Computer-aided diagnosis for colorectal polyp in comparison with endoscopists: A systematic review and meta-analysis
Notice bibliographique
Résumé
Aims Computer-aided diagnosis (CADx) is anticipated to enhance the prediction of colorectal polyp histology. This study aims to clarify the diagnostic accuracy of CADx in surface pattern diagnosis of colorectal polyps compared with experienced and inexperienced endoscopists. Methods Registered in the International Prospective Register of Systematic Review (PROSPERO) (ID: CRD42019136918) and published this protocol in Open Science Framework (OSF) (https://osf.io/2bajy/), this systematic review included studies assessing the diagnostic accuracy of CADx versus colonoscopists. We conducted a comprehensive bibliographic search of the following databases: MEDLINE (Ovid), Embase (Ovid), and the Cochrane Central Register of Controlled Trials (CENTRAL) (Ovid). A bivariate random effects model was employed. The primary outcome was the comparison of sensitivity and specificity between CADx and experienced endoscopists; the secondary outcome was the comparison between CADx and inexperienced endoscopists. To mitigate the influence of variability and explore potential sources of heterogeneity, we performed a subgroup analysis. This was categorized into real-time imaging, which represents the direct, in situ analysis during colonoscopy, and still imaging, which involves post-procedure analysis of static images. To assess whether results were robust enough for the conclusions drawn in the review, we performed the sensitivity analysis including only studies with clear definitions of experienced endoscopists. Results Twenty-one studies involving 5,477 polyps were included. The prevalence of adenoma ranged from 13% to 83%. The pooled sensitivities of CADx and experienced endoscopists were 0.874 (95% confidence interval [CI] 0.822-0.912) and 0.876 (95% CI 0.826-0.914), respectively (p=0.932). The pooled specificities were 0.850 (95% CI 0.784-0.898) for CADx and 0.873 (95% CI 0.815-0.915) for experienced endoscopists (p=0.534). In nine studies comparing CADx with inexperienced endoscopists, the pooled sensitivities were 0.879 (95% CI 0.818-0.921) for CADx and 0.849 (95% CI 0.778-0.900) for inexperienced endoscopists (p=0.460). The pooled specificities were 0.838 (95% CI 0.775-0.883) for CADx and 0.774 (95% CI 0.701-0.833) for inexperienced endoscopists (p=0.161). A subgroup analysis was performed to investigate the impact of sequential endoscopic imaging of CADx data. We compared real-time imaging (n=12) with still imaging (n=9), and the sensitivity and specificity between the two groups showed no significant differences. We performed sensitivity analysis, excluding one study without clear definitions of experienced endoscopists. Even with this exclusion, there were no significant differences between CADx and experienced endoscopist groups, consistent with the primary results. Conclusions CADx does not demonstrate superior diagnostic accuracy in surface pattern diagnosis of colorectal polyps compared to endoscopists, regardless of their experience level. Publication History Article published online: 27 March 2025 © 2025. European Society of Gastrointestinal Endoscopy. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,015 | 0,028 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».