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A Novel Method of Combining Blood Oxygenation and Blood Flow Sensitive Magnetic Resonance Imaging Techniques to Measure the Cerebral Blood Flow and Oxygen Metabolism Responses to an Unknown Neural Stimulus

机译:结合血液氧合和血流敏感磁共振成像技术的新方法,以测量对未知神经刺激的脑血流和氧代谢反应。

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摘要

Simultaneous implementation of magnetic resonance imaging methods for Arterial Spin Labeling (ASL) and Blood Oxygenation Level Dependent (BOLD) imaging makes it possible to quantitatively measure the changes in cerebral blood flow (CBF) and cerebral oxygen metabolism (CMRO2) that occur in response to neural stimuli. To date, however, the range of neural stimuli amenable to quantitative analysis is limited to those that may be presented in a simple block or event related design such that measurements may be repeated and averaged to improve precision. Here we examined the feasibility of using the relationship between cerebral blood flow and the BOLD signal to improve dynamic estimates of blood flow fluctuations as well as to estimate metabolic-hemodynamic coupling under conditions where a stimulus pattern is unknown. We found that by combining the information contained in simultaneously acquired BOLD and ASL signals through a method we term BOLD Constrained Perfusion (BCP) estimation, we could significantly improve the precision of our estimates of the hemodynamic response to a visual stimulus and, under the conditions of a calibrated BOLD experiment, accurately determine the ratio of the oxygen metabolic response to the hemodynamic response. Importantly we were able to accomplish this without utilizing a priori knowledge of the temporal nature of the neural stimulus, suggesting that BOLD Constrained Perfusion estimation may make it feasible to quantitatively study the cerebral metabolic and hemodynamic responses to more natural stimuli that cannot be easily repeated or averaged.
机译:同时实现磁共振成像方法以实现动脉自旋标记(ASL)和血液氧合水平依赖性(BOLD)成像,从而可以定量测量响应于此而发生的脑血流量(CBF)和脑氧代谢(CMRO2)的变化神经刺激。然而,迄今为止,适于定量分析的神经刺激的范围限于可以在简单的块或事件相关设计中呈现的神经刺激的范围,从而可以重复测量并取平均值以提高精度。在这里,我们研究了使用脑血流和BOLD信号之间的关系来改善血流波动的动态估计以及在刺激模式未知的情况下估计代谢-血液动力学耦合的可行性。我们发现,通过称为BOLD约束灌注(BCP)估计的方法,通过将同时采集的BOLD和ASL信号中包含的信息进行组合,我们可以显着提高我们对视觉刺激的血液动力学反应的估计精度,并且在这种情况下在经过校准的BOLD实验中,可以准确确定氧气代谢反应与血液动力学反应的比率。重要的是,我们能够在不利用神经刺激的时间性质的先验知识的情况下完成此操作,这表明BOLD约束灌注估计可能使定量研究对不易重复或无法重复的自然刺激的脑代谢和血液动力学反应变得可行。平均。

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