DOI:10.2214/AJR.06.1169
AJR 2007; 188:945-952
© American Roentgen Ray Society
Automated Polyp Measurement with CT Colonography: Preliminary Observations in a Phantom Colon Model
Joel G. Fletcher1,
Fargol Booya1,
Zachary Melton1,
Kristina Johnson1,
Lutz Guendel2,
Bernhard Schmidt2,
Cynthia H. McCollough1,
Brett Young1,
Jeff L. Fidler1 and
William S. Harmsen1
1 Department of Radiology, Mayo Clinic, 200 First St. SW, Mayo E-2, Rochester,
MN 55905.
2 Siemens Medical Solutions, Malvern, PA.
Received August 31, 2006;
accepted after revision October 11, 2006.
Address correspondence to J. G Fletcher
(fletcher.joel{at}mayo.edu).
This study was reviewed and approved by the institutional conflict of
interest committee of the Mayo Clinic. The authors from Mayo Clinic Rochester
had sole control of all data and subsequent statistical analysis. Data
generated were analyzed by a biostatistician without conflict of interest
using internal funds at Mayo Clinic Rochester. Siemens Medical Solutions
provided the automated polyp measurement software and the CT system.
J. G. Fletcher and C. H. McCollough receive partial salary support through
an unrestricted grant from Siemens Medical Solutions.
L. Guendel and B. Schmidt are employees of Siemens Medical Solutions and
assisted with software installation and training and manuscript preparation.
The experimental design was developed by collaborators from both
institutions.
Abstract
OBJECTIVE. The purpose of this study was to evaluate the accuracy
and precision of polyp measurements obtained with an automated tool in a colon
phantom containing polyps of multiple sizes, morphologic types, and
locations.
MATERIALS AND METHODS. A colon phantom was scanned at 12, 25, 50,
and 100 mA with standard CT colonographic acquisition parameters. Four
reviewers using manual 2D methods and an automated polyp measurement tool
measured 24 polyps of varying sizes and morphologic types, some at a haustral
fold tip and some not at a fold tip. The accuracy (difference from true value)
of manual and automated methods was compared across polyp sizes, morphologic
types, locations, and doses. Precision (closeness of different measures) was
compared for intraobserver and interobserver measurements.
RESULTS. The accuracy of automated polyp measurement was dependent
on morphologic type (p 
0.02), size (for three of four reviewers,
p 0.05), and location of polyps with respect to haustral folds
(two of four reviewers, p 0.01). For two of four reviewers,
automated measures were less accurate for 5-mm polyps, flat polyps, and polyps
at the tips of folds (p 0.04). Intraobserver precision was high,
two automated measurements being within 0.1 mm of each other 82-93% of the
time. Interobserver precision values for automated measures were more similar
85% of the time (82/96; p <0.001).
CONCLUSION. Accuracy of automated polyp measurements depends on
polyp size, morphologic type, and location. When using an automated tool,
radiologists should visually inspect automated polyp measurements,
particularly for small and flat polyps and those located on folds, because
manual measurements may be more accurate in this setting. Automated polyp
measurements are more precise than manual measurements.
Keywords: colon cancer • CT colonography • polyps
Introduction
CT colonography is an effective alternative for colorectal cancer
detection
[1-6].
The malignant potential of a polyp at colorectal structural examination is
estimated according to size, polyps 10-20 mm in diameter having an
approximately 4% risk of being carcinoma and a 21% risk of being high-grade
dysplasia [7,
8]. Subcentimeter polyps, on
the other hand, carry a much lower risk of being carcinoma ( 1%) or
high-grade dysplasia (3-5%) [9,
10].
In our colonographic practice, an increasing number of patients with polyps
are undergoing follow-up with CT colonography, particularly when the polyps
detected on colonography are of subcentimeter size or when patients have
comorbid conditions that increase the risk of endoscopic polypectomy. The
Working Group on Virtual Colonoscopy
[11] has recommended that
"for patients who do not have increased risk factors for development of
colorectal carcinoma...it is reasonable to recommend interval surveillance
when one or two 6-9 mm lesions are detected." Accurate measurement of
polyp size is needed to assess the risk of malignancy and the need for
referral for endoscopic polypectomy. Precise measurement of polyp size is
needed to assess for interval growth of polyps on follow-up imaging. The
purpose of our study was to assess the accuracy and precision of an automated
polyp measurement tool on CT colonography of a colon phantom containing polyps
of known sizes.
