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Objective: Current video-assisted thoracoscopic surgery training models rely on animals or mannequins to teach procedural skills. These approaches lack inherent teaching/testing capability and are limited by cost, anatomic variations, and single use. In response, we hypothesized that video-assisted thoracoscopic surgery right upper lobe resection could be simulated in a virtual reality environment with commercial software. Methods: An anatomy explorer (Maya [Autodesk Inc, San Rafael, Calif] models of the chest and hilar structures) and simulation engine were adapted. Design goals included freedom of port placement, incorporation of well-known anatomic variants, teaching and testing modes, haptic feedback for the dissection, ability to perform the anatomic divisions, and a portable platform. Results: Preexisting commercial models did not provide sufficient surgical detail, and extensive modeling modifications were required. Video-assisted thoracoscopic surgery right upper lobe resection simulation is initiated with a random vein and artery variation. The trainee proceeds in a teaching or testing mode. A knowledge database currently includes 13 anatomic identifications and 20 high-yield lung cancer learning points. The “patient” is presented in the left lateral decubitus position. After initial camera port placement, the endoscopic view is displayed and the thoracoscope is manipulated via the haptic device. The thoracoscope port can be relocated; additional ports are placed using an external “operating room” view. Unrestricted endoscopic exploration of the thorax is allowed. An endo-dissector tool allows for hilar dissection, and a virtual stapling device divides structures. The trainee’s performance is reported. Conclusions: A virtual reality cognitive task simulation can overcome the deficiencies of existing training models. Performance scoring is being validated as we assess this simulator for cognitive and technical surgical education. [Copyright &y& Elsevier]