Impact of image resolution on quantification of mineral properties and simulated mineral reaction rates
Establishing an Early CO2 Storage Complex in Kemper County, Mississippi (ECO2S): Image Resolution Impact on Mineral Data
Qin, Fanqi↗
SEARCH · Engineering Papers
Results for “image simulation”
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The effects of mapping CT images to Monte Carlo materials on GEANT4 proton simulation accuracy
Purpose: Monte Carlo simulations of radiation therapy require conversion from Hounsfield units (HU) in CT images to an exact tissue composition and density. The number of discrete densities (or density bins) used in this mapping affects the simulation accuracy, execution time, and memory usage in GEANT4 and other Monte Carlo code. The relationship between the number of density bins and CT noise was examined in general for all simulations that use HU conversion to density. Additionally, the effect of this on simulation accuracy was examined for proton radiation. Methods: Relative uncertainty from CT noise was compared with uncertainty from density binning to determine an upper limit on the number of density bins required in the presence of CT noise. Error propagation analysis was also performed on continuously slowing down approximation range calculations to determine the proton range uncertainty caused by density binning. These results were verified with Monte Carlo simulations. Results: In the presence of even modest CT noise (5 HU or 0.5%) 450 density bins were found to only cause a 5% increase in the density uncertainty (i.e., 95% of density uncertainty from CT noise, 5% from binning). Larger numbers of density bins are not required as CT noise will prevent increased density accuracy; this applies across all types of Monte Carlo simulations. Examining uncertainty in proton range, only 127 density bins are required for a proton range error of <0.1 mm in most tissue and <0.5 mm in low density tissue (e.g., lung). Conclusions: By considering CT noise and actual range uncertainty, the number of required density bins can be restricted to a very modest 127 depending on the application. Reducing the number of density bins provides large memory and execution time savings in GEANT4 and other Monte Carlo packages.
60 APPLIED LIFE SCIENCES↗
Optimizing cone beam CT scatter estimation in egs-cbct for a clinical and virtual chest phantom
Purpose: Cone beam computed tomography (CBCT) image quality suffers from contamination from scattered photons in the projection images. Monte Carlo simulations are a powerful tool to investigate the properties of scattered photons.egs-cbct, a recent EGSnrc user code, provides the ability of performing fast scatter calculations in CBCT projection images. This paper investigates how optimization of user inputs can provide the most efficient scatter calculations. Methods: Two simulation geometries with two different x-ray sources were simulated, while the user input parameters for the efficiency improving techniques (EITs) implemented inegs-cbct were varied. Simulation efficiencies were compared to analog simulations performed without using any EITs. Resulting scatter distributions were confirmed unbiased against the analog simulations. Results: The optimal EIT parameter selection depends on the simulation geometry and x-ray source. Forced detection improved the scatter calculation efficiency by 80%. Delta transport improved calculation efficiency by a further 34%, while particle splitting combined with Russian roulette improved the efficiency by a factor of 45 or more. Combining these variance reduction techniques with a built-in denoising algorithm, efficiency improvements of 4 orders of magnitude were achieved. Conclusions: Using the built-in EITs inegs-cbct can improve scatter calculation efficiencies by more than 4 orders of magnitude. To achieve this, the user must optimize the input parameters to the specific simulation geometry. Realizing the full potential of the denoising algorithm requires keeping the statistical uncertainty below a threshold value above which the efficiency drops exponentially.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
WE-DE-BRA-05: Monte Carlo Simulation of a Novel Multi-Layer MV Imager
Purpose: To develop and validate a Monte Carlo (MC) model of a novel multi-layer imager (MLI) for megavolt (MV) energy beams. The MC model will enable performance optimization of the MLI design for clinical applications including patient setup verification, tumor tracking and MVCBCT. Methods: The MLI is composed of four layers of converter, scintillator and light detector, each layer similar to the current clinical AS1200 detector (Varian Medical Systems, Inc). The MLI model was constructed using the Geant4 Application for Tomographic Emission (GATE v7.1) and includes interactions for x-ray photons, charged particles and optical photons. Computational experiments were performed to assess Modulation Transfer Function (MTF), Detective Quantum Efficiency (DQE) and Noise Power Spectrum normalized by photon fluence and average detector signal (qNNPS). Results were compared with experimental measurements. The current work incorporates, in one model, the complete chain of events occurring in the imager; i.e. starting from x-ray interaction to charged particle transport and energy deposition to subsequent generation, interactions and detection of optical photons. Results: There is good agreement between measured and simulated MTF, qNNPS and DQE values. Normalized root mean squared error (NRMSE) between measured and simulated values over all four layers was 2.18%, 2.43% and 6.05% for MTF, qNNPS and DQE respectively. The relative difference between simulated and measured values for qNNPS(0) was 1.68% and 1.57% for DQE(0). Current results were obtained using a 6MV Varian Truebeam™ spectrum. Conclusion: A comprehensive Monte Carlo model of the MLI prototype was developed to allow optimization of detector components. The model was assessed in terms of imaging performance using standard metrics (i.e. MTF, qNNPS, DQE). Good agreement was found between simulated and measured values. The model will be used to assess alternative detector constructions to facilitate advanced clinical imaging applications including MV-CBCT and tumor tracking. The project was supported, partially, by a grant from Varian Medical Systems, Inc., and Award No. R01CA188446-01 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.
60 APPLIED LIFE SCIENCES↗
SU-F-P-03: Management of Time to Treatment Inititation: Case for An Electronic Whiteboard
Purpose: To determine if data mining of an electronic whiteboard improves the management of the Time to Treatment Initiation (TTI) in radiation oncology. Methods: An electronic whiteboard designed to help in managing the planning workflow and improves communication regarding patient planning progress was used to record the dates at which each phase of the planning process began or completed. These are CT Sim date, Plan Start, Physician Review, Physicist Review, Approval for Treatment Delivery, Setup or Verification of Simulation. Results: During clinical implementation, the electronic whiteboard was able to fulfill its primary objective of providing a transparent account of the planning progress of each patient. Peer pressure also meant that individual tasks, such as contouring, were easily brought to the attention of the responsible party and prioritized accordingly. Data mining to analyze the electronic whiteboard per patient (figure 1), per diagnosis (figure 2), per treatment modality (figure 3), per physician (figure 4), per planner (figure 5), etc., added another sophisticated tool in the management of Time to Treatment Initiation without compromising quality of the plans being generated. A longer than necessary time between CT Sim and Plan Start can be discussed among the members of the treatment team as an indication of inadequate/outdated CT Simulator, Contouring Tools, Image Fusion Tools, Other Imaging Studies (MRI, PET/CT) performed, etc. The same for the Plan Start to Physician Review where an extended time than expected may be due unrealistic planning goals, limited planning system features, etc. Conclusion: An Electronic Whiteboard in radiation oncology is not only helping with organizing planning workflow, it is also a potent tool that can be used to reduce the Time to Treatment Initiation by providing the clinic with hard data about the duration of each phase treatment planning as a function of different variable affecting the planning process. The work is supported by the Global Medical Physics Institute.
60 APPLIED LIFE SCIENCES↗
Description of a computer simulation of an orbital SAR system
A computer simulation of an orbital SAR system has been developed in order to predict SAR performance for a wide variety of system and environmental parameters. The objectives of the simulation are: (1) to assess the effect of various antenna patterns on the SAR image, (2) to assess the effect of various SAR parameters on the system's ability to detect small differences in the radar cross section of adjacent homogeneous areas, and (3) to assess the effect of mapping geometry on SAR image quality. The simulation is implemented as seven programs: (1) simulation control, (2) terrain model, (3) slant range computation, (4) production of IPQ video, (5) motion compensation, (6) Doppler processor, and (7) postprocessor and display.
Crow, G. L.↗
Mathematical modeling and SAR simulation multifunction SAR technology efforts
The orbital SAR (synthetic aperture radar) simulation data was used in several simulation efforts directed toward advanced SAR development. Efforts toward simulating an operational radar, simulation of antenna polarization effects, and simulation of SAR images at serveral different wavelengths are discussed. Avenues for improvements in the orbital SAR simulation and its application to the development of advanced digital radar data processing schemes are indicated.
Griffin, C. R.↗
Simulation studies of the GOES-I Image Navigation and Registration (INR) system
The GOES-I Image Navigation and Registration (INR) system will fly on the next generation of NOAA geostationary meteorological satellites. This system uses observations of stars and earth landmarks made by the Imager and Sounder Instruments themselves to determine the orbit, attitude, and misalignment state of the spacecraft and instruments. An extensive program of simulation and analysis has been conducted to assess the expected performance of the INR system. This paper discusses these activities and presents some computer simulation results showing expected system performance under a variety of conditions including station-keeping.
Carr, James L.↗
Theory for synthetic aperture radar imaging of the ocean surface - With application to the Tower Ocean Wave and Radar Dependence experiment on focus, resolution, and wave height spectra
A one-dimensional model for simulating azimuthal SAR imaging of the ocean surface is developed which can admit both the 'distributed surface' and 'velocity bunching' approaches. Computer simulations demonstrate that the time-dependent modulation patterns due to the radar cross section variation and the velocity bunching effects provide optimum focusing around half the phase velocity of the long wave. The results indicate that in the Tower Ocean Wave and Radar Dependence experiment, SAR imaging at L band is approximately linear.
Kasilingam, Dayalan P.↗
Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography
Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.
Xu, Feng↗
A dissipative particle dynamics method for arbitrarily complex geometries
Not Available
Li, Zhen (ORCID:0000000209366928)↗
MO-C-BRF-01: Pediatric Treatment Planning I: Overview of Planning Strategies
Most Medical Physicists working in radiotherapy departments see few pediatric patients. This is because, fortunately, children get cancer at a rate nearly 100 times lower than adults. Children have not smoked, abused alcohol, or been exposed to environmental carcinogens for decades, and of course, have not fallen victim to the aging process. Children get very different cancers than adults. Breast or prostate cancers, typical in adults, are rarely seen in children but instead a variety of tumors occur in children that are rarely seen in adults; examples are germinomas, ependymomas and primitive neuroectodermal tumors, which require treatment of the child's brain or neuroblastoma, requiring treatment in the abdomen. The treatment of children with cancer using radiation therapy is one of the most challenging planning and delivery problems facing the physicist. This is because bones, brain, breast tissue, and other organs are more sensitive to radiation in children than in adults. Because most therapy departments treat mostly adults, when the rare 8 year-old patient comes to the department for treatment, the physicist may not understand the clinical issues of his disease which drive the planning and delivery decisions. Additionally, children are more prone than adults to developing secondary cancers after radiation. This fact has important implications for the choice of delivery techniques, especially when considering IMRT. For bilateral retinoblastoma for example, an irradiated child has a 50% chance of developing a second cancer by age 50. In the first presentation, an overview of childhood cancers and their corresponding treatment techniques will be given. These can be some of the most complex treatments that are delivered in the radiation therapy department. These cancers include leukemia treated with total body irradiation, medulloblastoma, treated with craniospinal irradiation plus a conformal boost to the posterior fossa, neuroblastoma, requiring focal abdominal irradiation to avoid kidney, liver, and vertebral body damage, retinoblastoma, requiring treatment to an eye while minimizing dose to surrounding tissues, and a variety of other tumors which occur anywhere in the body. Case studies will be presented showing the treatment technique and resulting dosimetry, highlighting the objectives for tumor coverage and organ-at-risk sparing. Practical issues that have to be faced when treating children will also be discussed such as daily sedation and immobilization. In the second presentation, specific focus will be on radiation therapy simulation, treatment planning guidelines, image guidance for delivery, and proton therapy for children. We will discuss uniqueness of pediatric simulation with different imaging modalities (CT, MRI, and PET). Some related issues are sedation for younger patients, radiation exposure reduction for CT, distortion and artifacts on pediatric MRI, and measuring pediatric organ motion. We will discuss the tradeoff of tumor coverage and normal tissue sparing in treatment planning using example organ data. Image guidance approaches for pediatric radiation therapy and methods for dose reduction will be reviewed. Finally, we will describe technical advances and trends in proton therapy for children. Advantages, caveats, and opportunities will be presented. Learning Objectives: Improve understanding about childhood cancer and treatment with radiation Understand treatment planning and delivery issues specific to children Become aware of specific treatment methods for the most challenging pediatric cancers Know the current status of state-of-the-art treatment techniques for pediatric radiation therapy.
