A Ding

Monte Carlo calculation of imaging doses from diagnostic multidetector CT and kilovoltage cone‐beam CT as part of prostate cancer treatment plans

PURPOSE To calculate imaging doses to the rectum, bladder, and femoral heads as part of a prostate cancer treatment plans, assuming an image guided radiation therapy (IGRT) procedure involving either the multidetector CT (MDCT) or kilovoltage cone-beam CT (kV CBCT). METHODS This study considered an IGRT treatment plan for a prostate carcinoma patient involving 50.4 Gy from 28 initial fractions and a boost of 28.8 Gy from 16 fractions. A total of 45 CT imaging procedures, each involving a MDCT or a kV CBCT scan procedure, were carefully modeled using the MCNPX code version 2.5.0. The MDCT scanner model is based on the GE LightSpeed 16-MDCT scanner and the kV CBCT scanner model is based on the Varian On-Board Imager using parameters reported by the CT manufacturers and literatures. A patient-specific treatment planning CT data set was used to construct the phantom for the dose calculation. The target, organs-at-risk (OARs), and background voxels in the CT data set were categorized into six tissue types according to CT numbers for Monte Carlo calculations. RESULTS For a total of 45 imaging procedures, it was found that the rectum received 78.4 and 76.7 cGy from MDCT and kV CBCT, respectively. The bladder received slightly greater doses of 82.4 and 77.9 cGy, while the femoral heads received much higher doses of 182.3 and 141.3 cGy from MDCT and kV CBCT, respectively. To investigate the impact of these imaging doses on treatment planning, OAR doses from MDCT or kV CBCT imaging procedures were added to the corresponding dose matrix reported by the original treatment plans to construct dose volume histograms. It was found that after the imaging dose is added, the rectum volumes irradiated to 75 and 70 Gy increased from 13.9% and 21.2%, respectively, in the original plan to 14.8% and 21.8%. The bladder volumes receiving 80 Gy increased to 4.6% from 4.1% in the original plan and the volume receiving 75 Gy increased to 7.9% from 7.5%. All values remained within the tolerance levels: V70<25%, V75 <15% for rectum and V75 < 25%, V80 < 15% for bladder. The irradiation of femoral heads was also acceptable with no volume receiving >45 Gy. CONCLUSIONS IGRT procedures can irradiate the OARs to an imaging dose level that is great enough to require careful evaluation and perhaps even adjustment of original treatment planning in order to still satisfy the dose constraints. This study only considered one patient CT because the CT x rays cover a relatively larger volume of the body and the dose distribution is considerably more uniform than those associated with the therapeutic beams. As a result, the dose to an organ from CT imaging doses does not vary much from one patient to the other for the same CT settings. One factor that would potentially affect such CT dose level is the size of the patient body. More studies are needed to develop accurate and convenient methods of accounting for the imaging doses as part of treatment planning.

COMPARISON OF PARTICLE-TRACKING FEATURES IN GEANT4 AND MCNPX CODES FOR APPLICATIONS IN MAPPING OF PROTON RANGE UNCERTAINTY.

Abstract The accuracy of proton therapy is partially limited by uncertainties that result from changing pathological conditions in the patient such as tumor motion and shrinkage. These uncertainties can be minimized with the help of a time-resolved range telescope. Monte Carlo methods can help improve the performance of range telescopes by tracking proton interactions on a particle-by-particle basis thus broadening our understanding on the behavior of protons within the patient and the detector. This paper compared the proton multiple coulomb scattering algorithms in the Monte Carlo codes MCNPX and Geant4 to well-established scattering theories. We focus only on beam energies associated with proton imaging. Despite slight discrepancies between scattering algorithms, both codes appear to be capable of providing useful particle-tracking information for applications such as the proton range telescope.

MO‐F‐213CD‐01: GPU‐Based Monte Carlo Methods for Accelerating Radiographic and CT Imaging Dose Calculations: Feasibility and Scalability

Purpose: To develop a Graphics Processing Unit (GPU) based Monte Carlo(MC) code that uses a dual‐GPU system to accelerate radiographic simulation and CTimaging dose calculations. Methods: We considered two clinical cases, a chest x‐ray radiography and an abdominal CT scan. In the first case, a voxelized VIP‐Man phantom with detailed 3D anatomical information was used and an x‐ray beam of 120kVp was simulated. In the second case, a voxelized abdomen phantom derived from 120 CT slices was used, and a GE LightSpeed 16‐MDCT scanner was modeled. The CPU version of the MC code was written in C++ and run on Intel Xeon X5660 2.8GHz CPU, then translated into GPU code written in CUDA C and tested on a dual Tesla m2090 GPU system. The code was featured with automatic assignment of simulation task to multiple GPUs, as well as accurate calculation of energy‐ and material‐dependent cross‐sections. Results: Double‐precision floating point format was used for accuracy. In the first case, radiograph formation was simulated and doses to the organs listed in ICRP‐60 were calculated. When running on a single GPU, the MC GPU code was found to be x13 times faster than the CPU code and x29 times faster than MCNPX. In the second case, doses to the rectum, prostate, bladder and femoral heads were calculated. A speedup of x19 was observed compared to CPU code. These speedup factors were doubled on the dual‐GPU system. The imaging dose was benchmarked against MCNPX and a maximum difference of 1% was observed when the relative error is kept below 0.1%. Conclusions: A GPU‐based MC code was developed to simulate radiography and calculate imaging dose using detailed patient and CTscanner models. Efficiency and accuracy were both guaranteed in this code. Scalability of the code was confirmed on the dual‐GPU system.

WE‐C‐BRB‐08: A GPU/CUDA Based Monte Carlo Code for Proton Transport: Preliminary Results of Proton Depth Dose in Water

Purpose: Although several studies have reported the use of GPUs to accelerate Monte Carlo calculations for x‐ray imaging and treatment planning, there is little effort to demonstrate the utility of this highly parallel yet affordable computing tool for protontreatment planning and dose verification. This paper describes a preliminary project to design a GPU/CUDA based proton transport MC code and to evaluate the timing for proton dose depth distribution. Methods: The proton transport in media was modeled by condensed history method, in which the effect of many interactions was grouped into single condensed step. The Moliere distribution and Valilov distribution were employed to calculate angular deflection and energy loss. The CPU code was written in C++ and GPU‐ based code was developed in CUDA C 4.0. The hardware platform was a desktop with Intel Xeon X5660 CPU and NVIDIA Tesla™ m2090 GPU. Nuclear interactions were not included in the preliminary study and the transport medium was limited to water. Results: The depth dose distributions of proton of different energies were simulated. It was found that 98% of the tallies had relative error less than 1%. The code was benchmarked against MCNPX and GEANT4 codes. For 200 MeV proton pencil beam incident on the water phantom, the dose difference between our code and GEANT4 (nuclear interaction disabled) was within 2% for 95% of all depths. The speedup factor of our GPU code over CPU code was x57. While compared with MCNPX(nuclear interaction on), the GPU code was x620 times faster. Conclusions: This is one of the first reported efforts to demonstrate a GPU/CUDA‐based proton transport MC code for dose calculations. Despite some limitations, this preliminary project was able to show significant gains in the GPU computing time, thus suggesting a promising role of such Monte Carlo tools in the future. This project was funded in part by National Institutes of Health (National Library of Medicine R01LM009362)

Independent calculation of monitor units for VMAT and SPORT

PURPOSE Dose and monitor units (MUs) represent two important facets of a radiation therapy treatment. In current practice, verification of a treatment plan is commonly done in dose domain, in which a phantom measurement or forward dose calculation is performed to examine the dosimetric accuracy and the MU settings of a given treatment plan. While it is desirable to verify directly the MU settings, a computational framework for obtaining the MU values from a known dose distribution has yet to be developed. This work presents a strategy to calculate independently the MUs from a given dose distribution of volumetric modulated arc therapy (VMAT) and station parameter optimized radiation therapy (SPORT). METHODS The dose at a point can be expressed as a sum of contributions from all the station points (or control points). This relationship forms the basis of the proposed MU verification technique. To proceed, the authors first obtain the matrix elements which characterize the dosimetric contribution of the involved station points by computing the doses at a series of voxels, typically on the prescription surface of the VMAT/SPORT treatment plan, with unit MU setting for all the station points. An in-house Monte Carlo (MC) software is used for the dose matrix calculation. The MUs of the station points are then derived by minimizing the least-squares difference between doses computed by the treatment planning system (TPS) and that of the MC for the selected set of voxels on the prescription surface. The technique is applied to 16 clinical cases with a variety of energies, disease sites, and TPS dose calculation algorithms. RESULTS For all plans except the lung cases with large tissue density inhomogeneity, the independently computed MUs agree with that of TPS to within 2.7% for all the station points. In the dose domain, no significant difference between the MC and Eclipse Anisotropic Analytical Algorithm (AAA) dose distribution is found in terms of isodose contours, dose profiles, gamma index, and dose volume histogram (DVH) for these cases. For the lung cases, the MC-calculated MUs differ significantly from that of the treatment plan computed using AAA. However, the discrepancies are reduced to within 3% when the TPS dose calculation algorithm is switched to a transport equation-based technique (Acuros™). Comparison in the dose domain between the MC and Eclipse AAA/Acuros calculation yields conclusion consistent with the MU calculation. CONCLUSIONS A computational framework relating the MU and dose domains has been established. The framework does not only enable them to verify the MU values of the involved station points of a VMAT plan directly in the MU domain but also provide a much needed mechanism to adaptively modify the MU values of the station points in accordance to a specific change in the dose domain.

