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用于四维流动磁共振成像中扩展速度动态范围的互质双速度编码

Coprime dual-velocity encoding for extended velocity dynamic range in 4D flow magnetic resonance imaging.

作者信息

Bartoli Marta Beghella, Boccalini Sara, Chechin David, Boussel Loic, Douek Philippe, Garcia Damien, Sigovan Monica

机构信息

University of Lyon, CREATIS Laboratory, Lyon, France.

University of Lyon, CREATIS Laboratory, Lyon, France; Department of Radiology, Hospices Civils de Lyon, Lyon, France.

出版信息

J Cardiovasc Magn Reson. 2025 Mar 7;27(1):101871. doi: 10.1016/j.jocmr.2025.101871.

Abstract

BACKGROUND

In the field of cardiovascular imaging, four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) provides non-invasive assessment of blood flow. Dual velocity encoding (dual-VENC) strategies have emerged to obtain quantitative information on both low and high blood flow velocities simultaneously. However, these strategies often encounter difficulties in coping with large velocity ranges. This work presents a dual-VENC 4D flow CMR sequence that utilizes the coprime rule to define the VENC ratio.

METHODS

A dual-VENC 4D flow CMR sequence and reconstruction algorithm were developed and validated in vitro at two different field strengths, using a flow phantom generating realistic complex flow patterns. A digital twin of the phantom allowed comparison of the MRI measurements with computational fluid dynamics (CFD) simulations. Three patients with different cardiac pathologies were scanned in order to evaluate the in vivo feasibility of the proposed method.

RESULTS

The results of the in vitro acquisitions demonstrated significant improvement in velocity-to-noise ratio (VNR) with respect to single-VENC acquisitions (110±3%) and conventional dual-VENC de-aliasing approach (75±3%). Furthermore, the effectiveness of aliasing correction was demonstrated even when both sets of images from the dual-VENC acquisition presented velocity aliasing artifacts. We observed a high degree of agreement between the measured and simulated velocity fields.

CONCLUSION

The strength of this approach lies in the fact that, unlike the conventional de-aliasing method, no data is discarded. The final image is obtained by a weighted average of the VENC and VENC datasets. Consequently, setting the value of the VENC to prevent aliasing is no longer necessary, and higher VNR gains are possible.

摘要

背景

在心血管成像领域,四维(4D)血流心血管磁共振(CMR)可对血流进行无创评估。双速度编码(dual-VENC)策略已出现,用于同时获取关于低血流速度和高血流速度的定量信息。然而,这些策略在应对较大速度范围时常常遇到困难。本研究提出了一种利用互质规则定义VENC比率的双VENC 4D血流CMR序列。

方法

开发了一种双VENC 4D血流CMR序列和重建算法,并在两种不同场强下进行体外验证,使用产生逼真复杂血流模式的流动模型。该模型的数字孪生体允许将MRI测量结果与计算流体动力学(CFD)模拟进行比较。扫描了三名患有不同心脏疾病的患者,以评估所提出方法的体内可行性。

结果

体外采集结果表明,相对于单VENC采集(110±3%)和传统双VENC去混叠方法(75±3%),速度噪声比(VNR)有显著提高。此外,即使双VENC采集中的两组图像都出现速度混叠伪影,也证明了混叠校正的有效性。我们观察到测量的和模拟的速度场之间有高度一致性。

结论

该方法的优势在于,与传统去混叠方法不同,不会丢弃任何数据。最终图像是通过VENC和VENC数据集的加权平均值获得的。因此,不再需要设置VENC值来防止混叠,并且可以获得更高的VNR增益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6eaa/12032882/8e75b9f450ed/ga1.jpg

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