A mathematical model of oxygen transport in intact muscle with imposed surface oscillations.

A one-dimensional (1D) reaction-diffusion equation is presented to model oxygen delivery by the microcirculation and oxygen diffusion and consumption in intact muscle. This model is motivated by in vivo experiments in which oscillatory boundary conditions are used to study the mechanisms of local blood flow regulation in response to changes in the tissue oxygen environment. An exact periodic solution is presented for the 1D 'in vivo' model and shown to agree with experimental data for the case where the blood flow regulation system is not activated. Approximate low- and high-frequency solutions are presented, and the latter is shown to agree with the pure diffusion solution in the absence of sources or sinks. For the low frequencies considered experimentally, the 1D in vivo model shows that as depth increases: (i) the mean of tissue O(2) oscillations changes exponentially, (ii) the amplitude of oscillations decreases very rapidly, and (iii) the phase of oscillations remains nearly the same as that of the imposed surface oscillations. The 1D in vivo model also shows that the dependence on depth of the mean, amplitude, and phase of tissue O(2) oscillations is nearly the same for all stimulation periods >30s, implying that experimentally varying the forcing period in this range will not change the spatial distribution of the O(2) stimulation.

[1]  George Keith Batchelor,et al.  An Introduction to Fluid Dynamics. , 1969 .

[2]  L. Rodrigues,et al.  Evaluation of the in vivo microcirculatory function by compartmental modelling of tcpO2 and LDF curves , 2006 .

[3]  J F Gross,et al.  Analysis of oxygen transport to tumor tissue by microvascular networks. , 1993, International journal of radiation oncology, biology, physics.

[4]  Daniel A Beard,et al.  Myocardial oxygenation in isolated hearts predicted by an anatomically realistic microvascular transport model. , 2003, American journal of physiology. Heart and circulatory physiology.

[5]  Mark A. Pinsky Partial differential equations and boundary-value problems with applications , 1991 .

[6]  C G Ellis,et al.  Application of image analysis for evaluation of red blood cell dynamics in capillaries. , 1992, Microvascular research.

[7]  Christopher G Ellis,et al.  Flow Visualization Tools for Image Analysis of Capillary Networks , 2004, Microcirculation.

[8]  Christopher G Ellis,et al.  Effect of sepsis on skeletal muscle oxygen consumption and tissue oxygenation: interpreting capillary oxygen transport data using a mathematical model. , 2004, American journal of physiology. Heart and circulatory physiology.

[9]  Christopher G Ellis,et al.  Automated Method for Tracking Individual Red Blood Cells Within Capillaries to Compute Velocity and Oxygen Saturation , 2005, Microcirculation.

[10]  C. Ellis,et al.  Determination of red blood cell oxygenation in vivo by dual video densitometric image analysis. , 1990, The American journal of physiology.

[11]  Christopher G Ellis,et al.  A New Video Image Analysis System to Study Red Blood Cell Dynamics and Oxygenation in Capillary Networks , 2005, Microcirculation.

[12]  Paul W. Berg,et al.  Elementary Partial Differential Equations , 1966 .

[13]  M. L. Ellsworth,et al.  Red blood cell-derived ATP as a regulator of skeletal muscle perfusion. , 2004, Medicine and science in sports and exercise.

[14]  N. Britton Reaction-diffusion equations and their applications to biology. , 1989 .