Predictive Power of a Radiomic Signature Based on ¹⁸F-FDG PET/CT Images for EGFR Mutational Status in NSCLC.

ABSTRACT: Radiomics has become an area of interest for tumor characterization in ¹⁸F-Fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging. The aim of the present study was to demonstrate how imaging phenotypes was connected to somatic mutations through an integrated analysis of 115 non-small cell lung cancer (NSCLC) patients with somatic mutation testings and engineered computed PET/CT image analytics. A total of 38 radiomic features quantifying tumor morphological, grayscale statistic, and texture features were extracted from the segmented entire-tumor region of interest (ROI) of the primary PET/CT images. The ensembles for boosting machine learning scheme were employed for classification, and the least absolute shrink age and selection

SUBMITTER: Li X 

PROVIDER: S-EPMC6803612 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature