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氧提取分数(OEF)和绝对脑代谢率(CMRO2)的测量:基于磁共振成像(MRI)的方法,采用交替和联合的高碳酸血症与高氧血症。

Measurement of OEF and absolute CMRO2: MRI-based methods using interleaved and combined hypercapnia and hyperoxia.

作者信息

Wise Richard G, Harris Ashley D, Stone Alan J, Murphy Kevin

机构信息

Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Park Place, Cardiff CF10 3AT, UK.

出版信息

Neuroimage. 2013 Dec;83:135-47. doi: 10.1016/j.neuroimage.2013.06.008. Epub 2013 Jun 13.

DOI:10.1016/j.neuroimage.2013.06.008
PMID:23769703
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4151288/
Abstract

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is most commonly used in a semi-quantitative manner to infer changes in brain activity. Despite the basis of the image contrast lying in the cerebral venous blood oxygenation level, quantification of absolute cerebral metabolic rate of oxygen consumption (CMRO2) has only recently been demonstrated. Here we examine two approaches to the calibration of fMRI signal to measure absolute CMRO2 using hypercapnic and hyperoxic respiratory challenges. The first approach is to apply hypercapnia and hyperoxia separately but interleaved in time and the second is a combined approach in which we apply hyperoxic challenges simultaneously with different levels of hypercapnia. Eleven healthy volunteers were studied at 3T using a dual gradient-echo spiral readout pulsed arterial spin labelling (ASL) imaging sequence. Respiratory challenges were conducted using an automated system of dynamic end-tidal forcing. A generalised BOLD signal model was applied, within a Bayesian estimation framework, that aims to explain the effects of modulation of CBF and arterial oxygen content to estimate venous deoxyhaemoglobin concentration ([dHb]0). Using CBF measurements combined with the estimated oxygen extraction fraction (OEF), absolute CMRO2 was calculated. The interleaved approach to hypercapnia and hyperoxia, as well as yielding estimates of CMRO2 and OEF demonstrated a significant increase in regional CBF, venous oxygen saturation (SvO2) (a decrease in OEF) and absolute CMRO2 in visual cortex in response to a continuous (20 min) visual task, demonstrating the potential for the method in measuring long term changes in CMRO2. The combined approach to oxygen and carbon dioxide modulation, as well as taking less time to acquire data, yielded whole brain grey matter estimates of CMRO2 and OEF of 184±45 μmol/100 g/min and 0.42±0.12 respectively, along with additional estimates of the vascular parameters α=0.33±0.06, the exponent relating relative increases in CBF to CBV, and β=1.35±0.13, the exponent relating deoxyhaemoglobin concentration to the relaxation rate R2*. Maps of cerebrovascular and cerebral metabolic parameters were also calculated. We show that combined modulation of oxygen and carbon dioxide can offer an experimentally more efficient approach to estimating OEF and absolute CMRO2 along with the additional vascular parameters that form an important part of the commonly used calibrated fMRI signal model.

摘要

血氧水平依赖(BOLD)功能磁共振成像(fMRI)最常用于以半定量方式推断大脑活动的变化。尽管图像对比度的基础在于脑静脉血氧水平,但直到最近才证明可以对绝对脑氧代谢率(CMRO2)进行量化。在这里,我们研究了两种校准fMRI信号以测量绝对CMRO2的方法,即使用高碳酸血症和高氧呼吸挑战。第一种方法是分别应用高碳酸血症和高氧血症,但在时间上交错进行,第二种方法是联合方法,即我们同时应用不同水平的高碳酸血症与高氧挑战。使用双梯度回波螺旋读出脉冲动脉自旋标记(ASL)成像序列在3T对11名健康志愿者进行了研究。使用动态呼气末强制自动系统进行呼吸挑战。在贝叶斯估计框架内应用了广义BOLD信号模型,该模型旨在解释脑血流量(CBF)和动脉血氧含量调制的影响,以估计静脉脱氧血红蛋白浓度([dHb]0)。结合CBF测量和估计的氧摄取分数(OEF),计算绝对CMRO2。高碳酸血症和高氧血症的交错方法,以及产生的CMRO2和OEF估计值,表明在连续(20分钟)视觉任务期间,视觉皮层中的区域CBF、静脉血氧饱和度(SvO2)(OEF降低)和绝对CMRO2显著增加,证明了该方法在测量CMRO2长期变化方面的潜力。氧和二氧化碳调制的联合方法,以及获取数据所需的时间更少,得出全脑灰质的CMRO2和OEF估计值分别为184±45μmol/100g/min和0.42±0.12,以及血管参数α=0.33±0.06(将CBF的相对增加与脑血容量(CBV)相关的指数)和β=1.35±0.13(将脱氧血红蛋白浓度与弛豫率R2*相关的指数)的额外估计值。还计算了脑血管和脑代谢参数图。我们表明,氧和二氧化碳的联合调制可以提供一种实验上更有效的方法来估计OEF和绝对CMRO2,以及构成常用校准fMRI信号模型重要组成部分的额外血管参数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/f43747fccf85/emss-60178-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/432c137225e2/emss-60178-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/d8d222f8262b/emss-60178-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/ab9f1ae00f89/emss-60178-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/f04b9ce3d5bf/emss-60178-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/f43747fccf85/emss-60178-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/432c137225e2/emss-60178-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/d8d222f8262b/emss-60178-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/ab9f1ae00f89/emss-60178-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/f04b9ce3d5bf/emss-60178-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bef/4151288/f43747fccf85/emss-60178-f0005.jpg

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