Monte Carlo simulation of portal dosimetry on a rectilinear voxel geometry: a variable gantry angle solution

Chin, M.; Spezi, Emiliano; Lewis, G. Malcolm

doi:10.1088/0031-9155/48/16/401

Cited by 14 publications

(5 citation statements)

References 20 publications

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“…With the recent introduction of two new sources, ISOURCE 20 and 21, in the DOSXYZnrc/EGSnrc code (Lobo and Popescu 2010), MC simulation and dose calculation of a continuous beam delivery in a single simulation for VMAT is now possible. Other previous studies (Chin et al 2003, Kairn et al 2011 have described a method of combining a CT defined density data set (representing a phantom or patient), and a non-CT defined density data set representing an EPID, validated for single or few conformal fields at arbitrary beam angles. However, a general tool incorporating CT defined patient/phantom data sets together with an arbitrary planar detector positioned as either an entrance or an exit detector has not yet been investigated for VMAT applications.…”

Section: Introductionmentioning

confidence: 99%

A Monte Carlo tool for evaluating VMAT and DIMRT treatment deliveries including planar detectors

et al. 2013

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The aim of this work is to describe and validate a new general research tool that performs Monte Carlo (MC) simulations for volumetric modulated arc therapy (VMAT) and dynamic intensity modulated radiation therapy (DIMRT), simultaneously tracking dose deposition in both the patient CT geometry and an arbitrary planar detector system. The tool is generalized to handle either entrance or exit detectors and provides the simulated dose for the individual control-points of the time-dependent VMAT and DIMRT deliveries. The MC simulation tool was developed with the EGSnrc radiation transport. For the individual control point simulation, we rotate the patient/phantom volume only (i.e. independent of the gantry and planar detector geometries) using the gantry angle in the treatment planning system (TPS) DICOM RP file such that each control point has its own unique phantom file. After MC simulation, we obtained the total dose to the phantom by summing dose contributions for all control points. Scored dose to the sensitive layer of the planar detector is available for each control point. To validate the tool, three clinical treatment plans were used including VMAT plans for a prostate case and a head-and-neck case, and a DIMRT plan for a head-and-neck case. An electronic portal imaging device operated in 'movie' mode was used with the VMAT plans delivered to cylindrical and anthropomorphic phantoms to validate the code using an exit detector. The DIMRT plan was delivered to a novel transmission detector, to validate the code using an entrance detector. The total MC 3D absolute doses in patient/phantom were compared with the TPS doses, while 2D MC doses were compared with planar detector doses for all individual control points, using the gamma evaluation test with 3%/3 mm criteria. The MC 3D absolute doses demonstrated excellent agreement with the TPS doses for all the tested plans, with about 95% of voxels having γ <1 for the plans. For planar dosimetry image comparisons, we defined an acceptable pass rate of >90% of percentage pixels with γ <1. We found that over 90% of control points in the plans passed this criterion. In general, our results indicate that the simulation tool is suitable for accurately calculating both patient/phantom doses and planar doses for VMAT dose delivery. The tool will be valuable to check performance and advance the development of in vivo planar detectors for use in measurement-based VMAT dose verification. In addition, the tool can be useful as an independent research tool for VMAT commissioning of the TPS and delivery system.

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Section: Introductionmentioning

confidence: 99%

A Monte Carlo tool for evaluating VMAT and DIMRT treatment deliveries including planar detectors

et al. 2013

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“…However, due to the resulting oblique angle of the surface of the virtual EPID relative to the rectilinear grid defined by the CT geometry, the surface was jagged rather than straight. This issue has been reported in the literature for Monte Carlo simulations of portal dose in oblique planes 35 . In the current study, the stepped edges at the surface of the virtual EPID varied from 0.7 to 2 mm but were not expected to have an impact on the calculated isodose lines since they were smaller than the calculation dose grid size used in the study (0.25 cm) a .…”

Section: Treatment Planning Using the Modified Ct Datamentioning

confidence: 67%

The use of a treatment planning system to investigate the potential for transmission dosimetry in detecting patient breathing during breast 3D CRT

Reich

Bezak

2008

Australas. Phys. Eng. Sci. Med.

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Transmission dosimetry has the potential for identifying dosimetry errors during radiotherapy treatments by detecting changes in effective beam path between the planned and delivered treatment geometry. In the current study, the Pinnacle treatment planning system was used to model transmitted dose in a "virtual" EPID to investigate the possibility of using transmission dosimetry for detecting patient breathing and setup errors in breast conformal radiotherapy treatments. An opposing tangential beams treatment plan was used as a proof-of-principle study for deliberately introducing shifts in the position of the beams and virtual EPID relative to the CT data, to simulate shallow and deep breathing excursions of 2 mm and 11 mm, respectively. In addition, breathing was combined with setup errors of 0 mm and 2.5 mm in a given direction for each beam. Due to spatial limitations in the original CT data, the CT data was modified to include an additional volume of air surrounding the patient to allow for the virtual EPID to be modelled at sufficient distances from the beam focus. Breathing excursions of both 2 mm and 11 mm could be detected in the transmitted dose planes below the patient. Breathing combined with a 2.5 mm set up errors in the superior-inferior direction further accentuated the distribution of the dose errors in the superior-inferior directions. The predicted changes in transmitted dose due to the simulated delivery errors shows promise for using transmitted dosimetry in the clinic.

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“…25 It is also worth noting that Monte-Carlo techniques have also been used widely for verifying treatment dosimetry through the use of Electronic Portal Imaging Detector (EPID)-based dosimetry. [26][27][28][29] The technique can offer an accurate calculation of the portal dose response of the detector for comparison to the measured portal dose.…”

Section: X-ray Tube Modellingmentioning

confidence: 99%

Monte-Carlo techniques for radiotherapy applications II: equipment and source modelling, dose calculations and radiobiology

Fielding

2023

J Radiother Pract

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Introduction: This is the second of two papers giving an overview of the use of Monte-Carlo techniques for radiotherapy applications. Methods: The first paper gave an introduction and introduced some of the codes that are available to the user wishing to model the different aspects of radiotherapy treatment. It also aims to serve as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal. Results and Conclusions: This paper focuses on the application of Monte-Carlo to specific problems in radiotherapy. These include radiotherapy and imaging beam production, brachytherapy, phantom and patient dosimetry, detector modelling and track structure calculations for micro-dosimetry, nano-dosimetry and radiobiology.

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Monte Carlo simulation of portal dosimetry on a rectilinear voxel geometry: a variable gantry angle solution

Cited by 14 publications

References 20 publications

A Monte Carlo tool for evaluating VMAT and DIMRT treatment deliveries including planar detectors

A Monte Carlo tool for evaluating VMAT and DIMRT treatment deliveries including planar detectors

The use of a treatment planning system to investigate the potential for transmission dosimetry in detecting patient breathing during breast 3D CRT

Monte-Carlo techniques for radiotherapy applications II: equipment and source modelling, dose calculations and radiobiology

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