Mr. Morten S. Spjuth Profile

Morten S. Spjuth

at Aalborg Univ

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Proceedings Article | 3 March 2007 Paper

Early detection of AD using cortical thickness measurements

M. Spjuth, F. Gravesen, S. Eskildsen, L. Østergaard

Proceedings Volume 6512, 65120L (2007) https://doi.org/10.1117/12.709806

KEYWORDS: Brain, Algorithm development, Image registration, Principal component analysis, Distance measurement, Magnetic resonance imaging, Magnetism, Neuroimaging, Alzheimer's disease, Functional imaging

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Alzheimer's disease (AD) is a neurodegenerative disorder that causes cortical atrophy and impaired cognitive functions. The diagnosis is difficult to make and is often made over a longer period of time using a combination of neuropsychological tests, and structural and functional imaging. Due to the impact of early intervention the challenge of distinguishing early AD from normal ageing has received increasing attention. This study uses cortical thickness measurements to characterize the atrophy in nine mild AD patients (mean MMSE-score 23.3 (std: 2.6)) compared to five healthy middle-aged subjects. A fully automated method based on deformable models is used for delineation of the inner and outer boundaries of the cerebral cortex from Magnetic Resonance Images. This allows observer independent high-resolution quantification of the cortical thickness. The cortex analysis facilitates detection of alterations throughout the entire cortical mantle. To perform inter-subject thickness comparison in which the spatial information is retained, a feature-based registration algorithm is developed which uses local cortical curvature, normal vector, and a distance measure. A comparison of the two study groups reveals that the lateral side of the hemispheres shows diffuse thinner areas in the mild AD group but especially the medial side shows a pronounced thinner area which can be explained by early limbic changes in AD. For classification principal component analysis is applied to reduce the high number of thickness measurements (>200,000) into fewer features. All mild AD and healthy middle-aged subjects are classified correctly (sensitivity and specificity 100%).

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