权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Personalized Motion Management for Truly 4D Lung Radiotherapy

真正 4D 肺部放射治疗的个性化运动管理

基本信息

批准号：
10674801
负责人：
THOMAS M ERNST
金额：
$ 60.29万
依托单位：
UNIVERSITY OF MARYLAND BALTIMORE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-16 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10674801
关键词：
3-Dimensional Address Adopted Adoption Aftercare Anatomy Breathing Cancer Patient Chest Clinical Clinical Research Collaborations Combined Modality Therapy Complex Data Dose Electromagnetics Engineering Evaluation Failure Fluoroscopy Four-dimensional Guidelines Imaging Techniques Industrialization Institution Lead Location Lung Magnetic Resonance Imaging Malignant neoplasm of lung Maryland Medical Modeling Monitor Motion Optics Organ Patients Performance Photogrammetry Positioning Attribute Prospective Studies Quality of life Radiation Radiation therapy Research Research Design Respiration Risk Robin bird Shapes Structure of parenchyma of lung Surface System Techniques Technology Testing Time Toxic effect Update Variant base clinical translation cost electron density experience four-dimensional computed tomography image guided image guided radiation therapy industry partner interest novel pre-clinical prospective prototype quality assurance radiation delivery real time monitoring respiratory response sensor side effect simulation soft tissue spatiotemporal standard of care translational approach tumor

项目摘要

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.

众所周知，意外的呼吸引起的运动可能导致在测量中的显著误差。胸部放疗（RT）中的计划剂量与输送剂量，导致局部区域失败和/或增加辐射引起的毒性。在这个建议中，我们建立在我们以前的运动管理研究和目标，为了克服当前运动管理策略的局限性，这些策略往往低估了程度和呼吸运动的时空复杂性。我们的总体前提是，随着我们的领域采用越来越多的有效的RT形式，实时单点监测需要被实时体积监测以捕获复杂的运动。最近可用的集成磁共振成像 (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，已被证明是其广泛临床应用的实质性障碍（不到美国直线加速器总安装基数的1%）。为了解决这一未得到满足的临床需求，我们建立了学术-工业合作伙伴关系，为肺部RT开发一种结合4DMRI和4DCT的新型室内实时运动管理解决方案 (4D=3D+时间）。在目标1中，我们开发和研究快速4DMRI技术。在目标2中，我们将从4DMRI和4DCT导出的体积运动信息，以创建患者特定的多周期运动一种模型，将来自CT的几何保真度和电子密度信息与软组织结合起来造影剂和无剂量，长期监测MRI。该模型由以下空间位置参数化： MRI兼容电磁（EM）传感器放置在患者胸腹表面。通过知道这些传感器在任何给定时间点的位置，我们可以估计照射体积内的每个体素。在每个治疗部分，使用室内kV重建模型在分娩前进行荧光透视，以说明外部-内部的部分间（日常）变化在剂量输送期间使用kV荧光透视进行更新，以说明部分内变化。在Aim中 3.我们开发了两个相同的临床前原型系统（EndoScoutRT），并组建了最终用户团队，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，通过进行前瞻性非介入性临床试验，对原型系统进行最终用户评价在两个机构的44名肺癌患者中进行的研究。我们比较我们的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。我们的团队已被在临床研究设计、图像引导RT、快速MRI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转化（超出目前的范围）将使更安全地给予高效和临床有效形式的胸部RT。