A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditions

One of the routine clinical treatments to eliminate ischemic stroke thrombi is injecting a biochemical product into the patient’s bloodstream, which breaks down the thrombi’s fibrin fibers: intravenous or intravascular thrombolysis. However, this procedure is not without risk for the patient; the worst circumstances can cause a brain hemorrhage or embolism that can be fatal. Improvement in patient management drastically reduced these risks, and patients who benefited from thrombolysis soon after the onset of the stroke have a significantly better 3-month prognosis, but treatment success is highly variable. The causes of this variability remain unclear, and it is likely that some fundamental aspects still require thorough investigations. For that reason, we conducted in vitro flow-driven fibrinolysis experiments to study pure fibrin thrombi breakdown in controlled conditions and observed that the lysis front evolved non-linearly in time. To understand these results, we developed an analytical 1D lysis model in which the thrombus is considered a porous medium. The lytic cascade is reduced to a second-order reaction involving fibrin and a surrogate pro-fibrinolytic agent. The model was able to reproduce the observed lysis evolution under the assumptions of constant fluid velocity and lysis occurring only at the front. For adding complexity, such as clot heterogeneity or complex flow conditions, we propose a 3-dimensional mesoscopic numerical model of blood flow and fibrinolysis, which validates the analytical model’s results. Such a numerical model could help us better understand the spatial evolution of the thrombi breakdown, extract the most relevant physiological parameters to lysis efficiency, and possibly explain the failure of the clinical treatment. These findings suggest that even though real-world fibrinolysis is a complex biological process, a simplified model can recover the main features of lysis evolution.</p

Mesoscopic Modeling of Stroke Treatment

Strokes are a leading cause of disability and death globally, and effective treatments remain a critical medical challenge. They are classified into two main types: ischemic and hemorrhagic. Ischemic strokes occur due to the occlusion of a brain vessel by a thrombus, while hemorrhagic strokes result from significant bleeding in the brain. The current state-of-the-art treatments involve techniques such as thrombolysis, thrombectomy, thrombus aspiration for ischemic strokes, and coiling, stenting, or slowing down blood flow for hemorrhagic strokes. Nevertheless, each treatment’s applicability and benefit-to-risk ratio is still not satisfying. The development of new therapies, often a lengthy, complex, and highly regulated process, could be eased by modeling. This idea materializes into so-called in silico trials, where existing or new medical procedures or drugs are simulated and tested numerically, hopefully guiding the improvement of clinical expertise. This thesis's major work consists of constructing a thrombolysis model within the context of the INSIST project, which aims at simulating and understanding every stage of ischemic stroke treatment and providing a framework for in silico trials. </p