<p dir="ltr">Fibromuscular Dysplasia (FMD) is a non-inflammatory, non-atherosclerotic blood vessel disorder characterized by a series of narrowed and dilated regions of vasculature. These patients are prescribed blood thinners or anti-platelet therapeutics as treatment to this systemic disease. Current image-based diagnostic methods cannot reliably predict a patient’s risk of stroke in order to properly manage medication. There are also challenges in distinguishing FMD from other diseases that can cause arterial obstructions, like atherosclerosis or vasculitis.</p><p dir="ltr">The ultimate goal of this research is to develop a methodology for evaluating the risk of mechanical platelet activation based on medical imaging. Our hypothesis is that subject-specific assessment of platelet activation due to hemodynamic stress can improve risk stratification of FMD patients. The aims of the projects were therefore to 1) Develop a CFD-based methodology for estimating platelet activation state, and 2) Test this methodology on a small cohort of subjects with FMD, carotid artery stenosis, and healthy controls. A modeling workflow was developed, combining Eulerian and Lagrangian approaches to compute flow fields and evaluate shear stress history of particles advected through the vascular geometries. From this stress history, predictive estimates of mechanical platelet activation can be calculated utilizing a platelet activation state (PAS) metric. We applied this modeling workflow to assess platelet activation in segments of carotid arteries of patients with Fibromuscular Dysplasia, Carotid Artery Stenosis, and healthy controls for comparison against experiments performed at the Cleveland Clinic assessing mechanical platelet activation in patients with each of these conditions. This work supports the development of a patient-specific determination of these same metrics, in order to more precisely assess patient risk of stroke.</p>