The Effects of Micro-vessel Curvature Induced Elongational Flows on Platelet Adhesion.

The emerging profile of blood flow and the cross-sectional distribution of blood cells have far reaching biological consequences in various diseases and vital internal processes, such as platelet adhesion. The effects of several essential blood flow parameters, such as red blood cell free layer width, wall shear rate, and hematocrit on platelet adhesion were previously explored to great lengths in straight geometries. In the current work, the effects of channel curvature on cellular blood flow are investigated by simulating the accurate cellular movement and interaction of red blood cells and platelets in a half-arc channel for multiple wall shear rate and hematocrit values. The results show significant differences in the emerging shear rate values and distributions between the inner and outer arc of the channel curve, while the cell distributions remain predominantly uninfluenced. The simulation predictions are also compared to experimental platelet adhesion in a similar curved geometry. The inner side of the arc shows elevated platelet adhesion intensity at high wall shear rate, which correlates with increased shear rate and shear rate gradient sites in the simulation. Furthermore, since the platelet availability for binding seems uninfluenced by the curvature, these effects might influence the binding mechanics rather than the probability. The presence of elongational flows is detected in the simulations and the link to increased platelet adhesion is discussed in the experimental results.

In silico trials for treatment of acute ischemic stroke: Design and implementation.

An in silico trial simulates a disease and its corresponding therapies on a cohort of virtual patients to support the development and evaluation of medical devices, drugs, and treatment. In silico trials have the potential to refine, reduce cost, and partially replace current in vivo studies, namely clinical trials and animal testing. We present the design and implementation of an in silico trial for treatment of acute ischemic stroke. We propose an event-based modelling approach for the simulation of a disease and injury, where changes to the state of the system (the events) are assumed to be instantaneous. Using this approach we are able to combine a diverse set of models, spanning multiple time scales, to model acute ischemic stroke, treatment, and resulting brain tissue injury. The in silico trial is designed to be modular to aid development and reproducibility. It provides a comprehensive framework for application to any potential in silico trial. A statistical population model is used to generate cohorts of virtual patients. Patient functional outcomes are also predicted with a statistical model, using treatment and injury results and the patient's clinical parameters. We demonstrate the functionality of the event-based modelling approach and trial framework by running proof of concept in silico trials. The proof of concept trials simulate the same cohort of patients twice: once with successful treatment (successful recanalisation) and once with unsuccessful treatment (unsuccessful treatment). Ways to overcome some of the challenges and difficulties in setting up such an in silico trial are discussed, such as validation and computational limitations.