Purpose: To compare a dedicated simulation model for hypoxia PET against tumor microsections stained for different parameters of the tumor microenvironment. The model can readily be adapted to a variety of conditions, such as different human head and neck squamous cell carcinoma (HNSCC) xenograft tumors. Methods: Nine different HNSCC tumor models were transplanted subcutaneously into nude mice. Tumors were excised and immunoflourescently labeled with pimonidazole, Hoechst 33342, and CD31, providing information on hypoxia, perfusion, and vessel distribution, respectively. Hoechst and CD31 images were used to generate maps of perfused blood vessels on which tissue oxygenation and the accumulation of the hypoxia tracer FMISO were mathematically simulated. The model includes a Michaelis-Menten relation to describe the oxygen consumption inside tissue. The maximum oxygen consumption rate M-0 was chosen as the parameter for a tumor-specific optimization as it strongly influences tracer distribution. M-0 was optimized on each tumor slice to reach optimum correlations between FMISO concentration 4 h postinjection and pimonidazole staining intensity. Results: After optimization, high pixel-based correlations up to R-2 = 0.85 were found for individual tissue sections. Experimental pimonidazole images and FMISO simulations showed good visual agreement, confirming the validity of the approach. Median correlations per tumor model varied significantly (p <0.05), with R-2 ranging from 0.20 to 0.54. The optimum maximum oxygen consumption rate M-0 differed significantly (p <0.05) between tumor models, ranging from 2.4 to 5.2 mm Hg/s. Conclusions: It is feasible to simulate FMISO distributions that match the pimonidazole retention patterns observed in vivo. Good agreement was obtained for multiple tumor models by optimizing the oxygen consumption rate, M-0, whose optimum value differed significantly between tumor models.
- PET imaging
- mathematical simulation