Visualization 1: Endoscopic high-resolution autofluorescence imaging and OCT of pulmonary vascular networks

Movie of OCT-AFI scan Originally published in Optics Letters on 15 July 2016 (ol-41-14-3209

Visualization 2: Endoscopic Doppler optical coherence tomography and autofluorescence imaging of peripheral pulmonary nodules and vasculature

Full pull-back movie Originally published in Biomedical Optics Express on 01 October 2015 (boe-6-10-4191

Validation of Airway Wall Measurements by Optical Coherence Tomography in Porcine Airways

<div><p>Examining and quantifying changes in airway morphology is critical for studying longitudinal pathogenesis and interventions in diseases such as chronic obstructive pulmonary disease and asthma. Here we present fiber-optic optical coherence tomography (OCT) as a nondestructive technique to precisely and accurately measure the 2-dimensional cross-sectional areas of airway wall substructure divided into the mucosa (WA_muc), submucosa (WA_sub), cartilage (WA_cart), and the airway total wall area (WAt). Porcine lung airway specimens were dissected from freshly resected lung lobes (N = 10). Three-dimensional OCT imaging using a fiber-optic rotary-pullback probe was performed immediately on airways greater than 0.9 mm in diameter on the fresh airway specimens and subsequently on the same specimens post-formalin-fixation. The fixed specimens were serially sectioned and stained with H&E. OCT images carefully matched to selected sections stained with Movat’s pentachrome demonstrated that OCT effectively identifies airway epithelium, lamina propria, and cartilage. Selected H&E sections were digitally scanned and airway total wall areas were measured. Traced measurements of WA_muc, WA_sub, WA_cart, and WA_t from OCT images of fresh specimens by two independent observers found there were no significant differences (p>0.05) between the observer’s measurements. The same wall area measurements from OCT images of formalin-fixed specimens found no significant differences for WA_sub, WA_cart and WA_t, and a small but significant difference for WA_muc. Bland-Altman analysis indicated there were negligible biases between the observers for OCT wall area measurements in both fresh and formalin-fixed specimens. Bland-Altman analysis also indicated there was negligible bias between histology and OCT wall area measurements for both fresh and formalin-fixed specimens. We believe this study sets the groundwork for quantitatively monitoring pathogenesis and interventions in the airways using OCT.</p></div

Correlating OCT imaging and histology.

<p>A) Experimental procedure for airway preparation and OCT imaging. B) Diagram outlining matching of H&E and OCT images, manual tracing of the morphological perimeters, and calculation of the airway wall area components. P_p = probe perimeter, P_i = luminal perimeter, P_mi = muscle inner perimeter, P_ci = cartilage inner perimeter, P_o = airway outer boundary perimeter. WA_muc = mucosal wall area, WA_sub = submucosal wall area, WA_cart = cartilage wall area. Scale bar = 1 mm.</p

Slopes of the linear fits with standard error for wall area component measurements between Fresh OCT, Post-Formalin OCT, and histology images for two observers.

<p>Wall areas denoted with a prime are for fits against histology wall areas with the whitespace area removed. R² values are shown in parentheses.</p

Fresh OCT airway wall component measurements versus histology.

<p>(A) Correlation plots for measurements of WA_muc, WA_sub, WA_cart, and WA_t by both observers for fresh OCT imaging vs. histology (whitespace included). The solid lines are linear regression fits of the data and dotted lines are the regression fits of the data with the intercept of the model constrained to pass through the origin. (B) Bland-Altman analysis for WA_muc, WA_sub, WA_cart, and WA_t measurements by both observers for fresh OCT imaging vs. histology. Solid lines represent the bias and dotted lines represent the 95% confidence intervals.</p

Correlation and Bland-Altman analysis for fresh OCT airway wall component measurements for two observers for all slices.

<p>A. There was a significant correlation between observer 1 and 2_t (r² = 0.98, p<0.0001), WA_muc (r² = 0.89, p<0.0001), WA_sub (r² = 0.94, p<0.0001) and WA_cart (r² = 0.84, p<0.0001). B. Bland-Altman analysis indicates a small bias between observers for WA_t (bias = −0.15±0.40, 95% CI = −0.64–0.95), WA_muc (bias = 0.06±0.14, 95% CI = −0.34–0.23), WA_sub (bias = 0.14±0.26, 95% CI = −0.37–0.66), WA_cart (bias = −0.06±0.50, 95% CI = −0.91–1.03). Solid lines represent the bias and dotted lines represent the 95% confidence intervals.</p

Matched and traced OCT and histology images of porcine airway.

<p>A, D) Fresh OCT images, B, E) H&E and Movat’s pentachrome photomicrographs respectively, C, F) Post-formalin fixed OCT images. Tracings: green = P_o, yellow = P_ci, blue = P_mi, red = P_i, white = P_p. in B) E = epithelium, LP = lamina propria, SM = smooth muscle, C = cartilage.</p