Monitoring of pulmonary mechanics in acute respiratory distress syndrome to titrate therapy

Setting positive end-expiratory pressure: using the pressure-volume curve

PURPOSE OF REVIEW

To discuss the role of pressure-volume curve (PV curve) in exploring elastic properties of the respiratory system and setting mechanical ventilator to reduce ventilator-induced lung injury.

RECENT FINDINGS

Nowadays, quasi-static PV curves and loops can be easily obtained and analyzed at the bedside without disconnection of the patient from the ventilator. It is shown that this tool can provide useful information to optimize ventilator setting. For example, PV curves can assess for patient's individual potential for lung recruitability and also evaluate the risk for lung injury of the ongoing mechanical ventilation setting.

SUMMARY

In conclusion, PV curve is an easily available bedside tool: its correct interpretation can be extremely valuable to enlighten potential for lung recruitability and select a high or low positive end-expiratory pressure (PEEP) strategy. Furthermore, recent studies have shown that PV curve can play a significant role in PEEP and driving pressure fine tuning: clinical studies are needed to prove whether this technique will improve outcome.

Accuracy of the estimations of respiratory mechanics using an expiratory time constant in passive and active breathing conditions: a bench study

BACKGROUND

Respiratory mechanics monitoring provides useful information for guiding mechanical ventilation, but many measuring methods are inappropriate for awake patients. This study aimed to evaluate the accuracy of dynamic mechanics estimation using expiratory time constant (RC_exp) calculation during noninvasive pressure support ventilation (PSV) with air leak in different lung models.

METHODS

A Respironics V60 ventilator was connected to an active breathing simulator for modeling five profiles: normal adult, restrictive, mildly and severely obstructive, and mixed obstructive/restrictive. Inspiratory pressure support was adjusted to maintain tidal volumes (V_T), achieving 5.0, 7.0, and 10.0 ml/kg body weight. PEEP was set at 5 cmH₂O, and the back-up rate was 10 bpm. Measurements were conducted at system leaks of 25-28 L/min. RC_exp was estimated from the ratio at 75% exhaled V_T and flow rate, which was then used to determine respiratory system compliance (C_rs) and airway resistance (R_aw).

RESULTS

In non-obstructive conditions (R_aw ≤ 10 cmH₂O/L/s), the C_rs was overestimated in the PSV mode. Peak inspiratory and expiratory flow and V_T increased with PS levels, as calculated C_rs decreased. In passive breathing, the difference of C_rs between different V_T was no significant. Underestimations of inspiratory resistance and expiratory resistance were observed at V_T of 5.0 ml/kg. The difference was minimal at V_T of 7.0 ml/kg. During non-invasive PSV, the estimation of airway resistance with the RC_exp method was accurately at V_T of 7.0 ml/kg.

CONCLUSIONS

The difference between the calculated C_rs and the preset value was influenced by the volume, status and inspiratory effort in spontaneously breathing.

Measurement of Electrical Impedance Tomography-Based Regional Ventilation Delay for Individualized Titration of End-Expiratory Pressure

RATIONALE

Individualized positive end-expiratory pressure (PEEP) titration might be beneficial in preventing tidal recruitment. To detect tidal recruitment by electrical impedance tomography (EIT), the time disparity between the regional ventilation curves (regional ventilation delay inhomogeneity [RVDI]) can be measured during controlled mechanical ventilation when applying a slow inflation of 12 mL/kg of body weight (BW). However, repeated large slow inflations may result in high end-inspiratory pressure (P_EI), which might limit the clinical applicability of this method. We hypothesized that PEEP levels that minimize tidal recruitment can also be derived from EIT-based RVDI through the use of reduced slow inflation volumes.

METHODS

Decremental PEEP trials were performed in 15 lung-injured pigs. The PEEP level that minimized tidal recruitment was estimated from EIT-based RVDI measurement during slow inflations of 12, 9, 7.5, or 6 mL/kg BW. We compared RVDI and P_EI values resulting from different slow inflation volumes and estimated individualized PEEP levels.

