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Wang L, Meng FJ, Jin YH, Wu LQ, Tang RY, Xu KH, Guo Y, Mao JJ, Ding JP, Li J. Effects of probiotic supplementation on 12 min run performance, mood management, body composition and gut microbiota in amateur marathon runners: A double-blind controlled trial. J Exerc Sci Fit 2024; 22:297-304. [PMID: 38706951 PMCID: PMC11066675 DOI: 10.1016/j.jesf.2024.04.004] [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: 10/22/2023] [Revised: 04/20/2024] [Accepted: 04/23/2024] [Indexed: 05/07/2024] Open
Abstract
Background Probiotic supplementation has a positive effect on endurance exercise performance and body composition in athletes, but the underlying mechanisms remain unclear. Gut microbiota can provide measurable markers of immune function in athletes, and microbial composition analysis may be sensitive enough to detect stress and metabolic disorders caused by exercise. Methods Nineteen healthy active amateur marathon runners (15 male and 4 female) with a mean age of 29.11 years volunteered to participate in this double-blind controlled study. Based on the performance of the Cooper 12-min running test (CRT), the participants were allocated into two groups to receive either a probiotic formulation comprising lactobacillus acidophilus and bifidobacterium longum (n = 10) or placebo containing maltodextrin (n = 9) for five weeks. Consistency of diet and exercise was ensured throughout the experimental period. Before and after the intervention, all participants were assessed for CRT, emotional stability and gastrointestinal symptoms, gut microbiota composition, body composition and magnetic resonance imaging (MRI) indicators of skeletal muscle microcirculation. Results Compared to before the intervention, the probiotics group showed an increase in CRT score (2.88 ± 0.57 vs 3.01 ± 0.60 km, P<0.05), significant improvement in GSRS and GIQLI (9.20 ± 4.64 vs 7.40 ± 3.24, 118.90 ± 12.30 vs 127.50 ± 9.85, P<0.05), while these indicators remained unchanged in the control group, with a significant time-group interaction effect on gastrointestinal symptoms. Additionally, some MRI metabolic cycling indicators of the thigh skeletal muscle also changed in the probiotics group (P<0.05). Regarding microbiota abundance, the probiotics group exhibited a significant increase in the abundance of beneficial bacteria and a significant decrease in the abundance of harmful bacteria post-intervention (P<0.05). Conclusion As a sports nutritional supplement, probiotics have the potential to improve athletic performance by optimizing the balance of gut microbiota, alleviating gastrointestinal symptoms.
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Affiliation(s)
- Le Wang
- Department of Radiology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
- Women's Hospital School of Medicine Zhejiang University, China
| | - Fan-Jing Meng
- Department of Radiology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China
| | - Yi-Han Jin
- Department of Radiology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China
| | - Li-Qiang Wu
- Department of Radiology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China
| | - Ruo-Yu Tang
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China
| | - Kuang-Hui Xu
- Department of Radiology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China
| | - Yun Guo
- Department of Gastroenterology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Jun-Jie Mao
- School of Physical Education, Hangzhou Normal University, China
| | - Jian-Ping Ding
- Department of Radiology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China
- Hangzhou Institute of Sports Medicine for Marathon, China
| | - Jie Li
- Department of Radiology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China
- Hangzhou Institute of Sports Medicine for Marathon, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, China
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Hooijmans MT, Schlaffke L, Bolsterlee B, Schlaeger S, Marty B, Mazzoli V. Compositional and Functional MRI of Skeletal Muscle: A Review. J Magn Reson Imaging 2024; 60:860-877. [PMID: 37929681 PMCID: PMC11070452 DOI: 10.1002/jmri.29091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/09/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
Due to its exceptional sensitivity to soft tissues, MRI has been extensively utilized to assess anatomical muscle parameters such as muscle volume and cross-sectional area. Quantitative Magnetic Resonance Imaging (qMRI) adds to the capabilities of MRI, by providing information on muscle composition such as fat content, water content, microstructure, hypertrophy, atrophy, as well as muscle architecture. In addition to compositional changes, qMRI can also be used to assess function for example by measuring muscle quality or through characterization of muscle deformation during passive lengthening/shortening and active contractions. The overall aim of this review is to provide an updated overview of qMRI techniques that can quantitatively evaluate muscle structure and composition, provide insights into the underlying biological basis of the qMRI signal, and illustrate how qMRI biomarkers of muscle health relate to function in healthy and diseased/injured muscles. While some applications still require systematic clinical validation, qMRI is now established as a comprehensive technique, that can be used to characterize a wide variety of structural and compositional changes in healthy and diseased skeletal muscle. Taken together, multiparametric muscle MRI holds great potential in the diagnosis and monitoring of muscle conditions in research and clinical applications. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Melissa T Hooijmans
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Lara Schlaffke
- Department of Neurology BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Bart Bolsterlee
- Neuroscience Research Australia (NeuRA), Sydney, New South Wales, Australia
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, New South Wales, Australia
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Sarah Schlaeger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Benjamin Marty
- Institute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France
| | - Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, California, USA
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Medical Center, New York, New York, USA
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Forsting J, Rehmann R, Rohm M, Kocabas A, De Lorenzo A, Güttsches AK, Vorgerd M, Froeling M, Schlaffke L. Prospective longitudinal cohort study of quantitative muscle magnetic resonance imaging in a healthy control population. NMR IN BIOMEDICINE 2024:e5214. [PMID: 38982853 DOI: 10.1002/nbm.5214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 06/03/2024] [Accepted: 06/18/2024] [Indexed: 07/11/2024]
Abstract
Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m2) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time.
