Deep learning reconstruction for turbo spin echo to prospectively accelerate ankle MRI: A multi-reader study

Abstract

PurposeTo evaluate a deep learning reconstruction for turbo spin echo (DLR-TSE) sequence of ankle magnetic resonance imaging (MRI) in terms of acquisition time, image quality, and lesion detectability by comparing with conventional TSE. MethodsBetween March 2023 and May 2023, patients with an indication for ankle MRI were prospectively enrolled. Each patient underwent a conventional TSE protocol and a prospectively undersampled DLR-TSE protocol. Four experienced radiologists independently assessed image quality using a 5-point scale and reviewed structural abnormalities. Image quality assessment included overall image quality, differentiation of anatomic details, diagnostic confidence, artifacts, and noise. Interchangeability analysis was performed to evaluate the equivalence of DLR-TSE relative to conventional TSE for detection of structural pathologies. ResultsIn total, 56 patients were included (mean age, 32.6 ± 10.6 years; 35 men). The DLR-TSE (233 s) protocol enabled a 57.4 % reduction in total acquisition time, compared with the conventional TSE protocol (547 s). DLR-TSE images had superior overall image quality, fewer artifacts, and less noise (all P < 0.05), compared with conventional TSE images, according to mean ratings by the four readers. Differentiation of anatomic details, diagnostic confidence, and assessments of structural abnormalities showed no differences between the two techniques (P > 0.05). Furthermore, DLR-TSE demonstrated diagnostic equivalence with conventional TSE, based on interchangeability analysis involving all analyzed structural abnormalities. ConclusionDLR can prospectively accelerate conventional TSE to a level comparable with a 4-minute comprehensive examination of the ankle, while providing superior image quality and similar lesion detectability in clinical practice.