bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐T‐453: Optimization of Dose Gradient for Gamma Knife Radiosurgery
Authors: Sheth N , Chen Y , Yang J
Published: June 2012

Purpose: The goals of stereotactic radiosurgery (SRS) are the ablation of target tissue and sparing of critical normal tissue. We develop tools to aid in the selection of collimation and prescription (Rx) isodose line to optimize the dose gradient for single isocenter intracranial stereotactic radiosurgery (SRS) with GammaKnife 4C utilizing the updated physics data in GammaPlan v10.1. Methods: Single isocenter intracranial SRS plans were created to treat the center of a solid water anthropomorphism head phantom for each GammaKnife collimator (4 mm, 8 mm, 14 mm, and 18 mm). The dose gradient, defined as the difference of effective radii of spheres equal to half and full Rx volumes, and Rx treatment volume was analyzed for isodoses from 99% to 20% of Rx. Results: The dosimetric data on Rx volume and dose gradient vs. Rx isodose for each collimator was compiled into an easy to read nomogram as well as plotted graphically. The 4, 8, 14, and 18 mm collimators have the sharpest dose gradient at the 64%, 70%, 76%, and 77% Rx isodose lines, respectively. This corresponds to treating 4.77 mm, 8.86 mm, 14.78 mm, and 18.77 mm diameter targets with dose gradients radii of 1.06 mm, 1.63 mm, 2.54 mm, and 3.17 mm, respectively. Conclusion: We analyzed the dosimetric data for the most recent version of GammaPlan treatment planning software to develop tools that when applied clinically will aid in the selection of a collimator and Rx isodose line for optimal dose gradient and target coverage for single isocenter intracranial SRS with GammaKnife 4C.
SU‐E‐T‐454: Dosimetric Comparison between Pencil Beam and Monte Carlo Algorithms for SBRT Lung Treatment Using IPlan V4.1 TPS and CIRS Thorax Phantom
Authors: Fernandez M Castrillon , Venencia C , Garrigó E , Caussa L
Published: June 2012

Purpose: To compare measured and calculated doses using Pencil Beam (PB) and Monte Carlo (MC) algorithm on a CIRS thorax phantom for SBRT lung treatments. Methods: A 6MV photon beam generated by a Primus linac with an Optifocus MLC (Siemens) was used. Dose calculation was done using iPlan v4.1.2 TPS (BrainLAB) by PB and MC (dose to water and dose to medium) algorithms. The commissioning of both algorithms was done reproducing experimental measurements in water. A CIRS thorax phantom was used to compare doses using a Farmer type ion chamber (PTW) and EDR2 radiographic films (KODAK). The ionization chamber, into a tissue equivalent insert, was placed in two position of lung tissue and was irradiated using three treatments plans. Axial dose distributions were measured for four treatments plans using conformal and IMRT technique. Dose distribution comparisons were done by dose profiles and gamma index (3%/3mm). Results: For the studied beam configurations, ion chamber measurements shows that PB overestimate the dose up to 8.5%, whereas MC has a maximum variation of 1.6%. Dosimetric analysis using dose profiles shows that PB overestimates the dose in the region corresponding to the lung up to 16%. For axial dose distribution comparison the percentage of pixels with gamma index bigger than one for MC and PB was, plan 1: 95.6% versus 87.4%, plan 2: 91.2% versus 77.6%, plan 3: 99.7% versus 93.1% and for plan 4: 98.8% versus 91.7%. It was confirmed that the lower dosimetric errors calculated applying MC algorithm appears when the spatial resolution and variance decrease at the expense of increased computation time. Conclusions: The agreement between measured and calculated doses, in a phantom with lung heterogeneities, is better with MC algorithm. PB algorithm overestimates the doses in lung tissue, which could have a clinical impact in SBRT lung treatments.
SU‐E‐T‐460: Isoeffective Dose Display (EQD2) for Composite Plan of Radiosurgery and Conventional 3D Radiotherapy
Authors: Zheng Y , Yuan J , Woods C , Machtay M , Wessels B
Published: June 2012

Purpose: Direct addition of doses between plans with different fractionation fails to provide accurate dose‐response information to anticipate clinical outcome. To combine different fractionation patterns, first‐order biological model correction for dose‐rate must be included. Moreover, 3‐D isoeffect patterns of the combined doses must be displayed so that overlap area to elegant volumes can be avoided. The linear quadratic (LQ) model and biologically effective dose (BED) method were used to produce a combined plan in equivalent 2 Gy fractions (EQD2) for radiosurgery and conventional 3D radiotherapy. Methods: For patients with multiple courses of radiotherapy, dose distributions of the prior and boost treatment plans were converted to BED. The fraction size specified by the prescription was applied globally for each BED calculation, α/β ratio of 10 and 2.5 was used for early and late effect, respectively. Image registration with CT or MR was performed for initial and boost plans. The registration information was applied to dose distributions to obtain the composite EQD2. Results: As a demonstration of this method, two patients were selected who had combined treatments from substantially different modalities. A patient with liver cancer initially received radiotherapy of 30 Gy/10 Fx and re‐irradiation with CyberKnife radiosurgery (15 Gy/1 Fx). The combined plan showed that the PTV received EQD2 of 63.8 Gy. Another patient had brain metastasis treated with GammaKnife of 18 Gy (50% isodose) followed by conventional 3D whole brain radiation of 30 Gy/10 Fx. The minimal combined tumor EQD2 was 74.5 Gy. Early and late calculated responses showed that all critical organ doses were within tolerance. Conclusions: For patients receiving radiation with different fractionation schemes, combined isoeffective dose distributions were calculated and displayed. In both cases, crucial information regarding 3‐D dose distributions assisted the physicians in determining whether tolerance limits of overlap areas of retreated critical structures were preserved.
SU‐E‐T‐462: Calculation of Prescribed Dose for Permanent Implant with Cs‐131 Using LQ Equation including Resensitization
Authors: Luo W , Aryal P , Randall M
Published: June 2012

