Endoscopy 2019; 51(02): 133-141
DOI: 10.1055/a-0757-7759
Original article
© Georg Thieme Verlag KG Stuttgart · New York

A multimodal (FACILE) classification for optical diagnosis of inflammatory bowel disease associated neoplasia

Marietta Iacucci
1  Division of Gastroenterology, University of Calgary, Calgary, Canada
2  Institute Translational of Medicine, Institute of immunology and immunotherapy and NIHR Biomedical Research Centre, University of Birmingham, Birmingham, United Kingdom
,
Kenneth McQuaid
3  Division of Gastroenterology, University of California, San Francisco, United States
,
X. Sean Gui
1  Division of Gastroenterology, University of Calgary, Calgary, Canada
,
Yasushi Iwao
4  Center for Preventive Medicine, Keio University l, Tokyo, Japan
,
Brendan C. Lethebe
5  Clinical Research Unit, University of Calgary, Canada
,
Mark Lowerison
5  Clinical Research Unit, University of Calgary, Canada
,
Takayuki Matsumoto
6  Division of Gastroenterology, Iwate Medical University, Japan
,
Uday N. Shivaji
2  Institute Translational of Medicine, Institute of immunology and immunotherapy and NIHR Biomedical Research Centre, University of Birmingham, Birmingham, United Kingdom
,
Samuel C. L. Smith
2  Institute Translational of Medicine, Institute of immunology and immunotherapy and NIHR Biomedical Research Centre, University of Birmingham, Birmingham, United Kingdom
,
Venkataraman Subramanian
7  Division of Gastroenterology, University of Leeds, Leeds, United Kingdom
,
Toshio Uraoka
8  Division of Gastroenterology, Tokyo Medical Center, Tokyo, Japan
,
Silvia Sanduleanu
9  Division of Gastroenterology and Hepatology, Maastricht University Medical Center, The Netherlands
,
Subrata Ghosh
1  Division of Gastroenterology, University of Calgary, Calgary, Canada
2  Institute Translational of Medicine, Institute of immunology and immunotherapy and NIHR Biomedical Research Centre, University of Birmingham, Birmingham, United Kingdom
,
Ralf Kiesslich
10  Division of Gastroenterology, HSK Hospital, Wiesbaden, Germany
› Author Affiliations
Further Information

Publication History

submitted 28 January 2018

accepted after revision 31 August 2018

Publication Date:
12 December 2018 (eFirst)

Abstract

Background Characterization of colonic lesions in inflammatory bowel disease (IBD) remains challenging. We developed an endoscopic classification of visual characteristics to identify colitis-associated neoplasia using multimodal advanced endoscopic imaging (Frankfurt Advanced Chromoendoscopic IBD LEsions [FACILE] classification).

Methods The study was conducted in three phases: 1) development – an expert panel defined endoscopic signs and predictors of dysplasia in IBD and, using multivariable logistic regression created the FACILE classification; 2) validation – using 60 IBD lesions from an image library, two assessments of diagnostic accuracy for neoplasia were performed and interobserver agreement between experts using FACILE was determined; 3) reproducibility – the reproducibility of the FACILE classification was tested in gastroenterologists, trainees, and junior doctors after completion of a training module.

Results The experts initially selected criteria such as morphology, color, surface, vessel architecture, signs of inflammation, and lesion border. Multivariable logistic regression confirmed that nonpolypoid lesion, irregular vessel architecture, irregular surface pattern, and signs of inflammation within the lesion were predictors of dysplasia. Area under the curve of this logistic model using a bootstrapped estimate was 0.76 (0.73 – 0.78). The training module resulted in improved accuracy and kappa agreement in all nonexperts, though in trainees and junior doctors the kappa agreement was still moderate and poor, respectively.

Conclusion We developed, validated, and demonstrated reproducibility of a new endoscopic classification (FACILE) for the diagnosis of dysplasia in IBD using all imaging modalities. Flat shape, irregular surface and vascular patterns, and signs of inflammation predicted dysplasia. The diagnostic performance of all nonexpert participants improved after a training module.