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Updated: Sep 28, 2026

Emergency Undocking in Robotic Surgery: A Simulation Curriculum
Published on: May 20, 2018
Development and clinical translation of a stepwise simulation-based curriculum for robotic lung transplantation
Jehad Feras Alsamhori1, Therese Hoof1, Benjamin Benavides1
1Department of Surgery, Houston Methodist Hospital, Houston, TX, USA.
Abstract:
Lung transplantation remains the definitive treatment for end-stage lung disease, with minimally invasive and robotic approaches may offer recovery benefits. Robotic lung transplantation is technically complex, and no formal training pathway is currently because of the novelty of the approach. We describe the development and clinical translation of a stepwise simulation-based curriculum that progressed from low-fidelity technical rehearsal to high-fidelity cadaveric training before implementation of our first robotic lung transplant. The simulation program progressed through five structured phases before clinical implementation and was supplemented by video-based cognitive preparation, procedure deconstruction, expert engagement, and multidisciplinary workflow rehearsal. Phase I used a low-fidelity Chamberlain model for anastomotic practice and bedside-assistance training. Phase II involved cadaveric pneumonectomy and anastomosis practice. Phases III and IV comprised full-procedural right- and left-sided cadaveric transplant simulations with iterative refinement of port placement, docking, instruments, sutures, positioning, and operative sequence. Phase V incorporated external expert validation and final technical and workflow adjustments. The primary focus was curriculum development and implementation outcomes; anastomosis duration was recorded as a secondary descriptive procedural metric. The curriculum generated implementation-relevant outcomes across technical, cognitive, and workflow domains. Simulation supported optimization of port placement, assistant access, camera positioning, vascular clamp selection, graft delivery, instrument selection, suture choice, and operative sequencing. It also supported development of a shared mental model, anticipation of intraoperative challenges, role clarification, and familiarization of the broader operative team with the robotic transplant workflow. Readiness was assessed informally through senior-surgeon observation, multidisciplinary debriefing, resolution of identified concerns, and continued consultation with an external subject-matter expert. The first clinical robotic lung transplant was successfully performed in April 2026. A structured, stepwise simulation curriculum facilitated safe clinical implementation of robotic lung transplantation. Progressive training from low-fidelity models to high-fidelity cadaveric simulation supported technical refinement, cognitive rehearsal, multidisciplinary workflow familiarization, and perceived readiness. Simulation-based curricula were essential for safe and reproducible adoption of complex novel robotic procedures at our institution.
