Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol

Abstract

ObjectivesThe aim of this study was to evaluate the image quality and diagnostic performance of a deep-learning (DL)–accelerated two–dimensional (2D) turbo spin echo (TSE) MRI of the knee at 1.5 and 3 T in clinical routine in comparison to standard MRI.Material and methodsSixty participants, who underwent knee MRI at 1.5 and 3 T between October/2020 and March/2021 with a protocol using standard 2D–TSE (TSES) and DL–accelerated 2D–TSE sequences (TSEDL), were enrolled in this prospective institutional review board–approved study. Three radiologists assessed the sequences regarding structural abnormalities and evaluated the images concerning overall image quality, artifacts, noise, sharpness, subjective signal-to-noise ratio, and diagnostic confidence using a Likert scale (1–5, 5 = best).ResultsOverall image quality for TSEDL was rated to be excellent (median 5, IQR 4–5), significantly higher compared to TSES (median 5, IQR 4 – 5, p < 0.05), showing significantly lower extents of noise and improved sharpness (p < 0.001). Inter- and intra-reader agreement was almost perfect (κ = 0.92–1.00) for the detection of internal derangement and substantial to almost perfect (κ = 0.58–0.98) for the assessment of cartilage defects. No difference was found concerning the detection of bone marrow edema and fractures. The diagnostic confidence of TSEDL was rated to be comparable to that of TSES (median 5, IQR 5–5, p > 0.05). Time of acquisition could be reduced to 6:11 min using TSEDL compared to 11:56 min for a protocol using TSES.ConclusionTSEDL of the knee is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared to TSES, reducing the acquisition time about 50%.Key Points• Deep-learning reconstructed TSE imaging is able to almost halve the acquisition time of a three-plane knee MRI with proton density and T1-weighted images, from 11:56 min to 6:11 min at 3 T.• Deep-learning reconstructed TSE imaging of the knee provided significant improvement of noise levels (p < 0.001), providing higher image quality (p < 0.05) compared to conventional TSE imaging.• Deep-learning reconstructed TSE imaging of the knee had similar diagnostic performance for internal derangement of the knee compared to standard TSE.