S1956
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
1 Radiation Oncology, St. Luke's Radiation Oncology Network, Dublin, Ireland. 2 Department of Neurosurgery, Beaumont Hospital, Dublin, Ireland Purpose/Objective: Benign base of skull (BOS) tumours are often treated with radiosurgery or fractionated stereotactic radiotherapy. These lesions develop along critical nerves, glands, and brainstem, located in heterogeneous tissue environments amongst air, cartilage, bone, and tissue. Clinical expectations in tumour response and dose-volume toxicities are based on simplistic dose calculation models (e.g. pencil beam). With the availability of fast Monte Carlo planning systems, the question is raised whether the community should shift to a more accurate dose calculation and how to adapt current clinical knowledge to the new regime. Material/Methods: Twelve (12) patients with optic pathway meningiomas previously treated with fractionated radiotherapy (9 x 50.4Gy delivered over 28 fractions and 3 x 25Gy in 5 fractions) were planned with Elements Cranial SRS (BrainlabTM) utilizing a pencil beam algorithm. Follow- up radiology reports and patient clinical notes were reviewed for tumour response and toxicities. All plans were recalculated with Monte Carlo algorithm (2%/2mm; Dose to medium) and dose to the target and the proximal organs at risk (ipsilateral optic nerve, chiasm, and pituitary) was recorded. Correspondence of tumour response and toxicities to dose was investigated. Results: All 12 patients presented with vision distortion and reduced acuity prior to radiotherapy. Mean target volume was 4.025cc [0.42 – 14.97]. One year post radiotherapy, all patients’ lesions were reported as stable. The most common reported side-effects were headache and fatigue. In 10 patients, visual acuity was either reported as stable or improved following treatment. Dosimetric analysis showed that in 11 patients target coverage was reduced after recalculation with Monte Carlo. The volume receiving the full prescription (VRx) reduced by up to 97%. V95% was reduced by up to 21.3% (Table 1) and for 4 patients V95% was below 90%. Institutional dose volume constraints to OARs were exceeded for one patient. Dose increase to the chiasm D0.035cc was up to 20.5% (Tables 2&3).
median Likert score of 5 and 4.5, respectively). Usability was rated highly, with all participants finding the experience pleasant and comfortable (median: 4). Moreover, collaborative interaction was also rated favorably (median: 4). The system was generally found to be simple and intuitive (median: 4). Participants recognized a high potential for clinical adoption and regarded integration into routine workflows as conceivable (median: 4). Regarding key use cases, the system was deemed most valuable for complex cases, including multiple brain metastases, re-irradiations, and plans with tight OAR proximity (e.g., acoustic neuroma). Users liked the "easy perception of spatial relationships" (mentioned by four participants) and “viewing from different angles” (mentioned by two). Criticisms centered on performance lag caused by the network connectivity and the desire to also show the
DVHs in parallel.
Conclusion: This study provides evidence that immersive 3D visualization considerably enhances spatial perception for complex radiotherapy plan evaluation, a critical limitation of conventional 2D-based reviews. The high user acceptance and perceived utility in complex cases (e.g., SRS and multiple brain metastases) underscore the technology's potential as a powerful collaborative tool. To achieve widespread clinical integration, future development should prioritize performance optimization, interaction design refinement, and, most importantly, embedding quantitative data (e.g., DVHs) from traditional 2D visualizations into 3D models. Keywords: Extended Reality, Virtual Reality, 3D Digital Poster 3837 Monte Carlo calculations for optic pathway meningiomas – determining the right prescription for tumour response Christina Skourou 1 , David Leen 1 , Lynda Fennell 1 , Donal Cummins 1 , David Fitzpatrick 1 , Darragh Browne 1 , Mohsen Javadpour 2 , Clare Faul 1
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