4-DIMENSIONAL LV TISSUE TRACKING IN CAD FROM TAGGED MRI

描述（改编自申请人的摘要）：申请人提出 开发和验证新的图像分析方法， 可重复和自动化的方法来评估局部左心室 (LV)功能和可视化的3D心脏运动从标记的MRI数据， 冠状动脉疾病（CAD）患者。申请人已经制定了一个 分析标记MRI数据的方法数量，这些方法已在 心肌梗死（MI）动物模型。他们提议 继续开发这些技术，利用所有可用的 条带信息，包括标记交叉点和线性标记线， 自动获取LV变形并重建密集位移， 所有心肌点，目的是常规应用这些技术， 患者数据。所开发的方法的优点是，由于位移 向量将在所有心肌点可用，LV功能指数将 也可以在心肌中的任何地方获得。这些指数可以相加 在局部心肌区域上产生节段性功能评分。人 研究中，所开发的方法将被应用于从正常人 志愿者，药物应激诱导的心肌缺血患者， 陈旧性、已愈合MI患者和缺血性扩张性MI患者 心肌病在每种情况下，节段性室壁运动由 算法将与经验证的临床技术进行比较和关联 例如2D超声心动图、电影MRI和钆（Gd）对比MRI。因此，在本发明中， 具体目标是：（a）衡量统计分布（平均数和 3D + t节段性功能评分（短轴和 长轴）标记的MRI在休息和药理学（多巴酚丁胺）的压力下， 正常对照者(b)测量根据2D + t确定的功能评分 （短轴）标记的MRI在药理学应激和分类为正常， 运动减退或运动不能类。 然后，这些标签将在统计上与分配给 2D超声心动图和电影NIRI显示相同节段。(c)测量节段性 根据标记的3D + t（短轴和长轴）确定的功能评分 静息时NIRI，分为正常、运动减退、运动不能或运动障碍 陈旧性已治愈心肌梗死患者的治疗。标签将在统计上 与分配给来自2D的相同片段的非nal或运动不全标签相比 超声心动图和电影MRI，以及Gd对比MRI。(d)测量 3D + t（短轴和长轴）标记MRI的节段性功能评分， 休息并分为正常、运动减退、运动不能或运动障碍类别 缺血性扩张型心肌病患者标签将是 与分配给2D中相同段的标签进行统计学比较 超声心动图和磁共振电影

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.