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Research Grants 2016


To view an abstract, select an author from the vertical list on the left.

2016 Grants - Kim

Analysis of Brain Degeneration in MCI Using a Biomechanical Framework

Jeongchul Kim, Ph.D.
Wake Forest University, Health Sciences
Winston-Salem, North Carolina

2016 Alzheimer’s Association Research Fellowship (AARF)

Can new methods to analyze subtle changes in brain structure be used to detect Alzheimer’s disease in its earliest stages?

Background
An important goal of Alzheimer’s research is to develop effective and non-invasive methods for detecting the disease as early as possible. Evidence suggests that brain changes associated with Alzheimer’s disease may begin decades before clinical symptoms are evident. A major focus of efforts to improve early diagnosis of Alzheimer’s disease has been research into brain imaging. Many advances in brain imaging have been made in the past decade, but there is a need to develop more sophisticated methods for analyzing the images, so that subtle changes can be detected. These types of analyses could help identify specific, early brain changes that may be strong predictors of later symptoms and eventual diagnosis of Alzheimer’s disease.

Research Plan
Jeongchul Kim, Ph.D., and colleagues will use novel methods to analyze changes in the shape and size of specific brain regions over time that may predict the onset of Alzheimer’s disease. They will compare changes between cognitively normal individuals to those with Alzheimer’s disease or mild cognitive impairment (MCI), a condition that can precede Alzheimer’s. The researchers will develop detailed, three-dimensional models of brain structure and use statistical methods to identify which early changes are most strongly related to the later development of Alzheimer’s. The research team will also analyze brain images from an exercise intervention study to determine if aerobic exercise can prevent or delay disease-related brain changes in individuals with MCI.

Impact
These studies could help advance the development of new ways to analyze brain images that could enhance our ability to detect and diagnose Alzheimer’s at its earliest stages.


Alzheimer's Association International Conference | July 16-20, 2017, London, England

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