AI-Aided Colonoscopy Technology Improves Adenoma Detection Rates
|
By HospiMedica International staff writers Posted on 26 Feb 2024 |

Colorectal cancer (CRC) is the third most prevalent cancer worldwide, and one of the deadliest. Typically, CRC begins with polyps or other precancerous growths in the colon or rectum. These can be spotted during a colonoscopy, a procedure where an endoscope with a camera is inserted through the rectum to examine the entire colon for anomalies. Despite its widespread adoption in many developed countries, the standard colonoscopy process has a notable drawback: high rates of missed and undetected adenomas. This means that even regularly screened patients remain at risk of developing colon cancer. As a result, the integration of Artificial Intelligence (AI) and Machine Learning (ML) into colonoscopy has emerged as a groundbreaking advancement in high-performance gastroenterology clinics, enhancing diagnostic accuracy and aiding in clinical decisions.
Now, new research has found that MAGENTIQ-EYE Ltd.’s (Haifa, Israel) AI-powered polyp detection system can improve adenoma detection rates (ADRs). The system, known as MAGENTIQ-COLO, fits seamlessly into the existing colonoscopy procedure, helping gastroenterologists identify polyps by providing information about their size, type, and maturity level, without disrupting the process. The MAGENTIQ-COLO device captures digital video signals from the endoscopy setup and applies deep learning algorithms in real time. It highlights detected polyps with a bounding box on the main or an auxiliary screen, drawing the doctor’s attention to potential concerns during the procedure.
Additionally, the system presents details about the polyp's size and characteristics on the screen's left side, offering the gastroenterologist vital insights for polyp identification and decision-making. After the procedure, videos with or without the bounding boxes can be stored and reviewed later. MAGENTIQ-COLO also generates a comprehensive report that includes the procedure's duration and findings, viewable on the device’s monitor and exportable for further use. A comprehensive 14-month study across 10 top medical centers, involving 31 endoscopists and 952 patients, underscores MAGENTIQ-COLO's leading performance in AI-assisted colonoscopy. This multicenter, randomized, controlled trial encompassed patients referred for non-immunochemical fecal occult blood test (iFOBT) screening or surveillance colonoscopy.
Participants were randomly assigned to either CAD-assisted or conventional colonoscopy, with a subset undergoing tandem colonoscopies (CAD followed by conventional or vice versa). The study focused on primary objectives like adenoma per colonoscopy (APC) and adenoma per extraction (APE), and secondary objectives such as the adenoma miss rate (AMR) in tandem colonoscopies. Results showed that MAGENTIQ-COLO boosted ADR by 7% in absolute terms. A higher ADR is closely linked to reduced CRC incidence and mortality. The study also assessed the system’s impact on AMR, revealing a 17% absolute reduction in AMR with the use of MAGENTIQ-COLO.
"It is important to note that measuring changes in both ADR and AMR in a single study is a novelty,” said Dror Zur, Founder and CEO of MAGENTIQ EYE. “In addition to FDA approval that we received last year, this milestone is a testament to the impact of MAGENTIQ-COLO™ in advancing the quality of colonoscopy and setting new healthcare standards in order to save more and more lives."
Latest AI News
- Facial Image Analysis Tracks Biological Aging, Predicts Cancer Outcomes
- AI Model Uses Eye Imaging to Identify Risk of Major Systemic Diseases
- AI Platform Interprets Real-Time Wearable Data for Parkinson’s Management
- Algorithm Identifies Cardiac Arrest Hotspots to Guide AED Placement
- AI Analysis of Pericardial Fat Refines Long-Term Heart Disease Risk
- Machine Learning Approach Enhances Liver Cancer Risk Stratification
- New AI Approach Monitors Brain Health Using Passive Wearable Data
- AI Tool Maps Early Risk Patterns in Bloodstream Infections
- AI Model Identifies Rare Endocrine Disorder from Hand Images
Channels
Artificial Intelligence
view channelFacial Image Analysis Tracks Biological Aging, Predicts Cancer Outcomes
Biological aging is the progressive loss of physiological function that may diverge from chronological age. In cancer care, clinicians need simple tools that reflect dynamic changes in patient resilience... Read more
AI Model Uses Eye Imaging to Identify Risk of Major Systemic Diseases
Early detection of systemic disease risk remains a persistent challenge in population health screening. Cardiometabolic conditions such as diabetes, heart disease, and stroke often progress without symptoms... Read moreCritical Care
view channel
Battery-Free ECG Patch Enables Continuous Arrhythmia Monitoring
Continuous electrocardiogram (ECG) monitoring supports early detection of arrhythmias and enables timely intervention, yet many wearables depend on bulky batteries that interrupt care when depleted.... Read more
Rapid Clotting Gel Improves Emergency Bleeding Control
Uncontrolled hemorrhage remains a leading cause of preventable death in trauma and major surgery. Conventional clots can form too slowly and fail under mechanical stress, limiting hemostasis and impairing... Read morePatient Care
view channel
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read moreHealth IT
view channel
EHR-Integrated Screening Workflow Detects Cognitive Impairment at Admission
Cognitive impairment involves difficulties with thinking, learning, memory, and decision-making, and is more common in older adults. In U.S. hospitals, more than 40% of admitted older adults have dementia,... Read more
AI System Detects and Quantifies Chronic Subdural Hematoma
Viz.ai (San Francisco, CA, USA) announced a strategic commercialization collaboration with Johnson & Johnson (New Brunswick, NJ, USA) to expand access in the United States to the Viz Subdural solution... Read more
Continuous Monitoring Platform Detects Infection Risk Across Care Transitions
Patients leaving skilled nursing facilities often lose continuous physiologic monitoring, increasing the risk of undetected infection and delayed intervention. Nursing home residents are seven times more... Read more
Automated System Classifies and Tracks Cardiogenic Shock Across Hospital Settings
Cardiogenic shock remains a difficult, time-sensitive emergency, with delayed identification driving poor outcomes and persistently high mortality. Many cases go undocumented even at advanced stages, hindering... Read morePoint of Care
view channel
Point-of-Care Viscoelastic Testing System Supports Obstetric Bleeding Management
HemoSonics (Durham, NC, USA) announced on May 5, 2026 that the company's Quantra Hemostasis System for Obstetric Procedures won Silver in the 2026 Edison Awards in the Women’s Health and Reproductive Innovations... Read moreBusiness
view channel
Johnson & Johnson Launches AI-Driven Cardiac Mapping System
Johnson & Johnson has introduced the CARTOSOUND SONATA Module for the CARTO System at the Heart Rhythm Society (HRS) 2026 meeting in Chicago. The module uses artificial intelligence with the CARTO... Read more







