Biomechanics and Modeling in Mechanobiology

, Volume 17, Issue 2, pp 465–477 | Cite as

Simulation of the human airways using virtual topology tools and meshing optimization

  • A. Fernández-Tena
  • A. C. Marcos
  • R. Agujetas
  • C. FerreraEmail author
Original Paper


A method is proposed to improve the quality of the three-dimensional airway geometric models using a commercial software, checking the number of elements, meshing time, and aspect ratio and skewness parameters. The use of real and virtual topologies combined with patch-conforming and patch-independent meshing algorithms results in four different models being the best solution the combination of virtual topology and patch-independent algorithm, due to an excellent aspect ratio and skewness of the elements, and minimum meshing time. The result is a reduction in the computational time required for both meshing and simulation due to a smaller number of cells. The use of virtual topologies combined with patch-independent meshing algorithms could be extended in bioengineering because the geometries handling is similar to this case. The method is applied to a healthy person using their computed tomography images. The resulting numerical models are able to simulate correctly a forced spirometry.


Human airways CT images CFD Virtual topology Meshing optimization 



Thanks to Dr. Alejo, Servicio Radiología (Hospital IC, Badajoz), who provided the images of this study. This work was financially supported by Junta de Extremadura under Project “Ayudas para la realización de actividades de investigación y desarrollo tecnológico, de divulgación y de transferencia de conocimiento por los Grupos de Investigación de Extremadura (GR150014)” and Sociedad Asturiana de Patología Respiratoria under project Experimental and numerical study of a three-dimensional model of an asthmatic patient airways reconstructed from CT or MR images.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. 3D Slicer V4.4.0 (2014).
  2. Agujetas R, Ferrera C, Marcos AC, Alejo JP, Montanero JM (2017) Numerical and experimental analysis of the transitional flow across a real stenosis. Biomech Model Mechanobiol 16(4):1447–1458.
  3. Ansys version 16.2 (2015) ANSYS IncGoogle Scholar
  4. Ashurst I, Malton A, Prime D, Sumby B (2000) Latest advances in the development of dry powder inhalers. Pharm Sci Technol Today 3:246–256CrossRefGoogle Scholar
  5. Choi L (2007) Simulation of fluid dynamics and particle transport in realistic human airways. Master’s thesis, School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Melbourne, AustraliaGoogle Scholar
  6. De Backer JW, Vos WG, Devolder A, Verhulst SL, Germonpré P, Wuyts FL, Parizel PM, De Backer W (2008) Computational fluid dynamics can detect changes in airway resistance in asthmatics after acute bronchodilation. J Biomech 41:106–113CrossRefGoogle Scholar
  7. De Backer JW, Vos WG, Vinchurkar SC, Claes R, Drollmann A, Wulfrank D, Parizel PM, Germonpré P, De Backer W (2010) Validation of computational fluid dynamics in CT-based airway models with SPECT/CT. Radiology 257:854–862CrossRefGoogle Scholar
  8. De Backer LA, Vos W, De Backer J, Van Holsbeke C, Vinchurkar S, De Backer W (2012) The acute effect of budesonide/formoterol in COPD: a multi-slice computed tomography and lung function study. Eur Respir J 40:298–305CrossRefGoogle Scholar
  9. Dyedov V, Einstein DR, Jiao X, Kuprat AP, Carson JP, Pin F (2009) Variational generation of prismatic boundary-layer meshes for biomedical computing. Int J Numer Meth Eng 79:907–945MathSciNetCrossRefzbMATHGoogle Scholar
  10. Fedorov A et al (2012) 3D slicer as an image computing platform for the quantitative imaging network. Magn Reson Imag 30:1323–1341CrossRefGoogle Scholar
  11. Fernández-Tena A (2014) Clinical applications of fluid dynamics models in respiratory disease. Ph.D. thesis, University of Oviedo, Spain.
  12. Fernández-Tena A, Casan Clarà P (2015) Use of computational fluid dynamics in respiratory medicine. Arch Bronconeumol 2015(51):293–298Google Scholar
  13. Fernández-Tena A, Fernández J, Casan P (2016) Particle deposition in healthy and bronchoconstricted lung. Eur Respir J 48(60):PA4402Google Scholar
  14. Fernández-Tena A, Fernández J, Álvarez E, Casan P, Walters K (2017a) Design of a numerical model of lung by means of a special boundary condition in the truncated branches. Int J Numer Methods Biomed Eng 33(6):e2830MathSciNetCrossRefGoogle Scholar
