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.
Cortical thinning and metabolic reduction can be possible imaging biomarkers for Alzheimer’s disease (AD) diagnosis and monitoring. Many techniques have been developed for the cortical measurement and widely used for the clinical statistical studies. However, the measurement consistency of individuals, an essential requirement for a clinically useful technique, requires proper further investigation. Here we leverage our previously developed BSIM technique 1 to measure cortical thickness and thinning and use it with longitudinal MRI from ADNI to investigate measurement consistency and spatial resolution. 10 normal, 10 MCI, and 10 AD subjects in their 70s were selected for the study. Consistent cortical thinning patterns were observed in all baseline and follow up images. Rapid cortical thinning was shown in some MCI and AD cases. To evaluate the correctness of the cortical measurement, we compared longitudinal cortical thinning with clinical diagnosis and longitudinal PET metabolic reduction measured using 3D-SSP technique2 for the same person. Longitudinal MR cortical thinning and corresponding PET metabolic reduction showed high level pattern similarity revealing certain correlations worthy of further studies. Severe cortical thinning that might link to disease conversion from MCI to AD was observed in two cases. In summary, our results suggest that consistent cortical measurements using our technique may provide means for clinical diagnosis and monitoring at individual patient’s level and MR cortical thinning measurement can complement PET metabolic reduction measurement.
Alzheimer’s disease (AD) is caused by pathological changes including cortical thinning occurring throughout the brain.
Traditional methods for assessing cortical thickness are challenged by the sub-millimeter accuracy required for clinical
conditions and the convoluted nature of brain surface. Furthermore, there is a significant overlap of gray and white
matter intensities. A novel Brain Surface Intensity Model (BSIM) has been developed for use as a potential imaging
biomarker for neurodegenerative diseases. BSIM technique extracts MR intensity profiles perpendicular to a mathematically defined gray matter iso-intensity layer (GMIIL) at predefined reference points, fits that profile to BSIM,
and computes cortical thickness. A 3D visualization tool has been developed to evaluate intensity extraction and model
calculation. 29 normal subjects aged between 70 to 80 years from ADNI database were used to generate normal
references and measure individual Z-score cortical thinning. 30 age-matched AD subjects were used to study thinning
patterns. Significant cortical thinning (p < 0.0001) was found for AD group. 95% confidence interval of the cortical
thinning in AD patients was from 0.17 to 0.23 mm. The cortical thinning of the AD patients showed distinct features that differentiate AD patients from normal controls. The thickness measurements of 29 normal controls were validated by comparing with results from literature (p = 0.94). BSIM technique avoids complicated 3D segmentation of brain gray
and white matters, and simplifies the thickness calculation. Moreover, it is less affected by the image noise, inhomogeneity, partial volume effects, and the intensity overlap of the white and gray matters.
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