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Vosshenrich J, Fritz J. [Accelerated musculoskeletal magnetic resonance imaging with deep learning-based image reconstruction at 0.55 T-3 T]. RADIOLOGIE (HEIDELBERG, GERMANY) 2024:10.1007/s00117-024-01325-w. [PMID: 38864874 DOI: 10.1007/s00117-024-01325-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/14/2024] [Indexed: 06/13/2024]
Abstract
CLINICAL/METHODICAL ISSUE Magnetic resonance imaging (MRI) is a central component of musculoskeletal imaging. However, long image acquisition times can pose practical barriers in clinical practice. STANDARD RADIOLOGICAL METHODS MRI is the established modality of choice in the diagnostic workup of injuries and diseases of the musculoskeletal system due to its high spatial resolution, excellent signal-to-noise ratio (SNR), and unparalleled soft tissue contrast. METHODOLOGICAL INNOVATIONS Continuous advances in hardware and software technology over the last few decades have enabled four-fold acceleration of 2D turbo-spin-echo (TSE) without compromising image quality or diagnostic performance. The recent clinical introduction of deep learning (DL)-based image reconstruction algorithms helps to minimize further the interdependency between SNR, spatial resolution and image acquisition time and allows the use of higher acceleration factors. PERFORMANCE The combined use of advanced acceleration techniques and DL-based image reconstruction holds enormous potential to maximize efficiency, patient comfort, access, and value of musculoskeletal MRI while maintaining excellent diagnostic accuracy. ACHIEVEMENTS Accelerated MRI with DL-based image reconstruction has rapidly found its way into clinical practice and proven to be of added value. Furthermore, recent investigations suggest that the potential of this technology does not yet appear to be fully harvested. PRACTICAL RECOMMENDATIONS Deep learning-reconstructed fast musculoskeletal MRI examinations can be reliably used for diagnostic work-up and follow-up of musculoskeletal pathologies in clinical practice.
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Affiliation(s)
- Jan Vosshenrich
- Department of Radiology, Grossman School of Medicine, New York University, 660 First Avenue, 10016, New York, NY, USA.
- Klinik für Radiologie und Nuklearmedizin, Universitätsspital Basel, Petersgraben 4, 4031, Basel, Schweiz.
| | - Jan Fritz
- Department of Radiology, Grossman School of Medicine, New York University, 660 First Avenue, 10016, New York, NY, USA
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Feuerriegel GC, Weiss K, Tu Van A, Leonhardt Y, Neumann J, Gassert FT, Haas Y, Schwarz M, Makowski MR, Woertler K, Karampinos DC, Gersing AS. Deep-learning-based image quality enhancement of CT-like MR imaging in patients with suspected traumatic shoulder injury. Eur J Radiol 2024; 170:111246. [PMID: 38056345 DOI: 10.1016/j.ejrad.2023.111246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 11/21/2023] [Accepted: 11/29/2023] [Indexed: 12/08/2023]
Abstract
PURPOSE To evaluate the diagnostic performance of CT-like MR images reconstructed with an algorithm combining compressed sense (CS) with deep learning (DL) in patients with suspected osseous shoulder injury compared to conventional CS-reconstructed images. METHODS Thirty-two patients (12 women, mean age 46 ± 14.9 years) with suspected traumatic shoulder injury were prospectively enrolled into the study. All patients received MR imaging of the shoulder, including a CT-like 3D T1-weighted gradient-echo (T1 GRE) sequence and in case of suspected fracture a conventional CT. An automated DL-based algorithm, combining CS and DL (CS DL) was used to reconstruct images of the same k-space data as used for CS reconstructions. Two musculoskeletal radiologists assessed the images for osseous pathologies, image quality and visibility of anatomical landmarks using a 5-point Likert scale. Moreover, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. RESULTS Compared to CT, all acute fractures (n = 23) and osseous pathologies were detected accurately on the CS only and CS DL images with almost perfect agreement between the CS DL and CS only images (κ 0.95 (95 %confidence interval 0.82-1.00). Image quality as well as the visibility of the fracture lines, bone fragments and glenoid borders were overall rated significantly higher for the CS DL reconstructions than the CS only images (CS DL range 3.7-4.9 and CS only range 3.2-3.8, P = 0.01-0.04). Significantly higher SNR and CNR values were observed for the CS DL reconstructions (P = 0.02-0.03). CONCLUSION Evaluation of traumatic shoulder pathologies is feasible using a DL-based algorithm for reconstruction of high-resolution CT-like MR imaging.
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Affiliation(s)
- Georg C Feuerriegel
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | | | - Anh Tu Van
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Yannik Leonhardt
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Jan Neumann
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany; Musculoskeletal Radiology Section, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Florian T Gassert
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Yannick Haas
- Department of Trauma Surgery, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Markus Schwarz
- Department of Trauma Surgery, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Marcus R Makowski
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Klaus Woertler
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany; Musculoskeletal Radiology Section, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Dimitrios C Karampinos
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Alexandra S Gersing
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany; Department of Neuroradiology, University Hospital of Munich, LMU Munich, Munich, Germany.
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Yoon MA, Gold GE, Chaudhari AS. Accelerated Musculoskeletal Magnetic Resonance Imaging. J Magn Reson Imaging 2023. [PMID: 38156716 DOI: 10.1002/jmri.29205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/13/2023] [Accepted: 12/14/2023] [Indexed: 01/03/2024] Open
Abstract
With a substantial growth in the use of musculoskeletal MRI, there has been a growing need to improve MRI workflow, and faster imaging has been suggested as one of the solutions for a more efficient examination process. Consequently, there have been considerable advances in accelerated MRI scanning methods. This article aims to review the basic principles and applications of accelerated musculoskeletal MRI techniques including widely used conventional acceleration methods, more advanced deep learning-based techniques, and new approaches to reduce scan time. Specifically, conventional accelerated MRI techniques, including parallel imaging, compressed sensing, and simultaneous multislice imaging, and deep learning-based accelerated MRI techniques, including undersampled MR image reconstruction, super-resolution imaging, artifact correction, and generation of unacquired contrast images, are discussed. Finally, new approaches to reduce scan time, including synthetic MRI, novel sequences, and new coil setups and designs, are also reviewed. We believe that a deep understanding of these fast MRI techniques and proper use of combined acceleration methods will synergistically improve scan time and MRI workflow in daily practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Min A Yoon
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Garry E Gold
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Orthopaedic Surgery, Stanford University, Stanford, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
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Herrmann J, Gassenmaier S, Keller G, Koerzdoerfer G, Almansour H, Nickel D, Othman A, Afat S, Werner S. Deep Learning MRI Reconstruction for Accelerating Turbo Spin Echo Hand and Wrist Imaging: A Comparison of Image Quality, Visualization of Anatomy, and Detection of Common Pathologies with Standard Imaging. Acad Radiol 2023; 30:2606-2615. [PMID: 36797172 DOI: 10.1016/j.acra.2022.12.042] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/20/2022] [Accepted: 12/26/2022] [Indexed: 02/16/2023]
Abstract
RATIONALE AND OBJECTIVES Magnetic resonance imaging (MRI) of the hand and wrist is a routine MRI examination and takes about 15-20 minutes, which can lead to problems resulting from the relatively long scan time, such as decreased image quality due to motion artifacts and lower patient throughput. The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the hand and wrist regarding image quality, visualization of anatomy, and diagnostic performance concerning common pathologies. MATERIALS AND METHODS Twenty-one patients (mean age: 43 ± 19 [19-85] years, 10 men, 11 female) were prospectively enrolled in this study between October 2020 and June 2021. Each participant underwent two MRI protocols: first, standard fully sampled TSE sequences reconstructed with a standard GRAPPA reconstruction (TSES) and second, prospectively undersampled TSE sequences using a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Both protocols were acquired consecutively in one examination. Two experienced MSK-imaging radiologists qualitatively evaluated the images concerning image quality, noise, edge sharpness, artifacts, and diagnostic confidence, as well as the delineation of anatomical structures (triangular fibrocartilage complex, tendon of the extensor carpi ulnaris muscle, extrinsic and intrinsic ligaments, median nerve, cartilage) using a five-point Likert scale and assessed common pathologies. Wilcoxon signed-rank test and kappa statistics were performed to compare the sequences. RESULTS Overall image quality, artifacts, delineation of anatomical structures, and diagnostic confidence of TSEDL were rated to be comparable to TSES (p > 0.05). Additionally, TSEDL showed decreased image noise (4.90, median 5, IQR 5-5) compared to TSES (4.52, median 5, IQR 4-5, p < 0.05) and improved edge sharpness (TSEDL: 4.10, median 4, IQR 3.5-5; TSES: 3.57, median 4, IQR 3-4; p < 0.05). Inter- and intrareader agreement was substantial to almost perfect (κ = 0.632-1.000) for the detection of common pathologies. Time of acquisition could be reduced by more than 60% with the protocol using TSEDL. CONCLUSION Compared to TSES, TSEDL provided decreased noise and increased edge sharpness, equal image quality, delineation of anatomical structures, detection of pathologies, and diagnostic confidence. Therefore, TSEDL may be clinically relevant for hand and wrist imaging, as it reduces examination time by more than 60%, thus increasing patient comfort and patient throughput.
