Sun Peng-Fei, Zhai Li-Xue, Dong Yun-Yun, Hu Xiang-Dong, Li Min, Qian Lin-Xue, Zhao Jun-Feng
Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Clinical Epidemiology and EBM Unit, Beijing Friendship Hospital, Capital Medical University, Beijing Clinical Research Institute, Beijing, China.
J Ultrasound Med. 2025 Aug;44(8):1437-1446. doi: 10.1002/jum.16699. Epub 2025 Apr 9.
To investigate the diagnostic value of quantitative analysis using ultra-resolution microscopy (URM) in differentiating benign from malignant breast lesions.
This prospective study enrolled 60 patients with 60 breast lesions who underwent contrast-enhanced ultrasound (CEUS) using SonoVue (Bracco Imaging, Italy) between June 2024 and August 2024. Quantitative parameters of microvascular density and velocity maps were generated for the lesion interior, rim region, and combined interior and rim area using URM software on CEUS images. The parameters were analyzed for differences between benign and malignant breast lesions, and their diagnostic efficacy was evaluated.
Multivariate analysis indicated that breast malignancy was associated with microvascular ratio and complexity level. The area under the curve (AUC) for the combined diagnostic method that included microvascular parameters at the lesion margin (Rim group) and BI-RADS classification + Rim was higher than other diagnostic approaches (AUC = 0.92), although there was no significant difference when compared with the combined approach of evaluating parameters within the lesion and at the margin alongside BI-RADS (Mass + Rim + BI-RADS group, P = .293). The BI-RADS group showed high sensitivity (100%) and negative predictive value (100%); the Mass group (parameters within the lesion) demonstrated higher sensitivity (87.0%), and the Rim group (parameters at the lesion margin) exhibited the highest specificity (91.9%).
URM shows potential in distinguishing between benign and malignant breast lesions, offering a precise assessment of lesion hemodynamics and providing valuable information for clinical diagnosis and treatment.
探讨超分辨率显微镜（URM）定量分析在鉴别乳腺良恶性病变中的诊断价值。
本前瞻性研究纳入了60例患有60个乳腺病变的患者，这些患者于2024年6月至2024年8月期间使用声诺维（意大利Bracco Imaging公司）接受了超声造影（CEUS）检查。使用URM软件在CEUS图像上生成病变内部、边缘区域以及内部和边缘联合区域的微血管密度和速度图的定量参数。分析这些参数在乳腺良恶性病变之间的差异，并评估其诊断效能。
多变量分析表明，乳腺恶性肿瘤与微血管比例和复杂程度相关。包括病变边缘微血管参数（边缘组）和BI-RADS分类+边缘的联合诊断方法的曲线下面积（AUC）高于其他诊断方法（AUC = 0.92），尽管与评估病变内部和边缘参数并结合BI-RADS的联合方法（肿块+边缘+BI-RADS组）相比无显著差异（P = 0.293）。BI-RADS组显示出高敏感性（100%）和阴性预测值（100%）；肿块组（病变内部参数）表现出较高的敏感性（87.0%），边缘组（病变边缘参数）表现出最高的特异性（91.9%）。
URM在鉴别乳腺良恶性病变方面显示出潜力，能够对病变血流动力学进行精确评估，并为临床诊断和治疗提供有价值的信息。
