Session: 10-04-01: Young Engineer Paper (YEP) Contest Fluids Engineering Division

Paper Number: 143625

143625 - In Silico Analysis of Flow-Mediated Drug Transport for Thrombolytic Therapy in Acute Ischemic Stroke 

Introduction: Ischemic stroke is a life threatening condition that occurs when an artery within the brain is blocked by a pathological blood clot, or thrombus. Current treatment approaches rely 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 can be attributed to clot-flow interactions and their effect on drug delivery into a thrombus. Detailed characterization of flow-mediated drug transport within and around the thrombus remains a challenge, especially when the thrombus is far upstream from the administration site. Here, we address this challenge by using an in silico finite element model to investigate how hemodynamics affect drug delivery and lysis in a fulling occluding thrombus within an anatomically realistic brain vascular segment. By coupling hemodynamics with advection and diffusion of tPA, and a fibrinolysis reaction model, we aim to elucidate the complex dynamics underlying drug delivery and clot dissolution within the vasculature.

 

Methods: A fully occluding, 3mm long thrombus was artificially placed inside a supplying artery within a three-dimensional anatomically realistic model of the major arterial network at the base of the brain (called the Circle of Willis). The thrombus is modeled as a homogeneous porous media, with an initial porosity of 0.05. Pulsatile inflow, derived from prior simulation data, is specified as boundary conditions at the left and right internal carotid artery and basillar artery. Resistance based outflow boundary conditions are used to distribute flow to the 6 major cerebral arteries: left and right anterior cerebral arteries (ACA), middle cerebral arteries (MCA), and posterior cerebral arteries (PCA).

Hemodynamics are modeled using a stabilized finite element method (FEM) implemented in an open source finite element library (FEniCS). Local flow within the thrombus is modeled using a Brinkman penalization term, where permeability is modeled as a function of the clot porosity based on the Kozeny-Carman model. A stabilized advection-diffusion model describes the transport of tPA throughout the domain. The average concentration of tPA within the occluding region is input into a six-species reaction model that describes porosity as a function of the temporal evolution of lysis proteins during tPA infusion. The clot is assumed to lyse homogeneously to reduce computational cost and enable rapid parametric studies on dissolution. 

 

Preliminary Results: Through preliminary efforts, we have successfully integrated pulsatile hemodynamics, the advection and diffusion of tPA, and fibrinolytic reactions in a simplified, single-vessel geometry, with a fully occluding thrombus. The simulations demonstrate that the coupled multiphysics approach can provide estimates of key endpoints: speed of lysis; and extent of clot lysis. We further demonstrated that clinical variables, such as dosimetry and dosing pattern of tPA, can be integrated as inputs to the framework; enabling robust translation of simulation endpoints to treatment outcome metrics. Finally, ongoing simulation efforts are expanding these analyses with a complex, cerebrovascular network model of the Circle of Willis as described above. 

 

Conclusions: In conclusion, modeling the dissolution dynamics in physiologically realistic pulsatile flow environments is feasible with our in silico approach. We aim to use this model to quantify key lysis variables, assess reperfusion outcomes, and provide insights into therapeutic strategies from a flow-physics informed lens.

 

 

Presenting Author: Nick Rovito University of Colorado Boulder

Presenting Author Biography: Nick Rovito is a 1st year mechanical engineering PhD student at the University of Colorado, Boulder. With an interest in interdisciplinary research, Nick is dedicated to exploring the intersections of mechanical engineering and biomedical sciences to address critical issues in cardiovascular health. Nick's research interests include computational modeling of biofluids and biomechanics, focusing on drug transport, thrombosis, and thrombolysis. He is excited about using computational fluid dynamics (CFD) techniques to study cardiovascular diseases and develop solutions for improved diagnosis and treatment.

Nick completed a Bachelor of Science in Mechanical Engineering and a Bachelor of Arts in Spanish Language at the University of Arkansas, and graduated with high distinction. While at the University of Arkansas, he developed CFD-based optimization algorithms for hydrokinetic energy systems.

Authors:

Nick Rovito University of Colorado Boulder
Debanjan Mukherjee University of Colorado Boulder