S1879
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
Digital Poster 2236
generated in Eclipse v18 (P1);Robust plan optimized in RayStation and recalculated on all CBCTs (P2). Robustness was optimized on CTV homogeneity and minimum dose, and on maximum dose to rectum and bladderDose constraints (bladder: V60 ≤ 5%, V48 ≤ 25%, V41 ≤ 50%; rectum: V46 ≤ 30%, V37 ≤ 50%) were assessed per fraction, normalized to 3 Gy. Statistical differences were tested using Friedman and post-hoc analysis.At this stage, only per-fraction dose distributions were evaluated to capture daily anatomical variability, avoiding confounding factors from dose accumulation. Results: Fractions with CTV V95% < 95% were 2.0%, 0%, and 0.5% for P0, P1, and P2, respectively. Mean CTV V95% was 98.4%, 100%, and 99.5% (Figure 1.A). Bladder V60 ≤ 5% failed in 4.2% (3.4%, 0.5%, 0.3% for P0, P1, P2) (Figure 1.B). Rectum V46 ≤ 30% failed in 1.4% of fractions, all in P0 (Figure 1.C). Differences were significant for bladder (p = 0.022) and rectum (p = 0.039), mainly between P0–P1 and P0–P2, only at 3 Gy. Post-hoc analysis found a statistically significant difference between P0 and P1 (p=0.030) for bladder and between P0 and P2 (p=0.036) for rectum.
Evaluation of Dose Calculation Accuracy between AAA and CCC Algorithms in Eclipse and RayPlan for Halcyon and Shinva 600E in SIB VMAT HN Plans. Rashmi D Puranik, Lingampalli Narsaiah, Jagadish R Radiation Oncology, Indrayani Hospital & Cancer Institute, Pune, India Purpose/Objective: This study aims to compare two volumetric modulated arc therapy (VMAT) planning techniques generated using two different treatment planning systems (TPSs): RayPlan with the collapsed cone convolution (CCC) algorithm and Eclipse with the anisotropic analytical algorithm (AAA). The comparison focuses on dosimetric performance in the treatment of head and neck (HN) cancer using flattened (FF) and flattening filter-free (FFF) photon beams. Material/Methods: A total of 30 head and neck cancer patients were retrospectively analyzed. For each patient, two VMAT plans were created using RayPlan 12A SP1 (Shinva 600E linac, 6 MV FF) and Eclipse version 16.1 (Halcyon- B Varian, 6 MV FFF). Both systems employed multileaf collimators (MLCs) with a 1 cm leaf width at the isocenter. Dose distributions for the planning target volume (PTV) and organs at risk (OARs) were compared. Plan quality was evaluated using the conformity index (CI), homogeneity index (HI), and gradient index (GI), derived from dose–volume histograms (DVHs). Results: Both TPSs produced clinically acceptable target coverage and OAR sparing. · PTV70:o HI (CCC vs. AAA): 0.1345 ± 0.0343 vs.0.1083 ± 0.0211 (p =0.086)o CI: CCC (0.9371 ± 0.0170) vs. AAA (0.9737 ± 0.0177, p <0.05)o GI: CCC (1.2982 ± 0.1983) vs. AAA (1.21 ± 0.0926, p = 0.42)· PTV56:o HI (CCC vs. AAA): 0.2186 ± 0.0102 vs.0.2251 ± 0.0302 (p = 0.654)o CI: CCC (0.9771 ± 0.0046) vs. AAA (0.9957 ± 0.0003, p < 0.05 )o GI: CCC (2.2711 ± 0.5745) vs. AAA (2.1163 ± 0.4521, p = 0.57)OAR doses were broadly comparable between algorithms:· Spinal cord (max): CCC (3667.85 ± 89.43 cGy) vs. AAA (3506.8 ± 218.77 cGy), p< 0.05· Brainstem (max): CCC (3525 ± 303.77 cGy) vs. AAA (3017.5 ± 1193 cGy), (p < 0.05)· Mean L-parotid dose: CCC (3636.85 ± 1691.21 Gy) vs. AAA (3618.8 ± 1390.95 cGy), p = 0.908Mean R-parotid dose: CCC (3636.143 ± 1700.5 Gy) vs. AAA (3290.143 ± 1889.43 cGy), p = 0.056 Conclusion: Both RayPlan (CCCS) and Eclipse (AAA) generated high- quality VMAT plans for head and neck cancer treatment. Although Eclipse with FFF beams achieved significantly improved conformity, the overall dosimetric performance of both systems was clinically acceptable, indicating that either TPS can be effectively
Conclusion: Robust planning achieved CTV coverage and OAR sparing comparable to daily oART, with consistent performance across all fractions. This strategy may represents a practical alternative to full daily adaptation, reducing workload while maintaining treatment safety. Keywords: oART, robust plan optimization, prostate
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