Materials and Methods
A colonic phantom consisting of hand-blown glass containing curved and
straight segments and haustral folds was filled with synthetic epoxy resin and
powder polyps (Solid Water, Gammex RMI) precisely milled in four sizes (5, 7,
10, and 12 mm). Polyps were milled to pedunculated, sessile, and flat shapes
as previously described [12].
Sessile polyps had a height equal to the diameter of the base, and flat polyps
had a height equal to one half the base. Pedunculated polyps had a stalk,
which was of less circumference than the polyp head and connected the polyp to
the colon phantom wall. The stalk was of the same length as the polyp head
diameter. For sessile and flat polyps, the known size of the polyp referred to
the greatest diameter at the base of each polyp. For pedunculated polyps, the
known size referred to the greatest diameter of the polyp head.
The colon phantom was submerged in a water bath simulating the attenuation
of the body cavity and was scanned with a 64-MDCT system (Sensation 64,
Siemens Medical Solutions) with four tube current values (12, 25, 50, and 100
mA). All other CT acquisition parameters were identical, corresponding to
those used in clinical practice (effective tube current, 120 kVp; tube
rotation time, 0.5 second; reconstruction kernel, B30f). All data sets were
reconstructed axially with 1.0-mm slice thickness and 0.8-mm reconstruction
interval.
CT colonography data sets were interpreted by reviewers using a Leonardo
workstation and Syngo Colonography software package with an automated polyp
measurement tool (Siemens Medical Solutions). Reviewers had 1-8 years of
experience in interpreting CT colonographic data sets and had participated in
one human or phantom study requiring manual polyp measurement. Each CT data
set was evaluated by four reviewers, who reported linear measurements for 24
polyps. There were six polyps of each size (5, 7, 10, and 12 mm). The polyps
in each size group were of three morphologic types (pedunculated, sessile, or
flat) and two locations (located at the tip of a haustral fold or not located
at the tip of a fold [i.e., between folds]).
Each reviewer evaluated four CT data sets (one at each dose level),
performing two automated measurements and one manual measurement. We performed
only one manual measurement because we had previously studied the accuracy and
precision of manual measurements
[13]. Reviewers performed the
automated measurements by activating the automated measurement tool and
clicking the computer mouse when the cursor was at various points along the
surface of a polyp on the 3D endoluminal view. The second automated
measurement was performed immediately after the first, but reviewers were
instructed to rotate the 3D view and click on a different point on the polyp
surface for the second measurement. The automated polyp measurement tool
showed the size of the polyp and circumscribed the measured polyp on 2D and 3D
views (Fig. 1A,
1B,
1C,
1D,
1E,
1F,
1G,
1H). Manual polyp measurements
were performed with a linear line tool and oblique 2D multiplanar reformatted
images at lung window settings
[13]. Care was taken to
measure the single largest linear dimension of the polyp head without the
stalk [11].
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Fig. 1A —Colon phantom. Images show use of automated polyp measurement tool.
Three-dimensional endoluminal view obtained with 50-mA data set shows 7-mm
sessile polyp not on haustral fold. After activation of automated polyp
measurement tool, single mouse click was made at tip of arrow. 3a = polyp
number assigned as part of study.
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Fig. 1B —Colon phantom. Images show use of automated polyp measurement tool.
Two-dimensional multiplanar reformation (MPR) corresponding to polyp in
A shows how automated polyp measurement tool circumscribes polyp in
box. Reported measurement is 0.63 cm. 3a = polyp number assigned as part of
study.
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Fig. 1D —Colon phantom. Images show use of automated polyp measurement tool.
