Automated fiber-type-specific cross-sectional area assessment and myonuclei counting in skeletal muscle

Fujun Liu, Christopher S. Fry, Jyothi Mula, Janna R. Jackson, Jonah D. Lee, Charlotte A. Peterson, Lin Yang

    Research output: Contribution to journalArticlepeer-review

    24 Scopus citations

    Abstract

    Skeletal muscle is an exceptionally adaptive tissue that compromises 40% of mammalian body mass. Skeletal muscle functions in locomotion, but also plays important roles in thermogenesis and metabolic homeostasis. Thus characterizing the structural and functional properties of skeletal muscle is important in many facets of biomedical research, ranging from myopathies to rehabilitation sciences to exercise interventions aimed at improving quality of life in the face of chronic disease and aging. In this paper, we focus on automated quantification of three important morphological features of muscle: 1) muscle fiber-type composition; 2) muscle fiber-type-specific cross-sectional area, and 3) myonuclear content and location. We experimentally prove that the proposed automated image analysis approaches for fiber-type-specific assessments and automated myonuclei counting are fast, accurate, and reliable.

    Original languageEnglish (US)
    Pages (from-to)1714-1724
    Number of pages11
    JournalJournal of Applied Physiology
    Volume115
    Issue number11
    DOIs
    StatePublished - Dec 1 2013

    Keywords

    • Cross-sectional area
    • Image segmentation
    • Muscle
    • Myonuclei counting

    ASJC Scopus subject areas

    • Physiology
    • Physiology (medical)

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