# 4D ventricle-valve model risk stratification for planning surgical treatment of ischemic mitral regurgitation > **NIH NIH F30** · UNIVERSITY OF PENNSYLVANIA · 2020 · $32,585 ## Abstract Project Summary/Abstract Ischemic mitral regurgitation (IMR) is a disease where the normal mitral valve (MV) structure is dysfunctional due to left ventricular (LV) remodeling after a myocardial infarction (MI). IMR affects nearly 3 million Americans and the magnitude of this problem is expected to grow as the population ages. IMR has a substantial mortality rate that is associated with even mild MR severity. Mitral valve repair with undersized ring annuloplasty has been the preferred treatment strategy for IMR; however, the recurrence of moderate or severe IMR within 12 months of surgery is common. Recent high profile results from the Cardiothoracic Surgical Trials Network (CTSN) mul- ticenter randomized trials on IMR have confirmed a high incidence of early recurrent IMR. More importantly, these studies highlighted the adverse impact of recurrent IMR on LV remodeling and clinical outcomes. The CTSN trials demonstrated no significant difference in LV volume reduction or survival at 12 and 24 months between repair and replacement groups; however, subgroup analysis demonstrated that repair patients that developed recurrent IMR had no reduction in LV volume while repair patients without recurrence experienced LV volume reduction that was superior to patients having valve replacement. The results of the CTSN IMR trials indicate an unmet need for a pre-operative risk stratification tool that reliably predicts MV repair failure. Such a tool would significantly reduce the problem of recurrent IMR by performing valve repair only in patients likely to experience a durable result and performing valve replacement in patients with high risk of recurrence. The long term goal is to improve quality of surgical therapy in IMR by improving risk-stratification pre-operatively using image analysis tools. The overall objective of this proposal is to improve the prediction IMR recurrence by ex- panding this model to include the left ventricle (LV). The rationale is that while IMR manifests as MV malcoapta- tion, the root cause of the disease is LV remodeling. The central hypothesis is that features extracted from the integrated left ventricular and mitral valve (LVMV) model will predict recurrence more accurately than the current MV-only model. To fulfill this objective and test the central hypothesis by pursuing the following specific aims: 1) Develop the 4D integrated LVMV model and compare the accuracy of fitting this model to intraoperative 3DTE images to that of the existing MV-only model. 2) Assess the ability of biomarkers derived from the integrated LVMV model to predict IMR recurrence, and compare to the predictive value of the MV-only model. The project is significant because, if successful, the integrated LVMV model will be incorporated into the Gorman lab ongoing effort translating this technology to the operating room, thus improving survival rates, reducing the impending clinical burden and the number of repeated procedures. ## Key facts - **NIH application ID:** 9922382 - **Project number:** 5F30HL142138-03 - **Recipient organization:** UNIVERSITY OF PENNSYLVANIA - **Principal Investigator:** Ahmed Aly - **Activity code:** F30 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $32,585 - **Award type:** 5 - **Project period:** 2018-05-01 → 2021-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9922382 ## Citation > US National Institutes of Health, RePORTER application 9922382, 4D ventricle-valve model risk stratification for planning surgical treatment of ischemic mitral regurgitation (5F30HL142138-03). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/9922382. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*