IMRT Dose Calculation Research Articles

EP-1757: Validation of Independent IMRT and VMAT Dose Calculation System based on Geant4 Monte Carlo Toolkit

EP-1757: Validation of Independent IMRT and VMAT Dose Calculation System based on Geant4 Monte Carlo Toolkit

SU‐E‐T‐430: Modeling MLC Leaf End in 2D for Sliding Window IMRT and Arc Therapy

Purpose:To develop a 2D geometric model for MLC accounting for leaf end dose leakage for dynamic IMRT and Rapidarc therapy.Methods:Leaf‐end dose leakage is one of the problems for MLC dose calculation and modeling. Dosimetric leaf gap used to model the MLC and to count for leakage in dose calculation, but may not be accurate for smaller leaf gaps. We propose another geometric modeling method to compensate for the MLC round‐shape leaf ends dose leakage, and improve the accuracy of dose calculation and dose verification. A triangular function is used to geometrically model the MLC leaf end leakage in the leaf motion direction, and a step function is used in the perpendicular direction. Dose measurements with different leaf gap, different window width, and different window height were conducted, and the results were used to fit the analytical model to get the model parameters.Results:Analytical models have been obtained for stop‐and‐shoot and dynamic modes for MLC motion. Parameters a=0.4, lw' =5.0 mm for 6X and a=0.54, lw' =4.1 mm for 15x were obtained from the fitting process. The proposed MLC leaf end model improves the dose profile at the two ends of the sliding window opening. This improvement is especially significant for smaller sliding window openings, which are commonly used for highly modulated IMRT plans and arc therapy plans.Conclusion:This work models the MLC round leaf end shape and movement pattern for IMRT dose calculation. The theory, as well as the results in this work provides a useful tool for photon beam IMRT dose calculation and verification.

SU-E-T-210: Independent MU Dose Calculation Software for S&S IMRT Using Modified Clarkson Integration Sector

Purpose: The purpose of this work was to develop and validate an open source independent MU dose calculation software for S and S IMRT based in the algorithm proposed by Kung et.al. Methods: Treatment plans were done using Iplan v4.5 BrainLAB TPS and S and S IMRT modality. A 6MV photon beam produced by a Primus linear accelerator equipped with an Optifocus MLC was used. TPS dose calculation algorithms were pencil beam and Monte Carlo. 230 IMRT treatments plans were selected for the study. The software was written under MALTLAB environment. Treatment plans were imported by the software using RTP format. Field fluences were reconstructed adding all segments.The algorithm implemented in the software calculates the dose at a reference point as the sum of primary and scatter dose. The primary dose is obtained by masking the fluence map with a circle of radius 1cm. The scatter dose is obtained through a shaped ring mask around the previous circle with a thickness of 0.5cm; the rings are increased one after another with constant thickness until cover the entire map of influence. The dosimetric parameters Sc, Sp and TPR vary depending on radio, the transmission effect of the MLC, inverse square lawmore » and dose profile are used for the calculation. Results: The average difference between measured and independent calculated dose was 0.4% ± 2.2% [−6.8%, 6.4%]. For 91% of the studied plans the difference was less than 3%. The difference between the measured and TPS dose with pencilbeam algorithm was 2.6% ± 1.41% [−2.0%, 5.6%] and Monte Carlo algorithm was 0.4% ± 1.5% [−4.9%, 3.7%]. The differences obtained are comparable to that obtained with the ionization chamber and TPS. Conclusion: The developed software is suitable for use in S and S IMRT dose calculation. This application is open and can be downloading under request.« less

SU-E-T-211: Induced Release of Nanocarrier Encapsulated Chemotherapeutic Drugs Using Proton Radiotherapy Beams

Purpose: The purpose of this work was to develop and validate an open source independent MU dose calculation software for SS the rings are increased one after another with constant thickness until cover the entire map of influence. The dosimetric parameters Sc, Sp and TPR vary depending on radio, the transmission effect of the MLC, inverse square law and dose profile are used for the calculation. Results: The average difference between measured and independent calculated dose was 0.4% ± 2.2% [−6.8%, 6.4%]. For 91% of the studied plans the difference was less than 3%. The difference between the measured and TPS dose with pencilbeam algorithm was 2.6% ± 1.41% [−2.0%, 5.6%] and Monte Carlo algorithm was 0.4% ± 1.5% [−4.9%, 3.7%]. The differences obtained are comparable to that obtained with the ionization chamber and TPS. Conclusion: The developed software is suitable for use in S&S IMRT dose calculation. This application is open and can be downloading under request.