Purpose: To develop a new biological equivalent dose (BED) formulism that includes repair, repopulation and resensitization (redistribution and reoxygenation), and can be used to calculate prescribed dose for permanent implant with Cs‐131. Methods: Because of lack of sufficient clinical data, the prescribed dose with new isotopes is usually calculated based on BED compared with other isotopes that have already been used in clinical practice. The current widely used formulism of BED calculation for permanent implant which was given by Dale includes cell repair and repopulation but not resensitization. Resensitization can be included in the extended LQ equation (LQR) proposed by Brenner. Applying Dales formulism to Brenners LQR, we obtained a new BED calculation formula that accounts for resensitization. We used this new formulism to calculate the BED that corresponds to the prescribed dose for cervix (with Au‐198) and prostate (with I‐125) permanent implant. Then, we obtained the prescribed dose with Cs‐131 which has the same BED as Au‐198 or I‐125. Results: The new formulism was used for prostate and cervix cancer permanent implant. The prescribed dose with Cs‐131 for cervix was 40 Gy (42 Gy without resensitization) and 66 Gy (69 Gy without resensitization) which were equivalent to 35 Gy and 60 Gy with Au‐198, respectively. For prostate implant, the prescribed dose with Cs‐131 that corresponded to 144 Gy with I‐125 was 135 Gy (124 Gy without resensitization).Conclusion: Resensitization led to significant dose correction for permanent implant. The calculation of BED and dose was dependent on dose itself and thus should be patient‐specific. Since this calculation relied on many biological parameters, and may not be accurate if the parameters are not accurate. Also, the dose prescription should be adjusted based on clinical outcomes.
SU‐E‐T‐463: Biological‐Based Optimization and VMAT is Unnecessary for Stereotactic Body Radiation Therapy
Authors: Mihailidis D , Harmon M , Whaley L , Raja P , Kagadis G
Published: June 2012

Purpose: This study shows that there is no clear dosimetric benefit of biological‐based optimization for either fixed‐beam IMRT or VMAT. Other than shorter delivery times, even VMAT does not offer additional advantage to fixed‐beam IMRT. Methods: A small number of patients for lung, pancreas, spine and brain CA were planned with fixed‐beam IMRT, optimized with (gEUD) and without (DV) biological objectives and, also planned for VMAT with and without gEUD, for comparison. For the lung and brain cases, a non‐coplanar 7–11 beam arrangement was used for fixed‐ beam IMRT and a coplanar ‘hybrid’ arc simulated VMAT with beams set every 5° spacing. For the other treatment sites, all beams were coplanar. For each case, the fixed‐beam IMRT and VMAT plans were optimized with the same objectives. It is important to note that, only 2 segments/beam were allowed for each plan, in order to create small fluence modulation, appropriate for small target volumes during SBRT. Results: For all plans we noticed that there were minor or no dosimetric differences between fixed‐ beam IMRT and VMAT, whether DV or gEUD objectives were used or whether fixed‐beam IMRT or VMAT is used. Keeping the level of beam modulation as‐low‐as possible, for small SBRT targets, one can show that VMAT with or without gEUD optimization does not offer any dosimetric advantage against fixed‐beam IMRT with multiple non‐coplanar beams. This is against the expectation that gEUD‐optimization can Result superior plans than DV‐optimization. The difference is that, for small target volumes like those encountered in SBRT, the complexity of the fluence is not as high as in large field intensity modulated cases. Conclusions: The fact that VMAT with or without gEUD can produce as good plans as fixed‐IMRT does not make VMAT a preferred treatment modality, other than the fact that requires reduced treatment time.
SU‐E‐T‐465: Exploring the Dosimetric and Tumor Control Consequences of Prostate Seed Loss and Migration
Authors: Knaup C , Mavroidis P , Esquivel C , Stathakis S , Swanson G , Papanikolaou N
Published: June 2012

Purpose: Once implanted, prostate brachytherapy seeds are vulnerable to loss and movement. A general estimation of these effects may be useful for making patient care decisions when seeds are lost after the post‐implant scan. The goal of this work was to explore the dosimetric and radiobiological effects of the types of seed loss and migration common in prostate brachytherapy. Methods: This study evaluates five patients. For each, three treatment plans were created using Iodine‐125, Palladium‐103 and Cesium‐131. The three seeds closest to the urethra were identified and modeled as seeds lost through the urethra. The three seeds closest to the exterior of prostatic capsule were identified and modeled as those lost from the prostate periphery. The seed locations and organ contours were exported from Prowess and used by in‐house software to perform the dosimetric and radiobiological evaluation. The radiobiological evaluation was based on the linear‐quadratic model. Seed loss was simulated by removing 1, 2 or 3 seeds near the urethra 0, 2 or 4 days after the implant or removing seeds near the exterior of the prostate 14, 21 or 28 days after the implant. Results: Loss of 1, 2 or 3 seeds through the urethra resulted in D90 reduction of 2%, 5% and 7% loss respectively. Due to delayed loss of peripheral seeds, effects were less severe than for loss through the urethra. However, while the dose reduction is modest for multiple lost seeds, the reduction in tumor control probability was minimal. Conclusions: The goal of this work was to explore the dosimetric and radiobiological effects of the types of seed loss and migration commonly seen in prostate brachytherapy. The results presented show that loss of multiple seeds can cause a substantial reduction of D90 coverage. However, the dose reduction was not seen to significantly reduce tumor control probability.
SU‐E‐T‐475: Nano‐Dosimetric Track Structure Scoring including Biological Modeling with TOPAS‐NBio
Authors: Schuemann J
Published: June 2012

Purpose: To develop a nano‐dosimetric Monte Carlo simulation package, TOPAS‐nBio, based on the TOPAS (TOol for PArticle Simulations) framework that is being developed in a collaboration between the Massachusetts General Hospital (MGH), the SLAC National Accelerator Laboratory and the University of California, San Francisco. The goal is to incorporate biological processes on a sub‐cell level that will provide the basis for a wide range of research in the field of radiobiology, such as bystander effects, biological dose calculations and effects of nano‐particles on radiation therapy. Methods: The TOPAS framework has been utilized to extend the functionality of this tool for particle transport to include nano‐ dosimetry. The physics lists of TOPAS have been extended to include efforts by the Geant4‐DNA group to model physics on nanometer scales, including chemical processes of the first millisecond after irradiation. TOPAS‐nBio uses the functionality of TOPAS to score energy depositions on nanometer scales. A simulation of the setup of a cell culture irradiation experiment has been used as to test the feasibility of the project. Results: Track structures for an irradiation of a cell culture experiment were successfully obtained. Delta‐electron distributions have been produced and single track delta electrons and their energy depositions were observed. Conclusions: This study is a first step in the development of TOPAS‐nBio, a tool that aims at bringing nanometer scale radiation physics and biology together and make Monte Carlo simulations accessible for all radiobiology researchers. The results presented here show a first proof of concept for the development of TOPAS‐nBio.
SU‐E‐T‐476: GPU‐Based Monte Carlo Radiotherapy Dose Calculation Using Phase‐ Space Sources
Authors: Townson R , Jia Xun , Zavgorodni S , Jiang S
Published: June 2012

Purpose: To design an efficient method for utilizing phase‐space source models in the GPU‐based Monte Carlo (MC) dose calculation engine gDPM. Methods: In GPU‐based MC algorithms, particles are transported in parallel on different threads. Particles of different types and energies can require significantly different execution times. This can cause “thread divergence” and lower efficiency when source particles are read sequentially from a phase‐space file. We have developed a strategy for utilizing phase‐ space files in a GPU compatible manner whereby the particles are grouped into phase‐space‐lets (PSLs) by type, energy, and location in the phase‐ space plane. This allows for dose calculations using only particles inside the field opening defined by the secondary collimators. For validation, the gDPM PSL implementation is compared with DOSXYZnrc using a BEAMnrc phase‐space source model as input. Results: Two phase‐spaces were generated using a BEAMnrc head model of a 6MV Varian Clinac 21EX, one above the upper jaws used to generate PSLs for gDPM and the other below the lower jaws used for DOSXYZnrc dose calculation. Profiles and depth dose curves for a variety of field sizes were generated in a water phantom. The agreement between gDPM and DOSXYZnrc is within 2% for all field sizes. For the 10 cm × 10 cm field, the calculation times of 650 million histories were 147 CPU hours and 54 GPU seconds for DOSXYZnrc and gDPM, respectively. In addition, we have tested the gDPM PSL implementation for dose calculation in a realistic 7‐field IMRT tongue treatment plan. The calculation times were 59 CPU‐hours and 66 GPU‐ seconds for DOSXYZnrc and gDPM for 485 million histories, respectively. Gamma pass rate for the two dose distributions was 99.54% for 3 mm/3% criteria within the 10% isodose. Conclusions: Methods for the efficient use of phase‐space sources for GPU‐based MC dose calculations have been developed.
SU‐E‐T‐482: A More Accurate Bare 125I Spectrum
Authors: Rodriguez M , Rogers D
Published: June 2012

Purpose: To compare measured energy spectra of 125I brachytherapy seeds with Monte Carlo calculated energy spectra when using the bare 125I energy spectrum recommended by TG43 and the one presented in NCRP Report 58 and to determine the impact of these different spectra on the calculation of the dose rate constant. Methods: The energy spectrum, absorbed dose at 1 cm on the bisector and air kerma strength of 10 different 125I seeds were calculated using the EGSnrc BrachyDose Monte Carlo code. Energy bin width was 0.2 keV. The simulations were done with the bare 125I energy spectrum recommended by TG43 or NCRP Report 58. Statistical uncertainties for the energy spectra were 0.02% and 0.1% or less for the other clinical parameters. Results are compared with published measuredvalues. Results: There is close agreement between the measured and calculated branching ratio generated by 125I seeds when simulated using the spectrum presented in NCRP58. However, for all seeds a 7% lower value is observed in the 31 keV peak when using data suggested by TG43. On the other hand, differences in the average energy, air kerma, absorbed dose and dose rate constant are undetectable (less than statistical uncertainty, <0.1%) when performed with either spectrum. Conclusions: For dosimetric parameter calculations, the bare 125I energy spectra presented in TG43 and NCRP58 produce indistinguishable results. However, for branching ratio investigation purposes, there is a clear difference in the 31 keV peak between values obtained using the different 125I bare energy spectra. Measured 125I branching ratios are in close agreement with those calculated using the bare 125I energy spectrum presented in NCRP58. Reassessment of the bare 125I energy spectrum recommended in TG43 is suggested.
SU‐E‐T‐484: Potential Clinical Impact of Dosimetric Uncertainties in Proton Therapy
Authors: Mirkovic D , Titt U , Mohan R
Published: June 2012

