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Critical to development of new therapies for Alzheimer's disease (AD) is the ability to detect clinical or pathological change over time. Clinical outcome measures typically used in therapeutic trials have unfortunately proven to be relatively variable and somewhat insensitive to change in this slowly progressive disease. For this reason, development of surrogate biomarkers that identify significant disease-associated brain changes are necessary to expedite treatment development in AD. Since AD pathology is present in the brain many years prior to clinical manifestation, ideally we want to develop biomarkers of disease that identify abnormal brain structure or function even prior to cognitive decline. Magnetic resonance imaging, fluorodeoxyglucose positron emission tomography, new amyloid imaging techniques, and spinal fluid markers of AD all have great potential to provide surrogate endpoint measures for AD pathology. The Alzheimer's disease neuroimaging initiative (ADNI) was developed for the distinct purpose of evaluating surrogate biomarkers for drug development in AD. Recent evidence from ADNI demonstrates that imaging may provide more sensitive, and earlier, measures of disease progression than traditional clinical measures for powering clinical drug trials in Alzheimer's disease. This review discusses recently presented data from the ADNI dataset, and the importance of imaging in the future of drug development in AD.

Current research supports the strong potential of structural MRI profiles, even within cross-sectional designs, as a promising method for the discrimination of Alzheimer's Disease (AD) from normal controls and for the prediction of Mild Cognitive Impairment (MCI) progression and conversion to AD. Findings suggest that measures of structural change in mesial and lateral temporal, cingulate, parietal and midfrontal areas may facilitate the assessment of a treatment's ability to halt the progressive structural loss that accompanies clinical decline in MCI. The performance of prediction is likely to continue to improve with the incorporation of measures from other neuroimaging modalities, clinical assessments, and neuromedical biomarkers, as the regional profile of individuals at risk for progression is refined.