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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; 60:2253-2271. [PMID: 38216545 DOI: 10.1002/jmri.29218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 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.
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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
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Birkbeck MG, Heskamp L, Schofield IS, Hall J, Sayer AA, Whittaker RG, Blamire AM. Whole Muscle and Single Motor Unit Twitch Profiles in a Healthy Adult Cohort Assessed With Phase Contrast Motor Unit MRI (PC-MUMRI). J Magn Reson Imaging 2024; 60:205-217. [PMID: 37776094 DOI: 10.1002/jmri.29028] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 09/13/2023] [Accepted: 09/13/2023] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND Motor units (MUs) control the contraction of muscles and degenerate with age. It is therefore of interest to measure whole muscle and MU twitch profiles in aging skeletal muscle. PURPOSE Apply phase contrast MU MRI (PC-MUMRI) in a cohort of healthy adults to measure whole anterior compartment, individual muscles, and single MU twitch profiles in the calf. Assess the effect of age and sex on contraction and relaxation times. STUDY TYPE Prospective cross-sectional study. SUBJECTS Sixty-one healthy participants (N = 32 male; age 55 ± 16 years [range: 26-82]). FIELD STRENGTH/SEQUENCES 3 T, velocity encoded gradient echo and single shot spin echo pulsed gradient spin echo, echo-planar imaging. ASSESSMENT Anterior shin compartment (N = 47), individual muscle (tibialis anterior, extensor digitorum longus, peroneus longus; N = 47) and single MU (N = 34) twitch profiles were extracted from the data to calculate contraction and relaxation times. STATISTICAL TESTS Multivariable linear regression to investigate relationships between age, sex and contraction and relaxation times of the whole anterior compartment. Pearson correlation to investigate relationships between age and contraction and relaxation times of individual muscles and single MUs. A P value <0.05 was considered statistically significant. RESULTS Age and sex predicted significantly increased contraction and relaxation time for the anterior compartment. Females had significantly longer contraction times than males (females 86 ± 8 msec, males 80 ± 9 msec). Relaxation times were longer, not significant (females 204 ± 36 msec, males 188 ± 34 msec, P = 0.151). Contraction and relaxation times of single MUs showed no change with age (P = 0.462, P = 0.534, respectively). DATE CONCLUSION Older participants had significantly longer contraction and relaxation times of the whole anterior compartment compared to younger participants. Females had longer contraction and relaxation times than males, significant for contraction time. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Matthew G Birkbeck
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University, Newcastle upon Tyne, UK
- Northern Medical Physics and Clinical Engineering, Freeman Hospital, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Linda Heskamp
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Ian S Schofield
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Julie Hall
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle University, Newcastle upon Tyne, UK
| | - Avan A Sayer
- NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University, Newcastle upon Tyne, UK
| | - Roger G Whittaker
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Andrew M Blamire
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
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Shin-Yi Lin C, Howells J, Rutkove S, Nandedkar S, Neuwirth C, Noto YI, Shahrizaila N, Whittaker RG, Bostock H, Burke D, Tankisi H. Neurophysiological and imaging biomarkers of lower motor neuron dysfunction in motor neuron diseases/amyotrophic lateral sclerosis: IFCN handbook chapter. Clin Neurophysiol 2024; 162:91-120. [PMID: 38603949 DOI: 10.1016/j.clinph.2024.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 02/07/2024] [Accepted: 03/12/2024] [Indexed: 04/13/2024]
Abstract
This chapter discusses comprehensive neurophysiological biomarkers utilised in motor neuron disease (MND) and, in particular, its commonest form, amyotrophic lateral sclerosis (ALS). These encompass the conventional techniques including nerve conduction studies (NCS), needle and high-density surface electromyography (EMG) and H-reflex studies as well as novel techniques. In the last two decades, new methods of assessing the loss of motor units in a muscle have been developed, that are more convenient than earlier methods of motor unit number estimation (MUNE),and may use either electrical stimulation (e.g. MScanFit MUNE) or voluntary activation (MUNIX). Electrical impedance myography (EIM) is another novel approach for the evaluation that relies upon the application and measurement of high-frequency, low-intensity electrical current. Nerve excitability techniques (NET) also provide insights into the function of an axon and reflect the changes in resting membrane potential, ion channel dysfunction and the structural integrity of the axon and myelin sheath. Furthermore, imaging ultrasound techniques as well as magnetic resonance imaging are capable of detecting the constituents of morphological changes in the nerve and muscle. The chapter provides a critical description of the ability of each technique to provide neurophysiological insight into the complex pathophysiology of MND/ALS. However, it is important to recognise the strengths and limitations of each approach in order to clarify utility. These neurophysiological biomarkers have demonstrated reliability, specificity and provide additional information to validate and assess lower motor neuron dysfunction. Their use has expanded the knowledge about MND/ALS and enhanced our understanding of the relationship between motor units, axons, reflexes and other neural circuits in relation to clinical features of patients with MND/ALS at different stages of the disease. Taken together, the ultimate goal is to aid early diagnosis, distinguish potential disease mimics, monitor and stage disease progression, quantify response to treatment and develop potential therapeutic interventions.
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Affiliation(s)
- Cindy Shin-Yi Lin
- Faculty of Medicine and Health, Central Clinical School, Brain and Mind Centre, University of Sydney, Sydney 2006, Australia.
