Reliable Evaluation of Coronary Artery Disease using Myocardial BOLD MRI with CO2

描述（由申请人提供）：冠状动脉疾病是美国的主要死亡原因。据估计，在美国，超过1600万人患有冠状动脉疾病（CAD），超过三分之一的死亡是由于CAD。此外，美国每年有超过100万人因CAD住院。最常见的CAD形式导致冠状动脉变窄（狭窄），导致供应给心肌的血流和氧气减少，导致心肌缺血-心肌的氧气需求远远超过可用供应的状况。心肌缺血的存在是主要不良心脏事件（MACE：死亡、心肌梗死和卒中）的重要风险因素。根据与稳定性CAD相关的缺血负荷的程度和严重程度进行适当的早期干预（冠状动脉搭桥术、血管成形术、药物或药物治疗）可能有助于降低MACE的风险。因此，一个可靠的，非侵入性的，可重复的方法来确定缺血的范围和严重程度是非常宝贵的管理与CAD患者。 该提案的广泛、长期目标是改善冠状动脉疾病患者的预后。评估临床显著心肌缺血的理想策略是完全非侵入性的;即，除了避免心导管插入术的风险外，它不含电离辐射、外源性造影剂和具有风险和副作用的药理学应激剂。尽管当前的临床标准并未提供其中许多益处，但心肌血氧水平依赖性（BOLD）MRI可以满足其中许多要求。然而，这种方法的广泛使用目前受到灵敏度、特异性不足和需要静脉内药理学（腺苷）应激的限制，所有这些都在临床实践中造成了相当大的限制。 在拟议的项目中，我们希望显着提高心肌BOLD MRI的可靠性，使其变得足够强大，以准确量化与临床显著的CAD相关的缺血体积，而无需静脉内药物应激或外源性造影剂。所提出的方法利用（i）动脉CO2分压（PaCO 2）的个体化目标变化作为非侵入性血管活性刺激，（ii）3 T下的快速、高分辨率、4D BOLD MRI，以及（iii）广义线性模型（GLM）理论来导出统计参数图（SPM），以可靠地检测和量化临床显著性。 以数据驱动的方式测量缺血心肌体积。这些研究有望为无创、可靠的冠状动脉疾病预后评估提供基础科学依据。

DESCRIPTION (provided by applicant): Coronary artery disease is the leading cause of death in the United States. It is estimated that in excess of 16 million people are living with coronary artery disease (CAD) and more than 1 in three deaths are due to CAD in the US. In addition, more than 1 million people are hospitalized each year in the US because of CAD. The most common form of CAD leads to the narrowing of the coronary arteries (stenosis) resulting in reduced blood flow and oxygen supplied to the heart muscle, results in myocardial ischemia - a condition where the oxygen demand of the myocardium is far in excess of the available supply. The presence of myocardial ischemia is an important risk factor for major adverse cardiac events (MACE: death, myocardial infarction, and stroke). Appropriate early interventions (coronary bypass, angioplasty, pharmacological, or medical therapy) that are guided by the extent and severity of ischemic burden associated with stable CAD may be instrumental in reducing the risk of MACE. Hence a reliable, non-invasive, and repeatable method for determining the extent and severity of ischemia is invaluable in managing patients with CAD. The broad, long-term objective of this proposal is to improve the prognosis of patients with coronary artery disease. An ideal strategy for assessing clinically significant myocardial ischemia would be completely non-invasive; that is, in addition to avoiding the risks of cardiac catheterization, it would be free of ionizing radiation, exogenous contrast media, and pharmacological stress-agents with both risks and side effects. Although the current clinical standards do not provide many of these benefits, a number of these requirements can be met by myocardial Blood-Oxygen-Level-Dependent (BOLD) MRI. However, the widespread use of this approach is currently limited by inadequate sensitivity, specificity, and the need for intravenous pharmacological (adenosine) stress, all of which pose considerable limitations in clinical practice. In the proposed project, we wish to significantly improve the reliability of myocardial BOLD MRI so that is becomes powerful enough to accurately quantify the ischemic volume associated with clinically significant CAD without intravenous pharmacological stress or exogenous contrast media. The proposed method utilizes (i) an individualized targeted change in arterial partial pressure of CO2 (PaCO2) as the non-invasive vasoactive stimulus, (ii) fast, high-resolution, 4D BOLD MRI at 3T and (iii) the generalized linear model (GLM) theory to derive statistical parametric maps (SPM) to reliably detect and quantify the clinically significant ischemic myocardial volume in a data-driven fashion. These studies are expected to provide the fundamental scientific basis for a non-invasive and reliable imaging strategy for evaluating prognosis of patients with coronary artery disease.