Quality Assurance In Radiation Oncology Research Articles

ACPSEM position paper: pre-treatment patient specific plan checks and quality assurance in radiation oncology.

The Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) has not previously made recommendations outlining the requirements for physics plan checks in Australia and New Zealand. A recent workforce modelling exercise, undertaken by the ACPSEM, revealed that the workload of a clinical radiation oncology medical physicist can comprise of up to 50% patient specific quality assurance activities. Therefore, in 2022 the ACPSEM Radiation Oncology Specialty Group (ROSG) set up a working group to address this issue. This position paper authored by ROSG endorses the recommendations of the American Association of Physicists in Medicine (AAPM) Task Group 218, 219 and 275 reports with some contextualisation for the Australia and New Zealand settings. A few recommendations from other sources are also endorsed to complete the position.

Provider perspectives on radiation oncology quality practices in peer review.

411 Background: Radiation oncology peer review involves presentation of new cases including pertinent patient history and case-specific qualitative treatment planning decisions. Yet implementation of peer recommendations is inconsistent. Thus, we sought to understand multidisciplinary perspectives on peer review to identify factors affecting stakeholder engagement. Methods: Participants in radiation oncology peer review completed semi-structured interviews and Likert surveys to explore the perceived value in peer review and its influence on their clinical practice and plan changes. Interviews were audio-recorded and transcribed, and two independent coders utilized a grounded theory approach to extract dominant themes. ANOVA and students t-test were used to analyze Likert scores. Results: Participants included 6 academic and 3 community radiation oncologists, 2 radiation oncology residents, 2 medical physicist, 2 radiation therapists, 4 dosimetrists and 1 industry representative. Analysis of interviews regarding perceived priorities of peer review revealed the following themes: understanding the clinical background to inform decision-making, detection of rare errors not found in other quality assurance processes, coherence in practice within an organization, and education on new techniques. Key facilitators included pre-planning communication between multidisciplinary teams, particularly for replanning and reirradiation scenarios. Barriers to adaptation of recommendations included resource limitations and lack of supporting data. Likert surveys (0=no importance, 10=highest importance) assigned a high value to the overall process (mean score: 8.3), reducing variation in practice (8.0), conformity of plans with institutional guidelines (7.8), and participant education (7.6), with a lower value placed on the detection of medical errors (7.4) and reduction of treatment incidents (6.9). When comparing Likert scores by provider, non-physicians rated overall importance of peer review (mean: 9.8 vs 6.5, p=0.03) and education (9.0 vs 6.7, p=0.02) significantly higher than physicians. There was no significant difference in Likert scores by academic vs community practice. Conclusions: All participants agreed peer review is an important process in radiation oncology quality assurance that may catch rare errors. However, there was significant variation in the perceived benefits of peer review, and a higher value was placed on alignment of clinical practice and non-physician participant education. Future processes to improve communication between multi-disciplinary teams was identified as beneficial to peer review discussions.

Feature Engineering for Interpretable Machine Learning for Quality Assurance in Radiation Oncology.

Chart checking is a time intensive process with high cognitive workload for physicists. Previous studies have partially automated and standardized chart checking, but limited studies implement data-driven approaches to reduce cognitive workload for quality assurance processes. This study aims to evaluate feature selection methods to improve the interpretability and transparency of machine learning models in predicting the degree of difficulty for a pretreatment physics chart check. We compare chi-square, mutual information, feature importance thresholding, and greedy feature selection for four different classifiers. Random forest has the highest performance with SMOTE oversampling using mutual information for feature selection (accuracy 84.0%, AUC 87.0%, precision 80.0%, recall 80.0%). This study demonstrates that feature selection methods can improve model interpretability and transparency.

