TY - JOUR AU - Bedetti, Benedetta AU - Schnorr, Philipp AU - Schmidt, Joachim AU - Scarci, Marco PY - 2017 TI - The role of wet lab in thoracic surgery JF - Journal of Visualized Surgery; Vol 3 (May 2017): Journal of Visualized Surgery Y2 - 2017 KW - N2 - During the last three decades, minimally invasive surgery has become common practice in all kinds of surgical disciplines and, in Thoracic Surgery, the minimally invasive approach is recommended as the treatment of choice for early-stage non-small cell lung cancer. Nevertheless, all over the world a large number of lobectomies is still performed by conventional open thoracotomy and not as video-assisted thoracic surgery (VATS), which shows the need of a proper training for this technique. Development and improvement of surgical skills are not only challenging and time-consuming components of the training curriculum for resident or fellow surgeons, but also for more experienced consultants learning new techniques. The rapid evolution of medical technologies like VATS or robotic surgery requires an evolution of the existing educational models to improve cognitive and procedural skills before reaching the operating room in order to increase patient safety. Nowadays, in the Thoracic Surgery field, there is a wide range of simulation-based training methods for surgeons starting or wanting to improve their learning curve in VATS. Aim is to overcome the learning curve required to successfully master this new technique in a brief time. In general, the basic difference between the various learning techniques is the distinction between “dry” and “wet” lab modules, which mainly reflects the use of synthetic or animal-model-based materials. Wet lab trainings can be further sub-divided into in vivo modules, where living anaesthetized animals are used, and ex vivo modules, where only animal tissues serve as basis of the simulation-based training method. In the literature, the role of wet lab in Thoracic Surgery is still debated. UR - https://jovs.amegroups.org/article/view/14690