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Affiliation(s)
- Judith Herrmann
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | - Sebastian Gassenmaier
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | - Gabriel Keller
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | | | - Haidara Almansour
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
| | - Dominik Nickel
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Ahmed Othman
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany; Department of Neuroradiology, University Medical Center Mainz, Mainz, Germany
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany.
| | - Sebastian Werner
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen, Germany
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Zhao Q, Xu J, Yang YX, Yu D, Zhao Y, Wang Q, Yuan H. AI-assisted accelerated MRI of the ankle: clinical practice assessment. Eur Radiol Exp 2023; 7:62. [PMID: 37857868 PMCID: PMC10587051 DOI: 10.1186/s41747-023-00374-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 08/04/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND High-spatial resolution magnetic resonance imaging (MRI) is essential for imaging ankle joints. However, the clinical application of fast spin-echo sequences remains limited by their lengthy acquisition time. Artificial intelligence-assisted compressed sensing (ACS) technology has been recently introduced as an integrative acceleration solution. We compared ACS-accelerated 3-T ankle MRI to conventional methods of compressed sensing (CS) and parallel imaging (PI) . METHODS We prospectively included 2 healthy volunteers and 105 patients with ankle pain. ACS acceleration factors for ankle protocol of T1-, T2-, and proton density (PD)-weighted sequences were optimized in a pilot study on healthy volunteers (acceleration factor 3.2-3.3×). Images of patients acquired using ACS and conventional acceleration methods were compared in terms of acquisition times, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), subjective image quality, and diagnostic agreement. Shapiro-Wilk test, Cohen κ, intraclass correlation coefficient, and one-way ANOVA with post hoc tests (Tukey or Dunn) were used. RESULTS ACS acceleration reduced the acquisition times of T1-, T2-, and PD-weighted sequences by 32-43%, compared with conventional CS and PI, while maintaining image quality (mostly higher SNR with p < 0.004 and higher CNR with p < 0.047). The diagnostic agreement between ACS and conventional sequences was rated excellent (κ = 1.00). CONCLUSIONS The optimum ACS acceleration factors for ankle MRI were found to be 3.2-3.3× protocol. The ACS allows faster imaging, yielding similar image quality and diagnostic performance. RELEVANCE STATEMENT AI-assisted compressed sensing significantly accelerates ankle MRI times while preserving image quality and diagnostic precision, potentially expediting patient diagnoses and improving clinical workflows. KEY POINTS • AI-assisted compressed sensing (ACS) significantly reduced scan duration for ankle MRI. • Similar image quality achieved by ACS compared to conventional acceleration methods. • A high agreement by three acceleration methods in the diagnosis of ankle lesions was observed.
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Affiliation(s)
- Qiang Zhao
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Jiajia Xu
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Yu Xin Yang
- United Imaging Research Institute of Intelligent Imaging, Beijing, People's Republic of China
| | - Dan Yu
- United Imaging Research Institute of Intelligent Imaging, Beijing, People's Republic of China
| | - Yuqing Zhao
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Qizheng Wang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China.
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Herrmann J, Afat S, Gassenmaier S, Koerzdoerfer G, Lingg A, Almansour H, Nickel D, Werner S. Image Quality and Diagnostic Performance of Accelerated 2D Hip MRI with Deep Learning Reconstruction Based on a Deep Iterative Hierarchical Network. Diagnostics (Basel) 2023; 13:3241. [PMID: 37892062 PMCID: PMC10606422 DOI: 10.3390/diagnostics13203241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/10/2023] [Accepted: 10/14/2023] [Indexed: 10/29/2023] Open
Abstract
OBJECTIVES Hip MRI using standard multiplanar sequences requires long scan times. Accelerating MRI is accompanied by reduced image quality. This study aimed to compare standard two-dimensional (2D) turbo spin echo (TSE) sequences with accelerated 2D TSE sequences with deep learning (DL) reconstruction (TSEDL) for routine clinical hip MRI at 1.5 and 3 T in terms of feasibility, image quality, and diagnostic performance. MATERIAL AND METHODS In this prospective, monocentric study, TSEDL was implemented clinically and evaluated in 14 prospectively enrolled patients undergoing a clinically indicated hip MRI at 1.5 and 3T between October 2020 and May 2021. Each patient underwent two examinations: For the first exam, we used standard sequences with generalized autocalibrating partial parallel acquisition reconstruction (TSES). For the second exam, we implemented prospectively undersampled TSE sequences with DL reconstruction (TSEDL). Two radiologists assessed the TSEDL and TSES regarding image quality, artifacts, noise, edge sharpness, diagnostic confidence, and delineation of anatomical structures using an ordinal five-point Likert scale (1 = non-diagnostic; 2 = poor; 3 = moderate; 4 = good; 5 = excellent). Both sequences were compared regarding the detection of common pathologies of the hip. Comparative analyses were conducted to assess the differences between TSEDL and TSES. RESULTS Compared with TSES, TSEDL was rated to be significantly superior in terms of image quality (p ≤ 0.020) with significantly reduced noise (p ≤ 0.001) and significantly improved edge sharpness (p = 0.003). No difference was found between TSES and TSEDL concerning the extent of artifacts, diagnostic confidence, or the delineation of anatomical structures (p > 0.05). Example acquisition time reductions for the TSE sequences of 52% at 3 Tesla and 70% at 1.5 Tesla were achieved. CONCLUSION TSEDL of the hip is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared with TSES, reducing the acquisition time significantly.
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Affiliation(s)
- Judith Herrmann
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Sebastian Gassenmaier
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Gregor Koerzdoerfer
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Andreas Lingg
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Haidara Almansour
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
| | - Dominik Nickel
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Sebastian Werner
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany
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Feuerriegel GC, Weiss K, Kronthaler S, Leonhardt Y, Neumann J, Wurm M, Lenhart NS, Makowski MR, Schwaiger BJ, Woertler K, Karampinos DC, Gersing AS. Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain. Eur Radiol 2023; 33:4875-4884. [PMID: 36806569 PMCID: PMC10289918 DOI: 10.1007/s00330-023-09472-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/07/2023] [Accepted: 01/22/2023] [Indexed: 02/21/2023]
Abstract
OBJECTIVES To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR images in patients with shoulder pain. METHODS Prospectively, thirty-eight patients (14 women, mean age 40.0 ± 15.2 years) with shoulder pain underwent morphological MRI using a pseudo-random, density-weighted k-space scheme with an acceleration factor of 2.5 using CS only. An automated DL-based algorithm (CS DL) was used to create reconstructions of the same k-space data as used for CS reconstructions. Images were analyzed by two radiologists and assessed for pathologies, image quality, and visibility of anatomical landmarks using a 4-point Likert scale. RESULTS Overall agreement for the detection of pathologies between the CS DL reconstructions and CS images was substantial to almost perfect (κ 0.95 (95% confidence interval 0.82-1.00)). Image quality and the visibility of the rotator cuff, articular cartilage, and axillary recess were overall rated significantly higher for CS DL images compared to CS (p < 0.03). Contrast-to-noise ratios were significantly higher for cartilage/fluid (CS DL 198 ± 24.3, CS 130 ± 32.2, p = 0.02) and ligament/fluid (CS DL 184 ± 17.3, CS 141 ± 23.5, p = 0.03) and SNR values were significantly higher for ligaments and muscle of the CS DL reconstructions (p < 0.04). CONCLUSION Evaluation of shoulder pathologies was feasible using a DL-based algorithm for MRI reconstruction and denoising. In clinical routine, CS DL may be beneficial in particular for reducing image noise and may be useful for the detection and better discrimination of discrete pathologies. Assessment of shoulder pathologies was feasible with improved image quality as well as higher SNR using a compressed sensing deep learning-based framework for image reconstructions and denoising. KEY POINTS • Automated deep learning-based reconstructions showed a significant increase in signal-to-noise ratio and contrast-to-noise ratio (p < 0.04) with only a slight increase of reconstruction time of 40 s compared to CS. • All pathologies were accurately detected with no loss of diagnostic information or prolongation of the scan time. • Significant improvements of the image quality as well as the visibility of the rotator cuff, articular cartilage, and axillary recess were detected.
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Affiliation(s)
- Georg C Feuerriegel
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany.
| | | | - Sophia Kronthaler
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Yannik Leonhardt
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Jan Neumann
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Musculoskeletal Radiology Section, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Markus Wurm
- Department of Trauma Surgery, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Nicolas S Lenhart
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Marcus R Makowski
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Benedikt J Schwaiger
- Department of Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Klaus Woertler
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Musculoskeletal Radiology Section, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
| | - Alexandra S Gersing
- Department of Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675, Munich, Germany
- Department of Neuroradiology, University Hospital of Munich, LMU Munich, Munich, Germany
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Jungmann PM, Lange T, Wenning M, Baumann FA, Bamberg F, Jung M. Ankle Sprains in Athletes: Current Epidemiological, Clinical and Imaging Trends. Open Access J Sports Med 2023; 14:29-46. [PMID: 37252646 PMCID: PMC10216848 DOI: 10.2147/oajsm.s397634] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 05/06/2023] [Indexed: 05/31/2023] Open
Abstract
Purpose Ankle injuries are frequent sports injuries. Despite optimizing treatment strategies during recent years, the percentage of chronification following an ankle sprain remains high. The purpose of this review article is, to highlight current epidemiological, clinical and novel advanced cross-sectional imaging trends that may help to evaluate ankle sprain injuries. Methods Systematic PubMed literature research. Identification and review of studies (i) analyzing and describing ankle sprain and (ii) focusing on advanced cross-sectional imaging techniques at the ankle. Results The ankle is one of the most frequently injured body parts in sports. During the COVID-19 pandemic, there was a change in sporting behavior and sports injuries. Ankle sprains account for about 16-40% of the sports-related injuries. Novel cross-sectional imaging techniques, including Compressed Sensing MRI, 3D MRI, ankle MRI with traction or plantarflexion-supination, quantitative MRI, CT-like MRI, CT arthrography, weight-bearing cone beam CT, dual-energy CT, photon-counting CT, and projection-based metal artifact reduction CT may be introduced for detection and evaluation of specific pathologies after ankle injury. While simple ankle sprains are generally treated conservatively, unstable syndesmotic injuries may undergo stabilization using suture-button-fixation. Minced cartilage implantation is a novel cartilage repair technique for osteochondral defects at the ankle. Conclusion Applications and advantages of different cross-sectional imaging techniques at the ankle are highlighted. In a personalized approach, optimal imaging techniques may be chosen that best detect and delineate structural ankle injuries in athletes.
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Affiliation(s)
- Pia M Jungmann
- Department of Diagnostic and Interventional Radiology, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Radiology, Kantonsspital Graubünden, Chur, Switzerland
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Markus Wenning
- Department of Orthopedic and Trauma Surgery, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Frédéric A Baumann
- Department of Vascular Medicine, Hospital of Schiers, Schiers, Switzerland
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias Jung
- Department of Diagnostic and Interventional Radiology, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Keller G, Estler A, Herrmann J, Afat S, Othman AE, Nickel D, Koerzdoerfer G, Springer F. Prospective intraindividual comparison of a standard 2D TSE MRI protocol for ankle imaging and a deep learning-based 2D TSE MRI protocol with a scan time reduction of 48. LA RADIOLOGIA MEDICA 2023; 128:347-356. [PMID: 36807027 PMCID: PMC10020308 DOI: 10.1007/s11547-023-01604-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 01/24/2023] [Indexed: 02/23/2023]
Abstract
PURPOSE Magnetic resonance imaging (MRI) scan time remains a limited and valuable resource. This study evaluates the diagnostic performance of a deep learning (DL)-based accelerated TSE study protocol compared to a standard TSE study protocol in ankle MRI. MATERIAL AND METHODS Between October 2020 and July 2021 forty-seven patients were enrolled in this study for an intraindividual comparison of a standard TSE study protocol and a DL TSE study protocol either on a 1.5 T or a 3 T scanner. Two radiologists evaluated the examinations regarding structural pathologies and image quality categories (5-point-Likert-scale; 1 = "non diagnostic", 5 = "excellent"). RESULTS Both readers showed almost perfect/perfect agreement of DL TSE with standard TSE in all analyzed structural pathologies (0.81-1.00) with a median "good" or "excellent" rating (4-5/5) in all image quality categories in both 1.5 T and 3 T MRI. The reduction of total acquisition time of DL TSE compared to standard TSE was 49% in 1.5 T and 48% in 3 T MRI to a total acquisition time of 5 min 41 s and 5 min 46 s. CONCLUSION In ankle MRI the new DL-based accelerated TSE study protocol delivers high agreement with standard TSE and high image quality, while reducing the acquisition time by 48%.
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Affiliation(s)
- Gabriel Keller
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
| | - Arne Estler
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Judith Herrmann
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Saif Afat
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Ahmed E Othman
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
- Universitätsklink für Neuroradiologie, Johannes Gutenberg-Universität Mainz, Mainz, Germany
| | - Dominik Nickel
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee Am Roethelheimpark 2, 91052, Erlangen, Germany
| | - Gregor Koerzdoerfer
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee Am Roethelheimpark 2, 91052, Erlangen, Germany
| | - Fabian Springer
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
- Department of Diagnostic Radiology, BG Trauma Center Tübingen, Eberhard Karls University Tübingen, Schnarrenbergstr. 95, 72076, Tübingen, Germany
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Foreman SC, Neumann J, Han J, Harrasser N, Weiss K, Peeters JM, Karampinos DC, Makowski MR, Gersing AS, Woertler K. Deep learning-based acceleration of Compressed Sense MR imaging of the ankle. Eur Radiol 2022; 32:8376-8385. [PMID: 35751695 DOI: 10.1007/s00330-022-08919-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 05/13/2022] [Accepted: 05/30/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To evaluate a compressed sensing artificial intelligence framework (CSAI) to accelerate MRI acquisition of the ankle. METHODS Thirty patients were scanned at 3T. Axial T2-w, coronal T1-w, and coronal/sagittal intermediate-w scans with fat saturation were acquired using compressed sensing only (12:44 min, CS), CSAI with an acceleration factor of 4.6-5.3 (6:45 min, CSAI2x), and CSAI with an acceleration factor of 6.9-7.7 (4:46 min, CSAI3x). Moreover, a high-resolution axial T2-w scan was obtained using CSAI with a similar scan duration compared to CS. Depiction and presence of abnormalities were graded. Signal-to-noise and contrast-to-noise were calculated. Wilcoxon signed-rank test and Cohen's kappa were used to compare CSAI with CS sequences. RESULTS The correlation was perfect between CS and CSAI2x (κ = 1.0) and excellent for CS and CSAI3x (κ = 0.86-1.0). No significant differences were found for the depiction of structures between CS and CSAI2x and the same abnormalities were detected in both protocols. For CSAI3x the depiction was graded lower (p ≤ 0.001), though most abnormalities were also detected. For CSAI2x contrast-to-noise fluid/muscle was higher compared to CS (p ≤ 0.05), while no differences were found for other tissues. Signal-to-noise and contrast-to-noise were higher for CSAI3x compared to CS (p ≤ 0.05). The high - resolution axial T2-w sequence specifically improved the depiction of tendons and the tibial nerve (p ≤ 0.005). CONCLUSIONS Acquisition times can be reduced by 47% using CSAI compared to CS without decreasing diagnostic image quality. Reducing acquisition times by 63% is feasible but should be reserved for specific patients. The depiction of specific structures is improved using a high-resolution axial T2-w CSAI scan. KEY POINTS • Prospective study showed that CSAI enables reduction in acquisition times by 47% without decreasing diagnostic image quality. • Reducing acquisition times by 63% still produces images with an acceptable diagnostic accuracy but should be reserved for specific patients. • CSAI may be implemented to scan at a higher resolution compared to standard CS images without increasing acquisition times.
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Affiliation(s)
- Sarah C Foreman
- Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
| | - Jan Neumann
- Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany
| | - Jessie Han
- Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany
| | - Norbert Harrasser
- Department of Orthopaedic Surgery, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany
| | - Kilian Weiss
- Philips GmbH, Röntgenstrasse 22, 22335, Hamburg, Germany
| | - Johannes M Peeters
- Philips Healthcare, Veenpluis 4-6, Building QR-0.113, 5684, Best, PC, Netherlands
| | - Dimitrios C Karampinos
- Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany
| | - Marcus R Makowski
- Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany
| | - Alexandra S Gersing
- Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.,Department of Neuroradiology, University Hospital Munich (LMU), Marchioninistrasse 15, 81377, Munich, Germany
| | - Klaus Woertler
- Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany
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11
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Ueki W, Nishii T, Umehara K, Ota J, Higuchi S, Ohta Y, Nagai Y, Murakawa K, Ishida T, Fukuda T. Generative adversarial network-based post-processed image super-resolution technology for accelerating brain MRI: comparison with compressed sensing. Acta Radiol 2022; 64:336-345. [PMID: 35118883 DOI: 10.1177/02841851221076330] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND It is unclear whether deep-learning-based super-resolution technology (SR) or compressed sensing technology (CS) can accelerate magnetic resonance imaging (MRI) . PURPOSE To compare SR accelerated images with CS images regarding the image similarity to reference 2D- and 3D gradient-echo sequence (GRE) brain MRI. MATERIAL AND METHODS We prospectively acquired 1.3× and 2.0× faster 2D and 3D GRE images of 20 volunteers from the reference time by reducing the matrix size or increasing the CS factor. For SR, we trained the generative adversarial network (GAN), upscaling the low-resolution images to the reference images with twofold cross-validation. We compared the structural similarity (SSIM) index of accelerated images to the reference image. The rate of incorrect answers of a radiologist discriminating faster and reference image was used as a subjective image similarity (ISM) index. RESULTS The SR demonstrated significantly higher SSIM than the CS (SSIM=0.9993-0.999 vs. 0.9947-0.9986; P < 0.001). In 2D GRE, it was challenging to discriminate the SR image from the reference image, compared to the CS (ISM index 40% vs. 17.5% in 1.3×; P = 0.039 and 17.5% vs. 2.5% in 2.0×; P = 0.034). In 3D GRE, the CS revealed a significantly higher ISM index than the SR (22.5% vs. 2.5%; P = 0.011) in 2.0 × faster images. However, the ISM index was identical for the 2.0× CS and 1.3× SR (22.5% vs. 27.5%; P = 0.62) with comparable time costs. CONCLUSION The GAN-based SR outperformed CS in image similarity with 2D GRE for MRI acceleration. In addition, CS was more advantageous in 3D GRE than SR.
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Affiliation(s)
- Wataru Ueki
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Tatsuya Nishii
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Kensuke Umehara
- Medical Informatics Section, QST Hospital, National Institutes for Quantum Science and Technology, Chiba, Japan
- Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Junko Ota
- Medical Informatics Section, QST Hospital, National Institutes for Quantum Science and Technology, Chiba, Japan
- Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Satoshi Higuchi
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Yasutoshi Ohta
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Yasuhiro Nagai
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Keizo Murakawa
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Takayuki Ishida
- Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Tetsuya Fukuda
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
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Comparison of compressed sensing-sensitivity encoding (CS-SENSE) accelerated 3D T2W TSE sequence versus conventional 3D and 2D T2W TSE sequences in rectal cancer: a prospective study. Abdom Radiol (NY) 2022; 47:3660-3670. [PMID: 35997800 PMCID: PMC9560929 DOI: 10.1007/s00261-022-03636-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 07/21/2022] [Accepted: 07/26/2022] [Indexed: 01/18/2023]
Abstract
PURPOSE This study aimed to evaluate the image quality and diagnostic value of compressed sensing-sensitivity encoding (CS-SENSE) accelerated 3-dimensional (3D) T2-weighted turbo spin-echo (T2W TSE) sequence in patients with rectal cancer compared with conventional 3D and 2-dimensional (2D) sequences. METHODS A total of 54 patients who underwent the above three sequences were enrolled. Two radiologists independently reviewed the image quality using an ordinal 5-point Likert scale. The quantitative measurement was performed to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The diagnostic value was assessed using TN staging, extramural vascular invasion and mesorectal fascia status. Friedman and McNemar's tests were applied for comparative analysis. RESULTS Forty-two patients were successfully included. Compared with 3D and 2D sequences, the CS-SENSE 3D sequence speeded up by 39% and 23%, respectively. The edge sharpness of CS-SENSE 3D images was similar to that of 3D and 2D images. The noise of CS-SENSE 3D images was comparable to that of 3D images but higher than that of 2D images. The SNRtumor and SNRrectal wall of CS-SENSE 3D images were considerably lower than those of 3D and 2D images. The CNR of CS-SENSE 3D images was similar to that of 3D images but lower than that of 2D images. However, no considerable differences were noted in diagnostic value among the three sequences. CONCLUSIONS CS-SENSE 3D T2 sequence provided comparable diagnostic performance, with substantially reduced imaging time and no significant sacrifices in image quality. This technique may serve as a reliable tool for evaluating rectal cancer.
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Combined Compressed Sensing and SENSE to Enhance Radiation Therapy Magnetic Resonance Imaging Simulation. Adv Radiat Oncol 2021; 7:100799. [PMID: 34765805 PMCID: PMC8569477 DOI: 10.1016/j.adro.2021.100799] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/06/2021] [Accepted: 08/15/2021] [Indexed: 11/23/2022] Open
Abstract
Purpose To assess the effect of a combination of compressed sensing and SENSitivity Encoding (SENSE) acceleration techniques on radiation therapy magnetic resonance imaging (MRI) simulation workflows. Methods and Materials Thirty-seven acquisitions were performed with both SENSE-only (SENSE) and combined compressed sensing and SENSE (CS) techniques in 24 patients receiving radiation therapy MRI simulation for a wide range of disease sites. The anatomic field of view prescription and image resolution were identical for both SENSE and CS acquisitions to ensure fair comparison. The acquisition time of all images was recorded to assess time savings. For each image pair, image quality, and ability to contour were assessed by 2 radiation oncologists. Aside from direct image pair comparisons, the feasibility of using CS to improve MRI simulation protocols by increasing image resolution, field of view, and reducing motion artifacts was also evaluated. Results CS resulted in an average reduction of 27% in scan time with negligible changes in image quality and the ability to contour structures for RT treatment planning compared with SENSE. Physician scoring of image quality and ability to contour shows that while SENSE still has slightly better image quality compared with CS, this observed difference in image quality did not affect the ability to contour. In addition, the higher acceleration capability of CS enabled use of superior-inferior direction phase encoding in a sagittal 3-dimensional T2-weighted scan for substantially improved visibility of the prostatic urethra, which eliminated the need for a Foley catheter in most patients. Conclusions The combination of compressed sensing and parallel imaging resulted in marked improvements in the MRI Simulation workflow. The scan time was reduced without significantly affecting image quality in the context of ability to contour. The acceleration capabilities allowed for increased image resolution under similar scanning times as well as significantly improved urethra visualization in prostate simulations.
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Herrmann J, Koerzdoerfer G, Nickel D, Mostapha M, Nadar M, Gassenmaier S, Kuestner T, Othman AE. Feasibility and Implementation of a Deep Learning MR Reconstruction for TSE Sequences in Musculoskeletal Imaging. Diagnostics (Basel) 2021; 11:diagnostics11081484. [PMID: 34441418 PMCID: PMC8394583 DOI: 10.3390/diagnostics11081484] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/23/2021] [Accepted: 07/31/2021] [Indexed: 01/15/2023] Open
Abstract
Magnetic Resonance Imaging (MRI) of the musculoskeletal system is one of the most common examinations in clinical routine. The application of Deep Learning (DL) reconstruction for MRI is increasingly gaining attention due to its potential to improve the image quality and reduce the acquisition time simultaneously. However, the technology has not yet been implemented in clinical routine for turbo spin echo (TSE) sequences in musculoskeletal imaging. The aim of this study was therefore to assess the technical feasibility and evaluate the image quality. Sixty examinations of knee, hip, ankle, shoulder, hand, and lumbar spine in healthy volunteers at 3 T were included in this prospective, internal-review-board-approved study. Conventional (TSES) and DL-based TSE sequences (TSEDL) were compared regarding image quality, anatomical structures, and diagnostic confidence. Overall image quality was rated to be excellent, with a significant improvement in edge sharpness and reduced noise compared to TSES (p < 0.001). No difference was found concerning the extent of artifacts, the delineation of anatomical structures, and the diagnostic confidence comparing TSES and TSEDL (p > 0.05). Therefore, DL image reconstruction for TSE sequences in MSK imaging is feasible, enabling a remarkable time saving (up to 75%), whilst maintaining excellent image quality and diagnostic confidence.
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Affiliation(s)
- Judith Herrmann
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany; (J.H.); (S.G.); (T.K.)
| | - Gregor Koerzdoerfer
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany; (G.K.); (D.N.)
| | - Dominik Nickel
- MR Applications Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany; (G.K.); (D.N.)
| | - Mahmoud Mostapha
- Digital Technology & Innovation, Siemens Medical Solutions USA, Inc., Princeton, NJ 08540, USA; (M.M.); (M.N.)
| | - Mariappan Nadar
- Digital Technology & Innovation, Siemens Medical Solutions USA, Inc., Princeton, NJ 08540, USA; (M.M.); (M.N.)
| | - Sebastian Gassenmaier
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany; (J.H.); (S.G.); (T.K.)
| | - Thomas Kuestner
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany; (J.H.); (S.G.); (T.K.)
| | - Ahmed E. Othman
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany; (J.H.); (S.G.); (T.K.)
