Reliability of the nitrogen washin-washout technique to assess end-expiratory lung volume at variable PEEP and tidal volumes

Individualized positive end-expiratory pressure guided by end-expiratory lung volume in early acute respiratory distress syndrome: study protocol for the multicenter, randomized IPERPEEP trial

Background

In acute respiratory distress syndrome (ARDS), response to positive end-expiratory pressure (PEEP) is variable according to different degrees of lung recruitability. The search for a tool to individualize PEEP based on patients’ individual response is warranted.

End-expiratory lung volume (EELV) assessment by nitrogen washing-washout aids bedside estimation of PEEP-induced alveolar recruitment and may therefore help titrate PEEP on patient’s individual recruitability.

We designed a randomized trial to test whether an individualized PEEP setting protocol driven by EELV measurement may improve a composite clinical outcome in patients with moderate-to-severe ARDS (IPERPEEP trial).

Methods

IPERPEEP is an open-label, multicenter, randomized trial that will be conducted in 10 intensive care units in Italy and will enroll 132 ARDS patients showing PaO₂/FiO₂ ratio ≤ 150 mmHg within 24 h from endotracheal intubation while on mechanical ventilation with PEEP 5 cmH₂O.

To standardize lung volumes at study initiation, all patients will undergo mechanical ventilation with tidal volume of 6 ml/kg of predicted body weight and PEEP set to obtain a plateau pressure within 28 and 30 cmH₂O for 30 min (EXPRESS PEEP).

Afterwards, a 5-step decremental PEEP trial will be conducted (EXPRESS PEEP to PEEP 5 cmH₂O), and EELV will be measured at each step. Recruitment-to-inflation ratio will be calculated for each PEEP range from EELV difference. Patients will be then randomized to receive mechanical ventilation with PEEP set according to the optimal recruitment observed in the PEEP trial (IPERPEEP arm) trial or to achieve a plateau pressure of 28–30 cmH₂O (control arm, EXPRESS strategy). In both groups, tidal volume size, use of prone positioning and neuromuscular blocking agents, and weaning from PEEP and from mechanical ventilation will be standardized.

The primary endpoint of the study is a composite clinical outcome incorporating in-ICU mortality, 60-day ventilator-free days, and serum interleukin-6 concentration over the course of the initial 72 h of treatment.

Discussion

The IPERPEEP study is a randomized trial powered to elucidate whether an individualized PEEP setting protocol based on bedside assessment of lung recruitability can improve a composite clinical outcome during moderate-to-severe ARDS.

Trial registration

ClinicalTrials.govNCT04012073. Registered 9 July 2019.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05993-0.

Effects of end-expiratory lung volume versus PaO2 guided PEEP determination on respiratory mechanics and oxygenation in moderate to severe ARDS

There is no ideal method for determination of positive end-expiratory pressure (PEEP) in acute respiratory distress syndrome (ARDS) patients. We compared the effects of end-expiratory lung volume (EELV)-guided versus PaO₂-guided PEEP determination on respiratory mechanics and oxygenation during the first 48 hours in moderate to severe ARDS.

Twenty-two patients with moderate to severe ARDS admitted to an academic medical ICU were assigned to PaO₂-guided (n = 11) or to EELV-guided PEEP determination (n = 11) group. First, an incremental PEEP trial was performed by increasing PEEP by 3 cmH₂O steps from 8 to 20 cmH₂O and in each step EELV and lung mechanics were measured in both groups. Then, oxygenation and respiratory mechanics were measured under the determined PEEP at 4, 12, 24, and 48th hours.

After the incremental PEEP trial, over the 48 hours of the study period, in the EELV-guided group PaO₂ and PaO₂/FiO₂ increased (p = 0.04 and p = 0.02; respectively), whereas they did not change in PaO₂-guided group (p = 0.09 and p = 0.27; respectively). In all patients, the median value of EELV change (ΔEELV) during incremental PEEP trial was 25%. In patients with ΔEELV > 25% (n = 11) PaO₂, PaO₂/FiO₂ and Cs increased over time in 48 hours (p = 0.03, p < 0.01, and p = 0.04; respectively), whereas they did not change in those with ΔEELV ≤ 25% (n = 11) (p = 0.73, p = 0.51, and p = 0.73; respectively).

Compared to PaO₂-guided PEEP determination, EELV-guided PEEP determination resulted in greater improvement in oxygenation over time. Patients who had > 25% improvement in EELV during a PEEP trial had greater improvement in oxygenation and compliance over 48 hours.

Supplemental data for this article is available online at.

Validation of a novel system to assess end-expiratory lung volume and alveolar recruitment in an ARDS model

Background

Personalizing mechanical ventilation requires the development of reliable bedside monitoring techniques. The multiple-breaths nitrogen washin–washout (MBNW) technique is currently available to measure end-expiratory lung volume (EELV_MBNW), but the precision of the technique may be poor, with percentage errors ranging from 28 to 57%. The primary aim of the study was to evaluate the reliability of a novel MBNW bedside system using fast mainstream sensors to assess EELV in an experimental acute respiratory distress syndrome (ARDS) model, using computed tomography (CT) as the gold standard. The secondary aims of the study were: (1) to evaluate trending ability of the novel system to assess EELV; (2) to evaluate the reliability of estimated alveolar recruitment induced by positive end-expiratory pressure (PEEP) changes computed from EELV_MBNW, using CT as the gold standard.

