Gesellschaft für Informatik e.V.

Lecture Notes in Informatics

INFORMATIK 2012 P-208, 1707-1716 (2012).

Gesellschaft für Informatik, Bonn

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High resolution diffusion tensor imaging of the human brain at 7T

Ralf Luetzkendorf , Sebastian Baecke , Johannes Mallow , Tim Herrmann , Joergstadler , Claus Tempelmann , Thomas Trantzschel and Johannes Bernarding


Magnetic resonance imaging (MRI) at 7T provides higher signal-to-noise ratio (SNR) which enables high-resolution functional and anatomic MRI. There is also an increased demand for high-resolution diffusion tensor imaging (DTI) providing important information about cell physiology and neuronal connectivity. DTI may also profit from higher SNR as diffusion-weighting reduces the signal exponentially. But the potential SNR gain in ultra-high field (UHF) DTI is counterbalanced mainly by shortened T2 relaxation times of brain tissue, increased signal inhomogeneities, and coil parameter dependencies for parallel imaging. High resolution DTI (1.15/1.15/3.0 mm3) was performed at 3T and 7T. Parallel imaging (GRAPPA, reconstruction factor 3) and data averaging was required to reduce image distortions, inhomogeneous signal distribution, and increase SNR. This allowed calculating high resolution Diffusion tensor and fractional anisotropy maps. In temporal and basal regions the reduced signal-to-noise ratio rendered the calculated parameter maps less reliable. A simulation of the distribution of the excitation radio frequency (RF) field at 7T in a human voxel model revealed that the inhomogeneities of brain tissue leads to inhomogeneous excitation which is a major cause for observed signal voids. High resolution DTI is therefore feasible at 7T with an image quality comparable or superior to 3T DTI. Main advantage for 7T DTI is combining DTI with anatomic and functional MRI acquired at 7T on the same MR scanner thereby reducing registration errors.

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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-602-2

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