- Department of Neuroradiology, University Medical Center, 55131 Mainz, Germany
- Correspondence: ; Tel.: +49-7071-29-86676; Fax: +49-7071-29-5845
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Probst FA, Burian E, Malenova Y, Lyutskanova P, Stumbaum MJ, Ritschl LM, Kronthaler S, Karampinos D, Probst M. Geometric accuracy of magnetic resonance imaging-derived virtual 3-dimensional bone surface models of the mandible in comparison to computed tomography and cone beam computed tomography: A porcine cadaver study. Clin Implant Dent Relat Res 2021; 23:779-788. [PMID: 34318580 DOI: 10.1111/cid.13033] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 04/29/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Providing accurate 3-dimensional virtual bone surface models is a prerequisite for virtual surgical planning and additive manufacturing in craniomaxillofacial surgery. For this purpose, magnetic resonance imaging (MRI) may be a radiation-free alternative to computed tomography (CT) and cone beam computed tomography (CBCT). PURPOSE The aim of this study was to assess the geometric accuracy of 3-dimensional T1-weighted MRI-derived virtual bone surface models of the mandible in comparison to CT and CBCT. MATERIALS AND METHODS Specimens of the mandible from porcine cadavers were scanned with (1) a 3-dimensional T1-weighted MRI sequence (0.6 mm isotropic voxel) optimized for bone imaging, (2) CT, and (3) CBCT. Cortical mandibular structures (n = 10) were segmented using semiautomated and manual techniques. Imaging-based virtual 3-dimensional models were aligned with a high-resolution optical 3-dimensional surface scan of the dissected bone (=ground truth) and global geometric deviations were calculated (mean surface distance [MSD]/root-mean-square distance [RMSD]). Agreement between the imaging modalities was assessed by equivalence testing and Bland-Altman analysis. RESULTS Intra- and inter-rater agreement was on a high level for all modalities. Global geometric deviations (MSD/RMSD) between optical scans and imaging modalities were 0.225 ± 0.020 mm/0.345 ± 0.074 mm for CT, 0.280 ± 0.067 mm/0.371 ± 0.074 mm for MRI, and 0.352 ± 0.076 mm/0.454 ± 0.071 mm for CBCT. All imaging modalities were statistically equivalent within an equivalence margin of ±0.3 mm, and Bland-Altman analysis indicated high agreement as well. CONCLUSIONS The results of this study indicate that the accuracy and reliability of MRI-derived virtual 3-dimensional bone surface models is equal to CT and CBCT. MRI may be considered as a reliable alternative to CT and CBCT in computer-assisted craniomaxillofacial surgery.
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Affiliation(s)
- Florian Andreas Probst
- Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, University Hospital, LMU München, Munich, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Yoana Malenova
- Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, University Hospital, LMU München, Munich, Germany
| | - Plamena Lyutskanova
- Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, University Hospital, LMU München, Munich, Germany
| | | | - Lucas Maximilian Ritschl
- Department of Oral and Maxillofacial Surgery, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Monika Probst
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
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Bratke G, Rau R, Kabbasch C, Zäske C, Maintz D, Haneder S, Große Hokamp N, Persigehl T, Siedek F, Weiss K. Speeding up the clinical routine: Compressed sensing for 2D imaging of lumbar spine disc herniation. Eur J Radiol 2021; 140:109738. [PMID: 33945923 DOI: 10.1016/j.ejrad.2021.109738] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 04/20/2021] [Accepted: 04/23/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE Increasing economic pressure and patient demands for comfort require an ever-increasing acceleration of scan times without compromising diagnostic certainty. This study tested the new acceleration technique Compressed SENSE (CS-SENSE) as well as different reconstruction methods for the lumbar spine. METHODS In this prospective study, 10 volunteers and 14 patients with lumbar disc herniation were scanned using a sagittal 2D T2 turbo spin echo (TSE) sequence applying different acceleration factors of SENSE and CS-SENSE. Gradient echo (GRE), autocalibration (CS-Auto) and TSE prescans were tested for reconstruction. Images were analysed by two readers regarding anatomical delineation, diagnostic certainty (for patients only) and image quality as well as objectively calculating the root mean square error (RMSE), structural similarity index (SSIM), SNR and CNR. The Friedman test and Chi-squared were used for ordinal, ANOVA for repeated measurements and Tukey Kramer test for continuous data. Cohen's kappawas calculated for interreader reliability. RESULTS CS-SENSE outperformed SENSE and CS-Auto regarding RMSE (e.g. CS-SENSE 1.5: 43.03 ± 11.64 versus SENSE 1.5: 80.41 ± 17.66; p = 0.0038) and SSIM as well as in the subjective rating for CS-SENSE 3 TSE. In the patient setting image quality was unchanged in all subjective criteria up to CS-SENSE 3 TSE (all p > 0.05) compared to standard T2 with 43 % less scan time while the GRE prescan only allowed a reduction of 32 %. CONCLUSION Combining a TSE prescan with CS-SENSE enables significant scan time reductions with unchanged ratings for lumbar spine disc herniation making this superior to the currently used SENSE acceleration or GRE reconstructions.
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Affiliation(s)
- Grischa Bratke
- Department of Radiology, University of Cologne, Cologne, Germany.
| | - Robert Rau
- Department of Radiology, Kantonsspital Graubünden, Chur, Switzerland
| | | | - Charlotte Zäske
- Department of Radiology, University of Cologne, Cologne, Germany
| | - David Maintz
- Department of Radiology, University of Cologne, Cologne, Germany
| | - Stefan Haneder
- Department of Radiology, University of Cologne, Cologne, Germany
| | | | | | - Florian Siedek
- Department of Radiology, University of Cologne, Cologne, Germany
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Rapid Musculoskeletal MRI in 2021: Clinical Application of Advanced Accelerated Techniques. AJR Am J Roentgenol 2021; 216:718-733. [DOI: 10.2214/ajr.20.22902] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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18
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Tomita H, Deguchi Y, Fukuchi H, Fujikawa A, Kurihara Y, Kitsukawa K, Mimura H, Kobayashi Y. Combination of compressed sensing and parallel imaging for T2-weighted imaging of the oral cavity in healthy volunteers: comparison with parallel imaging. Eur Radiol 2021; 31:6305-6311. [PMID: 33517492 DOI: 10.1007/s00330-021-07699-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 12/08/2020] [Accepted: 01/19/2021] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Compressed sensing (CS) and parallel imaging (PI) are magnetic resonance (MR) imaging acceleration techniques. Image quality of two-dimensional fast spin echo imaging of the oral cavity using CS or combined CS and PI has not been evaluated. The aim of this study was to compare the acquisition time and image quality between T2-weighted imaging (T2WI) with CS and PI (CSPI-T2WI) and T2WI with PI (PI-T2WI) of the oral cavity. MATERIALS AND METHODS Twenty healthy volunteers who underwent CSPI-T2WI and PI-T2WI of the oral cavity on a 3 T MR scanner were enrolled in the study. Contrast ratios of fat/muscle and bone/muscle on CSPI-T2WI and PI-T2WI were measured. Overall image quality, 4 kinds of artifacts, and visualization of 18 anatomical structures were independently evaluated by two radiologists with grading scales. The quantitative and qualitative measurements were compared between CSPI-T2WI and PI-T2WI by using the Wilcoxon signed-rank test. RESULTS Mean acquisition time of CSPI-T2WI and PI-T2WI was 72 s and 136 s, respectively (p < .001). CSPI-T2WI showed a significantly higher contrast ratio of fat/muscle than PI-T2WI (p < .01). There were no significant differences in the overall image quality, artifacts, and visualization of anatomical structures between CSPI-T2WI and PI-T2WI. CONCLUSIONS CSPI-T2WI of the oral cavity in healthy volunteers can provide a reduction in acquisition time without impaired image quality compared to PI-T2WI. KEY POINTS • The acquisition time of T2WI with the combined CS and PI provided a 47% reduction in acquisition time compared with T2WI with PI. • T2WI with the combined CS and PI did not show impaired image quality compared with T2WI with PI. • Combined CS and PI can be a useful technology to evaluate the oral cavity with high-speed acquisition.