TH‐C‐201B‐10: Development and Testing of a CT Dose Software “VirtualDose” Using Anatomically Realistic Patient Phantoms: Preliminary Results for the Phase I of the Project

Purpose: To demonstrate the need and feasibility for developing a new software for reporting patient imaging dose who undergoing CT or PET/CT examinations. Method and Materials: Existing CT dose reporting software do not meet the need because of the simplified anatomical phantoms updated ICRP data and scanner information. A new software is being designed with original dose data derived from Monte Carlo simulations involving CTscannermodels and anatomically realistic phantoms. Specified scanning protocols and CT sources are modeled. Dosimetry capabilities for tube current modulation (TCM) and PET/CT protocols are currently under development. The RPI Pregnant Women series RPI Adult Male and Adult Female phantoms are used in the dose calculation. Organ doses and effective doses are computed using ICRP Publication 60 and 103. The software framework is developed using the Visual C#.NET. Results: VirtualDose offers a modern graphical user interface (GUI) designed to allow interactive 3D phantom display and user‐selectable scanning parameters. Standard scanning ranges can be selected from a pull‐down menu or manually specified on the displayed phantom. When compared with data reported by existing software using stylized MIRD‐type phantoms the organ dose estimates have been found to differ by a ratio ranging from 0.77 to 1.24 for organs or tissues covered in the scan range and a ratio as small as 0.13 for organs outside of the scan region. The TCM technique can reduce the dose by around 20% for pregnant patient phantoms. Conclusion: It is clear that existing software do not meet the need for accurate and state‐of‐the‐art CT dose reporting. The preliminary GUI design and reporting features of VirtualDose improve upon existing tools by considering the latest CTscanners new ICRP recommendations and anatomically realistic patient phantoms. VirtualDose is expected to improve both the accuracy and usability in reporting CT doses in the future.

A dose-reconstruction study of the 1997 Sarov criticality accident using animated dosimetry techniques.

AbstractMost computational human phantoms are static, representing a standing individual. There are, however, cases when these phantoms fail to represent accurately the detailed effects on dose that result from considering varying human posture and even whole sequences of motion. In this study, the feasibility of a dynamic and deformable phantom is demonstrated with the development of the Computational Human for Animated Dosimetry (CHAD) phantom. Based on modifications to the limb structure of the previously developed RPI Adult Male, CHAD’s posture is adjustable using an optical motion capture system that records real-life human movement. To demonstrate its ability to produce dose results that reflect the changes brought about by posture-deformation, CHAD is employed to perform a dose-reconstruction analysis of the 1997 Sarov criticality accident, and a simulated total body dose of 13.3 Gy is observed, with the total body dose rate dropping from 1.4 Gy s−1 to 0.25 Gy s−1 over the first 4 s of retreat time. Additionally, dose measurements are calculated for individual organs and body regions, including a 36.8-Gy dose to the breast tissue, a 3.8-Gy dose to the bladder, and a 31.1-Gy dose to the thyroid, as well as the changes in dose rates for the individual organs over the course of the accident sequence. Comparison of results obtained using CHAD in an animated dosimetry simulation with reported information on dose and the medical outcome of the case shows that the consideration of posture and movement in dosimetry simulation allows for more detailed and precise analysis of dosimetry information, consideration of the evolution of the dose profile over time in the course of a given scenario, and a better understanding of the physiological impacts of radiation exposure for a given set of circumstances.

