Preoperative computed tomography-based tumoral radiomic features prediction for overall survival in resectable non-small cell lung cancer.

ABSTRACT:

Objectives

The purpose of this study was to evaluate whether preoperative radiomics features could meliorate risk stratification for the overall survival (OS) of non-small cell lung cancer (NSCLC) patients.

Methods

After rigorous screening, the 208 NSCLC patients without any pre-operative adjuvant therapy were eventually enrolled. We segmented the 3D volume of interest (VOI) based on malignant lesion of computed tomography (CT) imaging and extracted 1542 radiomics features. Interclass correlation coefficients (ICC) and LASSO Cox regression analysis were utilized to perform feature selection and radiomics model building. In the model evaluation phase, we carried out stratified analysis, receiver operating characteristic (ROC) curve, concordance index (C-index), and decision c

SUBMITTER: Peng B 

PROVIDER: S-EPMC10189057 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature