Sharmila Subramaniam1, Bu Hayee2, Patrick Aepli3, Erik Schoon4, Milan Stefanovic5, Kesavan Kandiah1, Sreedhari Thayalasekaran1, Asma Alkandari1, Paul Bassett6, Emmanuel Coron7, Oliver Pech8, Cesare Hassan9, Helmut Neumann10, Raf Bisschops11, Alessandro Repici12, Pradeep Bhandari1. 1. Department of Gastroenterology, Queen Alexandra Hospital, Portsmouth, Hampshire, UK. 2. Department of Gastroenterology, King's College Hospital NHS Foundation Trust, London, UK. 3. Department of Gastroenterology, Luzerner Kantonspittal, Lucerne, Switzerland. 4. Department of Gastroenterology, Catharina Hospital, Eindhoven, the Netherlands. 5. Department of Gastroenterology, Diagnostični center Bled, Ljubljana, Slovenia. 6. StatsConsultancy Limited, Amersham, UK. 7. Centre Hospitalier Universitaire and Faculté de Médecine de Nantes, Institut des Maladies de l'Appareil Digestif, Nantes, France. 8. Department of Gastroenterology and Interventional Endoscopy, St John of God Hospital, Regensburg, Bavaria, Germany. 9. Department of Gastroenterology, Nuovo Regina Margherita Hospital, Rome, Italy. 10. Department of Medicine, University Hospital Erlangen, Germany. 11. Department of Gastroenterology and Hepatology, Universitaire Ziekenhuizen Leuven, Belgium. 12. Istituto Clinico Humanitas, Rozzano, Lombardia, Italy.
Abstract
Background: Blue Light Imaging (BLI) is a new imaging technology that enhances mucosal surface and vessel patterns. A specific BLI classification was recently developed to enable better characterisation of colorectal polyps (BLI Adenoma Serrated International Classification (BASIC)). The aim of this study was to validate the diagnostic performance of BASIC in predicting polyp histology in experienced and trainee endoscopists. Methods: Five experienced and five trainee endoscopists evaluated high-definition white light (HDWL) and BLI images from 45 small polyps to assess baseline accuracy, sensitivity, specificity, and positive and negative predictive values (NPVs) of polyp histology. Each endoscopist was trained with the BLI classification before repeating the exercise. Results were compared pre- and post-training. Results: The overall pre-training accuracy improved from 87% to 94%. The sensitivity and NPV of adenoma diagnosis also improved significantly from 79% to 96% and 81% to 95% with BASIC training. This improvement was noted in both groups. The interobserver level of agreement was very good (K = 0.90) in the experienced cohort and good (K = 0.66) in the trainee group post-training. Conclusions: BLI is a useful tool for optical diagnosis, and the use of BASIC with adequate training can significantly improve the accuracy, sensitivity and NPV of adenoma diagnosis.
Background: Blue Light Imaging (BLI) is a new imaging technology that enhances mucosal surface and vessel patterns. A specific BLI classification was recently developed to enable better characterisation of colorectal polyps (BLI Adenoma Serrated International Classification (BASIC)). The aim of this study was to validate the diagnostic performance of BASIC in predicting polyp histology in experienced and trainee endoscopists. Methods: Five experienced and five trainee endoscopists evaluated high-definition white light (HDWL) and BLI images from 45 small polyps to assess baseline accuracy, sensitivity, specificity, and positive and negative predictive values (NPVs) of polyp histology. Each endoscopist was trained with the BLI classification before repeating the exercise. Results were compared pre- and post-training. Results: The overall pre-training accuracy improved from 87% to 94%. The sensitivity and NPV of adenoma diagnosis also improved significantly from 79% to 96% and 81% to 95% with BASIC training. This improvement was noted in both groups. The interobserver level of agreement was very good (K = 0.90) in the experienced cohort and good (K = 0.66) in the trainee group post-training. Conclusions: BLI is a useful tool for optical diagnosis, and the use of BASIC with adequate training can significantly improve the accuracy, sensitivity and NPV of adenoma diagnosis.
Entities:
Keywords:
Adenoma; Blue Light Imaging; classification; colorectal polyps; optical diagnosis
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