Purpose: The analytical algorithms which are used widely for proton treatment planning in the current clinical practice may have significant dosimetric uncertainties in highly heterogeneous regions. The aim of this study is the assessment of the potential clinical impact of these uncertainties. Methods: A cohort of 8 patients with local (in field) recurrences, originally treated for lung cancer at our institution, was selected for this study. CT scans and treatment plans were used to assemble the input files for the Monte Carlo (MC) code MCNPX. The total energy deposition inside the patient volume was computed with statistical uncertainty of less than 2% and converted to dose‐in‐water. The results were compared to the dose computed by the clinical treatment planning system (TPS). The area of the recurrence was contoured on the follow‐up PET/CT study for each of the patients and registered to the planning CT. Results: While there is acceptable agreement between the TPS and the Monte Carlo dose in homogeneous regions, there are noticeable differences caused by heterogeneities. The regions of largest differences are the points around and beyond the distal edge and points around the lateral penumbra and in several patients the target has received lower then the prescribed dose. The area of the recurrence corelates well with the MC predicted underdosed area of the target. Conclusions: The uncertanties in analytical dose algorithms used in clinical TPSs may result in suboptimal target coverage increasing the possibility of tumor recurrence. Accurate Monte Carlo simulations can be used to predict and avoid the situations in which the analytical algorithms have high uncertanties providing for more robust treatment planning.
SU‐E‐T‐488: Dose Calculation Model Using the Simplified Monte Carlo Method with an Initial Beam Model Adapted to a Beam‐Wobbling System
Authors: Tansho R , Kohno R , Takada Y , Hotta K , Hara Y , Nagafuchi K , Suzuki Y , Akimoto T
Published: June 2012

Purpose: We have developed an accurate dose calculation model based on a simplified Monte Carlo (SMC) method adapted to a beam‐wobbling delivery system at National Cancer Center Hospital East (NCCHE). We used an initial beam model specific to the beam‐wobbling system to reproduce accurately different dose distributions in two lateral directions (x‐ and y‐directions) perpendicular to each other. Methods: The SMC calculates a dose distribution by tracking individual protons. The SMC starts tracking protons at an entrance of a range compensator. Protons are generated in an initial phase space adapted to the wobbler system. Since two wobbling‐magnets are located at separate places with different distances from the iso‐center, different dose distributions are formed in x‐ and y‐directions. We derived an initial phase space distribution for the beam‐wobbling system using an analytical method. We used the SMC method with the initial beam model to calculate dose distributions accurately. To verify accuracy of the calculation method, we measured the dose distribution in a homogeneous phantom formed by 235 MeV protons passing through a L‐shaped range compensator. We used a 2D‐array of parallel‐plate ionization chambers (2D Array seven29®) to measure dose distributions with a sampling period of 5 mm. Results: The measured dose distribution in the x‐direction was different from that in the y‐direction. Our calculation model reproduces the measurement results well in both lateral directions. In addition, the calculation reproduced the dose increments in edge regions contributed by edge‐scattered protons in collimator. It indicates the advantage of the SMC. Conclusions: A dose calculation model has been developed based on the simplified Monte Carlo method applied to a beam‐wobbling system. By adapting the initial beam model to the wobbling system, the SMC method is found to reproduce observed different dose distributions in x‐ and y‐directions well.
SU‐E‐T‐489: Quantum versus Classical Trajectory Monte Carlo Simulations of Low Energy Electron Transport
Authors: Thomson R , Kawrakow I
Published: June 2012

Purpose: Widely‐used classical trajectory Monte Carlo simulations of low energy electron transport neglect the quantum nature of electrons; however, at sub‐1 keV energies quantum effects have the potential to become significant. This work compares quantum and classical simulations within a simplified model of electron transport in water. Methods: Electron transport is modeled in water droplets using quantum mechanical (QM) and classical trajectory Monte Carlo (MC) methods. Water droplets are modeled as collections of point scatterers representing water molecules from which electrons may be isotropically scattered. The role of inelastic scattering is investigated by introducing absorption. QM calculations involve numerically solving a system of coupled equations for the electron wavefield incident on each scatterer. A minimum distance between scatterers is introduced to approximate structured water. The average QM water droplet incoherent cross section is compared with the MC cross section; a relative error (RE) on the MC results is computed. Results: RE varies with electron energy, average and minimum distances between scatterers, and scattering amplitude. The mean free path is generally the relevant length scale for estimating RE. The introduction of a minimum distance between scatterers increases RE substantially (factors of 5 to 10), suggesting that the structure of water must be modeled for accurate simulations. Inelastic scattering does not improve agreement between QM and MC simulations: for the same magnitude of elastic scattering, the introduction of inelastic scattering increases RE. Droplet cross sections are sensitive to droplet size and shape; considerable variations in RE are observed with changing droplet size and shape. Conclusions: At sub‐1 keV energies, quantum effects may become non‐negligible for electron transport in condensed media. Electron transport is strongly affected by the structure of the medium. Inelastic scatter does not improve agreement between QM and MC simulations of low energy electron transport in condensed media.
SU‐E‐T‐490: Comparison of XVMC Monte Carlo Dose Calculations with Eclipse AAA Calculations for RapidArc Plans
Authors: Stelljes T , Alber M , Poppe B , Laub W
Published: June 2012

Purpose: The consistency between the AAA and XVMC algorithm in the treatment planning for RapidArc is investigated. While the majority of the radiation field is blocked by the MLC system, multiple small dose islands with MLC opened only slightly can be observed in one control point. This raises questions on how accurate the clinically used AAA algorithm in Eclipse is able to calculate RapidArc dose distributions. The fast Monte Carlo Code XVMC was used as a benchmark to test the AAA algorithm. Methods: RadpidArc plans of 25 patients were calculated with AAA and XVMC. The patient cohort consisted of 4 different cancer sites (H&N, upper abdominal, lung, prostate). Dose distributions, PTV and OAR coverage were compared looking at the PTV mean dose Dmean, the volume V95% of the PTV receiving 95% of the prescribed dose, the dose D95% delivered to 95% of the PTV Volume, the percentage PTV mean dose with respect to the prescribed dose Dmean/prescr and OAR mean dose. Results: The recalculation of RapidArc plans yielded good agreement of both calculation algorithms for treatment plans of all four cancer sites. PTV mean dose differences of AAA and XVMC were found to be in between −0.11% and 4.89% of the prescribed dose. The mean dose difference found was 0.48±0.77 Gy. Local dose differences were found when comparing dose distributions in regions of big mass density differences and in high dose regions. One head and neck plan and one prostate plan revealed significant differences in PTV coverage (ΔDmean=3.25 Gy) and OAR mean dose (prostate mean dose −13.71 Gy) respectively. Conclusions: The vast majority of treatment plans calculated with the AAA algorithm were found to agree within the expected and acceptable tolerances compared to XVMC results. Nevertheless in some cases dose differences were observed that could be of clinical significance. This work was funded by a Varian grant. Wolfram Laub is working in the physics group of CMS.
SU‐E‐T‐491: A FLUKA Monte Carlo Computational Model of a Scanning Proton Beam Therapy Nozzle at IU Proton Therapy Center
Authors: Moskvin V , Cheng C , Anferov V , Nichiporov D , Zhao Q , Takashina M , Parola R , Das I
Published: June 2012

Purpose: Charged particle therapy, especially proton therapy is a growing treatment modality worldwide. Monte Carlo (MC) simulation of the interactions of proton beam with equipment, devices and patient is a highly efficient tool that can substitute measurements for complex and unrealistic experiments. The purpose of this study is to design a MC model of a treatment nozzle to characterize the proton scanning beam and commissioning the model for the Indiana University Health Proton Therapy Center (IUHPTC. Methods: The general purpose Monte Carlo code FLUKA was used for simulation of the proton beam passage through the elements of the treatment nozzle design. The geometry of the nozzle was extracted from the design blueprints. The initial parameters for beam simulation were determined from calculations of beam optics design to derive a semi‐empirical model to describe the initial parameters of the beam entering the nozzle. The lateral fluence and energy distribution of the beam entering the nozzle is defined as a function of the requested range. The uniform scanning model at the IUHPTC is implemented. The results of simulation with the beam and nozzle model are compared and verified with measurements. Results: The lateral particle distribution and energy spectra of the proton beam entering the nozzle were compared with measurements in the interval of energies from 70 MeV to 204.8 MeV. The accuracy of the description of the proton beam by MC simulation is better than 2% compared with measurements, providing confidence for complex simulation in phantom and patient dosimetry with the MC simulated nozzle and the uniform scanning proton beam. Conclusions: The treatment nozzle and beam model was accurately implemented in the FLUKA Monte Carlo code and suitable for the research purpose to simulate the scanning beam at IUHPTC.
SU‐E‐T‐494: Variation of Mucosal Dose in Head‐And‐Neck Radiotherapy: A Phantom Study Using Monte Carlo Simulation
Authors: Chow J , Owrangi A
Published: June 2012

Purpose: This phantom study investigated variations of mucosal dose on photon beam energy, beam angle, multi‐beam configuration and mucosal thickness, when using small photon fields in head‐and‐neck radiotherapy. Methods: Cylindrical mucosa phantoms with bone and air heterogeneities were created with mucosal thickness (normal tissue) equal to 1, 2 and 3 mm. For dosimetric comparison, corresponding homogeneous phantom with all heterogeneities replaced by normal tissue was also used. These phantoms were irradiated by photon beams with field size = 1 × 1 cm2. Beam energies of 6 and 18 MV were used with beam angles varied to 0°, 90° and 180°. Moreover, multi‐beam configurations of 2, 4 and 8 beams were used, and doses along the central‐beam axis in the mucosal tissue were calculated using Monte Carlo simulations (EGSnrc code). Results: For beam angle equal to 0°, the mucosal surface doses decreased slightly with an increase of the mucosal thickness (1–3 mm), while the surface dose of the 6 MV photon beam was decreased more significantly than the 18 MV. For beam angle equal to 180°, variation of muscosal surface dose with its thickness was found insignificant. For different multi‐beam configurations, it was found that the variation of mucosal dose on its thickness became insignificant when the number of photon beams around the mucosa was increased. In addition, the change of mucosal dose due to the bone and air heterogeneities depended on the photon beam energy, beam angle and muscosal thickness. Conclusions: It is concluded that mucosal dose depends on variations of beam energy, beam angle, multi‐beam configuration and mucosal thickness for small photon fields. The dosimetric information in this study should be considered in studying the mucosal complications in head‐and‐neck IMRT, so that an optimized treatment strategy to minimize mucosal complications can be developed. This study is supported by the Deanâ€™s Fund Grant in the University of Toronto.
SU‐E‐T‐499: Validation of the Varian Generic Phase Space Files for Monte Carlo Calculations of Dose Distributions for the TrueBeam Linac Head
Authors: Wang L , Xing L , Sawkey D , Constantin M , Svatos M , Mok E
Published: June 2012

