METHODS FOR ANALYSIS OF TAGGED MR CARDIAC IMAGES

标记 MR 心脏图像的分析方法

基本信息

批准号：
6043944
负责人：
AMIR A AMINI
金额：
$ 9.36万
依托单位：
BARNES-JEWISH HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
1998
资助国家：
美国
起止时间：
1998-08-01 至 2002-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/6043944
关键词：
bioimaging /biomedical imaging cardiography clinical research computer data analysis computer simulation diagnosis design /evaluation heart motion histopathology human subject image processing magnetic resonance imaging myocardial ischemia /hypoxia swine

项目摘要

DESCRIPTION (Adapted from Applicant's Abstract): The aim of this proposal is to further develop and validate algorithms for analysis of SPAMM MR cardiac images based on novel spline methods. MRI is unique in its ability to non-invasively and selectively alter tissue magnetization, and create tagged patterns within the deforming tissue such as the heart muscle. The resulting pattern defines a time-varying curvilinear coordinate system on the underlying tissue, allowing for precise and quantitative measurement of tissue motion and deformation. The investigators are developing two frameworks for analysis of SPAMM tagged images, both of these aimed at providing a more automated and reproducible approach to analysis of SPAMM data, as well as providing dense 3-D displacement information at all points within the LV myocardium. The investigators propose to (a) further develop and extend our analyses techniques. The extensions considered will all be related and based on currently developed computer vision-based techniques for regional LV wall motion analysis, that operates either on a sequence of SA slice stacks or on a time sequence of single slice. (b) The investigators will validate the motion tracking methods by comparing "true" and algorithm-estimated motion trajectories: 1) on dense field of points derived from 3-D tagged computer models of objects that simulate the moving LV, 2) on dense field of points derived from Finite Element Model simulations of the constitutive equations of LV deformations (once again tag planes will be superimposed on the time course of simulated geometries), 3) on selected points in the LV myocardium of the in vivo heart using a porcine model. Here, "true" motion will be determined by tracking implanted image distinguishable markers. (c) The investigators will test whether regions of postmortem myocardial injury imply similar-sized and locate regions of altered deformations (as measured by parameters developed in (a)). The algorithm-derived LV function assessment based on the analysis of in vivo tagged MRI sequences will be compared with postmortem myocardial injury assessment determined by myocardial staining techniques. The validated parameters will also be use to examine the time-course of change in the ischemic areas of the chronic animal models.

描述（根据申请人的摘要改编）：该提案的目的是进一步开发和验证算法以分析垃圾邮件MR 基于新样条方法的心脏图像。 MRI的能力是独一无二的非侵入性和选择性地改变组织磁化，并创建变形组织中的标记图案，例如心肌。这最终的模式定义了随着时变的曲线坐标系基础组织，可以精确和定量测量组织运动和变形。调查人员正在开发两个用于分析垃圾邮件标记图像的框架，这两个均针对提供更自动化和可重现的垃圾邮件分析方法数据，并在所有点提供密集的3D位移信息在LV心肌内。调查人员建议（a）进一步发展并扩展我们的分析技术。所考虑的扩展都将是相关并基于当前开发的基于计算机视觉的技术对于区域LV壁运动分析，该分析要么以一系列序列运行 SA切片堆栈或单切片的时间顺序。（b）研究人员将通过比较“真实”来验证运动跟踪方法和算法估计的运动轨迹：1）在密集的点上来自模拟移动的3-D标记的对象的计算机模型 LV，2）在有限元模型得出的点的密集场上模拟LV变形的本构方程（再次标记飞机将被叠加在模拟几何形状的时间过程中），3）在体内心脏的LV心肌中的选定点上使用猪模型。在这里，“ True”运动将通过跟踪植入图像来确定可区分的标记。（c）调查人员将测试是否验尸心肌损伤意味着大小相似的区域变化变化（如在（a）中开发的参数测量）。这基于体内分析的算法衍生的LV功能评估标记的MRI序列将与验尸心肌损伤进行比较由心肌染色技术确定的评估。已验证参数也将用于检查变更的时间顺序慢性动物模型的缺血区域。