Estimation of optimal pivot point for remote center of motion alignment in surgery.
OBJECTIVE
The determination of an optimal pivot point ([Formula: see text]) is important for instrument manipulation in minimally invasive surgery. Such knowledge is of particular importance for robotic-assisted surgery where robots need to rotate precisely around a specific point in space in order to minimize trauma to the body wall while maintaining position control. Remote center of motion (RCM) mechanisms are commonly used, where the RCM point is manually and visually aligned. If not positioned appropriately, this misalignment might lead to intolerably high forces on the body wall with increased risk of postoperative complications or instrument damage. An automated method to align the RCM with the [Formula: see text] was developed and tested.


METHODS
Computer vision and a lightweight calibration procedure are used to estimate the optimal pivot point. One or two pre-calibrated cameras viewing the surgical scene are employed. The surgeon is asked to make short pivoting movements, applying as little torque as possible, with an instrument of choice passing through the insertion point while camera images are being recorded. The physical properties of an instrument rotating around a pivot point are exploited in a random sample consensus scheme to robustly estimate the ideal position of the RCM in the image planes. Triangulation is used to estimate the RCM position in 3D. Experiments were performed on a specially designed mockup to test the method.


RESULTS
The position of the pivot point is estimated with an average error less than 1.85 mm using two webcams placed from approximately 30 cm to 1 m away from the scene. The entire procedure was completed in a few seconds.


CONCLUSIONS
In automated method to estimate the ideal position of the RCM was shown to be reliable. The method can be implemented within a visual servoing approach to automatically place the RCM point, or the results can be displayed on a screen to provide guidance to the surgeon. Further work includes the development of an image-guided alignment method and validation with in vivo experiments.
KU Leuven, Department of Mechanical Engineering, 3001 , Leuven, Belgium, benoit.rosa@centraliens.net.
Benoît
B
Rosa
Caspar
C
Gruijthuijsen
Ben
B
Van Cleynenbreugel
Jos Vander
JV
Sloten
Dominiek
D
Reynaerts
Emmanuel Vander
EV
Poorten
D002138:Calibration; D006801:Humans; D019060:Minimally Invasive Surgical Procedures / Q000379:methods*; D009038:Motion; D012371:Robotics; D012399:Rotation; D025321:Surgery, Computer-Assisted / Q000379:methods*