Robust nondimensional estimators to assess the nasal airflow in health and disease

There are significant variations of both human nose shapes and airflow patternsinside nasal cavities, so it is difficult to provide a comprehensive medical identifica-tion using a universal template for what otolaryngologists consider normal breathingat rest. In addition, airflow patterns present ev...

Descripción completa

Detalles Bibliográficos
Autores: Sanmiguel Rojas, Enrique, Burgos Olmos, Manuel Antonio, Del Pino, Carlos, Sevilla García, Maria Agustina, Esteban Ortega, Francisco
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Universidad Politécnica de Cartagena(UPCT)
Repositorio:Repositorio Digital UPCT
OAI Identifier:oai:repositorio.upct.es:10317/13318
Acceso en línea:http://hdl.handle.net/10317/13318
https://onlinelibrary.wiley.com/doi/epdf/10.1002/cnm.2906
Access Level:acceso abierto
Palabra clave:3D model
Airway dynamics
Computational fluid dynamics
Healthy and diseased nasal cavities
Mecánica de Fluidos
2410.02 Anatomía Humana
Descripción
Sumario:There are significant variations of both human nose shapes and airflow patternsinside nasal cavities, so it is difficult to provide a comprehensive medical identifica-tion using a universal template for what otolaryngologists consider normal breathingat rest. In addition, airflow patterns present even more random characteristics in dis-eased nasal cavities. To give a medical assessment to differentiate the nasal cavitiesin health and disease, we propose 2 nondimensional estimators obtained from bothmedical images and computational fluid dynamics. The first mathematical estima-tor�������is a function of geometric features and potential asymmetries between nasalpassages, while the second estimatorRrepresents in fluid mechanics terms the totalnasal resistance that corresponds to the atmosphere-choana pressure drop. Theseestimators only require global information such as nasal geometry and magnitudesof flow determined by simulations under laminar conditions. We find that these esti-mators take low and high values for healthy and diseased nasal cavities, respectively.Our study, based on 24 healthy and 25 diseased Caucasian subjects, reveals that thereis an interval of values associated with healthy cavities that clusters in a small regionof the plane�������−R. Therefore, these estimators can be seen as a first approximationto provide nasal airflow data to the clinician in a noninvasive method, as the com-puted tomography scan that provides the required images is routinely obtained as aresult of the preexisting naso-sinusal condition