Personalized Motion Management for Truly 4D Lung Radiotherapy

众所周知，意外的呼吸诱导运动可能会导致严重的错误 胸部放射治疗(RT)的计划剂量与交付剂量相比，导致局部区域失败和/或增加 辐射毒性。在这项建议中，我们建立在我们之前的运动管理研究和目标的基础上 为了克服当前运动管理策略的局限性，这些策略往往不能充分代表 呼吸运动的广度和时空复杂性。我们的总体前提是，当我们的领域采用 越来越强大的RT、实时单点监控需要被实时取代 用于捕捉复杂运动的体积监控。最近推出的集成磁共振成像技术 (MRI)+直线加速器系统旨在解决当前传统解决方案的局限性。然而，高昂的成本 这些系统的复杂性以及工程和技术挑战已被证明是 它们在临床上的广泛应用存在很大障碍(不到美国直线加速器安装总数的1%)。 为了解决这一未得到满足的临床需求，我们形成了学术和产业合作伙伴关系，以研究和 开发一种结合4DMRI和4DCT的新型肺RT室内实时运动管理解决方案 (4D=3D+时间)。在目标1中，我们开发和研究了快速4DMRI技术。在目标2中，我们将 从4DMRI和4DCT获得的体积运动信息可创建特定于患者的多周期运动 将CT的几何保真度和电子密度信息与软组织相结合的模型 对比度和剂量免费，通过MRI进行长期监测。该模型由空间位置的 将与MRI兼容的电磁(EM)传感器放置在患者的胸腹表面。通过 知道这些传感器在任何给定时间点的位置，我们就可以估计出 照射体积内的每个体素。在每个处理分数处，使用室内千伏重建模型 在分娩前进行透视，以说明外部-内部的片间(每日)变化 在剂量传递过程中使用千伏荧光进行通信和更新，以考虑分数内的变化。在AIM 3、我们开发了两个相同的临床前原型系统(EndoScoutRT)，并组成了最终用户团队 制定临床工作流程、质量保证指南和临床翻译策略。在目标4中，我们 通过进行前瞻性非干预性临床试验，对原型系统进行最终用户评估 对两个机构的44例肺癌患者进行了研究。我们比较了我们基于模型的运动的性能 管理到当前的护理标准和基于MRI+LINAC的实时运动管理。我们队有 在临床研究设计、图像引导RT、快速磁共振成像和实时运动管理方面拥有丰富的专业知识。 我们预计，这种方法的成功临床翻译(超出当前范围)将使 更安全地使用高效和临床有效的胸腔RT。

It is well-recognized that unanticipated respiration-induced motion can result in significant errors in planned vs delivered dose in thoracic radiotherapy (RT), resulting in local regional failure and/or increased radiation-induced toxicity. In this proposal, we build upon our previous motion management research and aim to overcome the limitations of current motion management strategies, which tend to underrepresent both the extent and the spatiotemporal complexity of respiratory motion. Our overall premise is that, as our field adopts increasingly more potent forms of RT, real-time single-point monitoring needs to be replaced by real-time volumetric monitoring to capture complex motion. Recently available integrated magnetic resonance imaging (MRI)+Linac systems aim to address the limitations of current conventional solutions. However, the high cost and complexity of these systems, as well as engineering and technological challenges, have proven to be substantial barriers to their widespread clinical adoption (less than 1% of the total US install base for linacs). To address this unmet clinical need, we form an academic-industrial partnership to investigate and develop a novel in-room real-time motion management solution for lung RT that combines 4DMRI and 4DCT (4D=3D+time). In Aim 1, we develop and investigate rapid 4DMRI techniques. In Aim 2, we merge the volumetric motion information derived from 4DMRI and 4DCT to create a patient-specific, multi-cycle motion model that incorporates the geometric fidelity and electron density information from CT with the soft-tissue contrast and dose-free, long-term monitoring from MRI. This model is parameterized by the spatial positions of MRI-compatible electromagnetic (EM) sensors placed on the thoracoabdominal surface of the patient. By knowing the position of these sensors at any given time point, we can estimate the corresponding position of each voxel within the irradiated volume. At each treatment fraction, the model is rebuilt using in-room kV fluoroscopy prior to delivery to account for inter-fraction (day-to-day) changes in external-internal correspondence and updated using kV fluoro during dose delivery to account for intra-fraction changes. In Aim 3, we develop two identical preclinical prototype systems (EndoScoutRT) and form end-user teams tasked with formulating clinical workflows, quality assurance guidelines, and strategies for clinical translation. In Aim 4, we perform end-user evaluation of the prototype systems by conducting a prospective non-interventional clinical study in 44 lung cancer patients at two institutions. We compare the performance of our model-based motion management to current standard-of-care and MRI+Linac based real-time motion management. Our team has extensive expertise in clinical study design, image-guided RT, rapid MRI, and real-time motion management. We anticipate that the successful clinical translation of this approach (beyond the current scope) will enable safer administration of highly potent and clinically effective forms of thoracic RT.