A comprehensive valvular heart disease assessment with stress cardiac MRI

项目摘要/摘要 二尖瓣返流(MR)是一个日益严重的公共卫生问题，随着人口老龄化，其患病率 预计将急剧上升。对于磁共振诊断和严重程度评估，超声心动图技术 长期以来，这一直是护理的标准。然而，基于这些技术的评估在以下两个方面都有局限性 技术挑战和治疗建议。因此，对MR的优化管理，特别是 确定手术的时机仍然很复杂，并将受益于提供量化的工具 这个项目的总体目标是开发和验证压力 心血管磁共振成像方案，可为MR患者提供更明确的治疗计划。 心血管磁共振成像(CMR)是一种成熟的成像技术，它提供了最全面的 心血管系统的评估。结果表明，基于CMR的流量量化方法具有较好的重复性 优于超声心动图。尽管有这些优势，CMR的附加临床价值 MR患者尚未得到证实。最近，有证据表明，基于CMR的评估已经 更好地预测MR患者的临床结果，因此可以在确定 这类患者的管理计划。然而，现有的CMR技术具有显著的局限性， 排除了它们在常规临床护理中的使用。例如，使用传统的2D相-的流量量化- 对比磁共振成像(PC-MRI)对成像平面的位置敏感，不能测量跨瓣膜 直接流出，需要屏息，容易出现心律不齐。最近，4D血流成像， 由于其体积覆盖和三向编码，已获得重大兴趣，但收购 对于4D血流成像，使用现有的方案可能会太长，特别是对于全心脏覆盖。 此外，现有的4D血流成像协议仅在静止条件下进行成像，这不能完全 描述只有在压力测试下才显露出来的功能损伤。 在这项工作中，我们将开发和验证一个全面的CMR协议，该协议(I)提供阿魏酸甘油酯- 具有全心脏覆盖的增强型4D血流成像，(Ii)需要来自MRI技术专家的最小规划， (Iii)在临床可行的采集时间内进行，(Iv)不需要屏气或定期心脏跳动 节奏，(V)不需要导航器门控，(Vi)允许在运动压力下成像，暴露功能 损伤，以及(Vii)另外提供心功能量化来解释和解释应激诱导 MR患者可观察到功能损害。在目标1和目标2中，我们将开发和优化协议。在……里面 目标3和4，我们将在55名健康受试者和55名健康受试者身上验证该方案的准确性和重复性 被诊断为We先生的患者假设开发的方案会导致更可靠的评估 比单独TTE的MR更有可能，并为更大规模的临床研究奠定了基础，在这些研究中，CMR的力量 展示了预测临床结果的参数。

Project Summary/Abstract Mitral valve regurgitation (MR) is a growing public health concern, and with an aging population, its prevalence is expected to rise steeply. For MR diagnosis and severity assessment, echocardiographic techniques have long been the standard of care. Assessment based on such techniques, however, has limitations, both in terms of technical challenges and treatment recommendations. As a result, optimal management of MR, especially determining the timing of surgery, remains complex and stands to benefit from tools that provide quantitative and comprehensive characterization of MR. The overall goal of this project is to develop and validate a stress cardiovascular MRI protocol that can lead to a more definitive treatment plan for MR patients. Cardiovascular MRI (CMR) is a well-established imaging technique that provides the most comprehensive evaluation of the cardiovascular system. The reproducibility of CMR-based flow quantification has been shown to be superior to that of echocardiography. Despite these advantages, the additive clinical value of CMR for MR patients has not been established. More recently, evidence has emerged that CMR-based assessment has better predictive power for clinical outcomes for MR patients and thus could play a central role in determining management plans for such patients. Existing CMR techniques, however, have significant limitations, precluding their use in routine clinical care. For example, the flow quantification using traditional 2D phase- contrast MRI (PC-MRI) is sensitive to the placement of the imaging plane, cannot measure the transvalvular flow directly, requires breath-holding, and is susceptible to irregular cardiac rhythm. Recently, 4D flow imaging, due to its volumetric coverage and three-directional encoding, has gained significant interest, but acquisition for 4D flow imaging using existing protocols can be prohibitively long, especially for whole-heart coverage. Also, existing 4D flow imaging protocols only perform imaging under resting conditions, which cannot fully characterize functional impairment that is only unmasked under stress testing. In this work, we will develop and validate a comprehensive CMR protocol that (i) provides ferumoxytol- enhanced 4D flow imaging with whole-heart coverage, (ii) requires minimal planning from the MRI technologist, (iii) is performed in clinically feasible acquisition time, (iv) does not require breath-holds or regular cardiac rhythm, (v) does not require navigator gating, (vi) allows imaging during exercise stress, exposing functional impairment, and (vii) additionally provides cardiac function quantification to explain and interpret stress-induced functional impairment observed in MR patients. In Aims 1 and 2, we will develop and optimize the protocol. In Aims 3 and 4, we will validate the accuracy and reproducibility of the protocol in 55 healthy subjects and 55 patients diagnosed with MR. We hypothesize that the developed protocol leads to a more reliable assessment of MR than possible with TTE alone and set the stage for larger clinical studies where the power of CMR parameters to predict clinical outcomes is demonstrated.