Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain.

Objectives: To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR images in patients with shoulder pain.

Methods: Prospectively, thirty-eight patients (14 women, mean age 40.0 ± 15.

Assessment of Acute Lesions of the Biceps Pulley in Patients with Traumatic Shoulder Dislocation Using MR Imaging.

Background: Shoulder dislocations represent common injuries and are often combined with rotator cuff tears and potentially damage to the biceps pulley.

Purpose: To assess the occurrence and type of biceps pulley lesions in patients after traumatic anterior shoulder dislocation using 3T MRI.

Methods: Thirty-three consecutive patients were enrolled between June 2021 and March 2022 (14 women, mean age 48.