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C]Thymidine (TdR), a PET tracer for cellular proliferation, may be advantageous for monitoring brain tumor progression and response to therapy. Kinetic analysis of dynamic TdR images was performed to estimate the rate of thymidine transport (K1t) and thymidine flux ( KTdR) into brain tumors and normal brain. These estimates were compared to MRI and pathologic results. Methods: Twenty patients underwent sequential [ 11 C]CO2 (major TdR metabolite) and TdR PET studies with arterial blood sampling and metabolite analysis. The data were fitted using the five-compartment model described in the companion article. Results: Comparison of model estimates with clinical and pathologic data shows that K1t is higher for MRI contrast enhancing tumors ( p < .001), and KTdR increases with tumor grade ( p < .02). On average, TdR retention was lower after treatment in high-grade tumors. The model was able to distinguish between increased thymidine transport due to blood‐ brain barrier breakdown and increased tracer retention associated with tumor cell proliferation. Conclusion: Initial analysis of model estimates of thymidine retention and transport show good agreement with the clinical and pathological features of a wide range of brain tumors. Ongoing studies will evaluate its role in measuring response to treatment and predicting outcome. Mol Imaging (2002) 1, 145‐150.

UNLABELLED 2-[11C]Thymidine (TdR), a PET tracer for cellular proliferation, may be advantageous for monitoring brain tumor progression and response to therapy. We previously described and validated a five-compartment model for thymidine incorporation into DNA in somatic tissues, but the effect of the blood-brain barrier on the transport of TdR and its metabolites necessitated further validation before it could be applied to brain tumors. METHODS We investigated the behavior of the model under conditions experienced in the normal brain and brain tumors, performed sensitivity and identifiability analysis to determine the ability of the model to estirmine whether it can distinguish between thymidine transport and retention. RESULTS Sensitivity and identifiability analysis suggested that the non-CO2 metabolite parameters could be fixed without significantly affecting thymidine parameter estimation. Simulations showed that K1t and KTdR could be estimated accurately (r = .97 and .98 for estimated vs. true parameters) with standard errors < 15%. The model was able to separate increased transport from increased retention associated with tumor proliferation. CONCLUSION Our model adequately describes normal brain and brain tumor kinetics for thymidine and its metabolites, and it can provide an estimate of the rate of cellular proliferation in brain tumors.

Accurate quantitation of local glucose metabolic rates (LMRglc) of abnormal tissues such as brain tumors with the 2-deoxyglucose (DG) method requires knowledge of the tissue rate constants and lumped constant. The deoxyglucose rate constants were measured in an experimental intracerebral glioma in 24 awake rats with a dual tracer [(3H)-DG and (14C)-DG] method. Tissue time points were obtained at 2, 5, 10, 18, 30, 60, 90, and 180 min after injection by decapitation and liquid scintillation counting. Blood samples were obtained at 1 min intervals initially and at longer intervals later. The rate constants were estimated with parameter estimation. LMRglc was calculated from the rate constants, assuming a lumped constant of 0.5. K1for normal cerebrum was found to be 0.258 ml/g/min, and k2– k4were 0.406, 0.075, and 0.0103 min−1; LMRglc = 65.1 μ;mol/100 g/min. The corresponding values for the glioma were 0.108, 0.126, 0.040, and 0.0019 with LMRglc = 41.7. The considerably lower k4in the glioma was reflected in persistent higher activity in the glioma at longer times. Thus, tissue activity alone cannot be used to assess relative glucose metabolic rates in abnormal tissues such as gliomas, particularly at late times after injection.