Weiner, Michael W.

BackgroundThe promise of Alzheimer's disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer's disease and thus represents the most rational target for an initial effort at standardization.Methods and ResultsThe authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer's Disease Centers–Alzheimer's Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer's Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark.ConclusionsAlthough manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.

ObjectiveTo evaluate the degree to which longitudinal stability of subsyndromal symptoms of depression (SSD) is associated with conversion to dementia in patients with mild cognitive impairment (MCI).MethodsData from 405 MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were analyzed. Participants were evaluated at baseline and 12‐month intervals over 3 years. Participants were designated as MCI converters if dementia was diagnosed within 3 years or as cognitively stable MCI if dementia was not diagnosed during this interval. SSD were evaluated utilizing the 15‐item Geriatric Depression Scale (GDS). Endorsement of specific SSD at baseline and the stability of SSD over 36 months were compared between the two MCI groups.ResultsBaseline symptom endorsement and stability of total GDS scores did not differentiate MCI groups. Worsening of four individual items from the GDS over time (memory problems, feelings of helplessness, loss of interest, and preference for staying at home) differentiated MCI converters from cognitively stable MCI (p < 0.05 for all). However, only increased endorsement of memory symptoms over time was associated with progression to dementia after controlling for other clinical variables (p = 0.05).ConclusionsSSD in MCI participants largely consist of cognitive symptoms and activity limitations, and the stability of SSD over time differentiated the MCI groups better than baseline endorsement of symptoms. However, the only significant predictor of conversion to dementia was increased endorsement of memory problems, which likely represents insight into cognitive problems more than depressive symptomatology in MCI individuals. Copyright © 2011 John Wiley & Sons, Ltd.

The fourth Leon Thal Symposium (LTS2010) was convened in Toulouse, France, on November 3, 2010. This symposium reviewed design parameters that are necessary to develop comprehensive national databases on healthy aging. Such datasets offer the potential to serve as the foundation for a systems‐approach to solve the dual public health problems of: (1) early detection of people who are at elevated risk for Alzheimer's disease, and (2) the development of interventions to delay onset of, or prevent, late‐life dementia. The symposium considered three interrelated components of a National Database for Longitudinal Studies on Healthy Aging as follows: (a) a registry of healthy aging adults; (b) refined computer‐based assessments for data gathering, including assessments of behavioral/memory changes associated with aging that are appropriate for broad use in nonexpert settings; and (c) high performance computing/supercomputer‐based approaches for health data modeling and mining.