4D Flow MRI in Assessment of True Severe Low-Gradient Aortic Stenosis

4D Flow MRI 评估真正的严重低梯度主动脉瓣狭窄

• 批准号: 10735953
• 负责人: AMIR A AMINI
• 金额: $ 23.48万
• 依托单位: UNIVERSITY OF LOUISVILLE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10735953
• 关键词: 3-Dimensional; 4D MRI; Adopted; Affect; Anatomy; Aortic Diseases; Aortic Valve Stenosis; Area; Breathing; Catheterization; Cessation of life; Chest; Chronic; Classification; Clinical; Correlation Studies; Data; Diagnostic; Diagnostic Procedure; Dobutamine; Dobutamine Stress Echocardiography; Doppler Echocardiography; Drops; Echocardiography; Enrollment; Equation; Goals; Heart; Heart Valve Diseases; Heart failure; Image; Learning; Left Ventricular Ejection Fraction; Liquid substance; Magnetic Resonance Imaging; Maps; Measurement; Measures; Methods; Modality; Morphologic artifacts; Nature; Noise; Operative Surgical Procedures; Patients; Protocols documentation; Rest; Risk; Safety; Scanning; Severities; Severity of illness; Stratification; Stress; Subgroup; Survival Rate; Symptoms; Syncope; Therapeutic Embolization; Training; Work; adverse outcome; aging population; anatomic imaging; aortic valve; aortic valve disorder; aortic valve replacement; data space; deep learning; hemodynamics; human subject; imaging modality; improved; pressure; respiratory; simulation; tomography; ultrasound

Degenerative aortic stenosis is a progressive valvular heart disease affecting the aging population and when hemodynamically significant is associated with serious adverse outcomes, such as heart failure, syncope, and death. Although, symptomatic classical severe aortic stenosis (AS), wherein aortic valve anatomical or effective area is ≤ 1.0 𝑐𝑚2 and mean gradient ≥ 40 mmHg raises no diagnostic dilemma, patients with low gradient aortic stenosis (i.e., mean gradient < 40 mmHg) that may be severe (i.e., aortic valve area ≤ 1.0 𝑐𝑚2) remain a challenge for determining the true severity of aortic stenosis and present a significant unmet clinical need. The discordance between aortic valve area of ≤ 1.0 𝑐𝑚2 and mean gradient < 40 mmHg is encountered in as many as 30 to 40% of patients with aortic valve area ≤ 1.0 𝑐𝑚2 by transthoracic echocardiography (TTE). In patients with these discordant findings, the true severity is uncertain and have led to the use of dobutamine stress echocardiography (DSE). Based on DSE, one can classify the potentially severe low-gradient subjects into 4 distinct subgroups a) Low gradient severe aortic stenosis (LGS): aortic valve area of ≤ 1.0 𝑐𝑚2 and a mean gradient of ≥ 40 mmHg with DSE. b) Low gradient pseudo-severe aortic stenosis (LGPS): aortic valve area of > 1.0 𝑐𝑚2 and a mean gradient of < 40 mmHg with DSE. c) Low gradient indeterminate aortic stenosis severity (LGI): aortic valve area of ≤ 1.0 𝑐𝑚2 and a mean gradient of < 40 mmHg with DSE. d) Finally, aortic valve area of > 1.0 𝑐𝑚2 and a mean gradient of ≥ 40 mmHg with DSE are classified as moderate or less severe aortic stenosis (LSA). Nearly one-third of patients classified as LGS are classified as LGPS with DSE (6). Further, compounding the concern in patients classified as LGPS, LGI, LSA is that they often manifest with symptoms potentially attributable to severe AS suggesting an initial misclassification perhaps due to measurement errors. Compared to echo, with MRI, the velocities can be measured in all 3D directions and due to its tomographic nature, no geometric assumptions are required. The hypothesis of the study is that our planned CMR methods which we will develop based on previous work will be able to better stratify these AS subjects. Our specific aims are: 1) We will develop efficient rest and dobutamine stress 4D Spiral flow imaging protocols based on k-space dependent respiratory gating. 2) We have recently developed a Deep Learning framework which based on Computational Fluid Dynamics (CFD) simulations of training data learns to directly map velocities to pressures. This will be adapted to measure the transvalvular pressure gradients (TVPG) in human subjects and validated. 3) In 40 subjects with potentially severe low gradient AS (10 in each of the LGS, LGPS, LGI, LSA), a TTE study, and a CMR study will be performed both at rest and under dobutamine stress. To validate, TVPG will be measured with cath in a group with n=10 of moderate AS (MAS) subjects undergoing cath for other purposes. This group will also undergo TTE and CMR studies. Subjects with severe AS were not selected for cath for safety reasons. Classification across modalities, flow, velocity, pressure, and orifice area will be statistically correlated.

