CT-based conventional radiomics and quantification of intratumoral heterogeneity for predicting benign and malignant renal lesions.

ABSTRACT:

Background

With the increasing incidence of renal lesions, pretreatment differentiation between benign and malignant lesions is crucial for optimized management. This study aimed to develop a machine learning model utilizing radiomic features extracted from various regions of interest (ROIs), intratumoral ecological diversity features, and clinical factors to classify renal lesions.

Methods

CT images (arterial phase) of 1,795 renal lesions with confirmed pathology from three hospital sites were split into development (1184, 66%) and test (611, 34%) cohorts by surgery date. Conventional radiomic features were extracted from eight ROIs of arterial phase images. Intratumoral ecological diversity features were derived from intratumoral subregions. The combined model incorporatin

SUBMITTER: Yu S 

PROVIDER: S-EPMC11446113 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature