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NCT Number: NCT06543862

Autonomous Artificial Intelligence Versus AI Assisted Human Optical Diagnosis

Computer-aided image-enhanced endoscopy can predict the nature of colorectal polyps with over 90% accuracy. This technology uses artificial intelligence (AI) to analyze video recordings of polyps, learning to make diagnoses in real-time. This means that doctors can get immediate predictions about small polyps during the procedure, reducing the need for separate pathology exams and saving costs, ultimately improving patient care.

Human and AI interactions are complex and a framework to reap synergistic effects CADx systems when used by humans to harness optimal performance needs to be established. AI solutions in medicine are usually developed to be used as assistive devices, however, then they rely on humans to correct AI errors. Optical polyp diagnosis is a complex task. Non experts usually achieve diagnostic accuracy in 70-80%. CADx systems have a similar diagnostic accuracy when used autonomously. Clinical evaluation of CADx systems showed that CADx assisted OD performs equally to the operator performance when using non CADx assisted OD. To harness a benefit of clinical CADx implementation we would have to find a way that synergies between human and CADx come into play to eliminate cases in which CADx assisted and/ or human OD results in low diagnostic accuracy and also addresses the problem of serrated polyp recognition.

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Key information

Conditions

Colonic Polyp Artificial Intelligence Colonic Polyps Intestinal Polyps Pathological Conditions, Anatomical Pathological Conditions, Signs and Symptoms Polyps

Age range

45 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Ghislaine Ahoua

Montreal, Quebec, Canada

Location contact

Daniel von Renteln, MD

CONTACT

About this study

Our study hypothesis is that for CADx implementation, instead of using the high/low confidence framework, identifying cases with suboptimal diagnostic accuracy could be facilitated through identifying cases in which CADx and endoscopist disagreed in their diagnosis. Eliminating such cases might separate out cases with low accuracy when using CADx assisted OD. Since endoscopists have a high sensitivity but low specificity for serrated polyp OD, this framework will also allow us to implement a strategy to adequately manage serrated polyps found in the cohort.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Indication for full colonoscopy.

Exclusion criteria

  • Known inflammatory bowel disease
  • Active colitis
  • coagulopathy
  • familial polyposis syndrome
  • poor general health, defined as an American Society of Anesthesiologists class >3
  • emergency colonoscopy

Treatment and study plan

CADx (AI) system

Other

The CADx system will be used to predict the histopathology of the polyp detected.

Primary outcomes

  1. Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis

    Time frame: up to 100 weeks

    Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis , when histopathology results are used as the reference

Secondary outcomes

  1. Accuracy of optical diagnosis, for polyps 1-10mm, compared with an agreed upon CADx-assisted diagnosis

    Time frame: up to 100 weeks

    Accuracy of optical diagnosis, for polyps 1-10mm, compared with an agreed upon CADx-assisted diagnosis, when histopathology results are used as the reference

  2. Test characteristics, including recall, specificity, positive and negative predictive values (PPV/NPV), and particularly the NPV of rectosigmoid neoplastic polyps.

    Time frame: up to 100 weeks

    A ≥90% NPV will be used as a quality benchmark for a strategy to not resect such diminutive polyps.

  3. Agreement of surveillance interval recommendations of AI-A and AI-H compared with the pathology-based recommendations

    Time frame: up to 100 weeks

    For surveillance interval assignment, the pathology results of concomitant polyps >5 mm (including multiple concomitant polyps of all sizes and histology) will be considered when calculating the surveillance interval recommendation. Surveillance recommendations will be based on the 2020 United States Multi Society Task Force Guidelines as is current standard of practice at our center.

  4. Proportion of patients for whom an immediate surveillance recommendation can be directly provided for each approach, and how often histopathology-based polyp examination would have been avoided.

    Time frame: up to 100 weeks

    The potential cost-effectiveness of OD (either approaches) will be evaluated using the measured described above.

  5. Variability of OD (AI-A and AI-H) across participating endoscopists.

    Time frame: up to 100 weeks

    Each participating endoscopist will conduct a similar number of optical diagnoses to assess endoscopist-related factors.

  6. Cost-effectiveness of OD ((AI-A and AI-H)

    Time frame: up to 100 weeks

    A cost-effectiveness model will be applied to better quantify costs and understand cost impact including key cost drivers when generalized to a broader screening population.

Study contacts

Contact information is provided by the study sponsor or research team.

Daniel von Renteln, MD

CONTACT

[email protected]

514 890-8000 ext. 30912

Sponsors and collaborators

Lead sponsor

Centre hospitalier de l'Université de Montréal (CHUM)

Other

Registry information

Official study title

Autonomous Artificial Intelligence Versus AI Assisted Human Optical Diagnosis of Colorectal Polyps

Acronym: CADx-Prosp

Important dates

Study start
2024
Primary completion
2024
Study completion
2024
First posted
Aug 9, 2024
Registry last updated
Nov 15, 2024

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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