Cardio navigation: planning, simulation, and augmented reality in robotic assisted endoscopic bypass grafting.

BACKGROUND

The aim of this study is to optimize the set-up and port placement in robotic surgery and enhance intraoperative orientation by video overlay of the angiographic coronary tree.

METHODS

In three mongrel dogs and two sheep an electrocardiogram-triggered computed tomographic scan and coronary angiography were performed after placing cutaneous fiducials. The regions of interest (ie, heart, ribs, coronaries, internal thoracic artery) were segmented semiautomatically to create a virtual model of the animal. In this model the target regions of the total endoscopic bypass procedure along the internal thoracic artery and anastomotic area were defined. Algorithms for weighing visibility, dexterity, and collision avoidance were calculated after defining nonadmissible areas using a virtual model of the manipulator. Intraoperatively, registration of the animal and the telemanipulator was performed using encoder data of the telemanipulator by pointing to the fiducials. After pericardiotomy, the reconstructed coronary tree was projected into the videoscopic image using a semiautomatic alignment procedure. In dogs, the total endoscopic bypass procedure was completed on the beating heart. The first human case applying preoperative planning, intraoperative registration, and augmented reality was subsequently performed.

RESULTS

The rigid transformation linked the patient's preoperative frame and the robot coordinate frame with a root mean square error of 9 to 15 mm. The predicted port placement derived from the model initially varied from the one chosen due to an incomplete formulation of the weighing procedure. After only a few iterations, the algorithm became robust and predicted a collision free triangle. Video overlay of the angiographic coronary tree into the videoscopic image was feasible.

CONCLUSIONS

Surgical planning and augmented reality are likely to enhance robotic surgery in the future. A more complete understanding of the surgical decision process is required to better formalize the planning algorithms.