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NCT Number: NCT06715384

Evaluation of a CAM System for Colorectal Polyp Size Measurement

Accurate polyp size measurements are essential for risk stratification, selection of polypectomy techniques, and surveillance interval assignments. Evidence indicated that the clinical implementation of artificial intelligence is an optimal tool to improve the measurement of polyps during colonoscopy. This study aimed to evaluate the performance of a computer-aided measuring (CAM) system (EndoDASS) and compare its accuracy with routine sizing methods during real-time colonoscopy.

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Key information

Age range

18 year–85 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Changhai Hospital, Naval Medical University

Shanghai, Shanghai Municipality, 200433, China

Location status: Recruiting

Location contact

Cheng-Long Wang, MD

CONTACT

[email protected]

+86-18257806772

En-Da Yu, MBBS

PRINCIPAL_INVESTIGATOR

Sheng-Bing Zhao, MD

SUB_INVESTIGATOR

Xiang-Yu Sui, MD

CONTACT

[email protected]

+86-19916549745

Yu Bai, MD

PRINCIPAL_INVESTIGATOR

Zhao-Shen Li, MD

PRINCIPAL_INVESTIGATOR

About this study

This study will be conducted in 2 phases: the first phase will evaluate the value of the application of the computer-aided measuring (CAM) system for polyp size measurement accuracy in a small sample of clinical videos, recording the corresponding clinical videos for CAM measurements after measuring polyp size using real-time visual assessment and non-scaled device (open biopsy forceps or snare) assessment, and comparing the different methods of polyp size measurement through a video-based analysis [Autonomous artificial intelligence (AI) measurement, AI-assisted human measurement, non-scaled device assessment, and visual assessment] with different groups of endoscopists ( experts, gastroenterologists, surgeons, fellows) evaluating the corresponding clinical videos during real-time measurements, to obtain pilot data on the relative accuracy of polyp size measurement when using the CAM system, to test the feasibility of size measurement of freshly resected polyp specimens and to determine the sample size and reference for evaluating the CAM system in the subsequent phases of a randomized controlled trial of the study. The second phase will assess the value of using the AI-assisted human measurement versus the non-scaled device assessment for polyp size measurement accuracy in a clinical randomized controlled trial using a prospective, multicenter, patient-single-blind, randomized controlled trial design in which subjects are randomly assigned to the CAM group and the non-scaled device measurement group in a 1:1 ratio. Each patient will have a maximum of 3 polyps included in the study.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Adults aged 18-75, any gender; 76-85 years eligible case-by-case based on health status.
  • Colonoscopy screening, surveillance, or diagnostic participants.
  • Informed consent obtained.

Exclusion criteria

  • Anticoagulant use (e.g., aspirin, warfarin) within 7 days prior to colonoscopy or coagulopathy.
  • Inflammatory bowel disease.
  • Aronchick score >3 at entry.
  • Incomplete Case Report Form (CRF) data.
  • Emergency colonoscopy.
  • Pregnancy or lactation.
  • Gastrointestinal obstruction.
  • Refusal to participate.

Treatment and study plan

Polyp size measurement using autonomous AI measurement or AI-assisted human measurement with the CAM system

Diagnostic Test

The study of real-time polyp size measurement using the CAM system will be conducted in two phases. Phase I (pilot phase, n=24 polyps, about 27 patients) will be used to assess the feasibility of applying the CAM system in real-time in a clinical video in order to obtain pilot data on the relative accuracy of assessing polyp sizes using autonomous AI measurement and AI-assisted human measurement and to determine the relative accuracy of assessing polyp size in Phase II of the study ( Randomized Controlled Trial) to assess the sample size and reference standards for the CAM system. The sample size for the second phase of the randomized controlled trial (comparing AI-assisted human measurement to non-scaled device) will be based on pilot data in order to compare the relative accuracy of polyp size measurement with AI-assisted human measurement versus non-scaled device in clinical practice.

Other names: Polyp size measurement with the CAM system

Primary outcomes

  1. Evaluation of the computer-aided measuring (CAM) system

    Time frame: 7 days

    To evaluate the relative accuracies of the computer-aided measuring (CAM) system measurement (Autonomous AI measurement and AI-assisted human measurement), non-scaled device (open biopsy forceps or snare) assessment or visual assessment for measuring polyp size compared to with measurement of freshly resected polyp specimens by a digital vernier caliper as reference standard. Relative accuracy is defined as "[1-(CAM system measurement - ground truth measurement)/ground truth measurement] x100%". Scale: 0-100. Higher score is a better outcome.

Secondary outcomes

  1. video-based analysis

    Time frame: 7 days

    Compare in video-based analysis with different endoscopists (experts, gastroenterologists, surgeons, fellows) the relative size measurements accuracy of CAM system measurement with visual and non-scaled device assessment. Relative accuracy is defined as "[1-(CAM system measurement ground truth measurement)/ground truth measurement] x100%". Scale: 0-100. Higher score is a better outcome.

  2. Reliability between CAM system measurement and ground truth measurement

    Time frame: 7 days

    Reliability between CAM system measurement, non-scaled device assessment, visual assessment and ground truth measurement is evaluate by concordance correlation coefficient (CCC). CCC is a statistical measure used to evaluate the agreement between two continuous variables.The CCC considers both the correlation and the bias between the two variables. It ranges from -1 to 1;1: Perfect agreement. 0: No agreement. Negative values: Indicate that the variables diverge.

  3. Time taken for polyp size measurement

    Time frame: 7 days

    Measurement time of the AI-assisted human measurement, non-scaled device assessment, and visual estimation refers to the time taken by endoscopists using various measurement methods, starting from when a polyp appears in the field of view for measurement until the report of the polyp size is completed.

  4. Percentage differences between the AI-assisted human measurement and non-scaled device assessment

    Time frame: 7 days

    Calculate percentage differences between the AI-assisted human measurement and non-scaled device assessment.

  5. Instances of overestimation or underestimation by the AI-assisted human measurement and non-scaled device assessment

    Time frame: 7 days

    Evaluate the instances of overestimation or underestimation by the AI-assisted human measurement and non-scaled device assessment.

Study contacts

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

Cheng-Long Wang, MD

CONTACT

[email protected]

+86-18257806772

Xiang-Yu Sui, MD

CONTACT

[email protected]

+86-19916549745

Sponsors and collaborators

Lead sponsor

Changhai Hospital

Other

Registry information

Official study title

Performance Evaluation of a Computer-aided Measuring System for Colorectal Polyp Size Measurement: a Prospective Study

Acronym: CAM

Important dates

Study start
2024
Primary completion
2025
Study completion
2025
First posted
Dec 4, 2024
Registry last updated
Feb 19, 2025

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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