Deep learning-enhanced super-resolution diffusion-weighted liver MRI: improved image quality, diagnostic performance, and acceleration.

ABSTRACT:

Objectives

To investigate the impact of deep learning reconstruction (DLR) on the image quality of diffusion-weighted imaging (DWI) for liver and its ability to differentiate benign from malignant focal liver lesions (FLLs).

Materials and methods

Consecutive patients with suspected liver disease who underwent liver MRI between January and May 2025 were included. All patients received conventional DWI (DWI_C) and an accelerated reconstructed DWI (DWI_DLR) in which acquisition time was prospectively halved by reducing signal averages. Image quality was compared qualitatively using Likert scores (e.g., lesion conspicuity, overall quality) and quantitatively by measuring signal-to-noise ratio of the liver (SNR_Liver) and lesion (SNR_Lesion

SUBMITTER: Zhao D 

PROVIDER: S-EPMC12686321 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature