Image-based analysis and simulation of the effect of platelet storage temperature on clot mechanics under uniaxial strain.

Optimal strength and stability of blood clots are keys to hemostasis and in prevention of hemorrhagic or thrombotic complications. Clots are biocomposite materials composed of fibrin network enmeshing platelets and other blood cells. We have previously shown that the storage temperature of platelets significantly impacts clot structure and stiffness. The objective of this work is to delineate the relationship between morphological characteristics and mechanical response of clot networks. We examined scanning electron microscope images of clots prepared from fresh apheresis platelets, and from apheresis platelets stored for 5 days at room temperature or at 4 °C, suspended in pooled plasma. Principal component analysis of nine different morphometric parameters revealed that a single principal component (PC1) can distinguish the effect of platelet storage on clot ultrastructure. Finite element analysis of clot response to uniaxial strain was used to map the spatially heterogeneous distribution of strain energy density for each clot. At modest deformations (25% strain), a single principal component (PC2) was able to predict these heterogeneities as quantified by variability in strain energy density distribution and in linear elastic stiffness, respectively. We have identified structural parameters that are primary regulators of stress distribution, and the observations provide insights into the importance of spatial heterogeneity on hemostasis and thrombosis.

An Automated Algorithm to Quantify Collagen Distribution in Aortic Wall.

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.