title: Airway area distribution from the forced expiration maneuver.
abstract: The maximal expiratory flow-volume (MEFV) maneuver is a commonly used test of lung function. More detailed interpretation than is currently available might be useful to understand disease better. We propose that a previously published computational model (Lambert RK, Wilson TA, Hyatt RE, and Rodarte JR. J Appl Physiol 52: 44-56, 1982) can be used to deduce, from the MEFV curve, the serial distribution of airway areas in the larger airways. An automated procedure based on the simulated annealing technique was developed. It was tested with model-generated flow data in which airway areas were reduced one generation at a time. The procedure accurately located the constriction and predicted its size within narrow bounds when the constriction was in the six most central generations of airways. More peripheral constrictions were detected but were not precisely located, nor were their sizes accurately evaluated. Airway areas of generations upstream of the constriction were usually overestimated. The procedure was applied to spirometric data obtained from eight volunteers (4 asthmatic and 4 normal subjects) at baseline and after methacholine challenge. The predicted areas show individual differences both in absolute values, and in relative distribution of areas. This result shows that detailed information can be obtained from the MEFV curve through the use of a model. However, this initial model, which lacks airway smooth muscle, needs further refinement.
authors.affiliation: Institute of Fundamental Sciences, Massey University, Palmerston North, New Zealand. r.lambert@massey.ac.nz
authors.forename: Rodney K
authors.initials: RK
authors.lastname: Lambert
authors.forename: Kenneth C
authors.initials: KC
authors.lastname: Beck
mesh_terms: D001249:Asthma / Q000503:physiopathology*; D003198:Computer Simulation; D045853:Exhalation / Q000502:physiology*; D005541:Forced Expiratory Volume / Q000502:physiology*; D006801:Humans; D008168:Lung / Q000502:physiology* / Q000503:physiopathology; D008954:Models, Biological