Objectives: Anatomic studies have demonstrated that bipolar glenoid and humeral bone loss have a cumulative impact on shoulder instability, and that these defects may engage in functional positions depending on their size, location, and orientation, potentially resulting in failure of stabilization procedures. Determining which lesions pose a risk for engagement remains a challenge, with arthroscopic assessment and Itoi’s 3DCT based glenoid track method being the accepted approaches at this time. The purpose of this study 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 scanning the shoulder in abduction and external rotation 2) measurement of Bankart lesion width and a novel parameter, the intact anterior articular angle (IAAA), on conventional 2D multi-plane reformats. The results of these two approaches were compared to the results obtained using Itoi’s glenoid track method for predicting engagement. Methods: Hill-Sachs and Bony Bankart defects of varying size were created in 12 cadaveric upper limbs, producing 45 bipolar defect combinations. The shoulders were assessed for engagement using cone beam CT in various positions of function, from 30 to 90 degrees of both abduction and external rotation. The humeral and glenoid defects were characterized by measurement of their size, location, and orientation. Diagnostic performance measures for predicting engagement were calculated for both the abduction external rotation scan and 2D IAAA approaches using the glenoid track method as reference standard. Results: Engagement was predicted by Itoi’s glenoid track method in 24 of 45 specimens (53%). The abduction external rotation CT scan performed at 60 degrees of glenohumeral abduction (corresponding to 90 degrees of abduction relative to the trunk) and 90 degrees of external rotation predicted engagement accurately in 43 of 45 specimens (96%), with sensitivity and specificity of 92% and 100% respectively. A logistic model based on Bankart width and IAAA provided a prediction accuracy of 89% with sensitivity and specificity of 91% and 87%. Inter-rater agreement was excellent (Kappa = 1) for classification of engagement on the abduction external rotation CT, and good (intraclass correlation = 0.73) for measurement of IAAA. Conclusion: Bipolar lesions at risk for engagement can be identified using an abduction external rotation CT scan at 60 degrees of glenohumeral abduction and 90 degrees of external rotation, or by performing 2D measurements of Bankart width and IAAA on conventional CT multi-plane reformats. This information will be useful for decision making in the setting of bipolar bone defects prior to shoulder stabilization.