# Deep learning-based acceleration of high-resolution compressed sense MR imaging of the hip

## TL;DR

A new deep learning-based MRI framework improves hip cartilage imaging resolution and diagnostic confidence without increasing scan time.

## Contribution

The CSAI framework combines parallel imaging, compressed sense, and deep learning to achieve higher resolution hip MRI.

## Key findings

- CSAI significantly improved cartilage depiction compared to standard compressed sense imaging.
- Diagnostic confidence increased with CSAI for detecting cartilage lesions.
- CSAI achieved higher resolution images without extending acquisition times.

## Abstract

To evaluate a Compressed Sense Artificial Intelligence framework (CSAI) incorporating parallel imaging, compressed sense (CS), and deep learning for high-resolution MRI of the hip, comparing it with standard-resolution CS imaging.

Thirty-two patients with femoroacetabular impingement syndrome underwent 3 T MRI scans. Coronal and sagittal intermediate-weighted TSE sequences with fat saturation were acquired using CS (0.6 ×0.8 mm resolution) and CSAI (0.3 ×0.4 mm resolution) protocols in comparable acquisition times (7:49 vs. 8:07 minutes for both planes). Two readers systematically assessed the depiction of the acetabular and femoral cartilage (in five cartilage zones), labrum, ligamentum capitis femoris, and bone using a five-point Likert scale. Diagnostic confidence and abnormality detection were recorded and analyzed using the Wilcoxon signed-rank test.

CSAI significantly improved the cartilage depiction across most cartilage zones compared to CS. Overall Likert scores were 4.0 ± 0.2 (CS) vs 4.2 ± 0.6 (CSAI) for reader 1 and 4.0 ± 0.2 (CS) vs 4.3 ± 0.6 (CSAI) for reader 2 (p ≤ 0.001). Diagnostic confidence increased from 3.5 ± 0.7 and 3.9 ± 0.6 (CS) to 4.0 ± 0.6 and 4.1 ± 0.7 (CSAI) for readers 1 and 2, respectively (p ≤ 0.001). More cartilage lesions were detected with CSAI, with significant improvements in diagnostic confidence in certain cartilage zones such as femoral zone C and D for both readers. Labrum and ligamentum capitis femoris depiction remained similar, while bone depiction was rated lower. No abnormalities detected in CS were missed in CSAI.

CSAI provides high-resolution hip MR images with enhanced cartilage depiction without extending acquisition times, potentially enabling more precise hip cartilage assessment.

•CSAI framework enhances hip cartilage depiction in MRI scans.•Higher resolution images achieved without extending scan times.•Increased diagnostic confidence in detecting cartilage lesions.•Comparable labrum and ligament depiction to standard CS.•Potentially improves diagnostic accuracy and patient care in hip imaging.

CSAI framework enhances hip cartilage depiction in MRI scans.

Higher resolution images achieved without extending scan times.

Increased diagnostic confidence in detecting cartilage lesions.

Comparable labrum and ligament depiction to standard CS.

Potentially improves diagnostic accuracy and patient care in hip imaging.