Rapid high order diffusion imaging for stroke

中风的快速高阶扩散成像

• 批准号: 8563352
• 负责人: EDWARD VR DIBELLA
• 金额: $ 33.91万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8563352
• 关键词: Architecture; Area; Biological Markers; Brain; Clinical; Clinical Research; Code; Collaborations; Communities; Data; Data Set; Development; Dictionary; Diffusion; Diffusion Magnetic Resonance Imaging; Evaluation; Fiber; Goals; Growth; Image; Imaging Techniques; Knowledge; Longitudinal Studies; Magnetic Resonance Imaging; Maps; Measurement; Measures; Methods; Middle Cerebral Artery Infarction; Modeling; Monitor; Motion; Motor; Motor Skills; Neurons; Occupational Therapy; Operative Surgical Procedures; Patients; Persons; Pharmaceutical Preparations; Pharmacotherapy; Physical Medicine; Play; Population; Preparation; Public Health; Radiology Specialty; Rattus; Recovery; Rehabilitation therapy; Relative (related person); Research; Research Personnel; Resolution; Sampling; Scanning; Software Tools; Stimulus; Stroke; Techniques; Technology; Testing; Time; Touch sensation; Translating; Traumatic Brain Injury; Universities; Utah; Work; axonal sprouting; base; biocomputing; bioimaging; brain remodeling; computer science; computerized tools; disability; imaging modality; improved; insight; interest; motor deficit; novel; novel strategies; post stroke; public health relevance; rapid technique; reconstruction; research clinical testing; response; sildenafil; software development; spatiotemporal; stroke recovery; stroke therapy; success; tool; treatment response; tumor; white matter

DESCRIPTION (provided by applicant): New computational tools are critical to leverage progress in computational technologies to impact biomedical imaging with MRI. This work seeks to develop, evaluate and apply new MRI methods for high-end diffusion imaging. These high angular resolution methods work where diffusion tensor imaging (DTI) methods fail - in crossing or touching fibers, which corresponds too much of the brain. This is of particular value for assessing white matter tract integrity after stroke. Two small studies have shown that advanced "post-DTI" methods can give valuable information predicting the degree of recovery from stroke. However, the post-DTI methods require impractical scan duration. Thus this project aims to (1) develop advanced acquisition and reconstruction methods for rapid (undersampled in k- and q-space) diffusion measurements. (2) To characterize rapid acquisition and reconstruction methods for advanced diffusion imaging. (3) To determine white matter tract integrity changes over time when patients with stroke are treated with a neurogenic drug, sildenafil. This will allow for determining the predictive power of the high angular resolution post-DTI methods and give insight into changes in response to the drug therapy. These aims will be accomplished by developing software tools to provide post-DTI type data from short, clinically practical, acquisition times. Advanced reconstruction methods that include low rank and spatiotemporal constraints with intensity reordering, dictionary-based approaches, and parametric models will be developed and tested to obtain diffusion information in short time frames. The integrity of the white matter tracts will be estimated and the repeatability and accuracy of the new methods will be determined relative to full long scan acquisitions. The serial application of the methods to patients with stroke undergoing standard therapy and novel drug therapy will then provide new information regarding changes associated with neuronal remodeling and possibly differentiate responders from non-responders. The resulting software tools will be integrated into the insight toolkit (ITK) and provided for use to the research community. The relevance to public health is that stroke is a leading cause of disability. The development and use of accurate and repeatable measurements of diffusion will accelerate evaluation of clinical therapies. The project will also provide new tools and knowledge for better management of patients with stroke. The proposed approach can be extended to improve a wide range of multi-image MRI applications, such as the response of tumors to therapy and the response of the brain to stimuli.

描述（由申请人提供）：新的计算工具对于利用计算技术的进步影响MRI生物医学成像至关重要。这项工作旨在开发，评估和应用新的MRI方法进行高端扩散成像。这些高角分辨率方法适用于扩散张量成像（DTI）方法失败的地方-交叉或接触纤维，这对应于大脑的太多部分。这对于评估中风后白色物质束的完整性具有特别的价值。两项小型研究表明，先进的“后DTI”方法可以提供有价值的信息，预测中风的恢复程度。然而，后DTI方法需要不切实际的扫描持续时间。因此，本项目旨在（1）开发先进的采集和重建方法，用于快速（k和q空间中的欠采样）扩散测量。(2)描述高级弥散成像的快速采集和重建方法。(3)确定脑卒中患者接受神经源性药物西地那非治疗时，白色束完整性随时间的变化。这将允许 用于确定高角分辨率后DTI方法的预测能力，并深入了解药物治疗的变化。这些目标将通过开发软件工具来实现，以提供短的临床实用采集时间的DTI后类型数据。先进的重建方法，包括低秩和时空约束与强度重排，基于字典的方法，和参数模型将被开发和测试，以获得在短时间内的扩散信息。将估计白色物质束的完整性，并确定新方法相对于全长扫描采集的重复性和准确性。将这些方法连续应用于接受标准治疗和新型药物治疗的中风患者，将提供有关神经元重塑相关变化的新信息，并可能区分反应者和非反应者。由此产生的软件工具将被纳入洞察力工具包（ITK），并提供给研究界使用。与公共卫生相关的是，中风是残疾的主要原因。准确和可重复的扩散测量的开发和使用将加速临床治疗的评估。该项目还将为更好地管理中风患者提供新的工具和知识。所提出的方法可以扩展到改善广泛的多图像MRI应用，如肿瘤对治疗的反应和大脑对刺激的反应。