MyoSight-Semi-Automated Image Analysis of Skeletal Muscle Cross Sections

Authors

Lyle W Babcock
Amy D Hanna
Nadia H Agha
Susan L Hamilton

Publication Date

11-16-2020

Journal

Skeletal Muscle

DOI

10.1186/s13395-020-00250-5

PMID

33198807

PMCID

PMC7667765

PubMedCentral® Posted Date

11-16-2020

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

Keywords

Animals, Cell Nucleus, Image Processing, Computer-Assisted, Mice, Mice, Inbred C57BL, Mice, Inbred mdx, Muscle, Skeletal, Muscular Dystrophy, Duchenne, Software, Duchenne muscular dystrophy, Soleus, Cross-sectional area, Fiber type, Myonuclei, Central nuclei, FIJI Plugin

Abstract

BACKGROUND: Manual analysis of cross-sectional area, fiber-type distribution, and total and centralized nuclei in skeletal muscle cross sections is tedious and time consuming, necessitating an accurate, automated method of analysis. While several excellent programs are available, our analyses of skeletal muscle disease models suggest the need for additional features and flexibility to adequately describe disease pathology. We introduce a new semi-automated analysis program, MyoSight, which is designed to facilitate image analysis of skeletal muscle cross sections and provide additional flexibility in the analyses.

RESULTS: We describe staining and imaging methods that generate high-quality images of immunofluorescent-labelled cross sections from mouse skeletal muscle. Using these methods, we can analyze up to 5 different fluorophores in a single image, allowing simultaneous analyses of perinuclei, central nuclei, fiber size, and fiber-type distribution. MyoSight displays high reproducibility among users, and the data generated are in close agreement with data obtained from manual analyses of cross-sectional area (CSA), fiber number, fiber-type distribution, and number and localization of myonuclei. Furthermore, MyoSight clearly delineates changes in these parameters in muscle sections from a mouse model of Duchenne muscular dystrophy (mdx).

CONCLUSIONS: MyoSight is a new program based on an algorithm that can be optimized by the user to obtain highly accurate fiber size, fiber-type identification, and perinuclei and central nuclei per fiber measurements. MyoSight combines features available separately in other programs, is user friendly, and provides visual outputs that allow the user to confirm the accuracy of the analyses and correct any inaccuracies. We present MyoSight as a new program to facilitate the analyses of fiber type and CSA changes arising from injury, disease, exercise, and therapeutic interventions.

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