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Limitations of Airway Dimension Measurement on
Images Obtained Using Multi-Detector Row Computed
Tomography
Tsuyoshi Oguma
1
, Toyohiro Hirai
1
*, Akio Niimi
2
, Hisako Matsumoto
1
, Shigeo Muro
1
,
Michio Shigematsu
3
, Takashi Nishimura
4
, Yoshiro Kubo
5
, Michiaki Mishima
1
1Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan, 2Department of Medical Oncology and Immunology, Nagoya City
University Graduate School of Medical Sciences, Nagoya, Japan, 3Department of Respiratory Medicine, Sumitomo Hospital, Osaka, Japan, 4Department of Respiratory
Medicine, Kyoto-Katsura Hospital, Kyoto, Japan, 5Department of Respirology, Kansai Electric Power Hospital, Osaka, Japan
Abstract
Objectives:
(a) To assess the effects of computed tomography (CT) scanners, scanning conditions, airway size, and phantom
composition on airway dimension measurement and (b) to investigate the limitations of accurate quantitative assessment
of small airways using CT images.
Methods:
An airway phantom, which was constructed using various types of material and with various tube sizes, was
scanned using four CT scanner types under different conditions to calculate airway dimensions, luminal area (Ai), and the
wall area percentage (WA%). To investigate the limitations of accurate airway dimension measurement, we then developed
a second airway phantom with a thinner tube wall, and compared the clinical CT images of healthy subjects with the
phantom images scanned using the same CT scanner. The study using clinical CT images was approved by the local ethics
committee, and written informed consent was obtained from all subjects. Data were statistically analyzed using one-way
ANOVA.
Results:
Errors noted in airway dimension measurement were greater in the tube of small inner radius made of material with
a high CT density and on images reconstructed by body algorithm (p,0.001), and there was some variation in error among
CT scanners under different fields of view. Airway wall thickness had the maximum effect on the accuracy of measurements
with all CT scanners under all scanning conditions, and the magnitude of errors for WA% and Ai varied depending on wall
thickness when airways of ,1.0-mm wall thickness were measured.
Conclusions:
The parameters of airway dimensions measured were affected by airway size, reconstruction algorithm,
composition of the airway phantom, and CT scanner types. In dimension measurement of small airways with wall thickness
of ,1.0 mm, the accuracy of measurement according to quantitative CT parameters can decrease as the walls become
thinner.
Citation: Oguma T, Hirai T, Niimi A, Matsumoto H, Muro S, et al. (2013) Limitations of Airway Dimension Measurement on Images Obtained Using Multi-Detector
Row Computed Tomography. PLoS ONE 8(10): e76381. doi:10.1371/journal.pone.0076381
Editor: Arrate Mun
˜oz-Barrutia, University of Navarra, Spain
Received March 12, 2013; Accepted August 27, 2013; Published October 8, 2013
Copyright: ß2013 Oguma et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was partly supported by JSPS KAKENHI Grant No. 22590861 and a grant to the Respiratory Failure Research Group from the Ministry from
Health, Labour and Welfare, Japan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: t_hirai@kuhp.kyoto-u.ac.jp
Introduction
Computed tomography (CT) is considered a useful technique
for assessing airway dimensions and it is widely used for
noninvasive in vivo structural evaluation of airway remodeling in
asthma and chronic obstructive pulmonary disease (COPD) in
clinical research. Developments in CT scanners and techniques of
image analysis have contributed to the quantitative analysis of
airways by CT density [1–3], as well as the visual assessment of
airways. CT indices such as the ratio of airway wall area (WA) to
total airway wall area (WA%) and luminal area (Ai) have been
used for the quantitative analysis of airway thickening and
narrowing. In COPD, the structural changes and narrowing of
airways caused by chronic inflammation, in combination with
emphysema, contribute to airflow limitation [4]. In addition, the
small airways are key sites of obstruction [5]. Hence, structural
assessment by CT has focused on the smaller and more distal
airways. Some reports have described airway dimension measure-
ment in small bronchi up to the 6
th
or 10
th
generation of airway
branching [6–8], whereas other investigators have reported on the
limitations of accurate CT measurement of small airways [9]. To
validate the methods of airway dimension measurement, airway
phantom models are widely used. However, in some reports
airway dimension measurements have been performed outside the
range validated by their phantoms [6–8], and the materials used
for constructing airway phantoms have been varied–e.g., tubes
made of polyethylene [3], acrylic resin [6], and silicone [7]. In
PLOS ONE | www.plosone.org 1 October 2013 | Volume 8 | Issue 10 | e76381
these studies, they used different phantom materials, different CT
scanners and different scanning conditions: hence, what had
effects on errors in airway dimension measurement and what
decided the limitations to accurate dimension measurement of
small airways are not clear. In addition, to date, no report has
examined the effects of phantom materials and their CT density
on errors in airway dimension measurement using different CT
scanners and scanning conditions.
