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DOE OSTI2016

MO-F-204-00: Preparing for the ABR Diagnostic and Nuclear Medical Physics Exams

Adequate, efficient preparation for the ABR Diagnostic and Nuclear Medical Physics exams is key to successfully obtain ABR certification. Each part of the ABR exam presents its own challenges: Part I: Determine the scope of basic medical physics study material, efficiently review this material, and solve related written questions/problems. Part II: Understand imaging principles, modalities, and systems, including image acquisition, processing, and display. Understand the relationship between imaging techniques, image quality, patient dose and safety, and solve related written questions/problems. Part III: Gain crucial, practical, clinical medical physics experience. Effectively communicate and explain the practice, performance, and significance of all aspects of clinical medical physics. All parts of the ABR exam require specific skill sets and preparation: mastery of basic physics and imaging principles; written problem solving often involving rapid calculation; responding clearly and succinctly to oral questions about the practice, methods, and significance of clinical medical physics. This symposium focuses on the preparation necessary for each part of the ABR exam. Although there is some overlap, the nuclear exam covers a different body of knowledge than the diagnostic exam. A separate speaker will address those unique aspects of the nuclear exam, and how preparing for a second specialty differs from the first. Medical physicists who recently completed each ABR exam portion will share their experiences, insights, and preparation methods to help attendees best prepare for the challenges of each part of the ABR exam. In accordance with ABR exam security policy, no recalls or exam questions will be discussed. Learning Objectives: How to prepare for Part 1 of the ABR exam by determining the scope of basic medical physics study material and related problem solving/calculations How to prepare for Part 2 of the ABR exam by understanding diagnostic and/or nuclear imaging physics, systems, dosimetry, safety and related problem solving/calculations How to prepare for Part 3 of the ABR exam by effectively communicating the practice, methods, and significance of clinical diagnostic and/or nuclear medical physics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-F-204-01: Preparing for Part 1 of the ABR Diagnostic Physics Exam

Adequate, efficient preparation for the ABR Diagnostic and Nuclear Medical Physics exams is key to successfully obtain ABR certification. Each part of the ABR exam presents its own challenges: Part I: Determine the scope of basic medical physics study material, efficiently review this material, and solve related written questions/problems. Part II: Understand imaging principles, modalities, and systems, including image acquisition, processing, and display. Understand the relationship between imaging techniques, image quality, patient dose and safety, and solve related written questions/problems. Part III: Gain crucial, practical, clinical medical physics experience. Effectively communicate and explain the practice, performance, and significance of all aspects of clinical medical physics. All parts of the ABR exam require specific skill sets and preparation: mastery of basic physics and imaging principles; written problem solving often involving rapid calculation; responding clearly and succinctly to oral questions about the practice, methods, and significance of clinical medical physics. This symposium focuses on the preparation necessary for each part of the ABR exam. Although there is some overlap, the nuclear exam covers a different body of knowledge than the diagnostic exam. A separate speaker will address those unique aspects of the nuclear exam, and how preparing for a second specialty differs from the first. Medical physicists who recently completed each ABR exam portion will share their experiences, insights, and preparation methods to help attendees best prepare for the challenges of each part of the ABR exam. In accordance with ABR exam security policy, no recalls or exam questions will be discussed. Learning Objectives: How to prepare for Part 1 of the ABR exam by determining the scope of basic medical physics study material and related problem solving/calculations How to prepare for Part 2 of the ABR exam by understanding diagnostic and/or nuclear imaging physics, systems, dosimetry, safety and related problem solving/calculations How to prepare for Part 3 of the ABR exam by effectively communicating the practice, methods, and significance of clinical diagnostic and/or nuclear medical physics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-F-204-02: Preparing for Part 2 of the ABR Diagnostic Physics Exam

Adequate, efficient preparation for the ABR Diagnostic and Nuclear Medical Physics exams is key to successfully obtain ABR certification. Each part of the ABR exam presents its own challenges: Part I: Determine the scope of basic medical physics study material, efficiently review this material, and solve related written questions/problems. Part II: Understand imaging principles, modalities, and systems, including image acquisition, processing, and display. Understand the relationship between imaging techniques, image quality, patient dose and safety, and solve related written questions/problems. Part III: Gain crucial, practical, clinical medical physics experience. Effectively communicate and explain the practice, performance, and significance of all aspects of clinical medical physics. All parts of the ABR exam require specific skill sets and preparation: mastery of basic physics and imaging principles; written problem solving often involving rapid calculation; responding clearly and succinctly to oral questions about the practice, methods, and significance of clinical medical physics. This symposium focuses on the preparation necessary for each part of the ABR exam. Although there is some overlap, the nuclear exam covers a different body of knowledge than the diagnostic exam. A separate speaker will address those unique aspects of the nuclear exam, and how preparing for a second specialty differs from the first. Medical physicists who recently completed each ABR exam portion will share their experiences, insights, and preparation methods to help attendees best prepare for the challenges of each part of the ABR exam. In accordance with ABR exam security policy, no recalls or exam questions will be discussed. Learning Objectives: How to prepare for Part 1 of the ABR exam by determining the scope of basic medical physics study material and related problem solving/calculations How to prepare for Part 2 of the ABR exam by understanding diagnostic and/or nuclear imaging physics, systems, dosimetry, safety and related problem solving/calculations How to prepare for Part 3 of the ABR exam by effectively communicating the practice, methods, and significance of clinical diagnostic and/or nuclear medical physics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-F-204-03: Preparing for Part 3 of the ABR Diagnostic Physics Exam

Adequate, efficient preparation for the ABR Diagnostic and Nuclear Medical Physics exams is key to successfully obtain ABR certification. Each part of the ABR exam presents its own challenges: Part I: Determine the scope of basic medical physics study material, efficiently review this material, and solve related written questions/problems. Part II: Understand imaging principles, modalities, and systems, including image acquisition, processing, and display. Understand the relationship between imaging techniques, image quality, patient dose and safety, and solve related written questions/problems. Part III: Gain crucial, practical, clinical medical physics experience. Effectively communicate and explain the practice, performance, and significance of all aspects of clinical medical physics. All parts of the ABR exam require specific skill sets and preparation: mastery of basic physics and imaging principles; written problem solving often involving rapid calculation; responding clearly and succinctly to oral questions about the practice, methods, and significance of clinical medical physics. This symposium focuses on the preparation necessary for each part of the ABR exam. Although there is some overlap, the nuclear exam covers a different body of knowledge than the diagnostic exam. A separate speaker will address those unique aspects of the nuclear exam, and how preparing for a second specialty differs from the first. Medical physicists who recently completed each ABR exam portion will share their experiences, insights, and preparation methods to help attendees best prepare for the challenges of each part of the ABR exam. In accordance with ABR exam security policy, no recalls or exam questions will be discussed. Learning Objectives: How to prepare for Part 1 of the ABR exam by determining the scope of basic medical physics study material and related problem solving/calculations How to prepare for Part 2 of the ABR exam by understanding diagnostic and/or nuclear imaging physics, systems, dosimetry, safety and related problem solving/calculations How to prepare for Part 3 of the ABR exam by effectively communicating the practice, methods, and significance of clinical diagnostic and/or nuclear medical physics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-F-204-04: Preparing for Parts 2 & 3 of the ABR Nuclear Medicine Physics Exam

Adequate, efficient preparation for the ABR Diagnostic and Nuclear Medical Physics exams is key to successfully obtain ABR certification. Each part of the ABR exam presents its own challenges: Part I: Determine the scope of basic medical physics study material, efficiently review this material, and solve related written questions/problems. Part II: Understand imaging principles, modalities, and systems, including image acquisition, processing, and display. Understand the relationship between imaging techniques, image quality, patient dose and safety, and solve related written questions/problems. Part III: Gain crucial, practical, clinical medical physics experience. Effectively communicate and explain the practice, performance, and significance of all aspects of clinical medical physics. All parts of the ABR exam require specific skill sets and preparation: mastery of basic physics and imaging principles; written problem solving often involving rapid calculation; responding clearly and succinctly to oral questions about the practice, methods, and significance of clinical medical physics. This symposium focuses on the preparation necessary for each part of the ABR exam. Although there is some overlap, the nuclear exam covers a different body of knowledge than the diagnostic exam. A separate speaker will address those unique aspects of the nuclear exam, and how preparing for a second specialty differs from the first. Medical physicists who recently completed each ABR exam portion will share their experiences, insights, and preparation methods to help attendees best prepare for the challenges of each part of the ABR exam. In accordance with ABR exam security policy, no recalls or exam questions will be discussed. Learning Objectives: How to prepare for Part 1 of the ABR exam by determining the scope of basic medical physics study material and related problem solving/calculations How to prepare for Part 2 of the ABR exam by understanding diagnostic and/or nuclear imaging physics, systems, dosimetry, safety and related problem solving/calculations How to prepare for Part 3 of the ABR exam by effectively communicating the practice, methods, and significance of clinical diagnostic and/or nuclear medical physics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Automated construction of clear-sky dictionary from all-sky imager data

All-sky imagers (ASIs) have significant promise as scalable sensors for short-term solar irradiance forecasting. Many of the current computational techniques that use ASIs for this purpose rely on collections of clear-sky images indexed by time of day, solar angle, or both, called clear-sky dictionaries (CSDs). These CSDs act as baselines against which images can be compared to locate and classify clouds within the image frame. CSDs are often compiled by hand, where individuals visually inspect collections of images one at a time to find clear-sky images. This process is not scalable, and it is prone to error. This paper proposes an automated, nonparametric alternative that uses the principles of digital image processing to find clear-sky images within a set of images taken over several days. We use ground-truth measurements of the clearness index to assess the performance of our method, and we show that the images it selects accurately correspond to clear-sky images. We also compare our proposal, which is nonparametric, with a state-of-the-art parametric method. The numerical results indicate that the performance of the method proposed here is superior.

14 SOLAR ENERGY↗
DOE OSTI2015

Image-based occupancy sensor

An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generates an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Positron emission tomography harmonization in the Alzheimer's Disease Neuroimaging Initiative: A scalable and rigorous approach to multisite amyloid and tau quantification

Abstract INTRODUCTION A key goal of the Alzheimer's Disease NeuroImaging Initiative (ADNI) positron emission tomography (PET) Core is to harmonize quantification of β‐amyloid (Aβ) and tau PET image data across multiple scanners and tracers. METHODS We developed an analysis pipeline (Berkeley PET Imaging Pipeline, B‐PIP) for ADNI Aβ and tau PET images and applied it to PET data from other multisite studies. Steps include image pre‐processing, refacing, magnetic resonance imaging (MRI)/PET co‐registration, visual quality control (QC), quantification of tracer uptake, and standardization of Aβ and tau standardized uptake value ratios (SUVrs) across tracers. RESULTS Measurements from 10,105 cross‐sectional and longitudinal Aβ and tau PET scans acquired in several studies between 2010 and 2024 can be processed, harmonized, and directly merged across tracers and cohorts. DISCUSSION The B‐PIP developed in ADNI is a scalable image harmonization approach used in several observational studies and clinical trials that facilitates rigorous Aβ and tau PET quantification and data sharing. Highlights Quantitative results from ADNI Aβ and tau PET data are generated using a rigorous, scalable image processing pipeline This pipeline has been applied to PET data from several other large, multisite studies and trials Quantitative outcomes are harmonizable across studies and are shared with the scientific community

Neurosciences & Neurology↗
DOE OSTI2016

MO-FG-209-02: Development of a Virtual Breast Phantom From a Multi-Modality Perspective

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-209-05: Towards a Feature-Based Anthropomorphic Model Observer

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Utah FORGE: Seismic DAS and Geophone Borehole Data Processing and 3D Imaging of Vp/Vs Ratio in the 2024 Stimulated Reservoir

This dataset includes a final report and a 3D velocity model derived from seismic DAS and geophone borehole data collected during the April 2024 stimulation of the reservoir at Utah FORGE. The report details the processing of over 50,000 P- and S-wave travel times used in a tomographic inversion to estimate the Vp/Vs ratio, revealing anomalies adjacent to wells 16A and 16B that may be associated with injected fracturing fluids. Additionally, Wadati analysis of more than 27,000 pairs of differential P- and S-wave travel times supports this interpretation with a high Vp/Vs estimate of 1.86, averaged over the dimensions of the earthquake cluster. The accompanying data file provides a 3D model of P- and S-wave velocities and Vp/Vs ratios, structured with spatial coordinates and velocity values.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Automated Image Segmentation and Processing Pipeline Applied to X–Ray Computed Tomography Studies of Pitting Corrosion in Aluminum Wires

