Figure - available from: BMC Musculoskeletal Disorders
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Measuring the critical shoulder angle (CSA) in anteroposterior view. The angle by a line connecting the inferior tip and the superior tip of the glenoid and another line connecting the inferior tip of the glenoid and the most lateral margin of the acromion was measured as the CSA
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Background:
Morphological markers presenting the lateral extension of acromion and the greater tuberosity of humerus were proposed to diagnose and predict rotator cuff tears (RCTs) in recent years, but few studies have addressed the combined performance when using two predictors together. As a presence of a RCT may be associated with the impingeme...
Citations
... In their study, Qi et al. were able to show that the use of a combination of predictors is better suited for predicting rotator cuff tears than the use of a single parameter alone. Therefore, further sonographically determinable predictors should be identified in subsequent studies in order to achieve the advantages of radiation-free examination with the higher accuracy of combining several measurement methods to predict damage in the rotator cuff [26]. ...
Background: An increased or decreased critical shoulder angle (CSA) is a known risk factor for osteoarthritis, lesions, and re-ruptures in the rotator cuff. A CSA greater than 35◦ correlates with degenerative rotator cuff tears, while a CSA of less than 30◦ correlates with osteoarthritis in the glenohumeral joint. The diagnostic gold standard for its determination is X-ray or MRI. Objectives: The primary objective of this research was to assess the viability of utilizing sonography imaging as a diagnostic tool to determine the modified critical shoulder angle (mCSA). This study aimed to investigate the feasibility and effectiveness of sonographic techniques in accurately diagnosing CSA compared to MRI. Study Design and Methods: A cohort study was carried out (level of evidence 3). The CSA (MRI) and the mCSA (ultrasound) were assessed retrospectively by two independent board- certified investigators in 109 patients with shoulder pain by MRI and musculoskeletal sonography. The CSA in the MRI dataset was determined using routine protocols and then compared to the values assessed using the modified sonography-assisted method (mCSA). Both results were analyzed with linear regression to determine a possible correlation. All investigations were performed by a DEGUM (German Society for Medical Ultrasound)-certified specialist in musculoskeletal sonography. Results: A total of 112 patients were included in this study, namely 40 female patients and 72 male patients with a mean age of 54.7 years at the time of the investigation. The mean CSA in MRI was 31.5◦ ± 3.899, and the mCSA in sonography was 30.1◦ ± 4.753. The inter- and intraobserver reliability for the CSA was factual with values of 0.993 and 0.967. The inter- and intraobserver reliability for mCSA was factual as well, with values of 0.989 and 0.948. The ANOVA analysis did not reveal a significant difference between the CSA and the mCSA values, and linear regression determined the R2 value to be 0.358 with p < 0.05. Conclusions: Diagnosing the mCSA using sonography is a safe and valid method. No statistically significant differences between the results in MRI and sonography could be seen. Although this is a retrospective, single-center study including only Caucasian mid-Europeans, and with the known limitations of ultrasound imaging, it nevertheless shows that sonography can be used as a simple, cheap, and fast technique to assess a modified CSA, which shows very good correlation with the standard CSA without losing the diagnostic quality.
Background and PPPM-related working hypothesisIn the diagnosis of incomplete rotator cuff injuries (IRCI), magnetic resonance imaging (MRI) and ultrasound examination often have false-positive and false-negative results, while arthroscopy is expensive, invasive, and complex. From the strategy of predictive, preventive, and personalized medicine (PPPM), shoulder anatomical characteristics based on MRI have been demonstrated to accurately predict IRCI and their clinical applicability for personalized prediction of IRCI.AimsThis study aimed to develop and validate a nomogram based on anatomical features of the shoulder on MRI to identify IRCI for PPPM healthcare strategies.Methods
The medical information of 257 patients undergoing preoperative MRI examination was retrospectively reviewed and served as the primary cohort. Partial-thickness rotator cuff tears (RCTs) and tendinopathy observed under arthroscopy were considered IRCI. Using logistic regression analyses and least absolute shrinkage and selection operator (LASSO), IRCI was identified among various preoperative factors containing shoulder MRI and clinical features. A nomogram was constructed and subjected to internal and external validations (80 patients).ResultsThe following eight independent risk factors for IRCI were identified:
Age
The left injured sides
The Goutallier classification of supraspinatus in oblique coronal position
The Goutallier classification of supraspinatus in the axial position
Acromial thickness
Acromiohumeral distance
Coracohumeral distance
Abnormal acromioclavicular joint signals
The nomogram accurately predicted IRCI in the development (C-index, 0.932 (95% CI, 0.891, 0.973)) and validation (C-index, 0.955 (95% CI, 0.918, 0.992)) cohorts. The calibration curve was consistent between the predicted IRCI probability and the actual IRCI ratio of the nomogram. The decision curve analysis and clinical impact curves demonstrated that the model had high clinical applicability.Conclusions
Eight independent factors that accurately predicted IRCI were determined using MRI anatomical findings. These personalized factors can prevent unnecessary diagnostic interventions (e.g., arthroscopy) and can assist surgeons in implementing individualized clinical decisions in medical practice, thus addressing the goals of PPPM.
