There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Prayas Sanyal |
| Institution: | Heritage Institute of Technology |
| Department: | ECE |
| Country: | |
| Proposed Analysis: | Motive of this study is to use neuroimaging techniques to find the transitional state between a healthy aging brain and a dementia/Alzheimer's affected brain. Mild cognitive impairment was often thought of to be the stepping point between a healthy and affected brain. But recent studies show how many MCI patients may remain stable over time while only a significant percentage of them progress into Alzheimer's or dementia related diseases. We aim to do a longitudinal study of MR images of the human brain for a given test data (of 5-10 people) and predict the timeline for the early-onset of Alzheimer's disease. The temporal data will help us determine the change in intensity of brain atrophy and hypometabolism in key brain areas accurately and aid in distinguishing Alzheimer's Disease from normal aging and other dementia related diseases. Studies have shown how excess atrophy and hypometabolism in the median temporal lobe predict the decline from mild cognitive impairment to Alzheimer's disease. |
| Additional Investigators | |
| Investigator's Name: | Anindya Sen |
| Proposed Analysis: | Main motive of this study is to use neuroimaging techniques to find the transitional state between a healthy aging brain and a dementia/Alzheimer's affected brain. Mild cognitive impairment was often thought of to be the stepping point between a healthy and affected brain. But recent studies show how many MCI patients may remain stable over time while only a significant percentage of them progress into Alzheimer's or dementia related diseases. We aim to do a longitudinal study of MR images of the human brain for a given test data (of 5-10 people) and predict the timeline for the early-onset of Alzheimer's disease. The temporal data will help us determine the change in intensity of brain atrophy and hypometabolism in key brain areas accurately and aid in distinguishing Alzheimer's Disease from normal aging and other dementia related diseases. Studies have shown how excess atrophy and hypometabolism in the median temporal lobe predict the decline from mild cognitive impairment to Alzheimer's disease. |
