AdenomaNCT05089071
Effect of Two Colonoscopy AI Systems for Colon Polyp Detection
A study testing Assist by artificial intelligence system for colon polyp detection in people with Adenoma and Colonoscopy, run by Seoul National University Hospital at 1 site in South Korea.
Trial summary
Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. The investigators aim to identify the effect of two CADe systems according to the system performance on false positive rate Read more about this study
- Who is it for?
- Ages 45 to 100 yearsHealthy volunteers can take part
- Conditions the study is for
- Adenoma, Colonoscopy, Sessile Serrated Adenoma
- What is being tested?
- Assist by artificial intelligence system for colon polyp detection
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 3,046 participants
- Where
- 1 siteSouth Korea
- Study dates
- 1 Nov 2021to 31 Dec 2022
- 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 100 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- patient for screening or surveillance colonoscopy patients agreed with participating in the study
Who cannot join
- patients who do not agree with participating in the study patients with a history of colon resection patients with a history of inflammatory bowel resection patients with poor bowel preparation
Trial locations and contacts
1 site in 1 country.
South Korea1 site
Healthcare System Gangnam Center, Seoul National University Hospital
Seoul
About this study
Official title: Effect of Two Colonoscopy AI Systems for Colon Polyp Detection According to the False Positive Rates of the Systems: A Single-center Prospective Study
Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. The investigators aim to identify the effect of two CADe systems according to the system performance on false positive rate
Read the detailed description
Artificial intelligence technology based on deep learning is being applied in various medical fields, and research is being actively conducted to develop computer-aided detection (CADe) systems for colonoscopies to overcome the limitation of the variance of human skills. These well-trained CADe systems demonstrated high performance for neoplastic polyp detection and reported a 44% increase in adenoma detection rate (ADR) for endoscopists. However, the level of performance in the CADe system is not clear for expert endoscopists to be useful for ADR increase.
Furthermore, false positives(FPs) of the CADe system may negatively influence ADR during a screening colonoscopy. Accordingly, the investigators sought to identify the effect of the colonoscopy CADe system according to FP performance in endoscopists with various levels. The investigators hypothesized that the CADe system with low FPs would be useful to prevent the decrease in ADR in case of a high endoscopy workload according to the performance of CADe systems.
- Conditions
- Adenoma, Colonoscopy, Sessile Serrated Adenoma
- Being tested
- Assist by artificial intelligence system for colon polyp detection
- Keywords
- endoscopist, adenoma detection rate, colonoscopy, artificial intelligence
- Medical subject headings
- Adenoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Assist by artificial intelligence system for colon polyp detectionDevice
Assist by artificial intelligence system for colon polyp detection
| Study group | Role | What they receive |
|---|---|---|
| CADe group | Experimental | Endoscopists perform colonoscopy with CADe system Receives: Device: Assist by artificial intelligence system for colon polyp detection |
| Control | No intervention | Endoscopists perform colonoscopy without CADe system |
What is being measured
The primary outcome is the main question the study is designed to answer.
Adenoma detection rate
proportion of colonoscopies with at least one adenoma detected overall and as detected by the physician.
Measured: 12 months
Sessile serrated lesion detection rate
proportion of colonoscopies with at least one sessile serrated lesion detected overall and as detected by the physician.
Measured: 12 months
Secondary outcomes (1)
polyp detection rate
proportion of colonoscopies with at least one polyp detected overall and as detected by the physician.
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Oct 2021
- Study start1 Nov 2021
- Primary completion31 Oct 2022
- Study completion31 Dec 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for AdenomaStudies of the same condition, open and under way.
- More trials run by Seoul National University HospitalThe sponsor's other registered studies.
- 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
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Model description
- The primary outcome was the comparison of ADR between the control and AI groups according to the intervention system (SCAI vs ENAD system).
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 3,046 participants (actual)
Sponsor and investigators
- Lead sponsor
- Seoul National University Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Seoul National University
- Responsible party
- Sponsor
- Investigators
- Jung Ho Bae, MD, Principal investigator, Seoul National University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05089071
- Sponsor's protocol ID
- SNUH IRB 2107-235-1240
- Status last verified
- Mar 2022
- First submitted
- 11 Oct 2021
- Last updated
- 27 Jul 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.
