Determination of respiratory gas flow by electrical impedance tomography in an animal model of mechanical ventilation.

BACKGROUND: A recent method determines regional gas flow of the lung by electrical impedance tomography (EIT). The aim of this study is to show the applicability of this method in a porcine model of mechanical ventilation in healthy and diseased lungs. Our primary hypothesis is that global gas flow measured by EIT can be correlated with spirometry. Our secondary hypothesis is that regional analysis of respiratory gas flow delivers physiologically meaningful results. METHODS: In two sets of experiments n = 7 healthy pigs and n = 6 pigs before and after induction of lavage lung injury were investigated. EIT of the lung and spirometry were registered synchronously during ongoing mechanical ventilation. In-vivo aeration of the lung was analysed in four regions-of-interest (ROI) by EIT: 1) global, 2) ventral (non-dependent), 3) middle and 4) dorsal (dependent) ROI. Respiratory gas flow was calculated by the first derivative of the regional aeration curve. Four phases of the respiratory cycle were discriminated. They delivered peak and late inspiratory and expiratory gas flow (PIF, LIF, PEF, LEF) characterizing early or late inspiration or expiration. RESULTS: Linear regression analysis of EIT and spirometry in healthy pigs revealed a very good correlation measuring peak flow and a good correlation detecting late flow. PIFEIT = 0.702 · PIFspiro + 117.4, r(2) = 0.809; PEFEIT = 0.690 · PEFspiro-124.2, r(2) = 0.760; LIFEIT = 0.909 · LIFspiro + 27.32, r(2) = 0.572 and LEFEIT = 0.858 · LEFspiro-10.94, r(2) = 0.647. EIT derived absolute gas flow was generally smaller than data from spirometry. Regional gas flow was distributed heterogeneously during different phases of the respiratory cycle. But, the regional distribution of gas flow stayed stable during different ventilator settings. Moderate lung injury changed the regional pattern of gas flow. CONCLUSIONS: We conclude that the presented method is able to determine global respiratory gas flow of the lung in different phases of the respiratory cycle. Additionally, it delivers meaningful insight into regional pulmonary characteristics, i.e. the regional ability of the lung to take up and to release air.

Influence of fluid and volume state on PaO2 oscillations in mechanically ventilated pigs.

Varying pulmonary shunt fractions during the respiratory cycle cause oxygen oscillations during mechanical ventilation. In artificially damaged lungs, cyclical recruitment of atelectasis is responsible for varying shunt according to published evidence. We introduce a complimentary hypothesis that cyclically varying shunt in healthy lungs is caused by cyclical redistribution of pulmonary perfusion. Administration of crystalloid or colloid infusions would decrease oxygen oscillations if our hypothesis was right. Therefore, n=14 mechanically ventilated healthy pigs were investigated in 2 groups: crystalloid (fluid) versus no-fluid administration. Additional volume interventions (colloid infusion, blood withdrawal) were carried out in each pig. Intra-aortal PaO2 oscillations were recorded using fluorescence quenching technique. Phase shift of oxygen oscillations during altered inspiratory to expiratory (I:E) ventilation ratio and electrical impedance tomography (EIT) served as control methods to exclude that recruitment of atelectasis is responsible for oxygen oscillations. In hypovolemia relevant oxygen oscillations could be recorded. Fluid and volume state changed PaO2 oscillations according to our hypothesis. Fluid administration led to a mean decline of 105.3 mmHg of the PaO2 oscillations amplitude (P<0.001). The difference of the amplitudes between colloid administration and blood withdrawal was 62.4 mmHg in pigs not having received fluids (P=0.0059). Fluid and volume state also changed the oscillation phase during altered I:E ratio. EIT excluded changes of regional ventilation (i.e., recruitment of atelectasis) to be responsible for these oscillations. In healthy pigs, cyclical redistribution of pulmonary perfusion can explain the size of respiratory-dependent PaO2 oscillations.