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: | Farooq Kamal |
| Institution: | National Research Council |
| Department: | Medical Devices |
| Country: | |
| Proposed Analysis: | Cerebrovascular disease has been indicated as the starting point of a sequence of events leading to Alzheimer’s Disease (AD), neurodegeneration, and cognitive loss in aging research. Risk factors for AD can include diabetes, hypertension, dyslipidemia, and lifestyle. It's still unclear if vascular lesions have a role in the formation of AD or whether their presence can reduce the amount of AD pathology required to cause clinical signs of dementia. Estimating the role of cerebrovascular illness in cognitive decline is critical for understanding dementia's pathophysiology. White matter hyperintensities (WMH) assessed with magnetic resonance imaging (MRI), are typically used to examine cerebrovascular problems in healthy older adults and older adults with cognitive decline. WMH volume is linked to the likelihood and progression of clinical AD, as well as cognitive deterioration in AD. Most research has examined total WMH load, with less research on regional differences in WMH being examined in the older adult population. Regional differences in WMHs and their associations with specific cognitive functions are also unclear. Using structural MR images, we will segment the WMHs and obtain regional estimates of WMH burden across each brain lobe and hemisphere, as well as in different vascular territories. We will use linear mixed-effects modeling and machine learning, to combine cerebrovascular lifestyle risk factors, MRI features (e.g., cortical thickness, white matter hyperintensities), cognitive scores, and demographic and clinical information (sex, age, education, APOE status, and amyloid status) to build AD predictive models. |
| Additional Investigators | |
| Investigator's Name: | Mahsa Dadar |
| Proposed Analysis: | Cerebrovascular disease has been indicated as the starting point of a sequence of events leading to Alzheimer’s Disease (AD), neurodegeneration, and cognitive loss in aging research. Risk factors for AD can include diabetes, hypertension, dyslipidemia, and lifestyle. It's still unclear if vascular lesions have a role in the formation of AD or whether their presence can reduce the amount of AD pathology required to cause clinical signs of dementia. Estimating the role of cerebrovascular illness in cognitive decline is critical for understanding dementia's pathophysiology. White matter hyperintensities (WMH) assessed with magnetic resonance imaging (MRI), are typically used to examine cerebrovascular problems in healthy older adults and older adults with cognitive decline. WMH volume is linked to the likelihood and progression of clinical AD, as well as cognitive deterioration in AD. Most research has examined total WMH load, with less research on regional differences in WMH being examined in the older adult population. Regional differences in WMHs and their associations with specific cognitive functions are also unclear. Using structural MR images, we will segment the WMHs and obtain regional estimates of WMH burden across each brain lobe and hemisphere, as well as in different vascular territories. We will use linear mixed-effects modeling and machine learning, to combine cerebrovascular lifestyle risk factors, MRI features (e.g., cortical thickness, white matter hyperintensities), cognitive scores, and demographic and clinical information (sex, age, education, APOE status, and amyloid status) to build AD predictive models. |