Thus, the purpose of this study was to assess the effects of CT
scanners, scanning conditions, airway size, and phantom con-
struction on airway dimension measurement and then to
investigate the limitations of accurate quantitative CT assessment
of small airways.
Materials and Methods
Ethics Statement
The study using clinical CT images was approved by the ethics
committee of Kyoto University (approval No. E-829), and written
informed consent was obtained from all subjects.
1. The Effects of Scanning Conditions and CT Scanner
Type on Errors in Airway Dimension Measurement:
Phantom Study
Airway phantom. An airway phantom (phantom A: Kyoto
Kagaku Co., Ltd., Kyoto, Japan) comprising various sets of
different materials and tube sizes was used in this study. The tubes
(5-cm long) were composed of three types of material [fluorocar-
bon polymers (physical density: 2.1 g/cm
3
), acrylic resin (1.2 g/
cm
3
), and polyethylene (0.9 g/cm
3
)] that are embedded in three
types of material mimicking lung parenchyma [phenol resin
(0.32 g/cm
3
), acrylic foam (0.10 g/cm
3
), and air]. In addition, six
sets differing in the inner radius and wall thickness were made for
each different tube material type (Table 1). The tubes were
measured by a digital caliper (accuracy of wall thickness
#0.03 mm). All tubes were placed circularly in the same manner,
regardless of material type, and were embedded in each of the
three phantom lung parenchyma materials (Figure 1). Using this
phantom, a total of 54 sets of tubes were analyzed, comprising
combinations of three lung materials, three tube materials, and six
tube sizes.
CT scans. Computed tomography scanning was performed
in helical mode using four types of multi-detector row CT
(MDCT) scanners with 64 detectors (Table 2). We used Aquilion
64 (Toshiba, Tokyo, Japan) as the primary unit, then examined
the differences in results between this equipment and the other
three CT scanners (Light Speed VCT, GE Healthcare UK,
Buckinghamshire, UK; Brilliance 64, Philips, Eindhoven, Nether-
lands; and SOMATOM Definition, Siemens, Munich, Germany).
CT scans were acquired from four scanners with various scanning
conditions and reconstructions shown in Table 2. The phantom
was placed on the table strictly perpendicular to the scan slices. To
measure the tube sections at different oblique angles, the phantom
was then placed obliquely to the scan slices at 30uintervals from 0u
to 90uwhen scanned using Aquilion 64 with the scanning
parameters of 120 mAs and 350-mm FOV.
Airway dimension measurement. Airway measurements
were made using software described previously, with modifications
[3]. This software analyzed the dimensions of airways and tubes as
follows: first, the section in which the tube had the smallest area
and greatest circularity was selected as the provisional section for
each of the seven planes: i.e., horizontal, coronal, sagittal, and the
planes passing through the middle of these standard three planes.
Second, the center line of the tube was calculated by linking the
center points of the luminal areas of the provisional section with
the adjacent front and rear sections (Figure 2A). Third, the wall
and lumen of the tube were reconstructed three-dimensionally
along the center line (Figure 2B). Fourth, slice images perpendic-
ular to the center line were reconstructed using trilinear
interpolation, and on these images Ai, WA, and wall thickness
(WT) were calculated using the full-width half-maximum (FWHM)
method, as reported previously [3]. WA% was defined as WA/
(Ai+WA)6100. All these steps were performed using images with a
46magnification, and the middle two-thirds of the tubes in
phantom (3.3 cm long, about 190 slices) were analyzed. Finally,
mean values of Ai, WA%, and WT were calculated.
Comparison between actual values and CT
measurements. We assessed the errors in CT measurement
as a percentage of the actual values using the following formula:
Error (%)~CT measurement {actual value
actual value |100
2. Limitations of Airway Dimension Measurement Using
Clinical CT Images and a Second Airway Phantom
To apply the phantom study for clinical CT images and
investigate how distal generation of airway branching can be
Table 1. Tube sizes in airway phantom A.
Tube Number
123456
Inner radius (mm) 3 2 1.5 1 1.5 1
Wall thickness (mm) 1 1 1 1 0.5 0.5
doi:10.1371/journal.pone.0076381.t001
Figure 1. Axial slice computed tomography (CT) image of
phantom A. The inner space of the cylindrical container is filled with
successive layers of three materials: phenol resin, acrylic foam, and air. A
total of 18 tubes (three materials6six sizes) were embedded through
each layer (50 or 60 mm in length).
doi:10.1371/journal.pone.0076381.g001
Limitations of Airway Measurement on CT Images
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measured accurately, chest CT images in 10 healthy adults (mean
age: 62.0 years, range: 38–80 years; male/female: 2/8) were used
to analyze airway dimensions of the right posterior basal bronchus
and more distal bronchi (3
rd
–6
th
generation) by the same method
as in the phantom study. All subjects visited Kyoto University
Hospital for further examination of chest X-ray abnormalities and
underwent CT scanning with Aquilion 64 (350-mm FOV and lung
algorithm FC56). No contrast media were used. Subjects had no
respiratory symptoms, no history of respiratory disease, and no
abnormal findings on spirometry or chest CT.
According to the results obtained using airway phantom A, we
developed a second, thin-walled airway phantom (phantom B) to
assess the lower limitations of airway dimension measurement. In
phantom B, six acrylic resin tubes (inner radius: 1.5 mm) with
varying wall thickness (1.0, 0.9, 0.8, 0.7, 0.6, 0.5 mm) were placed
circularly and embedded in air. This phantom was then scanned
using Aquilion 64 (350-mm FOV and lung algorithm FC56).
Statistical Analysis
Data were statistically analyzed using one-way ANOVA in
differences between materials, tube sizes, scanners, and scanning
conditions with JMP 6.0.3 software (SAS Campus Drive, Cary,
NC, USA). Graphs were displayed as average with standard
deviation (SD).
Results
Effect of Scanning Conditions on Airway Dimension
Measurements
Figure 3A shows the errors recorded using Aquilion 64 from
actual values of WA% on images under varying FOVs and slice
thickness. Although the images scanned under lower FOVs were
associated with smaller error values, errors in tubes #5 and #6
with 0.5-mm wall thickness were .32% for all combinations of
FOV and slice thickness. The differences in errors between slice
thicknesses were less than those among FOVs. These results were
similar to the errors recorded for Ai.
Variations in radiation exposure (measured in mAs) had very
little effect on measured values. Maximum differences in error for
WA% between two exposures were 0.26%, 0.95%, 0.56%, and
0.72% for Aquilion 64, Light Speed VCT, Brilliance 64, and
SOMATOM Definition, respectively.
Figure 3B shows a comparison of error according to WA% for
each tube using the three different reconstruction algorithms [body
algorithm (FC13), lung algorithm (FC51), and lung algorithm with
beam-hardening correction (FC56)] using Aquilion 64. Errors
were significantly greater on images reconstructed by the body
algorithm than the lung algorithm (p,0.001 in tubes #1to#3).
Using the three other CT scanners, errors were also larger on
images reconstructed by the body algorithm than the lung
algorithm.
Effect of Phantom Materials on Measurement of Tube
Dimensions
The effects of differences in phantom materials on measurement
of tube dimensions are shown in Figure 4. The mean values of CT
density in the phantom materials mimicking lung parenchyma and
the mean values of maximum CT density in the tube walls on the
images scanned using four scanners (120 mAs, 350-mm FOV, and
lung reconstruction algorithm) are shown in Table 3. On images
scanned using Aquilion 64 (120 mAs, 0.5-mm collimation, 0.5-
mm slice thickness, 350-mm FOV, and lung reconstruction
algorithm FC56), the errors in WA% and Ai for acrylic resin
tubes enclosed by the three different materials used in the lung
phantom are shown in Figure 4A. The effect of differences in
materials used for the simulated lungs was quite small (,5.2% in
Table 2. The four CT scanners used in assessments and their respective scanning data.
