Airway Wall Thickness Assessed Using Computed Tomography and Optical Coherence Tomography

doi:10.1164/rccm.200712-1776OC

Am J Respir Crit Care Med. 2008 June 1; 177(11): 1201–1206.

Published online 2008 February 28. doi: 10.1164/rccm.200712-1776OC

PMCID: PMC2408438

Airway Wall Thickness Assessed Using Computed Tomography and Optical Coherence Tomography

Harvey O. Coxson,^1,² Brendan Quiney,^1,² Don D. Sin,^2,⁴ Li Xing,² Annette M. McWilliams,^3,⁴ John R. Mayo,¹ and Stephen Lam^3,⁴

¹Department of Radiology, Vancouver General Hospital, Vancouver, British Columbia, Canada; ²The James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research at the Heart and Lung Center of St. Paul's Hospital, Vancouver, British Columbia, Canada; ³British Columbia Cancer Agency, Vancouver, British Columbia, Canada; and ⁴Department of Medicine (Respiratory Division), The University of British Columbia, Vancouver, British Columbia, Canada

Correspondence and requests for reprints should be addressed to Harvey O. Coxson, Ph.D., Department of Radiology, Vancouver General Hospital, 855 West 12th Avenue, Room 3350 JPN, Vancouver, BC, Canada V5Z 1M9. E-mail: harvey.coxson/at/vch.ca

Received December 3, 2007; Accepted February 21, 2008.

This article has been cited by other articles in PMC.

Abstract

Rationale: Computed tomography (CT) has been shown to reliably measure the airway wall dimensions of medium to large airways. Optical coherence tomography (OCT) is a promising new micron-scale resolution imaging technique that can image small airways 2 mm in diameter or less.

Objectives: To correlate OCT measurements of airway dimensions with measurements assessed using CT scans and lung function.

Methods: Forty-four current and former smokers received spirometry, CT scans, and OCT imaging at the time of bronchoscopy. Specific bronchial segments were identified and measured using the OCT images and three-dimensional reconstructions of the bronchial tree using CT.

Measurements and Main Results: There was a strong correlation between CT and OCT measurements of lumen and wall area (r = 0.84, P < 0.001, and r = 0.89, P < 0.001, respectively). Compared with CT, OCT measurements were lower for both lumen and wall area by 31 and 66%, respectively. The correlation between FEV₁% predicted and CT and OCT measured wall area (as percentage of the total area) of fifth-generation airways was very strong (r = −0.79, r = −0.75), but the slope of the relationship was much steeper using OCT than using CT (y = −0.33x + 82, y = −0.1x + 78), indicating greater sensitivity of OCT in detecting changes in wall measurements that relate to FEV₁.

Conclusions: OCT can be used to measure airway wall dimensions. OCT may be more sensitive at detecting small airway wall changes that lead to FEV₁ changes in individuals with obstructive airway disease.

Keywords: chronic obstructive pulmonary disease

AT A GLANCE COMMENTARY

Scientific Knowledge on the Subject

Computed tomography is widely used to quantify airways in subjects with chronic obstructive pulmonary disease. Optical coherence tomography (OCT) is a new micron-scale resolution optical imaging method used in studies of the eye, gastrointestinal tract, and preneoplastic bronchial lesions.

What This Study Adds to the Field

OCT can be used to measure airway wall dimensions. OCT may be more sensitive at detecting small airway wall changes that lead to FEV₁ changes in individuals with obstructive airway disease.

Chronic obstructive pulmonary disease (COPD) is characterized by irreversible airflow obstruction, in most cases caused by inhalation of toxic particles, such as cigarette smoke (1, 2). It is well known that, in the susceptible host, chronic exposure to these particles causes an exaggerated inflammatory response that remodels the wall of the small airway, ultimately resulting in nonreversible airflow limitation (3, 4). Remodeling of the small airways is believed to occur early in the disease process and worsens with disease progression. The “gold standard” for assessing small airway disease is morphometry of resected lung tissue, but the invasiveness of this approach precludes its use in clinical studies. With the advent of high-resolution computed tomography (CT), and the development of multislice CT scanning techniques, CT has become a very popular technique for the noninvasive assessment of airway disease in COPD (5–8). Although there have been considerable improvements in the resolution of CT images over the past decade, CT scans are still limited by a pixel size of approximately 0.5 mm, which makes the measurement of small airways in particular prone to errors (9, 10). Moreover, there is growing concern regarding radiation-related cancer risks associated with repeated CT scanning, although the overall risk appears to be small (11–13).

