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Article

Reduction in Acquisition Time and Improvement in Image Quality in T2-Weighted MR Imaging of Musculoskeletal Tumors of the Extremities Using a Novel Deep Learning-Based Reconstruction Technique in a Turbo Spin Echo (TSE) Sequence

1
Department of Diagnostic and Interventional Radiology, University Hospital of Tuebingen, 72076 Tuebingen, Germany
2
MR Application Predevelopment, Siemens Healthcare GmbH, 91052 Erlangen, Germany
3
Department of Diagnostic and Interventional Neuroradiology, University Hospital of Mainz, 55131 Mainz, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Emilio Quaia, Mirko D’Onofrio and Nicolò Cardobi
Tomography 2022, 8(4), 1759-1769; https://doi.org/10.3390/tomography8040148
Received: 13 May 2022 / Revised: 23 June 2022 / Accepted: 30 June 2022 / Published: 6 July 2022
(This article belongs to the Special Issue New Advances in Magnetic Resonance Imaging (MRI))
Background: The aim of this study was to assess the technical feasibility and the impact on image quality and acquisition time of a deep learning-accelerated fat-saturated T2-weighted turbo spin echo sequence in musculoskeletal imaging of the extremities. Methods: Twenty-three patients who underwent MRI of the extremities were prospectively included. Standard T2w turbo inversion recovery magnitude (TIRMStd) imaging was compared to a deep learning-accelerated T2w TSE (TSEDL) sequence. Image analysis of 23 patients with a mean age of 60 years (range 30–86) was performed regarding image quality, noise, sharpness, contrast, artifacts, lesion detectability and diagnostic confidence. Pathological findings were documented measuring the maximum diameter. Results: The analysis showed a significant improvement for the T2 TSEDL with regard to image quality, noise, contrast, sharpness, lesion detectability, and diagnostic confidence, as compared to T2 TIRMStd (each p < 0.001). There were no differences in the number of detected lesions. The time of acquisition (TA) could be reduced by 52–59%. Interrater agreement was almost perfect (κ = 0.886). Conclusion: Accelerated T2 TSEDL was technically feasible and superior to conventionally applied T2 TIRMStd. Concurrently, TA could be reduced by 52–59%. Therefore, deep learning-accelerated MR imaging is a promising and applicable method in musculoskeletal imaging. View Full-Text
Keywords: deep learning; accelerated turbo spin echo MRI; musculoskeletal imaging; musculoskeletal tumors; artificial intelligence deep learning; accelerated turbo spin echo MRI; musculoskeletal imaging; musculoskeletal tumors; artificial intelligence
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MDPI and ACS Style

Wessling, D.; Herrmann, J.; Afat, S.; Nickel, D.; Othman, A.E.; Almansour, H.; Gassenmaier, S. Reduction in Acquisition Time and Improvement in Image Quality in T2-Weighted MR Imaging of Musculoskeletal Tumors of the Extremities Using a Novel Deep Learning-Based Reconstruction Technique in a Turbo Spin Echo (TSE) Sequence. Tomography 2022, 8, 1759-1769. https://doi.org/10.3390/tomography8040148

AMA Style

Wessling D, Herrmann J, Afat S, Nickel D, Othman AE, Almansour H, Gassenmaier S. Reduction in Acquisition Time and Improvement in Image Quality in T2-Weighted MR Imaging of Musculoskeletal Tumors of the Extremities Using a Novel Deep Learning-Based Reconstruction Technique in a Turbo Spin Echo (TSE) Sequence. Tomography. 2022; 8(4):1759-1769. https://doi.org/10.3390/tomography8040148

Chicago/Turabian Style

Wessling, Daniel, Judith Herrmann, Saif Afat, Dominik Nickel, Ahmed E. Othman, Haidara Almansour, and Sebastian Gassenmaier. 2022. "Reduction in Acquisition Time and Improvement in Image Quality in T2-Weighted MR Imaging of Musculoskeletal Tumors of the Extremities Using a Novel Deep Learning-Based Reconstruction Technique in a Turbo Spin Echo (TSE) Sequence" Tomography 8, no. 4: 1759-1769. https://doi.org/10.3390/tomography8040148

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