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Updated: May 13, 2026

Determining Glucose Metabolism Kinetics Using 18F-FDG Micro-PET/CT
Published on: May 2, 2017
Dual time point based quantification of metabolic uptake rates in 18F-FDG PET
Jörg van den Hoff1, Frank Hofheinz, Liane Oehme
1PET Center, Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, 01328, Germany. j.van_den_hoff@hzdr.de.
Background:
Assessment of dual time point (DTP) positron emission tomography was carried out with the aim of a quantitative determination of Km, the metabolic uptake rate of [18F]fluorodeoxyglucose as a measure of glucose consumption.
Methods:
Starting from the Patlak equation, it is shown that Km≈mt/ca0+V̄r/τa, where mt is the secant slope of the tissue response function between the dual time point measurements centered at t = t0. ca0=ca(t0) denotes arterial tracer concentration, V̄r is an estimate of the Patlak intercept, and τa is the time constant of the ca(t) decrease. We compared the theoretical predictions with the observed relation between Ks=mt/ca0 and Km in a group of nine patients with liver metastases of colorectal cancer for which dynamic scans were available, and Km was derived from conventional Patlak analysis. Twenty-two lesion regions of interest (ROIs) were evaluated. ca(t) was determined from a three-dimensional ROI in the aorta. Furthermore, the correlation between Km 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 Vr of V̄r=0.53±0.08 ml/ml. The patient averaged τa was 99 ± 23 min. Linear regression between Patlak-derived Km and DTP-derived Ks according to Ks = b · Km + 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 a≈-V̄r/τa. Ks exhibits better correlation with Km than late SUV and retention index, respectively. Ks(c)=Ks+V̄r/τa is proposed as a quantitative estimator of Km which is independent of patient weight, scan time, and scanner calibration.
Conclusion:
Quantification of Km 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. Ks and Ks(c) exhibit improved stability and better correlation with the true Km. These properties might prove especially relevant in the context of radiation treatment planning and therapy response control.
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