Diffusion Tensor Image Analysis in the Study of Age-Related Neurodegeneration
Professor Stephen WongThis collaboration addresses the problem of visualizing and analyzing large numbers of diffusion weighted and diffusion tensor (DTI) images in order to study the effects of aging on neurodegeneration. Aging and aging related neurodegeneration conditions affect tens of millions of Americans. Typical conditions affecting central nervous system include Alzheimer's disease, dementia, stroke, and Parkinson's disease. By one account, more than four million people in the United States suffer from Alzheimer's disease. In recent years, there has been increasing interest in research on aging. The study of aging has been underpinned by rapid technology development in medical imaging, such as MRI, CT, and PET. It is well accepted that during aging process the adult nervous system changes with deteriorating cognitive abilities, worsening reflexes, and much higher incidence of neurodegenerative disease. However, despite our current understanding of the etiology of neurodegeneration, the underpinnings of normal aging remain a complete mystery. Therefore, the age-related mechanisms of increased susceptibility to pathological alterations are also enigmatic. In order to address the scientific questions surrounding these issues, researchers in Professor Wong's group at Brigham and Women's Hospital are acquiring databases of DTI images, in order to quantify the affects of aging. The tools they need to do this will entail user interaction, and the corresponding visualization of DTI volumes.
The Harvard Center for Neurodegeneration and Repair (HCNR) is a Harvard-wide initiative of Harvard Medical School (HMS) and eight affiliated teaching hospitals, including Brigham and Women's Hospital and Massachusetts General Hospital. The HCNR is pursuing an interdisciplinary approach in neuroscience research. The HCNR Center for Bioinformatics, in particular, had the charter to investigate advanced magnetic resonance imaging and bioinformatics techniques to evaluate and compare normal brains and aging brains. They expect to derive longitudinal association and correlation among time-lapse, in-vivo, high-resolution MRI. They use diffusion tensor imaging (DTI) to examine age-related changes in genu, splenium, and centrum semiovale white matter diffusivity and calculate the relationship between diffusivity (trace) and fractional anisotropy (FA) across and within individual subjects. Researchers associated with this work perform DTI scans on both human and animal subjects (e.g., rat and mice of aging models). They are also studying the role of macrostructural and microstructural partial volume effects on the DTI metrics. They hypothesize that ellipsoid (diffusion tensor) shape analysis will provide insights into the relationship between morphometric erosion in the splenium and centrum and ages of subjects.