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At least 1,081 records · Page 60

Comparative Analysis of Direct and Indirect Cooling of Wide-Bandgap Power Modules and Performance Enhancement of Jet Impingement-Based Direct Substrate Cooling

With the development of high-power and high-torque machines, requirements for high-power density electronics are increasing. Thermal management of such systems requires high heat extraction. Conventional air cooling based heat sinks and cold plate based liquid cooling have their own benefits for various applications but has limitations for high power density applications. The current study explores a jet impingement based direct substrate cooling system that was implemented for a SiC based direct bonded Cu substrate for various power losses. Numerical comparison between jet impingement cooling and conventional horizontal/indirect cooling (pin fin heat sink and genetic algorithm-optimized heat sink) showed that the area weighted average of the heat transfer coefficient (HTC) is high for both horizontal cooling designs, and the local HTC is higher for jet impingement. Design iterations were undertaken to resolve the bottleneck of this cooling system. Increasing the number of nozzles helped to cover more area at the direct bonded Cu bottom plate, which drops the chip temperature considerably. With a constant flow rate, increasing the number of nozzles would decrease local jet velocity, which reduces the heat extraction by jet impingement. This issue can be addressed by reducing the diameter of nozzle but doing so results in a high pressure drop where the design constraint is 2 psi. A flared nozzle design is proposed, which has a higher spreading angle of the jet that increases the flow coverage and reduces the pressure drop of the coolant loop.

Barua, Himel↗

Microstructure of vapor deposited coatings on curved substrates

Thermal barrier coating systems consisting of a metallic bond coat and ceramic over layer are widely used to extend the life of gas turbine engine components. They are applied using either high-vacuum physical vapor deposition techniques in which vapor atoms rarely experience scattering collisions during propagation to a substrate, or by gas jet assisted (low-vacuum) vapor deposition techniques that utilize scattering from streamlines to enable non-line-of-sight deposition. Both approaches require substrate motion to coat a substrate of complex shape. Here, direct simulation Monte Carlo and kinetic Monte Carlo simulation methods are combined to simulate the deposition of a nickel coating over the concave and convex surfaces of a model airfoil, and the simulation results are compared with those from experimental depositions. The simulation method successfully predicted variations in coating thickness, columnar growth angle, and porosity during both stationary and substrate rotated deposition. It was then used to investigate a wide range of vapor deposition conditions spanning high-vacuum physical vapor deposition to low-vacuum gas jet assisted vapor deposition. The average coating thickness was found to increase initially with gas pressure reaching a maximum at a chamber pressure of 8–10 Pa, but the best coating thickness uniformity was achieved under high vacuum deposition conditions. However, high vacuum conditions increased the variation in the coatings pore volume fraction over the surface of the airfoil. The simulation approach was combined with an optimization algorithm and used to investigate novel deposition concepts to tailor the local coating thickness.

42 ENGINEERING↗

SU-E-T-309: Tangential Modulated Arc Therapy: A Novel Technique for the Treatment of Superficial Disease

Purpose: We propose a new type of treatment that employs a modulated and sliding tangential photon field to provide superior coverage of superficial targets when compared to other commonly employed methods while drastically reducing dose to the underlying sensitive structures often present in these cases. Methods: Modulated treatment plans were formulated for a set of three representative cases. The first was a revised treatment of a scalp sarcoma, while the second was a treatment of a right posterior chest wall sarcoma. For these cases, asymmetric jaw placement, angular limitations, and central isocenter placements were used to force the optimization algorithm into finding solutions with beamlines that were not perpendicular to the body surface. The final case targeted the chest wall of a breast cancer patient, in which standard treatments were compared to the use of modulated fields with multiple isocenters along the chest wall. Results: When compared with unrestricted modulated arcs, the tangential arc scalp treatment reduced the max and mean doses delivered to the brain by 33Gy (from 55 to 22Gy) and 6Gy (from 14Gy to 8Gy), respectively. In the right posterior chest wall case, the V10 in the ipsilateral lung was kept below 5% while retaining a Rx dose (45Gy) target coverage of over 97%. For the breast case, the modulated plan achieved reductions in high dose to the ipsilateral lung and heart by a factor of 2–3 when compared to classic laterally opposed tangents and reduced the V5 by 40% when compared to standard modulated arcs. Conclusion: Tangential modulated arc therapy has outperformed the conventional modalities of treatment for superficial lesions used in our clinic. We hope that with the advent of digitally controlled linear accelerators, we can uncover further benefits of this new technique and extend its applicability to a wider section of the patient population.

60 APPLIED LIFE SCIENCES↗

SU-C-16A-03: Direction Modulated Brachytherapy for HDR Treatment of Cervical Cancer

Purpose: To investigate a new Directional Modulated Brachytherapy (DMBT) intra-uterine tandem using various 192-Ir after-loaders. Methods: Dose distributions from the 192-Ir sources were modulated using a 6.3mm diameter tungsten shield (18.0g/cm3). The source moved along 6 longitudinal grooves, each 1.3mm in diameter, evenly spaced along periphery of the shield, The tungsten rod was enclosqed by 0.5mm thick Delrin (1.41g/cc). Monte Carlo N particle (MCNPX) was used to calculate dose distributions. 51million particles were calculated on 504 cores of a supercomputer. Fifteen different patients originally treated with a traditional tandem-and-ovoid applicator, with 5 fractions each, (15 patients X 5 fxs = 75 plans) were re-planned with the DMBT applicator combined with traditional ovoids, on an in-house developed HDR brachytherapy planning platform, which used intensity modulated planning capabilities using a constrained gradient optimization algorithm. For all plans the prescription dose was 6 Gy and they were normalized to match the clinical treated V100. Results: Generally, the DMBT plan quality was a remarkable improvement from conventional T and O plans because of the anisotropic dose distribution of DMBT. The largest difference was to the bladder which had a 0.59±0.87 Gy (8.5±28.7%) reduction in dose. This was because of the the horseshoe shape (U-shape) of the bladder. The dose reduction to rectum and sigmoid were 0.48±0.55 Gy (21.1±27.2%) and 0.10±0.38 Gy (40.6±214.9%), respectively. The D90 to the HRCTV was 6.55±0.96 Gy (conventional T and O) and 6.59±1.06 Gy (DMBT). Conclusion: For image guided adaptive brachytherapy, greater flexibility of radiation intensity is essential and DMBT can be the solution.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-00: Treatment Planning System Commissioning and QA

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG # 5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-01: Treatment Planning System Commissioning and QA: Challenges and Opportunities

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-02: TPS Commissioning and QA: A Process Orientation and Application of Control Charts

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-03: TPS Commissioning and QA: Incorporating the Entire Planning Process

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-04: The Recommendations of MPPG #5 and Practical Implementation Strategies

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

MO-G-201-01: A Multi-Institutional Study Investigating the Performance of a Knowledge-Based Planning System Against Pinnacle Auto-Planning Engine in SIB-IMRT for the Head-And-Neck Cancer

Purpose: Knowledge-based Planning (KBP) founded on prior planning experience and Auto-Planning Engine (APE; commercialized in Pinnacle v9.10 TPS) based on progressive optimization algorithm both aim to eliminate the trial-and-error process in radiotherapy inverse planning. This study investigates the performance of the approaches in a multi-institutional setting to evaluate their functionalities in oropharyngeal cancer and offers suggestions how they can be implemented in the clinic. Methods: Radboud University Medical Center (RUMC) provided 35 oropharyngeal cancer patients (SIB-IMRT with two-dose-level prescription: 68 Gy to PTV68 and 50.3 Gy to PTV50.3) with corresponding comparative APE plans. Johns Hopkins University (JHU) contributed to a three-dose-level (70 Gy 63 Gy and 58.1 Gy) plan library for RUMC’s patient KBP generation. MedStar Georgetown University Hospital (MGUH) contributed to a KBP approach employing overlap-volume histogram (OVH-KBP) for generating RUMC’s patient KBP plans using JHU’s plan library. Since both approaches need their own user-defined parameters as initial inputs the first 10 patients were set aside as training set to finalize them. Meanwhile cross-institutional comparisons and adjustments were implemented for investigating institutions’ protocol discrepancies and the approaches’ user-defined parameters were updated accordingly. The finalized parameters were then applied to the remaining 25 patients for OVH-KBP and APE generation. A Wilcoxon rank-sum test was used for statistical comparison with significance level of p<0.05. Results: On average PTV68’s V95 was 96.5% in APE plans vs. 97% in OVH-KBP plans (p=0.36); PTV50.3’s V95 in APE plans was 97.8% vs.97.6% in OVH-KBP plans (p=0.6); cord’s D0.1 cc was 38.6 Gy in OVH-KBP plans vs. 43.7 Gy in APE plans (p=0.0001); mean doses to larynxes oral cavities parotids and submandibular glands were similar with p>0.2. Conclusions: The study demonstrates that KBP and APE can generate plans of comparable quality in a multi-institutional setting. Variations in clinical protocols can be effectively addressed for cross-institutional adaptations. Binbin Wu and Todd McNutt are the co-inventors of a patent associated with the proposed knowledge-based planning system which was licensed to Varian Medical Systems in 2015; This research was in part supported by Philips Radiation Oncology Systems.

60 APPLIED LIFE SCIENCES↗

Designing Metabolic Division of Labor in Microbial Communities

ABSTRACT Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

59 BASIC BIOLOGICAL SCIENCES↗

A Nonlocal Feature-Driven Exemplar-Based Approach for Image Inpainting

Here, we present a nonlocal variational image completion technique which admits simultaneous inpainting of multiple structures and textures in a unified framework. The recovery of geometric structures is achieved by using general convolution operators as a measure of behavior within an image. These are combined with a nonlocal exemplar-based approach to exploit the self-similarity of an image in the selected feature domains and to ensure the inpainting of textures. We also introduce an anisotropic patch distance metric to allow for better control of the feature selection within an image and present a nonlocal energy functional based on this metric. Finally, we derive an optimization algorithm for the proposed variational model and examine its validity experimentally with various test images.

97 MATHEMATICS AND COMPUTING↗

A.I. for nuclear physics

Nuclear science is concerned with the understanding of the nature of matter, its basic constituents and their interaction to form the elements and the properties we observe. This includes the forms of matter we see around us and also exotic forms such as those that existed in the first moments after the Big Bang and that exist today inside neutron stars. The techniques, tools, and expertise needed for nuclear physics (NP) research are therefore diverse in nature. State-of-the art accelerators are being developed to illuminate the dynamical basis of the core of the atom in terms of the fundamental constituents called quarks and gluons and to increase the number of isotopes with known properties. This scientific infrastructure is reaching scales and complexities that require computational methods for tasks such as anomaly detection in operational data. New methodologies are needed to detect anomalies and to optimize operating parameters, predict failures as well as to discover new optimization algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Reconstruction of cosmic-ray muon events with CUORE

We report the in-situ 3D reconstruction of through-going muons in the CUORE experiment, a cryogenic calorimeter array searching for neutrinoless double beta (0vββ) decay, leveraging the segmentation of the detector. Due to the slow time response of the detector, time-of-flight estimation is not feasible. Therefore, the track reconstruction is performed using a multi-objective optimization algorithm that relies on geometrical information from the detector as a whole. We measure the integral flux of cosmic-ray muons underground at the Laboratori Nazionali del Gran Sasso, and find our value to be in good agreement with other experiments that have performed a similar measurement. To our knowledge, this work represents the first demonstration of 3D particle tracking and reconstruction of through-going muons with per-event angular determination in a millikelvin cryogenic detector array. The analysis performed for this work will be critical for validating the muon-related background in CUPID, a next-generation 0vββ experiment, and for follow-up studies on detector response and on delayed products induced by cosmic-ray muons.

