4-DIMENSIONAL LV TISSUE TRACKING IN CAD FROM TAGGED MRI

通过标记 MRI 在 CAD 中进行 4 维左心室组织追踪

• 批准号: 6197519
• 负责人: AMIR A AMINI
• 金额: $ 30.68万
• 依托单位: BARNES-JEWISH HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-01 至 2003-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6197519
• 关键词: bioimaging /biomedical imaging; clinical research; coronary disorder; heart motion; heart ventricle; human data; human subject; image enhancement; magnetic resonance imaging; mathematical model; myocardial infarction; phantom model; technology /technique development

DESCRIPTION (Adapted from Applicant's Abstract): The applicants propose to develop and validate new image analysis methods aimed at a more accurate, reproducible, and automated approach to assessment of regional left ventricular (LV) function and visualization of 3D cardiac motion from tagged MRI data of patients with coronary artery disease (CAD). The applicants have developed a number of methods for analysis of tagged MRI data which have been validated in phantoms and animal models of myocardial infarction (MI). They propose to continue development of these techniques which utilize all of the available stripe information, including tag intersections and linear tag lines, in automatically taking LV deformations and reconstructing dense displacements at all myocardial points, with the goal of routinely applying these techniques to patient data. The advantage of the developed methods is that since displacement vectors will be available at all myocardial points, indices of LV function will also be available everywhere in the myocardium. These indices can be summed over local myocardial regions resulting in segmental function scores. In human studies, the developed methods will be applied to images acquired from normal volunteers, patients with pharmacologic stress-induced myocardial ischemia, patients with old, healed MI, and patients with ischemic dilated cardiomyopathy. In each case, segmental wall motion as assessed by the algorithms will be compared and correlated with validated clinical techniques such as 2D echocardiography, cine-MRI, and Gadolinium (Gd) contrast MRI. Thus, the specific aims are: (a) To measure statistical distribution (mean and standard deviation) of segmental function scores from 3D + t (short-axis and long-axis) tagged MRI at rest and under pharmacologic (dobutamine) stress in normal controls. (b) To measure the function scores as determined from 2D + t (short-axis) tagged MRI during pharmacologic stress and classified into normal, hypokinetic, or akinetic classes in patients with stress-induced ischemia. These labels will then be statistically correlated to labels assigned to the same segments by 2D echocardiography and cine-NIRI. (c) To measure segmental function scores as determined from 3D + t (short-axis and long-axis) tagged NIRI at rest and classified into normal, hypokinetic, akinetic, or dyskinetic classes in patients with an old, healed MI. The labels will be statistically compared to non-nal or akinetic labels assigned to the same segment from 2D echocardiography and cine-MRI, and with Gd contrast MRI. (d) To measure the segmental function scores from 3D + t (short-axis and long-axis) tagged MRI at rest and classified into normal, hypokinetic, akinetic, or dyskinetic classes in patients with ischemic, dilated cardiomyopathy. The labels will be statistically compared to labels assigned to the same segment from 2D echocardiography and cine-MRI.

描述（根据申请人的摘要改编）：申请人建议 开发和验证针对更准确的新图像分析方法 可重现和自动化方法评估区域左心室 （LV）从标记的MRI数据的3D心脏运动的功能和可视化 冠状动脉疾病（CAD）患者。申请人已经开发了 用于分析已验证的标记MRI数据的方法数量 心肌梗塞（MI）的幻影和动物模型。他们建议 继续开发这些技术，这些技术利用所有可用的 条纹信息，包括标签相交和线性标签线， 自动采用LV变形并重建密集位移 所有心肌点，目的是将这些技术定期应用于 患者数据。开发方法的优点是，由于位移 向量将在所有心肌点可用，LV功能的索引将 也可以在心肌中到处可用。这些指数可以求和 在局部心肌区域，导致分段函数得分。在人类中 研究，开发的方法将应用于从正常的图像 志愿者，具有药理学胁迫诱导的心肌缺血的患者， 老年，治愈的MI和缺血性患者的患者扩张 心肌病。在每种情况下，由 将比较算法并与经过验证的临床技术相关 例如2D超声心动图，Cine-MRI和Gadolinium（GD）对比度MRI。因此， 具体目的是：（a）衡量统计分布（平均值和 从3D + t（短轴和 长轴）在静止和药理学（多丁胺）应力下标记为MRI 正常对照。 （b）测量从2D + T确定的功能得分 （短轴）在药理应力期间标记了MRI，并将其分类为正常 压力诱导的缺血患者的低动力或运动型类别。 然后，这些标签将在统计上与分配给的标签相关 2D超声心动图和Cine-Niri相同的段。 （c）测量分段 功能得分是从标记的3D + T（短轴和长轴）确定的 Niri休息并分类为正常，低动力，偶像或运动障碍 患有旧的，治愈的MI的患者的课程。标签将在统计上是 与分配给2D同一段的非最新或非轴向标签相比 超声心动图和Cine-MRI，以及GD对比度MRI。 （d）测量 从3D + T（短轴和长轴）标记MRI的节段函数得分 休息并归类为正常，低温，偶像或运动障碍类别 缺血性心肌病患者。标签将是 统计上与分配给2D同一段的标签进行了比较 超声心动图和Cine-MRI。