3D Free-breathing MRI with High Scan Efficiency for Assessment of Cardiovascular Disease: Combining Acceleration and Motion Correction Techniques

冠状动脉疾病是西方世界发病率和死亡率的主要原因，每年在英国造成超过65.000人死亡。改善心血管疾病的治疗和结果是英国国家医疗服务体系的主要优先事项之一。CAD减少了心肌的血液供应，可能导致胸痛(心绞痛)或心脏病发作。目前它的诊断是通过侵入性、电离和潜在有害的X射线心脏插管程序进行的。磁共振成像(MRI)是一种非常有前景的无创性工具，用于冠心病的早期风险评估、指导治疗和治疗监测。临床研究表明，血流灌注、心功能、晚期Gd增强(LGE；梗塞)和冠状动脉磁共振血管成像(CMRA)对冠心病的评估具有潜在价值。然而，仍需要技术发展才能使MRI达到与当前临床黄金标准相似的诊断准确率。心血管MRI的两个主要挑战是1)呼吸运动导致的图像质量下降，2)所需的高空间分辨率导致的长扫描时间。两者都可能导致非诊断性图像质量和患者吞吐量低，如果不能充分解决，会导致高昂的手术成本。目前促进这些问题的发展仍然存在采集时间长或需要多次屏气采集的问题，这在病情严重的患者中可能很困难，并导致诊断准确性降低。LGE和CMRA协议尤其受到这些限制的影响。LGE在存活和纤维化/梗死的心肌组织之间产生高对比度的图像，需要高分辨率才能准确测量梗死面积和跨壁情况，因为它对治疗决策和患者预后具有重要意义。同样，CMRA需要高分辨率3D成像才能准确显示冠状动脉狭窄。在自由呼吸LGE和CMRA成像中，最常见的检测和纠正呼吸运动的方法是使用横隔膜导航器回波来选通MR采集。利用该方法，仅当呼吸信号与呼吸周期的预定义接受窗口(例如，终止呼气)重合时，才获取MR数据，而所有其他数据被拒绝。3到5 mm的小门窗可以减少运动伪影，但会导致采集时间延长，这甚至可能导致呼吸模式高度不规则的患者的扫描流产。目前的方法往往会由于残留呼吸运动而导致采集时间较长和/或图像质量不佳。在本方案中，我们旨在开发、实施和测试用于LGE和CMRA的高效(扫描时间更短)和健壮(不需要规划或患者协作)的呼吸运动补偿框架的临床可行性。该框架应允许将当前CMRA和LGE协议的捕获时间从~10分钟减少到不到3分钟。我们假设，这可以通过开发一种新的3D方法来实现，该方法结合了新的数据采样方案、新的欠采样重建技术和用于同时进行欠采样图像重建和自由呼吸采集数据的运动校正的数学框架。在不久的将来，该项目将惠及从事冠状动脉成像和心肌组织表征领域的科研人员，以及从事核磁共振重建和运动矫正工作的人员。此外，它还将加强英国在医学成像研究方面本已强大的角色。从长远来看，这项研究的受益者可能是冠心病患者，他们将受益于高效和准确的非侵入性诊断测试。然而，广泛的临床应用需要在更多的患者中进行后续的临床研究。

Coronary artery disease (CAD) is the leading single cause of morbidity and mortality in the Western world, causing over 65.000 deaths every year in England. Improving the treatment and outcome of cardiovascular disease is one of the main priorities of the National Health Service in the UK. CAD reduces the blood supply to the cardiac muscle and can lead to chest pain (angina) or heart attack. Its diagnosis is currently performed by invasive, ionizing, and potentially harmful X-ray cardiac catheterization procedures. Magnetic Resonance Imaging (MRI) is a very promising non-invasive tool for early risk assessment, guidance of therapy and treatment monitoring of CAD. Clinical research studies have shown the potential of perfusion, cardiac function, late gadolinium enhancement (LGE; infarct) and coronary MR angiography (CMRA) for the assessment of CAD. However, technical developments are still needed to allow MRI achieving similar diagnostic accuracy as the current clinical gold standard. Two major challenges in cardiovascular MRI are 1) image quality degradation due to respiratory motion, and 2) long scan times resulting from the required high-spatial resolution. Both can lead to non-diagnostic image quality and a low patient throughput resulting in high operation costs if not adequately addressed. Current developments that facilitate these problems still suffer from either long acquisition times or require acquisitions under multiple breath-holds, which can be difficult in very sick patients and lead to a reduced diagnostic accuracy.LGE and CMRA protocols are particularly affected by these limitations. LGE yields images with a high contrast between viable and fibrotic/infarcted myocardial tissue and requires high resolution to accurately measure infarct size and transmurality as it has important implications on treatment decisions and patient prognosis. Similarly high-resolution 3D acquisitions are required in CMRA to accurately visualize coronary stenosis. The most common approach to detect and correct for respiratory motion in free-breathing LGE and CMRA imaging is the use of diaphragmatic navigator echoes to gate the MR acquisition. With this approach the MR data is acquired only when the respiratory signal coincides with a predefined acceptance window of the breathing cycle (e.g. end-expiration) with all other data being rejected. Small gating windows of 3 to 5mm allow to reduce motion artifacts but lead to prolonged acquisition times, which may even result in scan abortion in patients with highly irregular breathing patterns. Current approaches often lead to long acquisition times and/or suboptimal image quality due to residual respiratory motion.In this proposal we aim to develop, implement and test the clinical feasibility of an efficient (shorter scan time) and robust (neither planning nor patient collaboration required) respiratory motion compensation framework for LGE and CMRA. This framework should allow to reduce the acquisition time of current CMRA and LGE protocols from ~10 min to less than 3 min. We hypothesize that this can be achieved by developing a new 3D approach that combines novel data sampling schemes, novel undersampling reconstruction techniques and a mathematical framework for simultaneous undersampled image reconstruction and motion correction of the free-breathing acquired data. In the near future this project will benefit the scientific research community working in the field of coronary artery imaging and myocardial tissue characterization, as well as those working on MRI reconstruction and motion correction. Moreover, it will strengthen the UK's already strong role in medical imaging research. In the long term, the beneficiaries of this research may be patients with coronary artery disease who will benefit from efficient and accurate non-invasive diagnostic tests. However, a broad clinical application would require subsequent clinical studies in a larger number of patients.