Zhang Bao, Wang Shuaiyu, Wang Yaning, Liang Chen, Zhang Hongbo
Medical College of Jiaying University, Meizhou, 514031, China.
The Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China.
Histochem Cell Biol. 2025 Sep 5;163(1):89. doi: 10.1007/s00418-025-02414-0.
Quantifying myofiber size is essential for assessing the health and function of skeletal muscle. Although several ImageJ plugins are currently available for myofiber segmentation and size quantification, significant challenges remain-most notably limited accuracy and poor compatibility with hematoxylin and eosin (H&E)-stained skeletal muscle cross sections. In this study, we introduce MyoAnalyst, an ImageJ plugin designed to enable automated analysis of both immunofluorescence (IF)- and H&E-stained skeletal muscle cross sections. Compared to existing ImageJ plugins, MyoAnalyst delivers enhanced segmentation sensitivity and superior boundary delineation accuracy across both healthy and injured muscle tissue stained with IF. Importantly, it also supports fully automated analysis of H&E-stained sections. With its intuitive graphical interface and batch processing capabilities, MyoAnalyst provides a potentially efficient tool for myofiber size quantification in both research and clinical settings.
量化肌纤维大小对于评估骨骼肌的健康和功能至关重要。尽管目前有几个ImageJ插件可用于肌纤维分割和大小量化,但仍存在重大挑战——最显著的是准确性有限,且与苏木精和伊红(H&E)染色的骨骼肌横截面兼容性差。在本研究中,我们引入了MyoAnalyst,这是一个ImageJ插件,旨在对免疫荧光(IF)和H&E染色的骨骼肌横截面进行自动分析。与现有的ImageJ插件相比,MyoAnalyst在IF染色的健康和损伤肌肉组织中都具有更高的分割灵敏度和更好的边界描绘准确性。重要的是,它还支持对H&E染色切片进行全自动分析。凭借其直观的图形界面和批处理功能,MyoAnalyst为研究和临床环境中的肌纤维大小量化提供了一个潜在的有效工具。