Using optimized CT type to predict histological classifications of thymic epithelial tumors: a radiomics integrated analysis.

ABSTRACT:

Objective

To develop and externally validate an integrated model that utilizes optimized radiomics features from non-contrast-enhanced CT (NE-CT) or contrast-enhanced CT (CE-CT), along with morphological features and clinical risk factors, to predict histological classifications of thymic epithelial tumors (TETs).

Methods

A total of 182 patients with TET, classified as the low-risk group and the high-risk group based on histology, were divided into a training cohort (N = 122, center 1) and an external validation cohort (N = 60, center 2). Radiomics features were extracted from different CT types, followed by feature selection, including consistency, correlation, and importance tests, to generate Rad-scores for both NE-CT and CE-CT. The integrated model was developed by combi

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC11929666 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature