Identification of Individuals with MCI via Multimodality Connectivity Networks

  • Chong-Yaw Wee
  • Pew-Thian Yap
  • Daoqiang Zhang
  • Kevin Denny
  • Lihong Wang
  • Dinggang Shen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6892)

Abstract

Mild cognitive impairment (MCI), often an early stage of Alzheimer’s disease (AD), is difficult to diagnose due to the subtlety of cognitive impairment. Recent emergence of reliable network characterization techniques based on diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) has made the understanding of neurological disorders at a whole-brain connectivity level possible, providing new avenues for brain classification. Taking a multi-kernel SVM, we attempt to integrate these two imaging modalities for improving classification performance. Our results indicate that the multimodality classification approach performs better than the single modality approach, with statistically significant improvement in accuracy. It was also found that the prefrontal cortex, orbitofrontal cortex, temporal pole, anterior and posterior cingulate gyrus, precuneus, amygdala, thalamus, parahippocampal gyrus and insula regions provided the most discriminant features for classification, in line with the results reported in previous studies. The multimodality classification approach allows more accurate early detection of brain abnormalities with larger sensitivity, and is important for treatment management of potential AD patients.

Keywords

Mild Cognitive Impairment Fractional Anisotropy Mild Cognitive Impairment Patient Parahippocampal Gyrus Group Mild Cognitive Impairment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Chong-Yaw Wee
    • 1
  • Pew-Thian Yap
    • 1
  • Daoqiang Zhang
    • 1
  • Kevin Denny
    • 2
  • Lihong Wang
    • 2
  • Dinggang Shen
    • 1
  1. 1.Department of Radiology and Biomedical Research Imaging Center (BRIC)University of North CarolinaChapel HillUSA
  2. 2.Brain Imaging and Analysis Center (BIAC)Duke University Medical CenterDurhamUSA

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