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Understanding airflow dynamics: a computational study of nasal and oral breathers using patient-specific models
Shawn Ann Thomas1, Supriya Nambiar2, Mohammed Zuber3
1Department of Orthodontics and Dentofacial Orthopaedics, Manipal College of Dental Sciences Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Objective:
Breathing patterns and their influence on craniofacial growth and development have remained a subject of debate within orthodontics and otolaryngology. In this study, Computational Fluid Dynamics (CFD) was employed to analyze and compare airway morphology and airflow dynamics between individuals with normal nasal breathing and those with varying degrees of nasal obstruction.
Materials And Methods:
A total of five patients aged 18 to 28 years were selected for the study, comprising four individuals with varying degrees of nasal obstruction and one asymptomatic nasal breather, as verified by prior clinical evaluation from an otorhinolaryngologist. The samples were categorized into three groups: (1) nasal breathers with no anatomical abnormalities, (2) mouth breathers with septal deviation, and (3) predominant mouth breathers with nasal polyposis. High-resolution computed tomography (CT) scans were utilized for airway segmentation and subsequent CFD analysis. Key parameters like airflow patterns, velocity distribution, WSS, and airway resistance were evaluated at multiple sites within the pharyngeal airway.
Results:
The analysis revealed a non-uniform velocity distribution within the pharyngeal airway, influenced by anatomical variations in the nasal cavity. Flow parameters, including velocity streamlines, velocity contours, WSS, and pressure drop, varied notably across different grades of nasal obstruction.
Conclusion:
The observed airflow characteristics offer valuable insights into the combined effects of physiological and pathological breathing on airway dynamics. The airflow patterns identified in this study confirm the presence of altered airflow in obstructed nasal airways. Flow parameters, such as velocity streamlines, which illustrate the trajectory of air through the nasal cavity, may serve as supportive indicators for clinical symptoms such as anosmia. The non-invasive nature of CFD allows for a realistic assessment of airway flow behaviour.
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