PubMed 32598963
Study at a glance
From the registry record, last updated by the sponsor on 27 Jul 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effect of Two Colonoscopy AI Systems for Colon Polyp Detection According to the False Positive Rates of the Systems: A Single-center Prospective Study
- ClinicalTrials.gov ID
- NCT05089071
- Acronym / sponsor ID
- SNUH IRB 2107-235-1240
- Conditions
- Adenoma, Colonoscopy, Sessile Serrated Adenoma
- Keywords
- endoscopist, adenoma detection rate, colonoscopy, artificial intelligence
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 3,046 participants (actual)
- Lead sponsor
- Seoul National University HospitalUniversity, hospital or other
- Collaborators
- Seoul National University
- Study start
- 1 Nov 2021 (actual)
- Primary completion
- 31 Oct 2022 (actual)
- Study completion
- 31 Dec 2022 (actual)
- First posted
- 22 Oct 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.
Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. The investigators aim to identify the effect of two CADe systems according to the system performance on false positive rate
Detailed description
Artificial intelligence technology based on deep learning is being applied in various medical fields, and research is being actively conducted to develop computer-aided detection (CADe) systems for colonoscopies to overcome the limitation of the variance of human skills. These well-trained CADe systems demonstrated high performance for neoplastic polyp detection and reported a 44% increase in adenoma detection rate (ADR) for endoscopists. However, the level of performance in the CADe system is not clear for expert endoscopists to be useful for ADR increase.
Furthermore, false positives(FPs) of the CADe system may negatively influence ADR during a screening colonoscopy. Accordingly, the investigators sought to identify the effect of the colonoscopy CADe system according to FP performance in endoscopists with various levels. The investigators hypothesized that the CADe system with low FPs would be useful to prevent the decrease in ADR in case of a high endoscopy workload according to the performance of CADe systems.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- The primary outcome was the comparison of ADR between the control and AI groups according to the intervention system (SCAI vs ENAD system).
| Arm | Type | Receives |
|---|---|---|
| CADe group | Experimental | Device: Assist by artificial intelligence system for colon polyp detectionEndoscopists perform colonoscopy with CADe system |
| Control | No intervention | –Endoscopists perform colonoscopy without CADe system |
Who may qualify
- Ages
- 45 to 100 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- patient for screening or surveillance colonoscopy patients agreed with participating in the study
Key exclusion criteria (1 listed)
- patients who do not agree with participating in the study patients with a history of colon resection patients with a history of inflammatory bowel resection patients with poor bowel preparation
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 |
|---|---|---|
| Assist by artificial intelligence system for colon polyp detectionAssist by artificial intelligence system for colon polyp detection | Device | CADe group |
Primary outcome
Adenoma detection rate
Time frame: 12 months
proportion of colonoscopies with at least one adenoma detected overall and as detected by the physician.
Sessile serrated lesion detection rate
Time frame: 12 months
proportion of colonoscopies with at least one sessile serrated lesion detected overall and as detected by the physician.
1 secondary outcome
polyp detection rate
Time frame: 12 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Jul 2023.
- Background: PubMed 32598963Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.
- Individual participant dataSharing planned: No
Related trials for Adenoma
Active, not recruitingPhase 1/2
A Beta-only IL-2 ImmunoTherapY Study
Advanced Solid Tumor, Unresectable Solid Tumor
RecruitingPhase 1
SW-682 in Advanced Solid Tumors
Advanced Solid Tumor, Mesothelioma, Malignant
RecruitingEarly Phase 1
FET PET/CT Imaging To Localize Pituitary Adenomas In Cushing Disease
Cushing Disease, Pituitary Adenoma
RecruitingPhase 2/3
Zanzalintinib Versus Everolimus in Participants With Locally Advanced or Metastatic Neuroendocrine Tumors
Pancreatic Neuroendocrine Tumor (pNET), Extra-Pancreatic Neuroendocrine Tumor (epNET)
RecruitingPhase 4
68-Ga DOTATATE PET/MRI in the Diagnosis and Management of Somatostatin Receptor Positive CNS Tumors.
CNS Tumors, Meningioma
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.
Jung Ho Bae, MD principal investigator
Seoul National University Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Assist by artificial intelligence system for colon polyp detection in people with Adenoma and Colonoscopy, run by Seoul National University Hospital at 1 site in South Korea.
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 1 inclusion and 1 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: finished, as of the sponsor's last update on 27 Jul 2023. 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 South Korea. 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 is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Adenoma detection rate (time frame: 12 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05089071, which also lists 1 linked publication.
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 27 Jul 2023.