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Artificial Intelligence in Colonoscopy

NCT06621225 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 264

Last updated 2024-10-01

No results posted yet for this study

Summary

N = 264 patients (50% female) aged 75 years and above undergoing colonoscopy were enrolled. Patients were randomly assigned into one of the three intervention groups: the primary intervention arm (CADe in combination with the MED), the second group with MED alone, and the control group with WLE. All detected lesions were removed and sent to histopathology for diagnosis. The primary outcome was the adenoma detection rate. Secondary outcomes were adenoma detection in the left colon in our cohort of patients.

Conditions

  • Colorectal Carcinoma

Interventions

DEVICE

Artificial Intelligence

Medtronic GI Genius is an advanced AI-powered platform designed to assist gastroenterologists during colonoscopies. Utilizing deep learning algorithms, it analyzes real-time endoscopic images to detect and highlight polyps and other abnormalities, enhancing the detection rate and accuracy. The system provides visual cues to guide physicians in identifying potentially problematic areas that might be missed by the human eye alone. This technology aims to improve diagnostic precision, reduce missed detections, and ultimately enhance patient outcomes by facilitating earlier and more accurate interventions. GI Genius integrates seamlessly with existing endoscopy equipment, offering a valuable tool in the fight against colorectal cancer.

DEVICE

Mucosal Exposure Device

The Olympus Endocuff is an innovative device designed to enhance the effectiveness of colonoscopy procedures. It is a soft, flexible cuff that attaches to the end of the colonoscope and features multiple protruding \"fingers\" that help to improve mucosal exposure. By providing better visibility and maneuverability, the Endocuff helps gastroenterologists navigate and inspect the colon more thoroughly. It aids in the detection of polyps and other abnormalities by flattening folds and improving the overall view of the colon lining. This enhanced visualization contributes to more accurate diagnoses and can potentially reduce the miss rate of significant lesions, ultimately leading to better patient outcomes.

Sponsors & Collaborators

  • Pankaj Patel

    lead OTHER

Principal Investigators

  • Pankaj J Patel, MD · The Surgery and Endoscopy Center of Sebring

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
TRIPLE
Model
PARALLEL

Eligibility

Min Age
75 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-11-22
Primary Completion
2023-05-31
Completion
2023-06-30
FDA Device
Yes

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06621225 on ClinicalTrials.gov