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: | Bradley Hooker |
| Institution: | AbbVie |
| Department: | Translational Imaging |
| Country: | |
| Proposed Analysis: | Cognitive impairment in patients with Alzheimer’s disease (AD) is associated with brain atrophy including reduction in hippocampal volume in magnetic resonance imaging (MRI). It is unknown if changes in brain texture precede changes in volume. Machine learning will be used to predict those patients which are more likely to covert from mild cognitive impairment (MCI) to AD by texture-based analysis of T1W MRI scans from the ADNI database. Additionally, identifying patients likely to develop AD and respond to therapy is critical for clinical study design. Neurofibrillary tangle accumulation consisting of phosphorylated tau is a principal component of AD pathology. Machine learning will be used to stratify patients with a high probability to develop AD and respond to therapy based upon modeling longitudinal tau PET data. |
| Additional Investigators |