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Affiliation(s)
- Johannes Forsting
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Robert Rehmann
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
- Department of Neurology, Klinikum Dortmund, University Witten-Herdecke, Dortmund, Germany
| | - Marlena Rohm
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
- Heimer Institute for Muscle Research, BG-University Hospital Bergmannsheil, Bochum, Germany
| | - Abdulhadi Kocabas
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Alice De Lorenzo
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Anne-Katrin Güttsches
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Matthias Vorgerd
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
- Heimer Institute for Muscle Research, BG-University Hospital Bergmannsheil, Bochum, Germany
| | - Martijn Froeling
- Department of Radiology, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Lara Schlaffke
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
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Berry DB, Gordon JA, Adair V, Frank LR, Ward SR. From Voxels to Physiology: A Review of Diffusion Magnetic Resonance Imaging Applications in Skeletal Muscle. J Magn Reson Imaging 2024. [PMID: 39031753 DOI: 10.1002/jmri.29489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/03/2024] [Accepted: 06/03/2024] [Indexed: 07/22/2024] Open
Abstract
Skeletal muscle has a classic structure function relationship; both skeletal muscle microstructure and architecture are directly related to force generating capacity. Biopsy, the gold standard for evaluating muscle microstructure, is highly invasive, destructive to muscle, and provides only a small amount of information about the entire volume of a muscle. Similarly, muscle fiber lengths and pennation angles, key features of muscle architecture predictive of muscle function, are traditionally studied via cadaveric dissection. Noninvasive techniques such as diffusion magnetic resonance imaging (dMRI) offer quantitative approaches to study skeletal muscle microstructure and architecture. Despite its prevalence in applications for musculoskeletal research, clinical adoption is hindered by a lack of understanding regarding its sensitivity to clinically important biomarkers such as muscle fiber cross-sectional area. This review aims to elucidate how dMRI has been utilized to study skeletal muscle, covering fundamentals of muscle physiology, dMRI acquisition techniques, dMRI modeling, and applications where dMRI has been leveraged to noninvasively study skeletal muscle changes in response to disease, aging, injury, and human performance. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- David B Berry
- Department of Orthopaedic Surgery, University of California, San Diego, California, USA
| | - Joseph A Gordon
- Department of Orthopaedic Surgery, University of California, San Diego, California, USA
| | - Vincent Adair
- Department of Medicine, University of California, San Diego, California, USA
| | - Lawrence R Frank
- Center for Scientific Computation in Imaging, University of California, San Diego, California, USA
| | - Samuel R Ward
- Department of Orthopaedic Surgery, University of California, San Diego, California, USA
- Department of Radiology, University of California, San Diego, California, USA
- Department of Bioengineering, University of California, San Diego, California, USA
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Rubin EB, Schmidt AM, Koff MF, Kogan F, Gao K, Majumdar S, Potter H, Gold GE. Advanced MRI Approaches for Evaluating Common Lower Extremity Injuries in Basketball Players: Current and Emerging Techniques. J Magn Reson Imaging 2024; 59:1902-1913. [PMID: 37854004 DOI: 10.1002/jmri.29019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 10/20/2023] Open
Abstract
Magnetic resonance imaging (MRI) can provide accurate and non-invasive diagnoses of lower extremity injuries in athletes. Sport-related injuries commonly occur in and around the knee and can affect the articular cartilage, patellar tendon, hamstring muscles, and bone. Sports medicine physicians utilize MRI to evaluate and diagnose injury, track recovery, estimate return to sport timelines, and assess the risk of recurrent injury. This article reviews the current literature and describes novel developments of quantitative MRI tools that can further advance our understanding of sports injury diagnosis, prevention, and treatment while minimizing injury risk and rehabilitation time. Innovative approaches for enhancing the early diagnosis and treatment of musculoskeletal injuries in basketball players span a spectrum of techniques. These encompass the utilization of T2, T1ρ, and T2* quantitative MRI, along with dGEMRIC and Na-MRI to assess articular cartilage injuries, 3D-Ultrashort echo time MRI for patellar tendon injuries, diffusion tensor imaging for acute myotendinous injuries, and sagittal short tau inversion recovery and axial long-axis T1-weighted, and 3D Cube sequences for bone stress imaging. Future studies should further refine and validate these MR-based quantitative techniques while exploring the lifelong cumulative impact of basketball on players' knees. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Elka B Rubin
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Andrew M Schmidt
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Matthew F Koff
- Department of Radiology and Imaging, Hospital for Special Surgery, New York City, New York, USA
| | - Feliks Kogan
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Kenneth Gao
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Hollis Potter
- Department of Radiology and Imaging, Hospital for Special Surgery, New York City, New York, USA
| | - 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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Barbieri M, Hooijmans MT, Moulin K, Cork TE, Ennis DB, Gold GE, Kogan F, Mazzoli V. A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions. Sci Rep 2024; 14:8253. [PMID: 38589478 PMCID: PMC11002020 DOI: 10.1038/s41598-024-58812-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 04/03/2024] [Indexed: 04/10/2024] Open
Abstract
This work presents a deep learning approach for rapid and accurate muscle water T2 with subject-specific fat T2 calibration using multi-spin-echo acquisitions. This method addresses the computational limitations of conventional bi-component Extended Phase Graph fitting methods (nonlinear-least-squares and dictionary-based) by leveraging fully connected neural networks for fast processing with minimal computational resources. We validated the approach through in vivo experiments using two different MRI vendors. The results showed strong agreement of our deep learning approach with reference methods, summarized by Lin's concordance correlation coefficients ranging from 0.89 to 0.97. Further, the deep learning method achieved a significant computational time improvement, processing data 116 and 33 times faster than the nonlinear least squares and dictionary methods, respectively. In conclusion, the proposed approach demonstrated significant time and resource efficiency improvements over conventional methods while maintaining similar accuracy. This methodology makes the processing of water T2 data faster and easier for the user and will facilitate the utilization of the use of a quantitative water T2 map of muscle in clinical and research studies.
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Affiliation(s)
- Marco Barbieri
- Department of Radiology, Stanford University, Stanford, CA, USA.
| | - Melissa T Hooijmans
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Kevin Moulin
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tyler E Cork
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Daniel B Ennis
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Garry E Gold
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Feliks Kogan
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, CA, USA
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
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Torres-Velázquez M, Wille CM, Hurley SA, Kijowski R, Heiderscheit BC, McMillan AB. MRI radiomics for hamstring strain injury identification and return to sport classification: a pilot study. Skeletal Radiol 2024; 53:637-648. [PMID: 37728629 DOI: 10.1007/s00256-023-04449-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/31/2023] [Accepted: 08/31/2023] [Indexed: 09/21/2023]
Abstract
OBJECTIVE To determine if MRI-based radiomics from hamstring muscles are related to injury and if the features could be used to perform a time to return to sport (RTS) classification. We hypothesize that radiomics from hamstring muscles, especially T2-weighted and diffusion tensor imaging-based features, are related to injury and can be used for RTS classification. SUBJECTS AND METHODS MRI data from 32 athletes at the University of Wisconsin-Madison that sustained a hamstring strain injury were collected. Diffusion tensor imaging and T1- and T2-weighted images were processed, and diffusion maps were calculated. Radiomics features were extracted from the four hamstring muscles in each limb and for each MRI modality, individually. Feature selection was performed and multiple support vector classifiers were cross-validated to differentiate between involved and uninvolved limbs and perform binary (≤ or > 25 days) and multiclass (< 14 vs. 14-42 vs. > 42 days) classification of RTS. RESULT The combination of radiomics features from all diffusion tensor imaging and T2-weighted images provided the most accurate differentiation between involved and uninvolved limbs (AUC ≈ 0.84 ± 0.16). For the binary RTS classification, the combination of all extracted radiomics offered the most accurate classification (AUC ≈ 0.95 ± 0.15). While for the multiclass RTS classification, the combination of features from all the diffusion tensor imaging maps provided the most accurate classification (weighted one vs. rest AUC ≈ 0.81 ± 0.16). CONCLUSION This pilot study demonstrated that radiomics features from hamstring muscles are related to injury and have the potential to predict RTS.
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Affiliation(s)
- Maribel Torres-Velázquez
- Department of Biomedical Engineering, College of Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA.
| | - Christa M Wille
- Department of Biomedical Engineering, College of Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Orthopedics and Rehabilitation, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Badger Athletic Performance Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Samuel A Hurley
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Richard Kijowski
- Department of Radiology, New York University Grossman School of Medicine, New York University, New York, NY, 10016, USA
| | - Bryan C Heiderscheit
- Department of Biomedical Engineering, College of Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Orthopedics and Rehabilitation, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Badger Athletic Performance Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Alan B McMillan
- Department of Biomedical Engineering, College of Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
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Rauh SS, Suskens JJM, Monte JR, Smithuis F, Gurney-Champion OJ, Tol JL, Maas M, Nederveen AJ, Strijkers GJ, Hooijmans MT. Accelerated IVIM-corrected DTI in acute hamstring injury: towards a clinically feasible acquisition time. Eur Radiol Exp 2024; 8:38. [PMID: 38499843 PMCID: PMC10948680 DOI: 10.1186/s41747-024-00437-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 01/15/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND Intravoxel incoherent motion (IVIM)-corrected diffusion tensor imaging (DTI) potentially enhances return-to-play (RTP) prediction after hamstring injuries. However, the long scan times hamper clinical implementation. We assessed accelerated IVIM-corrected DTI approaches in acute hamstring injuries and explore the sensitivity of the perfusion fraction (f) to acute muscle damage. METHODS Athletes with acute hamstring injury received DTI scans of both thighs < 7 days after injury and at RTP. For a subset, DTI scans were repeated with multiband (MB) acceleration. Data from standard and MB-accelerated scans were fitted with standard and accelerated IVIM-corrected DTI approach using high b-values only. Segmentations of the injury and contralateral healthy muscles were contoured. The fitting methods as well as the standard and MB-accelerated scan were compared using linear regression analysis. For sensitivity to injury, Δ(injured minus healthy) DTI parameters between the methods and the differences between injured and healthy muscles were compared (Wilcoxon signed-rank test). RESULTS The baseline dataset consisted of 109 athletes (16 with MB acceleration); 64 of them received an RTP scan (8 with MB acceleration). Linear regression of the standard and high-b DTI fitting showed excellent agreement. With both fitting methods, standard and MB-accelerated scans were comparable. Δ(injured minus healthy) was similar between standard and accelerated methods. For all methods, all IVIM-DTI parameters except f were significantly different between injured and healthy muscles. CONCLUSIONS High-b DTI fitting with MB acceleration reduced the scan time from 11:08 to 3:40 min:s while maintaining sensitivity to hamstring injuries; f was not different between healthy and injured muscles. RELEVANCE STATEMENT The accelerated IVIM-corrected DTI protocol, using fewer b-values and MB acceleration, reduced the scan time to under 4 min without affecting the sensitivity of the quantitative outcome parameters to hamstring injuries. This allows for routine clinical monitoring of hamstring injuries, which could directly benefit injury treatment and monitoring. KEY POINTS • Combining high-b DTI-fitting and multiband-acceleration dramatically reduced by two thirds the scan time. • The accelerated IVIM-corrected DTI approaches maintained the sensitivity to hamstring injuries. • The IVIM-derived perfusion fraction was not sensitive to hamstring injuries.
