# Computational and Biological Approach to Flow Diversion

> **NIH NIH R01** · MAYO CLINIC ROCHESTER · 2020 · $375,815

## Abstract

PROJECT SUMMARY
This competitive renewal application focuses on advancing the rapidly-evolving field of intracranial flow
diversion, which, over the span of less than 5 years, has grown to encompass up to one-third of intracranial
aneurysm treatments in the US. We will address clinically-relevant, ongoing gaps in knowledge, including 1)
what constitutes the primary mechanism of action of flow diverter efficacy, 2) what underlies the unusual, but
devastating complications, including ipsilateral, intraparenchymal hemorrhage and spontaneous aneurysm
rupture, and 3) what design features of these devices can be enhanced to optimize outcomes? Our
translational, hypothesis-driven methodology traverses from computational/in vitro work (computational fluid
dynamics and in vitro bioreactor studies) to in vivo experiments in a rabbit model and, finally, to clinical studies.
Our statistically robust evaluations will directly address 1) the role of wall apposition in aneurysm healing and
risk for complication, 2) downstream hemodynamic derangements caused by flow diverter implantation vis-à-
vis risk for spontaneous hemorrhage, and 3) the relative impact of diversion of flow versus other factors,
including thrombus formation and endothelialization, in healing. The discoveries from this competitive renewal
will be directly applicable to clinicians treating patients with currently-approved devices and managing patients
following flow diversion treatment in order to optimize outcomes and minimize complications, as well as to
engineers and scientists focused on developing idealized, future devices, even those with patient-specific,
individualized features.

## Key facts

- **NIH application ID:** 9993648
- **Project number:** 5R01NS076491-10
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Juan R Cebral
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $375,815
- **Award type:** 5
- **Project period:** 2011-09-20 → 2021-12-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9993648

## Citation

> US National Institutes of Health, RePORTER application 9993648, Computational and Biological Approach to Flow Diversion (5R01NS076491-10). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9993648. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*