Application of ovarian-adnexal ultrasound reporting and data system in the diagnosis of ovarian benign and malignant tumors

doi:10.3969/j.issn.1006-7795.2023.06.007

Abstract

Abstract: Objective To evaluate the diagnostic efficiency and clinical application of ovarian-adnexal reporting and data system (O-RADS) risk scoring system in the ovarian tumor diagnosis through comparison of the diagnostic performance of the sonographers with varying levels of expertise.Methods The ultrasound images of 200 patients who were treated at Beijing Tiantan Hospital, Capital Medical University from January 2019 to June 2022 with ovarian tumors were retrospectively analyzed. The ovarian tumors were diagnosed by a senior doctor and a junior doctor separately, and then another two trained junior doctors -classified the diagnosed ovarian tumors referring to O-RADS. These two doctors came to a unanimous conclusion after discussion when they disagreed to each other. The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and kappa value by senior doctor, junior doctor and O-RADS system were calculated and compared by using the pathological diagnosis as the gold standard. Results A total of 222 ovarian tumors in 200 patients were enrolled, among which 147 were benign and 75 were malignant by pathological diagnosis. The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and kappa value for the senior doctor were 89.3%, 93.1%, 87.0%, 94.4%, 91.8%, 0.82, respectively, while that for the junior doctor were 73.3%, 80.9%, 66.2%, 85.6%, 78.4%, 0.53, respectively. Taken pathological diagnosis as the gold standard, the receiver operating characteristic was drawn，and the area under the curve was 0.892. Taken O-RADS > 3 as the best cut-off value, the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and kappa value of the O-RADS were 93.3%, 81.6%, 72.1%, 96.0%, 85.5%, 0.70, respectively. Conclusion O-RADS has good diagnostic efficacy in the diagnosis of ovarian tumors, and can be applied as a useful tool for junior doctor. When the application of O-RADS system meets with difficult classification, it is still necessary to refer to a senior doctor for consultation.

Key words: ovarian-adnexal reporting and data system, ovarian tumors, ultrasonography

CLC Number:

R445

Song Haiman, He Wen, Kang Ruijun, Wang Lishu, Yu Tengfei, Zhang Wei. Application of ovarian-adnexal ultrasound reporting and data system in the diagnosis of ovarian benign and malignant tumors[J]. Journal of Capital Medical University, doi: 10.3969/j.issn.1006-7795.2023.06.007.

References

［1］Siegel R L, Miller K D, Fuchs H E, et al. Cancer statistics, 2022［J］. CA Cancer J Clin, 2022, 72(1): 7－33.
［2］Torre L A, Trabert B, DeSantis C E, et al. Ovarian cancer statistics, 2018［J］. CA Cancer J Clin, 2018, 68(4): 284－296.
［3］Wang Y C, Tian J Y, Han Y Y, et al. Evaluation of the potential of ultrasound-mediated drug delivery for the treatment of ovarian cancer through preclinical studies［J］. Front Oncol, 2022, 12: 978603.
［4］Suh-Burgmann E, Brasic N, Jha P, et al. Ultrasound characteristics of early-stage high-grade serous ovarian cancer［J］. Am J Obstet Gynecol, 2021, 225(4): 409.e1－409.e8.
［5］Andreotti R F, Timmerman D, Strachowski L M, et al. O-RADS US risk stratification and management system: a consensus guideline from the ACR ovarian-adnexal reporting and data system committee［J］. Radiology, 2020, 294(1): 168－185.
［6］Timmerman D, Valentin L, Bourne T H, et al. Terms, definitions and measurements to describe the sonographic features of adnexal tumors: a consensus opinion from the international ovarian tumor analysis (IOTA) group［J］. Ultrasound Obstet Gynecol, 2000, 16(5): 500－505.
［7］Amor F, Vaccaro H, Alcázar J L, et al. Gynecologic imaging reporting and data system: a new proposal for classifying adnexal masses on the basis of sonographic findings［J］. J Ultrasound Med, 2009, 28(3): 285－291.
［8］Van Calster B, Van Hoorde K, Valentin L, et al. Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study［J］. BMJ, 2014, 349: g5920.
［9］卢颖澜, 吴青青, 和平, 等. 卵巢-附件报告和数据系统 (O-RADS) 定性诊断卵巢肿瘤效能［J］. 中国医学影像技术, 2022, 38(9): 1367－1370.
［10］Basha M A A, Metwally M I, Gamil S A, et al. Comparison of O-RADS, GI-RADS, and IOTA simple rules regarding malignancy rate, validity, and reliability for diagnosis of adnexal masses［J］. Eur Radiol, 2021, 31(2): 674－684.
［11］Cao L, Wei M J, Liu Y, et al. Validation of American college of radiology ovarian-adnexal reporting and data system ultrasound (O-RADS US): analysis on 1054 adnexal masses［J］. Gynecol Oncol, 2021, 162(1): 107－112.
［12］Hiett A K, Sonek J D, Guy M, et al. Performance of IOTA simple rules, simple rules risk assessment, ADNEX model and O-RADS in differentiating between benign and malignant adnexal lesions in North American women［J］. Ultrasound Obstet Gynecol, 2022, 59(5): 668－676.
［13］Xie W T, Wang Y Q, Xiang Z S, et al. Efficacy of IOTA simple rules, O-RADS, and CA125 to distinguish benign and malignant adnexal masses［J］. J Ovarian Res, 2022, 15(1): 15.
［14］Hack K, Gandhi N, Bouchard-Fortier G, et al. External validation of O-RADS US risk stratification and management system［J］. Radiology, 2022, 304(1): 114－120.
［15］Jha P, Gupta A, Baran T M, et al. Diagnostic performance of the ovarian-adnexal reporting and data system (O-RADS) ultrasound risk score in women in the United States［J］. JAMA Netw Open, 2022, 5(6): e2216370.
［16］高雪娇, 张璇, 付莹, 等. 卵巢-附件影像报告和数据系统模型及联合CA125对卵巢肿瘤的诊断价值［J］. 中国医学影像学杂志, 2022, 30(11): 1149－1153.
［17］Katlariwala P, Wilson M P, Pi Y L, et al. Reliability of ultrasound ovarian-adnexal reporting and data system amongst less experienced readers before and after training［J］. World J Radiol, 2022, 14(9): 319－328.
［18］Guo Y Y, Zhao B H, Zhou S, et al. A comparison of the diagnostic performance of the O-RADS, RMI4, IOTA LR2, and IOTA SR systems by senior and junior doctors［J］. Ultrasonography, 2022, 41(3): 511－518.