Quality Assurance in Radiation Oncology: Addressing a Changing Treatment Landscape

Quality Assurance in Radiation Oncology: Addressing a Changing Treatment Landscape

Initial Experience Using Cherenkov Imaging in a Radiation Oncology Quality Assurance (QA) Program

Cherenkov imaging is a novel technique that captures light emissions during radiation therapy, allowing for visualization of radiation treatments on patients, in real-time. We hypothesized that simply viewing the Cherenkov video images, both in real-time and with post-treatment review by radiation therapists, would identify events not previously reported in the existing QA program.In December 2020, Cherenkov imaging cameras were introduced into an academic medical center with an existing QA program consisting of a hospital wide incident reporting system that is anonymous, voluntary, and non-punitive. Events are reviewed monthly by a multidisciplinary group including representatives from radiation therapy, dosimetry, nursing, physics and radiation oncologists. The Cherenkov cameras were installed in each treatment bunker, positioned laterally on each side of the couch. The cameras provided continuous, real-time video images of the patients and visualization of the irradiated tissue. Live viewing of the treatments was provided via a dedicated monitor in the console room. All treatments were imaged with the exception of treatments where optical surface imaging lights were on for SGRT.During this 3-month period, 12 events were reported in the hospital-based incident reporting system. Events were reviewed and categorized as 3 operational/process improvement (e.g., scheduling errors), 3 other safety events (e.g., patient falls), 3 treatment planning errors (e.g., wrong shifts calculated for setup), 1 prescription transcription error, 1 treatment delivery error (a missed treatment field), and 1 simulation error (suboptimal immobilization equipment used). Aside from a patient fall, all events were deemed to have no detectable harm to the patient. In this same time period, review of Cherenkov images identified 3 treatment delivery events, which were not identified by other means. The first was an AP-PA thoracic spine treatment and on one day, the treating therapists noted the patient's chin in the treatment field. Treatment was stopped, the patient was re-positioned for the remainder of the treatment. Second was an AP-PA lumbar spine field that on post-treatment review was noted that the patient's hands moved into the field. The third was a 3-field sacrum plan that on post-treatment review was noted that for 7 of 10 fractions, the patient's left arm was positioned over the exit RPO beam. Physics review estimated that the uninvolved arm received approximately 3 Gy.Viewing of Cherenkov emission imaging by the treatment team identified delivery incidents due to non-ideal patient positioning during treatment and these events were not identified in the existing QA program. Future work will focus on determining incident rates detected by Cherenkov imaging and if this imaging can identify and/or avoid treatment delivery errors from reaching the patient. Automated detection and near real time notification of such events is a work in progress.

Quality assurance in radiation oncology.

The Children's Oncology Group (COG) has a strong quality assurance (QA) program managed by the Imaging and Radiation Oncology Core (IROC). This program consists of credentialing centers and providing real-time management of each case for protocol compliant target definition and radiation delivery. In the International Society of Pediatric Oncology (SIOP), the lack of an available, reliable online data platform has been a challenge and the European Society for Paediatric Oncology (SIOPE) quality and excellence in radiotherapy and imaging for children and adolescents with cancer across Europe in clinical trials (QUARTET) program currently provides QA review for prospective clinical trials. The COG and SIOP are fully committed to a QA program that ensures uniform execution of protocol treatments and provides validity of the clinical data used for analysis.

Abstract IA-22: Automated treatment planning and quality assurance in radiation oncology

Abstract The delivery of radiation for the treatment of cancer is a complicated process that requires both clinical and technical expertise to ensure radiation treatments are safe and effective. Sub-optimal radiation treatments have the potential to result in significant detriment to the patient and several studies have shown radiation treatments, which deviate from established clinical guidelines, result in worse patient outcomes. Therefore, the current radiation treatment process requires substantial multi-disciplinary resources to both generate and verify radiation treatments are of high-quality. In this talk, a previously validated machine learning platform customized for radiation oncology will be presented. The method automatically learns based on data from thousands of previously treated patients which relationships and patterns in radiation oncology image and treatment data and has been applied for automated data mining activities, automated quality assurance to support expedited radiation treatment review, and for radiation dose prediction to develop new radiation treatments by best deciding where dose should be placed and how dose should be delivered without requiring any manual intervention. Therefore, the method can be used to both generate personalized radiation treatments and to quantitatively score radiation treatments for quality and classify radiation treatments that have errors. The automated platform can readily be integrated into current clinical process to improve efficiency in the radiation treatment planning and plan review processes and to better utilize the vast data we have to ensure we are providing patients with highly personalized radiation treatments. Citation Format: Thomas G. Purdie. Automated treatment planning and quality assurance in radiation oncology [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-22.

