Colorectal NeoplasmsNCT05391477
Artificial Intelligence for Diminutive Polyp Characterization
A study testing GI-Genius artificial intelligence in people with Colorectal Neoplasms, run by Hospital Universitario La Fe at 1 site in Spain.
Trial summary
Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Colorectal Neoplasms
- What is being tested?
- GI-Genius artificial intelligence
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 643 participants
- Where
- 1 siteSpain
- Study dates
- 27 Feb 2023to Dec 2024
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- Patients attending a colonoscopy within a population-based CRC screening program (FIT- or colonoscopy-based) or because of post-polypectomy surveillance,
- Written informed consent before the colonoscopy,
Who cannot join
- None, patient included
- Previous history of inflammatory bowel disease.
- Previous history of CRC
- Previous CR resection
- Polyposis or hereditary CRC syndrome
- Coagulopathy/Anticoagulants
- Unwillingness to participate
Trial locations and contacts
1 site in 1 country.
Spain1 site, 1 recruiting
- Recruiting
Hospital Universitari i Politècnic La Fe
Valencia, 46026
Marco Bustamante Balén, M.D.;Ph.D., 961244000 ext. 440225, bustamante_mar@gva.es
Sylwia Jaworska Fernandez, 9621244262, sylwia_jaworska@iislafe.es
About this study
Official title: Efficacy and Cost-effectiveness of an Artificial Intelligence System (GI-Genius) on the Characterization of Diminutive Colorectal Polyps Within a Colorectal Cancer Screening Program: a Multicenter Randomized Controlled Trial (ODDITY Trial)
Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.
Read the detailed description
The resect-and-discard (R\&D) and diagnose-and-leave (D\&L) strategies have been proposed as a means to reduce costs in the evaluation of colorectal polyps avoiding a substantial number of pathology evaluations. A pre-requisite for this paradigm shift is an accurate optical diagnosis (HOD). However, performance results for HOD have been highly variable among endoscopists representing a barrier for the adoption of the R\&D and the D\&L strategies.
Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.
Methods and analysis: The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group or the HOD (control) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.
- Conditions
- Colorectal Neoplasms
- Being tested
- GI-Genius artificial intelligence
- Keywords
- Artificial Intelligence, Colorectal cancer, Polyp, Characterization
- Medical subject headings
- Colorectal Neoplasms, Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
GI-Genius artificial intelligenceDevice
The software allows for the real-time characterization of framed polyps during a colonoscopy classifying them on adenoma or non-adenoma.
| Study group | Role | What they receive |
|---|---|---|
| Human optical diagnosis (HOD) | No intervention | The examinator will provide a HOD for every lesion (regardless of their size) found during the examination (adenoma vs non-adenoma) following one of the available validated classifications (NICE, JNET, BASIC). He/she will also give a level of confidence in his/her diagnosis (high/low confidence). However, only diminutive lesions will be considered when analyzing the main outcome. The time to get a HOD will be recorded. An in situ surveillance interval will be provided if possible. |
| Artificial intelligence optical diagnosis (AIOD): | Experimental | GI-Genius will provide an artificial intelligence diagnosis (AIOD) for every lesion detected (adenoma vs non-adenoma). Only diminutive lesions will be considered for the analysis of the main outcome. However, data on larger lesions will be recorded to describe GI-Genius´ performance in detail (secondary outcome). The time to get an AIOD will be recorded. An in situ surveillance interval will be provided if possible Receives: Device: GI-Genius artificial intelligence |
What is being measured
The primary outcome is the main question the study is designed to answer.
Comparison of the AIOD and HOD accuracy of the post-polypectomy surveillance interval assignment with respect to the surveillance interval assigned by pathology
A surveillance interval will be assigned using optical diagnosis of ≤ 5 mm polyps (Arm 1: AIOD; Arm 2: HOD of polyps diagnosed with high confidence) plus histopathology of > 5 mm polyps and polyps ≤ 5 mm diagnosed with low confidence. For each patient included, the optical-diagnosis surveillance assignment will be matched with the histology-directed one, and a concordance rate will be calculated. The post-polypectomy surveillance interval will be calculated using the ESGE 2020 and the USMSTF 2020 guidelines. Per-patient analysis.
Measured: At the end of the study (2 years)
Comparison of the AIOD and HOD negative predictive value (NPV) for adenoma in rectosigmoid polyps ≤ 5 mm with respect to histology
The optical diagnosis of ≤ 5 mm rectosigmoid polyps (Arm 1: AIOD; Arm 2: HOD, only high-confidence diagnosis) reliability on ruling out the presence of an adenoma will be calculated using histopathology as the gold standard. Per-lesion analysis. NPV = number of confirmed hyperplastic polyps/number of hyperplastic optical diagnosis
Measured: At the end of the study (2 years)
Secondary outcomes (4)
Comparison of the AIOD and HOD diagnostic accuracy parameters of polyps ≤ 5 mm (Arm 1: AIOD; Arm 2: HOD) with respect to histology
Operative characteristics (sensitivity, specificity, positive and negative predictive value and positive likely hood ratio) using histopathology as the gold standard. Per-lesion analysis
Measured: Interim analysis (when half of the sample size had been included). At the end of the study (2 years)
Cost-effectiveness of AIOD
The economic burden of applying the AIOD and HOD to assign the post-polypectomy surveillance intervals compared to the histology-driven strategy. A direct cost evaluation will be performed including medical and non-medical costs. Per-patient analysis.
Measured: At the end of the study (2 years)
Comparison of the proportion of adverse events in colonoscopies with and without the AIOD device.
The occurrence and severity of adverse events in colonoscopies with and without the AIOD device will be monitored during the 30-days period after the procedure. Adverse events are defined as: abdominal pain or discomfort, post-polypectomy bleeding, perforation, post-polypectomy syndrome and infection. Per-patient analysis
Measured: 30 days after the colonoscopy (Day 30)
Proportion of patients accepting to have their polyps diagnosed by the AI system or human optical diagnosis (designed questionnaire)
The proportion of patients willing to have their polyps diagnosed by an AI system or HOD will be assessed using a structured questionnaire. Per-patient analysis.
Measured: Day of colonoscopy (Day 1)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 May 2022
- Study start27 Feb 2023
- Primary completionMay 2024 (estimated)
- Study completionDec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal NeoplasmsStudies 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
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group (group 1) or the HOD (control, group 2) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 643 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Hospital Universitario La Fe
- Sponsor type
- University, hospital or other
- Collaborators
- European Society of Gastrointestinal Endoscopy, Medtronic
- Responsible party
- Principal investigator, Marco Bustamante-Balén, Hospital Universitario La Fe
- Investigators
- Marco Bustamante Balén, M.D., Ph.D., Principal investigator, Hospital Universitario La Fe
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05391477
- Sponsor's protocol ID
- Oddity
- Status last verified
- May 2023
- First submitted
- 5 Apr 2022
- Last updated
- 31 May 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 31 May 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Efficacy and Cost-effectiveness of an Artificial Intelligence System (GI-Genius) on the Characterization of Diminutive Colorectal Polyps Within a Colorectal Cancer Screening Program: a Multicenter Randomized Controlled Trial (ODDITY Trial)
- ClinicalTrials.gov ID
- NCT05391477
- Acronym / sponsor ID
- Oddity
- Conditions
- Colorectal Neoplasms
- Keywords
- Artificial Intelligence, Colorectal cancer, Polyp, Characterization
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 643 participants (estimated)
- Lead sponsor
- Hospital Universitario La FeUniversity, hospital or other
- Collaborators
- European Society of Gastrointestinal Endoscopy, Medtronic
- Study start
- 27 Feb 2023 (actual)
- Primary completion
- May 2024 (estimated)
- Study completion
- Dec 2024 (estimated)
- First posted
- 26 May 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.
Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.
Detailed description
The resect-and-discard (R\&D) and diagnose-and-leave (D\&L) strategies have been proposed as a means to reduce costs in the evaluation of colorectal polyps avoiding a substantial number of pathology evaluations. A pre-requisite for this paradigm shift is an accurate optical diagnosis (HOD). However, performance results for HOD have been highly variable among endoscopists representing a barrier for the adoption of the R\&D and the D\&L strategies.
Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.
Methods and analysis: The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group or the HOD (control) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group (group 1) or the HOD (control, group 2) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.
| Arm | Type | Receives |
|---|---|---|
| Human optical diagnosis (HOD) | No intervention | –The examinator will provide a HOD for every lesion (regardless of their size) found during the examination (adenoma vs non-adenoma) following one of the available validated classifications (NICE, JNET, BASIC). He/she will also give a level of confidence in his/her diagnosis (high/low confidence). However, only diminutive lesions will be considered when analyzing the main outcome. The time to get a HOD will be recorded. An in situ surveillance interval will be provided if possible. |
| Artificial intelligence optical diagnosis (AIOD): | Experimental | Device: GI-Genius artificial intelligenceGI-Genius will provide an artificial intelligence diagnosis (AIOD) for every lesion detected (adenoma vs non-adenoma). Only diminutive lesions will be considered for the analysis of the main outcome. However, data on larger lesions will be recorded to describe GI-Genius´ performance in detail (secondary outcome). The time to get an AIOD will be recorded. An in situ surveillance interval will be provided if possible |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- Patients attending a colonoscopy within a population-based CRC screening program (FIT- or colonoscopy-based) or because of post-polypectomy surveillance,
- Written informed consent before the colonoscopy,
Key exclusion criteria (7 listed)
- None, patient included
- Previous history of inflammatory bowel disease.
- Previous history of CRC
- Previous CR resection
- Polyposis or hereditary CRC syndrome
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 |
|---|---|---|
| GI-Genius artificial intelligenceThe software allows for the real-time characterization of framed polyps during a colonoscopy classifying them on adenoma or non-adenoma. | Device | Artificial intelligence optical diagnosis (AIOD): |
Primary outcome
Comparison of the AIOD and HOD accuracy of the post-polypectomy surveillance interval assignment with respect to the surveillance interval assigned by pathology
Time frame: At the end of the study (2 years)
A surveillance interval will be assigned using optical diagnosis of ≤ 5 mm polyps (Arm 1: AIOD; Arm 2: HOD of polyps diagnosed with high confidence) plus histopathology of > 5 mm polyps and polyps ≤ 5 mm diagnosed with low confidence. For each patient included, the optical-diagnosis surveillance assignment will be matched with the histology-directed one, and a concordance rate will be calculated. The post-polypectomy surveillance interval will be calculated using the ESGE 2020 and the USMSTF 2020 guidelines. Per-patient analysis.
Comparison of the AIOD and HOD negative predictive value (NPV) for adenoma in rectosigmoid polyps ≤ 5 mm with respect to histology
Time frame: At the end of the study (2 years)
The optical diagnosis of ≤ 5 mm rectosigmoid polyps (Arm 1: AIOD; Arm 2: HOD, only high-confidence diagnosis) reliability on ruling out the presence of an adenoma will be calculated using histopathology as the gold standard. Per-lesion analysis. NPV = number of confirmed hyperplastic polyps/number of hyperplastic optical diagnosis
4 secondary outcomes
Comparison of the AIOD and HOD diagnostic accuracy parameters of polyps ≤ 5 mm (Arm 1: AIOD; Arm 2: HOD) with respect to histology
Time frame: Interim analysis (when half of the sample size had been included). At the end of the study (2 years)
Cost-effectiveness of AIOD
Time frame: At the end of the study (2 years)
Comparison of the proportion of adverse events in colonoscopies with and without the AIOD device.
Time frame: 30 days after the colonoscopy (Day 30)
Proportion of patients accepting to have their polyps diagnosed by the AI system or human optical diagnosis (designed questionnaire)
Time frame: Day of colonoscopy (Day 1)
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 May 2023.
- Individual participant dataSharing planned: Undecided
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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.
Marco Bustamante Balén, M.D., Ph.D. principal investigator
Hospital Universitario La Fe
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing GI-Genius artificial intelligence in people with Colorectal Neoplasms, run by Hospital Universitario La Fe at 1 site in Spain.
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 2 inclusion and 7 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 31 May 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 Spain. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Marco Bustamante Balén, M.D., Ph.D. (+34 961244000 ext. 440225, bustamante_mar@gva.es), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Comparison of the AIOD and HOD accuracy of the post-polypectomy surveillance interval assignment with respect to the surveillance interval assigned by pathology (time frame: At the end of the study (2 years)). 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?
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 31 May 2023.