@inproceedings{4ff10ae22baf440bac77093bbd37b7fa,
title = "Small world network measures predict white matter degeneration in patients with early-stage mild cognitive impairment",
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.",
keywords = "Alzheimer's disease, connectivity, diffusion imaging, graph theory, predictive models",
author = "Talia Nir and Neda Jahanshad and Jack, {Clifford R.} and Weiner, {Michael W.} and Toga, {Arthur W.} and Thompson, {Paul M.}",
year = "2012",
doi = "10.1109/ISBI.2012.6235831",
language = "English (US)",
isbn = "9781457718588",
series = "Proceedings - International Symposium on Biomedical Imaging",
pages = "1405--1408",
booktitle = "2012 9th IEEE International Symposium on Biomedical Imaging",
note = "2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 ; Conference date: 02-05-2012 Through 05-05-2012",
}