Preoperative prediction of the HER2 status and prognosis of patients with endometrial cancer using multiparametric MRI-based radiomics: a multicenter study.

ABSTRACT: Non-invasive preoperative assessment of HER2 status is critical for identifying candidates for targeted therapy and personalizing treatment strategies in endometrial cancer (EC). This study aims to assess the preoperative value of multiparametric magnetic resonance imaging (MRI)-based radiomics in predicting HER2 status and prognosis of EC patients. We included 492 patients with EC divided into training (n = 215), internal validation (n = 92), and external validation cohorts 1 (n = 64) and 2 (n = 121). Models were constructed using six machine learning algorithms based on radiomics features derived from multiparametric MRI, including T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted sequences. A fusion model integrating key clinical predictors with the radiomics score (Rad

SUBMITTER: Lin G 

PROVIDER: S-EPMC12518741 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature