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Cloud-Based AI System Shows Significant Improvement in Detecting High-Risk Colorectal Lesions During Colonoscopy

By Burstable Health Team

TL;DR

Olympus's CADDIE AI gives hospitals a competitive edge by increasing adenoma detection rates by 7.3% and boosting detection of high-risk lesions by up to 230%.

The cloud-based CADDIE system analyzes colonoscopy images in real-time using AI trained on datasets enriched with hard-to-detect lesions like flat sessile serrated lesions.

This technology improves early cancer detection, potentially saving lives by identifying dangerous lesions before they progress, making healthcare more effective globally.

A cloud AI system can spot tricky flat colon lesions with 230% better detection than humans alone, revolutionizing preventive medicine.

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Cloud-Based AI System Shows Significant Improvement in Detecting High-Risk Colorectal Lesions During Colonoscopy

The EAGLE trial, published in npj Digital Medicine, demonstrates that cloud-deployed artificial intelligence can assist endoscopists in detecting lesions most critical for preventing progression to colorectal cancer. The study evaluated the CADDIE™ device, the first cloud-based Computer-Aided Detection application for real-time polyp detection during colonoscopy that is both FDA-cleared and CE-marked. Conducted across eight centers in four European countries, the trial involved 841 patients and 22 endoscopists performing screening and surveillance colonoscopies. Patients were randomized to standard colonoscopy or CADDIE-assisted colonoscopy. The primary analysis revealed that use of the CADDIE application was associated with a 7.3% absolute increase in adenoma detection rate compared to standard colonoscopy.

Significant relative increases in lesions detected per colonoscopy were observed for clinically relevant lesion subtypes: 93% for large adenomas (>10 mm), 57% for non-polypoid adenomas, and 230% for sessile serrated lesions (SSLs). SSLs are high-risk lesions whose detection is critical to reducing the risk of post-colonoscopy colorectal cancer, according to research published in Gastrointestinal Endoscopy and The Lancet Gastroenterology & Hepatology. The ability to reliably detect SSLs is increasingly viewed as a critical quality consideration in colonoscopy, as noted in quality indicator guidelines published in Gastrointestinal Endoscopy.

The CADDIE application is trained on a dataset enriched in clinically relevant and hard-to-detect lesions, including flat sessile serrated lesions and large polyps. Lesions with sessile or flat morphology are difficult to detect and can harbor clinically relevant pathology. The system demonstrated real-time performance and operational efficiency across diverse testing environments. Cloud deployment offers hospitals flexibility, reducing reliance on hardware and enabling subscription-based procurement models. This approach can democratize access to advanced AI tools and lays the foundation for future AI applications in endoscopy.

Rawen Kader, Principal Investigator of the EAGLE Trial and GI Researcher at University College London, stated that this study marks a pivotal shift in the clinical translation of AI-assisted endoscopy. Cloud deployment can remove hardware barriers and give hospitals access to the latest AI innovations, which has the potential of improving detection of the lesions that matter most for reducing colorectal cancer risk. The gastroenterologist is responsible for reviewing CADDIE suspected polyp areas and confirming the presence or absence of a polyp based on their own medical judgment. CADDIE is not intended to replace a full patient evaluation, nor is it intended to be relied upon to make a primary interpretation of endoscopic procedures, medical diagnosis, or recommendations of treatment. For complete access to the EAGLE Trial study, visit https://doi.org/10.1038/s41746-025-02270-1.

Curated from NewMediaWire

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Burstable Health Team

Burstable Health Team

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