Zhu Yindi, Zhang Dian, Wang Xiao-Na, Chen Yue-Nan, Pan Mei-Fang, Guerrini Susanna, Ong Eugene, Gu Xin-Xian, Jiang Li
Department of Gynecology and Obstetrics, The First Affiliated Hospital of Soochow University, Suzhou, China.
Department of Ultrasound, Suzhou Xiangcheng People's Hospital, Suzhou, China.
Transl Cancer Res. 2025 Mar 30;14(3):2066-2077. doi: 10.21037/tcr-2025-485. Epub 2025 Mar 27.
Although conventional ultrasonography (CUS) and contrast-enhanced ultrasound (CEUS) play a critical role in cancer detection, diagnosis, and image-guided biopsies, there is no standardized diagnostic approach for the clinical evaluation of suspected Breast Imaging-Reporting and Data System (BI-RADS) category 4 breast lesions. This diagnostic test evaluates the complementary roles of CUS and CEUS in addressing limitations of conventional imaging, such as microvascular visualization. This study aimed to evaluate the diagnostic value of combining CUS with CEUS in subcategorizing suspicious breast lesions classified as BI-RADS for ultrasound (US-BI-RADS) category 4.
The data of 131 patients with BI-RADS category 4 breast lesions, examined between February 2017 and March 2023, were retrospectively analyzed. All lesions underwent pathological examination following surgery and served as the gold standard for diagnosis. Key features such as lesion margins, echogenicity, size, microcalcification, blood flow distribution via color Doppler flow imaging (CDFI), and CEUS characteristics were assessed. CEUS scores were calculated using a five-point scoring system. Stepwise logistic regression was applied to evaluate the odds ratios (ORs) of the lesion characteristics on US and CEUS. The combination of the US-BI-RADS and CEUS scores (termed the CEUS-BI-RADS) was compared to the US-BI-RADS alone, and a receiver operating characteristic (ROC) curve analysis was conducted to determine the diagnostic performance of these methods.
Of the 131 lesions, 62 (47.3%) were benign, and 69 (52.7%) were malignant. The multivariate logistic regression identified the primary indicators of malignancy as calcification [OR =1.58, 95% confidence interval (CI): 0.25-2.91, P=0.02], suspicious or abnormal axillary lymph nodes (OR =2.51, 95% CI: 0.59-4.44, P=0.01), obscure margins after enhancement (OR =2.67, 95% CI: 0.35 to 4.99, P=0.02), and increased lesion size (OR =4.89, 95% CI: 1.45-8.33, P=0.005). The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of the US-BI-RADS were 73.9%, 74.2%, 74.0%, 71.9%, and 76.1%, respectively, while those of the CEUS-BI-RADS were 92.8%, 79.0%, 86.3%, 90.7%, and 83.1%, respectively. The areas under the ROC curves for the US-BI-RADS and CEUS-BI-RADS were 0.741 and 0.859, respectively.
The CEUS-BI-RADS significantly enhances diagnostic efficacy for BI-RADS category 4 breast lesions, outperforming the US-BI-RADS and could reduce unnecessary biopsies.
尽管传统超声检查（CUS）和超声造影（CEUS）在癌症检测、诊断及图像引导活检中发挥着关键作用，但对于疑似乳腺影像报告和数据系统（BI-RADS）4类乳腺病变的临床评估，尚无标准化的诊断方法。本诊断试验评估了CUS和CEUS在解决传统成像局限性（如微血管可视化）方面的互补作用。本研究旨在评估CUS联合CEUS对归类为超声（US-BI-RADS）4类的可疑乳腺病变进行亚分类的诊断价值。
回顾性分析2017年2月至2023年3月期间检查的131例BI-RADS 4类乳腺病变患者的数据。所有病变均在手术后接受病理检查，并作为诊断的金标准。评估病变边界、回声性、大小、微钙化、通过彩色多普勒血流成像（CDFI）的血流分布以及CEUS特征等关键特征。使用五点评分系统计算CEUS评分。应用逐步逻辑回归评估超声和CEUS上病变特征的优势比（OR）。将US-BI-RADS和CEUS评分的组合（称为CEUS-BI-RADS）与单独的US-BI-RADS进行比较，并进行受试者工作特征（ROC）曲线分析以确定这些方法的诊断性能。
在131个病变中，62个（47.3%）为良性，69个（52.7%）为恶性。多因素逻辑回归确定恶性的主要指标为钙化[OR = 1.58，95%置信区间（CI）：0.25 - 2.91，P = 0.02]、可疑或异常腋窝淋巴结（OR = 2.51，95% CI：0.59 - 4.44，P = 0.01）、增强后边界不清（OR = 2.67，95% CI：0.35至4.99，P = 0.02）以及病变大小增加（OR = 4.89，95% CI：1.45 - 8.33，P = 0.005）。US-BI-RADS的敏感性、特异性、准确性、阳性预测值（PPV）和阴性预测值（NPV）分别为73.9%、74.2%、74.0%、71.9%和76.1%，而CEUS-BI-RADS的敏感性、特异性、准确性、PPV和NPV分别为92.8%、79.0%、86.3%、90.7%和83.1%。US-BI-RADS和CEUS-BI-RADS的ROC曲线下面积分别为0.741和0.859。
CEUS-BI-RADS显著提高了对BI-RADS 4类乳腺病变的诊断效能，优于US-BI-RADS，并且可以减少不必要的活检。
