The advent of modern mathematical and computational approaches to averaging imaging data across subjects has led to the generation of population-based probabilistic atlases. Such atlases are already in existence for the normal brain at different age ranges and for other regions of the body. Disease-based atlases may be useful for the differential diagnosis of human cerebral disorders.

The basic approach to generating such atlases is to obtain images from a large number of subjects (i.e., typically hundreds or even thousands) in a mathematical framework that produces a database that is probabilistic. Such an atlas allows the user to obtain relative information that takes into account the variance in structure and function in the human population (Fig. 12). Once established, such an atlas can interact with new data sets derived from individual subjects and patients or groups of subjects or patients. Thus, a clinician or investigator who performs an MRI scan of a single patient with focal epilepsy could call on a digital probabilistic atlas of normal subjects and compare the patient with the average normal atlas. The atlas will use the normal variance information estimated from the population of normals from which it is generated to determine whether a patient's scan falls within or outside normal morphometric limits. If the atlas is constructed from sufficient subjects, a subpopulation could be selected that more closely resembles a patient's demographic profile. In such a case, one might ask for only those normal subjects from the atlas who are right-handed, of a particular racial origin, and females ages 25-30. An increasing number of variables can be included in such a prior specification depending on the size of the data set constituting the atlas and the

Figure 12 Probabilistic atlases. Population-based probabilistic atlas of the normal human brain derived from 67 subjects, ages 20-40 years, seen from the lateral (A) or midsagittal (B) views. The structures have been segmented to show cortical regions at a 50% confidence limit in the population [courtesy of Alan Evans and colleagues. Montreal Neurologic Institute].

range of demographic information collected about the contributing subjects. As a result, it would become possible to detect subtle abnormalities of diagnostic importance that would not be identified by the less sensitive conventional approach of qualitatively examining two-dimensional image sets by eye. In addition, such an atlas-based approach will give an objective and quantifiable magnitude to any detected abnormality. The scan data from any patient can be added to an atlas database, increasing its value with regard to particular patient groups.

Disease-based atlases, thus generated, are currently being assessed. It is possible to imagine morphometric or functional atlases for Alzheimer's (Fig. 13) and

Parkinson's disease, schizophrenia, and other disorders. Such atlases would also provide a population and disease-based opportunity to examine the natural history of morphometric or functional abnormalities as a function of disease progression, age of onset, or other variables. Such atlases could also be used to identify changes in natural course as a function of therapeutic intervention. Consider, for example, a clinical trial with a new drug for Alzheimer's disease. The Alzheimer's disease population atlas would provide estimates of morphometric changes in focal atrophy as well as, for example, alterations in crerebral glucose metabolism as a function of disease progression. A population of patients at a certain stage of the disease could be divided into two groups, one given an experimental therapy and the other given placebo. Serial imaging of both groups with the appropriate techniques would then provide longitudinal imaging data. Comparisons of morphometric and metabolic changes as a function of time between the two groups would be undertaken to detect objective and quantitative differences between the two groups. Any differences would represent a measure of the effect of the therapeutic intervention on progressive atrophy or a- r/ -

Figure 13 Probabilistic population atlas derived from nine individuals with Alzheimer's disease. This atlas is presented as a set of two-dimensional orthogonal views plus a three-dimensional rendering (bottom right) and is produced using a continuum-mechanical approach. Note the influence of atrophy on the composite image demonstrating widening of the major fissures of the brain as well as sulci in the neocortex. Such disease-based population atlases will be useful not only in tracking the natural history of cerebral disorders but also in providing objective and quantifiable information about structural and functional changes associated with experimental therapy for these disorders (courtesy of Paul Thompson and colleagues. UCLA School of Medicine).

glucose metabolism due to the natural history of the disease. It is probable, although currently unproven, that such an approach will be more sensitive in detecting differences between control and experimental groups, thereby requiring either fewer subjects or shorter time frames for therapeutic assessment, thus resulting in lower costs of clinical trials.

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