Validation of CLASS MRI for personalized ACL footprints identification

Area of Science:

• Orthopedic Surgery
• Radiology
• Biomedical Engineering

Background:

• Anatomical reconstruction is key in anterior cruciate ligament (ACL) surgery for restoring knee kinematics.
• Optimal positioning of ACL footprints (FPs) remains challenging, particularly in revision surgeries.
• A novel MRI sequence, CLASS, offers potential for improved FP localization.

Purpose of the Study:

• To validate the reliability and reproducibility of the CLASS MRI sequence for localizing ACL FPs.
• To compare ACL FP identification using CLASS with existing methods.

Main Methods:

• The CLASS algorithm was applied to MRI scans of uninjured knees.
• ACL FPs were identified by a radiologist and an orthopedic knee surgeon.
• Intraobserver reliability and interobserver reproducibility were assessed.

Main Results:

• The CLASS sequence demonstrated 'almost perfect' reliability and reproducibility in identifying ACL FPs.
• Measurements showed high consistency, with some significant variations compared to literature.
• Variations in deep-shallow and high-low FP positions were noted.

Conclusions:

• The CLASS MRI sequence is a reliable and reproducible tool for identifying ACL FPs.
• The study underscores the importance of patient-specific surgical strategies due to observed FP variability.