Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer.

ABSTRACT: Radiomics is the use of quantitative imaging features extracted from medical images to characterize tumor pathology or heterogeneity. Features measured at pretreatment have successfully predicted patient outcomes in numerous cancer sites. This project was designed to determine whether radiomics features measured from non-small cell lung cancer (NSCLC) change during therapy and whether those features (delta-radiomics features) can improve prognostic models. Features were calculated from pretreatment and weekly intra-treatment computed tomography images for 107 patients with stage III NSCLC. Pretreatment images were used to determine feature-specific image preprocessing. Linear mixed-effects models were used to identify features that changed significantly with dose-fraction. Multivariate mod

SUBMITTER: Fave X 

PROVIDER: S-EPMC5428827 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature