Bronchial sleeve resection is a lung-sparing procedure that avoids pneumonectomy and reduces postoperative mortality, but it remains technically demanding. The rise of minimally invasive approaches such as video-assisted thoracic surgery (VATS) and robotic-assisted thoracic surgery (RATS) adds further complexity, increasing the need for realistic and high-fidelity training. The purpose of this study is to develop high fidelity dry lab for minimally invasive bronchial sleeve resection and reconstruction. A modular chest wall training device was created to support various minimally invasive approaches. The module includes 25 configurable 30 mm ports with detachable 8 mm rubber plugs, allowing simulation of multiportal and uniportal VATS, as well as RATS. A 3-dimensional precise bronchial model derived from computed tomography data was used to simulate right upper lobe sleeve resection. The training model was evaluated with a 5-point Likert scale (surgical exposure, manipulation, and usefulness as training) after four board-certified thoracic surgeons performed simulations with both approaches. The training was successfully conducted using both thoracoscopic and robotic approaches and could be repeated with no issues in port interference or stability. The evaluation by the four thoracic surgeons was generally acceptable (VATS: median score range on a 5-point Likert scale: surgical exposure 3.5 2-5, manipulation 2.5 2-5, usefulness as training 4.0 4-5. Robotic-assisted surgery: surgical exposure 4.5 4-5, manipulation 4.0 4-5, usefulness as training 5.0 4-5). This training system helps thoracic surgeons prepare for the growing demand for this type of procedure and ultimately improve surgical outcomes.
Hirata et al. (Fri,) studied this question.