Dynamic MRI for Myrocardial Perfusion and Viability

描述（由申请人提供）： 该提案旨在通过使用MRI和基于钆的顺磁造影剂来提高冠状动脉疾病的非侵入性诊断和预后的准确性。本文提出的建模方法的首过MRI可能能够以高空间分辨率提供绝对区域血流。这些首过研究还可以提供独特的可行性信息。具体目标是（1）开发和优化采集策略，以获得针对房室模型定制的数据（2）开发用于分析心脏对比MRI数据的临床实用方法（3）将此处开发的MRI方法的流量估计值与MRI上坡灌注指数和动态N-13-氨PET获得的绝对血流测量值进行比较。(4)将第一遍建模方法中的生存力测量值添加到延迟图像中，以确定这种方法是否改善了生存力预测。研究方法：（1）将使用逼真的计算机模拟和人体研究，对时间采样策略进行系统分析，并使用减少的k空间采集来增加体积覆盖范围，减少伪影，并保持信号和高空间分辨率。(2)将开发与时间聚类方法相结合的链接活动轮廓，以自动分割时间序列数据中的心内膜和心外膜。将开发并验证输入函数的盲识别方法（输入函数在高钆浓度下不准确）。将开发两种不同的生理模型，并在其提供绝对流量值和可靠的细胞外容积估计的能力方面进行比较。(3)将使用34项人体研究进行MRI上斜率和PET灌注的比较。(4)将首次通过的活力指标和三个综合活力指标与17例患者的延迟增强Gd MRI图像和血运重建后数据进行比较。该项目的成果将是经验证的成像协议和软件，用于首次通过MRI研究，以及用于体内心肌灌注和活力评估的实用和准确的方法。这些方法对于改善医疗保健和改善基础科学研究（如跟踪基因治疗中的新生血流变化）将是非常宝贵的。

DESCRIPTION (provided by applicant): This proposal seeks to improve the accuracy of noninvasive diagnosis and prognosis of coronary artery disease by using MRI and a gadolinium-based paramagnetic contrast agent. First-pass MRI with the modeling methods proposed here may be able to provide absolute regional blood flows at a high spatial resolution. These first-pass studies may also offer unique viability information. The specific aims are (1) To develop and optimize acquisition strategies to obtain data tailored for compartmental modeling (2) To develop clinically practical methods for analyzing the cardiac contrast MRI data with models (3) To compare the flow estimates from the MRI methods developed here to an MRI upslope perfusion index and to absolute blood flow measurements obtained with dynamic N-13-ammonia PET. (4) To add viability measures from the first pass modeling approach to delayed images to determine if such an approach improves prediction of viability. Methods: (1) Systematic analysis of temporal sampling strategies and the use of reduced k-space acquisitions to increase volume coverage, reduce artifacts, and maintain signal and high spatial resolution will be pursued using realistic computer simulations and human studies. (2) Linked active contours combined with temporal clustering methods will be developed to automatically segment the endocardium and epicardium in the time series data. Methods for blind identification of the input function (input functions are inaccurate at high gadolinium concentrations) will be developed and validated. Two different physiological models will be developed and compared in their ability to provide absolute flow values and reliable extracellular volume estimates. (3) The comparisons with MRI upslope and PET perfusion will be performed using 34 human studies. (4) The first-pass viability measures and three integrated viability measures will be compared to delayed enhancement Gd MRI images and to post-revascularization data in 17 patients. The outcome of this project will be validated imaging protocols and software for use with first-passMRI studies, and practical and accurate methods for myocardial perfusion and viability assessment in vivo. Such methods will be invaluable for improved health care and for improved basic science research, such as tracking nascent flow changes in gene therapy.