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Schwartz M. Editorial for "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; 60:218-219. [PMID: 37823331 DOI: 10.1002/jmri.29067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 09/29/2023] [Indexed: 10/13/2023] Open
Affiliation(s)
- Martin Schwartz
- Section on Experimental Radiology, Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany
- Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany
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2
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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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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] [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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6
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Raya JG, Duarte A, Wang N, Mazzoli V, Jaramillo D, Blamire AM, Dietrich O. Applications of Diffusion-Weighted MRI to the Musculoskeletal System. J Magn Reson Imaging 2024; 59:376-396. [PMID: 37477576 DOI: 10.1002/jmri.28870] [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: 02/22/2023] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 07/22/2023] Open
Abstract
Diffusion-weighted imaging (DWI) is an established MRI technique that can investigate tissue microstructure at the scale of a few micrometers. Musculoskeletal tissues typically have a highly ordered structure to fulfill their functions and therefore represent an optimal application of DWI. Even more since disruption of tissue organization affects its biomechanical properties and may indicate irreversible damage. The application of DWI to the musculoskeletal system faces application-specific challenges on data acquisition including susceptibility effects, the low T2 relaxation time of most musculoskeletal tissues (2-70 msec) and the need for sub-millimetric resolution. Thus, musculoskeletal applications have been an area of development of new DWI methods. In this review, we provide an overview of the technical aspects of DWI acquisition including diffusion-weighting, MRI pulse sequences and different diffusion regimes to study tissue microstructure. For each tissue type (growth plate, articular cartilage, muscle, bone marrow, intervertebral discs, ligaments, tendons, menisci, and synovium), the rationale for the use of DWI and clinical studies in support of its use as a biomarker are presented. The review describes studies showing that DTI of the growth plate has predictive value for child growth and that DTI of articular cartilage has potential to predict the radiographic progression of joint damage in early stages of osteoarthritis. DTI has been used extensively in skeletal muscle where it has shown potential to detect microstructural and functional changes in a wide range of muscle pathologies. DWI of bone marrow showed to be a valuable tool for the diagnosis of benign and malignant acute vertebral fractures and bone metastases. DTI and diffusion kurtosis have been investigated as markers of early intervertebral disc degeneration and lower back pain. Finally, promising new applications of DTI to anterior cruciate ligament grafts and synovium are presented. The review ends with an overview of the use of DWI in clinical routine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- José G Raya
- Department of Radiology, NYU Langone Health, New York, New York, USA
| | - Alejandra Duarte
- Division of Musculoskeletal Radiology, Department of Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, Indiana, USA
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, Indiana, USA
| | - Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Diego Jaramillo
- Department of Radiology, Columbia University Medical Center, New York, New York, USA
| | - Andrew M Blamire
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Olaf Dietrich
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
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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. [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.
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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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de Carvalho M, Swash M. Diagnosis and differential diagnosis of MND/ALS: IFCN handbook chapter. Clin Neurophysiol Pract 2023; 9:27-38. [PMID: 38249779 PMCID: PMC10796809 DOI: 10.1016/j.cnp.2023.12.003] [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: 08/23/2023] [Revised: 11/01/2023] [Accepted: 12/07/2023] [Indexed: 01/23/2024] Open
Abstract
•Accurate and rapid diagnosis of amyotrophic lateral sclerosis (ALS) is important to prevent erroneous interventions. •The recent Gold Coast criteria are easily applicable and have high sensitivity and specificity. •Future developments will help to distinguish ALS as a specific clinical-pathologic entity. Accurate and rapid diagnosis of amyotrophic lateral sclerosis (ALS) is essential in order to provide accurate information for patient and family, to avoid time-consuming investigations and to permit an appropriate management plan. ALS is variable regarding presentation, disease progression, genetic profile and patient reaction to the diagnosis. It is obviously important to exclude treatable conditions but, in most patients, for experienced neurologists the diagnosis is clear-cut, depending on the presence of progressive upper and lower motor neuron signs. Patients with signs of restricted lower motor neuron (LMN) or upper motor neuron (UMN) dysfunction may present diagnostic difficulty, but electromyography (EMG) is often a determinant diagnostic test since it may exclude other disorders. Transcranial magnetic stimulation may aid detection of UMN dysfunction, and brain and spinal cord MRI, ultrasound and blood neurofilament measurements, have begun to have clinical impact, although none are themselves diagnostic tests. Several sets of diagnostic criteria have been proposed in the past; all rely on clinical LMN and UMN signs in different anatomic territories, EMG changes, exclusion of other disorders, and disease progression, in particular evidence of spreading to other anatomic territories. Fasciculations are a characteristic clinical feature and increased importance is now attached to fasciculation potentials detected by EMG, when associated with classical signs of denervation and reinnervation. The Gold Coast diagnostic criteria rely on the presence of UMN and LMN signs in one (or more) anatomic territory, or LMN signs in two (or more) anatomic territories, recognizing the fundamental clinical requirements of disease progression and exclusion of other diseases. Recent studies confirm a high sensitivity without loss of specificity using these Gold Coast criteria. In considering the diagnosis of ALS a critical question for future understanding is whether ALS should be considered a syndrome or a specific clinico-pathologic entity; this can only be addressed in the light of more complete knowledge.
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Affiliation(s)
- Mamede de Carvalho
- Faculdade de Medicina- Instituto de Medicina Molecular, Centro de Estudos Egas Moniz, Universidade de Lisboa, Lisbon, Portugal
- Department of Neurosciences and Mental Health, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa-Norte, Lisbon, Portugal
| | - Michael Swash
- Faculdade de Medicina- Instituto de Medicina Molecular, Centro de Estudos Egas Moniz, Universidade de Lisboa, Lisbon, Portugal
- Departments of Neurology and Neurosciences, Barts and the London School of Medicine, Queen Mary University of London and Royal London Hospital, UK
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Rohlén R, Carbonaro M, Cerone GL, Meiburger KM, Botter A, Grönlund C. Spatially repeatable components from ultrafast ultrasound are associated with motor unit activity in human isometric contractions . J Neural Eng 2023; 20:046016. [PMID: 37437598 DOI: 10.1088/1741-2552/ace6fc] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 07/12/2023] [Indexed: 07/14/2023]
Abstract
Objective.Ultrafast ultrasound (UUS) imaging has been used to detect intramuscular mechanical dynamics associated with single motor units (MUs). Detecting MUs from ultrasound sequences requires decomposing a velocity field into components, each consisting of an image and a signal. These components can be associated with putative MU activity or spurious movements (noise). The differentiation between putative MUs and noise has been accomplished by comparing the signals with MU firings obtained from needle electromyography (EMG). Here, we examined whether the repeatability of the images over brief time intervals can serve as a criterion for distinguishing putative MUs from noise in low-force isometric contractions.Approach.UUS images and high-density surface EMG (HDsEMG) were recorded simultaneously from 99 MUs in the biceps brachii of five healthy subjects. The MUs identified through HDsEMG decomposition were used as a reference to assess the outcomes of the ultrasound-based components. For each contraction, velocity sequences from the same eight-second ultrasound recording were separated into consecutive two-second epochs and decomposed. To evaluate the repeatability of components' images across epochs, we calculated the Jaccard similarity coefficient (JSC). JSC compares the similarity between two images providing values between 0 and 1. Finally, the association between the components and the MUs from HDsEMG was assessed.Main results.All the MU-matched components had JSC > 0.38, indicating they were repeatable and accounted for about one-third of the HDsEMG-detected MUs (1.8 ± 1.6 matches over 4.9 ± 1.8 MUs). The repeatable components (JSC > 0.38) represented 14% of the total components (6.5 ± 3.3 components). These findings align with our hypothesis that intra-sequence repeatability can differentiate putative MUs from noise and can be used for data reduction.Significance.This study provides the foundation for developing stand-alone methods to identify MU in UUS sequences and towards real-time imaging of MUs. These methods are relevant for studying muscle neuromechanics and designing novel neural interfaces.
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Affiliation(s)
- Robin Rohlén
- Department of Biomedical Engineering, Lund University, Lund, Sweden
- Department of Radiation Sciences, Radiation Physics, Biomedical Engineering, Umeå University, Umeå, Sweden
| | - Marco Carbonaro
- Department of Electronics and Telecommunication, Laboratory for Engineering of the Neuromuscular System (LISiN), Politecnico di Torino, Turin, Italy
- PoliToBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Giacinto L Cerone
- Department of Electronics and Telecommunication, Laboratory for Engineering of the Neuromuscular System (LISiN), Politecnico di Torino, Turin, Italy
- PoliToBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Kristen M Meiburger
- PoliToBIOMed Lab, Politecnico di Torino, Turin, Italy
- Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
| | - Alberto Botter
- Department of Electronics and Telecommunication, Laboratory for Engineering of the Neuromuscular System (LISiN), Politecnico di Torino, Turin, Italy
- PoliToBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Christer Grönlund
- Department of Radiation Sciences, Radiation Physics, Biomedical Engineering, Umeå University, Umeå, Sweden
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German A, Türk M, Schramm A, Regensburger M. Bedeutung der Muskelsonographie in der Detektion von Faszikulationen
bei der ALS. KLIN NEUROPHYSIOL 2023. [DOI: 10.1055/a-2024-6346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
ZusammenfassungBei der amyotrophen Lateralsklerose sind Faszikulationen häufig bereits
in frühen Stadien in mehreren Körperregionen vorzufinden und
haben daher Eingang in die entsprechenden Leitlinien und Diagnosekriterien
gefunden. Während die invasive EMG-Diagnostik unverzichtbar zum Nachweis
von akut- und chronisch-neurogenen Veränderungen des elektrischen
Signalverhaltens motorischer Einheiten und zur Bestätigung von
Faszikulationspotenzialen bleibt, bietet die Muskelsonographie ein
hochsensitives Verfahren, um schnell und nicht-invasiv Faszikulationen in den
verschiedenen Muskel-Etagen zu erfassen. In dieser Übersichtsarbeit
stellen wir die bisherigen Daten zum Einsatz der Muskelsonographie zur
Faszikulationsdetektion dar. Durch ihren Einsatz ermöglicht die
Muskelsonographie im klinischen Alltag eine zielgerichtete und hierdurch
aussagekräftigere EMG-Diagnostik. Aktuelle Forschungsstudien zielen
darauf ab, Faszikulationen sonomorphologisch genauer zu charakterisieren, zu
quantifizieren und als Verlaufsparameter zu untersuchen.
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Affiliation(s)
- Alexander German
- Molekular-Neurologische Abteilung,
Friedrich-Alexander-Universität Erlangen-Nürnberg,
Erlangen
| | - Matthias Türk
- Neurologische Klinik, Friedrich-Alexander-Universität
Erlangen-Nürnberg, Erlangen
- Zentrum für Seltene Erkrankungen Erlangen (ZSEER),
Erlangen
| | | | - Martin Regensburger
- Molekular-Neurologische Abteilung,
Friedrich-Alexander-Universität Erlangen-Nürnberg,
Erlangen
- Zentrum für Seltene Erkrankungen Erlangen (ZSEER),
Erlangen
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Schwartz M, Yang B, Schick F. Classification-guided Neural Network-based Correction of Magnetic Resonance-related Gradient Artifact Residuals in Simultaneously Recorded Surface Electromyography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:3632-3635. [PMID: 36085922 DOI: 10.1109/embc48229.2022.9871062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Spontaneous muscular activities can be studied by simultaneous recordings of surface electromyography (sEMG) and diffusion-weighted magnetic resonance imaging (DW-MRI). For reliable assessment of the spontaneous activity rate in sEMG data during active MR imaging, it is necessary to have a decent gradient artifact (GA) correction algorithm enabling the detection of small spontaneous activities with an amplitude of few microvolts. In this work, a neural network with weak label annotations during the training process is utilized for enhanced correction of GA residuals in the sEMG recordings. Based on sEMG signal decomposition and class-activation maps from the neural network classification, the amount of GA residuals is iteratively decreased in the sEMG signal. This leads to a reduction of the false-positive rate in automated spontaneous activity detection. Quality of GA residual correction is therefore estimated by using a specialized second neural network model. Clinical relevance- This work establishes an improved GA residual correction for simultaneously recorded sEMG data during MRI to enhance the ability for small spontaneous activity detection.
