Physiological interpretations based on lumped element models fit to respiratory impedance data: use of forward-inverse modeling

Respiratory impedance (Z _rs) data at lower (<4 Hz) and higher (>32 Hz) frequencies require more complicated inverse models than the standard series combination of a respiratory resistance, inertance, and compliance. A forward-inverse modeling approach was used to provide insight on how the parameters in these more complicated inverse models reflect the true physiological system. Forward models are set up to incorporate explicit physiological and anatomical detail. Simulated forward data are then fit with identifiable inverse models and the parameter estimates related to the known detail in the forward model. It is shown that inverse fitting of low-frequency data alone will not allow a distinction between frequency dependence due to airway inhomogeneities and frequency dependence due to tissue viscoelasticity. With higher frequency data, a forward model based on an asymmetric branching airways network was used to simulate Z _rs from 0.1-128 Hz with increasing amounts of nonuniform peripheral airway obstruction. Hence, inverse modeling is more amenable to sensibly separating estimates of airway and tissue properties.