Graph-based risk assessment and error detection in radiation therapy.

The objective of this study was to formalize and automate quality assurance (QA) in radiation oncology. Quality assurance in radiation oncology entails a multistep verification of complex, personalized radiation plans to treat cancer involving an interdisciplinary team and high technology, multivendor software and hardware systems. We addressed the pretreatment physics chart review (TPCR) using methods from graph theory and constraint programming to study the effect of dependencies between variables and automatically identify logical inconsistencies and how they propagate. We used a modular approach to decompose the TPCR process into tractable units comprising subprocesses, modules and variables. Modules represented the main software entities comprised in the radiation treatment planning workflow and subprocesses grouped the checks to be performed by functionality. Module-associated variables served as inputs to the subprocesses. Relationships between variables were modeled by means of a directed graph. The detection of errors, in the form of inconsistencies, was formalized as a constraint satisfaction problem whereby checks were encoded as logical formulae. The sequence in which subprocesses were visited was described in an activity diagram. The comprehensive model for the TPCR process comprised 5 modules, 19 subprocesses and 346 variables, 225 of which were distinct. Modules included "Treatment Planning System" and "Record and Verify System." Subprocesses included "Dose Prescription," "Documents," "CT Integrity," "Anatomical Contours," "Beam Configuration," "Dose Calculation," "3D Dose Distribution Quality," and "Treatment Approval." Variable inconsistencies, and their source and propagation were determined by checking for constraint violation and through graph traversal. Impact scores, obtained through graph traversal, combined with severity scores associated with an inconsistency, allowed risk assessment. Directed graphs combined with constraint programming hold promise for formalizing complex QA processes in radiation oncology, performing risk assessment and automating the TPCR process. Though complex, the process is tractable.

Novel 3D polymer gel dosimeters based on N-(3-Methoxypropyl)acrylamide (NMPAGAT) for quality assurance in radiation oncology

New anoxic and normoxic polymer gel dosimeters containing different concentrations of N-(3-Methoxypropyl) acrylamide (NMPA) are introduced in this investigation for radiotherapy treatment planning dose validation. NMPA dosimeters were irradiated to 20 Gy using the 10 MV photon beam of a medical linear accelerator under a constant dose rate. The polymerization of NMPA dosimeters occurs and increases monotonically with increasing absorbed dose. Nuclear magnetic resonance (NMR) was used to investigate the degree of polymerization of gels. The dose response in terms of spin–spin relaxation rate (R2) of NMPA dosimeters increased with the addition of glycerol. The influence of the x-ray radiation energy, dose, and dose rate, as well as the stability of the irradiated NMPA gel dosimeters were studied in order to show this preliminary study is indicative of a promising low-toxicity polymer gel dosimeter.

Does Peer Review of Radiation Plans Affect Clinical Care? A Systematic Review of the Literature

Peer review is a recommended component of quality assurance in radiation oncology; however, it is resource-intensive and its effect on patient care is not well understood. We conducted a systematic review of the published data to assess the reported clinical impact of peer review on radiation treatment plans. A systematic review of published English studies was performed in accordance with the PRISMA guidelines using the MEDLINE and EMBASE databases and abstracts published from major radiation oncology scientific meeting proceedings. For inclusion, the studies were required to report the effect of peer review on ≥1 element of treatment planning (eg, target volume or organ-at-risk delineation, dose prescription or dosimetry). The initial search strategy identified 882 potentially eligible studies, with 11 meeting the inclusion criteria for full-text review and final analysis. Across a total of 11,491 patient cases, peer review programs led to modifications in a weighted mean of 10.8% of radiation treatment plans. Five studies differentiated between major and minor changes and reported weighted mean rates of change of 1.8% and 7.3%, respectively. The most common changes were related to target volume delineation (45.2% of changed plans), dose prescription or written directives (24.4%), and non-target volume delineation or normal tissue sparing (7.5%). Our findings suggest that peer review leads to changes in clinical care in approximately 1 of every 9 cases overall. This is similar to the reported rates of change in peer review studies from other oncology-related specialties, such as radiology and pathology.

WE‐A‐BRC‐01: Introduction to the Certificate Course

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk‐based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk‐based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomesD. Followill, NIH Grant CA180803

WE‐A‐BRC‐02: Lessons Learned: Clinical Trials and Operations

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk‐based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk‐based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomesD. Followill, NIH Grant CA180803

WE‐A‐BRC‐00: The Quality Gap

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk‐based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk‐based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomesD. Followill, NIH Grant CA180803

WE‐A‐BRC‐03: Lessons Learned: IROC Audits

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk‐based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk‐based assessments. Learning Objectives: Understand the impact of clinical and technical quality on outcomes Understand the importance of quality care in radiation oncology Learn to assess the impact of quality on clinical outcomesD. Followill, NIH Grant CA180803

SU-E-T-137: Evaluation of Linac Mechanical Systems Using Statistical Process Control

Purpose: Measuring the accuracy of the mechanical readouts on a linear accelerator is a staple of monthly quality assurance in Radiation Oncology. This study uses statistical quality control to determine if the current specifications and the frequency of the checks are reasonable. Methods: Statistical quality control looks at a set of data and determines the limits of the data. Changes can be made to the system with an eye toward improving the process. Previous measurements are used to determine the limits which are used to determine if the specifications are achievable or if they could be tightened.The study analyzed monthly mechanical data measured by several physicists on 5 linacs over several years. We looked at the difference between digital readout and measured value in gantry, collimator, and table angles, table motion, and jaw readout. Cp, Cpk, range limits and confidence limits were calculated. Results: Cp values were greater than 1 indicating each system was capable of performing within specification. Cpk values were also greater than 1 showing that each distribution was within specification. Each system showed raw results well within specification. Upper range limits for each system were well under the specifications. Upper and lower confidence limits were also within the specifications. There were no readings outside of specifications, however there were differences exceeding the range limits and the confidence levels. Conclusion: The general mechanical specifications set forth by manufacturers and national societies are easily achievable by modern linacs. The measurements and processes are able to be controlled. Range and control limits can be used to identify potential problems before they occur. Modern linacs can reliably and accurately display mechanical readouts well within specifications over long periods of time which may lead to a recommendation to decrease the frequency of mechanical measurements.

A Semiautomated Electronic System for Managing Physician Peer Review of Treatment Plans

Physician peer review of treatment plans is a cornerstone of quality assurance in Radiation Oncology. In large, high-volume centers, it is challenging to ensure that all cases are reviewed in a timely manner, results are tracked, and follow-up is completed when necessary. To achieve these goals at a large, multi-site (academic and community) Radiation Oncology department, an automated electronic system was developed that integrates into the clinical workflow, minimizes duplicate data entry, maintains structured records of patient chart review, and conforms to the requirements of patient privacy and confidentiality of peer review.

