Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377 München, Germany; Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching bei München, Germany.
Fraunhofer Institute for Industrial Mathematics (ITWM), Fraunhofer-Platz 1, 67663 Kaiserslautern, Germany.
Z Med Phys. 2019 Aug;29(3):216-228. doi: 10.1016/j.zemedi.2018.10.003. Epub 2018 Nov 5.
Proton radiotherapy (PT) requires accurate target alignment before each treatment fraction, ideally utilizing 3D in-room X-ray computed tomography (CT) imaging. Typically, the optimal patient position is determined based on anatomical landmarks or implanted markers. In the presence of non-rigid anatomical changes, however, the planning scenario cannot be exactly reproduced and positioning should rather aim at finding the optimal position in terms of the actually applied dose. In this work, dose-guided patient alignment, implemented as multicriterial optimization (MCO) problem, was investigated in the scope of intensity-modulated and double-scattered PT (IMPT and DSPT) for the first time. A method for automatically determining the optimal patient position with respect to pre-defined clinical goals was implemented. Linear dose interpolation was used to access a continuous space of potential patient shifts. Fourteen head and neck (H&N) and eight prostate cancer patients with up to five repeated CTs were included. Dose interpolation accuracy was evaluated and the potential dosimetric advantages of dose-guided over bony-anatomy-based patient alignment investigated by comparison of clinically relevant target and organ-at-risk (OAR) dose-volume histogram (DVH) parameters. Dose interpolation was found sufficiently accurate with average pass-rates of 90% and 99% for an exemplary H&N and prostate patient, respectively, using a 2% dose-difference criterion. Compared to bony-anatomy-based alignment, the main impact of automated MCO-based dose-guided positioning was a reduced dose to the serial OARs (spinal cord and brain stem) for the H&N cohort. For the prostate cohort, under-dosage of the target structures could be efficiently diminished. Limitations of dose-guided positioning were mainly found in reducing target over-dosage due to weight loss for H&N patients, which might require adaptation of the treatment plan. Since labor-intense online quality-assurance is not required for dose-guided patient positioning, it might, nevertheless, be considered an interesting alternative to full online re-planning for initially mitigating the effects of anatomical changes.
质子放疗 (PT) 要求在每次治疗前进行精确的靶区对准，理想情况下使用 3D 实时 X 射线计算机断层扫描 (CT) 成像。通常，根据解剖学标志或植入标记来确定最佳患者位置。然而，在存在非刚性解剖结构变化的情况下，无法完全再现计划场景，而应旨在根据实际应用的剂量找到最佳位置。在这项工作中，首次在强度调制和双散射质子治疗 (IMPT 和 DSPT) 的范围内研究了作为多准则优化 (MCO) 问题的剂量引导患者对准。实现了一种用于根据预定义临床目标自动确定最佳患者位置的方法。线性剂量插值用于访问潜在患者移位的连续空间。共纳入了 14 名头颈部 (H&N) 和 8 名前列腺癌患者，他们接受了多达 5 次重复 CT 扫描。通过比较临床相关的靶区和危及器官 (OAR) 剂量体积直方图 (DVH) 参数，评估了剂量插值的准确性，并研究了剂量引导相对于基于骨性解剖的患者对准的潜在剂量学优势。使用 2%剂量差异标准，对于示例性的 H&N 和前列腺患者，剂量插值的平均通过率分别为 90%和 99%，表明剂量插值足够准确。与基于骨性解剖的对准相比，自动 MCO 引导的剂量引导定位的主要影响是减少了 H&N 队列中的串行 OAR（脊髓和脑干）的剂量。对于前列腺队列，可以有效地减少靶区结构的剂量不足。剂量引导定位的局限性主要在于由于 H&N 患者体重减轻而导致的靶区过度剂量，这可能需要调整治疗计划。由于剂量引导患者定位不需要进行劳动密集型的在线质量保证，因此它可能仍然是一种有趣的替代方案，用于在最初缓解解剖结构变化的影响时，可以替代全在线重新计划。
