Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Acad Radiol. 2024 Aug;31(8):3106-3116. doi: 10.1016/j.acra.2024.01.038. Epub 2024 Feb 20.
To develop a nomogram by integrating B-mode ultrasound (US), strain ratio (SR), and radiomics signature (RS) effectively differentiating between benign and malignant lesions in the Breast Imaging Reporting and Data System (BI-RADS) 4.
We retrospectively recruited 709 consecutive patients who were assigned a BI-RADS 4 and underwent curative resection or biopsy between 2017 and 2022. US images were collected before surgery. A RS was developed through a multistep feature selection and construction process. Histology findings served as the gold standard. Univariate and multivariate regression analysis were employed to analyze the clinical and US characteristics and identify variables for developing a nomogram. The calibration and discrimination of the nomogram were conducted to evaluate its performance.
The study included a total of 709 patients, with 497 in the training set and 212 in the validation set. In the training set, the B-mode US had an AUC of 0.84 (95% confidence interval [CI], 0.80, 0.87). The SR demonstrated an AUC of 0.78 (95% CI, 0.74, 0.82), while the RS showed an AUC of 0.85 (95% CI, 0.81, 0.88). Notably, the nomogram exhibited superior performance compared to the conventional US, SR, and RS (AUC=0.93, both p < 0.05, as per the Delong test). The clinical usefulness of the nomogram was favorable.
The calibrated nomogram can be specifically designed to predict the malignancy of breast lesions in the BI-RADS 4 category.
开发一种列线图,通过有效整合 B 型超声(US)、应变比(SR)和放射组学特征(RS),对乳腺影像报告和数据系统(BI-RADS)4 类中的良恶性病变进行区分。
回顾性纳入 2017 年至 2022 年间进行根治性切除或活检的连续 709 例 BI-RADS 4 患者。所有患者术前均行 US 检查。采用多步特征选择和构建过程开发 RS。以组织学结果为金标准。采用单因素和多因素回归分析方法分析临床和 US 特征,并确定建立列线图的变量。对列线图进行校准和判别分析,以评估其性能。
本研究共纳入 709 例患者,其中训练集 497 例,验证集 212 例。在训练集中,B 型 US 的 AUC 为 0.84(95%置信区间:0.80,0.87)。SR 的 AUC 为 0.78(95%置信区间:0.74,0.82),RS 的 AUC 为 0.85(95%置信区间:0.81,0.88)。值得注意的是,与常规 US、SR 和 RS 相比,列线图具有更好的性能(AUC=0.93,均 p<0.05,根据 Delong 检验)。该列线图具有良好的临床应用价值。
校准后的列线图可专门用于预测 BI-RADS 4 类乳腺病变的恶性程度。