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DOE OSTI2015

Organic liquid scintillation detectors for on-the-fly neutron/gamma alarming and radionuclide identification in a pedestrian radiation portal monitor

Here, we present new experimental results from a radiation portal monitor based on the use of organic liquid scintillators. The system was tested as part of a 3 He-free radiation portal monitor testing campaign at the European Commission’s Joint Research Centre in Ispra, Italy, in February 2014. The radiation portal monitor was subjected to a wide range of test conditions described in ANSI N42.35, including a variety of gamma-ray sources and a 20,000 n/s 252 Cf source. A false alarm test tested whether radiation portal monitors ever alarmed in the presence of only natural background. The University of Michigan Detection for Nuclear Nonproliferation Group’s system triggered zero false alarms in 2739 trials. It consistently alarmed on a variety of gamma-ray sources travelling at 1.2 m/s at a 70 cm source to detector distance. The neutron source was detected at speeds up to 3 m/s and in configurations with up to 8 cm of high density polyethylene shielding. The success of on-the-fly radionuclide identification varied with the gamma-ray source measured as well as with which of two radionuclide identification methods was used. Both methods used a least squares comparison between the measured pulse height distributions to library spectra to pick the best match. The methods varied in how the pulse height distributions were modified prior to the least squares comparison. Correct identification rates were as high as 100% for highly enriched uranium, but as low as 50% for 241 Am. Lastly, both radionuclide identification algorithms produced mixed results, but the concept of using liquid scintillation detectors for gamma-ray and neutron alarming in radiation portal monitor was validated.

3He replacement technology↗

DOE OSTI2026

A call to standardize metrics for monitoring baleen whales near marine construction activities

Effective monitoring is necessary to protect marine mammal species during the construction of offshore infrastructure. The tools for detecting or monitoring marine mammals span traditional (e.g., visual observers, optical cameras), to newer (e.g., passive acoustic monitoring, infrared cameras, tags), and emerging (e.g., satellite imagery, environmental DNA, dimethyl sulfide concentration) technologies. Some are better suited for use during offshore development; however, peer-reviewed literature does not typically evaluate and report on the performance of these various technologies. We define a minimum set of metrics related to efficacy (i.e., confusion matrix, precision and recall, probability of missed mitigation), detection range (i.e., maximum and reliable detection range, spatial resolution), and data delivery (i.e., detection latency, system reliability, temporal resolution) that we recommend are needed to assess the utility of monitoring technologies for this purpose. Following a literature review of relevant studies, we highlight which publications reported these metrics and used multiple technologies to compare relative performance. We also emphasize the benefits of multi-modal approaches and recommend performance assessments through modeling or large-scale collaborative field testing. These metrics will standardize data collection, reporting, and analysis; promote consistent and comparable results; and foster collaboration among developers, regulatory agencies, and scientists. This may lead to the co-development of technology that achieves multiple goals, has greater application, and can answer research questions while collecting data to fulfill permitting requirements. These metrics may also inform decisions on what systems regulatory agencies might consider using and reduce monitoring costs, which is critical to support the marine sector's rapid growth alongside marine mammal conservation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Heat pulse testing at monitoring wells to estimate subsurface fluid velocities in geological CO 2 storage

Monitoring the injected CO 2 during geological CO 2 storage (GCS) is essential to assure containment and identify CO 2 leakage. Here in this work, a new approach is introduced to estimate the evolution of the downhole fluid velocity at a monitoring well and identify CO 2 arrival time using in-well heat pulse/tracer test. The proposed technique involves using a downhole heater to generate a series of heat pulses and measuring their corresponding temperature response. The surface temperature of the downhole heater is controlled by the supplied electrical power and the heat loss by convection to the surroundings. Convective heat transfer is well described using Newton's law of cooling in which the temperature difference between the heater and the surrounding fluids drives the heat transfer, for which the convection heat transfer coefficient (h) controls the magnitude of heat loss. Among various factors that control h, it depends on the type of the flowing fluid and its velocity. Through analyzing the measured temperature at different heat pulses, the changes in h - due to mobilization of the in-situ brine or CO 2 arrival - can be estimated. Consequently, the velocity of the flowing fluid across the heater can be obtained. Since heat transfer by convection is sensitive to the type of the surrounding fluid, intrusion of CO 2 can be detected from the relatively higher surface temperature obtained at CO 2 arrival. Churchill and Bernstein (1977)'s correlation is adopted to estimate the change of fluid velocity in terms of the change in h. To demonstrate the validity of the proposed technique, the results are applied and validated against those of COMSOL Multiphysics simulation tool for single-phase brine (before CO 2 arrival) and single-phase CO 2 (after CO 2 arrival). The observed temperature heating is sensitive to the flowing fluid velocity and fluid type. The temperature signal observed at CO 2 arrival is large and easily detectable using temperature monitoring tool which provides reliable indication for tracking CO 2 arrival at monitoring wells compared with passive temperature monitoring. The results obtained using the proposed technique agree very well with the numerical results obtained from the simulation tool with a maximum estimation error of 7 percent.

