Dr. Zhen Zhou Profile

Dr. Zhen Zhou

at University of Pennsylvania

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Proceedings Article | 4 April 2022 Presentation + Paper

Harmonization of multi-site functional connectivity measures in tangent space improves brain age prediction

Zhen Zhou, Dhivya Srinivasan, Hongming Li, Ahmed Abdulkadir, Haochang Shou, Christos Davatzikos, Yong Fan

Proceedings Volume 12036, 1203608 (2022) https://doi.org/10.1117/12.2611557

KEYWORDS: Brain, Functional magnetic resonance imaging, Neuroimaging, Data modeling, Performance modeling, Scanners, Magnetic resonance imaging

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Brain age prediction based on functional magnetic resonance imaging (fMRI) data has the potential to serve as a biomarker for quantifying brain health. To predict the brain age based on fMRI data robustly and accurately, we curated a large dataset (n = 4259) of fMRI scans from seven different data acquisition sites and computed personalized functional connectivity measures at multiple scales from each subject’s fMRI scan. Particularly, we computed personalized largescale functional networks and generated functional connectivity measures at multiple scales to characterize each fMRI scan. To account for inter-site effects on the functional connectivity measures, we harmonized the functional connectivity measures in their tangent space and then built brain age prediction models on the harmonized functional connectivity measures. We compared the brain age prediction models with alternatives that were built on the functional connectivity measures computed at a single scale and harmonized using different strategies. Comparison results have demonstrated that the best brain age prediction performance was achieved by the prediction model built on the multi-scale functional connectivity measures that were harmonized in tangent space, indicating that multi-scale functional connectivity measures provided richer information than those computed at any single scales and the harmonization of functional connectivity measures in tangent space improved the brain age prediction.

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