TU‐G‐103‐02: Clinical Evaluation of VirtualDose — a Software for Tracking and Reporting CTDI, DLP, Organ and Effective Dose for Adult and Pediatric Patient

PURPOSE To update the development and clinical testing of a new Software as a Service (SaaS) - VirtualDose for tracking and reporting CT doses. METHODS Incorporating SaaS technology and the comprehensive original dose data derived from Monte Carlo simulations on a family of adult and pediatric computational phantoms, covering 50th-percentile adults and children at different ages, pregnant females at three gestational stages, and a set of overweight and obese phantoms, VirtualDose is being designed as a Web based CT dose reporting platform. For the client-and server-side scripting, JavaScript, Hypertext Markup Language, Cascading Style Sheets, and C# were used. A JSON (JavaScript Object Notation) is used as a request-response interaction pattern to connect both the client-and server-side. Organ doses and effective doses are computed using ICRP Publication 60 and 103. Patient-specific dosimetry capabilities are included by integrating a DICOM reader function module which could automatically extract dose, patient, and CT scanner (e.g., CTDI, DLP, kVp, mAs, weight, age, gender, etc.) information. RESULTS VirtualDose has been developed as a CT dose reporting SaaS by offering a web-based dynamic user-friendly interface. Based on the user-specified scanning parameters, VirtualDose rapidly report the organ dose data from the remote server-side database and interactively tabulate and plot the results of interest within a web browser. Clinical testing found the dose up to 24% different as compared to those derived from the stylized MIRD-type phantoms. The morbidly obese phantom received up to 60% smaller CT dose than that of the normal weight phantomConclusion: VirtualDose is now available in the following website: http://www.virtualphantoms.com and being tested at more than 20 medical centers nationwide. Using a large library of adult and pediatric phantoms, it provides more accurate dose data and is expected to improve both the accuracy and usability in CT dose reporting in the future.

SU‐E‐T‐493: Accelerated Monte Carlo Methods for Photon Dosimetry Using a Dual‐GPU System and CUDA

PURPOSE To develop a Graphics Processing Unit (GPU) based Monte Carlo (MC) code that accelerates dose calculations on a dual-GPU system. METHODS We simulated a clinical case of prostate cancer treatment. A voxelized abdomen phantom derived from 120 CT slices was used containing 218×126×60 voxels, and a GE LightSpeed 16-MDCT scanner was modeled. A CPU version of the MC code was first developed in C++ and tested on Intel Xeon X5660 2.8GHz CPU, then it was translated into GPU version using CUDA C 4.1 and run on a dual Tesla m2 090 GPU system. The code was featured with automatic assignment of simulation task to multiple GPUs, as well as accurate calculation of energy- and material- dependent cross-sections. RESULTS Double-precision floating point format was used for accuracy. Doses to the rectum, prostate, bladder and femoral heads were calculated. When running on a single GPU, the MC GPU code was found to be ×19 times faster than the CPU code and ×42 times faster than MCNPX. These speedup factors were doubled on the dual-GPU system. The dose Result was benchmarked against MCNPX and a maximum difference of 1% was observed when the relative error is kept below 0.1%. CONCLUSIONS A GPU-based MC code was developed for dose calculations using detailed patient and CT scanner models. Efficiency and accuracy were both guaranteed in this code. Scalability of the code was confirmed on the dual-GPU system.

Training software using virtual-reality technology and pre-calculated effective dose data.

This paper describes the development of a software package, called VR Dose Simulator, which aims to provide interactive radiation safety and ALARA training to radiation workers using virtual-reality (VR) simulations. Combined with a pre-calculated effective dose equivalent (EDE) database, a virtual radiation environment was constructed in VR authoring software, EON Studio, using 3-D models of a real nuclear power plant building. Models of avatars representing two workers were adopted with arms and legs of the avatar being controlled in the software to simulate walking and other postures. Collision detection algorithms were developed for various parts of the 3-D power plant building and avatars to confine the avatars to certain regions of the virtual environment. Ten different camera viewpoints were assigned to conveniently cover the entire virtual scenery in different viewing angles. A user can control the avatar to carry out radiological engineering tasks using two modes of avatar navigation. A user can also specify two types of radiation source: 137Cs and 60Co. The location of the avatar inside the virtual environment during the course of the avatar’s movement is linked to the EDE database. The accumulative dose is calculated and displayed on the screen in real-time. Based on the final accumulated dose and the completion status of all virtual tasks, a score is given to evaluate the performance of the user. The paper concludes that VR-based simulation technologies are interactive and engaging, thus potentially useful in improving the quality of radiation safety training. The paper also summarizes several challenges: more streamlined data conversion, realistic avatar movement and posture, more intuitive implementation of the data communication between EON Studio and VB.NET, and more versatile utilization of EDE data such as a source near the body, etc., all of which needs to be addressed in future efforts to develop this type of software.