Modeling and optimization of nebulizers' performance in non-invasive ventilation using different fill volumes: Comparative study between vibrating mesh and jet nebulizers
JavaScript is disabled for your browser. Some features of this site may not work without it.
Modeling and optimization of nebulizers' performance in non-invasive ventilation using different fill volumes: Comparative study between vibrating mesh and jet nebulizers
Saeed, Haitham; Ali, Ahmed M. A.; Elberry, Ahmed A.; Eldin, Abeer Salah; Rabea, Hoda; Abdelrahim, Mohamed E. A.
Backgrounds: Substituting nebulisers by another, especially in non-invasive ventilation (NIV), involves many process-variables, e.g. nebulizer-type and fill-volume of respirable-dose, which might affect patient optimum therapy. The aim of the present work was to use neural-networks and genetic-algorithms to develop performance-models for two different nebulizers.
Methods: In-vitro, ex-vivo and in-vivo models were developed using input-variables including nebulizer-type [jet nebulizer (JN) and vibrating mesh nebulizer (VMN)] fill-volumes of respirable dose placed in the nebulization chamber with an output-variable e.g. average amount reaching NIV patient. Produced models were tested and validated to ensure effective predictivity and validity in further optimization of nebulization process.
Results: Data-mining produced models showed excellent training, testing and validation correlation-coefficients. VMN showed high nebulization efficacy than JN. JN was affected more by increasing the fill-volume. The optimization process and contour-lines obtained for in-vivo model showed increase in pulmonary-bioavailability and systemic-absorption with VMN and 2 mL fill-volumes.
Conclusions: Modeling of aerosol-delivery by JN and VMN using different fill-volumes in NIV circuit was successful in demonstrating the effect of different variable on dose-delivery to NIV patient. Artificial neural networks model showed that VMN increased pulmonary-bioavailability and systemic-absorption compared to JN. VMN was less affected by fill-volume change compared to JN which should be diluted to increase delivery.