Investigating Radiation-Induced Injury to Airways and Pulmonary Vasculature in Lung SABR

研究 Lung SABR 中辐射引起的气道和肺血管损伤

• 批准号: 9335323
• 负责人: Amit Sawant
• 金额: $ 58.61万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-19 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9335323
• 关键词: Address; Algorithms; Anatomy; Atelectasis; Biological; Bronchi; Bronchial Tree; Bronchoscopy; Caliber; Cancer Patient; Clinical; Clinical Protocols; Clinical Research; Clinical Treatment; Collaborations; Computer software; Data; Disease; Dose; Education; Elements; Environmental air flow; Evaluation; Fibrosis; Goals; Guidelines; High Resolution Computed Tomography; Image; Impairment; Individual; Industrialization; Injury; Investigation; Knowledge; Lesion; Lobar; Lobar bronchus structure; Lung; Malignant neoplasm of lung; Maps; Medical; Medical center; Minor; Minority; Modeling; Multicenter Studies; Non-Small-Cell Lung Carcinoma; Organ; Patients; Perfusion; Peripheral; Physicians; Population; Practice Guidelines; Primary Neoplasm; Process; Public Health; Pulmonary vessels; Quality of life; Radiation; Radiation Injuries; Radiation Pneumonitis; Radiation Tolerance; Radiation induced damage; Radiation therapy; Readability; Research; Residual state; Respiration; Respiratory physiology; Risk; Site; Stenosis; Structure; System; Techniques; Technology; Testing; Toxic effect; Translating; Tumor stage; Work; X-Ray Computed Tomography; base; cancer therapy; clinical practice; clinical translation; clinically translatable; follow-up; functional loss; high dimensionality; image guided; industry partner; novel; patient population; perfusion imaging; pre-clinical; prospective; prototype; public health relevance; pulmonary function; quality assurance; radiation effect; radiation-induced injury; radiosensitive; response; single photon emission computed tomography; treatment planning; tumor; virtual

 DESCRIPTION (provided by applicant): We form an academic-industrial collaboration to investigate and create a clinically translatable solution that accounts for a poorly-understood aspect of pulmonary toxicity in lung stereotactic ablative radiotherapy (SAbR) - radiation injury to branching serial structures (BSS), i.e., airways and pulmonary vessels. Lung SAbR involves the precise administration of very high, biologically potent doses (54-70 Gy) in relatively few fractions. While this highly successful technique has been demonstrated to achieve excellent 5-year local control (>90%), the use of such potent doses puts patients at risk for collateral toxiciy including radiation pneumonitis and radiation injury to airways, causing stenosis, atelectasis and ultimately fibrosis. A common limitation of current treatment planning strategies is that they use a relatively crude model of the lung as a uniform, solely parallel organ. There is compelling clinical evidence to show that this simplistic approach has limited power to predict and/or avoid toxicity. In order to address this gap in current knowledge, we propose the integration of virtual bronchoscopy technology into the radiation treatment planning process to map BSS segments, quantify their radiosensitivity and create treatment plans that limit dose to these structures. We hypothesize that anatomically variable radiation injury to the elements of the bronchial tree and pulmonary vasculature is an important determinant of post-SAbR toxicity and residual pulmonary function. We test this hypothesis through Aims 1-3 and develop a clinical translation framework for end-user evaluation of a prototype system in Aim 4. In Aim 1, we will perform a prospective clinical study with 40 lung cancer patients to assess the relationship between dose and radiation injury to BSS segments. Broncus will adapt their virtual bronchoscopy algorithms to create LungPointRT. This software will enable BSS autosegmentation and DICOMRT export. We will compute the dose to each segment and compare pre-SAbR and 8-12 months post-SAbR CT scans to assess radiation-induced segmental collapse. In Aim 2, we will acquire pre- and post-SAbR ventilation/perfusion (V/Q) SPECT-CT scans to spatially map the localized loss of pulmonary function, and determine the association between segmental collapse (Aim 1) and localized functional loss (Aim 2). These data will be used to estimate dose thresholds for each segment type. In Aim 3, we will develop novel treatment planning strategies that account for BSS radiosensitivity. In order to account for the increased complexity of the optimization problem, we will investigate parallelized global optimization implemented on graphic processor unit (GPU) platform. The optimization algorithms will be integrated into a research version of a clinical treatment planning system (TPS), Eclipse. In Aim 4, we will create a pre-clinical prototype system for end-user evaluation. The TPS and the LungpointRT will be installed on a GPU workstation. We will form an end-user evaluation team consisting of a physician, physicist and dosimetrist. The team will work with developers to iteratively refine user interfaces and clinical workflow, and to develop practice guidelines and education frameworks to facilitate clinical translation.

 描述（由申请人提供）：我们开展学术-工业合作，研究并创建一种可临床转化的解决方案，该解决方案解决了肺部立体定向消融放射治疗（SAbR）中肺毒性的一个鲜为人知的方面——对分支串行结构（BSS）（即气道和肺血管）的辐射损伤。 Lung SAbR 涉及以相对较少的分次精确施用非常高的生物有效剂量（54-70 Gy）。虽然这种非常成功的技术已被证明可以实现出色的 5 年局部控制（>90%），但使用如此强效的剂量会使患者面临附带毒性的风险，包括放射性肺炎和气道放射损伤，导致狭窄、肺不张并最终导致纤维化。当前治疗计划策略的一个常见限制是它们使用相对粗糙的肺模型作为统一的、完全平行的器官。有令人信服的临床证据表明，这种简单化的方法预测和/或避免毒性的能力有限。为了弥补当前知识中的这一差距，我们建议将虚拟支气管镜技术整合到放射治疗计划过程中，以绘制 BSS 片段、量化其放射敏感性并制定限制这些结构剂量的治疗计划。我们假设对支气管树和肺血管系统的解剖学变异辐射损伤是 SAbR 后毒性和残余肺功能的重要决定因素。我们通过目标 1-3 测试这一假设，并开发一个临床转化框架，用于最终用户评估目标 4 中的原型系统。在目标 1 中，我们将对 40 名肺癌患者进行一项前瞻性临床研究，以评估剂量与 BSS 节段辐射损伤之间的关系。 Broncus 将调整其虚拟支气管镜算法来创建 LungPointRT。该软件将启用 BSS 自动分段和 DICOMRT 导出。我们将计算每个节段的剂量，并比较 SAbR 前和 SAbR 后 8-12 个月的 CT 扫描，以评估辐射引起的节段塌陷。在目标 2 中，我们将获取 SAbR 前和后通气/灌注 (V/Q) SPECT-CT 扫描，以空间映射局部肺功能丧失，并确定节段塌陷（目标 1）和局部功能丧失（目标 2）之间的关联。这些数据将用于估计每个分段类型的剂量阈值。在目标 3 中，我们将制定考虑 BSS 放射敏感性的新型治疗计划策略。为了解决优化问题复杂性增加的问题，我们将研究在图形处理器单元（GPU）平台上实现的并行全局优化。优化算法将集成到临床治疗计划系统 (TPS) Eclipse 的研究版本中。在目标 4 中，我们将创建一个用于最终用户评估的临床前原型系统。 TPS 和 LungpointRT 将安装在 GPU 工作站上。我们将组建一个由医生、物理学家和剂量师组成的最终用户评估团队。该团队将与开发人员合作，迭代完善用户界面和临床工作流程，并制定实践指南和教育框架以促进临床转化。