Process-based quality management for clinical implementation of adaptive radiotherapy

Optimization of treatment workflow for 0.35T MR-Linac system

PURPOSE

This study presents a novel and comprehensive framework for evaluating magnetic resonance guided radiotherapy (MRgRT) workflow by integrating the Failure Modes and Effects Analysis (FMEA) approach with Time-Driven Activity-Based Costing (TDABC). We assess the workflow for safety, quality, and economic implications, providing a holistic understanding of the MRgRT implementation. The aim is to offer valuable insights to healthcare practitioners and administrators, facilitating informed decision-making regarding the 0.35T MRIdian MR-Linac system's clinical workflow.

METHODS

For FMEA, a multidisciplinary team followed the TG-100 methodology to assess the MRgRT workflow's potential failure modes. Following the mitigation of primary failure modes and workflow optimization, a treatment process was established for TDABC analysis. The TDABC was applied to both MRgRT and computed tomography guided RT (CTgRT) for typical five-fraction stereotactic body RT (SBRT) treatments, assessing total workflow and costs associated between the two treatment workflows.

RESULTS

A total of 279 failure modes were identified, with 31 categorized as high-risk, 55 as medium-risk, and the rest as low-risk. The top 20% risk priority numbers (RPN) were determined for each radiation oncology care team member. Total MRgRT and CTgRT costs were assessed. Implementing technological advancements, such as real-time multi leaf collimator (MLC) tracking with volumetric modulated arc therapy (VMAT), auto-segmentation, and increasing the Linac dose rate, led to significant cost savings for MRgRT.

CONCLUSION

In this study, we integrated FMEA with TDABC to comprehensively evaluate the workflow and the associated costs of MRgRT compared to conventional CTgRT for five-fraction SBRT treatments. FMEA analysis identified critical failure modes, offering insights to enhance patient safety. TDABC analysis revealed that while MRgRT provides unique advantages, it may involve higher costs. Our findings underscore the importance of exploring cost-effective strategies and key technological advancements to ensure the widespread adoption and financial sustainability of MRgRT in clinical practice.

NRG Oncology Assessment of Artificial Intelligence Deep Learning-Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions

Deep learning neural networks (DLNN) in Artificial intelligence (AI) have been extensively explored for automatic segmentation in radiotherapy (RT). In contrast to traditional model-based methods, data-driven AI-based models for auto-segmentation have shown high accuracy in early studies in research settings and controlled environment (single institution). Vendor-provided commercial AI models are made available as part of the integrated treatment planning system (TPS) or as a stand-alone tool that provides streamlined workflow interacting with the main TPS. These commercial tools have drawn clinics' attention thanks to their significant benefit in reducing the workload from manual contouring and shortening the duration of treatment planning. However, challenges occur when applying these commercial AI-based segmentation models to diverse clinical scenarios, particularly in uncontrolled environments. Contouring nomenclature and guideline standardization has been the main task undertaken by the NRG Oncology. AI auto-segmentation holds the potential clinical trial participants to reduce interobserver variations, nomenclature non-compliance, and contouring guideline deviations. Meanwhile, trial reviewers could use AI tools to verify contour accuracy and compliance of those submitted datasets. In recognizing the growing clinical utilization and potential of these commercial AI auto-segmentation tools, NRG Oncology has formed a working group to evaluate the clinical utilization and potential of commercial AI auto-segmentation tools. The group will assess in-house and commercially available AI models, evaluation metrics, clinical challenges, and limitations, as well as future developments in addressing these challenges. General recommendations are made in terms of the implementation of these commercial AI models, as well as precautions in recognizing the challenges and limitations.

Technical note: A universal worksheet for failure mode and effects analysis-A project of the Japanese College of Medical Physics

BACKGROUND

Failure mode and effects analysis (FMEA), which is an effective tool for error prevention, has garnered considerable attention in radiotherapy. FMEA can be performed individually, by a group or committee, and online.

PURPOSE

To meet the needs of FMEA for various purposes and improve its accessibility, we developed a simple, self-contained, and versatile web-based FMEA risk analysis worksheet.

METHODS

We developed an FMEA worksheet using Google products, such as Google Sheets, Google Forms, and Google Apps Script. The main sheet was created in Google Sheets and contained elements necessary for performing FMEA by a single person. Automated tasks were implemented using Apps Script to facilitate multiperson FMEA; these functions were built into buttons located on the main sheet.

RESULTS

The usability of the FMEA worksheet was tested in several situations. The worksheet was feasible for individual, multiperson, seminar, meeting, and online purposes. Simultaneous online editing, automated survey form creation, automatic analysis, and the ability to respond to the form from multiple devices, including mobile phones, were particularly useful for online and multiperson FMEA. Automation enabled through Google Apps Script reduced the FMEA workload.

CONCLUSIONS

The FMEA worksheet is versatile and has a seamless workflow that promotes collaborative work for safety.

A structured FMEA approach to optimizing combinations of plan-specific quality assurance techniques for IMRT and VMAT QA

BACKGROUND

Many commercial tools are available for plan-specific quality assurance (QA) of radiotherapy plans, with their functionality assessed in isolation. However, multiple QA tools are required to review the full range of potential errors. It is important to assess their effectiveness in combination with each other to look for ways to both streamline the QA process and to make certain that errors of high impact and/or high occurrence are caught before reaching patient treatment.

PURPOSE

To develop a structured method to assess the effective risk reduction of combinations of QA methods for IMRT/VMAT treatments.

METHODS

First, a structured prospective risk assessment was performed to establish the major failure modes (FMs) of IMRT/VMAT QA, and assign occurrence (O), severity (S), and baseline detectability (BD) rankings to them. The baseline assumed that chart checks and linear accelerator QA was performed, but no plan-specific secondary dose calculation or measurement was done. Second, the detectability of each FM for two secondary dose calculation methods and four plan measurement methods (point-based dose calculation, Monte-Carlo-based dose calculation, 2D fluence-based measurement, 2.5D phantom-based measurement, log file analysis with dose recalculation, and log file analysis combined with MLC QA) was determined. Third, we used a minimum detectability approach in addition to each FM's occurrence and severity to determine the optimal combination of QA methods. We analyzed the cumulative risk priority number of eight combinations of QA methods. The analysis was done on (1) all FMs, (2) FMs with high severity, (3) FMs with high-risk priority numbers (RPN) of O*S*BD, and (4) on FMs with both high severity and high RPN.

RESULTS

Our analysis resulted in 54 FMs, including commissioning, planning, data transfer, and linear accelerator failures. 1D secondary dose calculation plus measurement provided a 19%-22% risk reduction from baseline. 1D/3D secondary dose calculation plus log files created a 25%-32% reduction. 3D secondary dose calculation plus measurement resulted in a 27%-34% reduction. 3D secondary dose calculation plus log files with additional machine QA provided the greatest reduction of 31%-42%.

CONCLUSION

This novel structured approach to comparing combinations of QA methods will allow us to optimize our procedures, with the goal of detecting all clinically significant FMs. Our results show that log-file QA with 3D dose recalculation and supplemental machine QA provides better risk reduction than measurement-based QA. This work builds evidence to justify reducing or eliminating measurement-based PSQA with an independent 3D dose verification, log-file measurement, and appropriate supplementation of machine QA. The process also highlights FMs that cannot be caught by pre-treatment QA, prompting us to consider future directions for on-treatment QA.

Online adaptive radiotherapy and dose delivery accuracy: A retrospective analysis

PURPOSE

With online adaptive radiotherapy (ART), patient-specific quality assurance (PSQA) testing cannot be performed prior to delivery of the adapted treatment plan. Consequently, the dose delivery accuracy of adapted plans (i.e., the ability of the system to interpret and deliver the treatment as planned) are not initially verified. We investigated the variation in dose delivery accuracy of ART on the MRIdian 0.35 T MR-linac (Viewray Inc., Oakwood, USA) between initial plans and their respective adapted plans, by analyzing PSQA results.

METHODS

We considered the two main digestive localizations treated with ART (liver and pancreas). A total of 124 PSQA results acquired with the ArcCHECK (Sun Nuclear Corporation, Melbourne, USA) multidetector system were analyzed. PSQA result variations between the initial plans and their respective adapted plans were statistically investigated and compared with the variation in MU number.

RESULTS

For the liver, limited deterioration in PSQA results was observed, and was within the limits of clinical tolerance (Initial = 98.2%, Adapted = 98.2%, p = 0.4503). For pancreas plans, only a few significant deteriorations extending beyond the limits of clinical tolerance were observed and were due to specific, complex anatomical configurations (Initial = 97.3%, Adapted = 96.5%, p = 0.0721). In parallel, we observed an influence of the increase in MU number on the PSQA results.

CONCLUSION

We show that the dose delivery accuracy of adapted plans, in terms of PSQA results, is preserved in ART processes on the 0.35 T MR-linac. Respecting good practices, and minimizing the increase in MU number can help to preserve the accuracy of delivery of adapted plans as compared to their respective initial plans.

Determining the quality control frequency of an MR-linac using risk matrix (RM) analysis

PURPOSE

Quality control (QC) is performed routinely through professional guidelines. However, the recommended QC frequency may not be optimal among different institutional settings. Here we propose a novel method for determining the optimal QC frequency using risk matrix (RM) analysis.

METHODS AND MATERIALS

A newly installed Magnetic Resonance linac (MR-linac) was chosen as the testing platform and six routine QC items were investigated. Failures of these QC items can adversely affect treatment outcome for the patient. Accordingly, each QC item with its assigned frequency forms a unique failure mode (FM). Using FM-effect analysis (FMEA), the severity (S), occurrence (O), and detection (D) of each FM was obtained. Next, S and D based on RM was used to determine the appropriate QC frequency. Finally, the performance of new frequency for each QC item was evaluated using the metric E = O/D.

RESULTS

One new QC frequency was the same as the old frequency, two new QC frequencies were less than the old ones, and three new QC frequencies were higher than the old ones. For six QC items, E values at the new frequencies were not less than their values at the old frequencies. This indicates that the risk of machine failure is reduced at the new QC frequencies.

CONCLUSIONS

The application of RM analysis provides a useful tool for determining the optimal frequencies for routine linac QC. This study demonstrated that linac QC can be performed in a way that maintains high performance of the treatment machine in a radiotherapy clinic.

Prospective risk analysis of the online-adaptive artificial intelligence-driven workflow using the Ethos treatment system

PURPOSE

The recently introduced Varian Ethos system allows adjusting radiotherapy treatment plans to anatomical changes on a daily basis. The system uses artificial intelligence to speed up the process of creating adapted plans, comes with its own software solutions and requires a substantially different workflow. A detailed analysis of possible risks of the associated workflow is presented.

METHODS

A prospective risk analysis of the adaptive workflow with the Ethos system was performed using Failure Modes and Effects Analysis (FMEA). An interprofessional team collected possible adverse events and evaluated their severity as well as their chance of occurrence and detectability. Measures to reduce the risks were discussed.

RESULTS

A total of 122 events were identified, and scored. Within the 20 events with the highest-ranked risks, the following were identified: Challenges due to the stand-alone software solution with very limited connectivity to the existing record and verify software and digital patient file, unfamiliarity with the new software and its limitations and the adaption process relying on results obtained by artificial intelligence. The risk analysis led to the implementation of additional quality assurance measures in the workflow.

CONCLUSIONS

The thorough analysis of the risks associated with the new treatment technique was the basis for designing details of the workflow. The analysis also revealed challenges to be addressed by both, the vendor and customers. On the vendor side, this includes improving communication between their different software solutions. On the customer side, this especially includes establishing validation strategies to monitor the results of the black box adaption process making use of artificial intelligence.

Clinical commissioning of an adaptive radiotherapy platform: Results and recommendations

Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end-to-end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on-treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone-beam computed tomography (CT)-based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end-to-end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms.

Identifying risk characteristics using failure mode and effect analysis for risk management in online magnetic resonance-guided adaptive radiation therapy

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Failure mode and effect analysis with process map revealed risks.

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High-risk failure modes and their corrective measures were identified.

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Hazardous processes and characteristics of the treatment were identified.

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All failure modes including those identified in previous papers were summarized and compared.

Background and purpose

Materials and methods

Results

Conclusion

ESTRO-ACROP recommendations on the clinical implementation of hybrid MR-linac systems in radiation oncology

Online magnetic resonance-guided radiotherapy (oMRgRT) represents one of the most innovative applications of current image-guided radiation therapy (IGRT). The revolutionary concept of oMRgRT systems is the ability to acquire MR images for adaptive treatment planning and also online imaging during treatment delivery. The daily adaptive planning strategies allow to improve targeting accuracy while avoiding critical structures. This ESTRO-ACROP recommendation aims to provide an overview of available systems and guidance for best practice in the implementation phase of hybrid MR-linac systems. Unlike the implementation of other radiotherapy techniques, oMRgRT adds the MR environment to the daily practice of radiotherapy, which might be a new experience for many centers. New issues and challenges that need to be thoroughly explored before starting clinical treatments will be highlighted.

A practical implementation of risk management for the clinical introduction of online adaptive Magnetic Resonance-guided radiotherapy

Background and Purpose

The clinical introduction of on-table adaptive radiotherapy with Magnetic Resonance (MR)-guided linear accelerators (Linacs) yields new challenges and potential risks. Since the adapted plan is created within a highly interdisciplinary workflow with the patient in treatment position, time pressure or erroneous communication may lead to various possibly hazardous situations. To identify risks and implement a safe workflow, a proactive risk analysis has been conducted.

Materials and Methods

A process failure mode, effects and criticality analysis (P-FMECA) was performed within a group of radiation therapy technologists, physicians and physicists together with an external moderator. The workflow for on-table adaptive MR-guided treatments was defined and for each step potentially hazardous situations were identified. The risks were evaluated within the team in order to homogenize risk assessment. The team elaborated and discussed possible mitigation strategies and carried out their implementation.

Results

In total, 89 risks were identified for the entire MR-guided online adaptive workflow. After mitigation, all risks could be minimized to an acceptable level. Overall, the need for a standardized workflow, clear-defined protocols together with the need for checklists to ensure protocol adherence were identified among the most important mitigation measures. Moreover, additional quality assurance processes and automated plan checks were developed.

Conclusions

Despite additional workload and beyond the fulfilment of legal requirements, execution of the P-FMECA within an interdisciplinary team helped all involved occupational groups to develop and foster an open culture of safety and to ensure a consensus for an efficient and safe online adaptive radiotherapy workflow.

Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology

The integration of adaptive radiation therapy (ART), or modifying the treatment plan during the treatment course, is becoming more widely available in clinical practice. ART offers strong potential for minimizing treatment-related toxicity while escalating or de-escalating target doses based on the dose to organs at risk. Yet, ART workflows add complexity into the radiation therapy planning and delivery process that may introduce additional uncertainties. This work sought to review presently available ART workflows and technological considerations such as image quality, deformable image registration, and dose accumulation. Quality assurance considerations for ART components and minimum recommendations are described. Personnel and workflow efficiency recommendations are provided, as is a summary of currently available clinical evidence supporting the implementation of ART. Finally, to guide future clinical trial protocols, an example ART physician directive and a physics template following standard NRG Oncology protocol is provided.

X-Ray Beam Segment Size and Entrance Location Effects on the Integral Quality Monitor (IQM®) Signal and Usefulness in Predicting Complex Segment Output Signals

Background:

The Integral Quality Monitor (IQM®) is an independent online dosimetry device attached to the treatment machine to monitor the accuracy of radiation delivery.

Objective:

This study investigates the influence of beam segment size and displacement as projected onto the IQM chamber on the signals and determine how individual signals can be added to get a combined segment signal made up of smaller segments.

Material and Methods:

This is an experimental original research type of study. IQM response maps were generated by irradiating the IQM sensitive area with small elementary segments and measuring their corresponding signals per monitor unit (MU). The output signal/MU was measured for regular and irregular fields and compared with the predicted signal/MU obtained from decomposing the open segment into a set of smaller regular segments and summing their signals from their respective response maps. The dependence of signals on segment size, shape, location and combination was investigated.

Results:

Predicted signals were calculated within 95-98 % accuracy for regular fields and 90-98% for irregular fields. More uniform fluence contain distribution for larger segments was observed. Response maps were consistent with the geometrical symmetry in the chamber’s wedge shape and the symmetry in the linac fluence.

Conclusion:

The field decomposition method allows the pre-calculation of known segment output signals per MU within 2% error, although the accuracy drops significantly for smaller, irregular fields. A method of correcting predicted signals in smaller segments needs to be laid down to get a better match with measured signals.

Failure mode and effects analysis for proactive healthcare risk evaluation: A systematic literature review

RATIONALE, AIMS, AND OBJECTIVES

Failure mode and effects analysis (FMEA) is a valuable reliability management tool that can preemptively identify the potential failures of a system and assess their causes and effects, thereby preventing them from occurring. The use of FMEA in the healthcare setting has become increasingly popular over the last decade, being applied to a multitude of different areas. The objective of this study is to review comprehensively the literature regarding the application of FMEA for healthcare risk analysis.

METHODS

An extensive search was carried out in the scholarly databases of Scopus and PubMed, and we only chose the academic articles which used the FMEA technique to solve healthcare risk analysis problems. Furthermore, a bibliometric analysis was performed based on the number of citations, publication year, appeared journals, authors, and country of origin.

RESULTS

A total of 158 journal papers published over the period of 1998 to 2018 were extracted and reviewed. These publications were classified into four categories (ie, healthcare process, hospital management, hospital informatization, and medical equipment and production) according to the healthcare issues to be solved, and analyzed regarding the application fields and the utilized FMEA methods.

CONCLUSION

FMEA has high practicality for healthcare quality improvement and error reduction and has been prevalently employed to improve healthcare processes in hospitals. This research supports academics and practitioners in effectively adopting the FMEA tool to proactively reduce healthcare risks and increase patient safety, and provides an insight into its state-of-the-art.

Implementing a Novel Remote Physician Treatment Coverage Practice for Adaptive Radiation Therapy During the Coronavirus Pandemic

PURPOSE

The 2019 coronavirus disease pandemic has placed an increased importance on physical distancing to minimize the risk of transmission in radiation oncology departments. The pandemic has also increased the use of hypofractionated treatment schedules where magnetic resonance-guided online adaptive radiation therapy (ART) can aid in dose escalation. This specialized technique requires increased staffing in close proximity, and thus the need for novel coverage practices to increase physical distancing while still providing specialty care.

METHODS AND MATERIALS

A remote-physician ART coverage practice was developed and described using commercially available software products. Our remote-physician coverage practice provided control to the physician to contour and review of the images and plans. The time from completion of image registration to the beginning of treatment was recorded for 20 fractions before remote-physician ART coverage and 14 fractions after implementation of remote-physician ART coverage. Visual quality was calculated using cross-correlation between the treatment delivery and remote-physician computer screens.

RESULTS

For the 14 fractions after implementation, the average time from image registration to the beginning of treatment was 24.9 ± 6.1 minutes. In comparison, the 20 fractions analyzed without remote coverage had an average time of 29.2 ± 9.8 minutes. The correlation between the console and remote-physician screens was R = .95.