RESULTS

RVDI values from slow inflations of 12 and 9 mL/kg BW showed excellent linear correlation (R² = 0.87, p < 0.001). Correlations decreased for RVDI values from inflations of 7.5 (R² = 0.68, p < 0.001) and 6 (R² = 0.42, p < 0.001) mL/kg BW. Individualized PEEP levels estimated from 12 and 9 mL/kg BW were comparable (bias -0.3 cm H₂O ± 1.2 cm H₂O). Bias and scatter increased with further reduction in slow inflation volumes (for 7.5 mL/kg BW, bias 0 ± 3.2 cm H₂O; for 6 mL/kg BW, bias 1.2 ± 4.0 cm H₂O). P_EI resulting from 9 mL/kg BW inflations were comparable with P_EI during regular tidal volumes.

CONCLUSIONS

PEEP titration to minimize tidal recruitment can be individualized according to EIT-based measurement of the time disparity of regional ventilation courses during slow inflations with low inflation volumes_. This sufficiently decreases P_EI and may reduce potential clinical risks.

Accuracy of the dynamic signal analysis approach in respiratory mechanics during noninvasive pressure support ventilation: a bench study

OBJECTIVE

To evaluate the accuracy of respiratory mechanics using dynamic signal analysis during noninvasive pressure support ventilation (PSV).

METHODS

A Respironics V60 ventilator was connected to an active lung simulator to model normal, restrictive, obstructive, and mixed obstructive and restrictive profiles. The PSV was adjusted to maintain tidal volumes (V_T) that achieved 5.0, 7.0, and 10.0 mL/kg body weight, and the positive end-expiration pressure (PEEP) was set to 5 cmH₂O. Ventilator performance was evaluated by measuring the flow, airway pressure, and volume. The system compliance (C_rs) and airway resistance (inspiratory and expiratory resistance, R_insp and R_exp, respectively) were calculated.

RESULTS

Under active breathing conditions, the C_rs was overestimated in the normal and restrictive models, and it decreased with an increasing pressure support (PS) level. The R_insp calculated error was approximately 10% at 10.0 mL/kg of V_T, and similar results were obtained for the calculated R_exp at 7.0 mL/kg of V_T.

CONCLUSION

Using dynamic signal analysis, appropriate tidal volume was beneficial for R_rs, especially for estimating R_exp during assisted ventilation. The C_rs measurement was also relatively accurate in obstructive conditions.

A Modified Method to Assess Tidal Recruitment by Electrical Impedance Tomography

Avoiding tidal recruitment and collapse during mechanical ventilation should reduce the risk of lung injury. Electrical impedance tomography (EIT) enables detection of tidal recruitment by measuring regional ventilation delay inhomogeneity (RVDI) during a slow inflation breath with a tidal volume (V_T) of 12 mL/kg body weight (BW). Clinical applicability might be limited by such high V_Ts resulting in high end-inspiratory pressures (P_EI) during positive end-expiratory pressure (PEEP) titration. We hypothesized that RVDI can be obtained with acceptable accuracy from reduced slow inflation V_Ts. In seven ventilated pigs with experimental lung injury, tidal recruitment was quantified by computed tomography at PEEP levels changed stepwise between 0 and 25 cmH₂O. RVDI was measured by EIT during slow inflation V_Ts of 12, 9, 7.5, and 6 mL/kg BW. Linear correlation of tidal recruitment and RVDI was excellent for V_Ts of 12 (R² = 0.83, p < 0.001) and 9 mL/kg BW (R² = 0.83, p < 0.001) but decreased for V_Ts of 7.5 (R² = 0.76, p < 0.001) and 6 mL/kg BW (R² = 0.71, p < 0.001). With any reduction in slow inflation V_T, P_EI decreased at all PEEP levels. Receiver-Operator-Characteristic curve analyses revealed that RVDI-thresholds to predict distinct amounts of tidal recruitment differ when obtained from different slow inflation V_Ts. In conclusion, tidal recruitment can sufficiently be monitored by EIT-based RVDI-calculation with a slow inflation of 9 mL/kg BW.

Impact of Recruitment on Static and Dynamic Lung Strain in Acute Respiratory Distress Syndrome

BACKGROUND

Lung strain, defined as the ratio between end-inspiratory volume and functional residual capacity, is a marker of the mechanical load during ventilation. However, changes in lung volumes in response to pressures may occur in injured lungs and modify strain values. The objective of this study was to clarify the role of recruitment in strain measurements.

METHODS

Six oleic acid-injured pigs were ventilated at positive end-expiratory pressure (PEEP) 0 and 10 cm H2O before and after a recruitment maneuver (PEEP = 20 cm H2O). Lung volumes were measured by helium dilution and inductance plethysmography. In addition, six patients with moderate-to-severe acute respiratory distress syndrome were ventilated with three strategies (peak inspiratory pressure/PEEP: 20/8, 32/8, and 32/20 cm H2O). Lung volumes were measured in computed tomography slices acquired at end-expiration and end-inspiration. From both series, recruited volume and lung strain (total, dynamic, and static) were computed.

RESULTS

In the animal model, recruitment caused a significant decrease in dynamic strain (from [mean ± SD] 0.4 ± 0.12 to 0.25 ± 0.07, P < 0.01), while increasing the static component. In patients, total strain remained constant for the three ventilatory settings (0.35 ± 0.1, 0.37 ± 0.11, and 0.32 ± 0.1, respectively). Increases in tidal volume had no significant effects. Increasing PEEP constantly decreased dynamic strain (0.35 ± 0.1, 0.32 ± 0.1, and 0.04+0.03, P < 0.05) and increased static strain (0, 0.06 ± 0.06, and 0.28 ± 0.11, P < 0.05). The changes in dynamic and total strain among patients were correlated to the amount of recruited volume. An analysis restricted to the changes in normally aerated lung yielded similar results.

CONCLUSION

Recruitment causes a shift from dynamic to static strain in early acute respiratory distress syndrome.

A patient-specific airway branching model for mechanically ventilated patients

BACKGROUND

Respiratory mechanics models have the potential to guide mechanical ventilation. Airway branching models (ABMs) were developed from classical fluid mechanics models but do not provide accurate models of in vivo behaviour. Hence, the ABM was improved to include patient-specific parameters and better model observed behaviour (ABMps).

METHODS

The airway pressure drop of the ABMps was compared with the well-accepted dynostatic algorithm (DSA) in patients diagnosed with acute respiratory distress syndrome (ARDS). A scaling factor (α) was used to equate the area under the pressure curve (AUC) from the ABMps to the AUC of the DSA and was linked to patient state.

RESULTS

The ABMps recorded a median α value of 0.58 (IQR: 0.54-0.63; range: 0.45-0.66) for these ARDS patients. Significantly lower α values were found for individuals with chronic obstructive pulmonary disease (P < 0.001).

CONCLUSION

The ABMps model allows the estimation of airway pressure drop at each bronchial generation with patient-specific physiological measurements and can be generated from data measured at the bedside. The distribution of patient-specific α values indicates that the overall ABM can be readily improved to better match observed data and capture patient condition.

Tidal recruitment assessed by electrical impedance tomography and computed tomography in a porcine model of lung injury*

OBJECTIVES

To determine the validity of electrical impedance tomography to detect and quantify the amount of tidal recruitment caused by different positive end-expiratory pressure levels in a porcine acute lung injury model.

DESIGN

Randomized, controlled, prospective experimental study.

SETTING

Academic research laboratory.

SUBJECTS

Twelve anesthetized and mechanically ventilated pigs.

INTERVENTIONS

Acute lung injury was induced by central venous oleic acid injection and abdominal hypertension in seven animals. Five healthy pigs served as control group. Animals were ventilated with positive end-expiratory pressure of 0, 5, 10, 15, 20, and 25 cm H2O, respectively, in a randomized order.

MEASUREMENTS AND MAIN RESULTS

At any positive end-expiratory pressure level, electrical impedance tomography was obtained during a slow inflation of 12 mL/kg of body weight. Regional-ventilation-delay indices quantifying the time until a lung region reaches a certain amount of impedance change were calculated for lung quadrants and for every single electrical impedance tomography pixel, respectively. Pixel-wise calculated regional-ventilation-delay indices were plotted in a color-coded regional-ventilation-delay map. Regional-ventilation-delay inhomogeneity that quantifies heterogeneity of ventilation time courses was evaluated by calculating the scatter of all pixel-wise calculated regional-ventilation-delay indices. End-expiratory and end-inspiratory computed tomography scans were performed at each positive end-expiratory pressure level to quantify tidal recruitment of the lung. Tidal recruitment showed a moderate inter-individual (r = .54; p < .05) and intra-individual linear correlation (r = .46 up to r = .73 and p < .05, respectively) with regional-ventilation-delay obtained from lung quadrants. Regional-ventilation-delay inhomogeneity was excellently correlated with tidal recruitment intra- (r = .90 up to r = .99 and p < .05, respectively) and inter-individually (r = .90; p < .001).

