Abstract
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Objectives To determine (i) the 64CuATSM pharmacokinetics by dynamic PET imaging and (ii) the microdistribution by digital autoradiography in a head & neck tumor model FaDu.
Methods Eight FaDu tumor xenografts of 20 ± 4 mm were grown in nude rats. PET imaging determined venous input functions, and time-activity in tissue. Influx constant (Ki) and distribution volume (Vd) were calculated for tumors and healthy muscle. 64CuATSM autoradiographs at early (1 h) and late (>18 h) times post-injection were compared to immunohistochemical markers for hypoxia (Pimonidazole) and perfusion (Hoechst 33342).
Results Estimated Ki was 3.1x10-2 min-1 for tumor and 3.9x10-3 min-1 for muscle, a 12 fold difference. The tumor-to-muscle ratio of Vd was 4.6 ± 0.2 (p = 0.0002), while effective washout rates were indistinguishable (p = 0.06). Mean PET signal (PETmean) in muscle stayed constant (p >> 0.01) beyond 20 min post-injection. However, PETmean in tumors only reached pseudo steady state. At 20 min, tumor PETmean were 4.7 ± 0.2 times muscle, increasing to 5.2 ± 0.4 at 80 min, and 12.2 ± 0.8 by 18 h. Yet, the spatial distributions between PET image voxels appeared unchanged (Pearson’s r > 0.6). No significant trends emerged between 64CuATSM and Pimonidazole staining intensity. Bimodal behavior was observed at early times. Linear trends were found in late images, but varied from positive to negative correlation even among multiple cross-sections of the same tumor. 64CuATSM was co-distributed with Hoechst 33342 at 1 h.
Conclusions 64CuATSM PET distributions were unchanged after 20 min, yet tumor-to-muscle ratios continually increased even at 18 h. The oxygen partial pressures at which 64CuATSM and Pimonidazole are reduced and bound in cells are theorized to be distinct and separable. However, microscopic imaging has shown random relationships between distributions of Pimonidazole and accumulation of 64CuATSM in this head & neck tumor model. 64CuATSM uptake demonstrated clear tumor targeting, but was unable to discern between different microenvironmental sub-regions.
Research Support NIH grant P01 CA11567