- ICH GCP
- Registre américain des essais cliniques
- Essai clinique NCT06059378
Mise en œuvre réelle d'un diagnostic optique basé sur l'IA (AI-OD)
Mise en œuvre réelle d'une stratégie de diagnostic optique basée sur l'intelligence artificielle pour les polypes colorectaux diminutifs
This is a prospective study that is the first to implement resect and discard and diagnose and leave strategies in real-time practice using stringent documentation and adjudication by 2 expert endoscopists as the gold standard.
The primary aim of this study is to show the accuracy of intracolonoscopy AI-assisted optical diagnosis (CADx; autonomous or with human input) when the AI-assisted optical diagnosis made by the expert endoscopists is used as the reference standard. The specific aims are:
- To evaluate the accuracy of intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) by comparing it to the obtained optical histology diagnoses provided by two independent expert endoscopists as the reference standard.
- To evaluate the agreement between the intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) and the AI-assisted optical diagnosis performed by two independent expert endoscopists.
- To determine whether AI-assisted optical polyp diagnosis for diminutive (1-5 mm) polyps can be implemented in routine clinical practice by demonstrating that at least 70% of the approached patients are interested in undergoing AI-assisted optical diagnosis (autonomous or with human input).
- To evaluate the cost savings resulting from replacing pathology with AI-assisted optical diagnosis.
Aperçu de l'étude
Statut
Les conditions
Intervention / Traitement
Description détaillée
All patients who meet the inclusion criteria can be enrolled. Eligible patients will be informed about the study through a consent form that includes information on optical diagnosis (resect and discard, diagnose and leave) and AI/CADx systems. We will ask the patients' willingness to undergo AI-assisted optical diagnosis with endoscopists' input (the first 102 patients) and automomous AI-assisted optical diagnosis (from patient 103 to 204). Subsequently, patients will be asked if they are willing to participate in the study, using AI-assisted optical diagnosis and the "resect and discard" and "diagnose and leave" strategy. If a patient declines to undergo optical diagnosis, they will be asked about the reason for their refusal to participate in the study. The options for their response include:
- Concerns regarding undergoing an optical diagnosis.
- Reluctance to participate in research projects in general.
- Other reasons.
- Preference not to answer the question.
Patients who agree to participate in the study will undergo standard colonoscopy procedures with AI-assisted optical diagnosis for all diminutive colorectal polyps identified. High-definition colonoscopes with a joint computer-assisted classification (CADx) support (CAD-EYE software EW10-EC02) will be used.
For the first 102 patients (i.e., the CAD-assisted optical diagnosis with endoscopist's input), the endoscopists will use the CAD-EYE blue light imaging (BLI) mode to enhance the visualization of polyp features. During the optical diagnosis using CADx, the most probable diagnosis (neoplastic or hyperplastic) will be displayed on the endoscopy screen. If the serrated pathology subtype is determined as the most probable histology, the endoscopists will make the final decision. They will also indicate whether their optical diagnosis was made with low or high confidence.
For the second group of 102 patients (i.e., autonomous CADx-assisted optical diagnosis), endoscopists will use CADx and BLI mode to perform optical diagnosis. Based on the CADx diagnosis, all 1-5 mm polyps diagnosed as hyperplastic or neoplastic will be resected and discarded, while those located in the rectosigmoid and diagnosed as hyperplastic will be left in the colon. When high-risk histology features are observed using BLI, in any patient, the endoscopists will inform the research assistant to document them, and the polyp will be sent for pathology examination in accordance with the ASGE PIVI guidelines recommendations. All polyps >5mm will be send for pathology evaluation. Polyp size will be measured using virtual scale technology integrated in the computer-assisted system (CAD) to ensure an accurate polyp sizing.18 A research assistant will document the characteristics of the detected polyps (i.e., location, size, morphology, AI-assisted intracolonoscopy and endoscopists optical diagnoses). All identified colorectal polyps will be removed following standard polypectomy practices. The entire colonoscopy procedures will be video recorded for quality assurance purposes. All diminutive polyps will be resected and discarded as part of the resect and discard strategy. Additionally, diminutive polyps located in the rectosigmoid colon will be detected and left in situ (diagnose and leave strategy) if no high-risk features are present.
Type d'étude
Inscription (Estimé)
Phase
- N'est pas applicable
Contacts et emplacements
Lieux d'étude
-
-
Quebec
-
Montreal, Quebec, Canada
- Centre Hospitalier de l'Université de Montréal
-
-
Critères de participation
Critère d'éligibilité
Âges éligibles pour étudier
Accepte les volontaires sains
Sexes éligibles pour l'étude
La description
Inclusion Criteria:
- Age 45-80 years
- Undergoing an outpatient colonoscopy at the Centre Hospitalier de l'Université de Montréal (CHUM)
- Signed informed consent form
Exclusion Criteria:
- Inflammatory Bowel Disease;
- Active colitis;
- Hereditary CRC syndrome;
- Coagulopathy;
- American Society of Anesthesiologists (ASA) status >3
Plan d'étude
Comment l'étude est-elle conçue ?
Détails de conception
- Objectif principal: Diagnostique
- Répartition: Non randomisé
- Modèle interventionnel: Affectation parallèle
- Masquage: Aucun (étiquette ouverte)
Armes et Interventions
Groupe de participants / Bras |
Intervention / Traitement |
|---|---|
|
Autre: AI-assisted classification with endoscopist's input
AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with input from the endoscopist in the case of serrated polyps, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps. |
CADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon.
Autres noms:
|
|
Autre: Autonomous AI-assisted classification
AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with no input from the endoscopist, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps. |
CADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon.
Autres noms:
|
Que mesure l'étude ?
Principaux critères de jugement
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
|
Accuracy of the intracolonoscopy AI-assisted optical diagnosis
Délai: 120 days
|
Using the optical diagnosis obtained from 2 experts as the reference, the accuracy of the intracolonoscopy AI-assisted optical diagnosis (OD, with endoscopist input or autonomous) is measured as the number of correct ODs out of all ODs (%). |
120 days
|
Mesures de résultats secondaires
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
|
Proportion of patients who accept study participation
Délai: 120 days
|
Number of patients who accept to participate out of all patients approached |
120 days
|
|
Proportion of the patients unwilling to participate due to concerns regarding undergoing an optical diagnosis
Délai: 120 days
|
The proportion of the patients unwilling to participate in the study due to the concerns of resect and discard or diagnose and leave strategies (with endoscopist input or autonomous) and preference upon histopathological evaluation of all detected polyps |
120 days
|
|
Agreement between the intracolonoscopy AI-assisted optical diagnosis and the AI-assisted optical diagnosis by experts
Délai: 120 days
|
The agreement between AI-assisted OD (with and without endoscopist's input) and the experts' OD is measured as the number of cases where both ODs are the same out of all cases (%). |
120 days
|
|
Diagnostic characteristics of AI-assisted optical diagnosis using adjudication by two expert endoscopists as the reference standard
Délai: 120 days
|
To calculate the accuracy, sensitivity, specificity, positive predictive value, negative predictive value of (CADx) assisted optical diagnosis (resect and discard) strategy using adjudication by two expert endoscopists as the reference standard. |
120 days
|
|
Proportion of polyps with a low-confidence diagnosis
Délai: 120 days
|
Proportion of polyps with a low-confidence diagnosis intracolonoscopy and later by the expert independent reviewers |
120 days
|
|
Assessing cost savings through AI-assisted optical diagnosis
Délai: 120 days
|
The reduction in costs of the supplies and the pathology assessments according to the expenses reported by the CHUM gastroenterology and pathology departments including the expenses related to the supplies (e.g., snares, containers), immediate and delayed complications, specimen processing and equipment and physician fees. |
120 days
|
Collaborateurs et enquêteurs
Les enquêteurs
- Chercheur principal: Daniel von Renteln, MD, Centre hospitalier de l'Université de Montréal (CHUM)
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude (Réel)
Achèvement primaire (Réel)
Achèvement de l'étude (Estimé)
Dates d'inscription aux études
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première publication (Réel)
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Plus d'information
Termes liés à cette étude
Autres numéros d'identification d'étude
- 2024-11557/23.095
Plan pour les données individuelles des participants (IPD)
Prévoyez-vous de partager les données individuelles des participants (DPI) ?
Informations sur les médicaments et les dispositifs, documents d'étude
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