| | - James Howells
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Seward Rutkove
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Sanjeev Nandedkar
- Natus Medical Inc, Middleton, Wisconsin, USA and Medical College of Wisconsin, Milwaukee, WI, USA
| | - Christoph Neuwirth
- Neuromuscular Diseases Unit/ALS Clinic, Kantonsspital, St. Gallen, Switzerland
| | - Yu-Ichi Noto
- Department of Neurology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Nortina Shahrizaila
- Division of Neurology, Department of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Roger G Whittaker
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University., Newcastle Upon Tyne, United Kingdom
| | - Hugh Bostock
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, Queen Square, WC1N 3BG, London, United Kingdom
| | - David Burke
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Hatice Tankisi
- Department of Clinical Neurophysiology, Aarhus University Hospital and Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
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Heskamp L, Birkbeck MG, Hall J, Schofield IS, Bashford J, Williams TL, De Oliveira HM, Whittaker RG, Blamire AM. Whole-body fasciculation detection in amyotrophic lateral sclerosis using motor unit MRI. Clin Neurophysiol 2024; 161:246-255. [PMID: 38448302 DOI: 10.1016/j.clinph.2024.02.016] [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: 09/15/2023] [Revised: 01/19/2024] [Accepted: 02/07/2024] [Indexed: 03/08/2024]
Abstract
OBJECTIVE Compare fasciculation rates between amyotrophic lateral sclerosis (ALS) patients and healthy controls in body regions relevant for diagnosing ALS using motor unit MRI (MUMRI) at baseline and 6 months follow-up, and relate this to single-channel surface EMG (SEMG). METHODS Tongue, biceps brachii, paraspinals and lower legs were assessed with MUMRI and biceps brachii and soleus with SEMG in 10 healthy controls and 10 patients (9 typical ALS, 1 primary lateral sclerosis [PLS]). RESULTS MUMRI-detected fasciculation rates in typical ALS patients were higher compared to healthy controls for biceps brachii (2.40 ± 1.90 cm-3min-1vs. 0.04 ± 0.10 cm-3min-1, p = 0.004), paraspinals (1.14 ± 1.61 cm-3min-1vs. 0.02 ± 0.02 cm-3min-1, p = 0.016) and lower legs (1.42 ± 1.27 cm-3min-1vs. 0.13 ± 0.10 cm-3min-1, p = 0.004), but not tongue (1.41 ± 1.94 cm-3min-1vs. 0.18 ± 0.18 cm-3min-1, p = 0.556). The PLS patient showed no fasciculation. At baseline, 6/9 ALS patients had increased fasciculation rates compared to healthy controls in at least 2 body regions. At follow-up every patient had increased fasciculation rates in at least 2 body regions. The MUMRI-detected fasciculation rate correlated with SEMG-detected fasciculation rates (τ = 0.475, p = 0.006). CONCLUSION MUMRI can non-invasively image fasciculation in multiple body regions and appears sensitive to disease progression in individual patients. SIGNIFICANCE MUMRI has potential as diagnostic tool for ALS.
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Affiliation(s)
- Linda Heskamp
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, United Kingdom.
| | - Matthew G Birkbeck
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, United Kingdom; Newcastle Biomedical Research Centre (BRC), Newcastle University, Newcastle Upon Tyne, United Kingdom; Northern Medical Physics and Clinical Engineering, Freeman Hospital, Newcastle Upon Tyne NHS Foundation Trust, Newcastle Upon Tyne, United Kingdom.
| | - Julie Hall
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, United Kingdom; Department of Neuroradiology, Royal Victoria Infirmary, Newcastle Upon Tyne, United Kingdom.
| | - Ian S Schofield
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, United Kingdom.
| | - James Bashford
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
| | - Timothy L Williams
- Directorate of Clinical Neurosciences, Royal Victoria Infirmary, Newcastle Upon Tyne, United Kingdom.
| | - Hugo M De Oliveira
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, United Kingdom; Directorate of Clinical Neurosciences, Royal Victoria Infirmary, Newcastle Upon Tyne, United Kingdom.
| | - Roger G Whittaker
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, United Kingdom; Directorate of Clinical Neurosciences, Royal Victoria Infirmary, Newcastle Upon Tyne, United Kingdom.
| | - Andrew M Blamire
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle Upon Tyne, United Kingdom.
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Swash M, de Carvalho M. Imaging the fasciculating motor unit. Clin Neurophysiol 2024; 161:242-243. [PMID: 38458902 DOI: 10.1016/j.clinph.2024.02.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 02/16/2024] [Indexed: 03/10/2024]
Affiliation(s)
- Michael Swash
- Barts and the London School of Medicine, Queen Mary University of London, UK; Instituto de Fisiologia, Instituto de Medicina Molecular, Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa, Portugal.
| | - Mamede de Carvalho
- Instituto de Fisiologia, Instituto de Medicina Molecular, Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa, Portugal; Department of Neurosciences and Mental Health, Centro Hospitalar Universitário Lisboa Norte, Lisboa, Portugal
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Lubel E, Rohlen R, Sgambato BG, Barsakcioglu DY, Ibanez J, Tang MX, Farina D. Accurate Identification of Motoneuron Discharges From Ultrasound Images Across the Full Muscle Cross-Section. IEEE Trans Biomed Eng 2024; 71:1466-1477. [PMID: 38055363 DOI: 10.1109/tbme.2023.3340019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
OBJECTIVE Non-invasive identification of motoneuron (MN) activity commonly uses electromyography (EMG). However, surface EMG (sEMG) detects only superficial sources, at less than approximately 10-mm depth. Intramuscular EMG can detect deep sources, but it is limited to sources within a few mm of the detection site. Conversely, ultrasound (US) images have high spatial resolution across the whole muscle cross-section. The activity of MNs can be extracted from US images due to the movements that MN activation generates in the innervated muscle fibers. Current US-based decomposition methods can accurately identify the location and average twitch induced by MN activity. However, they cannot accurately detect MN discharge times. METHODS Here, we present a method based on the convolutive blind source separation of US images to estimate MN discharge times with high accuracy. The method was validated across Ten participants using concomitant sEMG decomposition as the ground truth. RESULTS 140 unique MN spike trains were identified from US images, with a rate of agreement (RoA) with sEMG decomposition of 87.4 ± 10.3%. Over 50% of these MN spike trains had a RoA greater than 90%. Furthermore, with US, we identified additional MUs well beyond the sEMG detection volume, at up to >30 mm below the skin. CONCLUSION The proposed method can identify discharges of MNs innervating muscle fibers in a large range of depths within the muscle from US images. SIGNIFICANCE The proposed methodology can non-invasively interface with the outer layers of the central nervous system innervating muscles across the full cross-section.
