The purpose of this study was to delineate the differences in intratumoral uptake and tracer distribution of (62)Cu-diacetyl-bis(N(4)-methylthiosemicarbazone) ((62)Cu-ATSM), a well-known hypoxic imaging tracer, and (18)F-FDG in patients with lung cancer of pathohistologically different types.
Methods: Eight patients with squamous cell carcinoma (SCC) and 5 with adenocarcinoma underwent (62)Cu-ATSM and (18)F-FDG PET within a 1-wk interval. For (62)Cu-ATSM PET, 10-min static data acquisition was started at 10 min after a 370- to 740-MBq tracer injection. After image reconstruction, (62)Cu-ATSM and (18)F-FDG images were coregistered, and multiple small regions of interest were drawn on tumor lesions of the 2 images to obtain standardized uptake values (SUVs). The regression lines were determined between SUVs for (62)Cu-ATSM and (18)F-FDG in each tumor. The slope values were compared between SCC and adenocarcinoma to observe pathohistologic differences in intratumoral distribution of the tracers.
Results: SUVs for (62)Cu-ATSM were lower than those for (18)F-FDG in both SCC and adenocarcinoma. SCC tumors showed high (62)Cu-ATSM and low (18)F-FDG uptakes in the peripheral region of tumors but low (62)Cu-ATSM and high (18)F-FDG uptakes toward the center (spatial mismatching). The relationship of SUVs for the 2 tracers was negatively correlated with a mean regression slope of -0.07 +/- 0.05. On the other hand, adenocarcinoma tumors had a spatially similar distribution of (62)Cu-ATSM and (18)F-FDG, with positive regression slopes averaging 0.24 +/- 0.13. The regression slopes for (62)Cu-ATSM and (18)F-FDG differed significantly between SCC and adenocarcinoma (P < 0.001).
Conclusion: The intratumoral distribution patterns of (62)Cu-ATSM and (18)F-FDG were different between SCC and adenocarcinoma in lung cancers, indicating that intratumoral regions of high glucose metabolism and hypoxia could differ with the pathohistologic type of lung cancer. The identification of regional biologic characteristics in tumors such as hypoxia, energy metabolism, and proliferation could play a significant role in the clinical diagnosis and therapy planning for non-small cell lung cancer patients.