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The Proceedings of the American Thoracic Society 5:910-914 (2008)
© 2008 The American Thoracic Society
doi: 10.1513/pats.200809-109QC
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Application of Three-Dimensional Airway Algorithms in a Clinical Study

Masaharu Nishimura1

1 First Department of Medicine, Hokkaido University School of Medicine, Sapporo, Japan

Correspondence and requests for reprints should be addressed to Masaharu Nishimura, M.D., Ph.D., First Department of Medicine, Hokkaido University School of Medicine, North 15, West 7, Kita-ku, Sapporo, 060-8638, Japan. E-mail: ma-nishi{at}med.hokudai.ac.jp

ABSTRACT

Three-dimensional airway analysis, using high-resolution computed tomography (CT), has only recently become a reality for studying airway dimensions and remodeling in chronic obstructive pulmonary disease (COPD). Herein, we show how we validated our new software using phantoms, and how we applied this software to a clinical study. Using this software, we have demonstrated that the percentage of predicted forced expiratory volume in 1 second in patients with COPD correlated highly with airway luminal area and, to a lesser extent, with percentage wall thickening (WA%) from the 3rd to the 6th generation of both the apical upper bronchus (B1) and the anterior lower bronchus (B8). More importantly, we also showed that correlation coefficients improved with decreasing airway size in both airways. In the near future, with further advances in both software and CT technology, this kind of approach will become even more attractive. Using this readily accessible and relatively noninvasive technique, we are conducting a longitudinal study of subjects recruited for the Hokkaido COPD cohort study. Potential problems in the application of three-dimensional airway analysis to such longitudinal follow-up studies and/or large-scale multicenter studies are also discussed.

Key Words: airway remodeling • emphysema • computed tomography • airflow limitation

Chronic obstructive pulmonary disease (COPD) is a disease characterized by airflow limitations that are not fully reversible and consists of small airways disease (obstructive bronchiolitis) and parenchymal destruction (emphysema), the relative contributions of which vary among patients (1). Thin-section computed tomography (CT) has been used to quantify emphysema by detecting low-attenuation areas (LAAs), and the role of CT in diagnosing emphysema is well established. However, airflow limitations as evaluated by forced expiratory volume in 1 second (FEV1) do not necessarily correlate well with the severity of emphysema as evaluated by CT (2, 3), since small airways disease appears to contribute more significantly to airflow limitations in COPD (1, 4–6).

Recent progress in CT technology has enabled the detection and quantification of airway abnormalities (7–9). Indeed, to improve the diagnostic yield for peripheral small nodules, several Japanese groups, including our group, have been using virtual bronchoscopy, a novel CT-based technique that allows noninvasive intraluminal evaluation of the airways up to about the 8th generation (10–12). Theoretically, thin-section CT can depict the dimensions of airways as small as approximately 1 to 2 mm in inner diameter. The use of CT to evaluate airway dimensions in a variety of diseases has thus been suggested (13–18). However, only a few studies had attempted to measure airway dimensions in patients with COPD (19–22) until 2006, when our study was published (23).

Most previous reports have, unfortunately, suffered from inherent technological problems with respect to the measurement of airway dimensions. First, accurate cross-sectional images could not always be obtained using conventional two-dimensional images, since airways run in various directions in the lung. Second, since investigators did not obtain longitudinal airway images, in which generation of the bronchus was actually being measured, could not be recognized. The idea of three-dimensional airway analysis is not entirely new (24–26), but has not previously been applied to measuring airway dimensions in patients with COPD.

We describe herein the software we have developed to overcome these problems, how we have applied the software to a clinical study for COPD, and what we plan to do in the future. We also discuss potential problems inherent in the measurement of airway dimensions, using high-resolution CT (HRCT), in general. This manuscript is not intended to review the field of three-dimensional airway analysis but focuses on our own work.

CT DATA ACQUISITION AND RECONSTRUCTION

In our first study (23), CT was performed using a multidetector-row spiral CT scanner with four detector arrays (SOMATOME plus Volume Zoom; Siemens, Berlin, Germany). Scans were acquired using the following parameters: 140 kVp; 150 mA; 4 detector x 1 mm collimation; and helical pitch 7. The entire lung of each subject was scanned while the subject was in the supine position, holding the breath at deep inspiration. All CT row datasets were reconstructed to isotropic voxel data using both soft-tissue and bone algorithms. The length of 1 voxel side was 0.625 mm. Reconstructed data were transferred to the workstation, then reconstructed into three-dimensional chest images (AZE Ltd, Tokyo, Japan). First, a three-dimensional bronchial skeleton was automatically reconstructed using a certain threshold level, determined on an individual basis (–950 HU to –980 HU) to obtain airway images as distal as possible. Any portions of lung parenchyma remaining with the skeleton were manually removed to prevent an analysis error. Finally, we obtained a bronchial skeleton and were able to identify any bronchus in the source images of axial, sagittal, and coronal slices. The selected bronchial pathway in the bronchial skeleton could be manually extended to at least the 6th generation of bronchi, when necessary, and be automatically converted to a curved multiplanar reconstruction (MPR) image (Figure 1). The bronchial long-axis image appears as if it was a straight pathway. Of note, we were able to obtain short-axis images exactly perpendicular to the long axis at any site, and to identify which generation of airway was actually picked up. Identification of the generation of bronchi must be relied on careful inspection of any bifurcation while proceeding longitudinally in the airway. We first define a segmental bronchus as the 3rd generation of bronchi, and then proceed toward peripherally, using the longitudinal image and the short axis image simultaneously and searching for any bifurcation all around circumference. On the monitor of the workstation, image interpretation was performed using a window width of 1,000 and a window level of –700. From the centroid point of the lumen, rays fanning out over 360° were examined to determine airway wall thickness along the rays using the full-width at half-maximum principle (8, 27). After this process, if the outline of automatically obtained airway walls was obviously out of contour, correction was made. Based on manual plotting at several points, our software used cubic spline interpolation and built a new circle. Finally, we could obtain values for the airway luminal area (Ai) and outer area of the bronchus (Ao). The percentage wall area (WA%) was defined as WA% = (Ao – Ai) / Ao x 100. Assuming that the airway lumen is a true circle and airway wall thickness is constant throughout the wall, inner diameter (Di), total diameter (Do), and airway wall thickness (T) were calculated as Di = 2{surd}Ai/{pi}, Do = 2{surd}Ao/{pi} and T = (Do – Di)/2.


Figure 1
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  		Figure 1. (A) Accurate bronchial skeleton. (B) Source images of axial, sagittal, and coronal slices. Yellow lines indicate the same series of airways in both A and B. (C) A curved multiplanar reconstruction (MPR) image of the selected airway from the right lower lobe. (D) Short-axis images obtained from the curved MPR image are precisely perpendicular to the long axis of the airway. Here a segmental bronchus is defined as the third generation of bronchus. See text for the details of how we identify the generation of bronchi. (Reprinted by permission from Reference 23).

 
PHANTOM STUDIES USING TWO DIFFERENT CT SCANNERS

We performed a validation study using three phantoms to test our newly developed software for the CT scanner described above. The phantoms were made of acrylic resin, and Di, Do, and T were optically accurate. Phantom 1 and Phantom 2 were both cylindrical. For Phantom 1, Di was 2 mm and T was 1 mm. For Phantom 2, Di was 1.5 mm and T was 1 mm. Phantom 3 had a sigmoid shape, and Di was 3 mm and T was 1 mm (Figure 2). Phantom 3 was used to confirm the accuracy of the algorithm, which should allow short-axis images to be obtained exactly perpendicular to the long axis at any site. When performing scans, phantoms were placed into polystyrene foam blocks, representing the lung parenchyma. CT was performed under the same conditions as used in the clinical study.


