). Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) and the confusion matrix were utilized to assess the performances of the radscore, nomogram and subjective evaluation model., Results: The nomogram, which combined age and the radscore, displayed a higher AUC than the radscore and subjective evaluation (0.910 vs 0.827 vs 0.773) in the training cohort. In the external validation cohort, the nomogram also had a higher AUC than the radscore and subjective evaluation (0.850 vs 0.790 vs 0.675). DCA and the confusion matrix confirmed the nomogram was superior to the radscore in both cohorts., Conclusions: This pilot study showed that a nomogram model combining the radscore and clinical characteristics is useful in detecting SOM in female GC cases. It may be applied to improve clinical treatment and is superior to subjective evaluation or the radscore alone., (© 2023. The Author(s).)