Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network

Alzheimer's Disease Neuroimaging Initiative

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learning model to predict conversion from MCI to DAT. Structural magnetic resonance imaging scans were used as input to a 3-dimensional convolutional neural network. The 3-dimensional convolutional neural network was trained using transfer learning; in the source task, normal control and DAT scans were used to pretrain the model. This pretrained model was then retrained on the target task of classifying which MCI patients converted to DAT. Our model resulted in 82.4% classification accuracy at the target task, outperforming current models in the field. Next, we visualized brain regions that significantly contribute to the prediction of MCI conversion using an occlusion map approach. Contributory regions included the pons, amygdala, and hippocampus. Finally, we showed that the model's prediction value is significantly correlated with rates of change in clinical assessment scores, indicating that the model is able to predict an individual patient's future cognitive decline. This information, in conjunction with the identified anatomical features, will aid in building a personalized therapeutic strategy for individuals with MCI.

Original languageEnglish (US)
Pages (from-to)53-64
Number of pages12
JournalNeurobiology of Aging
Volume99
DOIs
StatePublished - Mar 2021

Keywords

  • Convolutional neural network
  • Dementia of Alzheimer's type
  • Magnetic resonance imaging
  • Mild cognitive impairment
  • Predictive modeling

ASJC Scopus subject areas

  • Neuroscience(all)
  • Aging
  • Developmental Biology
  • Clinical Neurology
  • Geriatrics and Gerontology

Fingerprint

Dive into the research topics of 'Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network'. Together they form a unique fingerprint.

Cite this