ArticleOrthopaedic journal of sports medicine2026
Magnetic Resonance Imaging of Radiohumeral Synovial Plica: Prognostic Implications for Nonoperative Management in Lateral Epicondylitis.
Article in Orthopaedic journal of sports medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The role of magnetic resonance imaging (MRI) in the treatment protocol of lateral epicondylitis is controversial. Purpose: To explore the relationship between the radiohumeral synovial plica (RHSP) and surrounding anatomic landmarks through cadaveric studies, perform a precise and detailed morphometric parametric analysis of RHSP using MRI in patients with lateral epicondylitis, and assess the predictive power of RHSP syndrome on the failure of nonoperative treatment. Study Design: Cross-sectional study; Level of evidence, 3. Methods: There were a total of 8 elbow specimens in this study. The MRI findings were compared with those in anatomic sections and histological preparations. A total of 459 patients with lateral epicondylitis from 3 hospitals were included and divided into a nonoperative treatment failure group (n = 138) and a nonoperative treatment success group (n = 321). The prognostic prediction model for nonoperative treatment was developed using the logistic regression method. Model 1 was based on logistic regression results, and model 2 was model 1 with the parameter of RHSP syndrome removed. Results: The RHSP is contiguous with the radiohumeral articular capsule and subtly mingles with the lateral collateral ligament (LCL) complex and common extensor tendon (CET), forming an enthesis. Furthermore, the authors found that patients in the nonoperative treatment failure group had greater RHSP dimensions and a higher prevalence of RHSP syndrome (all Conclusion: The authors developed a model to predict the failure of nonoperative treatment in patients with lateral epicondylitis. Additionally, RHSP syndrome significantly improves the model's predictive capacity.
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