Abstract #1042

Harmonizing diffusion MRI data from multiple scanners

Hengameh Mirzaalian¹, Lipeng Ning¹, Peter Savadjiev¹, Ofer Pasternak¹, Sylvain Bouix¹, Oleg Michailovich², Marek Kubicki¹, Carl Fredrik Westin¹, Martha E. Shenton¹, and Yogesh Rathi¹

¹Harvard Medical School and Brigham and Women’s Hospital, Boston, USA., Boston, MA, United States, ²University of Waterloo, Toronto, ON, Canada

Diffusion MRI (dMRI) is increasing being used to study neuropsychiatric brain disorders. To increase sample size and statistical power of neuroscience studies, we need to aggregate data from multiple sites¹. However this is a challenging problem due to the presence of inter-site variability in the signal originating from several sources, e.g. number of head coils and their sensitivity, non-linearity in the imaging gradient, and other scanner related parameters². Prior works have addressed this issue either using meta analysis³, or by adding a statistical covariate⁴, which are not model free and may produce erroneous results.

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