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1 iautomated segmented 3D MRI models to assess glenohumeral anatomy, glenoid bone loss (GBL), and their
3 opposite direction to that of the center of glenohumeral contact area during external rotation to in
5 ase in anterior translation of the center of glenohumeral contact area was associated with the increa
6 ranslation of the center of humeral head and glenohumeral contact area were associated with the incre
7 ate the glenohumeral contact area, center of glenohumeral contact area, and center of humeral head du
9 The purpose of this study is to evaluate the glenohumeral contact area, center of glenohumeral contac
10 The glenohumeral contact area, center of glenohumeral contact area, center of humeral head, and o
12 of shoulder pain, variability in mechanics, glenohumeral internal rotation deficit, and accordance w
15 he software for bone surface modeling of the glenohumeral joint enabled quantitative assessment of gl
16 inflammatory arthritis, frozen shoulder, or glenohumeral joint instability), received corticosteroid
18 profiling of a bolus administration into the glenohumeral joint space reveals the brief systemic and
19 ommon injury sites include the rotator cuff, glenohumeral joint, acromioclavicular joint, biceps tend
20 one is posterior to the coronal plane of the glenohumeral joint, and with the contraction of this two
21 ewed arthrograms and in consensus classified glenohumeral joints in one of four categories: concentri
22 gliding occurs at the acromion-clavicle and glenohumeral joints, is different from and convergent to
25 ic glenohumeral joints; seven children, flat glenohumeral joints; 19 children, biconcave glenoid; and
27 nvisibility or discontinuity of the superior glenohumeral ligament (SGHL), presence of biceps tendino
28 best position for evaluation of the inferior glenohumeral ligament and anterior capsular attachment.
29 otation imaging best delineated the inferior glenohumeral ligament but did not improve assessment of
30 mprove assessment of the superior and middle glenohumeral ligaments in comparison with findings in ne
31 rly delineates the biceps-labral complex and glenohumeral ligaments, external rotation of the shoulde
32 ral joint enabled quantitative assessment of glenohumeral micromotion and be used for kinematic evalu
33 from May 2014 to April 2019 to create 3D MRI glenohumeral models by transfer learning using Dixon-bas
34 tic subjects to establish normal patterns of glenohumeral motion during abduction and adduction and i
35 These preliminary measurements of normal glenohumeral motion patterns begin to establish normal r
37 e of procedure, from 0.6% (0.5% to 0.8%) for glenohumeral stabilisation to 1.7% (1.5% to 1.8%) for fr
38 t risk, ranging from 2.7% (2.5% to 3.0%) for glenohumeral stabilisation to 5.7% (5.4% to 6.1%) for fr
39 ff repair, acromioclavicular joint excision, glenohumeral stabilisation, and frozen shoulder release.