Meeting Banner
Abstract #1923

Optimizing the Metric for Brain White Matter Comparisons

Natasha Lepore*1, Caroline Brun*2, Maxime Descoteaux3, Yi-Yu Chou4, Greig de Zubicaray5, Katie McMahon5, Margie Wright6, Nicholas Martin6, James Gee2, Paul Thompson *equal Contribution7

1Department of Radiology, Children's Hospital, Los Angeles, Los Angeles, CA, United States; 2Department of Radiology, Penn Image Computing & Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States; 3Universit de Sherbrooke, Canada; 4Laboratory of NeuroImaging, UCLA, United States; 5University of Queensland, Australia; 6Genetic Epidemiology Lab, QIMR, Australia; 7Laboratory of NeuroImaging, UCLA, Los Angeles, CA, United States

Diffusion MRI is a popular tool used to compare brain white matter structure between groups of subjects. When this technique is used to compare two populations, it is common practice to reduce the sometimes-large number of diffusion gradients to a univariate measure at each voxel, such as the fractional anisotropy. However, we and others have designed voxel-wise comparison methods for HARDI data and used multivariate measures for HARDI group comparisons. Here we compare statistical power for two scalar and two multivariate measures derived from the HARDI signal.