The Alzheimer's Association 2009 Alzheimer's Disease Facts and Figures report indicates that as many as 5.3 million Americans suffer from Alzheimer disease (AD), and it costs the country about $148 billion a year to provide care. AD triples healthcare costs for Americans who are 65 and older, and will have a devastating impact in the near future. It is expected that AD will affect as many as 16 million Americans by 2050 as the baby boomers reach the age at which they are most at risk. Because neuropathological changes related to AD may begin 20 to 30 years before the onset of clinical symptoms in individuals at great risk, the onset of AD is insidious and the boundaries between age-associated memory impairment and actual AD are blurred. It is of major challenge to develop new technologies for the early detection of AD in order to facilitate disease prevention, diagnosis, and effective treatment. The goal of this Small Business Innovation Research (SBIR) Program application is to develop an innovative imaging technology for the early detection of AD for the marketplace. In order to facilitate the translation of the fcMRI lab research into practical clinical applications, we will conduct the following specific aims in Phase I:
Aim 1. Design and develop streamlined workflow and user-friendly prototype software UI (user interface) to demonstrate that users without extensive analysis expertise can utilize the GFC index analysis.
Aim 2. Develop and validate (using existing datasets) a robust GFC index classifier that will individually discriminate cognitive normal (CN) subjects from Alzheimer's disease patients by using above mentioned prototype software.
Aim 3. Conduct the technological research to determine how different magnetic field strengths (1.5 v.s. 3 Tesla) of MRI scanner systems will affect the GFC index. It is our goal to demonstrate that the GFC index can be used by majority of scanners. With this Phase I of the SBIR grant, we will demonstrate the feasibility of the proposed GFC index method in order to achieve satisfactory results in clinical settings. This will lay the foundation for the SBIR Phase II study.
As many as 5.3 million Americans are suffering from Alzheimer disease (AD), and it costs the country around $148 billion a year to provide care. Because neuropathological changes related to AD may begin 20 to 30 years before the onset of clinical symptoms in individuals at great risk, the onset of AD is insidious and the boundaries between age-associated memory impairment and actual AD are blurred. The goal of this SBIR application is to develop an innovative imaging technology for the early detection of AD for the market place. We will design and develop streamlined workflow and user-friendly prototype software UI to provide a functional connectivity index. We will also develop and validate the index as a Classifier for individually discriminating between cognitive normal (CN) subjects and Alzheimer's disease patients. With this Phase I of SBIR grant, we will demonstrate the feasibility of the proposed functional connectivity index in order to facilitate disease prevention, diagnosis, and access effective treatments.
