Predicting normal glenoid version from the pathologic scapula: a comparison of 4 methods in 2- and 3-dimensional...

Area of Science:

• Orthopedic surgery
• Biomechanical engineering
• Radiology

Background:

• Pathologic glenoid retroversion complicates total shoulder arthroplasty by affecting mechanics and component wear.
• Accurate correction is challenging due to the variability of normal glenoid version.
• Predicting native glenoid version is crucial for successful surgical outcomes.

Purpose of the Study:

• To develop and validate methods for predicting native glenoid version in shoulders with pathologic retroversion.
• To establish conserved relationships between anatomical landmarks and glenoid version.
• To aid preoperative planning and intraoperative decision-making in total shoulder arthroplasty.

Main Methods:

• Utilized 3-D CT scans to measure anterior glenoid wall angle (AGWA) and Resch angle (RA) in osteologic and patient scapulae.
• Developed linear regression equations and a computer-generated vault model to predict native glenoid version.
• Validated predictions against contralateral nonpathologic shoulders.

Main Results:

• Linear regression equations based on AGWA and RA accurately predicted native glenoid version.
• A computer-generated glenoid vault model also demonstrated high accuracy in predicting native version.
• The developed methods showed reliable prediction of nonpathologic glenoid version.

Conclusions:

• 3-D CT-based measurements and predictive models can accurately determine native glenoid version from pathologic shoulders.
• These tools can assist surgeons in planning and executing corrections for pathologic glenoid retroversion.
• Improved preoperative planning may lead to better glenohumeral mechanics and reduced component wear post-arthroplasty.