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12
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The Curative Effect of Pregabalin in the Treatment of Postherpetic Neuralgia Analyzed by Deep Learning-Based Brain Resting-State Functional Magnetic Resonance Images. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:2250621. [PMID: 35615728 PMCID: PMC9113910 DOI: 10.1155/2022/2250621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/23/2021] [Indexed: 11/17/2022]
Abstract
This work aimed to investigate the brain resting-state functional magnetic resonance imaging (fMRI) technology based on the depth autoencoders algorithm and to evaluate the clinically curative effect of pregabalin in the treatment of postherpetic neuralgia (PHN). In this study, 40 patients with PHN were selected and rolled randomly into a treatment group and a control group (20 cases in each group). Then, a depth autoencoders algorithm was constructed and applied in the brain resting-state fMRI technology. The brains of 40 patients with PHN treated with pregabalin were scanned, and the time curve extracted from MRI images was convolved by linear drift removal bandpass filtering to reduce low-frequency drift and high-frequency noise, so the low-frequency amplitude was calculated. Based on the low-frequency amplitude method, the calculated low-frequency signal energy was eventually divided by the total power of the entire frequency band to obtain the low-frequency amplitude rate value. The amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (f-ALFF) before and after treatment were compared between the treatment group and the control group, and the visual analog scale (VAS) after treatment was also observed. After 4 weeks of taking the drug, the VAS scores of patients from the treatment group in the first week (6.5 ± 0.8 points), the second week (6.5 ± 0.8 points), the third week (3.1 ± 0.3 points), and the fourth week (2.3 ± 0.4 points) after treatment were lower steeply than the scores before treatment (8.3 ± 1.1 points) (P < 0.05). Resting-state fMRI images showed that the f-ALFF of the 4 brain areas in the treatment group was higher than that of the control group, mainly including the bilateral frontal lobes, bilateral parietal lobes, left parietal lobes, and right posterior cerebellar lobes. Besides, the f-ALFF of the 6 brain areas in the treatment group was lower than that of the control group, mainly including the right frontal lobe, right parietal lobe, right middle frontal gyrus, precuneus, left frontal lobe, and superior frontal gyrus. In conclusion, the resting-state fMRI technology based on the depth autoencoders algorithm could efficiently display the brain area characteristic changes of patients with PHN before and after treatment, thereby providing a reference for the diagnosis of the patient's condition.
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13
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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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14
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Englund EK, Reiter DA, Shahidi B, Sigmund EE. Intravoxel Incoherent Motion Magnetic Resonance Imaging in Skeletal Muscle: Review and Future Directions. J Magn Reson Imaging 2021; 55:988-1012. [PMID: 34390617 DOI: 10.1002/jmri.27875] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/23/2021] [Accepted: 07/26/2021] [Indexed: 12/29/2022] Open
Abstract
Throughout the body, muscle structure and function can be interrogated using a variety of noninvasive magnetic resonance imaging (MRI) methods. Recently, intravoxel incoherent motion (IVIM) MRI has gained momentum as a method to evaluate components of blood flow and tissue diffusion simultaneously. Much of the prior research has focused on highly vascularized organs, including the brain, kidney, and liver. Unique aspects of skeletal muscle, including the relatively low perfusion at rest and large dynamic range of perfusion between resting and maximal hyperemic states, may influence the acquisition, postprocessing, and interpretation of IVIM data. Here, we introduce several of those unique features of skeletal muscle; review existing studies of IVIM in skeletal muscle at rest, in response to exercise, and in disease states; and consider possible confounds that should be addressed for muscle-specific evaluations. Most studies used segmented nonlinear least squares fitting with a b-value threshold of 200 sec/mm2 to obtain IVIM parameters of perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D). In healthy individuals, across all muscles, the average ± standard deviation of D was 1.46 ± 0.30 × 10-3 mm2 /sec, D* was 29.7 ± 38.1 × 10-3 mm2 /sec, and f was 11.1 ± 6.7%. Comparisons of reported IVIM parameters in muscles of the back, thigh, and leg of healthy individuals showed no significant difference between anatomic locations. Throughout the body, exercise elicited a positive change of all IVIM parameters. Future directions including advanced postprocessing models and potential sequence modifications are discussed. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Erin K Englund
- Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - David A Reiter
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.,Department of Orthopedics, Emory University, Atlanta, Georgia, USA
| | - Bahar Shahidi
- Department of Orthopaedic Surgery, UC San Diego, San Diego, California, USA
| | - Eric E Sigmund
- Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, New York, USA.,Center for Advanced Imaging and Innovation (CAI2R), Bernard and Irene Schwarz Center for Biomedical Imaging (CBI), NYU Langone Health, New York, New York, USA
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15
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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: 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.
