Consolidation of common parameters from multiple fits in dynamic PET data analysis.
In dynamic positron emission tomography (PET) data analysis, regions of interest (ROI's) are analyzed by fitting a parametric model to the time-activity curve acquired after a radio-labeled tracer has been introduced into the patient's bloodstream. This procedure can be carried out for multiple ROI's and/or multiple injections of the same or a different radiopharmaceutical. The approach presented here takes advantage of prior knowledge that some of the parameters of those multiple fits are the same. Reduction of the total number of parameters to be estimated results in smaller statistical uncertainty for all parameter estimates, especially those common to multiple fits.
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D000465:Algorithms; D000818:Animals; D016477:Artifacts; D001921:Brain / Q000000981:diagnostic imaging / Q000378:metabolism; D005947:Glucose / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016013:Likelihood Functions; D008954:Models, Biological; D015233:Models, Statistical; D015635:Radionuclide Ventriculography; D019275:Radiopharmaceuticals / Q000008:administration & dosage / Q000097:blood; D013997:Time Factors; D014055:Tomography, Emission-Computed
D019275:Radiopharmaceuticals; D005947:Glucose