02 PETROLEUM↗

DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Systems engineering approach towards performance monitoring of emergency diesel generator

Systems engineering is an interdisciplinary approach and means to enable the realization of successful systems. In this study, systems engineering approach towards the performance monitoring of Emergency Diesel Generator (EDG) is presented. Performance monitoring is part and parcel of predictive maintenance where the systems and components conditions can be detected before they result into failures. In an effort to identify the proposal for addressing performance monitoring, the EDG boundary has been defined. Based on the Probabilistic Safety Analysis (PSA) results and industry operating experiences, the most critical component is identified. This paper proposed a systems engineering concept development framework towards EDG performance monitoring. The expected output of this study is that the EDG reliability can be improved by the performance monitoring alternatives through the systems engineering concept development effort.

42 ENGINEERING↗

DOE OSTI2014

The status and prospective of environmental radiation monitoring stations in Saudi Arabia

The use of nuclear technology requires an environmental monitoring program to ensure the safety of the environment, and to protect people from the hazards of radioactive materials, and nuclear accidents. Nuclear accidents are unique, for they incur effects that surpass international frontiers, and can even have a long lasting impact on Earth. Such was the case of the Chernobyl accident in the Ukraine on April 6, 1986. For that purpose, international and national efforts come together to observe for any nuclear or radioactive accident. Many states, including Saudi Arabia which oversees the operation of the National Radiation, Environmental and Early Monitoring Stations, The Radiation Monitoring Stations(RMS’s) are currently scattered across 35 cities in the country,. These locations are evaluated based on various technological criteria such as border cities, cities of high population density, wind direction, etc. For new nuclear power plants hovering around, it is strongly recommended to increase the number of radiation monitoring stations to warn against any threat that may arise from a nuclear leak or accident and to improve the performance of the existing RMS’s. SARA (Spectroscopic Monitoring Station for air) should be implemented due to the high sensitivity to artificial radiation, automatic isotope identification, free of maintenance, and fully independent due to solar power supply (incl. battery backup) and wireless communication (GPRS)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Effects-Based Monitoring of Geomagnetically-Induced Current Using a Convolutional Neural Network

Geomagnetically-induced current (GIC) due to space weather can flow in the power grid causing undesirable effects such as transformer overheating, misoperation of protection devices, and potential blackouts. It is therefore important to monitor GIC in the power grid to improve online situational awareness and decision-making of system operators during a geomagnetic disturbance. To avoid the costly installation of GIC monitors at transformers’ neutrals, it is desirable to find correlations between GIC and already-monitored parameters. Hence, this work proposed the use of a convolutional neural network (CNN) to compute GIC amplitudes from learned patterns in the time-series data of transformer even harmonic currents. Using an electromagnetic transient program, GIC injection simulations were performed for a modeled Dominion Energy Virginia (DEV) substation with two 504 MVA, 500/230 kV transformers. Data collected from these offline simulations were used to train the CNN to provide online GIC monitoring. Testing the CNN performance involved using real GIC measurements from published literature and from a physical GIC monitor in the DEV area. Finally, the results showed that the proposed method was able to provide GIC readings with a root mean squared error of 1.56 A/phase (equivalent to an average accuracy of 94%) for these real GIC waveforms.

42 ENGINEERING↗

DOE OSTI2019

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Digitally enhanced services for wind power could reduce Operations and Maintenance (O&M) costs as well as the Levelised Cost Of Energy (LCOE). Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things (IoT) and Big Data Analytics, revolutionizing the future of the energy sector. The heart of wind turbines is a rather complex epicyclic gearbox. Among others, extremely critical gearbox components which are often responsible for machinery stops are the rolling element bearings. The vibration signatures of bearings are rather weak compared to other components, such as gears, and as a result an extended number of signal processing techniques and tools have been proposed during the last decades, focusing towards accurate, early, and on time bearing fault detection with limited false alarms and missed detections. Envelope Analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated usually after filtering around a frequency band excited by impacts due to the bearing faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclic Spectral Correlation and Cyclic Spectral Coherence, based on Cyclostationary Analysis, have been proved as very powerful tools for condition monitoring. The monitoring techniques seem to have reached a mature level in case a machinery operates under steady speed and load. On the other hand, in case the operating conditions change, it is still unclear whether the change of the monitoring indicators is due to the change of the health of the machinery or due to the change of the operating parameters. Recently, the authors have proposed a new tool called IESFOgram, which is based on Cyclic Spectral Coherence and can automatically select the filtering band. Furthermore, the Cyclic Spectral Coherence is integrated along the selected frequency band leading to an Improved Envelope Spectrum. In this paper, the performance of the tool is evaluated and further extended on cases operating under different speeds and different loads. The effectiveness of the methodology is tested and validated on the National Renewable Energy Laboratory (NREL) wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.

17 WIND ENERGY↗

DOE OSTI2012

Monitoring Thermal Fatigue Damage In Nuclear Power Plant Materials Using Acoustic Emission

Proactive aging management of nuclear power plant passive components requires technologies to enable monitoring and accurate quantification of material condition at early stages of degradation (i.e., pre-macrocrack). Acoustic emission (AE) is well-suited to continuous monitoring of component degradation and is proposed as a method to monitor degradation during accelerated thermal fatigue tests. A key consideration is the ability to separate degradation responses from external sources such as water spray induced during thermal fatigue testing. Water spray provides a significant background of acoustic signals, which can overwhelm AE signals caused by degradation. Analysis of AE signal frequency and energy is proposed in this work as a means for separating degradation signals from background sources. Encouraging results were obtained by applying both frequency and energy filters to preliminary data. The analysis of signals filtered using frequency and energy provides signatures exhibiting several characteristics that are consistent with degradation accumulation in materials. Future work is planned to enable verification of the efficacy of AE for thermal fatigue crack initiation detection. While the emphasis has been placed on the use of AE for crack initiation detection during accelerated aging tests, this work also has implications with respect to the use of AE as a primary tool for early degradation monitoring in nuclear power plant materials. The development of NDE tools for characterization of aging in materials can also benefit from the use of a technology such as AE which can continuously monitor and detect crack initiation during accelerated aging tests.

acoustic emission↗

DOE OSTI2012

Automated size-specific CT dose monitoring program: Assessing variability in CT dose

Purpose: The potential health risks associated with low levels of ionizing radiation have created a movement in the radiology community to optimize computed tomography (CT) imaging protocols to use the lowest radiation dose possible without compromising the diagnostic usefulness of the images. Despite efforts to use appropriate and consistent radiation doses, studies suggest that a great deal of variability in radiation dose exists both within and between institutions for CT imaging. In this context, the authors have developed an automated size-specific radiation dose monitoring program for CT and used this program to assess variability in size-adjusted effective dose from CT imaging. Methods: The authors radiation dose monitoring program operates on an independent health insurance portability and accountability act compliant dosimetry server. Digital imaging and communication in medicine routing software is used to isolate dose report screen captures and scout images for all incoming CT studies. Effective dose conversion factors (k-factors) are determined based on the protocol and optical character recognition is used to extract the CT dose index and dose-length product. The patient's thickness is obtained by applying an adaptive thresholding algorithm to the scout images and is used to calculate the size-adjusted effective dose (ED{sub adj}). The radiation dose monitoring program was used to collect data on 6351 CT studies from three scanner models (GE Lightspeed Pro 16, GE Lightspeed VCT, and GE Definition CT750 HD) and two institutions over a one-month period and to analyze the variability in ED{sub adj} between scanner models and across institutions. Results: No significant difference was found between computer measurements of patient thickness and observer measurements (p= 0.17), and the average difference between the two methods was less than 4%. Applying the size correction resulted in ED{sub adj} that differed by up to 44% from effective dose estimates that were not adjusted by patient size. Additionally, considerable differences were noted in ED{sub adj} distributions between scanners, with scanners employing iterative reconstruction exhibiting significantly lower ED{sub adj} (range: 9%-64%). Finally, a significant difference (up to 59%) in ED{sub adj} distributions was observed between institutions, indicating the potential for dose reduction. Conclusions: The authors developed a robust automated size-specific radiation dose monitoring program for CT. Using this program, significant differences in ED{sub adj} were observed between scanner models and across institutions. This new dose monitoring program offers a unique tool for improving quality assurance and standardization both within and across institutions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

MO-G-BRE-01: A Real-Time Virtual Delivery System for Photon Radiotherapy Delivery Monitoring

Purpose: Treatment delivery monitoring is important for radiotherapy, which enables catching dosimetric error at the earliest possible opportunity. This project develops a virtual delivery system to monitor the dose delivery process of photon radiotherapy in real-time using GPU-based Monte Carlo (MC) method. Methods: The simulation process consists of 3 parallel CPU threads. A thread T1 is responsible for communication with a linac, which acquires a set of linac status parameters, e.g. gantry angles, MLC configurations, and beam MUs every 20 ms. Since linac vendors currently do not offer interface to acquire data in real time, we mimic this process by fetching information from a linac dynalog file at the set frequency. Instantaneous beam fluence map (FM) is calculated. A FM buffer is also created in T1 and the instantaneous FM is accumulated to it. This process continues, until a ready signal is received from thread T2 on which an inhouse developed MC dose engine executes on GPU. At that moment, the accumulated FM is transferred to T2 for dose calculations, and the FM buffer in T1 is cleared. Once the calculation finishes, the resulting 3D dose distribution is directed to thread T3, which displays it in three orthogonal planes overlaid on the CT image for treatment monitoring. This process continues to monitor the 3D dose distribution in real-time. Results: An IMRT and a VMAT cases used in our patient-specific QA are studied. Maximum dose differences between our system and treatment planning system are 0.98% and 1.58% for the two cases, respectively. The average time per MC calculation is 0.1sec with <2% relative uncertainty. The update frequency of ∼10Hz is considered as real time. Conclusion: By embedding a GPU-based MC code in a novel data/work flow, it is possible to achieve real-time MC dose calculations to monitor delivery process.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TH-C-17A-09: Direct Visualization and Monitoring of Medical Radiation Beams in Air

Purpose: Radiation therapy errors are rare but potentially catastrophic. Recent fatal incidents could have been avoided by utilizing real-time methods of monitoring delivery of radiation during treatment. However, few existing methods are practical enough to be used routinely. The study presents the first experimental demonstration of a novel non-perturbing method of monitoring radiation therapy through the phenomena of air scintillation. Methods: Monitoring of radiation delivery was devised by leveraging the phenomena of nitrogen excitation in air by ionizing radiation. The excitation induced weak luminescence in the 300–400 nm range, a process called air scintillation. An electron-multiplication charge-coupled device camera (f/0.95 lens; 440 nm shortpass) was set-up in a clinical treatment vault and was used to capture air scintillation images of kilovoltage and megavoltage beams. Monte Carlo simulations were performed to determine the correlation of radiation dose to air scintillation. Results: Megavoltage beams from a Varian Clinac 21EX and kilovoltage beams from an orthovoltage unit (50 kVp, 30 mA) were visualized with a relatively short exposure time (10 s). Cherenkov luminescence produced in a plastic transparent phantom did not interfere with detection of air scintillation. The image intensity displayed an inverse intensity falloff (r{sup 2} = 0.89) along the central axis and was proportional to dose rate (r{sup 2} = 0.9998). As beam energy increased, the divergence of the imaged beam decreased. Last, air scintillation was visualized during a simulated total skin irradiation electron treatment. Conclusion: Air scintillation can be clinically detected to monitor a radiation beam in an inexpensive and non-perturbing manner. This new method is advantageous in monitoring for gross delivery and uniquely capable of wide area in a single acquisition, such as the case for online verification of total body / skin / lymphoid irradiation treatments.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Quality assurance for the clinical implementation of kilovoltage intrafraction monitoring for prostate cancer VMAT

