Automated Image Analysis Pipeline Development to Monitor Disease Progression in Muscular Dystrophy Using Cell Profiler.
Automated Image Analysis Pipeline Development to Monitor Disease Progression in Muscular Dystrophy Using Cell Profiler.
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DOI：
10.26502/ami.936500115
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发表时间：
2023
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肌肉营养不良是以进行性肌肉退化为特征的遗传性疾病。这些疾病是由肌肉内编码结构元素的基因突变引起的，这导致对机械压力和肌膜损伤的易感性增加。虽然肌纤维具有再生的能力，但新形成的肌纤维仍然存在基因突变，导致肌纤维死亡和再生的连续循环。这种反复的循环伴随着炎症反应，最终导致过度的纤维沉积。骨骼肌组织的组织病理学改变是该病发病机制的核心。肌肉组织病理学分析是监测肌肉健康和疾病进展的黄金标准。然而，手工或半手工量化方法不仅极其繁琐，而且可能是主观的。在这里，我们介绍了CellProfiler内置的四个图像分析流水线，使没有计算机视觉或编程背景的用户可以对生物图像进行定量分析。这些图像分析管道旨在量化骨骼肌组织病理学染色的膜损伤、再生肌纤维的丰度和大小分布、通过量化CD68+M1巨噬细胞的炎症和胶原沉积。此外，我们还讨论了解决与显微图像量化相关的常见错误的方法。这些自动化工具不仅可以提高工作流程的效率，而且可以更好地了解肌营养不良的组织病理学进展。
Muscular dystrophies are inherited disorders that are characterized by progressive muscle degeneration. These disorders are caused by mutations in the genes encoding structural elements within the muscle, which leads to increased vulnerability to mechanical stress and sarcolemma damage. Although myofibers have the capacity to regenerate, the newly formed myofibers still harbor genetic mutation, which induces continuous cycles of muscle fiber death and regeneration. This repeated cycling is accompanied by an inflammatory response which eventually provokes excessive fibrotic deposition. The histopathological changes in skeletal muscle tissue are central to the disease pathogenesis. Analysis of muscle histopathology is the gold standard for monitoring muscle health and disease progression. However, manual, or semi-manual quantification methods, are not only immensely tedious but can be subjective. Here, we present four image analysis pipelines built in CellProfiler which enable users without a background in computer vision or programming to quantitatively analyze biological images. These image analysis pipelines are designed to quantify skeletal muscle histopathological staining for membrane damage, the abundance and size distribution of regenerating muscle fibers, inflammation via quantification of CD68+ M1 macrophages, and collagen deposition. Additionally, we discuss methods to address common errors associated with the quantification of microscopy images. These automated tools can not only improve workflow efficiency but can provide a better understanding of the histopathological progression of muscular dystrophy.