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Rohlén R, Lubel E, Grandi Sgambato B, Antfolk C, Farina D. Spatial decomposition of ultrafast ultrasound images to identify motor unit activity - A comparative study with intramuscular and surface EMG. J Electromyogr Kinesiol 2023; 73:102825. [PMID: 37757604 DOI: 10.1016/j.jelekin.2023.102825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023] Open
Abstract
The smallest voluntarily controlled structure of the human body is the motor unit (MU), comprised of a motoneuron and its innervated fibres. MUs have been investigated in neurophysiology research and clinical applications, primarily using electromyographic (EMG) techniques. Nonetheless, EMG (both surface and intramuscular) has a limited detection volume. A recent alternative approach to detect MUs is ultrafast ultrasound (UUS) imaging. The possibility of identifying MU activity from UUS has been shown by blind source separation (BSS) of UUS images, using optimal separation spatial filters. However, this approach has yet to be fully compared with EMG techniques for a large population of unique MU spike trains. Here we identify individual MU activity in UUS images using the BSS method for 401 MU spike trains from eleven participants based on concurrent recordings of either surface or intramuscular EMG from forces up to 30% of the maximum voluntary contraction (MVC) force. We assessed the BSS method's ability to identify MU spike trains from direct comparison with the EMG-derived spike trains as well as twitch areas and temporal profiles from comparison with the spike-triggered-averaged UUS images when using the EMG-derived spikes as triggers. We found a moderate rate of correctly identified spikes (53.0 ± 16.0%) with respect to the EMG-identified firings. However, the MU twitch areas and temporal profiles could still be identified accurately, including at 30% MVC force. These results suggest that the current BSS methods for UUS can accurately identify the location and average twitch of a large pool of MUs in UUS images, providing potential avenues for studying neuromechanics from a large cross-section of the muscle. On the other hand, more advanced methods are needed to address the convolutive and partly non-linear summation of velocities for recovering the full spike trains.
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Affiliation(s)
- Robin Rohlén
- Department of Biomedical Engineering, Lund University, Lund, Sweden.
| | - Emma Lubel
- Department of Bioengineering, Imperial College London, London, UK
| | | | | | - Dario Farina
- Department of Bioengineering, Imperial College London, London, UK.
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Mandeville R, Deshmukh S, Tan ET, Kumar V, Sanchez B, Dowlatshahi AS, Luk J, See RHB, Leochico CFD, Thum JA, Bazarek S, Johnston B, Brown J, Wu J, Sneag D, Rutkove S. A scoping review of current and emerging techniques for evaluation of peripheral nerve health, degeneration and regeneration: part 2, non-invasive imaging. J Neural Eng 2023; 20:041002. [PMID: 37369193 DOI: 10.1088/1741-2552/ace217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 06/27/2023] [Indexed: 06/29/2023]
Abstract
Peripheral neuroregenerative research and therapeutic options are expanding exponentially. With this expansion comes an increasing need to reliably evaluate and quantify nerve health. Valid and responsive measures of the nerve status are essential for both clinical and research purposes for diagnosis, longitudinal follow-up, and monitoring the impact of any intervention. Furthermore, novel biomarkers can elucidate regenerative mechanisms and open new avenues for research. Without such measures, clinical decision-making is impaired, and research becomes more costly, time-consuming, and sometimes infeasible. Part 1 of this two-part scoping review focused on neurophysiology. In part 2, we identify and critically examine many current and emerging non-invasive imaging techniques that have the potential to evaluate peripheral nerve health, particularly from the perspective of regenerative therapies and research.
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Affiliation(s)
- Ross Mandeville
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, United States of America
| | - Swati Deshmukh
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA 02215, United States of America
| | - Ek Tsoon Tan
- Department of Radiology, Hospital for Special Surgery, New York, NY 10021, United States of America
| | - Viksit Kumar
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States of America
| | - Benjamin Sanchez
- Department Electrical and Computer Engineering, University of Utah, Salt Lake City, UT 84112, United States of America
| | - Arriyan S Dowlatshahi
- Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA 02215, United States of America
| | - Justin Luk
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States of America
| | - Reiner Henson B See
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, United States of America
| | - Carl Froilan D Leochico
- Department of Physical Medicine and Rehabilitation, St. Luke's Medical Center, Global City, Taguig, The Philippines
- Department of Rehabilitation Medicine, Philippine General Hospital, University of the Philippines Manila, Manila, The Philippines
| | - Jasmine A Thum
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States of America
| | - Stanley Bazarek
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA 02115, United States of America
| | - Benjamin Johnston
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA 02115, United States of America
| | - Justin Brown
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States of America
| | - Jim Wu
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA 02215, United States of America
| | - Darryl Sneag
- Department of Radiology, Hospital for Special Surgery, New York, NY 10021, United States of America
| | - Seward Rutkove
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, United States of America
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Grönlund C, Rohlén R. Ultrafast ultrasound imaging can be used to access single motor units in deep muscles, but the underlying biomechanical source remains to be understood. J Electromyogr Kinesiol 2023; 71:102797. [PMID: 37348262 DOI: 10.1016/j.jelekin.2023.102797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/24/2023] [Accepted: 06/16/2023] [Indexed: 06/24/2023] Open
Affiliation(s)
- Christer Grönlund
- Department of Radiation Sciences, Radiation Physics, Biomedical Engineering, Umeå University, Umeå, Sweden
| | - Robin Rohlén
- Department of Radiation Sciences, Radiation Physics, Biomedical Engineering, Umeå University, Umeå, Sweden; Department of Biomedical Engineering, Lund University, Lund, Sweden.
