MENU

Click here to

×

Are you sure ?

Yes, do it No, cancel

Evaluating the Effects of Varying Statistical Uncertainty Using a Monte Carlo Based Treatment Planning System

J Rembish1*, P Myers1 , K Rasmussen1 , N Kirby1 , D Saenz1 , V Bry1 , P Mavroidis2 , N Papanikolaou1 , S Stathakis1 , (1) UT Health San Antonio, San Antonio, TX, (2) Univ North Carolina, Chapel Hill, NC

Presentations

(Sunday, 7/14/2019)  

Room: ePoster Forums

Purpose: This study aims to determine the severity of the effects on calculations of dose distributions caused by varying statistical uncertainties in a Monte Carlo based treatment planning system (TPS).

Methods: For this study, three archived patient prostate plans were selected for recalculation. These plans were each recalculated multiple times with varying uncertainty levels per control point as well as varying uncertainties per calculation using Elekta’s Monaco Version 5.11.00 Monte Carlo Gold Standard XVMC dose calculation algorithm. When setting the uncertainty per calculation, the uncertainty values ranged from 0.5% to 3% at intervals of 0.5%, with a final calculation at the maximum allowable statistical uncertainty of 5.0%. For the uncertainty per control point, uncertainty values ranged from 2% to 10% at intervals of 2%. The grid spacing was set at 3mm for all calculations. Indices defined by the RTOG describing conformity, coverage, and homogeneity were recorded for each recalculation. Additionaly, basic PTV DVH statistics were recorded.

Results: Of the observed DVH statistics, the most affected was the volume of the target receiving the prescription dose (TVPI). There was a negative correlation between the statistical uncertainty and this volume. In some cases, the difference was as large as 19.3 cubic centimeters. On average, the maximum dose to the target increased with an increase in uncertainty while the coverage and homogeneity decreased. As the uncertainty increases, the isodose lines become more irregular, and the target coverage and dose homogeneity both suffer.

Conclusion: Increasing the statistical uncertainty correlates with a decrease in TVPI and produces more irregular isodose lines. While time is spared using higher uncertainty levels, the plan quality is decreased. The same trends were observed whether varying the uncertainty per control point or per calculation. Additional plans will be recalculated to further improve statistical accuracy.

Keywords

Monte Carlo, Treatment Planning

Taxonomy

TH- External beam- photons: dose computation engines- Monte Carlo

Contact Email