Early Detection of Mild Cognitive Impairment

Identifying individuals at risk for Alzheimer's disease and improving our understanding of effective treatment strategies in Wisconsin

Full Project Name:Early Detection of Mild Cognitive ImpairmentPrincipal Investigator:Kevin M Koch, PhD, RadiologyAward Amount:800,000
Award Date
Project Duration:60 months

Project Description Narrative:

Alzheimer's disease is a progressive, age-related neurodegenerative disease that affects an estimated 5.3 million people in the U.S., including approximately 110,000 individuals in Wisconsin. Deaths attributed to Alzehimer's disease have increased significantly, making it the sixth leading cause of death. However, among the top 10 causes of death in America, Alzheimer's disease is unique in that there is no way to prevent, cure, or even slow its progression. Mild cognitive impairment (MCI) is a clinical term used to describe the cognitive state that is between normal aging and dementia. Researchers have a particular interest in MCI because they believe that it is a transitional state to Alzheimer's disease, and that detecting it may help identify individuals at risk for progression to Alzheimer's disease as well as define a window for initiating effective treatment strategies.

Through this award, the project investigators seek to develop a neuroimaging biomarker for early detection of individuals who are at risk of progression from a cognitive normal state to MCI.

Outcomes & Lessons Learned:

• Recruited new faculty member to lead project, modifying project aims to focus on quantitative susceptibility mapping and its application to cognitive impairment

• Developed method of greatly improved quantitative susceptibility mapping MRI and successfully applied method to patients suffering from sports concussions and brain cancer

• Filed patent on the method of Volume-Parcellated Quantitative Susceptibility Mapping developed in the context of this project

• Documented substantial progress on technical aspects of the research, however shifted translational components of project to better support skillset and background of faculty, therefore elected to end project early following technical progress

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