A characteristic feature of obstructive lung diseases is the narrowing of small airways, which affects regional airflow patterns within the lung. However, the extent to which these patterns differ between healthy and diseased states is unknown. To investigate airflow patterns in detail, we first used particle image velocimetry measurements to validate a large eddy simulation model of flow in a patient-specific geometry. We then predicted flow patterns in the central airway under exhalation for three flow conditions-normal, intermediate, and severe-where boundary conditions represented the effect of lower airway obstructions. We computed Pearson correlation coefficients (R) to assess the similarity of flow patterns, and found that flow patterns demonstrated the greatest differentiation between flow conditions in the right main bronchi (R ≤0.60), whereas those in the secondary branches and regions of the trachea showed high correlation (R ≥0.90). These results indicate that although flow patterns are distinct between flow conditions, the choice of measurement location is critical for differentiation.
Keywords: Airway geometry; Chronic obstructive pulmonary disorder (COPD); Computational fluid dynamics (CFD); Particle image velocimetry (PIV).
Published by Elsevier B.V.