CT Scanner
Aquilion 64 Light Speed VCT Brilliance 64 SOMATOM Definition
kVp (kV) 120 120 120 120
Exposure (mAs) 120/AEC 120/60 120/60 120/60
FOV (mm) 350/200 350/200 350/200 350/200
Reconstruction algorithm FC13/FC51/FC56 Standard/Lung B/YA B30/B70
Slice thickness and interval (mm) 1/0.5 0.625 0.67 0.6
kVp, kilovolts peak; FOV, field of view; AEC, automatic exposure control (actual range in this study: 25–30 mAs).
doi:10.1371/journal.pone.0076381.t002
Figure 2. Schema describing the method of airway dimension
measurement. A: Using sequential CT slices which included a section
of the target tube, the center (solid) line of the tube was calculated by
linking the center points of sections on each slice. B: Images were
constructed perpendicular to the center line.
doi:10.1371/journal.pone.0076381.g002
Limitations of Airway Measurement on CT Images
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tubes #1to#4). Figure 4B shows errors for WA% and Ai in tubes
made of the three different materials surrounded by acrylic foam.
The absolute value of error of measured Ai in the tube made of
fluorocarbon polymers with 1.0-mm inner radius and 1.0-mm wall
thickness (tube #4) was much greater than that in the tubes made
of other materials (p,0.001). Thus, the minimum limit of tube size
that could be measured with small error was greater in
fluorocarbon polymer tubes than in tubes made of polyethylene
or acrylic resin.
Figure 3. Effects of scanning conditions on errors of airway dimension measurement. A: Effects of field of view (FOV) and slice thickness
on errors for wall area percentage (WA%) in acrylic resin tubes surrounded by acrylic foam that were scanned using Aquilion 64 (120 mAs and lung
algorithm FC56). B: Effects of the reconstruction algorithm on the errors of WA% in acrylic resin tubes surrounded by acrylic foam that were scanned
using Aquilion 64 (120 mAs, 0.5-mm slice thickness, 350-mm FOV). FC13: body algorithm, FC51: lung algorithm, FC56: lung algorithm (FC51) with
beam-hardening correction. *: failure to measure. The error of airway dimensions was defined as follows: Error (%) = (CT measurement 2actual
value)/actual value6100.
doi:10.1371/journal.pone.0076381.g003
Figure 4. Effects of phantom composition on errors of airway dimension measurement. Percentage error of wall area (WA%) and luminal
area (Ai) for the phantom scanned using Aquilion 64 (120 mAs, 0.5-mm slice thickness, 350-mm FOV, lung reconstruction algorithm FC56). A:
Comparison of errors of WA% and Ai for acrylic resin tubes among materials simulating lung parenchyma, phenol resin (0.32 g/cm
3
), acrylic foam
(0.10 g/cm
3
), and air. B: Comparison of errors for WA% and Ai among tube materials, fluorocarbon polymers (2.1 g/cm
3
), acrylic resin (1.2 g/cm
3
), and
polyethylene (0.9 g/cm
3
) embedded in acrylic foam.
doi:10.1371/journal.pone.0076381.g004
Limitations of Airway Measurement on CT Images
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Effect of Phantom Angles on Measurement of Tube
Dimensions
The results described above were similar even when the
phantom was placed obliquely to the scanning section at various
angles (0u–90u). Absolute values of error in tubes #5 and #6, both
with wall thickness of 0.5 mm, were .38% at all angles.
Maximum differences in errors between phantom angles were
small (,7%) (Table 4). These results were similar in images with
1.0-mm slice thickness, and maximum differences in errors
between phantom angles were ,10%.
Difference between CT Scanners
Figure 5 shows a comparison of errors for WA% and Ai among
the four CT scanners under two different FOVs. In all CT
scanners under both FOVs, the absolute values of errors for WA%
and Ai in tubes of 0.5-mm thickness were .33% and 11%,
respectively. However, there were certain differences in errors in
tubes #1to#4 among CT scanners under different FOVs. The
errors for WA% in tubes #1to#3 using Brilliance 64 under 350-
mm FOV were greater than those using other scanners (p,0.001),
and these errors using Brilliance 64 improved when scanning was
carried out under 200-mm FOV. On the other hand, errors for Ai
in one tube (#4) with 1.0-mm inner radius and 1.0-mm wall
thickness using Light Speed VCT and SOMATOM Definition
were greater (.18%), and these did not improve even under a
smaller FOVs.
