A Phase-Space Model for Simulating Arbitrary Intensity Distribution for shaped Radiosurgery Beams Using the Monte Carlo Method

Chetty, Indrin J.; Marco, J. J. De; Solberg, T.D.; Arellano, A.; Fogg, R.; Mesa, Albert

doi:10.1159/000062297

Cited by 5 publications

(7 citation statements)

References 11 publications

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“…There have been a series of publications related to the use of RT_MCNP for a variety of applications, from radiosurgery to IMRT planning using a micromultileaf collimator. [86][87][88][89][90][91] Finally, treatment planning studies using the GEANT, [92][93][94] PENELOPE, 95 gamma electron positron transport system ͑GEPTS͒, 96,97 and ORANGE ͑Ref. 98͒ ͑MCNP-based͒ MC codes have also been reported.…”

Section: Iiia Review Of Current Monte Carlo Codesmentioning

confidence: 99%

“…111,121 Models developed for reference accelerators were used to accurately commission ͑within 2% / 2 mm of measurements in the high dose/high gradient profile regions͒ electron beams from other machines of similar design by adjusting a few parameters in the model. Implementation of photon and electron beam multiple-source models has been reported for a variety of accelerator manufacturers including, Varian, 122,123 Siemens, 73,124,125 Elekta, 73,86,88 Novalis ͑BrainLab͒, 87,89 and Cyberknife. 126 A possibly more practical approach to beam modeling involves derivation of the model parameters from a standard set of measurements.…”

Section: Iiic1 General Schemesmentioning

confidence: 99%

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Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning

et al. 2007

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The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

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Section: Iiia Review Of Current Monte Carlo Codesmentioning

confidence: 99%

Section: Iiic1 General Schemesmentioning

confidence: 99%

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning

et al. 2007

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“…The tally covers a circular region of diameter 7 cm, corresponding to 14 cm diameter at isocenter, which covers the 10ϫ10 cm 2 maximum field size. The fluence distributions for the open beam are then reconstructed into a 200ϫ200 pixel Cartesian grid with discrete photon fluence elements, in a process previously described by Chetty et al; 15 each pixel has dimensions of 0.5ϫ0.5 mm 2 at the isocenter.…”

Section: Acquisition Of Fluence Distributionmentioning

confidence: 99%

“…In this paper we describe the modifications to a previously developed phase space source model, which incorporate the necessary features for accurate Monte Carlo based verification of IMRT fields using a Novalis linear accelerator. The phase space model, as described by Chetty et al, 14,15 employs a treatment-specific intensity grid to adjust the open beam fluence map for arbitrarily shaped fields. This is an efficient method for simulating IMRT beams because the intensity grid is created in a preprocessing calculation, and it does not require transporting particles through the field defining collimators.…”

Section: Introductionmentioning

confidence: 99%

A Monte Carlo based phase space model for quality assurance of intensity modulated radiotherapy incorporating leaf specific characteristics

DeMarco

Chetty

et al. 2002

Medical Physics

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Dose calculations for intensity modulated radiation therapy (IMRT) require an accurate description of the radiation field defined by the multileaf collimator. A previously developed Monte Carlo phase space model has been modified to provide accurate dose verification for IMRT treatments on a Novalis linear accelerator. We have incorporated into the model the effects of the multileaf collimator geometry, including leaf transmission, interleaf leakage, the rounded leaf tips and the effects of leaf sequencing, as well as the beam divergence and energy variation across the field. The modified source model was benchmarked against standard depth dose and profile measurements, and the agreement between the calculation and measurement is within the AAPM Task Group No. 53 criteria for all benchmark fields used. Film dosimetry was used to evaluate the model for IMRT sequences and plans, and the ability of the model to account for leaf sequencing effects is also demonstrated.

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“…In 2000, BrainLAB provided an IMRT solution for the Novalis, with inverse planning based on the dynamically penalized maximum likelihood (DPL) algorithm described by Llacer (1997). Theoretical and practical characteristics of the DPL algorithm, including performance under gated operation, have been described by several authors (Chetty et al 2000;Arellano et al 2000;Solberg et al 2000a, b;Llacer et al 2001;Hugo et al 2002;. In 2001 BrainLAB introduced their image guidance system based on stereoscopic X-ray imaging.…”

Section: The Novalismentioning

confidence: 99%

Historical Development of Stereotactic Ablative Radiotherapy

Solberg

Siddon

Kavanagh

2012

Stereotactic Body Radiation Therapy

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A Phase-Space Model for Simulating Arbitrary Intensity Distribution for shaped Radiosurgery Beams Using the Monte Carlo Method

Cited by 5 publications

References 11 publications

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning

A Monte Carlo based phase space model for quality assurance of intensity modulated radiotherapy incorporating leaf specific characteristics

Historical Development of Stereotactic Ablative Radiotherapy

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