While computer-aided detection (CADe) and diagnosis (CADx) of colonic polyps via computed tomographic colonography (CTC) have made good progress for the subtypes of pedunculated and sessile polyps, the challenge remains for the subtypes of flat and serrated adenomas polyps. Oral fecal tagging has been widely used to increase the image contrast of colonic residues and fluids against the mucosal surface so that the colonic residues and fluids can be electronically cleansed for assessment of the entire mucosal surface, where the tagging solution containing barium, diatrizoate and/or iohexol has been frequently observed adherent coating on the polyps. This observation could provide additional useful information to relieve the challenges. This study aims to analyze the adherent coating performance of the oral tagging solution for the purpose of relieving the challenge for detection of the flat polyps and characterization of the serrated adenomas polyps. Total of 334 polyps detected by CTC and confirmed by clinical colonoscopy (OC) with pathology were analyzed, among which 251 tagged with solution containing barium and diatrizoate (BD) and the remaining 83 with tagging solution containing barium and iohexol (BL). An experience radiologist scored the polyp coating performance on all the polyps. This study evaluates the tagging efficiency for different polyp morphologies and finds that the tagging rate for flat polyps is slightly higher for BL than for BD (78.9% vs. 73.0%). For the primary goal of differentiation hyperplastic from serrated adenomas, we find that BD tags hyperplastic and serrated adenomas more that BL (75.4% and 91.8% vs. 63.2% and 80.0%, respectively). Though we find a difference in coating thickness using the BD protocol, it is not statistically significant based on the data acquired.

Date Published: 4 March 2019
PDF: 6 pages
Proc. SPIE 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, 1095215 (4 March 2019); doi: 10.1117/12.2513148

Published in SPIE Proceedings Vol. 10952:
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)