60 APPLIED LIFE SCIENCES↗
TU-F-CAMPUS-T-05: Replacement Computational Phantoms to Estimate Dose in Out-Of-Field Organs and Tissues
Purpose: To estimate the absorbed dose in organs and tissues at risk for radiogenic cancer for children receiving photon radiotherapy for localized brain tumors (LBTs) by supplementing their missing body anatomies with those of replacement computational phantoms. Applied beyond the extent of the RT Images collected by computed tomography simulation, these phantoms included RT Image and RT Structure Set objects that encompassed sufficient extents and contours for dosimetric calculations. Method: Nine children, aged 2 to 14 years, who received three-dimensional conformal radiotherapy for low-grade LBTs, were randomly selected for this study under Institutional-Review-Board protocol. Because the extents of their RT Images were cranial only, they were matched for size and sex with patients from a previous study with larger extents and for whom contours of organs at risk for radiogenic cancer had already been delineated. Rigid fusion was performed between the patients’ data and those of the replacement computational phantoms using commercial software. In-field dose was calculated with a clinically-commissioned treatment planning system, and out-of-field dose was estimated with an analytical model. Results: Averaged over all nine children and normalized for a therapeutic dose of 54 Gy prescribed to the PTV, where the PTV is the GTV, the highest mean organ doses were 3.27, 2.41, 1.07, 1.02, 0.24, and 0.24 Gy in the non-tumor remainder, red bone marrow, thyroid, skin, breasts, and lungs, respectively. The mean organ doses ranged by a factor of 3 between the smallest and largest children. Conclusion: For children receiving photon radiotherapy for LBTs, we found their doses in organs at risk for second cancer to be non-negligible, especially in the non-tumor remainder, red bone marrow, thyroid, skin, breasts, and lungs. This study demonstrated the feasibility for patient dosimetry studies to augment missing patient anatomy by applying size- and sex-matched replacement computational phantoms with pre-contoured organs. Funding is in part by the Fogarty International Center award K01TW008409, and the Portland Chapter of the Achievement Rewards for College Scientists. The content is solely the responsibility of the authors, and does not necessarily represent the official views of the sponsors. The authors declare no conflict of interest.
