Breath analysis for detection and trajectory monitoring of acute respiratory distress syndrome in swine

Abstract

Despite the enormous impact on human health, acute respiratory distress syndrome (ARDS) is ill-defined, and its timely diagnosis is difficult, as is tracking the course of the syndrome. The objective of this pilot study was to explore the utility of breath collection and analysis methodologies to detect ARDS through changes in the volatile organic compound (VOC) profiles present in breath. Five male Yorkshire mix swine were studied and ARDS was induced utilising both direct and indirect lung injury. An automated portable gas chromatography device developed in-house was used for point of care breath analysis and to monitor swine breath hourly, starting from the initiation of the experiment until the development of ARDS, which was adjudicated based on the Berlin criteria at the breath sampling points and confirmed by lung biopsy at the end of the experiment. A total of 67 breath samples (chromatograms) were collected and analyzed. Through machine learning, principal component analysis, and linear discrimination analysis, seven VOCs biomarkers were identified that distinguished ARDS. These represent seven of the nine biomarkers found in our breath analysis study of human ARDS corroborating our findings. We also demonstrated that breath analysis detects changes 1–6 h earlier than the clinical adjudication based on the Berlin criteria. The findings provide proof of concept that breath analysis can be used for the identification of early changes associated with ARDS pathogenesis in swine. Its clinical application could provide intensive care clinicians with a non-invasive diagnostic tool for early detection and continuous monitoring of ARDS.