Document Type
Article
Publication Date
2023
Journal Title
Acta Physiologica
Volume Number
239
Issue Number
1
First Page
1
Last Page
19
DOI
https://doi.org/10.1111/apha.13982
Version
Publisher PDF: the final published version of the article, with professional formatting and typesetting
Creative Commons License
This work is licensed under a CC BY-NC License
Disciplines
Engineering
Abstract
Aim While manual quantification is still considered the gold standard for skeletal muscle histological analysis, it is time-consuming and prone to investigator bias. To address this challenge, we assembled an automated image analysis pipeline, FiNuTyper (Fiber and Nucleus Typer). Methods We integrated recently developed deep learning-based image segmentation methods, optimized for unbiased evaluation of fresh and postmortem human skeletal muscle, and utilized SERCA1 and SERCA2 as type-specific myonucleus and myofiber markers after validating them against the traditional use of MyHC isoforms. Results Parameters including cross-sectional area, myonuclei per fiber, myonuclear domain, central myonuclei per fiber, and grouped myofiber ratio were determined in a fiber-type-specific manner, revealing that a large degree of sex- and muscle-related heterogeneity could be detected using the pipeline. Our platform was also tested on pathological muscle tissue (ALS and IBM) and adapted for the detection of other resident cell types (leucocytes, satellite cells, capillary endothelium). Conclusion In summary, we present an automated image analysis tool for the simultaneous quantification of myofiber and myonuclear types, to characterize the composition and structure of healthy and diseased human skeletal muscle.
Digital USD Citation
Lundquist, August; Lázár, Enikő; Han, Nan S.; Emanuelsson, Eric B.; Reitzner, Stefan M.; Chapman, Mark A.; Shirkova, Vera; Alkass, Kanar; Druid, Henrik; Petri, Susanne; Sundberg, Carl J.; and Bergmann, Olaf, "FiNuTyper: Design and Validation of an Automated Deep Learning-Based Platform for Simultaneous Fiber and Nucleus Type Analysis in Human Skeletal Muscle" (2023). School of Engineering: Faculty Scholarship. 39.
https://digital.sandiego.edu/engineering_facpub/39