Fast Dose Calculation Research Articles

Precalculated Track Monte Carlo Using GPGPU

To implement a pre-calculated track Monte Carlo (PMC) dose calculation algorithm using general-purpose graphics processing unit technology for electron and proton transport. The aim is to produce a fast dose calculation engine for proton therapy planning and inverse planning of modulated electron radiation therapy cases.

Easy-to-Use Online Software Package for Internal Dose Assessment After Radionuclide Treatment in Clinical Routine

Internal dose assessment after radionuclide therapy is usually performed using home-made software packages. The dose assessment includes image registration, region-of-interest drawing, time-activity curve generation, and manual calculation of residence times followed by dose calculation with the OLINDA/MIRD software. The drawback of these methods is that several steps have to be performed using various software products possibly installed on different workstations. The aforementioned approaches are error-prone as well as difficult and time-consuming. In this article, we present a commercial software package that implements all the required dose calculation steps in 1 application, which greatly facilitates the internal dose assessment. The workflow of the newly developed software package "Hybrid Dosimetry" proceeds from automatic image registration to region-of-interest drawing, followed by time-activity curve fitting and dose calculation according to the MIRD method. The software is available online and can be run on independent computers using images in the common DICOM format. We used the package for internal dosimetry of 8 patients treated with Lu-DOTATATE and compared the results with manual dose calculation. The online software package presented is platform independent and allows fast dose calculations. The results obtained with the new package were in perfect agreement with manual methods.

Benchmark measurements and simulations of dose perturbations due to metallic spheres in proton beams

Monte Carlo simulations are increasingly used for dose calculations in proton therapy due to its inherent accuracy. However, dosimetric deviations have been found using Monte Carlo code when high density materials are present in the proton beamline. The purpose of this work was to quantify the magnitude of dose perturbation caused by metal objects. We did this by comparing measurements and Monte Carlo predictions of dose perturbations caused by the presence of small metal spheres in several clinical proton therapy beams as functions of proton beam range and drift space. Monte Carlo codes MCNPX, GEANT4 and Fast Dose Calculator (FDC) were used. Generally good agreement was found between measurements and Monte Carlo predictions, with the average difference within 5% and maximum difference within 17%. The modification of multiple Coulomb scattering model in MCNPX code yielded improvement in accuracy and provided the best overall agreement with measurements. Our results confirmed that Monte Carlo codes are well suited for predicting multiple Coulomb scattering in proton therapy beams when short drift spaces are involved.

TU‐G‐103‐05: Affordable Supercomputer‐Based Monte Carlo CT Dose Calculations: A Hardware Comparison Between Nvidia M2090 GPU and Intel Xeon Phi 5110p Coprocessor

Purpose: To develop a fast Monte Carlo code ARCHER (a testbed for Accelerated Radiation‐transport Computation in Heterogeneous EnviRonments) to calculate CT imaging organ doses on heterogeneous computing systems. Methods: ARCHER simulates the transport of low‐energy (1∼140keV) photons in heterogeneous media using two selectable interaction models, simple and detailed. It includes an extensive library of voxelized human phantoms such as RPI‐Pregnant women with 3, 6, 9 month gestation, extended RPI‐Adult male and female phantoms representing patients of different obesity level. It contains a validated scanner model based on a GE LightSpeed third‐generation 16‐multi‐detector CT. A series of scan protocols are predefined, including a combination of scan mode (helical or axial), beam collimation (5, 10, or 20 mm) and kVp (80, 100, 120 or 140). ARCHER is targeted for three platforms, CPU (an Intel Xeon X5650 6‐core processor), GPU (Nvidia M2090 GPU), and coprocessor (Intel Xeon Phi 5110p coprocessor), and correspondingly has three code variants developed in MPI‐OpenMP, CUDA and offload OpenMP respectively. Results: Absorbed doses to 28 organs/tissues of dosimetric interest were calculated. MCNPX was used as the accuracy benchmark. The average difference of the organ doses calculated by MCNPX and ARCHER were found to be less than 5% and 0.5% for simple and detailed interaction models respectively, indicating an excellent agreement. While ARCHER's three variants were 63∼1207x faster than MCNPX, the GPU and coprocessor codes were 1.6∼3.4x faster than the CPU (6 core) code. Conclusion: The accelerator‐based new Monte Carlo code ARCHER is developed for accurate and fast CT imaging organ dose calculations. Its full capability to simulate patients of different genders and body sizes receiving different scan protocols exhibits high clinical value.

SU-D-141-05: Transmission Verification Using the On-Board EPID

Purpose: To provide in‐vivo dose and patient geometry verification for radiation therapy using an MV image acquired during treatment and a fast dose calculation method through the patient geometry. Methods: Dosimetric calibration of the EPID is performed using the known profile for a series of uniform phantoms with thickness between 0 to 22 cm. Phantom scattering within the EPID is corrected to minimize systemic error. The dose‐response of the EPID is linear with dose after correction. A fast ray‐tracing algorithm is used to calculate the total dose (separated into primary and scatter components from the patient geometry) on the EPID active imaging plane under perspective geometry. Attenuation of the primary dose as a function of radiological length is approximated by the attenuation function u. and off‐axis softening coefficient η. An iterative procedure is used to find a self‐consistent solution of total dose measured by the EPID and calculation through a series of phantoms with uniform thicknesses. 3D verification of the patient geometry is achieved through automatic 2D and 3D registration of a 2D radiograph kilovoltage OBI or megavoltage EPI to the 3D planning CT using one of three similarity measures: Pearson correlation coefficient, maximum likelihood measure with Gaussian noise [1] or mutual information. Results: The dose‐response curve for the amorphous‐silicon EPID was obtained. The fast ray‐tracing algorithm has been developed and tested on both phantom and Rando phantom patient geometry. First results have shown that the estimated patient dose is within 5% of that calculated by the treatment planning system. Conclusion: A fast in vivo 3D dose verification using EPID is demonstrated. Further development is warranted with a goal of clinical implementation, given its promise as a routine patient QA procedure for IMRT dose and geometry verifications. [1] Munbodh et al. Med. Phys. 36(10), 2009

A fast analytic dose calculation method for arc treatments for kilovoltage small animal irradiators

Arc treatments require calculation of dose for collections of discrete gantry angles. The sampling of angles must balance between short computation time of small angle sets and the better calculation reliability of large sets. In this paper, an analytical formula is presented that allows calculation of dose delivered during continuous rotation of the gantry. The formula holds valid for continuous short arcs of up to about 30° and is derived by integrating a dose formula over gantry angles within a small angle approximation. Doses for longer arcs may be obtained in terms of doses for shorter arcs. The formula is derived with an empirical beam model in water and extended to inhomogeneous media. It is validated with experimental data obtained by applying arc treatment using kV small animal irradiator to a phantom of solid water and lung-equivalent material. The results are a promising step towards efficient 3D dose calculation and inverse planning purposes. In principle, this method also applies to VMAT dose calculation and optimization but requires extensions.

蒙特卡罗技术在放射诊断剂量快速计算中的应用

蒙特卡罗技术在放射诊断剂量快速计算中的应用

GPU-based fast Monte Carlo dose calculation for proton therapy

Accurate radiation dose calculation is essential for successful proton radiotherapy. Monte Carlo (MC) simulation is considered to be the most accurate method. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. We have developed a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. In gPMC, proton transport is modeled by the class II condensed history simulation scheme with a continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons are not transported and their energies are locally deposited. After an inelastic nuclear interaction event, a variety of products are generated using an empirical model. Among them, charged nuclear fragments are terminated with energy locally deposited. Secondary protons are stored in a stack and transported after finishing transport of the primary protons, while secondary neutral particles are neglected. gPMC is implemented on the GPU under the CUDA platform. We have validated gPMC using the TOPAS/Geant4 MC code as the gold standard. For various cases including homogeneous and inhomogeneous phantoms as well as a patient case, good agreements between gPMC and TOPAS/Geant4 are observed. The gamma passing rate for the 2%/2 mm criterion is over 98.7% in the region with dose greater than 10% maximum dose in all cases, excluding low-density air regions. With gPMC it takes only 6–22 s to simulate 10 million source protons to achieve ∼1% relative statistical uncertainty, depending on the phantoms and energy. This is an extremely high efficiency compared to the computational time of tens of CPU hours for TOPAS/Geant4. Our fast GPU-based code can thus facilitate the routine use of MC dose calculation in proton therapy.

Sub-second high dose rate brachytherapy Monte Carlo dose calculations withbGPUMCD

To establish the accuracy and speed of bGPUMCD, a GPU-oriented Monte Carlo code used for high dose rate brachytherapy dose calculations. The first objective is to evaluate the time required for dose calculation when full Monte Carlo generated dose distribution kernels are used for plan optimization. The second objective is to assess the accuracy and speed when recalculating pre-optimized plans, consisting of many dwell positions. bGPUMCD is tested with three clinical treatment plans : one prostate case, one breast case, and one rectum case with a shielded applicator. Reference distributions, generated with GEANT4, are used as a basis of comparison. Calculations of full dose distributions of pre-optimized treatment plans as well as single dwell dosimetry are performed. Single source dosimetry, based on TG-43 parameters reproduction, is also presented for the microSelectron V2 (Nucletron, Veenendaal, The Netherlands). In timing experiments, the computation of single dwell position dose kernels takes between 0.25 and 0.5 s. bGPUMCD can compute full dose distributions of previously optimized plans in ∼2 s. bGPUMCD is capable of computing pre-optimized brachytherapy plans within 1% for the prostate case and 2% for the breast and shielded applicator cases, when comparing the dosimetric parameters D90 and V100 of the reference (GEANT4) and bGPUMCD distributions. For all voxels within the target, an absolute average difference of approximately 1% is found for the prostate case, less than 2% for the breast case and less than 2% for the rectum case with shielded applicator. Larger point differences (>5%) are found within bony regions in the prostate case, where bGPUMCD underdoses compared to GEANT4. Single source dosimetry results are mostly within 2% for the radial function and within 1%-4% for the anisotropic function. bGPUMCD has the potential to allow for fast MC dose calculation in a clinical setting for all phases of HDR treatment planning, from dose kernel calculations for plan optimization to plan recalculation.

SU-E-T-541: Dose Calculation Algorithm for External Neutron Radiotherapy Based on Pencil Beam Method.

To evaluate the availability and performance of pencil beam algorithm for fast neutrons radiotherapy dose calculations and to achieve improvements in universality, speed and inhomogeneities corrections. Pencil beam (PB) method uses integration of dose kernel cross field size to estimate dose distribution. In order to calculate dose kernels we used general purpose Monte-Carlo (MC) code MCNP. The same program was used also for PB benchmarking. Multi-group approach used for kernels calculation virtually allows calculation for arbitrary spectrum. Nevertheless we took four common spectra to investigate accuracy and to establish according corrections. Several approaches for inhomogeneities corrections have been investigated. The output of MC calculations is discrete kernel data, which does not allow fast calculations. To overcome this limitation we investigated different dose kernels approximations and integrations. PB dose kernel library was established. Comparison of PB calculation with reference algorithm shows adequate precision for arbitrary neutron spectra with inhomogeneities correction, while calculations are fast enough for optimization tasks. Secondary photon dose distributions comparison give worse still promising results. Researches of this paper show benefits and limitations of PB method for neutron teletherapy treatment planning. Calculations made during research allow saying that results of PB method are generally acceptable. Still additional data are needed to evaluate our results, probably voxel phantom MC calculations and/or beam data measurements.

WE‐C‐BRB‐09: Development of a GPU‐Based Monte Carlo Dose Calculation Package for Proton Radiotherapy

Purpose: Monte Carlo (MC) simulation is considered to be the most accurate method for proton therapy dose calculation. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. The purpose of this project is to develop a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. Methods: gPMC supports proton transport in the energy range of 0.5∼300 MeV. Proton transport is modeled by the Class II condensed history simulation scheme with continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons and charged nuclear fragments are not transported and their energies are locally deposited. Secondary protons are stored in a stack and transported after the primary protons finish, while secondary neutral particles are neglected. gPMC is implemented on GPU under the CUDA platform with each GPU thread responsible for the transport of a single proton. A high performance random number generator and hardware linear interpolation are utilized. Results: We have validated gPMC in various cases including homogeneous phantoms with different materials and a phantom of a half slab geometry. A mono‐energetic mono‐directional proton beam is used. Good agreements between results from gPMC and Geant4 are observed, and the gamma passing rate for 3%/3mm criterion is over 99.9% in the region with dose greater than 10% maximum dose. It takes 6.3∼24.1 sec to simulate 10 million source protons depending on the phantoms and the energy. A high efficiency has been achieved compared to the computational time of tens of CPU hours for Geant4. Conclusions: We have developed a GPU‐based MC proton dose calculation package, gPMC. The achieved accuracy and efficiency is promising for clinical applications.

TH‐A‐BRA‐09: Statistical Assessment of Plan Robustness Under Uncertainties: IMRT Vs. Proton Therapy

Purpose: Fair comparisons between x‐ray IMRT and Proton therapy plans should include assessment of plan robustness. However, this is difficult because the dose distribution can be altered in the presence of uncertainties in different ways for each modality. In order to fairly evaluate plan's robustness for both arms, we propose the use of statistical parameters to assess the probabilistic distribution of dose and DVHs under setup and range uncertainties. Methods: A lung cancer patient currently undergoing randomized trial was selected for this study. Physician approved x‐ray IMRT and passively scattered proton plans were created under identical planning objectives. For each of these plans, a total of 500 dose calculations were performed that simulated 50 virtual treatments with each treatment having 10 fractions. We found random error quickly converged within 10 fractions. A random setup error was introduced for each of the multiple fractions while a static systematic setup and range errors were introduced over simulated treatments. In calculating the doses, we assumed a static dose distribution for the IMRT plan. For Proton plans, a new dose calculation was performed for every simulation using a fast dose calculation method. Based on these simulations, the expectation value of DVH (E[DVH]) and standard deviation (SD[DVH]) were calculated. Both SD[DVH] and the difference between E[DVH] and the original DVH characterize the plan's robustness. Results: The E[DVH] showed that the V100% target coverage was 0.5% and 4% less than the original coverage for IMRT and Proton plans, respectively. The SD[DVH] near the prescription dose bin were 1% and 3% for IMRT and Proton plans respectively. Conclusions: Our results showed that the E[DVH] and SD[DVH] are viable options for evaluating plan robustness for both treatment modalities. Clinical prescription and dose objectives should be evaluated under uncertainty to assure treatment goals can be realized against uncertainties considered. Supported in part by NCI P01CA021239‐29A1.

SU‐C‐213AB‐01: Application of Ultra‐Fast Dose Calculation in Real‐Time Interactive Treatment Panning

Purpose: We are investigating a new treatment planning paradigm: realtime planning via interactive dose shaping (IDS). IDS is a universal two‐step process: First, a desired local dose variation is imposed for a 3D dose distribution by adjusting the correspondent fluence amplitudes. This dose modification inevitably causes unwanted dose changes outside the considered local dose area. Thus, second, a recovery strategy is applied to compensate for these unintended changes, so that the initial modification only has an influence on the desired region of the plan. The planning process could be carried out as a sequence of this Dose Modification and Recovery (DMR) steps. For implementing DMR strategies in realtime an ultra‐fast local dose calculation within a few milliseconds is needed for evaluating the incrementally modified dose distribution. Methods: The fast dose calculation algorithm is based on a pencil beam convolution technique using a set of measured pencil beam kernels whose convolutions with the beam fluence are carried out in a discretized spatial domain. This leads to three key features for our algorithm: i) A spatial‐limited modification of fluence amplitudes requested by the DMR strategy can be considered as a relatively small incremental term to the convolution in space domain ii) The discrete convolution consists of simple multiply‐add operations which are highly optimized on modern CPU and GPU hardware. iii) The trade‐off accuracy/runtime can be adapted selectively for each fluence region of interest by controlling the radius of the finite pencil beam kernel. Results: The runtime of dose updates over a fluence area of 20×20 mm is about 10 ms on a Intel i7 CPU with an accuracy of 1% in the high dose region. Conclusions: It could be shown that the proposed method of local dose update calculation is fast and accurate enough for our interactive realtime dose shaping planning approach.