Adams, D. Q. [University of South Carolina]↗

Modeling Alzheimer’s Disease Progression with Fused Laplacian Sparse Group Lasso

Alzheimer’s disease (AD), the most common type of dementia, not only imposes a huge financial burden on the health care system, but also a psychological and emotional burden on patients and their families. There is furthermore an urgent need to infer trajectories of cognitive performance over time and identify biomarkers predictive of the progression. Here, we introduce the multi-task learning with fused Laplacian sparse group lasso model, which can identify biomarkers closely related to cognitive measures due to its sparsity-inducing property, and model the disease progression with a general weighted (undirected) dependency graphs among the tasks. An efficient alternative directions method of multipliers based optimization algorithm is derived to solve the proposed non-smooth objective formulation. The effectiveness of the presented model is demonstrated by its superior prediction performance over multiple state-of-the-art methods and accurate identification of compact sets of cognition-relevant imaging biomarkers that are consistent with prior medical studies.

59 BASIC BIOLOGICAL SCIENCES↗

Graph Contractions for Calculating Correlation Functions in Lattice QCD

Computing correlation functions for many-particle systems in Lattice QCD is vital to extract nuclear physics observables like the energy spectrum of hadrons such as protons. However, this type of calculation has long been considered to be very challenging and computing-resource intensive because of the complex nature of a hadron composed of quarks with many degrees of freedom. In particular, a correlation function can be calculated through a sum of all possible pairs of quark contractions, each of which is a batched tensor contraction, dictated by Wick's theorem. Because the number of terms of this sum can be very large for any hadronic system of interest, fast evaluation of the sum faces several challenges: an extremely large number of contractions, a huge memory footprint at runtime, and the speed of tensor contractions. In this paper, we present a Lattice QCD analysis software suite, Redstar, which addresses these challenges by utilizing novel algorithmic and software engineering methods targeting modern computing platforms such as many-core CPUs and GPUs. In particular, Redstar represents every term in the sum of a correlation function by a graph, applies efficient graph algorithms to reduce the number of contractions to lower the cost of computations, and minimizes the total memory footprint. Moreover, Redstar carries out the contractions on either CPUs or GPUs utilizing an internal and highly efficient Hadron contraction library. Specifically, we illustrate some important algorithmic optimizations of Redstar, show various key design features of Hadron library, and present the speedup values due to the optimizations along with performance figures for calculating six correlations functions on four computing platforms.

Chen, Jie↗

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate feature sets, a consensus as to the best approach has not been reached, either in terms of the optimization algorithms or the instrumentation methods. Furthermore, although inconsistencies in the data sets, target classifiers, and functionality verification methods make head-to-head comparisons difficult, here we extract lessons learned and make recommendations for future research.

malware obfuscation↗

Topology Optimization of 3D Flow Fields for Flow Batteries

We report as power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An important aspect of a redox flow battery is the planar flow field, which is usually composed of two-dimensional channels etched into a backing plate. As reactant-laden electrolyte flows into the flow battery, the channels in the flow field distribute the fluid throughout the reactive porous electrode. We utilize topology optimization to design flow fields with full three-dimensional geometry variation, i.e., 3D flow fields. Specifically, we focus on vanadium redox flow batteries and use the optimization algorithm to generate 3D flow fields evolved from standard interdigitated flow fields by minimizing the electrical and flow pressure power losses. To understand how these 3D designs improve performance, we analyze the polarization of the reactant concentration and exchange current within the electrode to highlight how the designed flow fields mitigate the presence of electrode dead zones. While interdigitated flow fields can be heuristically engineered to yield high performance by tuning channel and land dimensions, such a process can be laborious; this work provides a framework for automating that design process.

25 ENERGY STORAGE↗