Deep learning-based reconstruction enhances image quality and improves diagnosis in magnetic resonance imaging of the shoulder joint.

ABSTRACT:

Background

Accelerated magnetic resonance imaging sequences reconstructed using the vendor-provided Recon deep learning algorithm (DL-MRI) were found to be more likely than conventional magnetic resonance imaging (MRI) sequences to detect subacromial (SbA) bursal thickening. However, the extent of this thickening was not extensively explored. This study aimed to compare the image quality of DL-MRI with conventional MRI sequences reconstructed via conventional pipelines (Conventional-MRI) for shoulder examinations and evaluate the effectiveness of DL-MRI in accurately demonstrating the degree of SbA bursal and subcoracoid (SC) bursal thickening.

Methods

This prospective cross-sectional study enrolled 41 patients with chronic shoulder pain who underwent 3-T MRI (including both

SUBMITTER: Liu Z 

PROVIDER: S-EPMC11007508 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature