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Neurology India
Medknow Publications on behalf of the Neurological Society of India
ISSN: 0028-3886
EISSN: 0028-3886
Vol. 59, No. 2, 2011, pp. 168-173
Bioline Code: ni11052
Full paper language: English
Document type: Research Article
Document available free of charge

Neurology India, Vol. 59, No. 2, 2011, pp. 168-173

 en Comparison of diffusion tensor image study in association fiber tracts among normal, amnestic mild cognitive impairment, and Alzheimer's patients
Zhang, Yu-Zhen; Chang, Cheng; Wei, Xiao-er; Fu, Jian-Liang & Li, Wen-Bin

Abstract

Aim : To compare diffusion tensor image (DTI) study in association fiber tracts among normal control (NC), amnestic mild cognitive impairment (aMCI) and Alzheimer′s disease (AD) subjects. To assess diagnostic value of DTI in aMCI and differential diagnosis of DTI study between aMCI and AD.
Material and Methods : DTI was used to assess changes in cerebral association fiber tracts in NC, aMCI, and AD subjects (n = 20/group). Regions of interest included the inferior fronto-occipital fascicles (IFOF), superior longitudinal fascicles and cingulum tract, genu of corpus callosum (Gcc) was set right, splenium of corpus callosum was set left. Bilateral fractional anisotropy (FA) and apparent diffusion coefficient values were compared in three groups.
Results : Relative to NC, aMCI subjects had significantly different FA values for the IFOF and cingulum tract, while AD subjects had significantly different FA values of IFOF, Gcc, and cingulum tract. Relative to aMCI, AD subjects had significantly different FA values of cingulum tract.
Conclusion : Based on the results, DTI could be used as a diagnostic method for aMCI with abnormal changes in IFOF and cingulum tract. DTI could also be used for differential diagnosis of aMCI and AD by comparing FA values of the cingulum tract. Abnormal FA values of IFOF, Gcc, and cingulum tract in AD patients may help to elucidate the pathological processes in this disease.

Keywords
Alzheimer′s disease, amnestic mild cognitive impairment, dementia, diffusion tensor imaging

 
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