Generalized estimation of the ventilatory distribution from the multiple-breath nitrogen washout

Simulation-based optimisation to quantify heterogeneity of specific ventilation and perfusion in the lung by the Inspired Sinewave Test

The degree of specific ventilatory heterogeneity (spatial unevenness of ventilation) of the lung is a useful marker of early structural lung changes which has the potential to detect early-onset disease. The Inspired Sinewave Test (IST) is an established noninvasive 'gas-distribution' type of respiratory test capable of measuring the cardiopulmonary parameters. We developed a simulation-based optimisation for the IST, with a simulation of a realistic heterogeneous lung, namely a lognormal distribution of spatial ventilation and perfusion. We tested this method in datasets from 13 anaesthetised pigs (pre and post-lung injury) and 104 human subjects (32 healthy and 72 COPD subjects). The 72 COPD subjects were classified into four COPD phenotypes based on 'GOLD' classification. This method allowed IST to identify and quantify heterogeneity of both ventilation and perfusion, permitting diagnostic distinction between health and disease states. In healthy volunteers, we show a linear relationship between the ventilatory heterogeneity versus age ([Formula: see text]). In a mechanically ventilated pig, IST ventilatory heterogeneity in noninjured and injured lungs was significantly different (p < 0.0001). Additionally, measured indices could accurately identify patients with COPD (area under the receiver operating characteristic curve is 0.76, p < 0.0001). The IST also could distinguish different phenotypes of COPD with 73% agreement with spirometry.

A simplified 4-parameter model of volumetric capnograms improves calculations of airway dead space and slope of Phase III

To evaluate a compact and easily interpretable 4-parameter model describing the shape of the volumetric capnogram, and the resulting estimates of anatomical dead space (VD_AW) and Phase III (alveolar plateau) slope (S_III). Data from of 8 mildly-endotoxemic pre-acute respiratory distress syndrome sheep were fitted to the proposed 4-parameter model (4p) and a previously established 7-parameter model (7p). Root mean square error (RMSE) and Akaike information criterion (AIC), as well as VD_AW and S_III derived from each model were compared. Confidence intervals for model's parameters, VD_AW and S_III were estimated with a jackknife approach. RMSE values were similar (4p: 1.13 ± 0.01 mmHg vs 7p: 1.14 ± 0.01 mmHg) in the 791 breath cycles tested. However, the 7p overfitted the curve and had worse AIC in more than 50% of the cycles (p < 0.001). The large number of degrees of freedom also resulted in larger between-animal range of confidence intervals for 7p (VD_AW: from 6.1 10^-12 to 34 ml, S_III: from 9.53 10^-7 to 1.80 mmHg/ml) as compared to 4p (VD_AW: from 0.019 to 0.15 ml, S_III: from 3.9 10^-4 to 0.011 mmHg/ml). Mean differences between VD_AW (2.1 ± 0.04 ml) and S_III (0.047 ± 0.004 mmHg/ml) from 7 and 4p were significant (p < 0.001), but within the observed cycle-by-cycle variability. The proposed 4-parameter model of the volumetric capnogram improves data fitting and estimation of VD_AW and S_III as compared to the 7-parameter model of reference. These advantages support the use of the 4-parameter model in future research and clinical applications.

Generalized estimation of the ventilatory distribution from the multiple-breath washout: a bench evaluation study

BACKGROUND

The multiple-breath washout (MBW) is able to provide information about the distribution of ventilation-to-volume (v/V) ratios in the lungs. However, the classical, all-parallel model may return skewed results due to the mixing effect of a common dead space. The aim of this work is to examine whether a novel mathematical model and algorithm is able to estimate v/V of a physical model, and to compare its results with those of the classical model. The novel model takes into account a dead space in series with the parallel ventilated compartments, allows for variable tidal volume (VT) and end-expiratory lung volume (EELV), and does not require a ideal step change of the inert gas concentration.

METHODS

Two physical models with preset v/V units and a common series dead space (vd) were built and mechanically ventilated. The models underwent MBW with N2 as inert gas, throughout which flow and N2 concentration signals were acquired. Distribution of v/V was estimated-via nonnegative least squares, with Tikhonov regularization-with the classical, all-parallel model (with and without correction for non-ideal inspiratory N2 step) and with the new, generalized model including breath-by-breath vd estimates given by the Fowler method (with and without constrained VT and EELV).

RESULTS

The v/V distributions estimated with constrained EELV and VT by the generalized model were practically coincident with the actual v/V distribution for both physical models. The v/V distributions calculated with the classical model were shifted leftwards and broader as compared to the reference.

CONCLUSIONS

The proposed model and algorithm provided better estimates of v/V than the classical model, particularly with constrained VT and EELV.