• Maurizio Cereda, Yi Xin, Hooman Hamedani, Giacomo Bellani, Stephen Kadlecek, Justin Clapp, Luca Guerra, Natalie Meeder, Jennia Rajaei, Nicholas J Tustison, James C Gee, Brian P Kavanagh, and Rahim R Rizi.
• Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
• Thorax. 2017 Nov 1; 72 (11): 981-989.

BackgroundUncertain prediction of outcome in acute respiratory distress syndrome (ARDS) impedes individual patient management and clinical trial design.ObjectivesTo develop a radiological metric of injurious inflation derived from matched inspiratory and expiratory CT scans, calibrate it in a model of experimental lung injury, and test it in patients with ARDS.Methods73 anaesthetised rats (acid aspiration model) were ventilated (protective or non-protective) for up to 4 hours to generate a spectrum of lung injury. CT was performed (inspiratory and expiratory) at baseline each hour, paired inspiratory and expiratory images were superimposed and voxels tracked in sequential scans. In nine patients with ARDS, paired inspiratory and expiratory CT scans from the first intensive care unit week were analysed.ResultsIn experimental studies, regions of lung with unstable inflation (ie, partial or reversible airspace filling reflecting local strain) were the areas in which subsequent progression of injury was greatest in terms of progressive infiltrates (R=0.77) and impaired compliance (R=0.67, p<0.01). In patients with ARDS, a threshold fraction of tissue with unstable inflation was apparent: >28% in all patients who died and ≤28% in all who survived, whereas segregation of survivors versus non-survivors was not possible based on oxygenation or lung mechanics.ConclusionsA single set of superimposed inspiratory-expiratory CT scans may predict progression of lung injury and outcome in ARDS; if these preliminary results are validated, this could facilitate clinical trial recruitment and individualised care.© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

31 keywords...

hide…