Modelling Virchow’s Triad to Improve Stroke Risk Assessment in Atrial Fibrillation Patients

Ahmed Qureshi1, Maximilian Balmus1, Steven Williams2, Gregory Lip3, David Nordsletten4, Oleg Aslanidi1, Adelaide de Vecchi1
1King's College London, 2University of Edinburgh, 3University of Liverpool, 4University of Michigan


Abstract

Introduction: Atrial fibrillation (AF) is associated with significantly increased risk of stroke due to the presence of three pro-thrombotic mechanisms known as Virchow’s triad – blood stasis, endothelial damage and hypercoagulability – which primarily occur in the left atrial appendage (LAA). In-silico evaluation of each factor can improve upon the current empirical stroke risk stratification for AF patients.

Methods: Computational fluid dynamics simulations were performed on two patient-specific models of the left atrium (LA), one in sinus rhythm (SR) and one in AF, over 10 cardiac cycles to quantify blood stasis and metrics of endothelial damage – the endothelial cell activation potential (ECAP). Hypercoagulability was assessed by solving reaction-diffusion-convection equations for thrombin, fibrinogen and fibrin – three key clotting proteins. An original grading system is proposed (A = low, B = moderate, C = high risk) for each component of the triad to form a patient-specific risk profile.

Results: The SR patient had a risk profile of [A, B, A] with low blood stasis due to peak LAA velocities of 0.78 m/s, moderate ECAP values of 2.7 and low remnant fibrin concentrations of 2e-6 mmol/m3. The AF patient had [C, C, C], indicating a high risk of thrombus formation for all aspects of Virchow’s triad, with peak LAA velocity of 0.19 m/s, high ECAP of 3.5 and 3.2mmol/m3 of remnant fibrin concentration after 10 cardiac cycles. Simulations of thrombus growth dynamics in the AF patient uncovered the formation of a thrombotic mass which detached from the LAA wall and moved in the blood stream. If the patient was reverted to SR, the thrombus may have been ejected from the LA towards the brain causing thromboembolic stroke.

Conclusion: This novel modelling approach encapsulates all fundamental mechanisms of thrombus formation and may be used to improve stroke risk assessment for AF patients.