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Positron Emission Tomography using 2-[18F]-2deoxy-D-glucose as radiotracer(FDG-PET) is currently one of the most frequently applied functional imagingmethods in clinical applications. The interpretation of FDG-PET data requiressophisticated mathematical approaches able to exploit the dynamical informationcontained in this kind of data. Most of these approaches are formulated withinthe framework of compartmental analysis, which connects the experimentalnuclear data with unknown tracer coefficients measuring the effectiveness ofthe tracer metabolism by means of Cauchy systems of ordinary differentialequations. This paper provides a coincise overview of linear compartmentalmethods, focusing on the analytical solution of the forward compartmentalproblem and on the specific issues concerning the corresponding compartmentalinverse problem.

Mathematical modelling of nuclear medicine data