SU‐C‐17A‐07: The Development of An MR Accelerator‐Enabled Planning‐To‐Delivery Technique for Stereotactic Palliative Radiotherapy Treatment of Spinal Metastases

Purpose:To develop an MR accelerator‐enabled online planning‐todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases. The technical challenges include; automated stereotactic treatment planning, online MR‐based dose calculation and MR guidance during treatment.Methods:Using the CT data of 20 patients previously treated at our institution, a class solution for automated treatment planning for spinal bone metastases was created. For accurate dose simulation right before treatment, we fused geometrically correct online MR data with pretreatment CT data of the target volume (TV). For target tracking during treatment, a dynamic T2‐weighted TSE MR sequence was developed. An in house developed GPU based IMRT optimization and dose calculation algorithm was used for fast treatment planning and simulation. An automatically generated treatment plan developed with this treatment planning system was irradiated on a clinical 6 MV linear accelerator and evaluated using a Delta4 dosimeter.Results:The automated treatment planning method yielded clinically viable plans for all patients. The MR‐CT fusion based dose calculation accuracy was within 2% as compared to calculations performed with original CT data. The dynamic T2‐weighted TSE MR Sequence was able to provide an update of the anatomical location of the TV every 10 seconds. Dose calculation and optimization of the automatically generated treatment plans using only one GPU took on average 8 minutes. The Delta4 measurement of the irradiated plan agreed with the dose calculation with a 3%/3mm gamma pass rate of 86.4%.Conclusions:The development of an MR accelerator‐enabled planning‐todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases was presented. Future work will involve developing an intrafraction motion adaptation strategy, MR‐only dose calculation, radiotherapy quality‐assurance in a magnetic field, and streamlining the entire treatment process on an MR accelerator.

SU-E-T-192: FMEA Severity Scores - Do We Really Know?

Purpose: Failure modes and effects analysis (FMEA) is a subjective risk mitigation technique that has not been applied to physics-specific quality management practices. There is a need for quantitative FMEA data as called for in the literature. This work focuses specifically on quantifying FMEA severity scores for physics components of IMRT delivery and comparing to subjective scores. Methods: Eleven physical failure modes (FMs) for head and neck IMRT dose calculation and delivery are examined near commonly accepted tolerance criteria levels. Phantom treatment planning studies and dosimetry measurements (requiring decommissioning in several cases) are performed to determine the magnitude of dose delivery errors for the FMs (i.e., severity of the FM). Resultant quantitative severity scores are compared to FMEA scores obtained through an international survey and focus group studies. Results: Physical measurements for six FMs have resulted in significant PTV dose errors up to 4.3% as well as close to 1 mm significant distance-to-agreement error between PTV and OAR. Of the 129 survey responses, the vast majority of the responders used Varian machines with Pinnacle and Eclipse planning systems. The average years of experience was 17, yet familiarity with FMEA less than expected. Survey reports perception of dose delivery error magnitudemore » varies widely, in some cases 50% difference in dose delivery error expected amongst respondents. Substantial variance is also seen for all FMs in occurrence, detectability, and severity scores assigned with average variance values of 5.5, 4.6, and 2.2, respectively. Survey shows for MLC positional FM(2mm) average of 7.6% dose error expected (range 0–50%) compared to 2% error seen in measurement. Analysis of ranking in survey, treatment planning studies, and quantitative value comparison will be presented. Conclusion: Resultant quantitative severity scores will expand the utility of FMEA for radiotherapy and verify accuracy of FMEA results compared to highly variable subjective scores.« less

