Improved cardiac T1 reactivity measures for gadolinium-free MRI assessment of ischemic heart disease

缺血性心脏病（IHD），也称为冠状动脉疾病，是一个主要的医疗保健问题 这影响了2000多万美国人，每年给我们国家造成的损失估计为828亿美元。心肌 灌注成像是检测和表征IHD的经验证的工具。计算单光子发射时 断层扫描（SPECT）成像在美国被广泛使用，MRI提供更高分辨率的灌注图像 没有电离辐射。然而，灌注MRI需要注射基于钆的造影剂， 识别灌注不足区域。钆在肾功能不佳的患者中是有问题的， 从这些心脏MR灌注研究中排除。心脏T1标测最近显示出希望， 在不使用钆的情况下识别和表征冠状动脉疾病。T1映射在 在心脏的静息状态下再次计算T1差异， 这一百分比被称为T1反应性。通过反映血容量的变化，T1反应性已被证明是 有望识别心肌中的缺血区域。T1反应性是一种有前途的生物标志物，不仅适用于 分类患者进行导管插入术，但也进行纵向研究，以确定治疗的有效性， 预测未来的心脏事件。然而，现有的协议是次优的，以可靠地检测T1变化， 应力患者在压力和运动不足的情况下也很难长时间屏住呼吸 补偿导致差的T1图质量。药理学应激的有限时间窗可以限制 切片覆盖率。为了充分评估非造影T1方法的潜力，我们计划开发一种 稳健的T1标测方法，通过开发稳健的运动来优化T1标测协议 补偿方法，并在有限的时间窗口内获得整个心脏覆盖， 减少屏气时间。本项目的具体目标是：（1）优化T1映射协议， 开发一种用于压力下大呼吸运动的鲁棒图像配准方法（2），以开发新的 同步多切片采集方法和最先进的深度学习技术， 心脏T1标测，以及（3）通过将新的快速T1标测与当前的钆- 基于灌注的IHD检测方法。我们的团队和机构拥有深厚的心脏MRI经验， 成功执行该项目的各个方面所需的技术。我们项目的成功将带来一个 用于疑似IHD患者的改变游戏规则的MRI技术：快速，全心脏覆盖的T1标测 不使用钆，以及准确表征新产品性能的验证研究 法

Summary: Ischemic heart disease (IHD), also called coronary artery disease, is a major healthcare problem that affects over 20 million Americans and costs our nation an estimated $82.8 billion each year. Myocardial perfusion imaging is a proven tool to detect and characterize IHD. While Single Photon Emission Computed Tomography (SPECT) imaging is widely used in the U.S., MRI offers higher resolution perfusion images without ionizing radiation. However, perfusion MRI requires injecting gadolinium-based contrast agents to identify regions of perfusion deficit. Gadolinium is problematic in patients with poor kidney function, who are excluded from these cardiac MR perfusion studies. Cardiac T1 mapping recently has shown promise to identify and characterize coronary artery disease without the use of gadolinium. T1 mapping is performed in a pharmacologically induced stress state and again in the resting state of the heart to compute T1 differences as a percentage known as T1 reactivity. By reflecting blood volume changes, T1 reactivity has shown to be promising to identify ischemic regions in the myocardium. T1 reactivity is a promising biomarker not only for triaging patients for catheterization but also in longitudinal studies to determine the efficacy of therapy and to predict future cardiac events. However, existing protocols are sub-optimal to reliably detect T1 changes at stress. It is also difficult for patients to hold their breath for long durations at stress and inadequate motion compensation leads to poor T1 map quality. The limited time window of pharmacological stress can limit the slice coverage. In order to fully evaluate the potential of the non-contrast T1 approach, we plan to develop a robust T1 mapping method that optimizes the T1 mapping protocol, by developing a robust motion compensation method and obtaining whole heart coverage within the limited time window and significantly reduce the breath-hold duration. Specific aims of the project are (1) to optimize T1 mapping protocol and develop a robust image registration method for large breathing motion at stress (2) to develop novel simultaneous multi-slice acquisition methods and state-of-the-art deep learning techniques for rapid, whole- heart T1 mapping, and (3) to validate the new rapid T1 mapping by comparing it to the current gadolinium- based perfusion method for IHD detection. Our team and institution have deep cardiac MRI experience and the technology needed to successfully execute all aspects of this project. The success of our project will deliver a game-changing MRI technology for patients with suspected IHD: rapid, whole-heart coverage T1 mapping without the use of gadolinium, and validation studies that accurately characterize the performance of the new method.