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Computerized Detection of Colonic Polyps at CT Colonography on the Basis of Volumetric Features: Pilot Study¹

¹ From the Departments of Radiology (H.Y., Y.M., P.M., A.H.D.) and Medicine (D.T.R.), University of Chicago, 5841 S Maryland Ave, MC2026, Chicago, IL 60637. Received February 22, 2001; revision requested March 21; revision received June 26; accepted July 27. Supported in part by a grant from the University of Chicago Cancer Research Center. Address correspondence to H.Y. (e-mail: yoshida@uchicago.edu).

View larger version (30K): [in a new window]   Figure 1. Diagram of the CAD scheme for detection of polyps at CT colonography.

View larger version (70K): [in a new window]   Figure 2. A, Coronal image of an isotropic volume data set generated from CT colonographic images in a 70-year-old woman. B, Image of the segmented colon obtained with an application of a segmentation algorithm to the isotropic volume in A. Our segmentation algorithm segments a thick region that contains the entire colon and not only the surface of the colonic wall. A portion of the small intestine (arrow) contiguous to the colon was extracted with the entire colon. Volumetric features used for the detection of polyps were calculated from individual voxels in this thick region.

View larger version (29K): [in a new window]   Figure 3. Illustration of the relationship between the values of the shape index and the shapes.

View larger version (64K): [in a new window]   Figure 4. CT images obtained from multiplanar reformatting of a volume of interest containing a 9-mm polyp (arrow). A-C, Transverse, coronal, and sagittal sections, respectively, of a volume of interest extracted from an isotropic volume set. D-F, Transverse, coronal, and sagittal sections, respectively, of the segmented colon obtained in the same volume of interest as in A-C. Voxels that have shape index values corresponding to the cap, saddle or ridge, and rut or cup shapes are green, pink, and brown, respectively. As expected, a substantial portion of the polyp is green, whereas folds and colonic walls are pink and brown, respectively.

View larger version (71K): [in a new window]   Figure 5. Three-dimensional endoscopic views of the polyp obtained with conventional volume rendering. Although the polyp is depicted as a bumpy structure (arrow in A), it is difficult to identify it with this representation. In B, the voxels are colored according to their shape index values with the same color scheme as in Figure 4. The polyp (arrow) is clearly depicted and differentiated from folds and the colonic wall. A and B demonstrate the effectiveness of the shape index in differentiating polyps from other normal structures in the colon.

View larger version (47K): [in a new window]   Figure 6a. (a, b) Scatterplots depict the distribution of the shape index and curvedness values for possible polyps before (a) and after (b) the fuzzy clustering process (Fig 1). Gray dots depict true-positive findings and black squares depict false-positive findings. The number of false-positive findings in b is much smaller than that in a because of the effect of fuzzy clustering. As expected, polyps have higher shape index values and lower curvedness values than do a majority of the false-positive findings. The solid line in b was used in the CAD scheme to help discriminate true- from false-positive findings. A substantial number of false-positive findings can be eliminated by disregarding the possible polyps in the upper left region above the line. (c, d) Scatterplots depict the distribution of CT and gradient values (Hounsfield units) for possible polyps before (c) and after (d) fuzzy clustering. Black squares depict true-positive findings and gray dots depict false-positive findings. The number of false-positive findings in d is much smaller than that in c because of the effect of fuzzy clustering. However, a substantial overlap remains between the true- and false-positive findings in d. Although the minimum and maximum threshold values for CT and gradient values (dashed lines) were used to reduce false-positive findings in the CAD scheme, thresholding was effective only for the elimination of outliers located outside the central rectangular region.

View larger version (36K): [in a new window]   Figure 6b. (a, b) Scatterplots depict the distribution of the shape index and curvedness values for possible polyps before (a) and after (b) the fuzzy clustering process (Fig 1). Gray dots depict true-positive findings and black squares depict false-positive findings. The number of false-positive findings in b is much smaller than that in a because of the effect of fuzzy clustering. As expected, polyps have higher shape index values and lower curvedness values than do a majority of the false-positive findings. The solid line in b was used in the CAD scheme to help discriminate true- from false-positive findings. A substantial number of false-positive findings can be eliminated by disregarding the possible polyps in the upper left region above the line. (c, d) Scatterplots depict the distribution of CT and gradient values (Hounsfield units) for possible polyps before (c) and after (d) fuzzy clustering. Black squares depict true-positive findings and gray dots depict false-positive findings. The number of false-positive findings in d is much smaller than that in c because of the effect of fuzzy clustering. However, a substantial overlap remains between the true- and false-positive findings in d. Although the minimum and maximum threshold values for CT and gradient values (dashed lines) were used to reduce false-positive findings in the CAD scheme, thresholding was effective only for the elimination of outliers located outside the central rectangular region.

View larger version (33K): [in a new window]   Figure 6c. (a, b) Scatterplots depict the distribution of the shape index and curvedness values for possible polyps before (a) and after (b) the fuzzy clustering process (Fig 1). Gray dots depict true-positive findings and black squares depict false-positive findings. The number of false-positive findings in b is much smaller than that in a because of the effect of fuzzy clustering. As expected, polyps have higher shape index values and lower curvedness values than do a majority of the false-positive findings. The solid line in b was used in the CAD scheme to help discriminate true- from false-positive findings. A substantial number of false-positive findings can be eliminated by disregarding the possible polyps in the upper left region above the line. (c, d) Scatterplots depict the distribution of CT and gradient values (Hounsfield units) for possible polyps before (c) and after (d) fuzzy clustering. Black squares depict true-positive findings and gray dots depict false-positive findings. The number of false-positive findings in d is much smaller than that in c because of the effect of fuzzy clustering. However, a substantial overlap remains between the true- and false-positive findings in d. Although the minimum and maximum threshold values for CT and gradient values (dashed lines) were used to reduce false-positive findings in the CAD scheme, thresholding was effective only for the elimination of outliers located outside the central rectangular region.

View larger version (36K): [in a new window]   Figure 6d. (a, b) Scatterplots depict the distribution of the shape index and curvedness values for possible polyps before (a) and after (b) the fuzzy clustering process (Fig 1). Gray dots depict true-positive findings and black squares depict false-positive findings. The number of false-positive findings in b is much smaller than that in a because of the effect of fuzzy clustering. As expected, polyps have higher shape index values and lower curvedness values than do a majority of the false-positive findings. The solid line in b was used in the CAD scheme to help discriminate true- from false-positive findings. A substantial number of false-positive findings can be eliminated by disregarding the possible polyps in the upper left region above the line. (c, d) Scatterplots depict the distribution of CT and gradient values (Hounsfield units) for possible polyps before (c) and after (d) fuzzy clustering. Black squares depict true-positive findings and gray dots depict false-positive findings. The number of false-positive findings in d is much smaller than that in c because of the effect of fuzzy clustering. However, a substantial overlap remains between the true- and false-positive findings in d. Although the minimum and maximum threshold values for CT and gradient values (dashed lines) were used to reduce false-positive findings in the CAD scheme, thresholding was effective only for the elimination of outliers located outside the central rectangular region.

View larger version (80K): [in a new window]   Figure 7. CT colonographic images of the supine view of a false-negative polyp (arrow in A) in the sigmoid colon. Although the polyp was 7 mm, it appears smaller than expected from the size, which was due mainly to the partial volume effect, and it also appears to be flat. On this view, the polyp did not contain adequate voxels with low curvedness values and high shape index to be detected. B, Prone view of the same polyp (arrow) as in A. The polyp appears rounder and larger than its supine counterpart; thus, it was depicted with the CAD scheme.

View larger version (28K): [in a new window]   Figure 8. Free-response ROC curves show the performance of the CAD scheme for clinically important (5 mm) polyps. The curves were generated by moving the dividing line in Figure 6b from the lower right corner to the upper right corner while maintaining the slope of the line and regarding the possible polyps above and below the line as false- and true-positive, respectively. The solid curve represents the performance of the scheme on the basis of results of CT colonography in 41 patients. A polyp was regarded as detected if it was detected on either the supine or the prone view. The dashed curve represents the performance of the scheme on the basis of 82 CT colonographic volumetric data sets. Polyps and false-positive findings on supine and prone views were counted independently.

View larger version (81K): [in a new window]   Figure 9. CT colonographic images of (A) a false-positive finding (arrow) due to a rectal tube and (B) a false-positive finding (arrow) due to the anorectal junction.

View larger version (109K): [in a new window]   Figure 10. CT colonographic image of a false-positive finding (arrow) due to motion artifact.