CHARACTERIZATION OF A LITHIUM FORMATE EPR-DOSIMETRY SYSTEM FOR PROTON RADIATION THERAPY.

The specific aim for the characterization of the lithium formate dosimetry system is to determine response and stability in a proton beam. The long-term goal for this investigation is an audit system for proton therapy like the end-to-end dose determinations performed for radiotherapy with photons. For a 150-MeV proton beam, the dose response was found to be linear in the dose interval 0-8.8 Gy. The accuracy of dose reconstruction was controlled in a blind test, in which the dose of 6.63 Gy was measured in samples irradiated with a real dose of 6.70 Gy. The stability was determined by irradiations of sets of four dosimeters every week during 1 month and analyzed at the same day thereafter. The fitting of the fading curve was done with a second-order polynomial resulting in a 6.6% lower value compared to the reference after 31 d.

Analytical calculation of proton linear energy transfer in voxelized geometries including secondary protons.

In order to integrate radiobiological modelling with clinical treatment planning for proton radiotherapy, we extended our in-house treatment planning system FoCa with a 3D analytical algorithm to calculate linear energy transfer (LET) in voxelized patient geometries. Both active scanning and passive scattering delivery modalities are supported. The analytical calculation is much faster than the Monte-Carlo (MC) method and it can be implemented in the inverse treatment planning optimization suite, allowing us to create LET-based objectives in inverse planning. The LET was calculated by combining a 1D analytical approach including a novel correction for secondary protons with pencil-beam type LET-kernels. Then, these LET kernels were inserted into the proton-convolution-superposition algorithm in FoCa. The analytical LET distributions were benchmarked against MC simulations carried out in Geant4. A cohort of simple phantom and patient plans representing a wide variety of sites (prostate, lung, brain, head and neck) was selected. The calculation algorithm was able to reproduce the MC LET to within 6% (1 standard deviation) for low-LET areas (under 1.7 keV µm(-1)) and within 22% for the high-LET areas above that threshold. The dose and LET distributions can be further extended, using radiobiological models, to include radiobiological effectiveness (RBE) calculations in the treatment planning system. This implementation also allows for radiobiological optimization of treatments by including RBE-weighted dose constraints in the inverse treatment planning process.