Purpose: To validate the generic phase space files for Varian TrueBeam linac head simulations. Methods: The generic phase space files include the simulation results of 6MV, 10MV, 6MV FFF, and 10MV FFF (flattening‐filter free) operating modes of TrueBeam for patient‐independent linac head components. Using the generic phase space files as the radiation sources, the BEAMnrc Monte Carlo codes are used to simulate the patient‐dependent parts of the TrueBeam linac and the resulting phase space files are generated at a plane just before entering a water phantom for 4 different field sizes (5×5, 10×10, 20×20, and 40×40 cm2). Dose distributions are calculated by DOSXYZnrc in the water phantom of size 50×50×40 cm3. The percentage‐depth‐dose (PDD) curves and lateral dose profiles at three different depths (dmax, 10cm, 20cm) are obtained. Comprehensive comparisons have been made for a total of 64 dose profiles (including PDDs) between the Monte Carlo calculations and the measured data. The gamma index analysis is performed for all the comparisons. Results: The matching of the calculated dose distributions to the measured ones is analyzed by the gamma index method with a criterion of 2% dose tolerance and 2 mm distance‐to‐agreement. Of the 64 comparisons, the minimum gamma index passing rate is at least 92%, after taking into account the statistical nature of the Monte Carlo calculated dose values. Despite the existence of latent variance of phase space files, the phantom dose calculation uncertainty can be less than 1% for field sizes as small as 5×5 cm2. The computing time saved by using phase space files could be a factor of 5–10. Conclusions: The Varian generic phase space files are accurate and efficient radiation sources for Monte Carlo calculations of radiation dose distributions for TrueBeam linac head. This work was supported in part by Varian Medical Systems and the NIH (1R01 CA104205 and 1R21 CA153587).
SU‐E‐T‐501: Perturbation of TG‐43 Parameters of the Brachytherapy Sources under Insufficient Scattering Materials
Authors: Zehtabian M , Sina S , Faghihi R , Meigooni A
Published: June 2012

Purpose: According to the TG‐43 recommendations of American Association of Physicist in Medicine (AAPM), the dosimetry parameters of brachytherapy sources are obtained in a water phantom with full scattering conditions. However, in many actual clinical treatments the source are not surrounded with sufficient tissue in all directions to provide the full scattering condition. HDR brachytherapy of the breast or 125I eye‐plaque treatment of the ocular melanoma are among the treatment sites that fits this category. In this project, the impact of insufficient phantom material surrounding the 137Cs, 192Ir, and 103Pd brachytherapy source on their TG43 dosimetric characteristics has been investigated. Methods: In this study, the effect of the insufficient tissue (referred here as missing tissues) around the brachytherapy sources on their TG‐43 dosimetric parameters have been investigated using MCNP5 Monte Carlo code. The brachytherapy sources were simulated in different locations inside a cubical water phantom with the dimensions of 30*30*30 cm3. The variation of the dosimetric parameters of the three sources (i.e. Î>, g(r), and F(r,θ)) were compared to the values from full scattering conditions (i.e. source at the center of the phantom). Results: The results of this study indicate the variation of g(r)and 2D anisotropy function of the brachytherapy sources as a function of the missing tissue thickness. These changes increase by decreasing the energy of the photons emitted by the brachytherapy sources. These differences are mainly due to the lack of full scattering condition for the points near the phantom boundary. Conclusions: Unlike the published data for symmetric, but insufficient phantom material around the source, the impact of asymmetric phantom materials have been evaluated on dosimetric characteristics of the brachytherapy sources.
SU‐E‐T‐502: Dose Perturbation Effects Near Implant Surfaces Caused by Secondary Electron Transport in Photon‐Beam Therapy
Authors: Chofor N , Poppe B , Harder D
Published: June 2012

Purpose: To investigate the dose perturbation effects at interfaces between water and a Titanium implant, attributable to secondary electron transport across the interface, during high energy photon radiotherapy. While dose enhancement is characteristic for the proximal interface of a high‐atomic number implant, the dose perturbation at the distal interface varies from reduction to enhancement, requiring proper computation of secondary electron transport effects. The backward and forward perturbation factors pb and pf will be calculated. Methods: Using DOSRZnrc, depth dose curves were computed in a water phantom using photon spectra of nominal energies 4, 6, 10, 15, 24 MV for conditions (i) homogeneous water without any insert, (ii) alternatively with Titanium inserts of thicknesses 3 and 5 cm placed at 10 cm water depth. Backscatter factor pb was computed as the ratio of the dose with implant against that without implant, whereas pf was calculated by first accounting for photon attenuation in the implant and then taking the ratio of the dose with implant against that without implant. Results: At the front interface, pb is independent of the material thickness and varies slightly with beam energy and incident angle. On consideration of photon attenuation in the implant, pf was also found to be independent on material thickness, but strongly varying with energy, including change of sign. Conclusions: For 4–24 MV photon beams the maximum spread of the dose perturbation effect remains within only a few millimeters from the interface, with pb values ranging from 1.18–1.22, while factor pf ranges from 0.9–1.21 at normal incidence, indicating the extent to which planning systems may over‐ or underestimate the doses near implant interfaces. At inclined beam incidence the dose perturbation effects even increase, and for instance pb (1.24–1.25) and pf (0.85–1.32) were determined for 6 MV and 24 MV beams at 45° incidence.
SU‐E‐T‐503: IMRT Optimization Using Monte Carlo Dose Engine: The Effect of Statistical Uncertainty
Authors: Tian Z , Jia X , Graves Y , Uribe‐Sanchez A , Jiang S
Published: June 2012

