Program Information

Evaluation of a Radiation-Induced Cell Proliferation Probability Formula Using Monte Carlo Simulation

Y Watanabe

Y Watanabe*, E Dahlman , University of Minnesota, Minneapolis, MN

Presentations

SU-E-J-65 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: To evaluate the analytic formula of the cell death probability after single fraction dose.

Methods: Cancer cells endlessly divide, but radiation causes the cancer cells to die. Not all cells die right away after irradiation. Instead, they continue dividing for next few cell cycles before they stop dividing and die. At the end of every cell cycle, the cell decides if it undertakes the mitotic process with a certain probability, Pdiv, which is altered by the radiation. Previously, by using a simple analytic model of radiobiology experiments, we obtained a formula of Pdeath (= 1 â‚‹ Pdiv). A question is if the proposed probability can reproduce the well-known survival data of the LQ model. In this study, we evaluated the formula by doing a Monte Carlo simulation of the cell proliferation process. Starting with Ns seed cells, the cell proliferation process was simulated for N generations or until all cells die. We counted the number of living cells at the end. Assuming that the cell colony survived when more than Nc cells were still alive, the surviving fraction S was estimated. We compared the S vs. dose, or Sâ‚‹D curve, with the LQ model.

Results: The results indicated that our formula does not reproduce the experimentally observed S-D curve without selecting appropriate α and α/β. With parameter optimization, there was a fair agreement between the MC result and the LQ curve of dose lower than 20Gy. However, the survival fraction of MC decreased much faster in comparison to the LQ data for doses higher than 20 Gy.

Conclusion: This study showed that the previously derived probability of cell death per cell cycle is not sufficiently accurate to replicate common radiobiological experiments. The formula must be modified by considering its cell cycle dependence and some other unknown effects.


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