Fast and Accurate Multiscale Reduced-Order Model for Prediction of Multibreath Washout Curves of Human Respiratory System

Abstract

The curve of exhaled inert gas concentration against exhaled volume is called gas washout curve. The slope at the end part of gas washout curve (Sₙ) is a measure of structural abnormalities. Sₙ depends on the spatial concentration distribution and dynamic of gas washout, which depends on several mechanisms including asymmetry of airways, nonhomogeneous ventilation, sequential emptying, and gas exchange with blood. Due to a large number of airways in human lungs, using simplified models is inevitable. On the other hand, these simplified models cannot capture some of the mentioned mechanisms and subsequently were not able to predict experimental trend of change in Sₙ with breath number in multibreath washout. The present study proposes a novel, accurate, and fast model of gas transport in human lungs, which can accurately predict this trend for the first time. The model consists of a proxy model of conducting airways and a reduced-order model of respiratory airways. A correlation is proposed for the estimation of model parameters, which are all functions of inert gas properties, ventilation, and structure of lung acini. The performance of the proposed model is validated in the prediction of Sₙ’s of various inert gases and lung clearance index. The obtained results show that the proposed model outperforms the previous ones based on both accuracy and required computational time. The effects of gas properties, functional residual capacity, and tidal volume on Sₙ are also investigated. The proposed model is fast where simulation of one breath nitrogen washout takes ∼0.18 s. Furthermore, it is flexible and can range from fully symmetric to detailed asymmetric airways.