Feasibility and clinical usefulness of deep learning-accelerated MRI for acute painful fracture patients wearing a splint: A prospective comparative study

PLoS One. 2023 Jun 28;18(6):e0287903. doi: 10.1371/journal.pone.0287903. eCollection 2023.

Abstract

Objective: To evaluate the feasibility and clinical usefulness of deep learning (DL)-accelerated turbo spin echo (TSEDL) sequences relative to standard TSE sequences (TSES) for acute radius fracture patients wearing a splint.

Methods: This prospective consecutive study investigated 50 patients' preoperative wrist MRI scans acquired between July 2021 and January 2022. Examinations were performed at 3 Tesla MRI with body array coils due to the wrist splint. Besides TSES obtained according to the routine protocol, TSEDL sequences for axial T2-, coronal T1-, and coronal PD-weighted TSE sequences were scanned for comparison. For quantitative assessment, the relative signal-to-noise ratio (rSNR), the relative contrast-to-noise ratio (rCNR), and the relative contrast ratio (rCR) were measured. For qualitative assessment, all images were assessed by two independent musculoskeletal radiologists in terms of perceived SNR, image contrast, image sharpness, artifacts disturbing evaluation, overall image quality and diagnostic confidence for injuries using a four- or five-point Likert scale.

Results: The scan time was shortened approximately by a factor of two for TSEDL compared to TSES. TSEDL images showed significantly better rSNR, rCNR, and rCR values for all sequences, and scored significantly better in terms of both image quality and diagnostic confidence for both readers than TSES images (all p < .05). Interrater reliabilities were in almost perfect agreement.

Conclusion: The DL-accelerated technique proved to be very helpful not only to reduce scan time but also to improve image quality for acute painful fracture patients wearing a splint despite using body array coils instead of a wrist-specific coil. Based on our study, the DL-accelerated technique can be very useful for MRI of any part of the extremities in trauma settings just with body array coils.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artifacts
  • Deep Learning*
  • Feasibility Studies
  • Humans
  • Magnetic Resonance Imaging / methods
  • Prospective Studies
  • Radius Fractures*
  • Splints

Grants and funding

This research was supported by Research Program 2021 funded by Seoul National University College of Medicine Research Foundation (https://e-donation.snu.ac.kr). Authors JC, JP and GK (initials) received the grant and the total amount was 2,000,000 KRW (1,524 USD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.