Author: Hao Gao, Yuting Lin, Jufri Setianegara, Aoxiang Wang, Peng Xiao, Qingguo Xie, Yanan Zhu 👨🔬
Affiliation: Department of Biomedical Engineering, Huazhong University of Science and Technology, Department of Radiation Oncology, University of Kansas Medical Center 🌍
Purpose: Intensity-modulated proton therapy (IMPT) achieves uniform tumor dose distribution while sparing organs-at-risk (OAR) by optimizing spot weights across energy layers. Accelerating IMPT delivery improves treatment efficiency and reduces motion-induced uncertainties. A practical approach is minimizing energy layers, yet most studies emphasize algorithmic methods without experimental validation due to the proprietary nature of clinical treatment planning systems (TPS). This study introduces an in-house TPS (IH-TPS) with a novel energy layer optimization (ELO) method, validated experimentally for accelerating IMPT delivery.
Methods: Within the dose calculation module, the beam data of IH-TPS is calculated from RayStation TPS. For planning, a novel ELO method based on a greedy selection algorithm reduces energy layers. The RayStation dose serves as the reference for calculating the 3D gamma index, validating treatment plans under various conditions. Patient-specific quality assurance (QA) experiments for each beam assessed the accuracy of dose delivery.
Results: The 3D gamma index comparing IH-TPS and RayStation TPS consistently exceeded 95% (2mm, 2%). The ELO method effectively reduced energy layers and delivery time while maintaining clinical plan quality. For example, in a brain case, reducing energy layers from 78 to 40 achieved a 62% delivery time reduction. Validation on the IBA Proteus®ONE proton machine showed >95% pass rates across all beams.
Conclusion: A novel ELO algorithm was implemented in an IH-TPS and experimentally validated, enabling faster IMPT delivery without compromising plan quality, significantly enhancing treatment efficiency.