SU‐E‐T‐380: Modeling MLC Leaf End in 2D for Sliding Window IMRT and Arc Therapy

Purpose: To develop a 2D geometric model for MLC accounting for leaf end dose leakage for IMRT and arc therapy. Methods: Leaf‐end dose leakage is one of the problems for MLC dose calculation and modeling. Dosimetric leaf gap used to model the MLC and to count for leakage in dose calculation, but may not be accurate for smaller leaf gaps. We propose another geometric modeling method to compensate for the MLC round‐shape leaf ends dose leakage, and improve the accuracy of dose calculation and dose verification. A triangular function is used to geometrically model the MLC leaf end leakage in the leaf motion direction, and a step function is used in the perpendicular direction. Dose measurements with different leaf gap, different window width, and different window height were conducted, and the results were used to fit the analytical model to get the model parameters. Results: Analytical models have been obtained for stop‐and‐shoot and dynamic modes for MLC motion. Parameters a=0.4, lw=5.0 mm for 6X and a=0.54, lw=4.1 mm for 15x were obtained from the fitting process. The proposed MLC leaf end model improves the dose profile at the two ends of the sliding window opening. This improvement is especially significant for smaller sliding window openings, which are commonly used for highly modulated IMRT plans and arc therapy plans. Conclusion: This work models the MLC round leaf end shape and movement pattern for IMRT dose calculation. The theory, as well as the results in this work provides a useful tool for photon beam IMRT dose calculation and verification.

SU‐C‐213AB‐04: Dosimetry for Dynamic IMRT Photon Beams

Purpose: To develop a model accounting for differences of dose per monitor unit between dynamic and stop‐and‐shoot IMRT. Methods: For IMRT photon beams, treatments can be divided into stop‐and‐shoot mode and dynamic mode based on the movement of the multileaf collimator (MLC) during the photon delivery. However, dose measurements from a Varian photon beam based on these two different types of treatments are varied for at least 8%. We propose a model to compensate for this discrepancy, based on the physical parameters of both the MLC shape and moving pattern. In this model, A MLC minimum width is developed to explain the cause of the discrepancy, and dose calculation is implemented by convolving the source kernel with the multi‐leaf profile function with different moving patterns. Thus, dose calculation under stop‐and‐shoot mode and dynamic mode are both obtained using this convolution method. Results: Analytical models have been obtained for stop‐and‐shoot and dynamic modes for IMRT. The theory predicts that doses from dynamic mode are higher than dose from the stop‐and‐shoot mode, which reflects the experimental results. MLC minimum widths for different photon beam energies are also obtained. Conclusions: This work models the MLC shape and movement pattern for IMRT dose calculation, and explains the dose difference between two modes. The theory, as well as the results in this work provides a useful tool for photon beam IMRT dose calculation.

Ultrafast convolution/superposition using tabulated and exponential kernels on GPU

Collapsed-cone convolution/superposition (CCCS) dose calculation is the workhorse for IMRT dose calculation. The authors present a novel algorithm for computing CCCS dose on the modern graphic processing unit (GPU). The GPU algorithm includes a novel TERMA calculation that has no write-conflicts and has linear computation complexity. The CCCS algorithm uses either tabulated or exponential cumulative-cumulative kernels (CCKs) as reported in literature. The authors have demonstrated that the use of exponential kernels can reduce the computation complexity by order of a dimension and achieve excellent accuracy. Special attentions are paid to the unique architecture of GPU, especially the memory accessing pattern, which increases performance by more than tenfold. As a result, the tabulated kernel implementation in GPU is two to three times faster than other GPU implementations reported in literature. The implementation of CCCS showed significant speedup on GPU over single core CPU. On tabulated CCK, speedups as high as 70 are observed; on exponential CCK, speedups as high as 90 are observed. Overall, the GPU algorithm using exponential CCK is 1000-3000 times faster over a highly optimized single-threaded CPU implementation using tabulated CCK, while the dose differences are within 0.5% and 0.5 mm. This ultrafast CCCS algorithm will allow many time-sensitive applications to use accurate dose calculation.

