Mechanical ventilation energy analysis: Recruitment focuses injurious power in the ventilated lung

Abstract

The progression of acute respiratory distress syndrome (ARDS) from its onset due to disease or trauma to either recovery or death is poorly understood. Currently, there are no generally accepted treatments aside from supportive care using mechanical ventilation. However, this can lead to ventilator-induced lung injury (VILI), which contributes to a 30 to 40% mortality rate. In this study, we develop and demonstrate a technique to quantify forms of energy transport and dissipation during mechanical ventilation to directly evaluate their relationship to VILI. A porcine ARDS model was used, with ventilation parameters independently controlling lung overdistension and alveolar/airway recruitment/derecruitment (RD). Hourly measurements of airflow, tracheal and esophageal pressures, respiratory system impedance, and oxygen transport were taken for six hours following lung injury to track energy transfer and lung function. The final degree of injury was assessed histologically. Total and dissipated energies were quantified from lung pressure-volume relationships and subdivided into contributions from airflow, tissue viscoelasticity, and RD. Only RD correlated with physiologic recovery. Despite accounting for a very small fraction (2 to 5%) of the total energy dissipation, RD is damaging because it occurs quickly over a very small area. We estimate power intensity of RD energy dissipation to be 100 W/m², equivalent to 10% of the Sun's luminance at the Earth's surface. Minimizing repetitive RD events may thus be crucial for mitigating VILI.

Keywords: ARDS; energy dissipation; power; ventilator-induced lung injury.

Fig. 1.

Components of energy dissipation. (A) Airflow. (B) Tissue stretching and air–liquid interfacial deformation, including surfactant transport. (C) Recruitment of airways and alveoli, where energy is dissipated through viscous interactions as airway walls peel apart to overcome adhesive surface tension forces that hold walls in apposition.

Fig. 2.

Schematic of a pressure–volume loop, with P_tp in blue outline and the tissue pressure P_tissue in green outline. The subareas of these loops quantify the energy dissipation from airflow (D_airflow = white), tissue level (D_tissue = blue hashed), and recruitment (D_recruit = red hashed).

Fig. 3.

Physiological measurements and their relationship to ventilation scenarios. Pulmonary mechanics assessed by normalized compliance (nC_RS) vs (A) time (T0–T6) and (B) treatment (T1–T6). Oxygenation was assessed by PaO₂/FiO₂ ratio vs (C) time (T0–T6), and (D) treatment (T1–T6). Histology represented for PaO₂/FiO₂ representative of (E) OD−RD−, and (F) OD+RD+. Time-course data (A and C) are represented as mean ± SEM for each time point. Treatment-based representation (B and D) symbols represent T1–T6 time-point means with error bars as treatment mean ± SEM. Each data point represents n =10 for OD−RD−, n = 7 for OD−RD+, n = 9 for OD+RD−, and n = 9 for OD+RD+ experimental subjects. ns = P > 0.05, *P ≤ 0.05, **P ≤ 0.01. Those not defined are all P ≤ 0.0001. Fig. 3 A and C reproduced with permission (22).

Fig. 4.

(A) Input work vs time. (B) Total energy dissipation ($D_{\mathit{total}}$) vs time. Data are presented as mean ± SEM. Other statistics are described in Fig. 6.

Fig. 5.

Dissipation components vs time. (A) Airflow dissipation (D_airflow), (B) tissue/surfactant dissipation (D_tissue), and (C) recruitment dissipation (D_recruit). Data are presented as mean ± SEM. Additional statistics are described in Fig. 7.

Fig. 6.

Correlation analysis of physiological outcome to overall energy delivery and dissipation. Comparison of the treatment-based (A) PaO₂/FiO₂ physiological outcome (from Fig. 3D) to the (B) applied energy and (C) total energy dissipation from Fig. 4. The (D) physiological rank-order response demonstrates no correlation with the (E) applied energy and total energy dissipation rank-orders, indicating that these cannot be responsible for the physiological response. Symbols represent T1–T6 time-point means, and error bars represent treatment mean ± SEM. ns = P > 0.05, *P ≤ 0.05, **P ≤ 0.01. Those not defined are P ≤ 0.0001.

Fig. 7.

Correlation analysis of physiological outcome to energy dissipation components. Comparison of the (A) PaO₂/FiO₂ physiological outcome (from Fig. 3D) to the (B) airflow dissipation, (C) tissue energy dissipation, and (D) recruitment dissipation from Fig. 5, respectively. The (E) physiological rank-order response demonstrates that no correlation exists between the (F) rank order of airflow and tissue dissipation, indicating that these cannot be responsible for the physiological response. In contrast, the (E) physiological rank-order correlates with the rank order of (G) recruitment dissipation, indicating that recruitment dissipation can be responsible for VILI. Symbols represent T1–T6 time-point means, and error bars represent treatment mean ± SEM. ns = P > 0.05, *P ≤ 0.05, **P ≤ 0.01. Those not defined are all P ≤ 0.0001.

Fig. 8.

Relationships between recruitment energy dissipation and physiological responses from T0 to T6 demonstrate recovery only for low levels of recruitment dissipation. Physiological responses [A–C: oxygenation (PaO₂/FiO₂) and D and E mechanics (nC_RS)] to recruitment energy dissipation D_Recruit. (A) Initial oxygenation is independent of the treatment modality; (B) T6 recovery of oxygenation demonstrates that recovery is dependent on D_Recruit; (C) Oxygen recovery for each treatment demonstrates recovery for low D_Recruit and continued injury for large D_Recruit. (D) Mechanics at T0 and T6 demonstrating compliance recovery is dependent on D_Recruit; (E) nC_RS recovery transition for each treatment demonstrates recovery for low D_Recruit and continued injury for large D_Recruit. Shaded regions represent 95% CI. Data in A, B, D, and E represent mean ± SD. Data in C and E represent mean values for T0–T6.

Fig. 9.

Experimental setup: The ARDS pig model is ventilated with APRV as respiratory system mechanics and physiological systems are monitored for six hours postinjury. Created with BioRender.com.

Fig. 10.

Respiratory system pressures. Created with BioRender.com

Fig. 11.

(A) Computational model description of compliance recovery during recruitment. The green curve describes the PV relationship for a completely recruited acinus during inflation (f = 1), and the red curve describes the PV relationship for an ARDS derecruited acinus ($f\sim 0$). With recruitment, f increases, and the PV relationship undergoes a dynamic transition toward a healthy acinus (black solid curve). The red hashed region reflects the energy dissipation from the transition in states. Reproduced with permission (53). (B) The inflation limb of an experimental PV loop from this study, with the location of the true inflection point and the region associated with recruitment indicated in red.