Diagnosis of Engaging Bipolar Bone Defects in the Shoulder Using 2-Dimensional Computed Tomography

Abstract

Background: Anatomic studies have demonstrated that bipolar glenoid and humeral bone loss have a cumulative effect on shoulder instability and that these defects may engage in functional positions depending on their size and location, potentially resulting in failure of stabilization procedures. Determining which lesions pose a risk for engagement remains challenging, with arthroscopic assessments and a 3-dimensional computed tomography (CT)–based glenoid track method being accepted approaches at this time. Purpose: The purpose was to investigate the interaction of humeral and glenoid bone defects on shoulder engagement in a cadaveric model. Two alternative approaches to predicting engagement were evaluated: (1) CT of the shoulder in abduction and external rotation (ABER) and (2) measurement of the glenoid lesion width and measurement of a novel parameter, the intact anterior articular angle (IAAA), on conventional 2-dimensional multiplane reformats. Study Design: Controlled laboratory study. Methods: Hill-Sachs and glenoid defects of varying sizes were created in 12 cadaveric upper limbs, producing 45 bipolar defect combinations. The defect characteristics were assessed using CT with the shoulder in a neutral position. ABER CT was performed with the shoulder positioned in 60° of glenohumeral abduction (corresponding to 90° of abduction relative to the trunk) and 90° of external rotation. The IAAA was measured as the cartilage arc angle anterior to the Hill-Sachs defect on the axial slice bisecting the humeral head. The performance of the ABER CT and IAAA approaches to predicting engagement were compared with the glenoid track method. Results: Of the 45 defect combinations, 24 (53%) were classified as engaging using the glenoid track method. ABER CT predicted engagement accurately in 43 of 45 (96%), with a sensitivity and specificity of 92% and 100%, respectively. A logistic model based on the glenoid defect width and IAAA provided a prediction accuracy of 87%, with a sensitivity and specificity of 92% and 81%, respectively. Conclusion/Clinical Relevance: Bipolar lesions at risk for engagement can be identified accurately using an ABER CT scan or by performing 2-dimensional measurements of the glenoid defect width and IAAA on conventional CT multiplane reformats. This information will be useful for surgical planning in the setting of bipolar bone defects before shoulder stabilization.