# Biomechanical Indices for Coronary Lesion Rupture Risk and Lesion Prognostication

> **NIH NIH R01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $501,240

## Abstract

PROJECT SUMMARY
Acute coronary syndromes (ACS) are a result of sudden luminal thrombosis. These pathologic events are a
significant clinical problem, not only because of their frequency, but also due to the diagnostic challenge in
stratifying risk for coronary lesions (i.e., stable versus rupture-prone) and identifying lesions that will undergo
rapid progression and increased vulnerability (i.e., lesion prognostication). Although invasive imaging modalities
can characterize plaque composition and phenotype, the use of imaging to risk stratify coronary lesions that will
precipitate an ACS event has proven less accurate. Thus, plaque risk stratification strategies should move
beyond image-based morphologic markers and focus on identifying the local environmental factor(s) that
contribute to rapid coronary artery disease (CAD) progression, heightened vulnerability, and rupture risk. The
overall goal of this R01 proposal, therefore, is to examine the predictive value of mechanical metrics for lesion
risk stratification and prognostication in prospective studies evaluating the natural history of coronary
atherosclerosis. Our central hypothesis is that mechanical indices will advance the identification of high-risk
coronary lesions and promote the ability to predict plaque rupture. To realize this goal, we will approach this
research through two hypothesis-driven Specific Aims: (i) examine the predictive value of plaque material
stiffness in stratifying risk for coronary lesion rupture and (ii) evaluate the prognostic value of deformation-
induced wall stress for identifying rapidly progressing CAD and increased plaque vulnerability. We propose to
develop and validate computational frameworks to extract the heterogeneous material properties of coronary
arteries and predict the 3D patient-specific coronary plaque mechanical environment through forward finite
element analysis. Subsequently, these frameworks will be clinically translated to establish their clinical value.
Successful completion of the proposed research will advance understanding of the prognostic value of
mechanics in the natural history of CAD and advance patient management and treatment strategies towards
minimizing adverse events associated with ACS.

## Key facts

- **NIH application ID:** 9866522
- **Project number:** 1R01HL150608-01
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Lucas H. Timmins
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $501,240
- **Award type:** 1
- **Project period:** 2020-01-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9866522

## Citation

> US National Institutes of Health, RePORTER application 9866522, Biomechanical Indices for Coronary Lesion Rupture Risk and Lesion Prognostication (1R01HL150608-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9866522. Licensed CC0.

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