Purpose: To generate parametric images of tumor hypoxia in a tumor-bearing rat model using voxel-based compartmental analysis of dynamic fluorine-18 labeled misonidazole (18F-FMISO) microPET? images, and to compare th...Purpose: To generate parametric images of tumor hypoxia in a tumor-bearing rat model using voxel-based compartmental analysis of dynamic fluorine-18 labeled misonidazole (18F-FMISO) microPET? images, and to compare the parametric images thus derived with static “late” 18F-FMISO microPET? images for the detection of tumor hypoxia. Materials and Methods: Nude rats bearing HT-29 colorectal carcinoma xenografts (≈1.5 - 2 cm in diameter) in the right hind limb were positioned in a custom-fabricated, animal-specific foam mold. Animals were injected via the tail vein with ≈55.5 MBq 18F-FMISO and continuously imaged for either 60 or 120 minutes, with additional late static images up to 3 hour post-injection. The raw list-mode data was reconstructed into 37 - 64 frames with earlier frames of shorter time durations (12 - 15 seconds) and later frames of longer durations (up to 300 seconds). Time activity curves (TACs) were generated over regions encompassing the tumor as well as an artery, the latter for use as an input function. A beta version of a compartmental modeling package (BioGuide?, Philips Healthcare) was used to generate parametric images of k3 and Ki, rate constants of entrapment and flux of 18F-FMISO, respectively. Results: Data for 7 HT-29 tumor xenografts were presented, 6 of which yielded clear areas of tumor hypoxia as defined by Ki/k3 maps. Importantly, intratumoral foci with high 18F-FMISO uptakes on the late images did not always exhibit high Ki/k3 values and may there- fore represent false-positives for radiobiologically significant hypoxia. Conclusions: This study attempts to quantify tumor hypoxia using compartmental analysis of dynamic 18F-FMISO PET images in rodent xenograft tumor models. The results demonstrate feasibility of the approach in small-animal imaging studies, and provide evidence for the possible unreliability of late-time static imaging of 18F-FMISO PET in identifying tumor hypoxia.展开更多
文摘Purpose: To generate parametric images of tumor hypoxia in a tumor-bearing rat model using voxel-based compartmental analysis of dynamic fluorine-18 labeled misonidazole (18F-FMISO) microPET? images, and to compare the parametric images thus derived with static “late” 18F-FMISO microPET? images for the detection of tumor hypoxia. Materials and Methods: Nude rats bearing HT-29 colorectal carcinoma xenografts (≈1.5 - 2 cm in diameter) in the right hind limb were positioned in a custom-fabricated, animal-specific foam mold. Animals were injected via the tail vein with ≈55.5 MBq 18F-FMISO and continuously imaged for either 60 or 120 minutes, with additional late static images up to 3 hour post-injection. The raw list-mode data was reconstructed into 37 - 64 frames with earlier frames of shorter time durations (12 - 15 seconds) and later frames of longer durations (up to 300 seconds). Time activity curves (TACs) were generated over regions encompassing the tumor as well as an artery, the latter for use as an input function. A beta version of a compartmental modeling package (BioGuide?, Philips Healthcare) was used to generate parametric images of k3 and Ki, rate constants of entrapment and flux of 18F-FMISO, respectively. Results: Data for 7 HT-29 tumor xenografts were presented, 6 of which yielded clear areas of tumor hypoxia as defined by Ki/k3 maps. Importantly, intratumoral foci with high 18F-FMISO uptakes on the late images did not always exhibit high Ki/k3 values and may there- fore represent false-positives for radiobiologically significant hypoxia. Conclusions: This study attempts to quantify tumor hypoxia using compartmental analysis of dynamic 18F-FMISO PET images in rodent xenograft tumor models. The results demonstrate feasibility of the approach in small-animal imaging studies, and provide evidence for the possible unreliability of late-time static imaging of 18F-FMISO PET in identifying tumor hypoxia.