# Optimizing Congenital Aortic Valve Surgery with Simulation-Guided Design

> **NIH NIH K25** · STANFORD UNIVERSITY · 2024 · $181,392

## Abstract

PROJECT SUMMARY
Congenital heart disease occurs in about 1% of births, making it the most common type of birth defect and leading
cause of infant mortality in the United States. Congenital aortic valve disease, one category of congenital heart
disease, frequently requires surgery. Despite generally positive results, undesirable outcomes remain common,
and measures of success are typically based on an empirical, retrospective “guess and check” approach. Due
to heterogeneous disease, clinical trials are difficult to conduct. Two promising procedures are bicuspidization
repair, in which the surgeon constructs a two leaflet valve, and bioprinted valve replacement, a new type of highly
experimental prosthetic valve that can potentially grow with the patient. The optimal valve geometry for both pro-
cedures remains under debate or unknown. Thus, there is an unmet clinical need for engineering design tools to
optimize postoperative valve geometry and improve outcomes. Simulations provide a controllable and efficient
means to predict optimal surgical procedures, and after validation, translate guidelines to the clinic. Central to
this work is a novel and robust modeling framework for simulating heart valves developed by the applicant, Dr.
Alexander D. Kaiser. This research will leverage his modeling methods combined with a multimodal approach
including in vitro and human studies to efficiently translate scientific knowledge to the clinic. Dr. Kaiser pro-
poses to (1) optimize the postoperative leaflet geometry of bicuspidization repair and bioprinted replacement with
simulation-guided design, (2) confirm and validate optimal valve performance in vitro and (3) translate guidelines
to the clinic to advise bicuspidization repairs. Dr. Kaiser has extensive previous training in applied mathematics,
numerical methods and computational modeling of heart valves. His career development plan includes training in
congenital heart disease pathophysiology and methods of surgical treatment, in vitro experimental methods and
medical imaging. The Department of Cardiothoracic Surgery at Stanford University will provide an outstanding
interdisciplinary environment to enable Dr. Kaiser’s transition from primarily researching applied mathematics
to being an interdisciplinary, medical investigator. Mentor Michael Ma is a leading, innovative pediatric cardiac
surgeon eager to incorporate new scientific information into his surgical practice. Co-mentor Alison Marsden is
a renowned expert in computational modeling of the cardiovascular system. Complementary expertise will be
offered by advisors Drs. Ennis (MRI, in vitro testing), Skylar-Scott (bioprinting), Feinstein (pediatric cardiology)
and Woo (cardiac surgeon). Dr. Kaiser will receive extensive mentoring, guidance and resources to transition to
independence. To conclude, the mentoring, training, research experience and clinical research environment will
prepare Dr. Kaiser to become an independent, interdisciplinary medical...

## Key facts

- **NIH application ID:** 10949651
- **Project number:** 1K25HL175208-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Alexander D Kaiser
- **Activity code:** K25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $181,392
- **Award type:** 1
- **Project period:** 2024-08-16 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10949651

## Citation

> US National Institutes of Health, RePORTER application 10949651, Optimizing Congenital Aortic Valve Surgery with Simulation-Guided Design (1K25HL175208-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10949651. Licensed CC0.

---

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