Generalized equivalent field size for nonuniform fluence maps in IMRT dose calculation

The equivalent field size (EFS) method is widely used to estimate dose of nonstandard fields, such as elongated or arbitrary shaped fields, for both central axis and off axis points. However, its application is limited to fluence maps with uniform intensity. In this work, we propose a generalized EFS (GEFS) for nonuniform fluence maps and present a formula for GEFS-based dose calculation. A parallel-beam dose table (PDT) consisting of central axis dose of circular fields of various diameters at various depths is used to define scatter contributions, based on which we calculate GEFS of any given fluence map. Such obtained GEFS, together with the radiological depth and PDT, is used to determine the dose at the point of interest. We tested GEFS-based dose calculation on a water phantom for both uniform and nonuniform fluence maps and compared the results with those by the collapsed cone convolution/superposition (CCCS) method. For all test cases, the gamma index is less than 1 based on the 3%/1 mm criteria for more than 96% of the calculated points. Larger discrepancies mainly occur along the field edges in the buildup region. A generalized equivalent field size for nonuniform fluence maps was proposed and its application in calculating dose at any point was presented and verified through comparison with the CCCS method.

SU-GG-T-595: Implementation of a Near Real-Time Dose Calculation Engine for IMRT

Introduction — IMRT field dose calculation is traditionally implemented through pencil beam convolution algorithm in various treatment planning systems. For quality assurance purpose, an independent patient specific IMRT dose calculation scheme is in need. Such calculation should be performed within a short timeframe in order to be clinically implementable. We develop a dose calculation engine that serves such purpose. Method — Once the treatment planning system finishes the dose optimization and calculation, the patient CT data and the treatment planning data are exported in DICOM format. Our calculation reads in the patient geometry and each IMRT beam/field setup including the MLC fractioned intensity map. The primary dose for each beam is calculated through patient attenuation function, output ratio considering the MLC setup, primary off-axis ratio and IMRT field intensity profile. A fast ray tracing algorithm is applied in calculating attenuation function in the primary dose. It traces the voxel density along the photon beam ray. The voxel densities are derived from patient CT numbers. The primary dose is then used to calculate the scatter dose by convolving a kernel with primary kerma. This convolution is calculated using a Fast Fourier Transform algorithm. The total dose for each beam is the sum of primary and scatter dose and repeated for each beam setup. Results — This IMRT dose calculation is performed within seconds from an IMRT plan. The resultant dose is comparable with the output from treatment planning system. Summary — We implemented a new IMRT dose calculation engine which is able to calculate the dose for a patient with IMRT fields. This engine takes into account of patient inhomogeneity through a precise fast ray tracing algorithm. A fast FFT convolution algorithm is used to obtain scatter dose. The calculation is performed with fast speed which allows potential real-time clinical applications.

MO‐EE‐A1‐05: Direct Aperture Optimization of Intensity Modulated Arc Therapy

Purpose: Intensity modulated radiation therapy has been a very popular and effective treatment technique for the treatment of prostate, head & neck and liver etc. Meanwhile, another innovative treatment technique, intensity modulated arc therapy, was developed to complement some drawbacks of IMRT like long treatment time and low MU efficiency. Since the IMAT completes the treatment just within one or two rotations, it is not easy to get optimized leaf sequences in a deterministic way. In this study, we tried to get optimized IMAT treatment plan by genetic algorithm. Method and Materials: First, the start/end positions of MLC leaves at each rotation angle with 10° interval were selected as optimization variables and encoded into genetic chromosomes. They experience genetic operations such as generation, selection, crossover, mutation and reproduction and the most optimized solution remains in the end of iteration. The constraint of maximum leaf speed was included in these operations. And the fitness of each population was evaluated by DVH volume constraint based objective function. IMAT dose distribution was calculated as a weighted sum of MLC shape at each angle and related Dij matrix similar to IMRT dose calculation. The algorithm was implemented in our treatment planning system and the dose distributions and DVHs of single and double gantry rotation cases were compared. Results: IMAT plan gave comparable results with conventional IMRT even with single gantry rotation and there was not significant improvement in double gantry rotations. Genetic algorithm required about 3,000 generations to reach optimized value due to its stochastic nature. Conclusion: It was possible to optimize IMAT plan with genetic algorithm and the results are optimized MLC leaf sequences readily deliverable in general linear accelerators. It can be an efficient method to solve IMAT optimization problem despite of relative slow convergence.