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10
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Bromberg MB. Quantitative electrodiagnosis of the motor unit. HANDBOOK OF CLINICAL NEUROLOGY 2023; 195:271-286. [PMID: 37562872 DOI: 10.1016/b978-0-323-98818-6.00016-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Electromyography (EMG) focuses on assessment of the motor unit (MU), and a given muscle has several hundred MUs, each innervating hundreds of muscle fibers. Assessment is limited by the recording radius of electrodes, 1-2 fibers with single-fiber electrodes and 7-15 fibers with concentric or monopolar electrodes. Routine qualitative EMG studies rely on observing MUs in free-run mode and qualitatively estimating common metrics. In contrast, quantitative EMG (QEMG) applied to routine studies includes assessment of individual MUs by software available in modern EMG machines with extraction of discrete values for common metrics, and also derived metrics. This results in greater precision and statistical interpretation. Other QEMG techniques assess muscle fiber density within the MU and time variability at the neuromuscular junction. The interference pattern can also be assessed. The number of MUs innervating a muscle can be estimated. Advanced signal processing, called near-fiber EMG, allows for extraction of underlying muscle fiber contributions to MU waveforms. It is also possible to use QEMG to make statistical probabilities of the state of a muscle as to whether normal, myopathic, or neuropathic. Time to acquire QEMG data is minimal. QEMG is most useful in situations where pathology is uncertain.
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Affiliation(s)
- Mark B Bromberg
- Department of Neurology, University of Utah, Salt Lake City, UT, United States.
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11
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Maitland S, Hall J, McNeill A, Stenberg B, Schofield I, Whittaker R. Ultrasound-guided motor unit scanning electromyography. Muscle Nerve 2022; 66:730-735. [PMID: 36106775 PMCID: PMC9828660 DOI: 10.1002/mus.27720] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 09/04/2022] [Accepted: 09/11/2022] [Indexed: 01/12/2023]
Abstract
INTRODUCTION/AIMS Measuring the spatial dimensions of a single motor unit remains a challenging problem, and current techniques, such as scanning electromyography (EMG), tend to underestimate the true dimensions. In this study we aimed to estimate more accurately the dimensions of a single motor unit by developing a clinically applicable scanning EMG protocol that utilizes ultrasound imaging to visualize and target a transect through the center of a single motor unit. METHODS Single motor unit twitches in the tibialis anterior muscles of healthy volunteers were elicited via stimulation of the fibular nerve, visualized with ultrasound, and targeted with an intramuscular EMG electrode. The electrode was moved by hand in small steps through the motor unit territory. Ultrasound video output was synchronized to EMG capture, and the needle position was tracked at each step. RESULTS Eight recordings from six participants were collected. The technique was quick and easy to perform (mean time, 6.1 minutes) with reasonable spatial resolution (mean step size, 1.85 mm), yielding motor unit territory sizes between 1.53 and 14.65 mm (mean, 7.15 mm). DISCUSSION Ultrasound-guided motor unit scanning EMG is a quick and accurate method for obtaining a targeted motor unit transect. This combination of two readily available clinical tools provides insights into the dimensions and internal structure of the motor unit as a marker for neuromuscular conditions.
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Affiliation(s)
- Stuart Maitland
- Translational and Clinical Research Institute, Henry Wellcome Building for NeuroecologyNewcastle UniversityNewcastle upon TyneUK
| | - Julie Hall
- Newcastle Upon Tyne Hospitals NHS TrustNewcastle upon TyneUK
| | - Andrew McNeill
- Newcastle Upon Tyne Hospitals NHS TrustNewcastle upon TyneUK
| | - Ben Stenberg
- Newcastle Upon Tyne Hospitals NHS TrustNewcastle upon TyneUK
| | - Ian Schofield
- Translational and Clinical Research Institute, Henry Wellcome Building for NeuroecologyNewcastle UniversityNewcastle upon TyneUK
| | - Roger Whittaker
- Translational and Clinical Research Institute, Henry Wellcome Building for NeuroecologyNewcastle UniversityNewcastle upon TyneUK,Newcastle Upon Tyne Hospitals NHS TrustNewcastle upon TyneUK
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12
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Optimization and comparison of two methods for spike train estimation in an unfused tetanic contraction of low threshold motor units. J Electromyogr Kinesiol 2022; 67:102714. [PMID: 36209700 DOI: 10.1016/j.jelekin.2022.102714] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 09/02/2022] [Accepted: 09/28/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Recent findings have shown that imaging voluntarily activated motor units (MUs) by decomposing ultrasound-based displacement images provides estimates of unfused tetanic signals evoked by spinal motoneurons' neural discharges (spikes). Two methods have been suggested to estimate its spike trains: band-pass filter (BPM) and Haar wavelet transform (HWM). However, the methods' optimal parameters and which method performs the best are unknown. This study will answer these questions. METHOD HWM and BPM were optimized using simulations. Their performance was evaluated based on simulations and 21 experimental datasets, considering their rate of agreement, spike offset, and spike offset variability to the simulated or experimental spikes. RESULTS A range of parameter sets that resulted in the highest possible agreement with simulated spikes was provided. Both methods highly agreed with simulated and experimental spikes, but HWM was a better spike estimation method than BPM because it had a higher agreement, less bias, and less variation (p < 0.001). CONCLUSIONS The optimized HWM will be an important contributor to further developing the identification and analysis of MUs using imaging, providing indirect access to the neural drive of the spinal cord to the muscle by the unfused tetanic signals.
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Lubel E, Grandi-Sgambato B, Barsakcioglu DY, Ibanez J, Tang MX, Farina D. Kinematics of individual muscle units in natural contractions measured in vivo using ultrafast ultrasound. J Neural Eng 2022; 19. [PMID: 36001952 DOI: 10.1088/1741-2552/ac8c6c] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/24/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The study of human neuromechanical control at the motor unit (MU) level has predominantly focussed on electrical activity and force generation, whilst the link between these, i.e., the muscle deformation, has not been widely studied. To address this gap, we analysed the kinematics of muscle units in natural contractions. APPROACH We combined high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) recordings, at 1000 frames per second, from the tibialis anterior muscle to measure the motion of the muscular tissue caused by individual MU contractions. The MU discharge times were identified online by decomposition of the HDsEMG and provided as biofeedback to 12 subjects who were instructed to keep the MU active at the minimum discharge rate (9.8 ± 4.7 pulses per second; force less than 10% of the maximum). The series of discharge times were used to identify the velocity maps associated with 51 single muscle unit movements with high spatio-temporal precision, by a novel processing method on the concurrently recorded US images. From the individual MU velocity maps, we estimated the region of movement, the duration of the motion, the contraction time, and the excitation-contraction (E-C) coupling delay. MAIN RESULTS Individual muscle unit motions could be reliably identified from the velocity maps in 10 out of 12 subjects. The duration of the motion, total contraction time, and E-C coupling were 17.9 ± 5.3 ms, 56.6 ± 8.4 ms, and 3.8 ± 3.0 ms (n = 390 across 10 participants). The experimental measures also provided the first evidence of muscle unit twisting during voluntary contractions and MU territories with distinct split regions. SIGNIFICANCE The proposed method allows for the study of kinematics of individual MU twitches during natural contractions. The described measurements and characterisations open new avenues for the study of neuromechanics in healthy and pathological conditions.
