title: Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease.
abstract: Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.
authors.affiliation: Institute of Psychology, Leiden University, The Netherlands; Department of Radiology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, The Netherlands. Electronic address: t.m.schouten@lumc.nl.
authors.forename: Tijn M
authors.initials: TM
authors.lastname: Schouten
authors.affiliation: Department of Neurology, Medical University of Graz, Austria.
authors.forename: Marisa
authors.initials: M
authors.lastname: Koini
authors.affiliation: Institute of Psychology, Leiden University, The Netherlands; Department of Radiology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, The Netherlands.
authors.forename: Frank
authors.initials: F
authors.lastname: de Vos
authors.affiliation: Department of Neurology, Medical University of Graz, Austria.
authors.forename: Stephan
authors.initials: S
authors.lastname: Seiler
authors.affiliation: Department of Radiology, Leiden University, The Netherlands.
authors.forename: Jeroen
authors.initials: J
authors.lastname: van der Grond
authors.affiliation: Department of Neurology, Medical University of Graz, Austria.
authors.forename: Anita
authors.initials: A
authors.lastname: Lechner
authors.affiliation: Institute of Psychology, Leiden University, The Netherlands; Department of Radiology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, The Netherlands.
authors.forename: Anne
authors.initials: A
authors.lastname: Hafkemeijer
authors.affiliation: Institute of Psychology, Leiden University, The Netherlands; Department of Radiology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, The Netherlands.
authors.forename: Christiane
authors.initials: C
authors.lastname: Möller
authors.affiliation: Department of Neurology, Medical University of Graz, Austria.
authors.forename: Reinhold
authors.initials: R
authors.lastname: Schmidt
authors.affiliation: Institute of Psychology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, The Netherlands.
authors.forename: Mark
authors.initials: M
authors.lastname: de Rooij
authors.affiliation: Institute of Psychology, Leiden University, The Netherlands; Department of Radiology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, The Netherlands.
authors.forename: Serge A R B
authors.initials: SARB
authors.lastname: Rombouts
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology; D001921:Brain / Q000473:pathology* / Q000503:physiopathology; D060825:Cognitive Dysfunction / Q000145:classification / Q000175:diagnosis* / Q000473:pathology; D056324:Diffusion Tensor Imaging / Q000379:methods; D005260:Female; D066128:Gray Matter / Q000473:pathology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D011446:Prospective Studies; D066127:White Matter / Q000473:pathology
keywords: Alzheimer's disease; Classification; DWI; MRI; Multimodal; fMRI