Frontiers in Oncology (Feb 2014)
Radioembolization and the dynamic role of 90Y PET/CT
Abstract
Before the advent of tomographic imaging, it was postulated that decay of 90Y to the 0+ excited state of 90Zr may result in emission of a positron-electron pair. While the branching ratio for pair production is small (~32x10-6), PET has been successfully used to image 90Y in numerous recent patient and phantom studies. 90Y PET imaging has been performed on a variety of PET/CT systems, with and without time-of-flight (TOF) and/or resolution recovery capabilities as well as on both BGO and L(Y)SO based scanners. On all systems, resolution and contrast superior to bremsstrahlung SPECT has been reported. The intrinsic radioactivity present in L(Y)SO-based PET scanners is a potential limitation associated with accurate quantification of 90Y. However, intrinsic radioactivity has been shown to have a negligible effect at the high activity concentrations common in 90Y radioembolization. Accurate quantification is possible on a variety of PET scanner models, with or without TOF, although TOF improves accuracy at lower activity concentrations. Quantitative 90Y PET images can be transformed into 3D maps of absorbed dose based on the premise that the 90Y activity distribution does not change after infusion. This transformation has been accomplished primarily with the use of 3D dose point-kernel convolution. From a clinical standpoint, 90Y PET provides a superior post-infusion evaluation of treatment technical success owing to its improved resolution. Absorbed dose maps generated from quantitative PET data can be used to predict treatment efficacy and manage patient follow-up. For patients who receive multiple treatments, this information can also be used to provide patient-specific treatment planning for successive therapies, potentially improving response. The broad utilization of 90Y PET has the potential to provide a wealth of dose-response information, which may lead to development of improved radioembolization treatment-planning models in the future.
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