bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐T‐674: Development and Validation of a Monte Carlo Model of a Kilovoltage X‐Ray Therapy Unit for Chest Wall Irradiation
Authors: Mosleh‐Shirazi MA , Faghihi R , Hadad K , Mosallaei A , Zeinali B , Karbasi S
Published: November 2011

Purpose: Given the high local control rates observed in breast cancer patients undergoing chest‐wall irradiation by kilovoltage x‐rays, we aimed to revisit this treatment modality by accurate calculation of dose distributions using Monte Carlo simulation. We report on the development of a Monte Carlo model of the Siemens Stabilipan kilovoltage unit and its validation using various experimental measurements for chest wall irradiation. Methods: The machine components including the housing, anode, filter, collimators, etc were simulated using the MCNP4C code. To validate the 120 kVp beam model, the 1st and 2nd half‐value layers (HVLs) were first measured using high‐purity Al foils and an ion chamber. The percentage depth doses (PDDs) and off‐axis beam profiles (depths 2 and 5 cm) for beams normally incident on a water phantom were also measured using diode and ion chamber dosimeters. Finally, dose measurements were performed for a realistic situation of oblique incidence on the chest wall using 10 thermoluminescence dosimeters (TLDs) placed within the chest wall, heart and lung of an inhomogeneous Rando phantom. The results of the experimental measurements and MCNP simulations were then compared. Results: The 1st and 2nd HVLs were 3.8 and 10.3 mmAl respectively, which were in close agreement with the values obtained by MCNP (3.8 and 10.6 mmAl). The differences between the measured and calculated PDDs and beam profiles in water were less than 2mm/2% for all data points. MCNP‐calculated relative doses agreed with TLD measurements in the Rando phantom to within 4.5% of the prescription dose, the differences for majority of the data points being within 2%. Conclusions: The acceptable level of agreement between the results of the simulations and the measurements validate the accuracy of the MCNP model for use in treatment planning studies of chest‐wall irradiation using this kilovoltage beam.
SU‐E‐T‐676: Dosimetric Dependence on Variations of the Lung Density and Geometry: A Monte Carlo Evaluation Using Virtual Dynamic Heterogeneous Phantom
Authors: Mylrajan L , Chow J , Grigorov G
Published: November 2011

Purpose: This Monte Carlo study investigates the dosimetry of the lung—soft tissue interface under different lung geometries using virtual dynamic heterogeneous phantoms. Methods: 6 and 18 MV photon beams (field sizes = 4×4 and 10×10 cm2), produced by a Varian 21EX linac were used. Three lung phantoms namely slab, column and cube representing different lung geometries were irradiated by the photon beams. The lung volume and density were varied in five phases mimicking the lung motion in breathing. The lung density was set to 0.15, 0.2, 0.25, 0.3 and 0.35 g/cc corresponding to phases 1 to 5 with the lung volume changed while keeping the lung mass constant. Relative depth doses and beam profiles for each phantom in the five phases were calculated using the DOSXYZnrc. Results: Our results show that there is obvious dosimetric variation around the lung—soft tissue interface among the five phases in the three lung phantoms. This is due to the positional and density change of the interface. Interpolation was done to register all dose distributions in the five phases to one in order to compare with the dosimetry of a static lung phantom (e.g. only phase 3 with lung density = 0.25 g/cc). Dose deviation was found to be about ±5%, when a breathing lung with changes of volume and density was considered. Moreover, the deviation is more significant for photon beams of relatively higher energy (18 MV) and smaller field size (4×4 cm2). Conclusions: Through Monte Carlo studies of lung heterogeneous correction, we concluded that more realistic dosimetry may be acquired by considering a virtual dynamic phantom to mimic the breathing motion. The accuracy of the lung motion can further be improved by increasing the number of phase and applying weight factor to each phase in the breathing cycle.
SU‐E‐T‐677: Tissue Inhomogeneity in Hadron Therapy
Authors: Fourkal E , Veltchev I , Lin M , Ma C
Published: November 2011

Purpose: Conventional proton therapy uses a beam spreading technique called passive scattering in which a small beamlet of particles is spread laterally to create field sizes needed to cover targets in lateral direction and subsequently an SOBP proton energy spectrum is formed using wheel modulators to deliver spread out dose distributions in depth. This beam delivery method however provides desirable dose distributions only in situations where no considerable tissue inhomogeneity is present. Otherwise, the SOBP dose distribution suffers significant modification known as the distal edge degradation effect, thus limiting the clinical use of passive scattering technique. As a result, such treatment site as lung where significant tissue heterogeneity is present cannot benefit from the dosimetric advantages of protons. The main aim of this work is to show that using spot scanning technique with beamlet size determined by the dimension of the tissue inhomogeneity yields conformal dose distribution with low target dose heterogeneity. Methods and Materials: Using Monte Carlo dose calculation with track repeating technique, in‐phantom dose distributions are calculated for different beamlet and density parameters. Conditions for improved dose distribution are presented. Results: It is shown that when the beamlet size is larger than the dimension of tissue inhomogeneity, significant distal dose degradation effect is observed. However, when the beamlet size becomes comparable to that of tissue inhomogeneity, improved target dose heterogeneity is seen. In the limiting case when the beamlet size is much smaller than the characteristic dimension of inhomogeneity, the dose distribution converges to that of homogeneous density phantom irradiated by laterally spread beam. Conclusions: Since the dose degradation effect is due to proton scattering at different tissue interfaces within the same field, reducing the field size of the beam results in significantly improved target dose coverage and limits the deleterious effects of distal edge degradation.
SU‐E‐T‐678: Monte Carlo Investigation on Dose Perturbations in the Lung Due to Constant Magnetic Fields during MRIgRT
Authors: Yang Y , Bednarz B
Published: November 2011

Purpose: Magnetic resonance image‐guided radiotherapy (MR‐IGRT) has emerged as a promising new technology to reduce tumor position uncertainty during photon radiotherapy treatments of lung cancer. MRIGRT improves upon traditional IGRT techniques by providing real‐time intrafraction imaging of tumor motion. However, the use of MRI during beam delivery complicates treatment planning since the magnetic field will perturb the radiation dose distribution especially in fields prescribed in heterogeneous regions of the body such as the lung. In this study we used Monte Carlo methods to investigate the magnetic field effects on dose distributions near interfaces of high‐ and low‐density regions where the influence of magnetic fields will be significant. Methods: The Monte Carlo code EGS4nrc was used for all simulations performed in this study. We investigated dose distributions from both Co‐60 and 6‐MV photon beam energy spectra in simple heterogeneous phantoms. The phantoms consisted of alternating slabs of PMMA and air or lung material with different thicknesses. Homogeneous transverse magnetic fields of varying strengths were applied to the phantom during the simulations. Results: Large perturbations in the dose distributions near PMMA‐air or PMMA‐lung interfaces were recorded when a transverse magnetic field was applied to the phantom, which can be attributed to electron return effect. It was demonstrated that the size of the perturbation at an interface depends not only on the magnetic field strength, but also on the primary photon beam energy spectrum and the length of the air cavity within the phantom. Conclusions: Preliminary results demonstrated that magnetic fields alter the delivered dose distributions near interfaces of high‐ and low‐density regions. Therefore, accurate planning for MR‐IGRT treatments of lung cancer may need to consider magnetic field effects on the dose distribution. Future work will use Monte Carlo methods to investigate dose perturbations due to magnetic fields in 4D patient geometry.
SU‐E‐T‐679: Electron Contamination Modeling in Longitudinal Field MRI‐Linac Systems
Authors: Oborn B , Metcalfe P , Butson M , Keall P , Rosenfeld A
Published: November 2011

Purpose: This work uses Monte Carlo simulations to model an unexpected dosimetry effect of electron contamination in Longitudinal Field MRI‐Linac systems (LF‐MRIGRT). These systems are under construction due to their dosimetric advantages over transverse‐field systems. However this work has yielded a potential major dosimetric problem and aims to investigate its scope. Methods: Geant4 Monte Carlo simulations of various generic longitudinal‐field MRI‐Linac systems are performed. The fringe‐field of the MRI system is included as it collects and propagates electron contamination from the Linac towards the patient. Field size, isocentre distance, and fringe‐ field style are all varied and examined. The Linac modeled is a Varian 2100c 6MV beam, and dose is scored in a 30×30×20cm3 phantom. Results: The longitudinal component of the MRI‐system fringe field acts to trap electron contamination arising from the Linac collimation system. This becomes focused and cumulates as it travels towards the patient level. As a result a massive concentration of electron contamination is present near CAX at the patient level, leading to entry skin dose hot spots of > 500% of dose at dmax (15 mm). Even if the Linac collimation system is fully magnetically shielded there is resultant lack of lateral spread (or dilution) of contamination by the main MRI‐field region. This still leads to skin dose hot spots approaching Dmax. Conclusion: Monte Carlo modeling predicts that electron contamination from the Linac in LF‐MRIGRT may be trapped by the MRI system and cause considerable patient entry skin dose hot spots near CAX, of the order of > 500% of Dmax. It is highly recommended that accurate modeling of the MRI fringe‐field and MRI‐Linac system be performed to ascertain this risk in potential TF‐MRI‐Linac systems.
SU‐E‐T‐680: Comparison between XVMC Monte Carlo and Eclipse AAA Dose Calculations for Rapidarc Plans
Authors: Laub W
Published: November 2011

Purpose: To investigate the dose calculation accuracy of the Eclipse AAA dose calculation algorithm for Rapidarc treatment plans by means of recalculating Rapidarc plans with the fast Monte Carlo code XVMV.Methods: The fast Monte Carlo code XVMC was commissioned for a Trilogy linear accelerator (Varian, Palo Alto) with a 6x photon beam. Dose calculation tests with XVMC in solid water demonstrated the high accuracy of the beam model for different field sizes compared to measurements and calculations with the clinically commissioned AAA algorithm in Eclipse (Varian, Palo Alto). Dose calculations for conventional treatment plans in the absence of large areas of high or low density inhomogeneities for 3D conformal treatment plans, like 4‐field pelvis plans, also demonstrated a high level of agreement. Clinical Rapidarc treatment plans of prostate and H&N cases were recalculated with XVMC.Results: Comparison between AAA and XVMC dose calculations of Rapidarc plans show differences in the presence of inhomogeneities as they have already been discussed in a variety of publications comparing AAA or Collapsed Cone calculations with Monte Carlo results. In addition we found that the overall dose is overestimated in Eclipse by several Gray (see Fig. 2). A typical prostate or H&N plan will show a dose of 3–4 Gy less in the XVMC dose calculation compared to AAA calculations Conclusions: This work indicates that in addition to the well known limitations of AAA or Collapsed Cone algorithms with respect to how they handle and correct for lateral electron scatter and electron disequilibrium the accuracy of absolute dose calculations with AAA may also be limited in Rapidarc treatment planning. This can be explained with the extremely small islands of dose and the high percentage of area blocked by the MLCs as it can often be observed for control point of Rapidarc treatment plans.