Three-dimensional endoluminal view of polyp in A shows polyp boundaries
circumscribed with automated polyp measurement tool (box). 3a = polyp
number assigned as part of study.
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Fig. 1E —Colon phantom. Images show use of automated polyp measurement tool.
Three-dimensional endoluminal view of polyp in A with orientation
changed. Automated polyp measurement tool is activated by clicking on another
point (arrow) on polyp surface. 3a = polyp number assigned as part of
study.
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Fig. 1F —Colon phantom. Images show use of automated polyp measurement tool.
Two-dimensional MPR image corresponding to polyp measurement in E.
Automated polyp measurement device shows diameter of 0.63 cm. 3a = polyp
number assigned as part of study.
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Fig. 1G —Colon phantom. Images show use of automated polyp measurement tool.
Three-dimensional endoluminal view of polyp in A-F obtained from 12-mA
data set. Automated polyp measurement tool circumscribes borders of polyp
(box). 2a = polyp number assigned as part of study.
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In constructing the experiment, we planned to sample as many polyps with
the given characteristics (morphologic type, size, location in relation to tip
of fold, dose) as possible and to hold other factors constant. We consequently
examined three sets of polyps with the given characteristics across the four
dose levels (Fig. 2). Reviewers
1 and 2 each measured a different set of 24 polyps over the four dose levels
(e.g., reviewer 1 examined the same 24 polyps at each dose). Data obtained
from reviewers 1 and 2 were used to determine the effect of dose on the
accuracy of automated polyp measurements. Reviewers 3 and 4 examined identical
polyps at each dose level, but the polyps at each dose level were different.
Data from reviewers 3 and 4 were used to determine interobserver precision
between two reviewers for a large number of polyps of different sizes,
morphologic types, and locations.
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Fig. 2 —Chart shows experimental design. Each reviewer performed two
automated measurements and one manual measurement for each polyp in each data
set. Each data set contained 24 polyps of three morphologic types
(pedunculated, sessile, or flat), four sizes (5, 7, 9, or 12 mm), and two
locations (tip of fold or not). Brackets indicate how measurement data were
pooled to address specific questions.
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Accuracy was measured as the absolute value of the difference between polyp
measurement and true size. Univariate regression was used to assess the
association between the accuracy of automated polyp measurement and polyp
size, morphologic type, and location for all reviewers. Accuracy of automated
polyp measurement across the four dose levels was assessed with data from
reviewers 1 and 2, who examined the same polyps at each dose level.
Multivariable regression analyses were performed for each reviewer to
determine which, if any, polyp features were independently associated with the
accuracy of automated measurement. Forward and stepwise selection procedures
were used for this modeling.
Intraobserver agreement of automated measurement was estimated for each of
the four observers by calculation of the difference between the two automated
measurements. Interobserver agreement was estimated between reviewers 3 and 4,
who evaluated the same data sets, by calculation of the difference between
their first automated measurements and the manual measurements. Both
interobserver and intraobserver agreement were estimated with the intraclass
correlation coefficient. Each observer evaluated all polyps, and the reviewers
in this study were assumed to be a random subset of radiologists.
Precision, both within an observer and between two observers, was estimated
with the coefficient of variation and estimation of the number of times two
different automated measures were 0.1 mm or less apart. A coefficient of
variation is the relative variance of the measured values from the mean (i.e.,
SD of differences divided by mean value of the differences). For reviewers 3
and 4, who measured the same polyps in every data set, we also counted the
number of times automated measurements between reviewers were closer than
manual measurements between reviewers.
The precision of automated measurement compared with the precision of
manual measurement was estimated, with precision being the absolute value of
the difference between the automated or manual measurements. For reviewers 3
and 4, the association between this difference in precision of the automated
and manual methods and the four polyp characteristics was made with linear
regression, as was done for the accuracy of automated measurement.
Results
Accuracy of Automated Polyp Measurement
Table 1 summarizes mean
absolute error and SD calculated as the absolute value of the difference
between the automated measurement and the known polyp size, according to polyp
characteristics and dose, for all four reviewers.
Table 2 shows the accuracy of
automated and manual measurements (i.e., mean absolute error) of polyps for
each characteristic (size, morphologic type, and location) with averages
across reviewers and doses.
Polyp size—For one of four reviewers, there was a
significant overall negative association between increasing polyp size and
absolute error with the automated measurement tool (p = 0.04). For
three of the four reviewers, the mean absolute error associated with automated
measurement of 5-mm polyps was significantly greater than the mean absolute
error associated with measurement of 12-mm polyps (p = 0.03-0.05). In
comparing automated with manual measurement accuracy, two of four reviewers
found that manual measurements had significantly better measurement accuracy
for 5-mm polyps (p = 0.037) compared with 12-mm polyps (p =
0.05). No reviewer had a significant difference in accuracy between manual and
automated measurements for polyps measuring 7 or 10 mm compared with 12-mm
polyps.
Morphologic type—There was a significant association between
morphologic type and absolute error of automated measurement for each of the
four reviewers (p 0.02 for each). All four reviewers found that
the automated polyp measurement tool was more accurate in measurement of
pedunculated polyps compared with flat (p 0.01 for each of the
four) and sessile (p 0.05 for each) polyps
(Table 1). Two of four
reviewers found that manual technique improved the accuracy of measurement of
flat polyps (p = 0.023) compared with that of pedunculated polyps
(p = 0.05). There was no significant difference in accuracy between
manual and automated measurements of sessile compared with pedunculated polyps
(p >0.05 for each of these comparisons).
Polyp location—Two of four reviewers found significantly
better accuracy of automated measurement for polyps not located on the tip of
a fold (p = 0.001 and p < 0.01). Data from these
reviewers indicated that polyps on the tips of folds, compared with those not
on the tips, were measured more accurately with manual techniques (p
= 0.001, p = 0.03). For the other two reviewers, accuracy of the
automated tool was not significantly related to polyp position (p
> 0.05).
Dose—Data from reviewers 1 and 2 showed that the dose
setting during CT colonographic acquisition was not significantly associated
with inaccuracy (p = 0.57-0.89). There was no significant association
between dose level and accuracy as measured by the difference between manual
and automated measurements for any dose level (p =0.36 to p
=0.96).
Combining factors—Figure
3A,
3B shows the mean absolute
error for different morphologic types of polyps located on the tip of a fold
and not on the tip of a fold. When several factors influencing accuracy are
combined, the absolute error can be large. For example, the mean absolute
error for 5-mm flat polyps on the tip of a fold was 3.5 mm with the automated
polyp measurement tool, compared with 0.8 mm with manual technique. No other
combination of polyp factors resulted in a mean absolute error in the
automated measurements greater than 2 mm. Figure
4A,
4B,
4C,
4D shows how large errors can
arise when automated tools are used to measure flat or sessile polyps located
on the tip of a fold. The automated tool can circumscribe a portion of a fold
during measurement of the polyp.
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Fig. 3A —Graphs show accuracy of automated polyp measurement tool. Mean
absolute error represents pooling of data across all four reviewers and all CT
data sets. When multiple polyp characteristics associated with measurement
inaccuracy are combined (e.g., small size, flat morphologic type, location on
tip of haustral fold), measurement errors can be large. Graph shows accuracy
of measurement of polyps not on tip of fold.
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Fig. 3B —Graphs show accuracy of automated polyp measurement tool. Mean
absolute error represents pooling of data across all four reviewers and all CT
data sets. When multiple polyp characteristics associated with measurement
inaccuracy are combined (e.g., small size, flat morphologic type, location on
tip of haustral fold), measurement errors can be large. Graph shows accuracy
of measurement of polyps on tip of fold.
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Fig. 4A —Colon phantom with 5-mm flat polyp (3a) on tip of fold. Example of
inaccurate measurement with automated tool. Two-dimensional multiplanar
reformation (MPR) image shows 5-mm flat polyp (arrow) obtained from
100-mA CT data set. Large arrow shows which polyp was measured.
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Fig. 4B —Colon phantom with 5-mm flat polyp (3a) on tip of fold. Example of
inaccurate measurement with automated tool. Oblique 2D MPR image bisecting
polyp (arrow) shows largest cross-sectional diameter and manual
measurement of 4.8 mm.
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Fig. 4C —Colon phantom with 5-mm flat polyp (3a) on tip of fold. Example of
inaccurate measurement with automated tool. Three-dimensional endoluminal view
of polyp in B shows that automated polyp measurement tool has included
underlying haustral fold in polyp, labeled 3a, boundary (box). 1a =
another polyp.
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Fig. 4D —Colon phantom with 5-mm flat polyp (3a) on tip of fold. Example of
inaccurate measurement with automated tool. Two-dimensional MPR image shows
polyp and underlying haustral fold, both of which were circumscribed by
automated polyp measurement tool, producing overestimate of polyp size at 7.3
mm.
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Multivariable linear regression analysis showed that morphologic type was
independently associated with inaccuracy of automated polyp measurement for
all four reviewers (p = 0.0002-0.024). Small polyp size (5 mm) was
independently and significantly associated with inaccuracy in automated polyp
measurements for three reviewers (p = 0.01-0.03).
Precision of Automated Polyp Measurements
The average differences between the two automated measurements for each
polyp (across all polyp types and doses) for the four reviewers were 0.05
± 0.1, 0.03 ± 0.09, 0.05 ± 0.20, and 0.07 ± 0.2
mm, respectively. In most cases, there were no differences between the two
automated measurements performed by a single observer (range, 77-82% of
measurements). The number of times the two automated measurements were within
0.1 mm or less of each other were 83/96 (86%), 84/96 (88%), 79/96 (82%), and
89/96 (93%) for reviewers 1-4, respectively.
Table 3 shows the
coefficients of variation representing the precision between automated and
manual measurement for intraobserver and interobserver measurements. For all
polyp characteristics, except 5-mm size and the interobserver agreement at 50
mA, the coefficients of variation were equal to or larger for manual
measurements between reviewers than for automated measurements between
reviewers.
Figure 5 shows the
precision of automated measurements between reviewers 3 and 4 versus manual
measurements for the same pair of reviewers. Eighty-five percent of the time
(82 of 96 instances), the difference between the two automated measurements
was smaller than the difference between the two manual measurements (95% CI,
77-92%; p < 0.001). Five percent of the time (five of 96
instances) the manual measurements were closer than the two automated
measurements (95% CI, 2-12%). The mean ± SD and median for the
differences between the two automated measurements were 0.07 ± 0.36 mm
and 0.0 mm compared with 0.53 ± 0.43 mm and 0.50 mm for the manual
measurements. The interclass correlation coefficients for intraobserver
variability across all four reviewers (i.e., the correlation between the first
and second automated measurements for each reviewer) were 0.98-1.0. Similarly,
the interclass correlation coefficients describing the interobserver
variability between the first automated measurements for reviewers 3 and 4
were 0.98-1.0, compared with 0.94-1.0 for manual measurements.
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Fig. 5 —Graph shows precision of manual measurements versus automated
measurements for two observers measuring 96 polyps. Precision is reported as
difference between either two manual measurements or two automated
measurements. Points above diagonal line represent polyps in which two
automated measurements were closer. Points below diagonal line represent
polyps in which two manual measurements were closer. For two observers,
difference between automated measurements was smaller than difference between
manual measurements for 82/96 (85%) of polyps (p < 0.01).
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Discussion
We examined the accuracy and precision of automated polyp measurement
software in a colon phantom containing polyps of different sizes, morphologic
types, and locations. Except in measurement of 5-mm polyps, the mean error
associated with automated polyp measurements by three of four reviewers was
less than 1.0 mm, the mean error being 1.4 mm or less for all reviewers across
all polyp sizes. We found that polyp characteristics such as size, morphologic
type, and location can affect the accuracy of an automated polyp measurement
tool. Automated measurements of 5-mm polyps and flat polyps were more
inaccurate than automated measurements of polyps of other sizes and
morphologic types, and they were also more inaccurate than manual
measurements. Two of four reviewers found that polyps on the tips of folds
were measured more inaccurately with the automated tool as opposed to manual
measurement. The accuracy of automated measurements of polyps of other sizes
and morphologic types was not significantly different from the accuracy of
manual measurements. The dose at which CT data sets were acquired also did not
affect accuracy.
