Accurate Tumor Delineation vs. Rough Volume of Interest Analysis for ¹⁸F-FDG PET/CT Radiomics-Based Prognostic Modeling inNon-Small Cell Lung Cancer.

ABSTRACT:

Background

The aim of this work was to investigate the ability of building prognostic models in non-small cell lung cancer (NSCLC) using radiomic features from positron emission tomography and computed tomography with 2-deoxy-2-[fluorine-18]fluoro-d-glucose (¹⁸F-FDG PET/CT) images based on a "rough" volume of interest (VOI) containing the tumor instead of its accurate delineation, which is a significant time-consuming bottleneck of radiomics analyses.

Methods

A cohort of 138 patients with stage II-III NSCLC treated with radiochemotherapy recruited retrospectively (n = 87) and prospectively (n = 51) was used. Two approaches were compared: firstly, the radiomic features were extracted from the delineated primary tumor volumes in both PET (using the aut

SUBMITTER: Sepehri S 

PROVIDER: S-EPMC8560021 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature