Quantification of hypoxia in non-small cell lung cancer patients using [¹⁸F]HX4

Objectives Hypoxia in tumor tissue is associated with poor prognosis and increased resistance to therapy. [¹⁸F]HX4 is a promising new PET tracer, developed to identify hypoxic areas. The purpose of the present study was to develop a kinetic model for quantifying [¹⁸F]HX4 uptake.

Methods 14 non-small cell lung cancer patients were included. Following injection of 426±72 MBq [¹⁸F]HX4, each patient underwent 2 PET scans: a 30 min dynamic scan started at time of injection followed by a 30 min static scan at 2h p.i. Time activity curves (TAC) were derived from volumes of interest defined in tumor tissue, within multiple areas to account for uptake heterogeneity. TAC were analyzed using several standard single and two tissue compartment models with image derived input functions from the ascending aorta. Pharmacokinetic parameters obtained with the preferred model, as selected by Akaike Information Criterion, were then used to validate simplified measures obtained from the static scans. Effects of plasma [¹⁸F]HX4 metabolism on these results were evaluated using a population based metabolite correction extrapolated to 82% at 2h (1).

Results Best fits to [¹⁸F]HX4 tumor TAC were obtained using the reversible two tissue compartment model with blood volume fraction correction. Comparison of volumes of distribution (V_T) with simplified measures yielded best results for tumor-to-blood ratio (T/B; R²=0.96), followed by tumor-to-muscle ratio (T/M; R²=0.90) and standardized uptake value (SUV) normalized to body surface area (R²=0.78; R²=0.75 for SUV normalized to body weight). Metabolite correction of the input function increased all V_T values by approximately 14%. Yet, model preference remained unchanged.

Conclusions [¹⁸F]HX4 kinetics in tumor tissue during 2 hr p.i. can best be described by a reversible two tissue compartment model. T/B or T/M at 2h p.i. correlated strongly with V_T derived with full kinetic analysis. (1) Doss et al. Nucl Med Commun. 2010

Research Support Center for Translational Molecular Medicine (AIRFORCE).