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自由流动运动抑制全心 MRA 的相似度驱动多维分箱算法(SIMBA)。

Similarity-driven multi-dimensional binning algorithm (SIMBA) for free-running motion-suppressed whole-heart MRA.

机构信息

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.

出版信息

Magn Reson Med. 2021 Jul;86(1):213-229. doi: 10.1002/mrm.28713. Epub 2021 Feb 24.

Abstract

PURPOSE

Whole-heart MRA techniques typically target predetermined motion states, address cardiac and respiratory dynamics independently, and require either complex planning or computationally demanding reconstructions. In contrast, we developed a fast data-driven reconstruction algorithm with minimal physiological assumptions and compatibility with ungated free-running sequences.

THEORY AND METHODS

We propose a similarity-driven multi-dimensional binning algorithm (SIMBA) that clusters continuously acquired k-space data to find a motion-consistent subset for whole-heart MRA reconstruction. Free-running 3D radial data sets from 12 non-contrast-enhanced scans of healthy volunteers and six ferumoxytol-enhanced scans of pediatric cardiac patients were reconstructed with non-motion-suppressed regridding of all the acquired data ("All Data"), with SIMBA, and with a previously published free-running framework (FRF) that uses cardiac and respiratory self-gating and compressed sensing. Images were compared for blood-myocardium sharpness and contrast ratio, visibility of coronary artery ostia, and right coronary artery sharpness.

RESULTS

Both the 20-second SIMBA reconstruction and FRF provided significantly higher blood-myocardium sharpness than All Data in both patients and volunteers (P < .05). The SIMBA reconstruction provided significantly sharper blood-myocardium interfaces than FRF in volunteers (P < .001) and higher blood-myocardium contrast ratio than All Data and FRF, both in volunteers and patients (P < .05). Significantly more ostia could be visualized with both SIMBA (31 of 36) and FRF (34 of 36) than with All Data (4 of 36) (P < .001). Inferior right coronary artery sharpness using SIMBA versus FRF was observed (volunteers: SIMBA 36.1 ± 8.1%, FRF 40.4 ± 8.9%; patients: SIMBA 35.9 ± 7.7%, FRF 40.3 ± 6.1%, P = not significant).

CONCLUSION

The SIMBA technique enabled a fast, data-driven reconstruction of free-running whole-heart MRA with image quality superior to All Data and similar to the more time-consuming FRF reconstruction.

摘要

目的

全心 MRA 技术通常针对预定的运动状态,独立处理心脏和呼吸动力学,并且需要复杂的规划或计算密集型重建。相比之下,我们开发了一种快速的数据驱动重建算法,该算法具有最小的生理假设,并且与无门控自由运行序列兼容。

理论与方法

我们提出了一种相似性驱动的多维分箱算法(SIMBA),该算法对连续采集的 k 空间数据进行聚类,以找到用于全心 MRA 重建的运动一致子集。使用非运动抑制的重新网格化对所有采集数据(“全部数据”)、SIMBA 和先前发表的使用心脏和呼吸自门控和压缩感知的自由运行框架(FRF)对 12 名非对比增强扫描的健康志愿者和 6 名儿科心脏患者的自由运行 3D 径向数据集进行重建。比较了图像的血液-心肌锐利度和对比度比、冠状动脉开口的可见性以及右冠状动脉锐利度。

结果

在患者和志愿者中,20 秒 SIMBA 重建和 FRF 均比全部数据提供了显著更高的血液-心肌锐利度(P <.05)。SIMBA 重建在志愿者中提供了显著更锐利的血液-心肌界面,比 FRF 更锐利(P <.001),并且与全部数据和 FRF 相比,血液-心肌对比度更高,在志愿者和患者中均如此(P <.05)。与全部数据(4/36)相比,SIMBA(31/36)和 FRF(34/36)均可观察到更多的开口(P <.001)。与 FRF 相比,使用 SIMBA 观察到下右冠状动脉锐利度降低(志愿者:SIMBA 36.1 ± 8.1%,FRF 40.4 ± 8.9%;患者:SIMBA 35.9 ± 7.7%,FRF 40.3 ± 6.1%,P = 无显著差异)。

结论

SIMBA 技术能够快速、数据驱动地重建自由运行的全心 MRA,其图像质量优于全部数据,与更耗时的 FRF 重建相似。

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