S1980
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
Digital Poster 4141
Preparation and introduction of a gantry-mounted in-vivo dosimetry chamber for patient treatment Rayk Nachtigall 1 , Sarah Peters 1 , Sebastian Frömbgen 1 , Oliver Bislich 1 , Sebastian Exner 2 , Felix Behrens 2 , Fabian Fehlauer 2 1 Medical Physics, Strahlenzentrum Hamburg MVZ, Hamburg, Germany. 2 Clinician, Strahlenzentrum Hamburg MVZ, Hamburg, Germany Purpose/Objective: Since the introduction and extensive in-house validation of the iQM detector (iRT-Systems) for patient and machine QA, the time required for QA procedures has been significantly reduced without compromising quality. The next step to fully exploit the potential of the iQM system is its use during patient treatment—eliminating the need for a dedicated fraction 0 and enabling real-time monitoring of the delivered dose for each treatment fraction. To ensure consistent treatment quality, the impact of the iQM on the beam was quantified in terms of absorption, shape, and applied dose. Material/Methods: To assess the influence of the iQM, several test fields were defined and irradiated both with and without the iQM mounted. Static 20 × 20 cm ² fields (gantry angles 0°, 90°, 180°, 270°; each with collimator angles 0° and 90°) and VMAT fields were evaluated with and without flattening filter. Measurements were performed using the QuickCheck, ArcCheck, and Octavius 2D-array detectors to determine absorption and to compare beam flatness and symmetry. Absolute dosimetry was conducted in a water phantom using a Farmer-type ionization chamber. Additionally, cross-validation of VMAT and IMRT plans was performed, comparing results with and without the iQM (considering its tray factor) using γ -analysis (3 mm/3%). All measurements were carried out on three Elekta linacs (two Harmony Pro and one Versa HD). Results: The measured absorption varied slightly depending on the detector used but was consistent across linacs and energies: QuickCheck 5.7 ± 0.3%, ArcCheck 5.9 ± 0.2%, Octavius 6.0 ± 0.2%, and water phantom 6.7 ± 0.1%. Differences in normalized flatness (fn < 0.4%) and symmetry (symn < 0.4%) were negligible for all devices. Cross-validation of VMAT plans yielded γ passing rates >98% when comparing iQM plans (with tray factor) to corresponding non-iQM QA plans. Conclusion: Implementation of the iQM detector for in-vivo patient treatment enables real-time dose verification without compromising treatment delivery or prescription accuracy. Furthermore, it eliminates the need for a separate QA fraction, thereby reducing overall QA time
Image2 shows average doses in bladder for 15 treatments planning without and with MCO tool. There is a significant decreases percentage change in doses when using the MCO tool (Dmean decreases 13.4%, V45Gy decreases 13.8% and V40Gy decreases 8.0%) In bowel, there is also a decreases percentage change but not so significant than bladder (Dmean decreases 1.9%; D65cm3 decreases 0.4%).
Conclusion: MCO is a useful tool for reducing doses in OARs while maintaining PTV coverage. An analysis should be conducted of the complexity that this introduces into planning. Keywords: Optimization, Multicriteria-decision
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