From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis.
Radiology. 2022 Jun;303(3):603-610. doi: 10.1148/radiol.212338. Epub 2022 Mar 22.
Background Several US risk stratification schemas for assessing adnexal lesions exist. These multiple-subcategory systems may be more multifaceted than necessary for isolated adnexal lesions in average-risk women. Purpose To explore whether a US-based classification scheme of classic versus nonclassic appearance can be used to help appropriately triage women at average risk of ovarian cancer without compromising diagnostic performance. Materials and Methods This retrospective multicenter study included isolated ovarian lesions identified at pelvic US performed between January 2011 and June 2014, reviewed between September 2019 and September 2020. Lesions were considered isolated in the absence of ascites or peritoneal implants. Lesions were classified as classic or nonclassic based on sonographic appearance. Classic lesions included simple cysts, hemorrhagic cysts, endometriomas, and dermoids. Otherwise, lesions were considered nonclassic. Outcomes based on histopathologic results or clinical or imaging follow-up were recorded. Diagnostic performance and frequency of malignancy were calculated. Frequency of malignancy between age groups was compared using the χ test, and Poisson regression was used to explore relationships between imaging features and malignancy. Results A total of 970 isolated lesions in 878 women (mean age, 42 years ± 14 [SD]) were included. The malignancy rate for classic lesions was less than 1%. Of 970 lesions, 53 (6%) were malignant. The malignancy rate for nonclassic lesions was 32% (33 of 103) when blood flow was present and 8% (16 of 194) without blood flow ( < .001). For women older than 60 years, the malignancy rate was 50% (10 of 20 lesions) when blood flow was present and 13% (five of 38) without blood flow ( = .004). The sensitivity, specificity, positive predictive value, and negative predictive value of the classic-versus-nonclassic schema was 93% (49 of 53 lesions), 73% (669 of 917 lesions), 17% (49 of 297 lesions), and 99% (669 of 673 lesions), respectively, for detection of malignancy. Conclusion Using a US classification schema of classic- or nonclassic-appearing adnexal lesions resulted in high sensitivity and specificity in the diagnosis of malignancy in ovarian cancer. The highest risk of cancer was in isolated nonclassic lesions with blood flow in women older than 60 years. © RSNA, 2022 See also the editorial by Baumgarten in this issue.
背景 美国有几种用于评估附件病变的风险分层方案。这些多分类系统对于平均风险女性的孤立附件病变来说可能过于复杂。 目的 探讨基于 US 的经典与非经典外观分类方案是否可用于帮助适当分诊无卵巢癌风险的平均风险女性，同时不影响诊断性能。 材料与方法 本回顾性多中心研究纳入 2011 年 1 月至 2014 年 6 月间行盆腔 US 检查时发现的孤立性卵巢病变，于 2019 年 9 月至 2020 年 9 月进行回顾性分析。病变在无腹水或腹膜种植的情况下被认为是孤立性的。病变根据超声表现分为经典或非经典外观。经典病变包括单纯囊肿、出血性囊肿、子宫内膜异位症和皮样囊肿。否则，病变被认为是非经典外观。记录基于组织病理学结果或临床或影像学随访的结局。计算诊断性能和恶性肿瘤的发生率。使用 χ 检验比较不同年龄组间的恶性肿瘤发生率，使用泊松回归分析探讨影像学特征与恶性肿瘤的关系。 结果 共纳入 878 例女性（平均年龄 42 岁±14[SD]）的 970 个孤立性病变。经典病变的恶性肿瘤发生率小于 1%。970 个病变中，53 个（6%）为恶性肿瘤。当存在血流时，非经典病变的恶性肿瘤发生率为 32%（33/103），当不存在血流时为 8%（16/194）（<.001）。对于年龄大于 60 岁的女性，当存在血流时，病变的恶性肿瘤发生率为 50%（10/20 个病变），当不存在血流时为 13%（5/38 个病变）（=.004）。经典-非经典分类方案的灵敏度、特异度、阳性预测值和阴性预测值分别为 93%（53/57 个病变）、73%（669/917 个病变）、17%（49/297 个病变）和 99%（669/673 个病变），用于检测恶性肿瘤。 结论 对于卵巢癌，使用经典或非经典外观的附件病变 US 分类方案进行诊断可获得较高的灵敏度和特异度。血流状态下孤立性非经典病变的风险最高，年龄大于 60 岁的女性癌症风险最高。 版权声明© 2022 RSNA，保留所有权利。 本期另见 Baumgarten 编辑述评。
