Patient-Specific Quantification of Normal and Bicuspid Aortic Valve Leaflet Deformations from Clinically Derived Images

Abstract

The clinical benefit of patient-specific modeling of heart valve disease remains an unrealized goal, often a result of our limited understanding of the in vivo milieu. This is particularly true in assessing bicuspid aortic valve (BAV) disease, the most common cardiac congenital defect in humans, which leads to premature and severe aortic stenosis or insufficiency (AS/AI). However, assessment of BAV risk for AS/AI on a patient-specific basis is hampered by the substantial degree of anatomic and functional variations that remain largely unknown. The present study was undertaken to utilize a noninvasive computational pipeline (https://doi.org/10.1002/cnm.3142) that directly yields local heart valve leaflet deformation information using patient-specific real-time three-dimensional echocardiographic imaging (rt-3DE) data. Imaging data was collected for patients with normal tricuspid aortic valve (TAV, $n = 8$) and those with BAV ($n = 5$ with fused left and right coronary leaflets and $n = 5$ with fused right and non-coronary leaflets), from which the medial surface of each leaflet was extracted. The resulting deformation analysis resulted in, for the first time, quantified differences between the in vivo functional deformations of the TAV and BAV leaflets. Our approach was able to capture the complex, heterogeneous surface deformation fields in both TAV and BAV leaflets. We were able to identify and quantify differences in stretch patterns between leaflet types, and found in particular that stretches experienced by BAV leaflets during closure differ from those of TAV leaflets in terms of both heterogeneity as well as overall magnitude. Deformation is a key parameter in the clinical assessment of valvular function, and serves as a direct means to determine regional variations in structure and function. This study is an essential step toward patient-specific assessment of BAV based on correlating leaflet deformation and AS/AI progression, as it provides a means for assessing patient-specific stretch patterns

Appendix

The image-based stretch estimation method employed in the present study has been previously validated for valvular tissues against both in vitro and in vivo fiducial marker-based deformation metrics.²¹ However, previous validation studies were performed only for the mitral valve, whose geometry is substantially distinct from that of the AV. To further validate our approach for the specific application to the AV, we applied the stretch estimation method to a computationally generated spline surface geometry of a bioprosthetic TAV implant.^27,31 While the bioprosthetic AV has an idealized geometry by design, this validation approach had the advantage of allowing for the comparison of our estimated stretch fields to ground-truth local stretch maps for the modeled TAV, which were obtained via isogeometric analysis.³¹ Resulting stretches from this validation study showed that our technique was able to accurately capture the complex, heterogeneous leaflet deformation field of the AV (Fig. 9). Specifically, our noninvasive method was able to yield stretch estimates within 5% of their ground-truth value over the entire leaflet surface.

Figure 9

In-plane stretch in the normal TAV, showing the capability of the method to capture substantial regional heterogeneity as well as directional differences in stretch.