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Affiliation(s)
- Susanne S Rauh
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Movement Sciences, Sports, Amsterdam, The Netherlands.
| | - Jozef J M Suskens
- Amsterdam Movement Sciences, Sports, Amsterdam, The Netherlands
- Department of Orthopedic Surgery and Sports Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Jithsa R Monte
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Frank Smithuis
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Johannes L Tol
- Department of Orthopedic Surgery and Sports Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Academic Center for Evidence Based Sports Medicine (ACES), Amsterdam, The Netherlands
- Amsterdam Collaboration for Health and Safety in Sports (ACHSS), AMC/VUmc IOC Research Center Amsterdam, Amsterdam, The Netherlands
| | - Mario Maas
- Amsterdam Movement Sciences, Sports, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Movement Sciences, Sports, Amsterdam, The Netherlands
| | - Melissa T Hooijmans
- Amsterdam Movement Sciences, Sports, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
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9
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Heiss R, Tol JL, Pogarell T, Roemer FW, Reurink G, Renoux J, Crema MD, Guermazi A. Imaging of muscle injuries in soccer. Skeletal Radiol 2023:10.1007/s00256-023-04514-1. [PMID: 37991553 DOI: 10.1007/s00256-023-04514-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 09/24/2023] [Accepted: 11/07/2023] [Indexed: 11/23/2023]
Abstract
Accurate diagnosis of muscle injuries is a challenge in everyday clinical practice and may have profound impact on the recovery and return-to-play decisions of professional athletes particularly in soccer. Imaging techniques such as ultrasound and magnetic resonance imaging (MRI), in addition to the medical history and clinical examination, make a significant contribution to the timely structural assessment of muscle injuries. The severity of a muscle injury determined by imaging findings has a decisive influence on therapy planning and affects prognosis. Imaging is of high importance when the diagnosis or grade of injury is unclear, when recovery is taking longer than expected, and when interventional or surgical management may be needed. This narrative review will discuss ultrasound and MRI for the assessment of sports-related muscle injuries in the context of soccer, including advanced imaging techniques, with the focus on the clinical relevance of imaging findings for the prediction of return to play.
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Affiliation(s)
- Rafael Heiss
- Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Johannes L Tol
- Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
- Department of Orthopedic Surgery and Sports Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands
- Musculoskeletal Health and Sports, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Tobias Pogarell
- Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Frank W Roemer
- Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Quantitative Imaging Center, Boston University School of Medicine, Boston, MA, USA
| | - Guus Reurink
- Musculoskeletal Health and Sports, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Jerome Renoux
- Institute of Sports Imaging, Sports Medicine Department, French National Institute of Sports (INSEP), Paris, France
| | - Michel D Crema
- Quantitative Imaging Center, Boston University School of Medicine, Boston, MA, USA
- Institute of Sports Imaging, Sports Medicine Department, French National Institute of Sports (INSEP), Paris, France
| | - Ali Guermazi
- Quantitative Imaging Center, Boston University School of Medicine, Boston, MA, USA.
- VA Boston Healthcare System, West Roxbury, MA, USA.
- Department of Radiology, VA Boston Healthcare System, 1400 VFW Parkway, Suite 1B106, West Roxbury, MA, 02132, USA.
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Hayashi D, Roemer FW, Tol JL, Heiss R, Crema MD, Jarraya M, Rossi I, Luna A, Guermazi A. Emerging Quantitative Imaging Techniques in Sports Medicine. Radiology 2023; 308:e221531. [PMID: 37552087 DOI: 10.1148/radiol.221531] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
This article describes recent advances in quantitative imaging of musculoskeletal extremity sports injuries, citing the existing literature evidence and what additional evidence is needed to make such techniques applicable to clinical practice. Compositional and functional MRI techniques including T2 mapping, diffusion tensor imaging, and sodium imaging as well as contrast-enhanced US have been applied to quantify pathophysiologic processes and biochemical compositions of muscles, tendons, ligaments, and cartilage. Dual-energy and/or spectral CT has shown potential, particularly for the evaluation of osseous and ligamentous injury (eg, creation of quantitative bone marrow edema maps), which is not possible with standard single-energy CT. Recent advances in US technology such as shear-wave elastography or US tissue characterization as well as MR elastography enable the quantification of mechanical, elastic, and physical properties of tissues in muscle and tendon injuries. The future role of novel imaging techniques such as photon-counting CT remains to be established. Eventual prediction of return to play (ie, the time needed for the injury to heal sufficiently so that the athlete can get back to playing their sport) and estimation of risk of repeat injury is desirable to help guide sports physicians in the treatment of their patients. Additional values of quantitative analyses, as opposed to routine qualitative analyses, still must be established using prospective longitudinal studies with larger sample sizes.
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Affiliation(s)
- Daichi Hayashi
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Frank W Roemer
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Johannes L Tol
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Rafael Heiss
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Michel D Crema
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Mohamed Jarraya
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Ignacio Rossi
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Antonio Luna
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
| | - Ali Guermazi
- From the Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass (D.H.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (D.H., F.W.R., M.D.C., A.G.); Department of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (F.W.R., R.H.); University of Amsterdam Academic Center for Evidence-based Sports Medicine, Amsterdam, the Netherlands (J.L.T.); Institute of Sports Imaging, French National Institute of Sports, Paris, France (M.D.C.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (M.J.); Centro Rossi, Buenos Aires, Argentina (I.R.); Department of Radiology, HT Medica, Jaén, Spain (A.L.); and Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, 1400 VFW Parkway, Suite 1B105, West Roxbury, MA 02132 (A.G.)
