Improved Gray Matter Atrophy Detection in Alzheimer Disease in Chinese Populations Using Chinese Brain Template
This study aimed to test the hypothesis that the statistical Chinese brain template would be more effective to detect gray matter (GM) changes in patients with Alzheimer disease (AD) in Chinese populations.
Materials and Methods:
In total, 50 patients with AD and 50 sex-matched and age-matched healthy controls were included in this study. Chinese2020, a typical statistical Chinese brain template, and MNI152, a typical Caucasian template were used for spatial normalization respectively. The GM volume alterations in patients with AD were examined by using voxel-based morphometry with education level and total intracranial volume as nuisance variables. The GM proportions of the identified brain areas with group difference were compared.
By using Chinese2020 and MNI152, significant GM atrophies in patients with AD were commonly detected in the bilateral medial temporal lobe, lateral temporal lobe, inferior/medial frontal cortex, as well as left thalamus. However, higher GM percentages of detected regions were acquired when Chinese2020 was used rather than MNI152. Furthermore, stronger statistical powers in the detected clusters were observed using Chinese2020 than MNI152. In addition, the laterality index analysis showed the bilateral atrophies with no hemispheric laterality in the para/hippocampus when using population-specific brain atlas (ie, Chinese2020).
These findings indicated that applying the population-specific brain atlas to neuroimaging studies may achieve higher accuracy in activation detection. This may have implications to the imaging study of neurodegenerative diseases.
Document Type: Research Article
Affiliations: 1: Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing Key Laboratory of MRI and Brain Informatics 2: Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China, Chow Yuk Ho Technology Centre for Innovative Medicine 3: MR Collaboration, Northeast Asia, Siemens Healthcare, Beijing 4: Department of Imaging and Interventional Radiology, Research Center for Medical Image Computing, Departments of Imaging and Interventional Radiology
Publication date: October 1, 2018