ESTRO 2025 - Abstract Book

S7

Invited Speaker

ESTRO 2025

machine QA. Assessing the sensitivity and specificity of PSQA is core to the work of ESTRO / AAPM Task Group 360, the report of which will provide details of different approaches to take. It is important to assess the complete clinically employed PSQA process and not just focus on the hardware and/or software used for PSQA. Selecting options and parameters in the PSQA workflow can significantly impact its ability to detect relevant problems in treatment plans and their deliverability. In order to be a viable QA tool, PSQA needs to be independent of the TPS commissioning process and vice versa. Tuning PSQA to local beam models can hide problems with the beam model, including inaccuracies in small-field output factors and MLC model parameters, and hence should be avoided. Like other QA measures, PSQA needs to be assessed in terms of its sensitivity to errors it is designed to catch. References: [1] Kry S.F. et al. Institutional Patient-specific IMRT QA Does Not Predict Unacceptable Plan Delivery IJROBP 90(5) 2014 [2] Lehmann, J. et al. SEAFARER–A new concept for validating radiotherapy patient specific QA for clinical trials and clinical practice. Radiotherapy and Oncology 171 2022 [3] O'Daniel J et al Which failures do patient-specific quality assurance systems need to catch? Med Phys 52 2025

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Speaker Abstracts The impact of poor beam modelling parameters on clinical plans Stephen Kry Radiation Physics, UT MD Anderson Cancer Center, Houston, USA

Abstract:

Modelling of the MLC, source, and scattering parameters is a central element of commissioning the treatment planning system. While modelling these components is critical for dose calculation accuracy, particularly for modulated treatments, the existing guidance on how to determine these values often lacks critical details to provide a uniform result. Moreover, these parameters often lack robust physical meaning, and are therefore often reduced to fudge factors. As a result, there is substantial variability in what these values are. Modelled values in the treatment planning system are more varied than consistently measured values on current linacs. This can introduce uncertainty and errors into the modelled dose distribution from the treatment planning system. The impact of this variability depends on the parameter in question, but recent studies have shown that this impact can be substantial. Moreover, the use of atypical parameter values (i.e., <10 th percentile or >90 th percentile) was correlated with poorer performance on dosimetric audits. In this talk we will review the observed spread in TPS modelling parameters, the dosimetric impact of suboptimal values, and evidence of the prevalence of suboptimal modelling across the community. The confounding impact of plan complexity will be reviewed, along with current efforts to standardize determination of MLC-based parameters.