Noninvasive Imaging Biomarker Identifies Small Airway Damage in Severe Chronic Obstructive Pulmonary Disease

Abstract

Rationale: Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify emphysema, but no such studies have been performed linking an imaging metric to small airway abnormality.Objectives: To correlate ex vivo parametric response mapping (PRM) analysis to in vivo lung tissue measurements of patients with severe COPD treated by lung transplantation and control subjects.Methods: Resected lungs were inflated, frozen, and systematically sampled, generating 33 COPD (n = 11 subjects) and 22 control tissue samples (n = 3 subjects) for micro-computed tomography analysis of terminal bronchioles (TBs; last generation of conducting airways) and emphysema.Measurements and Main Results: PRM analysis was conducted to differentiate functional small airways disease (PRM^fSAD) from emphysema (PRM^Emph). In COPD lungs, TB numbers were reduced (P = 0.01); surviving TBs had increased wall area percentage (P < 0.001), decreased circularity (P < 0.001), reduced cross-sectional luminal area (P < 0.001), and greater airway obstruction (P = 0.008). COPD lungs had increased airspace size (P < 0.001) and decreased alveolar surface area (P < 0.001). Regression analyses demonstrated unique correlations between PRM^fSAD and TBs, with decreased circularity (P < 0.001), decreased luminal area (P < 0.001), and complete obstruction (P = 0.008). PRM^Emph correlated with increased airspace size (P < 0.001), decreased alveolar surface area (P = 0.003), and fewer alveolar attachments per TB (P = 0.01).Conclusions: PRM^fSAD identifies areas of lung tissue with TB loss, luminal narrowing, and obstruction. This is the first confirmation that an imaging biomarker can identify terminal bronchial pathology in established COPD and provides a noninvasive imaging methodology to identify small airway damage in COPD.

Keywords: COPD; airways disease; imaging; micro-CT.

Figure 1.

Overview of image acquisition and tissue processing. Left panel: parametric response mapping (PRM) analysis was performed on in vivo thoracic computed tomography (CT) scans, classifying each voxel of lung into one of three classes: normal (PRM^Norm), functional small airways disease (PRM^fSAD), and emphysema (PRM^Emph). Middle panel: after lungs were removed, each explanted lung specimen was first air inflated and frozen to enable ex vivo scanning with a CT scanner. Subsequently, the lung specimen was cut into 2-cm slices, from which tissue cores were extracted for micro-CT imaging. The micro-CT scans enabled a detailed assessment of small airway morphometry and alveolar destruction. Right panel: finally, sample core locations were matched back to the preoperative in vivo CT scan to enable a correlation between the morphometric parameters and the PRM classification. 3D = three-dimensional; MDCT = multidetector CT.

Figure 2.

Three-dimensional (3D) renderings of representative small airway trees present in tissue samples extracted from control subjects and patients with chronic obstructive pulmonary disease (COPD). (A) Representative 3D segmentation of all visible airways within a control and COPD sample are provided in addition to the matched parametric response mapping (PRM) analysis from the ex vivo computed tomography scan. (B) The cross-sectional images along the terminal bronchiole (TB) branch length demonstrate normal airway morphology in TB1 and 2 of the control sample compared with the COPD sample, which demonstrates complete obstruction and scarring in TB1 and airway wall thickening and lumen narrowing in TB2. Yellow lines indicate the inner and outer wall segmentations used for the calculations of luminal cross-sectional area, inner and outer wall perimeter, wall thickness, and wall area percentage. Cross-sectional images are 900 μm wide. emph = emphysema; fSAD = functional small airways disease; Norm = normal.

Figure 3.

Relationship between parametric response mapping (PRM) classification, number of terminal bronchioles (TBs), and airspace size. Samples are color coded based on predominant PRM abnormality (≥33.3%) PRM^Norm (normal; green), PRM^fSAD (functional small airways disease; yellow), or PRM^Emph (emphysema; red), and by specimen type (control, circle; chronic obstructive pulmonary disease [COPD], triangle). Plot demonstrates that the majority of COPD lung samples dominant for PRM^fSAD had significantly reduced number of TBs and a mean linear intercept (Lm) value greater than the 95th percentile of controls. COPD lung samples that were PRM^Emph dominant had similar reduction in TB number but Lm greater than 1,000 μm, which is the lower limit of resolution for clinical computed tomography (CT) and therefore presents as detectable emphysematous disease.