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Systematic review and meta-analysis of magnetic resonance imaging features for diagnosis of adhesive capsulitis of the shoulder.
Suh, Chong Hyun; Yun, Seong Jong; Jin, Wook; Lee, Sun Hwa; Park, So Young; Park, Ji Seon; Ryu, Kyung Nam.
  • Suh CH; Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea.
  • Yun SJ; Department of Radiology, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, 892 Dongnam-ro, Gangdong-gu, Seoul, 05278, Republic of Korea. zoomknight@naver.com.
  • Jin W; Department of Radiology, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, 892 Dongnam-ro, Gangdong-gu, Seoul, 05278, Republic of Korea.
  • Lee SH; Department of Emergency Medicine, Sanggye Paik Hospital, Inje University College of Medicine, 1342 Dongil-ro, Nowon-gu, Seoul, 01757, Republic of Korea.
  • Park SY; Department of Radiology, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, 892 Dongnam-ro, Gangdong-gu, Seoul, 05278, Republic of Korea.
  • Park JS; Department of Radiology, Kyung Hee University Hospital, 23, Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Republic of Korea.
  • Ryu KN; Department of Radiology, Kyung Hee University Hospital, 23, Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Republic of Korea.
Eur Radiol ; 29(2): 566-577, 2019 Feb.
Article en En | MEDLINE | ID: mdl-29978436
ABSTRACT

OBJECTIVES:

To perform a systematic review and meta-analysis to identify magnetic resonance imaging (MRI) features that will aid in the diagnosis of adhesive capsulitis of the shoulder (ACS) and provide a summary of the diagnostic accuracy of the identified features

METHODS:

The MEDLINE and EMBASE databases were searched for studies assessing the diagnostic accuracy of MRI features of ACS. Overlapping descriptors used to denote the same imaging finding in different studies were subsumed under a single feature. The pooled accuracy including the diagnostic odd ratios (DORs) with 95% confidence intervals (CIs) of the identified features was calculated using a bivariate random-effects model.

RESULTS:

In total, 15 studies were included, and 74 overlapping descriptors were subsumed under six features. All six features were found to be informative for ACS diagnosis [coracohumeral ligament thickening DOR, 13; 95% CI, 6-29; fat obliteration of the rotator interval (RI) DOR, 8; 95% CI, 3-24; RI enhancement DOR, 44; 95% CI, 14-141; axillary joint capsule enhancement DOR, 52; 95% CI, 27-98; inferior glenohumeral ligament (IGHL) hyperintensity DOR, 31; 95% CI, 8-115; IGHL thickening DOR, 28; 95% CI, 11-70]. The sensitivity and specificity of enhancement of the RI and axillary joint capsule and IGHL hyperintensity were > 80%.

CONCLUSIONS:

Six informative MRI features for ACS diagnosis were identified in this study with RI and axillary joint capsule enhancement and IGHL hyperintensity showing the highest diagnostic accuracy. Informative features observed on non-arthrogram MRI can be as helpful as features observed on direct magnetic resonance arthrography for ACS diagnosis. KEY POINTS • Six informative MRI features for ACS diagnosis were identified (diagnostic odds ratio > 1). • RI and axillary joint capsule enhancement and IGHL hyperintensity showed high sensitivities/specificities (> 80%). • The use of non-arthrogram MRI is recommended for ACS diagnosis.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Bursitis Tipo de estudio: Diagnostic_studies / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Año: 2019 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Bursitis Tipo de estudio: Diagnostic_studies / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Año: 2019 Tipo del documento: Article