We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
ARAB HEALTH - INFORMA

Download Mobile App




AI in Colonoscopies Detects Early Signs of Bowel Cancer

By HospiMedica International staff writers
Posted on 16 Aug 2024
Print article
Image: The GI Genius in use during a colonscopy (Photo courtesy of NHS)
Image: The GI Genius in use during a colonscopy (Photo courtesy of NHS)

Technology using artificial intelligence (AI) to identify early signs of bowel cancer could gain prominence after a research study has demonstrated greater efficiency in detecting potential new cases.

Researchers at Newcastle University (Newcastle upon Tyne, UK) led the COLO-DETECT randomized controlled trial, where 2,032 participants were divided into two groups for colonoscopy procedures. A colonoscopy is a procedure involving a camera used to look inside the bowel to spot cancerous and precancerous polyps (adenomas). One group underwent colonoscopies with the assistance of the GI Genius AI device, a computer module that integrates with existing colonoscopy technology. The device highlights potential polyps by framing them with a green box on the monitor, though the final decision to remove a polyp rests with the clinician. The other group received standard, non-AI-assisted colonoscopies.

The findings published in Lancet Gastroenterology and Hepatology demonstrated that the AI-enhanced colonoscopies were more effective in identifying adenomas—polyps that could potentially develop into cancer. Specifically, the use of GI Genius led to the detection of an additional 0.36 adenomas per procedure, a significant improvement over traditional methods. Furthermore, the AI technology identified at least one adenoma in an additional 8 out of every 100 patients compared to those who had a standard colonoscopy. The technology was particularly effective in detecting sessile serrated adenomas, which are considered especially concerning due to their potential for rapid progression to malignancy. The study also found that smaller and flatter polyps were more frequently detected with the aid of the AI device. Importantly, the use of this technology did not lead to an increase in procedural complications. The incorporation of the GI Genius system extended the average duration of a colonoscopy by only about 90 seconds.

“We are delighted with the outcome of this trial. Simply put, it will save lives. This trial has demonstrated that using artificial intelligence can significantly increase detection of the kinds of abnormalities in the bowel that may progress to cancer. It allows us to find these lesions, remove them, and stop them from turning into cancer,” said Professor Colin Rees, Professor of Gastroenterology at Newcastle University who led the trial. “Crucially, we know that some of the polyps that lead to cancer are small polyps or flat polyps. The AI helped us find more of these lesions, it is finding the things we are concerned about as well as spotting things that we can miss with the human eye.”

Related Links:
Newcastle University

New
Gold Member
X-Ray QA Meter
T3 AD Pro
Gold Member
SARS‑CoV‑2/Flu A/Flu B/RSV Sample-To-Answer Test
SARS‑CoV‑2/Flu A/Flu B/RSV Cartridge (CE-IVD)
New
Transcatheter Heart Valve
SAPIEN 3 Ultra
New
Medical-Grade POC Terminal
POC-821

Print article

Channels

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.