Variation of poorly ventilated lung units (silent spaces) measured by electrical impedance tomography to dynamically assess recruitment

Abstract

BackgroundAssessing alveolar recruitment at different positive end-expiratory pressure (PEEP) levels is a major clinical and research interest because protective ventilation implies opening the lung without inducing overdistention. The pressure-volume (P-V) curve is a validated method of assessing recruitment but reflects global characteristics, and changes at the regional level may remain undetected. The aim of the present study was to compare, in intubated patients with acute hypoxemic respiratory failure (AHRF) and acute respiratory distress syndrome (ARDS), lung recruitment measured by P-V curve analysis, with dynamic changes in poorly ventilated units of the dorsal lung (dependent silent spaces [DSSs]) assessed by electrical impedance tomography (EIT). We hypothesized that DSSs might represent a dynamic bedside measure of recruitment.MethodsWe carried out a prospective interventional study of 14 patients with AHRF and ARDS admitted to the intensive care unit undergoing mechanical ventilation. Each patient underwent an incremental/decremental PEEP trial that included five consecutive phases: PEEP 5 and 10 cmH2O, recruitment maneuver + PEEP 15 cmH2O, then PEEP 10 and 5 cmH2O again. We measured, at the end of each phase, recruitment from previous PEEP using the P-V curve method, and changes in DSS were continuously monitored by EIT.ResultsPEEP changes induced alveolar recruitment as assessed by the P-V curve method and changes in the amount of DSS (p < 0.001). Recruited volume measured by the P-V curves significantly correlated with the change in DSS (rs = 0.734, p < 0.001). Regional compliance of the dependent lung increased significantly with rising PEEP (median PEEP 5 cmH2O = 11.9 [IQR 10.4–16.7] ml/cmH2O, PEEP 15 cmH2O = 19.1 [14.2–21.3] ml/cmH2O; p < 0.001), whereas regional compliance of the nondependent lung decreased from PEEP 5 cmH2O to PEEP 15 cmH2O (PEEP 5 cmH2O = 25.3 [21.3–30.4] ml/cmH2O, PEEP 15 cmH2O = 20.0 [16.6–22.8] ml/cmH2O; p <0.001). By increasing the PEEP level, the center of ventilation moved toward the dependent lung, returning to the nondependent lung during the decremental PEEP steps.ConclusionsThe variation of DSSs dynamically measured by EIT correlates well with lung recruitment measured using the P-V curve technique. EIT might provide useful information to titrate personalized PEEP.Trial registrationClinicalTrials.gov, NCT02907840. Registered on 20 September 2016.Electronic supplementary materialThe online version of this article (10.1186/s13054-017-1931-7) contains supplementary material, which is available to authorized users.

Prone positioning monitored by electrical impedance tomography in patients with severe acute respiratory distress syndrome on veno-venous ECMO

“…Third, we defined optimal PEEP as the best compromise between lowest overdistension and collapse, as previously described [20]. We cannot exclude that different optimal PEEP identification methods, e.g., inhomogeneity index [38] or dependent silent spaces [39], would have yielded different results. However, we can acknowledge that the selected optimal PEEP's influence on our results was probably limited because ventilator settings were unchanged throughout the entire protocol.…”

Influence of Positive End-Expiratory Pressure Titration on the Effects of Pronation in Acute Respiratory Distress Syndrome: A Comprehensive Experimental Study

“…The variation of impedance related to perfusion ( Zp) was normalized to the highest pixel level Zp, yielding values ranging from 0 to 1. The global inhomogeneity index of perfusion (GIp) was therefore calculated as follows: The EIT derived regional compliance was calculated both for the respiratory system and for the lungs, assuming that Zv = V, as previously described (Spadaro et al, 2018). Region of interest division was made using the mass content derived from the corresponding CT scans.…”

Assessment of changes of regional ventilation distribution in the lung tissue depending on the driving pressure applied during high frequency jet ventilation

“…The EIT was previously reported as an accurate method to detect ventilation inhomogeneity and was validated by several methods including radionuclide scanning, spirometer, and single-photo emission computed tomography [ 16 – 19 ]. Images gained by the EIT technology were previously used to identify the lung areas which are under and over ventilated (collapse or overinflated) [ 20 ].…”