A new noninvasive technique called optical coherence tomography (OCT) is gaining credibility as a thoracic imaging tool (14–17). Although similar in principle to B-type ultrasound, OCT uses near-infrared light instead of sound waves and does not require a transducing medium. A detector is used to collect back-scattered and reflected waves from the tissues, which are then compared with a reference beam using an inferometer (14). Due to the use of low coherence light, OCT can produce images with resolution in the range of 5 to 15 μm (14–17).

The hypothesis for this pilot study was that in vivo measurements of airway wall dimensions obtained using OCT would correlate with CT measurements of airway wall dimensions. Furthermore, we also evaluated if a correlation exists between OCT measures of airway wall area and FEV₁ and how this compares to similar measurements made using CT.

Some of the results of these studies have been previously reported in the form of an abstract (18).

METHODS

Subjects

Forty-four current and former smokers participating in two ongoing National Cancer Institute (NCI)–sponsored lung cancer chemoprevention trials were enrolled in this investigation before treatment with any chemopreventive agent. All subjects gave written, informed consent to participate in study. The study was approved by the Clinical Ethics Review Board of the British Columbia Cancer Agency and the University of British Columbia.

Spirometry

Spirometry was conducted using a flow-sensitive spirometer (Presto Flash Portable Spirometer, version 1.2; Spacelab Burdick, Inc., Deerfield, WI) according to American Thoracic Society recommendations (19). The FEV₁ and FVC were recorded in liters and as a percentage of predicted values using standardized prediction equations (20).

CT Imaging and Measurements

Contiguous 1-mm-thick CT images (“b35f,” 120 kVp, 215 mA, 0.5-s rotation time) were acquired at suspended full inspiration while the subject was supine using a Siemens Sensation 16 multislice scanner (Siemens Medical Solutions, Erlangen, Germany). CT scans were analyzed using Pulmonary Workstation 2.0 software (VIDA Diagnostics, Iowa City, IA). Briefly, the CT scans were reformatted into three-dimensional images (Figure 1) and the airway lumen (Ai), total airway area (Ao), airway wall area (Aaw), and wall area percentage (WA%) defined as (Ao − Ai)/Ao × 100% were measured at cross-section to the central axis of the airway as previously described (21). Additional detail on the method for making these measurements is provided in the online supplement.

Figure 1.

A screen shot of the Pulmonary Workstation 2.0 software (VIDA Diagnostics, Iowa City, IA) showing a multiplanar reformat of the right lateral basal segmental bronchus. The longitudinal section of the reformatted airway is shown in (A), and the cross-section (more ...)

OCT Imaging and Measurements

Bronchoscopy was performed using the Onco-LIFE device (Novadaq Technologies, Inc., Richmond, BC, Canada) under local anesthesia and conscious sedation (22). The design of the OCT system and measurement of the airways are further outlined in the online supplement. Briefly, a small optical probe (Pentax SOCT-PR-150300; Pentax Corp., Tokyo, Japan) with an outer diameter of 1.5 mm and a depth of focus of 2 mm was inserted through the biopsy channel of the bronchoscope and advanced in 5-mm increments until the catheter fit snugly into a small airway with a luminal diameter similar to the outer diameter of the OCT probe. Low coherence light with a bandwidth of 50 nm was split evenly, half toward the bronchial surface via a fiber-optic catheter and half toward a moving mirror. Light was then reflected both from within the tissue and from the mirror, and an interference image was created and stored as a digital video file. Airways were manually measured using ImageJ software (National Institutes of Health, Bethesda, MD) (Figure 2).

Figure 2.

Optical coherence tomography images of a third-generation airway (A) and a fifth-generation airway (B), which were compared with pulmonary function. The internal perimeter (Pi) and outer perimeter (Po) of the airway wall was manually traced using ImageJ (more ...)

Statistical Analysis

The relationships between OCT-based and CT-based measurements of airway dimensions were assessed using Pearson correlation analysis and linear regression modeling. A Bland-Altman plot was used to compare the difference in the measurements and the limits of agreement (bias ± 2 SD of bias) between the paired OCT and CT measurements of the same airway (23). The trend of the relationship was determined after smoothing the data using the locally weighted least squares (LOWESS) technique (24). A Z test was used to compare two slopes of different ordinal least square models. A P value less than 0.05 was considered statistically significant.

RESULTS

There were 44 subjects in this study. The baseline characteristics of the study participants are shown in Table 1.

TABLE 1.

SUMMARY OF BASELINE CHARACTERISTICS OF THE STUDY PARTICIPANTS

Relationship between OCT- and CT-based Measurements of Wall Area

To compare between OCT and CT, 22 matched airways were analyzed, which included 18 third-generation airways and 4 fourth-generation airways (see online supplement for more details). For OCT assessments, the mean Ai (airway luminal area) was 8.4 ± 4.6 mm² (mean ± SD) and the mean Aaw (airway wall area) was 7.5 ± 2.8 mm², whereas for CT, the mean Ai was 12.5 ± 6.1 mm² and the mean Aaw was 22.7 ± 8.5 mm². There was excellent correlation between OCT- and CT-based estimations of Ai (r = 0.89, P < 0.001), Aaw (r = 0.84, P < 0.001), and WA% (see Figure 3). In general, the CT measurements of Ai were consistently larger than those acquired using OCT (see online supplement for more details).

Figure 3.

The relationship between percentage of airway wall area (WA%) estimated by computed tomography (CT) and that by optical coherence tomography (OCT).

Table 2 summarizes the relationship between OCT- and CT-based measurements of various components of airway dimension from linear regression models. In all these analyses, OCT-based values were included as the “independent” variables (x axis) and the CT-based values were the “dependent” variables (y axis). All components of the airway dimension were increased with CT- compared with OCT-based assessments.

TABLE 2.

COMPARISON OF AIRWAY DIMENSIONS BETWEEN MEASUREMENTS MADE BY OPTICAL COHERENCE TOMOGRAPHY AND COMPUTED TOMOGRAPHY USING LINEAR REGRESSION MODELING^*

Relationship between OCT- and CT-based Measurements with FEV₁% Predicted in the Third- and Fifth-Generation Airways

To determine whether or not OCT- and CT-based measurements of airways correlated with the subject's FEV₁% predicted, we measured Ai and Aaw from the third- and fifth-generation airways separately. The Ai of the third-generation airways was 10.9 ± 5.7 mm² and Aaw was 8.3 ± 2.2 mm² for OCT-based measurements, whereas the Ai was 20.0 ± 7.5 mm² and Aaw was 30.3 ± 8.0 mm² for CT-based measurements. The Ai of the fifth-generation airways was 3.3 ± 0.33 mm² and Aaw was 4.1 ± 1.5 mm² for OCT-based measurements, whereas the Ai was 5.4 ± 1.7 mm² and Aaw was 12.8 ± 3.7 mm² for CT-based measurements.

FEV₁% predicted did not correlate significantly with the airway measurements of the third-generation airways regardless of whether CT or OCT was used (see Figure 4A). However, in the fifth-generation airways, we observed a significant negative correlation for both CT-based (r = −0.79, P < 0.001) and OCT-based (r = −0.75, P < 0.001) measurements of WA% (Figure 4B). However, the slope of OCT measurements was significantly steeper than that for CT-based measurements (P for the slope difference < 0.0001), indicating greater discriminative power (i.e., sensitivity) of OCT in detecting lung function changes. Representative matched CT and OCT airways for a subject with normal FEV₁ (118% predicted) and low FEV₁ (52%) are shown in Figure 5. The WA% measured using CT was only 5% different (69 vs. 74%) but 29% different (43 vs. 72%) using OCT. The subepithelial structure was denser in the airway from the subject with low FEV₁ in keeping with increase in collagen deposition with the airway remodeling process.

Figure 4.

The relationship between percentage of wall area of a third-generation airway (A) and a fifth-generation airway (B) as estimated by computed tomography (CT) (open circles) and by optical coherence tomography (OCT) (closed diamonds) and FEV₁% predicted. (more ...)

Figure 5.

Images of fifth-generation airways obtained using computed tomography (CT) (A, B) and optical coherence tomography (OCT) (C, D). The airways in (A) and (C) were obtained from a subject with normal FEV₁ (118% predicted) and in (B) and (D) are obtained (more ...)

DISCUSSION

The most important finding of this study is that, although there is a very good correlation between CT and OCT measurements of airway wall dimensions, OCT appears to be a more sensitive method for discriminating the changes in the more distal airways of subjects with a range of expiratory airflow obstruction. OCT-based measurements of WA%, which estimates airway wall thickness (corrected for the size of the airway), in the fifth-generation airway were more sensitive to changes in subjects' lung function, as assessed by FEV₁% predicted than were CT-based measurements on the same airways. Neither OCT- nor CT-based measurements in the large (third-generation) airways were associated with FEV₁. This is not surprising because the primary site of airflow obstruction is the small peripheral airways (4).

It is well known that the chronic airflow limitation seen in people with COPD is related to a combination of the loss of elastic recoil pressure due to emphysema and increased resistance in the small airways. The exact contribution of these mechanisms to COPD is believed to be under genetic control, and the ability to noninvasively phenotype individuals into those whose airflow limitation is due to airway remodeling versus emphysema is of great interest. CT scans have been proposed as an ideal method to phenotype subjects because both lung density changes due to emphysema and airway wall dimensions can be measured (7). However, it has been noted that CT has many problems associated with airway wall measurements, and its sensitivity in predicting FEV₁ is suboptimal. Nakano and colleagues originally published results that showed that FEV₁ was correlated with both low attenuating areas on CT (emphysema) and WA% of the apical segmental bronchus (7). Hasegawa and coworkers recently were unable to show this correlation between FEV₁ and third-generation airways, but by tracking the airways out to the sixth generation, they were able to show a modest correlation with FEV₁ (6). These findings make intuitive sense because it is well established that the major site of airflow limitation is in the small airways (3, 4). Therefore, the association between airway wall dimensions and FEV₁ should be stronger in smaller airways, especially in subjects with severe airflow obstruction. Furthermore, our data show that, although there is a significant correlation with FEV₁, the slope is not sufficiently steep to detect subtle (but likely clinical relevant) changes in FEV₁. It is possible that CT is not very sensitive to differences in FEV₁ because of suboptimal resolution of small airways as the limits of CT resolution are approached (10). OCT is a new, relatively noninvasive technique for measuring airway wall dimensions. Because the resolution of OCT is between 5 and 15 μm (14, 16, 17), this will provide greater spatial resolution and hence more accuracy to wall measurements of small airways.

The data from the present study show that there is a very good correlation between CT and OCT measurements of airway dimensions. Previous studies suggest that, compared with histologic measurements of small airways, which is the current gold standard, CT-based measurements tend to overestimate wall thickness and underestimate lumen area (10). The CT measurements of Ai are larger across all airway sizes, suggesting that increased lung volume during the CT scan compared with bronchoscopy may increase the lumen area. However, the change in WA will be minimal across the breathing cycle because it is a solid structure, which makes its dimensions harder to change. The relative difference in the WA measurements is largest in the small airways and least in the large (see online supplement). This suggests that, as the airway approaches the resolution of the CT scanner (i.e., as the pixel size of the CT image becomes larger than the airway of interest), the superior resolution of OCT becomes very important. Although newer CT airway algorithms may be able to measure airways with submillimeter resolution (21, 25), CT is still limited by the resolution of the CT scanner, which is approximately 0.5 mm. The current data indicate that, in all cases, OCT-based measurements of airway dimensions were smaller than those obtained on CT scans and, although we do not have histologic confirmation of the airway dimensions, we believe that OCT-based measurements of wall thickness may be more accurate in assessing remodeling changes in the small conducting airways because of the increased resolution of OCT compared with CT. This may explain why WA% values obtained on OCT were more responsive to changes in FEV₁ than were those generated from CT scans. Figure 5 shows images of airways obtained from a subject with normal FEV₁ and low FEV₁ and it is obvious from the data and the image that OCT can measure the differences in airway wall thickness in these fifth-generation airways. OCT may therefore be superior to CT in assessing the “small airway” phenotype of COPD and in evaluating disease progression over time and the effects of novel drugs on small airway remodeling of COPD.

The other major advantage of OCT is that there is no radiation exposure associated with this procedure. Although the risk of radiation-related cancer is low with CT scans, there is growing concern in the public regarding safety of CT scans (11). The use of OCT eliminates this risk. The disadvantage, however, is that OCT requires bronchoscopy.

There are limitations to the current study. First, although the distribution of FEV₁ values was heterogeneous, we only had two subjects whose FEV₁ was below 50% of predicted. Thus, the accuracy of detecting remodeling changes in the airways with OCT in patients with GOLD (Global Initiative for Chronic Obstructive Lung Disease) stage 3 and 4 disease requires further studies. Second, as the subjects in this study underwent only one bronchoscopic session, we could not evaluate the reproducibility of OCT measurements over time. However, it is important to further evaluate the use of OCT in combination with genomic or protein biomarker studies that require a bronchoscopic procedure to retrieve bronchial cells and bronchoalveolar lavage fluid to improve our understanding of the pathogenesis of airway diseases such as COPD and asthma as well as the effect of therapeutic intervention, especially novel treatments,

In summary, the present study suggests that OCT is a more sensitive tool in detecting airway wall remodeling in current and former smokers compared with CT scans, which raises the possibility that OCT could be used to study airway changes in vivo in patients with COPD and assess therapeutic potential of novel airway therapies.

Supplementary Material

[Online Supplement]

Click here to view.

Acknowledgments

The authors thank Dr. Ren Yuan, Lukas Holy, and Anh-Toan Tran for technical assistance with the CT images and data; Sukhinder Khattra for logistical assistance with the Lung Health Study database; Dr. Juerg Tschirren and John Garber at VIDA Diagnostics for assistance with the CT analysis software; and Pentax Corp. (Tokyo, Japan) for providing the OCT device for the study.

Notes

H.O.C. is a Canadian Institutes of Health Research/British Columbia Lung Association New Investigator. D.D.S. is a senior scholar of the Michael Smith Foundation for Health Research, Canadian Research Chair in COPD, and a St. Paul's Hospital Foundation Professor of COPD. S.L. is the MDS-Rix Endowed Director of Translational Lung Cancer Research at the BC Cancer Agency. This study is funded in part by NIH-NCI grants 1PO1-CA96964, U01CA96109, and the Michael Smith Foundation for Health Research COPD Team Grant. The OCT device was provided by Pentax Corp. (Tokyo, Japan).

This article has an online supplement, which is accessible from this issue's table of contents at www.atsjournals.org

Originally Published in Press as DOI: 10.1164/rccm.200712-1776OC on February 28, 2008

Conflict of Interest Statement: H.O.C. received $11,000 in 2005 and $4,800 in 2006 and 2007 for serving on an advisory board for GlaxoSmithKline (GSK). In addition, H.O.C is the co-investigator on two multicenter studies sponsored by GSK and has received travel expenses to attend meetings related to the project. H.O.C has three contract service agreements with GSK to quantify the CT scans in subjects with COPD and a service agreement with Spiration, Inc., to measure changes in lung volume in subjects with severe emphysema. A percentage of H.O.C.'s salary between 2003 and 2006 ($15,000/yr) derives from contract funds provided to a colleague, Peter D. Paré, by GSK for the development of validated methods to measure emphysema and airway disease using CT. H.O.C is the co-investigator (D. Sin, principal investigator) on a Canadian Institutes of Health–Industry (Wyeth) partnership grant. There is no financial relationship between any industry and the current study. B.Q. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. D.D.S. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. L.X. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. A.M.M. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. J.R.M. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. S.L. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript.

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