bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐AB‐BRD‐01: Process Mapping
Authors: Palta J. 
Published: June 2015

Current quality assurance and quality management guidelines provided by various professional organizations are prescriptive in nature, focusing principally on performance characteristics of planning and delivery devices. However, published analyses of events in radiation therapy show that most events are often caused by flaws in clinical processes rather than by device failures. This suggests the need for the development of a quality management program that is based on integrated approaches to process and equipment quality assurance. Industrial engineers have developed various risk assessment tools that are used to identify and eliminate potential failures from a system or a process before a failure impacts a customer. These tools include, but are not limited to, process mapping, failure modes and effects analysis, fault tree analysis. Task Group 100 of the American Association of Physicists in Medicine has developed these tools and used them to formulate an example risk‐based quality management program for intensity‐modulated radiotherapy. This is a prospective risk assessment approach that analyzes potential error pathways inherent in a clinical process and then ranks them according to relative risk, typically before implementation, followed by the design of a new process or modification of the existing process. Appropriate controls are then put in place to ensure that failures are less likely to occur and, if they do, they will more likely be detected before they propagate through the process, compromising treatment outcome and causing harm to the patient. Such a prospective approach forms the basis of the work of Task Group 100 that has recently been approved by the AAPM. This session will be devoted to a discussion of these tools and practical examples of how these tools can be used in a given radiotherapy clinic to develop a risk based quality management program.Learning Objectives:

Learn how to design a process map for a radiotherapy process
Learn how to perform failure modes and effects analysis analysis for a given process
Learn what fault trees are all about
Learn how to design a quality management program based upon the information obtained from process mapping, failure modes and effects analysis and fault tree analysis.
Dunscombe: Director, TreatSafely, LLC and Center for the Assessment of Radiological Sciences; Consultant to IAEA and VarianThomadsen: President, Center for the Assessment of Radiological SciencesPalta: Vice President of the Center for the Assessment of Radiological Sciences
TU‐AB‐BRD‐02: Failure Modes and Effects Analysis
Authors: Huq M. 
Published: June 2015

Current quality assurance and quality management guidelines provided by various professional organizations are prescriptive in nature, focusing principally on performance characteristics of planning and delivery devices. However, published analyses of events in radiation therapy show that most events are often caused by flaws in clinical processes rather than by device failures. This suggests the need for the development of a quality management program that is based on integrated approaches to process and equipment quality assurance. Industrial engineers have developed various risk assessment tools that are used to identify and eliminate potential failures from a system or a process before a failure impacts a customer. These tools include, but are not limited to, process mapping, failure modes and effects analysis, fault tree analysis. Task Group 100 of the American Association of Physicists in Medicine has developed these tools and used them to formulate an example risk‐based quality management program for intensity‐modulated radiotherapy. This is a prospective risk assessment approach that analyzes potential error pathways inherent in a clinical process and then ranks them according to relative risk, typically before implementation, followed by the design of a new process or modification of the existing process. Appropriate controls are then put in place to ensure that failures are less likely to occur and, if they do, they will more likely be detected before they propagate through the process, compromising treatment outcome and causing harm to the patient. Such a prospective approach forms the basis of the work of Task Group 100 that has recently been approved by the AAPM. This session will be devoted to a discussion of these tools and practical examples of how these tools can be used in a given radiotherapy clinic to develop a risk based quality management program.Learning Objectives:

Learn how to design a process map for a radiotherapy process
Learn how to perform failure modes and effects analysis analysis for a given process
Learn what fault trees are all about
Learn how to design a quality management program based upon the information obtained from process mapping, failure modes and effects analysis and fault tree analysis.
Dunscombe: Director, TreatSafely, LLC and Center for the Assessment of Radiological Sciences; Consultant to IAEA and VarianThomadsen: President, Center for the Assessment of Radiological SciencesPalta: Vice President of the Center for the Assessment of Radiological Sciences
TU‐AB‐BRB‐00: New Methods to Ensure Target Coverage
Authors: Siebers Jeffrey 
Published: June 2015

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV‐to‐CTV and CTV‐to‐PTV margins during the planning process to design a PTV‐conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter‐ and intra‐fractional positional variations, tissue motions, and initial contouring uncertainties.Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage‐based planning objectives. The treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP‐evaluation for the underlying CTVs and OARs to design an optimal treated volume.This symposium will describe CP‐evaluation methods as well as various robust planning techniques including use of probability‐weighted dose distributions, probability‐weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter‐fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra‐fractional organ motion. Clinical examples will be used to inter‐compare robust and margin‐based planning, highlighting advantages of robust‐plans in terms of target and normal tissue coverage. Robust‐planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning.Learning Objectives:

To understand robust‐planning as a clinical alternative to using margin‐based planning.
To understand conceptual differences between uncertainty and predictable motion.
To understand fundamental limitations of the PTV concept that probabilistic planning can overcome.
To understand the major contributing factors to target and normal tissue coverage probability.
To understand the similarities and differences of various robust planning techniques
To understand the benefits and limitations of robust planning techniques
TU‐B‐210‐02: MRg HIFU ‐ Advanced Approaches for Ablation and Hyperthermia
Authors: Moonen C. 
Published: June 2015

MR guided focused ultrasound (MRgFUS), or alternatively high‐intensity focused ultrasound (MRgHIFU), is approved for thermal ablative treatment of uterine fibroids and pain palliation in bone metastases. Ablation of malignant tumors is under active investigation in sites such as breast, prostate, brain, liver, kidney, pancreas, and soft tissue. Hyperthermia therapy with MRgFUS is also feasible, and may be used in conjunction with radiotherapy and for local targeted drug delivery. MRI allows in situ target definition and provides continuous temperature monitoring and subsequent thermal dose mapping during HIFU. Although MRgHIFU can be very precise, treatment of mobile organs is challenging and advanced techniques are required because of artifacts in MR temperature mapping, the need for intercostal firing, and need for gated HIFU or tracking of the lesion in real time. The first invited talk, “MR guided Focused Ultrasound Treatment of Tumors in Bone and Soft Tissue”, will summarize the treatment protocol and review results from treatment of bone tumors. In addition, efforts to extend this technology to treat both benign and malignant soft tissue tumors of the extremities will be presented. The second invited talk, “MRI guided High Intensity Focused Ultrasound – Advanced Approaches for Ablation and Hyperthermia”, will provide an overview of techniques that are in or near clinical trials for thermal ablation and hyperthermia, with an emphasis of applications in abdominal organs and breast, including methods for MRTI and tracking targets in moving organs.Learning Objectives:

Learn background on devices and techniques for MR guided HIFU for cancer therapy
Understand issues and current status of clinical MRg HIFU
Understand strategies for compensating for organ movement during MRgHIFU
Understand strategies for strategies for delivering hyperthermia with MRgHIFU
CM ‐ research collaboration with Philips
TU‐CD‐213‐01: Communication, Negotiation, and Persuasion: Approaches for Better Results
Authors: Johnson J. 
Published: June 2015

As part of the AAPM's Scope of Practice, medical physicists are expected to collaborate effectively with practioners and allied health care providers. Interpersonal skills such as communication, negotiation and persuasion are vital for successful collaboration to achieve shared goals. This session will provide some theoretical background of these interpersonal skills as well as specific techniques and practical tools to influence others. Applications of these interpersonal skills for administrative and human resource management purposes vital to medical physicists will be shared. Session attendees will gain knowledge and tools to help them effectively collaborate with administrative and physician leaders in areas such as capital and human resource selection, prioritization, and implementation. Participants will hear methods of how to articulate their goals and to understand the goals of administration, helping ensure alignment of purpose.Session speakers will present one of the topics: equipment selection, budget creation, contracts, and program‐related policy development. Specifics may include designing a business case in language that administrators understand, calculating the prioritization of budget requests, and influencing policies for safe and effective care. Human resource topics may include staffing justification, recruitment for fit, employment contracts, and benefits. Speakers will provide examples in both radiation therapy and diagnostic imaging departments and will share experiences and outcomes of their approaches for better results.Learning Objectives:After this course attendees will be better able to

Understand the shared goal between administrative and physicist leadership.
Articulate the “why” of the technical or human resource need.
Utilize communication, negotiation and persuasion tools to improve collaboration.
TU‐CD‐304‐02: Planning and Delivery of Fully Dynamic Trajectory Modulated Arc Therapy On Pituitary Adenoma: Dosimetric Advantages Over Conventional Volumetric Modulated Arc Therapy
Authors: Liang J , Hristov D , Otto K , Kim S 
Published: June 2015

Purpose:To assess the potential benefit of trajectory modulated arc therapy (TMAT) for treatments of small benign intracranial tumor, pituitary adenoma.Methods:A TMAT planning platform that incorporates complex source motion trajectory involving synchronized gantry rotation with translational and rotational couch movement was used for the study. The platform couples an interactive trajectory generation tool with a VMAT algorithm that performs multi‐resolution, progressive sampling MLC optimization on a user‐designed trajectory. A continuous couch rotation of 160° angular span with ±20° mini gantry arcs was used to emulate a non‐coplanar horizontal arc‐like trajectory. Compared to conventional non‐coplanar gantry arcs (60°‐100° gantry rotation with couch kicks), TMAT limited the unnecessary low to medium dose spread in the anterior and posterior directions, where primary OARs (e.g., brainstem, optic chiasm, optic nerves, and lens) are in close proximity to the targeted pituitary tumor volume. For 5 standard fractionation pituitary adenoma cases (50.4Gy/28fractions), TMAT and non‐coplanar VMAT plans were generated and compared under equivalent objectives/constraints. TMAT delivery was implemented and demonstrated on Varian TrueBeam via XML scripts.Results:Both techniques showed good target coverage while OARs were able to meet the constraints on QUANTEC guidelines. Notably, TMAT decreased the dose deposition in the anterior‐to‐posterior direction surrounding PTV. TMAT significantly reduced the mean doses on brainstem, optic nerves, eyes and lens by 47.29%±13.17%, 28.51%±8.68%, 80.82%±8.71% and 65.38%±19.99% compared with VMAT, all p≤0.01. Percentage reductions of maximum point dose in eyes and lens were 75.68%±10.30% and 70.72%±18.62% respectively for TMAT versus VMAT, all p≤0.01. A representative isocentric TMAT pituitary plan was delivered via an XML script with 200 control points and 282 MUs.Conclusion:Deliverable TMAT plans were achieved in developer mode in TrueBeam. TMAT was shown to be superior for pituitary adenoma irradiation in terms of OARs sparing.
TU‐CD‐304‐04: Scanning Field Total Body Irradiation Using Dynamic Arc with Variable Dose Rate and Gantry Speed
Authors: Yi B , Xu H , Mutaf Y , Prado K 
Published: June 2015

Purpose:Enable a scanning field total body irradiation (TBI) technique, using dynamic arcs, which is biologically equivalent to a moving couch TBI.Methods:Patient is treated slightly above the floor and the treatment field scans across the patient by a moving gantry. MLC positions change during gantry motion to keep same field opening at the level of the treatment plane (170 cm). This is done to mimic the same geometry as the moving couch TBI technique which has been used in our institution for over 10 years. The dose rate and the gantry speed are determined considering a constant speed of the moving field, variations in SSD and slanted depths resulting from oblique gantry angles. An Eclipse (Varian) planning system is commissioned to accommodate the extended SSD. The dosimetric foundations of the technique have been thoroughly investigated using phantom measurements.Results:Dose uniformity better than 2% across 180 cm length at 10cm depth is achieved by moving the gantry from −55 to +55 deg. Treatment range can be extended by increasing gantry range. No device such as a gravity‐oriented compensator is needed to achieve a uniform dose. It is feasible to modify the dose distribution by adjusting the dose rate at each gantry angle to compensate for body thickness differences. Total treatment time for 2 Gy AP/PA fields is 40–50 minutes excluding patient set up time, at the machine dose rate of 100 MU/min.Conclusion:This novel yet transportable moving field technique enables TBI treatment in a small treatment room with less program development preparation than other techniques. Treatment length can be extended per need, and. MLC‐based thickness compensation and partial lung blocking are also possible.
TU‐CD‐304‐05: 4Ï€ Non‐Coplanar Radiotherapy: From Mathematical Modeling to Clinical Implementation
Authors: Yu V , Nguyen D , Tran A , Ruan D , Cao M , Kaprealian T , Kupelian P , Low D , Sheng K 
Published: June 2015

