Fei Teng, Honglei Xie, Hong Wei, Dehong Che, Hongbo Wang, Chengwei Wu, Xin He, Xiaoqiu Dong
{"title":"卵巢-附件报告及数据系统超声诊断卵巢肿块的价值:一项双中心研究。","authors":"Fei Teng, Honglei Xie, Hong Wei, Dehong Che, Hongbo Wang, Chengwei Wu, Xin He, Xiaoqiu Dong","doi":"10.1093/bjr/tqae247","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to assess the diagnostic efficacy of the ovarian adnexal reporting and data system (O-RADS) and ultrasound (US) and its sub-classification system for distinguishing ovarian masses.</p><p><strong>Methods: </strong>O-RADS US was used for the retrospective analysis of 606 ovarian masses of Chinese from 2 medical centres by 2 gynaecologic sonographers with varying experience. The O-RADS 4 categories masses were further sub-classified into O-RADS 4a and O-RADS 4b through 3 different approaches (O-RADS A1/A2/A3).</p><p><strong>Results: </strong>The AUC of O-RADS US for differentiating benign from malignant ovarian masses was 0.927 (95% CI, 0.903-0.946, P < .001). The optimal cut-off value for predicting malignancy was >O-RADS 3, with sensitivity and specificity of 98.60% and 68.90%, respectively. The diagnostic efficacy of the 3 sub-classification systems surpassed that of O-RADS US (P < .05). Specifically, A2 approach (within O-RADS 4 lesions, unilocular and multilocular cysts with solid components were sub-classified as O-RADS 4b, whereas the remaining O-RADS 4 lesions were sub-classified as O-RADS 4a) resulted in an AUC of 0.942 (95% CI, 0.921-0.960, P < .001). The best cut-off value predicting malignancy was >O-RADS 4a, exhibiting relatively high specificity (82.51%) and maintaining a high sensitivity (93.01%).</p><p><strong>Conclusion: </strong>The diagnostic efficacy of O-RADS US for identifying ovarian tumours is good, but specificity is slightly lower. This study enhanced diagnostic specificity after subclassifying O-RADS 4 lesions, especially A2 approach. It holds significant clinical value for Chinese women and merits further clinical promotion and application.</p><p><strong>Advances in knowledge: </strong>The sub-classification of O-RADS US allows better identifying ovarian tumours, facilitating informed preoperative clinical management and diagnosis.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":"448-457"},"PeriodicalIF":1.8000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnostic value of the ovarian adnexal reporting and data system ultrasound in ovarian masses: a 2-center study.\",\"authors\":\"Fei Teng, Honglei Xie, Hong Wei, Dehong Che, Hongbo Wang, Chengwei Wu, Xin He, Xiaoqiu Dong\",\"doi\":\"10.1093/bjr/tqae247\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study aimed to assess the diagnostic efficacy of the ovarian adnexal reporting and data system (O-RADS) and ultrasound (US) and its sub-classification system for distinguishing ovarian masses.</p><p><strong>Methods: </strong>O-RADS US was used for the retrospective analysis of 606 ovarian masses of Chinese from 2 medical centres by 2 gynaecologic sonographers with varying experience. The O-RADS 4 categories masses were further sub-classified into O-RADS 4a and O-RADS 4b through 3 different approaches (O-RADS A1/A2/A3).</p><p><strong>Results: </strong>The AUC of O-RADS US for differentiating benign from malignant ovarian masses was 0.927 (95% CI, 0.903-0.946, P < .001). The optimal cut-off value for predicting malignancy was >O-RADS 3, with sensitivity and specificity of 98.60% and 68.90%, respectively. The diagnostic efficacy of the 3 sub-classification systems surpassed that of O-RADS US (P < .05). Specifically, A2 approach (within O-RADS 4 lesions, unilocular and multilocular cysts with solid components were sub-classified as O-RADS 4b, whereas the remaining O-RADS 4 lesions were sub-classified as O-RADS 4a) resulted in an AUC of 0.942 (95% CI, 0.921-0.960, P < .001). The best cut-off value predicting malignancy was >O-RADS 4a, exhibiting relatively high specificity (82.51%) and maintaining a high sensitivity (93.01%).</p><p><strong>Conclusion: </strong>The diagnostic efficacy of O-RADS US for identifying ovarian tumours is good, but specificity is slightly lower. This study enhanced diagnostic specificity after subclassifying O-RADS 4 lesions, especially A2 approach. It holds significant clinical value for Chinese women and merits further clinical promotion and application.</p><p><strong>Advances in knowledge: </strong>The sub-classification of O-RADS US allows better identifying ovarian tumours, facilitating informed preoperative clinical management and diagnosis.</p>\",\"PeriodicalId\":9306,\"journal\":{\"name\":\"British Journal of Radiology\",\"volume\":\" \",\"pages\":\"448-457\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"British Journal of Radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/bjr/tqae247\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"British Journal of Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/bjr/tqae247","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Diagnostic value of the ovarian adnexal reporting and data system ultrasound in ovarian masses: a 2-center study.
Objective: This study aimed to assess the diagnostic efficacy of the ovarian adnexal reporting and data system (O-RADS) and ultrasound (US) and its sub-classification system for distinguishing ovarian masses.
Methods: O-RADS US was used for the retrospective analysis of 606 ovarian masses of Chinese from 2 medical centres by 2 gynaecologic sonographers with varying experience. The O-RADS 4 categories masses were further sub-classified into O-RADS 4a and O-RADS 4b through 3 different approaches (O-RADS A1/A2/A3).
Results: The AUC of O-RADS US for differentiating benign from malignant ovarian masses was 0.927 (95% CI, 0.903-0.946, P < .001). The optimal cut-off value for predicting malignancy was >O-RADS 3, with sensitivity and specificity of 98.60% and 68.90%, respectively. The diagnostic efficacy of the 3 sub-classification systems surpassed that of O-RADS US (P < .05). Specifically, A2 approach (within O-RADS 4 lesions, unilocular and multilocular cysts with solid components were sub-classified as O-RADS 4b, whereas the remaining O-RADS 4 lesions were sub-classified as O-RADS 4a) resulted in an AUC of 0.942 (95% CI, 0.921-0.960, P < .001). The best cut-off value predicting malignancy was >O-RADS 4a, exhibiting relatively high specificity (82.51%) and maintaining a high sensitivity (93.01%).
Conclusion: The diagnostic efficacy of O-RADS US for identifying ovarian tumours is good, but specificity is slightly lower. This study enhanced diagnostic specificity after subclassifying O-RADS 4 lesions, especially A2 approach. It holds significant clinical value for Chinese women and merits further clinical promotion and application.
Advances in knowledge: The sub-classification of O-RADS US allows better identifying ovarian tumours, facilitating informed preoperative clinical management and diagnosis.
期刊介绍:
BJR is the international research journal of the British Institute of Radiology and is the oldest scientific journal in the field of radiology and related sciences.
Dating back to 1896, BJR’s history is radiology’s history, and the journal has featured some landmark papers such as the first description of Computed Tomography "Computerized transverse axial tomography" by Godfrey Hounsfield in 1973. A valuable historical resource, the complete BJR archive has been digitized from 1896.
Quick Facts:
- 2015 Impact Factor – 1.840
- Receipt to first decision – average of 6 weeks
- Acceptance to online publication – average of 3 weeks
- ISSN: 0007-1285
- eISSN: 1748-880X
Open Access option