Clinical Radiobiological Modelling for Radiopharmaceutical Therapy. Chapter 8

The objective of dosimetry in radiopharmaceutical therapy (RPT) is to understand or predict the likely biological consequences of administering a radiopharmaceutical to a patient. In diagnostic nuclear medicine the biological consequence of interest is risk of radiation detriment, which at the absorbed dose levels involved is primarily the risk of developing late occurring effects, like cancer. In RPT the relevant biological end points are toxicity and efficacy. In both cases, radiobiological models are invoked to convert the physical quantity, absorbed dose, into a biological response probability. The radiobiological model used in risk assessment for late stochastic effects (cancer induction) includes radiation and tissue weighting factors, wR and wT, respectively [8.1, 8.2]. These are associated with a 'reference person' and are used in conjunction with organ absorbed doses to calculate the effective dose, E. This quantity may be used to compare the cancer risk associated with diagnostic radiopharmaceuticals using lifetime attributable risk tables [8.3]. The weighting factors and lifetime attributable risk values may be thought of as parameters in a model by which absorbed dose, in Gy, is converted to cancer risk. The radiobiological 'model' in the diagnostic scenario has been standardized by international regulatory and professional bodies and is, in general, consistently applied throughout the world for radiation protection [8.4]. In RPT, such standardization of dose‑response modelling has not taken place yet. RPT is becoming more widely implemented and efforts to optimize such treatment using dosimetry based treatment planning [8.5] will require standardized dosimetry methods and standardized or 'reference' radiobiological models that are, in a sense, analogous to the 'reference person' concept applied in cancer risk evaluation. Continuing the analogy, reference radiobiological models will not predict efficacy and toxicity in an individual patient but would allow biologically based treatment optimization and comparison of therapeutic agents and treatment strategies.