A New Paradigm for Rapid, Accurate Cardiac Magnetic Resonance Imaging

项目摘要/摘要 心血管疾病(CVD)夺走的生命和成本比美国任何其他诊断疾病都要高。 心脏磁共振(CMR)是一种无创成像工具，它提供了最准确和 对心血管系统的全面评估，但其在临床心脏病学中的作用仍然有限。一个 阻碍CMR更广泛使用的主要障碍是低效的获取，这使得CMR考试过于频繁 长的，通常持续一个多小时；这降低了它的效率和成本效益 医疗模式。目前的范例提供了一种延长的节段性获取，需要有规律的心脏 节律和多次屏息，或降级的实时、自由呼吸采集的后备选项 低于心脏磁共振学会指南的空间和时间分辨率。这个 这项研究的长期目标是通过以下方式改善心血管疾病的诊断和评估 将现有的分段CMR捕获转换为更有效的协议。新的范式将 (一)消除屏气的需要，(二)对心律失常患者有效，(三)简化获取 协议，(Iv)减少扫描时间，(V)提供全心覆盖，以及(Vi)实现空间和时间 分辨率可与分段屏息收购提供的分辨率相媲美。 在过去的二十年里，磁共振成像技术发展迅速。最近，平行磁共振的组合 成像(PMRI)和压缩感觉(CS)恢复已在许多研究和 带来了前所未有的加速。虽然pMRI已经被MRI行业采用并可用 在几乎所有的临床平台上，CS恢复距离常规临床应用还有很长的路要走。带来CS 恢复到临床领域，有许多挑战需要解决，包括井- 认识到需要逐个调整的计算时间长和调整参数的问题。 在这项工作中，我们将开发和验证一种通用的CS恢复方法，称为稀疏自适应组合 恢复(SCORE)，通过利用跨多个 申述。更重要的是，SCORE提供对所有自由参数的数据驱动调优，因此 无需手动调整正则化权重。此外，SCORE是服从快速算法的，我们 预计在基于GPU的计算环境中，基于分数的图像恢复只需几秒钟。 我们假设，拟议的数据采集和处理方面的进步将产生一种新的CMR协议 这对患者和操作员来说都更快、更容易，而且在更广泛的患者范围内是可靠的。我们预计 通过在图像质量方面提供必要的改进来实现这一目标(目标1)，通过重建 适合临床使用的时间(目标2)，通过验证方法的性能(目标3)，以及通过 在临床试验中展示了这种新方法的有效性和效率(目标4)。

Project Summary/Abstract Cardiovascular disease (CVD) claims more lives and costs more than any other diagnostic group in the USA. Cardiac magnetic resonance (CMR) is a non-invasive imaging tool that provides the most accurate and comprehensive assessment of the cardiovascular system, yet its role in clinical cardiology remains limited. A major impediment to wider usage of CMR is the inefficient acquisition that makes CMR exams excessively long, often lasting for more than an hour; this diminishes its efficiency and cost effectiveness relative to other modalities. The current paradigm offers either a prolonged segmented acquisition that requires regular cardiac rhythm and multiple breath-holds or a fallback option of real-time, free-breathing acquisition with degraded spatial and temporal resolutions that are below the Society for Cardiac Magnetic Resonance guidelines. The long-term goal of this investigation is to improve the diagnosis and evaluation of cardiovascular disease by transforming the existing segmented CMR acquisition into a more efficient protocol. The new paradigm will (i) eliminate the need to breath-hold, (ii) be effective in patients with arrhythmia, (iii) simplify the acquisition protocol, (iv) reduce the scan time, (v) provide whole-heart coverage, and (vi) enable spatial and temporal resolutions that rival the resolutions provided by segmented breath-held acquisition. In the last two decades, MRI technology has evolved rapidly. More recently, the combination of parallel MR imaging (pMRI) and compressive sensing (CS) recovery has been featured in numerous research studies and has delivered unprecedented acceleration. While pMRI has been adopted by the MRI industry and is available on almost all clinical platforms, CS recovery is still a long way away from routine clinical use. To bring CS recovery to clinical realm, there are a number of challenges that need to be addressed, including the well- recognized issues of long computation times and tuning parameters that require case-by-case adjustment. In this work, we will develop and validate a versatile CS recovery method, called sparsity adaptive composite recovery (SCoRe), that provides unmatched acceleration by exploiting sparsity across multiple representations. More importantly, SCoRe provides a data-driven tuning of all free parameters and thus eliminates the need to hand-tune regularization weights. Also, SCoRe is amenable to fast algorithms, and we expect the SCoRe-based image recovery to take only seconds on a GPU-based computing environment. We hypothesize that the proposed advances in data acquisition and processing will yield a new CMR protocol that is faster, easier for both patient and operator, and reliable over a broader spectrum of patients. We expect to achieve this objective by providing the necessary improvements in image quality (Aim 1), by reconstructing images in times suitable for clinical use (Aim 2), by validating the performance of the methods (Aim 3), and by demonstrating the effectiveness and efficiency of this new approach in a clinical trial (Aim 4).