Statistical parametric mapping of three-dimensional local activity distribution of skeletal muscle using magnetic resonance imaging (MRI)
Abstract Analysis of the internal local activity distribution in human skeletal muscles is important for managing muscle fatigue/pain and dysfunction. However, no method is established for three-dimensional (3D) statistical analysis of features of activity regions common to multiple subjects during...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/c41ebd58f27d4e71a8c60604d64363bb |
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| Sumario: | Abstract Analysis of the internal local activity distribution in human skeletal muscles is important for managing muscle fatigue/pain and dysfunction. However, no method is established for three-dimensional (3D) statistical analysis of features of activity regions common to multiple subjects during voluntary motor tasks. We investigated the characteristics of muscle activity distribution from the data of ten healthy subjects (29 ± 1 year old, 2 women) during voluntary teeth clenching under two different occlusal conditions by applying spatial normalization and statistical parametric mapping (SPM) to analysis of muscle functional magnetic resonance imaging (mfMRI) using increase in transverse relaxation time (T2) of the skeletal muscle induced by exercise. The expansion of areas with significant T2 increase was observed in the masticatory muscles after clenching with molar loss comparing with intact dentition. The muscle activity distribution characteristics common to a group of subjects, i.e., the active region in the temporal muscle ipsilateral to the side with the molar loss and medial pterygoid muscle contralateral to the side with the molar loss, were clarified in 3D by applying spatial normalization and SPM to mfMRI analysis. This method might elucidate the functional distribution within the muscles and the localized muscular activity related to skeletal muscle disorders. |
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