Deep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of Interchangeability

Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To investigate the diagnostic interchangeability of...

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Veröffentlicht in:Radiology 2023-03, Vol.306 (3), p.e212922-e212922
Hauptverfasser: Almansour, Haidara, Herrmann, Judith, Gassenmaier, Sebastian, Afat, Saif, Jacoby, Johann, Koerzdoerfer, Gregor, Nickel, Dominik, Mostapha, Mahmoud, Nadar, Mariappan, Othman, Ahmed E
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Sprache:eng
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Zusammenfassung:Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To investigate the diagnostic interchangeability of an unrolled DL-reconstructed TSE (hereafter, TSE ) T1- and T2-weighted acquisition method with standard TSE and to test their impact on acquisition time, image quality, and diagnostic confidence. Materials and Methods This prospective single-center study included participants with various spinal abnormalities who gave written consent from November 2020 to July 2021. Each participant underwent two MRI examinations: standard fully sampled T1- and T2-weighted TSE acquisitions (reference standard) and prospectively undersampled TSE acquisitions with threefold and fourfold acceleration. Image evaluation was performed by five readers. Interchangeability analysis and an image quality-based analysis were used to compare the TSE and TSE images. Acquisition time and diagnostic confidence were also compared. Interchangeability was tested using the individual equivalence index regarding various degenerative and nondegenerative entities, which were analyzed on each vertebra and defined as discordant clinical judgments of less than 5%. Interreader and intrareader agreement and concordance (κ and Kendall τ and W statistics) were computed and Wilcoxon and McNemar tests were used. Results Overall, 50 participants were evaluated (mean age, 46 years ± 18 [SD]; 26 men). The TSE method enabled up to a 70% reduction in total acquisition time (100 seconds for TSE vs 328 seconds for TSE, < .001). All individual equivalence indexes were less than 4%. TSE acquisition was rated as having superior image noise by all readers ( < .001). No evidence of a difference was found between standard TSE and TSE regarding frequency of major findings, overall image quality, or diagnostic confidence. Conclusion The deep learning (DL)-reconstructed turbo spin-echo (TSE) method was found to be interchangeable with standard TSE for detecting various abnormalities of the spine at MRI. DL-reconstructed TSE acquisition provided excellent image quality, with a 70% reduction in examination time. German Clinical Trials Register no. DRKS00023278 © RSNA, 2022 See also the editorial by Hallinan in this issue.
ISSN:0033-8419
1527-1315
DOI:10.1148/radiol.212922