Figure 2
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  		Figure 2. Photograph of the sigmoid-shaped phantom (Phantom 3 in text) with a 3-mm inner diameter (upper). Curved MPR image obtained from original computed tomography (CT) data (middle). Nine short-axis images at various sites (lower). (Reprinted by permission from Reference 23.)

 
For Phantom 1, mean (± SD) Ai was 2.8 ± 0.1 mm2 and WA was 9.8 ± 0.2 mm2, both of which were close to the actual values (3.1 mm2 and 9.4 mm2, respectively). Coefficients of variation for Ai and WA were 2.8% and 2.2%, respectively; both were well within acceptable limits. On the other hand, for Phantom 2, with a Di of 1.5 mm, the coefficient of variation was 14.9% for Ai and 3.5% for WA; the coefficient of variation for Ai was thus not as good was not as good as that for Phantom 1, with a Di of 2 mm. These data roughly indicate that the measurement of airway dimensions using our new software is very accurate and reproducible for airways with Di greater than 2 mm. To confirm how accurately we could obtain precise short-axis images of bronchi running in various directions in the lung, we obtained images of the sigmoid-shaped Phantom 3. Axial images of Phantom 3 obtained at all points were perfect, round shapes, confirming that the software can be used for any bronchi. Data were obtained from 40 points of the sigmoid-shaped phantom (Ai, 7.1 mm2; WA, 12.6 mm2), with measured values of: Ai, 6.8 ± 0.8 mm2; and WA, 13.2 ± 0.2 mm2. Coefficients of variation for Ai and WA were 3.3% and 2.5%, respectively; both of these values were considered acceptable for human clinical studies.

We then performed another validation study, using the same phantoms, to confirm the acceptability of data using two different types of CT scanner. Such validation would be particularly important in longitudinal follow-up studies and/or large-scale multicenter studies, since the use of different types of CT scanners in one study could be considered a substantial obstacle, particularly in studies involving lung densitometry measurements (28–30). The same experimental protocol was used for a CT scanner with 64-detector arrays (Aquilion Multi, TSX-101A/HA; Toshiba Medical Systems, Tokyo, Japan) as had been performed for the CT scanner with 4-detector arrays. Data were acquired using the following parameters: 120 kVp; 300 mA; 0.5 s/rotation; 64 x 0.5 mm collimation; helical pitch 41; and slice thickness 0.5 mm. Ai and WA measured were 3.0 ± 0.1 mm2 and 9.2 ± 0.1 mm2 for Phantom 1 and 1.9 ± 0.1 mm2 and 7.8 ± 0.2 mm2 for Phantom 2, respectively. Coefficients of variation were 3.3% and 6.1% for measurements of Ai and 1.1% and 3.0% for measurements of WA in Phantoms 1 and 2, respectively. These figures were considered acceptable, except for the large CV in the measurement of Ai in Phantom 2. For Phantom 3, the measured area was 6.7 ± 0.1 mm2 and the coefficient of variation was 2.2%, which was again considered acceptable for further human studies, despite the small difference in absolute values between scanners.

Figures 3 shows representative MPR images of the same airway tree, which were taken with an interval of 1 year in one subject, using the two different CT scanners. Although we must remain cautious about the use of different CT scanners within a study, the phantom studies described above and this representative case indicate that our computer system and new software may allow analysis of data taken from different CT scanners.


Figure 3
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  		Figure 3. Two MPR images of the same airway tree taken at an interval of 1 year in 1 subject, using the two different CT scanners. The MPR image can be made at any angle, and the subtle difference in angle makes the appearance of image much different.

 
STRUCTURE–FUNCTION STUDY IN COPD

Nonreversible airflow limitation, which is characteristic in COPD, is believed to consist of small airways disease (obstructive bronchiolitis) and parenchymal destruction (emphysema). This concept basically derives from numerous historical studies that have examined correlations between pulmonary function parameters and pathological scores, using postmortem lung tissue or surgically resected tissue (1). However, the relative contribution of these pathologies to airflow limitation in COPD may vary among patients.

Nakano and coworkers were the first to report that wall thickening in the apical segmental bronchus (B1) of the right upper lobe is significantly correlated with FEV1 (%predicted) in patients with COPD (19). They selected the B1 bronchus for measurement because this airway is usually cut in cross-section and can be reliably identified on two-dimensional CT, thereby allowing comparison between individuals. Furthermore, they measured the percentage of LAA at the same time for the same group of patients with COPD, and indicated that airway thickening in the B1 segmental bronchus and the percentage of LAA independently contributed to airflow limitations in these subjects. In other words, some individuals with COPD only display an increased percentage of wall area at the B1 bronchus, whereas others have an increased percentage of LAA, and some show both airway wall thickening and emphysema. That study for the first time indicated that use of CT might have the capacity to separate COPD phenotypes, such as airway disease–predominant, emphysema-predominant, or mixed-type COPD. The data in that study were surprising to us, considering that they measured the dimensions of only one large airway in the right lung. However, they subsequently demonstrated that measuring airway dimensions in large airways allowed a rough estimation of small airway dimensions by comparing the CT findings of large airways with histologic measurement of small airways in lungs excised from the same subjects, so thickening and narrowing of the large airways may serve as surrogate measures to quantify remodeling of the small airways (20). Since the first description of airway dimensions in COPD by Nakano and colleagues, several other groups have attempted to examine the dimensions of smaller airways in COPD (21, 22), but unfortunately failed to identify which airways were actually being measured, thus making comparison among patients with COPD or comparison with pulmonary function rather difficult.

The software that we have developed has the advantage of allowing longitudinal imaging of the airways, enabling identification of the generation of the airways, based on the definition that segmental bronchi are the 3rd generation. Furthermore, we can accurately analyze short-axis images of airways perpendicular to the long axis, and thus do not need to consider the obliquity of targeted airways. Using this software, we analyzed relationships between airflow limitation and airway dimensions up to the 6th generation of bronchi in the upper and lower lobes of patients with COPD. We found that airflow limitation in patients with COPD is more closely linked to the dimensions of distal airways than to those of proximal airways. Two recent studies from different institutes (31, 32) have confirmed that the relationship between airway dimensions and airflow limitation is better in distal airways than in proximal airways. These results clearly support the concept that distal (small) airways, rather than proximal (large) airways, are the more important determinant of airflow limitation in COPD, as has previously been suggested by a number of pathology–function correlation studies (11–14). However, it must be noted that we are not measuring "small airways," as Di of the 6th generation of bronchi was greater than 2 mm on average in our study, and these airways are by definition not "small airways" by any means.

The important role of small airway lesions in COPD airflow limitation has long been recognized (4–6). Hogg and coworkers used a retrograde catheter technique and were the first to report that resistance in small airways of excised lungs from patients with COPD was greatly increased compared with normal lungs, in which 25% of total airway resistance is accounted for by the small airways (4). They further demonstrated that resistance correlated with histologic findings of narrowing and obliteration of small airways along with mucous plugging. Very recently, Hogg and colleagues again demonstrated that, in surgically excised lungs, the severity of small airway disease paralleled the clinical stage of COPD as defined by airflow limitation (33). Obstruction of the small airways consists of airway wall thickening occurring through a remodeling process and airway narrowing resulting from the accumulation of inflammatory cells and exudates in the lumen. Our study confirmed that the inner area and, to a lesser extent, the wall area in distal (small) airways, rather than proximal (large) airways, are closely related to the severity of airflow limitation in patients with COPD in vivo. Unlike Nakano and coworkers (19), we did not identify a significant correlation between FEV1 (%predicted) and WA% in the 3rd generation of B1, although a similar trend was observed in our study. However, the correlation coefficients we obtained for the 5th and 6th generations were as high as 0.6 to 0.7, much better than the correlation coefficient of 0.338 obtained in the 3rd generation of B1 in the study by Nakano and colleagues (19).

LIMITATIONS OF THREE-DIMENSIONAL AIRWAY ANALYSIS

In any analyses of airways in COPD, we must consider possible heterogeneity of airway lesions in the lung. Variations in airway dimensions may exist even in the lungs of normal subjects (34), although Kim and coworkers reported no significant differences in Di of the bronchus divided by Do among segments, lobes, and lungs in normal subjects (35). Conversely, King and colleagues recently reported that airway narrowing after methacholine challenge varied in the large airways of subjects with asthmatics and normal subjects, but not in the small airways (36). Further extensive studies are clearly required to examine possible variations in airway dimensions in COPD.

Second, more attention must be given to the relationship between lung volume and airway dimensions. Theoretically, airway caliber is dependent on lung volume even in the individual lung. Although we measured airway dimensions while subjects were at full inspiration in our first study, confirmation is needed of which lung volume is ideal for correlation studies with pulmonary function parameters. For longitudinal studies, the effects of lung volume on airway dimensions are particularly important as a potential confounding factor.

Third and more importantly, we must prove the accuracy and reproducibility of three-dimensional airway analysis, particularly for measurement of the smaller airways. This might be challenging considering the technical limitations inherent in both CT resolution and software. In addition, we have yet to perform further validation of the new software, which should ideally compare the airway dimensions obtained by CT measurements with those of excised lung specimens.

Finally, it must be noted that Ai is not a pure index of airway disease itself, particularly when measured in vivo. Rather, this parameter is influenced by several direct and/or indirect factors. Airway wall thickening certainly contributes to airway narrowing (37, 38), and secretions or exudates within the airway luminal area may further contribute to airway narrowing. In addition, airway caliber is influenced by the pressure balance between the inside and outside of the airway walls (1, 39). This would hold particularly true for small airways, which lack cartilage in the walls. Our study measured airway dimensions while subjects were holding their breath in deep inspiration. Elastic recoil pressure of the surrounding tissue may thus also have influenced airway caliber. For instance, if the airway being measured was surrounded by lung destruction (emphysema), this would contribute to further airway narrowing as a consequence of lowered elastic recoil pressure in addition to the presence of airway disease. This may account for the relatively higher correlation coefficients of Ai and FEV1 (%predicted) compared with WA% and FEV1 (%predicted) in our study. In addition, even WA% might be influenced by surrounding elastic recoil, since WA% is naturally dependent on Ai. Unfortunately, the current software does not permit the measurement of dynamic changes in airway caliber in association with respiration.

FUTURE DIRECTIONS

Three-dimensional airway analysis holds great promise as a tool for use in the characterization of patients with COPD, and has the potential to be used in both cross-sectional multi-center studies and longitudinal studies. First, we plan to determine the relative contributions of airway disease and emphysema to airflow limitation in a large number of patients with COPD by combined use of volume-based computed analysis of emphysema and three-dimensional airway analysis. Second, to clarify the feasibility of applying airway analysis to longitudinal clinical studies, we will examine short-term changes in bronchial caliber induced by bronchodilators and the possible heterogeneity of bronchodilator responses both within and between subjects. Finally, we wish to analyze longitudinal changes in airway remodeling and emphysema severity among subjects of the Hokkaido COPD cohort study, which is currently underway (3).

CONCLUSIONS

In conclusion, we have developed new software using curved MPR to analyze airway dimensions exactly perpendicular to the long axis of airways at any site in the lungs. Using this software, we have demonstrated in vivo in patients with COPD that FEV1 (%predicted) is highly correlated with airway luminal area and, to a lesser extent, with wall thickening from the 3rd to 6th generations of both B1 and B8, and that correlation coefficients improved as airway size decreased. In the near future, with further advances in CT technology and software, this type of approach will become even more attractive, and may facilitate the use of CT as an endpoint in interventional and therapeutic human studies of COPD.

FOOTNOTES

Supported by Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (17659242 and 19390221 to M.N.) and grants from Nippon Boehringer Ingelheim Co. Ltd and Pfizer Japan Inc.

Conflict of Interest Statement: M.N. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript.

(Received in original form September 24, 2008; accepted in final form October 22, 2008)

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