Computationally-Optimized Ventilation in the Prehospital and Hospital Setting
Abstract
The goal of this research project was to develop computationally-directed time-controlled adaptive ventilation (CD-TCAV), which automatically adjusts expiratory duration (Tlow) to reduce the injurious processes of cyclic recruitment / derecruitment (R/D). We hypothesize that a computational lung model may direct CD-TCAV settings for enhanced and personalized mechanical protection. To test this hypothesis, we simulated ARDS in a computational lung model using a random distribution of inflation-dependent surface tensions, to mimic the R/D associated with ARDS. Acinar recruitment within a subtree of the model decreased with increasing Tlow, and was much more pronounced at lower inspiratory pressures. There were expiratory durations for which decreasing Tlow offered no further benefit in terms of acinar recruitment. Estimates of global elastance of the subtree were highly correlated with the percentage of acinar derecruitment. We also modified a ZOLL EMV+(registered trademark) 731 transport ventilator to deliver a variant of CD-TCAV to a mechanical test load, with varying airway pressure levels as well as inspiratory and expiratory durations. We expect that the EMV+(registered trademark) 731 ventilator will be ready to deliver CD-TCAV in pigs with lung injury during the upcoming year. Preliminary results from these studies demonstrate that CD-TCAV will have a high likelihood of yielding a new, viable mode of ventilation for use in both military and civilian populations with ARDS.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2021
- Accession Number
- AD1161311
Entities
People
- A. Fonseca Cruz
- David W. Kaczka
- Gary F Nieman
- Jacob Herrmann
Organizations
- State University of New York