Evaluation of affine fiber kinematics in porcine tricuspid valve leaflets using polarized spatial frequency domain imaging and planar biaxial testing.

2021 
Abstract Collagen fibers are the primary load-bearing microstructural constituent of bodily soft tissues, and, when subjected to external loading, the collagen fibers reorient, uncrimp, and elongate. Specific to the atrioventricular heart valve leaflets, the collagen fiber kinematics form the basis of many constitutive models; however, some researchers claim that modeling the affine fiber kinematics (AFK) are sufficient for accurately predicting the macroscopic tissue deformations, while others state that modeling the non-affine kinematics (i.e., fiber uncrimping together with elastic elongation) is required. Experimental verification of the AFK theory has been previously performed for the mitral valve leaflets in the left-side heart; however, this same evaluation has yet to be performed for the morphologically distinct tricuspid valve (TV) leaflets in the right-side heart. In this work, we, for the first time, evaluated the AFK theory for the TV leaflets using an integrated biaxial testing-polarized spatial frequency domain imaging device to experimentally quantify the load-dependent collagen fiber reorientations for comparison to the AFK theory predictions. We found that the AFK theory generally underpredicted the fiber reorientations by 3.1°, on average, under the applied equibiaxial loading with greater disparity when the tissue was subjected to the applied non-equibiaxial loading. Furthermore, increased AFK errors were observed with increasing collagen fiber reorientations (Pearson coefficient r= - 0.36 , equibiaxial loading), suggesting the AFK theory is better suited for relatively smaller reorientations. Our findings suggest the AFK theory may require modification for more accurate predictions of the collagen fiber kinematics in the TV leaflets, which will be useful in refining modeling efforts for more accurate TV simulations.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    43
    References
    2
    Citations
    NaN
    KQI
    []