The author of this abstract holds a Varian research grant, is a guest speaker for Brainlab and has a part‐time commitment with Computerized Medical Systems.
SU‐E‐T‐682: Skin Dose Changes in Transverse Field MRIGRT: The ERE or the LFP?
Authors: Oborn B , Metcalfe P , Keall P
Published: November 2011

Purpose: This work investigates the ratio of the two source components of the undesirable skin dose increases seen in transverse field MRI‐Linac systems: the Lorentz‐force perturbation (LFP) and the electron return effect (ERE). Dose planning systems using kernels generated in magnetic fields will account for the LFP, however not the ERE. This work indicates the inaccuracies in not modeling the ERE in conventional planning. Methods: Geant4 Monte Carlo simulations of a Varian 2100C 6MV photon beam in the presence of transverse magnetic fields are performed. By using tracking options the dose deposited by the ERE can be compared with that delivered by both the LFP. The effect of surface angle and field size is also examined on a phantom of 30×30×20cm3. High resolution scoring voxels are used to extract the 70 micron skin dose values. Results: On the phantom entry side skin dose changes are clinically significant at large positive angles. The ERE causes about 50% of this depending on magnetic field strength. At negative angles the ERE plays a minimal role in the skin dose increases seen. On the phantom exit side the skin dose increase is the greatest at negative surface angles, and furthermore, this is almost entirely due to the ERE electrons. For positive surface angles the ERE only gives rise to a small fraction of the exit skin dose increases. Conclusion: The skin dose increases seen in 6MV transverse field MRI‐Linac systems are significant at positive angles on the entry side, and at negative angles on the exit side. The ERE can cause a large proportion of these changes, which will not be inherently modeled correctly inside a typical dose planning engine. These results suggest that improvements to current planning systems are needed if accurate estimates of the skin dose changes in MRI‐guided‐radiotherapy are required.
SU‐E‐T‐683: Improvement of LDR Brachytherapy TG‐43 Dose Calculations with a GPU‐Accelerated Raytracing Algorithm
Authors: Bourque A , Gariépy J , Mathieu D , Hissoiny S , Beaulieu L , Després P
Published: November 2011

Purpose: To compare a fast GPU‐based dose calculation algorithm to Monte Carlo (MC) simulations and TG‐43 results in low dose rate brachytherapy, in terms of accuracy and relative execution speed. Methods: Dose calculations were performed in a voxelized numerical phantom comprising bone, air and gold inserts. The source consisted in a single seed of 125I (SelectSeed, Nucletron, The Netherlands). Dose distributions were obtained from calculations based on the TG‐43 formalism, from MC simulations (GEANT4 v.9.3) and from a GPU‐based version of the TG‐43 formalism capable of handling heterogeneities. This feature was implemented in the GPU algorithm by computing the equivalent water length travelled through each voxel between the emission site and the dose calculation point. Results: Dose profiles were plotted along heterogeneities to visualize the behavior of each method, with MC simulation as the gold standard. Unsurprisingly, the TG‐43 method overestimated the dose behind high‐density/high‐Z regions with errors in excess of 100% in some cases. The modified TG‐43 algorithm implemented on the GPU algorithm was able to better reproduce MC results, with errors in the range −9.3% to 10.5% behind the same regions. Larger differences occurred for backscattering effects, which are only modeled in the MC method, but only on a limited region (1–2 mm). The TG‐43 formalism provides dose distributions almost instantaneously while MC simulations typically required up to four hours for statistically significant results. The modified TG‐43 GPU algorithm was able to reproduce MC results in approximately four seconds. Conclusions: For complex geometries, the GPU‐based TG‐43 algorithm was shown to provide dose distributions that are closer to those obtained with MC simulations while being significantly faster. This improvement can potentially improve the planning in LDR brachytherapy, where inter‐source attenuation and tissue heterogeneities were shown to influence dosimetric parameters.
SU‐E‐T‐685: Selection of the Optimized Source for Brachytherapy Treatment of Tongue Cancer Using Dose Distribution Simulation by MCNP4C
Authors: Faghihi R , Zeinali B
Published: November 2011