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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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16
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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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17
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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: 6] [Impact Index Per Article: 2.0] [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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18
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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: 4.0] [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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19
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Bashford J, Mills K, Shaw C. The evolving role of surface electromyography in amyotrophic lateral sclerosis: A systematic review. Clin Neurophysiol 2020; 131:942-950. [PMID: 32044239 PMCID: PMC7083223 DOI: 10.1016/j.clinph.2019.12.007] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 11/23/2019] [Accepted: 12/14/2019] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease that leads to inexorable motor decline and a median survival of three years from symptom onset. Surface EMG represents a major technological advance that has been harnessed in the development of novel neurophysiological biomarkers. We have systematically reviewed the current application of surface EMG techniques in ALS. METHODS We searched PubMed to identify 42 studies focusing on surface EMG and its associated analytical methods in the diagnosis, prognosis and monitoring of ALS patients. RESULTS A wide variety of analytical techniques were identified, involving motor unit decomposition from high-density grids, motor unit number estimation and measurements of neuronal hyperexcitability or neuromuscular architecture. Some studies have proposed specific diagnostic and prognostic criteria however clinical calibration in large ALS cohorts is currently lacking. The most validated method to monitor disease is the motor unit number index (MUNIX), which has been implemented as an outcome measure in two ALS clinical trials. CONCLUSION Surface EMG offers significant practical and analytical flexibility compared to invasive techniques. To capitalise on this fully, emphasis must be placed upon the multi-disciplinary collaboration of clinicians, bioengineers, mathematicians and biostatisticians. SIGNIFICANCE Surface EMG techniques can enrich effective biomarker development in ALS.
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Affiliation(s)
- J. Bashford
- UK Dementia Research Institute, Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK
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20
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Birkbeck MG, Heskamp L, Schofield IS, Blamire AM, Whittaker RG. Non-invasive imaging of single human motor units. Clin Neurophysiol 2020; 131:1399-1406. [PMID: 32122767 PMCID: PMC7208543 DOI: 10.1016/j.clinph.2020.02.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 02/10/2020] [Accepted: 02/11/2020] [Indexed: 11/01/2022]
Abstract
OBJECTIVE To determine the size, shape and distribution of single human motor units in-vivo in healthy controls of different ages. METHODS A novel diffusion-weighted magnetic resonance imaging (MRI) technique was used in combination with in-scanner electrical stimulation to quantify the shape, cross-sectional area, and dimensions of individual motor units in 10 healthy subjects. RESULTS Thirty-one discrete motor units were studied. The majority were elliptical or crescent shaped, but occasional split motor units were observed. The mean motor unit cross sectional area was 26.7 ± 11.2 mm2, the mean maximum dimension was 10.7 ± 3.3 mm, and the mean minimum dimension was 4.5 ± 1.2 mm. Subjects aged over 40 had significantly larger maximum dimensions than those below this age (p < 0.05). CONCLUSIONS Motor unit MRI (MUMRI) is a novel technique capable of revealing the size, shape and position of multiple motor units in human muscles. It is reproducible, non-invasive, and sufficiently sensitive to detect physiologically relevant changes in motor unit morphology with age. SIGNIFICANCE To our knowledge, these results provide the first imaging assessment of human motor unit morphology. The technique shows promise both as a diagnostic tool and as a biomarker in longitudinal studies of disease progression.
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Affiliation(s)
- Matthew G Birkbeck
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle upon Tyne NE1 7RU, UK; Newcastle Biomedical Research Centre, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; Northern Medical Physics and Clinical Engineering, Freeman Hospital, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK.
