A semi‐automated pipeline for quantitation of Pax7+, myonuclei, and cross‐sectional area by fiber type

Abstract

Manual analysis of skeletal muscle cross‐sections is time‐consuming and subject to error and user bias. To overcome these limitations, we developed and validated a semi‐automated, quantitative, and reproducible image‐analysis pipeline specifically tailored to quantify Pax7+ satellite cells, myonuclei, and cross‐sectional area by fiber type. The workflow combines Fiji/ImageJ‐based image preprocessing with CellProfiler, Cellpose, and a custom Python script to process and analyze immunohistological images of muscle tissue cross‐sections. Outcomes include Pax7+ satellite cells and myonuclei quantified per fiber by fiber type, along with cross‐sectional area, perimeter, and fiber type classification. This semi‐automated approach provides a robust and efficient platform for high‐throughput analysis of muscle tissue cross‐sections from large datasets.