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基于增强 4D 流 MRI 和自适应网格细化的 CFD 用于主动脉缩窄血流动力学评估。

Enhanced 4D Flow MRI-Based CFD with Adaptive Mesh Refinement for Flow Dynamics Assessment in Coarctation of the Aorta.

机构信息

Department of Mechanical Engineering, University of Wisconsin-Madison, 1111 Highland Ave, Room 2476 WIMR II, Madison, WI, 53705, USA.

Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

出版信息

Ann Biomed Eng. 2022 Aug;50(8):1001-1016. doi: 10.1007/s10439-022-02980-7. Epub 2022 May 27.

Abstract

4D Flow MRI is a diagnostic tool that can visualize and quantify patient-specific hemodynamics and help interventionalists optimize treatment strategies for repairing coarctation of the aorta (COA). Despite recent developments in 4D Flow MRI, shortcomings include phase-offset errors, limited spatiotemporal resolution, aliasing, inaccuracies due to slow aneurysmal flows, and distortion of images due to metallic artifact from vascular stents. To address these limitations, we developed a framework utilizing Computational Fluid Dynamics (CFD) with Adaptive Mesh Refinement (AMR) that enhances 4D Flow MRI visualization/quantification. We applied this framework to five pediatric patients with COA, providing in-vivo and in-silico datasets, pre- and post-intervention. These two data sets were compared and showed that CFD flow rates were within 9.6% of 4D Flow MRI, which is within a clinically acceptable range. CFD simulated slow aneurysmal flow, which MRI failed to capture due to high relative velocity encoding (V). CFD successfully predicted in-stent blood flow, which was not visible in the in-vivo data due to susceptibility artifact. AMR improved spatial resolution by factors of 10 to 10 and temporal resolution four-fold. This computational framework has strong potential to optimize visualization/quantification of aneurysmal and in-stent flows, improve spatiotemporal resolution, and assess hemodynamic efficiency post-COA treatment.

摘要

4D 血流磁共振成像是一种诊断工具,可用于可视化和量化患者特定的血液动力学,并帮助介入治疗师优化主动脉缩窄(COA)修复的治疗策略。尽管 4D 血流磁共振成像有了最近的发展,但仍存在一些缺点,包括相位偏移误差、有限的时空分辨率、混叠、由于动脉瘤流缓慢而导致的不准确以及由于血管支架的金属伪影而导致的图像失真。为了解决这些限制,我们开发了一个利用计算流体动力学(CFD)和自适应网格细化(AMR)的框架,以增强 4D 血流磁共振成像的可视化/量化。我们将该框架应用于五名患有 COA 的儿科患者,提供了体内和体外数据集,包括术前和术后。这两个数据集进行了比较,结果表明 CFD 流量与 4D 血流磁共振成像的差值在 9.6%以内,这在临床可接受的范围内。CFD 模拟了缓慢的动脉瘤样血流,由于相对较高的流速编码(V),MRI 无法捕捉到这种血流。CFD 成功预测了支架内的血流,由于磁化率伪影,体内数据中无法看到这种血流。AMR 将空间分辨率提高了 10 到 100 倍,将时间分辨率提高了四倍。这个计算框架有很大的潜力来优化动脉瘤和支架内血流的可视化/量化,提高时空分辨率,并评估 COA 治疗后的血液动力学效率。

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