Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
Department of Radiotherapy and Radiation Oncology, Paracelsus Medical University, Landeskrankenhaus, Salzburg, Austria.
Med Phys. 2019 Jul;46(7):3268-3277. doi: 10.1002/mp.13579. Epub 2019 Jun 7.
The need for four-dimensional (4D) treatment planning becomes indispensable when it comes to radiation therapy for moving tumors in the thoracic and abdominal regions. The primary purpose of this study is to combine the actual breathing trace during each individual treatment fraction with the Linac's log file information and Monte Carlo 4D dose calculations. We investigated this workflow on multiple computed tomography (CT) datasets in a clinical environment for stereotactic body radiation therapy (SBRT) treatment planning.
We have developed a workflow, which allows us to recalculate absorbed dose to a 4DCT dataset using Monte Carlo calculation methods and accumulate all 4D doses in order to compare them to the planned dose using the Linac's log file, a 4DCT dataset, and the patient's actual breathing curve for each individual fraction. For five lung patients, three-dimensional-conformal radiation therapy (3D-CRT) and volumetric modulated arc treatment (VMAT) treatment plans were generated on four different CT image datasets: a native free-breathing 3DCT, an average intensity projection (AIP) and a maximum intensity projection (MIP) CT both obtained from a 4DCT, and a 3DCT with density overrides based on the 3DCT (DO). The Monte Carlo 4D dose has been calculated on each 4DCT phase using the Linac's log file and the patient's breathing trace as a surrogate for tumor motion and dose was accumulated to the gross tumor volume (GTV) at the 50% breathing phase (end of exhale) using deformable image registration.
and between 4D dose and planned dose differed largely for 3DCT-based planning and also for DO in three patients. Least dose differences between planned and recalculated dose have been found for AIP and MIP treatment planning which both tend to be superior to DO, but the results indicate a dependency on the breathing variability, tumor motion, and size. An interplay effect has not been observed in the small patient cohort.
We have developed a workflow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workflow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out.
当涉及到胸部和腹部移动肿瘤的放射治疗时，四维（4D）治疗计划变得不可或缺。本研究的主要目的是将每个治疗分次的实际呼吸轨迹与直线加速器日志文件信息和蒙特卡罗 4D 剂量计算相结合。我们在立体定向体部放射治疗（SBRT）治疗计划的临床环境中，对多个计算机断层扫描（CT）数据集进行了这项工作流程的研究。
我们开发了一种工作流程，允许我们使用蒙特卡罗计算方法重新计算 4DCT 数据集的吸收剂量，并累积所有 4D 剂量，以便将其与直线加速器日志文件、4DCT 数据集和每个分次的患者实际呼吸曲线进行比较。对于五名肺癌患者，在四个不同的 CT 图像数据集上生成了三维适形放射治疗（3D-CRT）和容积调制弧形治疗（VMAT）治疗计划：一个自由呼吸的 3DCT 原始图像、一个从 4DCT 获得的平均强度投影（AIP）和最大强度投影（MIP）CT 图像、以及一个基于 3DCT 的密度覆盖（DO）的 3DCT。使用直线加速器日志文件和患者呼吸轨迹作为肿瘤运动的替代物，在每个 4DCT 相位上计算了蒙特卡罗 4D 剂量，并使用变形图像配准将剂量累积到 50%呼吸相（呼气末）的大体肿瘤体积（GTV）。
在三个患者中，基于 3DCT 的计划和 DO 的 4D 剂量与计划剂量之间存在很大差异。AIP 和 MIP 治疗计划的计划剂量与重新计算剂量之间的差异最小，这两种方法都优于 DO，但结果表明其依赖于呼吸变异性、肿瘤运动和大小。在小患者队列中没有观察到相互作用效应。
我们开发了一种工作流程，据我们所知，这是首次将患者在整个治疗分次过程中的呼吸轨迹与直线加速器日志文件信息以及实际治疗剂量的 4D 蒙特卡罗重新计算相结合。由于患者队列较小，因此无法就哪种 CT 可用于 SBRT 治疗计划提供明确建议，但经过临床应用改编后，该开发工作流程可用于增强未来的先验 4D 蒙特卡罗治疗计划，并有助于确定应进行哪种 CT 数据集治疗计划。
