Diagnostic accuracy and interobserver agreement of CT colonography (virtual colonoscopy). Issue 1 (1st July 2000)

• Record Type: Journal Article
• Authors: Pescatore, P; Glücker, T; Delarive, J; Meuli, R; Pantoflickova, D; Duvoisin, B; Schnyder, P; Blum, A L; Dorta, G
• Is Part Of: Gut. Volume 47:Issue 1(2000)
• Page Start: 126
• Page End: 130
• Publication Date: 2000-07-01
• Subjects: computed tomographic -- colonography -- colonoscopy -- diagnostic accuracy -- interobserver agreement; Gastroenterology -- Periodicals; 616.33
• DOI: 10.1136/gut.47.1.126
• Languages: English
• ISSNs: 0017-5749

Abstract

Abstract : BACKGROUND AND AIMS: Computed tomographic (CT) colonography or virtual colonoscopy (VC) is a non-invasive imaging method proposed for screening patients with colorectal neoplasias. Our aims were to study the diagnostic accuracy and interobserver agreement of VC for correct patient identification compared with conventional colonoscopy (CC). METHODS: This was a prospective study of 50 patients successively undergoing VC and CC. Multiplanar two dimensional CT images and three dimensional VC were constructed using surface rendering software and interpreted by two independent investigator teams. VC findings were compared with those of CC. Interobserver agreement was determined using kappa statistics. RESULTS: CC found 65 polyps in 24 patients. For identification of patients with polyps ⩾10 mm, the sensitivity of VC was 38% and 63%, and specificity was 74% and 74% for teams 1 and team 2. Interobserver agreement was good (kappa 0.72). For patients with polyps of any size, the sensitivity of VC was 75% and 71%, and specificity was 62% and 69% for teams 1 and 2. Interobserver agreement was fair (kappa 0.56). Accuracy improved when comparing the results of the first 24 with the last 26 patients. CONCLUSIONS: In our experience, VC had a low diagnostic value for identification of patients with colorectal neoplasias. Interobserver agreement for VC interpretation was fair. These results may be explained by software imperfections and a learning curve effect.