Lung density distribution in dynamic CT correlates with oxygenation in ventilated pigs with lavage ARDS

Fast dynamic computed tomography (dCT) has been used to assess regional dynamics of lung inflation and deflation processes. The aim of this study was to relate ventilation-induced changes in lung density distribution, as measured over several respiratory cycles by dCT, to oxygenation and shunt fraction in a lavage acute respiratory distress syndrome model.

Six anaesthetized pigs underwent pressure-constant ventilation (FIO2=1.0, inspiratory:expiratory ratio=1:1) before and after induction of lung damage by saline lavage. Mean airway pressure (Paw) was varied (8, 13, 18, 23, 28, 33, and 38 cm H2O) in random order. At each Paw level, dCT acquisitions were performed over several respiratory cycles (Somatom Plus4, Siemens; supradiaphragmatic transverse slice; thickness=1 mm; temporal resolution=100 ms). During scanning at each Paw, arterial and mixed venous blood were obtained for blood gas analysis and shunt calculation. In each CT image, fractional areas (FA) of defined density ranges representing ventilated lung and atelectasis were determined by planimetry using dedicated software. The FA data of individual 100 ms scans were averaged over several respiratory cycles, and expressed as mean FA in percentage of total lung area at each Paw. For atelectatic lung parenchyma a quantitative relationship of the respective mean FA to shunt fraction was studied using regression analysis.

Under steady-state conditions, mean FA of atelectasis correlated linearly with the calculated shunt fraction (healthy lungs, r=+0.76; lavaged lungs, r=+0.89). There is a non-linear relationship between mean FA of ventilated lung parenchyma and mean FA of atelectasis with PaO2.

We conclude that dCT allows assessment of the effects of ventilator adjustments and resultant Paw; changes upon lung aeration and oxygenation rapidly, and with good spatial and temporal resolution. This may benefit patients with acute lung injury, whose ventilatory pattern may be optimized as early as during their first diagnostic workup.