Cavus Hasan, Rondagh Thierry, Jankelevitch Alexandra, Tournel Koen, Orlandini Marc, Bulens Philippe, Delombaerde Laurence, Geens Kenny, Crijns Wouter, Reniers Brigitte
Department of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Limburg Oncology Center, 3500 Hasselt, Belgium.
Phys Imaging Radiat Oncol. 2024 Aug 3;31:100619. doi: 10.1016/j.phro.2024.100619. eCollection 2024 Jul.
In radiotherapy treatment planning, optimization is essential for achieving the most favorable plan by adjusting optimization criteria. This study introduced an innovative approach to automatically fine-tune optimization parameters for volumetric modulated arc therapy prostate planning, ensuring all constraints were met. A knowledge-based planning model was invoked, and the fine-tuning process was applied through an in-house developed script. Among 25 prostate plans, this fine-tuning increased the number of plans meeting all constraints from 10/25 to 22/25, with a reduction in mean monitor units per gray without increasing plan's complexity. This automation improved efficiency by saving time and resources in treatment planning.
在放射治疗治疗计划中，优化对于通过调整优化标准来实现最有利的计划至关重要。本研究引入了一种创新方法，用于自动微调容积调强弧形治疗前列腺计划的优化参数，确保满足所有约束条件。调用了基于知识的计划模型，并通过内部开发的脚本应用微调过程。在25个前列腺计划中，这种微调使满足所有约束条件的计划数量从10/25增加到22/25，同时在不增加计划复杂性的情况下，每灰度的平均监测单位数减少。这种自动化通过节省治疗计划中的时间和资源提高了效率。
