Metabolic Cerebral Imaging in Incipient Dementia (MCI-ID)

People experiencing mild cognitive changes represent an epidemiologically major segment of the geriatric patient population. In the present proposal, we aim to measure how knowledge of cerebral metabolic information 1) influences working diagnoses and management of patients being evaluated for symptoms of early cognitive decline, and 2) impacts upon long-term clinical outcomes, particularly of subjects having metabolic patterns consistent with presence of Alzheimer's disease (AD)-like changes in their brains. A total of 710 patients suffering from documentable decline of cognitive function in the absence of overt dementia will be studied at nine U.S. institutions with extensive experience and infrastructure in place for the evaluation of Alzheimer's disease and related disorders, and for neuroimaging. In this prospective, investigation, subjects will undergo baseline neuropsychologic testing and neuroimaging with MRI and FDGPET. PET scan reports will be sealed and randomized with respect to whether they are released to patients' managing physicians at the time of interpretation, or two years after the time that scanning is performed. Working diagnoses of managing physicians will be recorded, as will the treatment decisions made by the managing physicians and their patients. Cognitive abilities, functional status, utilization of healthcare resources, and other clinical and social contact parameters will be assessed every six months. Our major hypotheses are that among patients whose PET results are immediately conveyed to their referring physicians, diagnoses and management plans will be positively affected, leading to more effective utilization of healthcare resources and to maintenance of cognitive and functional abilities at a higher level. This project will also provide a rich source of data that can be used to address questions outside of its major focus (e.g., prognostic accuracy of volumetric MRI data used instead of, or in conjunction with, FDG-PET data; incremental predictive value of applying statistically parameterizing and/or quantifying software tools to imaging data).