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KMID : 1130620230190020138
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Journal of Clinical Neurology
2023 Volume.19 No. 2 p.138 ~ p.146
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Cortical Thickness and Brain Glucose Metabolism in Healthy Aging
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Baik Kyoung-Won
Jeon Se-Un
Yang Soh-Jeong
Na Yeon-A
Chung Seok-Jong
Yoo Han-Soo
Yun Mi-Jin
Lee Phil- Hyu
Sohn Young-H.
Ye Byoung-Seok
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Abstract
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Background and Purpose We aimed to determine the effect of demographic factors on cortical thickness and brain glucose metabolism in healthy aging subjects.
Methods The following tests were performed on 71 subjects with normal cognition: neurological examination, 3-tesla magnetic resonance imaging, 18F-fluorodeoxyglucose positronemission tomography, and neuropsychological tests. Cortical thickness and brain metabolism were measured using vertex- and voxelwise analyses, respectively. General linear models (GLMs) were used to determine the effects of age, sex, and education on cortical thickness and brain glucose metabolism. The effects of mean lobar cortical thickness and mean lobar metabolism on neuropsychological test scores were evaluated using GLMs after controlling for age, sex, and education. The intracranial volume (ICV) was further included as a predictor or covariate for the cortical thickness analyses.
Results Age was negatively correlated with the mean cortical thickness in all lobes (frontal and parietal lobes, p=0.001; temporal and occipital lobes, p<0.001) and with the mean temporal metabolism (p=0.005). Education was not associated with cortical thickness or brain metabolism in any lobe. Male subjects had a lower mean parietal metabolism than did female subjects (p<0.001), while their mean cortical thicknesses were comparable. ICV was positively correlated with mean cortical thickness in the frontal (p=0.016), temporal (p=0.009), and occipital (p=0.007) lobes. The mean lobar cortical thickness was not associated with cognition scores, while the mean temporal metabolism was positively correlated with verbal memory test scores.
Conclusions Age and sex affect cortical thickness and brain glucose metabolism in different ways. Demographic factors must therefore be considered in analyses of cortical thickness and brain metabolism.
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KEYWORD
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MRI, cortical thickness, FDG, brain glucose metabolism, healthy aging
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