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高场 MRI 定量分析人心血管和呼吸引起的脑变形。

Cardiac and respiration-induced brain deformations in humans quantified with high-field MRI.

机构信息

Radiology, University Medical Center Utrecht, the Netherlands.

Neurology, University Medical Center Utrecht, the Netherlands.

出版信息

Neuroimage. 2020 Apr 15;210:116581. doi: 10.1016/j.neuroimage.2020.116581. Epub 2020 Jan 23.

DOI:10.1016/j.neuroimage.2020.116581
PMID:31982580
Abstract

Microvascular blood volume pulsations due to the cardiac and respiratory cycles induce brain tissue deformation and, as such, are considered to drive the brain's waste clearance system. We have developed a high-field magnetic resonance imaging (MRI) technique to quantify both cardiac and respiration-induced tissue deformations, which could not be assessed noninvasively before. The technique acquires motion encoded snapshot images in which various forms of motion and confounders are entangled. First, we optimized the motion sensitivity for application in the human brain. Next, we isolated the heartbeat and respiration-related deformations, by introducing a linear model that fits the snapshot series to the recorded physiological information. As a result, we obtained maps of the physiological tissue deformation with 3mm isotropic spatial resolution. Heartbeat and respiration-induced volumetric strain were significantly different from zero in the basal ganglia (median (25-75% interquartile range): 0.85·10 (0.39·10-1.05·10), p ​= ​0.0008 and -0.28·10 (-0.41·10-0.06·10), p ​= ​0.047, respectively. Smaller volumetric strains were observed in the white matter of the centrum semi ovale (0.28·10 (0-0.59·10) and -0.06·10 (-0.17·10-0.20·10)), which was only significant for the heartbeat (p ​= ​0.02 and p ​= ​0.7, respectively). Furthermore, heartbeat-induced volumetric strain was about three times larger than respiration-induced volumetric strain. This technique opens a window on the driving forces of the human brain clearance system.

摘要

由于心脏和呼吸周期引起的微血管血液体积脉动导致脑组织变形,因此被认为是驱动大脑废物清除系统的因素。我们开发了一种高场磁共振成像(MRI)技术来量化心脏和呼吸引起的组织变形,在此之前,这些变形无法进行非侵入性评估。该技术获取运动编码快照图像,其中各种形式的运动和混杂因素纠缠在一起。首先,我们优化了运动灵敏度,以应用于人类大脑。接下来,我们通过引入一个线性模型,将快照系列拟合到记录的生理信息,从而分离与心跳和呼吸相关的变形。结果,我们获得了具有 3mm 各向同性空间分辨率的生理组织变形图。在基底节(中位数(25-75%四分位距):0.85·10(0.39·10-1.05·10),p=0.0008 和-0.28·10(-0.41·10-0.06·10),p=0.047)中,心跳和呼吸引起的体积应变明显不为零。在半卵圆中心的白质中观察到较小的体积应变(0.28·10(0-0.59·10)和-0.06·10(-0.17·10-0.20·10)),这仅对心跳有显著影响(p=0.02 和 p=0.7)。此外,心跳引起的体积应变大约是呼吸引起的体积应变的三倍。该技术为人类大脑清除系统的驱动力开辟了一扇窗口。

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