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Affiliation(s)
- Hayato Tomita
- Department of Radiology, St. Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan.
| | - Yuki Deguchi
- Department of Radiology, St. Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan
| | - Hirofumi Fukuchi
- Department of Radiology, St. Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan
| | - Atsuko Fujikawa
- Department of Radiology, St. Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan
| | - Yoshiko Kurihara
- Department of Radiology, Machida Municipal Hospital, 2-15-41 Asahi-cho, Machida, Tokyo, 194-0023, Japan
| | - Kaoru Kitsukawa
- Department of Radiology, St. Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan
| | - Hidefumi Mimura
- Department of Radiology, St. Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan
| | - Yasuyuki Kobayashi
- Department of Advanced Biomedical Imaging Informatics, St. Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan
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Kronthaler S, Rahmer J, Börnert P, Makowski MR, Schwaiger BJ, Gersing AS, Karampinos DC. Trajectory correction based on the gradient impulse response function improves high-resolution UTE imaging of the musculoskeletal system. Magn Reson Med 2020; 85:2001-2015. [PMID: 33251655 DOI: 10.1002/mrm.28566] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 09/30/2020] [Accepted: 10/02/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE UTE sequences typically acquire data during the ramping up of the gradient fields, which makes UTE imaging prone to eddy current and system delay effects. The purpose of this work was to use a simple gradient impulse response function (GIRF) measurement to estimate the real readout gradient waveform and to demonstrate that precise knowledge of the gradient waveform is important in the context of high-resolution UTE musculoskeletal imaging. METHODS The GIRF was measured using the standard hardware of a 3 Tesla scanner and applied on 3D radial UTE data (TE: 0.14 ms). Experiments were performed on a phantom, in vivo on a healthy knee, and in vivo on patients with spine fractures. UTE images were reconstructed twice, first using the GIRF-corrected gradient waveforms and second using nominal-corrected waveforms, correcting for the low-pass filter characteristic of the gradient chain. RESULTS Images reconstructed with the nominal-corrected gradient waveforms exhibited blurring and showed edge artifacts. The blurring and the edge artifacts were reduced when the GIRF-corrected gradient waveforms were used, as shown in single-UTE phantom scans and in vivo dual-UTE gradient-echo scans in the knee. Further, the importance of the GIRF-based correction was indicated in UTE images of the lumbar spine, where thin bone structures disappeared when the nominal correction was employed. CONCLUSION The presented GIRF-based trajectory correction method using standard scanner hardware can improve the quality of high-resolution UTE musculoskeletal imaging.
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Affiliation(s)
- Sophia Kronthaler
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | | | | | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Benedikt J Schwaiger
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Alexandra S Gersing
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
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20
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Li G, Wu D, Xu Z, Zuo X, Li X, Chang S, Dai Y. Evaluation of an accelerated 3D modulated flip-angle technique in refocused imaging with an extended echo-train sequence with compressed sensing for imaging of the knee: comparison with routine 2D MRI sequences. Clin Radiol 2020; 76:158.e13-158.e18. [PMID: 33250173 DOI: 10.1016/j.crad.2020.10.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 10/28/2020] [Indexed: 11/24/2022]
Abstract
AIM To accelerate the acquisition of high-resolution magnetic resonance imaging (MRI) by using the three-dimensional (3D) matrix sequence with compressed sensing and to compare it with conventional two-dimensional (2D) proton-density (PD) and fast spin-echo (FSE) sequences. MATERIALS AND METHODS 3D matrix, 2D FSE, and PD sequences were acquired from 68 participants using 3 T magnetic resonance imaging (MRI). Two radiologists scored image quality independently on a four-point scale. The structural similarity index (SSIM), and signal- (SNRs) and contrast-to-noise ratios (CNRs) of different anatomical structures of the knee were assessed and compared between sequences using Wilcoxon signed-rank tests and Cohen's kappa. RESULTS The median acquisition time reduction was 44.5%. There was a substantial to perfect agreement for the rating between the 3D matrix FSE and 2D FSE or PD sequences when evaluating cartilage, subchondral bone, and ligaments (κ=0.783-872, p>0.05). The mean SSIM values between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences was 0.994 and 0.971, respectively, which are acceptable. No significant differences were found in SNR between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences, even though the SNR appeared to be higher on routine 2D sequences. The CNR of subchondral bone-meniscus, subchondral bone-joint fluid, and meniscus-joint fluid did not differentiate significantly between the 3D matrix sequence and routine 2D sequences. CONCLUSIONS 3D matrix reduced the acquisition time in routine clinical knee MRI without the loss in image quality, SNR, and CNR.
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Affiliation(s)
- G Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - D Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, Shanghai, China
| | - Z Xu
- Xinzhuang Community Health Center, Shanghai, China
| | - X Zuo
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - X Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - S Chang
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| | - Y Dai
- Central Research Institute, United Imaging Healthcare, Shanghai, China
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21
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Ueda T, Ohno Y, Yamamoto K, Iwase A, Fukuba T, Hanamatsu S, Obama Y, Ikeda H, Ikedo M, Yui M, Murayama K, Toyama H. Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice. Eur J Radiol 2020; 134:109430. [PMID: 33276249 DOI: 10.1016/j.ejrad.2020.109430] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 11/03/2020] [Accepted: 11/16/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic MRI. METHOD Thirty consecutive patients with women's pelvic diseases (mean age 50 years) underwent T2-weighted imaging using Compressed SPEEDER as well as conventional SPEEDER reconstructed with and without AiCE. The examination times were recorded, and signal-to-noise ratio (SNR) was calculated for every patient. Moreover, overall image quality was assessed using a 5-point scoring system, and final scores for all patients were determined by consensus of two readers. Mean examination time, SNR and overall image quality were compared among the four data sets by Wilcoxon signed-rank test. RESULTS Examination times for Compressed SPEEDER with and without AiCE were significantly shorter than those for conventional SPEEDER with and without AiCE (with AiCE: p < 0.0001, without AiCE: p < 0.0001). SNR of Compressed SPEEDER and of SPEEDER with AiCE was significantly superior to that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER, p = 0.01; vs. SPEEDER, p = 0.009). Overall image quality of Compressed SPEEDER with AiCE and of SPEEDER with and without AiCE was significantly higher than that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER with AiCE, p < 0.0001; vs. SPEEDER with AiCE, p < 0.0001; SPEEDER without AiCE, p = 0.0003). CONCLUSION Image quality and shorten examination time for T2-weighted imaging in women's pelvic MRI can be significantly improved by using Compressed SPEEDER with AiCE in comparison with conventional SPEEDER, although other sequences were not tested.
