RESUMO
Picrosirius red staining constitutes an important and broadly used tool to visualize collagen and fibrosis in various tissues. Although multiple qualitative and quantitative analysis methods to evaluate fibrosis are available, many require specialized devices and software or lack objectivity and scalability. Here, we aimed to develop a versatile and powerful "QuantSeg" macro in the FIJI image processing software capable of automated, robust, and quick collagen quantification in cardiac tissue from light micrographs. To examine different patterns of fibrosis, an optional segmentation algorithm was implemented. To ensure the method's validity, we quantified the collagen content in a set of wild-type versus plakoglobin-knockout murine hearts exhibiting extensive fibrosis using both the macro and an established, fluorescence microscopy-based method, and compared results. To demonstrate the capabilities of the segmentation feature, rat hearts were examined post-myocardial infarction. We found the QuantSeg macro to robustly detect the differences in fibrosis between knockout and control hearts. In sections with low collagen content, the macro yielded more consistent results than using the fluorescence microscopy-based technique. With its wide range of output parameters, ease of use, cost effectiveness, and objectivity, the QuantSeg macro has the potential to become an established method for analysis of PSR-stained tissue. The novel segmentation feature allows for automated evaluation of different patterns of cardiac fibrosis for the first time.