Cruces, PabloRetamal, JaimeDamián, AndrésLago, GracielaBlasina, FernandaOviedo, VanessaMedina, TaniaPérez, AgustínVaamonde, LucíaDapueto, RosinaGonzález-Dambrauskas, SebastianSerra, Alberto2024-09-092024-09-092024-12Intensive Care Medicine Experimental. Volume 12, Issue 1. December 2024 Article number 602197-425Xhttps://repositorio.unab.cl/handle/ria/59990Indexación: Scopus.Background: The spatiotemporal progression and patterns of tissue deformation in ventilator-induced lung injury (VILI) remain understudied. Our aim was to identify lung clusters based on their regional mechanical behavior over space and time in lungs subjected to VILI using machine-learning techniques. Results: Ten anesthetized pigs (27 ± 2 kg) were studied. Eight subjects were analyzed. End-inspiratory and end-expiratory lung computed tomography scans were performed at the beginning and after 12 h of one-hit VILI model. Regional image-based biomechanical analysis was used to determine end-expiratory aeration, tidal recruitment, and volumetric strain for both early and late stages. Clustering analysis was performed using principal component analysis and K-Means algorithms. We identified three different clusters of lung tissue: Stable, Recruitable Unstable, and Non-Recruitable Unstable. End-expiratory aeration, tidal recruitment, and volumetric strain were significantly different between clusters at early stage. At late stage, we found a step loss of end-expiratory aeration among clusters, lowest in Stable, followed by Unstable Recruitable, and highest in the Unstable Non-Recruitable cluster. Volumetric strain remaining unchanged in the Stable cluster, with slight increases in the Recruitable cluster, and strong reduction in the Unstable Non-Recruitable cluster. Conclusions: VILI is a regional and dynamic phenomenon. Using unbiased machine-learning techniques we can identify the coexistence of three functional lung tissue compartments with different spatiotemporal regional biomechanical behavior. © The Author(s) 2024.esComputed tomographyDiagnostic imagingLung strainMechanical ventilationVentilator-induced lung injuryArtículoAtribución/Reconocimiento 4.0 Internacional