Modeling of human conducting airways by stochastic parametric L-system
Department of Chemical and Petroleum Engineering, Sharif University of Technology, P. O. Box 11365-9465, Tehran, Iran
Accepted: 29 January 2021
Published online: 10 February 2021
Gas exchange, particle deposition, and drug delivery in the human lungs depend on the structure of the human bronchial tree. The conducting airways occupy the main portion of the human lungs and transport air from outside into pulmonary acini where the O2–CO2 exchange with blood occurs. Therefore, the generation of three-dimensional accurate structure of the conducting airways is required for simulation of the transport phenomena in the human respiratory system. The present study proposes an intelligent method for generation of conducting airways based on stochastic parametric Lindenmayer system (L-system). The conducting airways grow into the bronchopulmonary segments simultaneously using the multi-threads parallelism approach. The proposed Lindenmayer system contains several alphabetic rules which determine how an airway should be divided into two new airways (called the daughters) and when the expansion of the string representing the growth process should be stopped. Each module in the rules of parametric L-system represents an airway and the module parameters represent the geometrical characteristics of the airway (i.e., length, diameter, and orientation). These characteristics are stochastic and found almost independently using an intelligent method. Furthermore, the proposed method uses dimensionless parameters and age-dependent terminating criteria. These two features make the model applicable to the generation of the bronchial tree with various shapes and sizes. The morphometric properties of the generated structure are very close to their corresponding experimental counterparts obtained in anatomical studies. The ability of the proposed method is compared against the other available methods both quantitatively and qualitatively. This comparison shows that the proposed method outperforms them in accuracy, flexibility, and computational demands.
© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2021