2019年7月
Evaluation of Yanagihara facial nerve grading system based on a muscle fiber analysis of human facial muscles
EUROPEAN ARCHIVES OF OTO-RHINO-LARYNGOLOGY
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- 巻
- 276
- 号
- 7
- 開始ページ
- 2055
- 終了ページ
- 2060
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1007/s00405-019-05462-0
- 出版者・発行元
- SPRINGER
PurposeWe morphometrically analyzed human facial muscles, and evaluated the Yanagihara facial nerve grading system using our data.MethodsWe used 15 types of human facial muscle, 2 types of masticatory muscle and 2 types of skeletal muscle. The materials were obtained from 11 Japanese male cadavers aged 43-86years. We counted the muscle fibers and measured the transverse area of the muscle fibers (TAMF), and then calculated the number of muscle fibers (NMF) per mm(2) and the average TAMF.ResultsWe found a significant correlation between average TAMF and NMF (r=-0.70; p<0.01). We classified facial muscles into three types based on the correlational results. Type A had a low average TAMF and high NMF. Type C had a high average TAMF and low NMF. Masticatory and skeletal muscles were characterized as Type C. Type B was intermediate between Types A and C.ConclusionsPathological changes in the facial muscles in facial nerve palsy seem to vary according to the type of facial muscle, because each facial muscle has a unique fiber-type composition. As the nine discrete facial expressive states evaluated in the Yanagihara system involve all three facial muscle types of our classification, the Yanagihara system is an outstanding system for grading facial nerve palsy in terms of the facial muscle morphology.
- リンク情報
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- DOI
- https://doi.org/10.1007/s00405-019-05462-0
- PubMed
- https://www.ncbi.nlm.nih.gov/pubmed/31076880
- PubMed Central
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6581922
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000472048600025&DestApp=WOS_CPL
- ID情報
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- DOI : 10.1007/s00405-019-05462-0
- ISSN : 0937-4477
- eISSN : 1434-4726
- PubMed ID : 31076880
- PubMed Central 記事ID : PMC6581922
- Web of Science ID : WOS:000472048600025