Identifying radiomics signatures in body composition imaging for the prediction of outcome following pancreatic cancer resection.

ABSTRACT:

Background

Computerized radiological image analysis (radiomics) enables the investigation of image-derived phenotypes by extracting large numbers of quantitative features. We hypothesized that radiomics features may contain prognostic information that enhances conventional body composition analysis. We aimed to investigate whether body composition-associated radiomics features hold additional value over conventional body composition analysis and clinical patient characteristics used to predict survival of pancreatic ductal adenocarcinoma (PDAC) patients.

Methods

Computed tomography images of 304 patients undergoing elective pancreatic cancer resection were analysed. 2D radiomics features were extracted from skeletal muscle and subcutaneous and visceral adipose tissue (SAT an

SUBMITTER: van der Kroft G 

PROVIDER: S-EPMC10449585 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature