Development and Validation of a Virtual Monte Carlo Radiotherapy Source Model and Characterization of the Influence of Heterogeneities on Dose Calculation Accuracy PDF Download

Author: Michael Paul Speiser
Publisher:
ISBN:
Category :
Languages : en
Pages : 750

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Author: Reid William Townson
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Monte Carlo (MC) methods for radiotherapy dose calculation are widely accepted as capable of achieving high accuracy. In particular, MC calculations have been demonstrated to successfully reproduce measured dose distributions in complex situations where alternative dose calculation algorithms failed (for example, regions of charged particle disequilibrium). For this reason, MC methods are likely to play a central role in radiotherapy dose calculations and dose verification in the future. However, clinical implementations of MC calculations have typically been limited due to the high computational demands. In order to improve the feasibility of using MC simulations clinically, the simulation techniques must be made more efficient. This dissertation presents a number of approaches to improve the efficiency of MC dose calculations. One of the most time consuming parts of source modeling is the simulation of the secondary collimators, which absorb particles to define the rectangular boundaries of radiation fields. The approximation of assuming negligible transmission through and scatter from the secondary collimators was evaluated for accuracy and efficiency using both graphics processing unit (GPU)-based and central processing unit (CPU)-based MC approaches. The new dose calculation engine, gDPM, that utilizes GPUs to perform MC simulations was developed to a state where accuracy comparable to conventional MC algorithms was attained. However, in GPU-based dose calculation, source modeling was found to be an efficiency bottleneck.

Author: Alexander J. Egan
Publisher:
ISBN:
Category : Monte Carlo method
Languages : en
Pages : 159

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Monte Carlo (MC) algorithms are widely accepted as the most accurate method to calculate dose in a patient geometry. For this work the EGSnrc MC code was used as a benchmark for the identification of dose calculation errors produced by the widely implemented analytical anisotropic algorithm (AAA). By correlating the location and magnitude of these errors with the physical conditions under which AAA is known to fail, a set of error prediction methods was developed which can help to identify clinical plans that are at high risk for AAA dose calculation errors. Once these plans are identified, they can be recalculated with a more accurate algorithm. First, in order to calculate clinical treatment plans with MC, a treatment plan calculation framework (MCTPCF) was developed and validated. The underlying beam model used in the MCTPCF was thoroughly benchmarked against a standard open field data set. Radiochromic film measurements were then used to validate the geometry of the employed MC multileaf collimator (MLC) model. Mechanical functionality of the MCTPCF was verified by calculating several highly modulated clinical treatment plans and comparing them with AAA calculations. Next, three novel error prediction algorithms were developed and validated to a limited extent. The first, designated the field size index (FSI), identifies regions in the treatment plan space where many small fields or blocks overlap, leading to a build-up of beam modeling and volume averaging errors. The second, designated the heterogeneous scatter index (HSI), identifies regions within the electron density distribution where the AAA rectilinear kernel scaling approximation is stressed. The third, designated the low-density index (LDI), identifies regions of very low electron density where AAA is known to overestimate dose. An open field beam model for the 6MV Varian Clinac has been fully parameterized and is able to calculate dose to within 1.3% and 1.0 mm DTA ([sigma][mean] = 0.3%). The MCTPCF has been shown to accurately calculate highly modulated, multiple field treatments. FSI calculations show excellent agreement with MC/AAA deviations in highly modulated MLC fields in water, and to a lesser extent in patient geometry RapidArc treatments. The LDI accurately predicts AAA overdosing for simple geometries, however for the lung case investigated other sources of error made identifying any correlation a challenge. The theoretical structure of the HSI has been developed, however its implementation is still underway. An accurate MC based treatment plan calculation tool has been developed and validated. Three novel error prediction algorithms have been developed, two of which have been validated for homogenous geometries. In particular, the FSI shows promise as both a direct predictor of AAA error, and also as a general treatment plan complexity index. With sufficient benchmarking, these methods may be developed into a clinical tool that can identify treatment plans that are at high risk for AAA dose calculation errors.

Author: H. Zaidi
Publisher: CRC Press
ISBN: 1000687686
Category : Medical
Languages : en
Pages : 441

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Therapeutic Applications of Monte Carlo Calculations in Nuclear Medicine examines the applications of Monte Carlo (MC) calculations in therapeutic nuclear medicine, from basic principles to computer implementations of software packages and their applications in radiation dosimetry and treatment planning. With chapters written by recognized authorit

Author: Mekala Chandrasekaran
Publisher:
ISBN:
Category :
Languages : en
Pages :

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The accuracy of dose calculation algorithms used for radiotherapy treatment planning play a significant role in the clinical outcome of various treatment regimens. Heterogeneities in human anatomy such as lung, air cavities, bone, soft tissue and fat present challenges to the dose calculation algorithms as they are prone to disrupt the charged-particle equilibrium. Monte Carlo (MC) based dose calculation algorithms are proven to be superior to all the current analytical algorithms owing to their ability to account for all the physical interactions that are involved in radiation transport. Numerous publications have examined the differences in physical doses calculated by analytical algorithms when compared to MC in dealing with heterogeneities. However, before this work the clinical significance of these differences in physical dose has never been investigated in detail. An EGSnrc, BEAMnrc and DOSXYZnrc based MC dose calculation engine was set up in a parallel computing environment to simulate three-dimensional conformal radiotherapy (3DCRT) and intensity modulated radiation therapy (IMRT). A Varian 2100 C/D accelerator head was modeled and validated to match measurements of open and dynamic wedged fields in a homogeneous water phantom which was found to be in good agreement with measurements within 2%/2mm and 3%/3mm respectively. In addition, MC calculated doses in a heterogeneous lung phantom were compared to radiochromic film measurements. Overall, there was good agreement between the two, although large differences of upto 16% were found in some cases. This dose calculation system was used to perform MC simulations on computed tomography (CT) images. The clinical impact of the differences in absolute doses calculated by various photon dose calculation algorithms for two clinical tumour sites was investigated. The tumour control probability (TCP) and normal tissue complication probability (NTCP) were estimated using well established bio-mathematical radiobiological models. This work includes the analysis of 7 convolution (i.e. pencil-beam) and convolution-superposition (CS) based photon dose algorithms available in commercial treatment planning systems (TPSs) as well as MC, in treatment plans of non-small cell lung carcinoma (NSCLC) and nasopharyngeal carcinoma (NPC). In both NSCLC and NPC, the convolution algorithms overestimate the dose to the tumour and hence overestimate the TCP to up to 45%. Some of the CS algorithms were comparable to MC though others exhibit significant differences. In NSCLC, the absolute differences in the NTCP values with radiation pneumonitis and rib fracture as end points were not as large as the differences found in the TCPs. On the other hand, in NPC, the overestimation of probability of occurrence of xerostomia by some TPS algorithms may be preventing dose escalation. Parameters for the TCP model were derived by fitting the TCP predictions to published outcome for four widely varying dose-fractionation regimens for a patient cohort undergoing radical radiotherapy treatment for NSCLC. The derived parameter sets strongly depend on the accuracy of the dose calculation algorithm involved. Parameters derived based on dose-distribution data sets obtained using one particular dose calculation algorithm may not hold good when evaluating treatment plans calculated with a different algorithm. In this sub-study, the influence of dose calculation algorithms on TCP model parameters was evaluated. Significant differences were found in TCPs when calculated with inconsistent parameters. Hence, the choice of dose calculation algorithm is crucial and although some algorithms generally perform close to MC in handling inhomogeneities, it is necessary to understand how the underlying differences affect the predicted clinical outcome.

Author: Andreas Kling
Publisher: Springer Science & Business Media
ISBN: 3642182119
Category : Science
Languages : en
Pages : 1200

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This book focuses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications. Special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields.

Author:
Publisher:
ISBN: 9781888340471
Category : Photon beams
Languages : en
Pages : 135

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Author:
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ISBN:
Category :
Languages : en
Pages :

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Targeted radionuclide therapy promises to expand the role of radiation beyond the treatment of localized tumors. This novel form of therapy targets metastatic cancers by combining radioactive isotopes with tumor-seeking molecules such as monoclonal antibodies and custom-designed synthetic agents. Ultimately, like conventional radiotherapy, the effectiveness of targeted radionuclide therapy is limited by the maximum dose that can be given to a critical, normal tissue, such as bone marrow, kidneys, and lungs. Because radionuclide therapy relies on biological delivery of radiation, its optimization and characterization are necessarily different than for conventional radiation therapy. We have initiated the development of a new, Monte Carlo transport-based treatment planning system for molecular targeted radiation therapy as part of the MINERVA treatment planning system. This system calculates patient-specific radiation dose estimates using a set of computed tomography scans to describe the 3D patient anatomy, combined with 2D (planar image) and 3D (SPECT, or single photon emission computed tomography) to describe the time-dependent radiation source. The accuracy of such a dose calculation is limited primarily by the accuracy of the initial radiation source distribution, overlaid on the patient's anatomy. This presentation provides an overview of MINERVA functionality for molecular targeted radiation therapy, and describes early validation and implementation results of Monte Carlo simulations.

Author: N. De Gangi
Publisher:
ISBN:
Category : Gamma rays
Languages : en
Pages : 104

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Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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The remarkable accuracy of Monte Carlo (MC) dose calculation algorithms has led to the widely accepted view that these methods should and will play a central role in the radiotherapy treatment verification and planning of the future. The advantages of using MC clinically are particularly evident for radiation fields passing through inhomogeneities, such as lung and air cavities, and for small fields, including those used in today's advanced intensity modulated radiotherapy techniques. Many investigators have reported significant dosimetric differences between MC and conventional dose calculations in such complex situations, and have demonstrated experimentally the unmatched ability of MC calculations in modeling charged particle disequilibrium. The advantages of using MC dose calculations do come at a cost. The nature of MC dose calculations require a highly detailed, in-depth representation of the physical system (accelerator head geometry/composition, anatomical patient geometry/composition and particle interaction physics) to allow accurate modeling of external beam radiation therapy treatments. To perform such simulations is computationally demanding and has only recently become feasible within mainstream radiotherapy practices. In addition, the output of the accelerator head simulation can be highly sensitive to inaccuracies within a model that may not be known with sufficient detail. The goal of this dissertation is to both improve and advance the implementation of MC dose calculations in modern external beam radiotherapy. To begin, a novel method is proposed to fine-tune the output of an accelerator model to better represent the measured output. In this method an intensity distribution of the electron beam incident on the model is inferred by employing a simulated annealing algorithm. The method allows an investigation of arbitrary electron beam intensity distributions and is not restricted to the commonly assumed Gaussian intensity. In a second component of.