# A predictive model of left ventricle remodeling in the presence of injected polymer > **NIH NIH F32** · UNIVERSITY OF TEXAS AT AUSTIN · 2024 · $76,756 ## Abstract PROJECT SUMMARY/ABSTRACT In the weeks following myocardial infarction, damaged tissue undergoes a structural change, where myocytes are broken down and removed, and collagenous tissue is restructured. This structural change impairs the tissue's ability to resist internal pressures and if left untreated can lead to aneurysmal growth, ischemic mitral regurgi- tation, and ultimately heart failure. Polymer injection therapy has been clinically shown to reduce post-infarct left-ventricle cardiac wall remodeling, but the development of this treatment thus far has been largely experimen- tal. Optimal therapy parameters, both for generic treatment and for individual patients are currently unknown. Our objective for this proposal is to develop an experimentally guided computational model of left ventricle remodeling that incorporates heart-specific imaging data, which will enable us to systematically optimize the polymer injection therapy by examining the impact of treatment parameters such as injection volume, site density, and polymer stiffness. This heart-specific imaging data will allow us to determine the effect of individual infarct geometry and myocardium microstructure, and to tailor treatment to individual cases. We also seek to use this image data to validate the long term predictions of this model, demonstrating that it can predict the remodeling that occurs, and the impact of different polymer injection configurations. Therefore, it will serve to preemptively consider multiple treatment options so clinicians can choose the best course of action for individual patients. The objectives of this proposal are summarized in the three following specific aims: SA1. Model post-infarct tissue remodeling matching established ovine MI model progression SA2. Validate in a heart-specific pipeline at the tissue and organ levels SA3. Utilize the previously generated model to optimize polymer injection treatment protocol ## Key facts - **NIH application ID:** 10744263 - **Project number:** 5F32HL162423-03 - **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN - **Principal Investigator:** Christian Goodbrake - **Activity code:** F32 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $76,756 - **Award type:** 5 - **Project period:** 2022-01-01 → 2024-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10744263 ## Citation > US National Institutes of Health, RePORTER application 10744263, A predictive model of left ventricle remodeling in the presence of injected polymer (5F32HL162423-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10744263. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*