Free-breathing and simultaneous multislice cine DENSE myocardial strain imaging

自由呼吸同时多层电影密集心肌应变成像

• 批准号: 10418633
• 负责人: Frederick H Epstein
• 金额: $ 38.53万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-17 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10418633
• 关键词: Algorithms; Aortic Valve Stenosis; Breathing; Cancer Patient; Cardiac; Cardiotoxicity; Collaborations; Data; Diagnosis; Evaluation; Financial compensation; Goals; Gold; Heart failure; Image; Left Ventricular Hypertrophy; Magnetic Resonance Imaging; Manuals; Manufacturer Name; Methods; Morphologic artifacts; Motion; Myocardial; Patient Schedules; Patient Selection; Patients; Phase; Physiologic pulse; Procedures; Prognosis; Protocols documentation; Radar; Relaxation; Reproducibility; Respiratory Diaphragm; Site; Source; Speed; System; Techniques; Undifferentiated; base; cardiac magnetic resonance imaging; cardiac resynchronization therapy; chemotherapy; healthy volunteer; heart imaging; imaging modality; improved; novel; prognostic; reconstruction; respiratory; risk stratification

Project summary The use and value of myocardial strain imaging have been increasing during the past 10 years. Among many applications, the most prominent include (a) the evaluation of cardiotoxicity in cancer patients undergoing chemotherapy, (b) prognosis and risk stratification in aortic stenosis, and (c) diagnosis and prognosis in undifferentiated left ventricular hypertrophy. We have developed Cine Displacement Encoding with Stimulated Echoes (DENSE) strain MRI, shared the method with other sites, and applied it to patient selection and procedure guidance in cardiac resynchronization therapy (CRT) for heart failure (HF). Cine DENSE is highly accurate and reproducible for the quantification of global and segmental myocardial strain, it is emerging as a gold standard technique, and it is being implemented by major manufacturers. However, current cine DENSE imaging requires multiple breathhold acquisitions or inefficient and inconvenient free-breathing acquisitions using diaphragm- based navigators, and neither approach is well suited for a rapid and efficient multiparametric cardiac MRI protocol or for sick patients with difficulty with breathhold-based protocols. In addition, inline strain analysis is not available and thus this task is performed offline on a workstation. With these limitations, more convenient methods such as feature tracking are often used, even though they are less accurate, less reproducible for segmental analysis, and/or less prognostic. This project will develop cine DENSE into a method that retains high accuracy and reproducibility and is also fast and easy-to-use. To achieve this goal, we propose four specific aims. In Aim 1, we will develop an efficient self-navigated free-breathing cine DENSE method, and in Aim 2 we will develop accelerated cine DENSE using simultaneous multislice methods. The methods in Aims 1 and 2 will be combined to enable accelerated free-breathing imaging. In Aim 3, we will develop methods for fully automatic displacement and strain analysis, enabling the implementation of inline strain mapping. Finally, in Aim 4 we will validate the methods developed in Aims 1-3 in healthy volunteers and HF patients scheduled to undergo CRT. Altogether, this project will result in a fast, reproducible, convenient and well-validated myocardial strain imaging method that will be broadly useful for the field of cardiac imaging.

项目摘要 在过去的10年中，心肌应变成像的使用和价值一直在增加。之中 许多应用，最突出的包括（a）评估正在接受的癌症患者中的心脏毒性 化学疗法，（b）主动脉狭窄中的预后和风险分层，以及（c）诊断和预后 未分化的左心室肥大。我们已经开发了用刺激的Cine位移编码 回声（密度）应变MRI，与其他站点共享该方法，并将其应用于患者的选择和程序 心脏衰竭（HF）心脏同步治疗（CRT）的指导。 Cine密集是高度准确的，并且 可重现用于量化全球和节段性心肌菌株，它正在作为黄金标准 技术，它是由主要制造商实施的。但是，当前的Cine密集成像需要 使用隔膜 - 基于基于的导航器，两种方法都非常适合快速有效的多参数MRI 方案或针对基于呼吸的方案困难的患者患者。此外，内联菌株分析是 不可用，因此此任务是在工作站上离线执行的。有这些限制，更方便 通常使用诸如功能跟踪之类的方法，即使它们的准确性较低，可再现的方法也不太可再现 节段分析和/或更少的预后。该项目将将Cine致密化成一种保留高的方法 准确性和可重复性，也可以快速且易于使用。为了实现这一目标，我们提出了四个具体的 目标。在AIM 1中，我们将开发一种有效的自由呼吸的Cine Cine密集方法，在Aim 2中我们 将使用同时的多层方法发展加速的Cine密集。目标1和2中的方法将 合并以实现加速的自由呼吸成像。在AIM 3中，我们将开发全自动的方法 位移和应变分析，实现内联菌株映射的实现。最后，在目标4中，我们将 验证在AIMS 1-3中在健康志愿者和计划接受CRT的HF患者中开发的方法。 总之，这个项目将导致快速，可重复，方便和验证的心肌菌株成像 对于心脏成像领域而言，将广泛有用的方法。

项目成果

Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping.

• DOI: 10.1186/s12968-021-00712-9
• 发表时间: 2021-03-11
• 期刊: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
• 作者: Ghadimi S;Auger DA;Feng X;Sun C;Meyer CH;Bilchick KC;Cao JJ;Scott AD;Oshinski JN;Ennis DB;Epstein FH
• 通讯作者: Epstein FH

Suppression of artifact-generating echoes in cine DENSE using deep learning.

• DOI: 10.1002/mrm.28832
• 发表时间: 2021-10
• 期刊: Magnetic resonance in medicine
• 影响因子: 3.3
• 作者: Abdi M;Feng X;Sun C;Bilchick KC;Meyer CH;Epstein FH
• 通讯作者: Epstein FH

Cardiac Magnetic Resonance Assessment of Response to Cardiac Resynchronization Therapy and Programming Strategies.

• DOI: 10.1016/j.jcmg.2021.06.015
• 发表时间: 2021-12
• 期刊: JACC. Cardiovascular imaging
• 作者: Gao X;Abdi M;Auger DA;Sun C;Hanson CA;Robinson AA;Schumann C;Oomen PJ;Ratcliffe S;Malhotra R;Darby A;Monfredi OJ;Mangrum JM;Mason P;Mazimba S;Holmes JW;Kramer CM;Epstein FH;Salerno M;Bilchick KC
• 通讯作者: Bilchick KC