- ICH GCP
- US Clinical Trials Registry
- Klinisk utprøving NCT07566078
Artificial Intelligence (AI)-Based Intraoperative Visualization is Increasingly Integrated Into Robotic Surgery Platforms; However, Its Impact on Surgeons' Cognitive Workload Remains Unclear. This Study Evaluated Perceived Workload Among Console Surgeons and Bedside Assistants According to Different
Impact of AI Visualization on Surgeons' Cognitive Workload in Single-Port Robotic Surgery
Robotic surgery is now widely adopted in urology, and the da Vinci Single-Port (SP) platform enables complex procedures through a single multichannel incision, with favorable perioperative and outpatient outcomes in selected patients. However, single-port access and AI implementation also introduce unique ergonomic and cognitive challenges for surgeons and operating room staff. Quantifying intraoperative workload has become crucial to understand how new technologies affect performance, safety and training.
The National Aeronautics and Space Administration Task Load Index (NASA-TLX) is a validated multidimensional instrument for subjective workload assessment and has been increasingly applied to surgical and specifically urologic practice. In parallel, augmented reality and artificial intelligence (AI) are emerging as tools to enhance intraoperative visualization and anatomical understanding during robot-assisted urologic procedures. The da Vinci TilePro multi-image display already allows simultaneous viewing of auxiliary imaging, but evidence on how real-time AI overlays integrated via TilePro affect cognitive workload in single-port urologic surgery is lacking. This prospective pilot study evaluates the impact of different TilePro visualization strategies on surgeon and bedside assistant workload, measured by weighted NASA-TLX scores, and explores associations with operative metrics in elective SP urologic procedures.
Studieoversikt
Studietype
Registrering (Antatt)
Fase
- Ikke aktuelt
Kontakter og plasseringer
Studiesteder
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Illinois
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Chicago, Illinois, Forente stater, 60612
- UI Health
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Deltakelseskriterier
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
- Voksen
- Eldre voksen
Tar imot friske frivillige
Beskrivelse
Inclusion Criteria: Urology surgeon or urology resident -
Exclusion Criteria: not urology surgeon or not urology resident
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Studieplan
Hvordan er studiet utformet?
Designdetaljer
- Primært formål: Annen
- Tildeling: Ikke-randomisert
- Intervensjonsmodell: Parallell tildeling
- Masking: Ingen (Open Label)
Våpen og intervensjoner
Deltakergruppe / Arm |
Intervensjon / Behandling |
|---|---|
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Aktiv komparator: Continuous AI visualization
the AI overlay was displayed continuously throughout the entire surgical procedure.
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The AI system employed in this study was based on a convolutional neural network (CNN) architecture implemented via the YOLO (You Only Look Once) framework, specifically designed for real-time instance segmentation of intraoperative anatomical structures.
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Aktiv komparator: Intermittent AI visualization
The operator selectively activated the AI visualization during key surgical phases according to preference
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The AI system employed in this study was based on a convolutional neural network (CNN) architecture implemented via the YOLO (You Only Look Once) framework, specifically designed for real-time instance segmentation of intraoperative anatomical structures.
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Ingen inngripen: No AI visualization
No AI visualization use
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Hva måler studien?
Primære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
|---|---|---|
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NASA Task Load Index (NASA-TLX) questionnaire
Tidsramme: 30 minutes after completing the surgey
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The National Aeronautics and Space Administration Task Load Index (NASA-TLX) is a validated multidimensional instrument for subjective workload assessment and has been increasingly applied to surgical and specifically urologic practice
|
30 minutes after completing the surgey
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Samarbeidspartnere og etterforskere
Studierekorddatoer
Studer hoveddatoer
Studiestart (Faktiske)
Primær fullføring (Antatt)
Studiet fullført (Antatt)
Datoer for studieregistrering
Først innsendt
Først innsendt som oppfylte QC-kriteriene
Først lagt ut (Faktiske)
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
Siste oppdatering sendt inn som oppfylte QC-kriteriene
Sist bekreftet
Mer informasjon
Begreper knyttet til denne studien
Ytterligere relevante MeSH-vilkår
Andre studie-ID-numre
- 2026-0199
Plan for individuelle deltakerdata (IPD)
Planlegger du å dele individuelle deltakerdata (IPD)?
IPD-planbeskrivelse
IPD-deling Støtteinformasjonstype
- SEVJE
Legemiddel- og utstyrsinformasjon, studiedokumenter
Studerer et amerikansk FDA-regulert medikamentprodukt
Studerer et amerikansk FDA-regulert enhetsprodukt
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