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Affiliation(s)
- Emma Lubel
- Department of Bioengineering, Imperial College London, Exhibition Road, London, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Bruno Grandi-Sgambato
- Department of Bioengineering, Imperial College London, Exhibition road, London, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Deren Y Barsakcioglu
- Department of Bioengineering, Imperial College London, Exhibition road, London, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Jaime Ibanez
- Bioengineering Group, Imperial College London, Engineering, London, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Meng-Xing Tang
- Department of Bioengineering, Imperial College London, Department of Bioeng, London, -- Select One --, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Dario Farina
- Department of Bioengineering, Imperial College London, Exhibition road, London, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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Verschueren A, Palminha C, Delmont E, Attarian S. Changes in neuromuscular function in elders: Novel techniques for assessment of motor unit loss and motor unit remodeling with aging. Rev Neurol (Paris) 2022; 178:780-787. [PMID: 35863917 DOI: 10.1016/j.neurol.2022.03.019] [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: 01/19/2022] [Revised: 03/08/2022] [Accepted: 03/08/2022] [Indexed: 11/24/2022]
Abstract
Functional muscle fiber denervation is a major contributor to the decline in physical function observed with aging and is now a recognized cause of sarcopenia, a muscle disorder characterized by progressive and generalized degenerative loss of skeletal muscle mass, quality, and strength. There is an interrelationship between muscle strength, motor unit (MU) number, and aging, which suggests that a portion of muscle weakness in seniors may be attributable to the loss of functional MUs. During normal aging, there is a time-related progression of MU loss, an adaptive sprouting followed by a maladaptive sprouting, and continuing recession of terminal Schwann cells leading to a reduced capacity for compensatory reinnervation in elders. In amyotrophic lateral sclerosis, increasing age at onset predicts worse survival ALS and it is possible that age-related depletion of the motor neuron pool may worsen motor neuron disease. MUNE methods are used to estimate the number of functional MU, data from MUNIX arguing for motor neuron loss with aging will be reviewed. Recently, a new MRI technique MU-MRI could be used to assess the MU recruitment or explore the activity of a single MU. This review presents published studies on the changes of neuromuscular function with aging, then focusing on these two novel techniques for assessment of MU loss and MU remodeling.
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Affiliation(s)
- A Verschueren
- Reference Centre for Neuromuscular Disorders and ALS, CHU La Timone, Aix-Marseille University, 264, rue Saint Pierre, 13005 Marseille, France.
| | - C Palminha
- Reference Centre for Neuromuscular Disorders and ALS, CHU La Timone, Aix-Marseille University, 264, rue Saint Pierre, 13005 Marseille, France
| | - E Delmont
- Reference Centre for Neuromuscular Disorders and ALS, CHU La Timone, Aix-Marseille University, 264, rue Saint Pierre, 13005 Marseille, France
| | - S Attarian
- Reference Centre for Neuromuscular Disorders and ALS, CHU La Timone, Aix-Marseille University, 264, rue Saint Pierre, 13005 Marseille, France
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15
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Ali H, Umander J, Rohlén R, Röhrle O, Grönlund C. Modelling intra-muscular contraction dynamics using in silico to in vivo domain translation. Biomed Eng Online 2022; 21:46. [PMID: 35804415 PMCID: PMC9270806 DOI: 10.1186/s12938-022-01016-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 06/20/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Advances in sports medicine, rehabilitation applications and diagnostics of neuromuscular disorders are based on the analysis of skeletal muscle contractions. Recently, medical imaging techniques have transformed the study of muscle contractions, by allowing identification of individual motor units' activity, within the whole studied muscle. However, appropriate image-based simulation models, which would assist the continued development of these new imaging methods are missing. This is mainly due to a lack of models that describe the complex interaction between tissues within a muscle and its surroundings, e.g., muscle fibres, fascia, vasculature, bone, skin, and subcutaneous fat. Herein, we propose a new approach to overcome this limitation. METHODS In this work, we propose to use deep learning to model the authentic intra-muscular skeletal muscle contraction pattern using domain-to-domain translation between in silico (simulated) and in vivo (experimental) image sequences of skeletal muscle contraction dynamics. For this purpose, the 3D cycle generative adversarial network (cycleGAN) models were evaluated on several hyperparameter settings and modifications. The results show that there were large differences between the spatial features of in silico and in vivo data, and that a model could be trained to generate authentic spatio-temporal features similar to those obtained from in vivo experimental data. In addition, we used difference maps between input and output of the trained model generator to study the translated characteristics of in vivo data. RESULTS This work provides a model to generate authentic intra-muscular skeletal muscle contraction dynamics that could be used to gain further and much needed physiological and pathological insights and assess and overcome limitations within the newly developed research field of neuromuscular imaging.