| | - Linda Heskamp
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Ian S Schofield
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Andrew M Blamire
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Roger G Whittaker
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University, Newcastle upon Tyne NE1 7RU, UK
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21
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Bashford JA, Wickham A, Iniesta R, Drakakis EM, Boutelle MG, Mills KR, Shaw CE. The rise and fall of fasciculations in amyotrophic lateral sclerosis. Brain Commun 2020; 2:fcaa018. [PMID: 32901231 PMCID: PMC7425399 DOI: 10.1093/braincomms/fcaa018] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Amyotrophic lateral sclerosis is a devastating neurodegenerative disease with a median survival of 3 years from symptom onset. Accessible and reliable biomarkers of motor neuron decline are urgently needed to quicken the pace of drug discovery. Fasciculations represent an early pathophysiological hallmark of amyotrophic lateral sclerosis and can be reliably detected by high-density surface electromyography. We set out to quantify fasciculation potentials prospectively over 14 months, seeking comparisons with established markers of disease progression. Twenty patients with amyotrophic lateral sclerosis and five patients with benign fasciculation syndrome underwent up to seven assessments each. At each assessment, we performed the amyotrophic lateral sclerosis-functional rating scale, sum power score, slow vital capacity, 30-min high-density surface electromyography recordings from biceps and gastrocnemius and the motor unit number index. We employed the Surface Potential Quantification Engine, which is an automated analytical tool to detect and characterize fasciculations. Linear mixed-effect models were employed to account for the pseudoreplication of serial measurements. The amyotrophic lateral sclerosis-functional rating scale declined by 0.65 points per month (P < 0.0001), 35% slower than average. A total of 526 recordings were analysed. Compared with benign fasciculation syndrome, biceps fasciculation frequency in amyotrophic lateral sclerosis was 10 times greater in strong muscles and 40 times greater in weak muscles. This was coupled with a decline in fasciculation frequency among weak muscles of -7.6/min per month (P = 0.003), demonstrating the rise and fall of fasciculation frequency in biceps muscles. Gastrocnemius behaved differently, whereby strong muscles in amyotrophic lateral sclerosis had fasciculation frequencies five times greater than patients with benign fasciculation syndrome while weak muscles were increased by only 1.5 times. Gastrocnemius demonstrated a significant decline in fasciculation frequency in strong muscles (2.4/min per month, P < 0.0001), which levelled off in weak muscles. Fasciculation amplitude, an easily quantifiable surrogate of the reinnervation process, was highest in the biceps muscles that transitioned from strong to weak during the study. Pooled analysis of >900 000 fasciculations revealed inter-fasciculation intervals <100 ms in the biceps of patients with amyotrophic lateral sclerosis, particularly in strong muscles, consistent with the occurrence of doublets. We hereby present the most comprehensive longitudinal quantification of fasciculation parameters in amyotrophic lateral sclerosis, proposing a unifying model of the interactions between motor unit loss, muscle power and fasciculation frequency. The latter showed promise as a disease biomarker with linear rates of decline in strong gastrocnemius and weak biceps muscles, reflecting the motor unit loss that drives clinical progression.
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Affiliation(s)
- James A Bashford
- UK Dementia Research Institute, Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Correspondence to: James A. Bashford, MRCP, PhD UK Dementia Research Institute, Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, 5 Cutcombe Road, King’s College London, London SE5 9RT, UK E-mail:
| | - Aidan Wickham
- Department of Bioengineering, Imperial College London, London, UK
| | - Raquel Iniesta
- Department of Biostatistics and Health Informatics, King’s College London, London, UK
| | | | | | - Kerry R Mills
- UK Dementia Research Institute, Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Chris E Shaw
- UK Dementia Research Institute, Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
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22
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Bromberg MB. The motor unit and quantitative electromyography. Muscle Nerve 2019; 61:131-142. [PMID: 31579956 DOI: 10.1002/mus.26718] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 09/10/2019] [Accepted: 09/11/2019] [Indexed: 12/13/2022]
Abstract
Electromyography (EMG) assesses the anatomic motor unit (A-MU), but knowledge of its anatomy, physiology, and changes with pathology is limited. The electrophysiological motor unit (E-MU) and its motor unit potential (E-MUP) represents a fraction of the A-MU. Routine EMG assesses a limited number of E-MUP waveform characteristics (metrics) and their magnitudes qualitatively scaled in a nonlinear manner. Another approach is quantitative EMG (QEMG), whereby 20+ E-MUPs are extracted and both basic and derived metrics obtained and values expressed quantitatively. In diseased muscle, many E-MUP metrics may be normal, which complicates diagnostic interpretation. In QEMG, E-MUP metrics can be clustered and statistical analyses performed to assign probabilities that E-MUPs (and the muscle) are normal, neuropathic, or myopathic. In this article we review what is known about the A-MU, the restricted E-MU, E-MUP metrics, and what QEMG offers currently and in the future.
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Affiliation(s)
- Mark B Bromberg
- Department of Neurology, University of Utah, Salt Lake City, Utah
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