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Real-time Diagnosis of Diminutive Colorectal Polyps Using AI (COMET-OPTICAL)

29. April 2022 aktualisiert von: Maastricht University Medical Center

Real Time Computer-aided Diagnosis (CADx) of Diminutive Colorectal Polyps Using Artificial Intelligence

Correct endoscopic prediction of the histopathology and differentiation between benign, pre-malignant, and malignant colorectal polyps (optical diagnosis) remains difficult. Artificial intelligence has great potential in image analysis in gastrointestinal endoscopy. Aim of this study is to investigate the real-time diagnostic performance of AI4CRP for the classification of diminutive colorectal polyps, and to compare it with the real-time diagnostic performance of commercially available CADx systems.

Studienübersicht

Status

Rekrutierung

Bedingungen

Intervention / Behandlung

Detaillierte Beschreibung

Correct endoscopic prediction of the histopathology and differentiation between benign, pre-malignant, and malignant colorectal polyps (optical diagnosis) remains difficult. Despite additional training, even experienced endoscopists continue to fail meeting international thresholds set for safe implementation of treatment strategies based on optical diagnosis.

Multiple machine learning techniques - computer-aided diagnosis (CADx) systems - have been developed for applications in medical imaging within colonoscopy and can improve endoscopic classification of colorectal polyps.

Aim of this study is to explore the feasibility of the workflow using AI4CRP (a CNN based CADx system) real-time in the endoscopy suite, and to investigate the real-time diagnostic performance of AI4CRP for the diagnosis of diminutive (<5mm) colorectal polyps. Secondary, the real-time performance of commercially available CADx systems will be investigated and compared with AI4CRP performance.

Studientyp

Beobachtungs

Einschreibung (Voraussichtlich)

105

Kontakte und Standorte

Dieser Abschnitt enthält die Kontaktdaten derjenigen, die die Studie durchführen, und Informationen darüber, wo diese Studie durchgeführt wird.

Studienkontakt

Studieren Sie die Kontaktsicherung

Studienorte

  • Niederlande
    • Limburg
    • Noord-Brabant
      • Eindhoven, Noord-Brabant, Niederlande, 5623 EJ
        • Abgeschlossen
        • Catharina Ziekenhuis Eindhoven

Teilnahmekriterien

Forscher suchen nach Personen, die einer bestimmten Beschreibung entsprechen, die als Auswahlkriterien bezeichnet werden. Einige Beispiele für diese Kriterien sind der allgemeine Gesundheitszustand einer Person oder frühere Behandlungen.

Zulassungskriterien

Studienberechtigtes Alter

18 Jahre und älter (Erwachsene, Älterer Erwachsener)

Akzeptiert gesunde Freiwillige

Nein

Studienberechtigte Geschlechter

Alle

Probenahmeverfahren

Nicht-Wahrscheinlichkeitsprobe

Studienpopulation

Patient receiving a colonoscopy because of regular care will be considered eligible for inclusion if at least one diminutive colorectal polyp is encountered during the colonoscopy. Patients receive an endoscopic procedure in the context of the Dutch national screening program, because of gastrointestinal symptoms, or because of follow-up of previously diagnosed bowel diseases.

Beschreibung

Inclusion Criteria:

  • Age >18 years;
  • Patients with at least one colorectal polyps encountered during colonoscopy;
  • Patients referred for a colonoscopy by the Dutch bowel cancer screening program, patients undergoing a colonoscopy for endoscopic surveillance, or patients undergoing a colonoscopy because of complaints;
  • Written informed consent.

Exclusion Criteria:

  • Patients with prior history of inflammatory bowel diseases (IBD) or polyposis syndromes;
  • Patients with inadequate bowel preparations after adequate washing, suctioning, and cleaning manoeuvres have been performed by the endoscopist;
  • Patients undergoing an emergency colonoscopy;
  • Written objection in the patient file for participation in scientific research.

Studienplan

Dieser Abschnitt enthält Einzelheiten zum Studienplan, einschließlich des Studiendesigns und der Messung der Studieninhalte.

Wie ist die Studie aufgebaut?

Designdetails

Kohorten und Interventionen

Gruppe / Kohorte
Intervention / Behandlung
Gastroenterology patients

Patient receiving a colonoscopy because of regular care will be considered eligible for inclusion if at least one diminutive colorectal polyp is encountered during the colonoscopy. Patients receive an endoscopic procedure in the context of the Dutch national screening program, because of gastrointestinal symptoms, or because of follow-up of previously diagnosed bowel diseases.