Purpose: Kilovoltage intrafraction monitoring (KIM) is a real-time 3D tumor monitoring system for cancer radiotherapy. KIM uses the commonly available gantry-mounted x-ray imager as input, making this method potentially more widely available than dedicated real-time 3D tumor monitoring systems. KIM is being piloted in a clinical trial for prostate cancer patients treated with VMAT (NCT01742403). The purpose of this work was to develop clinical process and quality assurance (QA) practices for the clinical implementation of KIM. Methods: Informed by and adapting existing guideline documents from other real-time monitoring systems, KIM-specific QA practices were developed. The following five KIM-specific QA tests were included: (1) static localization accuracy, (2) dynamic localization accuracy, (3) treatment interruption accuracy, (4) latency measurement, and (5) clinical conditions accuracy. Tests (1)–(4) were performed using KIM to measure static and representative patient-derived prostate motion trajectories using a 3D programmable motion stage supporting an anthropomorphic phantom with implanted gold markers to represent the clinical treatment scenario. The threshold for system tolerable latency is <1 s. The tolerances for all other tests are that both the mean and standard deviation of the difference between the programmed trajectory and the measured data are <1 mm. The (5) clinical conditions accuracy test compared the KIM measured positions with those measured by kV/megavoltage (MV) triangulation from five treatment fractions acquired in a previous pilot study. Results: For the (1) static localization, (2) dynamic localization, and (3) treatment interruption accuracy tests, the mean and standard deviation of the difference are <1.0 mm. (4) The measured latency is 350 ms. (5) For the tests with previously acquired patient data, the mean and standard deviation of the difference between KIM and kV/MV triangulation are <1.0 mm. Conclusions: Clinical process and QA practices for the safe clinical implementation of KIM, a novel real-time monitoring system using commonly available equipment, have been developed and implemented for prostate cancer VMAT.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

SU-E-T-251: Developing a Daily Proton Beam Monitoring System

Purpose: To develop a daily monitoring system for proton beam output check and beam uniformity check. Methods: Designed for continuously irradiated photon and electron beams with a field size of 20 cm x 20 cm, the daily output checker (Sun Nuclear, Inc.) is not suitable for monitoring proton beams with inter-pulse beam-off and a field size smaller than 14–16 cm in diameter. To allow such proton beam monitoring, the following tests were performed. 1. Absolute dose and array calibrations which accept continuous irradiation only, were performed using photon beams. 2. Five ion chambers within the central area of 8 cm x 8 cm were utilized to check constancy of output at the center of beam modulation and at distal edge and to check beam symmetry and flatness. 3. To simplify our evaluation, the array calibration was manually modified, such that all five chambers report equal values in spite of their differences in build-up thicknesses. 4. The chamber at the lower-right corner is placed under a buildup thickness that can offer dose measurement at the distal edge. This buildup thickness was determined by proton beam range measurements, which established buildup thickness for beam output measurement at the central chamber and range measurement at the corner chamber. 5. The beam-off delay which allows receipt of pulsed irradiation was activated and optimal delay times were determined for each proton beam at 149.6, 185.6, and 249.5 MeV. Results: The above system was tested by miss-steering proton beams and altering phantom thickness by 1 mm at a time. The system reliably monitored the beam with: 3% tolerance for beam flatness, symmetry and output. The range difference of 0.5 mm could be detected at all energies by setting a tolerance of 20%. Conclusion: A quick daily proton beam monitoring system was feasible.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2016

SU-F-J-44: Development of a Room Laser Based Real-Time Alignment Monitoring System Using An Array of Photodiodes

