Computer-generated surface and tone enhancements to distinguish neoplastic from non-neoplastic colon polyps less than 1 cm in diameter.

ABSTRACT

BACKGROUND AND STUDY AIMS: Computer-generated enhancements, which can highlight the surface and color of a colonic lesion, may be helpful to predict the histology; however, it remains unclear whether this technology can distinguish neoplastic from non-neoplastic colon polyps when the polyps are <1 cm without magnification. PATIENTS AND METHODS: Images of colorectal polyps less than 1 cm in diameter were obtained from 54 patients who underwent non-magnified colonoscopy with surface enhancement (SE) and tone enhancement (TE). We calculated the sensitivity, specificity, and accuracy in the prediction of histology. Inter- and intra-observer consistency was evaluated by inviting four endoscopists to rate 45 static images. RESULTS: Overall sensitivity, specificity, and accuracy following the sequence of SE, TE colon, and TE pit pattern modes were 87.7% (95% confidence interval 81.3-94.1%), 84.1% (76.9-91.3%), and 86.1% (79.4-92.8%), respectively. For each modality, the results were 75.0% (68.7-81.3%), 82.7% (77.2-88.2%), and 77.2% (71.1-83.3%) for SE; 71.1% (64.5-77.7%), 78.8 (72.8-84.8), and 73.3% (66.8-79.8%) for TE colon mode; and 75.0% (68.7-81.3%), 80.8% (75.0-86.8%), and 76.7% (70.5-82.9%) for TE pit pattern mode. Their inter- and intra-observer agreements were all fair (κ range 0.522-0.568) and good (0.605-0.694), respectively. When the same rater evaluated the same lesion under different modalities, eight of 45 (18%) polyps yielded discordant interpretations, and the possibility of incorrect diagnoses was the highest with the TE colon mode. CONCLUSION: Computer-generated enhancements are satisfactory in predicting the histology of small colon polyps without the need for magnification. This advantage is mostly related to the pit pattern enhancement.