Biceps Pulley Lesions: Diagnostic Accuracy of Nonarthrographic Shoulder MRI and the Value of Various Diagnostic Signs.

BACKGROUND: There is limited data in the literature regarding the role of nonarthrographic MRI for detecting biceps pulley (BP) lesions. PURPOSE: To assess the accuracy of nonarthrographic MRI for detecting BP lesions, and to evaluate the diagnostic value of various MRI signs (superior glenohumeral ligament discontinuity/nonvisibility, long head of biceps (LHB) displacement sign or subluxation/dislocation, LHB tendinopathy, and supraspinatus and subscapularis tendon lesions) in detecting such lesions. STUDY TYPE: Retrospective. POPULATION: 84 patients (32 in BP-lesion group and 52 in BP-intact group-as confirmed by arthroscopy). FIELD STRENGTH/SEQUENCE: 1.5-T, T1-weighted turbo spin echo (TSE), T2-weighted TSE, and proton density-weighted TSE spectral attenuated inversion recovery (SPAIR) sequences. ASSESSMENT: Three radiologists independently reviewed all MRI data for the presence of BP lesions and various MRI signs. The MRI signs and final MRI diagnoses were tested for accuracy regarding detecting BP lesions using arthroscopy results as the reference standard. Furthermore, the inter-reader agreement (IRA) between radiologists was determined. STATISTICAL TESTS: Student's t-tests, Chi-squared, and Fisher's exact tests, and 4-fold table test were used. The IRA was calculated using Kappa statistics. A P-value <0.05 was considered statistically significant. RESULTS: The sensitivity, specificity, and accuracy of nonarthrographic MRI for detecting BP lesions were 65.6%-78.1%, 90.4%-92.3%, and 81%-86.9%, respectively. The highest accuracy was noticed for the LHB displacement sign (84.5%-86.9%), and the highest sensitivity was registered for the LHB tendinopathy sign (87.5%). Furthermore, the highest specificity was observed for the LHB displacement sign and LHB subluxation/dislocation sign (98.1%-100%). The IRA regarding final MRI diagnosis and MRI signs of BP lesions was good to very good (κ = 0.76-0.98). DATA CONCLUSION: Nonarthrographic shoulder MRI may show good diagnostic accuracy for detecting BP lesions. The LHB displacement sign could serve as the most accurate and specific sign for diagnosis of BP lesions. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

MRI-Based Classification for Tibial Spine Fracture: Detection Efficacy, Classification Accuracy, and Reliability.

RATIONALE AND OBJECTIVES: Recently, a new MRI-based classification for evaluating tibial spine fractures (TSFs) was developed to aid in treating these injuries. Our objective was to assess the detection efficacy, classification accuracy, and reliability of this classification in detecting and grading TSFs, as well as its impact on treatment strategy, compared to the Meyers and McKeever (MM) classification. MATERIALS AND METHODS: A retrospective study included 68 patients with arthroscopically confirmed TSFs. All patients had plain radiography and conventional MRI of the affected knee before arthroscopy. Three experienced radiologists independently reviewed all plain radiographs and MRI data and graded each patient according to MM and MRI-based classifications. The detection efficacy, classification accuracy, and inter-rater agreement of both classifications were evaluated and compared, using arthroscopic findings as the gold standard. RESULTS: The final analysis included 68 affected knees. Compared to the MM classification, the MRI-based classification produced 22.0% upgrade of TSFs and 11.8% downgrade of TSFs. According to the reviewers, the fracture classification accuracy of the MRI-based classification (91.2-95.6%) was significantly higher than that of the MM classification (73.5-76.5%, p = 0.002-0.01). The fracture detection rate of MRI-based classification (94.1-98.5%) was non-significantly higher than that of the MM classification (83.8-89.7%, p = 0.07-0.4). The soft tissue injury detection accuracy for MRI-based classification was 91.2-94.1%. The inter-rater reliability for grading TSFs was substantial for both the MM classification (κ = 0.69) and MRI-based classification (κ = 0.79). CONCLUSION: MRI-based classification demonstrates greater accuracy and reliability compared to MM classification for detecting and grading TSFs and associated soft tissue injuries.