A method for empirically validating FMEA RPN scores in a radiation oncology clinic using physics QC data.

In failure modes and effects analysis (FMEA), the components of the risk priority number (RPN) for a failure mode (FM) are often chosen by consensus. We describe an empirical method for estimating the occurrence (O) and detectability (D) components of a RPN. The method requires for a given FM that its associated quality control measure be performed twice as is the case when a FM is checked for in an initial physics check and again during a weekly physics check. If instances of the FM caught by these checks are recorded, O and D can be computed. Incorporation of the remaining RPN component, Severity, is discussed. This method can be used as part of quality management design ahead of an anticipated FMEA or afterwards to validate consensus values.

Unlocking the adaptive advantage: correlation and machine learning classification to identify optimal online adaptive stereotactic partial breast candidates.

Objective.Online adaptive radiotherapy (OART) is a promising technique for delivering stereotactic accelerated partial breast irradiation (APBI), as lumpectomy cavities vary in location and size between simulation and treatment. However, OART is resource-intensive, increasing planning and treatment times and decreasing machine throughput compared to the standard of care (SOC). Thus, it is pertinent to identify high-yield OART candidates to best allocate resources.Approach.Reference plans (plans based on simulation anatomy), SOC plans (reference plans recalculated onto daily anatomy), and daily adaptive plans were analyzed for 31 sequential APBI targets, resulting in the analysis of 333 treatment plans. Spearman correlations between 22 reference plan metrics and 10 adaptive benefits, defined as the difference between mean SOC and delivered metrics, were analyzed to select a univariate predictor of OART benefit. A multivariate logistic regression model was then trained to stratify high- and low-benefit candidates.Main results.Adaptively delivered plans showed dosimetric benefit as compared to SOC plans for most plan metrics, although the degree of adaptive benefit varied per patient. The univariate model showed high likelihood for dosimetric adaptive benefit when the reference plan ipsilateral breast V15Gy exceeds 23.5%. Recursive feature elimination identified 5 metrics that predict high-dosimetric-benefit adaptive patients. Using leave-one-out cross validation, the univariate and multivariate models classified targets with 74.2% and 83.9% accuracy, resulting in improvement in per-fraction adaptive benefit between targets identified as high- and low-yield for 7/10 and 8/10 plan metrics, respectively.Significance.This retrospective, exploratory study demonstrated that dosimetric benefit can be predicted using only ipsilateral breast V15Gy on the reference treatment plan, allowing for a simple, interpretable model. Using multivariate logistic regression for adaptive benefit prediction led to increased accuracy at the cost of a more complicated model. This work presents a methodology for clinics wishing to triage OART resource allocation.

Development of Standard X-Ray Beams for Calibration of Radiobiology Cabinet and Conformal Irradiators.

This work seeks to develop standard X-ray beams that are matched to radiobiology X-ray irradiators. The calibration of detectors used for dose determination of these irradiators is performed with a set of standard X rays that are more heavily filtered and/or lower energy, which leads to a higher uncertainty in the dose measurement. Models of the XRad320, SARRP, and the X-ray tube at the University of Wisconsin Medical Radiation Research Center (UWMRRC) were created using the BEAMnrc user code of the EGSnrc Monte Carlo code system. These models were validated against measurements, and the resultant modeled spectra were used to determine the amount of added filtration needed to match the X-ray beams at the UWMRRC to those of the XRad320 and SARRP. The depth profiles and half-value layer (HVL) simulations performed using BEAMnrc agreed to measurements within 3% and 3.6%, respectively. A primary measurement device, a free-air chamber, was developed to measure air kerma in the medium energy range of X rays. The resultant spectra of the matched beams had HVL's that matched the HVL's of the radiobiology irradiators well within the 3% criteria recommended by the International Atomic Energy Agency (IAEA) and the average energies agreed within 2.4%. In conclusion, three standard X-ray beams were developed at the UWMRRC with spectra that more closely match the spectra of the XRad320 and SARRP radiobiology irradiators, which will aid in a more accurate dose determination during calibration of these irradiators.

Comparisons of 3-Dimensional Conformal and Intensity-Modulated Neutron Therapy for Head and Neck Cancers.

