A computer approach to assess age-related changes of the brain white matter in Alzheimer's disease

Abstract

Background: Age is one of the major risk factors for Alzheimer's disease (AD) which is considered the most common adult-onset dementia. There is little information about age-related changes during brain dementia. Methods: This study observed age-related variations in the brain throughout adulthood in magnetic resonance imaging (MRI) of the AD and healthy brains. The Open Access Series of Imaging Studies (OASIS) is used as a database. The method consists of design and develop a computer approach based on artificial intelligence (AI) to segment white matter (WM) from the MRI. Then, the number of pixels within the segmented white matter (WM) of the brain was calculated. Correlation was used to investigate age relation with WM changes in the normal and AD brain. Results: The WM change with aging was more correlated in AD group (rAD = −0.505, p-value = 0.0007) than control group (rControl = −0.357, p-value = 0.0001). Conclusion: Higher correlation of WM pixel counts with age in AD group approved that AD is characterized by the relevant involvement of the WM and age. Our approach gained additional information on the quantitative pathological changes associated with the AD as the most common brain disorder of the elderly.

Keywords

• Age-related brain variation
• White matter
• Alzheimer's disease
• MRI
• Aging