Integrated Magnetic Resonance Imaging for Radiation Therapy Applications

用于放射治疗应用的集成磁共振成像

• 批准号: RGPIN-2015-04857
• 负责人: Levesque, Ives
• 金额: $ 1.6万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=678739
• 关键词: Integrated; Magnetic; Resonance; Imaging; Radiation

Introduction*** Radiation therapy relies heavily on imaging information for treatment planning, dose prediction, and radiation delivery. The soft tissue contrast and imaging flexibility provided by MRI can greatly impact this process. The long-term goal of this program is an integrated MRI approach to robust anatomical and physiological imaging for radiation therapy. Our research will provide improved contrast to clinicians for accurate contouring, tissue type information for dose calculations, and robust physiological measures to guide treatment decisions, and further enable MRI-based planning.***Aims***1. Develop an optimized structural MR imaging approach for tailored in vivo imaging of tissue anatomy for RT planning, based on a multi-echo gradient echo (MGRE) sequence for T1- and T2*-weighted imaging, and compare the derived T2* contrast to conventional T2 contrast for lesion and organ delineation***2. Design, implement and validate an MRI approach to robustly delineate the major tissue categories (soft tissue, bone, air) based on magnetic susceptibility mapping, to overcome the limitations of conventional MRI in areas lacking water signal. ***3. Develop a practical physiological imaging method for the RT planning process using DCE MRI, with fast, robust pattern-recognition (PR)-based analysis. We will jointly design data acquisition, image reconstruction and analysis***Scientific Approach*** Volumetric multi-echo gradient echo imaging will be the foundation of this in vivo imaging approach tailored to RT treatment planning. Multi-contrast anatomical imaging will target organ delineation and lesion identification. Magnetic-susceptibility-based reconstruction of air, bone, and soft tissue information combined with tissue property assignment will be investigated as an approach to X-ray heterogeneity information for dose calculation. A practical and robust approach for contrast-enhanced perfusion MRI will be evaluated, compared to model-based perfusion metrics as a marker of tumor physiology, and evaluated for dose modulation. All components of the approach will be designed to share data and to make the entire process more efficient. The integration of our academic unit in the radiation oncology practice will be key to investigate critical aspects that can impact the planning and simulation workflow.***Novelty and Significance*** MR imaging will potentially transform RT simulation, planning, delivery, and treatment assessment for a number of cancers. The soft tissue contrast and physiological information from this MRI approach will impact RT planning, treatment decisions, and assessment. Our integrated approach will provide the necessary information for image-based RT treatment planning, and result in feasible MR-based simulation and practical follow-up imaging in the clinical RT context.**

放射治疗在很大程度上依赖于用于治疗计划、剂量预测和放射输送的成像信息。MRI提供的软组织对比度和成像灵活性可以极大地影响这一过程。该计划的长期目标是为放射治疗提供强大的解剖和生理成像的综合MRI方法。我们的研究将为临床医生提供更好的对比度，以获得准确的轮廓，用于剂量计算的组织类型信息，以及指导治疗决策的强大生理措施，并进一步实现基于MRI的计划。目标 *开发一种优化的结构MR成像方法，用于组织解剖结构的定制体内成像，用于RT计划，基于T1和T2* 加权成像的多回波梯度回波（MGRE）序列，并将导出的T2* 对比度与传统T2对比度进行比较，用于病变和器官描绘 *2。设计、实施和验证MRI方法，以基于磁化率标测稳健地描绘主要组织类别（软组织、骨、空气），以克服常规MRI在缺乏水信号的区域的局限性。*3。使用DCE MRI为RT计划过程开发实用的生理成像方法，并进行快速、稳健的基于模式识别（PR）的分析。我们将共同设计数据采集、图像重建和分析 *** 科学方法 *** 体积多回波梯度回波成像将是这种针对RT治疗计划定制的体内成像方法的基础。多对比度解剖成像将靶器官描绘和病变识别。将研究结合组织属性分配的空气、骨和软组织信息的基于磁化率的重建，作为用于剂量计算的X射线异质性信息的方法。将评价对比增强灌注MRI的实用且稳健的方法，与作为肿瘤生理学标志物的基于模型的灌注度量进行比较，并评价剂量调制。该方法的所有组成部分都将旨在共享数据，提高整个过程的效率。我们的学术单位在放射肿瘤学实践中的整合将是调查可能影响规划和模拟工作流程的关键方面的关键。新奇和意义 * MR成像将潜在地改变许多癌症的RT模拟、计划、递送和治疗评估。来自该MRI方法的软组织对比度和生理信息将影响RT计划、治疗决策和评估。我们的综合方法将为基于图像的RT治疗计划提供必要的信息，并在临床RT背景下实现可行的基于MR的模拟和实际的随访成像。