Multi-parametric MRI radiomics predicts different HER2 expression in breast cancer

多参数磁共振成像组学预测乳腺癌中不同的HER2表达

阅读:2

Abstract

PURPOSE: To develop and validate radiomic models using multi-parametric dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent movement (IVIM)-based features for the preoperative differentiation of HER2 expressions levels in breast cancer. MATERIALS AND METHODS: This retrospectively study analyzed 227 female breast cancer patients who underwent breast 3.0T MRI examination at our institution from December 2019 to December 2023. The least absolute shrinkage and selection operator (LASSO) ten-fold cross-validation method was used to develop the radiomic features to identify HER2 positive and HER2 negative cancer(task 1), and further identify HER2 low and HER2 zero cancer(task 2). Then the radiomic features were selected and combined with clinical characteristics to construct predicting models using the logistic regression analysis. The area under the receiver operating characteristic curve(AUC), sensitivity, and specificity were used to evaluate the performance of radiomic models. RESULTS: For task 1, the AUCs of clinical model (histological grade and peritumoral edema), DCE combined IVIM(D + D*+f) radiomic model and clinic combined radiomic model were 0.785 (95%CI:0.713,0.846), 0.866 (95%CI:0.803,0.915) and 0.903 (95%CI:0.846,0.944) respectively. In the validation cohort, The AUCs were 0.751 (95%CI:0.633,0.848), 0.751 (95%CI:0.633,0.848) and 0.830 (95%CI:0.720,0.910) respectively. For task 2, the AUCs of DCE combined IVIM radiomic model in training and validation cohort were 0.951 (95%CI:0.888,0.984) and 0.853 (95%CI:0.712,0.942) respectively, and the radiomics score was independent predictors of HER2 low cancer. CONCLUSION: The radiomic signature derived from multi-parametric MRI, together with peritumoral edema and histological grade, demonstrated strong performance in predicting HER2 expression preoperatively in breast cancer, which may support individualized treatment strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40644-025-00981-y.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。