Purpose: Among different kinds of oral cavity cancers, the frequency of tongue cancer occurrence is more significant. Brachytherapy is the most common method to cure tongue cancers. The objective of this study is to asses the dose distribution around long sources which use in tongue brachytherapy, comparing different radioisotopes as brachytherapy sources, measuring the homogeneity of delivered dose to treatment volume and also comparing mandible dose and dose of tongue in the regions near the mandible with and without using shield. Methods: The Monte Carlo code MCNP4C was used for simulation. Tongue, mandible, sources like Ir‐192, Cs‐137, Ra‐226, Au‐198, In‐111, Ba‐131, guide gutters and lead shield were simulated. The accuracy of simulation was verified by comparing the results with experimental data. The position of sources was determined by Paris system. Dose distribution around sources assessed by surfer software and compared with each other. Results: The percentages of mandible dose reduction with use of 2 mm Pb shield for Ir‐192, Cs‐137, Ra‐226, Au‐198, In‐111, Ba‐131 were: 35.4%, 20.1%, 86.6%, 32.24%, 75.6%, and 36.8%. The tongue dose near the mandible with use of shield did not change significantly. The dose homogeneity from the most to least was obtained from these sources: Cs‐137, Au‐198, Ir‐192, Ba‐131, In‐111 and Ra‐226. Conclusions: According to results of this study Ir‐192 and Cs‐137 were the best sources for tongue brachytherapy because of homogenous dose distribution in target volume and less time they required for delivering prescribed dose. Au‐198 and Ba‐131 had the same performance by Ir‐192 but they required more time to deliver the prescribed dose. Ra‐226 and In‐111 had the most reduction of mandible dose but they required much more time to deliver prescribed dose and they had more dose inhomogeneity in target volume so that they were not suitable sources for tongue brachy therapy.
SU‐E‐T‐687: Experimental Assessment of the Accuracy of a Semi‐Empirical Model and a Monte Carlo System for Proton Dose Calculations for Highly Inhomogeneous Media
Authors: Mohan R , Mirkovic D , Titt U , Song X , Li H , Zhu X , Gillin M
Published: November 2011

Purpose: To experimentally assess the accuracy of proton dose distributions, computed with a semi‐empirical algorithm and a Monte Carlo (MC) system, for inhomogeneous media. Methods: A complex range compensator for a lung patient, being treated with passively‐scattered proton therapy (PSPT) was used to represent the inhomogeneity. Planar dose distributions for a PSPT beam of exactly the same characteristics as the one used to treat the patient, incident normally on a water equivalent phantom, were measured at a series of depths using a calibrated chamber array detector. Semi‐empirical algorithm and MC (MCNPX) calculations were performed with exactly the same geometry. Absolute depth doses and lateral profiles at multiple depths were compared. Results: Agreement between MC and measured depth dose data was found to be within 2% or 2 mm except at the distal edge where the dose gradient was the highest. The corresponding differences between measurements and the semi‐empirical model were up to 5% in the regions of low gradients and distance to agreement in the distal edge region exceeded 1 cm. Comparison of measured vs. MC vs. se‐empirical profiles showed that, in some regions measured data agreed better with MC, whereas in other regions the agreement was better with semi‐empirical model. Generally, the agreement within the beam boundary was superior for measured vs. MC. The gamma analysis (points within 3% and 3 mm) indicated that the percentage of points passing was comparable for both modes of calculations. Conclusions: The differences between measured and semi‐empirical model dose distributions might be explainable based on the approximations in the latter. However, differences between measurements and MC require further examination of numerous sources of uncertainties, e.g., in modeling of beams and compensators, and the measurements (e.g., the depth of sensitive region of the chamber).

NCI P01CA021239
SU‐E‐T‐688: McCloud: Toward 10 Million Monte Carlo Primaries in 5 Minutes for Clinical Use
Authors: Keyes R , Arnold D , Reynaud A , Luan S
Published: November 2011

Purpose: At AAPM 2010, we presented the concept of using Cloud Computing to speed up clinical Monte Carlo calculations. Cloud Computing refers to a set of technologies that offers on‐demand computing resources using a pay‐as‐you‐go pricing model. We presented a feasibility study that included a variety of clinical relevant calculations using protons, electrons, and photons in water and a voxel patient geometry (Zubal phantom). While our initial study was designed for proof‐of‐concept, this research presents a more refined platform with an emphasis on particle therapy and demonstrates its potential to enable Monte Carlo dose calculation for routine clinical use.Methods: A Cloud Computing based distributed Monte Carlo dose calculation system called McCloud was developed. The system is based on Amazon EC2, Fluka, and a variety of “glue” technologies. The calculation involves these key steps: (1) A cluster is allocated in the Cloud. (2) A Monte Carlo task is launched on each node in the cluster. Extra care is used for random seed generations to ensure the correctness of the simulations. (3) The progress of the computation is dynamically monitored. (4) Once the computation is finished in the cluster, the results are aggregated using a linear model or a tree‐based distributive model, and a final dose distribution is returned to the user. Results: We found that for 14 Million 75MeV protons, an analog Monte Carlo simulation can be completed in 5 minutes 36 seconds. For this particular computation, the cost is less than 2 USD (based on official pricing at 8 cents per node per hour). Studies using various cluster sizes have shown the 1/n speed up expected from analytical Monte Carlo simulations Conclusions: Our implementations demonstrate the power of the existing cloud computing model, an extremely promising new paradigm for clinical and research computing. Further research is underway.

