Recommended dose voxel size and statistical uncertainty parameters for precision of Monte Carlo dose calculation in stereotactic radiotherapy

Abstract

Monte Carlo (MC)-based treatment planning requires a choice of dose voxel size (DVS) and statistical uncertainty (SU). These parameters effect both the precision of displayed dose distribution and time taken to complete a calculation. For efficient, accurate, and precise treatment planning in a clinical setting, optimal values should be selected. In this investigation, 30 volumetric modulated arc therapy (VMAT) stereotactic radiotherapy (SRT) treatment plans, 10 brain, 10 lung, and 10 spine were calculated in the Monaco 5.11.02 treatment planning system (TPS). Each plan was calculated with a DVS of 0.1 and 0.2 cm using SU values of 0.50%, 0.75%, 1.00%, 1.50%, and 2.00%, along with a ground truth calculation using a DVS of 0.1 cm and SU of 0.15%. The variance at each relative dose level was calculated for all SU settings to assess their relationship. The variation from the ground truth calculation for each DVS and SU combination was determined for a range of DVH metrics and plan quality indices along with the time taken to complete the calculations. Finally, the effect of defining the maximum dose using a volume of 0.035 cc was compared to 0.100 cc when considering DVS and SU settings. Changes in the DVS produced greater variations from the ground truth calculation than changes in SU across the values tested. Plan quality metrics and mean dose values showed less sensitivity to changes in SU than DVH metrics. From this study, it was concluded that while maintaining an average calculation time of <10 min, 75% of plans could be calculated with variations of <2.0% from their ground truth values when using an SU setting of 1.50% and a DVS of 0.1 cm in the case of brain or spine plans, and a 0.2 cm DVS in the case of lung plans.

Maintaining dosimetric quality when switching to a Monte Carlo dose engine for head and neck volumetric‐modulated arc therapy planning

“…22,24 However, an estimate can be made by simulating a family of the DVH curves for the same plan simulated with the progressively reduced statistical uncertainty. 49 In its limit, the solution converges to the real DVH with zero uncertainty. 50,51 Previously, the value of 0.15% was suggested as the relative statistical uncertainty for the target DVH curve to be considered effectively noiseless.…”

“…Even if taken at face value, it is still substantially more stringent than the values accepted by the cooperative groups 43,44 and typically reported in the literature. 11,13,16,49,52,53 For broader comparison, we calculated the often used homogeneity index (HI) HI = (D 2% − D 98% )∕D 50% for our patient cohort optimized with MC. Our average HI was 0.05 ± 0.01, or one-half of the typically reported values for HN plans generated with various algorithms.…”

“…50,51 Previously, the value of 0.15% was suggested as the relative statistical uncertainty for the target DVH curve to be considered effectively noiseless. 49 We used the 0.1% value, compared to 0.3% uncertainty used for planning. Based on that assumption, only a very small portion of the increase of the hot spot dose in the MC-based calculations with 0.3% uncertainty, compared to the deterministic CC-based algorithms, can be attributed to the statistical "blurring" of the PTV DVH (Figure 1).…”

“…The rigorous analysis of the influence of MC statistical uncertainty on the DVH “blurring” is quite involved, and so is removing of this uncertainty, or “deconvolving” the DVH to arrive at the noise‐free curve 22,24 . However, an estimate can be made by simulating a family of the DVH curves for the same plan simulated with the progressively reduced statistical uncertainty 49 . In its limit, the solution converges to the real DVH with zero uncertainty 50,51 .…”

“…In its limit, the solution converges to the real DVH with zero uncertainty 50,51 . Previously, the value of 0.15% was suggested as the relative statistical uncertainty for the target DVH curve to be considered effectively noiseless 49 . We used the 0.1% value, compared to 0.3% uncertainty used for planning.…”