Target Size Variation in Microdosimetric Distributions and its Impact on the Linear-Quadratic Parameterization of Cell Survival

Modelling tissue specific RBE for different radiation qualities based on a multiscale characterization of energy deposition

PURPOSE

We present the nanoCluE model, which uses nano- and microdosimetric quantities to model RBE for protons and carbon ions. Under the hypothesis that nano- and microdosimetric quantities correlates with the generation of complex DNA double strand breakes, we wish to investigate whether an improved accuracy in predicting LQ parameters may be achieved, compared to some of the published RBE models.

METHODS

The model is based on experimental LQ data for protons and carbon ions. We generated a database of track structure data for a number of proton and carbon ion kinetic energies with the Geant4-DNA Monte Carlo code. These data were used to obtain both a nanodosimetric quantity and a set of microdosimetric quantities. The latter were tested with different parameterizations versus experimental LQ-data to select the variable and parametrization that yielded the best fit.

RESULTS

For protons, the nanoCluE model yielded, for the ratio of the linear LQ term versus the test data, a root mean square error (RMSE) of 1.57 compared to 1.31 and 1.30 for two earlier other published proton models. For carbon ions the RMSE was 2.26 compared to 3.24 and 5.24 for earlier published carbon ion models.

CONCLUSION

These results demonstrate the feasibility of the nanoCluE RBE model for carbon ions and protons. The increased accuracy for carbon ions as compared to two other considered models warrants further investigation.

Experimental validation of an analytical microdosimetric model based on Geant4-DNA simulations by using a silicon-based microdosimeter

PURPOSE

To study the agreement between proton microdosimetric distributions measured with a silicon-based cylindrical microdosimeter and a previously published analytical microdosimetric model based on Geant4-DNA in-water Monte Carlo simulations for low energy proton beams.

METHODS AND MATERIAL

Distributions for lineal energy (y) are measured for four proton monoenergetic beams with nominal energies from 2.0 MeV to 4.5 MeV, with a tissue equivalent proportional counter (TEPC) and a silicon-based microdosimeter. The actual energy for protons traversing the silicon-based microdosimeter is simulated with SRIM. Monoenergetic beams with these energies are simulated with Geant4-DNA code by simulating a water cylinder site of dimensions equal to those of the microdosimeter. The microdosimeter response is calibrated by using the distribution peaks obtained from the TEPC. Analytical calculations fory ¯ F andy ¯ D using our methodology based on spherical sites are also performed choosing the equivalent sphere to be checked against experimental results.

RESULTS

Distributions for y at silicon are converted into tissue equivalent and compared to the Geant4-DNA simulated, yielding maximum deviations of 1.03% fory ¯ F and 1.17% fory ¯ D . Our analytical method generates maximum deviations of 1.29% and 3.33%, respectively, with respect to experimental results.

CONCLUSION

Simulations in Geant4-DNA with ideal cylindrical sites in liquid water produce similar results to the measurements in an actual silicon-based cylindrical microdosimeter properly calibrated. The found agreement suggests the possibility to experimentally verify the calculated clinicaly ¯ D with our analytical method.

Systematic microdosimetric data for protons of therapeutic energies calculated with Geant4-DNA

The purpose of this study was to generate physical data needed for microdosimetry-based models of proton RBE. Our focus was on the frequency and dose average lineal energies, y  F and y  D . We report data for proton energies from 0.1 to 100 MeV, for spherical volumes 2-103 nm in diameter. These data were calculated using Geant4-DNA Monte Carlo software. The physics implemented in Geant4-DNA has been extensively tested for this type of calculations but data on y  F and y  D for protons generated with this code have been very limited. An innovative aspect of our study is that we introduced a straightforward procedure for calculation of y  F and y  D for polyenergetic beams and presented the data in a format that simplifies these calculations. We compared our data with previous studies that used different Monte Carlo codes and with experimental data.