4.5 Article

Simultaneous blood-tissue exchange of oxygen, carbon dioxide, bicarbonate, and hydrogen ion

期刊

ANNALS OF BIOMEDICAL ENGINEERING
卷 34, 期 7, 页码 1129-1148

出版社

SPRINGER
DOI: 10.1007/s10439-005-9066-4

关键词

axially distributed model; convection-diffusion-permeation-reaction-binding model; blood-tissue exchange; oxygen and carbon dioxide transport; oxygen transport and metabolism; myoglobin-facilitated oxygen transport; oxyhemoglobin and carbamino hemoglobin dissociation curves

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A detailed nonlinear four-region (red blood cell, plasma, interstitial fluid, and parenchymal cell) axially distributed convection-diffusion-permeation-reaction-binding computational model is developed to study the simultaneous transport and exchange of oxygen (O-2) and carbon dioxide (CO2) in the blood tissue exchange system of the heart. Since the pH variation in blood and tissue influences the transport and exchange of O-2 and CO2 (Bohr and Haldane effects), and since most CO2 is transported as HCO3- (bicarbonate) via the CO2 hydration (buffering) reaction, the transport and exchange of HCO3- and H+ are also simulated along with that of O-2 and CO2. Furthermore, the model accounts for the competitive nonlinear binding of O-2 and CO2 with the hemoglobin inside the red blood cells (nonlinear O-2 - CO2 interactions, Bohr and Haldane effects), and myoglobin-facilitated transport of O-2 inside the parenchymal cells. The consumption of O-2 through cytochrome-c oxidase reaction inside the parenchymal cells is based on Michaelis - Menten kinetics. The corresponding production of CO2 is determined by respiratory quotient (RQ), depending on the relative consumption of carbohydrate, protein, and fat. The model gives a physiologically realistic description of O-2 transport and metabolism in the microcirculation of the heart. Furthermore, because model solutions for tracer transients and steady states can be computed highly efficiently, this model may be the preferred vehicle for routine data analysis where repetitive solutions and parameter optimization are required, as is the case in PET imaging for estimating myocardial O-2 consumption.

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