Chen Yunhao, Lu Juerong, Li Jie, Liao Jingtang, Huang Xinyue, Zhang Bo
Department of Ultrasonic Imaging, Xiangya Hospital, Central South University, Changsha, China.
Front Oncol. 2022 Nov 24;12:1053280. doi: 10.3389/fonc.2022.1053280. eCollection 2022.
To explore the diagnostic efficacy of ultrasound (US), two-dimensional and three-dimensional shear-wave elastography (2D-SWE and 3D-SWE), and contrast-enhanced ultrasound (CEUS) in breast neoplasms in category 4 based on the Breast Imaging Reporting and Data System (BI-RADS) from the American College of Radiology (ACR) and to develop a risk-prediction nomogram based on the optimal combination to provide a reference for the clinical management of BI-RADS 4 breast neoplasms.
From September 2021 to April 2022, a total of 104 breast neoplasms categorized as BI-RADS 4 by US were included in this prospective study. There were 78 breast neoplasms randomly assigned to the training cohort; the area under the receiver-operating characteristic curve (AUC), 95% confidence interval (95% CI), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 2D-SWE, 3D-SWE, CEUS, and their combination were analyzed and compared. The optimal combination was selected to develop a risk-prediction nomogram. The performance of the nomogram was assessed by a validation cohort of 26 neoplasms.
Of the 78 neoplasms in the training cohort, 16 were malignant and 62 were benign. Among the 26 neoplasms in the validation cohort, 6 were malignant and 20 were benign. The AUC values of 2D-SWE, 3D-SWE, and CEUS were not significantly different. After a comparison of the different combinations, 2D-SWE+CEUS showed the optimal performance. Least absolute shrinkage and selection operator (LASSO) regression was used to filter the variables in this combination, and the variables included Emax, Eratio, enhancement mode, perfusion defect, and area ratio. Then, a risk-prediction nomogram with BI-RADS was built. The performance of the nomogram was better than that of the radiologists in the training cohort (AUC: 0.974 vs. 0.863). In the validation cohort, there was no significant difference in diagnostic accuracy between the nomogram and the experienced radiologists (AUC: 0.946 vs. 0.842).
US, 2D-SWE, 3D-SWE, CEUS, and their combination could improve the diagnostic efficiency of BI-RADS 4 breast neoplasms. The diagnostic efficacy of US+3D-SWE was not better than US+2D-SWE. US+2D-SWE+CEUS showed the optimal diagnostic performance. The nomogram based on US+2D-SWE+CEUS performs well.
基于美国放射学会（ACR）的乳腺影像报告和数据系统（BI-RADS），探讨超声（US）、二维和三维剪切波弹性成像（2D-SWE和3D-SWE）以及超声造影（CEUS）对4类乳腺肿瘤的诊断效能，并基于最佳组合建立风险预测列线图，为BI-RADS 4类乳腺肿瘤的临床管理提供参考。
2021年9月至2022年4月，本前瞻性研究共纳入104例经超声诊断为BI-RADS 4类的乳腺肿瘤。78例乳腺肿瘤被随机分配到训练队列；分析并比较2D-SWE、3D-SWE、CEUS及其联合检查的受试者工作特征曲线下面积（AUC）、95%置信区间（95%CI）、敏感度、特异度、阳性预测值（PPV）和阴性预测值（NPV）。选择最佳组合建立风险预测列线图。通过26例肿瘤的验证队列评估列线图的性能。
训练队列的78例肿瘤中，16例为恶性，62例为良性。验证队列的26例肿瘤中，6例为恶性，20例为良性。2D-SWE、3D-SWE和CEUS的AUC值无显著差异。比较不同组合后，2D-SWE+CEUS表现出最佳性能。采用最小绝对收缩和选择算子（LASSO）回归对该组合中的变量进行筛选，变量包括Emax、Eratio、增强模式、灌注缺损和面积比。然后，建立了包含BI-RADS的风险预测列线图。列线图在训练队列中的性能优于放射科医生（AUC：0.974对0.863）。在验证队列中，列线图与经验丰富的放射科医生的诊断准确性无显著差异（AUC：0.946对0.842）。
US、2D-SWE、3D-SWE、CEUS及其联合检查可提高BI-RADS 4类乳腺肿瘤的诊断效率。US+3D-SWE的诊断效能不优于US+2D-SWE。US+2D-SWE+CEUS表现出最佳诊断性能。基于US+2D-SWE+CEUS的列线图性能良好。
