Abstract
Arterial diseases including abdominal aortic aneurysm and atherosclerosis are biomechanical diseases characterized by significant changes in the structure and strength of the vessel wall. It is now established that local variations in fibrillar collagen and elastin matrix turnover is critical to arterial stiffening and progression of the disease. The collagen content in the aortic wall has nominally been quantified by biochemical assays and immunohistochemical analysis as the total amount because of the difficulty in separating the media and adventitia. In this work, we have developed an algorithm for automatic quantification of layer-specific collagen content from bright-field and polarized microscopic images of histological sections of mouse aorta stained with Picrosirius red (PSR) stain. The images were processed sequentially including separation of layers, erosion, segregation of regions, binarization, and quantification of pixel intensities to obtain collagen content in the media and adventitia separately. We observed that the automated algorithm rapidly and accurately quantified collagen content from a wide range of image quality compared with manual measurements particularly when the medial and adventitial layers overlap. Together, our algorithm will be of significant impact in the rapid, reliable, and accurate analyses of collagen distribution in histological sections of connective tissues.