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A Correction of the Gamma Test for Monte Carlo Dose Distributions Comparison

M Cohilis*, E Sterpin , J Lee , K Souris , Universite Catholique de Louvain, Woluwe, Brussels


(Sunday, 7/29/2018) 3:00 PM - 6:00 PM

Room: Exhibit Hall

Purpose: For QA and commissioning purposes, the gamma index is often used to compare two dose distributions. However, this method is known to be asymmetric and dependent on the resolution and noise. This work suggests a correction of the gamma index method when applied to noisy Monte Carlo (MC) doses, while keeping a reasonable computation time.

Methods: The noise dependency of the gamma index is first analyzed by computing the gamma passing rate for multiple MC doses with various noise levels. These results are then fitted with a function derived theoretically. This fit enables to extrapolate the gamma passing rate to a low noise case, which would normally require to simulate a large number of particles with MC. To illustrate the method, four proton treatment doses (brain, prostate, lung, liver) were recalculated with the fast Monte Carlo code MCsquare and compared to the TPS doses using gamma tests (2%/2mm, 3%/3mm, 4%/4mm, with MC as reference). The noiseless gamma passing rates were then estimated using the proposed method, by fitting values obtained for 1E5, 5E5, 1E6, 5E6, 7E6, 1E7 and 2E7 simulated particles. This prediction was then validated with the passing rates obtained for low noise MC doses (1E9 particles).

Results: On average, the difference between original gamma passing rates obtained for 2E7 and for 1E9 particles simulations was 8.48%. The MC computation times were around 2 minutes and 2 hours respectively. For all patients, the absolute error between the real and the predicted passing rates remained below 3% and was around 1% in most cases.

Conclusion: This work offers an extension of the classical gamma index method when there is noise in the reference dose. It achieves good results on four proton treatment plans with, in some cases, quite important gains of precision while keeping the computation time tractable.


Monte Carlo, Noise, Quality Assurance


TH- External Beam- Particle therapy: Proton therapy - quality assurance

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