Low-dose liver CT: image quality and diagnostic accuracy of deep learning image reconstruction algorithm.

ABSTRACT:

Objectives

To perform a comprehensive within-subject image quality analysis of abdominal CT examinations reconstructed with DLIR and to evaluate diagnostic accuracy compared to the routinely applied adaptive statistical iterative reconstruction (ASiR-V) algorithm.

Materials and methods

Oncologic patients were prospectively enrolled and underwent contrast-enhanced CT. Images were reconstructed with DLIR with three intensity levels of reconstruction (high, medium, and low) and ASiR-V at strength levels from 10 to 100% with a 10% interval. Three radiologists characterized the lesions and two readers assessed diagnostic accuracy and calculated signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), figure of merit (FOM), and subjective image quality, the latter with a 5-poin

SUBMITTER: Caruso D 

PROVIDER: S-EPMC10957592 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature