<scp>FMEA</scp> of manual and automated methods for commissioning a radiotherapy treatment planning system

Wexler, Amy; Gu, B.; Goddu, S; Mutic, Maya; Yaddanapudi, S; Olsen, Lindsey; Harry, Taylor; Noël, C.; Pawlicki, Todd; Mutic, Sasa; Cai, Bin

doi:10.1002/mp.12278

Cited by 26 publications

(20 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…that makes it a challenging task to use equipment such as 3D water tanks for various measurements. This observation agrees well with other studies reported in the literature that demonstrate that automating the ATC process and using standard beam data reduces the probability of occurrence of errors . A comparison of using manufacturer‐supplied phantom and automation (with EPID) vs conventional techniques with tools that are not an integral part of the linac has shown that use of manufacturer‐supplied phantoms and automation reduces the number of FMs by slightly more than half, from 556 FMs to 255 FMs, for a c‐arm linac …”

Section: Discussionsupporting

confidence: 90%

“…This observation agrees well with other studies reported in the literature that demonstrate that automating the ATC process and using standard beam data reduces the probability of occurrence of errors. 17,18 A comparison of using manufacturer-supplied phantom and automation (with EPID) vs conventional techniques with tools that are not an integral part of the linac has shown that use of manufacturer-supplied phantoms and automation reduces the number of FMs by slightly more than half, from 556 FMs to 255 FMs, for a c-arm linac. 5 In the conventional approach of measurements of output in a c-arm linac, a reference detector is typically placed between the linac head and a water tank.…”

Section: Rankmentioning

confidence: 99%

“…These FMs were not identified in previous studies conducted on c-arm linacs. 4,5,18 A possible quality control measure for this machine-related FM is for the manufacturer to mark an approximate 5 9 5 cm 2 , and 10 9 10 cm 2 field on the bore cover.…”

Section: Rankmentioning

confidence: 99%

See 2 more Smart Citations

Application of TG‐100 risk analysis methods to the acceptance testing and commissioning process of a Halcyon linear accelerator

Teo

Hwang

Shields³

et al. 2019

Medical Physics

View full text Add to dashboard Cite

Purpose A new type of linear accelerator (linac) was recently introduced into the market by a major manufacturer. Our institution is one of the early users of this preassembled and preconfigured dual‐layer multileaf collimator (MLC), ring‐gantry linac — Halcyon™ (1st version). We performed a set of full acceptance testing and commissioning (ATC) measurements for three Halcyon machines and compared the measured data with the standard beam model provided by the manufacturer. The ATC measurements were performed following the guidelines given in different AAPM protocols as well as guidelines provided by the manufacturer. The purpose of the present work was to perform a risk assessment of the ATC process for this new type of linac and investigate whether the results obtained from this analysis could potentially be used as a guideline for improving the design features of this type of linac. Methods AAPM's TG100 risk assessment methodology was applied to the ATC process. The acceptance testing process relied heavily on the use of a manufacturer‐supplied phantom and the automated analysis of electronic portal imaging device (EPID) images. For the commissioning process, a conventional measurement setup and process (e.g., use of water tank for scanning) was largely used. ATC was performed using guidelines recommended in various AAPM protocols (e.g., TG‐106, TG‐51) as well as guidelines provided by the manufacturer. Six medical physicists were involved in this study. Process maps, process steps, and failure modes (FMs) were generated for the ATC procedures. Failure modes and effects analysis (FMEA) were performed following the guidelines given in AAPM TG‐100 protocol. The top 5 and top 10 highest‐ranked FMs were identified for the acceptance and commissioning procedures, respectively. Quality control measures were suggested to mitigate these FMs. Results A total of 38 steps and 88 FMs were identified for the entire ATC process. Fourteen steps and 34 FMs arose from acceptance testing. The top 5 FMs that were identified could potentially be mitigated by the manufacturer. For commissioning, a total of 24 steps and 54 potential FMs were identified. The use of separate measurement tools that are not machine‐integrated has been identified as a cause for the higher number of steps and FMs generated from the conventional ATC approach. More than half of the quality control measures recommended for both acceptance and commissioning could potentially be incorporated by the manufacturer in the design of the Halcyon machine. Conclusion This paper presents the results of FMEA and quality control measures to mitigate the FMs for the ATC process for Halcyon machine. Unique FMs that result from the differences in the ATC guidelines provided by the vendor and current conventional protocols, and the challenges of performing the ATC due to the new linac features and ring‐gantry design were highlighted for the first time. The FMs identified in the present work along with the suggested quality control measures, could potentially be used to impro...

show abstract

Section: Discussionsupporting

confidence: 90%

Section: Rankmentioning

confidence: 99%

See 1 more Smart Citation

Application of TG‐100 risk analysis methods to the acceptance testing and commissioning process of a Halcyon linear accelerator

Teo

Hwang

Shields³

et al. 2019

Medical Physics

View full text Add to dashboard Cite

show abstract

“…Failure mode and effects analysis (FMEA) is an established technique for methodically and prospectively identifying the risks involved in a process. This method has been used by several other groups to assess the risks of various processes in radiation oncology practice …”

Section: Introductionmentioning

confidence: 99%

“…This method has been used by several other groups to assess the risks of various processes in radiation oncology practice. [4][5][6][7][8] Our group recently developed a fully automatic treatment planning tool, the Radiation Planning Assistant (RPA). 9,10 In addition to developing algorithms to automate treatment planning, we also implemented a quality assurance (QA) program specific to the RPA in order to enhance the safety of automated planning.…”

Section: Introductionmentioning

confidence: 99%

A risk assessment of automated treatment planning and recommendations for clinical deployment

et al. 2019

View full text Add to dashboard Cite

Purpose: To assess the risk of failure of a recently developed automated treatment planning tool, the Radiation Planning Assistant (RPA) and to determine the reduction in these risks with implementation of a quality assurance (QA) program specifically designed for the RPA. Methods: We used failure mode and effects analysis (FMEA) to assess the risk of the RPA. The steps involved in the workflow of planning a 4-field box treatment of cervical cancer with the RPA were identified. Then, the potential failure modes at each step and their causes were identified and scored according to their likelihood of occurrence, severity, and likelihood of going undetected. Additionally, the impact of the components of the QA program on the detectability of the failure modes was assessed. The QA program was designed to supplement a clinic’s standard QA processes and consisted of 3 components: (1) automatic, independent verification of the results of automated planning; (2) automatic comparison of treatment parameters to expected values; and (3) guided manual checks of the treatment plan. A risk priority number (RPN) was calculated for each potential failure mode with and without use of the QA program. Results: In the RPA automated treatment planning workflow, we identified 68 potential failure modes with 113 causes. The average RPN was 91 without the QA program and 68 with the QA program (maximum RPNs were 504 and 315, respectively). The reduction in RPN was due to an improvement in the likelihood of detecting failures, resulting in lower detectability scores. The top-ranked failure modes included incorrect identification of the marked isocenter, inappropriate beam aperture definition, incorrect entry of the prescription into the RPA plan directive, and lack of a comprehensive plan review by the physician. Conclusions: Using FMEA, we assessed the risks in the clinical deployment of an automated treatment planning workflow and showed that a specialized QA program for the RPA, which included automatic QA techniques, improved the detectability of failures, reducing this risk. However, some residual risks persisted, which were similar to those found in manual treatment planning, and human error remained a major cause of potential failures. Through the risk analysis process, we identified 3 key aspects of safe deployment of automated planning: (1) user training on potential failure modes; (2) comprehensive manual plan review by physicians and physicists; and (3) automated QA of the treatment plan.

show abstract

Failure modes and effects analysis for surface‐guided DIBH breast radiotherapy

Bright

Foster

Hampton

et al. 2022

J Applied Clin Med Phys

View full text Add to dashboard Cite

Despite breast cancer prevalence and widespread adoption of deep inspiration breath‐hold (DIBH) radiation techniques, few data exist on the error risks related to using surface‐guided (SG) DIBH during breast radiation therapy (RT). Due to the increasingly technical nature of these methods and being a paradigm shift from traditional breast setups/treatments, the associated risk for error is high. Failure modes and effects analysis (FMEA) has been used in identifying risky RT processes yet is time‐consuming to perform. A subset of RT staff and a hospital patient‐safety representative performed FMEA to study SG‐DIBH RT processes. After this group (cohort 1) analyzed these processes, additional scoring data were acquired from RT staff uninvolved in the original FMEA (cohort 2). Cohort 2 received abbreviated FMEA training while using the same process maps that cohort 1 had created, which was done with the goal of validating our results and exploring the feasibility of expedited FMEA training and efficient implementation elsewhere. An extensive review of the SG‐DIBH RT process revealed 57 failure modes in 16 distinct steps. Risks deemed to have the highest priority, large risk priority number (RPN), and severity were addressed with policy changes, checklists, and standardization; of these, most were linked with operator error via manual inputs and verification. Reproducibility results showed that 5% of the average RPN between cohorts 1 and 2 was statistically different. Unexpected associations were noted between RPN and RT staff role; 12% of the physicist and therapist average scores were statistically different. Different levels of FMEA training yielded similar scoring within one RT department, suggesting a time‐savings can be achieved with abbreviated training. Scores between professions, however, yielded significant differences suggesting the importance of involving staff across disciplines.

show abstract

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

Abstract: 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.

Cited by 26 publications

References 26 publications

Application of TG‐100 risk analysis methods to the acceptance testing and commissioning process of a Halcyon linear accelerator

Application of TG‐100 risk analysis methods to the acceptance testing and commissioning process of a Halcyon linear accelerator

A risk assessment of automated treatment planning and recommendations for clinical deployment

Failure modes and effects analysis for surface‐guided DIBH breast radiotherapy

Contact Info

Product

Resources

About