CONCLUSIONS

Regional-ventilation-delay can be noninvasively measured by electrical impedance tomography during a slow inflation of 12 mL/kg of body weight and visualized using ventilation delay maps. Our experimental data suggest that the impedance tomography-based analysis of regional-ventilation-delay inhomogeneity provides a good estimate of the amount of tidal recruitment and may be useful to individualize ventilatory settings.

Lung impedance measurements to monitor alveolar ventilation

PURPOSE OF REVIEW

Electrical impedance tomography (EIT) is an attractive method of monitoring patients during mechanical ventilation because it can provide a noninvasive continuous image of pulmonary impedance, which indicates the distribution of ventilation. This article will discuss ongoing research on EIT, with a focus on methodological aspects and limitations and novel approaches in terms of pathophysiology, diagnosis and therapeutic advancements.

RECENT FINDINGS

EIT enables the detection of regional distribution of alveolar ventilation and, thus, the quantification of local inhomogeneities in lung mechanics. By detecting recruitment and derecruitment, a positive end-expiratory pressure level at which tidal ventilation is relatively homogeneous in all lung regions can be defined. Additionally, different approaches to characterize the temporal local behaviour of lung tissue during ventilation have been proposed, which adds important information.

SUMMARY

There is growing evidence that supports EIT usage as a bedside measure to individually optimize ventilator settings in critically ill patients in order to prevent ventilator-induced lung injury. A standardization of current approaches to analyse and interpret EIT data is required in order to facilitate the clinical implementation.

Maximal hysteresis: a new method to set positive end-expiratory pressure in acute lung injury?

BACKGROUND

No methods are superior when setting positive end-expiratory pressure (PEEP) in acute lung injury (ALI). In ALI, the vertical distance (hysteresis) between the inspiratory and expiratory limbs of a static pressure-volume (PV) loop mainly indicates lung recruitment. We hypothesized that PEEP set at the pressure where hysteresis is 90% of its maximum (90%MH) would give similar oxygenation, but less cardiovascular depression than PEEP set at the pressure at lower inflection point (LIP) on the inspiratory limb or at the point of maximal curvature (PMC) on the expiratory limb in ALI.

METHODS

In 12 mechanically ventilated pigs, ALI was induced in a randomized fashion by lung lavage, lung lavage plus injurious ventilation, or by oleic acid. From a static PV loop obtained by an interrupted low-flow method, the pressures at LIP [25 (25, 25) cmH(2)O, mean and 25, 75 percentiles], at PMC [24 (20, 24) cmH(2)O], and at 90% MH [19 (18, 19) cmH(2)O] were determined and used for the PEEP-settings. We measured lung inflation (by computed tomography), end-expiratory lung volume (EELV), airway pressures, compliance of the respiratory system (Crs), blood gases, cardiac output and arterial blood pressure.

RESULTS

There were no differences between the PEEP settings in EELV or oxygenation, but the 90%MH setting gave lower end-inspiratory pause pressure (P<0.025), higher Crs (P<0.025), less hyper-aeration (P<0.025) and better maintained hemodynamics.

CONCLUSION

In this porcine lung injury model, PEEP set at 90% MH gave better lung mechanics and hemodynamics, than PEEP set at PMC or LIP.

Monitoring the mechanically ventilated patient

In the intensive care setting, monitored data relevant to the output, efficiency, and reserve of the respiratory system alert the clinician to sudden untoward events, aid in diagnosis, help guide management decisions, aid in determining prognosis, and enable the assessment of therapeutic response. This review addresses those aspects of monitoring we find of most value in the care of patients receiving ventilatory support. We concentrate on those modalities and variables that are routinely available or easily calculated from data readily collected at the bedside.

