Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system

M., C.; Pawlicki, Todd; Jiang, Steve B; Li, J. S.; Deng, Jun; Mok, E; Kapur, Ajay; Liu, Xing; Ma, Lijun; Boyer, Arthur L.

doi:10.1088/0031-9155/45/9/303

Cited by 139 publications

(104 citation statements)

References 36 publications

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“…Ma et al [5] used the Monte Carlo method to verify IMRT dose distributions previously computed by the Corvus TPS, employing a finite-size pencil beam algorithm. In their work, they also investigated the dosimetric effect of the conversion of calculated dose to different materials for a vertebra IMRT dose plan delivered with photon beams of 15 MV.…”

Section: Introductionmentioning

confidence: 99%

The use of non-standard CT conversion ramps for Monte Carlo verification of 6 MV prostate IMRT plans

Zarza-Moreno

Cardoso²,

Teixeira

et al. 2013

Physica Medica

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Monte Carlo (MC) dose calculation algorithms have been widely used to verify the accuracy of intensity-modulated radiotherapy (IMRT) dose distributions computed by conventional algorithms due to the ability to precisely account for the effects of tissue inhomogeneities and multileaf collimator characteristics. Both algorithms present, however, a particular difference in terms of dose calculation and report. Whereas dose from conventional methods is traditionally computed and reported as the water-equivalent dose (D w ), MC dose algorithms calculate and report dose to medium (D m ). In order to compare consistently both methods, the conversion of MC D m into D w is therefore necessary.This study aims to assess the effect of applying the conversion of MC-based D m distributions to D w for prostate IMRT plans generated for 6 MV photon beams. MC phantoms were created from the patient CT images using three different ramps to convert CT numbers into material and mass density: a conventional four material ramp (CTCREATE) and two simplified CT conversion ramps: (1) air and water with variable densities and (2) air and water with unit density. MC simulations were performed using the BEAMnrc code for the treatment head simulation and the DOSXYZnrc code for the patient dose calculation. The conversion of D m to D w by scaling with the stopping power ratios of water to medium was also performed in a post-MC calculation process.The comparison of MC dose distributions calculated in conventional and simplified (water with variable densities) phantoms showed that the effect of material composition on dose-volume histograms (DVH) was less than 1% for soft tissue and about 2.5% near and inside bone structures. The effect of material density on DVH was less than 1% for all tissues through the comparison of MC distributions performed in the two simplified phantoms considering water. Additionally, MC dose distributions were compared with the predictions from an Eclipse treatment planning system (TPS), which employed a pencil beam convolution (PBC) algorithm with Modified Batho Power Law heterogeneity correction. Eclipse PBC and MC calculations (conventional and simplified phantoms) agreed well (<1%) for soft tissues. For femoral heads, differences up to 3% were observed between the DVH for Eclipse PBC and MC calculated in conventional phantoms. The use of the CT conversion ramp of water with variable densities for MC simulations showed no dose discrepancies (0.5%) with the PBC algorithm. Moreover, converting D m to D w using mass stopping power ratios resulted in a significant shift (up to 6%) in the DVH for the femoral heads compared to the Eclipse PBC one. Our results show that, for prostate IMRT plans delivered with 6 MV photon beams, no conversion of MC dose from medium to water using stopping power ratio is needed. In contrast, MC dose calculations using water with variable density may be a simple way to solve the problem found using the dose conversion method based on the stopping power ratio.

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Section: Introductionmentioning

confidence: 99%

The use of non-standard CT conversion ramps for Monte Carlo verification of 6 MV prostate IMRT plans

Zarza-Moreno

Cardoso²,

Teixeira

et al. 2013

Physica Medica

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“…When irradiated, this dramatic dissimilarity in tissue density results in a loss of charged particle equilibrium (CPE) at the tumor/lung interface. This, in turn, yields a buildup of dose within the higher‐density tumor tissue on the radiation beam entrance side of the tumor and/or a builddown of dose on the beam exit side of the tumor 5 , 7 . Dosimetrically, the tumor tissue near the tumor/lung interface becomes underdosed relative to the portions of the tumor which are more interior to this buildup or builddown region.…”

Section: Introductionmentioning

confidence: 99%

Practical methods for improving dose distributions in Monte Carlo‐based IMRT planning of lung wall‐seated tumors treated with SBRT

