Assessment of shoulder joint derangements with magnetic resonance imaging in adult Nigerians

利用磁共振成像评估尼日利亚成年人的肩关节紊乱

阅读:1

Abstract

OBJECTIVES: Shoulder pain secondary to various aetiologies is a common musculoskeletal complaint worldwide, and Magnetic Resonance Imaging (MRI) is the most accurate imaging method for evaluating shoulder pain in all age groups. While the patterns of shoulder MRI abnormalities in various demographics have been reported, data on sub-Sahara African populations are still sparse. This study aims to describe the imaging features and spectrum of shoulder joint pathologies on MRI in adult Nigerians. MATERIALS AND METHODS: This was a retrospective review of the shoulder MRI of 100 adult Nigerians (with and without trauma) from September 2020 to December 2021. Their clinical data and shoulder MRI findings were extracted and analysed. Statistical significance was set at P ≤ 0.05. RESULTS: There were 64 males and 36 females aged 18-82 years. Right shoulder MRI was done in 53 subjects (53%), while the left shoulder was studied in 47 (47%). Supraspinatus tendinopathy (73%), acromioclavicular joint arthropathy (68%), and subacromial-subdeltoid (SASD) bursitis (64%) were the most frequently detected pathologies. Other demonstrated derangements include glenohumeral joint effusion (24%), long head of biceps tendon sheath effusion (18%), labral abnormalities (16%), subcoracoid bursitis (4%), Hill Sach's deformity (3%), anterior glenohumeral dislocation (2%), fatty degeneration of the supraspinatus/infraspinatus muscles (2%), adhesive capsulitis (1%), and other bony abnormalities (contusion, erosion, subchondral cysts). There was no significant difference in the frequency of shoulder abnormalities between the male and female subjects. CONCLUSION: Acromioclavicular joint arthropathy, SASD bursitis, and rotator cuff disorders were the dominant pathologies in the participants' shoulders.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。