Virtual Chromoendoscopy With FICE for the Classification of Polypoid and Nonpolypoid Raised Lesions in Ulcerative Colitis. Issue 4 (April 2019) - Cassinotti, Andrea; Buffoli, Federico; Fociani, Paolo; Staiano, Teresa; Villanacci, Vincenzo; Nebuloni, Manuela; Duca, Piergiorgio; Fichera, Maria; Grassia, Roberto; Manes, Gianpiero; Salemme, Marianna; Molteni, Paola; et al.
Abstract : Goals: The aim of this study was to analyze the performance of Fuji Intelligent Color Enhancement (FICE) using the classification of Kudo in the differentiation of neoplastic and non-neoplastic raised lesions in ulcerative colitis (UC). Background: The Kudo classification of mucosal pit patterns is an aid for the differential diagnosis of colorectal polyps in the general population, but no systematic studies are available for all forms of raised lesions in UC. Study: All raised, polypoid and nonpolypoid, lesions found during consecutive surveillance colonoscopies with FICE for long-standing UC were included. In the primary prospective analysis, the Kudo classification was used to predict the histology by FICE. In a post hoc analysis, further endoscopic markers were also explored. Results: Two hundred and five lesions (mean size, 8 mm; range, 2 to 30 mm) from 59 patients (mean age, 56 y; range, 21 to 79 y) were analyzed. Twenty-three neoplastic (11%), 18 hyperplastic (9%), and 164 inflammatory (80%) lesions were found. Thirty-one lesions (15%), none of which were neoplastic, were unclassifiable according to Kudo. After logistic regression, a strong negative association resulted between endoscopic activity and neoplasia, whereas the presence of a fibrin cap was significantly associated with endoscopic activity. Using FICE, the sensitivity, specificity, and positive and negative likelihood ratios of the Kudo classification were 91%, 76%, 3.8, and 0.12, respectively. The corresponding values by adding the fibrin cap as a marker of inflammation were 91%, 93%, 13, and 0.10, respectively. Conclusions: FICE can help to predict the histology of raised lesions in UC. A new classification of pit patterns, based on inflammatory markers, should be developed in the setting of UC to improve the diagnostic performance.