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

Improving the safety of radiotherapy treatment processes via incident-driven FMEA feedback loops

BACKGROUND

Failure mode and effects analysis (FMEA) is a valuable tool for radiotherapy risk assessment, yet its outputs might be unreliable due to failures not being identified or due to a lack of accurate error rates.

PURPOSE

A novel incident reporting system (IRS) linked to an FMEA database was tested and evaluated. The study investigated whether the system was suitable for validating a previously performed analysis and whether it could provide accurate error rates to support the expert occurrence ratings of previously identified failure modes.

METHODS

Twenty-three pre-identified failure modes of our external beam radiotherapy process, covering the process steps from patient admission to treatment delivery, were proffered on dedicated FMEA feedback and incident reporting terminals generated by the IRS. The clinical setting involved a computed tomography scanner, dosimetry, and five linacs. Incoming reports were used as basis to identify additional failure modes or confirm initial ones. The Kruskal-Wallis H test was applied to compare the risk priorities of the retrospective and prospective failure modes. Wald's sequential probability ratio test was used to investigate the correctness of the experts' occurrence ratings by means of the number of incoming reports.

RESULTS

Over a 15-month period, 304 reports were submitted. There were 0.005 (confidence interval [CI], 0.0014-0.0082) reported incidents per imaging study and 0.0006 (CI, 0.0003-0.0009) reported incidents per treatment fraction. Sixteen additional failure modes could be identified, and their risk priorities did not differ from those of the initial failure modes (p = 0.954). One failure mode occurrence rating could be increased, whereas the other 22 occurrence ratings could not be disproved.

CONCLUSIONS

Our approach is suitable for validating FMEAs and deducing additional failure modes on a continual basis. Accurate error rates can only be provided if a sufficient number of reports is available.

Process failure mode and effects analysis for external beam radiotherapy: Introducing a literature-based template and a novel action priority

PURPOSE

The first aim of the study was to create a general template for analyzing potential failures in external beam radiotherapy, EBRT, using the process failure mode and effects analysis (PFMEA). The second aim was to modify the action priority (AP), a novel prioritization method originally introduced by the Automotive Industry Action Group (AIAG), to work with different severity, occurrence, and detection rating systems used in radiation oncology.

METHODS AND MATERIALS

The AIAG PFMEA approach was employed in combination with an extensive literature survey to develop the EBRT-PFMEA template. Subsets of high-risk failure modes found through the literature survey were added to the template where applicable. Our modified AP for radiation oncology (RO AP) was defined using a weighted sum of severity, occurrence, and detectability. Then, Monte Carlo simulations were conducted to compare the original AIAG AP, the RO AP, and the risk priority number (RPN). The results of the simulations were used to determine the number of additional corrective actions per failure mode and to parametrize the RO AP to our department's rating system.

RESULTS

An EBRT-PFMEA template comprising 75 high-risk failure modes could be compiled. The AIAG AP required 1.7 additional corrective actions per failure mode, while the RO AP ranged from 1.3 to 3.5, and the RPN required 3.6. The RO AP could be parametrized so that it suited our rating system and evaluated severity, occurrence, and detection ratings equally to the AIAG AP.

CONCLUSIONS

An adjustable EBRT-PFMEA template is provided which can be used as a practical starting point for creating institution-specific templates. Moreover, the RO AP introduces transparent action levels that can be adapted to any rating system.

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.

Initial end-to-end testing of the ExacTrac dynamic deep inspiration breath hold workflow using a breath hold breast phantom

ExacTrac Dynamic (ETD) provides a Deep Inspiration Breath Hold (DIBH) workflow for breast patients. Stereoscopic x-ray imaging combined with optical and thermal mapping allows localisation against simulation imaging, alongside surface guided breath hold monitoring. This work aimed to determine appropriate imaging parameters, the optimal Hounsfield Unit (HU) threshold for patient contour generation and workflow evaluation via end-to-end (E2E) positioning using a custom breast DIBH phantom. After localisation via existing Image Guidance (IG), stereoscopic imaging was performed with a range of parameters to determine best agreement. Similarly, residual errors in prepositioning were minimised using a range of HU threshold contours. E2E positioning was completed for clinical workflows allowing residual isocentre position error measurement and existing IG comparison. Parameters of 60 kV and 25mAs were determined appropriate for patient imaging and HU thresholds between -600 HU and -200 HU enabled adequate prepositioning. The average and standard deviation in residual isocentre position error was 1.0 ± 0.9 mm, 0.4 ± 1.0 mm and 0.1 ± 0.5 mm in the lateral, longitudinal and vertical directions, respectively. Errors measured using existing IG were -0.6 ± 1.1 mm, 0.5 ± 0.7 mm and 0.2 ± 0.4 mm in the lateral, longitudinal and vertical directions, and 0.0 ± 1.0o, 0.5 ± 1.7o and -0.8 ± 1.8o for pitch roll and yaw. The use of bone weighted matching increased residual error, while simulated reduction of DIBH volume maintained isocentre positioning accuracy despite anatomical changes. This initial testing indicated suitability for clinical implementation during DIBH breast treatments.

Fuzzy analytic hierarchy process-based risk priority number for risk assessments of commissioning process of a ring gantry LINAC

PURPOSE

We propose a fuzzy analytic hierarchy process (AHP)-based risk priority number (RPN) method in failure modes and effects analysis (FMEA) to overcome the shortcomings of traditional RPN-based FMEA. Our research group has previously published the FMEA to mitigate the failure modes (FMs) for the commissioning process of a ring gantry LINAC. However, inter-relationships among FMs were observed in high ranked FMs due to a heavy reliance on imaging system.

METHODS

Fuzzy AHP was applied to determine relative weights of risk impacts based on inter-relationships among FMs. Since the time sequence dependency is a major factor for risk factors, a hierarchical structure of AHP was used to reflect the directional impacts such as causal influence and feedback loop. Two fuzzy weighted RPNs, called (RPN_W and FRPN_W , were calculated depending on the input values of severity (S), occurrence (O), and probability of not being detected (D) from the evaluators. The RPN_W used numerical values, whereas the fuzzy values were used for FRPN_W . Both RPNs were calculated by multiplying the weighted O, S, and D using the fuzzy AHP method.

RESULTS

The differences between the two fuzzy RPN rankings are due to inherent fuzzy uncertainty and deviations in O, S, and D values submitted by the evaluators. Considering all results of traditional and fuzzy-based FMEA, the two most highly ranked FMs were identified: errors in determining the non-isocentric SSD and SSD from MV images because of the unique features of the ring gantry LINAC.

CONCLUSION

This study has demonstrated the feasibility of the use of a fuzzy AHP-based RPN to perform comprehensive analysis and prioritization of FMs. The risk analysis using fuzzy AHP can be improved and/or refined based on the department's specific workflow and clinical preferences taking various priority weighting approaches into account.

ESTRO-ACROP guideline on surface guided radiation therapy

Surface guidance systems enable patient positioning and motion monitoring without using ionising radiation. Surface Guided Radiation Therapy (SGRT) has therefore been widely adopted in radiation therapy in recent years, but guidelines on workflows and specific quality assurance (QA) are lacking. This ESTRO-ACROP guideline aims to give recommendations concerning SGRT roles and responsibilities and highlights common challenges and potential errors. Comprehensive guidelines for procurement, acceptance, commissioning, and QA of SGRT systems installed on computed tomography (CT) simulators, C-arm linacs, closed-bore linacs, and particle therapy treatment systems are presented that will help move to a consensus among SGRT users and facilitate a safe and efficient implementation and clinical application of SGRT.