Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Institute for Biomedical Engineering, ETH Zürich and PSI, Villigen, Switzerland.
Med Phys. 2022 Jul;49(7):4780-4793. doi: 10.1002/mp.15683. Epub 2022 May 4.
Evaluating plan robustness is a key step in radiotherapy.
To develop a flexible Monte Carlo (MC)-based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity-modulated radiotherapy (IMRT) treatment plans by exploring the impact of systematic and random uncertainties resulting from patient setup, patient anatomy changes, and mechanical limitations of machine components.
The robustness tool consists of two parts: the first part includes automated MC dose calculation of multiple user-defined uncertainty scenarios to populate a robustness space. An uncertainty scenario is defined by a certain combination of uncertainties in patient setup, rigid intrafraction motion and in mechanical steering of the following machine components: angles of gantry, collimator, table-yaw, table-pitch, table-roll, translational positions of jaws, multileaf-collimator (MLC) banks, and single MLC leaves. The Swiss Monte Carlo Plan (SMCP) is integrated in this tool to serve as the backbone for the MC dose calculations incorporating the uncertainties. The calculated dose distributions serve as input for the second part of the tool, handling the quantitative evaluation of the dosimetric impact of the uncertainties. A graphical user interface (GUI) is developed to simultaneously evaluate the uncertainty scenarios according to user-specified conditions based on dose-volume histogram (DVH) parameters, fast and exact gamma analysis, and dose differences. Additionally, a robustness index (RI) is introduced with the aim to simultaneously evaluate and condense dosimetric robustness against multiple uncertainties into one number. The RI is defined as the ratio of scenarios passing the conditions on the dose distributions. Weighting of the scenarios in the robustness space is possible to consider their likelihood of occurrence. The robustness tool is applied on IMRT, a volumetric modulated arc therapy (VMAT), a dynamic trajectory radiotherapy (DTRT), and a dynamic mixed beam radiotherapy (DYMBER) plan for a brain case to evaluate the robustness to uncertainties of gantry-, table-, collimator angle, MLC, and intrafraction motion. Additionally, the robustness of the IMRT, VMAT, and DTRT plan against patient setup uncertainties are compared. The robustness tool is validated by Delta4 measurements for scenarios including all uncertainty types available.
The robustness tool performs simultaneous calculation of uncertainty scenarios, and the GUI enables their fast evaluation. For all evaluated plans and uncertainties, the planning target volume (PTV) margin prevented major clinical target volume (CTV) coverage deterioration (maximum observed standard deviation of was 1.3 Gy). OARs close to the PTV experienced larger dosimetric deviations (maximum observed standard deviation of was 14.5 Gy). Robustness comparison by RI evaluation against patient setup uncertainties revealed better dosimetric robustness of the VMAT and DTRT plans as compared to the IMRT plan. Delta4 validation measurements agreed with calculations by >96% gamma-passing rate (3% global/2 mm).
The robustness tool was successfully implemented. Calculation and evaluation of uncertainty scenarios with the robustness tool were demonstrated on a brain case. Effects of patient and machine-specific uncertainties and the combination thereof on the dose distribution are evaluated in a user-friendly GUI to quantitatively assess and compare treatment plans and their robustness.
评估计划稳健性是放射治疗的关键步骤。
开发一种灵活的基于蒙特卡罗(MC)的稳健性计算和评估工具,通过探索患者摆位、患者解剖结构变化以及机器部件的机械限制引起的系统和随机不确定性的影响,评估和量化调强放疗(IMRT)治疗计划的剂量学稳健性。
稳健性工具由两部分组成:第一部分包括多个用户定义的不确定性场景的自动化 MC 剂量计算,以填充稳健性空间。不确定性场景由患者摆位、刚性分次内运动以及以下机器部件的机械转向中的某些不确定性组合定义:旋转机架角度、准直器、床偏航、床俯仰、床滚转、叶片的平移位置、多叶准直器(MLC)组和单个 MLC 叶片。瑞士蒙特卡罗计划(SMCP)集成到该工具中,作为 MC 剂量计算的骨干,纳入不确定性。计算的剂量分布作为工具第二部分的输入,用于处理不确定性对剂量学影响的定量评估。开发了一个图形用户界面(GUI),根据用户指定的条件同时评估不确定性场景,这些条件基于剂量-体积直方图(DVH)参数、快速准确的伽马分析和剂量差异。此外,引入了稳健性指数(RI),旨在将针对多个不确定性的剂量学稳健性评估和浓缩为一个数字。RI 定义为通过剂量分布上条件的场景的比例。可以对稳健性空间中的场景进行加权,以考虑其发生的可能性。该稳健性工具应用于脑部病例的 IMRT、容积调制弧形治疗(VMAT)、动态轨迹放疗(DTRT)和动态混合束放疗(DYMBER)计划,以评估对旋转机架、床、准直器角度、MLC 和分次内运动不确定性的稳健性。此外,还比较了 IMRT、VMAT 和 DTRT 计划对患者摆位不确定性的稳健性。通过 Delta4 测量对包括所有可用不确定性类型的场景进行了稳健性工具的验证。
稳健性工具能够同时计算不确定性场景,并通过 GUI 快速评估。对于所有评估的计划和不确定性,计划靶区(PTV)的边缘防止了主要临床靶区(CTV)覆盖恶化(最大观察到的标准差为 1.3Gy)。靠近 PTV 的 OAR 经历了更大的剂量学偏差(最大观察到的标准差为 14.5Gy)。通过 RI 评估与患者摆位不确定性的稳健性比较表明,VMAT 和 DTRT 计划的剂量学稳健性优于 IMRT 计划。Delta4 验证测量与计算的伽马通过率>96%(3%全局/2mm)一致。
成功实现了稳健性工具。在脑部病例上演示了使用稳健性工具计算和评估不确定性场景。在用户友好的 GUI 中评估患者和机器特定的不确定性及其组合对剂量分布的影响,以定量评估和比较治疗计划及其稳健性。