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Alzheimer’s Disease Classification with Novel Microstructural Metrics from Diffusion-Weighted MRI

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Book cover Computational Diffusion MRI

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

Alzheimer’s disease (AD) deficits may be due in part to declining white matter (WM) integrity and disrupted connectivity. Numerous diffusion-weighted MRI (dMRI) studies of AD report WM deficits based on tensor model metrics. New microstructural measures derived from additional dMRI models may carry different information about WM microstructure including the geometry of diffusion anisotropy, diffusivity, complexity, estimated number of distinguishable fiber compartments, number of crossing fibers and neurite dispersion. Here we aimed to find the most helpful dMRI metrics and brain regions from a set of 17 dMRI-derived feature maps, to predict diagnostic group (AD or healthy control). The best metrics for classification were non-tensor metrics in the hippocampus and temporal lobes, areas consistently implicated in AD.

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Author information

Authors and Affiliations

  1. Imaging Genetics Center, University of Southern California, Marina del Rey, Los Angeles, CA, USA

    Talia M. Nir, Julio E. Villalon-Reina, Boris A. Gutman, Daniel Moyer & Neda Jahanshad

  2. Brain and Creativity Institute, University of Southern California, Los Angeles, CA, USA

    Morteza Dehghani

  3. Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA

    Clifford R. Jack Jr.

  4. Department of Radiology, UCSF School of Medicine, San Francisco, CA, USA

    Michael W. Weiner

Authors
  1. Talia M. Nir
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  2. Julio E. Villalon-Reina
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  3. Boris A. Gutman
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  4. Daniel Moyer
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  5. Neda Jahanshad
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  6. Morteza Dehghani
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  7. Clifford R. Jack Jr.
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  8. Michael W. Weiner
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  9. Paul M. Thompson
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for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Corresponding author

Correspondence to Talia M. Nir .

Editor information

Editors and Affiliations

  1. Dept of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands

    Andrea Fuster

  2. Centre for Medical Image Computing, University College London, London, United Kingdom

    Aurobrata Ghosh

  3. Centre for Medical Image Computing, University College London, London, United Kingdom

    Enrico Kaden

  4. Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA

    Yogesh Rathi

  5. Department of Radiology, University Medical Center, Freiburg, Germany

    Marco Reisert

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© 2016 Springer International Publishing Switzerland

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Nir, T.M. et al. (2016). Alzheimer’s Disease Classification with Novel Microstructural Metrics from Diffusion-Weighted MRI. In: Fuster, A., Ghosh, A., Kaden, E., Rathi, Y., Reisert, M. (eds) Computational Diffusion MRI. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-28588-7_4

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