Introduction. Osteoarthritis of the glenohumeral joint leads to global degeneration of the shoulder and often results in humeral or glenoid osteophytes. It is established that the axillary neurovascular bundle is in close proximity to the glenohumeral capsule. Similar to other compressive neuropathies, osteophytic impingement of the axillary nerve could result in axillary nerve symptoms. The purpose of this study was to compare the proximity of the axillary neurovascular bundle to the inferior humerus in shoulders to determine distance of the neurovascular bundle as the osteophyte (goat's beard) of
The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular fracture involvement, on plain radiographs. The CNN was trained and tested on radiographs sourced from 11 hospitals in Australia and externally validated on radiographs from the Netherlands. Each radiograph was paired with corresponding CT scans to serve as the reference standard based on dual independent evaluation by trained researchers and attending orthopaedic surgeons. Presence of a fracture, classification (non- to minimally displaced; two-part, multipart, and glenohumeral dislocation), and four characteristics were determined on 2D and 3D CT scans and subsequently allocated to each series of radiographs. Fracture characteristics included greater tuberosity displacement ≥ 1 cm, NSA ≤ 100°, shaft translation (0% to < 75%, 75% to 95%, > 95%), and the extent of articular involvement (0% to < 15%, 15% to 35%, or > 35%).Aims
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