(Sunday, 7/29/2018) 2:05 PM - 3:00 PM
Room: Karl Dean Ballroom A1
Purpose: We report the preliminary results of our group’s efforts to model the relative biological effectiveness (RBE) of carbon ion irradiation experiments performed at Deutsches Krebsforschungzentrum (DKFZ) in Heidelberg, Germany.
Methods: A variable range selector was made out of PMMA, enabling irradiation of a 96-well cell culture plate at 12 depths along the Bragg curve. The carbon ion energy spectrum at each depth was simulated using the Geant4 Monte Carlo toolkit. Using the Geant4 DNA extension, the lineal energy distribution function (f(y)) for 57 energies, from 3 MeV/u to 144 MeV/u, were calculated. These energies covered the carbon ion energy distributions simulated by Geant4. Using a fluence-weighting technique, the dose mean lineal energy (yD) was calculated. The microdosimetric kinetic model (MKM) models RBE as a function of yD, as well as the domain radius (rd) and the cell nucleus radius (Rn). Assuming Rn is on the order of ~3.5 μm, rd can be used as a fitting parameter and varied to obtain close agreement between the RBE predicted by MKM and RBE from the experiment.
Results: Preliminary results show RBE increased with dose-averaged LET (LETd), reached a peak of 3.9 at 78 keV/μm and decreased with increasing LETd. To model this RBE maximum and then decrease with increasing LETd, a saturation correction for the non-Poissonian distribution of lethal DNA lesions must be included in MKM. We used the method proposed by Hawkins (2003) to correct for saturation. By including the saturation correction in MKM and setting rd = 0.310 μm and Rn = 3.55 μm, we were able to model the increasing RBE, with a maximum RBE of 3.7 at 90 keV/μm, and then a decrease with further increases of LETd.
Conclusion: This work provides a theoretical basis of variable RBE as a function of LETd in carbon ion irradiation.
Keywords
Microdosimetry, Monte Carlo, Heavy Ions
Taxonomy
TH- External Beam- Particle therapy: Carbon ion therapy - computational dosimetry-Monte Carlo
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