Validation of airway resistance models for predicting pressure loss through anatomically realistic conducting airway replicas of adults and children

J Biomech. 2015 Jul 16;48(10):1988-96. doi: 10.1016/j.jbiomech.2015.03.035. Epub 2015 Apr 7.

Abstract

This work describes in vitro measurement of the total pressure loss at varying flow rate through anatomically realistic conducting airway replicas of 10 children, 4 to 8 years old, and 5 adults. Experimental results were compared with analytical predictions made using published airway resistance models. For the adult replicas, the model proposed by van Ertbruggen et al. (2005. J. Appl. Physiol. 98, 970-980) most accurately predicted central conducting airway resistance for inspiratory flow rates ranging from 15 to 90 L/min. Models proposed by Pedley et al. (1970. J. Respir. Physiol. 9, 371-386) and by Katz et al. (2011. J. Biomech. 44, 1137-1143) also provided reasonable estimates, but with a tendency to over predict measured pressure loss for both models. For child replicas, the Pedley and Katz models both provided good estimation of measured pressure loss at flow rates representative of resting tidal breathing, but under predicted measured values at high inspiratory flow rate (60 L/min). The van Ertbruggen model, developed based on flow simulations performed in an adult airway model, tended to under predict measured pressure loss through the child replicas across the range of flow rates studied (2 to 60 L/min). These results are intended to provide guidance for selection of analytical pressure loss models for use in predicting airway resistance and ventilation distribution in adults and children.

Keywords: Airway resistance; Conducting airways; Pressure drop; Pressure loss; Ventilation distribution.

Publication types

  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Aged, 80 and over
  • Airway Resistance*
  • Child
  • Child, Preschool
  • Female
  • Humans
  • Inhalation / physiology
  • Male
  • Middle Aged
  • Models, Anatomic*
  • Pressure*
  • Regression Analysis
  • Respiration
  • Respiratory System / anatomy & histology*