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Noise concerns and post-processing procedures in cerebral blood flow (CBF) and cerebral blood volume (CBV) functional magnetic resonance imaging

机译:脑血流量(CBF)和脑血容量(CBV)功能磁共振成像中的噪声问题和后处理程序

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摘要

Functional neuroimaging with blood oxygenation level-dependent (BOLD) contrast has emerged as the most popular method for evaluating qualitative changes in brain function in humans. At typical human field strengths (1.5–3.0 Tesla), BOLD contrast provides a measure of changes in transverse water relaxation rates in and around capillary and venous blood, and as such provides only a surrogate marker of brain function that depends on dynamic changes in hemodynamics (e.g., cerebral blood flow and volume) and metabolism (e.g., oxygen extraction fraction and the cerebral metabolic rate of oxygen consumption). Alternative functional neuroimaging methods that are specifically sensitive to these constituents of the BOLD signal are being developed and applied in a growing number of clinical and neuroscience applications of quantitative cerebral physiology. These methods require additional considerations for interpreting and quantifying their contrast responsibly. Here, an overview of two popular methods, arterial spin labeling and vascular space occupancy, is presented specifically in the context of functional neuroimaging. Appropriate post-processing and experimental acquisition strategies are summarized with the motivation of reducing sensitivity to noise and unintended signal sources and improving quantitative accuracy of cerebral hemodynamics.
机译:具有血液氧合水平依赖性(BOLD)对比的功能性神经影像学已成为评估人类脑功能质变的最流行方法。在典型的人类场强(1.5–3.0特斯拉)下,BOLD对比度可测量毛细血管和静脉血液及其周围的横向水松弛率的变化,因此仅提供了依赖于血流动力学动态变化的大脑功能的替代指标(例如,脑血流量和体积)和新陈代谢(例如,氧提取分数和氧消耗的脑代谢率)。对BOLD信号的这些成分特别敏感的替代功能性神经影像学方法正在开发中,并在越来越多的定量脑生理学的临床和神经科学应用中得到应用。这些方法需要另外考虑,以便负责地解释和量化它们的对比度。在此,在功能性神经影像学的背景下,专门介绍了两种流行的方法,即动脉自旋标记和血管空间占用。总结了适当的后处理和实验采集策略,其动机是降低对噪声和意外信号源的敏感性,并提高脑血流动力学的定量准确性。

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