Lan Cao1, Mingjie Wei1, Ying Liu1, Juan Fu1, Honghuan Zhang2, Jing Huang2, Xiaoqing Pei3, Jianhua Zhou4. 1. Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China. 2. Department of Ultrasound, Jiangmen Central Hospital, Jiangmen, China. 3. Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China. Electronic address: peixq@sysucc.org.cn. 4. Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China. Electronic address: zhoujh@sysucc.org.cn.
Abstract
OBJECTIVE: To assess the diagnostic performance and inter-observer agreement of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US). METHODS: From January 2016 to December 2018 a total of 1054 adnexal lesions in 1035 patients with pathologic results from two hospitals were retrospectively included. Each lesion was assigned to an O-RADS US category according to the criteria. Kappa (κ) statistics were applied to assess inter-observer agreement between a less experienced and an expert radiologist. RESULTS: Of the 1054 adnexal lesions, 750 were benign and 304 were malignant. The malignancy rates of O-RADS 5, O-RADS 4, O-RADS 3, and O-RADS 2 lesions were 89.57%, 34.46%, 1.10%, and 0.45% respectively. Area under the receiver operating characteristic curve was 0.960 (95% CI, 0.947-0.971). The optimal cutoff value for predicting malignancy was >O-RADS 3 with a sensitivity and specificity of 98.7% (95% CI, 0.964-0.996) and 83.2% (95% CI, 0.802-0.858) respectively. When sub-classifying multilocular cysts and smooth solid lesions in O-RADS 4 lesions as O-RADS 4a lesions and the rest cystic lesions with solid components as O-RADS 4b lesions, the malignancy rate were 17.02% and 42.57% respectively, which showed better risk stratification (P < 0.001). The inter-observer agreement between a less-experienced and an expert radiologist of O-RADS categorization was good (κ = 0.714). CONCLUSIONS: The ACR O-RADS US provides effective malignancy risk stratification for adnexal lesions with high reliability for radiologists with different experience. Sub-grouping of O-RADS 4 lesions into two groups facilitated better stratification of the intermediate risk.
OBJECTIVE: To assess the diagnostic performance and inter-observer agreement of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US). METHODS: From January 2016 to December 2018 a total of 1054 adnexal lesions in 1035 patients with pathologic results from two hospitals were retrospectively included. Each lesion was assigned to an O-RADS US category according to the criteria. Kappa (κ) statistics were applied to assess inter-observer agreement between a less experienced and an expert radiologist. RESULTS: Of the 1054 adnexal lesions, 750 were benign and 304 were malignant. The malignancy rates of O-RADS 5, O-RADS 4, O-RADS 3, and O-RADS 2 lesions were 89.57%, 34.46%, 1.10%, and 0.45% respectively. Area under the receiver operating characteristic curve was 0.960 (95% CI, 0.947-0.971). The optimal cutoff value for predicting malignancy was >O-RADS 3 with a sensitivity and specificity of 98.7% (95% CI, 0.964-0.996) and 83.2% (95% CI, 0.802-0.858) respectively. When sub-classifying multilocular cysts and smooth solid lesions in O-RADS 4 lesions as O-RADS 4a lesions and the rest cystic lesions with solid components as O-RADS 4b lesions, the malignancy rate were 17.02% and 42.57% respectively, which showed better risk stratification (P < 0.001). The inter-observer agreement between a less-experienced and an expert radiologist of O-RADS categorization was good (κ = 0.714). CONCLUSIONS: The ACR O-RADS US provides effective malignancy risk stratification for adnexal lesions with high reliability for radiologists with different experience. Sub-grouping of O-RADS 4 lesions into two groups facilitated better stratification of the intermediate risk.
Authors: Yang Guo; Catherine H Phillips; Krista Suarez-Weiss; Lauren A Roller; Mary C Frates; Carol B Benson; Atul B Shinagare Journal: Radiol Imaging Cancer Date: 2022-09
Authors: Julio Vara; Nabil Manzour; Enrique Chacón; Ana López-Picazo; Marta Linares; Maria Ángela Pascual; Stefano Guerriero; Juan Luis Alcázar Journal: Cancers (Basel) Date: 2022-06-27 Impact factor: 6.575
Authors: Priyanka Jha; Akshya Gupta; Timothy M Baran; Katherine E Maturen; Krupa Patel-Lippmann; Hanna M Zafar; Aya Kamaya; Neha Antil; Lisa Barroilhet; Elizabeth A Sadowski Journal: JAMA Netw Open Date: 2022-06-01
Authors: Neha Antil; Preethi R Raghu; Luyao Shen; Thodsawit Tiyarattanachai; Edwina M Chang; Craig W K Ferguson; Amanzo A Ho; Amelie M Lutz; Aladin J Mariano; L Nayeli Morimoto; Aya Kamaya Journal: Abdom Radiol (NY) Date: 2022-06-28
Authors: Wen Ting Xie; Yao Qin Wang; Zhi Sheng Xiang; Zhong Shi Du; Shi Xin Huang; Yi Jie Chen; Li Na Tang Journal: J Ovarian Res Date: 2022-01-23 Impact factor: 4.234