Importance of airway geometry and respiratory parameters variability for particle deposition in the human respiratory tract
Importance of airway geometry and respiratory parameters variability for particle deposition in the human respiratory tract
Tomasz R Sosnowski
Professor, Head of “Biomedical Engineering and Products” Graduate Program, Faculty of Chemical and Process Engineering, Warsaw University of Technology, Warynskiego 1, 00-645 Warsaw, Poland.
Corresponding to:Tomasz R Sosnowski, PhD. Faculty of Chemical and Process Engineering , Warsaw University of Technology, Warynskiego 1, 00-645 Warsaw, Poland. Tel: +48-22-234-6278 ; Fax: +48-22-825-144. Email:
J Thorac Dis 2011;3:153-155. DOI: 10.3978/j.issn.2072-1439.2011.06.01
The quantitative estimation of particle deposition in the respiratory tract is the important practical step for prediction of potential health outcome of inhaled aerosols. Such knowledge is indispensable in assessing aerosol toxicology as well as in the optimization of the drug delivery to the lungs by inhalation (1-3).
This problem is complex since many factors simultaneously play a role in this process, resulting in a high variability of regional and total deposition efficiency. These most important factors can be listed as follows:
a) the respiratory tract geometry, which is highly variable with age or body size and health conditions
b) the breathing pattern, which depends on the age and health, but also on the momentary physical activity
c) aerosol properties (particle size, shape, density, hygroscopity, surface properties, etc).
Aerosol particles, depending on their size and mass, can be deposited in different parts of the respiratory system due to action of several physical mechanisms, where the inertial impaction, gravitational settling and Brownian diffusion are the predominant ones.
Several approaches are used to estimate quantitatively the aerosol deposition fractions in different regions of the respiratory tract. The recent concepts - which are still under development - employ the Computational Fluid Dynamics (CFD) to identify the air flow pattern and motion of aerosol particles in the human respiratory system (4). This technique is demanding both from conceptual and computer-power viewpoints. Providing that the regional geometry of the air passages can be implemented correctly in form of the numerical mesh, CFD allows for a very detailed flow analysis of inhaled aerosol particles in the network of the real airways. Any type of physiological situation can be potentially modeled with this computational approach, including diseased lungs, pediatric patients, etc. Anyway, the methodology is not straightforward and quite often simplifying assumptions are introduced into the models to obtain the results in the reasonable computational time and accuracy. For instance, CFD simulations for the respiratory system are typically simplified by assuming constant airflow rates (5-9), although such presumption is far from the reality. Recently, the more accurate simulations for the unsteady airflow patterns (i.e. the real-like breathing curves) has become available (10-12).
Another method used for the estimation of aerosol deposition in the human respiratory system employs semi-empirical models which were developed taking into account the averaged deposition data obtained in vivo and in vitro (13-15). In this method the information on the deposition in the whole lungs as well as in the selected regions of the respiratory system can be analyzed. The advantage of such approach is its mathematical lucidity, although the proposed equations certainly are lacking the universality as they do not address many of the significant factors indicated earlier.
In any method of quantitative prediction of aerosol deposition the important problem is their validation due to the large scatter of in vivo data (variability) observed among different subjects (16). In this issue of the Journal of Thoracic Disease, Hussain et al. discuss the problem of variability in the estimated regional deposition fractions of inhaled aerosol particles, which is caused by intersubject differences of extrathoracic (ET) dimensions and breathing patterns (17). The authors use selected models (13,14,19,20) to calculate the deposition efficiency in nasal and oral regions for variable airways dimensions taken from the literature (21,22), and then combine these results with the stochastic IDEAL model (23,24) which allows to determine the deposition fractions in each generation of the tracheobronchial tree. In effect, the authors are able to demonstrate that variability in ET geometry have a noticeable influence on the total and regional deposition fraction, both for oral and nasal breathing. Obviously, such deposition data are dependent on breathing regime, what is also demonstrated in the paper (breathing at rest vs. light exercise). Based on their computational results, the authors show that intersubject variability of the ET geometry is an important factor for the regional and total aerosol particle deposition in the respiratory tract. It is also concluded that some more general metrics of ET anatomy (e.g., the scaling factor: SF) can be appropriate for description of the intersubject deposition variability.
This interesting paper does not cover of course the full complexity of the problem which was stated in the beginning of this editorial. However, the presented results - according to the authors’ conclusion - may serve as a baseline to analyze more complicated cases in the future, e.g., for the lung pathology, when the intersubject deposition variability is expected to be much higher (the reasons for that are the different regional geometry of diseased lungs due to airways obstructions and highly variable airflow patterns - for some recent data on that issue see for example (25).
Readers of the paper by Hussain et al. will also take an additional advantage from the comprehensive presentation of the most common semi-empirical computational models that can be used for the estimation of aerosol deposition in the human respiratory system. This undoubtly helps to recognize the importance of different physical mechanisms in the deposition of inhaled aerosol particles with different sizes, but also – of the parametric sensitivity of the process under consideration. The awareness in this aspect seems to be essential in the designing the effective therapy of lung diseases by inhalation of aerosolized medicines.
