Colonic Adenomatous PolypABCNCT04607083
Impact of Computer-aided Optical Diagnosis (CAD) in Predicting Histology of Diminutive Rectosigmoid Polyps: a Multicenter Prospective Trial (ABC Study).
An observational study of Colonic Adenomatous Polyp, run by Valduce Hospital at 1 site in Italy.
Trial summary
Recently, a CNN-based artificial intelligence (AI) system for polyp characterization has been developed by Fujifilm Co., Tokyo, Japan. It works in conjunction with BLI system. In the present study we prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90%… Read more about this study
- Who is it for?
- Ages 18 to 85 years
- Conditions the study is for
- Colonic Adenomatous Polyp
- What is being tested?
- Polyp carachterization by combing endoscopist evaluation and Ai output
- How many people
- 1,134 participants
- Where
- 1 siteItaly
- Study dates
- 22 Oct 2020to 30 Mar 2021
- 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
- Adult, Older adult
Study population: Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected
Who may be able to join
- Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected.
Who cannot join
- patients with CRC history or hereditary polyposis syndromes or hereditary non-polyposis colorectal cancer
- patients with inadequate bowel preparation
- patients scheduled for partial examinations
- polyps could not be resected due to ongoing anticoagulation preventing resection and pathologic assessment
- patients undergoing urgent colonoscopy
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Impact of Computer-aided Optical Diagnosis (CAD) in Predicting Histology of Diminutive Rectosigmoid Polyps: a Multicenter Prospective Trial (Artificial Intelligence BLI Characterization - ABC Study).
Recently, a CNN-based artificial intelligence (AI) system for polyp characterization has been developed by Fujifilm Co., Tokyo, Japan. It works in conjunction with BLI system. In the present study we prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps having histopathology as reference standard. Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected are included. During endoscopic procedures all polyps identified by the endoscopist are documented for size, location and morphology. All diminutive polyps are characterized by a three sequential steps process: I) endoscopist prediction: the endoscopist evaluates the polyp by using BLI through the BASIC classification; the confidence level (high vs. low) in histology prediction is recorded; II) AI prediction: the AI system is switched on and the output of the automatic evaluation is recorded; this outcome is rated as stable or unstable, depending of the consistency over time of the outcome; III) combined prediction: a final classification is provided by endoscopist in light of the results of the first and of the second step; the confidence level is recorded. All polyps are resected and retrieved in separate jars and sent for pathology assessment. Only polyps characterized with high confidence will be included in the per-polyp analysis; the high-confidence characterization rate will be also calculated; the rate of polyps characterized with a CAD stable outcome will be calculated. Operative characteristics (sensitivity, specificity, positive and negative predictive value and accuracy) in distinguishing adenomatous from non-adenomatous polyps, evaluated with high confidence, will be calculated for each diminutive polyp and for each diminutive rectosigmoid polyp, having histopathology report as reference standard. The post-polypectomy surveillance intervals will be calculated on the basis of polyp histology (reference standard) in all patients according to both USMSTF and ESGE guidelines.
- Conditions
- Colonic Adenomatous Polyp
- Being tested
- Polyp carachterization by combing endoscopist evaluation and Ai output
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Polyp carachterization by combing endoscopist evaluation and Ai outputDiagnostic test
A polyp characterization (adenoma vs. non adenoma) is provided by endoscopist in light of the results of this own evaluation and of the Ai system output. The confidence level (high vs. low) in polyp characterization is recorded. The combined evaluation is compared with histopathology results.
| Study group | Role | What they receive |
|---|---|---|
| Patients with at least one diminutive rectosigmoid polyp | Consecutive adult (>18 years) outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected.
Exclusion criteria:
* patients with CRC history or hereditary polyposis syndromes or hereditary non-polyposis colorectal cancer
* patients with inadequate bowel preparation
* patients in which caecal intubation was not achieved or scheduled for partial examinations
* polyps could not be resected due to ongoing anticoagulation preventing resection and pathologic assessment
* patients undergoing urgent colonoscopy. Receives: Diagnostic Test: Polyp carachterization by combing endoscopist evaluation and Ai output |
What is being measured
The primary outcome is the main question the study is designed to answer.
Agreement of combined prediction with PIVI I statement
To prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps (i.e. PIVI I threshold) having histopathology as reference standard.
Measured: 6 months
Secondary outcomes (3)
Endoscopist prediction
to calculate the performance measures (sensitivity, specificity, positive and negative predictive value) of the endoscopist alone in characterizing diminutive rectosigmoid polyps
Measured: 6 months
Ai prediction
- to calculate the performance measures (sensitivity, specificity, positive and negative predictive value) of the AI system alone in characterizing diminutive rectosigmoid polyps
Measured: 6 months
Agreement of combined prediction with PIVI II statement
- to evaluate if the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in the assignment of post-polypectomy surveillance intervals, according to US and EU guidelines, when combined with the histopathology assessment of polyps >5 mm in size
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Oct 2020
- Study start22 Oct 2020
- Primary completion27 Feb 2021
- Study completion30 Mar 2021
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 Colonic Adenomatous 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
- 1,134 participants (actual)
Sponsor and investigators
- Lead sponsor
- Valduce Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Franco Radaelli, Valduce Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04607083
- Sponsor's protocol ID
- 599/2020
- Acronym
- ABC
- Status last verified
- Jun 2021
- First submitted
- 22 Oct 2020
- Last updated
- 10 Jun 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Rondonotti E, Hassan C, Tamanini G, Antonelli G, Andrisani G, Leonetti G, Paggi S, Amato A, Scardino G, Di Paolo D, Mandelli G, Lenoci N, Terreni N, Andrealli A, Maselli R, Spadaccini M, Galtieri PA, Correale L, Repici A, Di Matteo FM, Ambrosiani L, Filippi E, Sharma P, Radaelli F. Artificial intelligence-assisted optical diagnosis for the resect-and-discard strategy in clinical practice: the Artificial intelligence BLI Characterization (ABC) study. Endoscopy. 2023 Jan;55(1):14-22. doi: 10.1055/a-1852-0330. Epub 2022 May 13.
