ESTRO 2021 Abstract Book

S432

ESTRO 2021

Beam & CT modelling Patient & dose modelling

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Optimisation & dose calculation

IT & automation

Updates & upgrades A series of comprehensive tests are proposed in each chapter, allowing an easy QA Program to be used for commissioning, and update/upgrade checks. Results General remarks: This chapter adds remarks concerning the TP process in general and provides recommendations on standardisation, safety and users education. Beam modelling & CT: In addition to the collection of basic beam data, focus is on modelling of the MLC and analysis of clinical plan verification. Tests are proposed for the different steps of the beam modelling: treatment machine definition, measurement of beam data, creation of the model itself, and its verification. Patient & dose modelling: A synthetic data set, consisting of a CT, RTStruct, RTPlan and RTDose, was developed and can be used for both patient modelling verification and dose representation/reporting. Once imported, the Dicom objects enable an extensive check of different parameters inside the TPS. This data set will be provided with the report. Optimisation & dose calculation: Recommendations about class solutions, machine, dose and plan optimisation parameters, and automated TP solution are provided. IT & automation: This chapter aims to give a set of recommendations for the safe implementation of automation in the TPS. A distinction is made between tools that automate a sequence of repetitive tasks to steer the TPS for the preparation of the plan and scripts or software packages which support the clinical decision making process. The latter are always considered as medical devices and fall upon the European Medical Devices Regulation. Updates & upgrades: Before a new version can be used in the clinic, it needs to be tested. The amount of testing depends on whether the release can be regarded as an update (bug fixes and small improvements) or an upgrade. For example, if significant changes were made to the dose calculation or the optimisation algorithms, these should be considered as upgrades and rigorous testing is then required. Conclusion A new NCS subcommittee was initiated in 2018 with the purpose to review the best practice for TP QA. With a recommended set of tests, from beam modelling to treatment plan analysis, we aim to set up a standardised and comprehensive QA program for photon beam TP with a publicly available dataset to facilitate readers in setting up their QA program. PH-0548 Pareto Navigation Guided Automated Planning for Extreme Hypo-fractionated Prostate Radiotherapy S. Berenato 1 , N. Abbott 2 , O. Woodley 2 , M. Chu 2 , N. Palaniappan 2 , A. Millin 2 , P. Wheeler 2 1 Velindre Cancer Centre, Medical physics, Cardiff, United Kingdom; 2 Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom Purpose or Objective Automated treatment planning (AP) is an innovation in the field of radiotherapy treatment planning, proposed as a method to increase efficiency and ensure consistent plan quality. Pareto navigation is an interactive multi-criteria optimization (MCO), which enables a more intuitive exploration of competing trade-offs, ensuring plans are aligned with clinician preference. Pareto navigation guided automated planning (PN-AP) combines these two important innovations through utilization of Pareto navigation to directly calibrate a fully automated solution. This work evaluates the application of PN-AP to support implementation of an extreme hypo-fractionated radiotherapy (EHRT) service for prostate cancer. Materials and Methods A calibration dataset was populated with delineated CT scans of 6 historical prostate patients (standard fractionation) and the 1 st EHRT patient treated at our centre. 22 subsequent EHRT clinical patients (2 nd -23 rd ) were sequentially selected to form a validation cohort. All EHRT clinical patients were treated with a manually produced treatment plan prescribed to 36.25 Gy in 5#. The Pareto navigation calibration process was performed on two calibration patients, with differing treatment options intuitively explored and competing trade-offs balanced according to the protocol aims. The resultant solution was tested and refined across the remaining calibration patients. Once calibrated, a single automated plan (VMAT Auto ) was generated for each patient in the validation cohort. VMAT Auto plan quality was compared against the manual reference plan (VMAT Manual ) quantitatively, using a range of DVH metrics, and qualitatively through blind review by a clinical oncologist. Results Table 1 and figure 1 present a summary of the quantitative and qualitative study results. VMAT Auto led to statistically significant reductions in bladder V37Gy, femoral head V14.5Gy and all rectal dose metrics. With the exception of bowel V18.1Gy, which exhibited a minor increase, no other significant deviations in OAR doses were observed. In terms of target coverage, VMAT Auto yielded a statistically significantly lower PTV V95% (to enable increased rectal spacing), yet did not compromise the CTV V95%, which was increased. Results of the blind review demonstrate a clear preference for VMAT Auto (17/22 considered superior), with the clinician preferring plans where rectum doses were prioritized over PTV coverage. All VMAT Auto plans were considered clinically acceptable.