Evidence map›Paper›PMID 41951865›Full record

ArticlePharmaceutical research2026

Effects of Airway Generation Depth on Particle Deposition Behaviour in the Main Respiratory Airways-A Computational Modelling Study.

Xinyu Cai, Damien Chong, Hui Xin Ong, Kiao Inthavong, Ann Lee, Jingliang Dong, Agisilaos Kourmatzis, Shaokoon Cheng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Pharmaceutical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xinyu CaiSchool of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, Australia.
Damien ChongChemical Biological Radiological and Nuclear Defence, Sensors and Effectors Division, Defence Science and Technology Group, 506 Lorimer St., Fishermans Bend, Melbourne, VIC, 3207, Australia.
Hui Xin OngFaculty of Medicine, Healthy and Human Sciences, Macquarie University, Sydney, NSW, 2109, Australia.
Kiao InthavongSchool of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Plenty Road, Bundoora, Melbourne, VIC, PO Box 71, 3083, Australia.
Ann LeeSchool of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, Australia.
Jingliang DongInstitute for Sustainable Industries & Liveable Cities, Victoria University, Melbourne, VIC, PO Box 14428, 8001, Australia. Jingliang.Dong@vu.edu.au.ORCID http://orcid.org/0000-0002-2812-6188
Agisilaos KourmatzisSchool of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, Australia.
Shaokoon ChengSchool of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, Australia.

Funding

Australian Research Council DE210101549Australian Research Council DP190101237
6 · The paper itself

Abstract

purposeEffective inhaled drug delivery depends on formulation, device, and a clear understanding of aerosol transport in the respiratory tract. This study explores how lower airway anatomical complexity affects airflow and particle deposition in the main respiratory airways.

methodsSeven 3D bronchial models with varying airway generational depths were developed. Numerical simulations were conducted using the discrete phase model (DPM) to simulate aerosol transport and deposition under transient inspiratory flows at inhalation peak flow rates of 60 and 120 L/min.

resultsOur results showed that simplified models with three bronchial generations could underestimate the deposition efficiency in the main respiratory airways by up to 65.6% compared to the seven-generation lower airway model. Additionally, disparities in deposition outcomes and flow characteristics diminished with increasing lower airway complexity, with minimal changes in flow dynamics and deposition observed beyond the model with six bronchial generation.

conclusionsThis study suggests that airway models incorporating at least up to the 6th generation of bronchial branching may be required to sufficiently capture the implications for inhalation therapy design and the development of reliable in silico testing frameworks. Notably, insufficient lower airway detail not only compromises lung deposition estimates but also affects airflow dynamics throughout the entire respiratory tract, including the upper airway. This study highlights the importance of retaining detailed geometry in the design of inhalation therapies and the development of in silico testing frameworks.

Indexed as

BronchiModels, BiologicalRespiratory SystemAdministration, InhalationAerosolsComputer SimulationDrug Delivery SystemsHumansLungModels, AnatomicParticle SizeAerosolscomputational fluid dynamicshuman airwayparticle depositionrealistic lower airway

Identifiers

PMID41951865
PMCPMC13545025

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.