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Affiliation(s)
- Hazrat Ali
- Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | | | - Robin Rohlén
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Oliver Röhrle
- Stuttgart Center for Simulation Technology (SC SimTech), University of Stuttgart, Stuttgart, Germany
- Institute for Modelling and Simulation of Biomechanical Systems, Chair for Computational Biophysics and Biorobotics, University of Stuttgart, Stuttgart, Germany
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16
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de Carvalho M, Swash M. Imaging motor unit territory. Clin Neurophysiol 2022; 141:88-89. [DOI: 10.1016/j.clinph.2022.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Accepted: 06/20/2022] [Indexed: 11/24/2022]
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17
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Heskamp L, Miller AR, Birkbeck MG, Hall J, Schofield I, Blamire AM, Whittaker RG. In vivo 3D imaging of human motor units in upper and lower limb muscles. Clin Neurophysiol 2022; 141:91-100. [PMID: 35853787 DOI: 10.1016/j.clinph.2022.05.018] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 05/17/2022] [Accepted: 05/30/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To assess in-vivo cross-sectional and 3D morphology of human motor units in hand, forearm and lower leg muscles using magnetic resonance imaging (MRI). METHODS Diffusion weighted MRI was used with in-scanner electrical stimulation in healthy controls to image motor units at a single slice in lower leg, forearm and hand muscles (n = 6) and multiple slices in the lower leg for 3D assessment (n = 7). RESULTS Motor unit cross-sectional area (CSA) and maximum Feret diameter (FDmax) did not differ between the lower leg (CSA: 22.4 ± 8.4 mm2; FDmax: 8.7 ± 2.4 mm), forearm (CSA: 23.6 ± 14.1 mm2; FDmax: 9.0 ± 3.3 mm) and hand (CSA: 26.8 ± 12.8 mm2 and FDmax: 9.6 ± 2.7 mm) (ANOVA; p = 0.487 and p = 0.587, respectively). Lower leg motor units were 8.0 ± 3.8 cm long with largest CSA in the motor unit's middle section. 3D motor unit imaging revealed a complex structure with several units splitting and re-forming along their length. CONCLUSIONS Motor unit MRI (MUMRI) can be applied to upper limb muscles, and can reveal the 3D structure of human motor units in-vivo. SIGNIFICANCE MUMRI provides the first in-vivo 2D images of upper limb motor units and 3D images of lower leg motor units. 3D imaging suggest a more complex human motor unit structure than previously thought.
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Maitland S, Escobedo-Cousin E, Schofield I, O'Neill A, Baker S, Whittaker R. Electrical cross-sectional imaging of human motor units in vivo. Clin Neurophysiol 2022; 136:82-92. [DOI: 10.1016/j.clinph.2021.12.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 12/13/2021] [Accepted: 12/30/2021] [Indexed: 11/03/2022]
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de Meeûs d'Argenteuil C, Boshuizen B, Vidal Moreno de Vega C, Leybaert L, de Maré L, Goethals K, De Spiegelaere W, Oosterlinck M, Delesalle C. Comparison of Shifts in Skeletal Muscle Plasticity Parameters in Horses in Three Different Muscles, in Answer to 8 Weeks of Harness Training. Front Vet Sci 2021; 8:718866. [PMID: 34733900 PMCID: PMC8558477 DOI: 10.3389/fvets.2021.718866] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 09/07/2021] [Indexed: 12/02/2022] Open
Abstract
Training-induced follow-up of multiple muscle plasticity parameters in postural stability vs. locomotion muscles provides an integrative physiological view on shifts in the muscular metabolic machinery. It can be expected that not all muscle plasticity parameters show the same expression time profile across muscles. This knowledge is important to underpin results of metabolomic studies. Twelve non-competing Standardbred mares were subjected to standardized harness training. Muscle biopsies were taken on a non-training day before and after 8 weeks. Shifts in muscle fiber type composition and muscle fiber cross-sectional area (CSA) were compared in the m. pectoralis, the m. vastus lateralis, and the m. semitendinosus. In the m. vastus lateralis, which showed most pronounced training-induced plasticity, two additional muscle plasticity parameters (capillarization and mitochondrial density) were assessed. In the m. semitendinosus, additionally the mean minimum Feret's diameter was assessed. There was a significant difference in baseline profiles. The m. semitendinosus contained less type I and more type IIX fibers compatible with the most pronounced anaerobic profile. Though no baseline fiber type-specific and overall mean CSA differences could be detected, there was a clear post-training decrease in fiber type specific CSA, most pronounced for the m. vastus lateralis, and this was accompanied by a clear increase in capillary supply. No shifts in mitochondrial density were detected. The m. semitendinosus showed a decrease in fiber type specific CSA of type IIAX fibers and a decrease of type I fiber Feret's diameter as well as mean minimum Feret's diameter. The training-induced increased capillary supply in conjunction with a significant decrease in muscle fiber CSA suggests that the muscular machinery models itself toward an optimal smaller individual muscle fiber structure to receive and process fuels that can be swiftly delivered by the circulatory system. These results are interesting in view of the recently identified important fuel candidates such as branched-chain amino acids, aromatic amino acids, and gut microbiome-related xenobiotics, which need a rapid gut-muscle gateway to reach these fibers and are less challenging for the mitochondrial system. More research is needed with that respect. Results also show important differences between muscle groups with respect to baseline and training-specific modulation.
