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

The reliability and accuracy of plain radiographs, MRI and CT Arthrography to detect the presence of loose bodies was evaluated in twenty-six patients with mechanical elbow symptoms. The location of loose bodies found by the imaging studies was compared to arthroscopic findings. Overall sensitivity for the detection of loose bodies was 88 – 100% and specificity was 20 – 70%. Plain radiographs had a similar sensitivity and specificity of 84% and 71% respectively. MRI and CT Arthrography were similar to plain radiography, suggesting that routine use of these modalities is not indicated.

The purpose of this study was to determine the clinical utility of MRI and CT Arthrography (CTA) to reliably and accurately predict the presence of loose bodies in the elbow.

Twenty-six patients with mechanical elbow symptoms underwent plain radiography, MRI and CTA, followed by standard elbow arthroscopy. Three musculoskeletal radiologists reviewed the ‘blinded’ plain radiographs with both the MRI and CTA at separate sittings. The location and number of loose bodies on the MRI and CTA were recorded. The preoperative plain radiographs, MRI and CTA were compared to the arthroscopic findings.

Agreement between radiologists was higher for the number of loose bodies identified in the posterior compartment (ICC=0.72 for both MRI and CTA) than in the anterior compartment (ICC=0.41 and 0.52 for MRI and CTA respectively). The correlation between the number of lose bodies observed on MRI and CTA compared to those found arthroscopically was also higher in the posterior compartment (r=0.54–0.85) than in the anterior compartment (r=0.01–0.45). Both MRI and CTA had excellent sensitivity (92–100%) but moderate to low specificity (15–77%) in identifying posteriorly located loose bodies. Neither MRI nor CTA were consistently sensitive (46–91%) or specific (13–73%) in predicting anterior loose bodies. Overall sensitivity for the detection of loose bodies in either compartment was 88–100% and specificity was 20–70%. The preoperative radiographs had a similar sensitivity and specificity of 84% and 71% respectively.

MRI and CTA were similar to plain radiography in the prediction of elbow loose bodies.

Introduction and Aims: Ganglia are commonly seen during investigation of patients with wrist pain. Our aim was to determine the prevalence of ganglia in an asymptomatic population.

Method: Following Institutional Ethical approval, Magnetic Resonance Imaging (MRI) was performed on the wrists of 103 asymptomatic volunteers. There were 67 males and 37 females, with an average age of 36, range 19–67 years. There were 52 right wrists and 51 left wrists.

Using a 1.89 Tesla surface coil Magnetic Resonance Imager the following sequences were obtained: Coronal T 1, Proton Density, T 2 and Inversion Recovery sequences; Sagittal Inversion Recovery sequences; Axial T 1 and Inversion Recovery Sequences. The images were then evaluated independently by two Muskuloskeletal Radiologists and one Orthopaedic Surgeon.

Results: Wrist Ganglia were identified in 53 out of 103 wrists. Wrist Ganglia were more prevalent in females than males, 58% compared to 48% respectively. The average long axis measurement was 7.5 mm (range 2.7–22.2), the average short axis measurement was 3.2 mm (range 1.6–10.1). Seventy percent of the Ganglia were found to originate from the volar capsule in the region of the interval between the Radio-Scapho-Capitate Ligament and the Long Radio-Lunate Ligament. Fourteen percent of the ganglia were dorsal and originated from the dorsal, distal fibres of the Scapho-Lunate Ligament. Two ganglia had surrounding soft tissue oedema and one had an associated intra-osseous component.

Conclusion: The prevalence of asymptomatic wrist ganglia is high – 51%. Unlike previous surgical and pathological series, our study showed volar wrist ganglia are more common than dorsal wrist ganglia in the asymptomatic population. The vast majority of these asymptomatic ganglia do not show associated ligamentous disruption, soft tissue oedema or intra-osseous communication.

Our aim was to determine the clinical value of MRI and CT arthrography in predicting the presence of loose bodies in the elbow.

A series of 26 patients with mechanical symptoms in the elbow had plain radiography, MRI and CT arthrography, followed by routine arthroscopy of the elbow. The location and number of loose bodies determined by MRI and CT arthrography were recorded. Pre-operative plain radiography, MRI and CT arthrography were compared with arthroscopy.

Both MRI and CT arthrography had excellent sensitivity (92% to 100%) but low to moderate specificity (15% to 77%) in identifying posteriorly-based loose bodies. Neither MRI nor CT arthrography was consistently sensitive (46% to 91%) or specific (13% to 73%) in predicting the presence or absence of loose bodies anteriorly. The overall sensitivity for the detection of loose bodies in either compartment was 88% to 100% and the specificity 20% to 70%. Pre-operative radiography had a similar sensitivity and specificity of 84% and 71%, respectively.

Our results suggest that neither CT arthrography nor MRI is reliable or accurate enough to be any more effective than plain radiography alone in patients presenting with mechanical symptoms in the elbow.