Aeroszoldepozíciós légzőrendszeri modell fejlesztése

My dissertation begins with the introduction of the Stochastic Lung Model (SLM). This numerical model was purposed to model aerosol deposition mechanisms in the human respiratory system based on data of the individual and the inhaled aerosol (mainly the particle diameter). In the introduction I described the evolution of the model, and the history of the development of human airway deposition models in the literature. Section 2 shows the first results of my PhD research. For asthma and emphysema, we have intended to develop a tool for pulmonologists and drug manufacturers for the optimization of drug delivery to the lung to treat these diseases. The symmetric model described in section 3 takes a much shorter computational time but it can still be used with an acceptable accuracy (i.e., achieving results that are similar to other models), among other aims, to optimize the particle size mentioned above. Based on consultations with pulmonologist co-authors, I wrote the prototype-implementation to verify the new model and, indeed, this prototype has verified the expected accuracy. Finally, section 4 guides the Reader through the history of our clearance model of inhaled radon progenies. The section starts with the question: why does the highest chance of lung cancer development due to radon progenies happen in the large central airways? The chapter describes the details and applications of our clearance models to compare the radiation burdens originating from primary deposition and the cleared-up fractions as a function of bronchial airway generation number. The results clearly demonstrate that the cleared-up fractions result significantly higher burden in the large central airways than the primary deposition. Thus, the description of clearance is important at the interpretation of the related biological and health effects. Section 4 also points out to possible useful directions regarding future research work.