Virtual Monoenergetic Images of Dual-Energy CT-Impact on Repeatability, Reproducibility, and Classification in Radiomics.

ABSTRACT: The purpose of this study was to (i) evaluate the test-retest repeatability and reproducibility of radiomic features in virtual monoenergetic images (VMI) from dual-energy CT (DECT) depending on VMI energy (40, 50, 75, 120, 190 keV), radiation dose (5 and 15 mGy), and DECT approach (dual-source and split-filter DECT) in a phantom (ex vivo), and (ii) to assess the impact of VMI energy and feature repeatability on machine-learning-based classification in vivo in 72 patients with 72 hypodense liver lesions. Feature repeatability and reproducibility were determined by concordance-correlation-coefficient (CCC) and dynamic range (DR) ≥0.9. Test-retest repeatability was high within the same VMI energies and scan conditions (percentage of repeatable features ranging from 74% for SFDE mode at 40 ke

SUBMITTER: Euler A 

PROVIDER: S-EPMC8467875 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature