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Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_XLIV | Pages 51 - 51
1 Oct 2012
Claasen G Martin P Picard F
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Over the past fifteen years, computer-assisted surgery systems have been more commonly used, especially in joint arthroplasty. They allow a greater accuracy and precision in surgical procedures and thus should improve outcomes and long term results.

New instruments such as guided handheld tools have been recently developed to ultimately eliminate the need for drilling/cutting or milling guides.

To make sure that the handheld tool cuts and/or drills in the desired plane, it has to be servo-controlled. For this purpose, the tool joints are actuated by computer-controlled motors. A tracking system gives the tool position and orientation and a computer calculates the corrections for the motors to keep the tool in the desired plane.

For this servo-control, a very fast tracking system would be necessary. It should be fast enough to follow human motion. Current optical tracking systems used for computer-assisted surgery have a bandwidth of about 10–60 Hz [3]. For servo-control, a bandwidth of about 200–300 Hz would be required to be faster than human reaction; the latency of the system should also be small, about 2–3 ms. Optical tracking systems with a higher bandwidth exist but are too expensive for applications in surgery; besides the latency – due to the complex computer vision treatment involved – is too big.

We have developed a hybrid tracking system consisting of two cameras pointed at the operating field and a sensor unit which can be attached to a handheld tool.

The sensor unit is made up of an inertial measuring unit (IMU) and numerous optical markers. The data from the IMU (three gyroscopes and three accelerometers placed such that their measurement axes are perpendicular to each other) and the marker images from the cameras looking at the optical markers are fed to a data fusion algorithm. This algorithm calculates the position and the orientation of any handheld tool. It can do so at the higher of the two sensor sample rates which is the IMU sample rate in our case.

Our experimental setup consists of an ADIS 16355 IMU which runs at a sample rate of 250 Hz and a pair of stereo cameras which are sampled at 16.7 Hz. The data collected from these sensors are processed offline by the data fusion algorithm. To compare the results of our hybrid system to those of a purely optical tracking system, we use only the marker image data to recalculate the sensor unit's position by triangulation.

The experiment we conducted was a fast motion in a horizontal direction starting from a rest position. The sensor unit position was calculated by the hybrid system and by the optical tracking system using the experimental data. The fast motion started right after the optical sample at t1 and the hybrid system detects it at once. The optical tracking system, on the other hand, only sees the motion at the next optical sample time t2.

These results show that our hybrid system is able to follow a fast motion of the sensor unit whereas a purely optical tracking system is not.

The proposed hybrid tracking system calculates position and orientation of any handheld tool at a high frequency of 250 Hz and thus makes it possible to servo-control the tool to keep it in the desired plane.

Several similar systems fusing optical and inertial data have been described in the literature. They all use processed optical data, i.e. 3D marker positions. Our algorithm uses raw image data to considerably reduce computation time. This hybrid tracking system can be used with any handheld tool developed to substitute existing drilling, cutting or milling instruments used in orthopaedic surgery and particularly in arthroplasty.

The sensor unit can be easily implemented into an existing optical tracking system. For the surgeon, the only change is an additional small inertial sensor besides the optical markers already attached to the tool.

The authors would like to thank the AXA Research Fund for funding G.C. Claasen's work with a doctoral grant and Guillaume Picard for his contributions to the experimental setup.


Orthopaedic Proceedings
Vol. 93-B, Issue SUPP_III | Pages 375 - 375
1 Jul 2011
Hooper G Rothwell A Martin P Frampton C
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This study reviewed the revision rate of fully cemented, hybrid and cementless primary total knee replacements (TKR) registered in the New Zealand Joint Registry from 1999 to May 2008 to determine whether there was any significant difference in the survival and reason for revision with these different types of fixation.

The percentage rate of revision was calculated per 100 person years (HPY) and compared to the reason for revision, type of fixation and the patient’s age.

Of the 28707 primary TKR registered, 522 underwent revision procedures requiring change of at least one component with a survival rate of 0.44 HPY (1.8%). The majority of revisions were for pain (153) followed by deep infection (133) followed by loosening of the tibial component (98). Overall the rate of tibial loosening was 0.07 HPY (0.3 %) in the cemented group vs 0.25 HPY (1%) in the cementless group (p < 0.001). There was no significant difference in the type of fixation used for the femoral component, but there was a significant difference in the different types of fixation when revised for pain, with the uncemented tibia performing the poorest. There was no significantly difference in the younger patient (< 55 years) with respect to tibial loosening (p=0.92).

Failure of the uncemented total knee replacement was due to pain and tibial loosening although the results in patients under 55 years were similar in all fixation groups. There was no difference in the fixation method of the femoral component.


Orthopaedic Proceedings
Vol. 90-B, Issue SUPP_II | Pages 242 - 243
1 Jul 2008
PICARD F SCHOCKMEL G LEITNER F MARTIN P
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Purpose of the study: Knee prosthesis surgery has reached a high level of reproducibility, providing very satisfactory results in the large majority of patients. There remains however a certain lack of precision concerning this surgical procedure concerning the determination of the hip center. This point is used to establish the mechanical axis of the femur for positioning the prosthesis. Navigation systems can be used to localize this center. We conducted a cadaver study to determine the accuracy and repeatability of this method for determining the center of the hip joint.

Material and methods: A computerized navigation system was applied to seven fresh cadavers with normal hips. We compared the anatomic center of the hip joint with the point determined with the navigation system. We also compared the navigation technique using different navigation techniques: marker fixed on the iliac crest and without marker fixed on the iliac crest. We also determined the accuracy of the result as a function of hip circumduction during acquisition (5°, 8°, 10°).

Results: There was no statistical difference between investigator A (0.66±0.15, max error: 0.99) and B (0.68±0.10, max error: 0.87), p=0.98 (inter or intra-observer) for comparisons between the anatomic center of the hip joint and the point determined by the navigation system. The results were not statistically different between the navigation techniques (with and without a marker fixed on the iliac crest):(mean < 0.71 ± 032, max. error: 1.91) for each hip with the iliac marker (0.66 ± 0.20, max. error max: 0.99) or without the iliac marker (0.61 ± 0.41, max. error: 1.29) for hip 1. Accuracy was better for hip movement at 10° (0.60 ± 0.21, max. error: 0.92) than at 8° (0.81 ± 0.52, max. error: 1.91) or at 5° (0.67 ± 0.46, max. error: 1.91). In addition, without an iliac crest marker, 75% of the errors were less than 1, and 95% less than 1.5.

Discussion: Acquisition of the hip center of rotation using a computerized navigation system with or without use of markers fixed on the iliac crest is remarkably accurate.

Conclusion: New algorithms and control systems should help improve reproducibility above that obtained with the conventional technique.