PI's: Prof. Dr. Stefan Kramer, Prof. Dr. Alexander Drzezga
PhD Candidate: Rui Li, M.Sc.

Neuroimaging techniques such as [18F]-fluoro-2-deoxy-glucose ([18F]-FDG) positron emission tomography (PET) for the assessment of cerebral glucose metabolism are widely applied in the diagnosis and research of dementing disorders such as Alzheimer´s disease (AD). The understanding of associations between basic pathomechanisms and their clinical expression as dementia is of major interest. Usually, subsets of patients are pre-defined on the basis of clinical data and correlations between clinical and neuroimaging findings are subsequently identified according to a priori hypotheses. However, important associations remain undiscovered because of these constraints. The present project therefore takes the opposite approach, starting with the imaging data to identify clusters of distinctive imaging patterns and generating subgroups of patients according to their affiliation to these clusters. Subsequently, differences and commonalities between these clusters are addressed in terms of non-imaging variables, such as demographic variables and psychometric test results. Hence, more complete descriptions of interesting subgroups will be obtained. To achieve this goal, data-mining and clustering algorithms will be applied to whole brain scans for the first time in a close collaboration of the relevant institutions. The project is based at the Institute for Informatics at TUM.