METHODS FOR ANALYSIS OF TAGGED MR CARDIAC IMAGES

描述（改编自申请人摘要）：本提案的目的 进一步开发和验证SPAMM MR分析算法 心脏图像的基础上，新的样条方法。 核磁共振成像是独一无二的 以非侵入性和选择性地改变组织磁化， 在变形的组织如心肌中标记的模式。 的 所得到的图案定义时变曲线坐标系， 下面的组织，允许精确和定量测量 组织运动和变形。 调查人员正在开发两个 用于分析SPAMM标记图像的框架，这两个框架都旨在 提供了一种更加自动化和可重复的方法来分析SPAMM 数据，并提供所有点的密集三维位移信息 在左心室心肌内。 研究人员建议：（a）进一步发展 扩展我们的分析技术。 考虑的扩展都将是 基于当前开发的基于计算机视觉的技术 对于局部LV室壁运动分析，其对以下序列进行操作： SA切片堆叠或在单个切片的时间序列上。 (b)的 研究人员将通过比较“真实” 和算法估计的运动轨迹：1）在密集的点场上 来自模拟移动物体的3D标记计算机模型 LV，2）关于有限元模型导出的稠密点域 模拟LV变形的本构方程（再次标记 平面将叠加在模拟几何形状的时间过程上），3） 在体内心脏的LV心肌中的选定点上，使用猪 模型 这里，“真实”运动将通过跟踪植入图像来确定 可区分的标记。 (c)研究人员将测试这些地区是否 死后心肌损伤意味着相似大小和位置的 改变的变形（通过（a）中开发的参数测量）。 的 基于体内分析的算法推导的LV功能评估 将标记的MRI序列与死后心肌损伤进行比较 通过心肌染色技术确定的评估。 经验证的 参数也将被用来检查时间过程中的变化， 慢性动物模型的缺血区域。

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.