Results

Seven pigs were studied in 6 experimental conditions: at baseline, after experimental ARDS and during a decremental PEEP trial at PEEP 16, 12, 6 and 2 cmH₂O. EELV was computed at each PEEP step by both the MBNW technique (EELV_MBNW) and CT (EELV_CT). Repeatability was assessed by performing replicate measurements. Alveolar recruitment between two consecutive PEEP levels after lung injury was measured with CT (Vrec_CT), and computed from EELV measurements (Vrec_MBNW) as ΔEELV minus the product of ΔPEEP by static compliance.

EELV_MBNW and EELV_CT were significantly correlated (R² = 0.97). An acceptable non-constant bias between methods was identified, slightly decreasing toward more negative values as EELV increased. The conversion equation between EELV_MBNW and EELV_CT was: EELV_MBNW = 0.92 × EELV_CT + 36. The 95% prediction interval of the bias amounted to ± 86 mL and the percentage error between both methods amounted to 13.7%.

The median least significant change between repeated measurements amounted to 8% [CI_95%: 4–10%]. EELV_MBNW adequately tracked EELV_CT changes over time (concordance rate amounting to 100% [CI_95%: 87%–100%] and angular bias amounting to − 2° ± 10°).

Vrec_MBNW and Vrec_CT were significantly correlated (R² = 0.92). A non-constant bias between methods was identified, slightly increasing toward more positive values as Vrec increased.

Conclusions

We report a new bedside MBNW technique that reliably assesses EELV in an experimental ARDS model with high precision and excellent trending ability.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-021-00410-x.

Clinical and experimental validation of a capnodynamic method for end-expiratory lung volume assessment

INTRODUCTION

Lung protective ventilation can decrease post-operative pulmonary complications. The aim of this study was to evaluate a capnodynamic method estimating effective lung volume (ELV) as a proxy for end-expiratory lung volume in response to PEEP changes in patients, healthy subjects and a porcine model.

METHODS

Agreement and trending ability for ELV in anaesthetized patients and agreement in awake subjects were evaluated using nitrogen multiple breath wash-out/in and plethysmography as a reference respectively. Agreement and trending ability were evaluated in pigs during PEEP elevations with inert gas wash-out as reference.

RESULTS

In anaesthetized patients bias (95% limits of agreement [LoA]) and percentage error (PE) at PEEP 0 cm H₂ O were 133 mL (-1049 to 1315) and 71%, at PEEP 5 cm H₂ O 161 mL (-1291 to 1613 mL) and 66%. In healthy subjects: 21 mL (-755 to 796 mL) and 26%. In porcines, at PEEP 5-20 cm H₂ O bias decreased from 223 mL to 136 mL LoA (34-412) to (-30 to 902) and PE 29%-49%. Trending abilities in anaesthetized patients and porcines were 100% concordant.

CONCLUSION

The ELV-method showed low bias but high PE in anaesthetized patients. Agreement was good in awake subjects. In porcines, agreement was good at lower PEEP levels. Concordance related to PEEP changes reached 100% in all settings. This method may become a useful trending tool for monitoring lung function during mechanical ventilation, if findings are confirmed in other clinical contexts.

Validating the inspired sinewave technique to measure the volume of the 'baby lung' in a porcine lung-injury model

BACKGROUND

Bedside lung volume measurement could personalise ventilation and reduce driving pressure in patients with acute respiratory distress syndrome (ARDS). We investigated a modified gas-dilution method, the inspired sinewave technique (IST), to measure the effective lung volume (ELV) in pigs with uninjured lungs and in an ARDS model.

METHODS

Anaesthetised mechanically ventilated pigs were studied before and after surfactant depletion by saline lavage. Changes in PEEP were used to change ELV. Paired measurements of absolute ELV were taken with IST (ELV_IST) and compared with gold-standard measures (sulphur hexafluoride wash in/washout [ELV_SF6] and computed tomography (CT) [ELV_CT]). Measured volumes were used to calculate changes in ELV (ΔELV) between PEEP levels for each method (ΔELV_IST, ΔELV_SF6, and ΔELV_CT).

RESULTS

The coefficient of variation was <5% for repeated ELV_IST measurements (n=13 pigs). There was a strong linear relationship between ELV_IST and ELV_SF6 in uninjured lungs (r²=0.97), and with both ELV_SF6 and ELV_CT in the ARDS model (r²=0.87 and 0.92, respectively). ELV_IST had a mean bias of -12 to 13% (95% limits=±17 - 25%) compared with ELV_SF6 and ELV_CT. ΔELV_IST was concordant with ΔELV_SF6 and ΔELV_CT in 98-100% of measurements, and had a mean bias of -73 to -77 ml (95% limits=±128 - 186 ml) compared with ΔELV_SF6 and -1 ml (95% limits ±333 ml) compared with ΔELV_CT.