  • Moskal A, Sosnowski TR, Gradoń L. Inhalation and deposition of nanoparticles: fundamentals, phenomenology and practical aspects. In: Marijnissen J, Gradoń L, editors. Nanoparticles in medicine and environment. Inhalation and health effects. Dordrecht:Springer;2010. p. 113-44.[LinkOut]
  • Newman S. Respiratory drug delivery. Essential theory and practice. Richmond, VA: RDD Online/VCU/Davis Healthcare Int. Publ; 2009.[LinkOut]
  • Kleinstreuer C, Zhang Z, Donohue JF. Targeted drug-aerosol delivery in the human respiratory system. Annu Rev Biomed Eng 2008;10:195–220.[LinkOut]
  • Rostami AA. Computational modeling of aerosol deposition in respiratory tract: a review. Inhal Toxicol 2009;21:262-90.[LinkOut]
  • Matida EA, Finlay WH, Lange CF, Grgic B. Improved numerical simulation of aerosol deposition in an idealized mouth–throat. J Aerosol Sci 2004;35:1–19.[LinkOut]
  • Zhang Z, Kleinstreuer C, Donohue JF, Kim CS. Comparison of micro- and nano-size particle depositions in a human upper airway model. J Aerosol Sci 2005;36:211–33.[LinkOut]
  • Longest PW, Vinchurkar S. Validating CFD predictions of respiratory aerosol deposition: Effects of upstream transition and turbulence. J Biomechanics 2007;40:305-16.[LinkOut]
  • Farkas A, Balashazy I. Quantification of particle deposition in asymmetrical tracheobronchial model geometry. Comput Biol Med 2008;38:508-18.[LinkOut]
  • Ma B, Lutchen KR. CFD Simulation of aerosol deposition in an anatomically based human large–medium airway model. Ann Biomed Eng 2009;37:271-85.[LinkOut]
  • Moskal A, Gradoń L. Temporary and spatial deposition of aerosol particles in the upper human airways during breathing cycle. J Aerosol Sci 2002;33:1525–39.[LinkOut]
  • Zhang Z, Kleinstreuer C, Kim CS. Cyclic micron-size particle inhalation and deposition in a triple bifurcation lung airway model. J Aerosol Sci 2002;33:257–81.[LinkOut]
  • Sosnowski TR, Moskal A, Gradoń L. Mechanims of aerosol particle deposition in the oro-pharynx under non-steady airflow. Ann Occup Hyg 2007;51:19–25.[LinkOut]
  • Annals of the ICRP 24. International Commission on Radiological Protection (ICRP) Publication 66, Human respiratory tract model for radiological protection. Oxford: Elsevier Science; 1994.[LinkOut]
  • National Council on Radiation Protection and Measurements (NCRP) Report No. 125: Deposition, retention, and dosimetry of inhaled radioactive substances. Bethesda, MD:NCRP. 1997.[LinkOut]
  • Finlay WH, Martin AE. Recent advances in predictive understanding of respiratory tract deposition. J Aerosol Med Pulm Drug Deliv 2008;21:189-206.[LinkOut]
  • Stahlhofen W, Rudolf G, James AC. Intercomparison of experimental regional aerosol deposition data. J Aerosol Med 1989;2:285–308.[LinkOut]
  • Hussain M, Renate W, Werner H. Effect of intersubject variability of extrathoracic morphometry, lung airways dimensions and respiratory parameters on particle deposition. J Thoracic Dis 2011;3:156-70.[LinkOut]
  • Martonen TB, Zhang Z, Yue G, Musante CJ. Fine particle deposition within human nasal airways. Inhal Toxicol 2003;15:283–303.[LinkOut]
  • Cheng YS. Aerosol deposition in the extrathoracic region. Aerosol Sci Technol 2003;37:659–71.[LinkOut]
  • Grgic B, Finlay WH, Burnell PKP, Heenan AF. In vitro intersubject and intrasubject deposition measurement in realistic mouth-throat geometries. J Aerosol Sci 2004;35:1025-40.[LinkOut]
  • Cheng KH, Cheng YS, Yeh HS, Raymond A, Guilmette, Steven Q, et al. In vivo measurement of nasal airway dimension and ultrafine aerosol deposition in the human nasal and oral airways. J Aerosol Sci 1996;5:785–801.[LinkOut]
  • Hofmann W, Bergmann R, Ménache MG. The effect of intersubject variability in airway morphology on intersubject variations in particle deposition. J Aerosol Sci 1998;29:S943–4.[LinkOut]
  • Koblinger L, Hofmann W. Monte Carlo modeling of aerosol deposition in human lungs: Part I: Simulation of particle transport in a stochastic lung structure. J Aerosol Sci 1990;21:661–74.[LinkOut]
  • Hofmann W, Koblinger L. Monte Carlo modeling of aerosol deposition in human lungs. Part II: Deposition fractions and their parameter variations. J Aerosol Sci 1990;21:675–88.[LinkOut]
  • Sosnowski TR, Zaniewska A, Kramek-Romanowska K. Experimental studies on particle deposition in obstructed bronchial bifurcations. In: Dalby RN, Byron PR, Peart J, Suman JD, Young PM, editors. Respiratory Drug Delivery Europe 2011, Vol 2. Richmond/River Groove: VCU/Davis Healthcare Publ. p. 543-6.[LinkOut]
Cite this article as: Sosnowski TR. Importance of airway geometry and respiratory parameters variability for particle deposition in the human respiratory tract. J Thorac Dis 2011;3(3):153-155. doi: 10.3978/j.issn.2072-1439.2011.06.01

Download Citation