Characterizing the interplay of treatment parameters and complexity and their impact on performance on an IROC IMRT phantom using machine learning

Aim of the Study: To elucidate the important factors and their interplay that drive performance on IMRT phantoms from the Imaging and Radiation Oncology Core (IROC). Methods: IROC's IMRT head and neck phantom contains two targets and an organ at risk. Point and 2D dose are measured by TLDs and film, respectively. 1,542 irradiations between 2012-2020 were retrospec-tively analyzed based on output parameters, complexity metrics, and treatment parameters. Univariate analysis compared parameters based on pass/fail, and random forest modeling was used to predict out-put parameters and determine the underlying importance of the variables. Results: The average phantom pass rate was 92% and has not significantly improved over time. The step -and-shoot irradiation technique had significantly lower pass rates that significantly affected other treat-ment parameters' pass rates. The complexity of plans has significantly increased with time, and all aperture-based complexity metrics (except MCS) were associated with the probability of failure. Random forest-based prediction of failure had an accuracy of 98% on held-out test data not used in model training. While complexity metrics were the most important contributors, the specific metric depended on the set of treatment parameters used during the irradiation. Conclusion: With the prevalence of errors in radiotherapy, understanding which parameters affect treat-ment delivery is vital to improve patient treatment. Complexity metrics were strongly predictive of irra-diation failure; however, they are dependent on the specific treatment parameters. In addition, the use of one complexity metric is insufficient to monitor all aspects of the treatment plan. (c) 2023 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 182 (2023) 1-6

Automated summary

The aim of this study was to identify the key factors and their interactions that influence performance on IMRT phantoms from IROC. The findings revealed that the complexity of treatment and various parameters significantly affected the pass rates, and complexity metrics had high predictive accuracy for irradiation failures.