Using diffusion imaging measures in gray matter to predict cognitive decline
and Alzheimer's disease 
   Lead Investigator:    Hamsi Radhakrishnan
   Institution      :    University of California, Irvine
   E-Mail           :    kathryn_gauthreaux@yahoo.com
   Proposal ID      :    1651



   Proposal Description:
   While diffusion imaging is often used in white matter to measure neurodegeneration, the same measures in gray matter have been less frequently studied. Diffusion metrics, especially those derived from multi-shell imaging, may have the potential to be sensitive to specific microstructural changes in gray matter (like neuroinflammation and astrogliosis) that precede visible signs of cognitive decline or gross structural atrophy- enabling earlier diagnosis, and hopefully more proactive treatment. Here, we aim to use tensor measures as well as NODDI metrics derived from higher order diffusion imaging in a multivariate model (along with age and some structural parameters like volume) to determine if we can develop early predictive models for accurate AD diagnosis.