Purpose: To develop a real-time alignment monitoring system (RAMS) to compensate for the limitations of the conventional room laser based alignment system, and to verify the feasibility of the RAMS. Methods: The RAMS was composed of a room laser sensing array (RLSA), an analog-todigital converter, and a control PC. In the RLSA, seven photodiodes (each in 1 mm width) are arranged in a pattern that the RAMS provides alignment in 1 mm resolution. It works based on detecting laser light aligned on one of photodiodes. When misaligned, the laser would match with different photodiode(s) giving signal at unexpected location. Thus, how much displaced can be determined. To verify the reproducibility of the system with respect to time as well as repeated set-ups, temporal reproducibility and repeatability test was conducted. The accuracy of the system was tested by obtaining detection signals with varying laser-match positions. Results: The signal of the RAMS was found to be stable with respect to time. The repeatability test resulted in a maximum coefficient of variance of 1.14%, suggesting that the signal of the RAMS was stable over repeated set-ups. In the accuracy test, signals between when the laser was aligned and notaligned with any of sensors could be distinguished by signal intensity. The signals of not-aligned sensors were always below 75% of the signal of the aligned sensor. It was confirmed that the system could detect 1 mm of movement by monitoring the pattern of signals, and could observe the movement of the system in real-time. Conclusion: We developed a room laser based alignment monitoring system. The feasibility test verified that the system is capable of quantitative alignment monitoring in real time. The system is relatively simple, not expensive, and considered to be easily incorporated into conventional room laser systems for real-time alignment monitoring. This research was supported by the Mid-career Researcher Program through NRF funded by the Ministry of Science, ICT & Future Planning of Korea (NRF-2014R1A2A1A10050270) and by the Radiation Technology R&D program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (No. 2013M2A2A7038291)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

MO-FG-202-08: Real-Time Monte Carlo-Based Treatment Dose Reconstruction and Monitoring for Radiotherapy

Purpose: This proof-of-concept study is to develop a real-time Monte Carlo (MC) based treatment-dose reconstruction and monitoring system for radiotherapy, especially for the treatments with complicated delivery, to catch treatment delivery errors at the earliest possible opportunity and interrupt the treatment only when an unacceptable dosimetric deviation from our expectation occurs. Methods: First an offline scheme is launched to pre-calculate the expected dose from the treatment plan, used as ground truth for real-time monitoring later. Then an online scheme with three concurrent threads is launched while treatment delivering, to reconstruct and monitor the patient dose in a temporally resolved fashion in real-time. Thread T1 acquires machine status every 20 ms to calculate and accumulate fluence map (FM). Once our accumulation threshold is reached, T1 transfers the FM to T2 for dose reconstruction ad starts to accumulate a new FM. A GPU-based MC dose calculation is performed on T2 when MC dose engine is ready and a new FM is available. The reconstructed instantaneous dose is directed to T3 for dose accumulation and real-time visualization. Multiple dose metrics (e.g. maximum and mean dose for targets and organs) are calculated from the current accumulated dose and compared with the pre-calculated expected values. Once the discrepancies go beyond our tolerance, an error message will be send to interrupt the treatment delivery. Results: A VMAT Head-and-neck patient case was used to test the performance of our system. Real-time machine status acquisition was simulated here. The differences between the actual dose metrics and the expected ones were 0.06%–0.36%, indicating an accurate delivery. ∼10Hz frequency of dose reconstruction and monitoring was achieved, with 287.94s online computation time compared to 287.84s treatment delivery time. Conclusion: Our study has demonstrated the feasibility of computing a dose distribution in a temporally resolved fashion in real-time and quantitatively and dosimetrically monitoring the treatment delivery.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-E-209-00: Radiation Dose Monitoring and Protocol Management

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data-driven protocol management and informed case follow up are now feasible. Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co-exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex. Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home-grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope. Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home-grown IT solution and dose data analysis framework. Learning Objectives: Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice Review examples of data available from a variety of systems and how it managed and conveyed. Reflect on the role of the physicist in radiation dose awareness.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-E-209-01: Fluoroscopic Dose Monitoring and Patient Follow-Up Program at Massachusetts General Hospital

60 APPLIED LIFE SCIENCES↗