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Updated: May 28, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
MRI patterns of atrophy and hypoperfusion associations across brain regions in frontotemporal dementia
Duygu Tosun1, Howard Rosen, Bruce L Miller
1Center for Imaging Neurodegenerative Diseases, Veterans Affairs Medical Center, San Francisco, CA 94121, USA. duygu.tosun@ucsf.edu
Abstract:
Magnetic Resonance Imaging (MRI) provides various imaging modes to study the brain. We tested the benefits of a joint analysis of multimodality MRI data in combination with a large-scale analysis that involved simultaneously all image voxels using joint independent components analysis (jICA) and compared the outcome to results using conventional voxel-by-voxel unimodality tests. Specifically, we designed a jICA to decompose multimodality MRI data into independent components that explain joint variations between the image modalities as well as variations across brain regions. We tested the jICA design on structural and perfusion-weighted MRI data from 12 patients diagnosed with behavioral variant frontotemporal dementia (bvFTD) and 12 cognitively normal elderly individuals. While unimodality analyses showed widespread brain atrophy and hypoperfusion in the patients, jICA further revealed two significant joint components of variations between atrophy and hypoperfusion across brain regions. The 1st joint component revealed associated brain atrophy and hypoperfusion predominantly in the right brain hemisphere in behavioral variant frontotemporal dementia, and the 2nd joint component revealed greater atrophy relative to hypoperfusion affecting predominantly the left hemisphere in behavioral variant frontotemporal dementia. The patterns are consistent with the clinical symptoms of behavioral variant frontotemporal dementia that relate to asymmetric compromises of the left and right brain hemispheres. The joint components also revealed that that structural alterations can be associated with physiological alterations in spatially separated but potentially connected brain regions. Finally, jICA outperformed voxel-by-voxel unimodal tests significantly in terms of an effect size, separating the behavioral variant frontotemporal dementia patients from the controls. Taken together, the results demonstrate the benefit of multimodality MRI in conjunction with jICA for mapping neurodegeneration, which may lead ultimately to an improved diagnosis of behavioral variant frontotemporal dementia and other forms of neurodegenerative diseases.
Insights
Joint Independent Component Analysis (jICA) of multimodality MRI data effectively identified neurodegeneration patterns in behavioral variant frontotemporal dementia (bvFTD). This advanced analysis significantly outperformed traditional methods in distinguishing patients from controls.
Area of Science:
- Neuroimaging
- Neurology
- Biomedical Engineering
Background:
- Magnetic Resonance Imaging (MRI) offers diverse brain study modes.
- Conventional voxel-by-voxel unimodality tests have limitations in analyzing complex neurodegenerative patterns.
Purpose of the Study:
- To evaluate the benefits of joint analysis of multimodality MRI data using joint Independent Component Analysis (jICA).
- To compare jICA outcomes with conventional unimodality tests for neurodegeneration detection.
Main Methods:
- Designed a jICA to decompose multimodality MRI data (structural and perfusion-weighted) into independent components.
- Applied jICA to data from 12 behavioral variant frontotemporal dementia (bvFTD) patients and 12 controls.
- Compared jICA results with voxel-by-voxel unimodality analyses.
Main Results:
- Unimodality analyses revealed widespread atrophy and hypoperfusion in bvFTD patients.
- jICA identified two significant joint components linking atrophy and hypoperfusion, showing hemispheric asymmetry consistent with bvFTD symptoms.
- jICA demonstrated superior effect size in differentiating bvFTD patients from controls compared to unimodal tests.
Conclusions:
- Multimodality MRI combined with jICA offers significant benefits for mapping neurodegeneration.
- This approach may enhance the diagnosis of bvFTD and other neurodegenerative diseases.
- jICA reveals associations between structural and physiological changes in potentially connected brain regions.
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