TU‐A‐350‐02: Monte Carlo Dose Calculation for Clinical IMRT Treatment Planning

Monte Carlo (MC) dose calculation algorithms are now available in some commercial treatment planning systems for applications in photon beam IMRT planning. This course will examine the various stages of a MC IMRT dose calculation, including methods for particle sourcing, fluence modulation, and patient dose computation dose. The use MC as a QA tool to validate commercial IMRT dose calculation algorithms and its use as a QA tool to validate 3D dose distributions for individual IMRT plans will be reviewed. To this end, large‐scale comparison of clinical IMRT plans created with a commercial planning system with MC dose re‐calculation will be presented. Advantages of using MC algorithms directly in the IMRT optimization loop to circumvent optimization convergence errors and strategies to reduce MC dose calculation time when used within an optimization framework will be discussed.Educational Objectives:1. To understand the stages of a Monte Carlo dose calculation when applied to clinical IMRT treatment planning.2. To illustrate the role of Monte Carlo for IMRT treatment planning quality assurance.3. To evaluate the dose accuracy of a commercial non‐Monte Carlo IMRT dose calculation algorithms with respect to Monte Carlo dose computations.4. To demonstrate methods for Monte Carlo‐based clinical IMRT dose optimization.The author is supported in part by NCI Grant P01 CA116602, by Philips Medical Systems and by Varian Medical Systems.

TU‐C‐AUD A‐03: Integrating Research Into the Clinic: Experiences From Implementing Monte Carlo, IMRT, and …

Clinical implementation of in‐house developed research‐based treatment planning software poses challenges for both the code developer and clinical user. This presentation will examine several important aspects of the implementation and integration processes, using in‐house IMRT and Monte Carlo dose calculation programs as examples. For the developer, challenges include the creation of fail‐safe strategies to ensure patient safety; procedures for upgrades, including updates to address clinically urgent issues; and separation of clinically implemented code from research‐based code which is under continual development. Jointly, the developer and clinical user are challenged to create commissioning and quality assurance procedures which not only meet AAPM TG guidelines, but which also test pre‐identified failure modes that are specific to the software implementation. They are further challenged to develop per‐patient quality assurance methods to ensure patient plan quality. A useful strategy in this regard is to utilize a vendor‐supplied FDA approved product for cross‐comparison of the deliverable treatment plan. Finally, the implementation and integration processes should include procedures for dealing with non‐compliant cases, including identifying error sources and implementing remedies. Examples of how these challenges were addressed in our clinic will be presented.Educational Objectives:1. To appreciate the challenges inherent in safe clinical implementation of in‐house developed software.2. To understand strategies for overcoming the challenges of clinical implementation of in‐house developed software.3. To understand the role of QA in safe clinical implementation of research.The research discussed is supported in part by NCI Grant P01 CA116602, by Philips Medical Systems, and by Varian Medical Systems.

A method to determine the planar dose distributions in patient undergone radiotherapy

A 2D-array equipped with 729 vented plane parallel ion-chambers has been calibrated as a portal dose detector for radiotherapy in vivo measurements. The array has been positioned by a radiographic film stand at 120cm from the source orthogonal to the radiotherapy beam delivered with the gantry angle at 180°. The collision between the 2D-array and the patient’s couch have been avoided. In this work, using the measurements of the portal detector, we present a method to reconstruct the dose variations in the patient treated with step and shoot intensity-modulated beams (IMRT) for head–neck tumours. For this treatment morphological changes often occur during the fractionated therapy.In a first step an in-house software supplied the comparison between the measured portal dose and the one computed by a commercial treatment planning system within the field of view of the computed tomography (CT) scanner. For each patient, the percentage Pγ of chambers, where the comparison is in agreement within a selected acceptance criteria, was determined 8 times. At the first radiotherapy fraction the γ-index analysis supplied Pγ values of about 95%, within acceptance criteria in terms of dose-difference, ΔD, and distance-agreement, Δd, that was equal to 5% and 4mm, respectively. These acceptance criteria were taken into account for small errors in the patient’s set-up reproducibility and for the accuracy of the portal dose calculated by the treatment planning system (TPS) in particular when the beam was attenuated by inhomogeneous tissues and the shape of the head–neck body contours were irregular. During the treatment, some patients showed a reduction of the Pγ below 90% because due to radiotherapy treatment there was a change of the patient’s morphology.In a second step a method, based on dosimetric measurements that used standard phantoms, supplied the percentage dose variations in a coronal plane of the patient using the percentage dose variations measured by the 2D-array portal detector. The results showed that the dose variations due to the change of the patient’s morphology reached 15% and such discrepancies were displayed on the digitally reconstructed radiography of the patient. The dose discrepancies were confirmed by the hybrid plan obtained by the treatment planning system. The good results here reported show that once it is possible to have the portal dose distributions even for other gantry angles, these tests could be introduced in the clinical protocol to have major support to decide when to repeat the patient’s CT scan and to re-plan the new IMRT dose calculation.

