Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3â¯Tesla.
Eur J Radiol Open
; 12: 100557, 2024 Jun.
Article
em En
| MEDLINE
| ID: mdl-38495213
ABSTRACT
Purpose:
The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performance to that of a standard 2D TSE protocol.Methods:
Patients undergoing shoulder MRI between October 2020 and June 2021 were prospectively enrolled. Each patient underwent two MRI examinations first a standard, fully sampled TSE (TSES) protocol reconstructed with a standard reconstruction followed by a second fast, prospectively undersampled TSE protocol with a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Image quality and visualization of anatomic structures as well as diagnostic performance with respect to shoulder lesions were assessed using a 5-point Likert-scale (5 = best). Interchangeability analysis, Wilcoxon signed-rank test and kappa statistics were performed to compare the two protocols.Results:
A total of 30 participants was included (mean age 50±15 years; 15 men). Overall image quality was evaluated to be superior in TSEDL versus TSES (p<0.001). Noise and edge sharpness were evaluated to be significantly superior in TSEDL versus TSES (noise p<0.001, edge sharpness p<0.05). No difference was found concerning qualitative diagnostic confidence, assessability of anatomical structures (p>0.05), and quantitative diagnostic performance for shoulder lesions when comparing the two sequences.Conclusions:
A fast 5-minute TSEDL MRI protocol of the shoulder is feasible in routine clinical practice at 1.5 and 3â¯T, with interchangeable results concerning the diagnostic performance, allowing a reduction in scan time of more than 50% compared to the standard TSES protocol.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article