Limitations of Airway Dimension Measurement Using
Clinical Images and Airway Phantom B
Table 5 shows the dimension measurement of the airways of the
right posterior basal bronchus (3
rd
generation) and more distal
bronchi. Although the average inner radius and WT of the 6
th
bronchus were 1.44 mm and 1.06 mm, respectively, some subjects
showed WT of ,1.0 mm in the 5
th
and more distal bronchi
(Figure 6).
Figure 7 and Table 6 show a comparison of errors for Ai,
WA%, and WT among tubes of varying wall thickness in the
images of airway phantom B scanned using Aquilion 64. The
errors for WA% and WT increased with thinness of airway wall,
whereas the errors for Ai were ,5% in tubes of $0.7-mm wall
thickness.
Discussion
This study showed two main findings with regard to airway
dimension measurement by CT imaging. First, the error of
measurement varies with regard to CT scanner, reconstruction
algorithm, and airway phantom construction. This suggests that in
airway dimension measurement using clinical CT imaging,
validation using the same scanner and scanning conditions is
necessary, and materials of similar CT density to that of bronchial
wall should be used for the airway phantom in validation studies.
Second, errors in the widely used quantitative CT parameters,
WA% and luminal area, could depend on WT, particularly when
distal airways of ,1.0-mm WT are measured.
To investigate the pathophysiology of obstructive lung disease,
the assessment of airway remodeling in the smaller and more distal
airways using MDCT was considered following the development
of CT scanners and techniques of image analysis. Because CT
images have certain limitations with regard to spatial resolution, it
is important to be aware of the errors and limitations of airway
dimension measurement. Thus, phantom studies have been widely
used for the validation of methods. However, several reports using
phantoms have presented findings for small and distal airway
dimensions that were outside the range validated by their
particular study [6–8]. Although Hasegawa et al. [6] showed that
the average WT in the 6
th
branch was 0.9 mm, wall thickness of
the phantom tubes used in that validation study was 1.0 mm.
Montaudon et al. [7,8] reported that WT of the 10
th
branch
measured ,0.2 mm, but the airway phantom in their validation
Table 3. The mean values of CT density (HU) in the phantom materials mimicking lung parenchyma and the mean values of
maximum CT density in the tube walls.
CT Scanner
Aquilion 64 Light Speed VCT Brilliance 64 SOMATOM Definition
phenol resin 2653.1 (39.3) 2666.7 (24.2) 2671.4 (27.7) 2672.5 (37.6)
acrylic foam 2930 (25.7) 2923.4 (16.0) 2923.4 (18.1) 2918.7 (26.2)
air 21014 (22.3) 2999.83 (12.3) 2999.8 (14.5) 2999.0 (20.7)
fluorocarbon polymers 1163.4 (134.4) 1370.3 (152.0) 543.6 (73.3) 1326.2 (166.6)
acrylic resin 209 (80.6) 348.5 (87.7) 2108.6 (34.3) 285.2 (93.2)
polyethylene 231.4 (61.1) 39.5 (63.8) 2295.0 (30.8) 3.0 (76.6)
Average of measured values (SD).
doi:10.1371/journal.pone.0076381.t003
Table 4. Effects of phantom angles on errors of airway
dimension measurement.
angle Tube Number
123456
0u8.27
(0.59)
5.56
(0.70)
5.87
(0.5)
6.02
(1.65)
45.43
(2.62)
44.76
(1.01)
30u7.61
(0.92)
4.11
(1.43)
5.16
(1.13)
3.88
(0.57)
46.77
(0.81)
40.93
(2.28)
60u6.68
(0.58)
5.52
(0.98)
4.64
(0.46)
5.01
(0.90)
46.34
(1.69)
40.21
(1.40)
90u6.73
(0.94)
7.31
(0.08)
3.89
(0.02)
5.93
(1.18)
49.45
(1.50)
38.39
(1.61)
Percent errors from actual value (SD).
Errors of WA% in acrylic resin tubes embedded in acrylic foam at various angles
using Aquilion 64 (120 mAs, 0.5-mm slice thickness, 350-mm FOV, lung
reconstruction algorithm FC56).
doi:10.1371/journal.pone.0076381.t004
Limitations of Airway Measurement on CT Images
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study had wall thickness of $0.86 mm. Moreover, the phantom
materials used for validation varied with the studies. For
quantitative analysis using CT images, it is appropriate that the
CT density of the phantom material simulates the density of the
actual airway wall (0–400 HU) and surrounding lung parenchyma
(2900 to 2800 HU). However, to our knowledge, no reports have
shown how phantom materials and their CT density affect airway
dimension measurement. In the present study, the effects of lung
phantom composition were limited. On the other hand, with
regard to airway phantom composition, the errors for Ai were least
in acrylic resin tubes. A small tube (1.0-mm inner radius)
constructed from fluorocarbon polymers showed the largest error
for Ai compared with those of other materials. Materials such as
fluorocarbon polymers, which have a higher CT density than the
human bronchial wall, may not be suitable for use in the airway
phantom.
Next, using four CT scanner types, we investigated the effects of
scanning conditions and reconstruction algorithm on the error of
airway dimensions. The effects of radiation exposure and slice
thickness were found to be very small in ranges used to assess
airway dimensions. Robinson et al. [10] also reported that
radiation dose had no effect on measurement error. Our results
showed that, for all CT scanners used, the reconstruction function
for lung images was correct for airway dimension measurement,
whereas that for body images was not. Saba et al. [11] reported
that mean error decreased as image sharpness increased when
using the Imatron electron beam CT scanner, and Kim et al. [12]
reported similar results using the Siemens Sensation 16 CT
scanner when they analyzed images obtained using the FWHM
method. Regarding the effect of FOV, Saba et al. [11] and Kim
et al. [12] reported a similar error for all FOVs studied, whereas
Takahashi et al. [13] reported that FOV had an inuence on
airway dimension measurement especially for the tubes of 1.0-mm
wall thickness when using Light Speed VCT. In the present study,
we found variation in the error of airway dimension measurement
and in the effect of FOV among CT scanners. These results
suggest that it is important to validate the characteristics of the
method employed, including software and hardware, before
obtaining clinical images.
Figure 5. Effects of CT scanner and FOV on errors of airway dimension measurement. Comparison of errors WA% and luminal area (Ai) in
acrylic resin tubes embedded in acrylic foam among four CT scanners under varying FOV (A: 200 mm, B: 350 mm). The images were reconstructed by
the lung algorithm. The definition of error is shown in the legend to Figure 3.
doi:10.1371/journal.pone.0076381.g005
Table 5. Dimension measurement of the airways of the right basal bronchus (by generation) in healthy subjects.
3
rd
4
th
5
th
6
th
Inner radius (mm) 2.50 (1.73–3.26) 2.27 (1.28–3.10) 1.79 (0.89–2.38) 1.44 (0.84–2.27)
Wall thickness (mm) 1.29 (1.12–1.48) 1.23 (1.01–1.57) 1.12 (0.98–1.30) 1.06 (0.93–1.31)
Average (range).
doi:10.1371/journal.pone.0076381.t005
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The factor having the greatest effect on airway dimension
measurement in the present study was wall thickness. Tubes of 0.5-
mm wall thickness could not be measured with sufficient accuracy
with any scanner under any scanning parameters, even when the
inner radius (1.5 mm) was greater than the minimum limit of 1.0-
mm wall thickness. This result can be explained by the fact that
the dimension of 0.5 mm is close to the size of the detector and
pixel dimensions that are responsible for resolution on clinical CT
images. From our study using airway phantom B with thinner
walls, the luminal area of tubes of $0.7-mm wall thickness could
be accurately measured with an error ,5%, whereas the error for
WA% and WT increased with thinness of airway wall in tubes of
,1.0-mm wall thickness. In practical use, when 1-mm wall
thickness (error ,10%) is set to be the limitation for accurate
measurement, measured WT values less than 1.12 mm is not
accurate in the present study (Table 6 and Figure 7). This means
that some measured values in bronchial branching of the 5
th
generation or more were not accurate in dimension measurement
of the airways of the right basal bronchus using clinical images of
healthy subjects (Table 5). The present study suggests that the
quantitative CT parameters WA% and Ai may be associated with
greater error depending on the thinness of the airway wall,
especially when small and distal airways of #1.0-mm WT are
measured. For example, the differences in WA% between healthy
controls and patients with asthma were reported to be 5–10%
[14], and thus, errors more than 10% can be too large to detect
changes in diseases accurately. This means that there may be
severe limitations to assess peripheral small airways directly using
CT images.
