Quantifying Regional and Age-Dependent Microstructural Changes in Porcine Ventricles from Neonatal to Adulthood Using DT-MRI and TPEF-SHG Microscopy

Abstract The heart undergoes substantial structural changes in response to new physiological demands, which occur with the rapid opening of pulmonary circulation immediately after birth. The dependence on pulmonary circulation causes an immediate increase in ventricular workload, resulting in microstructural changes that serve to maintain overall physiological homeostasis. Ageing continues to evolve the heart’s structure due to increased myocardial tissue stress and strain, initiating the formation of a new extracellular matrix to facilitate the physiology of an adult. Quantifying the region-specific and age-dependent microstructural changes in tissue due to ageing is pivotal for the development of constitutive models for computational simulations. This study aimed to determine the microstructure of porcine ventricles at four time points from neonatal to adulthood. The three-dimensional microstructure was investigated using diffusion-tensor magnetic resonance imaging, two-photon excited fluorescence and second-harmonic generation microscopy to quantify fibre tractography, fractional anisotropy (FA), spherical measure, rotation and dispersion of cardiomyocytes and collagen fibrils. The results revealed that the left ventricle possessed greater FA than the right. Adult hearts demonstrated smaller FA than the young. The anterior left and right ventricles exhibited greater cardiomyocyte and collagen fibril rotation and dispersion than the posterior. The adult hearts possessed greater cardiomyocyte and collagen fibril rotation and dispersion than young hearts. The right ventricle demonstrated greater cardiomyocyte rotation in the younger hearts, and the Left in the adult. This study provides baseline data that should prove useful to bioengineers, researchers, and mathematicians in developing region-specific and age-dependent constitutive models to enhance the accuracy and bio-fidelity of computational simulations.