The precision of the automated measurement tool was extremely high between
both multiple measurements made by a single observer and measurements made by
different observers. All four reviewers in our study measured each polyp twice
using the automated polyp measurement tool by mouse-clicking at different
points on the surface of the polyp. The difference between these two automated
measurements was 0.1 mm or less 82-93% of the time, indicating that there is
negligible click-point dependency associated with polyp measurement.
Furthermore, automated measurements made by two observers were more precise
than manual measurements 85% of the time (p < 0.01). Given this
high precision, automated polyp measurement may be particularly useful in
gauging polyp growth when a polyp is followed with CT colonography.
In previous phantom studies with CT colonographic workstations,
investigators examined manual techniques of polyp measurement and found that
optimal measurement methods likely depend on the computer workstation used
[13,
14]. Young et al.
[13] found that pedunculated
polyps were measured more accurately than flat polyps with manual techniques,
in agreement with our findings with an automated measurement tool.
Automated polyp measurement has been examined in two previous phantom
studies [15,
16]. Although the effect of
polyp morphologic type or location on haustral folds on accuracy of automated
measurement was not examined in either of these studies, Blake et al.
[15] predicted our finding
that haustral folds may limit the utility of automated measurements in some
instances. We found that for some polyps on the tip of a haustral fold, the
automated polyp measurement tool circumscribed a portion of the fold tip in
addition to the polyp itself, including the fold in the measurement and
causing overestimation of polyp size. Like Burling et al.
[16], we found that automated
measurements were more precise than manual measurements but also found that
the accuracy of automated polyp measurements depended on the morphologic type
and location of the polyp.
There were several weaknesses to our study. We relied on a rigid colon
phantom that presented a limited number of geometric configurations of polyps
and folds and did not contain feces or simulate suboptimal inflation. Our
polyps were composed of epoxy resins and powders (Solid Water), not soft
tissue, which allowed for milling to precise sizes. The fact that the polyps
were composed of epoxy whereas the colonic wall was composed of glass may have
aided the manual measurements because there is an attenuation difference
between these two materials. Furthermore, none of our flat polyps was
completely flat. The flat polyps had a height one half the width, whereas flat
polyps in clinical practice can have heights of 1-2 mm, regardless of size. It
will be difficult to detect the edges of such lesions with automated
methods.
Another limitation was that we performed manual measurements with 2D
methods. The Siemens software used does not allow 3D measurement of the
endoluminal rendering. However, the 2D method used on the workstation compared
favorably with 3D measurements obtained with two other commercial workstations
[13]. Finally, polyps are
deformable, size depending on factors such as pathologic features, geometric
configuration, the effect of gravity, colonic inflation, and rotation. The
ability to acquire precise polyp measurements between two CT examinations with
any manual or automated system depends on the complex interaction of these
parameters. It also depends on measurement technique and the limits of
reproducibility of CT colonographic images for reliable similar display of
polyps at each examination. This comparison can only be performed on patients
undergoing CT colonography twice within a short time. We performed a
methodologic analysis of accuracy and precision on individual polyps. In the
clinical situation, however, data sets are compared side by side.
In conclusion, the accuracy of an automated polyp measurement tool can be
affected by polyp size, morphologic type, and location with respect to a
haustral fold. When using an automated tool, radiologists should visually
inspect automated polyp measurements to ensure they do not include adjacent
haustral folds, particularly for small and flat polyps. Manual measurements
are more accurate in this setting and may be required when an automated polyp
measurement tool yields incorrect polyp boundaries. The precision of polyp
measurements obtained with an automated tool is superior to that of manual
measurements and may be particularly helpful in assessing interval polyp
growth on CT colonography.
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Abstract
Introduction
