Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla
Purpose: The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performa...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-06-01
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| Series: | European Journal of Radiology Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352047724000121 |
| _version_ | 1827223463292567552 |
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| author | Judith Herrmann You-Shan Feng Sebastian Gassenmaier Jan-Peter Grunz Gregor Koerzdoerfer Andreas Lingg Haidara Almansour Dominik Nickel Ahmed E. Othman Saif Afat |
| author_facet | Judith Herrmann You-Shan Feng Sebastian Gassenmaier Jan-Peter Grunz Gregor Koerzdoerfer Andreas Lingg Haidara Almansour Dominik Nickel Ahmed E. Othman Saif Afat |
| author_sort | Judith Herrmann |
| collection | DOAJ |
| description | Purpose: The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performance to that of a standard 2D TSE protocol. Methods: Patients undergoing shoulder MRI between October 2020 and June 2021 were prospectively enrolled. Each patient underwent two MRI examinations: first a standard, fully sampled TSE (TSES) protocol reconstructed with a standard reconstruction followed by a second fast, prospectively undersampled TSE protocol with a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Image quality and visualization of anatomic structures as well as diagnostic performance with respect to shoulder lesions were assessed using a 5-point Likert-scale (5 = best). Interchangeability analysis, Wilcoxon signed-rank test and kappa statistics were performed to compare the two protocols. Results: A total of 30 participants was included (mean age 50±15 years; 15 men). Overall image quality was evaluated to be superior in TSEDL versus TSES (p<0.001). Noise and edge sharpness were evaluated to be significantly superior in TSEDL versus TSES (noise: p<0.001, edge sharpness: p<0.05). No difference was found concerning qualitative diagnostic confidence, assessability of anatomical structures (p>0.05), and quantitative diagnostic performance for shoulder lesions when comparing the two sequences. Conclusions: A fast 5-minute TSEDL MRI protocol of the shoulder is feasible in routine clinical practice at 1.5 and 3 T, with interchangeable results concerning the diagnostic performance, allowing a reduction in scan time of more than 50% compared to the standard TSES protocol. |
| first_indexed | 2024-04-25T01:22:01Z |
| format | Article |
| id | doaj.art-034153336cf7428989428ce8738241eb |
| institution | Directory Open Access Journal |
| issn | 2352-0477 |
| language | English |
| last_indexed | 2025-03-21T16:54:47Z |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | European Journal of Radiology Open |
| spelling | doaj.art-034153336cf7428989428ce8738241eb2024-06-15T06:11:55ZengElsevierEuropean Journal of Radiology Open2352-04772024-06-0112100557Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 TeslaJudith Herrmann0You-Shan Feng1Sebastian Gassenmaier2Jan-Peter Grunz3Gregor Koerzdoerfer4Andreas Lingg5Haidara Almansour6Dominik Nickel7Ahmed E. Othman8Saif Afat9Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Eberhard Karls University, Tuebingen, GermanyInstitute for Clinical Epidemiology and Applied Biometrics, University Hospital Tuebingen, Eberhard Karls University, Tuebingen, GermanyDepartment of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Eberhard Karls University, Tuebingen, GermanyDepartment of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, GermanyMR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, GermanyDepartment of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Eberhard Karls University, Tuebingen, GermanyDepartment of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Eberhard Karls University, Tuebingen, GermanyMR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, GermanyDepartment of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Eberhard Karls University, Tuebingen, Germany; Department of Neuroradiology, University Medical Center Mainz, Mainz, GermanyDepartment of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Eberhard Karls University, Tuebingen, Germany; Correspondence to: Department of Diagnostic and Interventional Radiology, Tübingen University Hospital, Hoppe-Seyler-Str 3, Tübingen 72076, GermanyPurpose: The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performance to that of a standard 2D TSE protocol. Methods: Patients undergoing shoulder MRI between October 2020 and June 2021 were prospectively enrolled. Each patient underwent two MRI examinations: first a standard, fully sampled TSE (TSES) protocol reconstructed with a standard reconstruction followed by a second fast, prospectively undersampled TSE protocol with a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Image quality and visualization of anatomic structures as well as diagnostic performance with respect to shoulder lesions were assessed using a 5-point Likert-scale (5 = best). Interchangeability analysis, Wilcoxon signed-rank test and kappa statistics were performed to compare the two protocols. Results: A total of 30 participants was included (mean age 50±15 years; 15 men). Overall image quality was evaluated to be superior in TSEDL versus TSES (p<0.001). Noise and edge sharpness were evaluated to be significantly superior in TSEDL versus TSES (noise: p<0.001, edge sharpness: p<0.05). No difference was found concerning qualitative diagnostic confidence, assessability of anatomical structures (p>0.05), and quantitative diagnostic performance for shoulder lesions when comparing the two sequences. Conclusions: A fast 5-minute TSEDL MRI protocol of the shoulder is feasible in routine clinical practice at 1.5 and 3 T, with interchangeable results concerning the diagnostic performance, allowing a reduction in scan time of more than 50% compared to the standard TSES protocol.http://www.sciencedirect.com/science/article/pii/S2352047724000121AccelerationMagnetic resonance imagingDeep learning reconstructionImage processingDiagnostic imaging |
| spellingShingle | Judith Herrmann You-Shan Feng Sebastian Gassenmaier Jan-Peter Grunz Gregor Koerzdoerfer Andreas Lingg Haidara Almansour Dominik Nickel Ahmed E. Othman Saif Afat Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla European Journal of Radiology Open Acceleration Magnetic resonance imaging Deep learning reconstruction Image processing Diagnostic imaging |
| title | Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla |
| title_full | Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla |
| title_fullStr | Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla |
| title_full_unstemmed | Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla |
| title_short | Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla |
| title_sort | fast 5 minute shoulder mri protocol with accelerated tse sequences and deep learning image reconstruction for the assessment of shoulder pain at 1 5 and 3 tesla |
| topic | Acceleration Magnetic resonance imaging Deep learning reconstruction Image processing Diagnostic imaging |
| url | http://www.sciencedirect.com/science/article/pii/S2352047724000121 |
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