Recent evidence has shown that structural magnetic resonance imaging (MRI) is an effective tool for Alzheimer’s disease (AD) prediction. While traditional MRI-based prediction uses images acquired at a single time point, a longitudinal study is more sensitive and accurate in detecting early pathological changes of the AD. Two main statistical difficulties arise in the longitudinal MRI-based analysis: (i) the inconsistent longitudinal scans among subjects (i.e., the different scanning time and the different total number of scans); (ii) the heterogeneous progressions of high-dimensional regions of interest (ROIs) in MRI. In this work, we propose a new feature selection and estimation method which can be applied to extract AD-related features from the heterogeneous longitudinal MRI. A key ingredient of our approach is a hybrid of the smoothing splines and the l1-penalty. Smoothing splines can integrate information from heterogeneous progressions of ROIs and adapt to inconsistent scans of MRIs. The selection property of the l1-penalty helps to select important ROIs related to AD. We introduce an efficient algorithm to perform the proposed method. Real data experiments on the Alzheimer’s Disease Neuroimaging Initiative database are provided to corroborate some advantages of the proposed method for AD prediction in longitudinal studies.
Funding
ADNI (National Institutes of Health Grant U01 AG024904 and Department of Defense award number W81XWH-12-2-0012) is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai, Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development, LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of Southern California. The research was supported in part by NSF grant DMS-1308877.
