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Srinivasan, R. Srini

Publications and source records attributed to Srinivasan, R. Srini.

Mathematical model of diffusion-limited evolution of multiple gas bubbles in tissue

Models of gas bubble dynamics employed in probabilistic analyses of decompression sickness incidence in man must be theoretically consistent and simple, if they are to yield useful results without requiring excessive computations. They are generally formulated in terms of ordinary differential equations that describe diffusion-limited gas exchange between a gas bubble and the extravascular tissue surrounding it. In our previous model (Ann. Biomed. Eng. 30: 232-246, 2002), we showed that with appropriate representation of sink pressures to account for gas loss or gain due to heterogeneous blood perfusion in the unstirred diffusion region around the bubble, diffusion-limited bubble growth in a tissue of finite volume can be simulated without postulating a boundary layer across which gas flux is discontinuous. However, interactions between two or more bubbles caused by competition for available gas cannot be considered in this model, because the diffusion region has a fixed volume with zero gas flux at its outer boundary. The present work extends the previous model to accommodate interactions among multiple bubbles by allowing the diffusion region volume of each bubble to vary during bubble evolution. For given decompression and tissue volume, bubble growth is sustained only if the bubble number density is below a certain maximum.

Evaluation Studies↗

A Mathematical Model of Diffusion-Limited Gas Bubble Dynamics in Tissue with Varying Diffusion Region Thickness

A three-region mathematical model of gas bubble dynamics has been shown suitable for describing diffusion-limited dynamics of more than one bubble in a given volume of extravascular tissue. The model is based on the dynamics of gas exchange between a bubble and a well-stirred tissue region through an intervening unperfused diffusion region previously assumed to have constant thickness and uniform gas diffusivity. As a result, the gas content of the diffusion region remains constant as the volume of the region increases with bubble growth, causing dissolved gas in the region to violate Henry's law. Earlier work also neglected the relationship between the varying diffusion region volume and the fixed total tissue volume, because only cases in which the diffusion region volume is a small fraction of the overall tissue volume were considered. We herein extend the three-region model to correct these theoretical inconsistencies by allowing both the thickness and gas content of the diffusion region to vary during bubble evolution. A postulated difference in gas diffusivity between an infinitesimally thin layer at the bubble surface and the remainder of the diffusion region leads to variation in diffusion region gas content and thickness during bubble growth and resolution. This variable thickness, differential diffusivity (VTDD) model can yield bubble lifetimes considerably longer than those yielded by earlier three-region models for given model and decompression parameters, and meets a need for theoretically consistent but relatively simple bubble dynamics models for use in studies of decompression sickness (DCS) in human subjects, Keywords: decompression sickness, gas diffusion in tissue, diffusivity

Srinivasan, R. Srini↗

Mathematical modeling of acute and chronic cardiovascular changes during Extended Duration Orbiter (EDO) flights

The purpose of NASA's Extended Duration Orbiter program is a gradual extension of the capabilities of the Space Shuttle Orbiter beyond its current 7-10 day limit on mission duration, as warranted by deepening understanding of the long-term physiological effects of weightlessness. Attention is being given to the cardiovascular problem of orthostatic tolerance loss due to its adverse effects on crew performance and health during reentry and initial readaptation to earth gravity. An account is given of the results of the application of proven mathematical models of circulatory and cardiovascular systems under microgravity conditions.

White, Ronald J.↗

Computer simulation of cardiovascular changes during extended duration space flights

The application of mathematical modeling and computer simulation to the study of spaceflight cardiovascular changes is examined using a multicompartment representation model of the entire human cardiovascular system including its control elements. The model simulates the beat-to-beat dynamic responses of the cardiovascular system to orthostatic stresses. Simulation results pertaining to long-term space flight, the combined effect of +G(z) and blood volume loss, and the effect of anti-G suit inflation are discussed, including past results on the original version of the model which has been used in a number of analysis applications at NASA. New results pertain to analysis of cardiovascular changes in extended duration space flights and demonstrate the use of this model in evaluation of physiological factors that contribute to orthostatic intolerance following an exposure to weightlessness, in particular, blood volume loss and changes in the sensitivity of baroreceptors.

Srinivasan, R. Srini↗

Applicability of mathematical modeling to problems of environmental physiology

The paper traces the evolution of mathematical modeling and systems analysis from terrestrial research to research related to space biomedicine and back again to terrestrial research. Topics covered include: power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and, computer-aided diagnosis programs used in conjunction with a special on-line biomedical computer library.

White, Ronald J.↗

Terrestrial implications of mathematical modeling developed for space biomedical research

This paper summarizes several related research projects supported by NASA which seek to apply computer models to space medicine and physiology. These efforts span a wide range of activities, including mathematical models used for computer simulations of physiological control systems; power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and computer-aided diagnosis programs.

Lujan, Barbara F.↗