PubMed 35562098
Study at a glance
From the registry record, last updated by the sponsor on 10 Jun 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Impact of Computer-aided Optical Diagnosis (CAD) in Predicting Histology of Diminutive Rectosigmoid Polyps: a Multicenter Prospective Trial (Artificial Intelligence BLI Characterization - ABC Study).
- ClinicalTrials.gov ID
- NCT04607083
- Acronym / sponsor ID
- ABC / 599/2020
- Conditions
- Colonic Adenomatous Polyp
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,134 participants (actual)
- Lead sponsor
- Valduce HospitalUniversity, hospital or other
- Study start
- 22 Oct 2020 (actual)
- Primary completion
- 27 Feb 2021 (actual)
- Study completion
- 30 Mar 2021 (actual)
- First posted
- 28 Oct 2020 (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.
Recently, a CNN-based artificial intelligence (AI) system for polyp characterization has been developed by Fujifilm Co., Tokyo, Japan. It works in conjunction with BLI system. In the present study we prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps having histopathology as reference standard. Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected are included. During endoscopic procedures all polyps identified by the endoscopist are documented for size, location and morphology. All diminutive polyps are characterized by a three sequential steps process: I) endoscopist prediction: the endoscopist evaluates the polyp by using BLI through the BASIC classification; the confidence level (high vs. low) in histology prediction is recorded; II) AI prediction: the AI system is switched on and the output of the automatic evaluation is recorded; this outcome is rated as stable or unstable, depending of the consistency over time of the outcome; III) combined prediction: a final classification is provided by endoscopist in light of the results of the first and of the second step; the confidence level is recorded. All polyps are resected and retrieved in separate jars and sent for pathology assessment. Only polyps characterized with high confidence will be included in the per-polyp analysis; the high-confidence characterization rate will be also calculated; the rate of polyps characterized with a CAD stable outcome will be calculated. Operative characteristics (sensitivity, specificity, positive and negative predictive value and accuracy) in distinguishing adenomatous from non-adenomatous polyps, evaluated with high confidence, will be calculated for each diminutive polyp and for each diminutive rectosigmoid polyp, having histopathology report as reference standard. The post-polypectomy surveillance intervals will be calculated on the basis of polyp histology (reference standard) in all patients according to both USMSTF and ESGE guidelines.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients with at least one diminutive rectosigmoid polyp | – | Diagnostic Test: Polyp carachterization by combing endoscopist evaluation and Ai outputConsecutive adult (>18 years) outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected. Exclusion criteria: * patients with CRC history or hereditary polyposis syndromes or hereditary non-polyposis colorectal cancer * patients with inadequate bowel preparation * patients in which caecal intubation was not achieved or scheduled for partial examinations * polyps could not be resected due to ongoing anticoagulation preventing resection and pathologic assessment * patients undergoing urgent colonoscopy. |
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected
Key inclusion criteria (1 listed)
- Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected.
Key exclusion criteria (5 listed)
- patients with CRC history or hereditary polyposis syndromes or hereditary non-polyposis colorectal cancer
- patients with inadequate bowel preparation
- patients scheduled for partial examinations
- polyps could not be resected due to ongoing anticoagulation preventing resection and pathologic assessment
- patients undergoing urgent colonoscopy
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 |
|---|---|---|
| Polyp carachterization by combing endoscopist evaluation and Ai outputA polyp characterization (adenoma vs. non adenoma) is provided by endoscopist in light of the results of this own evaluation and of the Ai system output. The confidence level (high vs. low) in polyp characterization is recorded. The combined evaluation is compared with histopathology results. | Diagnostic test | Patients with at least one diminutive rectosigmoid polyp |
Primary outcome
Agreement of combined prediction with PIVI I statement
Time frame: 6 months
To prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps (i.e. PIVI I threshold) having histopathology as reference standard.
3 secondary outcomes
Endoscopist prediction
Time frame: 6 months
Ai prediction
Time frame: 6 months
Agreement of combined prediction with PIVI II statement
Time frame: 6 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 10 Jun 2021.
- Derived from this study: PubMed 35562098Rondonotti E, Hassan C, Tamanini G, Antonelli G, Andrisani G, Leonetti G, Paggi S, Amato A, Scardino G, Di Paolo D, Mandelli G, Lenoci N, Terreni N, Andrealli A, Maselli R, Spadaccini M, Galtieri PA, Correale L, Repici A, Di Matteo FM, Ambrosiani L, Filippi E, Sharma P, Radaelli F. Artificial intelligence-assisted optical diagnosis for the resect-and-discard strategy in clinical practice: the Artificial intelligence BLI Characterization (ABC) study. Endoscopy. 2023 Jan;55(1):14-22. doi: 10.1055/a-1852-0330. Epub 2022 May 13.
- 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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Colonic Adenomatous Polyp, run by Valduce Hospital at 1 site in Italy.
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 5 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 10 Jun 2021. 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 Italy. 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?
Agreement of combined prediction with PIVI I statement (time frame: 6 months). 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 NCT04607083, 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 10 Jun 2021.