Fast on‐site Monte Carlo tool for dose calculations in CT applications

Monte Carlo (MC) simulation is an established technique for dose calculation in diagnostic radiology. The major drawback is its high computational demand, which limits the possibility of usage in real-time applications. The aim of this study was to develop fast on-site computed tomography (CT) specific MC dose calculations by using a graphics processing unit (GPU) cluster. GPUs are powerful systems which are especially suited to problems that can be expressed as data-parallel computations. In MC simulations, each photon track is independent of the others; each launched photon can be mapped to one thread on the GPU, thousands of threads are executed in parallel in order to achieve high performance. For further acceleration, the authors considered multiple GPUs. The total computation was divided into different parts which can be calculated in parallel on multiple devices. The GPU cluster is an MC calculation server which is connected to the CT scanner and computes 3D dose distributions on-site immediately after image reconstruction. To estimate the performance gain, the authors benchmarked dose calculation times on a 2.6 GHz Intel Xeon 5430 Quad core workstation equipped with two NVIDIA GeForce GTX 285 cards. The on-site calculation concept was demonstrated for clinical and preclinical datasets on CT scanners (multislice CT, flat-detector CT, and micro-CT) with varying geometry, spectra, and filtration. To validate the GPU-based MC algorithm, the authors measured dose values on a 64-slice CT system using calibrated ionization chambers and thermoluminesence dosimeters (TLDs) which were placed inside standard cylindrical polymethyl methacrylate (PMMA) phantoms. The dose values and profiles obtained by GPU-based MC simulations were in the expected good agreement with computed tomography dose index (CTDI) measurements and reference TLD profiles with differences being less than 5%. For 10(9) photon histories simulated in a 256 × 256 × 12 voxel thorax dataset with voxel size of 1.36 × 1.36 × 3.00 mm(3), calculation times of about 70 and 24 min were necessary with single-core and multiple-core central processing unit (CPU) solutions, respectively. Using GPUs, the same MC calculations were performed in 1.27 min (single card) and 0.65 min (two cards) without a loss in quality. Simulations were thus speeded up by factors up to 55 and 36 compared to single-core and multiple-core CPU, respectively. The performance scaled nearly linearly with the number of GPUs. Tests confirmed that the proposed GPU-based MC tool can be easily adapted to different types of CT scanners and used as service providers for fast on-site dose calculations. The Monte Carlo software package provides fast on-site calculation of 3D dose distributions in the CT suite which makes it a practical tool for any type of CT-specific application.

Fast patient-specific Monte Carlo brachytherapy dose calculations via the correlated sampling variance reduction technique

