Beyond the learning curve: a review of complex cases in robotic thoracic surgery

Abstract

The number of thoracic surgery cases performed on the robotic platform has increased steadily over the last two decades. An increasing number of surgeons are training on the robotic system, which like any new technique or technology, has a progressive learning curve. Central to establishing a successful robotic program is the development of a dedicated thoracic robotic team that involves anesthesiologists, nurses, and bed-side assistants. With an additional surgeon console, the robot is an excellent platform for teaching. Compared to current methods of video-assisted thoracoscopic surgery (VATS), the robot offers improved wristed motion, a magnified, high definition three-dimensional vision, and greater surgeon control of the operation. These advantages are paired with integrated adjunctive technology such as infrared imaging. For pulmonary resection, these advantages of the robotic platform have translated into several clinical benefits, such as fewer overall complications, reduced pain, shorter length of stay, better postoperative pulmonary function, lower operative blood loss, and a lower 30-day mortality rate compared to open thoracotomy. With increased experience, cases of greater complexity are being performed. This review article details the process of becoming an experienced robotic thoracic surgeon and discusses a series of challenging cases in robotic thoracic surgery that a surgeon may encounter "beyond the learning curve". Nearly all thoracic surgery can now be approached robotically, including sleeve lobectomy, pneumonectomy, resection of large pulmonary and mediastinal masses, decortication, thoracic duct ligation, rib resection, and pulmonary resection after prior chest surgery and/or chemoradiation.

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