Using high-dimensional machine learning methods to estimate an anatomical risk factor for Alzheimer's disease across imaging databases.

Journal: NeuroImage
Published Date: Aug 18, 2018

Abstract

INTRODUCTION: The main goal of this work is to investigate the feasibility of estimating an anatomical index that can be used as an Alzheimer's disease (AD) risk factor in the Women's Health Initiative Magnetic Resonance Imaging Study (WHIMS-MRI) using MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a well-characterized imaging database of AD patients and cognitively normal subjects. We called this index AD Pattern Similarity (AD-PS) scores. To demonstrate the construct validity of the scores, we investigated their associations with several AD risk factors. The ADNI and WHIMS imaging databases were collected with different goals, populations and data acquisition protocols: it is important to demonstrate that the approach to estimating AD-PS scores can bridge these differences.

Authors

  • Ramon Casanova
    Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.
  • Ryan T Barnard
    Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.
  • Sarah A Gaussoin
    Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.
  • Santiago Saldana
    Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.
  • Kathleen M Hayden
    Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC, USA.
  • JoAnn E Manson
    Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Robert B Wallace
    Department of Epidemiology University of Iowa College of Public Health, Iowa City, IA, USA.
  • Stephen R Rapp
    Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC, USA.
  • Susan M Resnick
    Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
  • Mark A Espeland
    Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
  • Jiu-Chiuan Chen
    Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA.

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