Clinical Plan Sensitivity to TPS Parameters and the Complexity Metrics That Best Capture This Relationship
F Brooks1,2*, M Glenn3, J Pollard-Larkin1, R Howell1,2, C Peterson1, C Nelson1, C Clark4, S Kry1,2, (1) MD Anderson Cancer Center, Houston, TX, (2) IROC Houston QA Center, Houston, TX, (3) University of Washington, Seattle, WA, (4) UCLH, London, SRY, GB,
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PO-GePV-T-312 (Sunday, 7/10/2022) [Eastern Time (GMT-4)]
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Purpose: Evaluate the impact of atypical treatment planning system beam model parameters (associated with poor dosimetry audit results) on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on patient care.
Methods: The MLC offset, transmission, and eight additional beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 75 and 97.5 percentile levels. These modifications were evaluated on twenty-five patient cases for each of the following anatomical sites: prostate, non-small cell lung, H&N, brain, and mesothelioma; generating one thousand plan perturbations. Differences in the mean dose delivered to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the dose delivered using the reference (50th-percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R-squared values were used to determine the best metric.
Results: Variation in the MLC offset and MLC transmission parameters resulted in the greatest dose differences: up to 5.7% for the CTV and 27% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and mean tongue & groove index (T&G) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed between all sites.
Conclusion: Extreme values for MLC offset and MLC transmission beam modeling parameters (previously associated with failing IROC phantoms) were found to substantially impact the dose distribution of clinical plans. Careful attention should be given to these beam modeling parameters. The mean MLC Gap and mean T&G index complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors.
Funding Support, Disclosures, and Conflict of Interest: This work was supported by Public Health Service Grants CA180803 and CA214526, awarded by the National Cancer Institute, United States Department of Health and Human Services.
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