Electrical impedance myography combined with quantitative assessment techniques in paretic muscle of stroke survivors: Insights and challenges.
electrical impedance myography
skeletal muscle
spasticity
stroke
ultrasonography
Journal
Frontiers in aging neuroscience
ISSN: 1663-4365
Titre abrégé: Front Aging Neurosci
Pays: Switzerland
ID NLM: 101525824
Informations de publication
Date de publication:
2023
2023
Historique:
received:
23
12
2022
accepted:
27
02
2023
medline:
7
4
2023
entrez:
6
4
2023
pubmed:
7
4
2023
Statut:
epublish
Résumé
Aging is a non-modifiable risk factor for stroke and the global burden of stroke is continuing to increase due to the aging society. Muscle dysfunction, common sequela of stroke, has long been of research interests. Therefore, how to accurately assess muscle function is particularly important. Electrical impedance myography (EIM) has proven to be feasible to assess muscle impairment in patients with stroke in terms of micro structures, such as muscle membrane integrity, extracellular and intracellular fluids. However, EIM alone is not sufficient to assess muscle function comprehensively given the complex contributors to paretic muscle after an insult. This article discusses the potential to combine EIM and other common quantitative methods as ways to improve the assessment of muscle function in stroke survivors. Clinically, these combined assessments provide not only a distinct advantage for greater accuracy of muscle assessment through cross-validation, but also the physiological explanation on muscle dysfunction at the micro level. Different combinations of assessments are discussed with insights for different purposes. The assessments of morphological, mechanical and contractile properties combined with EIM are focused since changes in muscle structures, tone and strength directly reflect the muscle function of stroke survivors. With advances in computational technology, finite element model and machine learning model that incorporate multi-modal evaluation parameters to enable the establishment of predictive or diagnostic model will be the next step forward to assess muscle function for individual with stroke.
Identifiants
pubmed: 37020859
doi: 10.3389/fnagi.2023.1130230
pmc: PMC10069712
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1130230Informations de copyright
Copyright © 2023 Gong, Lo, Wang and Li.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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