Adjacent-room dual-console Remote Surgical Training (ReST) with takeover capability on the da Vinci Xi: a porcine-model feasibility study
We evaluated a Remote Surgical Training model (ReST) in which the tutor operates a second da Vinci Xi console from an adjacent room while preserving integrated audio and the ability to take over control. A comparative feasibility study was conducted at RAIN (A. Cardarelli Hospital, Naples, Italy) between March 2021 and April 2023 using a porcine model. Thirty training sessions were analysed (15 ReST, 15 in-room dual-console controls). Trainee performance was assessed with the Global Evaluative Assessment of Robotic Skills (GEARS); post-session surveys captured perceptions, tutor-trainee agreement (weighted Cohen’s κ), priority rankings (Kemeny aggregation with τX) and satisfaction. GEARS internal consistency was acceptable (Cronbach’s α overall 0.805; control 0.837; ReST 0.768). No statistically significant differences were observed for the GEARS total score (Mann-Whitney U = 105, p = 0.595) or domains (p = 0.074–0.683). Tutor-trainee agreement was significant for three interaction items: ease of teaching/training (p = 0.004), ability to follow the trainee’s actions (p = 0.011) and overall interaction quality (p = 0.014). Priority rankings in both roles emphasised clarity of instruction and takeover capability, while physical proximity ranked lowest. Tutors and trainers reported high satisfaction in both groups; one trainee reported low satisfaction in the ReST group. Adjacent-room ReST with takeover capability was feasible in this porcine-model training setting and showed no observed performance decrement compared with conventional in-room dual-console training. These findings should not be interpreted as proof of equivalence or as validation of true long-distance teleproctoring; further work is required for larger samples, participant-level baseline adjustment, and longer-distance configurations.
Authors
- Luigi Napolitano (ORCID: https://orcid.org/0000-0003-2036-0356)
- Antonio Di Girolamo
- Lorenzo Spirito (ORCID: https://orcid.org/0000-0003-1175-8637)
- Carmine Sciorio (ORCID: https://orcid.org/0000-0001-6846-079X)
- G. Romeo (ORCID: https://orcid.org/0000-0003-3239-6057)
- Guido De Sena (ORCID: https://orcid.org/0009-0009-6469-3786)
- Vittorio Imperatore
- Riccardo Giannella
- Lorenzo Romano (ORCID: https://orcid.org/0000-0002-6581-7930)
- Antonio D’Ambrosio
- Roberta Siciliano
- Antonio Ruffo
- Paola Coppola
- Fabio Esposito
Institutions
- Ospedale Antonio Cardarelli (IT)
- Ingegneria dei Trasporti (Italy) (IT)
- Azienda Ospedaliera S.Giuseppe Moscati (IT)
- Alessandro Manzoni Hospital (IT)
- Casa di Cura Columbus (IT)
- University of Campania "Luigi Vanvitelli" (IT)
- University of Naples Federico II (IT)
Publication Details
- Journal
- Journal of Robotic Surgery
- Published
- 2026-04-21
- DOI
- https://doi.org/10.1007/s11701-026-03391-9
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Intuitive Foundation
- Università degli Studi della Campania Luigi Vanvitelli