Supported in part by NSF CBET‐0853157 and NSF CBET‐0755054.
SU‐E‐T‐690: Fast Monte Carlo Treatment Planning for Prostate Brachytherapy: A Comparison with VariSeed
Authors: Abboud F , Scalliet P , Vynckier S
Published: November 2011

Purpose: Treatment planning for prostate Brachytherapy with seeds uses mainly the TG43 algorithm for dose calculations. It doesnˈt take into account the interseed attenuations (known as the interseed effect) due to its complexity. A fast Monte Carlo dose calculation engine, taking into account the interseed effect, has been developed, using the MCNP5 code. Methods: Three MC techniques were used to calculate the dose distributions of the prostate implants: MCOSST, FMCT and MCOSSIT. The two last techniques take into account the interseed effect. IsoSeed (Bebig) seeds were chosen for this work. A 3D comparison has been performed to validate the new MC techniques for 8 patients. Dose distributions are compared on each ultrasound imaging slide. Moreover, a DVH comparison is also performed for some organs. Results: The interseed effect was investigated by comparing MCOSST with FMCT. It leads to the appearance of cold spots in the planar dose distribution which varies from 4% to 6%. It depends on number, position and composition of seeds. Moreover, the interseed effect becomes more important as the number of implanted seeds increases. We can especially notice it at the end of the strand and also behind set of seeds implanted each 5 mm in the same plane. DVH comparison between VariSeed and MC techniques was also performed. VariSeed overestimates the average dose deposited in the prostate by 3% up to 5%. MCOSSIT can be considered being a more accurate and faster (2–3 sec) calculation method in a near future as it taks into account the interseed effect and can also be applied on line Conclusions: MCOSSIT is a new calculation technique of dose distribution for prostate Brachytherapy that can be used for all types of seeds. All these advantages make from MCOSSIT very accurate and fast system for online permanent brachytherapy of the prostate.

This work is submited by UCL University to get a patent.
SU‐E‐T‐691: On the Use of Multiple Beam Angles to Minimize the Impact of High Density Fiducial Markers in the Prostate Proton Radiotherapy
Authors: Zhang M , Mo X , Levinson L , Goyal S , Yue N
Published: November 2011

Purpose: Fiducial markers are commonly used in prostate radiotherapy to improve accuracy of target localization. However, in proton therapy, since the proton range is sensitive to the material it travels through, under‐dose to the prostate has been reported in conventional passive scattering treatment and 3D‐modulation based intensity modulated proton therapy (IMPT), in the presence of high density fiducial markers inside the prostate. This study investigated the ability of using multiple beam angles to minimize the dosimetric impact of fiducial markers in 3D‐modulation and distal edge tracking (DET) based IMPT. Methods: CT images of a typical prostate patient with three gold markers (3mm by 1mm, density = 19.3 g/cc) were used in this study. 2‐field lateral and 4‐field box type 3D‐modulation proton treatment plans as well as DET plans with evenly spaced 18, 10, and 6 beam angles were generated to deliver 70Gy to 95% of the PTV. Geant4 Monte Carlo code was used for dose calculation. The plan was performed on images with fiducial markers artificially removed. Then the delivered dose distribution was calculated with fiducial markers present in the patient. The dose distributions between the planed and delivered were then compared to evaluate the efficacy of using multiple beam angles to minimize the dosimetric deviations. The tumor control probability (TCP) was also used to quantify the dose variation. Results: The preliminary result shows all the 3D‐modulation and DET plans yielded equivalent PTV coverage. The planned and delivered D98% of prostate was 68.68Gy vs. 68.32Gy in 18‐field DET, 67.83Gy vs. 65.53Gy in 10‐field DET, and 67.82Gy vs. 58.19Gy in 2‐field 3D‐Modulation. No significant dose change to rectum and bladder was observed. Conclusions: With high density fiducial markers present in the target, multiple beam angles are recommended in proton treatment plans to avoid significant under‐dose to the target.
SU‐E‐T‐692: Evaluation of Surface Dose Calculation of Superposition‐Convolution Algorithms Using Monte Carlo Simulation
Authors: Chow J , Jiang R , Leung M
Published: November 2011

Purpose: This study evaluated the surface dosimetry predicted by the anisotropic analytical algorithm (AAA) and collapsed cone convolution (CCC) algorithm using the tangential‐like photon beam and phantom geometry. Monte Carlo (MC) simulation (EGSnrc code) was used as a benchmark for comparison. Methods: The 6 and 15 MV photon beams with field sizes of 4×4 (or 7×7), 10×10 and 20×20 cm2, produced by a Varian 21EX linear accelerator were used. Horizontal dose profiles at different depths, phantom skin profiles (i.e. vertical dose profiles at a distance of 2 mm from the phantom lateral surface), gamma dose distributions, and dose‐volume histograms (DVHs) of skin slab were determined. Results: For dose profiles at different depths, the CCC agreed better with doses in the air‐phantom region, while both the AAA and CCC agreed well with doses in the penumbra region, when compared to the MC. Gamma evaluations between the AAA/CCC and MC revealed that deviations of 2D dose distribution occurred in both beam edges in the phantom and air‐phantom interface. DVHs of skin slab showed that both the AAA and CCC underestimated the width of the slope for both the 6 and 15 MV photon beams. The mean dose differences along the phantom skin profiles for the AAA and CCC were respectively: 7.6±2.6% and 2.1±1.3% for a 10×10 cm2 field, 6 MV; 16.3±2.1% and 6.7±2.1% for a 20×20 cm2 field, 6 MV; 5.5±1.2% and 1.7±1.4% for a 10×10 cm2, 15 MV; 18.0±1.3% and 8.3±1.8% for a 20×20 cm2, 15 MV. Conclusions: As surface dose with tangential‐like photon beam geometry is important in some radiation treatment sites such as breast, chest wall and sarcoma, the dosimetry data and beam and phantom geometry in this study are worthwhile to be considered, when carrying out quality assurance and commissioning for treatment planning systems.
SU‐E‐T‐694: Evaluating Pencil Beam Dose Algorithm in Lung with Monte Carlo
Authors: Depauw N , Seco J , Adams J , Panahandeh H , Paganetti H , Kooy H
Published: November 2011

