TY - JOUR
T1 - Differences in early and late mild cognitive impairment tractography using a diffusion tensor MRI
AU - Lee, Seung Hak
AU - Seo, Jongbum
AU - Lee, Jong Min
AU - Park, Hyunjin
N1 - Publisher Copyright:
© 2014 Wolters Kluwer Health Lippincott Williams & Wilkins.
Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014/12/3
Y1 - 2014/12/3
N2 - Diffusion tensor MRI tractography is an imaging tool that can provide information of in-vivo neuronal fiber tracts to assess progress for Alzheimer's disease (AD). In an effort to detect early AD progression, we focused on distinguishing subgroups within mild cognitive impairment (MCI): early MCI and late MCI. Tractography was applied not only to white matter regions but also neighboring gray matter regions known to be affected by AD. Nerve fibers touching the hippocampus, thalamus, and amygdala in both hemispheres were extracted to quantify limbic system fiber connectivity. Two fiber extraction algorithms, fiber assignment by continuous tracking and the Runge Kutta approach, were applied to an AD imaging database. We computed the number of fibers touching regions of interest as the imaging feature. The imaging feature could distinguish between the MCI subgroups. It was also significantly correlated with a known genetic marker for AD, the apolipoprotein E epsilon 4 allele. The number of fibers might be a useful imaging biomarker to complement conventional region of interest-based biomarkers for AD research.
AB - Diffusion tensor MRI tractography is an imaging tool that can provide information of in-vivo neuronal fiber tracts to assess progress for Alzheimer's disease (AD). In an effort to detect early AD progression, we focused on distinguishing subgroups within mild cognitive impairment (MCI): early MCI and late MCI. Tractography was applied not only to white matter regions but also neighboring gray matter regions known to be affected by AD. Nerve fibers touching the hippocampus, thalamus, and amygdala in both hemispheres were extracted to quantify limbic system fiber connectivity. Two fiber extraction algorithms, fiber assignment by continuous tracking and the Runge Kutta approach, were applied to an AD imaging database. We computed the number of fibers touching regions of interest as the imaging feature. The imaging feature could distinguish between the MCI subgroups. It was also significantly correlated with a known genetic marker for AD, the apolipoprotein E epsilon 4 allele. The number of fibers might be a useful imaging biomarker to complement conventional region of interest-based biomarkers for AD research.
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U2 - 10.1097/WNR.0000000000000279
DO - 10.1097/WNR.0000000000000279
M3 - Article
C2 - 25325351
AN - SCOPUS:84916600095
VL - 25
SP - 1393
EP - 1398
JO - NeuroReport
JF - NeuroReport
SN - 0959-4965
IS - 17
ER -