The quantification of collagen fibers following Masson's trichrome staining is a critical procedure in histopathological analysis, especially for the study of fibrotic conditions. Fibrosis is a pathological feature of numerous chronic diseases, marked by the excessive production and deposition of extracellular matrix components, such as collagen, in various organs including the lungs. The progression of fibrosis can severely impair organ function, making it crucial to quantify the extent of fibrosis for evaluating potential treatments, understanding disease mechanisms, and predicting outcomes. For instance, in pulmonary fibrosis, the quantification of collagen in lung tissue can help assess the severity of the disease and monitor the response to antifibrotic therapies. Similarly, in liver cirrhosis, measuring collagen deposition can aid in evaluating the progression of liver damage. Thus, accurate quantification of collagen fibers is invaluable across a range of clinical and research settings.
Open ImageJ Software:
Open Acquired Image:
File -> Open
or use the shortcut Ctrl+O
to open the image acquired using a confocal microscope at a magnification of 10x.Set Image Scale:
Analyze -> Set Scale
.Download Color Deconvolution Plugin:
Apply Color Deconvolution:
Plugins -> Scripts -> Color Deconvolution
.Set Threshold:
Ctrl+Shift+T
.Create and Save ROI:
Analyze -> Tools -> ROI Manager
.Measure Area:
Analyze -> Measure
or use the shortcut Ctrl+M
to measure the area of the collagen fibers within the ROI.Repeat Measurements:
This SOP is designed based on the methods outlined in specific research papers. When utilizing this protocol, it's important to cite the original research that has employed this method for collagen quantification. Additionally, incorporating a flowchart from a published paper, that summarizes the steps can enhance the understanding and reproducibility of the protocol.
Note: It is crucial to always ensure that the same scale (e.g., 1.3 pixels/µm) and threshold values (e.g., min 235 and max 255) are used consistently across all images to maintain accuracy in quantification.
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