  15. Fernández-Tena A, Marcos AC, Martínez C, Walters DK (2017b) A new adaptive time step method for unsteady flow simulations in a human lung. Comput Methods Biomech Biomed Eng 20(8):915–917CrossRefGoogle Scholar
  16. Foucault G, Cuilliére JC, Francoise V, Leon JC, Maranzana R (2007) Adaptation of cad model topology for finite element analysis. Comput Aided Des 40:176–196CrossRefGoogle Scholar
  17. Gibson GJ, Loddenkemper R, Sibille Y, Lundbäck B, Fletcher M (2013) Lung health in europe: facts and figures. European Lung Foundation, SheffeldGoogle Scholar
  18. Hofmann W, Martonen TB, Graham RC (1989) Predicted deposition of nonhygroscopic aerosols in the human lung as a function of subject age. J Aerosol Med 1989(2):49–68CrossRefGoogle Scholar
  19. Hörschler I, Meinke M, Schröder W (2003) Numerical simulation of the flow field in a model of the nasal cavity. Comput Fluids 32:39–45CrossRefzbMATHGoogle Scholar
  20. Hounsfield GN (1973) Computerized transverse axial scanning (tomography): part I. Description of system. Br J Radiol 46:1016–1022CrossRefGoogle Scholar
  21. Inthavong K, Choi L, Tu J, Ding S, Thien F (2010) Micron particle deposition in a tracheobronchial airway model under different breathing conditions. Med Eng Phys 32:1198–1212CrossRefGoogle Scholar
  22. Islam MS, Saha SC, Sauret E, Gu Y, Ristovski Z (2015) Numerical investigation of aerosol particle transport and deposition in realistic lung airway. In: Liu GR, Das R (eds) The 6th international conference on computational methods (ICCM2015), ICCM. Scientech Publisher llc, USA, Auckland, New ZealandGoogle Scholar
  23. Jahangiri M, Saghafian M, Sadeghi MR (2015) Numerical study of turbulent pulsatile blood flow through stenosed artery using fluid–solid interaction. Comput Math Methods Med 2015:515613CrossRefzbMATHGoogle Scholar
  24. Kannan R, Guo P, Przekwas A (2016) Particle transport in the human respiratory tract: formulation of a nodal inverse distance weighted Eulerian–Lagrangian transport and implementation of the Wind–Kessel algorithm for an oral delivery. Int J Numer Meth Biomed Eng 32(6).
  25. Kannan R, Singh N, Przekwas A, Delvadia R, Tian G, Walenga R (2017a) Pharmaceutical aerosols deposition patterns from a dry powder inhaler: Euler Lagrangian prediction and validation. Med Eng Phys 42:35–47CrossRefGoogle Scholar
  26. Kannan R, Chen ZJ, Singh N, Przekwas A, Delvadia R, Tian G, Walenga R (2017b) A quasi-3D wire approach to model pulmonary airflow in human airways. Int J Numer Methods Biomed Eng 33(7):e2838CrossRefGoogle Scholar
  27. Kitaoka H, Takaki R, Suki B (1999) A three-dimensional model of the human airway tree. J Appl Physiol 87(6):2207–2217CrossRefGoogle Scholar
  28. Kleinstreuer C (2006) Biofluid dynamics: principles and selected applications. CRC Press, Boca RatonCrossRefGoogle Scholar
  29. Kleinstreuer C, Zhang Z, Donohue JF (2008) Targeted drug-aerosol delivery in the human respiratory system. Annu Rev Biomed Eng 10:195–220CrossRefGoogle Scholar
  30. Kolanjiyil AV, Kleinstreuer C, Sadikot RT (2017) Computationally efficient analysis of particle transport and deposition in a human whole-lung-airway model. Part II: dry powder inhaler application. Comput Biol Med 84:247–253CrossRefGoogle Scholar
  31. Lin C, Tawhai MH, Merryn H, McLennan G, Hoffman EA (2007) Characteristics of the turbulent laryngeal jet and its effect on airflow in the human intra-thoracic airways. Respir Physiol Neurobiol 157:295–309CrossRefGoogle Scholar
  32. Lip K, Philip C (2015) Pharmaceutical aerosol electrostatics: a field with much potential for development. Ther Deliv 6:105–107CrossRefGoogle Scholar
  33. Marchandise E, Geuzaine C, Remacle JF (2013) Cardiovascular and lung mesh generation based on centerlines. Int J Numer Method Biomed Eng 2013(29):665–682CrossRefGoogle Scholar
  34. Menter F, Langtry R, Völker S (2006) Transition modelling for general purpose CFD codes. Flow Turbul Combust 77:277–303CrossRefzbMATHGoogle Scholar
  35. Miller MR, Hankinson JATS, Brusasco V, Burgos F, Casaburi R, Coates A, Crapo R, Enright P, Van der Grinten CP, Gustafsson P et al (2005) Standardisation of spirometry. Eur respir J 26(2):319–338CrossRefGoogle Scholar
  36. Miyawaki S, Tawhai MH, Hoffman EA, Wenzel SE, Lin CL (2017) Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface. Biomech Model Mechanobiol 16:583–596CrossRefGoogle Scholar