Purpose: To validate the Massachusetts General Hospitalˈs (MGHˈs) proton pencil beam algorithm (PBA) dose calculations in lung cancer patients against GEANT4 Monte Carlo simulations. Methods: Three lung cancer patients with variations in tumor size and location, were considered in this study. Treatment planning was first performed for each patient following specific protocol guidelines and dose distributions were calculated with MGH PBA. The same plans were subsequently simulated with the GEANT4 Monte Carlo toolkit using a complete implementation of the MGHˈs proton delivery system with demonstrated accuracy in other tumor sites such as head and neck, prostate, etc. 20 million particles were simulated for each beam to ensure sufficient statistical accuracy. The dose distributions for each plan, as well as for each individual beams, were then compared 1) visually using an in‐house analysis tool Dose Comparison Application (DCA), and 2) systematically using a 2mm/2% and 3mm/3% 3D gamma index analysis. Results: GEANT4 simulations and PBA calculations show excellent visual agreement in lung cancer patients. Every plan successfully passes a full 3D gamma index test (95% γ values ≤ 1). No significant discrepancy were seen for any of each individual beams, hence showing agreement between the two fully independent models. These results highlight the accuracy of MGHˈs proton dosimetry in lung, and the ability to safely plan treatments for lung tumor patients at MGH. Conclusions: MGHˈs PBA dose calculations in lung were successfully compared with simulated Monte Carlo dose distributions. Monte Carlo is considered the gold standard for proton dose calculations, and these results therefore stress the high quality of the pencil beam algorithm calculations at MGH. This work further emphasizes the excellence of radiotherapeutic treatments at MGHˈs Francis H. Burr Proton Center.
SU‐E‐T‐696: The Need for Segmentation of Breast Tissue in Monte Carlo Calculations for Low‐Energy Brachytherapy
Authors: Sutherland JGH , Thomson RM , Rogers DWO
Published: November 2011

Purpose: To investigate the use of various breast tissue segmentation models in Monte Carlo calculations for low‐energy brachytherapy. Methods: The EGSnrc user‐code BrachyDose is used to perform Monte Carlo simulations of a breast brachytherapy treatment using TheraSeed Pd‐103 seeds with various breast tissue segmentation models. Models used include a phantom where voxels are randomly assigned to be gland or adipose (randomly segmented), a phantom where a single tissue of averaged gland and adipose is present (averaged tissue) and a realistically segmented phantom created from numerical phantoms in the literature. Transporting photons in averaged tissue and scoring in gland is investigated. The inclusion of calcifications in the breast is also studied in averaged tissue and randomly segmented phantoms. Results: In randomly segmented and averaged tissue phantoms, the photon energy fluence is approximately equal; however, differences occur in the DVHs as a result of scoring in gland and adipose (whose mass energy absorption coefficients differ by 30%) or averaged tissue. A realistically segmented phantom is shown to significantly change the photon energy fluence compared to that in an averaged tissue or randomly segmented phantom. Despite this, resulting DVHs agree reasonably because fluence differences are compensated by dose scoring differences. Calcifications affect photon energy fluence to such a degree that the effects cannot be overcome by dose scoring differences in averaged tissue phantoms. Conclusions: For low‐energy brachytherapy, if photon transport and dose scoring both occur in an averaged tissue, the resulting DVH is reasonably accurate because inaccuracies in photon energy fluence are compensated for by inaccuracies in localized dose scoring. Scoring dose in a separate medium (water/gland) when transporting in the averaged tissue phantom causes inaccuracies in resulting DVHs because of inaccurate photon energy fluence. Including calcifications necessitates the use of proper tissue segmentation.
SU‐E‐T‐697: Online Monte‐Carlo‐Accurate Real‐Time Proton Dose Calculator
Authors: yepes P , Mirkovic D
Published: November 2011

Purpose: Demonstrate the feasibility of a online tool to provide Monte‐Carlo accurate therapeutic proton dose distributions. Methods: The Fast Dose Calculator (FDC), a fast track‐repeating algorithm for proton therapy, has been deployed on the High Performance Research Blue BioU IBM computer cluster at Rice University. FDC utilizes a database of discretized proton trajectories in water generated with GEANT4. Information about the energy deposited, length and direction is stored for each trajectory step. Proton trajectories and dose distributions in any other material are extrapolated from the database by scaling step lengths and angles. A web interface to upload anonymized patient and field data to be processed by the Blue BioU implementation of FDC has been developed. Once the data is uploaded, the website user can request a calculation of the dose distribution for a particular field configuration. The results can be displayed on the website and compared with dose distributions calculated with alternative methods. Results: Doses calculated with FDC reproduced the results obtained with traditional Monte Carlos, i.e. GEANT4, within 2%. The web interface with the Blue BioU back‐end can deliver Monte‐Carlo accurate dose distributions for proton treatment plans within a few seconds. Conclusions: An online real‐time tool for proton dose calculations has been developed. The tool could be utilized for treatment plan validation and radiation treatment research.
SU‐E‐T‐698: Clinical Evaluation of the McGill Monte Carlo Treatment Planning System (MMCTP) for Fixed‐Field IMRT and RapidArc Plans
Authors: Davis S , Alexander A , Renaud M , Hobson M , Soisson E , Ruo R , Seuntjens J
Published: November 2011

