[1] 中国抗癌协会乳腺专业委员会.中国抗癌协会乳腺癌诊治指南与规范(2019年版)[J]. 中国癌症杂志, 2019,29(8):609-680. [2] Mercado C L.BI-RADS update[J].Radiologic Clinics of North America, 2014,52(3):481-487. [3] 朱庆莉, 姜玉新. 乳腺影像报告与数据系统指南(第5版)超声内容更新介绍[J].中华医学超声杂志(电子版), 2016,13(1):5-7. [4] 王立平, 蒋天安, 杨琛, 等. 乳腺良性结节超声BI-RADS分级的可靠性及其影响因素分析[J].中华超声影像学杂志,2011,20(4):314-317. [5] 朱巧英, 周锋盛, 周婉, 等. 灰阶超声造影对乳腺BI-RADS-US 4类病灶的应用价值[J].中华超声影像学杂志, 2015,24(10):890-893. [6] Horvath E, Majlis S, Rossi R, et al. An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management[J].Journal of Clinical Endocrinology and Metabolism, 2009,94(5):1748-1751. [7] Tessler F N, Middleton W D, Grant E G, et al. ACR thyroid imaging, reporting and data system(TI-RADS):white paper of the ACR TI-RADS committee[J].Journal of the American College of Cardiology, 2017,14(5):587-595. [8] 刘红, 胡正明, 罗海愉, 等.ACR TI-RADS分类在诊断甲状腺结节中的应用价值探究[J]. 中国超声医学杂志.2018,34(8):673-675. [9] 傅强, 熊颖, 闫妍, 等.三种甲状腺影像报告和数据系统临床应用评估[J].中国医学装备, 2020,17(6):33-37. [10] Middleton W D, Teefey S A, Reading C C, et al. Comparison of performance characteristics of American College of Radiology TI-RADS, Korean Society of Thyroid Radiology TIRADS, and American Thyroid Association guidelines[J]. American Journal of Roentgenology, 2018,210(5):1148-1154. [11] 杨艳. 超声TI-RADS分类对甲状腺结节的诊断价值[J].影像研究与医学应用, 2018,2(16):117-118. [12] 王盼盼.彩超诊断甲状腺结节的特征分析[J].医学食疗与健康, 2020,18(18):171-172. [13] 梁晓雯, 陈智毅.甲状腺结节超声分类诊断研究进展[J].中华超声影像学杂志, 2018,27(9):823-826, 828. [14] 刘锐洪, 何瑞琦, 陈英银, 等. ACR TI-RADS与ATA指南分级评估甲状腺结节的对比研究[J].中国中西医结合影像学杂志, 2019,7(4):380-383. [15] 赵静, 赵利辉, 忻晓洁, 等. 甲状腺滤泡癌与甲状腺乳头状癌的TI-RADS分类及超声特征分析[J].中华普通外科杂志, 2016,31(9):754-757. [16] Zhu L C, Ye L Y, Luo W H, et al. A model to discriminate malignant from benign thyroid nodules using artificial neural network[J].PLoS One, 2013,8:e82211. [17] Wildman-Tobriner B, Buda M, Hoang J K, et al. Using artificial intelligence to revise ACR TI-RADS risk stratification of thyroid nodules:diagnostic accuracy and utility[J].Radiology, 2019,292(1):112-119. [18] 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].Journal of Ultrasound in Medicine, 2009,28(3):285-291. [19] Andreotti R, Timmerman D, Strachowski L, 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. [20] 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].European Radiology, 2021,31(2):674-684. [21] 杨丹, 李锐. 美国放射学院超声造影LI-RADS指南(2016版)[J]. 临床超声医学杂志, 2017,19(10):712-718. [22] Chernyak V, Fowler K, Kamaya A, et al. Liver imaging reporting and data system (LI-RADS) Version 2018:imaging of hepatocellular carcinoma in at-risk patients[J].Radiology, 2018,289(3):816-830. [23] Fetzer D T, Rodgers S K, Harris A C, et al. Screening and surveillance of hepatocellular carcinoma:an introduction to ultrasound liver imaging reporting and data system[J].Radiologic Clinics of North America, 2017,55(6):1197-1209. [24] Bruix J, Ayuso C. Diagnosis of hepatic nodules in patients at risk for hepatocellular carcinoma:LI-RADS probability versus certainty[J]. Gastroenterology, 2019,156(4):860-862. [25] Henderson M, Silver M, Tran Q, et al. A noninvasive blood-based combinatorial proteomic biomarker assay to detect breast cancer in women over age 50 with BI-RADS 3, 4, or 5 assessment[J]. Clinical Cancer Research, 2019,25(1):142-149. [26] 马姣姣, 张波. 甲状腺结节超声风险分层的利与弊[J]. 中国癌症杂志, 2020,30(7):546-550. [27] Yau T, Tang V, Yao T, et al. Development of Hong Kong liver cancer staging system with treatment stratification for patients with hepatocellular carcinoma[J].Gastroenterology, 2014,146(7):1691-1700. |