The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's disease. Magnetic resonance imaging (MRI), (18F)-fluorodeoxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross-linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was

MCI and AD patients had less medial temporal lobe activation on the memory task than the normal subjects but similar activation as normal subjects on the sensory task. These findings suggest decreased medial temporal activation may be a specific marker of limbic dysfunction due to the neurodegenerative changes of AD. In addition, fMRI is sufficiently sensitive to detect changes in the prodromal, MCI, phase of the disease.

We developed a 3D spherical navigator (SNAV) echo technique that can measure rigid body motion in all six degrees of freedom simultaneously by sampling a spherical shell in k-space. 3D rotations of an imaged object simply rotate the data on this shell and can be detected by registration of k-space magnitude values. 3D translations add phase shifts to the data on the shell and can be detected with a weighted least-squares fit to the phase differences at corresponding points. MRI pulse sequences were developed to study k-space sampling strategies on such a shell. Data collected with a computer-controlled motion phantom with known rotational and translational motions were used to evaluate the technique. The accuracy and precision of the technique depend on the sampling density. Roughly 2000 sample points were necessary for accurate detection to within the error limits of the motion phantom when using a prototype time-intensive sampling method. This number of samples can be captured