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Positron Emission Tomography in Radiation Treatment

  • Sang-Moo Lim
  • E. Edmund Kim
Chapter

Abstract

In the era of image-guided radiation therapy, treatment plans require narrower tumor margins and more attention dedicated to the location and configuration of tumor for better outcomes. Traditional anatomy-based modalities such as plain radiographs, computed tomography (CT), sonography, and magnetic resonance imaging (MRI) that yield high spatial resolution and accurate anatomic localization, are essential for radiation therapy planning, but may significantly under- or overestimate the extent of the disease. Advances in medical imaging, such as portal imaging, ultrasound, cone-beam CT, positron emission tomography (PET), MRI, and new software and hardware systems demonstrate accurate staging, planning, and delivery in radiation therapy with high geometric precision. Functional imaging such as single-photon emission computed tomography, PET/CT, and magnetic resonance spectroscopy that permit the visualization of the biologic pathways of tumors, are being incorporated into the algorithm for the workup, management, and evaluation of treatment effects in the radiation oncology practice. PET/CT could provide biologic imaging information and modify the clinical staging and target definition from the anatomic imaging. In addition to the concept of gross tumor volume, clinical and planning target volume, biologic target volume and dose painting were introduced (Schinagl et al. Cancer Imaging 6:S107–16, 2006; Grosu et al. Onkol 181:483–99, 2005; Nestle et al. Phys Med Biol 54:R1–25, 2009). This chapter will focus on the role of PET/CT in the staging (sensitivity and specificity), target volume definition, and possible assessment of response to radiation treatment. Future possibilities of new radiotracers to evaluate hypoxia, and proliferation, etc. will be discussed.

Keywords

Positron Emission Tomography Planning Target Volume Epidermal Growth Factor Receptor Expression Target Volume Definition Dose Painting 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Nuclear MedicineKorea Institute of Radiological & Medical SciencesSeoulSouth Korea
  2. 2.Departments of Nuclear Medicine and Diagnostic RadiologyThe University of Texas MD Anderson Cancer Center and Medical SchoolHoustonUSA
  3. 3.Graduate School of Convergence Science and TechnologySeoul National UniversitySeoulSouth Korea

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