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11
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Monte JR, Hooijmans MT, Froeling M, Oudeman J, Tol JL, Strijkers GJ, Nederveen AJ, Maas M. Diffusion tensor imaging and quantitative T2 mapping to monitor muscle recovery following hamstring injury. NMR IN BIOMEDICINE 2023; 36:e4902. [PMID: 36630472 DOI: 10.1002/nbm.4902] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 01/07/2023] [Accepted: 01/09/2023] [Indexed: 06/15/2023]
Abstract
MRI examinations are accurate for diagnosing sports-related acute hamstring injuries. However, sensitive imaging methods for assessing recovery of these injuries are lacking. Diffusion tensor imaging (DTI) and quantitative T2 (qT2) mapping have both shown promise for assessing recovery of muscle micro trauma and exercise effects. The purpose of this study was to explore the potential of DTI and qT2 mapping for monitoring the muscle recovery processes after acute hamstring injury. In this prospective study, athletes with an acute hamstring injury underwent a 3-T MRI examination of the injured and contralateral hamstrings including DTI and qT2 measurements at three time points: (1) within 1 week after sustaining the injury, (2) 2 weeks after time point 1, and (3) return to play (RTP). A linear mixed model was used for time-effect analysis and paired t-tests for the detection of differences between injured and uninjured muscles. Forty-one athletes (age 27.8 ± 7 years; two females and 39 males) were included. Mean RTP time was 50 (range 12-169) days. A significant time effect was found for mean diffusivity, radial diffusivity, and the second and third eigenvalues (p ≤ 0.001) in the injured muscles. Fractional anisotropy (p = 0.40), first eigenvalue (p = 0.02), and qT2 (p = 0.61) showed no significant time effect. All DTI indices, except for fractional anisotropy, were significantly elevated compared with control muscles right after the injury (p < 0.001). Values normalized during the recovery period, with no significant differences between control and injured muscles at RTP (p values ranged from 0.08 to 0.51). Mean qT2 relaxation times in injured muscles were not significantly elevated compared with control muscles at any time point (p > 0.04). In conclusion, DTI can be used to monitor recovery after an acute hamstring injury. Future work should explore the potential of DTI indices to predict RTP and recovery times in athletes after an acute strain injury.
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Affiliation(s)
- Jithsa R Monte
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Melissa T Hooijmans
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Martijn Froeling
- Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jos Oudeman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
- Department of Orthopaedics, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Johannes L Tol
- Department of Orthopaedic Surgery, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
- Academic Center for Evidence Based Sports Medicine (ACES), Amsterdam, the Netherlands
- Amsterdam Collaboration for Health and Safety in Sports (ACHSS), AMC/VUmc IOC Research Center, Amsterdam, the Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Mario Maas
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands
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12
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Enax-Krumova E, Forsting J, Rohm M, Schwenkreis P, Tegenthoff M, Meyer-Frießem CH, Schlaffke L. Quantitative muscle magnetic resonance imaging depicts microstructural abnormalities but no signs of inflammation or dystrophy in post-COVID-19 condition. Eur J Neurol 2023; 30:970-981. [PMID: 36693812 DOI: 10.1111/ene.15709] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 12/22/2022] [Accepted: 01/12/2023] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND PURPOSE Post-COVID-19 condition (PCC) has high impact on quality of life, with myalgia and fatigue affecting at least 25% of PCC patients. This case-control study aims to noninvasively assess muscular alterations via quantitative muscle magnetic resonance imaging (MRI) as possible mechanisms for ongoing musculoskeletal complaints and premature exhaustion in PCC. METHODS Quantitative muscle MRI was performed on a 3 Tesla MRI scanner of the whole legs in PCC patients compared to age- and sex-matched healthy controls, including a Dixon sequence to determine muscle fat fraction (FF), a multi-echo spin-echo sequence for quantitative water mapping reflecting putative edema, and a diffusion-weighted spin-echo echo-planar imaging sequence to assess microstructural alterations. Clinical examination, nerve conduction studies, and serum creatine kinase were performed in all patients. Quantitative muscle MRI results were correlated to the results of the 6-min walk test and standardized questionnaires assessing quality of life, fatigue, and depression. RESULTS Twenty PCC patients (female: n = 15, age = 48.8 ± 10.1 years, symptoms duration = 13.4 ± 4.2 months, body mass index [BMI] = 28.8 ± 4.7 kg/m2 ) were compared to 20 healthy controls (female: n = 15, age = 48.1 ± 11.1 years, BMI = 22.9 ± 2.2 kg/m2 ). Neither FF nor T2 revealed signs of muscle degeneration or inflammation in either study groups. Diffusion tensor imaging (DTI) revealed reduced mean, axial, and radial diffusivity in the PCC group. CONCLUSIONS Quantitative muscle MRI did not depict any signs of ongoing inflammation or dystrophic process in the skeletal muscles in PCC patients. However, differences observed in muscle DTI depict microstructural abnormalities, which may reflect potentially reversible fiber hypotrophy due to deconditioning. Further longitudinal and interventional studies should prove this hypothesis.
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Affiliation(s)
- Elena Enax-Krumova
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
| | - Johannes Forsting
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
| | - Marlena Rohm
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
- Heimer Institute for Muscle Research, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Peter Schwenkreis
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
| | - Martin Tegenthoff
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
| | - Christine H Meyer-Frießem
- Department of Anaesthesiology, Intensive Care, and Pain Management, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
| | - Lara Schlaffke
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr University Bochum, Bochum, Germany
- Heimer Institute for Muscle Research, BG University Hospital Bergmannsheil, Bochum, Germany
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13
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Rauh SS, Maier O, Gurney-Champion OJ, Hooijmans MT, Stollberger R, Nederveen AJ, Strijkers GJ. Model-based reconstructions for intravoxel incoherent motion and diffusion tensor imaging parameter map estimations. NMR IN BIOMEDICINE 2023:e4927. [PMID: 36932842 DOI: 10.1002/nbm.4927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 01/16/2023] [Accepted: 03/06/2023] [Indexed: 06/18/2023]
Abstract
Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.
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Affiliation(s)
- Susanne S Rauh
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Oliver Maier
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Melissa T Hooijmans
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
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14
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Carpenter RS, Samaan MA, Clasey JL, Butterfield TA, Gao F, Hardy PA, Bollinger LM. Association of vastus lateralis diffusion properties with in vivo quadriceps contractile function in premenopausal women. Scand J Med Sci Sports 2023; 33:213-223. [PMID: 36337008 PMCID: PMC9928607 DOI: 10.1111/sms.14266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 09/10/2022] [Accepted: 10/23/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Diffusion tensor imaging (DTI) parameters correlate with muscle fiber composition, but it is unclear how these relate to in vivo contractile function. PURPOSE To determine the relationship between DTI parameters of the vastus lateralis (VL) and in vivo knee extensor contractile. METHODS Thirteen healthy, premenopausal women underwent magnetic resonance imaging of the mid-thigh to determine patellar tendon moment arm length and quadriceps cross-sectional area. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of the VL were determined using diffusion tensor imaging (DTI). Participants underwent an interpolated twitch (ITT) experiment before and after a fatiguing concentric-eccentric isokinetic knee extension (60°·s-1 ). During the ITT, supramaximal electrical stimuli were delivered to elicit twitch responses from the knee extensors before, during, and after a maximal voluntary isometric contraction (MVIC). Knee extensor-specific tension during twitch and MVIC were calculated from isometric torque data. Pearson's correlations were used to determine the relationship between muscle contractile properties and DTI parameters. RESULTS MD and RD were moderately correlated with peak twitch force and rate of force development. FA and AD were moderately inversely related to percent change in MVIC following exercise. CONCLUSION MD and RD are associated with in vivo quadriceps twitch properties but not voluntary strength, which may reflect the mechanical properties of constituent fiber types. FA and AD appear to relate to MVIC strength following fatiguing exercise.
