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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).

项目总结/文摘

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.