Understanding pitting corrosion is critical, yet its kinetics and morphology remain challenging to study from X-ray computed tomography (XCT) due to manual segmentation barriers. To address this, an automated pipeline leveraging deep learning for efficient large-scale XCT analysis is developed, revealing new corrosion insights. The pipeline enables pit segmentation, 3D reconstruction, statistical characterization, and a topological transformation for visualization. Here, the pipeline is applied to 87 648 XCT images capturing commercial purity aluminum (1100 Al) wire exposed to sodium chloride (NaCl) salt particles over a period of 122 h. The pipeline achieves complete feature extraction and statistical quantification across the entire XCT dataset, leveraging distributed computing environment for high efficiency. Global growth kinetics such as high-level stepwise sigmoidal volume loss patterns and granular individual pit developments are both captured for 36 detected pits. By combining automation, computer vision, and extensive XCT datasets, this research accelerates precise corrosion assessment to enable materials science discoveries at scale.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-J-97: Quality Assurance of Deformable Image Registration Algorithms: How Realistic Should Phantoms Be?

Purpose: Deformable image registration (DIR) has widespread uses in radiotherapy for applications such as dose accumulation studies, multi-modality image fusion, and organ segmentation. The quality assurance (QA) of such algorithms, however, remains largely unimplemented. This work aims to determine how detailed a physical phantom needs to be to accurately perform QA of a DIR algorithm. Methods: Virtual prostate and head-and-neck phantoms, made from patient images, were used for this study. Both sets consist of an undeformed and deformed image pair. The images were processed to create additional image pairs with one through five homogeneous tissue levels using Otsu’s method. Realistic noise was then added to each image. The DIR algorithms from MIM and Velocity (Deformable Multipass) were applied to the original phantom images and the processed ones. The resulting deformations were then compared to the known warping. A higher number of tissue levels creates more contrast in an image and enables DIR algorithms to produce more accurate results. For this reason, error (distance between predicted and known deformation) is utilized as a metric to evaluate how many levels are required for a phantom to be a realistic patient proxy. Results: For the prostate image pairs, the mean error decreased from 1–2 tissue levels and remained constant for 3+ levels. The mean error reduction was 39% and 26% for Velocity and MIM respectively. For head and neck, mean error fell similarly through 2 levels and flattened with total reduction of 16% and 49% for Velocity and MIM. For Velocity, 3+ levels produced comparable accuracy as the actual patient images, whereas MIM showed further accuracy improvement. Conclusion: The number of tissue levels needed to produce an accurate patient proxy depends on the algorithm. For Velocity, three levels were enough, whereas five was still insufficient for MIM.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Low-noise humidity controller for imaging water mediated processes in atomic force microscopy

We demonstrate the construction of a novel low-noise continuous flow humidity controller and its integration with a commercial variable-temperature atomic force microscope fluid cell, allowing precise control of humidity and temperature at the sample during nanoscale measurements. Based on wet and dry gas mixing, the design allows a high mechanical stability to be achieved by means of an ultrasonic atomiser for the generation of water-saturated gas, improving upon previous bubbler-based architectures. Water content in the flow is measured both at the inflow and outflow of the fluid cell, enabling the monitoring of water condensation and icing, and allowing controlled variation of the sample temperature independently of the humidity. To benchmark the performance of the controller, the results of detailed noise studies and time-based imaging of the formation of ice layers on highly oriented pyrolytic graphite are shown.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Advanced Control Architecture and Sensor Information Development for Process Automation, Optimization, and Imaging of Chemical Looping Systems

The Syngas Chemical Looping (SCL) process developed at The Ohio State University (OSU) uses an iron-based oxygen carrier to convert syngas into high-purity hydrogen while simultaneously capturing carbon dioxide that is readily sequestrable. A 25 kWth sub-pilot unit was successfully demonstrated multiple times on the OSU Clean Coal Research Facility, and a 250 kWth – 3 MWth pilot demonstration unit has been designed and constructed at the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The focus of this project is to develop multiple technologies to automate the startup and shutdown of chemical looping system. Success of this project will propel the advanced carbon capture method toward commercialization, hence be disruptive to the fossil fuel and power industries. Advanced process automation control architecture and imaging and optimization sensor software were developed for OSU chemical looping process. A high-level controller (HLC) consisting of decision-making and controller-selection logic integrated with sliding mode controllers (SMCs) were developed to perform chemical looping process startup and shutdown. Babcock & Wilcox Power Generation Group’s FocalPoint Optimization System was implemented to optimize the process operating conditions. The process automation controller and optimization information were realized and tested on OSU’s existing sub-pilot chemical looping test unit under atmospheric condition. The implemented control architecture was able to perform the complete process procedure from startup, steady-state reaction operation to shutdown with minimal operator intervention. The controller was also implemented on the pressurized syngas chemical looping (SCL) pilot test unit constructed at the National Carbon Capture Center (NCCC), demonstrating its pressure control capability with a designed transient state trajectory. An electrical capacitance volume tomography (ECVT) sensor device and its software were developed to image the packed moving bed and slugging fluidized bed of oxygen carriers in chemical looping systems at elevated temperatures. The ECVT device constructed was capable of tracking the subtle voidage variance along the moving bed axis as a feature for directly measuring the oxygen carrier particles’ linear velocity. Also, the high temperature ECVT device was used to study the fluidization characteristics of Geldart Group D particles.

08 HYDROGEN↗
DOE OSTI2016

SU-F-P-37: Implementation of An End-To-End QA Test of the Radiation Therapy Imaging, Planning and Delivery Process to Identify and Correct Possible Sources of Deviation

Purpose: To implement an end-to-end QA test of the radiation therapy imaging, planning and delivery process, aimed to assess the dosimetric agreement accuracy between planned and delivered treatment, in order to identify and correct possible sources of deviation. To establish an internal standard for machine commissioning acceptance. Methods: A test involving all steps of the radiation therapy: imaging, planning and delivery process was designed. The test includes analysis of point dose and planar dose distributions agreement between TPS calculated and measured dose. An ad hoc 16 cm diameter PMMA phantom was constructed with one central and four peripheral bores that can accommodate calibrated electron density inserts. Using Varian Eclipse 10.0 and Elekta XiO 4.50 planning systems, IMRT, RapidArc and 3DCRT with hard and dynamic wedges plans were planned on the phantom and tested. An Exradin A1SL chamber is used with a Keithley 35617EBS electrometer for point dose measurements in the phantom. 2D dose distributions were acquired using MapCheck and Varian aS1000 EPID.Gamma analysis was performed for evaluation of 2D dose distribution agreement using MapCheck software and Varian Portal Dosimetry Application.Varian high energy Clinacs Trilogy, 2100C/CD, 2000CR and low energy 6X/EX where tested.TPS-CT# vs. electron density table were checked for CT-scanners used. Results: Calculated point doses were accurate to 0.127% SD: 0.93%, 0.507% SD: 0.82%, 0.246% SD: 1.39% and 0.012% SD: 0.01% for LoX-3DCRT, HiX-3DCRT, IMRT and RapidArc plans respectively. Planar doses pass gamma 3% 3mm in all cases and 2% 2mm for VMAT plans. Conclusion: Implementation of a simple and reliable quality assurance tool was accomplished. The end-to-end proved efficient, showing excellent agreement between planned and delivered dose evidencing strong consistency of the whole process from imaging through planning to delivery. This test can be used as a first step in beam model acceptance for clinical use.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-BRB-12: Real-Time Visualization of Discrete Spot Scanning Proton Therapy Beam for Quality Assurance

Purpose: With the growing adoption of proton beam therapy there is an increasing need for effective and user-friendly tools for performing quality assurance (QA) measurements. The speed and versatility of spot-scanning proton beam (PB) therapy systems present unique challenges for traditional QA tools. To address these challenges a proof-of-concept system was developed to visualize, in real-time, the delivery of individual spots from a spot-scanning PB in order to perform QA measurements. Methods: The PB is directed toward a custom phantom with planar faces coated with a radioluminescent phosphor (Gd2O2s:Tb). As the proton beam passes through the phantom visible light is emitted from the coating and collected by a nearby CMOS camera. The images are processed to determine the locations at which the beam impinges on each face of the phantom. By so doing, the location of each beam can be determined relative to the phantom. The cameras are also used to capture images of the laser alignment system. The phantom contains x-ray fiducials so that it can be easily located with kV imagers. Using this data several quality assurance parameters can be evaluated. Results: The proof-of-concept system was able to visualize discrete PB spots with energies ranging from 70 MeV to 220 MeV. Images were obtained with integration times ranging from 20 to 0.019 milliseconds. If not limited by data transmission, this would correspond to a frame rate of 52,000 fps. Such frame rates enabled visualization of individual spots in real time. Spot locations were found to be highly correlated (R{sup 2}=0.99) with the nozzle-mounted spot position monitor indicating excellent spot positioning accuracy Conclusion: The system was shown to be capable of imaging individual spots for all clinical beam energies. Future development will focus on extending the image processing software to provide automated results for a variety of QA tests.

60 APPLIED LIFE SCIENCES↗