Construction of prediction model for KRAS mutation status of colorectal cancer based on CT radiomics.

ABSTRACT:

Background

In this study, we used computed tomography (CT)-based radiomics signatures to predict the mutation status of KRAS in patients with colorectal cancer (CRC) and to identify the phase of radiomics signature with the most robust and high performance from triphasic enhanced CT.

Methods

This study involved 447 patients who underwent KRAS mutation testing and preoperative triphasic enhanced CT. They were categorized into training (n = 313) and validation cohorts (n = 134) in a 7:3 ratio. Radiomics features were extracted using triphasic enhanced CT imaging. The Boruta algorithm was used to retain the features closely associated with KRAS mutations. The Random Forest (RF) algorithm was used to develop radiomics, clinical, and combined clinical-radiomics models for KRAS mu

SUBMITTER: Cao Y 

PROVIDER: S-EPMC10613595 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature