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Not yet recruiting NCT07738484

AI-Assisted Optical Diagnosis (CADx) for Diminutive Colorectal Polyps

Observational Colorectal Polyps Colorectal Adenoma Diminutive Colorectal Polyp

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: GI Genius CADx module (Medtronic).
Who it may be relevant to
Registry conditions: Colorectal Polyps, Colorectal Adenoma, Diminutive Colorectal Polyp. Basic parameters: 45 years — 80 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Center list to be confirmed — check the primary protocol.
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Prospective Multicenter Validation of an Artificial Intelligence-Assisted Optical Diagnosis Strategy (CADx) for the Real-Time Characterization of Diminutive Colorectal Polyps: A STARD-Compliant Diagnostic Accuracy Study

Overview

This study evaluates whether an artificial intelligence system (GI Genius, Medtronic), already approved by Health Canada, can help doctors accurately identify, in real time during colonoscopy, which small colorectal polyps (5 mm or less) need to be monitored (adenomas) versus those that do not (for example, hyperplastic polyps). For each small polyp found, the endoscopist will first record a diagnosis without the help of the artificial intelligence system, then activate the system and record a second diagnosis after seeing its assessment. Both diagnoses will be compared to the final result from standard pathology testing, which remains the reference standard. This is an observational diagnostic accuracy study: it does not change any clinical care. All polyps continue to be removed and sent for pathology analysis as usual, whether or not the artificial intelligence system agrees with the doctor. The study will take place during colonoscopies already scheduled for standard clinical reasons (screening, surveillance, or diagnostic work-up), with no additional visits, blood draws, imaging, or sedation. Approximately 840 participants will be enrolled across three Canadian centres (Santé Québec - CHUM, McGill University Health Centre, and St. Paul's Hospital, Vancouver). The goal is to determine whether this AI-assisted approach helps doctors reach the internationally recognized performance thresholds (at least 80% sensitivity and 80% specificity) needed to support clinical adoption of real-time optical diagnosis, which could eventually reduce unnecessary pathology testing.

Detailed description

Colonoscopy with polypectomy is the cornerstone of colorectal cancer (CRC) screening and prevention. The majority of polyps detected during colonoscopy are diminutive (≤5 mm) and carry a very low risk of harbouring advanced pathology. In Canada, over 1.9 million colonoscopies are performed annually, and sending all diminutive polyps for histopathological examination (at a cost of approximately $150-$300 CAD per specimen) generates a substantial economic burden with limited benefit for cancer prevention.

Two international guideline frameworks define the performance thresholds required for clinical adoption of optical diagnosis strategies for diminutive colorectal polyps. The ASGE PIVI initiative (2011) established (1) ≥90% negative predictive value (NPV) for adenomatous histology among diminutive rectosigmoid polyps diagnosed with high confidence ("diagnose-and-leave" threshold), and (2) ≥90% agreement between optical-diagnosis-based and pathology-based post-polypectomy surveillance intervals ("resect-and-discard" threshold). The more recent ESGE SODA position statement (2022) adopted sensitivity and specificity as the foundational, prevalence-independent performance measures for high-confidence real-time characterization of colorectal neoplasia, applicable across all colonic locations: sensitivity ≥90% and specificity ≥80% for the rectosigmoid subset, and sensitivity ≥80% and specificity ≥80% across all diminutive colorectal polyps regardless of location.

The investigators' research group has previously conducted several single-centre studies evaluating early-generation, Health Canada-approved computer-aided diagnosis (CADx) systems in routine clinical practice, generating one of the largest real-world CADx implementation datasets in the literature (868 patients, 1,660 diminutive polyps). These studies consistently demonstrated suboptimal overall diagnostic accuracy (62.7%-66.4%), attributable to restricted training datasets and limited polyp-classification capabilities in early-generation devices. GI Genius (Medtronic), the newer-generation, Health Canada-approved CADx module evaluated in this study, was trained on a larger and more diverse dataset of annotated endoscopic images and videos. Whether this translates into measurable gains in diagnostic performance sufficient to meet international competence thresholds has not been established in an independent, prospective, multicentre study, and is the question this study addresses.

This is a prospective, three-centre diagnostic accuracy study conducted in accordance with the Standards for Reporting Diagnostic Accuracy Studies (STARD 2015). It is a single-arm study validating a CADx-assisted optical-diagnosis strategy - rather than autonomous or standalone CADx performance - in which the endoscopist's final CADx-assisted optical diagnosis constitutes the primary index test. For each diminutive polyp (≤5 mm) identified during an already-scheduled elective colonoscopy, the following sequential steps are performed: (1) the endoscopist records a CADx-unassisted optical diagnosis (adenoma, hyperplastic polyp, or other) and confidence level (high or low), which is electronically locked before any device output is viewed; (2) the CADx module is activated and displays its own characterization of the polyp; (3) the endoscopist records a final CADx-assisted optical diagnosis and confidence level, remaining free to agree or disagree with the device; (4) a research assistant documents polyp size, morphology (Paris classification), and colonic location; and (5) the polyp is resected per standard technique and sent for histopathological examination, which serves as the reference standard. This sequential-locking design - recording and locking the unassisted diagnosis before CADx activation - is the study's key strategy for minimizing contamination bias between the two diagnostic strategies, and allows each polyp to generate two paired diagnostic data points (CADx-unassisted and CADx-assisted) compared against a single histopathological reference standard.

The study will enroll consecutive patients aged 45-80 years undergoing elective colonoscopy (screening, surveillance, or diagnostic indication) at three Canadian academic centres: Santé Québec - CHUM (Montreal), the McGill University Health Centre (MUHC/CUSM, Montreal), and St. Paul's Hospital (Vancouver), who provide written informed consent before the colonoscopy and before sedation.

Inclusion criteria: signed informed consent obtained before the colonoscopy and before sedation; age 45-80 years; indication for elective colonoscopy (screening, surveillance, or diagnostic); and at least one diminutive polyp (≤5 mm) detected during the procedure, which is required for inclusion in the analytic cohort (consented patients in whom no eligible polyp is detected are documented as screen failures and do not contribute to the primary analysis).

Exclusion criteria: known inflammatory bowel disease; active colitis; coagulopathy or thrombocytopenia (INR ≥1.5 or platelets \<50×10⁹/L); familial polyposis syndrome; American Society of Anesthesiologists (ASA) classification \>III; emergency colonoscopy; and inadequate bowel preparation (Boston Bowel Preparation Scale \<6).

All staff gastroenterologists and gastroenterology trainees performing elective colonoscopies at participating centres are eligible to participate as endoscopists, with no additional optical-diagnosis training provided, reflecting real-world implementation conditions.

The primary objective is to determine the sensitivity and specificity of CADx-assisted optical diagnosis for adenomatous histology among all diminutive colorectal polyps, benchmarked against the ESGE SODA competence thresholds (sensitivity ≥80%, specificity ≥80%), using histopathology as the reference standard. Secondary objectives include: the NPV of CADx-assisted diagnosis among high-confidence diminutive rectosigmoid polyps (ASGE PIVI threshold ≥90%); agreement between CADx-assisted and pathology-based surveillance interval recommendations (ASGE PIVI threshold ≥90%); sensitivity and specificity for the rectosigmoid subset (ESGE SODA threshold: sensitivity ≥90%, specificity ≥80%); a paired comparison of CADx-assisted versus CADx-unassisted diagnostic performance; diagnostic confidence calibration; and the proportion of CADx-assisted diagnoses made with high confidence. Prespecified exploratory subgroup analyses will evaluate diagnostic performance by polyp size (≤3 mm vs. 4-5 mm), morphology, colonic location, endoscopist experience level, patient biological sex, and study centre. A tertiary/exploratory objective is an integrated health economic evaluation - combining a decision tree and a state-transition Markov model, from both health-system and societal perspectives - assessing the cost-effectiveness of a possible future CADx-assisted "resect-and-discard"/"diagnose-and-leave" strategy compared with universal histopathological examination, with results reported per the CHEERS 2022 checklist.

A minimum of 826 patients is required to evaluate both co-primary outcomes (sensitivity and specificity) with an overall power of 80%, accounting for intra-patient clustering of polyps (design effect 1.3, based on an average of 1.91 diminutive polyps per patient and an intraclass correlation of 0.3). A recruitment target of 840 patients (approximately 1,605 diminutive polyps), enrolled evenly across the three centres (280 per centre) over an expected 24-month recruitment period, has been set to exceed this minimum. Sensitivity and specificity will be estimated using generalized linear mixed models with a logit link and a random effect for patient, to account for clustering of polyps within patients; each one-sided hypothesis test (H₀: sensitivity or specificity ≤80%) will be conducted at α=0.025, with study success requiring rejection of both null hypotheses. Prespecified sensitivity analyses include a per-protocol analysis, a high-confidence-only analysis aligned with formal ESGE SODA competence assessment, a reclassification of serrated lesions as neoplastic, models incorporating a random effect for endoscopist, and a temporal analysis for learning-curve or fatigue effects. No interim analyses are planned; all analyses will be conducted after complete enrolment.

There is no increased risk to participants beyond the standard risks of colonoscopy, since all polyps are resected according to usual clinical practice regardless of study participation, and no additional procedures (blood sampling, imaging, additional sedation, or follow-up visits) are performed for research purposes. This is an investigator-initiated study (Sponsor-Investigator: Dr. Daniel von Renteln, CHUM/CRCHUM); Medtronic Canada provides the GI Genius CADx equipment on loan for the study period, together with related installation and technical support only, and has no role in study design, recruitment, data collection, endpoint adjudication, statistical analysis, interpretation, or publication decisions.

