Park Chang Sub, Payne Stephen J
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, United Kingdom.
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, United Kingdom.
Med Eng Phys. 2016 Jan;38(1):41-7. doi: 10.1016/j.medengphy.2015.09.004. Epub 2015 Oct 21.
The cerebral microvasculature plays a vital role in adequately supplying blood to the brain. Determining the health of the cerebral microvasculature is important during pathological conditions, such as stroke and dementia. Recent studies have shown the complex relationship between cerebral metabolic rate and transit time distribution, the transit times of all the possible pathways available dependent on network topology. In this paper, we extend a recently developed technique to solve for residue function, the amount of tracer left in the vasculature at any time, and transit time distribution in an existing model of the cerebral microvasculature to calculate cerebral metabolism. We present the mathematical theory needed to solve for oxygen concentration followed by results of the simulations. It is found that oxygen extraction fraction, the fraction of oxygen removed from the blood in the capillary network by the tissue, and cerebral metabolic rate are dependent on both mean and heterogeneity of the transit time distribution. For changes in cerebral blood flow, a positive correlation can be observed between mean transit time and oxygen extraction fraction, and a negative correlation between mean transit time and metabolic rate of oxygen. A negative correlation can also be observed between transit time heterogeneity and the metabolic rate of oxygen for a constant cerebral blood flow. A sensitivity analysis on the mean and heterogeneity of the transit time distribution was able to quantify their respective contributions to oxygen extraction fraction and metabolic rate of oxygen. Mean transit time has a greater contribution than the heterogeneity for oxygen extraction fraction. This is found to be opposite for metabolic rate of oxygen. These results provide information on the role of the cerebral microvasculature and its effects on flow and metabolism. They thus open up the possibility of obtaining additional valuable clinical information for diagnosing and treating cerebrovascular diseases.
脑微血管系统在为大脑充分供血方面起着至关重要的作用。在诸如中风和痴呆等病理状况下，确定脑微血管系统的健康状况很重要。最近的研究表明了脑代谢率与通过时间分布之间的复杂关系，所有可能路径的通过时间取决于网络拓扑结构。在本文中，我们扩展了一种最近开发的技术，用于求解残留函数（即血管系统中在任何时刻剩余的示踪剂数量）以及现有脑微血管系统模型中的通过时间分布，以计算脑代谢。我们给出了求解氧浓度所需的数学理论，随后是模拟结果。研究发现，氧摄取分数（即组织从毛细血管网络血液中去除的氧的分数）和脑代谢率取决于通过时间分布的均值和异质性。对于脑血流量的变化，平均通过时间与氧摄取分数之间可观察到正相关，平均通过时间与氧代谢率之间可观察到负相关。对于恒定的脑血流量，通过时间异质性与氧代谢率之间也可观察到负相关。对通过时间分布的均值和异质性进行的敏感性分析能够量化它们对氧摄取分数和氧代谢率的各自贡献。平均通过时间对氧摄取分数的贡献大于异质性。而对于氧代谢率，情况则相反。这些结果提供了有关脑微血管系统的作用及其对血流和代谢影响的信息。因此，它们为获取用于诊断和治疗脑血管疾病的额外有价值的临床信息开辟了可能性。
