MO-F-BRB-04: Fast Estimation of Secondary Particle Therapy Dose Using a Modified Track Repeating Method
Purpose:
Charged particle beams are of great interest, because they can achieve highly conformal radiation dose distributions. Despite this, some scattered radiation is inevitably present outside of the target volumes, and is of concern because of risks such as radiogenic cancer. Accurately calculating the secondary dose in regions far from the target volume is very difficult due to extremely low particle fluence and the effect of heterogeneities on particle ranges, making calculations possible only with CPU-week long Monte Carlo runs. By using a modified track repeating method, we demonstrate fast and accurate estimation of secondary dose appropriate for clinical use.
Methods:
Primary and secondary particle track databases (including protons, electrons, photons, neutrons, and positrons) were generated with the Geant4 Monte Carlo toolkit. Several new strategies were developed or employed to improve the performance of non- primary particle propagation, including: (1) processing the databases such that only primary tracks producing deep penetrating photons or neutrons were kept and particles falling below transport thresholds were discarded, (2) a search algorithm that can locate a sub-track for a given energy in constant time, (3) multiplying photon and neutron tracks during propagation and scoring using particle 'splitting1.
Results:
Performance and accuracy were benchmarked against full Monte Carlo calculations (Geant4 and FLUKA). Filtering out tracks that did not produce deep penetrating photons or neutrons did not affect the accuracy of the secondary dose calculation. Preliminary performance analysis indicated 60- 100X speed up over Fluka and 700-1000X speed up over Geant4 with well maintained accuracy.
Conclusions:
Estimation of secondary dose from particle therapy has so far been largely an academic exercise. This method for fast estimation of secondary dose brings patient / plan specific information within reach, allowing clinicians to make informed decisions on the potential long-term risks associated with specific dose delivery plans. Partial funding from NSF grant CBET-0853157.
