Dual time point based quantification of metabolic uptake rates in (18)F-FDG PET

BACKGROUND: Assessment of dual time point (DTP) positron emission tomography was carried out with the aim of a quantitative determination of K(m), the metabolic uptake rate of [(18)F]fluorodeoxyglucose as a measure of glucose consumption. METHODS: Starting from the Patlak equation, it is shown that [Formula: see text] , where m(t) is the secant slope of the tissue response function between the dual time point measurements centered at t = t(0). [Formula: see text] denotes arterial tracer concentration, [Formula: see text] is an estimate of the Patlak intercept, and τ(a) is the time constant of the c(a)(t) decrease. We compared the theoretical predictions with the observed relation between [Formula: see text] and K(m) in a group of nine patients with liver metastases of colorectal cancer for which dynamic scans were available, and K(m) was derived from conventional Patlak analysis. Twenty-two lesion regions of interest (ROIs) were evaluated. c(a)(t) was determined from a three-dimensional ROI in the aorta. Furthermore, the correlation between K(m) and late standard uptake value (SUV) as well as retention index was investigated. Additionally, feasibility of the approach was demonstrated in a whole-body investigation. RESULTS: Patlak analysis yielded a mean V(r) of [Formula: see text] ml/ml. The patient averaged τ(a) was 99 ± 23 min. Linear regression between Patlak-derived K(m) and DTP-derived K(s) according to K(s) = b · K(m) + a yielded b = 0.98 ± 0.05 and a = -0.0054 ± 0.0013 ml/min/ml (r = 0.98) in full accordance with the theoretical predictions b = 1 and [Formula: see text]. K(s) exhibits better correlation with K(m) than late SUV and retention index, respectively. [Formula: see text] is proposed as a quantitative estimator of K(m) which is independent of patient weight, scan time, and scanner calibration. CONCLUSION: Quantification of K(m) from dual time point measurements compatible with clinical routine is feasible. The proposed approach eliminates the issues of static SUV and conventional DTP imaging regarding influence of chosen scanning times and inter-study variability of the input function. K(s) and [Formula: see text] exhibit improved stability and better correlation with the true K(m). These properties might prove especially relevant in the context of radiation treatment planning and therapy response control.