Purpose: With the development of ultra‐fast GPU‐based Monte Carlo (MC) dose engine, it becomes clinically realistic to compute the dose‐deposition coefficients (DDC) for IMRT optimization using MC simulation. However, it is still time‐consuming if we want to compute DDC with small statistical uncertainty. This work studies the effects of the statistical error in DDC matrix on IMRT optimization. Methods: The MC‐computed DDC matrices are simulated here by adding statistical uncertainties at a desired level to the ones generated with a finite‐size pencil beam algorithm. A statistical uncertainty model for MC dose calculation is employed. We adopt a penalty‐based quadratic optimization model and gradient descent method to optimize fluence map and then recalculate the corresponding actual dose distribution using the noise‐free DDC matrix. The impacts of DDC noise are assessed in terms of the deviation of the resulted dose distributions. We have also used a stochastic perturbation theory to theoretically estimate the statistical errors of dose distributions on a simplified optimization model. Results: A head‐and‐neck case is used to investigate the perturbation to IMRT plan due to MC's statistical uncertainty. The relative errors of the final dose distributions of the optimized IMRT are found to be much smaller than those in the DDC matrix, which is consistent with our theoretical estimation. When history number is decreased from 108 to 106, the dose‐volume‐histograms are still very similar to the error‐free DVHs while the error in DDC is about 3.8%. Conclusions: The results illustrate that the statistical errors in the DDC matrix have a relatively small effect on IMRT optimization in dose domain. This indicates we can use relatively small number of histories to obtain the DDC matrix with MC simulation within a reasonable amount of time, without considerably compromising the accuracy of the optimized treatment plan. This work is supported by Varian Medical Systems through a Master Research Agreement.
SU‐E‐T‐506: Dosimetric Study for Shallow‐Seated Tumor Using Passive/active Scanning Proton Beam
Authors: Toramatsu C , Matsuura T , Nihongi H , Takao S , Miyamoto N , Shimizu S , Kinoshita R , Umegaki K , Shirato H
Published: June 2012

Purpose: To investigate the possibility of using a single spot scanning proton beam to treat superficial lesions. Methods: A cylindrical phantom with a simulated superficial target (it seated 0.5–4cm depth from the surface, volume: 270cm3) was created in Eclipse treatment planning system. Three proton plans were generated: (a) a single AP uniform scanning beam with aperture and range compensator; (b) a single AP spot scanning beam with a pre‐absorber. The location and thickness of the pre‐absorber were calculated using Geant4 to Monte Carlo code to make use of the available spot scanning beams to get a conformal plan. (c) a five‐beam spot scanning beam plan using multi‐field optimization. The prescription is 54 cobalt grey equivalent (CGE) which covers 95% of the target. The target coverage, lateral penumbra at 2 and 4cm depth in water, the doses to normal tissue (phantom‐target) and skin (2mm from the surface) were evaluated and compared for three plans. Results: The mean doses to the target are comparable within 2.4% for all three plans. The conformity indices (at 95%) are 1.36, 1.04 and 0.98 for plan (a), (b) and (c) respectively. The lateral penumbra (80% to 20%) for plan (a), (b) are both 0.73 cm, while it is 3.75 cm for plan (c). The skin dose which received more than 40 (CGE) from plan (a) is 10% higher than that of other two plans. Plan (c) has 70% higher mean doses to normal tissue than that of plan (a) and (b). Conclusions: Each plan provides good coverage of target. And in this study, it showed that, with a properly designed pre‐absorber, it is possible to use a single spot scanning beam to treat superficial lesion. The plan provides good target coverage and maintains normal tissue sparing in the mean time.
SU‐E‐T‐512: Evaluation of Treatment Planning Dose Calculation Accuracy at the Interface of Prosthetic Devices
Authors: Paulu D , Alaei P
Published: June 2012

Purpose: To evaluate the ability of treatment planning algorithm to accurately predict dose delivered at the interface of high density implanted devices. Methods: A high density (7.6 g/cc) Cobalt‐Chromium‐Molybdenum hip prosthesis was molded into an epoxy‐based cylindrical leg phantom. The phantom was designed to be separated in half to access the prosthesis and to place the TLDs. Using MVCT to image the apparatus, a simple treatment plan was developed using the Philips Pinnacle treatment planning system. Wires were placed in the molded epoxy to allow for accurate definition of measurement sites (TLD positions) along the surface of the prosthesis. Micro‐cube TLDs (1 mm3) were placed at six measurement locations for which the dose had been calculated by the treatment planning system. An Elekta Synergy linear accelerator was used to deliver a 400 cGy plan to the phantom with 6 MV photons in a single fraction. A total of four 10 cm × 21 cm fields were used at 0, 90, 180, and 270 degree gantry rotations. Results: Initial results indicate that the measured dose is 7–17% lower than the dose calculated by the treatment planning system. Further study using high energy beams are also in progress. Conclusions: Initial results indicate that the treatment planning system does predict the dose near a high density prosthetic device within 10–15% but underestimates the dose. The results of this study could help in designing treatment plans which would reduce the uncertainty of the dose delivered in the vicinity of prosthetic hip implants and similar devices.
SU‐E‐T‐514: Implementation and Commissioning of a Micro Multileaf Collimator in Pinnacle Treatment Planning System
Authors: Hernández T García , González L Brualla , González A Vicedo , Ferrando J Rosello , Cabañero D Granero
Published: June 2012

