<abstract xmlns="http://www.w3.org/1999/xhtml"><bold>Background</bold>: The aim of this study was to use a computerized lung model to simulate the deposition of inhaled particles in the human airways during a severe asthma attack, in order to find the combination of breathing- and particle-related parameters which leads to the highest deposited fractions in the target areas of the airways.<bold>Material and Method</bold>: A stochastic lung model was used to simulate the deposition of 1 nm – 100 μm particles during a severe asthma attack in bronchial generations 9-16. Breathing parameters were chosen to reflect the use of a therapeutic inhalation device, with a 10 s symmetrical breathing cycle and 2000 ml tidal volume. To maximize the deposited fraction in the target areas, further simulations were carried out changing the tidal volume (750-3000 ml), the length of the breathing cycle (2-20 s) and the length of breathing pause following inhalation (0-10 s).<bold>Results</bold>: The highest deposited fraction of 51.50% in bronchial generations 9–16 was obtained in the case of 0.01 μm particles, this value being more than4 times higher compared to the highest deposition of 3–6 μm particles currently used in inhalation devices (11.81% in the case of 5 μm particles). Modifying breathing-related parameters did not lead to valuable increases in the deposited fractions in the investigated region.<bold>Conclusions</bold>: Deposition fractions in the therapeutically important areas of the airways may be more than4 times higher in the case of 0.01 μm particles, compared to particles currently used in the treatment of asthma bronchiale.</abstract>

Background: The aim of this study was to use a computerized lung model to simulate the deposition of inhaled particles in the human airways during a severe asthma attack, in order to find the combination of breathing- and particle-related parameters which leads to the highest deposited fractions in the target areas of the airways.Material and Method: A stochastic lung model was used to simulate the deposition of 1 nm – 100 μm particles during a severe asthma attack in bronchial generations 9-16. Breathing parameters were chosen to reflect the use of a therapeutic inhalation device, with a 10 s symmetrical breathing cycle and 2000 ml tidal volume. To maximize the deposited fraction in the target areas, further simulations were carried out changing the tidal volume (750-3000 ml), the length of the breathing cycle (2-20 s) and the length of breathing pause following inhalation (0-10 s).Results: The highest deposited fraction of 51.50% in bronchial generations 9–16 was obtained in the case of 0.01 μm particles, this value being more than4 times higher compared to the highest deposition of 3–6 μm particles currently used in inhalation devices (11.81% in the case of 5 μm particles). Modifying breathing-related parameters did not lead to valuable increases in the deposited fractions in the investigated region.Conclusions: Deposition fractions in the therapeutically important areas of the airways may be more than4 times higher in the case of 0.01 μm particles, compared to particles currently used in the treatment of asthma bronchiale.

Maximizing the Amount of Deposited Particles During a Severe Asthma Attack Using the Stochastic Lung Model

University of Medicine and Pharmacy, Tîrgu Mures, Romania

Acta Marisiensis - Seria Medica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Background: The aim of this study was to use a computerized lung model to simulate the deposition of inhaled particles in the human airways during a severe...

Maximizing the Amount of Deposited Particles During a Severe Asthma Attack Using the Stochastic Lung Model

Published Online: Nov 07, 2015

Page range: 217 - 220

Received: Dec 09, 2014

Accepted: Jun 04, 2015

DOI: https://doi.org/10.1515/amma-2015-0043

Keywords
asthma, modelling, stochastic, inhalation, particles

© 2015 Sarkany Zoltan, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Maximizing the Amount of Deposited Particles During a Severe Asthma Attack Using the Stochastic Lung Model

Published Online: Nov 07, 2015

Page range: 217 - 220

Received: Dec 09, 2014

Accepted: Jun 04, 2015

DOI: https://doi.org/10.1515/amma-2015-0043

Keywordsasthma, modelling, stochastic, inhalation, particles

© 2015 Sarkany Zoltan, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
asthma, modelling, stochastic, inhalation, particles