Abstract
Cardiac architecture is fundamental to cardiac function and can be assessed non-invasively with diffusion tensor imaging (DTI). Here, we aimed to overcome technical challenges in ex vivo DTI in order to extract fine anatomical details and to provide novel insights in the 3D structure of the heart. An integrated set of methods was implemented in ex vivo rat hearts, including dynamic receiver gain adjustment, gradient system scaling calibration, prospective adjustment of diffusion gradients, and interleaving of diffusion-weighted and non-diffusion-weighted scans. Together, these methods enhanced SNR and spatial resolution, minimised orientation bias in diffusion-weighting, and reduced temperature variation, enabling detection of tissue structures such as cell alignment in atria, valves and vessels at an unprecedented level of detail. Improved confidence in eigenvector reproducibility enabled tracking of myolaminar structures as a basis for segmentation of functional groups of cardiomyocytes. Ex vivo DTI facilitates acquisition of high quality structural data that complements readily available in vivo cardiac functional and anatomical MRI. The improvements presented here will facilitate next generation virtual models integrating micro-structural and electro-mechanical properties of the heart.
Highlights
Traditional histo-anatomical methods have laid the foundation for understanding heart structure[1], as condensed in a number of modern cardiac models[2]
The technical refinements are first assessed in terms of image signal-to-noise ratio (SNR), and fractional anisotropy (FA) and 95% cone-of-uncertainty (COU) of the Diffusion tensor imaging (DTI) data
That v1 tracks reconfirm the transition from left- to right-handed helical fibres progressing from the left ventricle (LV) subepicardium to subendocardium. v3 tracks were largely oriented in a radial manner in the LV anterior and posterior walls, suggesting that in these regions, myocardial sheetlets in relaxed hearts are aligned in planes that deviate only little from the myocardial wall surface[8]
Summary
Traditional histo-anatomical methods have laid the foundation for understanding heart structure[1], as condensed in a number of modern cardiac models[2]. Recent developments in computational models of heart function utilised ex vivo DTI data for prediction of properties such as myocardial stiffness[14], ventricular pressures, and cardiac geometry, kinematics and function[15,16,17]. Such models could assist pre-surgical planning and predict outcomes of invasive interventions. Gradient calibration[19] and temperature variations[20], and difficulty distinguishing v2 from v3 in the presence of noise[21] To overcome these obstacles, we implemented a set of refinements to increase SNR and spatial resolution, minimise orientation bias in diffusion-weighting, and reduce temperature variation in DTI. The improvement in data quality enabled identification of fine anatomical features not previously described with DTI, and novel segmentation of cardiomyocyte populations
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