Alveolar and dead space volume measured by oscillations of inspired oxygen in awake adults

Cerebrovascular reactivity (CVR) MRI with CO2 challenge: A technical review

Cerebrovascular reactivity (CVR) is an indicator of cerebrovascular reserve and provides important information about vascular health in a range of brain conditions and diseases. Unlike steady-state vascular parameters, such as cerebral blood flow (CBF) and cerebral blood volume (CBV), CVR measures the ability of cerebral vessels to dilate or constrict in response to challenges or maneuvers. Therefore, CVR mapping requires a physiological challenge while monitoring the corresponding hemodynamic changes in the brain. The present review primarily focuses on methods that use CO2 inhalation as a physiological challenge while monitoring changes in hemodynamic MRI signals. CO2 inhalation has been increasingly used in CVR mapping in recent literature due to its potency in causing vasodilation, rapid onset and cessation of the effect, as well as advances in MRI-compatible gas delivery apparatus. In this review, we first discuss the physiological basis of CVR mapping using CO2 inhalation. We then review the methodological aspects of CVR mapping, including gas delivery apparatus, the timing paradigm of the breathing challenge, the MRI imaging sequence, and data analysis. In addition, we review alternative approaches for CVR mapping that do not require CO2 inhalation.

The Inspired Sinewave Technique: A Comparison Study With Body Plethysmography in Healthy Volunteers

The inspired sinewave technique is a noninvasive method to measure airway dead space, functional residual capacity, pulmonary blood flow, and lung inhomogeneity simultaneously. The purpose of this paper was to assess the repeatability and accuracy of the current device prototype in measuring functional residual capacity, and also participant comfort when using such a device. To assess within-session repeatability, six sinewave measurements were taken over two-hour period in 17 healthy volunteers. To assess day-to-day repeatability, measurements were taken over 16 days in 3 volunteers. To assess accuracy, sinewave measurements were compared to body plethysmography in 44 healthy volunteers. Finally, 18 volunteers who experienced the inspired sinewave device, body plethysmography and spirometry were asked to rate the comfort of each technique on a scale of 1–10. The repeatability coefficients for dead space, functional residual capacity, and blood flow were 48.7 ml, 0.48L, and 2.4L/min respectively. Bland-Altman analyses showed a mean BIAS(SD) of −0.68(0.42)L for functional residual capacity when compared with body plethysmography. 14 out of 18 volunteers rated the inspired sinewave device as their preferred technique. The repeatability and accuracy of functional residual capacity measurements were found to be as good as other techniques in the literature. The high level of comfort and the non-requirement of patient effort meant that, if further refined, the inspired sinewave technique could be an attractive solution for difficult patient groups such as very young children, elderly, and ventilated patients.

A modification of the Bohr method to determine airways deadspace for non-uniform inspired gas tensions

BACKGROUND

The Bohr method is a technique to determine airways deadspace using a tracer gas such as carbon dioxide or nitrogen. It is based on the assumption that the inspired concentration of the tracer gas is constant throughout inspiration. However, in some lung function measurement techniques where inspired concentration of the tracer gas may be required to vary, or where rapid injection of the tracer gas is made in real time, uniform inspired concentration is difficult or impossible to achieve, which leads to inaccurate estimation of deadspace using the Bohr equation. One such lung function measurement technique is the inspired sinewave technique.

OBJECTIVE

In this paper, we proposed a modification of the Bohr method, relaxing the requirement of absolute uniformity of tracer concentration in the inspired breath.

METHOD

The new method used integration of flow and concentration. A computer algorithm sought an appropriate value of deadspace to satisfy the mass balance equation for each breath. A modern gas mixing apparatus with rapid mass flow controllers was used to verify the procedure.

RESULT

Experiments on a tidally ventilated bench lung showed that the new method estimated dead space within 10% of the actual values whereas the traditional Bohr deadspace gave more than 50% error.

CONCLUSION

The new method improved the accuracy of deadspace estimation when the inspired concentration is not uniform. This improvement would lead to more accurate diagnosis and more accurate estimations of other lung parameters such as functional residual capacity and pulmonary blood flow.

