Full daily re-optimization improves plan quality during online adaptive radiotherapy

• Published in: Physics and imaging in radiation oncology 2024-01, Vol.29, p.100534, Article 100534
• Main Authors: Tengler, Benjamin, Künzel, Luise A., Hagmüller, Markus, Mönnich, David, Boeke, Simon, Wegener, Daniel, Gani, Cihan, Zips, Daniel, Thorwarth, Daniela
• Format: Article
• Language: English
• Subjects: Adaptive treatment planning; MR-Linac; MRI guided radiotherapy; Online plan optimization; Original
• ISSN: 2405-6316; 2405-6316
• DOI: 10.1016/j.phro.2024.100534

Daily online treatment plan adaptation requires a fast workflow and planning process. Current online planning consists of adaptation of a predefined reference plan, which might be suboptimal in cases of large anatomic changes. The aim of this study was to investigate plan quality differences between the current online re-planning approach and a complete re-optimization. Magnetic resonance linear accelerator reference plans for ten prostate cancer patients were automatically generated using particle swarm optimization (PSO). Adapted plans were created for each fraction using (1) the current re-planning approach and (2) full PSO re-optimization and evaluated overall compliance with institutional dose-volume criteria compared to (3) clinically delivered fractions. Relative volume differences between reference and daily anatomy were assessed for planning target volumes (PTV60, PTV57.6), rectum and bladder and correlated with dose-volume results. The PSO approach showed significantly higher adherence to dose-volume criteria than the reference approach and clinical fractions (p