Li Yunhua, Li Hui, Du Lianfang, Shi Qiusheng, Li Gang, Jia Chao, Jin Lifang, Liang Hongmei, Li Fan
Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 201620, China.
Department of Nursing, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 201620, China.
Br J Radiol. 2025 Mar 1;98(1167):422-431. doi: 10.1093/bjr/tqae242.
To analyze the multi-parametric ultrasonographic (MpUS) features of atypical/malignant papillary lesions of the breast with clinical information, identify independent risk factors, and construct a nomogram to improve the diagnostic accuracy.
This retrospective study analyzed consecutively hospitalized patients diagnosed with pathologically confirmed papillary breast lesions from January 2017 to June 2023. Preoperative sonographic examinations, including gray-scale ultrasound (G-US), color Doppler flow imaging (CDFI), and contrast-enhanced ultrasound (CEUS), were conducted. Sonographic scans were retrospectively reviewed alongside clinicopathological data. Binary logistic regression identified independent risk factors for screening atypical/malignant papillary lesions. The receiver operating characteristic curve evaluated the predictive accuracy of these lesions, resulting in the development of a nomogram for assessing risk.
The study involved 176 female patients with breast papillary lesions, identifying key predictors for atypical or malignant outcomes: age 57 or order, US diameter ≥13.95 mm, resistive index ≥0.70, enlarged enhancement on CEUS, and contrast agent retention, with respective odds ratios of 6.279, 8.078, 9.246, 9.401, and 5.047. The integrated use of G-US, CDFI, and CEUS in the MpUS approach offered higher diagnostic accuracy (area under the curve [AUC]: 0.966) than G-US or CDFI alone (0.869/0.918). CEUS particularly enhanced prediction for non-mass-like lesions, with a positive predictive value of 83.3%. A nomogram incorporating MpUS and patient age achieved an AUC of 0.956 for predicting atypical or malignant papillary lesions.
MpUS imaging is highly effective for predicting malignant breast papillary lesions, especially considering patient age. The nomogram offers an intuitive framework for assessing malignant risk in these lesions.
Ultrasound excels in identifying papillary lesions, and integrating diverse data and multi-parametric imaging enhances malignant risk evaluation. This study establishes a predictive risk model using the nomogram method, demonstrating heightened diagnostic efficacy in breast papillary lesions.
结合临床信息分析乳腺非典型/恶性乳头状病变的多参数超声（MpUS）特征，识别独立危险因素，并构建列线图以提高诊断准确性。
这项回顾性研究分析了2017年1月至2023年6月期间连续住院的经病理证实为乳腺乳头状病变的患者。进行了术前超声检查，包括灰阶超声（G-US）、彩色多普勒血流成像（CDFI）和超声造影（CEUS）。超声扫描与临床病理数据一起进行回顾性分析。二元逻辑回归确定了筛查非典型/恶性乳头状病变的独立危险因素。受试者操作特征曲线评估了这些病变的预测准确性，从而制定了一个用于评估风险的列线图。
该研究纳入了176例患有乳腺乳头状病变的女性患者，确定了非典型或恶性结果的关键预测因素：年龄57岁及以上、超声直径≥13.95毫米、阻力指数≥0.70、CEUS上增强扩大以及造影剂滞留，相应的比值比分别为6.279、8.078、9.246、9.401和5.047。在MpUS方法中综合使用G-US、CDFI和CEUS比单独使用G-US或CDFI具有更高的诊断准确性（曲线下面积[AUC]：0.966）（0.869/0.918）。CEUS尤其增强了对非肿块样病变的预测，阳性预测值为83.3%。结合MpUS和患者年龄的列线图在预测非典型或恶性乳头状病变时的AUC为0.956。
MpUS成像在预测乳腺恶性乳头状病变方面非常有效，尤其是考虑患者年龄时。列线图为评估这些病变的恶性风险提供了一个直观的框架。
超声在识别乳头状病变方面表现出色，整合多种数据和多参数成像可增强恶性风险评估。本研究使用列线图方法建立了一个预测风险模型，证明在乳腺乳头状病变中具有更高的诊断效能。
