Evidence map›Paper›PMID 29297393›Full record

ArticleBMC medical informatics and decision making2017

Substance deposition assessment in obstructed pulmonary system through numerical characterization of airflow and inhaled particles attributes.

Antonios Lalas, Stavros Nousias, Dimitrios Kikidis, Aris Lalos, Gerasimos Arvanitis, Christos Sougles, Konstantinos Moustakas, Konstantinos Votis, Sylvia Verbanck, Omar Usmani and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 31% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

11 authors at 5 institutions in 3 countries.

Antonios LalasInformation Technologies Institute, Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece. lalas@iti.gr.
Stavros NousiasDepartment of Electrical and Computer Engineering, University of Patras, Patra, Greece.
Dimitrios KikidisInformation Technologies Institute, Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece.
Aris LalosDepartment of Electrical and Computer Engineering, University of Patras, Patra, Greece.
Gerasimos ArvanitisDepartment of Electrical and Computer Engineering, University of Patras, Patra, Greece.
Christos SouglesInformation Technologies Institute, Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece.
Konstantinos MoustakasDepartment of Electrical and Computer Engineering, University of Patras, Patra, Greece.
Konstantinos VotisInformation Technologies Institute, Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece.
Sylvia VerbanckRespiratory Division, University Hospital UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium.
Omar UsmaniNational Heart and Lung Institute (NHLI), Imperial College London and Royal Brompton Hospital, London, UK.
Dimitrios TzovarasInformation Technologies Institute, Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece.
Centre for Research and Technology Hellas · GRUniversity of Patras · GRImperial College London · GBInformation Technologies Institute · GRVrije Universiteit Brussel · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic obstructive pulmonary disease (COPD) and asthma are considered as the two most widespread obstructive lung diseases, whereas they affect more than 500 million people worldwide. Unfortunately, the requirement for detailed geometric models of the lungs in combination with the increased computational resources needed for the simulation of the breathing did not allow great progress to be made in the past for the better understanding of inflammatory diseases of the airways through detailed modelling approaches. In this context, computational fluid dynamics (CFD) simulations accompanied by fluid particle tracing (FPT) analysis of the inhaled ambient particles are deemed critical for lung function assessment. Also they enable the understanding of particle depositions on the airways of patients, since these accumulations may affect or lead to inflammations. In this direction, the current study conducts an initial investigation for the better comprehension of particle deposition within the lungs. More specifically, accurate models of the airways obstructions that relate to pulmonary disease are developed and a thorough assessment of the airflow behavior together with identification of the effects of inhaled particle properties, such as size and density, is conducted. Our approach presents a first step towards an effective personalization of pulmonary treatment in regards to the geometric characteristics of the lungs and the in depth understanding of airflows within the airways.

methodsA geometry processing technique involving contraction algorithms is established and used to employ the different respiratory arrangements associated with lung related diseases that exhibit airways obstructions. Apart from the normal lung case, two categories of obstructed cases are examined, i.e. models with obstructions in both lungs and models with narrowings in the right lung only. Precise assumptions regarding airflow and deposition fraction (DF) over various sections of the lungs are drawn by simulating these distinct incidents through the finite volume method (FVM) and particularly the CFD and FPT algorithms. Moreover, a detailed parametric analysis clarifies the effects of the particles size and density in terms of regional deposition upon several parts of the pulmonary system. In this manner, the deposition pattern of various substances can be assessed.

resultsFor the specific case of the unobstructed lung model most particles are detected on the right lung (48.56% of total, when the air flowrate is 12.6 L/min), a fact that is also true when obstructions arise symmetrically in both lungs (51.45% of total, when the air flowrate is 6.06 L/min and obstructions occur after the second generation). In contrast, when narrowings are developed on the right lung only, most particles are pushed on the left section (68.22% of total, when the air flowrate is 11.2 L/min) indicating that inhaled medication is generally deposited away from the areas of inflammation. This observation is useful when designing medical treatment of lung diseases. Furthermore, particles with diameters from 1 μm to 10 μm are shown to be mainly deposited on the lower airways, whereas particles with diameters of 20 μm and 30 μm are mostly accumulated in the upper airways. As a result, the current analysis indicates increased DF levels in the upper airways when the particle diameter is enlarged. Additionally, when the particles density increases from 1000 Kg/m

conclusionsThe treatment of respiratory diseases with inhaled medical substances can be advanced by the clinical use of accurate CFD and FPT simulations and specifically by evaluating the deposition of inhaled particles in a regional oriented perspective in regards to different particle sizes and particle densities. Since a drug with specific characteristics (i.e. particle size and density) exhibits maximum deposition on particular lung areas, the current study provides initial indications to a qualified physician for proper selection of medication.

Indexed as

Administration, InhalationComputer SimulationLung Diseases, ObstructiveModels, BiologicalHumansHydrodynamicsParticle SizeAerosol depositionComputational fluid dynamicsFluid particle tracingHuman airwaysObstructive lung diseases

Identifiers

PMID29297393
PMCPMC5751792
OpenAlexW2781351714

What OpenQuestion holds

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LicenceCC BY
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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.