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Affiliation(s)
- Constance de Meeûs d'Argenteuil
- Department of Translational Physiology, Infectiology and Public Health, Research Group of Comparative Physiology, Faculty of Veterinary Medicine, Research Group of Comparative Physiology, Ghent University, Merelbeke, Belgium
| | - Berit Boshuizen
- Department of Translational Physiology, Infectiology and Public Health, Research Group of Comparative Physiology, Faculty of Veterinary Medicine, Research Group of Comparative Physiology, Ghent University, Merelbeke, Belgium
- Wolvega Equine Hospital, Oldeholtpade, Netherlands
| | - Carmen Vidal Moreno de Vega
- Department of Translational Physiology, Infectiology and Public Health, Research Group of Comparative Physiology, Faculty of Veterinary Medicine, Research Group of Comparative Physiology, Ghent University, Merelbeke, Belgium
| | - Luc Leybaert
- Department of Basic and Applied Medical Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Lorie de Maré
- Department of Translational Physiology, Infectiology and Public Health, Research Group of Comparative Physiology, Faculty of Veterinary Medicine, Research Group of Comparative Physiology, Ghent University, Merelbeke, Belgium
| | - Klara Goethals
- Department of Veterinary and Biosciences, Faculty of Veterinary Medicine, Research Group Biometrics, Ghent University, Merelbeke, Belgium
| | - Ward De Spiegelaere
- Department of Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Maarten Oosterlinck
- Department of Large Animal Surgery, Anaesthesia and Orthopaedics, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Cathérine Delesalle
- Department of Translational Physiology, Infectiology and Public Health, Research Group of Comparative Physiology, Faculty of Veterinary Medicine, Research Group of Comparative Physiology, Ghent University, Merelbeke, Belgium
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20
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Roesl C, Evans ER, Dissanayake KN, Boczonadi V, Jones RA, Jordan GR, Ledahawsky L, Allen GCC, Scott M, Thomson A, Wishart TM, Hughes DI, Mead RJ, Shone CC, Slater CR, Gillingwater TH, Skehel PA, Ribchester RR. Confocal Endomicroscopy of Neuromuscular Junctions Stained with Physiologically Inert Protein Fragments of Tetanus Toxin. Biomolecules 2021; 11:1499. [PMID: 34680132 PMCID: PMC8534034 DOI: 10.3390/biom11101499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 10/07/2021] [Accepted: 10/08/2021] [Indexed: 01/09/2023] Open
Abstract
Live imaging of neuromuscular junctions (NMJs) in situ has been constrained by the suitability of ligands for inert vital staining of motor nerve terminals. Here, we constructed several truncated derivatives of the tetanus toxin C-fragment (TetC) fused with Emerald Fluorescent Protein (emGFP). Four constructs, namely full length emGFP-TetC (emGFP-865:TetC) or truncations comprising amino acids 1066-1315 (emGFP-1066:TetC), 1093-1315 (emGFP-1093:TetC) and 1109-1315 (emGFP-1109:TetC), produced selective, high-contrast staining of motor nerve terminals in rodent or human muscle explants. Isometric tension and intracellular recordings of endplate potentials from mouse muscles indicated that neither full-length nor truncated emGFP-TetC constructs significantly impaired NMJ function or transmission. Motor nerve terminals stained with emGFP-TetC constructs were readily visualised in situ or in isolated preparations using fibre-optic confocal endomicroscopy (CEM). emGFP-TetC derivatives and CEM also visualised regenerated NMJs. Dual-waveband CEM imaging of preparations co-stained with fluorescent emGFP-TetC constructs and Alexa647-α-bungarotoxin resolved innervated from denervated NMJs in axotomized WldS mouse muscle and degenerating NMJs in transgenic SOD1G93A mouse muscle. Our findings highlight the region of the TetC fragment required for selective binding and visualisation of motor nerve terminals and show that fluorescent derivatives of TetC are suitable for in situ morphological and physiological characterisation of healthy, injured and diseased NMJs.
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Affiliation(s)
- Cornelia Roesl
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Elizabeth R. Evans
- Public Health England, National Infection Service, Porton Down, Salisbury SP4 0JG, UK; (E.R.E.); (C.C.S.)
| | - Kosala N. Dissanayake
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Veronika Boczonadi
- Applied Neuromuscular Junction Facility, Bio-Imaging Unit, Biosciences Institute, University of Newcastle-upon-Tyne, Framlington Place, Newcastle-upon-Tyne NE2 4HH, UK; (V.B.); (C.R.S.)
| | - Ross A. Jones
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Graeme R. Jordan
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Leire Ledahawsky
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Guy C. C. Allen
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Molly Scott
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Alanna Thomson
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Thomas M. Wishart
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, College of Medicine and Veterinary Medicine, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG, UK;
| | - David I. Hughes
- Spinal Cord Research Group, Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QQ, UK;
| | - Richard J. Mead
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Glossop Road, Sheffield S10 2HQ, UK;
| | - Clifford C. Shone
- Public Health England, National Infection Service, Porton Down, Salisbury SP4 0JG, UK; (E.R.E.); (C.C.S.)
| | - Clarke R. Slater
- Applied Neuromuscular Junction Facility, Bio-Imaging Unit, Biosciences Institute, University of Newcastle-upon-Tyne, Framlington Place, Newcastle-upon-Tyne NE2 4HH, UK; (V.B.); (C.R.S.)
| | - Thomas H. Gillingwater
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Paul A. Skehel
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
| | - Richard R. Ribchester
- Centre for Discovery Brain Sciences and the Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, George Square, Edinburgh EH8 9XD, UK; (C.R.); (K.N.D.); (R.A.J.); (G.R.J.); (L.L.); (G.C.C.A.); (M.S.); (A.T.); (T.H.G.)
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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: 1.8] [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.
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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
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22
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Tullo E, Dodds RM, Birkbeck M, Habiballa L, Sayer AA. Paving the translational ageing research pathway-training the next generation of researchers. Age Ageing 2021; 50:362-365. [PMID: 33156893 DOI: 10.1093/ageing/afaa233] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Indexed: 11/12/2022] Open
Abstract
Ageing is an archetypal translational research topic, spanning a breadth of academic disciplines. This poses challenges for researchers aiming to act upon laboratory findings to develop and implement interventions that directly benefit older people. Divisions between distinct academic research cultures present barriers to collaborative working. We present potential strategies to improve the translation of ageing research with examples of successful projects working across disciplines. Researchers and clinicians in ageing should be supported to develop a translational interest and receive specific training about translational research.
