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Completed

NCT Number: NCT04510545

Computer Aided Diagnosis of Colorectal Polyps

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.

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Key information

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Endobrain, Computer Aided Diagnosis (CAD)

Diagnostic Test

Artificial intelligence

Primary outcomes

  1. True positive adenoma detection rate

    Time frame: 6 months

    True positive adenoma detection rate with visual inspection versus true positive adenoma detection rate with visual inspection plus CAD

Secondary outcomes

  1. True negative adenoma detection rate

    Time frame: 6 months

    True negative adenoma detection rate with visual inspection versus true negative adenoma detection rate with visual inspection plus CAD

  2. To estimate the sensitivity, specificity, of visual inspection and the use of the EndoBRAIN CAD technology

    Time frame: 6 months

    To estimate the sensitivity, specificity, of visual inspection and the use of the EndoBRAIN CAD technology

  3. To estimate the positive predictive value [PPV], and NPV of the combination of visual inspection and the use of the EndoBRAIN CAD technology

    Time frame: 6 months

    To estimate the positive predictive value [PPV], and NPV of the combination of visual inspection and the use of the EndoBRAIN CAD technology

  4. To estimate the percentage of diminutive colorectal polyps from which endocytoscopic images can be successfully captured (acquisition rate).

    Time frame: 6 months

    To estimate the percentage of diminutive colorectal polyps from which endocytoscopic images can be successfully captured (acquisition rate).

  5. To estimate the rate of high-confidence diagnosis with EndoBRAIN as compared to visual polyp inspection alone.

    Time frame: 6 months

    To estimate the rate of high-confidence diagnosis with EndoBRAIN as compared to visual polyp inspection alone.

  6. Time of colonoscopy

    Time frame: during procedure

    Time of colonoscopy to be recorded.

  7. Complications

    Time frame: 6 months

    complications to be recorded.

Sponsors and collaborators

Lead sponsor

King's College Hospital NHS Trust

Other

Registry information

Official study title

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

Acronym: EndoBrain

Important dates

Study start
2020
Primary completion
2021
Study completion
2021
First posted
Aug 12, 2020
Registry last updated
Jan 31, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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