Quantitative Analysis in Nuclear Oncologic Imaging

  • Mankoff D
  • Muzi M
  • Zaidiy H
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Abstract

The role of PET during the past decade has evolved rapidly from that of a pure research tool to a methodology of enormous clinical potential. FDG-PET is widely used in the diagnosis, staging, and assessment of tumor response to therapy, since metabolic changes generally precede the more conventionally measured parameter of change in tumor size. Data are accumulating rapidly to validate the efficacy of FDG imaging in a wide variety of malignant tumors with sensitivities and specificities often in the high 90-percentile range. Although metabolic imaging is an obvious choice, the design of specific clinical protocols is still under development. The tracers or combinations of tracers to be used, when the imaging should be done after therapy, the selection of optimal acquisition and processing protocols, the method of accurately performing quantitative or semi-quantitative analysis of data are still undetermined. Moreover, each tumor-therapy combination may need to be independently optimized and validated. We expect that whole-body FDG-PET-based techniques may be accurate and cost-effective for staging or restaging of different cancer types and can contribute to the improvement of cancer patients’ management and monitoring with respect to medical cost. In addition to improving overall scanner performance, further work will focus on implementing practical corrections for patient-related perturbations such as non-homogeneous scatter and photon attenuation. During the next few years, it is believed that such sophisticated techniques will become more widely available in clinical settings and not only limited to research studies in nuclear medicine departments with advanced scientific and technical support. Therefore, it is expected that commercial hardware and software for accurate quantitative analysis will undertake major revisions in the future to be capable of facing emerging clinical applications and challenging research perspectives

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Mankoff, D. A., Muzi, M., & Zaidiy, H. (2006). Quantitative Analysis in Nuclear Oncologic Imaging. In Quantitative Analysis in Nuclear Medicine Imaging (pp. 494–536). Springer US. https://doi.org/10.1007/0-387-25444-7_16

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