Purpose: To investigate the clinical application of a Monte Carlo treatment planning system for verification of fixed‐field IMRT and RapidArc® treatment plans. Methods: The McGill Monte Carlo treatment planning (MMCTP) system was used to calculate dose distributions from fixed‐field IMRT and RapidArc plans that had been generated in Eclipse v8.6 using the AAA dose calculation algorithm. Planar dose measurements were performed using the MapCHECK 2 diode array in three different measurement geometries. The first measurement geometry collapsed all of the gantry angles to 0° for the treatment delivery, and was only possible for the fixed‐field IMRT plans. The second measurement geometry used an Isocentric Mounting Fixture (IMF) that rotated the MapCHECK 2 array while the gantry rotated during RapidArc delivery. The third measurement geometry placed the MapCHECK 2 array between two 6 cm Solid Water® slabs with the detector remaining stationary on the treatment couch while the gantry rotated during RapidArc delivery. Results: A benchmark head and neck fixed‐field IMRT plan demonstrated excellent agreement between the Eclipse calculations, MMCTP calculations, and the MapCHECK 2 measurements for the collapsed gantry angle geometry. The Eclipse and MMCTP calculations were generally in good agreement for the RapidArc plans, but differences of up to 7% were seen in high dose gradient regions. For the RapidArc plans, the MapCHECK 2 results agreed well with the calculated distributions for stationary measurements between the Solid Water slabs but had poorer agreement when the IMF delivery was used. Conclusions: This work demonstrates that MMCTP can be used as an independent verification of fixed‐field IMRT and RapidArc treatment plans. MapCHECK 2 measurements between the Solid Water slabs agreed well with the calculated results and were the preferred QA method since the measured distributions best simulated the intended dose distributions in the patientˈs treatment plan.
SU‐E‐T‐702: Accuracy of a Commercially Available Dose Calculation Algorithm for Small Field Dosimetry
Authors: Stathakis S , Esquivel C , Gutierrez A , Mihailidis D , Buckey C , Myers P , Mavroidis P , Papanikolaou N
Published: November 2011

Purpose: To validate the AcurosXB dose calculation algorithm for small field dosimetry for high energy photon beams. Methods: Calculations in water phantom of 0.2×0.2×0,2cm3 voxel size with slabs of inhomogeneity materials (air rho=0.0012g/cm3, lung rho =0.2 g/cm3 and bone rho =1.85 g/cm3) were used in this study. Fields sizes ranging from 1×1cm2 to 10×10cm2 and energies of 6, 10 and 18MV were calculated using the Acuros XB dose calculation algorithm available in the Eclipse treatment planning system (TPS). The calculations were compared to the Analytical Anisotropic Algorithm (AAA) also available in Eclipse as well to Collapsed Cone Convolution Superposition (CCCS) algorithm available in the Pinnacle3 TPS. Comparison between the dose calculations and Monte Carlo calculations using EGSnrc\BEAMnrc and EGSnrc\DOSXYZnrc package was also performed. Results: The AcurosXB calculation algorithm was in general in good agreement with Monte Carlo calculations. Discrepancies were observed at the interfaces of the inhomogeneities. Good agreement between CCCS and AcurosXB was also observed for the majority of the cases with discrepancies observed only at the interfaces of the media. The AAA did not successfully calculate the dose for the test geometries when small fields were used. Discrepancies in the order of 50–70% were observed. The AAA overestimated the dose in the low density material and failed to predict the second buildup region accurately for the very small field sizes. Conclusion: In general, the overall degree of accuracy for AcurosXB in the conditions of electronic disequilibrium was in good agreement with Monte Carlo calculations (within 2%) and comparable with the CCCS algorithm. The AAA on the other hand failed to accurately predict the dose for the small fields studied in the presence of inhomogeneities
SU‐E‐T‐703: An Artificial Neural Network Treatment Planning System Based on Monte Carlo Calculation for VARIAN 2100C LINAC
Authors: Hadad K , Moshkriz M , Nedaie H
Published: November 2011

Purpose: Artificial neural network to obtain two‐dimensional dose distribution and of the linear accelerator Varian 2100C based on Monte Carlo calculations, MCNP5 code, were used. In this study we want to overcome the time consuming problem of Monte Carlo method in dose distribution calculation with the used artificial neural Methods: Monte Carlo MCNP is employed to simulate a linear accelerator head, for calculation of dose distribution and the depth dose profile in water phantom. Dose profile obtained from the MCNP were validated using experimental data. Mesh tally card, fmesh4, with mesh dimension 0.5*0.5*0.5 cm̂3 was overlaid on the water phantom with dimension 50*50*50cm̂3 to calculate the photon dose distribution in phantom. This calculation used to train the artificial neural network (ANN) with MATLAB. Number of nodes and number of the iteration in neural network adjusted to optimize accuracy and speed. 70% of the MCNP data were used for training and the rest were employed for network verification. Results: The evaluation of dose distribution of an unknown field size evaluated by ANN compared with MCNP simulation confirms the accuracy of the trained ANN. The dose distribution for the largest considered field size has a difference of less than 2% in the center and 5% in the edge of field size when compared with the MCNP calculation results. Conclusions: This study showed the ability of artificial neural network to calculate dose distribution in radiotherapy treatment planning. This method could be further developed for heterogeneous medium. The plan has the accuracy of Monte carlo and the speed is comparable with conventional practice in radiation oncology clinics.
SU‐E‐T‐704: Backscatter Correction Factor for Megavoltage Photon Beam Using Divergent Point‐Spread Kernels
Authors: Liang X , Zhu T
Published: November 2011

