Developing tractography algorithms for detecting abnormal structural brain
networks in Alzheimer's disease: Application to NACC data 
   Lead Investigator:    Hiroko Dodge
   Institution      :    Oregon Health  Science University
   E-Mail           :    hdodge@med.umich.edu
   Proposal ID      :    615


   Publications:


1  Wang Q, Guo L, Thompson PM, Jack CR, Dodge H, Zhan L, Zhou J
   The Added Value of Diffusion-Weighted MRI-Derived Structural Connectome in Evaluating Mild Cognitive Impairment: A Multi-Cohort Validation
   Journal Article  J Alzheimers Dis,64:149-169,2018,PMC6272125

   PUBLISHED





   Proposal Description:
   Alzheimer???s disease is a neurodegenerative disease that involves progressive    loss of both structures and functions of the neurons in the brain. Over the       past a few years our team has focused on building disease progression models      and validate on the Alzheimer???s Disease Neuroimaging Initiative (ADNI) data     [1] and we would like to extend our efforts to the NACC dataset, collaborating    with ADC affiliated researchers and validating the existing disease progression   models, and also designing novel machine learning technologies to build more      accurate disease progression models.                                                                                                                                In this project we propose to design novel disease progression models using       both structural and functional aspects of the brain. Especially, we would like    to study the brain connectome networks, and evaluate how the functional changes   that are captured by the brain networks can be used to predict the progression    of the disease. Our preliminary studies on ADNI dataset [3-5] have shown the      effectiveness of such networks in modeling disease progression, and we are very   interested to see if we obtain similar results on the NACC dataset. We are also   interested in applying our techniques for imbalanced data [2] to the NACC         dataset.                                                                                                                                                            A list of papers related to the proposed approaches:                                                                                                                1. Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, and Jieping Ye. Modeling Disease      Progression via Multi-task Learning. NeuroImage, 78:233-248, 2013                 2. Rashmi Dubey, Jiayu Zhou, Yalin Wang, Paul M. Thompson, and Jieping Ye.        Analysis of Sampling Techniques