INTRODUCTION: The purpose of this study was to determine the most accurate imaging modality to quantify glenoid bone loss in recurrent anterior shoulder instability. This will allow the best preoperative prediction for patients needing a bone graft. MATERIALS AND METHODS: Seven fresh frozen shoulder cadavers were imaged with radiographs, magnetic resonance imaging (MRI), computed tomography (CT), and 3-dimensional CT (3-D CT). Native shoulders were imaged, and 3 sequential anterior-inferior glenoid defects were created, measured, and reimaged. Defect sizes were <12.5%, 12.5% to 27%, and >27%. Four blinded evaluators (2 musculoskeletal radiologists, 2 shoulder fellowship-trained surgeons) reviewed the 112 image sets and estimated the percentage of glenoid bone loss. Images were scrambled and re-reviewed by the same observers 2 months later to determine intraobserver reliability. RESULTS: Pearson correlation coefficients between predicted vs true bone loss across all 4 raters were 0.875 (3-D CT), 0.831 (CT), 0.693 (MRI), and 0.457 (x-ray imaging). Prediction errors (PE) were (mean ± SD in percentages) 3-D CT (-3.3 ± -6.6), CT (-3.7 ± -8.0), MRI (-2.75 ± -10.6), and x-ray images (-6.9 ± -13.1). Mean PE values were not significantly different among 3-D CT, CT, and MRI; however, the PE SDs were similar among the 4 evaluators for 3-D CT and lower than all other imaging techniques. Prediction based on x-ray images had the largest PE and SD. Covariance parameters revealed large variances for shoulders for MRI and x-ray imaging. The intraobserver intraclass correlation coefficients were 0.947 (3-D CT), 0.927 (CT), 0.837 (MRI), and 0.726 (x-ray image). CONCLUSIONS: The most accurate imaging modality in predicting glenoid bone loss among the 4 blinded independent evaluators was 3-D CT.
INTRODUCTION: The purpose of this study was to determine the most accurate imaging modality to quantify glenoid bone loss in recurrent anterior shoulder instability. This will allow the best preoperative prediction for patients needing a bone graft. MATERIALS AND METHODS: Seven fresh frozen shoulder cadavers were imaged with radiographs, magnetic resonance imaging (MRI), computed tomography (CT), and 3-dimensional CT (3-D CT). Native shoulders were imaged, and 3 sequential anterior-inferior glenoid defects were created, measured, and reimaged. Defect sizes were <12.5%, 12.5% to 27%, and >27%. Four blinded evaluators (2 musculoskeletal radiologists, 2 shoulder fellowship-trained surgeons) reviewed the 112 image sets and estimated the percentage of glenoid bone loss. Images were scrambled and re-reviewed by the same observers 2 months later to determine intraobserver reliability. RESULTS: Pearson correlation coefficients between predicted vs true bone loss across all 4 raters were 0.875 (3-D CT), 0.831 (CT), 0.693 (MRI), and 0.457 (x-ray imaging). Prediction errors (PE) were (mean ± SD in percentages) 3-D CT (-3.3 ± -6.6), CT (-3.7 ± -8.0), MRI (-2.75 ± -10.6), and x-ray images (-6.9 ± -13.1). Mean PE values were not significantly different among 3-D CT, CT, and MRI; however, the PE SDs were similar among the 4 evaluators for 3-D CT and lower than all other imaging techniques. Prediction based on x-ray images had the largest PE and SD. Covariance parameters revealed large variances for shoulders for MRI and x-ray imaging. The intraobserver intraclass correlation coefficients were 0.947 (3-D CT), 0.927 (CT), 0.837 (MRI), and 0.726 (x-ray image). CONCLUSIONS: The most accurate imaging modality in predicting glenoid bone loss among the 4 blinded independent evaluators was 3-D CT.
Authors: Kevin J McHale; George Sanchez; Kyle P Lavery; William H Rossy; Anthony Sanchez; Marcio B Ferrari; Matthew T Provencher Journal: Arthrosc Tech Date: 2017-06-19
Authors: Anna Maria Kubicka; Jakub Stefaniak; Przemysław Lubiatowski; Jan Długosz; Marcin Dzianach; Marcin Redman; Janusz Piontek; Leszek Romanowski Journal: Int Orthop Date: 2016-08-05 Impact factor: 3.075
Authors: Joel Locher; Umile Giuseppe Longo; Francesco Pirato; Roman Susdorf; Heath B Henninger; Thomas Suter Journal: Arch Orthop Trauma Surg Date: 2021-07-05 Impact factor: 3.067