S2354
Physics - Quality assurance and auditing
ESTRO 2026
the Unity MR-Linac (Elekta). The data for every fraction is stored in a structured database for review and statistical analysis. In addition to reference, adapted and delivery plan parameters (MUs, iso-shifts, MR sequences etc), the user enters multi-stage time- stamp data for each treatment session. Information about secondary MU checks, music preferences, setup position, image fusion are also recorded for reference and analysis. Results: As a replacement for traditional QA, the PASC tool (figure 1a) has been used to quickly and accurately verify and record online adapted plan parameters for 12 treatment sites, ~450 treatment courses and ~4000 fractions. PASC can alert the treatment team to discrepancies exceeding pre-set limits between the reference and adapted beam data, field-code naming errors and isocentre shifts exceeding tolerances. Average session times for each site (sample data, figure 1b) may be used to optimise linac schedules, reducing initial 45min time slots to 30min for sites with shorter adapt-to-position workflows, and increasing slots to 60min for longer, adapt-to-shape workflows.
is owed to the large uncertainty of the SbS signal3,4. Of the 18 error fields, 17 were detected with the IQM, along with a 1.1% rate of false positives from the clinical fields. Based on this detection performance, the IQM can be implemented as the primary PSQA device in our clinic. References: 1. Islam, MK. et al. An integral quality monitoring system for real-time verification of intensity modulated radiation therapy. Medical Physics. 2009 Dec 1;36(12):5420–8. 2. Alharthi, T. et al. An investigation of the IQM signal variation and error detection sensitivity for patient specific pre-treatment QA. Physica Medica. 2021 Jun 1;86:6–18. 3. Pasler, M. et al. Error detection capability of a novel transmission detector: a validation study for online VMAT monitoring. Phys Med Biol. 2017 Sep 1;62(18):7440– 50. 4. Razinskas, G. et al. Sensitivity of the IQM transmission detector to errors of VMAT plans. Medical Physics. 2018 Dec 1;45(12):5622–30. Keywords: IQM, PSQA, verification Poster Discussion 2000 Automated plan QA for online adapted radiotherapy Leah McDermott, Sandra Fisher Radiation Oncology, Austin Health, Melbourne, Australia Purpose/Objective: Quality assurance for radiotherapy has taken many forms with advances in technology over recent decades. With the advent of online-adapted radiotherapy, traditional pre-treatment phantom measurements are no longer feasible. Imaging, adaption, optimisation, verification and delivery, allow no time for measurement QA. Instead, the focus must turn to effective processes based on essential QA principles – 1) error prevention and 2) record of accuracy, resources permitting. As a result of the complex workflows associated with MR-guided radiotherapy, many centres have introduced a ‘sanity check’ – a QA process that efficiently and accurately assesses and records parameters before delivery. We developed a tool: ‘Plan Adaption Sanity Check’ (PASC), to perform necessary QA tasks prior to online-adapted treatment for the MR-Linac. The aim of this work was to create an integrated online-adaption safety management QA tool and demonstrate how the format and function enables alerts for discrepancies and data for trials and clinical optimisation. Material/Methods: PASC (developed in-house, Python v3.8), reads treatment data from MOSAIQ and Monaco (Elekta) planning system to semi-automate QA processes for
Conclusion: Essential QA tasks can be performed efficiently and accurately for online adaption with automated plan checking tools, replacing traditional measurement QA
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