The Alzheimer's Disease Cooperative Study (ADCS) has an established organizational infrastructure to conduct large scale clinical trials in Alzheimer's disease (AD) in the academic setting. Over the 19 years since its inception, the ADCS has completed multiple seminal AD studies by coordinating clinical trial activity across more than 80 participant sites. By the end of 2011, recent ADCS trials will have collected nearly 3000 brain magnetic resonance imaging (MRI) and positron emission tomography (PET) scans. The Biomedical Informatics Research Network (BIRN) provides an ideal resource for sharing ADCS clinical and brain imaging data with the broader research community. The primary goal of the proposed work is to use BIRN tools to analyze and share cross-sectional and longitudinal brain imaging data from prior and ongoing ADCS clinical trials. To achieve this goal, the investigators will 1) Assemble clinical and brain imaging data using BIRN tools and procedures for quality assurance and de-identification. 2) Provide regional volumetric brain imaging data using BIRN tools for cross-sectional volumetry, cortical parcellation, and cortical thickness measurements, combined with MRI-PET registration for quantification of regional metabolic activity when PET imaging data is available. 3) Provide measurements of regional atrophy using longitudinal brain imaging data and a novel procedure to quantify subregional volumetric change over time. 4) Provide data modeling and links between data objects with adherence to existing ontologies. 5) Share all raw and processed brain images as well as linked volumetric, metabolic, and clinical data using BIRN infrastructure. The project leverages the existing infrastructure and expertise assembled at the University of California, San Diego for large scale AD clinical trials and for large scale analyses of brain imaging data. Nevertheless, the richness of the dataset is far too great for researchers at a single university to fully exploit, and the importance of the data calls for collaboration across universities that the BIRN infrastructure enables. In summary, the proposed work will make a valuable dataset accessible to researchers otherwise unable to study this topic on such a scale, and will facilitate collaborative research likely to greatly advance knowledge about the structural and functional consequences of AD on the brain.
The proposed work will assemble, analyze, and share ADCS clinical and brain imaging data using BIRN infrastructure and tools. These large datasets, which were collected through multi-site clinical trials of AD, are unique and of great value to researchers investigating the effects of AD on the brain. Thus the proposed work will advance individual and collaborative studies of AD.
| Galasko, Douglas R; Shaw, Leslie M (2017) Alzheimer disease: CSF biomarkers for Alzheimer disease - approaching consensus. Nat Rev Neurol 13:131-132 |
| Yu, Peng; Sun, Jia; Wolz, Robin et al. (2014) Operationalizing hippocampal volume as an enrichment biomarker for amnestic mild cognitive impairment trials: effect of algorithm, test-retest variability, and cut point on trial cost, duration, and sample size. Neurobiol Aging 35:808-18 |
| Desikan, R S; Rafii, M S; Brewer, J B et al. (2013) An expanded role for neuroimaging in the evaluation of memory impairment. AJNR Am J Neuroradiol 34:2075-82 |
| McEvoy, Linda K; Brewer, James B (2012) Biomarkers for the clinical evaluation of the cognitively impaired elderly: amyloid is not enough. Imaging Med 4:343-357 |
| Seibert, Tyler M; Murphy, Elizabeth A; Kaestner, Erik J et al. (2012) Interregional correlations in Parkinson disease and Parkinson-related dementia with resting functional MR imaging. Radiology 263:226-34 |
