Prospective 3-D Treatment Planning for MR-Guided Laser Induced Thermal Therapy Pr

MR 引导激光诱导热疗法的前瞻性 3D 治疗计划

• 批准号: 8136671
• 负责人: R JASON STAFFORD
• 金额: $ 22.78万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8136671
• 关键词: 3-Dimensional; Address; Aftercare; Algorithms; Anatomy; Area; Brain; Cancerous; Canis familiaris; Clinical Research; Clinical Trials; Complement; Computational algorithm; Computer Simulation; Conventional Surgery; Data; Decision Making; Devices; Dose; Environment; Evaluation; Feedback; Fiber; Generations; Goals; Government; Heating; Hemorrhage; Human; Image; Lasers; Lesion; Magnetic Resonance Imaging; Measures; Modeling; Monitor; Noise; Outcome; Patients; Perfusion; Positioning Attribute; Predisposition; Procedures; Process; Relative (related person); Research; Retreatment; Rosa; Safety; Signal Transduction; Simulate; Slice; System; Technology; Temperature; Therapeutic; Time; Tissues; Translating; Treatment outcome; Uncertainty; United States; Update; base; dosimetry; experience; high risk; in vivo; innovation; minimally invasive; novel; open source; operation; programs; prospective; public health relevance; real time model; spatiotemporal; tool; treatment planning; virtual

DESCRIPTION (provided by applicant): MR-guided laser induced thermal therapy (MRgLITT) for treatment of cancerous lesions in the brain presents a minimally invasive alternative to conventional surgery, gaining use worldwide with multiple on-going clinical trials currently. These therapies incorporate real-time MR temperature imaging (MRTI) to provide feedback which makes these procedures safe and feasible. However, as these therapies translate into clinical studies, there are two deficiencies worth addressing. Firstly, laser heating in the presence of tissue interfaces and convective heat transfer (e.g., ventricles, vessels and tissue perfusion) may render planning of treatments by assuming symmetric ellipsoidal lesion generation difficult, particularly when multiple applicators with arbitrary placement are used. Second, MRTI information may become corrupt in some regions (e.g., from temperature dependent signal losses, blood, or susceptibility effects at interfaces) and the temperature information may be lost or become extremely uncertain, making decisions about treatment outcome difficult. Therefore, in order to enhance the safety, efficacy and conformality of treatment delivery, there exists a critical need for prospective 3D treatment planning of MRgLITT procedures as well as more robust real-time monitoring to complement MRTI. The primary goal of the proposed research is to develop and validate algorithms to provide both prospective 3D treatment planning and real-time model driven treatment monitoring for MRgLITT procedures in the brain. Such a system will incorporate the use of 3D MRI acquisitions currently used for neurosurgical and stereotactic treatment planning and allow the user to interactively navigate the tissue and simulate the effects of various applicator trajectories and laser exposures, update these plans once the laser is positioned, as well as provide real-time 3D estimation of damage based on the acquired multi-slice MR temperature imaging input. Completion of this project will provide not only the tools outlined above, but a framework for our long term goal of applying these models for computer optimized inverse treatment planning as well as real-time modeling for adaptive control of therapy. This project is both innovative and timely in that no technology presently exists for prospective 3D planning of this emerging therapeutic option, much less, integration of such an algorithm with data driven model prediction assistance for monitoring and treatment assessment. This research is high risk in that the complexity of the computational problems to be addressed in near real-time present both physical and theoretical hurdles to overcome, but our previous experience in this area indicate it is feasible. PUBLIC HEALTH RELEVANCE: MR-guided laser induced thermal therapy (MRgLITT) for the treatment of cancerous lesions in the brain is a minimally invasive alternative to conventional surgery and is now available as a commercialized product with many clinical trials in operation or beginning. The primary goal of the proposed research is to develop, investigate and validate 3D prospective treatment planning and real-time MRTI driven model prediction assisted monitoring for MRgLITT procedures in the brain in order to enhance the efficacy and safety of these procedures. This project is both innovative and timely in that no technology presently exists to support prospective 3D treatment planning of this emerging therapeutic option nor data driven real-time modeling for prediction of temperature and tissue damage.

描述（由申请人提供）：用于治疗脑部癌性病变的MR引导激光诱导热疗（MRgLITT）是传统手术的微创替代方案，目前正在全球范围内进行多项临床试验。这些疗法结合了实时MR温度成像（MRTI），以提供反馈，使这些程序安全可行。然而，随着这些疗法转化为临床研究，有两个不足之处值得解决。首先，在存在组织界面和对流热传递（例如，心室、血管和组织灌注）可能通过假设对称椭圆体损伤产生困难而使得治疗计划制定，特别是当使用具有任意放置的多个施加器时。第二，MRTI信息可能在某些区域（例如，来自温度相关的信号损失、血液或界面处的敏感性效应），并且温度信息可能丢失或变得极其不确定，使得关于治疗结果的决定变得困难。因此，为了增强治疗递送的安全性、有效性和适形性，迫切需要MRgLITT程序的前瞻性3D治疗规划以及更稳健的实时监测来补充MRI。 拟议研究的主要目标是开发和验证算法，为大脑中的MRgLITT程序提供前瞻性3D治疗计划和实时模型驱动治疗监测。这种系统将结合使用目前用于神经外科和立体定向治疗计划的3D MRI采集，并允许用户交互式导航组织并模拟各种施加器轨迹和激光照射的影响，一旦定位激光器就更新这些计划，以及基于采集的多层MR温度成像输入提供实时3D损伤估计。该项目的完成不仅将提供上述工具，而且还将为我们的长期目标提供一个框架，即将这些模型应用于计算机优化的逆向治疗计划以及用于自适应治疗控制的实时建模。该项目是创新和及时的，因为目前还没有技术用于这种新兴治疗选择的前瞻性3D规划，更不用说将这种算法与数据驱动的模型预测辅助集成用于监测和治疗评估。这项研究是高风险的，因为要解决的计算问题的复杂性，在近实时的物理和理论上的障碍，以克服，但我们以前在这方面的经验表明，这是可行的。 公共卫生相关性：用于治疗脑部癌性病变的MR引导激光诱导热疗（MRgLITT）是传统手术的微创替代方案，目前已作为商业化产品上市，许多临床试验正在进行或正在开始。拟议研究的主要目标是开发、调查和验证3D前瞻性治疗计划和实时MRTI驱动模型预测辅助监测，用于大脑中的MRgLITT程序，以提高这些程序的有效性和安全性。该项目是创新和及时的，因为目前没有技术支持这种新兴治疗方案的前瞻性3D治疗计划，也没有数据驱动的实时建模来预测温度和组织损伤。