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Technology Reviews

# Oxygen Transport in Brain Tissue

[+] Author and Article Information
Kazuto Masamoto

Education and Research Center for Frontier Science and Engineering, University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, Japanmasamoto@mce.uec.ac.jp

Kazuo Tanishita1

Department of System Design Engineering, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japantanishita@sd.keio.ac.jp

1

Corresponding author.

J Biomech Eng 131(7), 074002 (Jul 27, 2009) (6 pages) doi:10.1115/1.3184694 History: Received June 23, 2009; Revised June 29, 2009; Published July 27, 2009

## Abstract

Oxygen is essential to maintaining normal brain function. A large body of evidence suggests that the partial pressure of oxygen $(pO2)$ in brain tissue is physiologically maintained within a narrow range in accordance with region-specific brain activity. Since the transportation of oxygen in the brain tissue is mainly driven by a diffusion process caused by a concentration gradient of oxygen from blood to cells, the spatial organization of the vascular system, in which the oxygen content is higher than in tissue, is a key factor for maintaining effective transportation. In addition, a local mechanism that controls energy demand and blood flow supply plays a critical role in moment-to-moment adjustment of tissue $pO2$ in response to dynamically varying brain activity. In this review, we discuss the spatiotemporal structures of brain tissue oxygen transport in relation to local brain activity based on recent reports of tissue $pO2$ measurements with polarographic oxygen microsensors in combination with simultaneous recordings of neural activity and local cerebral blood flow in anesthetized animal models. Although a physiological mechanism of oxygen level sensing and control of oxygen transport remains largely unknown, theoretical models of oxygen transport are a powerful tool for better understanding the short-term and long-term effects of local changes in oxygen demand and supply. Finally, emerging new techniques for three-dimensional imaging of the spatiotemporal dynamics of $pO2$ map may enable us to provide a whole picture of how the physiological system controls the balance between demand and supply of oxygen during both normal and pathological brain activity.

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## Figures

Figure 1

Time-relationships of the neural activity induced changes among the cerebral blood flow (light gray), tissue pO2 (dark gray), and estimated oxygen supply (black) (data modified from Masamoto (30)). The CBF and tissue pO2 were simultaneously recorded with laser Doppler flowmetry (LDF) and polarographic microelectrode, respectively, in anesthetized rat somatosensory cortex, while the sensory stimulation (black bar) was induced for 2 s. Note that the estimated supply of oxygen was expected to lag behind the increase in demand due to a lag in the CBF onset (light gray box) and the diffusion time for oxygen (dark gray box).

Figure 2

The dynamic comparisons of relative changes in tissue pO2 induced by tissue oxygen supply (black) and oxygen demand (dark gray) (data modified from Masamoto , (46)). Based on the actual measurement of tissue pO2 with polarographic microelectrodes under the normal CBF condition (light gray) and suppressed CBF condition (dark gray), the tissue oxygen supply induced by normal CBF (gray) was estimated. The 10-s stimulation induced 14 mmHg increase in tissue pO2 by the increase in supply and 5 mm Hg decrease in tissue pO2 by the increase in demand, while the CBF and CMRO2 increase 48% and 10% from the baseline, respectively. Note that the 2.5 times larger increase in oxygen supply was maintained relative to the pO2 change induced by evoked CMRO2.

Figure 3

Microvascular structure in rat somatosensory cortex (X-Y projection image). The image was obtained with in vivo two-photon microscopy. The blood plasma was fluorescently labeled with Qdot 605.

Figure 4

Estimated pO2 distribution based on the geometry of one cerebral arteriole (black circle) and randomly-distributed capillaries (black bar). The images were represented for the spatial distribution of tissue pO2 at different layers (depths of 50 μm, 150 μm, and 500 μm). The gray scale indicates tissue pO2 level.

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