COLLABORATING MEDICAL CENTERS

Gorman Cardiovascular Research Group


UT Southwestern Children's Medical Center and Cardiothoracic Surgery

Wafic Said Molecular Cardiology Lab

Austin Heart Hospital

UT Dell Medical School
COLLABORATING ENGINEERING LABORATORIES

Cardiovascular Fluid Mechanics Laboratory

Artificial Heart & Cardiovascular Fluid Dynamics Lab

Computational Fluid-Structure Interaction Laboratory

LATEST NEWS

1). WCCMS Recent Publication: 04/13/2021

Isogeometric finite element-based simulation of the aortic heart valve: Integration of neural network structural material model and structural tensor fiber architecture representations

Wembo Zhang | Giovanni Rossini | David Kamensky | Tan Bui-Thanh | Michael S. Sacks

The functional complexity of native and replacement aortic heart valves (AVs) is well known, incorporating such physical phenomenons as time‐varying non‐linear anisotropic soft tissue mechanical behavior, geometric non‐linearity, complex multi‐surface time varying contact, and fluid–structure interactions to name a few. It is thus clear that computational simulations are critical in understanding AV function and for the rational basis for design of their replacements. However, such approaches continued to be limited by ad‐hoc approaches for incorporating tissue fibrous structure, high‐fidelity material models, and valve geometry. To this end, we developed an integrated tri‐leaflet valve pipeline built upon an isogeometric analysis framework. A high‐order structural tensor (HOST)‐based method was developed for efficient storage and mapping the two‐dimensional fiber structural data onto the valvular 3D geometry. We then developed a neural network (NN) material model that learned the responses of a detailed meso‐structural model for exogenously cross‐linked planar soft tissues. The NN material model not only reproduced the full anisotropic mechanical responses but also demonstrated a considerable efficiency improvement, as it was trained over a range of realizable fibrous structures. Results of parametric simulations were then performed, as well as population‐based bicuspid AV fiber structure, that demonstrated the efficiency and robustness of the present approach. In summary, the present approach that integrates HOST and NN material model provides an efficient computational analysis framework with increased physical and functional realism for the simulation of native and replacement tri‐leaflet heart valves.

“Isogeometric finite element‐based simulation of the aortic heart valve: Integration of neural network structural material model and structural tensor fiber architecture representations - Zhang - 2021 - International Journal for Numerical Methods in Biomedical Engineering - Wiley Online Library.” https://onlinelibrary.wiley.com/doi/full/10.1002/cnm.3438

2). Postdoctoral Fellow Dr. Toni M. West Awarded AHA Postdoctoral Fellowship


Dr. Toni M. West has recently been awarded a 2-year fellowship from the American Heart Association to complete her project entitled, “Elucidating the Role of Altered Cyclic Stretch in Bicuspid Aortic Valves: Implications for Cell Signaling and Mechanics.” Through her work in WCCMS, Toni is collaborating closely with Dr. Aaron Baker from UT BME and Dr. Giovanni Ferrari from Columbia University to identify novel pharmacological targets for human aortic stenosis. To identify such targets, Dr. West is investigating signaling networks that are hyper-activated in valve interstitial cells when these cells are under cyclical mechanical loads similar to those seen in bicuspid aortic valves.

3). WCCMS Paper receives 13 Citations and 1831 Downloads

A WCCMS paper published in APL Bioengineering titled, “Transmural remodeling of right ventricular myocardium in response to pulmonary arterial hypertension,” has thus far received 13 citations and 1831 full-text downloads. In this work, we extended our constitutive model for right ventricular free wall myocardium to investigate the transmural mechanical and structural remodeling post-Pulmonary arterial hypertension (PAH). The paper can be accessed here.