A New Paradigm for Rapid, Accurate Cardiac Magnetic Resonance Imaging

快速、准确的心脏磁共振成像的新范例

基本信息

批准号：
10171886
负责人：
Rizwan Ahmad
金额：
$ 66.34万
依托单位：
OHIO STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10171886
关键词：
Acceleration Address Adopted Algorithms Arrhythmia Back Blood Breathing Cardiac Cardiology Cardiovascular Diagnostic Techniques Cardiovascular Diseases Cardiovascular system Clinical Clinical Trials Data Diagnosis Diagnostic Effectiveness Environment Goals Guidelines Hand Heart Heart Diseases Hour Image Image Compression Imaging Device Imaging Techniques Imaging technology Industry Investigation Lead Magnetic Resonance Magnetic Resonance Imaging Methodology Methods Modality Modeling Morphology Motion Outcome Study Patients Performance Perfusion Physiologic pulse Physiological Prevalence Protocols documentation Recovery Resolution Role Route Sampling Scanning Slice Societies Structure System Time Translating Validation Weight Work base clinical imaging computerized data processing cost cost effectiveness data acquisition diagnosis evaluation head-to-head comparison healthy volunteer heart function heart imaging heart rhythm hemodynamics imaging modality improved non-invasive imaging novel strategies parallel computer patient population perfusion imaging reconstruction relative effectiveness research clinical testing research study temporal measurement tool

项目摘要

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).

项目摘要/摘要心血管疾病（CVD）的生活和成本比美国任何其他诊断组高。心脏磁共振（CMR）是一种非侵入性成像工具，可提供最准确和最精确的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。一个更广泛使用CMR的主要障碍是使CMR考试过度的效率低下的收购长时间持续一个多小时；这降低了相对于其他的效率和成本效益方式。当前的范式提供了长时间的分段收购，需要常规心脏节奏和多种呼吸呼吸或实时，自由呼吸获取的后备选择在心脏磁共振准则以下的空间和时间分辨率。这这项调查的长期目标是通过将现有的分段CMR获取转换为更有效的协议。新范式将（i）消除呼吸的需求，（ii）在心律不齐的患者中有效，（iii）简化了收购协议，（iv）减少扫描时间，（v）提供全心覆盖范围，（vi）启用空间和时间与分段呼吸收购提供的决议相媲美的决议。在过去的二十年中，MRI技术迅速发展。最近，平行MR的组合在许多研究和已经提供了前所未有的加速度。虽然PMRI已被MRI行业采用，并且可以使用在几乎所有临床平台上，CS恢复与常规临床使用还有很长的路要走。带CS 恢复到临床领域，需要解决许多挑战，包括需要逐案调整的较长计算时间和调整参数的公认问题。在这项工作中，我们将开发和验证一种多功能CS恢复方法，称为稀疏自适应复合材料恢复（得分），通过跨多个稀疏性利用稀疏性，可以提供无与伦比的加速度表示。更重要的是，得分提供了所有自由参数的数据驱动调整，从而提供了消除了手工调整正则化重量的需求。另外，得分适合快速算法，我们期望基于分数的图像恢复仅在基于GPU的计算环境上仅需几秒钟。我们假设提出的数据获取和处理方面的进步将产生新的CMR协议对于患者和操作员来说，这更快，更容易，并且在更广泛的患者中可靠。我们期望通过重建图像质量的必要改进来实现这一目标适用于临床使用（AIM 2）的图像，通过验证方法的性能（AIM 3）以及通过在临床试验中证明了这种新方法的有效性和效率（AIM 4）。

项目成果

期刊论文数量（21）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Cardiac and respiratory motion extraction for MRI using pilot tone-a patient study.

使用导频音进行 MRI 心脏和呼吸运动提取 - 一项患者研究。

DOI：
10.1007/s10554-023-02966-z
发表时间：
2024
期刊：
The international journal of cardiovascular imaging
影响因子：
0
作者：
Chen,Chong;Liu,Yingmin;Simonetti,OrlandoP;Tong,Matthew;Jin,Ning;Bacher,Mario;Speier,Peter;Ahmad,Rizwan
通讯作者：
Ahmad,Rizwan

High-dimensional fast convolutional framework (HICU) for calibrationless MRI.