SU‐D‐214‐02: Quality Assurance Tool for Radiation Therapy Patients: Peer Review System Design and Implementation

Purpose: To demonstrate the efficacy of a peer review system (PRS) for remote quality assurance in radiation oncology. The PRS is a Web‐based system which allows radiation oncologists to share anonymous treatment plans (imaging, structure sets, and dose distributions) with peer reviewers for their feedback. Methods: We have developed a DICOM‐RT compliant PRS that can store patient images and treatment planning data. The PRS infrastructure consisting of three components: Gateway, Web Server and Web Viewer, which is developed with current Web technology, utilizing .NET framework and Silverlight plug‐in for web interface. The patient data can be visualized through a Web browser and distributed across multiple locations by the local area network and the Internet. The submitter uses the Gateway to anomymize patient data, chooses a reviewer from the master list, adds annotations and messages and submits patient data for review via the PRS Web Server. Upon receiving the data from the submitter, the reviewer is notified via email and prompted to review the submitted treatment plan from the Web Viewer simply by clicking on the embedded URL. The PRS Web Server has built‐in functionality to keep track of reviewer comments communication between submitter and reviewers. Results: The system was evaluated at two facilities with different treatment planning systems (Varian Eclipse v.8.9 and Philips Pinnacle v.9.0). The CT images and related DICOM‐RT objects for several different patients from each facility were successfully submitted and reviewed using the prototype PRS. Conclusions: The PRS has been successfully pilot‐tested for remote peer‐review of treatment planning data. The PRS allows radiation oncology service providers access to treatment planning data from any location and an ability to review it in an interactive and collaborative manner. The broader implementation of the PRS in clinical settings will improve the quality and safety of radiation therapy.

Technical aspects of quality assurance in radiation oncology

The technical aspects of quality assurance (QA) in radiation oncology as practice in the United States will be reviewed and updated in the spirit of offering the experience to the radiation oncology communities in the Asia-Pacific region. The word “technical” is used to express the organisational components or processes and not the materials within the QA program. A comprehensive QA program in radiation oncology will have an official statement declaring the quality plan for effective patient care services it provides in a document. The QA program will include all aspects of patient care: physical, clinical, and medical aspects of the services. The document will describe the organisational structure, responsibilities, checks and procedures, and resources allocated to ensure the successful implementation of the quality of patient management. Regulatory guidelines and guidelines from accreditation agencies should be incorporated in the QA program to ensure compliance. The organisational structure will have a multidisciplinary QA committee that has the authority to evaluate continuously the effectiveness of the QA program to provide prompt corrective recommendations and to request feedback as needed to monitor the response. The continuous monitoring aspects require meetings to be held at regular intervals with the minutes of the meetings officially recorded and documented. To ensure that a QA program is effective, the program itself should be audited for quality at regular intervals at least annually. It has been recognised that the current QA program has not kept abreast with the rapid implementation of new and advanced radiation therapy technologies with the most recent in image-based radiation therapy technology. The societal bodies (ASTRO and AAPM) and federal agency (NCI) acknowledge this inadequacy and have held workshops to address this issue. The challenges for the societal bodies and federal agency are numerous that include (a) the prescriptive methodology used may not be appropriate for currently implemented new technologies, (b) resources are becoming scarce, (c) advanced radiation therapy technologies have been introduced too rapidly, (d) advances in radiation therapy technologies have become too sophisticated and specialised with each therapy modality having its own separate set of equipment, for example its own dose planning software, computer system and dose delivery systems requiring individualised QA procedures. At the present time, industrial engineers are being recruited to assist in devising a methodology that is broad-based and more process-oriented risk-based formulation of QA in radiation oncology.

206 Quality assurance in radiation oncology: Validation of methods and monitoring process to reduce errors and dysfunctions (quaraton)

206 Quality assurance in radiation oncology: Validation of methods and monitoring process to reduce errors and dysfunctions (quaraton)

Quality Assurance in Radiation Oncology

Assuring quality in the practice of radiation oncology has become increasingly important because of the greater complexity of treatments and the advancing knowledge of the diseases that are treated. Increased public attention to errors in medicine, the increasing use of new imaging modalities to plan therapy, the availability of new therapeutic techniques such as intensity-modulated radiation therapy, and greater dependence on information technology have increased the need for intense quality assurance (QA) in the specialty. The process of QA and the resources available to radiation oncology staff members are described.