Articular cartilage and labral lesions of the glenohumeral joint: diagnostic performance of 3D water-excitation true FISP MR arthrography

Autor: Dietrich, Tobias, Zanetti, Marco, Saupe, Nadja, Pfirrmann, Christian, Fucentese, Sandro, Hodler, Juerg
Jazyk: angličtina
Rok vydání: 2018
Popis: Objective: To evaluate the diagnostic performance of MR arthrography in the detection of articular cartilage and labral lesions of the glenohumeral joint using a transverse 3D water-excitation true fast imaging with steady-state precession (FISP) sequence. Materials and Methods: Seventy-five shoulders were included retrospectively. Shoulder arthroscopy was performed within 6months of MR arthrography. MR images were evaluated separately by two radiologists. They were blinded to clinical and arthroscopic information. Arthroscopy served as the reference standard. Results: For the detection of humeral cartilage lesions, sensitivities and specificities were 86% (12/14)/89% (50/56) for observer 1 and 93%/86% for observer 2) for the transverse true FISP sequence and 64%/86% (50%/82% for observer 2) for the coronal intermediate-weighted spin-echo images. The corresponding values for the glenoidal cartilage were 60% (6/10)/88% (51/58) (80%/76% for observer 2) and 70%/86% (60%/74% for observer 2) respectively. For the detection of abnormalities of the anterior labrum (only assessed on true FISP images) the values were 94% (15/16)/84% (36/43) (88%/79% for observer 2). The corresponding values for the posterior labrum were 67% (8/12)/77% (36/47) (observer 2: 25%/74%). The kappa values for the grading of the humeral and glenoidal cartilage lesions were 0.81 and 0.55 for true FISP images compared with 0.49 and 0.43 for intermediate-weighted fast spin-echo images. Kappa values for true FISP evaluation of the anterior and posterior part of the labrum were 0.81 and 0.70. Conclusion: Transverse 3D true FISP MR arthrography images are useful for the difficult diagnosis of glenohumeral cartilage lesions and suitable for detecting labral abnormalities
Databáze: OpenAIRE