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24.05.2022 | Original Article

Texas TriValve 1.0 : a reverse-engineered, open model of the human tricuspid valve

verfasst von: Mrudang Mathur, William D. Meador, Marcin Malinowski, Tomasz Jazwiec, Tomasz A. Timek, Manuel K. Rausch

Erschienen in: Engineering with Computers | Ausgabe 5/2022

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Abstract

Nearly 1.6 million Americans suffer from a leaking tricuspid heart valve. To make matters worse, current valve repair options are far from optimal leading to recurrence of leakage in up to 30% of patients. We submit that a critical step toward improving outcomes is to better understand the “forgotten” valve. High-fidelity computer models may help in this endeavour. However, the existing models are limited by averaged or idealized geometries, material properties, and boundary conditions. In our current work, we overcome the limitations of existing models by (reverse) engineering the tricuspid valve from a beating human heart in an organ preservation system. The resulting finite-element model faithfully captures the kinematics and kinetics of the native tricuspid valve as validated against echocardiographic data and others’ previous work. To showcase the value of our model, we also use it to simulate disease-induced and repair-induced changes to valve geometry and mechanics. Specifically, we simulate and compare the effectiveness of tricuspid valve repair via surgical annuloplasty and via transcatheter edge-to-edge repair. Importantly, our model is openly available for others to use. Thus, our model will allow us and others to perform virtual experiments on the healthy, diseased, and repaired tricuspid valve to better understand the valve itself and to optimize tricuspid valve repair for better patient outcomes.

Vorheriger Artikel Special Issue: Imaging-based methods in computational medicine

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Titel: Texas TriValve 1.0 : a reverse-engineered, open model of the human tricuspid valve
verfasst von: Mrudang Mathur
William D. Meador
Marcin Malinowski
Tomasz Jazwiec
Tomasz A. Timek
Manuel K. Rausch
Publikationsdatum: 24.05.2022
Verlag: Springer London
Erschienen in: Engineering with Computers / Ausgabe 5/2022
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI: https://doi.org/10.1007/s00366-022-01659-w

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