Diffusion tensor imaging of the posterior cingulate is a useful biomarker of mild cognitive impairment

Terence C Chua, Wei Wen, Xiaohua Chen, Nicole Kochan, Melissa J Slavin, Julian N Trollor, Henry Brodaty, Perminder S Sachdev
American Journal of Geriatric Psychiatry 2009, 17 (7): 602-13

OBJECTIVES: Mild cognitive impairment (MCI) is recognized as a predementia state, but its definition is inconsistent and only 20%-30% develop dementia after 2 years. Biomarkers may help identify individuals at greatest risk of progressive decline. The authors examine a novel neuroimaging technique, diffusion tensor imaging (DTI) as a potential biomarker of MCI.

DESIGN: Cross-sectional prospective study.

SETTING: Subjects were recruited randomly using the electoral roll from two electorates in East Sydney, Australia.

PARTICIPANTS: A community-dwelling sample (N = 249) and age 70-90 years.

MEASUREMENTS: Screening to exclude dementia, comprehensive neuropsychiatric assessment, cognitive test battery, structural magnetic resonance imaging and DTI to obtain measures of fractional anisotropy (FA) and mean diffusivity (MD). MCI was diagnosed by standard criteria.

RESULTS: After controlling for age, sex, and years of education, the amnestic MCI (aMCI) group demonstrated microstructural pathology in the parahippocampal white matter, frontal white matter, splenium of corpus callosum, and posterior cingulate region. The nonamnestic MCI (naMCI) group demonstrated microstructural pathology in the frontal white matter, internal capsule, occipital white matter, and the posterior cingulate region. A binary logistic regression model showed that DTI of the left posterior cingulate was significant in identifying persons with aMCI to an accuracy of 85.1%. Receiver operating characteristics curve analysis yielded a sensitivity of 80% and specificity of 60.3% in distinguishing aMCI from naMCI and the normal comparison group.

CONCLUSION: DTI of the posterior cingulate region discriminates MCI from cognitively normal individuals with accuracy and has the potential to be used as a biomarker of MCI, in particular aMCI.

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