A New Paradigm for Rapid, Accurate Cardiac Magnetic Resonance Imaging

项目总结/摘要 心血管疾病（CVD）在美国比任何其他诊断组都要夺去更多的生命和成本。 心脏磁共振（CMR）是一种非侵入性成像工具，可提供最准确和最可靠的诊断。 尽管它对心血管系统有着全面的评估，但它在临床心脏病学中的作用仍然有限。一 CMR广泛使用的主要障碍是低效率的获取，使得CMR考试过度 长，往往持续一个多小时;这降低了其效率和成本效益相对于其他 方式。目前的范例提供了需要定期心脏检查的长时间分段采集， 或实时、自由呼吸采集的后备选项， 空间和时间分辨率低于心脏磁共振协会指南。的 这项研究的长期目标是通过以下方法改善心血管疾病的诊断和评估： 将现有的分段CMR采集转换为更有效的协议。新的范式将 (i)消除屏气的需要，（ii）对心律失常患者有效，（iii）简化采集 协议，（iv）减少扫描时间，（v）提供整个心脏覆盖，以及（vi）使空间和时间 与分段屏气采集提供的分辨率相媲美的分辨率。 在过去的二十年里，MRI技术发展迅速。最近，并行MR的组合 成像（pMRI）和压缩感知（CS）恢复已经在许多研究中得到了体现， 带来了前所未有的加速虽然pMRI已被MRI行业采用， 在几乎所有的临床平台上，CS的恢复离常规临床应用还有很长的路要走。把CS 恢复到临床领域，有一些挑战需要解决，包括良好的- 已经认识到的问题是计算时间长和调整参数，需要逐个情况进行调整。 在这项工作中，我们将开发和验证一个通用的CS恢复方法，称为稀疏自适应复合 恢复（SCoRe），通过利用多个节点之间的稀疏性提供无与伦比的加速 表示。更重要的是，SCoRe提供了所有自由参数的数据驱动调优， 消除了手动调整正则化权重的需要。此外，SCoRe适用于快速算法，我们 在基于GPU的计算环境中，基于SCORE的映像恢复预计只需几秒钟。 我们假设，在数据采集和处理方面提出的进展将产生一个新的CMR协议 这对于患者和操作者来说更快、更容易，并且在更广泛的患者范围内可靠。我们预计 为了通过提供必要的图像质量改进（目标1）来实现这一目标， 在适合临床使用的时间（目标2），通过验证方法的性能（目标3），并通过 在临床试验中证明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).