Purpose: Accurate determination of the flexion-extension axis of the elbow is critical to the successful placement of elbow arthroplasties, articulated external fixators and ligament reconstructions. We expect axis alignment using computer-assisted techniques to improve the outcome of these procedures. For image-based procedures, registration (i.e. the transformation needed to align two sets of points) during surgery is critical for accurate alignment. A surface-based registration technique, employing a hand-held laser scanner, was evaluated against a stand-alone paired-point registration method to determine whether it led to improved alignment of the elbow’s flexion-extension axis.

Methods: Twelve cadaveric distal-humeri were selected for registration. To perform paired-point (TP-PP) registration, key anatomical landmarks (capitellum, trochlear sulcus and distal humeral shaft) were digitized using a tracked-probe (TP) and an electromagnetic tracking device (Flock of Birds, Ascension Tech). Using the geometric centers of these landmarks, TP-PP registration to CT data was performed. Surface registration was achieved using the iterative closest point (ICP) least-squares algorithm and the results were evaluated for two devices; registration employing the tracked-probe (TP-ICP) and registration employing a hand-held laser scanner, HHS-ICP (FastSCAN, Polhemus). For surface registration, to be consistent with the amount of the joint exposed during a typical surgical procedure, only the articular surface was used for alignment.

Results: Registration error (Figure 1) was lowest for the HHS-ICP method with a mean of 0.8±0.3-mm (maximum error, 1.4-mm) in translation, compared with a mean error of 1.5±0.5-mm (maximum error, 2.4-mm) for the TP-ICP method and 1.9±1.0-mm (maximum error, 4.4-mm) for the TP-PP method (p< 0.001). Errors in TP-PP registration were greatest in the coronal plane while TP-ICP registration often resulted in an error along the transverse plane (Figure 2).

Conclusions: Overall, the reliability of surface-based registration combined with the implementation of the hand-held laser scanner demonstrated greater registration accuracy. A reliable surface-based registration technique may lead to a more accurate determination of the elbow’s flexion-extension axis during surgical procedures, leading to improved joint motion and implant longevity. The implications of these results can also be extended to other joints that employ comparable computer-assisted surgical techniques.

Purpose: Glenoid replacement remains challenging due to the difficult visualization of anatomical reference landmarks and highly variable version angles. Improper positioning of the glenoid component leads to loosening, early wear, and instability. The objective of this study was to develop and evaluate a tracking system for glenoid implantation. We hypothesized that Computer Assisted Glenoid Implantation (CAGI) would achieve a more accurate and reliable placement of the glenoid component compared to traditional methods.

Methods: 3D CT models of sixteen paired cadaveric shoulder specimens were reconstructed and angles were measured using 3D modeling softwares. Jigs were developed to track instruments and to correct for scapular motion. A standardized protocol for determining in real-time via electromagnetic tracking the glenoid centre, version, inclination and ultimate component placement was previously developed and validated in our laboratory. Specimens were randomized to either traditional or CAGI performed by one of two blinded fellowship trained shoulder surgeons. The mean age was 67 years (range 61–88). Native version and inclination were similar in both groups. All phases of glenoid implantation were navigated.

Results: CAGI was more accurate in achieving the correct version during all phases of glenoid implantation (p < 0.05; paired t-test). CAGI CONTROL Initial pin * 6.3 ± 2.9° Reaming *7.0 ± 3.9° Post drilling * 0.6 ± 0.4° 8.3 ± 4.6°|Post cement * 2.3 ± 2.0° 7.9 ± 3.6°|Post implant CT * 1.8 ± 0.9° 7.7 ± 4.0°. Table 1. Absolute values of the mean error ± SD of version angles obtained with either CAGI or the traditional method (goal = 0° version; * p < 0.05). The largest errors with traditional were observed during drilling and reaming where visualization was especially obscured by the reamer heads. The trend was to retrovert the glenoid. There was no difference with respect to inclination angles (p > 0.05).

Conclusions: Preoperative planning using CT imaging with 3D modeling and intra-operative tracking were combined to produce improved accuracy and reliability of glenoid implantation.

Funding : Other Education Grant

Funding Parties : National Sciences & Engineering Research Council research grant