MRI-Based peritumoral radiomics for predicting recurrence risk in ER+/HER2- breast cancer

基于磁共振成像的肿瘤周围放射组学预测ER+/HER2-乳腺癌的复发风险

阅读:1

Abstract

BACKGROUND: The application of 21-gene assays in clinical practice is jeopardized by their cost and availability. This study aimed to predict the recurrence score (RS) of a 21-gene assay using MRI peritumoral radiomics in ER+/HER2- breast cancers. METHODS: 154 and 39 patients with ER+/HER2- breast cancer from two centers were enrolled, who underwent 21-gene test and preoperative MRI. Patients from Center 1 were divided into training (n = 108) and internal validation (n = 46) cohorts, and patients from Center 2 were enrolled in the external validation cohort. Radiomics features were extracted from the tumoral, peritumoral and dilation volumes of interest with peritumoral ranges of 1 mm, 3 mm, 5 mm, 7 mm, and 9 mm. After feature selection, RS-prediction models were constructed using support vector machine method to distinguish high (RS ≥ 26) from low RS (RS < 26). RESULTS: As the thickness of the peritumor tissue increased, the AUC of models increased and then decreased, with the 3-mm model performing the best. Among all RS-prediction models, the 3 mm peritumoral model based on T2WI (T2-p3) achieved larger AUCs (0.70 and 0.69 in the internal and external validation cohorts, separately). The peritumoral-fusion model integrating intratumoral radiomic and imaging-clinicopathological features with the T2-p3 model, obtained greater AUCs (0.82 and 0.75 in the internal and external validation cohorts, separately). CONCLUSIONS: MRI peritumoral radiomic data exhibits the potential to serve as a biomarker of recurrence risk in patients with ER+/HER2- breast cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12880-026-02153-1.

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。