Current clinical assessment of functional tricuspid valve regurgitation relies on metrics quantified from medical imaging modalities. Although these clinical methodologies are generally successful, the lack of detailed information about the mechanical environment of the valve presents inherent challenges for assessing tricuspid valve regurgitation. In the present study, we have developed a finite element‐based in silico model of one porcine tricuspid valve (TV) geometry to investigate how various pathological conditions affect the overall biomechanical function of the TV. There were three primary observations from our results. Firstly, the results of the papillary muscle (PM) displacement study scenario indicated more pronounced changes in the TV biomechanical function. Secondly, compared to uniform annulus dilation, nonuniform dilation scenario induced more evident changes in the von Mises stresses (83.8‐125.3 kPa vs 65.1‐84.0 kPa) and the Green‐Lagrange strains (0.52‐0.58 vs 0.47‐0.53) for the three TV leaflets. Finally, results from the pulmonary hypertension study scenario showed opposite trends compared to the PM displacement and annulus dilation scenarios. Furthermore, various chordae rupture scenarios were simulated, and the results showed that the chordae tendineae attached to the TV anterior and septal leaflets may be more critical to proper TV function. This in silico modeling‐based study has provided a deeper insight into the tricuspid valve pathologies that may be useful, with moderate extensions, for guiding clinical decisions.Novelty StatementThe novelties of the research are summarized below:
A comprehensive in silico pilot study of how isolated functional tricuspid regurgitation pathologies and ruptured chordae tendineae would alter the tricuspid valve function;
An extensive analysis of the tricuspid valve function, including mechanical quantities (eg, the von Mises stress and the Green‐Lagrange strain) and clinically‐relevant geometry metrics (eg, the tenting area and the coaptation height); and
A developed computational modeling pipeline that can be extended to evaluate patient‐specific tricuspid valve geometries and enhance the current clinical diagnosis and treatment of tricuspid regurgitation.