Background
Ventilation of patients with acute hypoxemic respiratory failure (AHRF) and acute respiratory distress syndrome (ARDS) [
1] should provide adequate gas exchange while minimizing the risk of ventilator-induced lung injury (VILI) [
2,
3]. Mechanisms underlying VILI include tidal collapse and reopening of unstable lung units, overstretch of the “baby lung” [
4], and heterogeneous ventilation that increases regional transpulmonary pressure [
5‐
7]. Strategies aimed at “opening the lung and keeping it open” by means of alveolar recruitment may reduce the risk of VILI [
3,
5,
8], and positive end-expiratory pressure (PEEP) set to stabilize re-aerated alveoli while avoiding overdistention might be a key aspect of protective ventilation [
9]. Despite a recent large trial that showed the potential harmfulness of a maximal recruitment strategy [
10], other studies in which researchers compared higher versus lower PEEP levels did not yield definitive results [
11,
12]. One reason could have been the pathophysiologic heterogeneity of ARDS, with large interindividual variations in the extent and distribution of alveolar collapse that reduced clinical benefits of arbitrarily higher PEEP levels [
13]. Thus, a bedside method of accurately assessing recruitment and overdistention might be fundamental to the design of future studies applying personalized “optimum” PEEP levels [
2].
Lung recruitment may be evaluated by performing pressure-volume (P-V) curves of the respiratory system [
14]. Several studies have validated the P-V curve method as a reliable estimate of PEEP-induced changes in aerated lung volume [
15‐
20]. However, P-V curves are relatively complex to perform, time-consuming, noncontinuous, and not feasible in spontaneously breathing patients.
Recently, electrical impedance tomography (EIT) has been introduced as a bedside radiation-free technique that provides dynamic regional information on changes in lung aeration, ventilation, and heterogeneity [
21]. EIT can identify and quantify breath-by-breath poorly ventilated lung units, also called
silent spaces. In a recent study, researchers suggested that in postoperative patients with healthy lungs, silent spaces in the dependent lungs may indicate atelectasis, whereas increase in silent spaces in the nondependent lungs may correspond to overdistention [
22].
In this study, we compared, in intubated patients with AHRF and 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 EIT. We hypothesized that changes in DSS might represent a dynamic bedside measure of lung recruitment and collapse.
Discussion
The main findings of this study are as follows: (1) PEEP-induced changes in EIT-derived poorly ventilated areas in the dependent lungs (DSSs) correlate with recruitment determined by the P-V curve, and (2) the reduction of DSS, obtained by progressive increases of PEEP, is associated with a more homogeneous distribution of ventilation and improved regional compliance of the dependent portions of the lung; however, higher levels of PEEP were associated with lower compliance of the nondependent part of the lung, which might indicate overdistention.
In the present study, we compared the EIT imaging technique with the P-V curve of the respiratory system to explore the hypothesis that these two methods deliver similar information about PEEP-induced lung recruitment. Silent spaces are a new EIT-derived parameter aimed at identifying areas of the lung in which air content changes minimally during tidal ventilation, potentially representing collapse or overdistention [
22]. We hypothesized that changes in silent spaces, representing changes in functional lung size, would also have been seen in the P-V curve as changes of recruited lung volume. Confirming our hypothesis, changes in DSS observed with EIT were statistically correlated with changes of lung volume measured by the P-V curve. Although the response to changes in PEEP and to the RM was heterogeneous in terms of lung volume and DSS changes, the two parameters changed accordingly (Fig.
2) because the increase/decrease of lung volume was associated with an opposite change of DSS (Table
3). Interestingly, the PEEP level corresponding to the lowest value of DSS was 15 cmH
2O in 12 (86%) of the patients and 10 cmH
2O in 2 (14%) of the patients (Additional file
1: Table S1).