To demonstrate potential of correlated sampling Monte Carlo (CMC) simulation to improve the calculation efficiency for permanent seed brachytherapy (PSB) implants without loss of accuracy. CMC was implemented within an in-house MC code family (PTRAN) and used to compute 3D dose distributions for two patient cases: a clinical PSB postimplant prostate CT imaging study and a simulated post lumpectomy breast PSB implant planned on a screening dedicated breast cone-beam CT patient exam. CMC tallies the dose difference, ΔD, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled in a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. The prostate case consisted of 78 Model-6711 (125)I seeds. The breast case consisted of 87 Model-200 (103)Pd seeds embedded around a simulated lumpectomy cavity. Systematic and random errors in CMC were unfolded using low-uncertainty uncorrelated MC (UMC) as the benchmark. CMC efficiency gains, relative to UMC, were computed for all voxels, and the mean was classified in regions that received minimum doses greater than 20%, 50%, and 90% of D(90), as well as for various anatomical regions. Systematic errors in CMC relative to UMC were less than 0.6% for 99% of the voxels and 0.04% for 100% of the voxels for the prostate and breast cases, respectively. For a 1 × 1 × 1 mm(3) dose grid, efficiency gains were realized in all structures with 38.1- and 59.8-fold average gains within the prostate and breast clinical target volumes (CTVs), respectively. Greater than 99% of the voxels within the prostate and breast CTVs experienced an efficiency gain. Additionally, it was shown that efficiency losses were confined to low dose regions while the largest gains were located where little difference exists between the homogeneous and heterogeneous doses. On an AMD 1090T processor, computing times of 38 and 21 sec were required to achieve an average statistical uncertainty of 2% within the prostate (1 × 1 × 1 mm(3)) and breast (0.67 × 0.67 × 0.8 mm(3)) CTVs, respectively. CMC supports an additional average 38-60 fold improvement in average efficiency relative to conventional uncorrelated MC techniques, although some voxels experience no gain or even efficiency losses. However, for the two investigated case studies, the maximum variance within clinically significant structures was always reduced (on average by a factor of 6) in the therapeutic dose range generally. CMC takes only seconds to produce an accurate, high-resolution, low-uncertainly dose distribution for the low-energy PSB implants investigated in this study.

Investigation of voxel warping and energy mapping approaches for fast 4D Monte Carlo dose calculations in deformed geometries using VMC++

A new deformable geometry class for the VMC++ Monte Carlo code was implemented based on the voxel warping method. Alternative geometries which use tetrahedral sub-elements were implemented and efficiency improvements investigated. A new energy mapping method, based on calculating the volume overlap between deformed reference dose grid and the target dose grid, was also developed. Dose calculations using both the voxel warping and energy mapping methods were compared in simple phantoms as well as a patient geometry. The new deformed geometry implementation in VMC++ increased calculation times by approximately a factor of 6 compared to standard VMC++ calculations in rectilinear geometries. However, the tetrahedron-based geometries were found to improve computational efficiency, relative to the dodecahedron-based geometry, by a factor of 2. When an exact transformation between the reference and target geometries was provided, the voxel and energy warping methods produced identical results. However, when the transformation is not exact, there were discrepancies in the energy deposited on the target geometry which lead to significant differences in the dose calculated by the two methods. Preliminary investigations indicate that these energy differences may correlate with registration errors; however, further work is needed to determine the usefulness of this metric for quantifying registration accuracy.

Fast dose calculation in magnetic fields with GPUMCD

A new hybrid imaging-treatment modality, the MRI-Linac, involves the irradiation of the patient in the presence of a strong magnetic field. This field acts on the charged particles, responsible for depositing dose, through the Lorentz force. These conditions require a dose calculation engine capable of taking into consideration the effect of the magnetic field on the dose distribution during the planning stage. Also in the case of a change in anatomy at the time of treatment, a fast online replanning tool is desirable. It is improbable that analytical solutions such as pencil beam calculations can be efficiently adapted for dose calculations within a magnetic field. Monte Carlo simulations have therefore been used for the computations but the calculation speed is generally too slow to allow online replanning. In this work, GPUMCD, a fast graphics processing unit (GPU)-based Monte Carlo dose calculation platform, was benchmarked with a new feature that allows dose calculations within a magnetic field. As a proof of concept, this new feature is validated against experimental measurements. GPUMCD was found to accurately reproduce experimental dose distributions according to a 2%-2 mm gamma analysis in two cases with large magnetic field-induced dose effects: a depth-dose phantom with an air cavity and a lateral-dose phantom surrounded by air. Furthermore, execution times of less than 15 s were achieved for one beam in a prostate case phantom for a 2% statistical uncertainty while less than 20 s were required for a seven-beam plan. These results indicate that GPUMCD is an interesting candidate, being fast and accurate, for dose calculations for the hybrid MRI-Linac modality.

