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（改编自申请人的摘要）：申请人提议 开发和验证新的图像分析方法，旨在更准确、 可重复且自动化的区域左心室评估方法 (LV) 功能以及来自标记 MRI 数据的 3D 心脏运动可视化 患有冠状动脉疾病（CAD）的患者。申请人已经开发出一种 多种分析标记 MRI 数据的方法已在 心肌梗塞（MI）的体模和动物模型。他们提议 继续开发这些技术，利用所有可用的 条带信息，包括标签交叉点和线性标签线， 自动进行 LV 变形并重建密集位移 所有心肌点，目标是常规应用这些技术 患者数据。所开发方法的优点是由于位移 向量将在所有心肌点可用，左心室功能指数将 也可分布于心肌各处。这些指数可以相加 局部心肌区域导致节段功能评分。在人类 研究中，所开发的方法将应用于从正常情况下获取的图像 志愿者、药物应激引起的心肌缺血患者、 陈旧且已治愈的心肌梗死患者以及缺血性扩张患者 心肌病。在每种情况下，节段性室壁运动均由 算法将与经过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， 具体目标是： (a) 衡量统计分布（平均值和 3D + t（短轴和 长轴）标记的静息和药理（多巴酚丁胺）应激下的 MRI 正常控制。 (b) 测量由 2D + t 确定的功能分数 （短轴）标记药物应激期间的 MRI 并分为正常、 应激性缺血患者的运动机能减退或无运动类别。 然后，这些标签将与分配给该标签的标签进行统计相关。 通过 2D 超声心动图和电影 NIRI 检测相同的节段。 (c) 衡量分段 根据 3D + t（短轴和长轴）标记确定的功能分数 休息时的 NIRI，分为正常、运动不足、运动不能或运动障碍 为患有陈旧但已治愈的心肌梗死的患者开设课程。标签将被统计 与从 2D 分配给同一段的非最终或运动标签相比 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 的节段功能评分 休息并分为正常、运动不足、运动不能或运动障碍类别 患有缺血性扩张型心肌病的患者。标签将是 与从 2D 分配给同一段的标签进行统计比较 超声心动图和电影 MRI。