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Affiliation(s)
- Rebekah S Carpenter
- Department of Kinesiology and Health Promotion, University of Kentucky, Lexington, Kentucky, USA
| | - Michael A Samaan
- Department of Kinesiology and Health Promotion, University of Kentucky, Lexington, Kentucky, USA
| | - Jody L Clasey
- Department of Kinesiology and Health Promotion, University of Kentucky, Lexington, Kentucky, USA
- Center for Muscle Biology, University of Kentucky, Lexington, Kentucky, USA
- Body Composition Core Laboratory, University of Kentucky, Lexington, Kentucky, USA
| | - Tim A Butterfield
- Center for Muscle Biology, University of Kentucky, Lexington, Kentucky, USA
- Department of Athletic Training, University of Kentucky, Lexington, Kentucky, USA
| | - Fan Gao
- Department of Kinesiology and Health Promotion, University of Kentucky, Lexington, Kentucky, USA
| | - Peter A Hardy
- Department of Radiology, University of Kentucky, Lexington, Kentucky, USA
- Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, Kentucky, USA
| | - Lance M Bollinger
- Department of Kinesiology and Health Promotion, University of Kentucky, Lexington, Kentucky, USA
- Center for Muscle Biology, University of Kentucky, Lexington, Kentucky, USA
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15
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Heiss R, Janka R, Uder M, Hotfiel T, Gast L, Nagel AM, Roemer FW. [Imaging of muscle injuries in sports medicine]. RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:249-258. [PMID: 36797330 DOI: 10.1007/s00117-023-01118-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/09/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND Early diagnosis of muscle injuries is indispensable in order to initiate appropriate treatment and to facilitate optimal healing. PURPOSE The aim of this review is to provide an update on imaging of muscle injuries in sports medicine with a focus on ultrasound and magnetic resonance imaging (MRI) and to present experimental approaches in addition to routine diagnostic procedures. MATERIALS AND METHODS A PubMed literature search for the years 2012-2022 using the following keywords was performed: muscle, muscle injury, muscle imaging, muscle injury classification, delayed onset muscle soreness, ultrasound, MRI, sodium MRI, potassium MRI, ultra-high-field MRI, injuries of athletes. RESULTS Imaging is crucial to confirm and assess the extent of sports-related muscle injuries and may help establishing treatment decisions, which directly affect the prognosis. This is of importance when the diagnosis or grade of injury is unclear, when recovery is taking longer than expected, and when interventional or surgical management may be necessary. In addition to established methods such as B‑mode ultrasound and 1H‑MRI, individual studies show promising approaches to further improve the imaging of muscle injuries in the future. Prior to the integration of contrast-enhanced ultrasound and X‑nuclei into clinical routine, additional studies are needed to validate these techniques further. CONCLUSION B‑mode ultrasound represents an easily available, cost-effective modality for the initial diagnosis of muscle injuries. MRI is still considered the reference standard and enables an accurate morphological assessment of the extent of the injury. There are still no imaging approaches available for the objective determination of the optimal point of return to play.
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Affiliation(s)
- Rafael Heiss
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Maximiliansplatz 3, 91054, Erlangen, Deutschland.
| | - Rolf Janka
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Maximiliansplatz 3, 91054, Erlangen, Deutschland
| | - Michael Uder
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Maximiliansplatz 3, 91054, Erlangen, Deutschland
| | - Thilo Hotfiel
- Unfallchirurgische und Orthopädische Klinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland.,Osnabrücker Zentrum für Muskuloskelettale Chirurgie (OZMC), Klinikum Osnabrück, Osnabrück, Deutschland
| | - Lena Gast
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Maximiliansplatz 3, 91054, Erlangen, Deutschland
| | - Armin M Nagel
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Maximiliansplatz 3, 91054, Erlangen, Deutschland.,Abteilung Medizinische Physik in der Radiologie, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Deutschland
| | - Frank W Roemer
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Maximiliansplatz 3, 91054, Erlangen, Deutschland.,Quantitative Imaging Center (QIC), Department of Radiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
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16
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Chianca V, Albano D, Rizzo S, Maas M, Sconfienza LM, Del Grande F. Inter-vendor and inter-observer reliability of diffusion tensor imaging in the musculoskeletal system: a multiscanner MR study. Insights Imaging 2023; 14:32. [PMID: 36757529 PMCID: PMC9911574 DOI: 10.1186/s13244-023-01374-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/09/2023] [Indexed: 02/10/2023] Open
Abstract
BACKGROUND To evaluate the inter-observer and inter-vendor reliability of diffusion tensor imaging parameters in the musculoskeletal system. METHODS This prospective study included six healthy volunteers three men (mean age: 42; range: 31-52 years) and three women (mean age: 36; range: 30-44 years). Each subject was scanned using different 3 Tesla magnetic resonance scanners from three different vendors at three different sites bilaterally. First, the intra-class correlation coefficient was used to determine between-observers agreement for overall measurements and clinical sites. Next, between-group comparisons were made through the nonparametric Friedman's test. Finally, the Bland-Altman method was used to determine agreement among the three scanner measurements, comparing them two by two. RESULTS A total of 792 measurement were calculated. ICC reported high levels of agreement between the two observers. ICC related to MD, FA, and RD measurements ranged from 0.88 (95% CI 0.85-0.90) to 0.95 (95% CI 0.94-0.96), from 0.85 (95% CI 0.81-0.88) to 0.95 (95% CI 0.93-0.96), and from 0.89 (0.85-0.90) to 0.92 (0.90-0.94). No statistically significant inter-vendor differences were observed. The Bland-Altmann method confirmed a high correlation between parameter values. CONCLUSION An excellent inter-observer and inter-vendor reliability was found in our study.
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Affiliation(s)
- Vito Chianca
- Clinica di Radiologia EOC IIMSI, Lugano, Switzerland. .,Ospedale Evangelico Betania, Via Argine 604, 80147, Naples, Italy.
| | - Domenico Albano
- grid.417776.4IRCCS Istituto Ortopedico Galeazzi, Milan, Italy
| | | | - Mario Maas
- grid.7177.60000000084992262Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, The Netherlands ,Amsterdam Movement Sciences Research Institute, Amsterdam, The Netherlands
| | - Luca Maria Sconfienza
- grid.417776.4IRCCS Istituto Ortopedico Galeazzi, Milan, Italy ,grid.4708.b0000 0004 1757 2822Department of Biomedical Sciences for Health, University of Milano, Milan, Italy
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Klontzas ME, Karantanas AH. Research in Musculoskeletal Radiology: Setting Goals and Strategic Directions. Semin Musculoskelet Radiol 2022; 26:354-358. [PMID: 35654100 DOI: 10.1055/s-0042-1748319] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The future of musculoskeletal (MSK) radiology is being built on research developments in the field. Over the past decade, MSK imaging research has been dominated by advancements in molecular imaging biomarkers, artificial intelligence, radiomics, and novel high-resolution equipment. Adequate preparation of trainees and specialists will ensure that current and future leaders will be prepared to embrace and critically appraise technological developments, will be up to date on clinical developments, such as the use of artificial tissues, will define research directions, and will actively participate and lead multidisciplinary research. This review presents an overview of the current MSK research landscape and proposes tangible future goals and strategic directions that will fortify the future of MSK radiology.
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Affiliation(s)
- Michail E Klontzas
- Department of Medical Imaging, University Hospital of Heraklion, Crete, Greece.,Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), Heraklion, Crete, Greece.,Department of Radiology, School of Medicine, University of Crete, Heraklion, Greece
| | - Apostolos H Karantanas
- Department of Medical Imaging, University Hospital of Heraklion, Crete, Greece.,Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), Heraklion, Crete, Greece.,Department of Radiology, School of Medicine, University of Crete, Heraklion, Greece
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18
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Waterval NFJ, Meekes VL, Hooijmans MT, Froeling M, Jaspers RT, Oudeman J, Nederveen AJ, Brehm MA, Nollet F. The relationship between quantitative magnetic resonance imaging of the ankle plantar flexors, muscle function during walking and maximal strength in people with neuromuscular diseases. Clin Biomech (Bristol, Avon) 2022; 94:105609. [PMID: 35247697 DOI: 10.1016/j.clinbiomech.2022.105609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 02/24/2022] [Accepted: 02/25/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND Progression of plantar flexor weakness in neuromuscular diseases is usually monitored by muscle strength measurements, although they poorly relate to muscle function during walking. Pathophysiological changes such as intramuscular adipose tissue affect dynamic muscle function independent from isometric strength. Diffusion tensor imaging and T2 imaging are quantitative MRI measures reflecting muscular pathophysiological changes, and are therefore potential biomarkers to monitor plantar flexor functioning during walking in people with neuromuscular diseases. METHODS In fourteen individuals with plantar flexor weakness diffusion tensor imaging and T2 scans of the plantar flexors were obtained, and the diffusion indices fractional anisotropy and mean diffusivity calculated. With a dynamometer, maximal isometric plantar flexor strength was measured. 3D gait analysis was used to assess maximal ankle moment and power during walking. FINDINGS Fractional anisotropy, mean diffusivity and T2 relaxation time all moderately correlated with maximal plantar flexor strength (r > 0.512). Fractional anisotropy and mean diffusivity were not related with ankle moment or power (r < 0.288). T2 relaxation time was strongly related to ankle moment (r = -0.789) and ankle power (r = -0.798), and moderately related to maximal plantar flexor strength (r < 0.600). INTERPRETATION In conclusion, T2 relaxation time, indicative of multiple pathophysiological changes, was strongly related to plantar flexor function during walking, while fractional anisotropy and mean diffusivity, indicative of fiber size, only related to maximal plantar flexor strength. This indicates that these measures may be suitable to monitor muscle function and gain insights into the pathophysiological changes underlying a poor plantar flexor functioning during gait in people with neuromuscular diseases.