Interventions

  • Device GI Genius CADx module (Medtronic)
    Computer-aided diagnosis (CADx) device recently approved by Health Canada, used to provide real-time optical characterization of diminutive colorectal polyps (≤5 mm) during colonoscopy. For each diminutive polyp detected, the endoscopist first records a CADx-unassisted optical diagnosis (electronically locked before device activation), then activates the GI Genius CADx module, which displays a device-provided characterization. The endoscopist then records a final CADx-assisted optical diagnosis,

Primary outcome measures

  • Sensitivity of CADx-assisted optical diagnosis for adenomatous histology [Time frame: Within 14 to 45 days after polypectomy (colorectal polyp resection during the index colonoscopy), once histopathology results are available]
  • Specificity of CADx-assisted optical diagnosis for adenomatous histology [Time frame: Within 14 to 45 days after polypectomy (colorectal polyp resection during the index colonoscopy), once histopathology results are available]
Secondary outcome measures (6)
  • NPV of CADx-assisted optical diagnosis for adenomatous histology (rectosigmoid, high confidence) [Time frame: Within 14 to 45 days after polypectomy (colorectal polyp resection during the index colonoscopy), once histopathology results are available]
  • Surveillance interval agreement [Time frame: Outcome assessed throughout the 24-month recruitment period, with total study duration of 36 months]
  • Sensitivity and specificity, rectosigmoid subset [Time frame: Outcome assessed throughout the 24-month recruitment period, with total study duration of 36 months]
  • CADx-assisted vs. CADx-unassisted diagnostic performance [Time frame: Outcome assessed throughout the 24-month recruitment period, with total study duration of 36 months]
  • High-confidence prediction rate [Time frame: Outcome assessed throughout the 24-month recruitment period, with total study duration of 36 months]
  • Confidence calibration [Time frame: Outcome assessed throughout the 24-month recruitment period, with total study duration of 36 months]

Eligibility criteria

Inclusion criteria

  • Signed informed consent, obtained before the colonoscopy and before sedation
  • Age 45-80 years
  • Indication for elective colonoscopy (screening, surveillance, or diagnostic)
  • At least one diminutive polyp (≤5 mm) detected during the procedure (required for inclusion in the analytic cohort; consented patients without an eligible polyp are documented as screen failures)

Exclusion criteria

  • Known inflammatory bowel disease
  • Active colitis
  • Coagulopathy or thrombocytopenia (INR ≥1.5 or platelets <50×10⁹/L)
  • Familial polyposis syndrome
  • American Society of Anesthesiologists classification >III
  • Emergency colonoscopy
  • Inadequate bowel preparation (Boston Bowel Preparation Scale <6)

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

Center list to be confirmed — check the primary protocol.

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. PMID 32598963
  • Biffi C, Salvagnini P, Dinh NN, Hassan C, Sharma P; GI Genius CADx Study Group; Cherubini A. A novel AI device for real-time optical characterization of colorectal polyps. NPJ Digit Med. 2022 Jun 30;5(1):84. doi: 10.1038/s41746-022-00633-6. PMID 35773468
  • Byrne MF, Chapados N, Soudan F, Oertel C, Linares Perez M, Kelly R, Iqbal N, Chandelier F, Rex DK. Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model. Gut. 2019 Jan;68(1):94-100. doi: 10.1136/gutjnl-2017-314547. Epub 2017 Oct 24. PMID 29066576
  • Mori Y, Kudo SE, Misawa M, Saito Y, Ikematsu H, Hotta K, Ohtsuka K, Urushibara F, Kataoka S, Ogawa Y, Maeda Y, Takeda K, Nakamura H, Ichimasa K, Kudo T, Hayashi T, Wakamura K, Ishida F, Inoue H, Itoh H, Oda M, Mori K. Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy: A Prospective Study. Ann Intern Med. 2018 Sep 18;169(6):357-366. doi: 10.7326/M18- PMID 30105375
  • Husereau D, Drummond M, Augustovski F, de Bekker-Grob E, Briggs AH, Carswell C, Caulley L, Chaiyakunapruk N, Greenberg D, Loder E, Mauskopf J, Mullins CD, Petrou S, Pwu RF, Staniszewska S; CHEERS 2022 ISPOR Good Research Practices Task Force. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. BMJ. 20 PMID 35017145
  • Hassan C, Pickhardt PJ, Rex DK. A resect and discard strategy would improve cost-effectiveness of colorectal cancer screening. Clin Gastroenterol Hepatol. 2010 Oct;8(10):865-9, 869.e1-3. doi: 10.1016/j.cgh.2010.05.018. Epub 2010 Jun 1. PMID 20621680
  • Djinbachian R, Haumesser C, Taghiakbari M, Pohl H, Barkun A, Sidani S, Liu Chen Kiow J, Panzini B, Bouchard S, Deslandres E, Alj A, von Renteln D. Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial. Gastroenterology. 2024 Jul;167(2):392-399.e2. doi: 10.1053/j.gastro.2024.01.044. Epub 2024 Feb 7. PMID 38331204
  • Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, Lijmer JG, Moher D, Rennie D, de Vet HC, Kressel HY, Rifai N, Golub RM, Altman DG, Hooft L, Korevaar DA, Cohen JF; STARD Group. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ. 2015 Oct 28;351:h5527. doi: 10.1136/bmj.h5527. PMID 26511519

Identifiers

NCT: NCT07738484 · MP-02-2027-13785

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