From the Departments of Surgery (S.A.L., H.G.M.), Radiology (Y.L., W.K.M., S.H.L.), and Pathology (H.S.R.), Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea (M.J.J.).
Radiology. 2022 Nov;305(2):307-316. doi: 10.1148/radiol.213174. Epub 2022 Jul 5.
Background Accurate preoperative prediction of upstaging in women with biopsy-proven ductal carcinoma in situ (DCIS) is important for surgical planning, but published models using predictive MRI features remain lacking. Purpose To develop and validate a predictive model based on preoperative breast MRI to predict upstaging in women with biopsy-proven DCIS and to select high-risk women who may benefit from sentinel lymph node biopsy at initial surgery. Materials and methods Consecutive women with biopsy-proven DCIS who underwent preoperative 3.0-T breast MRI including dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) and who underwent surgery between June 2019 and March 2020 were retrospectively identified (development set) from an academic medical center. The apparent diffusion coefficients of lesions from DWI, lesion size and morphologic features on DCE MRI scans, mammographic findings, age, symptoms, biopsy method, and DCIS grade at biopsy were collected. The presence of invasive cancer and axillary metastases was determined with surgical pathology. A predictive model for upstaging was developed by using multivariable logistic regression and validated in a subsequent prospective internal validation set recruited between July 2020 and April 2021. Results Fifty-seven (41%) of 140 women (mean age, 53 years ± 11 [SD]) in the development set and 43 (41%) of 105 women (mean age, 53 years ± 10) in the validation set were upstaged after surgery. The predictive model combining DWI and clinical-pathologic factors showed the areas under the receiver operating characteristic curve at 0.87 (95% CI: 0.80, 0.92) in the development set and 0.76 (95% CI: 0.67, 0.84) in the validation set. The predicted probability of invasive cancer showed good interobserver agreement (intraclass correlation coefficient, 0.79); the positive predictive value was 85% (28 of 33), and the negative predictive value was 92% (22 of 24). Conclusion A predictive model based on diffusion-weighted breast MRI identified women at high risk of upstaging. © RSNA, 2022 See also the editorial by Baltzer in this issue.
背景 准确预测经活检证实的导管原位癌(DCIS)女性的升级分期对于手术计划非常重要,但使用预测性 MRI 特征的已发表模型仍然缺乏。目的 基于术前乳腺 MRI 开发和验证预测模型,以预测经活检证实的 DCIS 女性的升级分期,并选择可能从初始手术中前哨淋巴结活检中获益的高危女性。材料与方法 回顾性分析 2019 年 6 月至 2020 年 3 月期间在学术医疗中心接受术前 3.0-T 乳腺 MRI(包括动态对比增强 [DCE] MRI 和弥散加权成像 [DWI])并接受手术的经活检证实的 DCIS 连续女性(开发集)。收集 DWI 中病变的表观扩散系数、DCE MRI 扫描上的病变大小和形态特征、乳房 X 线摄影表现、年龄、症状、活检方法和活检时的 DCIS 分级。通过手术病理确定浸润性癌和腋窝转移的存在。使用多变量逻辑回归建立升级分期预测模型,并在 2020 年 7 月至 2021 年 4 月期间招募的后续前瞻性内部验证集中进行验证。结果 在开发集的 140 名女性(平均年龄,53 岁±11[标准差])中,有 57 名(41%)女性在手术后升级,在验证集的 105 名女性(平均年龄,53 岁±10)中,有 43 名(41%)女性在手术后升级。结合 DWI 和临床病理因素的预测模型在开发集的受试者工作特征曲线下面积为 0.87(95%CI:0.80,0.92),在验证集的面积为 0.76(95%CI:0.67,0.84)。预测浸润性癌的概率具有良好的观察者间一致性(组内相关系数,0.79);阳性预测值为 85%(28/33),阴性预测值为 92%(22/24)。结论 基于扩散加权乳腺 MRI 的预测模型确定了升级风险较高的女性。©RSNA,2022 也可参见本期巴尔策的社论。