Three-dimensional-based native alignment phenotype classification system: Description for use in planning for...

Area of Science:

• Orthopedic Surgery
• Radiology
• Biomedical Engineering

Background:

• Traditional total knee arthroplasty (TKA) planning relies on 2D radiographs, which may lack detailed anatomical information.
• Limitations in pre-operative imaging can impact the precision of TKA procedures and patient outcomes.

Purpose of the Study:

• To introduce the Native Alignment Phenotype classification system for TKA.
• To utilize 3D computed tomography (CT) scans for a more detailed understanding of knee anatomy and deformities.
• To enhance pre-operative planning for TKA by characterizing individual knee alignment patterns.

Main Methods:

• Analysis of 1406 pre-operative non-weight-bearing CT scans.
• Creation of 3D models to assess coronal and sagittal plane deformities.
• Development of the Native Alignment Phenotype system to categorize knee malalignments.

Main Results:

• Identification of four primary malalignments: varus, valgus, and two sagittal plane deformities.
• Discovery of 77 distinct phenotypic alignment patterns.
• Most common coronal plane deformity: varus HKA between 6-10° (36.9%). Most common sagittal plane deformity: neutral/flexion contracture between 0-5° (32.6%).

Conclusions:

• The Native Alignment Phenotype system provides a detailed, 3D-based classification of knee deformities.
• This system promotes a more individualized and data-driven approach to TKA planning.
• Improved understanding of knee anatomy through CT scans can lead to better TKA surgical outcomes.