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Affiliation(s)
- N F J Waterval
- Amsterdam UMC, University of Amsterdam, Department of Rehabilitation Medicine, Amsterdam Movement Sciences, Meibergdreef 9, Amsterdam, the Netherlands.
| | - V L Meekes
- Amsterdam UMC, University of Amsterdam, Department of Rehabilitation Medicine, Amsterdam Movement Sciences, Meibergdreef 9, Amsterdam, the Netherlands
| | - M T Hooijmans
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands
| | - M Froeling
- University Medical Center Utrecht, Department of Radiology, Heidelberglaan 100, Utrecht, the Netherlands
| | - R T Jaspers
- Laboratory for Myology, Department of Human Movement Sciences, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, the Netherlands
| | - J Oudeman
- University Medical Center Utrecht, Department of Radiology, Heidelberglaan 100, Utrecht, the Netherlands
| | - A J Nederveen
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands
| | - M A Brehm
- Amsterdam UMC, University of Amsterdam, Department of Rehabilitation Medicine, Amsterdam Movement Sciences, Meibergdreef 9, Amsterdam, the Netherlands
| | - F Nollet
- Amsterdam UMC, University of Amsterdam, Department of Rehabilitation Medicine, Amsterdam Movement Sciences, Meibergdreef 9, Amsterdam, the Netherlands
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Zaeske C, Brueggemann GP, Willwacher S, Maehlich D, Maintz D, Bratke G. The behaviour of T2* and T2 relaxation time in extrinsic foot muscles under continuous exercise: A prospective analysis during extended running. PLoS One 2022; 17:e0264066. [PMID: 35176114 PMCID: PMC8893273 DOI: 10.1371/journal.pone.0264066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 02/02/2022] [Indexed: 12/02/2022] Open
Abstract
Objectives Previous studies on T2* and T2 relaxation time of the muscles have shown that exercise leads to an initial increase, presumably representing different intramuscular physiological processes such as increase in intracellular volume or blood oxygenation level dependent effects with a subsequent decrease after cessation of exercise. Their behaviour during prolonged exercise is still unknown but could provide important information for example about the pathophysiology of overuse injuries. The aim of this study was to evaluate the temporal course of T2* and T2 relaxation time in extrinsic foot muscles during prolonged exercise and determine the optimal mapping technique. Methods Ten participants had to run a total of 75 minutes at their individual highest possible running speed, with interleaved MR scans at baseline and after 2.5, 5, 10, 15, 45 and 75 minutes. The examined extrinsic foot muscles were manually segmented, and relaxation time were analysed regarding its respective time course. Results T2* and T2 relaxation time showed an initial increase, followed by a plateau phase between 2.5 and 15 minutes and a subsequent decrease. For the T2* relaxation time, this pattern was also apparent, but less pronounced, with more muscles not reaching significance (p<0.05) when comparing different time points. Conclusions T2* and T2 relaxation time showed a similar course with an initial rapid increase, a plateau phase and a subsequent decrease under prolonged exercise. Moderate but long-term muscular activity appears to have a weaker effect on T2* relaxation time than on T2 relaxation time.
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Affiliation(s)
- Charlotte Zaeske
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
- * E-mail:
| | | | - Steffen Willwacher
- Institute of Biomechanics and Orthopaedics, German Sport University, Cologne, Germany
| | - Daniela Maehlich
- Institute of Biomechanics and Orthopaedics, German Sport University, Cologne, Germany
| | - David Maintz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Grischa Bratke
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
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20
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Tan ET, Zochowski KC, Sneag DB. Diffusion MRI fiber diameter for muscle denervation assessment. Quant Imaging Med Surg 2022; 12:80-94. [PMID: 34993062 PMCID: PMC8666740 DOI: 10.21037/qims-21-313] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 05/28/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND To develop and evaluate a diffusion MRI-based apparent muscle fiber diameter (AFD) method in patients with muscle denervation. It was hypothesized that AFD differences between denervated, non-denervated and control muscles would be greater than those from standard diffusion metrics. METHODS A spin-echo diffusion acquisition with multi-b-valued diffusion sampling was used. An orientation-invariant dictionary approach utilized a cylinder-based forward model and multi-compartment model for obtaining restricted and free fractions. Simulations were performed to determine precision, bias, and optimize dictionary parameters. In all, 18 exams of patients with muscle denervation and 8 exams of healthy subjects were performed at 3T. Six regions of interests (ROIs) within separate shoulder muscles were selected, yielding three groups consisting 47 control (healthy), 36 non-denervated (patients), and 68 denervated (patients) muscle ROIs. Two-sample t-tests (α=0.05) between groups were performed with Holm-Bonferroni correction. T2- and fat fraction (FF)-mapping were acquired for comparison. RESULTS Mean AFD was 89.7±13.6 µm in control, 71.6±15.3 µm in non-denervated, and 60.7±15.9 µm in denervated muscles and were significantly different (P<0.001) in paired comparisons and in 10/12 individual muscle region comparisons. Correlation between AFD and FF (-0.331, P<0.001) was low, but correlation between FA and FF was negligible (0.197, P=0.016). Correlation was low between AFD and T2 (-0.395, P<0.001) and between FA and T2 (0.359, P<0.001). CONCLUSIONS Diffusion MRI-based AFD complements T2- and FF-mapping techniques to non-invasively assess muscle denervation.
