The coagulation cascade, triggered by tissue factor (TF) exposure after endothelial injury, drives fibrin formation and may result in thrombotic events such as stroke. The mechanisms driving differences in thrombus extent among patients remain poorly understood, but interactions between patient-specific coagulation and local blood flow are thought to be critical. This study presents a unified workflow with an assay-calibrated, experimentally validated in silico model that links coagulation assays to flow-resolved simulations in patient-specific geometries. Plasma from ischemic stroke patients was analyzed with a thrombin generation (TG) assay, and a 0D computational model was fitted to TG curves to infer patient-specific coagulation parameters. These parameters were validated against thrombodynamics (TD) outcomes using 1D computational reaction–diffusion simulations. The framework was extended to 2D computational flow domains to assess the influence of shear rate, TF patch size and location, and geometric features such as stenosis. Finally, 3D carotid simulations combined patient-specific vascular geometries with plasma parameters. The 0D model reproduced TG data, while 1D simulations matched TD outcomes for clot size, fibrin growth, and thrombin wave speed. In 2D, fibrin formation was reduced at higher shear or smaller TF patches, and 3D simulations demonstrated the combined effect of flow, geometry, and plasma composition on fibrin formation. This approach provides a bridge from bench assays to hemodynamic contexts and offers a potential path toward individualized thrombotic risk assessment.
Cruts et al. (2026) studied this question.