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Title: SU-F-T-377: Monte Carlo Re-Evaluation of Volumetric-Modulated Arc Plans of Advanced Stage Nasopharygeal Cancers Optimized with Convolution-Superposition Algorithm

Abstract

Background: Commercial treatment planning system Pinnacle3 (Philips, Fitchburg, WI, USA) employs a convolution-superposition algorithm for volumetric-modulated arc radiotherapy (VMAT) optimization and dose calculation. Study of Monte Carlo (MC) dose recalculation of VMAT plans for advanced-stage nasopharyngeal cancers (NPC) is currently limited. Methods: Twenty-nine VMAT prescribed 70Gy, 60Gy, and 54Gy to the planning target volumes (PTVs) were included. These clinical plans achieved with a CS dose engine on Pinnacle3 v9.0 were recalculated by the Monaco TPS v5.0 (Elekta, Maryland Heights, MO, USA) with a XVMC-based MC dose engine. The MC virtual source model was built using the same measurement beam dataset as for the Pinnacle beam model. All MC recalculation were based on absorbed dose to medium in medium (Dm,m). Differences in dose constraint parameters per our institution protocol (Supplementary Table 1) were analyzed. Results: Only differences in maximum dose to left brachial plexus, left temporal lobe and PTV54Gy were found to be statistically insignificant (p> 0.05). Dosimetric differences of other tumor targets and normal organs are found in supplementary Table 1. Generally, doses outside the PTV in the normal organs are lower with MC than with CS. This is also true in the PTV54-70Gy doses but higher dose in themore » nasal cavity near the bone interfaces is consistently predicted by MC, possibly due to the increased backscattering of short-range scattered photons and the secondary electrons that is not properly modeled by the CS. The straight shoulders of the PTV dose volume histograms (DVH) initially resulted from the CS optimization are merely preserved after MC recalculation. Conclusion: Significant dosimetric differences in VMAT NPC plans were observed between CS and MC calculations. Adjustments of the planning dose constraints to incorporate the physics differences from conventional CS algorithm should be made when VMAT optimization is carried out directly with MC dose engine.« less

Authors:
; ; ; ; ; ; ;  [1]
  1. Tuen Mun Hospital, Hong Kong (Hong Kong)
Publication Date:
OSTI Identifier:
22648975
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ABSORBED RADIATION DOSES; ALGORITHMS; MONTE CARLO METHOD; NEOPLASMS; OPTIMIZATION; PLANNING; RADIOTHERAPY

Citation Formats

Lee, K, Leung, R, Law, G, Wong, M, Lee, V, Tung, S, Cheung, S, and Chan, M. SU-F-T-377: Monte Carlo Re-Evaluation of Volumetric-Modulated Arc Plans of Advanced Stage Nasopharygeal Cancers Optimized with Convolution-Superposition Algorithm. United States: N. p., 2016. Web. doi:10.1118/1.4956562.
Lee, K, Leung, R, Law, G, Wong, M, Lee, V, Tung, S, Cheung, S, & Chan, M. SU-F-T-377: Monte Carlo Re-Evaluation of Volumetric-Modulated Arc Plans of Advanced Stage Nasopharygeal Cancers Optimized with Convolution-Superposition Algorithm. United States. doi:10.1118/1.4956562.
Lee, K, Leung, R, Law, G, Wong, M, Lee, V, Tung, S, Cheung, S, and Chan, M. 2016. "SU-F-T-377: Monte Carlo Re-Evaluation of Volumetric-Modulated Arc Plans of Advanced Stage Nasopharygeal Cancers Optimized with Convolution-Superposition Algorithm". United States. doi:10.1118/1.4956562.
@article{osti_22648975,
title = {SU-F-T-377: Monte Carlo Re-Evaluation of Volumetric-Modulated Arc Plans of Advanced Stage Nasopharygeal Cancers Optimized with Convolution-Superposition Algorithm},
author = {Lee, K and Leung, R and Law, G and Wong, M and Lee, V and Tung, S and Cheung, S and Chan, M},
abstractNote = {Background: Commercial treatment planning system Pinnacle3 (Philips, Fitchburg, WI, USA) employs a convolution-superposition algorithm for volumetric-modulated arc radiotherapy (VMAT) optimization and dose calculation. Study of Monte Carlo (MC) dose recalculation of VMAT plans for advanced-stage nasopharyngeal cancers (NPC) is currently limited. Methods: Twenty-nine VMAT prescribed 70Gy, 60Gy, and 54Gy to the planning target volumes (PTVs) were included. These clinical plans achieved with a CS dose engine on Pinnacle3 v9.0 were recalculated by the Monaco TPS v5.0 (Elekta, Maryland Heights, MO, USA) with a XVMC-based MC dose engine. The MC virtual source model was built using the same measurement beam dataset as for the Pinnacle beam model. All MC recalculation were based on absorbed dose to medium in medium (Dm,m). Differences in dose constraint parameters per our institution protocol (Supplementary Table 1) were analyzed. Results: Only differences in maximum dose to left brachial plexus, left temporal lobe and PTV54Gy were found to be statistically insignificant (p> 0.05). Dosimetric differences of other tumor targets and normal organs are found in supplementary Table 1. Generally, doses outside the PTV in the normal organs are lower with MC than with CS. This is also true in the PTV54-70Gy doses but higher dose in the nasal cavity near the bone interfaces is consistently predicted by MC, possibly due to the increased backscattering of short-range scattered photons and the secondary electrons that is not properly modeled by the CS. The straight shoulders of the PTV dose volume histograms (DVH) initially resulted from the CS optimization are merely preserved after MC recalculation. Conclusion: Significant dosimetric differences in VMAT NPC plans were observed between CS and MC calculations. Adjustments of the planning dose constraints to incorporate the physics differences from conventional CS algorithm should be made when VMAT optimization is carried out directly with MC dose engine.},
doi = {10.1118/1.4956562},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • The reliability of the convolution/superposition (C/S) algorithm of the Hi-Art tomotherapy system is evaluated by using the Monte Carlo model TomoPen, which has been already validated for homogeneous phantoms. The study was performed in three stages. First, measurements with EBT Gafchromic film for a 1.25x2.5 cm{sup 2} field in a heterogeneous phantom consisting of two slabs of polystyrene separated with Styrofoam were compared to simulation results from TomoPen. The excellent agreement found in this comparison justifies the use of TomoPen as the reference for the remaining parts of this work. Second, to allow analysis and interpretation of the results inmore » clinical cases, dose distributions calculated with TomoPen and C/S were compared for a similar phantom geometry, with multiple slabs of various densities. Even in conditions of lack of lateral electronic equilibrium, overall good agreement was obtained between C/S and TomoPen results, with deviations within 3%/2 mm, showing that the C/S algorithm accounts for modifications in secondary electron transport due to the presence of a low density medium. Finally, calculations were performed with TomoPen and C/S of dose distributions in various clinical cases, from large bilateral head and neck tumors to small lung tumors with diameter of <3 cm. To ensure a ''fair'' comparison, identical dose calculation grid and dose-volume histogram calculator were used. Very good agreement was obtained for most of the cases, with no significant differences between the DVHs obtained from both calculations. However, deviations of up to 4% for the dose received by 95% of the target volume were found for the small lung tumors. Therefore, the approximations in the C/S algorithm slightly influence the accuracy in small lung tumors even though the C/S algorithm of the tomotherapy system shows very good overall behavior.« less
  • The purpose of this study is to evaluate dose prediction errors (DPEs) and optimization convergence errors (OCEs) resulting from use of a superposition/convolution dose calculation algorithm in deliverable intensity-modulated radiation therapy (IMRT) optimization for head-and-neck (HN) patients. Thirteen HN IMRT patient plans were retrospectively reoptimized. The IMRT optimization was performed in three sequential steps: (1) fast optimization in which an initial nondeliverable IMRT solution was achieved and then converted to multileaf collimator (MLC) leaf sequences; (2) mixed deliverable optimization that used a Monte Carlo (MC) algorithm to account for the incident photon fluence modulation by the MLC, whereas a superposition/convolutionmore » (SC) dose calculation algorithm was utilized for the patient dose calculations; and (3) MC deliverable-based optimization in which both fluence and patient dose calculations were performed with a MC algorithm. DPEs of the mixed method were quantified by evaluating the differences between the mixed optimization SC dose result and a MC dose recalculation of the mixed optimization solution. OCEs of the mixed method were quantified by evaluating the differences between the MC recalculation of the mixed optimization solution and the final MC optimization solution. The results were analyzed through dose volume indices derived from the cumulative dose-volume histograms for selected anatomic structures. Statistical equivalence tests were used to determine the significance of the DPEs and the OCEs. Furthermore, a correlation analysis between DPEs and OCEs was performed. The evaluated DPEs were within {+-}2.8% while the OCEs were within 5.5%, indicating that OCEs can be clinically significant even when DPEs are clinically insignificant. The full MC-dose-based optimization reduced normal tissue dose by as much as 8.5% compared with the mixed-method optimization results. The DPEs and the OCEs in the targets had correlation coefficients greater than 0.71, and there was no correlation for the organs at risk. Because full MC-based optimization results in lower normal tissue doses, this method proves advantageous for HN IMRT optimization.« less
  • Purpose: The purpose of this study was to evaluate the risks of second cancers and cardiovascular diseases associated with an optimized volumetric modulated arc therapy (VMAT) planning solution in a selected cohort of stage I/II Hodgkin lymphoma (HL) patients treated with either involved-node or involved-site radiation therapy in comparison with 3-dimensional conformal radiation therapy (3D-CRT). Methods and Materials: Thirty-eight patients (13 males and 25 females) were included. Disease extent was mediastinum alone (n=8, 21.1%); mediastinum plus unilateral neck (n=19, 50%); mediastinum plus bilateral neck (n=11, 29.9%). Prescription dose was 30 Gy in 2-Gy fractions. Only 5 patients had mediastinal bulkymore » disease at diagnosis (13.1%). Anteroposterior 3D-CRT was compared with a multiarc optimized VMAT solution. Lung, breast, and thyroid cancer risks were estimated by calculating a lifetime attributable risk (LAR), with a LAR ratio (LAR{sub VMAT}-to-LAR{sub 3D-CRT}) as a comparative measure. Cardiac toxicity risks were estimated by calculating absolute excess risk (AER). Results: The LAR ratio favored 3D-CRT for lung cancer induction risk in mediastinal alone (P=.004) and mediastinal plus unilateral neck (P=.02) presentations. LAR ratio for breast cancer was lower for VMAT in mediastinal plus bilateral neck presentations (P=.02), without differences for other sites. For thyroid cancer, no significant differences were observed, regardless of anatomical presentation. A significantly lower AER of cardiac (P=.038) and valvular diseases (P<.0001) was observed for VMAT regardless of disease extent. Conclusions: In a cohort of patients with favorable characteristics in terms of disease extent at diagnosis (large prevalence of nonbulky presentations without axillary involvement), optimized VMAT reduced heart disease risk with comparable risks of thyroid and breast cancer, with an increase in lung cancer induction probability. The results are however strongly influenced by the different anatomical presentations, supporting an individualized approach.« less
  • Purpose: To investigate the Monte Carlo (MC)-based dose verification for VMAT plans by a treatment planning system (TPS). Methods: The AAPM TG-119 test structure set was used for VMAT plans by the Pinnacle3 (convolution/superposition), using a Synergy radiation head of a 6 MV beam with the Agility MLC. The Synergy was simulated with the EGSnrc/BEAMnrc code, and VMAT dose distributions were calculated with the EGSnrc/DOSXYZnrc code by the same irradiation conditions as TPS. VMAT dose distributions of TPS and MC were compared with those of EBT3 film, by 2-D gamma analysis of ±3%/3 mm criteria with a threshold of 30%more » of prescribed doses. VMAT dose distributions between TPS and MC were also compared by DVHs and 3-D gamma analysis of ±3%/3 mm criteria with a threshold of 10%, and 3-D passing rates for PTVs and OARs were analyzed. Results: TPS dose distributions differed from those of film, especially for Head & neck. The dose difference between TPS and film results from calculation accuracy for complex motion of MLCs like tongue and groove effect. In contrast, MC dose distributions were in good agreement with those of film. This is because MC can model fully the MLC configuration and accurately reproduce the MLC motion between control points in VMAT plans. D95 of PTV for Prostate, Head & neck, C-shaped, and Multi Target was 97.2%, 98.1%, 101.6%, and 99.7% for TPS and 95.7%, 96.0%, 100.6%, and 99.1% for MC, respectively. Similarly, 3-D gamma passing rates of each PTV for TPS vs. MC were 100%, 89.5%, 99.7%, and 100%, respectively. 3-D passing rates of TPS reduced for complex VMAT fields like Head & neck because MLCs are not modeled completely for TPS. Conclusion: MC-calculated VMAT dose distributions is useful for the 3-D dose verification of VMAT plans by TPS.« less
  • Purpose: Real-time adaptive planning and treatment has been infeasible due in part to its high computational complexity. There have been many recent efforts to utilize graphics processing units (GPUs) to accelerate the computational performance and dose accuracy in radiation therapy. Data structure and memory access patterns are the key GPU factors that determine the computational performance and accuracy. In this paper, the authors present a nonvoxel-based (NVB) approach to maximize computational and memory access efficiency and throughput on the GPU. Methods: The proposed algorithm employs a ray-tracing mechanism to restructure the 3D data sets computed from the CT anatomy intomore » a nonvoxel-based framework. In a process that takes only a few milliseconds of computing time, the algorithm restructured the data sets by ray-tracing through precalculated CT volumes to realign the coordinate system along the convolution direction, as defined by zenithal and azimuthal angles. During the ray-tracing step, the data were resampled according to radial sampling and parallel ray-spacing parameters making the algorithm independent of the original CT resolution. The nonvoxel-based algorithm presented in this paper also demonstrated a trade-off in computational performance and dose accuracy for different coordinate system configurations. In order to find the best balance between the computed speedup and the accuracy, the authors employed an exhaustive parameter search on all sampling parameters that defined the coordinate system configuration: zenithal, azimuthal, and radial sampling of the convolution algorithm, as well as the parallel ray spacing during ray tracing. The angular sampling parameters were varied between 4 and 48 discrete angles, while both radial sampling and parallel ray spacing were varied from 0.5 to 10 mm. The gamma distribution analysis method (γ) was used to compare the dose distributions using 2% and 2 mm dose difference and distance-to-agreement criteria, respectively. Accuracy was investigated using three distinct phantoms with varied geometries and heterogeneities and on a series of 14 segmented lung CT data sets. Performance gains were calculated using three 256 mm cube homogenous water phantoms, with isotropic voxel dimensions of 1, 2, and 4 mm. Results: The nonvoxel-based GPU algorithm was independent of the data size and provided significant computational gains over the CPU algorithm for large CT data sizes. The parameter search analysis also showed that the ray combination of 8 zenithal and 8 azimuthal angles along with 1 mm radial sampling and 2 mm parallel ray spacing maintained dose accuracy with greater than 99% of voxels passing the γ test. Combining the acceleration obtained from GPU parallelization with the sampling optimization, the authors achieved a total performance improvement factor of >175 000 when compared to our voxel-based ground truth CPU benchmark and a factor of 20 compared with a voxel-based GPU dose convolution method. Conclusions: The nonvoxel-based convolution method yielded substantial performance improvements over a generic GPU implementation, while maintaining accuracy as compared to a CPU computed ground truth dose distribution. Such an algorithm can be a key contribution toward developing tools for adaptive radiation therapy systems.« less