Ahmad, F., Soe, S., White, N, Johnston, R, Khan, I, Liao, J, Jones, M. ![]() ![]() |
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Abstract
The neonate transitions from placenta-derived oxygen, to supply from the pulmonary system, moments after birth. This requires a series of structural developments to divert more blood through the right heart and onto the lungs, with the tissue quickly remodelling to the changing ventricular workload. In some cases, however, the heart structure does not fully develop causing poor circulation and inefficient oxygenation, which is associated with an increase in mortality and morbidity. This study focuses on developing an enhanced knowledge of the 1-day old heart, quantifying the region-specific microstructural parameters of the tissue. This will enable more accurate mathematical and computational simulations of the young heart. Hearts were dissected from 12, 1-day-old deceased Yorkshire piglets (mass: 2.1–2.4 kg, length: 0.38–0.51 m), acquired from a breeding farm. Evans blue dye was used to label the heart equator and to demarcate the left and right ventricle free walls. Two hearts were used for three-dimensional diffusion-tensor magnetic resonance imaging, to quantify the fractional anisotropy (FA). The remaining hearts were used for two-photon excited fluorescence and second-harmonic generation microscopy, to quantify the cardiomyocyte and collagen fibril structures within the anterior and posterior aspects of the right and left ventricles. FA varied significantly across both ventricles, with the greatest in the equatorial region, followed by the base and apex. The FA in each right ventricular region was statistically greater than that in the left. Cardiomyocyte and collagen fibre rotation was greatest in the anterior wall of both ventricles, with less dispersion when compared to the posterior walls. In defining these key parameters, this study provides a valuable insight into the 1-day-old heart that will provide a valuable platform for further investigation the normal and abnormal heart using mathematical and computational models.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Optometry and Vision Sciences Engineering |
Publisher: | Springer Verlag |
ISSN: | 0090-6964 |
Date of First Compliant Deposit: | 10 July 2018 |
Date of Acceptance: | 3 July 2018 |
Last Modified: | 15 Nov 2023 15:04 |
URI: | https://orca.cardiff.ac.uk/id/eprint/113115 |
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