[1]	Song Le, Li Hui, Zhang Weifang. A comparative analysis of ¹⁸F-FDG PET/CT and MRI in bone marrow necrosis [J]. Journal of Capital Medical University, 2024, 45(1): 36-41.
[2]	Li Lina, Yang Minfu. Current status and prospect of cardiovascular fibroblast imaging [J]. Journal of Capital Medical University, 2024, 45(1): 46-51.
[3]	Yu Tengfei, Yin Lu, Tian Daoran, Song Haiman, Yin Ziyi, Zhang Wei, He Wen . The value of combined superb microvascular imaging and color Doppler flow imaging in breast BI-RADS class 4 micronodules [J]. Journal of Capital Medical University, 2023, 44(6): 921-927.
[4]	Wei Xingyue, Wang Lianshuang, Wang Yuanyuan, Gao Mengze, He Qiong, Zhang Yao, Luo Jianwen. Intelligent grading diagnosis of liver fibrosis, inflammation, and steatosis in chronic liver disease based on multimodal ultrasound imaging data [J]. Journal of Capital Medical University, 2023, 44(6): 928-935.
[5]	Zhuang Jiamian, Zeng Yuran, Chen Shaoqi. Evaluation of the mechanical properties of supraspinatus tendons in hemodialysis patients with high frame rate sound touch elastography [J]. Journal of Capital Medical University, 2023, 44(6): 936-940.
[6]	Jia Xiaoxia, Chang Ying, Hou Wenying, Fu Ying, Zhang Huidan, Yang Jingchun. nalysis of factors related to the absorption rate of papillary thyroid microcarcinoma after ultrasound-guided radiofrequency ablation [J]. Journal of Capital Medical University, 2023, 44(6): 941-947.
[7]	Song Qian, Zhou Qian, Sun Hong, Li Shuo, Mei Xue, Guo Ruijun, Ge Huiyu. Clinical value of Lindegaard in the early diagnosis of sepsis-associated encephalopathy [J]. Journal of Capital Medical University, 2023, 44(6): 959-965.
[8]	Sun Zhe, Ma Jiaojiao, Zhang Bo. Application status and prospects of pleural ultrasound in respiratory diseases [J]. Journal of Capital Medical University, 2023, 44(6): 966-972.
[9]	Song Haiman, He Wen, Kang Ruijun, Wang Lishu, Yu Tengfei, Zhang Wei. Application of ovarian-adnexal ultrasound reporting and data system in the diagnosis of ovarian benign and malignant tumors [J]. Journal of Capital Medical University, 0, (): 948-952.
[10]	Zhang Shu, Wang Kai, Yang Zihao, Qiao Zhen, Li Xiaotong, Yuan Leilei, Ai Lin. Application of ¹¹C-MET PET/CT in screening isocitric dehydrogenase and 1p/19q status in supratentorial lower-grade gliomas [J]. Journal of Capital Medical University, 2022, 43(6): 826-833.
[11]	Geng Yiqiang, Liu Jiajin, Wu Shina, Sun Shuwei, Zhao Dong, Song Jingbin, Sun Yabing, Wang Ruimin. Evaluation of the effect of NEMA NU 2-2018 Standards in performance test of PET/CT system [J]. Journal of Capital Medical University, 2022, 43(6): 840-844.
[12]	Xu Yang, Wang Kai, Chen Qiang, Ai Lin. Advances about molecular imaging of nuclear medicine in diagnosis and treatment of glioma [J]. Journal of Capital Medical University, 2022, 43(6): 880-885.
[13]	Huang Lixiang, Wang Shaozhou, Cao Chen, Xia Shuang. To explore the influence of lenticulostriate artery on quantitative perfusion of basal ganglia brain tissue and predict the prognosis of patients [J]. Journal of Capital Medical University, 2022, 43(1): 53-60.
[14]	Wang Li, Shi Zhao, Kong Xiang, Yang Liu, Liu Ya, Luo Song, Zhang Longjiang. Association between A1 segment dysplasia, bifurcation angles of anterior cerebral artery and the formation of anterior communicating aneurysms [J]. Journal of Capital Medical University, 2022, 43(1): 61-66.
[15]	Zhang Huibo, Yang Xiaoxu, Liu Xinyuan, Gu Hua, Wang Shuangkun, Yang Qi. Diagnostic value of magnetic resonance imaging for cerebral venous sinus thrombosis [J]. Journal of Capital Medical University, 2022, 43(1): 67-73.