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Reproducibility of Tumor Volume Measurement at MicroCT Colonography in Living Mice

Posted Feb 29, 2008 Updated Apr 7, 2023
By Benjamin Y. Durkee , Sarah R. Mudd , Calista N. Roen , Linda Clipson , Michael A. Newton , Jamey P. Weichert , Perry J. Pickhardt MD , Richard B. Halberg
8 min read

Rationale and Objectives

We sought to demonstrate the viability of microcomputed tomographic colonography (μCTC) as a tool for monitoring tumorigenesis in mouse models of human colorectal cancer during prospective longitudinal studies. The precision and accuracy of volumetric measurements were determined to assess whether changes in tumor volume over time were readily detectable.

Materials and Methods

All animal studies were conducted under the guidelines set forth by the Institutional Animal Care and Use Committee of the American Association for Assessment and Accreditation of Laboratory Animal Care. μCTC was performed on C57BL/6J (B6) mice carrying the Min allele of Apc , ultimately yielding 18 scans. Assessments of scan quality and tumor volume were both performed once per week over 8 weeks.

Results

Scans with a good quality rating had a mean standard deviation in tumor volume measurement of 8%. By contrast, scans with a poor quality rating had a mean standard deviation in tumor volume measurement of 35%. Variables affecting μCTC scan quality in living mice included bowel preparation, motion artifact, and tumor morphology. Tumor volume measurements were highly correlated with tumor weight ( r 2 = 0.87).

Conclusions

The reproducibility of tumor volume measurement at μCTC in living mice makes prospective longitudinal evaluation of colonic tumor response feasible. For μCTC scans of good quality, a 16% change in tumor volume can be detected at the 95% confidence level.

Colorectal cancer is the second leading cause of cancer-related mortality in the United States. The American Cancer Society projects 153,760 new cases of colon and rectal cancer for 2007 ( ). Importantly, colorectal cancer is largely preventable if detected early. The 5-year survival rate for a stage I diagnosis is 90% ( ). Unfortunately, only 39% of cases are detected at this stage, owing to low rates of screening and patient compliance ( ). Although optical colonoscopy is the current gold standard for the detection of colorectal neoplasia, computed tomographic colonography (CTC) is rapidly emerging as a viable less invasive alternative. CTC touts the noteworthy advantage of not requiring sedation or pain control. In addition, one study has reported sensitivity comparable to that of optical colonoscopy ( ).

Pickhardt et al described the ability to reliably detect colonic tumors in living mice using microcomputed tomographic colonography (μCTC) ( ). They found that μCTC has good sensitivity (93.3%) and specificity (98.5%) for in vivo detection of polyps with a maximum diameter greater than 2 mm. This experimental platform permits prospective longitudinal evaluation of tumorigenesis in the mammalian colon and has two major advantages over a cross-sectional study design. First, individual tumors can be monitored serially, eliminating animal-to-animal variation and ultimately reducing the number of mice needed to achieve high statistical power ( ). Second, specific tumors can be identified as either responders or nonresponders and then studied ex vivo to assess differences at the molecular level.

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Materials and methods

Mouse Model

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Bowel Preparation

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MicroCT Technique

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μCTC Scan Analysis

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Table 1

Criteria for Scan Quality Rating of Microcomputed Tomographic Colonography Studies

Rating Criteria Good Meets at least three of the four criteria: good colon distension, no motion artifact, typical polypoid tumor shape, and well-defined tumor margins. Fair Meets two of the four criteria. Poor Meets only one of the four criteria, or else reproducible segmentation is deemed not possible.

Figure 1, Scan quality is variable. Image A was consistently rated as good because of good colonic distension, low motion artifact, typical shape, and well-defined tumor margins. Image B was consistently rated poor because of motion artifact, ill-defined tumor margins, and proximity of a fecal pellet (arrowhead) to the tumor (arrow). Approximately 78% of microCT colonoscopies currently done in our lab are good.

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Tumor Volume Measurement

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Figure 2, The segmentation process is rigorously designed to minimize reader subjectivity. One or several slices in each orthogonal plane are selected to use as the skeleton for our segmentation volume (a, b) . Next a wrap filter is applied (c, d) using an algorithm based on scattered data interpolation with radial basis functions. The volume is trimmed using a gradient image (e, f) . Finally, a morphologic three-dimensional dilation filter is applied (g, h) . Images in the bottom row are three-dimensional renderings of two-dimensional segmentations in the top row.

