There are numerous factors that determine the biological response of tissues that contain radioactivity such as radiosensitivity, distribution of radioactivity, type and number of radiations emitted by the radionuclide, biokinetics of the radionuclide, repair time, etc. Traditionally, the mean absorbed dose to the tissue is calculated to correlate the biological response with mean absorbed dose. However, nonuniform activity distributions in tissue at the multicellular and subcellular levels result in nonuniform doses and therefore have made it difficult to adequately correlate biological response with mean absorbed dose. This is an important problem in diagnostic and therapeutic nuclear medicine. In the case of diagnosis, the risk of the radiation insult can in principle be drastically underestimated and potentially lead to increased risk of inducing cancer. In contrast, patients can be over- or under-treated in radionuclide therapy of cancer. Over-treatment or under-treatment in radionuclide therapy of cancer can have very adverse consequences in the final outcome for the patient. While calculation of absorbed dose at the cellular level has been advocated as a means to address this problem, this has largely remained a theoretical exercise. The applicants hypothesize that the biological response of tissues containing incorporated radionuclides can be correlated with absorbed dose when calculated at the cellular level. To test the hypothesis, a novel in vitro multicellular cluster model will be used which allows tight control over variables. Multicellular clusters will be assembled with mammalian cells containing radioactivity and the cell survival fraction as a function of cluster activity will be determined for several different radiopharmaceuticals which emit alpha particles, beta particles, or Auger electrons. Different percentages of the cells will be labeled with the different radiochemicals to ascertain the impact of nonuniform distributions of radioactivity at the cellular and subcellular levels. By controlling the percentage of cells labeled, this model will also be used to ascertain the role of bystander effects in the biological effects of incorporated radioactivity. These data and cellular dosimetry calculations will be used to develop a theoretical model to predict response based on cellular absorbed dose and bystander effects. The outcome of this research is expected to have a major impact on understanding and predicting the biological response of tumor and normal tissue to nonuniform distributions of radioactivity.
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