Identifying the regional substrates predictive of Alzheimer's disease progression through a convolutional neural network model and occlusion
Abstract
Progressive brain atrophy is a key neuropathological hallmark of Alzheimer's disease (AD) dementia. However, atrophy patterns along the progression of AD dementia are diffuse and variable and are often missed by univariate methods. Consequently, identifying the major regional atrophy patterns underlying AD dementia progression is challenging. In the current study, we propose a method that evaluates the degree to which specific regional atrophy patterns are predictive of AD dementia progression, while holding all other atrophy changes constant using a total sample of 334 subjects. We first trained a dense convolutional neural network model to differentiate individuals with mild cognitive impairment (MCI) who progress to AD dementia versus those with a stable MCI diagnosis. Then, we retested the model multiple times, each time occluding different regions of interest (ROIs) from the model's testing set's input. We also validated this approach by occluding ROIs based on Braak's staging scheme. We found that the hippocampus, fusiform, and inferior temporal gyri were the strongest predictors of AD dementia progression, in agreement with established staging models. We also found that occlusion of limbic ROIs defined according to Braak stage III had the largest impact on the performance of the model. Our predictive model reveals the major regional patterns of atrophy predictive of AD dementia progression. These results highlight the potential for early diagnosis and stratification of individuals with prodromal AD dementia based on patterns of cortical atrophy, prior to interventional clinical trials.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 29, 2022
- Source ID
- 10.1002/hbm.26026
Entities
People
- Eran Dayan
- For The Alzheimer’s Disease Neuroimaging Initiative*
- Kichang Kwak
- William Stanford
Organizations
- AbbVie
- Alzheimer's Association
- Alzheimer's Disease Neuroimaging Initiative
- Alzheimer's Drug Discovery Foundation
- BioClinica
- Biogen
- Canadian Institutes of Health Research
- Eli Lilly and Company
- Foundation for the National Institutes of Health
- GE HealthCare
- Hoffmann-La Roche
- Lundbeck
- Merck & Co.
- National Institute of Biomedical Imaging and Bioengineering
- National Institute on Aging
- National Institutes of Health
- Norman Cousins Center for Psychoneuroimmunology
- Northern California Institute for Research and Education
- Roche (United States)
- Takeda (United States)
- United States Department of Defense
- University of North Carolina at Chapel Hill
- University of Southern California