Real Time Motion correction for Brain MRI

大脑 MRI 的实时运动校正

• 批准号: 7575217
• 负责人: Truman R Brown
• 金额: $ 5.38万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-01 至 2010-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7575217
• 关键词: Address; Algorithms; Area; Blood; Brain; Cerebrovascular Circulation; Child; Collection; Computer software; Data; Data Set; Dementia; Detection; Development; Devices; Diagnosis; Disease; Effectiveness; Elderly; Epilepsy; Evaluation; Frequencies; Functional Magnetic Resonance Imaging; Head; Head Movements; Height; Human; Human Volunteers; Image; Inferior; Injection of therapeutic agent; Left; Magnetic Resonance Imaging; Measurement; Measures; Methods; Metric; Monitor; Morphologic artifacts; Motion; Motor; Movement; Neurons; Parkinson Disease; Patients; Physiologic pulse; Population; Positioning Attribute; RF coil; Recording of previous events; Relaxation; Research; Rotation; Scanning; Scheme; Schizophrenia; Series; Signal Transduction; Slice; Solid; Speed; Spin Labels; Subject Headings; Techniques; Testing; Time; Tissues; Translations; Weight; Width; base; data acquisition; deoxyhemoglobin; improved; millimeter; motor control; novel; older patient; patient population; prevent; programs; prospective; relating to nervous system; response; success; tool; visual stimulus; volunteer

DESCRIPTION (provided by applicant): Magnetic resonance imaging (MRI) of the head and brain is a powerful tool for research and diagnosis. During a MRI scan patients are asked to keep their head very still because slight movements can spoil the MRI data, but this can be difficult for young children, elderly people, and those who suffer from Parkinson's disease, schizophrenia, epilepsy, and dementia. Our research will let MRI better serve these patients by allowing accurate data to be collected even when head movements occur during scanning. The standard approach to correct motion artifacts in MRI is retrospective image-based motion detection and correction as implemented in popular analysis packages such as SPM and AIR. This approach is well suited to motion within the imaging plane, but cannot handle substantial through-plane motion which both cannot be described by a single rotation/translation and alters the spin magnetization history of the tissue in the imaging field of view (FOV). Prospective motion correction techniques which measure head position in real time and adjust the FOV prior to data acquisition thus offer a compelling advantage for through-plane motion. However, existing 'prospective techniques such as navigator echoes and PACE impose a delay in data acquisition rates. Our objective is to implement and validate a novel scheme for prospective correction of MRI motion artifact that operates in parallel with the acquisition of imaging data, preventing temporal delay. We have developed a tracking device for real-time monitoring of three- dimensional changes in head position using three RF tracking coils for spatial localization simultaneous with image data acquisition via a standard head coil. Our first specific aim is to implement dynamic motion detection using our tracking device and prospective re-alignment of the imaging plane on a Philips Achieva scanner. Our second specific aim is to create realistic motion artifacts in MRI data from phantoms. Four metrics will be used to evaluate the success of the correction algorithm. Our third specific will study twelve volunteers who have been instructed to turn their heads to track a moving visual stimulus. The metrics used to evaluate the algorithm consist of a) comparison with standard retrospective motion correction using AIR, b) evaluation of the high spatial frequencies present in the images collected with and without the motion correction scheme, c) comparison of line profiles through the images of corrected vs. uncorrected images and d) measurement of the width at = height of small cylinders in one of the phantoms. We expect that our scheme will be better able to address the degree of motion typically seen in patient populations.

描述（由申请人提供）：头和大脑的磁共振成像（MRI）是研究和诊断的强大工具。在MRI扫描期间，要求患者保持头部非常静止，因为轻微的动作会破坏MRI数据，但是对于年幼的孩子，老年人以及患有帕金森氏病，精神分裂症，癫痫和痴呆症患者而言，这可能很困难。我们的研究将使MRI通过允许在扫描过程中收集精确的数据来更好地为这些患者提供服务。在MRI中纠正运动伪影的标准方法是基于图像的运动检测和校正，如SPM和空气等流行分析包中所实现的。这种方法非常适合在成像平面内运动，但不能处理实质的整个平面运动，这两者都无法通过单个旋转/翻译来描述，并且可以改变视野（FOV）中组织的自旋磁化历史记录。前瞻性运动校正技术实时测量头部位置并在数据获取之前调整FOV，从而为整个平面运动提供了令人信服的优势。但是，现有的前瞻性技术（例如导航器的回声和速度）迫使数据采集率延迟。我们的目标是实施和验证一种新的方案，以预期校正MRI运动伪像，该方案与获取成像数据并肩作用，从而防止时间延迟。我们已经开发了一种跟踪设备，用于使用三个RF跟踪线圈进行实时监视头部位置的三维变化，以通过标准头线圈同时与图像数据采集同时进行空间定位。我们的第一个具体目的是使用我们的跟踪设备和飞利浦Achieva扫描仪上成像平面的前瞻性重新调整实施动态运动检测。我们的第二个具体目的是在Phantoms的MRI数据中创建现实的运动伪影。四个指标将用于评估校正算法的成功。我们的第三个特定将研究十二名志愿者，他们被指示转动头部以跟踪移动的视觉刺激。用于评估该算法的指标包括a）与空气使用空气的标准回顾性运动校正进行比较，b）评估以有或没有运动校正方案收集的图像中存在的高空间频率的评估，c）通过校正图的图像进行比较。我们希望我们的计划能够更好地解决患者人群中通常看到的运动程度。