Purpose: To model and validate, in a Pinnacle treatment planning system, a Brainlab micromultileaf collimator mounted on a Primus Siemens accelerator. The objective is to take advantage of the collapsed cone convolution algorithm and the ability of this system modelling rounded leaf‐ end MLC's. Method: The micro multileaf collimator was modelled using fixed accelerator jaws with a value of 9.2×9.2 cm2. Profiles and depth dose curves for a wide range of square fields at SSD of 100 cm and depths of 1.5,5,10 and 20 cm were measured using a Scanditronix stereotactic SFD diode. Output factors were measured using a stereotactic unshielded diode for field sizes from 0.6×0.6 cm2 to 3×3 cm2. For wider fields a Scanditronix ic15 ionization chamber was used. EDR2 films were used to measure adjacent fields in the transverse and longitudinal direction. The film measurements were compared to Pinnacle calculations to model and validate the leaf tip radius, leaf offset calibration values and tongue and groove width. Results: Pinnacle calculations and measurements agree within 2% or 2mm except for the tails of largest fields where differences are <3.5%. Comparison of film measurements and Pinnacle calculations give the optimal value for leaf tip radius of 15 cm and for tongue and groove width of 0.04 cm. Conclusions: Pinnacle models a Brainlab micromultileaf collimator mounted on a Siemens Primus accelerator with acceptable results for clinical treatments.
SU‐E‐T‐520: Quantitative Evaluation of Metal Artifacts in CT and Cone‐Beam CT Images on the Accuracy of Dose Calculation
Authors: Oyewale S , Ahmad S , Ali I
Published: June 2012

Purpose: To investigate effects of metal artifacts on the dose calculation accuracy of three dose calculation algorithms on CT and cone‐beam CT images. Methods: A phantom with and without metal objects was scanned using CT simulator and on‐board kV CBCT. Conformal 5‐field treatment plans with identical physical and dosimetric parameters were created in the Eclipse™ treatment planning system for CT and CBCT images. The beams were designed to avoid entering through metallic object. Three dose calculation algorithms were used in the plans: (a) pencil beam convolution with modified Batheo (PBC‐MB), (b) equivalent TAR (PBC‐ET), and (c) analytical anisotropic algorithm (AAA). The dose calculation on the phantom CT images without metal was used as reference to compare with doses calculated using scans with metal objects. The gamma analysis and percentage dose differences were used to quantify the dosimetric effects of image artifacts from metal on CT and CBCT numbers. Results: The dose difference analysis shows that mean percentage dose differences (MPDD) for CBCT with metal artifacts ranged from −0.12% to −0.26% with an average of −0.20% for PBC‐MB, −0.25% to −0.39%, with average −0.31% for PBC‐ET, and −0.25 to −0.84%, with average −0.62% for AAA for all planes. The PBC‐MB showed the least difference in dose and highest gamma passing rates with the AAA consistently having the highest differences and lowest gamma passing rates. This might result from accurate consideration of scattered dose in heterogeneities by AAA. All MPDD for doses calculated on CT and CBCT using different dose calculation algorithms were not significant (within 1%). Conclusion: The image artifacts due to streaking from metal objects were generally small (within 1%) for the dose calculated using the different treatment planning algorithms on CT and CBCT images. Furthermore, the dose difference from CT‐number variation between CBCT and CT were negligible.
SU‐E‐T‐521: Dosimetric Effect on Variation of Patient Size in Prostate Volumetric Modulated Arc Therapy
Authors: Chow J , Jiang R
Published: June 2012

Purpose: To evaluate dosimetric variations of planning target volume (PTV) on critical organs such as rectal wall, bladder and femoral head, when the patient size changes due to weight loss in prostate volumetric modulated arc therapy (VMAT). Methods: Three patients with small (32.0 cm3), medium (48.4 cm3) and large (86.5 cm3) prostate, selected from a group of 30 were planned for prostate VMAT using the 6 MV photon beam. Patient size reduction due to weight loss was modeled by contracting the external body contour with reduced depths (0.5 – 2 cm) in the anterior and both lateral directions. Original normal tissue excluded from the contracted body contour was replaced by air. Dose calculation was repeated with the same planned beam geometry and dose prescription. Dose‐volume histograms, dose‐volume points of the PTV, clinical target volume (CTV) and critical organs were calculated with variations of reduced depth. Results: D99% of the PTV and CTV were found to have increased 2.65 ± 0.03% per cm and 2.75 ± 0.15% per cm of reduced depth in the range of 0.5 and 2 cm. D30% of the rectal wall and bladder increased 2.29 ± 0.12% per cm and 2.31 ± 0.83% per cm, respectively. D5% of the femoral head increased by 3.30 ± 0.11% per cm of reduced depth. Moreover, there was more than 5% increase of minimum, maximum and means doses for the PTV, CTV and critical organs when the reduced depth reached 2 cm. Conclusions: This study provided estimated results of dosimetric changes due to variation of patient size in prostate VMAT. The dosimetric information should help radiation oncology staff to justify changes of dose distribution, when patient weight loss occurs during prostate VMAT. Dose variations of more than 5% were found when the patient's reduced depth was equal to 2 cm. Actual or potential conflicts of interest do not exist.