A virtual photon source model of an Elekta linear accelerator with integrated mini MLC for Monte Carlo based IMRT dose calculation

A dedicated, efficient Monte Carlo (MC) accelerator head model for intensity modulated stereotactic radiosurgery treatment planning is needed to afford a highly accurate simulation of tiny IMRT fields. A virtual source model (VSM) of a mini multi-leaf collimator (MLC) (the Elekta Beam Modulator (EBM)) is presented, allowing efficient generation of particles even for small fields. The VSM of the EBM is based on a previously published virtual photon energy fluence model (VEF) (Fippel et al 2003 Med. Phys. 30 301) commissioned with large field measurements in air and in water. The original commissioning procedure of the VEF, based on large field measurements only, leads to inaccuracies for small fields. In order to improve the VSM, it was necessary to change the VEF model by developing (1) a method to determine the primary photon source diameter, relevant for output factor calculations, (2) a model of the influence of the flattening filter on the secondary photon spectrum and (3) a more realistic primary photon spectrum. The VSM model is used to generate the source phase space data above the mini-MLC. Later the particles are transmitted through the mini-MLC by a passive filter function which significantly speeds up the time of generation of the phase space data after the mini-MLC, used for calculation of the dose distribution in the patient. The improved VSM model was commissioned for 6 and 15 MV beams. The results of MC simulation are in very good agreement with measurements. Less than 2% of local difference between the MC simulation and the diamond detector measurement of the output factors in water was achieved. The X, Y and Z profiles measured in water with an ion chamber (V = 0.125 cm3) and a diamond detector were used to validate the models. An overall agreement of 2%/2 mm for high dose regions and 3%/2 mm in low dose regions between measurement and MC simulation for field sizes from 0.8 × 0.8 cm2 to 16 × 21 cm2 was achieved. An IMRT plan film verification was performed for two cases: 6 MV head&neck and 15 MV prostate. The simulation is in agreement with film measurements within 2%/2 mm in the high dose regions (⩾0.1 Gy = 5% Dmax) and 5%/2 mm in low dose regions (<0.1 Gy).

SU-FF-T-253: Improvement of the Convolution/Superposition Algorithm for IMRT Dose Calculations

Purpose: To study improvements to the Convolution/Superposition (CS) dose calculation algorithm which enhance IMRT dose calculation accuracy. Method and Materials: Several aspects of typical CS calculation algorithms can be improved in order to increase the accuracy of IMRT dose calculations. To improve beam modeling and fitting, CS polyenergetic kernels were based on newly generated individual energy deposition kernels which are calculated on a high resolution grid using the Monte Carlo simulation package PENELOPE and relative contributions obtained from a detailed simulation of the accelerator head using the Monte Carlo code BEAM. Further improvement resulted from beam fitting based on data carefully measured using different detectors to better model dose in different regions of the dose distribution (e.g. beam penumbra, leaf and jaw transmission, buildup region, etc). Additional features added to enhance the CS algorithm included calculation of collimator scatter (for shaped and IMRT fields), an electron contamination correction for the buildup region for both the individual beamlet and final dose calculations, and modeling of the complete SMLC delivery sequence, allowing a more realistic final dose calculation after the optimization process is completed. Results: Comparison of output, depth dose and various dose profiles for square and shaped fields demonstrate the improved results for basic beam modeling. Ion chamber and 2-D dose distributions measured for a series of IMRT fields illustrate the increased accuracy possible with the enhanced algorithm. Routine IMRT QA accuracy showed an average improvement of 3% with respect to the more standard CS implementation. Conclusion: Enhancements to standard convolution/superposition algorithm implementations can significantly improve accuracy for shaped field and IMRT dose calculations throughout the patient, including the buildup region, penumbra and outside the field.

