Joint Independent Component Analysis of Brain Perfusion and Structural Magnetic Resonance Images in Dementia

Magnetic Resonance Imaging (MRI) provides various imaging modes to study the brain. We tested the benefits of joint analysis of multimodality MRI data using joint independent components analysis (jICA) in comparison to unimodality analyses. Specifically, we designed a jICA to decompose the joint distributions of multimodality MRI data across image voxels and subjects into independent components that explain joint variations between image modalities across subjects. We applied jICA to structural and perfusion-weighted MRI data from 12 patients diagnosed with behavioral variant front temporal dementia (bvFTD), a type of dementia, and 12 healthy elderly individuals. While unimodality analyses showed widespread brain atrophy and hypoperfusion in the patients, jICA further revealed links between atrophy and hypoperfusion in specific brain regions. Moreover, significant links were confined to the right brain hemisphere in FTLD, consistent with the clinical symptoms. Considering multimodality effect size between bvFTD patients and controls, brain atrophy and hypoperfusion regions identified by multimodality jICA yielded the large effect size while regions identified by unimodality analysis of atrophy and hypoperfusion differences revealed only a medium multimodality effect size between bvFTD patients and controls. The findings demonstrate the power of jICA to effectively evaluate multimodality brain imaging data.