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: | Hongyu Yuan |
| Institution: | Wake Forest schoold of medicine |
| Department: | radiology |
| Country: | |
| Proposed Analysis: | ADNI data collection: To download images for more than 1,000 subjects with multiple MRI scans from the baseline to 4-year follow-up, we recruited four works-study students who are supported by the Federal Government Program. For each student, four different cognitive groups (cognitively normal, early mild cognitive impairment, late cognitive impairment, and Alzheimer's disease) were assigned. Each student has their own ADNI account and they have been collecting longitudinal MRI (T1w) and amyloid PET images, and performing quality control (missing time point, imaging resolution, motion artifact). • Network data storage and computing cluster setup: With institutional support, 30 TB high-speed network storage was allocated to share downloaded ADNI data and processed images. • Automated image processing pipeline development: To process the large ADNI longitudinal dataset, The ADNI Processing Pipeline is implemented in Amazon Web Service using Python programming language, leveraging the Nipype package. We have completed MRI processing for all ADNI Cognitively Normal (CN) and Early MCI participants. Currently, we are working on correlation analyses between imaging measures and neuropsychological assessments. • IRB Application: A new IRB application dedicated to ADNI data analysis has been submitted to extend the current research to the institutional ADNI Service Platform. |
| Additional Investigators |
