Relevance of magnetic resonance imaging for early detection and diagnosis of Alzheimer disease

Hippocampus volumetry currently is the best-established imaging biomarker for AD. However, the effect of multicenter acquisition on measurements of hippocampus volume needs to be explicitly considered when it is applied in large clinical trials, for example by using mixed-effects models to take the clustering of data within centers into account. The marker needs further validation in respect of the underlying neurobiological substrate and potential confounds such as vascular disease, inflammation, hydrocephalus, and alcoholism, and with regard to clinical outcomes such as cognition but also to demographic and socioeconomic outcomes such as mortality and institutionalization. The use of hippocampus volumetry for risk stratification of predementia study samples will further increase with the availability of automated measurement approaches. An important step in this respect will be the development of a standard hippocampus tracing protocol that harmonizes the large range of presently available manual protocols. In the near future, regionally differentiated automated methods will become available together with an appropriate statistical model, such as multivariate analysis of deformation fields, or techniques such as cortical-thickness measurements that yield a meaningful metrics for the detection of treatment effects. More advanced imaging protocols, including DTI, DSI, and functional MRI, are presently being used in monocenter and first multicenter studies. In the future these techniques will be relevant for the risk stratification in phase IIa type studies (small proof-of-concept trials). By contrast, the application of the broader established structural imaging biomarkers, such as hippocampus volume, for risk stratification and as surrogate end point is already today part of many clinical trial protocols. However, clinical care will also be affected by these new technologies. Radiologic expert centers already offer “dementia screening” for well-off middle-aged people who undergo an MRI scan with subsequent automated, typically VBM-based analysis, and determination of z-score deviation from a matched control cohort. Next-generation scanner software will likely include radiologic expert systems for automated segmentation, deformation-based morphometry, and multivariate analysis of anatomic MRI scans for the detection of a typical AD pattern. As these developments will start to change medical practice, first for selected subject groups that can afford this type of screening but later eventually also for other cohorts, clinicians must become aware of the potentials and limitations of these technologies. It is decidedly unclear to date how a middle-aged cognitively intact subject with a seemingly AD-positive MRI scan should be clinically advised. There is no evidence for individual risk prediction and even less for specific treatments. Thus, the development of preclinical diagnostic imaging poses not only technical but also ethical problems that must be critically discussed on the basis of profound knowledge. From a neurobiological point of view, the main determinants of cognitive impairment in AD are the density of synapses and neurons in distributed cortical and subcortical networks. MRI-based measures of regional gray matter volume and associated multivariate analysis techniques of regional interactions of gray matter densities provide insight into the onset and temporal dynamics of cortical atrophy as a close proxy for regional neuronal loss and a basis of functional impairment in specific neuronal networks. From the clinical point of view, clinicians must bear in mind that patients do not suffer from hippocampus atrophy or disconnection but from memory impairment, and that dementia screening in asymptomatic subjects should not be used outside of clinical studies.