PROCEEDINGS ARTICLE | March 13, 2014
Proc. SPIE. 9038, Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging
KEYWORDS: Visualization, Sensors, Databases, Magnetic resonance imaging, Cerebral cortex, Neuroimaging, Alzheimer's disease, Positron emission tomography, Dementia, Brain
Age-related cortical thinning has been studied by many researchers using quantitative MR images for the past three decades and vastly differing results have been reported. Although results have shown age-related cortical thickening in elderly cohort statistically in some brain regions under certain conditions, cortical thinning in elderly cohort requires further systematic investigation. This paper leverages our previously reported brain surface intensity model (BSIM)1 based technique to measure cortical thickness to study cortical changes due to normal aging. We measured cortical thickness of cognitively normal persons from 60 to 89 years old using Australian Imaging Biomarkers and Lifestyle Study (AIBL) data. MRI brains of 56 healthy people including 29 women and 27 men were selected. We measured average cortical thickness of each individual in eight brain regions: parietal, frontal, temporal, occipital, visual, sensory motor, medial frontal and medial parietal. Unlike the previous published studies, our results showed consistent age-related thinning of cerebral cortex in all brain regions. The parietal, medial frontal and medial parietal showed fastest thinning rates of 0.14, 0.12 and 0.10 mm/decade respectively while the visual region showed the slowest thinning rate of 0.05 mm/decade. In sensorimotor and parietal areas, women showed higher thinning (0.09 and 0.16 mm/decade) than men while in all other regions men showed higher thinning than women. We also created high resolution cortical thinning rate maps of the cohort and compared them to typical patterns of PET metabolic reduction of moderate AD and frontotemporal dementia (FTD). The results seemed to indicate vulnerable areas of cortical deterioration that may lead to brain dementia. These results validate our cortical thickness measurement technique by demonstrating the consistency of the cortical thinning and prediction of cortical deterioration trend with AIBL database.