Modelling mixing within the dead space of the lung improves predictions of functional residual capacity

Routine estimation of functional residual capacity (FRC) in ventilated patients has been a long held goal, with many methods previously proposed, but none have been used in routine clinical practice. This paper proposes three models for determining FRC using the nitrous oxide concentration from the entire expired breath in order to improve the precision of the estimate. Of the three models proposed, a dead space with two mixing compartments provided the best results, reducing the mean limits of agreement with the FRC measured by whole body plethysmography by up to 41%. This moves away from traditional lung models, which do not account for mixing within the dead space. Compared to literature values for FRC, the results are similar to those obtained using helium dilution and better than the LUFU device (Dräger Medical, Lubeck, Germany), with significantly better limits of agreement compared to plethysmography.

Systematic errors and susceptibility to noise of four methods for calculating anatomical dead space from the CO 2 expirogram

BACKGROUND

Anatomical dead space is usually measured using the Fowler equal area method. Alternative methods include the Hatch, Cumming, and Bowes methods, in which first, second, and third order polynomials, respectively, fitted to an expired CO2 volume vs expired volume curve, intercept the x-axis at the anatomical dead space. This study assessed systematic errors and susceptibility to noise of the Fowler, Hatch, Cumming, and Bowes dead spaces calculated over 40-80% of the CO2 expirogram.

METHODS

Simulated CO2 expirograms with 220 ml anatomical dead space and varying alveolar plateau slopes were generated digitally and zero-mean Gaussian noise added. CO2 expirograms were recorded in 10 anaesthetized human subjects. Anatomical dead space was calculated by the Fowler, Hatch, Cumming, and Bowes methods.

RESULTS

The Fowler, Hatch, Cumming, and Bowes methods displayed systematic biases of -1.8%, 13.2%, 2.4%, and -1.3%, respectively, at a normalized simulated alveolar plateau slope of 1.6 litre(-1). At a noise level of 0.0066 vol/vol, the standard deviations of recovered simulated dead spaces were 70.6, 1.8, 2.4, and 3.7 ml, respectively. The Hatch, Cumming, and Bowes methods applied to human expirograms differed significantly from that of Fowler by 13, -4, and -11 ml, respectively. In the human study, the Hatch and Cumming methods yielded the lowest intra-individual dead space variability.

CONCLUSIONS

The Fowler method shows greatest susceptibility to measurement noise and the Hatch method exhibits the largest systematic error. The Cumming method, which exhibits both low bias and low noise susceptibility, is preferred for estimating anatomical dead space from CO2 expirograms.

Modelling inert gas exchange in tissue and mixed-venous blood return to the lungs

Inert gas exchange in tissue has been almost exclusively modelled by using an ordinary differential equation. The mathematical model that is used to derive this ordinary differential equation assumes that the partial pressure of an inert gas (which is proportional to the content of that gas) is a function only of time. This mathematical model does not allow for spatial variations in inert gas partial pressure. This model is also dependent only on the ratio of blood flow to tissue volume, and so does not take account of the shape of the body compartment or of the density of the capillaries that supply blood to this tissue. The partial pressure of a given inert gas in mixed-venous blood flowing back to the lungs is calculated from this ordinary differential equation. In this study, we write down the partial differential equations that allow for spatial as well as temporal variations in inert gas partial pressure in tissue. We then solve these partial differential equations and compare them to the solution of the ordinary differential equations described above. It is found that the solution of the ordinary differential equation is very different from the solution of the partial differential equation, and so the ordinary differential equation should not be used if an accurate calculation of inert gas transport to tissue is required. Further, the solution of the PDE is dependent on the shape of the body compartment and on the density of the capillaries that supply blood to this tissue. As a result, techniques that are based on the ordinary differential equation to calculate the mixed-venous blood partial pressure may be in error.

Estimation of pulmonary blood flow from sinusoidal gas exchange during anaesthesia: a theoretical study

We simulated the use of simultaneous sinusoidal changes of inspired O2 and N2O (Williams et al., J Appl Physiol, 1994; 76: 2130-9) at fractional concentrations up to 0.3 and 0.7, respectively, to estimate FRC and pulmonary blood flow (PBF) during anaesthesia, using O2 as an insoluble indicator. Hahn's approximate equations, which neglect the effect of pulmonary uptake and excretion on expiratory flow, estimate dead space and alveolar volume (VA) with systematic errors less than 10%, but yield systematic errors in PBF which are approximately proportional to FIN2O in magnitude. A correction factor (1 - P)-1 for Hahn's equations for PBF (where P is the mean partial pressure of the soluble indicator) reduces the dependence of PBF estimates of FIN2O, and the solution of equations describing the simultaneous mass balance of both indicators yields accurate results for a wide range of mean FIN2O. However, PBF estimates are sensitive to measurement errors and a third gas must be present to ensure that the indicator gases behave independently.