Using pressure-volume curves to set proper PEEP in acute lung injury

The evolution of respiratory care on patients with acute respiratory distress syndrome (ARDS) has been focused on preventing the deleterious effects of mechanical ventilation, termed ventilator-induced lung injury (VILI). Currently, reduced tidal volume is the standard of ventilatory care for patients with ARDS. The current focus, however, has shifted to the proper setting of positive end-expiratory pressure (PEEP). The whole lung pressure-volume (P/V) curve has been used to individualize setting proper PEEP in patients with ARDS, although the physiologic interpretation of the curve remains under debate. The purpose of this review is to present the pros and cons of using P/V curves to set PEEP in patients with ARDS. A systematic analysis of recent and relevant literature was conducted. It has been hypothesized that proper PEEP can be determined by identifying P/V curve inflection points. Acquiring a dynamic curve presents the key to the curve's bedside application. The lower inflection point of the inflation limb has been shown to be the point of massive alveolar recruitment and therefore an option for setting PEEP. However, it is becoming widely accepted that the upper inflection point (UIP) of the deflation limb of the P/V curve represents the point of optimal PEEP. New methods used to identify optimal PEEP, including tomography and active compliance measurements, are currently being investigated. In conclusion, we believe that the most promising method for determining proper PEEP settings is use of the UIP of the deflation limb. However, tomography and dynamic compliance may offer superior bedside availability.

Reproducibility of regional lung ventilation distribution determined by electrical impedance tomography during mechanical ventilation

Electrical impedance tomography (EIT) has the potential to become a new tool for bedside monitoring of regional lung ventilation. The aim of our study was to assess the reproducibility of regional lung ventilation distribution determined by EIT during mechanical ventilation under identical ventilator settings. The experiments were performed on 10 anaesthetized supine pigs ventilated in a volume-controlled mode. EIT measurements were performed with the Goe-MF II device (Viasys Healthcare, Höchberg, Germany) during repeated changes in positive end-expiratory pressure (PEEP) from 0 to 10 cm H2O. Regional lung ventilation was determined in the right and left hemithorax as well as in 64 regions of interest evenly distributed over each chest side in the ventrodorsal direction. Ventilation distributions in both lungs were visualized as ventrodorsal ventilation profiles and shifts in ventilation distribution quantified in terms of centres of ventilation in relation to the chest diameter. The proportion of the right lung on total ventilation in the chest cross-section was 0.54+/-0.04 and remained unaffected by repetitive PEEP changes. Initial PEEP increase resulted in a redistribution of ventilation towards dorsal lung regions with a shift of the centre of ventilation from 45+/-3% to 49+/-3% of the chest diameter in the right and from 47+/-2% to 50+/-2% in the left hemithorax. Excellent reproducibility of the results in the individual regions of interest with almost identical patterns of ventilation distribution was found during repeated PEEP changes.

[Mechanical ventilation induced lung injury]

Mechanical ventilation is associated with important complications, among which production or perpetuation of acute lung injury and product of distant organ injuries of the lung basically through the release of inflammatory mediators to the systemic circulation. There is increasingly greater evidence in both in vitro and in vivo experimental models that show the reality of this lesional mechanism. The main lesional mechanisms are both stretching and rupture of the lung structures (volutrauma) and cyclical opening and closure of the closed alveolar zones (atelectrauma). Studies on the use of protective lung ventilation strategies have shown a beneficial effect in patients with ARDS of the use of open lung ventilation strategies, use of circulating volumes less than 10 ml/kg and of maintaining alveolar pressure under 30 cm of H2O. It should be investigated if these same strategies would be useful in preventing the appearance of ARDS in mechanically ventilated patients for another reason, basically in those with risk factors for the development of this condition.

Comparative study of four sigmoid models of pressure-volume curve in acute lung injury

Background

The pressure-volume curve of the respiratory system is a tool to monitor and set mechanical ventilation in acute lung injury. Mathematical models of the static pressure-volume curve of the respiratory system have been proposed to overcome the inter- and intra-observer variability derived from eye-fitting. However, different models have not been compared.

Methods

The goodness-of-fit and the values of derived parameters (upper asymptote, maximum compliance and points of maximum curvature) in four sigmoid models were compared, using pressure-volume data from 30 mechanically ventilated patients during the early phase of acute lung injury.

Results

All models showed an excellent goodness-of-fit (R² always above 0.92). There were significant differences between the models in the parameters derived from the inspiratory limb, but not in those derived from the expiratory limb of the curve. The within-case standard deviations of the pressures at the points of maximum curvature ranged from 2.33 to 6.08 cmH₂O.

Conclusion

There are substantial variabilities in relevant parameters obtained from the four different models of the static pressure-volume curve of the respiratory system.