TY - GEN
T1 - Alzheimer’s disease classification with novel microstructural metrics from diffusion-weighted MRI
AU - Alzheimer’s Disease Neuroimaging Initiative (ADNI)
AU - Nir, Talia M.
AU - Villalon-Reina, Julio E.
AU - Gutman, Boris A.
AU - Moyer, Daniel
AU - Jahanshad, Neda
AU - Dehghani, Morteza
AU - Jack, Clifford R Jr.
AU - Weiner, Michael W.
AU - Thompson, Paul M.
PY - 2016
Y1 - 2016
N2 - Alzheimer’s disease (AD) deficits may be due in part to declining white matter (WM) integrity and disrupted connectivity. Numerous diffusionweighted MRI (dMRI) studies of AD report WM deficits based on tensor model metrics. New microstructural measures derived from additional dMRI models may carry different information about WM microstructure including the geometry of diffusion anisotropy, diffusivity, complexity, estimated number of distinguishable fiber compartments, number of crossing fibers and neurite dispersion. Here we aimed to find the most helpful dMRI metrics and brain regions from a set of 17 dMRI-derived feature maps, to predict diagnostic group (AD or healthy control). The best metrics for classification were non-tensor metrics in the hippocampus and temporal lobes, areas consistently implicated in AD.
AB - Alzheimer’s disease (AD) deficits may be due in part to declining white matter (WM) integrity and disrupted connectivity. Numerous diffusionweighted MRI (dMRI) studies of AD report WM deficits based on tensor model metrics. New microstructural measures derived from additional dMRI models may carry different information about WM microstructure including the geometry of diffusion anisotropy, diffusivity, complexity, estimated number of distinguishable fiber compartments, number of crossing fibers and neurite dispersion. Here we aimed to find the most helpful dMRI metrics and brain regions from a set of 17 dMRI-derived feature maps, to predict diagnostic group (AD or healthy control). The best metrics for classification were non-tensor metrics in the hippocampus and temporal lobes, areas consistently implicated in AD.
UR - http://www.scopus.com/inward/record.url?scp=84964049767&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-28588-7_4
DO - 10.1007/978-3-319-28588-7_4
M3 - Conference contribution
SN - 9783319285863
VL - none
T3 - Mathematics and Visualization
SP - 41
EP - 54
BT - Mathematics and Visualization
PB - Springer Heidelberg
T2 - Workshop on Computational Diffusion MRI, MICCAI 2015
Y2 - 9 October 2015 through 9 October 2015
ER -