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基于冲击射流的动脉自旋标记 MRI 灌注体模。

A perfusion phantom for ASL MRI based on impinging jets.

机构信息

Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

出版信息

Magn Reson Med. 2021 Aug;86(2):1145-1158. doi: 10.1002/mrm.28697. Epub 2021 Mar 27.

Abstract

PURPOSE

We present a novel perfusion phantom for validation of arterial spin labeled (ASL) perfusion MRI methods and protocols.

METHODS

Impinging jets, driven by a peristaltic pump, were used to achieve perfusion-like mixing of magnetically labeled inflowing fluid within a perfusion compartment. The phantom was validated by varying pump rates and obtaining ASL-MRI data at multiple postlabeling delays using a pseudo-continuous ASL sequence with a 3D stack-of-spirals readout. An additional data set was acquired using a pseudo-continuous ASL sequence with a 2D EPI readout. Phantom sensitivity to pseudo-continuous ASL labeling efficiency was also tested.

RESULTS

Fluid dynamics simulations predicted that maximum mixing would occur near the central axis of the perfusion compartment. Experimentally observed signal changes within this region were reproducible and well fit by the standard Buxton general kinetic model. Simulations and experimental data showed no label outflow from the perfusion chamber and calculated perfusion rates, averaged over the entire phantom volume, agreed with the expected volumetric flow rates provided by the flow pump. Phantom sensitivity to pseudo-continuous ASL labeling parameters was also demonstrated.

CONCLUSION

Perfusion-like signal can be simulated using impinging jets to create a well-mixed compartment. Observed perfusion and transit time values were reproducible and within the physiological range for brain perfusion. This phantom design has a broad range of potential applications in both basic and clinical research involving ASL MRI.

摘要

目的

我们提出了一种新型的灌注体模,用于验证动脉自旋标记(ASL)灌注 MRI 方法和方案。

方法

通过蠕动泵驱动的冲击射流,实现了在灌注腔内流动标记的流入流体的灌注样混合。通过改变泵的流速,并使用具有 3D 螺旋堆栈读出的伪连续 ASL 序列在多个标记后延迟获得 ASL-MRI 数据,对该体模进行了验证。使用具有 2D EPI 读出的伪连续 ASL 序列获得了另外一组数据。还测试了体模对伪连续 ASL 标记效率的灵敏度。

结果

流体动力学模拟预测,最大混合将发生在灌注腔的中心轴附近。在该区域内观察到的信号变化具有可重复性,并且与标准 Buxton 一般动力学模型拟合良好。模拟和实验数据表明,没有标签从灌注室流出,并且计算出的灌注率,平均整个体模体积,与流量泵提供的预期体积流量相符。还证明了体模对伪连续 ASL 标记参数的灵敏度。

结论

可以使用冲击射流模拟出类似灌注的信号,从而创建一个混合良好的腔室。观察到的灌注和过渡时间值具有可重复性,并且在脑灌注的生理范围内。这种体模设计在涉及 ASL MRI 的基础和临床研究中具有广泛的潜在应用。

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