ABSTRACT
BACKGROUND: To improve implant survival after reverse shoulder arthroplasty (RSA), surgeons need to maximize screw fixation. However, bone density variation and distribution within the scapula are not well understood as they relate to RSA. The three columns of bone in the scapula surrounding the glenoid fossa are the lateral border, the base of the coracoid process, and the spine of the scapula. In our previous study by Daalder et al on cadaveric specimens, the coracoid column was significantly less dense than the lateral border and spine. This study's objective was to verify whether these results are consistent with computer tomography (CT) scan information from patients undergoing RSA. METHODS: Two-dimensional axial CT images from twelve patients were segmented, and a three-dimensional digital model of the scapula was subsequently created using Mimics 17.0 Materialise Software (Leuven, Belgium). Hounsfield unit (HU) values representing cortical bone were filtered out to determine the distributions of trabecular bone density. An analysis of variance with post hoc Bonferroni tests determined the differences in bone density between the columns of bone in the scapula. RESULTS: The coracoid superolateral (270 ± 45.6 HU) to the suprascapular notch was significantly less dense than the inferior (356 ± 63.6 HU, P = .03, ds = 1.54) and anterosuperior portion of the lateral border (353 ± 68.9 HU, P = .04, ds = 1.42) and the posterior (368 ± 70 HU, P = .007, ds = 1.65) and anterior spine (370 ± 78.9 HU, P = .006, ds = 1.54). DISCUSSION/CONCLUSION: The higher-density bone in the spine and lateral border compared with the coracoid region may provide better bone purchase for screws when fixing the glenoid baseplate in RSA. This is in agreement with our previous study and indicates that the previous cadaveric results are applicable to clinical CT scan data. When these studies are taken together, they provide robust evidence for clinical applications, including having surgeons aim screws for higher-density regions to increase screw fixation, which may decrease micromotion and improve implant longevity.
ABSTRACT
PURPOSE: Osteophytes are common radiographic markers of osteoarthritis. However, they are not accurately depicted using conventional imaging, thus hampering surgical interventions that rely on pre-operative images. Studies have shown that ultrasound (US) is promising at detecting osteophytes and monitoring the progression of osteoarthritis. Furthermore, three-dimensional (3D) ultrasound reconstructions may offer a means to quantify osteophytes. The purpose of this study was to compare the accuracy of osteophyte depiction in the knee joint between 3D US and conventional computed tomography (CT). METHODS: Eleven human cadaveric knees were pre-screened for the presence of osteophytes. Three osteoarthritic knees were selected, and then, 3D US and CT images were obtained, segmented, and digitally reconstructed in 3D. After dissection, high-resolution structured light scanner (SLS) images of the joint surfaces were obtained. Surface matching and root mean square (RMS) error analyses of surface distances were performed to assess the accuracy of each modality in capturing osteophytes. The RMS errors were compared between 3D US, CT and SLS models. RESULTS: Average RMS error comparisons for 3D US versus SLS and CT versus SLS models were 0.87 mm ± 0.33 mm (average ± standard deviation) and 0.95 mm ± 0.32 mm, respectively. No statistical difference was found between 3D US and CT. Comparative observations of imaging modalities suggested that 3D US better depicted osteophytes with cartilage and fibrocartilage tissue characteristics compared to CT. CONCLUSION: Using 3D US can improve the depiction of osteophytes with a cartilaginous portion compared to CT. It can also provide useful information about the presence and extent of osteophytes. Whilst algorithm improvements for automatic segmentation and registration of US are needed to provide a more robust investigation of osteophyte depiction accuracy, this investigation puts forward the potential application for 3D US in routine diagnostic evaluations and pre-operative planning of osteoarthritis.