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Affiliation(s)
- Ellen Tullo
- Age Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle-upon-Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle-upon-Tyne NE4 5PL, UK
| | - Richard M Dodds
- Age Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle-upon-Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle-upon-Tyne NE4 5PL, UK
| | - Matthew Birkbeck
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle-upon-Tyne NE4 5PL, UK
| | - Leena Habiballa
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle-upon-Tyne NE4 5PL, UK
| | - Avan Aihie Sayer
- Age Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle-upon-Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle-upon-Tyne NE4 5PL, UK
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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: 0.5] [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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24
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Birkbeck MG, Blamire AM, Whittaker RG, Sayer AA, Dodds RM. The role of novel motor unit magnetic resonance imaging to investigate motor unit activity in ageing skeletal muscle. J Cachexia Sarcopenia Muscle 2021; 12:17-29. [PMID: 33354940 PMCID: PMC7890268 DOI: 10.1002/jcsm.12655] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 10/27/2020] [Accepted: 11/05/2020] [Indexed: 12/14/2022] Open
Abstract
Sarcopenia is a progressive and generalized disease, more common in older adults, which manifests as a loss of muscle strength and mass. The pathophysiology of sarcopenia is still poorly understood with many mechanisms suggested. Age associated changes to the neuromuscular architecture, including motor units and their constituent muscle fibres, represent one such mechanism. Electromyography can be used to distinguish between different myopathies and produce counts of motor units. Evidence from electromyography studies suggests that with age, there is a loss of motor units, increases to the sizes of remaining units, and changes to their activity patterns. However, electromyography is invasive, can be uncomfortable, does not reveal the exact spatial position of motor units within muscle and is difficult to perform in deep muscles. We present a novel diffusion-weighted magnetic resonance imaging technique called 'motor unit magnetic resonance imaging (MUMRI)'. MUMRI aims to improve our understanding of the changes to the neuromuscular system associated with ageing, sarcopenia and other neuromuscular diseases. To date, we have demonstrated that MUMRI can be used to detect statistically significant differences in fasciculation rate of motor units between (n = 4) patients with amyotrophic lateral sclerosis (mean age ± SD: 53 ± 15) and a group of (n = 4) healthy controls (38 ± 7). Patients had significantly higher rates of fasciculation compared with healthy controls (mean = 99.1/min, range = 25.7-161.0 in patients vs. 7.7/min, range = 4.3-9.7 in controls; P < 0.05. MUMRI has detected differences in size, shape, and distribution of single human motor units between (n = 5) young healthy volunteers (29 ± 2.2) and (n = 5) healthy older volunteers (65.6 ± 14.8). The maximum size of motor unit territories in the older group was 12.4 ± 3.3 mm and 9.7 ± 2.7 mm in the young group; P < 0.05. MUMRI is an entirely non-invasive tool, which can be used to detect physiological and pathological changes to motor units in neuromuscular diseases. MUMRI also has the potential to be used as an intermediate outcome measure in sarcopenia trials.
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Affiliation(s)
- Matthew G Birkbeck
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.,NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.,Northern Medical Physics and Clinical Engineering, Freeman Hospital, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Andrew M Blamire
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Roger G Whittaker
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Avan Aihie Sayer
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.,NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Richard M Dodds
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.,NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
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25
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Rohlén R, Stålberg E, Grönlund C. Identification of single motor units in skeletal muscle under low force isometric voluntary contractions using ultrafast ultrasound. Sci Rep 2020; 10:22382. [PMID: 33361807 PMCID: PMC7759573 DOI: 10.1038/s41598-020-79863-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 12/14/2020] [Indexed: 01/23/2023] Open
Abstract
The central nervous system (CNS) controls skeletal muscles by the recruitment of motor units (MUs). Understanding MU function is critical in the diagnosis of neuromuscular diseases, exercise physiology and sports, and rehabilitation medicine. Recording and analyzing the MUs’ electrical depolarization is the basis for state-of-the-art methods. Ultrafast ultrasound is a method that has the potential to study MUs because of the electrical depolarizations and consequent mechanical twitches. In this study, we evaluate if single MUs and their mechanical twitches can be identified using ultrafast ultrasound imaging of voluntary contractions. We compared decomposed spatio-temporal components of ultrasound image sequences against the gold standard needle electromyography. We found that 31% of the MUs could be successfully located and their firing pattern extracted. This method allows new non-invasive opportunities to study mechanical properties of MUs and the CNS control in neuromuscular physiology.
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Affiliation(s)
- Robin Rohlén
- Department of Radiation Sciences, Biomedical Engineering, Umeå University, Umeå, Sweden.
| | - Erik Stålberg
- Department of Clinical Neurophysiology, Institute of Neuroscience, Uppsala University, Uppsala, Sweden.,Department of Neurosciences, University Hospital, Uppsala, Sweden
| | - Christer Grönlund
- Department of Radiation Sciences, Biomedical Engineering, Umeå University, Umeå, Sweden
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26
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Goedee HS, Sleutjes BTHM, Bakers JNE, Kruithof WJ, Kruitwagen-van Reenen ET, van der Pol WL. Electrophysiology of fatigue in chronic inflammatory demyelinating polyneuropathy: Can it be useful? Clin Neurophysiol 2020; 131:2912-2914. [PMID: 33250076 DOI: 10.1016/j.clinph.2020.09.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 09/30/2020] [Indexed: 11/26/2022]
Affiliation(s)
- H Stephan Goedee
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, the Netherlands.
| | - Boudewijn T H M Sleutjes
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, the Netherlands
| | - Jaap N E Bakers
- Department of Rehabilitation, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, the Netherlands
| | - Willeke J Kruithof
- Department of Rehabilitation, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, the Netherlands
| | | | - W Ludo van der Pol
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, UMC Utrecht, Utrecht, the Netherlands
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27
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de Carvalho M, Swash M. Motor unit estimation by MRI: Integrating old and new ideas. Clin Neurophysiol 2020; 131:1379-1380. [PMID: 32201104 DOI: 10.1016/j.clinph.2020.03.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 03/04/2020] [Indexed: 10/24/2022]
Affiliation(s)
- Mamede de Carvalho
- Instituto de Fisiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Univeridade de Lisboa, Lisbon, Portugal; Department of Neurosciences and Mental Health, Hospital de Santa Maria, Centro Hospitalar Universitário de Lisboa Norte, Lisbon, Portugal.
| | - Michael Swash
- Instituto de Fisiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Univeridade de Lisboa, Lisbon, Portugal; Departments of Neurology and Neuroscience, Barts and the London School of Medicine, Queen Mary University of London and Royal London Hospital, UK
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