退行性主动脉瓣狭窄是一种进行性瓣膜性心脏病，影响人口老龄化，当 血流动力学显着与严重的不良后果相关，例如心力衰竭、晕厥和 虽然，有症状的典型严重主动脉瓣狭窄（AS），主动脉瓣解剖还是有效的。 面积 ≤ 1.0 𝑐𝑚2 且平均梯度 ≥ 40 mmHg 不会引起诊断困境，低梯度主动脉患者 可能严重的狭窄（即平均梯度 < 40 mmHg）（即主动脉瓣面积 ≤ 1.0 𝑐𝑚2）仍然是 确定主动脉瓣狭窄的真实严重程度是一项挑战，并且提出了重大的未满足的临床需求。 主动脉瓣面积 ≤ 1.0 𝑐𝑚2 与平均梯度 < 40 mmHg 之间的不一致在许多情况下都会遇到 经胸超声心动图（TTE）显示，30% 至 40% 的患者主动脉瓣面积 ≤ 1.0 𝑐𝑚2。 由于这些不一致的发现，真正的严重程度是不确定的，并导致使用多巴酚丁胺应激 超声心动图（DSE） 基于DSE，可以将潜在严重的低梯度受试者分为4 类。 不同的亚组 a) 低梯度严重主动脉瓣狭窄 (LGS)：主动脉瓣面积 ≤ 1.0 𝑐𝑚2 且平均值 DSE 梯度≥ 40 mmHg b) 低梯度假性重度主动脉瓣狭窄 (LGPS)：主动脉瓣面积 > 1.0 𝑐𝑚2 且 DSE 平均梯度 < 40 mmHg c) 低梯度不确定主动脉瓣狭窄严重程度。 (LGI)：主动脉瓣面积 ≤ 1.0 𝑐𝑚2，DSE 平均梯度 < 40 mmHg d) 最后，主动脉瓣面积。 DSE 的 > 1.0 𝑐𝑚2 且平均梯度 ≥ 40 mmHg 被归类为中度或较轻的主动脉疾病 近三分之一被分类为 LGS 的患者被分类为具有 DSE 的 LGPS (6)。 对 LGPS、LGI、LSA 患者更令人担忧的是，他们经常表现出症状 可能归因于严重的 AS，表明最初的错误分类可能是由于测量误差造成的。 与回波相比，MRI 可以在所有 3D 方向上测量速度，并且由于其断层扫描 自然，不需要几何假设，该研究的假设是我们计划的 CMR 方法。 我们将在以前的工作基础上开发的，将能够更好地对这些 AS 主题进行分层。 是：1）我们将开发基于k空间的高效休息和多巴酚丁胺应激4D螺旋流成像协议 2）我们最近开发了一个基于呼吸门控的深度学习框架。 训练数据的计算流体动力学 (CFD) 模拟学习如何将速度直接映射到压力。 这将适用于测量人类受试者的跨瓣膜压力梯度（TVPG）并进行验证。 3) 在 40 名可能患有严重低梯度 AS 的受试者中（LGS、LGPS、LGI、LSA 各 10 名），一项 TTE 研究， 为了验证 TVPG，将在休息和多巴酚丁胺应激下进行 CMR 研究。 在一组 n=10 的中度 AS (MAS) 受试者中进行导管测量，这些受试者因其他目的而接受导管治疗。 该组还将接受 TTE 和 CMR 研究，出于安全考虑，未选择患有严重 AS 的受试者进行导管治疗。 不同模式、流量、速度、压力和孔口面积的分类将相互关联。

项目成果

4Dflow-VP-Net: A deep convolutional neural network for noninvasive estimation of relative pressures in stenotic flows from 4D flow MRI.

• DOI: 10.1002/mrm.29791
• 发表时间: 2023-11
• 期刊: MAGNETIC RESONANCE IN MEDICINE
• 影响因子: 3.3
• 作者: Nath, Ruponti;Kazemi, Amirkhosro;Callahan, Sean;Stoddard, Marcus F.;Amini, Amir A.
• 通讯作者: Amini, Amir A.