Abstract
Acute Ischemic Stroke (AIS) is a life threatening condition that occurs when an artery within the brain is blocked by a pathological blood clot, called a thrombus. The most popular treatment approach for AIS relies on intravenous administration of a drug named tissue plasminogen activator (tPA) to dissolve fibrin fibers within the clot. Despite the widespread use of tPA, treatment outcomes are often unsuccessful. This is commonly attributed to local clot-flow interactions and their effect on drug delivery into a thrombus. Yet, detailed characterization of flow-mediated drug transport within and around the thrombus remains a challenge, especially when the thrombus is far downstream from the administration site. Here, we address this challenge by using an in silico finite element model to investigate how hemodynamics affects drug delivery and lysis in a fully occluding thrombus within an anatomically realistic brain vascular segment. Specifically, we developed a computational methodology for coupling unsteady pulsatile hemodynamics with advection and diffusion of tPA, and a fibrinolysis reaction model, to elucidate the complex dynamics underlying drug delivery and clot dissolution within realistic patient-specific vasculature. In our study, the thrombus is modeled as an immersed homogeneous porous media. A pulsatile inflow profile, based on prior simulation data, is specified as boundary conditions at the left and right internal carotid arteries and the basilar artery. The flow is advected to the 6 major cerebral arteries. Our coupling scheme leverages a stabilized finite element method, using a fictitious domain approach to represent the effect of the clot on blood flow using a Brinkman model, where interior permeability is modeled as a function of clot porosity. A staggered multiphysics scheme couples this with a stabilized finite element framework for advection-diffusion equations. The average concentration of tPA is input into a five-species biochemical reaction model of the fibrinolysis cascade that describes porosity as a function of the temporal evolution of lysis proteins during tPA infusion. We demonstrate that our methodology can effectively capture this flow-transport-reaction-dissolution coupling, generate detailed spatiotemporal predictions of lysis drug delivery and action, and generate key computational descriptors that are otherwise challenging to obtain in vivo or in vitro.
