Integrating Radiomics with Genomics for Non-Small Cell Lung Cancer Survival Analysis.

ABSTRACT:

Purpose

The objectives of our study were to assess the association of radiological imaging and gene expression with patient outcomes in non-small cell lung cancer (NSCLC) and construct a nomogram by combining selected radiomic, genomic, and clinical risk factors to improve the performance of the risk model.

Methods

A total of 116 cases of NSCLC with CT images, gene expression, and clinical factors were studied, wherein 87 patients were used as the training cohort, and 29 patients were used as an independent testing cohort. Handcrafted radiomic features and deep-learning genomic features were extracted and selected from CT images and gene expression analysis, respectively. Two risk scores were calculated through Cox regression models for each patient based on radiomic feature

SUBMITTER: Chen W 

PROVIDER: S-EPMC9440821 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature