ESTRO 2022 - Abstract Book

S727

Abstract book

ESTRO 2022

The use of atypical beam model parameters (based on current radiotherapy practice) is associated with poor performance during dosimetry audits. This study evaluated the impact of this variety in parameter values on clinical treatment plans, and determined which complexity metrics best describe the impact beam modeling errors have on patient care. Materials and Methods The multi-leaf collimator offset (MLC offset), transmission (MLC transmission), leaf tip width (LTW), and seven additional beam modeling parameters for a Varian accelerator were modified in RayStation to match the community data at the 2.5, 25, 75 and 97.5 percentile levels (Glenn Med Phys 2020). The impact of these modifications was evaluated on twenty-five patient cases, including prostate, lung, mesothelioma, head and neck, and brain plans, generating a total of one thousand perturbations. The difference in the mean dose delivered to the clinical target volume (CTV) and parallel organs at risk (OAR), and the maximum dose to the serial OAR, were evaluated with respect to the dose delivered using 50 th -percentile parameter values. Correlation between the CTV dose differences and 18 different complexity metrics were evaluated using linear regression, where the best complexity metric was selected based on average R-squared values. Results Variation in the MLC offset, MLC transmission, and PDD parameters resulted in the greatest dose difference across all anatomical sites. The greatest impact to the mean CTV and OAR dose was: 5.7% and 16.7%, respectively, at the 97.5- percentile for the MLC offset, -5.0% and -27.7%, respectively, at the 2.5-percentile for MLC transmission, and 2.3% and 2.1%, respectively, at the 97.5-percentile for PDD. Generally, the greatest dose impact occurred for the H&N plans, and the least occurred for the lung or brain, although there was overlapping impact across all anatomic sites. The mean MLC Gap, Tongue & Groove index, and edge metric were found to be the three best complexity metrics at describing the impact of TPS beam modeling variations on clinical dose delivery across all sites. For these metrics, all anatomical sites showed similar, although not identical, trends between complexity and dose perturbation.

Conclusion Extreme values for MLC offset, MLC transmission, and PDD beam modeling parameters, which have previously been associated with failing IROC’s IMRT phantom dosimetry audit, have been found to also substantially impact the dose distribution of clinical plans. Careful attention should be given to these beam modeling parameters. The mean MLC Gap, T&G index, and edge metric complexity metrics were the metrics best suited to identifying clinical plans that are more sensitive to beam modeling errors.