Work

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

Year: 2012

Type: conference-paper

Abstract: Alzheimer's Disease (AD) has long been considered a cortical degenerative disease, but impaired brain connectivity, due to white matter injury, may exacerbate cognitive problems. Predicting brain changes is critically important for early treatment. In a longitudinal diffusion tensor imaging study, we investigated white matter fiber integrity in 19 patients (mean age: 74.7 +/- 8.4 yrs at baseline) displaying early signs of mild cognitive impairment (eMCI). We first examined whether baseline average fractional anisotropy (FA) measures in the corpus callosum (CC) predicted changes in white matter integrity over the following 6 months. We then examined whether "small world" architecture measures - calculated from baseline connectivity maps - predicted white matter changes over the next 6 months. While average CC FA measures at baseline were not associated with future changes in FA, network measures were a sensitive biomarker for predicting white matter changes during this critical time before AD strikes.

Source: IEEE International Symposium on Biomedical Imaging (ISBI)

DOI: 10.1109/isbi.2012.6235831

Authors: Talia Nir, Neda Jahanshad, Clifford R. Jack, Michael W. Weiner, Arthur W. Toga, Paul M. Thompson

Institutions: University of California, Los Angeles, Mayo Clinic, University of California, San Francisco, University of California San Francisco Medical Center

Language: English

Topic: Advanced Neuroimaging Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering, National Center for Research Resources