Differential Role for Hippocampal Subfields in Alzheimer’s Disease Progression Revealed with Deep Learning
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 29, 2021
- Source ID
- 10.1093/cercor/bhab223
Entities
People
- Eran Dayan
- For The Alzheimer’s Disease Neuroimaging Initiative*
- Kelly S. Giovanello
- Kichang Kwak
- Marc Niethammer
- Martin Styner
Organizations
- National Institutes of Health
- United States Department of Defense