Methods

This study presents an alternative robotic controlled cutting technique to perform the bone resections during TKA by milling a slot with a long slender high-speed milling tool. The system is composed by a long milling tool driven by a high-speed motor and a protector covering the end of the cutter. The protector is rigidly connected to the motor by the support structure next to the mill, which moves behind the mill in the slot created by the cutter. The protector at the end of the cutter has four functions: providing mechanical support for the mill, preventing soft tissue to come into contact with the cutter, sensing the edge of the bone to accurately follow the shape of the bone and releasing the attached soft tissue. The edge of the bone is sensed by force feedback and with the help of a probing motion the adaptive algorithm enables the protector to follow the edge of the bone closely by compensating for small segmentation and registration errors. A pilot test to evaluate the concept was performed on three fresh frozen knees. The flatness of the resection, the iatrogenic soft tissue damage, the cutting time and the efficiency of the bone contour following algorithm was measured.

MATERIALS & METHODS

A total of five cadaveric fresh frozen lower limb specimens have been used to quantitatively assess the difference between the golden standard, CT based, method and the newly developed real-time method. A schematic of the data flow for both methods. Prior to testing, both methods require a CT scan of the full lower limb. During the tests, the proximal femur and distal tibia are necessarily resected to fit the knees in the test setup, thus also removing the anatomical landmarks needed to evaluate their mechanical axis. Subsequently, a set of three passive markers are rigidly attached to the femur and tibia, referred to as M3F and M3T respectively. For the CT based method, the marker positions are captured during the tests and a second CT scan is eventually performed to link the marker positions to the knee anatomy. Using in-house developed software, this allowed to offline evaluate the knee kinematics in six degrees of freedom by combining both CT datasets with the tracked marker positions. For the newly developed real-time method, a calibration procedure is first performed. This calibration aims to link the position of the 3D reconstructed bone and landmarks with the attached markers. A set of bone surface points is therefore registered. These surface points are obtained by tracking the position of a pen while touching the bone surface. The pen's position is thereby tracked by three rigidly attached markers, denoted M3P. The position of the pen tip is subsequently calculated from the known pen geometry. The iterative closest point (ICP) algorithm is then used to match the 3D reconstructed bone to the registered surface points. Two types of 3D reconstructions have therefore been considered. First, the original reconstructions were used, obtained from the CT data. Second, a modified reconstruction was used. This modification accounted for the finite radius (r = 1.0 mm) of the registration pen, by shifting the surface nodes 1.0 mm along the direction of the outer surface normal. During the tests, the positions of the femur and tibia markers are tracked and streamed in real-time to an in-house developed, Matlab based software framework (MathWorks Inc., Natick, Massachussets, USA). This software framework simultaneously calculates the bone positions and knee kinematics in six degrees of freedom, displaying this information to the surgeons and operators. To assess the accuracy, all knee specimens have been subjected to passive flexion-extension movement ranging from 0 to 120 degrees of flexion. For each degree of freedom, the average root mean square (RMS) difference between both measurement methods has been evaluated during this movement. In addition, the distribution of the registered surface points has been assessed along the principal directions of the uniformly meshed 3D reconstructions (average mesh size of 1.0 mm).

Methods

Both a two and three dimensional simulation model have been created using the AnyBody Modelling System (AMS). In the two dimensional model, the knee joint is represented by a hinge. Similarly, the ankle and hip joint are represented by a hinge joint and a variable amplitude quadriceps force is applied to a rigid bar connected to the tibia (Figure 1a). In line with this simulation model, a hinge model was created that could be mounted in the UGent knee simulator to evaluate the performance of the simulated model. The hinge model thereby performs a cyclic motion under varying quadriceps load while recording the ankle reaction forces.

In addition to the two dimensional model, a three dimensional model has been developed (Figure 1b). More specifically, a model is built of a sawbone leg holding a posterior stabilized single radius total knee implant. The physical sawbone model contains simplified medial and lateral collateral ligaments. In line with the boundary conditions of the UGent knee simulator, the simulated hip contains a single rotational degree of freedom and the ankle holds four degrees of freedom (three rotations, single translation). In the simulations, the knee is modelled using the force-dependent kinematics (FDK) method built in the AMS. This leaves the knee with six degrees of freedom that are controlled by the ligament tension in combination with the applied quadriceps load and shape of the implant. The physical sawbone model goes through five cycles in the UGent simulator using while recording the kinematics of the femur and tibia using a set of markers rigidly attached to the femur and tibia bone. The position of the implant with respect to the markers was evaluated by CT-scanning the sawbone model.