Diffusion-Weighted Imaging-Based Adaptive Replanning for the MR-Linac

MR-Linac 基于扩散加权成像的自适应重新规划

• 批准号: 10237410
• 负责人: Brigid Anne McDonald
• 金额: $ 3.08万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10237410
• 关键词: Affect; Algorithms; Anatomy; Clinic; Clinical; Clinical Trials; Complication; Data; Data Set; Deglutition; Dental; Development; Devices; Diffusion Magnetic Resonance Imaging; Dose; Feedback; Foundations; Functional Imaging; Functional Magnetic Resonance Imaging; Geometry; Goals; Head and neck structure; Health; Human Papillomavirus; Hybrids; Image; Imaging Techniques; Institution; Jaw; Knowledge; Linear Accelerator Radiotherapy Systems; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Methods; Modeling; Monitor; Mouth Sore; Normal tissue morphology; Oral; Oral health; Oral mucous membrane structure; Organ; Outcome; Patient imaging; Patient-Focused Outcomes; Patients; Physiologic pulse; Process; Quality of life; Radiation; Radiation Tolerance; Radiation therapy; Risk; Scheme; Signal Transduction; Statistical Models; Testing; Tissues; Toxic effect; Tumor Tissue; Tumor Volume; United States; Vendor; Work; Xerostomia; anatomic imaging; base; craniofacial; experience; experimental study; image guided radiation therapy; in silico; malignant mouth neoplasm; malignant oropharynx neoplasm; novel; patient response; prototype; radiation response; radiation-induced injury; radioresistant; response; side effect; survivorship; tissue injury; treatment planning; treatment response; treatment strategy; tumor

Project Summary Patients undergoing radiation therapy (RT) for oral and craniofacial cancers such as human papillomavirus- positive oropharyngeal cancer (HPV+ OPC) experience a host of side effects caused by radiation-induced injury to healthy tissues. Although RT is highly curative for HPV+ OPC, radiation-induced sequelae can persist for decades of survivorship, significantly degrading a patient's oral health and quality of life. Toxicity to healthy tissues can be reduced by adaptive replanning, in which the geometry of the radiation beams is re-optimized periodically during a multi-week course of RT to account for tumor shrinkage and normal tissue deformation. Adaptive replanning is now clinically feasible for oral and craniofacial cancers due the recent development of a hybrid MRI/linear accelerator device (MR-Linac). Adaptive treatments have used only basic anatomical MRI pulse sequences to monitor the tumor volume. However, we propose an adaptive treatment strategy that uses a functional MRI technique called diffusion-weighted imaging (DWI), which can assess normal tissue function, identify radioresistant sub-volumes within tumors, and predict patient response to RT. The hypothesis of this study is that the functional information from DWI can be implemented into the adaptive replanning process for oral and craniofacial cancers such that it is clinically feasible (with the new MR-Linac device) and will reduce side effects. To test this hypothesis, we will first develop a multivariate regression model relating changes in ADC values of the tumor and healthy tissues to HPV+ OPC patient outcomes. This information will be integrated into a DWI-based adaptive replanning workflow for the MR-Linac (Specific Aim 1). Next, the DWI- based adaptive replanning approach will be modeled retrospectively on daily patient images. A dose accumulation algorithm compatible with the MR-Linac's MRI-based dose calculation method will be developed and employed to measure cumulative doses to organs at risk. Cumulative doses will be related to normal tissue complication probability models to determine whether this approach lowers the risk of side effects (Specific Aim 2). The expected outcome of these specific aims is the development of an adaptive RT approach that uses functional data from DWI. The clinical feasibility and benefit of this treatment scheme will be demonstrated through in silico and statistical modeling so that it may eventually be used in the clinic. This project will positively impact patients with HPV+ OPC by enabling the delivery of personalized, targeted RT to the tumor while sparing normal tissues and reducing side effects. Further, this work will have a broader impact on the field of oral, dental, and craniofacial health by introducing a novel treatment paradigm that directly monitors and reacts to normal tissue injury without compromising tumor control.

项目摘要 接受放射治疗（RT）的口腔和颅面癌患者，如人乳头瘤病毒- 阳性口咽癌（HPV+ OPC）经历由辐射诱导的许多副作用， 对健康组织的伤害。尽管RT对HPV+ OPC具有高度治愈性，但放射引起的后遗症可能持续存在 几十年的生存，显著降低了患者的口腔健康和生活质量。对健康的毒性 其中放射束的几何形状被重新优化 在RT的多周过程中周期性地进行，以考虑肿瘤收缩和正常组织变形。 适应性重新计划现在在临床上对口腔和颅面癌是可行的，这是由于最近的发展， 混合MRI/直线加速器设备（MR-Linac）。适应性治疗仅使用基本的解剖MRI 脉冲序列来监测肿瘤体积。然而，我们提出了一种适应性治疗策略， 一种被称为弥散加权成像（DWI）的功能性MRI技术，可以评估正常组织的功能， 识别肿瘤内的抗辐射子体积，并预测患者对RT的反应。 研究表明，DWI的功能信息可以应用到自适应重新规划过程中， 口腔和颅面癌症，使其在临床上可行（使用新的MR-Linac设备），并将减少 副作用.为了检验这一假设，我们将首先建立一个多元回归模型， 肿瘤和健康组织的ADC值与HPV+ OPC患者结局的关系。此信息将 集成到MR直线加速器（特定目标1）的基于DWI的自适应重新规划工作流程中。下一篇：DWI- 基于自适应重新规划方法将在每日患者图像上回顾性建模。的剂量 将开发与MR直线加速器基于MRI的剂量计算方法兼容的累积算法 并用于测量处于危险中的器官的累积剂量。累积剂量将与正常 组织并发症概率模型，以确定这种方法是否降低了副作用的风险 （具体目标2）。这些具体目标的预期结果是发展一种适应性RT方法 使用DWI的功能数据。该治疗方案的临床可行性和受益将 通过计算机模拟和统计建模证明，以便最终可以用于临床。这 该项目将通过提供个性化的、有针对性的RT， 同时保留正常组织并减少副作用。此外，这项工作将产生更广泛的影响 在口腔，牙齿和颅面健康领域，通过引入一种新的治疗模式， 监测并对正常组织损伤做出反应，而不影响肿瘤控制。