Incremental diagnostic value of tumor habitat radiomics for risk stratification in thymic epithelial tumors.

ABSTRACT:

Purpose

To determine the incremental diagnostic value of habitat radiomics for risk stratification of thymic epithelial tumors (TETs) based on contrast-enhanced CT (CECT).

Methods

This retrospective study included 220 patients with pathologically confirmed TETs (82 high-risk [B2/B3/thymic carcinoma] and 138 low-risk [A/AB/B1]) who underwent preoperative CECT. Tumors were segmented into 3 subregions (habitats) using k-means clustering, and radiomic features were extracted from both whole-tumor and subregions. After feature selection (variance threshold, reproducibility evaluation, XGBoost-based importance ranking, and recursive feature elimination), three machine learning models were developed (1): a conventional radiomics model (2), a habitat radiomics model, and (3) a combi

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12440988 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature