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Abstract #0328

MR-Encephalography Using a Spherical Stack of Spirals Trajectory

MAGNA25Jakob Asslnder1, Marco Reisert1, Benjamin Zahneisen1, Thimo Hugger1, Jrgen Hennig1

1Dep. of Radiology, Medical Physics, University Medical Center, Freiburg, Baden-Wrttemberg, Germany

A spherical stack of spirals trajectory for fast single shot 3D-imaging is presented. Contrary to a shell trajectory, in a stack of spirals trajectory off-resonance leads to distortions rather than blurring and signal dropout. Latter one is hard or impossible to correct for. It is shown, that the off-resonance behavior strongly depends on the direction of the acquisition. Furthermore the stack of spirals easily allows a reduction of the FOV in z-direction to save acquisition time. This can be used to increase the resolution.

Keywords

achieved acquisition activation allows ambiguous analytically arrays assumed assuming behavior better blurring brain channel coil column combined completely computed concentric conjugate connected constant constraint contrary coordinates cost creates depending derived desired disadvantage distorted distortions dropout dwell efficient empirical encoding equation equations especially even experiment explained exploit exploiting explored fast field flickering flipped flipping form forward frames frequency full functional good gradient gradients head hugger illustrates improved in vivo inhomogeneity leads linear loss maps matrix meaningful measured medical minimize moderate monitoring moreover multiplied negative nerve noise object operator opposite overlays part partial parts passing peripheral physics physiological planar possibilities produces property propose radiology radius rather read recent reciprocal reconstruction reconstructions reduce reduction regularized repeated resolution respects rest sampling scaled sensitivities shell shells short shot simulation sinuses slew slice slope smoothly space spatial spherical spirals spoiled stack stimulation strength strong surface system taken temporal though trajectories trajectory transformation trio turned unambiguous variation varying visualize worst