Altman

Jin

Kim

et al. 2012

J Applied Clin Med Phys

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Current commercially available planning systems with Monte Carlo (MC)‐based final dose calculation in IMRT planning employ pencil‐beam (PB) algorithms in the optimization process. Consequently, dose coverage for SBRT lung plans can feature cold‐spots at the interface between lung and tumor tissue. For lung wall (LW)‐seated tumors, there can also be hot spots within nearby normal organs (example: ribs). This study evaluated two different practical approaches to limiting cold spots within the target and reducing high doses to surrounding normal organs in MC‐based IMRT planning of LW‐seated tumors. First, “iterative reoptimization”, where the MC calculation (with PB‐based optimization) is initially performed. The resultant cold spot is then contoured and used as a simultaneous boost volume. The MC‐based dose is then recomputed. The second technique uses noncoplanar beam angles with limited path through lung tissue. Both techniques were evaluated against a conventional coplanar beam approach with a single MC calculation. In all techniques the prescription dose was normalized to cover 95% of the PTV. Fifteen SBRT lung cases with LW‐seated tumors were planned. The results from iterative reoptimization showed that conformity index (CI) and/or PTV dose uniformity (UPTV) improved in 12/15 plans. Average improvement was 13%, and 24%, respectively. Nonimproved plans had PTVs near the skin, trachea, and/or very small lung involvement. The maximum dose to 1cc volume (D1cc) of surrounding OARs decreased in 14/15 plans (average 10%). Using noncoplanar beams showed an average improvement of 7% in 10/15 cases and 11% in 5/15 cases for CI and UPTV, respectively. The D1cc was reduced by an average of 6% in 10/15 cases to surrounding OARs. Choice of treatment planning technique did not statistically significantly change lung V5. The results showed that the proposed practical approaches enhance dose conformity in MC‐based IMRT planning of lung tumors treated with SBRT, improving target dose coverage and potentially reducing toxicities to surrounding normal organs.PACS numbers: 87.55.de, 87.55.kh

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“…Accordingly, MC has been regarded as a powerful tool to obtain the accurate dose distributions in the (heterogeneous) patient. Efforts have been made to implement MC in clinical treatment planning and plan verification [14], and suitable TPS are currently put on the market. There have been several fast MC codes developed, such as VMC/XVMC [15,16], DPM [17], MCV [18] or MCDOSE [19].…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo simulations to replace film dosimetry in IMRT verification

Goetzfried

Rickhey

Treutwein³

et al. 2011

Zeitschrift für Medizinische Physik

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Patient-specific verification of intensity-modulated radiation therapy (IMRT) plans can be done by dosimetric measurements or by independent dose or monitor unit calculations. The aim of this study was the clinical evaluation of IMRT verification based on a fast Monte Carlo (MC) program with regard to possible benefits compared to commonly used film dosimetry.25 head-and-neck IMRT plans were recalculated by a pencil beam based treatment planning system (TPS) using an appropriate quality assurance (QA) phantom. All plans were verified both by film and diode dosimetry and compared to MC simulations. The irradiated films, the results of diode measurements and the computed dose distributions were evaluated, and the data were compared on the basis of gamma maps and dose-difference histograms.Average deviations in the high-dose region between diode measurements and point dose calculations performed with the TPS and MC program were 0.7 ± 2.7 % and Preprint submitted to Elsevier 11 February 20101.2 ± 3.1 %, respectively. For film measurements, the mean gamma values with 3 % dose difference and 3 mm distance-to-agreement were 0.74 ± 0.28 (TPS as reference) with dose deviations up to 10 %. Corresponding values were significantly reduced to 0.34 ± 0.09 for MC dose calculation. The total time needed for both verification procedures is comparable, however, by far less labor intensive in the case of MC simulations.The presented study showed that independent dose calculation verification of IMRT plans with a fast MC program has the potential to eclipse film dosimetry more and more in the near future. Thus, the linac-specific QA part will necessarily become more important. In combination with MC simulations and due to the simple set-up, point-dose measurements for dosimetric plausibility checks are recommended at least in the IMRT introduction phase.

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Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system

Cited by 139 publications

References 36 publications

The use of non-standard CT conversion ramps for Monte Carlo verification of 6 MV prostate IMRT plans

The use of non-standard CT conversion ramps for Monte Carlo verification of 6 MV prostate IMRT plans

Practical methods for improving dose distributions in Monte Carlo‐based IMRT planning of lung wall‐seated tumors treated with SBRT

Monte Carlo simulations to replace film dosimetry in IMRT verification

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