title: Connectivity network measures predict volumetric atrophy in mild cognitive impairment.
abstract: Alzheimer's disease (AD) is characterized by cortical atrophy and disrupted anatomic connectivity, and leads to abnormal interactions between neural systems. Diffusion-weighted imaging (DWI) and graph theory can be used to evaluate major brain networks and detect signs of a breakdown in network connectivity. In a longitudinal study using both DWI and standard magnetic resonance imaging (MRI), we assessed baseline white-matter connectivity patterns in 30 subjects with mild cognitive impairment (MCI, mean age 71.8 ± 7.5 years, 18 males and 12 females) from the Alzheimer's Disease Neuroimaging Initiative. Using both standard MRI-based cortical parcellations and whole-brain tractography, we computed baseline connectivity maps from which we calculated global "small-world" architecture measures, including mean clustering coefficient and characteristic path length. We evaluated whether these baseline network measures predicted future volumetric brain atrophy in MCI subjects, who are at risk for developing AD, as determined by 3-dimensional Jacobian "expansion factor maps" between baseline and 6-month follow-up anatomic scans. This study suggests that DWI-based network measures may be a novel predictor of AD progression.
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA.
authors.forename: Talia M
authors.initials: TM
authors.lastname: Nir
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Neda
authors.initials: N
authors.lastname: Jahanshad
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA.
authors.forename: Arthur W
authors.initials: AW
authors.lastname: Toga
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Matt A
authors.initials: MA
authors.lastname: Bernstein
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Clifford R
authors.initials: CR
authors.lastname: Jack
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California-San Francisco School of Medicine, San Francisco, CA, USA.
authors.forename: Michael W
authors.initials: MW
authors.lastname: Weiner
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA; Department of Neurology, University of Southern California, Los Angeles, CA, USA; Department of Psychiatry, University of Southern California, Los Angeles, CA, USA; Department of Radiology, University of Southern California, Los Angeles, CA, USA; Department of Engineering, University of Southern California, Los Angeles, CA, USA; Department of Pediatrics, University of Southern California, Los Angeles, CA, USA; Department of Ophthalmology, University of Southern California, Los Angeles, CA, USA. Electronic address: pthomp@usc.edu.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
mesh_terms: D000368:Aged; D000544:Alzheimer Disease; D001284:Atrophy; D060825:Cognitive Dysfunction / Q000473:pathology* / Q000503:physiopathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D018450:Disease Progression; D005260:Female; D005544:Forecasting; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000473:pathology / Q000503:physiopathology; D009431:Neural Conduction; D059906:Neuroimaging / Q000379:methods*; D066127:White Matter / Q000473:pathology* / Q000503:physiopathology*
keywords: ADNI; Brain networks; Connectivity; DTI; Graph theory; Small worldness; TBM; Tractography; White matter