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

29. april 2022 oppdatert av: 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.

Studieoversikt

Status

Rekruttering

Forhold

Intervensjon / Behandling

Detaljert beskrivelse

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.

Studietype

Observasjonsmessig

Registrering (Forventet)

105

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

Studer Kontakt Backup

Studiesteder

  • Nederland
    • Limburg
    • Noord-Brabant
      • Eindhoven, Noord-Brabant, Nederland, 5623 EJ
        • Fullført
        • Catharina Ziekenhuis Eindhoven

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

18 år og eldre (Voksen, Eldre voksen)

Tar imot friske frivillige

Nei

Kjønn som er kvalifisert for studier

Alle

Prøvetakingsmetode

Ikke-sannsynlighetsprøve

Studiepopulasjon

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.

Beskrivelse

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.

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

Kohorter og intervensjoner

Gruppe / Kohort
Intervensjon / Behandling
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).
Enhet: 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).
Andre navn:
  • AI4CRP, artificial intelligence for colorectal polyps (COMET-OPTICAL research group)
  • CAD EYE (Fujifilm® Corporation, Tokyo, Japan)

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Technical feasibility of real-time use of AI4CRP.
Tidsramme: 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.
Tidsramme: 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).
Tidsramme: 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).
Tidsramme: 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).
Tidsramme: 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).
Tidsramme: 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).
Tidsramme: 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).
Tidsramme: 1 year
The real-time Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).
1 year

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
The diagnostic accuracy of AI4CRP per polyp.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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.
Tidsramme: 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

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

Maastricht University Medical Center

Samarbeidspartnere

Catharina Ziekenhuis Eindhoven
Eindhoven University of Technology

Etterforskere

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

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Faktiske)

20. august 2021

Primær fullføring (Forventet)

1. september 2022

Studiet fullført (Forventet)

1. desember 2022

Datoer for studieregistrering

Først innsendt

31. mars 2022

Først innsendt som oppfylte QC-kriteriene

21. april 2022

Først lagt ut (Faktiske)

27. april 2022

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

5. mai 2022

Siste oppdatering sendt inn som oppfylte QC-kriteriene

29. april 2022

Sist bekreftet

1. april 2022

Mer informasjon

Begreper knyttet til denne studien

Nøkkelord

Ytterligere relevante MeSH-vilkår

Andre studie-ID-numre

  • METC2021-3036

Plan for individuelle deltakerdata (IPD)

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IPD-planbeskrivelse

A data sharing plan is not yet decided on.

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