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应用欠采样径向快速小角度激发和非线性逆重建技术的心血管血流实时相位对比 MRI。

Real-time phase-contrast MRI of cardiovascular blood flow using undersampled radial fast low-angle shot and nonlinear inverse reconstruction.

机构信息

Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen, Germany.

出版信息

NMR Biomed. 2012 Jul;25(7):917-24. doi: 10.1002/nbm.1812. Epub 2011 Dec 19.

DOI:10.1002/nbm.1812
PMID:22180216
Abstract

Velocity-encoded phase-contrast MRI of cardiovascular blood flow commonly relies on electrocardiogram-synchronized cine acquisitions of multiple heartbeats to quantitatively determine the flow of an averaged cardiac cycle. Here, we present a new method for real-time phase-contrast MRI that combines flow-encoding gradients with highly undersampled radial fast low-angle shot acquisitions and phase-sensitive image reconstructions by regularized nonlinear inversion. Apart from calibration studies using steady and pulsatile flow, preliminary in vivo applications focused on through-plane flow in the ascending aorta of healthy subjects. With bipolar velocity-encoding gradients of alternating polarity that overlap the slice-refocusing gradient, the method yields flow-encoded images with an in-plane resolution of 1.8 mm, section thickness of 6 mm and measuring time at 3 T of 24 ms (TR/TE = 3.44/2.76 ms; flip angle, 10º; seven radial spokes per image). Accordingly, phase-contrast maps and corresponding velocity profiles achieve a temporal resolution of 48 ms. The evaluated peak velocities, stroke volumes, flow rates and respective variances over at least 20 consecutive heartbeats are in general agreement with literature data.

摘要

心血管血流的速度编码相位对比 MRI 通常依赖于心电图同步的多心跳电影采集,以定量确定平均心动周期的流动。在这里,我们提出了一种新的实时相位对比 MRI 方法,该方法将流动编码梯度与高度欠采样的径向快速低角度 shot 采集以及通过正则化非线性反演进行的相位敏感图像重建相结合。除了使用稳态和脉动流进行校准研究外,初步的体内应用还集中在健康受试者升主动脉的平面内流动上。使用极性交替的双极速度编码梯度来重叠切片重聚焦梯度,该方法可获得具有 1.8mm 平面分辨率、6mm 节厚和在 3T 下 24ms 的测量时间的流动编码图像(TR/TE=3.44/2.76ms;翻转角,10°;每张图像有七个径向射线)。因此,相位对比图和相应的速度图达到 48ms 的时间分辨率。评估的峰值速度、stroke volumes、流量和至少 20 次连续心跳的相应方差通常与文献数据一致。

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