Home Conspicuity of Colorectal Polyps at CT Colonography
Post
Cancel

Conspicuity of Colorectal Polyps at CT Colonography

Rationale and Objectives

The factors that influence the conspicuity of polyps on computed tomographic (CT) colonography (CTC) are poorly understood. The aim of this study is to compare radiologists’ visual assessment of polyp conspicuity to quantitative image features and show the relationship between visual conspicuity and the detection of colonic polyps by computer-aided detection (CAD) on CTC.

Methods

One polyp (size range 6—10 mm) was selected from the CTC examination of each of 29 patients from a larger cohort. All patients underwent oral contrast-enhanced CTC with same-day optical colonoscopy with segmental unblinding. The polyps were analyzed by a previously validated CAD system and placed into one of two groups (detected [ n = 12] or not detected [ n = 17] by CAD). The study population was intentionally enriched with polyps that were not detected by the CAD system. Four board-certified radiologists, blinded to the CAD results, reviewed two- and three-dimensional CTC images of the polyps and scored the conspicuity of the polyps using a 4-point scale (0 = least conspicuous, 3 = most conspicuous). Polyp height and width were measured by a trained observer. A t -test (two-tailed, unpaired equal variance) was done to determine statistical significance. Intra- and interobserver variabilities of the conspicuity scores were assessed using the weighted κ test. Regression analysis was used to investigate the relationship of conspicuity to polyp height and width.

Results

A statistically significant difference was found between the average conspicuity scores for polyps that were detected by CAD compared to those that were not (2.3 ± 0.6 vs. 1.4 ± 0.8) ( P = .004). There was moderate intraobserver agreement of the conspicuity scores (weighted κ 0.57 ± 0.09). Interobserver agreement was fair (average weighted κ for six pair-wise comparisons, 0.38 ± 0.15). Conspicuity was correlated with manual measurement of polyp height ( r 2 = 0.38–0.56, P < .001).

Conclusions

This CAD system tends to detect 6—10 mm polyps that are more visually conspicuous. Polyp height is a major determinant of visual conspicuity. The generalizability of these findings to other CAD systems is currently unknown. Nevertheless, CAD developers may need to specifically target flatter and less conspicuous polyps for CAD to better assist the radiologist to find polyps in this clinically important size category.

Accurate detection and diagnosis of colonic polyps using computed tomographic (CT) colonography (CTC) is dependent upon many factors. One of the most important factors is the ability of a human observer to visually locate and properly classify polyp candidates. Unfortunately, this ability is inconsistent as demonstrated by studies that reported high intra- and interobserver variabilities among radiologists ( ).

To ensure that patients are properly diagnosed, it is desirable to both reduce observer variability and increase average diagnostic performance. One way to achieve these goals is through the use of computer-aided detection (CAD) systems. For example, CAD systems are available to help detect breast cancers on mammography, pulmonary nodules on chest computed tomography and polyps on CTC.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Materials and methods

Get Radiology Tree app to read full this article<

Patient Population

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Figure 1, Polyp flowchart. CAD, computer-aided design.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Patient Preparation

Get Radiology Tree app to read full this article<

CT Scanning

Get Radiology Tree app to read full this article<

Polyp Identification

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Computer-aided Polyp Detection

Get Radiology Tree app to read full this article<

Data Preparation

Get Radiology Tree app to read full this article<

Figure 2, Example series of ( top row ) three-dimensional perspective rendered endoluminal and ( bottom row ) two-dimensional transverse supine computer tomographic colonography images shown to the radiologists in this study. The polyp ( blue and white arrows ) is a 6-mm sessile adenoma in the ascending colon of a 68-year-old man. The average conspicuity score over all four radiologists and two readings sessions was 2.5. The manually measured polyp height and width were 3.3 and 3.8 mm, respectively. The blue arrows were included on the images shown to the radiologists.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Data Collection—Observer

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Quantitative Information

Get Radiology Tree app to read full this article<

Qualitative Information

Get Radiology Tree app to read full this article<

Data Collection—Measurements

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Statistical Analysis

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Results

Polyp Size

Get Radiology Tree app to read full this article<

Reader Agreement

Get Radiology Tree app to read full this article<

Table 1

Intraobserver Agreement of Conspicuity Score

Reader Supine Prone Supine and Prone A 0.58 0.64 0.62 B 0.51 0.63 0.48 C 0.30 0.47 0.50 D 0.68 0.67 0.67 Mean ± SD 0.52 ± 0.16 0.60 ± 0.09 0.57 ± 0.09

SD, standard deviation.

