Regional flow and deposition variability in adult female lungs: A numerical simulation pilot study

2018 
Abstract Background Despite the promise of respiratory simulations improving diagnosis and treatment of pulmonary diseases, model predictions have yet to be translated into the clinical setting. Current state-of-the-art in silico models have not yet incorporated subject variability in their predictions of airflow distributions and extent of deposited particles. Until inter-subject variability is accounted for in lung modeling, it will remain impossible to translate model predictions into clinical practice. Methods Airflow and particle trajectories ( d p  = 1,3,5 μm ) are calculated in three subject-specific female adults by performing physiologically-based simulations. The computation framework features the ability to track air and particles throughout the respiration cycle and in the entire lung. Airway resistances, air velocities, and local deposition sites are correlated to airway anatomical features. Findings Smaller airway diameters are correlated to larger airway resistances and pressure gradients in one subject compared to the other two. Irregular shape of the airway and flow direction (e.g. inspiration or expiration) correspond with peak velocities and secondary flow motions. Largest subject variability in deposition between conducting and respiratory zones is seen for 1 μm diameter particles. Little difference in total deposition is found among subjects. Localized deposited particle concentration hotspots are linked to airway anatomy and flow motion. Interpretation Simulation predictions provide a first look into the correlation of anatomical features with airflow characteristics and deposited particle concentrations. Global deposition percentages ranged (at most, by 20 % ) between subjects and variances in localized deposition hotspots are correlated to variances in flow characteristics.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    42
    References
    13
    Citations
    NaN
    KQI
    []