title: Physiological relevance and performance of a minimal lung model: an experimental study in healthy and acute respiratory distress syndrome model piglets.
abstract: BACKGROUND
  Mechanical ventilation (MV) is the primary form of support for acute respiratory distress syndrome (ARDS) patients. However, intra- and inter- patient-variability reduce the efficacy of general protocols. Model-based approaches to guide MV can be patient-specific. A physiological relevant minimal model and its patient-specific performance are tested to see if it meets this objective above.
  
  
  METHODS
  Healthy anesthetized piglets weighing 24.0 kg [IQR: 21.0-29.6] underwent a step-wise PEEP increase manoeuvre from 5cmH2O to 20cmH2O. They were ventilated under volume control using Engström Care Station (Datex, General Electric, Finland), with pressure, flow and volume profiles recorded. ARDS was then induced using oleic acid. The data were analyzed with a Minimal Model that identifies patient-specific mean threshold opening and closing pressure (TOP and TCP), and standard deviation (SD) of these TOP and TCP distributions. The trial and use of data were approved by the Ethics Committee of the Medical Faculty of the University of Liege, Belgium.
  
  
  CONCLUSIONS
  3 of the 9 healthy piglets developed ARDS, and these data sets were included in this study. Model fitting error during inflation and deflation, in healthy or ARDS state is less than 5.0% across all subjects, indicating that the model captures the fundamental lung mechanics during PEEP increase. Mean TOP was 42.4cmH2O [IQR: 38.2-44.6] at PEEP = 5cmH2O and decreased with PEEP to 25.0cmH2O [IQR: 21.5-27.1] at PEEP = 20cmH2O. In contrast, TCP sees a reverse trend, increasing from 10.2cmH2O [IQR: 9.0-10.4] to 19.5cmH2O [IQR: 19.0-19.7]. Mean TOP increased from average 21.2-37.4cmH2O to 30.4-55.2cmH2O between healthy and ARDS subjects, reflecting the higher pressure required to recruit collapsed alveoli. Mean TCP was effectively unchanged.
  
  
  CONCLUSIONS
  The minimal model is capable of capturing physiologically relevant TOP, TCP and SD of both healthy and ARDS lungs. The model is able to track disease progression and the response to treatment.
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
authors.forename: Yeong Shiong
authors.initials: YS
authors.lastname: Chiew
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
authors.forename: Bernard
authors.initials: B
authors.lastname: Lambermont
authors.forename: Nathalie
authors.initials: N
authors.lastname: Janssen
authors.forename: Christoph
authors.initials: C
authors.lastname: Schranz
authors.forename: Knut
authors.initials: K
authors.lastname: Moeller
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Shaw
authors.forename: Thomas
authors.initials: T
authors.lastname: Desaive
mesh_terms: D000818:Animals; D004195:Disease Models, Animal; D018450:Disease Progression; D008168:Lung / Q000502:physiology* / Q000503:physiopathology*; D008954:Models, Biological; D019301:Oleic Acid / Q000009:adverse effects; D011175:Positive-Pressure Respiration; D012128:Respiratory Distress Syndrome / Q000139:chemically induced / Q000503:physiopathology*; D015656:Respiratory Mechanics / Q000502:physiology; D013552:Swine
chemical_list: D019301:Oleic Acid