# Unique value of real-time shear stress to enhance coronary disease management

> **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $811,873

## Abstract

Management of CAD is hindered by our inability to investigate fundamental pathobiologic processes
that lead to individual coronary plaque progression, destabilization, and adverse clinical events. A critical
mechanism responsible for plaque behavior is local endothelial shear stress (ESS), the frictional force of blood
flowing across the endothelium, which is governed by the artery’s detailed local geometry. Focal regions of low
ESS drive a host of proatherogenic, proinflammatory, and prothrombotic processes; it is therefore not
surprising that low ESS has now been found to be the most powerful predictor of future coronary events.
However, current methods to compute local ESS in vivo require unique expertise and are extremely time- and
resource-intensive, involving a lengthy, off-line procedure for reconstructing the 3D artery lumen from separate
OCT and angiographic images and a computational fluid dynamics (CFD) simulation that takes many hours.
These limitations prevent the use of this vital information to improve the treatment of patients.
 Our goal is to utilize ESS to guide optimal management during cardiac catheterization for patients with
a broad array of coronary syndromes. We will accomplish this goal by developing and validating a single
catheter/computer console system that will automatically compute ESS in real time (RT-ESS). Components
include a novel, multimodality optical coherence tomography (OCT) catheter that senses its own shape by
detecting strain-sensitive changes in fluorescence from single-walled carbon nanotubes (SWCNT) coated
inside its sheath. Using OCT images acquired simultaneously with SWCNT fluorescence, we will develop
algorithms to automatically create an anatomically-correct 3D artery model for CFD. By accelerating the CFD
process, detailed ESS maps from human coronaries will be computed in 1-3 minutes and displayed with
anatomic OCT images. The RT-ESS technology will be first validated using a swine coronary atherosclerosis
model and then in patients undergoing percutaneous coronary intervention (PCI). In the final Aim, we will
conduct a clinical study to determine the relationship between ESS and fractional flow reserve (FFR). The
combination of pathobiologic/anatomic RT-ESS data and FFR will likely improve prognostication of individual
coronary lesions, leading to more informed clinical decision-making and better patient outcomes.

## Key facts

- **NIH application ID:** 9844977
- **Project number:** 5R01HL140498-03
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Peter Howard Stone
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $811,873
- **Award type:** 5
- **Project period:** 2018-01-01 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9844977

## Citation

> US National Institutes of Health, RePORTER application 9844977, Unique value of real-time shear stress to enhance coronary disease management (5R01HL140498-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9844977. Licensed CC0.

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