Validation of a GPU‐Based 3D dose calculator for modulated beams

&NA; A superposition/convolution GPU‐accelerated dose computation algorithm (the Calculator) has been recently incorporated into commercial software. The algorithm requires validation prior to clinical use. Three photon energies were examined: conventional 6 MV and 15 MV, and 10 MV flattening filter free (10 MVFFF). For a set of IMRT and VMAT plans based on four of the five AAPM Practice Guideline 5a downloadable datasets, ion chamber (IC) measurements were performed on the water‐equivalent phantoms. The average difference between the Calculator and IC was −0.3 ± 0.8% (1SD). The same plans were projected on a phantom containing a biplanar diode array. We used the forthcoming criteria for routine gamma analysis, 3% dose‐error (global (G) normalization, 2 mm distance to agreement, and 10% low dose cutoff). The γ (3%G/2 mm) average passing rate was 98.9 ± 2.1%. Measurement‐guided three‐dimensional dose reconstruction on the patient CT dataset (excluding the Lung) resulted in a similar average agreement rate with the Calculator: 98.2 ± 2.0%. The mean γ (3%G/2 mm) passing rate comparing the Calculator to the TPS (again excluding the Lung) was 99.0 ± 1.0%. Because of the significant inhomogeneity, the Lung case was investigated separately. The calculator has an alternate heterogeneity correction mode that can change the results in the thorax for higher‐energy beams (15 MV). As this correction is nonphysical and was optimized for simple slab geometries, its application leads to mixed results when compared to the TPS and independent Monte Carlo calculations, depending on the CT dataset and the plan. The Calculator vs. TPS 15 MV Guideline 5a IMRT and VMAT plans demonstrate 96.3% and 93.4% γ (3%G/2 mm) passing rates respectively. For the lower energies, which should be predominantly used in the thoracic region, the passing rates for the same plans and criteria range from 98.6 to 100%. Overall, the Calculator accuracy is sufficient for the intended use.

[1]  J J Battista,et al.  Generation of photon energy deposition kernels using the EGS Monte Carlo code. , 1988, Physics in medicine and biology.

[2]  Todd McNutt,et al.  An Improved Method of Heterogeneity Compensation for the Convolution / Superposition Algorithm , 2014 .

[3]  Lei Dong,et al.  Dosimetry tools and techniques for IMRT. , 2011, Medical physics.

[4]  J. Sempau,et al.  PRIMO: A graphical environment for the Monte Carlo simulation of Varian and Elekta linacs , 2013, Strahlentherapie und Onkologie.

[5]  K Bush,et al.  Monte Carlo simulation of RapidArc radiotherapy delivery , 2008, Physics in medicine and biology.

[6]  A. Ahnesjö Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. , 1989, Medical physics.

[7]  Philippe Lambin,et al.  The next step in patient-specific QA: 3D dose verification of conformal and intensity-modulated RT based on EPID dosimetry and Monte Carlo dose calculations. , 2008, Radiotherapy and Oncology.

[8]  P. Keall,et al.  Modeling the truebeam linac using a CAD to Geant4 geometry implementation: dose and IAEA-compliant phase space calculations. , 2011, Medical physics.

[9]  Yuji Nakaguchi,et al.  3D evaluation of 3DVH program using BANG3 polymer gel dosimeter. , 2013, Medical physics.

[10]  P. Lambin,et al.  A literature review of electronic portal imaging for radiotherapy dosimetry. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[11]  Lu Wang,et al.  4D patient dose reconstruction using online measured EPID cine images for lung SBRT treatment validation. , 2012, Medical physics.

[12]  Indrin J Chetty,et al.  Dose Specification for NRG Radiation Therapy Trials. , 2016, International journal of radiation oncology, biology, physics.

[13]  M. Kaus,et al.  Development and evaluation of an efficient approach to volumetric arc therapy planning. , 2009, Medical physics.

[14]  Geoffrey G. Zhang,et al.  Initial dosimetric evaluation of SmartArc – a novel VMAT treatment planning module implemented in a multi‐vendor delivery chain , 2010, Journal of applied clinical medical physics.

[15]  J. Battista,et al.  A convolution method of calculating dose for 15-MV x rays. , 1985, Medical physics.

[16]  Murty S. Goddu,et al.  Evaluation of the efficiency and effectiveness of independent dose calculation followed by machine log file analysis against conventional measurement based IMRT QA , 2012, Journal of applied clinical medical physics.

[17]  Colin G Orton,et al.  Point/Counterpoint. Patient-specific QA for IMRT should be performed using software rather than hardware methods. , 2013, Medical physics.

[18]  Elinore Wieslander,et al.  Dose perturbation in the presence of metallic implants: treatment planning system versus Monte Carlo simulations. , 2003, Physics in medicine and biology.

[19]  I. Rosen,et al.  Beam‐commissioning methodology for a three‐dimensional convolution/superposition photon dose algorithm , 2000, Journal of applied clinical medical physics.

[20]  James Wheeler,et al.  Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems. , 2012, Practical radiation oncology.

[21]  Andrea Molineu,et al.  Technical Report: Reference photon dosimetry data for Varian accelerators based on IROC-Houston site visit data. , 2016, Medical physics.

[22]  J. Mechalakos,et al.  IMRT commissioning: multiple institution planning and dosimetry comparisons, a report from AAPM Task Group 119. , 2009, Medical physics.

[23]  Geoffrey G. Zhang,et al.  Validation of measurement‐guided 3D VMAT dose reconstruction on a heterogeneous anthropomorphic phantom , 2013, Journal of applied clinical medical physics.

[24]  M. N. Anjum,et al.  IMRT quality assurance using a second treatment planning system. , 2010, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[25]  Geoffrey G. Zhang,et al.  VMAT QA: Measurement-guided 4D dose reconstruction on a patient. , 2012, Medical physics.

[26]  C. Nelson,et al.  Commissioning results of an automated treatment planning verification system , 2014, Journal of applied clinical medical physics.

[27]  Russell H. Taylor,et al.  Real-time dose computation: GPU-accelerated source modeling and superposition/convolution. , 2010, Medical physics.

[28]  Yi Rong,et al.  Parallel/Opposed: IMRT QA using treatment log files is superior to conventional measurement‐based method , 2015, Journal of applied clinical medical physics.

[29]  T Yamamoto,et al.  An integrated Monte Carlo dosimetric verification system for radiotherapy treatment planning , 2007, Physics in medicine and biology.

[30]  Weiguo Lu,et al.  Accurate convolution/superposition for multi-resolution dose calculation using cumulative tabulated kernels , 2005, Physics in medicine and biology.

[31]  Kai Yang,et al.  A real time dose monitoring and dose reconstruction tool for patient specific VMAT QA and delivery. , 2012, Medical physics.

[32]  Fang-Fang Yin,et al.  Task Group 142 report: quality assurance of medical accelerators. , 2009, Medical physics.

[33]  Tufve Nyholm,et al.  Patient-specific IMRT verification using independent fluence-based dose calculation software: experimental benchmarking and initial clinical experience. , 2007, Physics in medicine and biology.

[34]  T. Zhu,et al.  Verification of monitor unit calculations for non-IMRT clinical radiotherapy: report of AAPM Task Group 114. , 2010, Medical physics.

[35]  Indra J. Das,et al.  AAPM Medical Physics Practice Guideline 5.a.: Commissioning and QA of Treatment Planning Dose Calculations — Megavoltage Photon and Electron Beams , 2015, Journal of applied clinical medical physics.

[36]  G. Starkschall,et al.  American Association of Physicists in Medicine Radiation Therapy Committee Task Group 53: quality assurance for clinical radiotherapy treatment planning. , 1998, Medical physics.

[37]  Geoffrey G. Zhang,et al.  Cross-validation of two commercial methods for volumetric high-resolution dose reconstruction on a phantom for non-coplanar VMAT beams. , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.