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Affiliation(s)
- Takahiro Ueda
- Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Yoshiharu Ohno
- Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan; Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Kaori Yamamoto
- Canon Medical Systems Corporation, 1385, Shimoishigami, Otawara, Tochigi, 324-0036, Japan.
| | - Akiyoshi Iwase
- Department of Radiology, Fujita Health University Hospital, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Takashi Fukuba
- Department of Radiology, Fujita Health University Hospital, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Yuki Obama
- Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Masato Ikedo
- Canon Medical Systems Corporation, 1385, Shimoishigami, Otawara, Tochigi, 324-0036, Japan.
| | - Masao Yui
- Canon Medical Systems Corporation, 1385, Shimoishigami, Otawara, Tochigi, 324-0036, Japan.
| | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University, School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
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Iuga AI, Abdullayev N, Weiss K, Haneder S, Brüggemann-Bratke L, Maintz D, Rau R, Bratke G. Accelerated MRI of the knee. Quality and efficiency of compressed sensing. Eur J Radiol 2020; 132:109273. [DOI: 10.1016/j.ejrad.2020.109273] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 08/26/2020] [Accepted: 09/06/2020] [Indexed: 10/23/2022]
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Baur O, Den Harder J, Hemke R, Farid FM, Smithuis F, De Weerdt E, Nederveen A, Maas M. The road to optimal acceleration of Dixon imaging and quantitative T2-mapping in the ankle using compressed sensing and parallel imaging. Eur J Radiol 2020; 132:109295. [DOI: 10.1016/j.ejrad.2020.109295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 09/11/2020] [Accepted: 09/17/2020] [Indexed: 11/26/2022]
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Probst FA, Schweiger J, Stumbaum MJ, Karampinos D, Burian E, Probst M. Magnetic resonance imaging based
computer‐guided
dental implant surgery—A clinical pilot study. Clin Implant Dent Relat Res 2020; 22:612-621. [DOI: 10.1111/cid.12939] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 06/23/2020] [Accepted: 07/15/2020] [Indexed: 12/28/2022]
Affiliation(s)
- Florian Andreas Probst
- Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery University Hospital, LMU Munich Munich Germany
| | - Josef Schweiger
- Department of Prosthetic Dentistry University Hospital, LMU Munich Munich Germany
| | | | - Dimitrios Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar Technical University Munich Munich Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar Technical University Munich Munich Germany
| | - Monika Probst
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar Technical University Munich Munich Germany
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Yokota Y, Takeda C, Kidoh M, Oda S, Aoki R, Ito K, Morita K, Haraoka K, Yamashita Y, Iizuka H, Kato S, Tsujita K, Ikeda O, Yamashita Y, Utsunomiya D. Effects of Deep Learning Reconstruction Technique in High-Resolution Non-contrast Magnetic Resonance Coronary Angiography at a 3-Tesla Machine. Can Assoc Radiol J 2020; 72:120-127. [DOI: 10.1177/0846537119900469] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Purpose: To evaluate the effects of deep learning reconstruction (DLR) in qualitative and quantitative image quality of non-contrast magnetic resonance coronary angiography (MRCA). Methods: Ten healthy volunteers underwent conventional MRCA (C-MRCA) and high-resolution (HR) MRCA on a 3T magnetic resonance imaging with a voxel size of 1.8 × 1.1 × 1.7 mm3 and 1.8 × 0.6 × 1.0 mm3, respectively, for C-MRCA and HR-MRCA. High-resolution magnetic resonance coronary angiography was also reconstructed with the DLR technique (DLR-HR-MRCA). We compared the contrast-to-noise ratio (CNR) and visual evaluation scores for vessel sharpness and traceability of proximal and distal coronary vessels on a 4-point scale among 3 image series. Results: The vascular CNR value on the C-MRCA and the DLR-HR-MRCA was significantly higher than that on the HR-MRCA in the proximal and distal coronary arteries (13.9 ± 6.4, 11.3 ± 4.4, and 7.8 ± 2.6 for C-MRCA, DLR-HR-MRCA, and HR-MRCA, P < .05, respectively). Mean visual evaluation scores for the vessel sharpness and traceability of proximal and distal coronary vessels were significantly higher on the HR-DLR-MRCA than the C-MRCA ( P < .05, respectively). Conclusion: Deep learning reconstruction significantly improved the CNR of coronary arteries on HR-MRCA, resulting in both higher visual image quality and better vessel traceability compared with C-MRCA.
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Affiliation(s)
- Yasuhiro Yokota
- Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto-shi, Japan
| | - Chika Takeda
- Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama-shi, Japan
| | - Masafumi Kidoh
- Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto-shi, Japan
| | - Seitaro Oda
- Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto-shi, Japan
| | - Ryo Aoki
- Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama-shi, Japan
| | - Kenichi Ito
- Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama-shi, Japan
| | - Kosuke Morita
- Central Radiology, Kumamoto University Hospital, Kumamoto-shi, Japan
| | - Kentaro Haraoka
- MRI Systems Division, Canon Medical Systems Corporation, Kawasaki-shi, Japan
| | - Yuichi Yamashita
- MRI Systems Division, Canon Medical Systems Corporation, Kawasaki-shi, Japan
| | - Hitoshi Iizuka
- Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama-shi, Japan
| | - Shingo Kato
- Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama-shi, Japan
- Cardiology, Kanagawa Cardiovascular and Respiratory Center, Yokohama-shi, Japan
| | - Kenichi Tsujita
- Cardiovascular Medicine, Faculty of Life Sciences, Kumamoto University, Kumamoto-shi, Japan
| | - Osamu Ikeda
- Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto-shi, Japan
| | - Yasuyuki Yamashita
- Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto-shi, Japan
| | - Daisuke Utsunomiya
- Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama-shi, Japan
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Sartoretti T, Sartoretti E, Wyss M, Schwenk Á, van Smoorenburg L, Eichenberger B, Najafi A, Binkert C, Becker AS, Sartoretti-Schefer S. Compressed SENSE accelerated 3D T1w black blood turbo spin echo versus 2D T1w turbo spin echo sequence in pituitary magnetic resonance imaging. Eur J Radiol 2019; 120:108667. [PMID: 31550639 DOI: 10.1016/j.ejrad.2019.108667] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 08/23/2019] [Accepted: 09/08/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE To compare image quality between a 2D T1w turbo spin echo (TSE) sequence and a Compressed SENSE accelerated 3D T1w black blood TSE sequence (equipped with a black blood prepulse for blood signal suppression) in pre- and postcontrast imaging of the pituitary and to assess scan time reductions. METHODS AND MATERIALS For this retrospective study, 56 patients underwent pituitary MR imaging at 3T. 28 patients were scanned with the 2D- and 28 patients with the accelerated 3D sequence. Two board certified neuroradiologists independently evaluated 13 qualitative image features (12 features on postcontrast- and 1 feature on precontrast images).SNR and CNR measurements were obtained. Interreader agreement was assessed with the intraclass correlation coefficient while differences in scores were assessed with exact Wilcoxon rank sum tests. RESULTS The interreader agreement ranged from fair (visibility of the ophthalmic nerve, ICC = 0.57) to excellent (presence and severity of pulsation artefacts, ICC = 0.97). The Compressed SENSE accelerated 3D sequence outperformed the 2D sequence in terms of "overall image quality" (median: 4 versus 3, p = 0.04) and "presence and severity of pulsation artefacts" (median: 0 versus 1, p < 0.001). There were no significant differences in any other qualitative and quantitative (SNR, CNR) image quality features. Scan time was reduced by 03:53 min (33.1%) by replacing the 2D with the 3D sequence. CONCLUSION The Compressed SENSE accelerated 3D T1w black blood TSE sequence is a reliable alternative for the standard 2D sequence in pituitary imaging. The black blood prepulse may aid in suppression of pulsation artefacts.
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Affiliation(s)
- Thomas Sartoretti
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Elisabeth Sartoretti
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Michael Wyss
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland; Philips Healthsystems, Zürich, Switzerland.
| | - Árpád Schwenk
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Luuk van Smoorenburg
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Barbara Eichenberger
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Arash Najafi
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Christoph Binkert
- Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
| | - Anton S Becker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zürich, University of Zürich, Raemistrasse 100, CH-8091, Zürich, Switzerland; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
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