Small world network measures predict white matter degeneration in patients with early-stage mild cognitive impairment

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2012, Pages 1405-1408

  Nir, Talia ^a   Jahanshad, Neda ^a   Jack, Clifford R ^b   Weiner, Michael W ^c   Toga, Arthur W ^a   Thompson, Paul M ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b MAYO CLINIC   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Alzheimer's disease; connectivity; diffusion imaging; graph theory; predictive models

Indexed keywords

ALZHEIMER'S DISEASE; BRAIN CONNECTIVITY; COGNITIVE IMPAIRMENT; CONNECTIVITY; CORPUS CALLOSUM; CRITICAL TIME; DEGENERATIVE DISEASE; DIFFUSION IMAGING; FRACTIONAL ANISOTROPY; LONGITUDINAL DIFFUSIONS; MEAN AGES; NETWORK MEASURES; PREDICTIVE MODELS; SMALL WORLD NETWORKS; SMALL WORLDS; WHITE MATTER; WHITE MATTER FIBERS;

BRAIN; DIFFUSION TENSOR IMAGING; GRAPH THEORY; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; TENSORS;

FORECASTING;

EID: 84864861845     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2012.6235831     Document Type: Conference Paper

References (23)

1. Filippi CG et al., 2001. Diffusion tensor imaging of patients with HIV and normal-appearing white matter on MR images of the brain. Am J Neuroradiol., 22(2):277-283.
2. Delbeuck X et al., 2003. Alzheimer's disease as a disconnection syndrome? Neuropsychol. Rev., 13:79-92.
3. Pearson RCA et al., 1985. Anatomical correlates of the distribution of the pathological changes in the neocortex in Alzheimer's disease. PNAS, 82: 4531-4534.
4. De Lacoste MC, White CL, 1993. The role of cortical connectivity in Alzheimer's disease pathogenesis: A review and model system. Neurobiol. Aging, 14: 1-16.
5. Rose SE et al., 2000. Loss of connectivity in Alzheimer's disease: an evaluation of white matter tract integrity with colour coded MR diffusion tensor imaging. JNNP, 69:528-530.
6. Medina D et al., 2006. White matter changes in mild cognitive impairment and AD: a diffusion tensor imaging study. Neurobiol Aging, 27:663-672.
7. Bullmore E, Sporns O, 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Rev. Neurosci., 10:186-198.
8. He Y et al., 2008. Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease.#J. Neurosci., 28(18):4756-4766.
9. Smith SM, 2002. Fast robust automated brain extraction, Hum. Brain Mapp., 17(3):143-155.
10. Holmes CJ et al., 1998. Enhancement of MR images using registration for signal averaging. JCAT, 22(2):324-333.
11. Jenkinson M et al., 2002. Improved optimisation for the robust and accurate linear registration and motion correction of brain images. NeuroImage, 17(2):825-841.
12. Leow AD et al., 2007. Statistical properties of Jacobian maps and the realization of unbiased large-deformation nonlinear image registration. IEEE Trans. on Medical Imaging, 26(6): 822-832.
13. Basser PJ et al., 1994. MR diffusion tensor spectroscopy and imaging. Biophys. Journal, 66(1):259-267.
14. Gutman B et al., 2010. Creating unbiased minimal deformation templates for brain volume registration. OHBM, Barcelona, Spain.
15. Lepore N et al., 2007. Mean template for tensor-based morphometry using deformation tensors. MICCAI, 10(2): 826-833.
16. Yanovsky I et al., 2007. Topology preserving log-unbiased nonlinear image registration: theory and implementation. IEEE CVPR, pp 1-8.
17. Mori S et al., 2008. Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. NeuroImage, 40(2):570-582.
18. Jahanshad N et al., 2011. 4-Tesla high angular resolution diffusion tractography analysis of the human connectome in 234 subjects: Sex differences and EPI distortion effects, ISMRM 2011.
19. Fischl B. et al., 2004. Automatically parcellating the human cerebral cortex, Cereb. Cortex, 14:11-22.
20. Jahanshad N et al., 2011. Sex differences in the Human Connectome: 4-Tesla high angular resolution diffusion tensor imaging (HARDI) tractography in 234 young adult twins. ISBI 2011, pp 939-943.
21. Langers DR et al., 2007. Enhanced signal detection in neuroimaging by means of regional control of the global false discovery rate. NeuroImage, 38 (1):43-56.
22. Douaud G et al., 2011. DTI measures in crossing-fiber areas: increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease. NeuroImage, 55(3):880-890.
23. Zhan L et al., 2009. Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function. ISBI 2009, pp 1402-1405.