AUTHOR=Wu Jianfeng , Dong Qunxi , Zhang Jie , Su Yi , Wu Teresa , Caselli Richard J. , Reiman Eric M. , Ye Jieping , Lepore Natasha , Chen Kewei , Thompson Paul M. , Wang Yalin TITLE=Federated Morphometry Feature Selection for Hippocampal Morphometry Associated Beta-Amyloid and Tau Pathology JOURNAL=Frontiers in Neuroscience VOLUME=15 YEAR=2021 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2021.762458 DOI=10.3389/fnins.2021.762458 ISSN=1662-453X ABSTRACT=
Amyloid-β (Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. One of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research focuses in the AD pathophysiological progress. This work proposes a novel framework, Federated Morphometry Feature Selection (FMFS) model, to examine subtle aspects of hippocampal morphometry that are associated with Aβ/tau burden in the brain, measured using positron emission tomography (PET). FMFS is comprised of hippocampal surface-based feature calculation, patch-based feature selection, federated group LASSO regression, federated screening rule-based stability selection, and region of interest (ROI) identification. FMFS was tested on two Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts to understand hippocampal alterations that relate to Aβ/tau depositions. Each cohort included pairs of MRI and PET for AD, mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects. Experimental results demonstrated that FMFS achieves an 89× speedup compared to other published state-of-the-art methods under five independent hypothetical institutions. In addition, the subiculum and