Mode-based Decomposition of Multimodality Reveals Relationships across Spatial Scales in Alzheimer’s
Poster No:
233
Submission Type:
Abstract Submission
Authors:
Boning Tong1, Trang Cao2, Duy Duong-Tran3, Andrew Saykin4, Alex Fornito2, Li Shen5
Institutions:
1University of Pennsylvania, Philadelphia, PA, 2Monash University, Clayton, Victoria, 3United States Naval Academy, Annapolis,MD, 4Indiana University School of Medicine, Indianapolis, IN, 5Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
First Author:
Co-Author(s):
Introduction:
In Alzheimer's disease (AD), imaging is essential for diagnosis, monitoring disease progression, and understanding the underlying pathophysiology. Different imaging modalities provide distinct, yet complementary, insights: molecular imaging (Amyloid, Tau PET) can reveal early disease progression, functional imaging (fMRI, FDG-PET) can detect intermediate stages of neuronal dysfunction, and structural imaging (MRI) charts atrophic decline. However, it is currently unclear how these distinct modalities are related to each other. Disentangling these relationships will provide a more comprehensive picture towards Alzheimer's pathology and etiology. Recent work has shown that spatial brain maps can be viewed as resulting from the excitation of specific resonant modes, called eigenmodes, of brain geometry, providing a unifying framework to link case-control differences observed in different kinds of brain maps.
Methods:
Here, mode-based morphometry (Cao, 2024) produces a spectral decomposition of group-contrast brain maps using structural MRI, AV45 (Amyloid) PET, and FDG PET scans from the ADNI database (Weiner, 2013), including 243 cognitive normal (CN), 514 mild cognitive impairment (MCI), and 124 AD subjects. The decomposition uses geometric eigenmodes as a basic set representing different spatial scales.
Results:
The resulting coefficient spectra, representing the degree to which each mode contributes to the spatial pattern of group differences defined in each map, were highly correlated within a modality and moderately correlated between modalities. Leveraging the spatial frequency content of the spectra, we further show that group differences in Amyloid PET maps are expressed at higher-frequency spatial scales compared to differences between AD and CN; AD and MCI in MRI and FDG.
Conclusions:
These results suggest that group differences in each modality involve a common set of modes as well as some that are modality-specific, and that amyloid pathology may be expressed at a more fine-grained spatial scales than the more global differences observed in metabolism and grey matter volume.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Novel Imaging Acquisition Methods:
Multi-Modal Imaging 2
Keywords:
Aging
Computational Neuroscience
MRI
Positron Emission Tomography (PET)
1|2Indicates the priority used for review
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Provide references using APA citation style.
Weiner, M. W., Veitch, D. P., Aisen, P. S., Beckett, L. A., Cairns, N. J., Green, R. C., ... & Trojanowski, J. Q. (2013). The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimer's & Dementia, 9(5), e111-e194.