Table values are weighted κ for each of the four radiologist’s conspicuity scores comparing the first and second reads. Weighted κ is shown separately for the supine, prone, and combined (supine and prone) reads.

Table 2

Interobserver Agreement of Conspicuity Score

Reader B C D A 0.53 0.38 0.26 B — 0.30 0.23 C — — 0.60

Table values are weighted κ for each pairwise comparison of radiologist conspicuity scores for the first of the two reads, when using the supine and prone images together (the “combined read”) to grade conspicuity.

Get Radiology Tree app to read full this article<

Conspicuity and CAD

Get Radiology Tree app to read full this article<

Figure 3, Mean conspicuity score for polyps. Conspicuity ratings from four radiologists (Rad) for 12 polyps detected and 17 polyps not detected by computer-aided detection. Conspicuity ratings were from the readings showing both the supine and prone views of the polyp. There was statistically significantly greater conspicuity for polyps detected by CAD (0.003 ≤ P ≤ 0.035 for each radiologist, two-tailed t -test assuming unequal variance). FN, false negative; TP, true positive.

Get Radiology Tree app to read full this article<

Conspicuity and Image Features

Get Radiology Tree app to read full this article<

Figure 4, Three-dimensional endoluminal supine computed tomographic colonography images of a 10-mm highly conspicuous sessile adenomatous polyp ( white arrows ) in the ascending colon of a 69-year-old man. The same polyp is shown from two different viewing directions. The average conspicuity score over all four radiologists and two readings was 2.75. The manually measured polyp height and width were 5.9 and 8.6 mm, respectively.

Figure 5, Three-dimensional endoluminal supine computed tomographic colonography images of an 8-mm inconspicuous hyperplastic sessile polyp ( large arrows ) in the rectum of a 67-year-old man. The same polyp is shown from two different viewing directions. The average conspicuity score over all four radiologists and two readings was 0.75. The manually measured polyp height and width were 0.6 and 6.3 mm, respectively. A fluid subtraction artifact ( small arrows ) is incidentally noted and does not affect assessment of the polyp's conspicuity.

Get Radiology Tree app to read full this article<

Conspicuity and True Polyp Size

Get Radiology Tree app to read full this article<

Qualitative Features

Get Radiology Tree app to read full this article<

Table 3

Readers’ Description of Less Conspicuous Polyps

Physical Characteristics of Polyps Polyps Not Found by CAD Polyps Found by CAD Flat 21%, 12/56 9%, 2/23 Edges not prominent (ie, less well defined) 50%, 28/56 22%, 5/23 Difficult to distinguish from a normal fold 21%, 12/56 35%, 8/23 Looks like noise or a normal bump on the colonic surface 68%, 38/56 57%, 13/23 Looks like stool 16%, 9/56 9%, 2/23

Data are numbers of readings having each description for less conspicuous polyps (conspicuity scores <3). Assessments are for the first reading session on review of the supine and prone images together.

Get Radiology Tree app to read full this article<

Discussion

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Acknowledgments

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

References

  • 1. Johnson C.D., Toledano A.Y., Herman B.A., et. al.: Computerized tomographic colonography: performance evaluation in a retrospective multicenter setting. Gastroenterology 2003; 125: pp. 688-695.

  • 2. Petrick N., Haider M., Summers R.M., et. al.: CT Colonography and computer-aided detection as a second reader: observer performance study. Radiology 2008; 246: pp. 148-156.

  • 3. Kundel H.L., Revesz G.: Lesion conspicuity, structured noise, and film reader error. Am J Roentgenol 1976; 126: pp. 1233-1238.

  • 4. Revesz G., Kundel H.L., Graber M.A.: The influence of structured noise on the detection of radiologic abnormalities. Invest Radiol 1974; 9: pp. 479-486.

  • 5. Revesz G., Kundel H.L.: Psycholophysical studies of detection errors in chest radiology. Radiology 1977; 123: pp. 559-562.

  • 6. Krupinski E.A., Berger W.G., Dallas W.J., Roehrig H.: Searching for nodules: what features attract attention and influence detection?. Acad Radiol 2003; 10: pp. 861-868.

