In Vivo Imaging and Computational Analysis of the Aortic Root. Application in Clinical Research and Design of Transcatheter Aortic Valve Systems

A validated computational framework to predict outcomes in TAVI

Transcatheter aortic valve implantation (TAVI) still presents complications: paravalvular leakage (PVL) and onset of conduction abnormalities leading to permanent pacemaker implantation. Our aim was testing a validated patient-specific computational framework for prediction of TAVI outcomes and possible complications. Twenty-eight TAVI patients (14 SapienXT and 14 CoreValve) were retrospectively selected. Pre-procedural CT images were post-processed to create 3D patient-specific implantation sites. The procedures were simulated with finite element analysis. Simulations' results were compared against post-procedural clinical fluoroscopy and echocardiography images. The computational model was in good agreement with clinical findings: the overall stent diameter difference was 2.6% and PVL was correctly identified with a post-processing algorithm in 83% of cases. Strains in the implantation site were studied to assess the risk of conduction system disturbance and were found highest in the patient who required pacemaker implantation. This study suggests that computational tool could support safe planning and broadening of TAVI.

Population-specific material properties of the implantation site for transcatheter aortic valve replacement finite element simulations

Patient-specific computational models are an established tool to support device development and test under clinically relevant boundary conditions. Potentially, such models could be used to aid the clinical decision-making process for percutaneous valve selection; however, their adoption in clinical practice is still limited to individual cases. To be fully informative, they should include patient-specific data on both anatomy and mechanics of the implantation site. In this work, fourteen patient-specific computational models for transcatheter aortic valve replacement (TAVR) with balloon-expandable Sapien XT devices were retrospectively developed to tune the material parameters of the implantation site mechanical model for the average TAVR population. Pre-procedural computed tomography (CT) images were post-processed to create the 3D patient-specific anatomy of the implantation site. Balloon valvuloplasty and device deployment were simulated with finite element (FE) analysis. Valve leaflets and aortic root were modelled as linear elastic materials, while calcification as elastoplastic. Material properties were initially selected from literature; then, a statistical analysis was designed to investigate the effect of each implantation site material parameter on the implanted stent diameter and thus identify the combination of material parameters for TAVR patients. These numerical models were validated against clinical data. The comparison between stent diameters measured from post-procedural fluoroscopy images and final computational results showed a mean difference of 2.5 ± 3.9%. Moreover, the numerical model detected the presence of paravalvular leakage (PVL) in 79% of cases, as assessed by post-TAVR echocardiographic examination. The final aim was to increase accuracy and reliability of such computational tools for prospective clinical applications.

Coupled Simulation of Heart Valves: Applications to Clinical Practice

The last few decades have seen great advances in the understanding of heart valves, and consequently, in the development of novel treatment modalities and surgical procedures for valves afflicted by disease. This is due in part to the profound advancements in computing technology and noninvasive medical imaging techniques that have made it possible to numerically model the complex heart valve systems characterized by distinct features at different length scales and various interacting processes. In this article, we highlight the importance of explicitly coupling these multiple scales and diverse processes to accurately simulate the true behavior of the heart valves, in health and disease. We examine some of the computational modeling studies that have a direct consequence on clinical practice.

Quantification of biomechanical interaction of transcatheter aortic valve stent deployed in porcine and ovine hearts

Success of the deployment and function in transcatheter aortic valve replacement is heavily reliant on the tissue-stent interaction. The present study quantified important tissue-stent contact variables of self-expanding transcatheter aortic valve stents when deployed into ovine and porcine aortic roots, such as the stent radial expansion force, stent pullout force, the annulus deformation response and the coefficient of friction on the tissue-stent contact interface. Braided Nitinol stents were developed, tested to determine stent crimped diameter vs. stent radial force from a stent crimp experiment, and deployed in vitro to quantify stent pullout, aortic annulus deformation, and the coefficient of friction between the stent and the aortic tissue from an aortic root-stent interaction experiment. The results indicated that when crimped at body temperature from 26 mm to 19, 21 and 23 mm stent radial forces were approximately 30-40% higher than those crimped at room temperature. Coefficients of friction leveled to approximately 0.10 ± 0.01 as stent wire diameter increased and annulus size decreased from 23 to 19 mm. Regardless of aortic annulus size and species tested, it appeared that a minimum of about 2.5 mm in annular dilatation, caused by about 60 N of radial force from stent expansion, was needed to anchor the stent against a pullout into the left ventricle. The study of the contact biomechanics in animal aortic tissues may help us better understand characteristics of tissue-stent interactions and quantify the baseline responses of non-calcified aortic tissues.

Virtual and real bench testing of a new percutaneous valve device: a case study

AIMS

To validate patient-specific computational testing of a second-generation device for percutaneous pulmonary valve implantation (PPVI), against realistic in vitro data.

METHODS AND RESULTS

Tests were initially carried out in a simple loading mode, performing a compliance test on a rapid prototyped cylinder. This model was reproduced computationally and validated against the experimental data. A second-generation PPVI stent-graft, with no valve mounted, was then deployed in a simplified cylindrical geometry, measuring its displacement when subjected to a pressure pulse. Experimental and computational measurements were in good agreement. Finally, having selected a patient regarded as unsuitable for first-generation PPVI, but potentially suitable for a second-generation device, the stent-graft was studied in the rapidly prototyped patient-specific right ventricular outflow tract (RVOT). Stent positioning and radial displacements with pulsatile flow were observed in a mock circuit using fluoroscopy imaging. Stent deformation and anchoring were measured both in vitro and computationally. Both tests indicated that the stent was well anchored in the RVOT, especially in the distal position, and its central region was rounded, ensuring, were a valve present, optimal valve function.

CONCLUSION

We suggest that an experimentally validated computational model can be used for preclinical device characterisation and patient selection.

Computed tomography in the evaluation for transcatheter aortic valve implantation (TAVI)

If left untreated, symptomatic, severe aortic stenosis (AS) is associated with a dismal prognosis. Open-heart surgical valve replacement is the treatment of choice and is associated with excellent short and long-term outcome. However, many older patients with multiple co-morbidities and anticipated increased surgical risk are excluded from surgical intervention. For these patients, transcatheter aortic valve implantation (TAVI) is emerging as a viable treatment alternative. Transcatheter valvular heart procedures are characterized by lack of exposure and visualization of the operative field, therefore relying on image guidance, both for patient selection and preparation and the implantation procedure itself. This article describes the role of multi-detector row computed tomography (MDCT) for detailed assessment of the aortic valve, aortic root, and iliac arteries in the context of TAVI.