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Most radiotracers used in dynamic positron emission tomography (PET) scanningact in a linear time-invariant fashion so that the measured time-course dataare a convolution between the time course of the tracer in the arterial supplyand the local tissue impulse response, known as the tissue residue function. Instatistical terms the residue is a life table for the transit time of injectedradiotracer atoms. The residue provides a description of the tracer kineticinformation measurable by a dynamic PET scan. Decomposition of the residuefunction allows separation of rapid vascular kinetics from slower blood-tissueexchanges and tissue retention. For voxel-level analysis, we propose thatresidues be modeled by mixtures of nonparametrically derived basis residuesobtained by segmentation of the full data volume. Spatial and temporal aspectsof diagnostics associated with voxel-level model fitting are emphasized.Illustrative examples, some involving cancer imaging studies, are presented.Data from cerebral PET scanning with $^{18}$F fluoro-deoxyglucose (FDG) and$^{15}$O water (H2O) in normal subjects is used to evaluate the approach.Cross-validation is used to make regional comparisons between residuesestimated using adaptive mixture models with more conventional compartmentalmodeling techniques. Simulations studies are used to theoretically examine meansquare error performance and to explore the benefit of voxel-level analysiswhen the primary interest is a statistical summary of regional kinetics. Thework highlights the contribution that multivariate analysis tools andlife-table concepts can make in the recovery of local metabolic informationfrom dynamic PET studies, particularly ones in which the assumptions ofcompartmental-like models, with residues that are sums of exponentials, mightnot be certain.

Voxel-level mapping of tracer kinetics in PET studies: A statistical approach emphasizing tissue life tables