optimizing injected dose in clinical pet by accurately modeling the countingrate response functions specific to individual patient scans unlabelled to optimize the injected dose of radiopharmaceutical in pet one needs to know its relationship to some metric of data quality for individual patient scans such as noiseequivalent counting rate necr in this paper we show how one may accurately model the clinical necr response corresponding to specific patient scans much as if a countingrate test had been performed on each patient we apply this technique to patient data and show how it can lead to improved clinical scanning protocolsmethods true and random coincidence rates expressed as functions of an appropriate measurable system parameter such as the detector singleevent rate have functional forms that are largely independent of the object being scanned thus reference true and random response functions may be scaled directly to the specific counting rates measured on a clinical scan thereby yielding a curve of necr versus injected dose we have applied this technique to 2 groups of 163 clinical 18ffdg scans each one of the groups was obtained on a lutetium oxyorthosilicate petct scanner with conventional frontend electronics and the other was obtained on a lutetium oxyorthosilicate petct scanner with a new digital data processing system pico3dresults at 9095 of maximum signaltonoise ratio snr the mean optimal dose for a 60min uptake period ranged from 366 to 717 mbq depending on the electronics and randoms processing method there was only a slight 1 mbqkg dependence of optimal dose on patient weight but a larger dependence on position in the body pico3d electronics improved optimal data snr by 35 for a 70kg person but in both cases necr fell rapidly with increasing weight 14kg for an equivalent data snr a 120kg person would have to be scanned 23 times longer than a 60kg person over this range of weight the mean scatter fraction increased by 12 whereas the ratio of mean randoms to trues increased by 48conclusion the methodology developed here allows one to directly estimate the optimal dose to inject for specific clinical scans and permits a detailed analysis of the sources of noise in pet data and of their variation with parameters such as patient weight