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Correlation Coefficient

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ρX,Y=cov(X,Y)σXσY ρ

X

,

Y

=

cov

⁡

(

X

,

Y

)

σ

X

σ

Y

The random variables, X and Y , are volumes defined by two distinct segmentation attempts. The covariance of X and Y is defined by

cov(X,Y)=n∑xyii−∑xi∑yi cov

⁡

(

X

,

Y

)

=

n

∑

x

y

i

i

−

∑

x

i

∑

y

i

The product of the sample standard deviations σ X and σ Y is defined by

σXσY=n∑x2i−(∑xi)2.n∑y2i−(∑yi)2 σ

X

σ

Y

=

n

∑

x

i

2

−

(

∑

x

i

)

2

.

n

∑

y

i

2

−

(

∑

y

i

)

2

where the sum is from i = 1 to n voxels. The correlation coefficient was an indication of the relative number of voxels in common between two segmented volumes (ie, how well the two volumes match up). A correlation coefficient of 0 indicated no overlap between two volumes in space and a coefficient of 1 indicated perfect alignment with respect to morphology and position.

Figure 3, The importance of measuring three-dimensional correlation is illustrated by two segmentation attempts shown in blue and red. (a, b) Two segmentation attempts of a tumor in a good scan. The reader made similar decisions regarding tumor boundary and the three-dimensional rendering shows a significant amount of volume in common (c) . The volumes were 49.3 mm 3 (a) and 49.9 mm 3 (b) and the correlation in three-dimensional space was 95.4%. (e, f) Two segmentation attempts of a tumor in a poor scan. The reader had difficulty with precise segmentation and the result was less volume in common (f) . The volumes measured for these scans were coincidently both 3.5 mm 3 but the correlation in three-dimensional space was only 73.5%. This example demonstrates why volume measurements alone are not sufficient to evaluate precision.

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Reader Drift

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V¯¯¯t=118∑mi=1∑Δj=1Vi,j V

¯

t

=

1

18

∑

i

=

1

m

∑

j

=

1

Δ

V

i

,

j

where t is the trial number or segmentation attempt ranging from 1 through 8, m is the particular mouse, and Δ is the scan number ranging 1 through 18.

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Recall Bias

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R¯¯¯t=118∑mi=1∑Δj=1ri,j R

¯

t

=

1

18

∑

i

=

1

m

∑

j

=

1

Δ

r

i

,

j

where t is the segmentation attempt or trial number ranging 1 through 8, m is the particular mouse, and Δ is the scan number ranging 1 through 18.

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Accuracy

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Statistical Methods

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Results

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Consistency of Scan Rating

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Table 2

Summary of Reader Consistency in Assessing Scan Quality, Tumor Volume, and Tumor Morphology

Assessment, Mean ± SD Scan Quality_n_ Quality Rating Tumor Volume (mm 3 ) Correlation Coefficient Good 56 3.7 ± 0.4 16.1 ± 1.3 0.89 ± 0.03 Fair 48 2.6 ± 0.4 11.4 ± 1.6 0.82 ± 0.05 Poor 40 1.1 ± 0.3 8.1 ± 2.6 0.64 ± 0.08

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Consistency of Tumor Volume Measurement

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Figure 4, Precision in volume measurements is related to scan quality. The box plot depicts the smallest observation, lower quartile, median, upper quartile, largest observation, and outliers. The standard deviation for all 144 measurements was 19%. The standard deviations for good, fair and poor were 8%, 14%, and 32%, respectively.

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Table 3

Probability that a Measured Change in Tumor Volume with Good Scans is Real

Measured Change in Tumor Volume (%) Certainty that Change is Real (%) 5% 45% 10 76 15 92 20 98

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Consistency of Tumor Volume Correlation

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Figure 5, Correlation coefficients increase with scan quality. The correlation coefficient is an indication of consistent delineation of tumor margins. Each datapoint represents the mean of eight segmentations. Quality ratings are >3 for good scans, 2–3 for fair scans, and <2 for poor scans.

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Reader Drift

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Recall Bias

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Accuracy of Tumor Volume Measurements

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Discussion

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References

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  • 3. Pickhardt P.J., Halberg R.B., Taylor A.J., et. al.: Microcomputed tomography colonography for polyp detection in an in vivo mouse tumor model. Proc Natl Acad Sci U S A 2005; 102: pp. 3419-3422.

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  • 7. Quon A., Napel S., Beaulieu C.F., et. al.: “Flying through” and “flying around” a PET/CT scan: pilot study and development of 3D integrated 18F-FDG PET/CT for virtual bronchoscopy and colonoscopy. J Nucl Med 2006; 47: pp. 1081-1087.

  • 8. Magnotta V.A., Heckel D., Andreasen N.C., et. al.: Measurement of brain structures with artificial neural networks: two- and three-dimensional applications. Radiology 1999; 211: pp. 781-790.

  • 9. Heidelberger C., Ansfield F.J.: Experimental and clinical use of fluorinated pyrimidines in cancer chemotherapy. Cancer Res 1963; 23: pp. 1226-1243.

Academic Radiology, Volume 15, Issue 3
Journals General Radiology
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