# In-Vivo Patient-Specific Optimization of Transcatheter-Edge-to-Edge Repair in Mitral Regurgitation

> **NIH NIH F31** · UNIVERSITY OF TEXAS AT AUSTIN · 2024 · $40,493

## Abstract

PROJECT SUMMARY
Mitral regurgitation (MR) is a prevalent and deadly disease characterized by the inability of the mitral
valve (MV) leaflets to coapt properly, permitting backflow of blood from the left ventricle into the left
atrium. The etiologies of MR are complex and diverse, ranging from myxomatous degeneration of the
valvular tissue to myocardial infarction to non-ischemic cardiomyopathy. Several types of treatment are
available, but the efficacy of these interventions remains suboptimal and unpredictable. One of these
options is the relatively recent transcatheter edge-to-edge leaflet clipping technique called the MitraClip
procedure (or TEER). Though the procedure is safe, its outcomes in clinical trials, particularly compared
to other surgical and therapeutic treatments, have been highly contradictory, largely due to the
multifactorial nature of MR. Therefore, it is clear that a predictive approach to treatment selection that
accounts for patient specific variations in MV shape and deformation is necessary to optimize long-
term patient outcomes. Our group has developed a noninvasive, image-based method for in vivo MV
strain estimation which allows us to quantify MV shape and deformation directly from clinically available
imaging data. We have also previously demonstrated that this technique can be used to identify
predictive, presurgical factors of repair efficacy for ischemic MR patients undergoing undersized ring
annuloplasty. However, previous work by our lab and others has focused on limited subsets of MR
patients; in order to develop a comprehensive treatment selection guide, simulations must be grounded
in a robust understanding of the altered MV biomechanical state in the full range of MR etiologies.
Furthermore, the effects of the highly non-physiological focal stress of the MitraClip on the immediate
and long-term shape and deformation of the MV leaflets remains almost completely unknown. We will
additionally develop a fully predictive finite element simulation of the TEER procedure in order to
preoperatively test various MitraClip scenarios directly on a 3D model of the patient's MV apparatus,
use our understanding of the MV functional state to predict the 12-month outcomes of each
configuration, and select the most optimal option. Therefore, in this study, we aim to (1) establish the
pre-operative state of the MV across the MR spectrum and (2) elucidate and predict the consequences
of the MitraClip on MV leaflet geometry, behavior, and remodeling in order to explain and ultimately
predict the outcomes of this treatment in a patient-specific and quantitative manner.

## Key facts

- **NIH application ID:** 10934339
- **Project number:** 5F31HL170754-02
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Natalie Simonian
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $40,493
- **Award type:** 5
- **Project period:** 2023-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10934339

## Citation

> US National Institutes of Health, RePORTER application 10934339, In-Vivo Patient-Specific Optimization of Transcatheter-Edge-to-Edge Repair in Mitral Regurgitation (5F31HL170754-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10934339. Licensed CC0.

---

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