CONCLUSIONS

Our novel remote-physician ART coverage practice is secure, interactive, timely, and of high visual quality. When using remote physicians for ART, our department was able to increase physical distancing to lower the risk of virus transmission while providing specialty care to patients in need.

Online daily adaptive proton therapy

It is recognized that the use of a single plan calculated on an image acquired some time before the treatment is generally insufficient to accurately represent the daily dose to the target and to the organs at risk. This is particularly true for protons, due to the physical finite range. Although this characteristic enables the generation of steep dose gradients, which is essential for highly conformal radiotherapy, it also tightens the dependency of the delivered dose to the range accuracy. In particular, the use of an outdated patient anatomy is one of the most significant sources of range inaccuracy, thus affecting the quality of the planned dose distribution. A plan should be ideally adapted as soon as anatomical variations occur, ideally online. In this review, we describe in detail the different steps of the adaptive workflow and discuss the challenges and corresponding state-of-the art developments in particular for an online adaptive strategy.

Practical Clinical Workflows for Online and Offline Adaptive Radiation Therapy

Adaptive radiotherapy emerged over 20 years ago and is now an established clinical practice in a number of organ sites. No one solution for adaptive therapy exists. Rather, adaptive radiotherapy is a process which combines multiple tools for imaging, assessment of need for adaptation, treatment planning, and quality assurance of this process. Workflow is therefore a critical aspect to ensure safe, effective, and efficient implementation of adaptive radiotherapy. In this work, we discuss the tools for online and offline adaptive radiotherapy and introduce workflow concepts for these types of adaptive radiotherapy. Common themes and differences between the workflows are introduced and controversies and areas of active research are discussed.

A practical implementation of physics quality assurance for photon adaptive radiotherapy

The fast evolution of technology in radiotherapy (RT) enabled the realization of adaptive radiotherapy (ART). However, the new characteristics of ART pose unique challenges for efficiencies and effectiveness of quality assurance (QA) strategies. In this paper, we discuss the necessary QAs for ART and introduce a practical implementation. A previously published work on failure modes and effects analysis (FMEA) of ART is introduced first to explain the risks associated with ART sub-processes. After a brief discussion of QA challenges, we review the existing QA strategies and tools that might be suitable for each ART step. By introducing the MR-guided online ART QA processes developed at our institute, we demonstrate a practical implementation. The limitations and future works to develop more robust and efficient QA strategies are discussed at the end.

Status and Perception of Risk Management in Radiation Therapy: Survey Among Korean Medical Physicists

This study was conducted as part of an endeavor to improve the risk management system of radiation therapy departments in the Republic of Korea. An online survey on the status and perception of Korea's medical physicists on risk management in radiation therapy was carried out. A total of 40 domestic radiation oncology departments participated. This survey is divided into three categories: (1) work environment; (2) risk management status; and (3) opinions on how to improve risk management. Based on the results of the survey, the conclusions that can be derived are (1) the majority of respondents have a high interest in the risk management of radiation therapy; (2) the lack of staffing is one cause of risk management difficulties; (3) a risk-related terminology and classification system at the national or professional association level are required; (4) each hospital should create a voluntary reporting system for the handling of incidents; (5) medical physicists should establish incident reporting, analysis and countermeasures; and (6) government should develop education and training programs. It was confirmed that the current risk management system should be changed by education in the hospital and at the national level in order to improve risk management related to radiation therapy. In addition, it was recognized that a dedicated staff and a risk management certification system and organization for patient safety in radiotherapy are needed.

FMEA of manual and automated methods for commissioning a radiotherapy treatment planning system

PURPOSE

To evaluate the level of risk involved in treatment planning system (TPS) commissioning using a manual test procedure, and to compare the associated process-based risk to that of an automated commissioning process (ACP) by performing an in-depth failure modes and effects analysis (FMEA).

METHODS

The authors collaborated to determine the potential failure modes of the TPS commissioning process using (a) approaches involving manual data measurement, modeling, and validation tests and (b) an automated process utilizing application programming interface (API) scripting, preloaded, and premodeled standard radiation beam data, digital heterogeneous phantom, and an automated commissioning test suite (ACTS). The severity (S), occurrence (O), and detectability (D) were scored for each failure mode and the risk priority numbers (RPN) were derived based on TG-100 scale. Failure modes were then analyzed and ranked based on RPN. The total number of failure modes, RPN scores and the top 10 failure modes with highest risk were described and cross-compared between the two approaches. RPN reduction analysis is also presented and used as another quantifiable metric to evaluate the proposed approach.

RESULTS

The FMEA of a MTP resulted in 47 failure modes with an RPN_ave of 161 and S_ave of 6.7. The highest risk process of "Measurement Equipment Selection" resulted in an RPN_max of 640. The FMEA of an ACP resulted in 36 failure modes with an RPN_ave of 73 and S_ave of 6.7. The highest risk process of "EPID Calibration" resulted in an RPN_max of 576.

CONCLUSIONS

An FMEA of treatment planning commissioning tests using automation and standardization via API scripting, preloaded, and pre-modeled standard beam data, and digital phantoms suggests that errors and risks may be reduced through the use of an ACP.

Evaluating the application of failure mode and effects analysis technique in hospital wards: a systematic review

Background:

Medical errors are one of the greatest problems in any healthcare systems. The best way to prevent such problems is errors identification and their roots. Failure Mode and Effects Analysis (FMEA) technique is a prospective risk analysis method. This study is a review of risk analysis using FMEA technique in different hospital wards and departments.

Methods:

This paper has systematically investigated the available databases. After selecting inclusion and exclusion criteria, the related studies were found. This selection was made in two steps. First, the abstracts and titles were investigated by the researchers and, after omitting papers which did not meet the inclusion criteria, 22 papers were finally selected and the text was thoroughly examined. At the end, the results were obtained.

Results:

The examined papers had focused mostly on the process and had been conducted in the pediatric wards and radiology departments, and most participants were nursing staffs. Many of these papers attempted to express almost all the steps of model implementation; and after implementing the strategies and interventions, the Risk Priority Number (RPN) was calculated to determine the degree of the technique’s effect. However, these papers have paid less attention to the identification of risk effects.

Conclusions:

The study revealed that a small number of studies had failed to show the FMEA technique effects. In general, however, most of the studies recommended this technique and had considered it a useful and efficient method in reducing the number of risks and improving service quality.

Characterization and evaluation of an integrated quality monitoring system for online quality assurance of external beam radiation therapy

Purpose

The aim of this work was to comprehensively evaluate a new large field ion chamber transmission detector, Integral Quality Monitor (IQM), for online external photon beam verification and quality assurance. The device is designed to be mounted on the linac accessory tray to measure and verify photon energy, field shape, gantry position, and fluence before and during patient treatment.

Methods

Our institution evaluated the newly developed ion chamber's effect on photon beam fluence, response to dose, detection of photon fluence modification, and the accuracy of the integrated barometer, thermometer, and inclinometer. The detection of photon fluence modifications was performed by measuring 6 MV with fields of 10 cm × 10 cm and 1 cm × 1 cm “correct” beam, and then altering the beam modifiers to simulate minor and major delivery deviations. The type and magnitude of the deviations selected for evaluation were based on the specifications for photon output and MLC position reported in AAPM Task Group Report 142. Additionally, the change in ion chamber signal caused by a simulated IMRT delivery error is evaluated.

Results

The device attenuated 6 MV, 10 MV, and 15 MV photon beams by 5.43 ± 0.02%, 4.60 ± 0.02%, and 4.21 ± 0.03%, respectively. Photon beam profiles were altered with the IQM by < 1.5% in the nonpenumbra regions of the beams. The photon beam profile for a 1 cm × 1 cm² fields were unchanged by the presence of the device. The large area ion chamber measurements were reproducible on the same day with a 0.14% standard deviation and stable over 4 weeks with a 0.47% SD. The ion chamber's dose–response was linear (R² = 0.99999). The integrated thermometer agreed to a calibrated thermometer to within 1.0 ± 0.7°C. The integrated barometer agreed to a mercury barometer to within 2.3 ± 0.4 mmHg. The integrated inclinometer gantry angle measurement agreed with the spirit level at 0 and 180 degrees within 0.03 ± 0.01 degrees and 0.27 ± 0.03 at 90 and 270 degrees. For the collimator angle measurement, the IQM inclinometer agreed with a plum‐bob within 0.3 ± 0.2 degrees. The simulated IMRT error increased the ion chamber signal by a factor of 11–238 times the baseline measurement for each segment.

Conclusions

The device signal was dependent on variations in MU delivered, field position, single MLC leaf position, and nominal photon energy for both the 1 cm × 1 cm and 10 cm × 10 cm fields. This detector has demonstrated utility repeated photon beam measurement, including in IMRT and small field applications.

Failure mode and effects analysis based risk profile assessment for stereotactic radiosurgery programs at three cancer centers in Brazil

PURPOSE

The goal of this study was to evaluate the safety and quality management program for stereotactic radiosurgery (SRS) treatment processes at three radiotherapy centers in Brazil by using three industrial engineering tools (1) process mapping, (2) failure modes and effects analysis (FMEA), and (3) fault tree analysis.

METHODS

The recommendations of Task Group 100 of American Association of Physicists in Medicine were followed to apply the three tools described above to create a process tree for SRS procedure for each radiotherapy center and then FMEA was performed. Failure modes were identified for all process steps and values of risk priority number (RPN) were calculated from O, S, and D (RPN = O × S × D) values assigned by a professional team responsible for patient care.

RESULTS

The subprocess treatment planning was presented with the highest number of failure modes for all centers. The total number of failure modes were 135, 104, and 131 for centers I, II, and III, respectively. The highest RPN value for each center is as follows: center I (204), center II (372), and center III (370). Failure modes with RPN ≥ 100: center I (22), center II (115), and center III (110). Failure modes characterized by S ≥ 7, represented 68% of the failure modes for center III, 62% for center II, and 45% for center I. Failure modes with RPNs values ≥100 and S ≥ 7, D ≥ 5, and O ≥ 5 were considered as high priority in this study.

CONCLUSIONS

The results of the present study show that the safety risk profiles for the same stereotactic radiotherapy process are different at three radiotherapy centers in Brazil. Although this is the same treatment process, this present study showed that the risk priority is different and it will lead to implementation of different safety interventions among the centers. Therefore, the current practice of applying universal device-centric QA is not adequate to address all possible failures in clinical processes at different radiotherapy centers. Integrated approaches to device-centric and process specific quality management program specific to each radiotherapy center are the key to a safe quality management program.

Process improvement for the safe delivery of multidisciplinary-executed treatments-A case in Y-90 microspheres therapy

PURPOSE

To develop a safe and robust workflow for yttrium-90 (Y-90) radioembolization procedures in a multidisciplinary team environment.

METHODS AND MATERIALS

A generalized Define-Measure-Analyze-Improve-Control (DMAIC)-based approach to process improvement was applied to a Y-90 radioembolization workflow. In the first DMAIC cycle, events with the Y-90 workflow were defined and analyzed. To improve the workflow, a web-based interactive electronic white board (EWB) system was adopted as the central communication platform and information processing hub. The EWB-based Y-90 workflow then underwent a second DMAIC cycle. Out of 245 treatments, three misses that went undetected until treatment initiation were recorded over a period of 21 months, and root-cause-analysis was performed to determine causes of each incident and opportunities for improvement. The EWB-based Y-90 process was further improved via new rules to define reliable sources of information as inputs into the planning process, as well as new check points to ensure this information was communicated correctly throughout the process flow.

RESULTS

After implementation of the revised EWB-based Y-90 workflow, after two DMAIC-like cycles, there were zero misses out of 153 patient treatments in 1 year.

CONCLUSIONS

The DMAIC-based approach adopted here allowed the iterative development of a robust workflow to achieve an adaptable, event-minimizing planning process despite a complex setting which requires the participation of multiple teams for Y-90 microspheres therapy. Implementation of such a workflow using the EWB or similar platform with a DMAIC-based process improvement approach could be expanded to other treatment procedures, especially those requiring multidisciplinary management.

The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for "intensity modulated radiation therapy (IMRT)" as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.

Quantitative evaluation of patient setup uncertainty of stereotactic radiotherapy with the frameless 6D ExacTrac system using statistical modeling

The purpose of this study is to evaluate patient setup accuracy and quantify individual and cumulative positioning uncertainties associated with different hardware and software components of the stereotactic radiotherapy (SRS/SRT) with the frameless 6D ExacTrac system. A statistical model is used to evaluate positioning uncertainties of the different components of SRS/SRT treatment with the Brainlab 6D ExacTrac system using the positioning shifts of 35 patients having cranial lesions. All these patients are immobilized with rigid head‐and‐neck masks, simulated with Brainlab localizer and planned with iPlan treatment planning system. Stereoscopic X‐ray images (XC) are acquired and registered to corresponding digitally reconstructed radiographs using bony‐anatomy matching to calculate 6D translational and rotational shifts. When the shifts are within tolerance (0.7 mm and 1°), treatment is initiated. Otherwise corrections are applied and additional X‐rays (XV) are acquired to verify that patient position is within tolerance. The uncertainties from the mask, localizer, IR ‐frame, X‐ray imaging, MV, and kV isocentricity are quantified individually. Mask uncertainty (translational: lateral, longitudinal, vertical; rotational: pitch, roll, yaw) is the largest and varies with patients in the range (−2.07−3.71mm,−5.82−5.62mm,−5.84−3.61mm;−2.10−2.40∘,−2.23−2.60∘,and−2.7−3.00∘) obtained from mean of XC shifts for each patient. Setup uncertainty in IR positioning (0.88, 2.12, 1.40 mm, and 0.64°, 0.83°, 0.96°) is extracted from standard deviation of XC. Systematic uncertainties of the frame (0.18, 0.25, −1.27mm, −0.32∘, 0.18°, and 0.47°) and localizer (−0.03, −0.01, 0.03 mm, and −0.03∘, 0.00°, −0.01∘) are extracted from means of all XV setups and mean of all XC distributions, respectively. Uncertainties in isocentricity of the MV radiotherapy machine are (0.27, 0.24, 0.34 mm) and kV imager (0.15, −0.4, 0.21 mm). A statistical model is developed to evaluate the individual and cumulative systematic and random positioning uncertainties induced by the different hardware and software components of the 6D ExacTrac system. The uncertainties from the mask, localizer, IR frame, X‐ray imaging, couch, MV linac, and kV imager isocentricity are quantified using statistical modeling.

