Department of Physics, TU Dortmund University, Dortmund, Germany.
OncoRay-National Center of Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
Med Phys. 2024 Jan;51(1):622-636. doi: 10.1002/mp.16809. Epub 2023 Oct 25.
Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1.
This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses.
The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LET distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives.
In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/β from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp).
The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.
在假设相对生物效应（RBE）为 1.1 的情况下，将光子治疗的危险器官（OAR）耐受剂量应用于质子治疗会引入不确定性。
本研究引入了新颖的脏污剂量概念，该概念允许为 OAR 创建更类似于光子剂量反应的治疗计划，从而在应用基于光子的耐受剂量时减少不确定性。
该概念将 1.1 加权剂量分布分为两部分：清洁剂量和脏污剂量。清洁剂量和脏污剂量分别由线性能量转移（LET）低于和高于设定 LET 阈值的质子沉积。对于前者，假设具有类似于光子的剂量反应，而对于后者，RBE 可能超过 1.1。为了减少 OAR 中的脏污剂量，在治疗计划优化中添加了 MaxDirtyDose 目标。它需要设置两个参数：LET 阈值和最大脏污剂量水平。使用包含一个靶区和一个 OAR 的简单水几何形状，研究了在计划优化过程中选择两个 MaxDirtyDose 目标参数时，OAR 中脏污剂量的减少情况。使用最佳性能参数组合为两个颅部患者病例创建了多个脏污剂量优化（DDopt）治疗计划。对于每个 DDopt 计划，计算并比较了 1.1 加权剂量、使用 Wedenberg RBE 模型的可变 RBE 加权剂量以及剂量平均 LET 分布，以及由此产生的正常组织并发症概率（NTCP）值，与无 MaxDirtyDose 目标的参考计划（RefPlan）进行比较。
在水模研究中，LET 阈值在 1.5 至 2.5 keV/µm 之间产生了最佳的计划，随后被使用。对于患者病例，几乎所有的 DDopt 计划都导致关键 OAR 中的 Wedenberg 剂量降低。这种减少是由于 LET 减少导致的，与 RefPlan 相比，NTCP 减少了高达 19 个百分点。OAR 中的 1.1 加权剂量略有增加（患者 1：0.45 Gy（RBE），患者 2：0.08 Gy（RBE）），但从未超过临床耐受剂量。此外，还观察到健康脑组织中 1.1 加权剂量略有增加（患者 1：0.81 Gy（RBE），患者 2：0.53 Gy（RBE））。对于 DDopt，由于 α/β 从 2 到 3 Gy 的变化导致的 NTCP 值的变化比 RefPlans（5 pp）小得多（2 pp）。
新颖的脏污剂量概念允许创建具有更类似于光子剂量反应的生物学上更稳健的质子治疗计划。RBE 中减少的不确定性可以减轻使用基于光子的 OAR 耐受剂量引入的不确定性。