PURPOSE: Neutron therapy is a high linear energy transfer modality that is useful for the treatment of radioresistant head and neck (H&N) cancers. It has been limited to 3-dimensioanal conformal-based fast-neutron therapy (3DCNT), but recent technical advances have enabled the clinical implementation of intensity-modulated neutron therapy (IMNT). This study evaluated the comparative dosimetry of IMNT and 3DCNT plans for the treatment of H&N cancers. MATERIALS AND METHODS: Seven H&N IMNT plans were retrospectively created for patients previously treated with 3DCNT at the University of Washington (Seattle). A custom RayStation model with neutron-specific scattering kernels was used for inverse planning. Organ-at-risk (OAR) objectives from the original 3DCNT plan were initially used and were then systematically reduced to investigate the feasibility of improving a therapeutic ratio, defined as the ratio of the mean tumor to OAR dose. The IMNT and 3DCNT plan quality was evaluated using the therapeutic ratio, isodose contours, and dose volume histograms. RESULTS: When compared with the 3DCNT plans, IMNT reduces the OAR dose for the equivalent tumor coverage. Moreover, IMNT is most advantageous for OARs in close spatial proximity to the target. For the 7 patients with H&N cancers examined, the therapeutic ratio for IMNT increased by an average of 56% when compared with the 3DCNT. The maximum OAR dose was reduced by an average of 20.5% and 20.7% for the spinal cord and temporal lobe, respectively. The mean dose to the larynx decreased by an average of 80%. CONCLUSION: The IMNT significantly decreases the OAR doses compared with 3DCNT and provides comparable tumor coverage. Improvements in the therapeutic ratio with IMNT are especially significant for dose-limiting OARs near tumor targets. Moreover, IMNT provides superior sparing of healthy tissues and creates significant new opportunities to improve the care of patients with H&N cancers treated with neutron therapy.

The role of surface-guided radiation therapy for improving patient safety.

Emerging data indicates SGRT could improve safety and quality by preventing errors in its capacity as an independent system in the treatment room. The aim of this work is to investigate the utility of SGRT in the context of safety and quality. Three incident learning systems (ILS) were reviewed to categorize and quantify errors that could have been prevented with SGRT: SAFRON (International Atomic Energy Agency), UW-ILS (University of Washington) and AvIC (Skåne University Hospital). A total of 849/9737 events occurred during the pre-treatment review/verification and treatment stages. Of these, 179 (21%) events were predicted to have been preventable with SGRT. The most common preventable events were wrong isocentre (43%) and incorrect accessories (34%), which appeared at comparable rates among SAFRON and UW-ILS. The proportion of events due to wrong accessories was much smaller in the AvIC ILS, which may be attributable to the mandatory use of SGRT in Sweden. Several case scenarios are presented to demonstrate that SGRT operates as a valuable complement to other quality-improvement tools routinely used in radiotherapy. Cases are noted in which SGRT itself caused incidents. These were mostly related to workflow issues and were of low severity. Severity data indicated that events with the potential to be mitigated by SGRT were of higher severity for all categories except wrong accessories. Improved vendor integration of SGRT systems within the overall workflow could further enhance its clinical utility. SGRT is a valuable tool with the potential to increase patient safety and treatment quality in radiotherapy.

A multi-institutional assessment of COVID-19-related risk in radiation oncology.

PURPOSE: The COVID-19 pandemic has presented challenges to delivering safe and timely care for cancer patients. The oncology community has undertaken substantial workflow adaptations to reduce transmission risk for patients and providers. While various control measureshave been proposed and implemented, little is known about their impact on safety of the radiation oncology workflow and potential for transmission. The objective of this study was to assess potential safety impacts of control measures employed during the COVID-19 pandemic. METHODS: A multi-institutional study was undertaken to assess the risks of pandemic-associated workflow adaptations using failure mode and effects analysis (FMEA). Failure modes were identified and scored using FMEA formalism. FMEA scores were used to identify highest-risk aspects of the radiation therapy process. The impact of control measures on overall risk was quantified. Agreement among institutions was evaluated. RESULTS: Thirty three failure modes and 22 control measures were identified. Control measures resulted in risk score reductions for 22 of the failure modes, with the largest reductions from screening of patients and staff, requiring use of masks, and regular cleaning of patient areas. The median risk score for all failure modes was reduced from 280 to 168. There was high institutional agreement for 90.3% of failure modes but only 47% of control measures. CONCLUSIONS: COVID-related risks are similar across oncology practices in this study. While control measures can reducerisk, their use varied. The effectiveness of control measures on risk may guide selection of the highest-impact workflow adaptions to ensure safe care in oncology.