Prospective Randomized Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy
Prospective Randomized Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy
Colonoscopy is currently the best method of detection of intestinal tumors and polyps, particularly because polyps can also be biopsied and removed. There is a clear correlation between the adenoma detection rate and prevented carcinomas, so adenoma detection rate is the main parameter for the outcome quality of diagnostic colonoscopy. The efficiency of preventive colonoscopy needs optimisation by increase in adenoma detection rate, as it is known from many studies that approximately 15-30% of all adenomas can be overlooked. This mainly applies to smaller and flat adenomas. However, since even smaller polyps may be relevant for colorectal cancer development, the aim of colonoscopy should be to preferably be able to recognize all polyps and other changes.The latest and by far the most interesting development in this field is the use of artificial intelligence systems. They consist of a switched-on software with a small computer connected to the endoscope processor; the patient's introduced endoscope is completely unchanged.
The present study therefore compares the adenoma detection rate (ADR) of the latest generation of devices with high-resolution imaging from Fujifilm with and without the connection of artificial intelligence.
Methods of Computer Vision (CV) and Artificial Intelligence (AI) provide completely new opportunities, e.g. in the automatic polyp detection and differentiation of a lesion based on its endoscopic image. Computer vision using artificial intelligence methods means the application of "trained" so-called deep neural net (DNN) with a set of defined images (e.g. everyday scenes) and well-known solutions ( e.g. name of the pictured item; c.f. e.g. the "ImageNet Challenge"). The technical feasibility of using AI algorithms in endoscopy has already been proven in many cases. In the present study, it is an AI system from Fujifilm, which is already clinically usable. By using Fujifilm high-resolution imaging devices in colonoscopies, AI will be added randomly.
Inclusion Criteria:
Exclusion Criteria:
t.roesch@uke.de+49 40 7410 ext. 50098
g.schachschal@uke.de+49 40 7410 ext. 50814
Leipzig, Saxony 04103, Germany
albrecht.hoffmeister@medizin.uni-leipzig.de+49 341 97 ext. 12240
Cologne, 50733, Germany
gastroenterologen@berlin.de+49 30 814 59 ext. 190
gastroenterologen@berlin.de+49 30 814 59 ext. 190
Dominik.Kaczmarek@ukbonn.de+49 228-287 ext. 14338
philipp.zervoulakos@cellitinnen.de+49 221 7712 ext. 4660
t.roesch@uke.de+49 40 7410 ext. 50098
g.schachschal@uke.de+49 40 7410 ext. 50814
jochen.weigt@med.ovgu.de
Oliver.Moeschler@niels-stensen-kliniken.de+49 541 326 ext. 4100
an.may@asklepios.com+49 611 847 ext. 2331