PACS number(s): 87.56.B‐, 87.59.B‐

Failure mode and effects analysis in a dual-product microsphere brachytherapy environment

PURPOSE

We performed a failure mode and effects analysis (FMEA) during the addition of a new microspheres product into our existing microsphere brachytherapy program to identify areas for safety improvements.

METHODS AND MATERIALS

A diverse group of team members from the microsphere program participated in the project to create a process map, identify and score failure modes, and discuss programmatic changes to address the highest ranking items. We developed custom severity ranking scales for staff- and institution-related failure modes to encompass possible risks that may exist outside of patient-based effects.

RESULTS

Between both types of microsphere products, 173 failure mode/effect pairs were identified: 90 for patients, 35 for staff, and 48 for the institution. The SIR-Spheres program was ranked separately from the TheraSphere program because of significant differences in workflow during dose calculation, preparation, and delivery. High-ranking failure modes in each category were addressed with programmatic changes.

CONCLUSIONS

The FMEA aided in identifying potential risk factors in our microsphere program and allowed a theoretically safer and more efficient design of the workflow and quality assurance for both our new SIR-Spheres program and our existing TheraSphere program. As new guidelines are made available, and our experience with the SIR-Spheres program increases, we will update the FMEA as an efficient starting point for future improvements.

Application of failure mode and effects analysis in a clinical chemistry laboratory

BACKGROUND

Timely delivery of correct results has long been considered as the goal of quality management in clinical laboratory. With increasing workload as well as complexities of laboratory testing and patient care, the traditional technical adopted like internal quality control (IQC) and external quality assessment (EQA) may not enough to cope with quality management problems for clinical laboratories. We applied failure mode and effects analysis (FMEA), a proactive tool, to reduce errors associated with the process beginning with sample collection and ending with a test report in a clinical chemistry laboratory. Our main objection was to investigate the feasibility of FMEA in a real-world situation, namely the working environment of hospital.

METHODS

A team of 8 people (3 laboratory workers, 2 couriers, 2 nurses, and 1 physician) from different departments who were involved in the testing process were recruited and trained. Their main responsibility was to analyze and score all possible clinical chemistry laboratory failures based on three aspects: the severity of the outcome (S), the likeliness of occurrence (O), and the probability of being detected (D). These three parameters were multiplied to calculate risk priority numbers (RPNs), which were used to prioritize remedial measures. Failure modes with RPN≥200 were deemed as high risk, meaning that they needed immediate corrective action. After modifications that were put, we compared the resulting RPN with the previous one.

RESULTS

A total of 33 failure modes were identified. Many of the failure modes, including the one with the highest RPN (specimen hemolysis) appeared in the pre-analytic phase, whereas no high-risk failure modes (RPN≥200) were found during the analytic phase. High-priority risks were "sample hemolysis" (RPN, 336), "sample delivery delay" (RPN, 225), "sample volume error" (RPN, 210), "failure to release results in a timely manner" (RPN, 210), and "failure to identify or report critical results" (RPN, 200). The corrective measures that we took allowed a decrease in the RPN, especially for the high-priority risks. The maximum reduction was approximately 70%, as observed for the failure mode "sample hemolysis".

CONCLUSIONS

FMEA can effectively reduce errors in clinical chemistry laboratories.

Failure mode and effect analysis oriented to risk-reduction interventions in intraoperative electron radiation therapy: the specific impact of patient transportation, automation, and treatment planning availability

BACKGROUND AND PURPOSE

Industrial companies use failure mode and effect analysis (FMEA) to improve quality. Our objective was to describe an FMEA and subsequent interventions for an automated intraoperative electron radiotherapy (IOERT) procedure with computed tomography simulation, pre-planning, and a fixed conventional linear accelerator.

MATERIAL AND METHODS

A process map, an FMEA, and a fault tree analysis are reported. The equipment considered was the radiance treatment planning system (TPS), the Elekta Precise linac, and TN-502RDM-H metal-oxide-semiconductor-field-effect transistor in vivo dosimeters. Computerized order-entry and treatment-automation were also analyzed.

RESULTS

Fifty-seven potential modes and effects were identified and classified into 'treatment cancellation' and 'delivering an unintended dose'. They were graded from 'inconvenience' or 'suboptimal treatment' to 'total cancellation' or 'potentially wrong' or 'very wrong administered dose', although these latter effects were never experienced. Risk priority numbers (RPNs) ranged from 3 to 324 and totaled 4804. After interventions such as double checking, interlocking, automation, and structural changes the final total RPN was reduced to 1320.

CONCLUSIONS

FMEA is crucial for prioritizing risk-reduction interventions. In a semi-surgical procedure like IOERT double checking has the potential to reduce risk and improve quality. Interlocks and automation should also be implemented to increase the safety of the procedure.