A three-dimensional model of the human airway tree

Kitaoka, Hiroko; Takaki, Ryuji; Suki, Bélâ

doi:10.1152/jappl.1999.87.6.2207

Cited by 250 publications

(218 citation statements)

References 25 publications

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“…One possibility is that the process is not precisely controlled, for example if branching occurs randomly to fill available space. Another is that control is precise but coding is simplified by repeated use of a branching mechanism, as in Mandelbrot's fractal model and other elegant algorithms [10][11][12][13][14][15][16][17] . Even with these attractive models and recent progress in identifying lung development genes 18 , understanding of the program that directs branching remains rudimentary.…”

Section: Introductionmentioning

confidence: 99%

The branching programme of mouse lung development

Metzger

Klein

Martin

et al. 2008

Nature

704

786

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Mammalian lungs are branched networks containing thousands to millions of airways arrayed in intricate patterns that are crucial for respiration. How such trees are generated during development, and how the developmental patterning information is encoded, have long fascinated biologists and mathematicians. However, models have been limited by a lack of information on the normal sequence and pattern of branching events. Here we present the complete three-dimensional branching pattern and lineage of the mouse bronchial tree, reconstructed from an analysis of hundreds of developmental intermediates. The branching process is remarkably stereotyped and elegant: the tree is generated by three geometrically simple local modes of branching used in three different orders throughout the lung. We propose that each mode of branching is controlled by a genetically-encoded subroutine, a series of local patterning and morphogenesis operations, which are themselves controlled by a more global master routine. We show that this hierarchical and modular program is genetically tractable, and it is ideally suited to encoding and evolving the complex networks of the lung and other branched organs.Many organs are composed of highly ramified tubular networks, each with a distinct architecture tailored to its physiological function. The bronchial tree of the human lung has over 10 5 conducting and 10 7 respiratory airways arrayed in an intricate pattern crucial for oxygen flow [1][2][3][4] . Classical studies of lung structure 5-8 raise the question of how the information required to generate a tree of such complexity is biologically encoded 9 . Individually configuring thousands or millions of branches would require a tremendous amount of patterning information, far more than is biologically plausible, to specify when and where each branch forms during development, and the size, shape, and direction of outgrowth of each branch. One possibility is that the process is not precisely controlled, for example if branching occurs randomly to fill available space. Another is that control is precise but coding is simplified by repeated use of a branching mechanism, as in Mandelbrot's fractal model and other elegant algorithms [10][11][12][13][14][15][16][17] . Even with these attractive models and recent progress in identifying lung development genes 18 , understanding of the program that directs branching remains rudimentary. This is largely due to the complexity of the bronchial tree, which makes it difficult to follow branching dynamics beyond the earliest events [19][20][21] . Although branching of the lung and other organs can occur in culture [22][23][24][25] , it is unlikely these recapitulate the full pattern. Here, we have determined the complete in vivo pattern of branching and branch lineage of the mouse bronchial tree, and show that it is generated using three geometrically distinct local modes of branching coupled in three different sequences. The branch lineage of the mouse bronchial treeThe bronchial tree develops by bran...

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Section: Introductionmentioning

confidence: 99%

The branching programme of mouse lung development

Metzger

Klein

Martin

et al. 2008

Nature

704

786

View full text Add to dashboard Cite

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“…The three-dimensional branching patterns of the airways form a fractal structure, where each branch repeats itself over multiple length scales [7]. Power laws are closely related to fractals, and it can be shown that dynamic processes propagating from fractal structures also exhibit fluctuations in time that follow power law distributions [8].…”

Section: Introductionmentioning

confidence: 99%

Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction

Ahlström

Liljefeldt

Hult

et al. 2005

IEEE Signal Process. Lett.

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Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0.34/spl plusmn/0.25, 0.50/spl plusmn/0.33, 0.46/spl plusmn/0.35, and 0.94/spl plusmn/0.64 dB/Hz in the frequency bands 20-40, 40-70, 70-150, and 150-300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.Original publication: Ahlstrom, C., Liljefeldt, O., Hult, P. and Ask, P., Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction, 2005, IEEE Signal Processing Letters, (12), 12, 812-815. http://dx.doi.org/10.1109/LSP.2005.859528. Copyright: IEEE, http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9

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“…The throat reproduces the model written in [7]. The geometry follows the models developed by Weibel [1] and Kitoaka et al [8]. The 3D numerical model has been made with the commercial code Ansys Gambit© [9].…”

Section: Methodsmentioning

confidence: 99%

“…The bifurcation angle was set to 35º according to the guidelines given in [1,8]. The geometry of the bifurcations in the bronchus at all the generations is created by a similar procedure.…”

Section: Methodsmentioning

confidence: 99%

Characterization of particle deposition in a lung model using an individual path

Tena

Casán

Pastor

et al. 2013

EPJ Web of Conferences

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Abstract. Suspended particles can cause a wide range of chronic respiratory illnesses such as asthma and chronic obstructive pulmonary diseases, as well as worsening heart conditions and other conditions. To know the particle depositions in realistic models of the human respiratory system is fundamental to prevent these diseases. The main objective of this work is to study the lung deposition of inhaled particles through a numerical model using UDF (User Defined Function) to impose the boundary conditions in the truncated airways. For each generation, this UDF puts the values of velocity profile of the flow path to symmetrical truncated outlet. The flow rates tested were 10, 30 and 60 ℓ/min, with a range of particles between 0.1 m and 20 m.

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A three-dimensional model of the human airway tree

Cited by 250 publications

References 25 publications

The branching programme of mouse lung development

The branching programme of mouse lung development

Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction

Characterization of particle deposition in a lung model using an individual path

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