X Xu

Predictive modeling of lung motion over the entire respiratory cycle using measured pressure-volume data, 4DCT images, and finite-element analysis.

PURPOSE Predicting complex patterns of respiration can benefit the management of the respiratory motion for radiation therapy of lung cancer. The purpose of the present work was to develop a patient-specific, physiologically relevant respiratory motion model which is capable of predicting lung tumor motion over a complete normal breathing cycle. METHODS Currently employed techniques for generating the lung geometry from four-dimensional computed tomography data tend to lose details of mesh topology due to excessive surface smoothening. Some of the existing models apply displacement boundary conditions instead of the intrapleural pressure as the actual motive force for respiration, while others ignore the nonlinearity of lung tissues or the mechanics of pleural sliding. An intermediate nonuniform rational basis spline surface representation is used to avoid multiple geometric smoothing procedures used in the computational mesh preparation. Measured chest pressure-volume relationships are used to simulate pressure loading on the surface of the model for a given lung volume, as in actual breathing. A hyperelastic model, developed from experimental observations, has been used to model the lung tissue material. Pleural sliding on the inside of the ribcage has also been considered. RESULTS The finite-element model has been validated using landmarks from four patient CT data sets over 34 breathing phases. The average differences of end-inspiration in position between the landmarks and those predicted by the model are observed to be 0.450 +/- 0.330 cm for Patient P1, 0.387 +/- 0.169 cm for Patient P2, 0.319 +/- 0.186 cm for Patient P3, and 0.204 +/- 0.102 cm for Patient P4 in the magnitude of error vector, respectively. The average errors of prediction at landmarks over multiple breathing phases in superior-inferior direction are less than 3 mm. CONCLUSIONS The prediction capability of pressure-volume curve driven nonlinear finite-element model is consistent over the entire breathing cycle. The biomechanical parameters in the model are physiologically measurable, so that the results can be extended to other patients and additional neighboring organs affected by respiratory motion.

Modeling Respiratory Motion for Cancer Radiation Therapy Based on Patient-Specific 4DCT Data

Prediction of respiratory motion has the potential to substantially improve cancer radiation therapy. A nonlinear finite element (FE) model of respiratory motion during full breathing cycle has been developed based on patient specific pressure-volume relationship and 4D Computed Tomography (CT) data. For geometric modeling of lungs and ribcage we have constructed intermediate CAD surface which avoids multiple geometric smoothing procedures. For physiologically relevant respiratory motion modeling we have used pressure-volume (PV) relationship to apply pressure loading on the surface of the model. A hyperelastic soft tissue model, developed from experimental observations, has been used. Additionally, pleural sliding has been considered which results in accurate deformations in the superior-inferior (SI) direction. The finite element model has been validated using 51 landmarks from the CT data. The average differences in position is seen to be 0.07 cm (SD = 0.20 cm), 0.07 cm (0.15 cm), and 0.22 cm (0.18 cm) in the left-right, anterior-posterior, and superior-inferior directions, respectively.

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)

SU‐FF‐T‐333: Monte Carlo Simulations Using Whole‐Body Pediatric and Adult Phantoms as Virtual Patients to Assess Secondary Organ Doses in Proton Radiation Therapy

Introduction: Early cancer detection combined with new treatment technologies has resulted in higher numbers of long‐term cancer survivors. The risk of radiation‐induced secondary cancers to tissues away from the PTV is a growing concern in particular for pediatric patients. The focus of this project is to use whole‐body pediatric phantoms in Monte Carlodose calculations in order to determine the effective dose from secondary radiation in patients undergoing protontreatment.Methods: Age and gender specific pediatric phantoms have been implemented into the Geant4 Monte Carlo package for organdose calculations. A proton therapytreatment plan for a pediatric head and neck tumor case was chosen to address the significance of age dependent phantoms for radiation protection calculations. To mimic radiation therapytreatment, the setup of the phantom position was based on field parameters (based on a full treatment head model), including gantry angle, couch angle, and iso‐center position. We distinguish between secondary radiation from the treatment head and secondary radiation generated within the patient. Results: Results using an adult phantom as well as phantoms of a 4‐year old female and an 11‐year old male were analyzed. Organdoses and radiation and tissue weighting factors were used to calculate the effective dose. For protontreatments with double‐scattering system, range modulator and aperture, a significant number of secondary neutrons are generated in the treatment head. More important, differences between phantoms (age dependent) were found with respect to dose to specific organs and relative importance of neutrons generated in the patient versus neutrons from the treatment head. Conclusion: We present results of doses to various anatomic sites in the human body for whole‐body phantoms. The magnitude of secondary dose in organs/tissues depends on the distance from the PTV. For the first time, the significance of age‐dependent phantoms for secondary dose calculations was studied.

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.

TU-D-209-07: Monte Carlo Assessment of Dose to the Lens of the Eye of Radiologist Using Realistic Phantoms and Eyeglass Models

PURPOSE To study how eyeglass design features and postures of the interventional radiologist affect the radiation dose to the lens of the eye. METHODS A mesh-based deformable phantom, consisting of an ultra-fine eye model, was used to simulate postures of a radiologist in fluoroscopically guided interventional procedure (facing the patient, 45 degree to the left, and 45 degree to the right). Various eyewear design features were studied, including the shape, lead-equivalent thickness, and separation from the face. The MCNPX Monte Carlo code was used to simulate the X-ray source used for the transcatheter arterial chemoembolization procedure (The X-ray tube is located 35 cm from the ground, emitting X-rays toward to the ceiling; Field size is 40cm X 40cm; X-ray tube voltage is 90 kVp). Experiments were also performed using dosimeter placed on a physical phantom behind eyeglasses. RESULTS Without protective eyewear, the radiologists eye lens can receive an annual dose equivalent of about 80 mSv. When wearing a pair of lead eyeglasses with lead-equivalent of 0.5-mm Pb, the annual dose equivalent of the eye lens is reduced to 31.47 mSv, but both exceed the new ICRP limit of 20 mSv. A face shield with a lead-equivalent of 0.125-mm Pb in the shape of a semi-cylinder (13cm in radius and 20-cm in height) would further reduce the exposure to the lens of the eye. Examination of postures and eyeglass features reveal surprising information, including that the glass-to-eye separation also plays an important role in the dose to the eye lens from scattered X-ray from underneath and the side. Results are in general agreement with measurements. CONCLUSION There is an urgent need to further understand the relationship between the radiation environment and the radiologists eyewear and posture in order to provide necessary protection to the interventional radiologists under newly reduced dose limits.

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.