CONCLUSIONS

IST provides a repeatable measure of absolute ELV and shows minimal bias when tracking PEEP-induced changes in lung volume compared with CT in a saline-lavage model of ARDS.

Voxel-wise assessment of lung aeration changes on CT images using image registration: application to acute respiratory distress syndrome (ARDS)

PURPOSE

(1) To improve the accuracy of global and regional alveolar-recruitment quantification in CT scan pairs by accounting for lung-tissue displacements and deformation, (2) To propose a method for local-recruitment calculation.

METHODS

Recruitment was calculated by subtracting the quantity of non-aerated lung tissues between expiration and inspiration. To assess global recruitment, lung boundaries were first interactively delineated at inspiration, and then they were warped based on automatic image registration to define the boundaries at expiration. To calculate regional recruitment, the lung mask defined at inspiration was cut into pieces, and these were also warped to encompass the same tissues at expiration. Local-recruitment map was calculated as follows: For each voxel at expiration, the matching location at inspiration was determined by image registration, non-aerated voxels were counted in the neighborhood of the respective locations, and the voxel count difference was normalized by the neighborhood size. The methods were evaluated on 120 image pairs of 12 pigs with experimental acute respiratory distress syndrome.

RESULTS

The dispersion of global- and regional-recruitment values decreased when using image registration, compared to the conventional approach neglecting tissue motion. Local-recruitment maps overlaid onto the original images were visually consistent, and the sum of these values over the whole lungs was very close to the global-recruitment estimate, except four outliers.

CONCLUSIONS

Image registration can compensate lung-tissue displacements and deformation, thus improving the quantification of alveolar recruitment. Local-recruitment calculation can also benefit from image registration, and its values can be overlaid onto the original image to display a local-recruitment map. They also can be integrated over arbitrarily shaped regions to assess regional or global recruitment.

Endexpiratory lung volume measurement correlates with the ventilation/perfusion mismatch in lung injured pigs

Background

In acute respiratory respiratory distress syndrome (ARDS) a sustained mismatch of alveolar ventilation and perfusion (V_A/Q) impairs the pulmonary gas exchange. Measurement of endexpiratory lung volume (EELV) by multiple breath-nitrogen washout/washin is a non-invasive, bedside technology to assess pulmonary function in mechanically ventilated patients. The present study examines the association between EELV changes and V_A/Q distribution and the possibility to predict V_A/Q normalization by means of EELV in a porcine model.

Methods

After approval of the state and institutional animal care committee 12 anesthetized pigs were randomized to ARDS either by bronchoalveolar lavage (n = 6) or oleic acid injection (n = 6). EELV, V_A/Q ratios by multiple inert gas elimination and ventilation distribution by electrical impedance tomography were assessed at healthy state and at five different positive endexpiratory pressure (PEEP) steps in ARDS (0, 20, 15, 10, 5 cmH₂O; each maintained for 30 min).

Results

V_A/Q, EELV and tidal volume distribution all displayed the PEEP-induced recruitment in ARDS. We found a close correlation between V_A/Q < 0.1 (representing shunt and low V_A/Q units) and changes in EELV (spearman correlation coefficient −0.79). Logistic regression reveals the potential to predict V_A/Q normalization (V_A/Q < 0.1 less than 5%) from changes in EELV with an area under the curve of 0.89 with a 95%-CI of 0.81–0.96 in the receiver operating characteristic. Different lung injury models and recruitment characteristics did not influence these findings.

Conclusion

In a porcine ARDS model EELV measurement depicts PEEP-induced lung recruitment and is strongly associated with normalization of the V_A/Q distribution in a model-independent fashion. Determination of EELV could be an intriguing addition in the context of lung protection strategies.

Lung volume assessment in acute respiratory distress syndrome

PURPOSE OF REVIEW

Measurements of lung volumes allow evaluating the pathophysiogical severity of acute respiratory distress syndrome (ARDS) in terms of the degree of reduction in aerated lung volume, calculating strain, quantifying recruitment and/or hyperinflation, and gas volume distribution. We summarize the current techniques for lung volume assessment selected according to their possible usage in the ICU and discuss the recent findings obtained with implementation of these techniques in patients with ARDS.

RECENT FINDINGS

Computed tomography technique remains irreplaceable in terms of quantitative aeration of different lung regions, but the commonly used cut-offs for classification may be questioned with recent findings on nonpathological lungs. Monitoring end expiratory lung volume using nitrogen washout technique enhanced our understanding on lung volume change during positioning, pleural effusion drainage, intra-abdominal hypertension, and recruitment maneuver. Recent studies supported that tidal volume could not surrogate tidal strain, which needs measurement of functional residual capacity and which is correlated with pro-inflammatory lung response.

SUMMARY

Although lung volume measurements are still limited to research area of ARDS, recent progress in technology provides clinicians more opportunities to evaluate lung volumes noninvasively at the bedside and may facilitate individualization of ventilator settings based on the specific physiological understandings of a given patient.