60 APPLIED LIFE SCIENCES↗
WE-EF-303-06: Feasibility of PET Image-Based On-Line Proton Beam-Range Verification with Simulated Uniform Phantom and Human Brain Studies
Purpose: To study the feasibility of clinical on-line proton beam range verification with PET imaging Methods: We simulated a 179.2-MeV proton beam with 5-mm diameter irradiating a PMMA phantom of human brain size, which was then imaged by a brain PET with 300*300*100-mm{sup 3} FOV and different system sensitivities and spatial resolutions. We calculated the mean and standard deviation of positron activity range (AR) from reconstructed PET images, with respect to different data acquisition times (from 5 sec to 300 sec with 5-sec step). We also developed a technique, “Smoothed Maximum Value (SMV)”, to improve AR measurement under a given dose. Furthermore, we simulated a human brain irradiated by a 110-MeV proton beam of 50-mm diameter with 0.3-Gy dose at Bragg peak and imaged by the above PET system with 40% system sensitivity at the center of FOV and 1.7-mm spatial resolution. Results: MC Simulations on the PMMA phantom showed that, regardless of PET system sensitivities and spatial resolutions, the accuracy and precision of AR were proportional to the reciprocal of the square root of image count if image smoothing was not applied. With image smoothing or SMV method, the accuracy and precision could be substantially improved. For a cylindrical PMMA phantom (200 mm diameter and 290 mm long), the accuracy and precision of AR measurement could reach 1.0 and 1.7 mm, with 100-sec data acquired by the brain PET. The study with a human brain showed it was feasible to achieve sub-millimeter accuracy and precision of AR measurement with acquisition time within 60 sec. Conclusion: This study established the relationship between count statistics and the accuracy and precision of activity-range verification. It showed the feasibility of clinical on-line BR verification with high-performance PET systems and improved AR measurement techniques. Cancer Prevention and Research Institute of Texas grant RP120326, NIH grant R21CA187717, The Cancer Center Support (Core) Grant CA016672 to MD Anderson Cancer Center.
60 APPLIED LIFE SCIENCES↗
The effect of averaging adjacent planes for artifact reduction in matrix inversion tomosynthesis
Purpose: Matrix inversion tomosynthesis (MITS) uses linear systems theory and knowledge of the imaging geometry to remove tomographic blur that is present in conventional backprojection tomosynthesis reconstructions, leaving in-plane detail rendered clearly. The use of partial-pixel interpolation during the backprojection process introduces imprecision in the MITS modeling of tomographic blur, and creates low-contrast artifacts in some MITS planes. This paper examines the use of MITS slabs, created by averaging several adjacent MITS planes, as a method for suppressing partial-pixel artifacts. Methods: Human chest tomosynthesis projection data, acquired as part of an IRB-approved pilot study, were used to generate MITS planes, three-plane MITS slabs (MITSa3), five-plane MITS slabs (MITSa5), and seven-plane MITS slabs (MITSa7). These were qualitatively examined for partial-pixel artifacts and the visibility of normal and abnormal anatomy. Additionally, small (5 mm) subtle pulmonary nodules were simulated and digitally superimposed upon human chest tomosynthesis projection images, and their visibility was qualitatively assessed in the different reconstruction techniques. Simulated images of a thin wire were used to generate modulation transfer function (MTF) and slice-sensitivity profile curves for the different MITS and MITS slab techniques, and these were examined for indications of partial-pixel artifacts and frequency response uniformity. Finally, mean-subtracted, exposure-normalized noise power spectra (ENNPS) estimates were computed and compared for MITS and MITS slab reconstructions, generated from 10 sets of tomosynthesis projection data of an acrylic slab. The simulated in-plane MTF response of each technique was also combined with the square root of the ENNPS estimate to yield stochastic signal-to-noise ratio (SNR) information about the different reconstruction techniques. Results: For scan angles of 20 Degree-Sign and 5 mm plane separation, seven MITS planes must be averaged to sufficiently remove partial-pixel artifacts. MITSa7 does appear to subtly reduce the contrast of high-frequency 'edge' information, but the removal of partial-pixel artifacts makes the appearance of low-contrast, fine-detail anatomy even more conspicuous in MITSa7 slices. MITSa7 also appears to render simulated subtle 5 mm pulmonary nodules with greater visibility than MITS alone, in both the open lung and regions overlying the mediastinum. Finally, the MITSa7 technique reduces stochastic image variance, though the in-plane stochastic SNR (for very thin objects which do not span multiple MITS planes) is only improved at spatial frequencies between 0.05 and 0.20 cycles/mm. Conclusions: The MITSa7 method is an improvement over traditional single-plane MITS for thoracic imaging and the pulmonary nodule detection task, and thus the authors plan to use the MITSa7 approach for all future MITS research at the authors' institution.
