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Computer Aided Diagnosis of Colorectal Polyps

Real-Time Artificial Intelligence Aided Diagnosis of Colorectal Polyps During Colonoscopy: A Clinical Trial With the EndoBRAIN Technology

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04510545
Acronym
EndoBrain
Enrollment
89
Registered
2020-08-12
Start date
2020-06-01
Completion date
2021-05-05
Last updated
2022-01-31

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Colonic Polyp, Colorectal Cancer

Brief summary

The purpose of this study is to assess whether computer aided technology (CAD) can help in the diagnosis of polyps found the bowel compared with visual inspection alone and therefore whether it is beneficial in helping clinicians to decide whether to remove a polyp or not. Presently, most endoscopists remove all polyps found and send them to the laboratory for testing. The number of colonoscopies is increasing, meaning that more polyps are detected and removed. This comes at a significant cost to the health service and increases the time taken to complete a colonoscopy.

Detailed description

Removing precancerous polyps from the bowel during a colonoscopy (camera test) is the cornerstone of colorectal cancer screening and prevents polyps developing into bowel cancer. Most polyps develop in the rectosigmoid colon (lower part of the bowel). Many polyps never grow into cancer and it can be difficult for the clinicians performing the procedure (endoscopists) to tell which ones are precancerous. This means many polyps are removed unnecessarily, with a considerable waste of resources. A recent preliminary study indicates a novel artificial intelligence system (EndoBRAIN) for computer-aided diagnosis may be able to distinguish different types of polyps during colonoscopy and therefore help doctors decide which polyps to remove. This study aims to compare the in accuracy of artificial intelligence against the endoscopist's assessment for diagnosis of diminutive (\<5mm) polyps in the lower colon. Patients who are age 18 years or older who undergo colonoscopy for any indication at the participating clinical centres and are diagnosed with diminutive rectosigmoid polyps are eligible for study enrolment. For each detected polyp in the rectosigmoid colon, endoscopists will assess the polyp type using standard colonoscopies (cameras) and then with the use of the EndoBRAIN technology. The polyps will be removed and sent to the laboratory for testing. The difference between clinician diagnosis and EndoBRAIN diagnosis will be compared with the laboratory findings. We hypothesize that the EndoBRAIN technology provides a superior accuracy in identifying precancerous rectosigmoid polyps, compared to endoscopist's own prediction with a standard colonoscope. If the trial confirms the superior accuracy of the EndoBRAIN system, polyps classified as non-cancerous with the EndoBRAIN system no longer need to be removed, meaning a large gain for patients and society, due to significantly less polypectomies and pathology reviews.

Interventions

DIAGNOSTIC_TESTEndobrain, Computer Aided Diagnosis (CAD)

Artificial intelligence

Sponsors

King's College Hospital NHS Trust
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 90 Years
Healthy volunteers
Yes

Inclusion criteria

* Individuals 18 years or older who are scheduled for screening, surveillance, diagnostic, or therapeutic colonoscopy at at King's College Hospital with diminutive rectosigmoid polyps.

Exclusion criteria

* Diminutive polyps with known histology * Inflammatory bowel disease * Polyposis syndrome (e.g., familial adenomatous polyposis, serrated polyposis) * History of chemotherapy or radiation therapy for colorectal lesions * Inability to undergo polypectomy (e.g. intake of anticoagulants, comorbidities, or patient refusal) * Pregnancy

Design outcomes

Primary

MeasureTime frameDescription
True positive adenoma detection rate6 monthsTrue positive adenoma detection rate with visual inspection versus true positive adenoma detection rate with visual inspection plus CAD

Secondary

MeasureTime frameDescription
To estimate the sensitivity, specificity, of visual inspection and the use of the EndoBRAIN CAD technology6 monthsTo estimate the sensitivity, specificity, of visual inspection and the use of the EndoBRAIN CAD technology
To estimate the positive predictive value [PPV], and NPV of the combination of visual inspection and the use of the EndoBRAIN CAD technology6 monthsTo estimate the positive predictive value \[PPV\], and NPV of the combination of visual inspection and the use of the EndoBRAIN CAD technology
To estimate the percentage of diminutive colorectal polyps from which endocytoscopic images can be successfully captured (acquisition rate).6 monthsTo estimate the percentage of diminutive colorectal polyps from which endocytoscopic images can be successfully captured (acquisition rate).
True negative adenoma detection rate6 monthsTrue negative adenoma detection rate with visual inspection versus true negative adenoma detection rate with visual inspection plus CAD
Time of colonoscopyduring procedureTime of colonoscopy to be recorded.
Complications6 monthscomplications to be recorded.
To estimate the rate of high-confidence diagnosis with EndoBRAIN as compared to visual polyp inspection alone.6 monthsTo estimate the rate of high-confidence diagnosis with EndoBRAIN as compared to visual polyp inspection alone.

Countries

United Kingdom

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026