In Silico Evaluation of Cardiac Tissue-Engineered Patch Interventions

TL;DR

This study uses a microstructure-driven, 3D solid mechanics model of the heart coupled to a 0D circulatory model to evaluate surface and transmural cardiac tissue-engineered patches after myocardial infarction. By varying patch activation, muscle fiber alignment, stiffness, and attachment strategy across anatomically realistic geometries, the authors quantify impacts on LV pump function, demonstrating that transmural patches with higher activation and native-like fiber orientation yield the greatest improvements, while surface patches offer limited gains except in chronically thinned geometries. The work provides quantitative design principles for patch maturation, orientation, and stiffness to maximize functional recovery, and highlights tradeoffs and practical considerations for clinical translation. Overall, the findings support prioritizing transmural, mature patches with native fiber alignment to enhance stroke volume, ejection fraction, and stroke work, while acknowledging remodeling and patient-specific factors that warrant future investigation.

Abstract

Myocardial infarction significantly degrades heart function, and current treatments can bring forth serious cost and complications including blood clots and infections. To improve the current state of treatment, researchers are developing tissue patches from induced-pluripotent stem cells that can be incorporated into the heart, improving organ function after a myocardial infarction. These tissue patches include surface patches, attached to the epicardium of the heart, and thick transmural patches that replace the infarcted region. However, little is known about the impact of cardiac tissue patches on pump function in a patient's heart. In addition, it is not clear what patch structural properties - such as active stress generation, muscle fiber alignment, or material stiffness - may best augment existing heart tissue. Computational modeling can be used to examine different implementations and patch properties, illuminating the mechanical impact of cardiac tissue patches in the beating heart. In this work, we computationally implement different cardiac tissue patches to understand benefits of particular patch types and properties. We find that in transmural cardiac tissue patches, both activation and fiber alignment improve function. A transmural patch generating 10% of healthy active stress can increase stroke volume by 18%, and higher generated active stress in a circumferential muscle fiber orientation can recover stroke volume by over 50%. Furthermore, we find that surface cardiac tissue patches can enhance heart function slightly despite limiting diastolic filling, especially when fibrotic thinning has occurred. These conclusions identify broad design goals for the engineering of cardiac tissue patches to improve heart function after a myocardial infarction.

Figures (9)

• Figure 1: Geometry and structure analyzing patch performance. A) The biventricular geometry with healthy myocardium in red and the fibrotic region and border zone in grey. B) The chronically thinned fibrotic left ventricular morphology shown in black with the acute fibrotic left ventricular morphology overlaid in light gray. C) The analytical engineered surface patch geometry and its adherence onto the biventricular heart D) Volume plot showing the volume of the fibrotic regions and the surface patch divided by the total mesh volume for each geometry. In this case, the fibrotic region includes the border zone volume according to its extent of fibrosis. E) From left to right - cardiac muscle fiber orientation for the native fibers, circumferential muscle fibers in the transmural patch, longitudinal muscle fibers in the transmural patch, and the surface patch. $\mathbf{\hat{e}_C}$ refers to the unit vector in the circumferential direction.
• Figure 2: 3D-0D coupled diagram: Variables represented by the letter $p$ indicate chamber pressure in the 3D ventricles and 0D lumped parameter representation atrial and circulatory elements, letters $R$ indicate resistance of the given vessel to flow for a given pressure (with $Z$ representing a second resistor in the same vessel), letters $E$ indicate a time-varying elastance that allows for blood ejection from arteries, letters $C$ indicate the compliance of a vessel to change flow for a given pressure time derivative, and letters $L$ indicate an inductance element that drives the vessel's resistance to change in flow rate for a given pressure. The circulatory model contains 0D chambers for arterial and venous pressure in both systemic and pulmonary circulatory pathways, with subscript $\text{ven}$ indicating venous circulation, subscript $\text{ar}$ indicating arterial circulation, superscript $\text{sys}$ identifying systemic circulation, and superscript $\text{pul}$ identifying pulmonary circulation. The superscript letters $\text{l}$ and $\text{r}$ indicate ventricular circulation. Adapted from hirschvogel_monolithic_2017
• Figure 3: Patch properties considered in this study. For applying the patch, we can consider a surface patch that is attached to the epicardium of the LV, and we can also consider a transmural patch that replaces the entire LV wall in place of the fibrotic region. We can consider both "acute" geometries with thick walls and "chronically thinned" geometry in the case of the surface patch. Lastly, for patch structural properties, we consider activation, mechanical stiffness, and cardiac muscle fiber alignment.
• Figure 4: Heart function for the healthy baseline heart model. A) LV pressure and LV pressure-volume relationship, with black dots indicating the illustrated times in Figure \ref{['fig:healthy_fiber_stretch']}C. B) 0D lumped parameter representation parameters for this model illustrated for one cardiac cycle, reflecting the simulated cardiovascular system - $p^l_{\text{at}}$ indicating left atrial pressure, $p^r_{\text{at}}$ indicating right atrial pressure, $q^l_{\text{v,in}}$ indicating mitral valve flow rate, and $q^l_{\text{v,out}}$ indicating aortic valve flow rate out of the LV. C) Fiber stretch illustrated at selected times in the cardiac cycle, with a short axis and long axis view.
• Figure 5: Results for transmural patch variations. A) Pressure-Volume relationships for transmural patches with increasing activation, circumferential fiber orientation. B) Pressure-Volume relationships for transmural patches with different cardiac muscle fiber alignments and activation levels. C) Cardiac functional metrics for the transmural simulations, namely stroke volume, stroke work, ejection fraction, and peak systolic pressure.