Wision A.I. Achieves CE-MDR Mark Approval for AI-assisted Diagnostic Software Medical Device Supporting Colonoscopy

Wision A.I. Achieves CE-MDR Mark Approval for AI-assisted Diagnostic Software Medical Device Supporting Colonoscopy

PR Newswire

SHANGHAI, Nov. 13, 2021

SHANGHAI, Nov. 13, 2021 /PRNewswire/ -- Wision A.I. Ltd, a startup in the field of artificial intelligence assisted diagnostics for gastrointestinal endoscopy, today announced it received the European CE Mark approval for EndoScreener, its AI-assisted polyp detection software during colonoscopy. It is the first CE Mark class II certificate under the new Medical Devices Regulation (MDR 2017/745).

Outstanding product performance and strong clinical evidence

Compared with previously self-declared class I devices for automatic polyp detection during colonoscopy[1], EndoScreener has an overwhelming advantage in terms of  randomized controlled trial (RCT) clinical evidences. EndoScreener has demonstrated its efficacy in improving adenoma detection on more than 5000 patients in six rigorous randomized controlled trials, including three open RCTs[2], [3],one double-blinded RCTs[4] and two tandem colonoscopy RCTs[5], [6]. In the latest published multi-center tandem colonoscopy trial conducted at four U.S. leading academic medical institutions, EndoScreener reduced precancerous lesion (adenoma and SSL) miss rate by 41 % (19.13 vs 32.52 p=0.0047), and improved adenoma per colonoscopy (APC) by 33 % (0.9000 vs 1.1947 p=0.323 ). Even with high average adenoma detection rate (ADR) of 43.64% in screening/surveillance population under standard of care, no ceiling effect was found in this study.

Advanced AI technology in medical field enters the European market

Colorectal cancer (CRC) is a highly prevalent human malignancy, with over 1.9 million new cases and 935,000 deaths worldwide in 2020. It is also the second leading cancer killer in Europe, with one European dying of CRC every 3 minutes. Detection and removal of adenomatous polyps at early diagnosis and regular colonoscopy screening are the most effective ways to reduce the incidence and mortality of colorectal cancer. The opening of the European market for EndoScreener will eventually contribute to the prevention of colorectal cancer, saving resources in health services and reducing country expenditures. Wision A.I. is open for country-level collaborators to speed up making the solution generally available in different regions of the EU.

High compatibility and easy deployment

EndoScreener is a real-time computer-aided diagnosis software that assists endoscopists to provide a simultaneous visual notification and sound alarm for polyp detection during colonoscopy. As a software-only medical device (SaMD) with relatively economical total cost of ownership (TCO), EndoScreener is compatible with most mainstream endoscope systems With proper off-the-shelf computer hardware, the AI solution can be deployed with high flexibility in various clinical environments for colonoscopy

About Wision A.I.

Wision A.I. has extensive expertise in mathematics and algorithm development. The company integrates medical knowledge into flexible and scalable models that leverage cutting-edge, convolutional neural networks and general-purpose computing to achieve stable detection efficacy in diagnostic imaging.

To learn more about Wision A.I., please email ai@wision.com

[1] Kudo SE, Mori Y, Misawa M, et al. Artificial intelligence and colonoscopy: Current status and future perspectives. Dig Endosc. 2019;31(4):363-371. doi:10.1111/den.13340

[2] Wang P, Berzin TM, Glissen Brown JR, et al. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019;68(10):1813-1819. doi:10.1136/gutjnl-2018-317500

[3] Liu P, Wang P, Glissen Brown JR, et al. The single-monitor trial: an embedded CADe system increased adenoma detection during colonoscopy: a prospective randomized study. Therap Adv Gastroenterol. 2020;13:1756284820979165. Published 2020 Dec 15. doi:10.1177/1756284820979165

[4] Wang P, Liu X, Berzin TM, et al. Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study [published correction appears in Lancet Gastroenterol Hepatol. 2020 Apr;5(4):e3]. Lancet Gastroenterol Hepatol. 2020;5(4):343-351. doi:10.1016/S2468-1253(19)30411-X

[5] Wang P, Liu P, Glissen Brown JR, et al. Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study. Gastroenterology. 2020;159(4):1252-1261.e5. doi:10.1053/j.gastro.2020.06.023

[6] Glissen Brown JR, Mansour NM, Wang P, et al. Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial) [published online ahead of print, 2021 Sep 14]. Clin Gastroenterol Hepatol. 2021;S1542-3565(21)00973-3. doi:10.1016/j.cgh.2021.09.009

 

 

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