# Computational modeling of platelets and thrombosis in cerebral aneurysm treatment

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2024 · $409,473

## Abstract

Here we seek to improve the accuracy of hemodynamic modeling of cerebral aneurysms. This goal of this
project is to predict the outcome of cerebral aneurysm treatment. This is significant due to the prevalence of
cerebral aneurysms, their dismal prognosis when ruptured, and treatment failure rates (resulting in aneurysm
recurrence and risk of either brain hemorrhage or need for retreatment) of up to 40%. Hemodynamic forces are
thought to influence aneurysm treatment outcomes, and can be simulated using computational fluid dynamics
(CFD) methods, but such studies have not been widely accepted due to conflicting results. Traditional CFD
analysis (termed “Eulerian” metrics) only studies the effect of blood flow on the vascular walls, largely ignoring
circulating blood products such as platelets that initiate intra-aneurysmal thrombosis (termed “Lagrangian”
metrics), which have a critical role in treatment outcome. Better prediction through a holistic approach
combining both types of analyses could identify patients at risk for treatment failure, influencing pre-surgical
decision-making.
 This project builds on our ongoing NIH-funded expertise (via a renewal of R01NS105692) in the CFD
modeling of cerebral aneurysms before and after treatment. We have developed an innovative method of
incorporating novel Lagrangian metrics, such as residence time and shear history, into CFD simulations in with
existing Eulerian hemodynamic metrics, to create a holistic approach to modeling the effects of aneurysm
treatment. Feasibility studies have characterized the post-treatment hemodynamic environment with special
attention to platelet-representative particles that experience prolonged intra-aneurysmal residence time and
low cumulative shear history within treated aneurysms. Previous in vitro studies of platelets in similar
conditions demonstrate thrombosis in such environments, which would be advantageous after aneurysm
treatment to develop a stable thrombus leading to aneurysm healing.
 First, we will perform CFD simulations before and after treatment on a cohort of cerebral aneurysms
whose treatment outcome (success or failure) is known. We will include both Eulerian and Lagrangian metrics
to determine associations with treatment outcome. Second, we will use an established animal model of
cerebral aneurysms, treated with commercially-available endovascular devices. We will perform CFD
simulations a similar holistic model as the human aneurysm cohort, and investigate the relationship between
Lagrangian metrics and treatment-related thrombosis on histological analysis. The final result will be an
optimized CFD methodology and set of Eulerian and Lagrangian variables predictive of outcome after cerebral
aneurysm embolization.

## Key facts

- **NIH application ID:** 10901980
- **Project number:** 5R01NS105692-07
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Michael Robert Levitt
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $409,473
- **Award type:** 5
- **Project period:** 2018-01-01 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10901980

## Citation

> US National Institutes of Health, RePORTER application 10901980, Computational modeling of platelets and thrombosis in cerebral aneurysm treatment (5R01NS105692-07). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10901980. Licensed CC0.

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