Age-related Changes of White Matter in the Elderly Population Measured by Diffusion Tensor Imaging
|Sheng-Heng Tsai1, Jachih Fu2, Jyh-Wen Chai1,3,4, Yi-Ying Wu1 and Clayton Chi-Chang Chen1,5,6,7*|
|1Department of Radiology, Taichung Veterans General Hospital, Taiwan|
|2Computer Aided Measurement and Diagnostic Systems Laboratory, Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, Yunlin, Taiwan|
|3Division of Radiology, College of Medicine, China Medical University, Taichung, Taiwan|
|4Department of Biomedical Engineering, HungKuang University, Taichung, Taiwan|
|5Department of Radiological Technology and Graduate Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan|
|6Department of Physical Therapy, Hungkuang University of Technology, Taichung, Taiwan|
|7Department of Physical Therapy and Assistive Technology, National Yang Ming University, Taipei, Taiwan|
|Corresponding Author :||Dr. Clayton Chi-Chang Chen
No 160, Sec 3, Taichung Harbor oad
Department of Radiology
Taichung Veterans General Hospital
Tel: 04-23592525 ext 3701
E-mail: [email protected]
|Received July 23, 2012; Accepted August 19, 2012; Published August 22, 2012|
|Citation: Tsai SH, Fu J, Chai JW, Wu YY, Chen CCC (2012) Age-related Changes of White Matter in the Elderly Population Measured by Diffusion Tensor Imaging. OMICS J Radiology. 1:107. doi: 10.4172/2167-7964.1000107|
|Copyright: © 2012 Tsai SH. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
Background: A decline in cerebral White Matter (WM) integrity occurs across the adult lifespan, with more rapid degradation later in life. Diffusion Tensor Imaging (DTI) is a non-invasive method to evaluate the microscopic changes of WM in vivo. Linear regression models have been applied to depict the relationship between diffusion properties, such as Fractional Anisotropy (FA) and Mean Diffusivity (MD), derived from DTI and age. However, the fit of these linear regression models is unsatisfactory.
Objectives: The purpose of our study was to investigate the age-related changes of WM in an elderly population.
Methods: We performed statistical parametric mapping with DTI to evaluate the patterns of age-related microscopic WM changes with voxel-based analysis in the elderly population (>55 years old). A linear regression model was used to examine the associations between DTI parameters and age.
Results: The fit of the linear regression model depicting the association between mean global FA, MD values (FA, MD derived from global WM), and age was better than that reported in prior studies using DTI (R2=0.4252, p<0.001 for global FA and age; R2=0.5309, p<0.001 for global MD and age). Moreover, comparable to previous studies, the mean global FA showed a significant negative correlation with mean global MD, indicating a true age-related phenomenon of increased interstitial or intracellular fluid accumulation in cerebral WM. The mean frontal FA value was significantly lower than the mean global FA value. However, there was no significant difference between the mean frontal MD value and the mean global MD value.
Conclusions: Focusing on the elderly population, we can improve the fit of linear regression models to investigate the age-related changes of WM by DTI. These results suggest that age-related microscopic changes of WM might be occurring more consistently in later life.