MRI-based modelling of left atrial flow and coagulation to predict risk of thrombogenesis in atrial fibrillation

Abstract

Atrial fibrillation (AF), impacting nearly 50 million individuals globally, is a major contributor to ischaemic strokes, predominantly originating from the left atrial appendage (LAA). Current clinical scores like CHA₂DS₂-VASc, while useful, provide limited insight into the pro-thrombotic mechanisms of Virchow's triad—blood stasis, endothelial damage, and hypercoagulability. This study leverages biophysical computational modelling to deepen our understanding of thrombogenesis in AF patients. Utilising high temporal resolution Cine magnetic resonance imaging (MRI), a 3D patient-specific modelling pipeline for simulating patient-specific flow in the left atrium was developed. This computational fluid dynamics (CFD) approach was coupled with reaction-diffusion-convection equations for key clotting proteins, leading to an innovative risk stratification score that combines clinical and modelling data. This approach categorises thrombogenic risk into low (A), moderate (B), and high (C) levels. Applied to a cohort of nine patients, pre- and post-catheter ablation therapy, this approach generates novel risk scores of thrombus formation, which are based of mechanistic characterisation of all aspects of the Virchow's triad. Currently, thrombogenesis mechanisms are not factored in widespread clinical risks scores based on demographic characteristics and co-morbidities. Notably, some patients with a CHA₂DS₂-VASc score of 0 (lowest clinical risk) exhibited much higher risks once the individual pathophysiology was accounted for. This discrepancy highlights the limitations of the CHA₂DS₂-VASc score in providing detailed mechanistic insights into patient-specific thrombogenic risk. This work introduces a comprehensive method for assessing thrombus formation risks in AF patients, emphasising the value of integrating biophysical modelling with clinical scores to enhance personalised stroke prevention strategies.