Artificial Intelligence in Colonoscopy

NCT ID: NCT06621225

Last Updated: 2024-10-01

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

264 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-11-22

Study Completion Date

2023-06-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

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.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

264 patients, with an equal gender distribution (50% female), aged 75 years and above, undergoing screening and diagnostic colonoscopy at The Surgery and Endoscopy Center of Sebring, Sebring, Florida, were enrolled in this study. The eligibility criteria for a randomized controlled trial (RCT) comparing AI and mucosal exposure devices together, mucosal exposure devices alone, and white light endoscopy in patients 75 years and older could be structured as follows.

Patients were randomly allocated into one of three study groups: the primary intervention arm, where colonoscopy was performed using the CADe in combination with the MED; the second group underwent colonoscopy solely with the MED, while the control group underwent colonoscopy solely with the WLE. We used a Convolutional Neural Network-based CADe system, GI Genius, acquired for licensed use from Medtronic Inc., Minneapolis, MN. The MED employed was the EndoCuff Vision (ECV) developed by Olympus America, Center Valley, PA, which constitutes part of the standard equipment available. All detected lesions were identified and excised throughout the colonoscopy procedures, and specimens were promptly sent for histopathological analysis.

The primary outcome of interest was adenoma detection rate (ADR), defined as the percentage of patients in whom at least one histologically proven adenoma or carcinoma was identified during colonoscopy. Secondary outcomes included ADR in the left colon in our cohort of patients.

This study was conducted according to accepted ethical principles and approved by the institutional review board (IRB) of "The Surgery and Endoscopy Center of Sebring.\" Informed consent was obtained from all participants before enrollment, and measures were taken to ensure patient confidentiality and data protection throughout the study period.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Colorectal Carcinoma

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Patients were randomly allocated into one of three study groups: the primary intervention arm, where colonoscopy was performed using the CADe in combination with the MED; the second group underwent colonoscopy solely with the MED, while the control group underwent colonoscopy solely with the WLE. Randomization was executed by a scheduler responsible for patient appointments at the practice, ensuring impartial allocation, with the investigators maintaining no involvement in subject assignment to study arms. We used a Convolutional Neural Network-based CADe system, GI Genius, acquired for licensed use from Medtronic Inc., Minneapolis, MN. The MED employed was the EndoCuff Vision (ECV) developed by Olympus America, Center Valley, PA, which constitutes part of the standard equipment available. All detected lesions were identified and excised throughout the colonoscopy procedures, and specimens were promptly sent for histopathological analysis.
Primary Study Purpose

SCREENING

Blinding Strategy

TRIPLE

Participants Caregivers Investigators

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Primary Intervention Arm

In this arm, colonoscopy was performed using Computer Aided detection in combination with a Mucosal Exposure Device, which is FDA approved.

Group Type EXPERIMENTAL

Artificial Intelligence

Intervention Type DEVICE

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.

Mucosal Exposure Device

Intervention Type 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.

Secondary Intervention Arm

In this arm, participants underwent colonoscopy solely with an FDA approved Mucosal Exposure Device

Group Type EXPERIMENTAL

Mucosal Exposure Device

Intervention Type 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.

Control group

In this arm, the participants underwent standard white light endoscopy without any intervention.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

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.

Intervention Type 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.

Intervention Type DEVICE

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

1. Patients aged 75 years and older.
2. Patients who were able to provide informed consent or had a legally authorized representative who can consent on their behalf.
3. Patients who were deemed fit for colonoscopy based on a pre-procedure evaluation.

Exclusion Criteria

1. Patients with acute gastrointestinal conditions such as active colitis, acute diverticulitis, or bowel obstruction.
2. Patients with a history of major colorectal surgery that might alter normal colon anatomy (e.g., colectomy).
3. Patients with severe comorbid conditions that would contraindicate colonoscopy, such as severe cardiopulmonary disease or advanced liver disease.
4. Patients with uncorrected coagulopathies or those on anticoagulation therapy that cannot be safely managed around the time of the procedure.
5. Patients who are unable to adequately prepare the bowel for colonoscopy.
6. Patients who refuse to participate in the study or have a legally authorized representative who refuses consent.
Minimum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Pankaj Patel

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Pankaj Patel

Gastroenterologist and Medical Director of The Surgery and Endoscopy Center

Responsibility Role SPONSOR_INVESTIGATOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Pankaj J Patel, MD

Role: PRINCIPAL_INVESTIGATOR

The Surgery and Endoscopy Center of Sebring

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

The Surgery and Endoscopy Center of Sebring

Sebring, Florida, United States

Site Status

Countries

Review the countries where the study has at least one active or historical site.

United States

References

Explore related publications, articles, or registry entries linked to this study.

Pohl H, Robertson DJ. Colorectal cancers detected after colonoscopy frequently result from missed lesions. Clin Gastroenterol Hepatol. 2010 Oct;8(10):858-64. doi: 10.1016/j.cgh.2010.06.028. Epub 2010 Jul 22.

Reference Type BACKGROUND
PMID: 20655393 (View on PubMed)

Dekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB. Colorectal cancer. Lancet. 2019 Oct 19;394(10207):1467-1480. doi: 10.1016/S0140-6736(19)32319-0.

Reference Type BACKGROUND
PMID: 31631858 (View on PubMed)

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

Pro00069956

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.