Osteophytes are bony spurs on normal bone that develop as an adaptive reparative process due to excessive stress at/near a joint. As osteophytes develop from normal bone, they are not always well depicted in common imaging techniques (e.g. CT, MRI). This creates a challenge for preoperative planning and image-guided surgical methods that are commonly incorporated in the clinical routine of orthopaedic surgery.

The study examined the accuracy of osteophyte detection in clinical CT and MRI scans of varying types of joints.

The investigation was performed on fresh-frozen ex-vivo human resected joints identified as having a high potential for presentation of osteophytes. The specimens underwent varying imaging protocols for CT scanning and clinical protocols for MRI. After dissection of the joint, the specimens were subjected to structured 3D light scanning to establish a reference model of the anatomy. Scans from the imaging protocols were segmented and their 3D models were co-registered to the light scanner models. The quality of the osteophyte images were evaluated by determining the Root Mean Square (RMS) error between the segmented osteophyte models and the light scan model.

The mean RMS errors for CT and MRI scanning were 1.169mm and 1.419mm, respectively. Comparing the different CT parameters, significance was achieved with scanning at 120kVp and 1.25mm slice thickness to depict osteophytes; significance was also apparent at a lower voltage (100kVp).

Preliminary results demonstrate that osteophyte detection may be dependent on the degree of calcification of the osteophyte. They also illustrate that while some imaging parameters were more favourable than others, a more accurate osteophyte depiction may result from the combination of both MRI and CT scanning.