Optimizing MRI for Radiation Therapy Treatment Planning

优化 MRI 以制定放射治疗计划

• 批准号: 8528922
• 负责人: JAMES M BALTER
• 金额: $ 36.49万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8528922
• 关键词: Abdomen; Ablation; Anatomy; Arts; Biological Markers; Blinded; Blood Volume; Bone Tissue; Brain; Classification; Clinic; Clinical Trials; Communities; Dependence; Development; Diagnosis; Diagnostic radiologic examination; Diffusion; Disorder by Site; Dose; Environment; Event; Excision; Fatty acid glycerol esters; Image; Image Guided Biopsy; Imaging Techniques; Imaging technology; Inferior; Intervention; Investigation; Label; Liquid substance; Magnetic Resonance Imaging; Malignant Neoplasms; Maps; Masks; Measures; Methods; Modality; Modeling; Molecular; Molecular Probes; Movement; Neck; Normal tissue morphology; Ointments; Operative Surgical Procedures; Patients; Pelvis; Physiologic pulse; Physiological; Play; Positioning Attribute; Private Hospitals; Process; Property; RF coil; Radiation Oncology; Radiation therapy; Relative (related person); Research; Residual state; Resources; Risk; Role; Sampling; Scanning; Security; Signal Transduction; Software Tools; Solid; System; Techniques; Testing; Tissue Differentiation; Tissues; Toxic effect; Treatment outcome; Tumor Tissue; Uncertainty; Water; Width; X-Ray Computed Tomography; base; bone; cancer radiation therapy; clinical practice; computerized data processing; cost; design; electron density; image processing; improved; next generation; outcome forecast; prospective; public health relevance; response; soft tissue; treatment planning; tumor; virtual

DESCRIPTION (provided by applicant): While Magnetic Resonance Imaging (MRI) has significant advantages in Radiation Therapy (RT) planning and assessment, its role is limited to support of computed tomography (CT) RT due to concerns about distortion, ability to support dose calculations, and missing information to support image guidance at the treatment unit. This project pursues the hypothesis that MRI RT can be shown to be at least as accurate as CT RT, with the clear implication that MRI RT will in fact far exceed the benefits of CT. The specific aims are: SA1 Assess and improve the geometric accuracy of routine MRI pulse sequences by combining acquisition and processing methods to minimize residual distortions, and performing phantom and patient-specific assessments to determine whether residual geometric errors are within acceptable bounds for RT SA2 Optimize patient modeling methods to create MRI-derived representations most appropriate for contouring, dose calculation, and support of image-guided positioning of patients undergoing RT SA3 Conduct virtual clinical trials to demonstrate that treatment decisions based on MRI RT are not inferior to those derived from CT RT This project will explore two methods of distortion correction (rectification and field mapping), and will characterize the geometric accuracy of MRI. Imaging techniques that enhance signals from bone, quantify fat and water distributions, and provide differential contrast from other tissues, will be analyzed via clustering techniques to label tissue/material types (e.g. free fluid, dense solid tissue, bone, various fat concentrations isolated or embedded within other tissues). These classified tissues can be assigned properties to generate electron density maps for dose calculation as well as new patient models for contouring and image guidance. A virtual clinical trial will be performed to evaluate the accuracy of MRI RT relative to CT RT. This research will support removal of redundant and potentially confounding CT scans from the planning process for certain patients. It will facilitate the use of MRI-derived physiologic, molecular, and advance morphologic information for treatment planning. It will enhance collaborative development of optimized imaging resource utilization between diagnostic radiology and radiotherapy departments in academic as well as private hospital settings. It will help optimize workflow for patients that may be treated with the evolving next generation of MRI-guided teletherapy systems. Finally it will directly support the use of emerging MRI-derived biomarkers for individualized adaptive radiotherapy, and will reduce the cost as well as complexity of longitudinal assessment of treatment outcome. In the unlikely event that CT-based radiotherapy is still demonstrated to be better, these investigations will improve the geometric integrity of MR to maximally benefit augmentation of CT-based patient models. This will also impact the value of MRI in guiding non-radiotherapy focal interventions such as surgery, focused ablation, and image-guided biopsy.

描述（由申请人提供）：虽然磁共振成像（MRI）在放射疗法（RT）计划和评估方面具有显着优势，但由于对失真的疑虑，支持剂量计算的能力以及支持治疗单位的图像指导的信息，其作用仅限于支持计算机断层扫描（CT）RT。该项目提出了一个假设，即MRI RT可以至少与CT RT一样准确，这显然暗示MRI RT实际上将远远超过CT的好处。 The specific aims are: SA1 Assess and improve the geometric accuracy of routine MRI pulse sequences by combining acquisition and processing methods to minimize residual distortions, and performing phantom and patient-specific assessments to determine whether residual geometric errors are within acceptable bounds for RT SA2 Optimize patient modeling methods to create MRI-derived representations most appropriate for contouring, dose calculation, and support of image-guided positioning of patients经过RT SA3进行虚拟临床试验，以证明基于MRI RT的治疗决策不如CT RT衍生的决策，该项目将探索两种失真校正方法（纠正和现场映射），并将表征MRI的几何准确性。将通过聚类技术来分析从骨骼，量化脂肪和水分布并提供与其他组织的差异对比度的信号的成像技术，以标记组织/材料类型（例如，自由液体液体，密集的固体组织，骨骼，骨骼，各种脂肪浓度分离或嵌入其他组织中））。这些分类组织可以分配特性，以生成用于剂量计算的电子密度图以及用于轮廓和图像指导的新患者模型。将进行虚拟临床试验，以评估MRI RT相对于CT RT的准确性。这项研究将支持去除某些患者的计划过程中冗余且可能混淆的CT扫描。它将促进使用MRI衍生的生理，分子和预先用于治疗计划的形态信息。它将增强在学术和私人医院环境中诊断放射学和放射治疗部门之间优化成像资源利用的协作开发。它将有助于优化可通过不断发展的下一代MRI引导远程疗法系统治疗的患者的工作流程。最后，它将直接支持新兴的MRI衍生生物标志物作为个性化的适应性放射疗法，并降低了治疗结果的纵向评估的成本和复杂性。在不太可能的情况下，基于CT的放射疗法仍证明更好，这些研究将改善MR的几何完整性，从而最大程度地使基于CT的患者模型增强。这还将影响MRI在指导非放射疗法局灶性干预（例如手术，聚焦消融和图像引导活检）方面的价值。