Deep learning in knee MRI: a prospective study to enhance efficiency, diagnostic confidence and sustainability

Rationale and Objectives - The objective of this study was to evaluate a combination of deep learning (DL)-reconstructed parallel acquisition technique (PAT) and simultaneous multislice (SMS) acceleration imaging in comparison to conventional knee imaging. - Materials and Methods - Adults undergoing...

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Hauptverfasser: Reschke, Philipp (VerfasserIn) , Gotta, Jennifer (VerfasserIn) , Gruenewald, Leon D. (VerfasserIn) , Bachir, Ahmed Ait (VerfasserIn) , Strecker, Ralph (VerfasserIn) , Nickel, Dominik (VerfasserIn) , Booz, Christian (VerfasserIn) , Martin, Simon S. (VerfasserIn) , Scholtz, Jan-Erik (VerfasserIn) , D’Angelo, Tommaso (VerfasserIn) , Dahm, Daniel (VerfasserIn) , Solim, Levent A. (VerfasserIn) , Konrad, Paul (VerfasserIn) , Mahmoudi, Scherwin (VerfasserIn) , Bernatz, Simon (VerfasserIn) , Al-Saleh, Saber (VerfasserIn) , Hong, Quang Anh Le (VerfasserIn) , Sommer, Christof-Matthias (VerfasserIn) , Eichler, Katrin (VerfasserIn) , Vogl, Thomas J. (VerfasserIn) , Haberkorn, Sebastian M. (VerfasserIn) , Koch, Vitali (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: June 2025
In: Academic radiology
Year: 2025, Jahrgang: 32, Heft: 6, Pages: 3585-3596
ISSN:1878-4046
DOI:10.1016/j.acra.2025.03.018
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.acra.2025.03.018
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S1076633225002156
Volltext
Verfasserangaben:Philipp Reschke, MD, Jennifer Gotta, MD, Leon D. Gruenewald, MD, Ahmed Ait Bachir, MD, Ralph Strecker, PhD, Dominik Nickel, PhD, Christian Booz, MD, Simon S. Martin, MD, Jan-Erik Scholtz, MD, Tommaso D’Angelo, MD, Daniel Dahm, cand. med., Levent A. Solim, MD, Paul Konrad, cand. med., Scherwin Mahmoudi, MD, Simon Bernatz, MD, Saber Al-Saleh, Mr, Quang Anh Le Hong, MD, Christof M. Sommer, MD, Katrin Eichler, MD, Thomas J. Vogl, MD, Sebastian M. Haberkorn, MD, Vitali Koch, MD

MARC

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520 |a Rationale and Objectives - The objective of this study was to evaluate a combination of deep learning (DL)-reconstructed parallel acquisition technique (PAT) and simultaneous multislice (SMS) acceleration imaging in comparison to conventional knee imaging. - Materials and Methods - Adults undergoing knee magnetic resonance imaging (MRI) with DL-enhanced acquisitions were prospectively analyzed from December 2023 to April 2024. The participants received T1 without fat saturation and fat-suppressed PD-weighted TSE pulse sequences using conventional two-fold PAT (P2) and either DL-enhanced four-fold PAT (P4) or a combination of DL-enhanced four-fold PAT with two-fold SMS acceleration (P4S2). Three independent readers assessed image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and radiomics features. - Results - 34 participants (mean age 45±17years; 14 women) were included who underwent P4S2, P4, and P2 imaging. Both P4S2 and P4 demonstrated higher CNR and SNR values compared to P2 (P<.001). P4 was diagnostically inferior to P2 only in the visualization of cartilage damage (P<.005), while P4S2 consistently outperformed P2 in anatomical delineation across all evaluated structures and raters (P<.05). Radiomics analysis revealed significant differences in contrast and gray-level characteristics among P2, P4, and P4S2 (P<.05). P4 reduced time by 31% and P4S2 by 41% compared to P2 (P<.05). - Conclusion - P4S2 DL acceleration offers significant advancements over P4 and P2 in knee MRI, combining superior image quality and improved anatomical delineation at significant time reduction. Its improvements in anatomical delineation, energy consumption, and workforce optimization make P4S2 a significant step forward. 
650 4 |a Deep learning 
650 4 |a Knee joint 
650 4 |a Magnetic resonance imaging 
650 4 |a Simultaneous multislice imaging 
650 4 |a Sustainability 
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