Quantitative correlation between small airway morphology with respiratory function during disease progression in COPD: CFD analysis of human airways based on CT and OCT imaging.

Authors
Category Primary study
JournalComputer methods and programs in biomedicine
Year 2025
BACKGROUND AND OBJECTIVE: The quantitative knowledge of the influence of the small airway disease on the functional changes in chronic obstructive pulmonary disease (COPD) patients has been severely limited. METHODS: This study presents an innovative patient-specific computational framework that integrates CT and OCT imaging data with multiscale computational fluid dynamics (CFD) analysis. A three-dimensional tracheobronchial tree is reconstructed from CT scans of a mild COPD patient, spanning from the central airway to the 4th generation bronchial bifurcations. OCT imaging is subsequently conducted on upper, middle, and lower lobe bronchi of the right lung to quantify airway radius and wall thickness at 5th-9th generation bifurcations. These morphological parameters, hypothesized to correlate with small airway resistance and compliance, are implemented as impedance boundary conditions at the 3D model outlets. RESULTS: The simulation results demonstrate significant alterations in pressure gradients and velocity profiles under varying impedance conditions. The structure-function analysis quantify the morphological changes in small airways and their influences on the global respiratory function during disease progression. It is found that the relative residual volume (RV/TV) in the lung grows by up to 20 % from the early stage to the current stage of the disease. Additionally, the value of RV/TV may increase by up to 60 % if the radius of the 5th generation airway is halved. CONCLUSIONS: By synergizing patient-specific geometry with impedance-adaptive boundary conditions derived from multimodal imaging, the framework facilitates accurate quantification of the structure-function relationships between small airway morphology and lung function, and enables patient-specific assessments for COPD patients.
Epistemonikos ID: c6817ebabdb43c86ce6bf1d51bfde1a75991dbb6
First added on: Sep 08, 2025