Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer’s Disease
Functional brain imaging provides key information to characterize neurodegenerative diseases, such as Alzheimer’s disease (AD). Specifically, the metabolic activity measured through fluorodeoxyglucose positron emission tomography (FDG-PET) and the connectivity extracted from resting-state functional magnetic resonance imaging (fMRI), are promising biomarkers that can be used for early assessment and prognosis of the disease and to understand its mechanisms. FDG-PET is the best suited functional marker so far, as it gives a reliable quantitative measure, but is invasive. On the other hand, non-invasive fMRI acquisitions do not provide a straightforward quantification of brain functional activity. To analyze populations solely based on resting-state fMRI, we propose an approach that leverages a metabolic prior learned from FDG-PET. More formally, our classification framework embeds population priors learned from another modality at the voxel-level, which can be seen as a regularization term in the analysis. Experimental results show that our PET-informed approach increases classification accuracy compared to pure fMRI approaches and highlights regions known to be impacted by the disease.
KeywordsClassification prior connectivity metabolism resting-state fMRI FDG-PET Alzheimer’s disease
Unable to display preview. Download preview PDF.
- 1.Gramfort, A., Thirion, B., Varoquaux, G.: Identifying predictive regions from fMRI with TV-L1 prior. In: Pattern Recognition in Neuroimaging (PRNI), p. 17 (2013)Google Scholar
- 2.Gray, K.R., Wolz, R., Heckemann, R.A., Aljabar, P., Hammers, A., Rueckert, D.: Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer’s disease. NeuroImage 60(1), 221–229 (2012)Google Scholar
- 3.Jones, D.T., Vemuri, P., Murphy, M.C., et al.: Non-stationarity in the “resting brain’s” modular architecture. PloS One 7(6), e39731 (2012)Google Scholar
- 5.Lillemark, L., Sørensen, L., et al.: Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI. BMC Med. Imag. 14(1), 21 (2014)Google Scholar