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Multi-Site mcDESPOT

Multi-Site mcDESPOT. Nov. 7, 2011 Jason Su. Motivation. Primary advantage of mcDESPOT is whole-brain coverage Enables the analysis of maps in standard space, voxel-by-voxel comparisons between normal and subjects or between longitudinal time points

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Multi-Site mcDESPOT

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  1. Multi-Site mcDESPOT Nov. 7, 2011 Jason Su

  2. Motivation • Primary advantage of mcDESPOT is whole-brain coverage • Enables the analysis of maps in standard space, voxel-by-voxel comparisons between normal and subjects or between longitudinal time points • Need assess the reliability of this methodology as well as mcDESPOT at many sites

  3. London & Dresden • MSmcDESPOT – 26 normals • London, Canada • Mean age 42, max 66, min 24 • 1.7x1.7x2mm, 128x128x76 • GE 1.5T 14-15x, 8ch head coil • 9 SPGR angles, 9 phase-cycled SSFP angles • DEV/CISmcDESPOT – 26 normals (more in progress) • Dresden, Germany • Mean age 31, max 52, min 20 • Siemens 1.5T Sonata (Syngo MR A30 4VA30A), coil? • Scanner recon to 256x256x96 • Downsampled to 160x160x96 with linear interp. for processing • 9 SPGR angles, 9 SSFP angles no phase-cycling • SPGR angles same • SSFP angles covers lower range 9-60 deg. (vs. 11-67 deg.)

  4. Methods • Same pre-processing pipeline as MSmcDESPOT, i.e. coregistration and brain masking to SPGR fa18 target via FSL • Processing for Dresden is different, using older version of Sean’s code w/o phase-cycling • pcmcdespot supports non-phase-cycled data sets, not sure why they went with this • Nonlinear registration to 1mm MNI standard space with SPGR registration target • Voxel-by-voxel rank sum test in standard space

  5. Results • MWF is significantly different between the normal groups of the two sites in a majority of WM • Regions where the groups are indistinguishable are generally regions where the standard deviation is high due to imperfect registration

  6. MNI152

  7. Rank Sum MWF Significance Map

  8. Std. Dev. of MWF in London

  9. MWF • In *** ROI • London, mean 0.105, std 0.0797 • Dresden, mean 0.177 std 0.0632 London Dresden

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