Assessment of Posterosuperior Rotator Cuff tear risk based on shoulder CT-A Novel Scoring System

Background Rotator cuff tear (RCT) is a primary cause of shoulder pain and a leading source of shoulder disability in later stages. Although various computed tomography (CT) based measurements of the shoulder have been identified as predictors for RCT, we hypothesize that a combination of predictors will provide superior diagnostic and predictive performance compared to individual predictors. Thus, the aims of this study are: (i) to integrate various shoulder CT-based measurement parameters for predicting rotator cuff tears, and (ii) to develop a scoring system based on these predictors for estimating the likelihood of posterosuperior rotator cuff tears ( RCT-PT). (iii) To provide a diagnostic basis and predict the risk of posterosuperior rotator cuff tears for patients with contraindications to magnetic resonance imaging(MRI), an inability to cooperate with or complete the examination, or for whom MRI is deemed unnecessary. Methods This retrospective study analyzed 326 cases who underwent both shoulder CT and MRI examinations at our hospital. Based on the shoulder MRI findings, patients were stratified into two groups: a rotator cuff tear group and a control group. The selected predictors included the Critical Shoulder Angle (CSA), Acromial Index (AI), Goutallier grade of fatty infiltration, Supraspinatus Occupation Ratio, the Hounsfield Unit (HU) ratio of the deltoid to supraspinatus muscle, and other variables such as gender, age, symptom duration, and BMI. These factors were analyzed using univariate and multivariate analyses. The factors identified in the multivariate analysis were subsequently integrated into a scoring system based on their odds ratios (OR). Results Multivariate analysis identified the following independent risk factors: age (p < 0.01, OR = 1.090), fatty infiltration grade (p = 0.047, OR = 2.252), symptom duration (p = 0.012, OR = 1.036), critical shoulder angle (p = 0.028, OR = 1.175), and acromial index (p = 0.034, OR = 1.068). A 7-point scoring system was subsequently developed. Based on the weighting derived from the multivariate analysis odds ratios, one point each was assigned to age, symptom duration, supraspinatus occupation ratio, critical shoulder angle, and acromial index, while two points were assigned to the fatty infiltration grade. A score of 4 points was established as the threshold for predicting posterosuperior rotator cuff tears, yielding a sensitivity of 0.866 and a specificity of 0.904. Conclusion The developed numerical score, which integrates shoulder CT measurements with clinical factors, serves as a practical tool for predicting rotator cuff tears. It facilitates risk assessment based on CT findings and overcomes the limitation of MRI contraindication by providing a reliable predictive alternative for such cases.