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Evaluation of the usefulness of an intraoperative focus point automatic identification model using deep learning in laparoscopic cholecystectomy

Evaluation of the usefulness of an intraoperative focus point automatic identification model using deep learning in laparoscopic cholecystectomy - Evaluation of the usefulness of an intraoperative focus point automatic identification model using deep learning in laparoscopic cholecystectomy

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
JPRN
Registry ID
JPRN-UMIN000058609
Enrollment
20
Registered
2025-07-30
Start date
2025-07-17
Completion date
Unknown
Last updated
2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gallstone disease, Gallbladder polyps, Chronic cholecystitis

Interventions

None listed

Sponsors

The University of Tokyo hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: New patient cohort: Patients who undergo laparoscopic cholecystectomy at the Department of Hepatobiliary and Pancreatic Surgery and Organ Transplantation, The University of Tokyo Hospital, between the approval date and November 30, 2026, and who have provided informed consent.Specifically, this study excludes cases with severe gallbladder inflammation, such as acute cholecystitis following PTGBD or cholangitis with yellow granuloma, and instead focuses on cases with mild gallbladder inflammation, such as gallbladder polyps, gallstone disease, or mild chronic cholecystitis. Control group: Patients who underwent laparoscopic cholecystectomy at the Department of Hepatobiliary and Pancreatic Surgery, Tokyo University Hospital, between January 2008 and May 2025. The study focuses on cases with minimal gallbladder inflammation.

Exclusion criteria

Exclusion criteria: Patients aged 17 years or younger. Patients who are unable to give consent. Patients who have previously undergone laparoscopic cholecystectomy and have refused to participate.

Design outcomes

Primary

MeasureTime frame
We will compare the times deemed appropriate and inappropriate for surgical videos for each video and evaluate the usefulness of the new algorithm and select the most appropriate algorithm. We will also compare postoperative outcomes such as the length of hospital stay including patient information, the incidence of complications within 30 days, and the readmission rate within 90 days.

Countries

Japan

Contacts

Public ContactRyo Oikawa

The University of Tokyo Hospital Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery

oikawar-sur@h.u-tokyo.ac.jp03-3815-5411

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026