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Research Papers

Development of Characteristic Upper Tracheobronchial Airway Models for Testing Pharmaceutical Aerosol Delivery

[+] Author and Article Information
Ross L. Walenga

e-mail: walengarl@vcu.edu

Geng Tian

e-mail: tiang@mymail.vcu.edu
Department of Mechanical and
Nuclear Engineering,
Virginia Commonwealth University,
Richmond, VA 23284

P. Worth Longest

Department of Mechanical and
Nuclear Engineering,
Virginia Commonwealth University,
Richmond, VA 23284;
Department of Pharmaceutics,
Virginia Commonwealth University,
Richmond, VA 23284
e-mail: pwlongest@vcu.edu

See http://www.rddonline.com (accessed Nov. 15, 2012).

See www.via.cornell.edu/databases/lungdb.html (accessed on Dec. 5, 2012).

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received January 8, 2013; final manuscript received April 24, 2013; accepted manuscript posted May 23, 2013; published online July 10, 2013. Assoc. Editor: Ender A. Finol.

J Biomech Eng 135(9), 091010 (Jul 10, 2013) (18 pages) Paper No: BIO-13-1011; doi: 10.1115/1.4024630 History: Received January 08, 2013; Revised April 24, 2013; Accepted May 23, 2013

Characteristic models of the upper conducting airways are needed to evaluate the performance of existing pharmaceutical inhalers and to develop new respiratory drug delivery strategies. Previous studies have focused on the development of characteristic mouth–throat (MT) geometries for orally inhaled products; however, characteristic upper tracheobronchial (TB) geometries are currently not available. In this study, a new characteristic model of the upper TB airways for an average adult male was developed based on an analysis of new and existing anatomical data. Validated computational fluid dynamics (CFD) simulations were used to evaluate the deposition of monodisperse and realistic polydisperse aerosols from multiple inhalers. Comparisons of deposition results between the new model and a simpler geometry were used to identify the effects of different anatomical features on aerosol deposition. The CFD simulations demonstrated a good match to regional pharmaceutical aerosol deposition from in vitro experiments in the same geometry. The deposition of both monodisperse and pharmaceutical aerosols was increased in the new TB geometry as a result of additional anatomical detail on a regional and highly localized basis. Tracheal features including an accurate coronal angle, asymmetry, and curvature produced a skewed laryngeal jet and significantly increased regional deposition. Branch curvature and realistic cross-sections increased deposition in the remainder of the TB model. A hexahedral mesh style was utilized to provide the best solution. In conclusion, a number of physiological features in the upper TB region were shown to influence deposition and should be included in a characteristic model of respiratory drug delivery.

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Figures

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Fig. 1

Surface geometries of (a) and (c) Model C compared with (b) and (d) Model D. Each airway was evaluated in combination with a metered dose inhaler (MDI) and dry powder inhaler (DPI). The cases evaluated were: (a) Model C with an MDI, (b) Model D with an MDI, (c) Model C with a DPI, and (d) Model D with a DPI.

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Fig. 7

Deposition fraction (DF) in the mouth-throat (MT) and tracheobronchial (TB) airways for the MDI used in (a) Model C and (b) Model D, and for the DPI used in (c) Model C and (d) Model D. Also shown at the five lobar outlets are the fractions remaining (FR) and the mass median aerodynamic diameter (MMAD) of the remaining aerosol.

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Fig. 6

Sagittal plane velocity contours with midplane vector fields, along with selected axial cross-sectional contours and streamlines, in (a) Model C and (b) Model D for the DPI

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Fig. 5

Sagittal plane velocity contours with midplane vector fields, along with selected axial cross-sectional contours and streamlines, in (a) Model C and (b) Model D for the MDI

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Fig. 4

CFD predictions of deposition fraction (DF) for polydisperse pharmaceutical aerosols in Model C with both the (a) DPI and (b) MDI as compared with existing experimental data in the same geometry. The experimentally determined polydisperse particle profiles for both the DPI and MDI are shown as figure inserts. The DPI profile was corrected for deposition in the preseparator based on additional CFD simulations.

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Fig. 3

Deposition efficiency (DE) of monodisperse aerosols in Model D using Zhou and Cheng [69] empirical formulations compared to CFD predictions at 30 L/min within different regions of the upper TB airways. The regions of interest are highlighted for each case.

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Fig. 2

Deposition efficiency (DE) of monodisperse aerosols in Model C using the Zhou and Cheng [69] empirical formulations compared to CFD predictions at 30 L/min within different regions of the upper TB airways. The regions of interest are highlighted for each case.

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Fig. 8

Regional deposition fraction (DF) in the TB airways through the third bifurcation (B3) for Model C and Model D with the (a) MDI and (b) DPI. Deposition in B2 and B3 represents the total DF among multiple bifurcations in the TB model.

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Fig. 9

Deposition enhancement factor (DEF) for the MDI used in (a) Model C and (b) Model D, and the DPI used in (c) Model C and (d) Model D

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Fig. 10

Deposition fraction (DF) in tetrahedral mesh as compared with hexahedral mesh results for the MDI used in (a) Model C and (b) Model D. Experimental values of DF are also included with Model C data based on identical inlet flow conditions.

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Fig. 11

Computation time for tetrahedral and hexahedral meshes of Model C and Model D with the MDI

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