Differential Role for Hippocampal Subfields in Alzheimer's Disease Progression Revealed with Deep Learning.

Journal: Cerebral cortex (New York, N.Y. : 1991)
Published Date:

Abstract

Mild cognitive impairment (MCI) is often considered the precursor of Alzheimer's disease. However, MCI is associated with substantially variable progression rates, which are not well understood. Attempts to identify the mechanisms that underlie MCI progression have often focused on the hippocampus but have mostly overlooked its intricate structure and subdivisions. Here, we utilized deep learning to delineate the contribution of hippocampal subfields to MCI progression. We propose a dense convolutional neural network architecture that differentiates stable and progressive MCI based on hippocampal morphometry with an accuracy of 75.85%. A novel implementation of occlusion analysis revealed marked differences in the contribution of hippocampal subfields to the performance of the model, with presubiculum, CA1, subiculum, and molecular layer showing the most central role. Moreover, the analysis reveals that 10.5% of the volume of the hippocampus was redundant in the differentiation between stable and progressive MCI.

Authors

  • Kichang Kwak
    Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Marc Niethammer
    Department of Computer Science, University of North Carolina, Chapel Hill, NC, 27599, USA.
  • Kelly S Giovanello
    Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Martin Styner
    Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA.
  • Eran Dayan
    Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.