SU-FF-T-251: Improvement in IMRT Dose Calculation Accuracy with Megavoltage CT Imaging in the Presence of High Z Materials

Purpose: The purpose of this study was to evaluate the dosimetric uncertainties in TomoTherapy IMRT treatment planning due to the presence of high Z materials. Treatment plan calculations, and chamber measurements, were compared for accuracy with kilovoltage (KVCT), and megavoltage imaging (MVCT). Method and Materials: Electron density calibration curves were created using a Siemens Open Sensation unit for KVCT, and a TomoTherapy Hi-Art II unit for MVCT. Treatment plans were compared for a pelvic patient with bilateral hip replacements. In addition, for chamber measurements, treatment plans were also carried out on a phantom containing two high Z cerrobend inserts. The TomoTherapy Planned Adaptive module was used for IMRT calculation comparisons of KVCT and MVCT. Film profiles in the region of the heterogeneity were analyzed and compared using MatLab 7.0. Results: IMRT treatment planning calculations in the clinical image dataset resulted in a dose calculation discrepancy of 2.5% between KVCT and MVCT images. In addition, treatment planning with the phantom dataset, containing the high Z material, resulted in a 3.4% higher dose in the KVCT calculation compared to the MVCT calculation. Chamber measurements confirmed that the MVCT calculated treatment plan was within 0.05% of expected, while the KVCT calculated treatment plan was higher by 3.4% of actual measurement. Rendering from MatLab 7.0 showed that the KVCT film image was much noisier than MVCT film. Conclusion: These results demonstrate that KVCT IMRT treatment planning may be prone to error in the presence of high Z prosthetics. Under these conditions, MVCT imaging may result in more accurate treatment planning calculations.

Monte Carlo based IMRT dose verification using MLC log files and R/V outputs

Conventional IMRT dose verification using film and ion chamber measurements is useful but limited with respect to the actual dose distribution received by the patient. The Monte Carlo simulation has been introduced as an independent dose verification tool for IMRT using the patient CT data and MLC leaf sequence files, which validates the dose calculation accuracy but not the plan delivery accuracy. In this work, we propose a Monte Carlo based IMRT dose verification method that reconstructs the patient dose distribution using the patient CT, actual beam data based on the information from the record and verify system (R/V), and the MLC log files obtained during dose delivery that record the MLC leaf positions and MUs delivered. Comparing the Monte Carlo dose calculation with the original IMRT plan using these data simultaneously validates the accuracy of both the IMRT dose calculation and beam delivery. Such log file based Monte Carlo simulations are expected to be employed as a useful and efficient IMRT QA modality to validate the dose delivered to the patient. We have run Monte Carlo simulations for eight IMRT prostate plans using this method and the results for the target dose were consistent with the original CORVUS treatment plans to within 3.0% and 2.0% with and without heterogeneity corrections in the dose calculation. However, significant dose deviations in nearby critical structures have been observed. The results showed that up to 9.0% of the bladder dose and up to 38.0% of the rectum dose, to which leaf position errors were found to contribute <2%, were underestimated by the CORVUS treatment planning system. The concept of average leaf position error has been defined to analyze MLC leaf position errors for an IMRT plan. A linear correlation between the target dose error and the average position error has been found based on log file based Monte Carlo simulations, showing that an average position error of 0.2 mm can result in a target dose error of about 1.0%.

14 Evaluation of Pencil Beam, Collapsed Cone and Monte Carlo IMRT dose calculation algorithms for dual target sites

14 Evaluation of Pencil Beam, Collapsed Cone and Monte Carlo IMRT dose calculation algorithms for dual target sites