Colorectal PolypNCT05545189
Polyp Histology Prediction by Artificial Intelligence
An observational study of Colorectal Polyp, run by Petz Aladar County Teaching Hospital.
Trial summary
We have been developing artificial intelligence based polyp histology prediction (AIPHP) method to classify Narrow Band Imaging(NBI) colonoscopy images to predict the hyperplastic or neoplastic histology of polyps. Read more about this study
- Who is it for?
- Ages 18 to 85 years
- Conditions the study is for
- Colorectal Polyp
- What is being tested?
- colonoscopy,polypectomy
- How many people
- 1,200 participants
- Where
- No sites listed yet
- Study dates
- 31 Oct 2022to 31 Mar 2024
- How long will I take part?
- 3 Years
- Phase
- Observational
- 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 18 to 85 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: patients with colorectal polyps detected by colonoscopy
Who may be able to join
- colorectal polyps removed by polypectomy
Who cannot join
- colorectal polyps with IBD
About this study
Official title: Colorectal Polyp Histology Prediction by Artificial Ingelligence Method Based on NBI Colonoscopy Images.
We have been developing artificial intelligence based polyp histology prediction (AIPHP) method to classify Narrow Band Imaging(NBI) colonoscopy images to predict the hyperplastic or neoplastic histology of polyps.
We plan to study colonoscopy polyp samples taken by polypectomy from 1200 patients.The documented NBI still images will be analyzed by the AIPHP method and by the NICE classification parallel.Our aim is to analyze the accuracy of AIPHP and NBI classification based histology predictions and also compare the results of the two methods.
Read the detailed description
Background:
Colonoscopy with polypectomy or early colorectal neoplastic lesions (polyp) is a proven and widely accepted method of reducing colorectal cancer mortality rates.
Predicting histology prior to endoscopic colorectal polyp removal is useful especially for diminutive (1-5mm) and small (6-10mm ) polyps.
Evaluation of colorectal polyps using the narrow-band imaging (NBI) technique and the NBI International Colorectal Endoscopic (NICE) classification are useful to predict the histology during endoscopy.However, NBI and magnification based polyp histology prediction needs training and endoscopic experience. Morever , the final and objective diagnosis still requires histology.
Therefore,we have been developing arteficial intelligence-based polyp histology prediction (AIPHP) software to automatically evaluate the magnified NBI colonoscopy images aiming the histology prediction of polyps.
Materials and methods:
We plan to examine 1200 colorectal polyps obtained from patients. Polyps will be removed by traditional polypectomy or with mucosectomy.Endoscopic procedures and histological examinations performed at the participation hospitals. Colonoscopy will be performed with Olympus EXERA III CFHQ190I (Olympus ,Tokyo,Japan) high reolution NBI colonoscopes providing 65x optical magnification. Colorectal polyps will be detected first by high definition colonoscopy then by NBI at the optical maximum magnification (65x). All studied polyps will be photo-documented. The stored NBI photos were anelyzed by the NICE classification and AIPHP parallel system.
Histological examination methods:
We use WHO classification of colorectal polyps. The two -class classification will considere hyperplastic or neoplastic ((SSLs,tubular or villous adenomas, and invasive adenocarcinomas).
AIPHP software systtem:
The AIPHP software is based on the categorization of the vascular pattern and color of the polyps.The main steps of AIPHP software development will be the following: 1) feature vector calculation 2) training of classifier module, and 3) AIPHP classifier testing. Five features will be used by our AIPHP software.
- Conditions
- Colorectal Polyp
- Being tested
- colonoscopy,polypectomy
- Keywords
- colorectal polyp,histology,artificial intelligence
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
colonoscopy,polypectomyDiagnostic test
polyp removal during colonoscopy
| Study group | Role | What they receive |
|---|---|---|
| colonoscopy group1 | Polypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients. Receives: Diagnostic Test: colonoscopy,polypectomy | |
| colonoscopy group 2 | Polypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients Receives: Diagnostic Test: colonoscopy,polypectomy | |
| colonoscopy group 3 | Polypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients Receives: Diagnostic Test: colonoscopy,polypectomy | |
| colonoscopy group 4 | Polypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients Receives: Diagnostic Test: colonoscopy,polypectomy | |
| colonoscopy group 5 | Polypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients Receives: Diagnostic Test: colonoscopy,polypectomy | |
| colonoscopy group 6 | Polypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients Receives: Diagnostic Test: colonoscopy,polypectomy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Polyp histology accuracy by AI method
polyp histology prediction by AI
Measured: two weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Sep 2022
- Study start31 Oct 2022 (estimated)
- Primary completion31 Dec 2023 (estimated)
- Study completion31 Mar 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal PolypStudies 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,200 participants (estimated)
- Target duration
- 3 Years
Sponsor and investigators
- Lead sponsor
- Petz Aladar County Teaching Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05545189
- Sponsor's protocol ID
- PetzACTH2
- Status last verified
- Sep 2022
- First submitted
- 14 Sep 2022
- Last updated
- 22 Sep 2022
- Results posted
- 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 22 Sep 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Colorectal Polyp Histology Prediction by Artificial Ingelligence Method Based on NBI Colonoscopy Images.
- ClinicalTrials.gov ID
- NCT05545189
- Acronym / sponsor ID
- PetzACTH2
- Conditions
- Colorectal Polyp
- Keywords
- colorectal polyp,histology,artificial intelligence
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,200 participants (estimated)
- Lead sponsor
- Petz Aladar County Teaching HospitalUniversity, hospital or other
- Study start
- 31 Oct 2022 (estimated)
- Primary completion
- 31 Dec 2023 (estimated)
- Study completion
- 31 Mar 2024 (estimated)
- First posted
- 19 Sep 2022 (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.
We have been developing artificial intelligence based polyp histology prediction (AIPHP) method to classify Narrow Band Imaging(NBI) colonoscopy images to predict the hyperplastic or neoplastic histology of polyps.
We plan to study colonoscopy polyp samples taken by polypectomy from 1200 patients.The documented NBI still images will be analyzed by the AIPHP method and by the NICE classification parallel.Our aim is to analyze the accuracy of AIPHP and NBI classification based histology predictions and also compare the results of the two methods.
Detailed description
Background:
Colonoscopy with polypectomy or early colorectal neoplastic lesions (polyp) is a proven and widely accepted method of reducing colorectal cancer mortality rates.
Predicting histology prior to endoscopic colorectal polyp removal is useful especially for diminutive (1-5mm) and small (6-10mm ) polyps.
Evaluation of colorectal polyps using the narrow-band imaging (NBI) technique and the NBI International Colorectal Endoscopic (NICE) classification are useful to predict the histology during endoscopy.However, NBI and magnification based polyp histology prediction needs training and endoscopic experience. Morever , the final and objective diagnosis still requires histology.
Therefore,we have been developing arteficial intelligence-based polyp histology prediction (AIPHP) software to automatically evaluate the magnified NBI colonoscopy images aiming the histology prediction of polyps.
Materials and methods:
We plan to examine 1200 colorectal polyps obtained from patients. Polyps will be removed by traditional polypectomy or with mucosectomy.Endoscopic procedures and histological examinations performed at the participation hospitals. Colonoscopy will be performed with Olympus EXERA III CFHQ190I (Olympus ,Tokyo,Japan) high reolution NBI colonoscopes providing 65x optical magnification. Colorectal polyps will be detected first by high definition colonoscopy then by NBI at the optical maximum magnification (65x). All studied polyps will be photo-documented. The stored NBI photos were anelyzed by the NICE classification and AIPHP parallel system.
Histological examination methods:
We use WHO classification of colorectal polyps. The two -class classification will considere hyperplastic or neoplastic ((SSLs,tubular or villous adenomas, and invasive adenocarcinomas).
AIPHP software systtem:
The AIPHP software is based on the categorization of the vascular pattern and color of the polyps.The main steps of AIPHP software development will be the following: 1) feature vector calculation 2) training of classifier module, and 3) AIPHP classifier testing. Five features will be used by our AIPHP software.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 3 Years
- Number of arms
- 6
| Arm | Type | Receives |
|---|---|---|
| colonoscopy group1 | – | Diagnostic Test: colonoscopy,polypectomyPolypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients. |
| colonoscopy group 2 | – | Diagnostic Test: colonoscopy,polypectomyPolypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients |
| colonoscopy group 3 | – | Diagnostic Test: colonoscopy,polypectomyPolypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients |
| colonoscopy group 4 | – | Diagnostic Test: colonoscopy,polypectomyPolypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients |
| colonoscopy group 5 | – | Diagnostic Test: colonoscopy,polypectomyPolypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients |
| colonoscopy group 6 | – | Diagnostic Test: colonoscopy,polypectomyPolypectomy, histological examination, NICE classification and AIPHP analyzis will be performed 200 patients |
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- patients with colorectal polyps detected by colonoscopy
Key inclusion criteria (1 listed)
- colorectal polyps removed by polypectomy
Key exclusion criteria (1 listed)
- colorectal polyps with IBD
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 |
|---|---|---|
| colonoscopy,polypectomypolyp removal during colonoscopy | Diagnostic test | colonoscopy group 2, colonoscopy group 3, colonoscopy group 4, colonoscopy group 5, colonoscopy group 6, colonoscopy group1 |
Primary outcome
Polyp histology accuracy by AI method
Time frame: two weeks
polyp histology prediction by AI
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Sep 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.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Colorectal Polyp, run by Petz Aladar County Teaching Hospital.
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: status not confirmed, as of the sponsor's last update on 22 Sep 2022. Status can change between updates, so confirm with the study contact before making plans.
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?
Results are not available in the source record.
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?
Polyp histology accuracy by AI method (time frame: two weeks). 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 22 Sep 2022.