Validation of GPUMCD for low‐energy brachytherapy seed dosimetry

To validate GPUMCD, a new package for fast Monte Carlo dose calculations based on the GPU (graphics processing unit), as a tool for low-energy single seed brachytherapy dosimetry for specific seed models. As the currently accepted method of dose calculation in low-energy brachytherapy computations relies on severe approximations, a Monte Carlo based approach would result in more accurate dose calculations, taking in to consideration the patient anatomy as well as interseed attenuation. The first step is to evaluate the capability of GPUMCD to reproduce low-energy, single source, brachytherapy calculations which could ultimately result in fast and accurate, Monte Carlo based, brachytherapy dose calculations for routine planning. A mixed geometry engine was integrated to GPUMCD capable of handling parametric as well as voxelized geometries. In order to evaluate GPUMCD for brachytherapy calculations, several dosimetry parameters were computed and compared to values found in the literature. These parameters, defined by the AAPM Task-Group No. 43, are the radial dose function, the 2D anisotropy function, and the dose rate constant. These three parameters were computed for two different brachytherapy sources: the Amersham OncoSeed 6711 and the Imagyn IsoStar IS-12501. GPUMCD was shown to yield dosimetric parameters similar to those found in the literature. It reproduces radial dose functions to within 1.25% for both sources in the 0.5< r <10 cm range. The 2D anisotropy function was found to be within 3% at r =5 cm and within 4% at r = 1 cm. The dose rate constants obtained were within the range of other values reported in the literature. GPUMCD was shown to be able to reproduce various TG-43 parameters for two different low-energy brachytherapy sources found in the literature. The next step is to test GPUMCD as a fast clinical Monte Carlo brachytherapy dose calculations with multiple seeds and patient geometry, potentially providing more accurate results than the TG-43 formalism while being much faster than calculations using general purpose Monte Carlo codes.

SU‐E‐T‐697: Online Monte‐Carlo‐Accurate Real‐Time Proton Dose Calculator

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-717: Research on the Inhomogeneous Correction Algorithm Based on Monte Carlo Simulation

Purpose: Batho is one of inhomogeneous correction algorithms which has high correction accuracy in homogeneous tissue, but has lower correction accuracy in cavum and the interface between different density tissues. In this paper, the database of dose distribution with every kinds of different density tissues combination by Monte Carlo simulation is built up for the purpose of development for fast and accurate dose calculation method. Methods: The MC simulation models are built as follow. Model 1: in 30cm×30cm×30cm cube phantom full of one homogeneity tissue. In module 2:1cm×1cm×1cm cube inhomogeneous tissue is put in the central axis (0,0,0.5),(0,0,1.5,)…(0,0,29.5) (each down 1cm) of model 1 respectively. These phantoms are segmented into 0.2cm × 0.2cm × 0.2cm volumes. For simplicity, the inhomogeneous tissue of human body is classified to typical tissues (water, bone etc.) by electron densities. The dose distribution of homogeneous tissue and inhomogeneous tissue is simulated by MC in model 1 and model 2.All dose value is normalized to the point (0,0,1.5). Then database of dose distribution relative error between dose distribution of mode 2 and mode l could be established. At any point p, the destiny change along the primary ray path judged by program firstly. Batho algorithm is used in uniform region. In the interface between different tissues and inside cavity, the dose value will be corrected by the database of relative error. Results: Comparing with the correction result of pure Batho algorithm, this program can gain more accurate correction results close to MC in short time in the interface between different tissues and cavity. Conclusions: In this paper, the higher correction accuracy could be achieved and the method is simple, easy to implement. The result of this study can provide fast and accurate dose calculation module radiation planning system. The work is supported by National 973 Planned Project (2006CB708307), the National Natural Science Foundation of China (60872112 and 10805012), the Natural Science Foundation of Zhejiang Province (Z207588), the College Science Research Projects of Anhui Province (KJ2008B268).