Purpose:To develop and clinically implement 4π radiotherapy, an inverse optimization platform that maximally utilizes non‐coplanar intensity modulated radiotherapy (IMRT) beams to significantly improve critical organ sparing.Methods:A 3D scanner was used to digitize the human and phantom subject surfaces, which were positioned in the computer assisted design (CAD) model of a TrueBeam machine to create a virtual geometrical model, based on which, the feasible beam space was calculated for different tumor locations. Beamlets were computed for all feasible beams using convolution/superposition. A column generation algorithm was employed to optimize patient specific beam orientations and fluence maps. Optimal routing through all selected beams were calculated by a level set method. The resultant plans were converted to XML files and delivered to phantoms in the TrueBeam developer mode. Finally, 4π plans were recomputed in Eclipse and manually delivered to recurrent GBM patients.Results:Compared to IMRT utilizing manually selected beams and volumetric modulated arc therapy plans, markedly improved dosimetry was observed using 4π for the brain, head and neck, liver, lung, and prostate patients. The improvements were due to significantly improved conformality and reduced high dose spillage to organs mediolateral to the PTV. The virtual geometrical model was experimentally validated. Safety margins with 99.9% confidence in collision avoidance were included to the model based model accuracy estimates determined via 300 physical machine to phantom distance measurements. Automated delivery in the developer mode was completed in 10 minutes and collision free. Manual 4 π treatment on the GBM cases resulted in significant brainstem sparing and took 35–45 minutes including multiple images, which showed submillimeter cranial intrafractional motion.Conclusion:The mathematical modeling utilized in 4π is accurate to create and guide highly complex non‐coplanar IMRT treatments that consistently and significantly outperform human‐operator‐created plans. Deliverability of such plans is clinically demonstrated.This work is funded by Varian Medical Systems and the NSF Graduate Research Fellowship DGE‐1144087.
TU‐CD‐BRD‐00: Incident Learning / RO‐ILS
Authors: Ezzell Gary 
Published: June 2015

It has long been standard practice in radiation oncology to report internally when a patient's treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non‐punitive environment.There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include:

How to create a system that is easy for front line staff to access
How to motivate staff to report
How to promote the system as positive and educational and not punitive or demeaning
How to organize the team for reviewing and responding to reports
How to prioritize which reports to discuss in depth
How not to dismiss the rest
How to identify underlying causes
How to design corrective actions and implement change
How to develop useful statistics and analysis tools
How to coordinate a departmental system with a larger risk management system
How to do this without a dedicated quality manager
Some speakers’ experience is with in‐house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO‐ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown.There will be ample time set aside for audience members to contribute to the discussion.Learning Objectives:

Learn how to promote the use of an incident learning system in a clinic.
Learn how to convert “event reporting” into “incident learning”.
See examples of practice changes that have come out of learning systems.
Learn how the RO‐ILS system can be used as a primary internal learning system.
Learn how to create succinct, meaningful reports useful to outside readers.
Gary Ezzell chairs the AAPM committee overseeing RO‐ILS and has received an honorarium from ASTRO for working on the committee reviewing RO‐ILS reports.Derek Brown is a director of TreatSafely.org.Brett Miller has previously received travel expenses and an honorarium from Varian.Phillip Beron has nothing to report.
TU‐CD‐BRD‐03: UCSD Experience, with Focus On Implementing Change
Authors: Brown D. 
Published: June 2015

It has long been standard practice in radiation oncology to report internally when a patient's treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non‐punitive environment.There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include:

How to create a system that is easy for front line staff to access
How to motivate staff to report
How to promote the system as positive and educational and not punitive or demeaning
How to organize the team for reviewing and responding to reports
How to prioritize which reports to discuss in depth
How not to dismiss the rest
How to identify underlying causes
How to design corrective actions and implement change
How to develop useful statistics and analysis tools
How to coordinate a departmental system with a larger risk management system
How to do this without a dedicated quality manager
Some speakers’ experience is with in‐house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO‐ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown.There will be ample time set aside for audience members to contribute to the discussion.Learning Objectives:

Learn how to promote the use of an incident learning system in a clinic.
Learn how to convert “event reporting” into “incident learning”.
See examples of practice changes that have come out of learning systems.
Learn how the RO‐ILS system can be used as a primary internal learning system.
Learn how to create succinct, meaningful reports useful to outside readers.
Gary Ezzell chairs the AAPM committee overseeing RO‐ILS and has received an honorarium from ASTRO for working on the committee reviewing RO‐ILS reports.Derek Brown is a director of TreatSafely.org.Brett Miller has previously received travel expenses and an honorarium from Varian.Phillip Beron has nothing to report.