3D Characterization of the Aortic Valve and Aortic Arch in Bicuspid Aortic Valve Patients.

Patients with bicuspid aortic valve (BAV) commonly have associated aortic stenosis and aortopathy. The geometry of the aortic arch and BAV is not well defined quantitatively, which makes clinical classifications subjective or reliant on limited 2D measurements. The goal of this study was to characterize the 3D geometry of the aortic arch and BAV using objective and quantitative techniques. Pre-TAVR computed tomography angiogram (CTA) in patients with BAV and aortic stenosis (AS) were analyzed (n = 59) by assessing valve commissural angle, presence of a fused region, percent of fusion, and calcium volume. The ascending aorta and aortic arch were reconstructed from patient-specific imaging segmentation to generate a centerline and calculate maximum curvature and maximum area change for the ascending aorta and the descending aorta. Aortic valve commissural angle signified a bimodal distribution suggesting tricuspid-like (≤ 150°, 52.5% of patients) and bicuspid-like (> 150°, 47.5%) morphologies. Tricuspid like was further classified by partial (10.2%) or full (42.4%) fusion, and bicuspid like was further classified into valves with fused region (27.1%) or no fused region (20.3%). Qualitatively, the aortic arch was found to have complex patient-specific variations in its 3D shape with some showing extreme diameter changes and kinks. Quantitatively, subgroups were established using maximum curvature threshold of 0.04 and maximum area change of 30% independently for the ascending and descending aorta. These findings provide insight into the geometric structure of the aortic valve and aortic arch in patients presenting with BAV and AS where 3D characterization allows for quantitative classification of these complex anatomic structures.

Calcium Fracture and Device Over Expansion in Transcatheter Aortic Valve Replacement for Bicuspid Aortic Valves.

Transcatheter aortic valve replacement (TAVR) in patients with bicuspid aortic valve disease (BAV) has potential risks of under expansion and non-circularity which may compromise long-term durability. This study aims to investigate calcium fracture and balloon over expansion in balloon-expandable TAVs on the stent deformation with the aid of simulation. BAV patients treated with the SAPIEN 3 Ultra with pre- and post-TAVR CTs were analyzed (n = 8). Simulations of the stent deployment were performed (1) with baseline simulation allowing calcium fracture, (2) without allowable calcium fracture and (3) with balloon over expansion (1 mm larger diameter). When compared to post CT, baseline simulations had minimal error in expansion (2.5% waist difference) and circularity (3.0% waist aspect ratio difference). When compared to baseline, calcium fracture had insignificant impact on the expansion (- 0.5% average waist difference) and circularity (- 1.6% average waist aspect ratio difference). Over expansion had significantly larger expansion compared to baseline (15.4% average waist difference) but had insignificant impact on the circularity (- 0.5% waist aspect ratio difference). We conclude that stent deformation can be predicted with minimal error, calcium fracture has small differences on the final stent deformation except in extreme calcified cases, and balloon over expansion expands the waist closer to nominal values.

Image Registration-Based Method for Reconstructing Transcatheter Heart Valve Geometry from Patient-Specific CT Scans.

Accurate reconstruction of transcatheter aortic valve (TAV) geometries and other stented cardiac devices from computed tomography (CT) images is challenging, mainly associated with blooming artifacts caused by the metallic stents. In addition, bioprosthetic leaflets of TAVs are difficult to segment due to the low signal strengths of the tissues. This paper describes a method that exploits the known device geometry and uses an image registration-based reconstruction method to accurately recover the in vivo stent and leaflet geometries from patient-specific CT images. Error analyses have shown that the geometric error of the stent reconstruction is around 0.1mm, lower than 1/3 of the stent width or most of the CT scan resolutions. Moreover, the method only requires a few human inputs and is robust to input biases. The geometry and the residual stress of the leaflets can be subsequently computed using finite element analysis (FEA) with displacement boundary conditions derived from the registration. Finally, the stress distribution in self-expandable stents can be reasonably estimated by an FEA-based simulation. This method can be used in pre-surgical planning for TAV-in-TAV procedures or for in vivo assessment of surgical outcomes from post-procedural CT scans. It can also be used to reconstruct other medical devices such as coronary stents.

Biomechanics of Transcatheter Aortic Valve Replacement Complications and Computational Predictive Modeling.

Transcatheter aortic valve replacement (TAVR) is a rapidly growing field enabling replacement of diseased aortic valves without the need for open heart surgery. However, due to the nature of the procedure and nonremoval of the diseased tissue, there are rates of complications ranging from tissue rupture and coronary obstruction to paravalvular leak, valve thrombosis, and permanent pacemaker implantation. In recent years, computational modeling has shown a great deal of promise in its capabilities to understand the biomechanical implications of TAVR as well as help preoperatively predict risks inherent to device-patient-specific anatomy biomechanical interaction. This includes intricate replication of stent and leaflet designs and tested and validated simulated deployments with structural and fluid mechanical simulations. This review outlines current biomechanical understanding of device-related complications from TAVR and related predictive strategies using computational modeling. An outlook on future modeling strategies highlighting reduced order modeling which could significantly reduce the high time and cost that are required for computational prediction of TAVR outcomes is presented in this review paper. A summary of current commercial/in-development software is presented in the final section.