Quasi-rigid image registration for DCE-MRI

DCE-MRI 的准刚性图像配准

• 批准号: 8598873
• 负责人: Abhijit J Chaudhari
• 金额: $ 7.04万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8598873
• 关键词: Address; Adjuvant; Adult; Algorithms; Angiogenesis Inhibitors; Arthritis; BAY 54-9085; Biological Markers; Body Regions; Body part; Clinic; Clinical; Clinical Management; Clinical Trials; Collaborations; Communities; Computer software; Computers; Data; Derivation procedure; Development; Disease; Drug Formulations; Elasticity; Elements; Funding; Future; Goals; Gold; Head and Neck Cancer; Human; Hybrids; Image; Image Analysis; Imaging Device; Imaging technology; Individual; Longitudinal Studies; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Medicine; Methods; Metric; Modeling; Monitor; Motion; Musculoskeletal Diseases; Patient Selection; Patients; Performance; Pharmaceutical Preparations; Physicians; Physics; Play; Population; Positron-Emission Tomography; Process; Protocols documentation; Radiation therapy; Radiology Specialty; Reading; Research; Role; Scanning; Scheme; Software Tools; Surgical Oncologist; Surgical Oncology; Surrogate Endpoint; System; Techniques; Technology; Testing; Therapeutic; Three-Dimensional Image; Training; United States National Institutes of Health; Validation; Visual; Work; base; bone; cancer imaging; combat; design; flexibility; human disease; image registration; innovation; insight; novel; novel therapeutics; open source; pre-clinical; public health relevance; radiologist; response; sarcoma; soft tissue; tool; treatment duration; treatment response

DESCRIPTION (provided by applicant): Dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI) biomarkers are displaying significant promise as early indicators of therapeutic response in the modern clinic. As a consequence, they possess an evolving role in the current realm of individualized medicine. Challenges remain however regarding their application in cross-sectional contemporaneous or longitudinal studies - it is critical in these studies to decouple errors due to intra-scan patient motion or repositioning on the scanner from anatomical or functional changes occurring due to treatment that these biomarkers reflect. Tools that are capable of rapid, but reliable derivation of DCE-MRI biomarkers are therefore urgently needed. The GOAL of this proposed work is to develop, implement and validate three-dimensional image registration technology for enabling the rapid derivation of disease-associated biomarkers from clinical DCE-MRI. The focus is on the alignment of intra-subject anatomical images of body regions that involve both rigid (bone) and non-rigid (soft tissue) components. In our innovative registration scheme, pre-determined components such as bones deform in a rigid manner while soft tissue warps non-rigidly. We HYPOTHESIZE therefore that our method will provide better modeling of patient repositioning compared to currently clinically used technologies as well as state-of-the-art registration methods. In our SPECIFIC AIMS, we will: (1) develop the quasi-rigid, intra-subject registration method for MR image alignment, and (2) validate the registration method using MR images of adult patients with soft tissue sarcoma in a retrospective setting. Both computer-based and human observers will be used to compare the performance of the proposed method against conventional rigid and non-rigid registration methods. A novel system for radiologic scoring of the merits of image registration is devised and will be tested. The registration method will be developed as an open-source technique allowing easy distribution. DCE-MRI biomarkers are currently being evaluated as surrogate end-points in clinical trials of several novel drug treatments. The proposed registration method will enable rapid quantitative change analyses of DCE-MRI biomarkers over the treatment period. Physicians will be able to use this information to tailor therapeutic strategies according to the individual requirements of their patients. In this context, techniques developed in this proposal are applicable to a broad class of human diseases, e.g., oncologic (e.g., sarcomas, head and neck cancer, etc) or musculoskeletal disease (e.g., arthritis, etc). This work is a close collaboration with Robert Canter, a surgical oncologist who specializes in the clinical management of soft tissue sarcoma, Michael Buonocore, an MRI physicist whose expertise lies in clinical MRI protocol design and image analysis, Robert Boutin, a clinical radiologist with expertise in soft tissue sarcoma and consultant Wayne Monsky, an expert in cancer imaging biomarker development.

描述（由申请人提供）：动态对比增强磁共振成像（DCE-MRI）生物标志物作为现代临床治疗反应的早期指标显示出巨大的前景。因此，它们在当前个体化医疗领域中发挥着不断发展的作用。然而，关于它们在横断面同期或纵向研究中的应用仍然存在挑战——在这些研究中，将扫描内患者运动或扫描仪上重新定位引起的误差与这些生物标志物反映的治疗所发生的解剖或功能变化分开是至关重要的。因此，迫切需要能够快速、可靠地得出 DCE-MRI 生物标志物的工具。这项工作的目标是开发、实施和验证三维图像配准技术，以便能够从临床 DCE-MRI 中快速推导出疾病相关的生物标志物。重点是涉及刚性（骨骼）和非刚性（软组织）组件的身体区域的受试者体内解剖图像的对齐。在我们的创新配准方案中，预先确定的组件（例如骨骼）以刚性方式变形，而软组织则非刚性地扭曲。因此，我们假设与当前临床使用的技术以及最先进的配准方法相比，我们的方法将提供更好的患者重新定位模型。在我们的具体目标中，我们将：（1）开发用于 MR 图像对齐的准刚性主体内配准方法，以及（2）在回顾性环境中使用成年软组织肉瘤患者的 MR 图像验证配准方法。基于计算机和人类观察者都将用于将所提出的方法与传统的刚性和非刚性配准方法的性能进行比较。设计了一种新颖的图像配准优点放射学评分系统，并将对其进行测试。注册方法将作为一种开源技术开发，以便于分发。 DCE-MRI 生物标志物目前正在作为几种新型药物治疗的临床试验的替代终点进行评估。所提出的配准方法将能够在治疗期间对 DCE-MRI 生物标志物进行快速定量变化分析。医生将能够利用这些信息根据患者的个人需求制定治疗策略。在这种情况下，本提案中开发的技术适用于广泛的人类疾病，例如肿瘤（例如肉瘤、头颈癌等）或肌肉骨骼疾病（例如关节炎等）。这项工作是与专门从事软组织肉瘤临床管理的外科肿瘤学家 Robert Canter、专门从事临床 MRI 协议设计和图像分析的 MRI 物理学家 Michael Buonocore、具有专业知识的临床放射科医生 Robert Boutin 的密切合作软组织肉瘤领域的专家和顾问韦恩·蒙斯基（Wayne Monsky），癌症成像生物标志物开发专家。