Computational imaging analysis of fibrin matrices with the inclusion of erythrocytes from homozygous SS blood reveals agglomerated and amorphous structures.

Sickle cell disease is a single point mutation disease that is known to alter the coagulation system, leading to hypercoagulable plasma conditions. These hypercoagulable conditions can lead to complications in the vasculature, caused by fibrin clots that form undesirably. There is a need to understand the morphology and structure of fibrin clots from patients with sickle cell disease, as this could lead to further discovery of treatments and life-saving therapies. In this work, a computational imaging analysis method is presented to evaluate fibrin agglomeration in the presence of erythrocytes (RBCs) homozygous for the sickle cell mutation (SS). Numerical algorithms were used to determine agglomeration of fibrin fibers within a matrix with SS RBCs to test the hypothesis that fibrin matrices with the inclusion of SS RBCs possess a more agglomerated structure than native fibrin matrices with AA RBCs. The numerical results showed that fibrin structures with SS RBCs displayed an overall higher degree of agglomeration as compared to native fibrin structures. The computational algorithm was also used to evaluate fibrin fiber overlap (aggregation) and anisotropy (orientation) in normal fibrin matrices compared to fibrin matrices polymerized around SS RBCs; however, there was no statistical difference. Ultrasound measurements of stiffness revealed rigid RBCs in the case of samples derived from homozygous SS blood, and densely evolving matrices, when compared to normal fibrin with the inclusion of AA RBCs. An agglomeration model is suggested to quantify the fibrin aggregation/clustering near RBCs for both normal fibrin matrices and for the altered structures. The results of this work are important in the sense that the understanding of aggregation and morphology in fibrin clots with incorporation of RBCs from persons living with sickle cell anemia may elucidate the complexities of comorbidities and other disease complications.

Computational imaging analysis of glycated fibrin gels reveals aggregated and anisotropic structures.

In this article, a computational imaging analysis method is presented for the evaluation of aggregation and anisotropy in both native (unglycated) and glycated fibrin matrix structures. The imaging analysis was used to test the hypothesis that glycated fibrin structures are more aggregated and anisotropic than unglycated (native) fibrin structures. Glycation of fibrinogen, and subsequently fibrin, occurs under normal physiological conditions; however, excess glycation due to disease states such as diabetes can disrupt the fibrin matrix and cause an abnormal structure and function. Studies that elucidate morphological changes in glucose incubated fibrin matrices are necessary to better understand thrombosis, which occurs due to hypercoagulable conditions. In this study, imaging algorithms were designed for the determination of aggregation of fibrin fibers within a matrix as well as preferential orientation (anisotropy) due to glycation. The results showed that glycated fibrin structures displayed an overall higher degree of aggregation and anisotropy as compared to unglycated fibrin structures. However, for glycated fibrin matrices that were polymerized utilizing extended incubation periods representative of physiological plasma glucose conditions, the results showed that fibrin aggregation and anisotropy decreased when compared to unglycated matrices. The algorithms showed that incorporation of the crosslinking agent FXIII into the fibrin matrix was shown to decrease both aggregation and anisotropy. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 105A: 2191-2198, 2017.