Countercurrent compartmental models describe hind limb skeletal muscle helium kinetics at resting and low blood flows in sheep

Probabilistic pharmacokinetic models of decompression sickness in humans: Part 2, coupled perfusion-diffusion models

Decompression sickness (DCS) can be experienced following a reduction in ambient pressure; such as that associated with diving or ascent to high altitudes. DCS is believed to result when supersaturated inert gas dissolved in biological tissues exits solution and forms bubbles. Models to predict the probability of DCS are typically based on nitrogen and/or helium gas uptake and washout in several theoretical tissues, each represented by a single perfusion-limited compartment. It has been previously shown that coupled perfusion-diffusion compartments are better descriptors than solely perfusion-based models of nitrogen and helium uptake and elimination kinetics observed in the brain and skeletal muscle of sheep. In this work, we examine the application of these coupled pharmacokinetic structures with at least one diffusion compartment to the prediction of the incidence of decompression sickness in humans. We compare these models to LEM-NMRI98, a well-described U.S. Navy gas content model, consisting of three uncoupled perfusion-limited compartments incorporating oxygen and linear-exponential kinetics. Pharmacokinetic gas content models with a diffusion component describe the probability of DCS in human bounce dives made with air, single non-air bounce dives, and oxygen decompression dives better than LEM-NMRI98. However, for the full data set, LEM-NMRI98 remains the best descriptor of the data.

Probabilistic pharmacokinetic models of decompression sickness in humans, part 1: Coupled perfusion-limited compartments

Decompression sickness (DCS) is a disease caused by gas bubbles forming in body tissues following a reduction in ambient pressure, such as occurs in scuba diving. Probabilistic models for quantifying the risk of DCS are typically composed of a collection of independent, perfusion-limited theoretical tissue compartments which describe gas content or bubble volume within these compartments. It has been previously shown that 'pharmacokinetic' gas content models, with compartments coupled in series, show promise as predictors of the incidence of DCS. The mechanism of coupling can be through perfusion or diffusion. This work examines the application of five novel pharmacokinetic structures with compartments coupled by perfusion to the prediction of the probability and time of onset of DCS in humans. We optimize these models against a training set of human dive trial data consisting of 4335 exposures with 223 DCS cases. Further, we examine the extrapolation quality of the models on an additional set of human dive trial data consisting of 3140 exposures with 147 DCS cases. We find that pharmacokinetic models describe the incidence of DCS for single air bounce dives better than a single-compartment, perfusion-limited model. We further find the U.S. Navy LEM-NMRI98 is a better predictor of DCS risk for the entire training set than any of our pharmacokinetic models. However, one of the pharmacokinetic models we consider, the CS2T3 model, is a better predictor of DCS risk for single air bounce dives and oxygen decompression dives. Additionally, we find that LEM-NMRI98 outperforms CS2T3 on the extrapolation data.

Altering blood flow does not reveal differences between nitrogen and helium kinetics in brain or in skeletal miracle in sheep

In underwater diving, decompression schedules are based on compartmental models of nitrogen and helium tissue kinetics. However, these models are not based on direct measurements of nitrogen and helium kinetics. In isoflurane-anesthetized sheep, nitrogen and helium kinetics in the hind limb (n = 5) and brain (n = 5) were determined during helium-oxygen breathing and after return to nitrogen-oxygen breathing. Nitrogen and helium concentrations in arterial, femoral vein, and sagittal sinus blood samples were determined using headspace gas chromatography, and venous blood flows were monitored continuously using ultrasonic Doppler. The experiment was repeated at different states of hind limb blood flow and cerebral blood flow. Using arterial blood gas concentrations and blood flows as input, parameters and model selection criteria of various compartmental models of hind limb and brain were estimated by fitting to the observed venous gas concentrations. In both the hind limb and brain, nitrogen and helium kinetics were best fit by models with multiexponential kinetics. In the brain, there were no differences in nitrogen and helium kinetics. Hind limb models fit separately to the two gases indicated that nitrogen kinetics were slightly faster than helium, but models with the same kinetics for both gases fit the data well. In the hind limb and brain, the blood:tissue exchange of nitrogen is similar to that of helium. On the basis of these results, it is inappropriate to assign substantially different time constants for nitrogen and helium in all compartments in decompression algorithms.

Hyperbaric conditions

Exposure to elevated ambient pressure (hyperbaric conditions) occurs most commonly in underwater diving, during which respired gas density and partial pressures, work of breathing, and physiological dead space are all increased. There is a tendency toward hypercapnia during diving, with several potential causes. Most importantly, there may be reduced responsiveness of the respiratory controller to rising arterial CO₂, leading to hypoventilation and CO₂ retention. Contributory factors may include elevated arterial PO₂, inert gas narcosis and an innate (but variable) tendency of the respiratory controller to sacrifice tight control of arterial CO₂ when work of breathing increases. Oxygen is usually breathed at elevated partial pressure under hyperbaric conditions. Oxygen breathing at modest hyperbaric pressure is used therapeutically in hyperbaric chambers to increase arterial carriage of oxygen and diffusion into tissues. However, to avoid cerebral and pulmonary oxygen toxicity during underwater diving, both the magnitude and duration of oxygen exposure must be managed. Therefore, most underwater diving is conducted breathing mixtures of oxygen and inert gases such as nitrogen or helium, often simply air. At hyperbaric pressure, tissues equilibrate over time with high inspired inert gas partial pressure. Subsequent decompression may reduce ambient pressure below the sum of tissue gas partial pressures (supersaturation) which can result in tissue gas bubble formation and potential injury (decompression sickness). Risk of decompression sickness is minimized by scheduling time at depth and decompression rate to limit tissue supersaturation or size and profusion of bubbles in accord with models of tissue gas kinetics and bubble formation and growth.

A new class of biophysical models for predicting the probability of decompression sickness in scuba diving

Interconnected compartmental models have been used for decades in physiology and medicine to account for the observed multi-exponential washout kinetics of a variety of solutes (including inert gases) both from single tissues and from the body as a whole. They are used here as the basis for a new class of biophysical probabilistic decompression models. These models are characterized by a relatively well-perfused, risk-bearing, central compartment and one or two non-risk-bearing, relatively poorly perfused, peripheral compartment(s). The peripheral compartments affect risk indirectly by diffusive exchange of dissolved inert gas with the central compartment. On the basis of the accuracy of their respective predictions beyond the calibration regime, the three-compartment interconnected models were found to be significantly better than the two-compartment interconnected models. The former, on the basis of a number of criteria, was also better than a two-compartment parallel model used for comparative purposes. In these latter comparisons, the models all had the same number of fitted parameters (four), were based on linear kinetics, had the same risk function, and were calibrated against the same dataset. The interconnected models predict that inert gas washout during decompression is relatively fast, initially, but slows rapidly with time compared with the more uniform washout rate predicted by an independent parallel compartment model. If empirically verified, this may have important implications for diving practice.