  37. Nahar K, Gupta N, Gauvin R, Absar S, Patel B, Gupta V, Khademhosseini A, Ahsan F (2013) In vitro, in vivo and ex vivo models for studying particle deposition and drug absorption of inhaled pharmaceuticals. Eur J Phar Sci 49:805–818CrossRefGoogle Scholar
  38. OECD/UE (2016) Health at a glance: Europe 2016. state of health in the EU cycle. Technical report OECD/UEGoogle Scholar
  39. Przywara B (2010) Projecting future health care expenditure at European level: drivers, methodology and main result. European Commission, Economic and Financial Affairs Publications, BrusselsGoogle Scholar
  40. Rochefort L, Vial L, Fodil R, Mâıtre X, Louis B, Isabey D, Caillibotte G, Thiriet M, Bittoun J, Durand E, Sbirlea-Apiou G (2007) In vitro validation of computational fluid dynamic simulation in human proximal airways with hyperpolarized 3 He magnetic resonance phase-contrast velocimetry. J Appl Physiol 102:2012–2023CrossRefGoogle Scholar
  41. Sbirlea-Apiou G, Katz I, Caillibotte G, Martonen T, Yang Y (2007) Deposition mechanics of pharmaceutical particles in human airways. In: Hickey AJ (ed) Inhalation aerosols. Physical and biological basis for therapy, 2nd edn. Informa Healthcare USA, New York, pp 1–30Google Scholar
  42. Scotti A, Piomelli U (2002) Turbulence models in pulsating flows. AIAA 40:537–544CrossRefGoogle Scholar
  43. Stahlhofen W, Rudolf G, James AC (1989) Intercomparison of experimental regional aerosol deposition data. J Aerosol Med 1989(2):285–308CrossRefGoogle Scholar
  44. Streinbenner JP, Wyman NJ, Chawner JR (2000) Fast surface meshing on imperfect cad models. In: 9th international meshing roundtable, Sandia National Laboratories, New Orleans, USA, pp 33–41Google Scholar
  45. Taherian S, Rahai HR, Waddington T (2011) CFD modelling and analysis of pulmonary airways/particles transport and deposition. In: 41st AIAA fluid dynamics conference and exhibit, American Institute of Aeronautics and Astronautics. American Institute of Aeronautics and Astronautics, Honolulu, USA, pp 2011–3270Google Scholar
  46. Tan FPP, Wood NB, Tabor G, Xu XY (2011) Comparison of LES of steady transitional flow in an idealized stenosed axisymmetric artery model with a RANS transitional model. J Biomech Eng 133:051001CrossRefGoogle Scholar
  47. Varghese SS, Frankel SH, Fischer PF (2007a) Direct numerical simulation of stenotic flows. Part 1. Steady flow. J Fluid Mech 582:253MathSciNetCrossRefzbMATHGoogle Scholar
  48. Varghese SS, Frankel SH, Fischer PF (2007b) Direct numerical simulation of stenotic flows. Part 2. Pulsatile flow. J Fluid Mech 582:281MathSciNetCrossRefzbMATHGoogle Scholar
  49. Varghese SS, Frankel SH, Fischer PF (2008) Modelling transition to turbulence in eccentric stenotic flows. J Biomech Eng 130:014503CrossRefGoogle Scholar
  50. Versteeg HK, Malalasekera W (2007) An Introduction to Computational Fluid Dynamics. Pearson Education Limited, EnglandGoogle Scholar
  51. Vos W, De Backer J, Poli G, De Volder A, Ghys L, Van Holsbeke C, Vinchurkar S, De Backer L, De Backer W (2013) Novel functional imaging of changes in small airways of patients treated with extrafine beclomethasone/formoterol. Respiration 86:393–401CrossRefGoogle Scholar
  52. Weibel ER (1963) Morphometry of the human lung. Academic, New YorkCrossRefGoogle Scholar
  53. Weibel ER (2009) What makes a good lung? The morphometric basis of lung function. Swiss Med Wkly 139:375–386Google Scholar
  54. Wilcox DC (2006) Turbulence modelling for CFD. DCW Industries, FlintridgeGoogle Scholar
  55. Zhang Y, Finlay WH (2005) Measurement of the effect of cartilaginous rings on particle deposition in a proximal lung bifurcation model. Aerosol Sci Technol 39:394–399CrossRefGoogle Scholar
  56. Zhang Z, Kleinstreuer C, Hyun S (2012) Size-change and deposition of conventional and composite cigarette smoke particles during inhalation in a subject-specific airway model. J Aerosol Sci 45:34–52CrossRefGoogle Scholar
  57. Zheng J (2014) Numerical simulation of nanoparticle transportation and deposition in pulmonary vasculature. Master’s thesis, Department of Mechanical Engineering and Mechanics, Lehigh University, Lehigh, USAGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Universidad de Oviedo and Hospital Universitario Central de AsturiasOviedoSpain
  2. 2.Dpto. de Expresión GráficaUniversidad de ExtremaduraBadajozSpain
  3. 3.Dpto. de Ingeniería Mecánica, Energética y de los Materiales and Instituto de Computación Científica Avanzada (ICCAEx)Universidad de ExtremaduraBadajozSpain

Personalised recommendations