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Affiliation(s)
| | - Kelly C. Zochowski
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA
| | - Darryl B. Sneag
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA
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21
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Effect of Daily Oral Lactobacillus plantarum PS128 on Exercise Capacity Recovery after a Half-Marathon. Nutrients 2021; 13:nu13114023. [PMID: 34836278 PMCID: PMC8619570 DOI: 10.3390/nu13114023] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/09/2021] [Accepted: 11/09/2021] [Indexed: 12/21/2022] Open
Abstract
A half-marathon (HM) is a vigorous high-intensity exercise, which could induce lower extremity musculoskeletal injury risks for recreational runners. They usually consume nonsteroidal anti-inflammatory drugs (NSAIDs) in order to shorten their return to play but ignore the side effects, such as peptic ulcers and renal and vascular disorders. Lactobacillus plantarum PS128 (PS128) could improve inflammation and oxidative stress by modulating the gut microbiota, thus potentially improving muscle damage and recovery. However, few studies have addressed the PS128 exercise capacity recovery 96 h after HM. Thus, this study aimed to investigate the effect of PS128 on exercise capacity and physiological adaptation after HM. A double-blind, randomized, placebo-controlled, counterbalanced, crossover trial was used for the experiment. HM was conducted at the beginning and end of the 4-week nutritional supplement administration. Eight recreational runners took two capsules (3 × 1010 CFU/capsule) of PS128 each morning and evening before meals for 4 weeks as the PS128 treatment (LT), or they took two capsules of placebo for 4 weeks as the placebo treatment (PT). In both treatments, an exercise capacity test (lower extremity muscle strength, anaerobic power, lower extremity explosive force, and aerobic capacity) and blood test (muscle fatigue, muscle damage, oxidative stress, and renal injury) were performed before the administration of the nutritional supplement (baseline), 48 h before HM (pre), and 0 h (0 h post), 3 h (3 h post), 24 h (24 h post), 48 h (48 h post), 72 h (72 h post), and 96 h (96 h post) after HM. There was no significant difference in the total duration of HM between PT and LT, but PT was found to be significantly higher than LT at Stage 4 (15,751–21,000 m) of HM (3394 ± 727 s vs. 2778 ± 551 s, p = 0.02). The lower extremity muscle strength measured using an isokinetic dynamometer in PT was significantly lower than that in LT at 72 h after HM. The lower extremity explosive force from the countermovement jump (CMJ) in PT was significantly decreased compared to 24 h prior. There was no significant difference between anaerobic power and aerobic capacity between the two treatments after HM. After HM, LT had lower muscle damage indices, such as myoglobin (3 h post-PT vs. -LT: 190.6 ± 118 ng/mL vs. 91.7 ± 68.6 ng/mL, p < 0.0001) and creatine phosphokinase (24 h post-PT vs. -LT: 875.8 ± 572.3 IU/L vs. 401 ± 295.7 IU/L, p < 0.0001). Blood urea nitrogen recovered in 24 h (24 h pre- vs. post-LT, p > 0.05) and higher superoxide dismutase was found in LT (96 h post-PT vs. -LT: 0.267 ± 0.088 U/mL vs. 0.462 ± 0.122 U/mL, p < 0.0001). In conclusion, PS128 supplementation was associated with an improvement in muscle damage, renal damage, and oxidative stress caused by HM through microbiota modulation and related metabolites but not in exercise capacity.
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22
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Shu D, Zhang C, Dai S, Wang S, Liu J, Ding J. Acute Effects of Foam Rolling on Hamstrings After Half-Marathon: A Muscle Functional Magnetic Resonance Imaging Study. Front Physiol 2021; 12:723092. [PMID: 34690798 PMCID: PMC8526727 DOI: 10.3389/fphys.2021.723092] [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: 06/10/2021] [Accepted: 09/15/2021] [Indexed: 11/20/2022] Open
Abstract
Purpose: Foam rolling (FR) is widely used for post-exercise muscle recovery; yet, the effects of FR on skeletal muscle inflammation and microvascular perfusion following prolonged exercise are poorly understood. We aim to address the gap in knowledge by using magnetic resonance imaging (MRI) T2 mapping and intravoxel incoherent motion (IVIM) sequences to study the acute effects of FR on hamstrings following half-marathon running in recreational runners. Methods: Sixteen healthy recreational marathon runners were recruited. After half-marathon running, FR was performed on the hamstrings on the dominant side, while the other limb served as a control. MRI T2 and IVIM scans were performed bilaterally at baseline (pre-run), 2–3 h after running (post-run), immediately after FR (post-FR0), 30 min after FR (post-FR30) and 60 min after FR (post-FR60). T2, a marker for inflammatory edema, as well as IVIM microvascular perfusion fraction index f for biceps femoris long head (BFL), semitendinosus (ST) and semimembranosus (SM) were determined. Total Quality Recovery (TQR) scale score was also collected. Results: Both T2 and f were higher at post-run compared to pre-run in all hamstrings on both sides (all p < 0.05; all d > 1.0). For the FR side, T2 decreased, and f increased significantly at post-FR0 and post-FR30 compared to post-run in all muscles (p < 0.05; all d > 0.4) except for f at BFL and SM at post-FR30 (both p > 0.05), though f at BFL was still marginally elevated at post-FR30 (p = 0.074, d = 0.91). Both parameters for all muscles returned to post-run level at post-FR60 (all p > 0.05; all d < 0.4) except for T2 at SM (p = 0.037). In contrast, most MRI parameters were not changed at post-FR0, post-FR30 and post-FR60 compared to post-run for the control side (p < 0.05; d < 0.2). TQR scores were elevated at post-FR0 and post-FR30 compared to post-run (both p < 0.05; both d > 1.0), and returned to the post-run level at post-FR60 (p > 0.99; d = 0.09). Changes in TQR scores compared to post-run at any time points after FR were correlated to T2 for ST at post-FR30 (r = 0.50, p = 0.047) but not T2 for other muscles and any changes in f values. Conclusions: Hamstrings inflammatory edema and microvascular perfusion were elevated following half-marathon running, which were detectable with MRI T2 mapping and IVIM sequences. FR resulted in acute alleviation in inflammation and greater microvascular perfusion; however, the effects seemed to last only for a short period of time (30–60 min). FR can provide short-term benefits to skeletal muscle after prolonged running.
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Affiliation(s)
- Dingbo Shu
- Department of Radiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China.,Institute of Sport Medicine, Hangzhou Normal University, Hangzhou, China
| | - Chuan Zhang
- School of Physical Education and Sports, Central China Normal University, Wuhan, China
| | - Siyu Dai
- School of Clinical Medicine, Hangzhou Normal University, Hangzhou, China.,Institute of Sport Medicine, Hangzhou Normal University, Hangzhou, China
| | - Shubo Wang
- Department of Mechanical Engineering, University of Delaware, Newark, DE, United States
| | - Jie Liu
- Department of Radiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Sport Medicine, Hangzhou Normal University, Hangzhou, China
| | - Jianping Ding
- Department of Radiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Sport Medicine, Hangzhou Normal University, Hangzhou, China
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23
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Mazzoli V, Moulin K, Kogan F, Hargreaves BA, Gold GE. Diffusion Tensor Imaging of Skeletal Muscle Contraction Using Oscillating Gradient Spin Echo. Front Neurol 2021; 12:608549. [PMID: 33658976 PMCID: PMC7917051 DOI: 10.3389/fneur.2021.608549] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 01/08/2021] [Indexed: 01/01/2023] Open
Abstract
Diffusion tensor imaging (DTI) measures water diffusion in skeletal muscle tissue and allows for muscle assessment in a broad range of neuromuscular diseases. However, current DTI measurements, typically performed using pulsed gradient spin echo (PGSE) diffusion encoding, are limited to the assessment of non-contracted musculature, therefore providing limited insight into muscle contraction mechanisms and contraction abnormalities. In this study, we propose the use of an oscillating gradient spin echo (OGSE) diffusion encoding strategy for DTI measurements to mitigate the effect of signal voids in contracted muscle and to obtain reliable diffusivity values. Two OGSE sequences with encoding frequencies of 25 and 50 Hz were tested in the lower leg of five healthy volunteers with relaxed musculature and during active dorsiflexion and plantarflexion, and compared with a conventional PGSE approach. A significant reduction of areas of signal voids using OGSE compared with PGSE was observed in the tibialis anterior for the scans obtained in active dorsiflexion and in the soleus during active plantarflexion. The use of PGSE sequences led to unrealistically elevated axial diffusivity values in the tibialis anterior during dorsiflexion and in the soleus during plantarflexion, while the corresponding values obtained using the OGSE sequences were significantly reduced. Similar findings were seen for radial diffusivity, with significantly higher diffusivity measured in plantarflexion in the soleus muscle using the PGSE sequence. Our preliminary results indicate that DTI with OGSE diffusion encoding is feasible in human musculature and allows to quantitatively assess diffusion properties in actively contracting skeletal muscle. OGSE holds great potential to assess microstructural changes occurring in the skeletal muscle during contraction, and for non-invasive assessment of contraction abnormalities in patients with muscle diseases.
