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Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.

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Title
  • Studying Ventricular Abnormalities in Mild Cognitive Impairment With Hyperbolic Ricci Flow and Tensor-Based Morphometry
Contributors
Date Created
2015-01-01
Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1016/j.neuroimage.2014.09.062
    • Identifier Type
      International standard serial number
      Identifier Value
      1053-8119
    • Identifier Type
      International standard serial number
      Identifier Value
      1095-9572
    Note
    • NOTICE: this is the author's version of a work that was accepted for publication. Changes may have been made to this work since it was submitted. The definitive version was subsequently published at http://dx.doi.org/10.1016/j.neuroimage.2014.09.062

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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Shi, Jie, Stonnington, Cynthia M., Thompson, Paul M., Chen, Kewei, Gutman, Boris, Reschke, Cole, Baxter, Leslie C., Reiman, Eric M., Caselli, Richard J., & Wang, Yalin (2015). Studying ventricular abnormalities in mild cognitive impairment with hyperbolic Ricci flow and tensor-based morphometry. NEUROIMAGE, 104, 1-20. http://dx.doi.org/10.1016/j.neuroimage.2014.09.062

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