There are some limitations to this study. First, we were unable
to investigate the effects of different algorithms on errors in airway
dimension measurement. Several alternative methods, such as the
maximum-likelihood algorithm [15], a method of ellipse fitting to
the airway lumen and wall [11], a score-guided erosion algorithm
Figure 6. Examples of airways measured at different generations. The representative images of right posterior basal bronchi (3
rd
generation)
and more distal bronchi of a healthy control on Aquilion 64 (Auto Exposure Control, 0.5-mm slice thickness, 350-mm FOV, lung reconstruction
algorithm FC56). At the 6
th
to 7
th
generation, the thickness of the bronchus wall had equal or less than pixels size.
doi:10.1371/journal.pone.0076381.g006
Figure 7. Effects of wall thickness on errors of airway dimension measurement. Comparison of errors of Ai, WA%, and wall thickness (WT)
for various wall thickness using airway phantom B scanned by Aquilion 64 (120 mAs, 0.5-mm slice thickness, 350-mm FOV, and lung reconstruction
algorithm FC56).
doi:10.1371/journal.pone.0076381.g007
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[16], and an integral-based method [17], have been reported
previously. When using different algorithms for airway analysis,
the effects on measurement accuracy may be different. However,
the FWHM principle used in this study is the most widely used
method, and there is no clear indication that any one algorithm
provides more useful data than another [9]. Moreover, also in
those reports, when wall thickness was ,1.01–1.16 mm, mea-
surement errors were .10% [11,15–17], as shown in the present
study using the FWHM principle. This may suggest that small
airway measurement using any algorithms for the measurement of
distance close to spatial resolution of CT images can have larger
errors. A further limitation is that accuracy is not guaranteed in
phantom airway dimension measurement. The inner and outer
contours of actual airways are not always completely circular and
their walls are not homogeneous with regard to physical density.
However, to validate this method of analysis, a phantom study is
required to define the errors of measurements, and it is widely used
for such validation.
Conclusions
In conclusion, the parameters of airway dimensions measured
using CT images were affected by airway size, reconstruction
algorithm, composition of the airway phantom, and CT scanner
types. In dimension measurement of small airways with wall
thickness of ,1.0 mm, the accuracy of measurement according to
quantitative CT parameters can decrease as the walls become
thinner.
Acknowledgments
The authors wish to thank Mr. K. Koizumi and Mr. R. Tanaka (both
Clinical Radiology Service, Kyoto University Hospital) for their technical
assistance with regard to CT scanning, and Kyoto Kagaku Co., Ltd.
(Kyoto, Japan) for their assistance with regard to the development of the
phantom.
Author Contributions
Conceived and designed the experiments: TO TH MM. Performed the
experiments: TO TH AN HM SM MS TN YK. Analyzed the data: TO
TH. Contributed reagents/materials/analysis tools: TO TH AN HM SM.
Wrote the paper: TO TH.
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Table 6. Effects of wall thickness on airway dimension
measurement.
Actual wall thickness (mm)
1 0.9 0.8 0.7 0.6 0.5
Ai (mm
2
) 7.37
(0.05)
6.97
(0.08)
6.76
(0.29)
6.87
(0.15)
6.30
(0.29)
5.99
(0.16)
WA% (%) 66.60
(0.38)
66.41
(0.35)
66.42
(0.87)
62.18
(0.40)
64.27
(1.29)
63.76
(0.35)
WT (mm) 1.12
(0.01)
1.08
(0.01)
1.06
(0.01)
0.93
(0.01)
0.95
(0.02)
0.91
(0.00)
Average of measured values (SD).
Measured values of Ai, WA%, and wall thickness (WT) for various wall thickness
using airway phantom B (actual luminal area: 7.07 mm
2
) scanned by Aquilion 64
(120 mAs, 0.5-mm slice thickness, 350-mm FOV, and lung reconstruction
algorithm FC56).
doi:10.1371/journal.pone.0076381.t006
Limitations of Airway Measurement on CT Images
PLOS ONE | www.plosone.org 8 October 2013 | Volume 8 | Issue 10 | e76381