Purpose: To determine the backscatter correction factor using Monte‐Carlo simulated divergent point‐spread kernels, and thus to determine the minimum thickness of backscatter phantom material to ensure that full backscatter condition. Methods: In case of insufficient backscatter thickness, one can determine the backscatter correction factor, BCF(s,d, t), defined as the ratio of absorbed dose measured on the central‐axis of a phantom with backscatter thickness of t to that with full backscatter for square field size s and forward depth d. Measurements were performed in 30 SAD geometry for 6MV and 15MV photon beams using a 0.125cc thimble chamber for field sizes between 10×10cm and 30×30cm at depths between dmax (1.5 cm for 6MV and 3cm for 15 MV) and 20cm. However, BCFs calculated by a convolution method using Monte‐Carlo simulated point‐spread kernels for clinical photon beams do not correspond with experimental data. Beam divergence is incorporated with the point‐spread kernels to improve the MC simulations. Results: The MC calculation agrees with the experimental measurements to within 0.8% with the same physical trend. The BCFs are corrected using divergent point‐spread kernels. According to the results of our convolution method, the largest correction occurs at forward depth dmax with 40×40cm field size, 0.970 for 6MV and 0.983 for 15MV. Conclusions: We concluded that backscatter thickness is 6.0 cm for 6MV and 4.0 cm 40 for 15MV for field size up to 10×10 cm when BCF = 0.998. If 4cm backscatter thickness is used, BCF is 0.997 and 0.982 for field size of 10×10 and 40×40cm for 6 MV, and is 0.998 and 0.990 for 10×10 and 40 ×40cm for 15 MV, respectively.
SU‐E‐T‐705: The Effects of Applicator Displacement on Dose Distribution around Cs‐137 Brachytherapy Sources
Authors: Siavashpour Z , Mosleh‐Shirazi M , Faghihi R
Published: November 2011

Purpose: The uncertainties in brachytherapy source localization can cause significant errors in dose estimation around the sources because of the high dose gradient in brachytherapy. The effects of applicator movement on the dose values in gynecological brachytherapy are investigated in this study. Methods: The MCNP4C Monte Carlo code was used for estimation of the effects of applicator movements on the dose distribution around Selectron Cs‐137 LDR source (Nucletron Trading BV, Netherlands). The simulations were done for vaginal applicator and tandem‐ovoid set. The applicator movements of 1 to 5 mm in both longitudinal and transverse planes and the applicator rotation of 1o to 5o were also simulated in both cases. The small spherical tally cells were used in dose estimation around LDR sources using *F8 tally. Results: For typical source configurations in vaginal and tandem‐ovoid applicator, an upward superior movement of 5 cm in vaginal applicator causes an error of 1.9% in dose of reference points, while 5 cm movement in transverse direction would led to an error of about 54.9%. In case of tandem‐ovoid set, those errors were 8.1 % and 27.6 % respectively. The uncertainties caused by 5o rotation of vaginal and tandem‐ovoid were 73.1% and 2.8% at reference points. The rotation angle of 1o caused a dose error of 11.9% and 1.2% at reference points for vaginal and tandem‐ovoid applicators. Conclusions: The results obtained for Cs‐137 source indicate that the displacement of the applicator in longitudinal direction has less pronounced effect on doses than in transverse. The difference in dose error values of vaginal and tandem‐ovoid is mainly due to the more complicated geometry of tandem‐ovoid set and the different number of sources inside the applicators.
SU‐E‐T‐706: A GEANT4 Simulation of Light‐Ion Beams in Water
Authors: Johnson D , Ahmad S
Published: November 2011

Purpose: The purpose of this investigation has been to study the Bragg peaks of energetic light‐ions including H, Li, B, C, N, O, and Ne in water via a GEANT4 simulation to reveal potential benefits for radiation therapy. Methods: Electromagnetic processes for energy losses of hadrons and leptons are defined in GEANT4 as either “standard” (SP) or “low energy” (LEP). Our study used LEP for an extension of particle cutoff energies below that of SP. The hadronic interactions for proton and neutron were simulated using low energy elastic interactions and a binary cascade model. Other light‐ion hadronic interactions were simulated through the application of quasi‐molecular dynamics (QMD) model. A 27 liter water phantom consisting of 3000 packed rectangular detector discs (30 cm × 30 cm × 0.1 mm) was used in this simulation. The energy deposition in each disc was monitored to produce Bragg peaks. The simulations for each ion were carried out by 1 million incident particles with a pencil beam of 1 mm diameter. The energies of the ion beams were selected in order to create Bragg peak positions in three depths: 5, 15, and 25 cm. Results: The dose ratio of tail to peak was found to be 1.7 times higher for Ne compared to Li at 25 cm Bragg peak depth. It was found that Bragg peak widths at the 50% level decrease with increase of the atomic mass and this trend can be modeled with a power law. The entrance to peak dose ratio was found to be 1.35 times higher for Ne compared to protons at the 25 cm Bragg peak depth. At shallower depths, this dose increase with increasing atomic mass was not seen. Conclusions: This preliminary simulation demonstrates that GEANT4 is able to model multiple light‐ion beams for potential use in radiation therapy.