Faculty, Staff and Student Publications
Publication Date
1-1-2022
Journal
Neuro-Oncology Advances
Abstract
Background: Stereotactic radiosurgery (SRS) is a common treatment for intracranial lesions. This work explores the state of SRS treatment delivery to characterize current treatment accuracy based on treatment parameters.
Methods: NCI clinical trials involving SRS rely on an end-to-end treatment delivery on a patient surrogate (credentialing phantom) from the Imaging and Radiation Oncology Core (IROC) to test their treatment accuracy. The results of 1072 SRS phantom irradiations between 2012 and 2020 were retrospectively analyzed. Univariate analysis and random forest models were used to associate irradiation conditions with phantom performance. The following categories were evaluated in terms of how they predicted outcomes: year of irradiation, TPS algorithm, machine model, energy, and delivered field size.
Results: Overall, only 84.6% of irradiations have met the IROC/NCI acceptability criteria. Pass rate has remained constant over time, while dose calculation accuracy has slightly improved. Dose calculation algorithm (P < .001), collimator (P = .024), and field size (P < .001) were statistically significant predictors of pass/fail. Specifically, pencil beam algorithms and cone collimators were more likely to be associated with failing phantom results. Random forest modeling identified the size of the field as the most important factor for passing or failing followed by algorithm.
Conclusion: Constant throughout this retrospective study, approximately 15% of institutions fail to meet IROC/NCI standards for SRS treatment. In current clinical practice, this is particularly associated with smaller fields that yielded less accurate results. There is ongoing need to improve small field dosimetry, beam modeling, and QA to ensure high treatment quality, patient safety, and optimal clinical trials.
Keywords
IROC, phantoms, QA, random forest, SRS
DOI
10.1093/noajnl/vdac058
PMID
35664554
PMCID
PMC9154323
PubMedCentral® Posted Date
4-20-2022
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Neurosciences Commons, Oncology Commons