AI making earlier detection of colorectal cancer possible

Early detection is crucial for effective treatment of colorectal cancer, but the initial stages are easily missed during endoscopy screenings. With GI Genius, Medtronic presents an AI-powered tool to help detect precancerous lesions in real-time. In an upcoming large-scale trial, the intelligent endoscopy module will demonstrate its benefit in the clinical context.

Colorectal cancer is among the most common in developed countries and is responsible for more than 150,000 deaths per year in Europe alone.¹ On the other hand, 90% of patients can recover when the cancer is detected at an early stage.² While small benign polyps can start to grow in the colon, they can become adenomas and from that, progress into cancer.

This process can take years, often without symptoms, so early detection is essential. To prevent undetected progression, many countries have established endoscopy screening programmes. However, since the initial polyps may be very small, and the procedure covers a considerable distance of the colon, abnormalities can be easily missed, even by experienced endoscopists. This is further exacerbated by an increasing workload in the specialty.

A second set of eyes – but not a replacement for human skill

To mitigate this problem, GI Genius system acts like a “second set of eyes” to support gastroenterologists during colorectal cancer screening. The system reviews the colonoscopy images, in real time³ and throughout the procedure, highlights suspected regions that the clinician may use to confirm whether the area contains a lesion. This overlay marker may be accompanied by an additional AI assessment of the area, categorizing it as either adenoma, non-adenoma or no prediction. The final decision remains with the expert endoscopist, but the technology is designed to increase the level of confidence⁴ in the optical diagnosis, and, unlike the operator, whose vigilance may deteriorate after several hours of looking at similar images, the AI remains laser-focused on its task, supporting the detection of colorectal polyps of various shapes, size, location and histology.⁵^,⁶

The increased diagnostic confidence can also bring financial benefits. Current practice is to remove almost every suspicious finding from the colon and send it to histopathology for further analysis, which can be time-consuming and a significant cost burden. The international guidelines suggest that a highly accurate optical diagnosis should permit the implementation of cost saving strategies such as resect-and-discard and a diagnose and-leave. AI-assisted polyp characterization with high accuracy could expand the uptake of optical diagnosis, increasing the cost-effectiveness of colonoscopy.⁷

Large-scale clinical study puts AI to the test

GI Genius is the most studied AI system in endoscopy which so far proved its credentials in a series of studies: Research found an increase of adenoma detection rate of 14.4% and approx. 50% reduction in adenoma miss rate when the system was used.⁸^,⁹ Especially the detection of smaller lesions (≤ 5 mm) improved significantly when the AI assisted the endoscopists.⁸ The system also contributes to maintaining a consistency of care by increasing diagnostic confidence of less experienced examiners, another study found.¹⁰

Two new major pieces of research are underway to further evaluate GI Genius

COLO-DETECT is a randomised control trial that will evaluate whether colonoscopy assisted with the GI Genius improves the detection of abnormalities such as polyps and cancer compared to standard colonoscopy. 2,000 participants, across 11 sites in the UK, have been randomised to receive either GI Genius assisted colonoscopy or standard colonoscopy. The study has found that GI Genius significantly increased the adenoma detection rate and increased sessile serrate polyp detection, overall, it recommends GI Genius to be in used in all colonoscopies.¹¹

Our NAIAD study is set to explore the use of AI in a ‘real world’ setting, and how it might influence endoscopists in their day-to-day practice
Bu Hayee

In addition, a large-scale study which was made possible by the NHS award, is designed to assess the system’s diagnostic performance and its impact on endoscopists in a “real-world” clinical setting has kicked off in the UK. The National study of Artificial Intelligence in Adenoma Detection for colonoscopy (NAIAD) is led by King’s College London. The trial will be carried out over two years and eventually involve the deployment of 60 AI systems across 20 hospitals in the UK National Health System (NHS) in England. The study is the result of set-up funding from NHS England, which ran a competition to identify and fast-track AI technology into clinical services.¹² “Our NAIAD study is set to explore the use of AI in a ‘real world’ setting, and how it might influence endoscopists in their day-to-day practice.” says Dr Bu Hayee, Consultant Gastroenterologist and Principal Investigator of the study at King’s College Hospital.

The use of AI in endoscopies is set to expand as GI genius has the possibility to host multiple real-time applications which will support development and access to these tools. AI in endoscopy has a bright future and has the potential to continue to improve patient outcomes.

GI Genius™ intelligent endoscopy system

Indications for use
The GI Genius™ module is a computer-assisted reading tool designed to aid endoscopists in detecting colonic mucosal lesions (such as polyps and adenomas) in real time during standard white-light endoscopy examinations of patients undergoing screening and surveillance endoscopic mucosal evaluations. GI Genius™ computer-assisted detection device is limited for use with standard white-light endoscopy imaging only. This device is not indented to replace clinical decision-making.
Risks
If the device is used outside of Instructions For Use, it could potentially lead to inappropriate diagnostic information being displayed to the user (e.g. to analyze images from an unintended patient population, on images acquired with incompatible imaging hardware or incompatible image acquisition parameters).
Incorrect detection or characterization of lesion(s) may lead to false positive or false negative which may result in incorrect patients’ management with possible adverse effects: Unnecessary treatment, unnecessary additional medical imaging and/or unnecessary additional diagnostic workup such as biopsy, complications, including incorrect diagnosis and delay in disease management.
Device failure could lead to the absence of results, delay of results or incorrect results, which could likewise lead to inaccurate patient assessment. In the event of unrecoverable failure, please switch off and revert to Non AI enhanced colonoscopy.
Important: Always refer to the Instructions For Use (IFU) packaged with the product for complete instructions, indications, contraindications, warnings and precautions.

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