1
|
Heskamp L, Birkbeck MG, Baxter-Beard D, Hall J, Schofield IS, Elameer M, Whittaker RG, Blamire AM. Motor Unit Magnetic Resonance Imaging (MUMRI) In Skeletal Muscle. J Magn Reson Imaging 2024. [PMID: 38216545 DOI: 10.1002/jmri.29218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/14/2024] Open
Abstract
Magnetic resonance imaging (MRI) is routinely used in the musculoskeletal system to measure skeletal muscle structure and pathology in health and disease. Recently, it has been shown that MRI also has promise for detecting the functional changes, which occur in muscles, commonly associated with a range of neuromuscular disorders. This review focuses on novel adaptations of MRI, which can detect the activity of the functional sub-units of skeletal muscle, the motor units, referred to as "motor unit MRI (MUMRI)." MUMRI utilizes pulsed gradient spin echo, pulsed gradient stimulated echo and phase contrast MRI sequences and has, so far, been used to investigate spontaneous motor unit activity (fasciculation) and used in combination with electrical nerve stimulation to study motor unit morphology and muscle twitch dynamics. Through detection of disease driven changes in motor unit activity, MUMRI shows promise as a tool to aid in both earlier diagnosis of neuromuscular disorders and to help in furthering our understanding of the underlying mechanisms, which proceed gross structural and anatomical changes within diseased muscle. Here, we summarize evidence for the use of MUMRI in neuromuscular disorders and discuss what future research is required to translate MUMRI toward clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.
Collapse
Affiliation(s)
- Linda Heskamp
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Matthew G Birkbeck
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
- Newcastle Biomedical Research Centre (BRC), Newcastle University, Newcastle upon Tyne, UK
- Northern Medical Physics and Clinical Engineering, Freeman Hospital, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Daniel Baxter-Beard
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
| | - Julie Hall
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Ian S Schofield
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
| | - Mathew Elameer
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Roger G Whittaker
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
- Directorate of Clinical Neurosciences, Royal Victoria Infirmary, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Andrew M Blamire
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, UK
| |
Collapse
|
2
|
Heskamp L, Birkbeck MG, Whittaker RG, Schofield IS, Blamire AM. The muscle twitch profile assessed with motor unit magnetic resonance imaging. NMR IN BIOMEDICINE 2021; 34:e4466. [PMID: 33410277 PMCID: PMC7900994 DOI: 10.1002/nbm.4466] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 11/29/2020] [Accepted: 12/09/2020] [Indexed: 05/03/2023]
Abstract
Localised signal voids in diffusion-weighted (DW) images of skeletal muscle have been postulated to occur as a result of muscle fibre contraction and relaxation. We investigated the contrast mechanism of these signal voids using a combination of modelling and experimental measurements by employing DW and phase contrast (PC) imaging sequences. The DW signal and PC signal were simulated for each time point of a theoretical muscle twitch. The model incorporated compaction (simulating actively contracting muscle fibres) and translation (simulating passively moving surrounding fibres). The model suggested that the DW signal depended on contraction time and compaction whereas the PC signal depended on contraction time, compaction and translation. In a retrospective study, we tested this model with subgroup analyses on 10 healthy participants. Electrical nerve stimulation was used to generate muscle twitches in lower leg muscles; the resulting force was measured using an MR-compatible force transducer. At current levels causing a visible muscle twitch (~13 mA), the width of the first signal drop in the DW signal (mean ± SD: 103 ± 20 ms) was comparable with the force contraction time (93 ± 34 ms; intraclass correlation coefficient [ICC] = 0.717, P = .010). At current levels activating single motor units (~9 mA), the contraction time determined from the DW signal was 75 ± 13 ms and comparable with the PC contraction time (81 ± 15 ms; ICC = 0.925, P = .001). The maximum positive velocity was 0.55 ± 0.26 cm/s and the displacement was 0.20 ± 0.10 mm. Voxel-wise analysis revealed localised DW changes occurring together with more widespread phase changes. In conclusion, local signal attenuations in DW images following muscle fibre activation are primarily caused by compaction. The PC sequence also detects translating muscle tissue being passively pulled. The magnitude of the changes in DW and PC images depends on the twitch's contractile properties and percentage contraction. DW imaging and PC imaging can therefore measure twitch profiles of skeletal muscle fibres.
Collapse
Affiliation(s)
- Linda Heskamp
- Newcastle University Translational and Clinical Research Institute (NUTCRI)Newcastle UniversityNewcastle upon TyneUK
| | - Matthew G. Birkbeck
- Newcastle University Translational and Clinical Research Institute (NUTCRI)Newcastle UniversityNewcastle upon TyneUK
- Newcastle Biomedical Research CentreNewcastle UniversityNewcastle upon TyneUK
- Northern Medical Physics and Clinical EngineeringFreeman Hospital, Newcastle upon Tyne NHS Foundation TrustNewcastle upon TyneUK
| | - Roger G. Whittaker
- Newcastle University Translational and Clinical Research Institute (NUTCRI)Newcastle UniversityNewcastle upon TyneUK
| | - Ian S. Schofield
- Newcastle University Translational and Clinical Research Institute (NUTCRI)Newcastle UniversityNewcastle upon TyneUK
| | - Andrew M. Blamire
- Newcastle University Translational and Clinical Research Institute (NUTCRI)Newcastle UniversityNewcastle upon TyneUK
| |
Collapse
|
3
|
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.
Collapse
Affiliation(s)
- Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, CA, United States
| | | | | | | | | |
Collapse
|