Affiliation:
1. Institute of Experimental and Clinical Research, UCLouvain, MIRO Lab Brussels Belgium
2. Department of Radiation Oncology Emory University Atlanta Georgia USA
3. Department of Oncology, KU Leuven Laboratory of Experimental Radiotherapy Leuven Belgium
4. Particle Therapy Interuniversity Center Leuven—PARTICLE Leuven Belgium
Abstract
AbstractPurposeAn accurate estimation of range uncertainties is essential to exploit the potential of proton therapy. According to Paganetti's study, a value of 2.4% (1.5 standard deviation) is currently recommended for planning robust treatments with Monte Carlo dose engines. This number is based on a dominant contribution from the mean excitation energy of tissues. However, it was recently shown that expressing tissues as a mixture of water and “dry” material in the CT calibration process allowed for a significant reduction of this uncertainty. We thus propose an adapted framework for pencil beam scanning robust optimization. First, we move towards a spot‐specific range uncertainty (SSRU) determination. Second, we use the water‐based formalism to reduce range uncertainties and, potentially, to spare better the organs at risk.MethodsThe stoichiometric calibration was adapted to provide a molecular decomposition (including water) of each voxel of the CT. The SSRU calculation was implemented in MCsquare, a fast Monte Carlo dose engine dedicated to proton therapy. For each spot, a ray‐tracing method was used to propagate molecular I‐values uncertainties and obtain the corresponding effective range uncertainty. These were then combined with other sources of range uncertainties, according to Paganetti's study of 2012. The method was then assessed on three head‐and‐neck patients. Two plans were optimized for each patient: the first one with the classical 2.4% flat range uncertainty (FRU), the second one with the variable range uncertainty. Both plans were then compared in terms of target coverage and OAR mean dose reduction. Robustness evaluations were also performed, using the SSRU for both plans in order to simulate errors as realistically as possible.ResultsFor patient 1, it was found that the median SSRU was 1.04% (1.5 standard deviation), yielding, therefore, a very large reduction from the 2.4% FRU. All three SSRU plans were found to have a very good robustness level at a 90% confidence interval while sparing OAR better than the classical plan. For instance, in nominal cases, average reductions in the mean dose of 15.7, 8.4, and 13.2% were observed in the left parotid, right parotid, and pharyngeal constrictor muscle, respectively. As expected, the classical plans showed a higher but unnecessary level of robustness.ConclusionsPromising results of the SSRU framework were observed on three head‐and‐neck cases, and more patients should now be considered. The method could also benefit to other tumor sites and, in the long run, the variable part of the range uncertainty could be generalized to other sources of uncertainty in order to move towards more and more patient‐specific treatments.
Funder
Fonds De La Recherche Scientifique - FNRS