Characteristics of Particle Depositions in Imaging-based Asthmatic Clusters

This study aims to assess computed tomography (CT) imaging-based classification scheme for asthmatic subjects compared to traditional spirometry-based criteria, with the goal of gaining deeper insights into the relationships between cluster-specific CT metrics, ventilation heterogeneity, and particle deposition. A total of 209 asthmatic subjects were classified into 4 imaging clusters (C#) characterized by C1: mild reduction in lung deformation, C2: airway narrowing, C3: wall thickening, C4: significant reduction in lung deformation and air trapping. This scheme reflects the severity stages when compared with spirometry-based criteria. However, the effectiveness of this scheme lies in distinguishing C4, which exhibits a significantly distinct ventilation profile compared to the other clusters. This distinction contrasts with the insignificant differences between ventilation profiles in traditional subgroups. A CT-based subject-specific whole-lung computational fluid and particle dynamics (CFPD) model was applied to predict airway resistance and particle deposition. We computed the coefficient of variation (CV) to study ventilation heterogeneity within and across clusters. We also computed the deposition fractions of particles of varying sizes in large conducting airways, small conducting airways, and respiratory airways, and explored correlations between CT, CFPD, and clinical variables.

Funding Acknowledgments:

NIH R01 HL168116, FDA U01 FD005837 and ED P116S210005