Determination of a pharmacokinetic model for [11C]-acetate in brown adipose tissue.

BACKGROUND: [11C]-acetate positron emission tomography is used to assess oxidative metabolism in various tissues including the heart, tumor, and brown adipose tissue. For brown adipose tissue, a monoexponential decay model is commonly employed. However, no systematic assessment of kinetic models has been performed to validate this model or others. The monoexponential decay model and various compartmental models were applied to data obtained before and during brown adipose tissue activation by cold exposure in healthy men. Quality of fit was assessed visually and by analysis of residuals, including the Akaike information criterion. Stability and accuracy of compartmental models were further assessed through simulations, along with sensitivity and identifiability of kinetic parameters. RESULTS: Differences were noted in the arterial input function between the warm and cold conditions. These differences are not taken into account by the monoexponential decay model. They are accounted for by compartmental models, but most models proved too complex to be stable. Two and three-tissue models with no more than four distinct kinetic parameters, including blood volume fraction, provided the best compromise between fit quality and stability/accuracy. CONCLUSION: For healthy men, a three-tissue model with four kinetic parameters, similar to a heart [11C]-palmitate model seems the most appropriate based on model stability and its ability to describe the main [11C]-acetate pathways in BAT cells. Further studies are required to validate this model in women and people with metabolic disorders.

Determination of an Optimal Pharmacokinetic Model of 18F-FET for Quantitative Applications in Rat Brain Tumors.

O-(2-18F-fluoroethyl)-l-tyrosine (18F-FET) is a radiolabeled artificial amino acid used in PET for tumor delineation and grading. The present study compares different kinetic models to determine which are more appropriate for 18F-FET in rats. Methods: Rats were implanted with F98 glioblastoma cells in the right hemisphere and scanned 9-15 d later. PET data were acquired during 50 min after a 1-min bolus of 18F-FET. Arterial blood samples were drawn for arterial input function determination. Two compartmental pharmacokinetic models were tested: the 2-tissue model and the 1-tissue model. Their performance at fitting concentration curves from regions of interest was evaluated using the Akaike information criterion, F test, and residual plots. Graphical models were assessed qualitatively. Results: Metrics indicated that the 2-tissue model was superior to the 1-tissue model for the current dataset. The 2-tissue model allowed adequate decoupling of 18F-FET perfusion and internalization by cells in the different regions of interest. Of the 2 graphical models tested, the Patlak plot provided adequate results for the tumor and brain, whereas the Logan plot was appropriate for muscles. Conclusion: The 2-tissue-compartment model is appropriate to quantify the perfusion and internalization of 18F-FET by cells in various tissues of the rat, whereas graphical models provide a global measure of uptake.

PET Metabolic Biomarkers for Cancer.

The body's main fuel sources are fats, carbohydrates (glucose), proteins, and ketone bodies. It is well known that an important hallmark of cancer cells is the overconsumption of glucose. Positron emission tomography (PET) imaging using the glucose analog (18)F-fluorodeoxyglucose ((18)F-FDG) has been a powerful cancer diagnostic tool for many decades. Apart from surgery, chemotherapy and radiotherapy represent the two main domains for cancer therapy, targeting tumor proliferation, cell division, and DNA replication-all processes that require a large amount of energy. Currently, in vivo clinical imaging of metabolism is performed almost exclusively using PET radiotracers that assess oxygen consumption and mechanisms of energy substrate consumption. This paper reviews the utility of PET imaging biomarkers for the detection of cancer proliferation, vascularization, metabolism, treatment response, and follow-up after radiation therapy, chemotherapy, and chemotherapy-related side effects.