Reconstruction of cardiac ventricular geometry and fiber orientation using magnetic resonance imaging

DF Scollan, A Holmes, J Zhang, RL Winslow - Annals of biomedical …, 2000 - Springer
DF Scollan, A Holmes, J Zhang, RL Winslow
Annals of biomedical engineering, 2000Springer
An imaging method for the rapid reconstruction of fiber orientation throughout the cardiac
ventricles is described. In this method, gradient-recalled acquisition in the steady-state
(GRASS) imaging is used to measure ventricular geometry in formaldehyde-fixed hearts at
high spatial resolution. Diffusion-tensor magnetic resonance imaging (DTMRI) is then used
to estimate fiber orientation as the principle eigenvector of the diffusion tensor measured at
each image voxel in these same hearts. DTMRI-based estimates of fiber orientation in …
Abstract
An imaging method for the rapid reconstruction of fiber orientation throughout the cardiac ventricles is described. In this method, gradient-recalled acquisition in the steady-state (GRASS) imaging is used to measure ventricular geometry in formaldehyde-fixed hearts at high spatial resolution. Diffusion-tensor magnetic resonance imaging (DTMRI) is then used to estimate fiber orientation as the principle eigenvector of the diffusion tensor measured at each image voxel in these same hearts. DTMRI-based estimates of fiber orientation in formaldehyde-fixed tissue are shown to agree closely with those measured using histological techniques, and evidence is presented suggesting that diffusion tensor tertiary eigenvectors may specify the orientation of ventricular laminar sheets. Using a semiautomated software tool called HEARTWORKS, a set of smooth contours approximating the epicardial and endocardial boundaries in each GRASS short-axis section are estimated. These contours are then interconnected to form a volumetric model of the cardiac ventricles. DTMRI-based estimates of fiber orientation are interpolated into these volumetric models, yielding reconstructions of cardiac ventricular fiber orientation based on at least an order of magnitude more sampling points than can be obtained using manual reconstruction methods. © 2000 Biomedical Engineering Society.
PAC00: 8761-c, 8757Gg
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