Dosimetry in nuclear medicine therapy: radiobiology application and results

Q J Nucl Med Mol Imaging. 2011 Apr;55(2):205-21.

Abstract

The linear quadratic model (LQM) has largely been used to assess the radiobiological damage to tissue by external beam fractionated radiotherapy and more recently has been extended to encompass a general continuous time varying dose rate protocol such as targeted radionuclide therapy (TRT). In this review, we provide the basic aspects of radiobiology, from a theoretical point of view, starting from the "four Rs" of radiobiology and introducing the biologically effective doses, which may be used to quantify the impact of a treatment on both tumors and normal tissues. We also present the main parameters required in the LQM, and illustrate the main models of tumor control probability and normal tissue complication probability and summarize the main dose-effect responses, reported in literature, which demonstrate the tentative link between targeted radiotherapy doses and those used in conventional radiotherapy. A better understanding of the radiobiology and mechanisms of action of TRT could contribute to describe the clinical data and guide the development of future compounds and the designing of prospective clinical trials.

Publication types

  • Review

MeSH terms

  • Bone Marrow / injuries
  • Bone Marrow / radiation effects
  • Cell Proliferation / radiation effects
  • Cell Survival / radiation effects
  • Dose-Response Relationship, Radiation
  • Humans
  • Kidney / injuries
  • Kidney / radiation effects
  • Linear Models
  • Liver / injuries
  • Liver / radiation effects
  • Lung / radiation effects
  • Models, Biological
  • Neoplasms / pathology
  • Neoplasms / radiotherapy*
  • Nuclear Medicine / statistics & numerical data
  • Radiobiology / statistics & numerical data
  • Radiotherapy / adverse effects
  • Radiotherapy / methods*
  • Radiotherapy / statistics & numerical data
  • Radiotherapy Planning, Computer-Assisted / methods*
  • Radiotherapy Planning, Computer-Assisted / statistics & numerical data