AUTHOR=Kollisch-Singule Michaela , Cruz Andrea F. , Herrmann Jacob , Satalin Joshua , Satalin Sarah , Harvey Brian P. , LeCroy Dorian , Beck George , Lutz Mark , Charlamb Jacob , Kenna Joshua , Baker Mark , Nieman Gary F. , Kaczka David W. 

TITLE=Computationally-directed mechanical ventilation in a porcine model of ARDS

JOURNAL=Frontiers in Physiology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2025.1602578

DOI=10.3389/fphys.2025.1602578

ISSN=1664-042X

ABSTRACT=BackgroundDespite the implementation of protective mechanical ventilation, ventilator-induced lung injury remains a significant driver of ARDS-associated morbidity and mortality. Mechanical ventilation must be personalized and adaptive for the patient and evolving disease course to achieve sustained improvements in patient outcomes. In this study, we modified a military-grade transport ventilator to deliver the airway pressure release ventilation (APRV) modality. We developed a computationally-directed (CD) method of adjusting the expiratory duration (TLow) during APRV using physiologic feedback to reduce alveolar derecruitment and tested this modality in a porcine model of moderate-to-severe ARDS.MethodsFemale Yorkshire-cross pigs (n = 27) were ventilated using a ZOLL EMV+® 731 Series ventilator during general anesthesia and subjected to a heterogeneous Tween lung injury followed by injurious mechanical ventilation. Animals were subsequently ventilated for 6 hours under general anesthesia after randomization to one of three groups: VT6 (n = 9) with a tidal volume (VT) of 6 mL/kg and stepwise adjustments in PEEP and FiO2; VT10 (n = 9) with VT of 10 mL/kg and PEEP of 5 cmH2O; CD-APRV group (n = 9) with computationally-directed adjustments in TLow based on a nonlinear equation of motion to describe respiratory mechanics. Results are reported as median [interquartile range].ResultsAll groups developed moderate-to-severe ARDS and had similar recovery in lung injury, with all demonstrating final PaO2:FiO2 > 300 mmHg (VT6: 415.5 [383.0–443.4], VT10: 353.3 [297.3–397.7], CD-APRV: 316.6 [269.8–362.4]; p = 0.12). PaCO2 was significantly higher in the VT6 group compared with the CD-APRV group (59.3 [52.3–60.1] mmHg vs. 38.5 [32.7–52.2] mmHg, p = 0.04) but not significantly different from the VT10 group (47.5 [45.3–54.4] mmHg; p = 0.32 vs. VT6) despite having a significantly higher respiratory rate (30.0 [30.0–32.0] breaths/min) compared with VT10 (12.0 [12.0–15.0] breaths/min, p = 0.001) and CD-APRV (14.0 [14.0–14.0] breaths/min, p < 0.001) groups at the study end.ConclusionWe successfully implemented a computationally directed APRV modality on a transport ventilator, adjusting TLow based on respiratory mechanics. This study demonstrated that CD-APRV can be safely used, with the advantage of guiding expiratory duration adjustments based on physiologic feedback from the lungs.