Single fiber curvature for muscle impairment assessment: Phase contrast imaging of stroke-induced animals.

curvature volume impairment murine single fiber stroke synchrotron radiation x-ray micro-computed tomography

Journal

Microscopy research and technique
ISSN: 1097-0029
Titre abrégé: Microsc Res Tech
Pays: United States
ID NLM: 9203012

Informations de publication

Date de publication:
20 Nov 2023
Historique:
revised: 15 10 2023
received: 28 05 2023
accepted: 05 11 2023
medline: 20 11 2023
pubmed: 20 11 2023
entrez: 20 11 2023
Statut: aheadofprint

Résumé

There are technical challenges in imaging studies that can three-dimensionally (3D) analyze a single fiber (SF) to observe the functionality of the entire muscle after stroke. This study proposes a 3D assessment technique that only segments the SF of the right stroke-induced soleus muscle of a gerbil using synchrotron radiation x-ray microcomputed tomography (SR-μCT), which is capable of muscle structure analysis. Curvature damage in the SF of the left soleus muscle (impaired) progressed at 7-day intervals after the stroke in the control; particularly on the 7 days (1 week) and 14 days (2 weeks), as observed through visualization analysis. At 2 weeks, the SF volume was significantly reduced in the control impaired group (p = .033), and was significantly less than that in the non-impaired group (p = .009). We expect that animal post-stroke studies will improve the basic field of rehabilitation therapy by diagnosing the degree of SF curvature. RESEARCH HIGHLIGHTS: Muscle evaluation after ischemic stroke using synchrotron radiation x-ray microcomputed tomography (SR-μCT). Curvature is measured by segmenting a single fiber (SF) in the muscle. Structural changes in the SF of impaired gerbils at 7-day intervals were assessed.

Identifiants

pubmed: 37983687
doi: 10.1002/jemt.24459
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : BK21 FOUR (Fostering Outstanding Universities for Research)
ID : 5199990914048
Organisme : National Research Foundation of Korea (NRF)
ID : 2022R1A2C1010170
Organisme : Soonchunhyang University Research Fund

Informations de copyright

© 2023 Wiley Periodicals LLC.

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Auteurs

Subok Kim (S)

Department of Software Convergence, Graduate School, Soonchunhyang University, Asan, Republic of Korea.

Sanghun Jang (S)

Department of Physical Therapy, College of Health and Life Sciences, Korea National University of Transportation, Jeungpyeong-gun, Republic of Korea.

Onseok Lee (O)

Department of Software Convergence, Graduate School, Soonchunhyang University, Asan, Republic of Korea.
Department of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, Asan, Republic of Korea.

Classifications MeSH