A Bayesian Model for Highly Accelerated Phase-Contrast MRI
A Bayesian Model for Highly Accelerated Phase-Contrast MRI
复制标题
DOI：
10.1002/mrm.25904
复制
发表时间：
2016-08-01
影响因子：
3.3
通讯作者：
Ahmad, Rizwan
中科院分区：
文献类型：
--
作者：
Rich, Adam;Potter, Lee C.;Ahmad, Rizwan
目的：相衬磁共振成像是一种通过量化血流来评估心血管疾病的非侵入性工具;然而，低数据采集效率限制了空间和时间分辨率、实时应用以及临床环境中四维血流成像的扩展。我们提出了一种新的数据处理方法，称为重建速度编码的MRI与近似的消息传递aLtaxms（ReVEAL），加快收购利用数据结构独特的相位对比磁共振imaging.Theory and Methods：所提出的方法模型物理相关性跨越空间，时间和速度编码。所提出的贝叶斯方法利用速度编码之间的幅度和相位的关系。提出了一种基于消息传递的快速迭代恢复算法。为了进行验证，对脉动流体模和五名健康志愿者的前瞻性欠采样数据进行了处理。结果：通过峰值速度和每搏输出量（SV）量化，所提出的方法与加速率参考数据一致性良好R = 0.99对于体模成像（n = 24）和r >= 0.96对于前瞻性加速体内成像（n = 10）R
Purpose: Phase-contrast magnetic resonance imaging is a noninvasive tool to assess cardiovascular disease by quantifying blood flow; however, low data acquisition efficiency limits the spatial and temporal resolutions, real-time application, and extensions to four-dimensional flow imaging in clinical settings. We propose a new data processing approach called Reconstructing Velocity Encoded MRI with Approximate message passing aLgorithms (ReVEAL) that accelerates the acquisition by exploiting data structure unique to phase-contrast magnetic resonance imaging.Theory and Methods: The proposed approach models physical correlations across space, time, and velocity encodings. The proposed Bayesian approach exploits the relationships in both magnitude and phase among velocity encodings. A fast iterative recovery algorithm is introduced based on message passing. For validation, prospectively undersampled data are processed from a pulsatile flow phantom and five healthy volunteers.Results: The proposed approach is in good agreement, quantified by peak velocity and stroke volume (SV), with reference data for acceleration rates R = 0.99 for phantom imaging (n = 24) and r >= 0.96 for prospectively accelerated in vivo imaging (n = 10) for R