Connectivity network measures predict volumetric atrophy in mild cognitive impairment

NEUROBIOLOGY OF AGING

卷:36

Article

Nir, Talia M.¹  Jahanshad, Neda^1,2  Toga, Arthur W.¹  Bernstein, Matt A.²  Jack, Clifford R., Jr.²  Weiner, Michael W.³  Thompson, Paul M.^{1,4,5,6,7,8,9} 

[1] Univ So Calif, Imaging Genet Ctr, Inst Neuroimaging & Informat, Los Angeles, CA 90032 USA

[2] Mayo Clin & Mayo Fdn, Dept Radiol, Rochester, MN USA

[3] Univ Calif San Francisco, Sch Med, Dept Radiol & Biomed Imaging, San Francisco, CA USA

[4] Univ So Calif, Dept Neurol, Los Angeles, CA 90032 USA

[5] Univ So Calif, Dept Psychiat, Los Angeles, CA 90032 USA

[6] Univ So Calif, Dept Radiol, Los Angeles, CA 90032 USA

[7] Univ So Calif, Dept Engn, Los Angeles, CA 90032 USA

[8] Univ So Calif, Dept Pediat, Los Angeles, CA 90032 USA

[9] Univ So Calif, Dept Ophthalmol, Los Angeles, CA 90032 USA

关键词: Graph theory;    Brain networks;    White matter;    DTI;    Tractography;    ADNI;    TBM;    Small worldness;    Connectivity;   

DOI  :  10.1016/j.neurobiolaging.2014.04.038

来源: Elsevier

【 摘 要 】

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. (C) 2015 Elsevier Inc. All rights reserved.

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