60 APPLIED LIFE SCIENCES↗
MO-F-CAMPUS-J-05: Verification for Prompt Gamma Ray Imaging During Proton Boron Fusion Therapy
Purpose: The purpose of this study is to verify the acquisition of the three dimensional single photon emission computed tomography (SPECT) image using prompt gamma ray originated from proton boron fusion therapy (PBFT). Methods: The real-time imaging system during the PBFT was simulated to acquire the tomographic image of the prompt gamma ray from treated tumor by the proton boron reaction, using Monte Carlo simulation (MCNPX). We acquired percentage depth dose (PDD) of the proton beam in the water phantom including the boron uptake region (BUR), the energy spectra of the prompt gamma ray and tomographic image which can show treated tumor regions. The prompt gamma ray image was reconstructed using maximum likelihood estimation maximization (MLEM) reconstruction algorithm with 64 projections. In addition, in order to evaluate the reconstructed image, the image profiles between BURs were extracted from the image. Results: In the PDD results, the Bragg-peak was amplified definitely when the proton’s maximum dose level was located at the BUR. This amplification is based on the generation of alpha particles. In addition, the prompt gamma ray peak of 719 keV was observed from the energy spectrum. Through the previous process, the tomographic image of prompt gamma ray from the BUR was reconstructed. The line profile was extracted from image including BURs, and it shows high signal-to-noise ratio. Conclusion: We confirmed that the real-time prompt gamma ray image during the PBFT was successfully deducted, and results of quantitative image analysis show good agreement with the original pattern of the BUR. This study first verified the imaging capability of the PBFT-SPECT system. In conclusion, the PBFT-SPECT system can realize the treated tumor monitoring during the PBFT.
60 APPLIED LIFE SCIENCES↗
Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies
Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dPETSTEP can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.
60 APPLIED LIFE SCIENCES↗
TU-FG-BRB-08: Challenges, Limitations and Future Outlook Towards Clinical Translation of Proton Acoustic Range Verification
Purpose: To report our investigations of proton acoustic imaging, including computer simulations and preliminary experimental studies at clinical facilities. The ultimate achievable accuracy, sensitivity and clinical translation challenges are discussed. Methods: The acoustic pulse due to pressure rise was estimated using finite element model. Since the ionoacoustic pulse is highly dependent on the proton pulse width and energy, multiple pulse widths were studied. Based on the received signal spectrum at piezoelectric ultrasound transducer with consideration of random thermal noise, maximum spatial resolution of the proton-acoustic imaging modality was calculated. The simulation studies defined the design specifications of the system to detect proton acoustic signal from Hitachi and Mevion clinical machines. A 500 KHz hydrophone with 100 dB amplification was set up in a water tank placed in front of the proton nozzle A 40 MHz data acquisition was synchronized by a trigger signal provided by the machine. Results: Given 30–800 mGy dose per pulse at the Bragg peak, the minimum number of protons detectable by the proton acoustic technique was on the order of 10×10^6 per pulse. The broader pulse widths produce signal with lower acoustic frequencies, with 10 µs pulses producing signals with frequency less than 100 kHz. As the proton beam pulse width increases, a higher dose rate is required to measure the acoustic signal. Conclusion: We have established the minimal detection limit for protonacoustic range validation for a variety of pulse parameters. Our study indicated practical proton-acoustic range verification can be feasible with a pulse shorter than 10 µs, 5×10^6 protons/pulse, 50 nA beam current and a highly sensitive ultrasonic transducer. The translational challenges into current clinical machines include proper magnetic shielding of the measurement equipment, providing a clean trigger signal from the proton machine, providing a shorter proton beam pulse and higher dose per pulse.
60 APPLIED LIFE SCIENCES↗