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Inter-reader reliability of Ovarian-Adnexal Reporting and Data System US: a systematic review and meta-analysis.
Abdom Radiol (NY)
January 2025
Hanyang University Guri Hospital, Guri-si, Korea, Republic of.
Purpose: Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized lexicon for ovarian and adnexal lesions, facilitating risk stratification based on morphological features for malignancy assessment, which is essential for proper management. However, systematic determination of inter-reader reliability in O-RADS US categorization remains unexplored. This study aimed to systematically determine the inter-reader reliability of O-RADS US categorization and identify the factors that affect it.
View Article and Find Full Text PDFA Multimodal Model Based on Transvaginal Ultrasound-Based Radiomics to Predict the Risk of Peritoneal Metastasis in Ovarian Cancer: A Multicenter Study.
Acad Radiol
January 2025
Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui, China (Y.Z., Y.D., Q.Z., C.Z.). Electronic address:
Rationale And Objectives: This study aimed to develop a predictive model for peritoneal metastasis (PM) in ovarian cancer using a combination radiomics and clinical biomarkers to improve diagnostic accuracy.
Patients And Methods: This retrospective cohort study of 619 ovarian cancer patients involved demographic data, radiomics, O-RADS standardized description, clinical biomarkers, and histological findings. Radiomics features were extracted using 3D Slicer and Pyradiomics, with selective feature extraction using Least Absolute Shrinkage and Selection Operator regression.
Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnexal masses.
Insights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
Implementation of O-RADS Ultrasound Reporting System: A Quality Improvement Initiative.
Can Assoc Radiol J
January 2025
Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
To determine the feasibility of implementing Ovarian-Adnexal Reporting & Data System (O-RADS) ultrasound (US) for reporting of adnexal masses at our institution, with a specific goal of increasing the use of O-RADS from a baseline of <5% to at least 75% over a 16-month period. A prospective interrupted time series quality improvement study was undertaken over a 16-month period. Plan, do, study, act cycles included: (1) Engagement of interested parties, (2) Targeted educational sessions, (3) Development of reporting templates, (4) Weekly audit-feedback.
View Article and Find Full Text PDFValue of MRI-Based Ovarian-Adnexal Reporting and Data System for the Diagnosis of Adnexal Masses.
Zhongguo Yi Xue Ke Xue Yuan Xue Bao
December 2024
Department of Radiology,The Central Hospital of Wuhan,Tongji Medical College, Huazhong University of Science and Technology,Wuhan 430014,China.
Objective To assess the value of the MRI-based ovarian-adnexal reporting and data system (O-RADS MRI) for the diagnosis of adnexal masses. Methods A total of 407 patients who underwent dynamic contrast enhancement (DCE)-MRI and pathological examination (gold standard) at the Department of Radiology,Central Hospital of Wuhan between May 2017 and December 2022 were enrolled in this study.Two radiologists performed the O-RADS MRI scoring of adnexal masses according to MRI features and calculated the malignancy rate of adnexal masses by O-RADS MRI score,enhancement type,and mass type.
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