The application of PEEP is a key but still challenging element of lung-protective ventilation, one of its effects being the redistribution of ventilation toward dependent lungs, which results in a more homogeneous aeration [
34]. Because this technique provides information about regional lung ventilation [
35], several indexes addressing ventilation homogeneity have been proposed [
21], and EIT has been shown to be useful for assessing the effects of PEEP on the distribution of ventilation [
36‐
41].
The TDI is used to evaluate the ratio of V
T distributed to the nondependent and dependent lung. This index is an indirect signal of the homogeneity of the tidal ventilation. Our data show that incremental PEEP levels resulted in significant recruitment and a reduction of value of TDI closer to 1, which implies more homogeneous ventilation by a shift of ventilation toward dorsal regions. This phenomenon is also demonstrated by the modification of the CoV: The increased change of the CoV toward 50% suggests that the tidal ventilation is moved toward the dependent lung regions. This index, in fact, changes significantly (
p < 0.001) from PEEP 5 cmH
2O (41.9%) to PEEP 15 cmH
2O (49.4%). Interestingly, TDI indicated the most homogeneous distribution of ventilation at PEEP 15, 10, and 5 cmH
2O in 9 (64%), 4 (28%), and 1 (7%) patients, respectively (Additional file
1: Table S1). These results show that different PEEP levels were able to achieve better lung homogeneity; indeed, tailored mechanical ventilation reducing lung inhomogeneity might decrease regional lung stress [
42] and improve patient survival [
43].
The use of silent spaces as a bedside method to determine the recruitment of functional lung volume has many advantages compared with the P-V curve because the monitoring is breathwise and continuous, providing local information. Furthermore, it does not require the use of high doses of sedatives or muscle relaxants.
EIT allows for assessment of regional lung mechanics on a pixel basis by tracking changes in regional lung compliance [
44]. Mauri and colleagues showed that rising PEEP levels reduced lung strain and increased EELV, but at the expense of nondependent lung overinflation [
39]. In our study, dependent regional compliance appeared to significantly increase rising PEEP levels, whereas nondependent regional compliance acted inversely, suggesting that higher PEEP can be associated with the risk of overdistention of that region. The determination of regional lung compliance might further support PEEP selection as the value that balances recruitment of dependent lung with “acceptable” overdistention of the nondependent one. Hence, the information obtained by EIT can be clinically relevant because the interpretation of global respiratory mechanics is often misleading in patients undergoing mechanical ventilation. In fact, global respiratory mechanics, like the static P-V curve, can only summarize overlapping information stemming from several ventilated units with different mechanical behaviors [
45‐
47]. Indeed, the linear part of a static P-V curve may result from the overlap of already overdistended units and those that are opening during inspiration. Thus, a combination of different parameters obtained by EIT could reflect in more detail the properties of different lung regions that remain unrecognized by global assessments of respiratory mechanics.
Our study has some limitations. First, the method used to determine ΔEELV requires the removal of PEEP for a limited number of breaths; hence, we cannot exclude a potential alveolar derecruitment between steps. However, the correlation between the two methods should not have been affected, because ΔEELV was calculated at the end of data collection for each step, and its determination was always obtained during the same condition, making the influence on the quality of our data limited. Second, EIT imaging covers only the central part of the lungs (approximately 50%) close to where the EIT belt is positioned. Third, we enrolled both patients with AHRF and patients with ARDS, in keeping with previous studies [
39], but this might have introduced some heterogeneity of the population. Fourth, the number of patients enrolled in this physiological study was low but was in keeping with previous studies in this field [
39]. Fourth, further studies are needed to integrate silent spaces into a clinical protocol for bedside selection of personalized PEEP, despite the fact that our study does not suggest a straightforward protocol to select PEEP on the basis of DSSs. Finally, further studies are required to find out if the variation of silent spaces determined by EIT is also correlated with recruitment in spontaneously breathing patients so that these spaces could be used to set a personalized level of PEEP. However, a reference standard different from P-V curve analysis should be used in that context.