Osburg Aaron Paul, Lysakovski Peter, Magro Giuseppe, Harrabi Semi, Haberer Thomas, Abdollahi Amir, Debus Jürgen, Tessonnier Thomas, Mairani Andrea
Faculty of Physics and Astronomy, Heidelberg University, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany.
Heidelberg Ion-Beam Therapy Center (HIT), Im Neuenheimer Feld 450, 69120 Heidelberg, Germany.
Phys Imaging Radiat Oncol. 2024 Nov 20;32:100679. doi: 10.1016/j.phro.2024.100679. eCollection 2024 Oct.
In carbon ion radiotherapy (CIRT), different relative biological effectiveness (RBE) models have been used for calculating RBE-weighted dose (D). Conversion between current RBE predictions and introduction of novel approaches remains a challenging task. Our aim is to introduce a framework considering multiple RBE models simultaneously during CIRT plan optimization, easing the translation between D prescriptions.
An in-house developed Monte Carlo treatment planning system was extended to incorporate the local effect model version I (LEM-I), the modified microdosimetric kinetic model (mMKM) and the MKM-derived Japanese biological model (NIRS-MKM). Four clinical cases (two head-and-neck and two prostate patients), initially optimized with LEM-I for both targets and organs at risk (OARs), underwent two further optimizations: to fulfill mMKM/NIRS-MKM-based target prescriptions (mixed-RBE approach) or to simultaneously consider two biological models within the target regions (multi-RBE approach). Both approaches retained LEM-I-derived dose constraints for OARs.
The developed optimization strategies have been successfully applied, fulfilling all the clinical criteria for the applied RBE models. One of the RBE models showed unfavorable dose distribution when not explicitly considered in the optimization, while multi-RBE model optimization allowed meeting dose objectives for the selected OARs for both models simultaneously.
The introduced optimization approaches allow for mixed- or multi-RBE optimization in CIRT through the selection of RBE models independently for each region of interest. This capability addresses challenges of adhering to multiple RBE frameworks and proposes an advanced solution for tailored patient treatment plans.
在碳离子放射治疗（CIRT）中，不同的相对生物效应（RBE）模型已被用于计算RBE加权剂量（D）。当前RBE预测之间的转换以及新方法的引入仍然是一项具有挑战性的任务。我们的目的是在CIRT计划优化过程中引入一个同时考虑多个RBE模型的框架，简化D处方之间的转换。
对内部开发的蒙特卡罗治疗计划系统进行扩展，以纳入局部效应模型版本I（LEM-I）、修正的微剂量动力学模型（mMKM）和MKM衍生的日本生物模型（NIRS-MKM）。四个临床病例（两名头颈癌患者和两名前列腺癌患者），最初使用LEM-I对靶区和危及器官（OARs）进行优化，随后又进行了两次优化：以满足基于mMKM/NIRS-MKM的靶区处方（混合RBE方法）或在靶区内同时考虑两种生物模型（多RBE方法）。两种方法都保留了基于LEM-I得出的OARs剂量约束。
所开发的优化策略已成功应用，满足了所应用RBE模型的所有临床标准。当在优化过程中未明确考虑时，其中一种RBE模型显示出不利的剂量分布，而多RBE模型优化能够同时满足两种模型所选OARs的剂量目标。
所引入的优化方法允许通过为每个感兴趣区域独立选择RBE模型，在CIRT中进行混合或多RBE优化。这一能力解决了遵循多个RBE框架的挑战，并为定制患者治疗计划提出了一种先进的解决方案。
