Soft robotic platform for progressive and reversible aortic constriction in a small-animal model.

Our understanding of cardiac remodeling processes due to left ventricular pressure overload derives largely from animal models of aortic banding. However, these studies fail to enable control over both disease progression and reversal, hindering their clinical relevance. Here, we describe a method for progressive and reversible aortic banding based on an implantable expandable actuator that can be finely tuned to modulate aortic banding and debanding in a rat model. Through catheterization, imaging, and histologic studies, we demonstrate that our platform can recapitulate the hemodynamic and structural changes associated with pressure overload in a controllable manner. We leveraged soft robotics to enable noninvasive aortic debanding, demonstrating that these changes can be partly reversed because of cessation of the biomechanical stimulus. By recapitulating longitudinal disease progression and reversibility, this animal model could elucidate fundamental mechanisms of cardiac remodeling and optimize timing of intervention for pressure overload.

Robust automated calcification meshing for personalized cardiovascular biomechanics.

Calcification has significant influence over cardiovascular diseases and interventions. Detailed characterization of calcification is thus desired for predictive modeling, but calcium deposits on cardiovascular structures are still often manually reconstructed for physics-driven simulations. This poses a major bottleneck for large-scale adoption of computational simulations for research or clinical use. To address this, we propose an end-to-end automated image-to-mesh algorithm that enables robust incorporation of patient-specific calcification onto a given cardiovascular tissue mesh. The algorithm provides a substantial speed-up from several hours of manual meshing to ~1 min of automated computation, and it solves an important problem that cannot be addressed with recent template-based meshing techniques. We validated our final calcified tissue meshes with extensive simulations, demonstrating our ability to accurately model patient-specific aortic stenosis and Transcatheter Aortic Valve Replacement. Our method may serve as an important tool for accelerating the development and usage of personalized cardiovascular biomechanics.

Hemodynamic evaluation of biomaterial-based surgery for Tetralogy of Fallot using a biorobotic heart, in silico, and ovine models.

Tetralogy of Fallot is a congenital heart disease affecting newborns and involves stenosis of the right ventricular outflow tract (RVOT). Surgical correction often widens the RVOT with a transannular enlargement patch, but this causes issues including pulmonary valve insufficiency and progressive right ventricle failure. A monocusp valve can prevent pulmonary regurgitation; however, valve failure resulting from factors including leaflet design, morphology, and immune response can occur, ultimately resulting in pulmonary insufficiency. A multimodal platform to quantitatively evaluate the effect of shape, size, and material on clinical outcomes could optimize monocusp design. This study introduces a benchtop soft biorobotic heart model, a computational fluid model of the RVOT, and a monocusp valve made from an entirely biological cell-assembled extracellular matrix (CAM) to tackle the multifaceted issue of monocusp failure. The hydrodynamic and mechanical performance of RVOT repair strategies was assessed in biorobotic and computational platforms. The monocusp valve design was validated in vivo in ovine models through echocardiography, cardiac magnetic resonance, and catheterization. These models supported assessment of surgical feasibility, handling, suturability, and hemodynamic and mechanical monocusp capabilities. The CAM-based monocusp offered a competent pulmonary valve with regurgitation of 4.6 ± 0.9% and a transvalvular pressure gradient of 4.3 ± 1.4 millimeters of mercury after 7 days of implantation in sheep. The biorobotic heart model, in silico analysis, and in vivo RVOT modeling allowed iteration in monocusp design not now feasible in a clinical environment and will support future surgical testing of biomaterials for complex congenital heart malformations.