  • 7. Mulhall B.P., Veerappan G.R., Jackson J.L.: Meta-analysis: computed tomographic colonography. Ann Intern Med 2005; 142: pp. 635-650.

  • 8. Shi R., Schraedley-Desmond P., Napel S., et. al.: CT colonography: influence of 3D viewing and polyp candidate features on interpretation with computer-aided detection. Radiology 2006; 239: pp. 768-776.

  • 9. Summers R.M., Yao J., Pickhardt P.J., et. al.: Computed tomographic virtual colonoscopy computer-aided polyp detection in a screening population. Gastroenterology 2005; 129: pp. 1832-1844.

  • 10. Soetikno R.M., Kaltenbach T., Rouse R.V., et. al.: Prevalence of nonpolypoid (flat and depressed) colorectal neoplasms in asymptomatic and symptomatic adults. JAMA 2008; 299: pp. 1027-1035.

  • 11. Pickhardt P.J., Choi J.R., Hwang I., et. al.: Computed tomographic virtual colonoscopy to screen for colorectal neoplasia in asymptomatic adults. N Engl J Med 2003; 349: pp. 2191-2200.

  • 12. Pickhardt P.J., Choi J.H.: Electronic cleansing and stool tagging in CT colonography: advantages and pitfalls with primary three-dimensional evaluation. AJR Am J Roentgenol 2003; 181: pp. 799-805.

  • 13. Altman D.G.: Practical statistics for medical research.1999.Chapman & Hall/CRCBoca Raton, FL

  • 14. Park S.H., Ha H.K., Kim A.Y., et. al.: Flat polyps of the colon: detection with 16-MDCT colonography—preliminary results. AJR Am J Roentgenol 2006; 186: pp. 1611-1617.

  • 15. Park S.H., Ha H.K., Kim M.J., et. al.: False-negative results at multi-detector row CT colonography: multivariate analysis of causes for missed lesions. Radiology 2005; 235: pp. 495-502.

  • 16. Pickhardt P.J., Nugent P.A., Choi J.R., Schindler W.R.: Flat colorectal lesions in asymptomatic adults: implications for screening with CT virtual colonoscopy. AJR Am J Roentgenol 2004; 183: pp. 1343-1347.

  • 17. Li J, Franaszek M, Petrick N, Yao J, Huang A, Summers RM. Wavelet method for CT colonography computer-aided polyp detection. In: 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings, 2006; 2006:1316–1319.

  • 18. Li J., Van Uitert R., Yao J., et. al.: Wavelet method for CT colonography computer-aided polyp detection. Med Phys 2008; 35: pp. 3527-3538.

  • 19. Pickhardt P.J., Choi J.R., Nugent P.A., Schindler W.R.: The effect of diagnostic confidence on the probability of optical colonoscopic confirmation of potential polyps detected on CT colonography: prospective assessment in 1,339 asymptomatic adults. AJR Am J Roentgenol 2004; 183: pp. 1661-1665.

  • 20. Krupinski E.A.: Visual search of mammographic images: influence of lesion subtlety. Acad Radiol 2005; 12: pp. 965-969.

  • 21. Kundel H.L., Revesz G., Toto L.: Contrast gradient and the detection of lung nodules. Invest Radiol 1979; 14: pp. 18-22.

  • 22. Doshi T., Rusinak D., Halvorsen R.A., Rockey D.C., Suzuki K., Dachman A.H.: CT colonography: false-negative interpretations. Radiology 2007; 244: pp. 165-173.

  • 23. Gluecker T.M., Fletcher J.G., Welch T.J., et. al.: Characterization of lesions missed on interpretation of CT colonography using a 2D search method. AJR Am J Roentgenol 2004; 182: pp. 881-889.

  • 24. Arnesen R.B., Adamsen S., Svendsen L.B., Raaschou H.O., von Benzon E., Hansen O.H.: Missed lesions and false-positive findings on computed-tomographic colonography: a controlled prospective analysis. Endoscopy 2005; 37: pp. 937-944.

  • 25. Fidler J.L., Fletcher J.G., Johnson C.D., et. al.: Understanding interpretive errors in radiologists learning computed tomography colonography. Acad Radiol 2004; 11: pp. 750-756.

This post is licensed under CC BY 4.0 by the author.