Utility of CT radiomics for prediction of PD-L1 expression in advanced lung adenocarcinomas.

ABSTRACT:

Background

We aimed to assess if quantitative radiomic features can predict programmed death ligand 1 (PD-L1) expression in advanced stage lung adenocarcinoma.

Methods

This retrospective study included 153 patients who had advanced stage (>IIIA by TNM classification) lung adenocarcinoma with pretreatment thin section computed tomography (CT) images and PD-L1 expression test results in their pathology reports. Clinicopathological data were collected from electronic medical records. Visual analysis and radiomic feature extraction of the tumor from pretreatment CT were performed. We constructed two models for multivariate logistic regression analysis (one based on clinical variables, and the other based on a combination of clinical variables and radiomic features), and compared

SUBMITTER: Yoon J 

PROVIDER: S-EPMC7113038 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature