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Clinical Application of an AI-based Dissection Trajectory Prediction System (ADTPS) in Endoscopic Submucosal Dissection

16. september 2026 oppdatert av: Qilu Hospital of Shandong University

Clinical Application of an AI-based Dissection Trajectory Prediction System (ADTPS) in Endoscopic Submucosal Dissection: A Prospective Paired Diagnostic Study and a Randomized Controlled Clinical Trial

In this prospective paired diagnostic study and single-center, randomized controlled trial, patients with early esophageal squamous neoplasia or high-grade intraepithelial neoplasia meeting the inclusion and exclusion criteria will be enrolled in a paired diagnostic cohort (60 patients) and subsequently randomly assigned (1:1) to receive endoscopic submucosal dissection (ESD) with AI-based Dissection Trajectory Prediction System (ADTPS) guidance or conventional ESD (without AI). Clinical data and operator workload scores (NASA-TLX) are collected during the procedure, and postoperative follow-up assessments are performed at days 1, 3, 7, and 14. The study aims to analyze the impact of ADTPS on the mean single-dissection time and operator workload in patients undergoing ESD by comparing the efficacy differences between the experimental and control groups. Additionally, the study investigates the effects of ADTPS on other postoperative complications including R0 resection rate, muscularis propria injury, intraoperative bleeding, perforation (acute and delayed), and total procedure time; conducts a comparative analysis of the safety and efficiency of AI-assisted versus conventional ESD; and develops effective clinical strategies for optimizing dissection trajectory and reducing complications in endoscopic submucosal dissection.

Studieoversikt

Status

Aktiv, ikke rekrutterende

Forhold

Intervensjon / Behandling

Studietype

Intervensjonell

Registrering (Antatt)

160

Fase

  • Ikke aktuelt

Kontakter og plasseringer

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

Studiesteder

  • Kina
    • Shandong
      • Jinan, Shandong, Kina, 250012
        • 山东大学齐鲁医院

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

  • Voksen
  • Eldre voksen

Tar imot friske frivillige

Nei

Beskrivelse

Inclusion Criteria:

  • Chinese patients aged 18-80 years.

Lesions meeting ESD indications for esophageal, gastric, or colorectal early cancer or high-grade intraepithelial neoplasia, as defined by:

Non-invasive tumors regardless of size; or

Differentiated-type intramucosal carcinoma without ulceration, regardless of size; or

Differentiated-type intramucosal carcinoma with ulceration and a diameter ≤3 cm; or

Undifferentiated-type intramucosal carcinoma without ulceration and a diameter ≤2 cm.

Planned to undergo ESD treatment.

No prior treatment for the lesion (including ESD, surgery, radiotherapy, chemotherapy, etc.).

Platelet count >100 × 10⁹/L and PT-INR <1.5, with antiplatelet agents (aspirin, clopidogrel, etc.) discontinued for at least 5 days.

American Society of Anesthesiologists (ASA) physical status grade I or II.

Voluntarily signed informed consent.

Exclusion Criteria:

  • Patients currently undergoing dialysis.

Patients with severe cardiopulmonary disease or other severe comorbidities that may increase the risk of the ESD procedure.

Pregnant or breastfeeding women.

Studieplan

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

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Behandling
  • Tildeling: Randomisert
  • Intervensjonsmodell: Parallell tildeling
  • Masking: Dobbelt

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Aktiv komparator: Conventional ESD without AI
Enhet: Conventional ESD Procedure
The same endoscopic hardware platform is used, but the AI-based Dissection Trajectory Prediction System (ADTPS) is turned off. The endoscopist performs the ESD procedure based solely on clinical judgment and personal experience, following standard conventional ESD steps including marking, injection, circumferential incision, and submucosal dissection.
Eksperimentell: AI-assisted ESD with ADTPS
Enhet: AI-based Dissection Trajectory Prediction System (ADTPS)
The ADTPS is an artificial intelligence software system that analyzes endoscopic images in real time during ESD. It automatically identifies lesion boundaries and generates a recommended dissection trajectory overlaid on the endoscopic view. The endoscopist follows the AI-generated trajectory to perform submucosal dissection. The system provides visual guidance only and does not alter the standard surgical workflow.

Hva måler studien?

Primære resultatmål

Resultatmål
Tidsramme
NASA-TLX Workload Score
Tidsramme: Immediately after the ESD procedure
Immediately after the ESD procedure
Mean Single Dissection Time
Tidsramme: During the ESD procedure
During the ESD procedure

Sekundære resultatmål

Resultatmål
Tidsramme
R0 Resection Rate
Tidsramme: At the time of pathological examination
At the time of pathological examination
Muscularis Propria Injury Rate
Tidsramme: During the ESD procedure
During the ESD procedure
Intraoperative Bleeding Episodes
Tidsramme: During the ESD procedure
During the ESD procedure
Intraoperative Perforation Rate
Tidsramme: During the ESD procedure
During the ESD procedure
Delayed Bleeding Rate
Tidsramme: Within 14 days after procedure
Within 14 days after procedure
Delayed Perforation Rate
Tidsramme: Within 14 days after procedure
Within 14 days after procedure
Total Procedure Time
Tidsramme: During the ESD procedure
During the ESD procedure

Samarbeidspartnere og etterforskere

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

Sponsor

Qilu Hospital of Shandong University

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)

29. juli 2026

Primær fullføring (Antatt)

28. juli 2027

Studiet fullført (Antatt)

1. oktober 2027

Datoer for studieregistrering

Først innsendt

6. august 2026

Først innsendt som oppfylte QC-kriteriene

6. august 2026

Først lagt ut (Faktiske)

11. august 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

18. september 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

16. september 2026

Sist bekreftet

1. juli 2026

Mer informasjon

Begreper knyttet til denne studien

Nøkkelord

Ytterligere relevante MeSH-vilkår

Andre studie-ID-numre

  • 2026SDU-QILU-4

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

NEI

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

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