Abstract #0309

FatNavs: Exploiting the Natural Sparsity of Head Fat Images for High-Resolution Motion-Navigation at Very High Acceleration Factors

Daniel Gallichan¹, Jos P. Marques², Rolf Gruetter³,⁴

¹LIFMET, Ecole Polytchnique Fdrale de Lausanne, Lausanne, Vaud, Switzerland; ²Dept. of Radiology, University of Lausanne, Lausanne, Vaud, Switzerland; ³LIFMET, cole Polytechnique Fdrale de Lausanne, Lausanne, Vaud, Switzerland; ⁴Depts. of Radiology, Universities of Lausanne and Geneva, Lausanne, Vaud, Switzerland

We tested the feasibility of using the fat signals in the head for high-resolution motion-navigation at very high acceleration factors. 6 subjects were scanned at high resolution with both fat and water excitations at 3 time-points during a single session where there was no intentional movement. The registration of the water images was used as the reference for motion, and the parameters extracted from the fat images, both fully sampled and accelerated to R=50, were compared. Although consistent results were obtained from the fat images, there was a tendency to slightly underestimate the true motion which requires further investigation.