Subscapularis (SSC) tendon tears: diagnostic performance and reliability of magnetic resonance arthrography (MRA) with arthroscopic correlation and comparison with clinical tests

SSR white paper: guidelines for utilization and performance of direct MR arthrography

OBJECTIVE

Direct magnetic resonance arthrography (dMRA) is often considered the most accurate imaging modality for the evaluation of intra-articular structures, but utilization and performance vary widely without consensus. The purpose of this white paper is to develop consensus recommendations on behalf of the Society of Skeletal Radiology (SSR) based on published literature and expert opinion.

MATERIALS AND METHODS

The Standards and Guidelines Committee of the SSR identified guidelines for utilization and performance of dMRA as an important topic for study and invited all SSR members with expertise and interest to volunteer for the white paper panel. This panel was tasked with determining an outline, reviewing the relevant literature, preparing a written document summarizing the issues and controversies, and providing recommendations.

RESULTS

Twelve SSR members with expertise in dMRA formed the ad hoc white paper authorship committee. The published literature on dMRA was reviewed and summarized, focusing on clinical indications, technical considerations, safety, imaging protocols, complications, controversies, and gaps in knowledge. Recommendations for the utilization and performance of dMRA in the shoulder, elbow, wrist, hip, knee, and ankle/foot regions were developed in group consensus.

CONCLUSION

Although direct MR arthrography has been previously used for a wide variety of clinical indications, the authorship panel recommends more selective application of this minimally invasive procedure. At present, direct MR arthrography remains an important procedure in the armamentarium of the musculoskeletal radiologist and is especially valuable when conventional MRI is indeterminant or results are discrepant with clinical evaluation.

Subscapularis tendon tear classification and diagnosis: A systemic review and meta-analysis

Background

In the current study, we performed a systematic review and meta-analysis regarding the comparison of accuracy, sensitivity, and specificity of the techniques in diagnosing SSC tendon tears. Also, we performed a systematic review of the classification of SSC tendon tears.

Methods

English language, peer-reviewed journal publications from the first date available to March 2022 were extracted by searching PubMed and Web of Science databases. A forest plot was used to graphically show the results of pooled sensitivity, specificity, and accuracy of different diagnostic modalities.

Results

There were six studies on using MRI to diagnose subscapularis tendon tears, five studies on MRI, four studies on clinical examination, one on ultrasonography, and one on CT arthrography. Pooled sensitivity values for MRI, MRA, clinical examination, ultrasonography, and CT arthrography were 0.71 (CI: 0.54; 0.87), 0.83 (0.77; 0.88), 0.49 (0.31; 0.67), 0.39 (0.29; 0.51), and 0.90 (0.72–0.97), respectively. The pooled specificity values for MRI, MRA, clinical examination, ultrasonography, and CT arthrography were 0.93 (CI: 0.89; 0.96), 0.86 (0.75; 0.93), 0.89 (0.73; 0.96), 0.93 (0.88; 0.96), and 0.90 (0.69; 0.98), respectively. The pooled diagnostic accuracy values for MRI, MRA, clinical examination, ultrasonography, and CT arthrography were 0.84 (CI: 0.80; 0.88), 0.85 (0.77; 0.90), 0.76 (0.66; 0.84), 0.76 (0.70; 0.81), and 0.90 (0.78; 0.96), respectively.

Conclusion

According to our systematic review and meta-analysis, MR arthrography was the most accurate in diagnosing subscapularis tears. MR arthrography was the most sensitive, and MRI and ultrasonography were the most specific in detecting subscapularis tears.

Quantitative MRI indicators and features for partial subscapularis tendon tears on conventional shoulder MRI

Background

Diagnosing partial subscapularis (SSC) tendon tears still faces challenges. A failure rate of massive posterosuperior rotator cuff tear repair will be highly increased when extending more than one-third of SSC tendon. This study aims to investigate the quantitative indicators and features of partial SSC tears on conventional shoulder MRI and improve the preoperative diagnostic accuracy.

Materials and methods

Four hundred and thirty-seven patients underwent MRI and arthroscopy were retrospectively reviewed; 89 patients with partial SSC tears in case group and 50 patients with normal SSC in control group were included. Six MRI features with the explicit definition of some quantitative indicators were evaluated.

Results

Fissure sign showed the highest diagnostic efficiency for the partial SSC tears, with a specificity of 92%, sensitivity of 75.3%, and accuracy of 81.3%. Thinning of SSC, fluid collection under the coraco-glenoid arch (CGA), and combined SSP complete tear also showed high specificity of 86%, 80%, and 80%, respectively, while the sensitivity and accuracy were moderate, with a sensitivity of 38.2%, 50.6%, and 48.3%, respectively, an accuracy of 55.4%, 61.2%, and 59.7%, respectively. The specificity, sensitivity, and accuracy of lesser tuberosity cysts were all moderate with values of 68%, 56.2%, and 60%, respectively. However, fat accumulation under the CGA showed no significant difference between the partial SSC tears group and the control group.

Conclusion

Several specific MRI features with quantitative indicators defined in this study can be used to improve the accuracy of preoperative MRI diagnosis of partial SSC tears.

[Development of a risk stratification model for subscapularis tendon tear based on patient-specific data from 528 shoulder arthroscopy]

OBJECTIVE

To identify and screen sensitive predictors associated with subscapularis (SSC) tendon tear and develop a web-based dynamic nomogram to assist clinicians in early identification and intervention of SSC tendon tear.

METHODS

Between July 2016 and December 2021, 528 consecutive cases of patients who underwent shoulder arthroscopic surgery with completely MRI and clinical data were retrospectively analyzed. Patients admitted between July 2016 and July 2019 were included in the training cohort, and patients admitted between August 2019 and December 2021 were included in the validation cohort. According to the diagnosis of arthroscopy, the patients were divided into SSC tear group and non-SSC tear group. Univariate analysis, least absolute shrinkage and selection operator (LASSO) method, and 10-fold cross-validation method were used to screen for reliable predictors highly associated with SSC tendon tear in a training set cohort, and R language was used to build a nomogram model for internal and external validation. The prediction performance of the nomogram was evaluated by concordance index (C-index) and calibration curve with 1 000 Bootstrap. Receiver operating curves were drawn to evaluate the diagnostic performance (sensitivity, specificity, predictive value, likelihood ratio) of the predictive model and MRI (based on direct signs), respectively. Decision curve analysis (DCA) was used to evaluate the clinical implications of predictive models and MRI.

RESULTS

The nomogram model showed good discrimination in predicting the risk of SSC tendon tear in patients [C-index=0.878; 95% CI(0.839, 0.918)], and the calibration curve showed that the predicted results were basically consistent with the actual results. The research identified 6 predictors highly associated with SSC tendon tears, including coracohumeral distance (oblique sagittal) reduction, effusion sign (Y-plane), subcoracoid effusion sign, biceps long head tendon displacement (dislocation/subluxation), multiple posterosuperior rotator cuff tears (≥2, supra/infraspinatus), and MRI suspected SSC tear (based on direct sign). Compared with MRI diagnosis based on direct signs of SSC tendon tear, the predictive model had superior sensitivity (80.2% vs. 57.0%), positive predictive value (53.9% vs. 53.3%), negative predictive value (92.7% vs. 86.3%), positive likelihood ratio (3.75 vs. 3.66), and negative likelihood ratio (0.25 vs. 0.51). DCA suggested that the predictive model could produce higher clinical benefit when the risk threshold probability was between 3% and 93%.

CONCLUSION

The nomogram model can reliably predict the risk of SSC tendon tear and can be used as an important tool for auxiliary diagnosis.