A predictive model for the critical shoulder angle based on a three-dimensional analysis of scapular angular and...

Area of Science:

• Orthopedic surgery
• Biomechanical analysis
• Radiographic assessment

Background:

• The critical shoulder angle (CSA) is crucial for shoulder biomechanics.
• Understanding scapular morphology's influence on CSA is vital for diagnosing and treating shoulder pathologies.
• Current models may not fully capture the complex interplay of scapular features affecting CSA.

Purpose of the Study:

• To identify specific scapular morphological features associated with variations in CSA.
• To develop a predictive model for CSA using 3D scapular assessments.
• To explore multiple potential explanatory variables for CSA prediction.

Main Methods:

• 3D reconstruction of scapular meshes from CT DICOM data.
• Analysis of 17 angular, linear, and area measurements of scapular morphology.
• Application of Pearson's correlation and multivariable linear regression with cross-validation for model development.

Main Results:

• Glenoid inclination (GI) and coronal plane angulation of the acromion (CPAA) showed the strongest correlation with CSA.
• The optimal predictive model for CSA incorporated 10 variables, including glenoid, scapular spine, and acromial factors.
• CPAA and GI were identified as the most influential factors in CSA prediction.

Conclusions:

• Scapular morphology's relationship with CSA is complex, involving multiple factors beyond GI and acromial offset.
• CPAA and GI are the most significant contributors to CSA variation.
• Further research in specific patient cohorts, like those with rotator cuff tears, is needed to inform clinical applications.