Adenomatous PolypsNCT04811937
Development of a Computer-aided Polypectomy Decision Support
A study testing Computer-aided polypectomy decision support by Artificial Intelligence in people with Adenomatous Polyps, run by Centre hospitalier de l'Université de Montréal (CHUM) at 1 site in Canada.
Trial summary
Quality components of colonoscopy include the detection and complete removal of colorectal polyps, which are precursors to CRC. However, endoscopic ablation may be incomplete, posing a risk for the development of "interval cancers". Read more about this study
- Who is it for?
- Ages 45 to 80 years
- Conditions the study is for
- Adenomatous Polyps
- What is being tested?
- Computer-aided polypectomy decision support by Artificial Intelligence
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 0 participants
- Where
- 1 siteCanada
- Study dates
- Dec 2021to Apr 2023
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 45 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Signed informed consent
- Age 45-80 years
- Indication to undergo a lower GI endoscopy.
Who cannot join
- Known inflammatory bowel disease
- Active colitis
- Coagulopathy
- Familial polyposis syndrome;
- Poor general health, defined as an American Society of Anesthesiologists (ASA) physical status class >3
- Emergency colonoscopies
Trial locations and contacts
1 site in 1 country.
About this study
Quality components of colonoscopy include the detection and complete removal of colorectal polyps, which are precursors to CRC. However, endoscopic ablation may be incomplete, posing a risk for the development of "interval cancers". The investigators propose to develop a solution based on artificial intelligence (AI) (CADp computer-aided decision support polypectomy) to solve this problem.This research project aims to develop CADp, a computer decision support solution (CDS) for the ablation of colorectal polyps from 1 to 20 mm.
Read the detailed description
This research project aims to develop CADp, a computer-based decision support (CDS) solution for the removal of colorectal polyps ranging from 1-20 mm. The investigators will use a video and image dataset of polypectomy procedures to train the CADp model; thus, it can provide real-time overlaid video feedback for polypectomy procedures based on five specific metrics: 1) estimation of polyp size; 2) prediction of morphology and histology; 3) suggestion of an appropriate resection accessory and technical approach based on the characteristics, size, and histology of the polyp according to current guidelines; 4) image overlay, based on semantic image segmentation technology, showing the extent of the lesion and suggestion of an appropriate resection margin contour around the polyp to ensure its complete removal; 5) post-resection analysis to identify any remnant polyp tissue or insufficient resection margin that may increase this risk.
The investigators will collect a set of images and video data from live polypectomy procedures to leverage recent advances in AI technology to train deep learning models. This dataset will be obtained prospectively from a cohort of adults (ages 45-80) undergoing screening, diagnostic, or surveillance colonoscopies. To train the CADp solution, the investigators will obtain the corresponding completeness of resection status using the yield of post-resection margin biopsies. The dataset will be divided into two groups, the training, and the CADp test, respectively.
- Conditions
- Adenomatous Polyps
- Being tested
- Computer-aided polypectomy decision support by Artificial Intelligence
- Keywords
- Polyps detection, Artificial Intelligence, Adenoma detection, Polyps classification, Computer decision support
- Medical subject headings
- Adenomatous Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Computer-aided polypectomy decision support by Artificial IntelligenceDiagnostic test
The AI system will capture the live video of the procedure and the AI feedbackwill be shown on a second screen installed next to the regular endoscopy screen. Screen A will show the regular endoscopy image and screen B will show the regular endoscopy image together with the areas that might harbor a polyp and the information to help the polypectomy.
| Study group | Role | What they receive |
|---|---|---|
| Artificial intelligence for real-time Computer decision support of resection of colorectal polyps | Experimental | A standard colonoscopy will be performed according to the standard of routine care. All optically diagnosed polyps will be removed and sent to the CHUM pathology laboratory for histopathological evaluation according to institutional standards. The AI system will capture video of the procedure in real time, and provide additional information about polypectomy procedures. Receives: Diagnostic Test: Computer-aided polypectomy decision support by Artificial Intelligence |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of the CADp system
accuracy with which the CADp system predicts completeness of polypectomy in the test set with the reference standard for completeness being determined by the histology of post-polypectomy margin biopsies; if free from any polyp tissue (adenomatous, serrated or hyperplastic), the resection will be considered complete. If remnant polyp tissue is detected in any one or more of the margin biopsies the resection is deemed incomplete
Measured: 3 weeks
Completeness of polypectomy
We will evaluate the agreement between the different subjective and objective ways of assessing the completeness of the polypectomy : evaluation of margins (presence or not, measurement of margins) by endoscopists self-assessment, and by expert consensus.
Measured: 1 month
Training CADp
Evaluation of the concordance of data on polyp size, extension of margins around the polyp, quality of resection between clinical data (endoscopists' self-assessment and experts' assessments) and CADp prediction.
Measured: 1 month
Validity of the choice of primary outcome
Based on the results and comparison of the different assessment methods, we will perform sensitivity analyses to assess the validity and robustness of the choice of primary outcome.
Measured: 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Mar 2021
- Study startDec 2021 (estimated)
- Primary completionApr 2023 (estimated)
- Study completionApr 2023 (estimated)
Why it stopped: The study was abandoned due to the Covid pandemic which prevented recruitment.
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Adenomatous PolypsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- prospective, multi-endoscopist, single center, clinical study at tertiary referral center (CHUM)
- Masking
- None (open label)
- Enrolment
- 0 participants (actual)
Sponsor and investigators
- Lead sponsor
- Centre hospitalier de l'Université de Montréal (CHUM)
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Daniel von Renteln, Principal investigator, Centre hospitalier de l'Université de Montréal (CHUM)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04811937
- Sponsor's protocol ID
- 20.382
- Status last verified
- Dec 2022
- First submitted
- 16 Feb 2021
- Last updated
- 13 Dec 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 Dec 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Computer-aided Polypectomy Decision Support
- ClinicalTrials.gov ID
- NCT04811937
- Acronym / sponsor ID
- 20.382
- Conditions
- Adenomatous Polyps
- Keywords
- Polyps detection, Artificial Intelligence, Adenoma detection, Polyps classification, Computer decision support
- Study type
- Interventional
- Recruitment status
- WithdrawnReason stopped: The study was abandoned due to the Covid pandemic which prevented recruitment.
- Enrolment
- 0 participants (actual)
- Lead sponsor
- Centre hospitalier de l'Université de Montréal (CHUM)University, hospital or other
- Study start
- Dec 2021 (estimated)
- Primary completion
- Apr 2023 (estimated)
- Study completion
- Apr 2023 (estimated)
- First posted
- 23 Mar 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Quality components of colonoscopy include the detection and complete removal of colorectal polyps, which are precursors to CRC. However, endoscopic ablation may be incomplete, posing a risk for the development of "interval cancers". The investigators propose to develop a solution based on artificial intelligence (AI) (CADp computer-aided decision support polypectomy) to solve this problem.This research project aims to develop CADp, a computer decision support solution (CDS) for the ablation of colorectal polyps from 1 to 20 mm.
Detailed description
This research project aims to develop CADp, a computer-based decision support (CDS) solution for the removal of colorectal polyps ranging from 1-20 mm. The investigators will use a video and image dataset of polypectomy procedures to train the CADp model; thus, it can provide real-time overlaid video feedback for polypectomy procedures based on five specific metrics: 1) estimation of polyp size; 2) prediction of morphology and histology; 3) suggestion of an appropriate resection accessory and technical approach based on the characteristics, size, and histology of the polyp according to current guidelines; 4) image overlay, based on semantic image segmentation technology, showing the extent of the lesion and suggestion of an appropriate resection margin contour around the polyp to ensure its complete removal; 5) post-resection analysis to identify any remnant polyp tissue or insufficient resection margin that may increase this risk.
The investigators will collect a set of images and video data from live polypectomy procedures to leverage recent advances in AI technology to train deep learning models. This dataset will be obtained prospectively from a cohort of adults (ages 45-80) undergoing screening, diagnostic, or surveillance colonoscopies. To train the CADp solution, the investigators will obtain the corresponding completeness of resection status using the yield of post-resection margin biopsies. The dataset will be divided into two groups, the training, and the CADp test, respectively.
Study design
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- prospective, multi-endoscopist, single center, clinical study at tertiary referral center (CHUM)
| Arm | Type | Receives |
|---|---|---|
| Artificial intelligence for real-time Computer decision support of resection of colorectal polyps | Experimental | Diagnostic Test: Computer-aided polypectomy decision support by Artificial IntelligenceA standard colonoscopy will be performed according to the standard of routine care. All optically diagnosed polyps will be removed and sent to the CHUM pathology laboratory for histopathological evaluation according to institutional standards. The AI system will capture video of the procedure in real time, and provide additional information about polypectomy procedures. |
Who may qualify
- Ages
- 45 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Signed informed consent
- Age 45-80 years
- Indication to undergo a lower GI endoscopy.
Key exclusion criteria (6 listed)
- Known inflammatory bowel disease
- Active colitis
- Coagulopathy
- Familial polyposis syndrome;
- Poor general health, defined as an American Society of Anesthesiologists (ASA) physical status class >3
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Computer-aided polypectomy decision support by Artificial IntelligenceThe AI system will capture the live video of the procedure and the AI feedbackwill be shown on a second screen installed next to the regular endoscopy screen. Screen A will show the regular endoscopy image and screen B will show the regular endoscopy image together with the areas that might harbor a polyp and the information to help the polypectomy. | Diagnostic test | Artificial intelligence for real-time Computer decision support of resection of colorectal polyps |
Primary outcome
Accuracy of the CADp system
Time frame: 3 weeks
accuracy with which the CADp system predicts completeness of polypectomy in the test set with the reference standard for completeness being determined by the histology of post-polypectomy margin biopsies; if free from any polyp tissue (adenomatous, serrated or hyperplastic), the resection will be considered complete. If remnant polyp tissue is detected in any one or more of the margin biopsies the resection is deemed incomplete
Completeness of polypectomy
Time frame: 1 month
We will evaluate the agreement between the different subjective and objective ways of assessing the completeness of the polypectomy : evaluation of margins (presence or not, measurement of margins) by endoscopists self-assessment, and by expert consensus.
Training CADp
Time frame: 1 month
Evaluation of the concordance of data on polyp size, extension of margins around the polyp, quality of resection between clinical data (endoscopists' self-assessment and experts' assessments) and CADp prediction.
Validity of the choice of primary outcome
Time frame: 1 month
Based on the results and comparison of the different assessment methods, we will perform sensitivity analyses to assess the validity and robustness of the choice of primary outcome.
Results and safety
The study was withdrawn before enrolling participants, so there are no results.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Dec 2022.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Daniel von Renteln principal investigator
Centre hospitalier de l'Université de Montréal (CHUM)
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Computer-aided polypectomy decision support by Artificial Intelligence in people with Adenomatous Polyps, run by Centre hospitalier de l'Université de Montréal (CHUM) at 1 site in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: withdrawn, as of the sponsor's last update on 13 Dec 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study was withdrawn before enrolling participants, so there are no results.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of the CADp system (time frame: 3 weeks). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Dec 2022; AzTrials last refreshed its copy on 27 Oct 2026.