Ultrasound Department of the First Affiliated Hospital of Dalian Medical University, No.222 Zhongshan Road, Xigang District, Dalian City, Liaoning Province, China.
Sci Rep. 2023 Jul 31;13(1):12340. doi: 10.1038/s41598-023-39686-2.
This study aimed to develop a nomogram through the collection of quantitative ultrasound parameters to predict breast cancer. From March 2021 to September 2022, a total of 313 breast tumors were included with pathological results. Through collecting quantitative ultrasound parameters of breast tumors and multivariate regression analysis, a nomogram was developed. The diagnostic performances, calibration and clinical usefulness of the nomogram for predicting breast cancer were assessed. A total of 182 benign and 131 malignant breast tumors were included in this study. The nomogram indicated excellent predictive properties with an AUC of 0.934, sensitivity of 0.881, specificity of 0.848, PPV of 0.795 and NPV of 0.841. The calibration curve showed the predicted values are basically consistent with the actual observed values. The optimum cut-off for the nomogram was 0.310 for predicting cancer. The decision curve analysis results corroborated good clinical usefulness. The model including BI-RADS score, SWE and VI is potentially useful for predicting breast cancer.
本研究旨在通过收集定量超声参数来开发一种列线图以预测乳腺癌。2021 年 3 月至 2022 年 9 月，共纳入 313 例经病理证实的乳腺肿瘤患者。通过收集乳腺肿瘤的定量超声参数并进行多变量回归分析，构建了一个列线图。评估了列线图预测乳腺癌的诊断性能、校准和临床实用性。本研究共纳入 182 例良性和 131 例恶性乳腺肿瘤。列线图预测性能优异，AUC 为 0.934，灵敏度为 0.881，特异性为 0.848，PPV 为 0.795，NPV 为 0.841。校准曲线表明预测值与实际观察值基本一致。列线图预测癌症的最佳截断值为 0.310。决策曲线分析结果证实了良好的临床实用性。包含 BI-RADS 评分、SWE 和 VI 的模型可能对预测乳腺癌有帮助。
