Prospective Collection and Registry Study of Multicenter, Multidisciplinary Surgical Minimally Invasive Videos (VISION)
Prospective Observational Cohort Study on the Construction of Standardized Video Datasets for Multicenter, Multidisciplinary Minimally Invasive Laparoscopic and Robotic Surgery and Their Application in the Development of Surgical AI Large Models
Studienübersicht
Status
Status
Bedingungen
Bedingungen
Studientyp
Studientyp
Einschreibung (Geschätzt)
Einschreibung
Kontakte und Standorte
Studienkontakt
Studienkontakt
- Name: KUNSHAN HE
- Telefonnummer: +86 18500535530
- E-Mail: hekunshan@buaa.edu.cn
Studienorte
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Beijing, China
- Institute of Automation, Chinese Academy of Sciences
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Teilnahmekriterien
Zulassungskriterien
Zulassungskriterien
Studienberechtigtes Alter
- Erwachsene
- Älterer Erwachsener
Akzeptiert gesunde Freiwillige
Probenahmeverfahren
Studienpopulation
Beschreibung
Inclusion Criteria:
- Patients aged ≥ 18 years old hospitalized to receive minimally invasive endoscopic, laparoscopic or robotic surgical treatment for diseases of various body systems;
- Complete full-length intraoperative surgical videos can be recorded during operation, with complete medical records and preoperative imaging data;
- Participants fully understand the study, voluntarily sign written informed consent, and agree that their de-identified intraoperative images and clinical data can be used for scientific research.
Exclusion Criteria:
- Minors under 18 years of age;
- Patients with incomplete intraoperative videos or missing clinical imaging documents;
- Patients with consciousness disturbance or mental disorders who cannot sign informed consent independently;
- Subjects who refuse to participate in the study and disapprove the use of their medical data for research;
- Patients who are predicted to be unavailable for long-term postoperative follow-up.
Studienplan
Wie ist die Studie aufgebaut?
Designdetails
Was misst die Studie?
Primäre Ergebnismessungen
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Zeitfenster |
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Completion rate of qualified intraoperative surgical imaging data
Zeitfenster: Immediately after each surgery
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Immediately after each surgery
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Sekundäre Ergebnismessungen
Sekundäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
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Completeness rate of long-term postoperative clinical follow-up
Zeitfenster: 3 months, 1 year, 3 years and 5 years after surgery
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3 months, 1 year, 3 years and 5 years after surgery
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Reusability rate of annotated key anatomical structures in videos
Zeitfenster: From completion of data warehousing and annotation, the reusability rate will be analyzed within 3 months, assessed up to 3 months after annotation completion.
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From completion of data warehousing and annotation, the reusability rate will be analyzed within 3 months, assessed up to 3 months after annotation completion.
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Feasibility rate (%) of surgical video dataset applied in different clinical AI research scenarios
Zeitfenster: After full construction of the surgical video dataset, scenario feasibility assessment will be finished within 6 months, assessed up to 6 months after dataset construction.
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Three core application scenarios are predefined: 1) training of surgical computer vision AI models; 2) validation of intraoperative surgical recognition algorithms; 3) surgical skill assessment and teaching research. An expert review panel consisting of at least 3 attending surgeons and 2 medical AI researchers independently evaluates whether the dataset has sufficient sample size, annotation completeness and video quality to support each scenario. Feasibility proportion is calculated as: (Number of scenarios the dataset is suitable for / Total predefined scenarios) × 100%. |
After full construction of the surgical video dataset, scenario feasibility assessment will be finished within 6 months, assessed up to 6 months after dataset construction.
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Accuracy percentage (%) of AI-based surgical procedure identification on annotated surgical videos
Zeitfenster: After completion of data warehousing and annotation, AI surgical procedure identification accuracy testing will be conducted within 3 months, assessed up to 3 months post annotation completion.
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After all surgical videos are imported into the data warehouse and manually annotated by experienced surgeons to generate gold-standard procedure labels, the surgical video analysis AI model automatically outputs predicted surgical procedure categories for each video clip. Each AI-predicted label is compared against the manual gold-standard annotation label. Identification accuracy is calculated by the formula: (Number of video clips with correctly predicted surgical procedures / Total number of tested video clips) × 100%. |
After completion of data warehousing and annotation, AI surgical procedure identification accuracy testing will be conducted within 3 months, assessed up to 3 months post annotation completion.
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Mitarbeiter und Ermittler
Sponsor
Sponsor
Mitarbeiter
Mitarbeiter
Studienaufzeichnungsdaten
Haupttermine studieren
Studienbeginn (Geschätzt)
Studienbeginn
Primärer Abschluss (Geschätzt)
Primärer Abschluss
Studienabschluss (Geschätzt)
Studienabschluss
Studienanmeldedaten
Zuerst eingereicht
Zuerst eingereicht
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst gepostet (Tatsächlich)
Zuerst gepostet
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Tatsächlich)
Letztes Update gepostet
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Zuletzt verifiziert
Zuletzt verifiziert
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Schlüsselwörter
Andere Studien-ID-Nummern
Andere Studien-ID-Nummern
- VISION
Arzneimittel- und Geräteinformationen, Studienunterlagen
Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt
Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt
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