Colonoscopies will be executed using Fujifilm endoscopy systems (Fujifilm® Corporation, Tokyo, Japan), using Pentax endoscopy systems (Pentax Medical®, Hamburg, Germany), and using Olympus endoscopy systems (Olympus®, Tokyo, Japan).
Gerät: Computer-aided diagnosis (CADx) systems
  • AI4CRP (artificial intelligence for colorectal polyps), a CNN based computer-aided diagnosis system for diagnosis of colorectal polyps (COMET-OPTICAL research group);
  • CAD EYE, a computer-aided diagnosis system for diagnosis of colorectal polyps (Fujifilm® Corporation, Tokyo, Japan).
Andere Namen:
  • AI4CRP, artificial intelligence for colorectal polyps (COMET-OPTICAL research group)
  • CAD EYE (Fujifilm® Corporation, Tokyo, Japan)

Was misst die Studie?

Primäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Technical feasibility of real-time use of AI4CRP.
Zeitfenster: 6 months
The technical feasibility of real-time use of AI4CRP in the endoscopy suite regarding a proper reception of the video output from the local endoscopy processor towards AI4CRP (in high definition quality, without any delays in time).
6 months
User interface feasibility of real-time use of AI4CRP.
Zeitfenster: 6 months
The user interface feasibility of real-time use of AI4CRP in the endoscopy suite regarding a correct alignment of the user interface of AI4CRP with the video output from the local endoscopy system (resizing image pixels and anonymization).
6 months
The diagnostic accuracy of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Zeitfenster: 1 year
The real-time diagnostic accuracy of AI4CRP per image modality (HDWL, BLI, LCI, i-scan). Diagnostic accuracy defined as the percentage of correctly optically diagnosed colorectal polyps.
1 year
The sensitivity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Zeitfenster: 1 year
The real-time sensitivity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
1 year
The specificity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Zeitfenster: 1 year
The real-time specificity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
1 year
The negative predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Zeitfenster: 1 year
The real-time negative predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
1 year
The positive predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Zeitfenster: 1 year
The real-time positive predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
1 year
The Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
Zeitfenster: 1 year
The real-time Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
1 year

Sekundäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
The diagnostic accuracy of AI4CRP per polyp.
Zeitfenster: 1 year
The real-time diagnostic accuracy of AI4CRP per polyp (comprising the combination of different imaging modalities).
1 year
The sensitivity of AI4CRP per polyp.
Zeitfenster: 1 year
The real-time sensitivity of AI4CRP per polyp (comprising the combination of different imaging modalities).
1 year
The specificity of AI4CRP per polyp.
Zeitfenster: 1 year
The real-time specificity of AI4CRP per polyp (comprising the combination of different imaging modalities).
1 year
The negative predictive value of AI4CRP per polyp.
Zeitfenster: 1 year
The real-time negative predictive value of AI4CRP per polyp (comprising the combination of different imaging modalities).
1 year
The positive predictive value of AI4CRP per polyp.
Zeitfenster: 1 year
The real-time positive predictive value of AI4CRP per polyp (comprising the combination of different imaging modalities).
1 year
The Area Under ROC Curve (AUC) of AI4CRP per polyp.
Zeitfenster: 1 year
The real-time Area Under ROC Curve (AUC) of AI4CRP per polyp (comprising the combination of different imaging modalities).
1 year
The diagnostic accuracy of CAD EYE in BLI mode, per polyp.
Zeitfenster: 1 year
The real-time diagnostic accuracy of CAD EYE in BLI mode, per polyp.
1 year
The sensitivity of CAD EYE in BLI mode, per polyp.
Zeitfenster: 1 year
The real-time sensitivity of CAD EYE in BLI mode, per polyp.
1 year
The specificity of CAD EYE in BLI mode, per polyp.
Zeitfenster: 1 year
The real-time specificity of CAD EYE in BLI mode, per polyp.
1 year
The negative predictive value of CAD EYE in BLI mode, per polyp.
Zeitfenster: 1 year
The real-time negative predictive value of CAD EYE in BLI mode, per polyp.
1 year
The positive predictive value of CAD EYE in BLI mode, per polyp.
Zeitfenster: 1 year
The real-time positive predictive value of CAD EYE in BLI mode, per polyp.
1 year
The Area Under ROC Curve (AUC) of CAD EYE in BLI mode, per polyp.
Zeitfenster: 1 year
The real-time Area Under ROC Curve (AUC) of CAD EYE in BLI mode, per polyp.
1 year
The diagnostic accuracy of AI4CRP per patient.
Zeitfenster: 1 year
The real-time diagnostic accuracy of AI4CRP per patient (in case of multiple polyps per patient).
1 year
The diagnostic accuracy of CAD EYE per patient.
Zeitfenster: 1 year
The real-time diagnostic accuracy of CAD EYE per patient (in case of multiple polyps per patient).
1 year
The localization score of AI4CRP.
Zeitfenster: 1 year
The localization score of AI4CRP regarding the number of images in which the heatmap produced by AI4CRP pointed out the area of interest (scale: correct, incorrect, or partly correct area of interest).
1 year
The difference in diagnostic accuracy of endoscopists per polyp before and after AI.
Zeitfenster: 1 year
The difference in real-time diagnostic accuracy of endoscopists per polyp before and after AI.
1 year
The difference in sensitivity of endoscopists per polyp before and after AI.
Zeitfenster: 1 year
The difference in real-time sensitivity of endoscopists per polyp before and after AI.
1 year
The difference in specificity of endoscopists per polyp before and after AI.
Zeitfenster: 1 year
The difference in real-time specificity of endoscopists per polyp before and after AI.
1 year
The difference in negative predictive value of endoscopists per polyp before and after AI.
Zeitfenster: 1 year
The difference in real-time negative predictive value of endoscopists per polyp before and after AI.
1 year
The difference in positive predictive value of endoscopists per polyp before and after AI.
Zeitfenster: 1 year
The difference in real-time positive predictive value of endoscopists per polyp before and after AI.
1 year
The agreement in surveillance interval based on optical diagnosis and histopathology.
Zeitfenster: 1 year
The agreement in surveillance interval based on optical diagnosis of diminutive colorectal polyps and histopathology of small and large colorectal polyps, compared to the surveillance interval based on histopathology of all colorectal polyps (diminutive, small, and large).
1 year

Mitarbeiter und Ermittler

Hier finden Sie Personen und Organisationen, die an dieser Studie beteiligt sind.

Sponsor

Maastricht University Medical Center

Mitarbeiter

Catharina Ziekenhuis Eindhoven
Eindhoven University of Technology

Ermittler

  • Hauptermittler: Erik Schoon, Prof Dr MD, Maastricht Universitair Medisch Centrum

Studienaufzeichnungsdaten

Diese Daten verfolgen den Fortschritt der Übermittlung von Studienaufzeichnungen und zusammenfassenden Ergebnissen an ClinicalTrials.gov. Studienaufzeichnungen und gemeldete Ergebnisse werden von der National Library of Medicine (NLM) überprüft, um sicherzustellen, dass sie bestimmten Qualitätskontrollstandards entsprechen, bevor sie auf der öffentlichen Website veröffentlicht werden.

Haupttermine studieren

Studienbeginn (Tatsächlich)

20. August 2021

Primärer Abschluss (Voraussichtlich)

1. September 2022

Studienabschluss (Voraussichtlich)

1. Dezember 2022

Studienanmeldedaten

Zuerst eingereicht

31. März 2022

Zuerst eingereicht, das die QC-Kriterien erfüllt hat

21. April 2022

Zuerst gepostet (Tatsächlich)

27. April 2022

Studienaufzeichnungsaktualisierungen

Letztes Update gepostet (Tatsächlich)

5. Mai 2022

Letztes eingereichtes Update, das die QC-Kriterien erfüllt

29. April 2022

Zuletzt verifiziert

1. April 2022

Mehr Informationen

Begriffe im Zusammenhang mit dieser Studie

Schlüsselwörter

Zusätzliche relevante MeSH-Bedingungen

Andere Studien-ID-Nummern

  • METC2021-3036

Plan für individuelle Teilnehmerdaten (IPD)

Planen Sie, individuelle Teilnehmerdaten (IPD) zu teilen?

UNENTSCHIEDEN

Beschreibung des IPD-Plans

A data sharing plan is not yet decided on.

Arzneimittel- und Geräteinformationen, Studienunterlagen

Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt

Nein

Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt

Nein

Diese Informationen wurden ohne Änderungen direkt von der Website clinicaltrials.gov abgerufen. Wenn Sie Ihre Studiendaten ändern, entfernen oder aktualisieren möchten, wenden Sie sich bitte an register@clinicaltrials.gov. Sobald eine Änderung auf clinicaltrials.gov implementiert wird, wird diese automatisch auch auf unserer Website aktualisiert .

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