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Affiliation(s)
- Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, CA, United States
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Forsting J, Rehmann R, Rohm M, Froeling M, Schlaffke L. Evaluation of interrater reliability of different muscle segmentation techniques in diffusion tensor imaging. NMR IN BIOMEDICINE 2021; 34:e4430. [PMID: 33217106 DOI: 10.1002/nbm.4430] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 09/22/2020] [Accepted: 09/25/2020] [Indexed: 06/11/2023]
Abstract
INTRODUCTION Muscle diffusion tensor imaging (mDTI) is a quantitative MRI technique that can provide information about muscular microstructure and integrity. Ultrasound and DTI studies have shown intramuscular differences, and therefore separation of different muscles for analysis is essential. The commonly used methods to assess DTI metrics in muscles are manual segmentation and tract-based analysis. Recently methods such as volume-based tractography have been applied to optimize muscle architecture estimation, but can also be used to assess DTI metrics. PURPOSE To evaluate diffusion metrics obtained using three different methods-volume-based tractography, manual segmentation-based analysis and tract-based analysis-with respect to their interrater reliability and their ability to detect intramuscular variance. MATERIALS AND METHODS 30 volunteers underwent an MRI examination in a 3 T scanner using a 16-channel Torso XL coil. Diffusion-weighted images were acquired to obtain DTI metrics. These metrics were evaluated in six thigh muscles using volume-based tractography, manual segmentation and standard tractography. All three methods were performed by two independent raters to assess interrater reliability by ICC analysis and Bland-Altman plots. Ability to assess intramuscular variance was compared using an ANOVA with muscle as a between-subjects factor. RESULTS Interrater reliability for all methods was found to be excellent. The highest interrater reliability was found for volume-based tractography (ICC ≥ 0.967). Significant differences for the factor muscle in all examined diffusion parameters were shown in muscles using all methods (main effect p < 0.001). CONCLUSIONS Diffusion data can be assessed by volume tractography, standard tractography and manual segmentation with high interrater reliability. Each method produces different results for the investigated DTI parameters. Volume-based tractography was superior to conventional manual segmentation and tractography regarding interrater reliability and detection of intramuscular variance, while tract-based analysis showed the lowest coefficients of variation.
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Affiliation(s)
- Johannes Forsting
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Robert Rehmann
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Marlena Rohm
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Martijn Froeling
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Lara Schlaffke
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
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25
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Secondulfo L, Ogier AC, Monte JR, Aengevaeren VL, Bendahan D, Nederveen AJ, Strijkers GJ, Hooijmans MT. Supervised segmentation framework for evaluation of diffusion tensor imaging indices in skeletal muscle. NMR IN BIOMEDICINE 2021; 34:e4406. [PMID: 33001508 PMCID: PMC7757256 DOI: 10.1002/nbm.4406] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 08/11/2020] [Accepted: 08/14/2020] [Indexed: 05/05/2023]
Abstract
Diffusion tensor imaging (DTI) is becoming a relevant diagnostic tool to understand muscle disease and map muscle recovery processes following physical activity or after injury. Segmenting all the individual leg muscles, necessary for quantification, is still a time-consuming manual process. The purpose of this study was to evaluate the impact of a supervised semi-automatic segmentation pipeline on the quantification of DTI indices in individual upper leg muscles. Longitudinally acquired MRI datasets (baseline, post-marathon and follow-up) of the upper legs of 11 subjects were used in this study. MR datasets consisted of a DTI and Dixon acquisition. Semi-automatic segmentations for the upper leg muscles were performed using a transversal propagation approach developed by Ogier et al on the out-of-phase Dixon images at baseline. These segmentations were longitudinally propagated for the post-marathon and follow-up time points. Manual segmentations were performed on the water image of the Dixon for each of the time points. Dice similarity coefficients (DSCs) were calculated to compare the manual and semi-automatic segmentations. Bland-Altman and regression analyses were performed, to evaluate the impact of the two segmentation methods on mean diffusivity (MD), fractional anisotropy (FA) and the third eigenvalue (λ3 ). The average DSC for all analyzed muscles over all time points was 0.92 ± 0.01, ranging between 0.48 and 0.99. Bland-Altman analysis showed that the 95% limits of agreement for MD, FA and λ3 ranged between 0.5% and 3.0% for the transversal propagation and between 0.7% and 3.0% for the longitudinal propagations. Similarly, regression analysis showed good correlation for MD, FA and λ3 (r = 0.99, p < 60; 0.0001). In conclusion, the supervised semi-automatic segmentation framework successfully quantified DTI indices in the upper-leg muscles compared with manual segmentation while only requiring manual input of 30% of the slices, resulting in a threefold reduction in segmentation time.
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Affiliation(s)
- Laura Secondulfo
- Department of Biomedical Engineering and Physics, Amsterdam University Medical CentersUniversity of AmsterdamThe Netherlands
| | - Augustin C. Ogier
- Aix Marseille Universite, Universite de Toulon, CNRS, LISMarseilleFrance
- Aix Marseille Universite, CNRS, CRMBMMarseilleFrance
| | - Jithsa R. Monte
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentersUniversity of AmsterdamThe Netherlands
| | - Vincent L. Aengevaeren
- Radboud Institute for Health Sciences, Department of PhysiologyRadboud University Medical CenterNijmegenThe Netherlands
| | | | - Aart J. Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentersUniversity of AmsterdamThe Netherlands
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical CentersUniversity of AmsterdamThe Netherlands
| | - Melissa T. Hooijmans
- Department of Biomedical Engineering and Physics, Amsterdam University Medical CentersUniversity of AmsterdamThe Netherlands
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Klontzas ME, Papadakis GZ, Marias K, Karantanas AH. Musculoskeletal trauma imaging in the era of novel molecular methods and artificial intelligence. Injury 2020; 51:2748-2756. [PMID: 32972725 DOI: 10.1016/j.injury.2020.09.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/14/2020] [Accepted: 09/15/2020] [Indexed: 02/08/2023]
Abstract
Over the past decade rapid advancements in molecular imaging (MI) and artificial intelligence (AI) have revolutionized traditional musculoskeletal radiology. Molecular imaging refers to the ability of various methods to in vivo characterize and quantify biological processes, at a molecular level. The extracted information provides the tools to understand the pathophysiology of diseases and thus to early detect, to accurately evaluate the extend and to apply and evaluate targeted treatments. At present, molecular imaging mainly involves CT, MRI, radionuclide, US, and optical imaging and has been reported in many clinical and preclinical studies. Although originally MI techniques targeted at central nervous system disorders, later on their value on musculoskeletal disorders was also studied in depth. Meaningful exploitation of the large volume of imaging data generated by molecular and conventional imaging techniques, requires state-of-the-art computational methods that enable rapid handling of large volumes of information. AI allows end-to-end training of computer algorithms to perform tasks encountered in everyday clinical practice including diagnosis, disease severity classification and image optimization. Notably, the development of deep learning algorithms has offered novel methods that enable intelligent processing of large imaging datasets in an attempt to automate decision-making in a wide variety of settings related to musculoskeletal trauma. Current applications of AI include the diagnosis of bone and soft tissue injuries, monitoring of the healing process and prediction of injuries in the professional sports setting. This review presents the current applications of novel MI techniques and methods and the emerging role of AI regarding the diagnosis and evaluation of musculoskeletal trauma.
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Affiliation(s)
- Michail E Klontzas
- Department of Medical Imaging, Heraklion University Hospital, Crete, 70110, Greece; Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece.
| | - Georgios Z Papadakis
- Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece; Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013, Heraklion, Crete, Greece; Department of Radiology, School of Medicine, University of Crete, 70110 Greece.
| | - Kostas Marias
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013, Heraklion, Crete, Greece; Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410, Heraklion, Crete, Greece.
| | - Apostolos H Karantanas
- Department of Medical Imaging, Heraklion University Hospital, Crete, 70110, Greece; Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece; Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013, Heraklion, Crete, Greece; Department of Radiology, School of Medicine, University of Crete, 70110 Greece.
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