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Background  High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both  ex-vivo  and  in-vivo  by OCT and correlate these to histology.    Methods  Patients with lung cancer, prior to lobectomy, underwent bronchoscopy including  in-vivo  OCT imaging.  Ex-vivo  OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated.    Results  13 airways of 5 patients were imaged by OCT. Histology was matched with 51  ex-vivo  OCT images and 39  in-vivo  OCT images. A significant correlation was found between  ex-vivo  OCT imaging and histology,  in-vivo  OCT imaging and histology and  ex-vivo  OCT imaging and  in-vivo  OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected.    Conclusions  OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases.

Optical coherence tomography for identification and quantification of human airway wall layers