Introduction: Total knee arthroplasty (TKA) is a complex surgical procedure that traditionally relies on two-dimensional radiographs for pre-operative planning. These radiographs may not capture the intricate details of individual knee anatomy, potentially limiting the precision of surgical interventions. With advancements in imaging technology, there is an opportunity to refine TKA outcomes. This study introduces the Native Alignment Phenotype classification system that is based on pre-operative 3-dimensional computed tomography (CT) scans, aiming to provide a more detailed understanding of knee deformities and their influence on characterizing knee osteoarthritis and planning for TKA procedures.
Methods: There were 1406 pre-operative non-weight-bearing CT scans analyzed by a single surgeon experienced with robotically-assisted total knee arthroplasties. These scans were converted into three-dimensional models, focusing on the coronal and sagittal planes. Intraoperatively, the robotic system was used to capture native coronal and sagittal deformities for each patient. These values were captured with the patient's leg held in a non-stress, extension pose. A new classification system, 'The Native Alignment Phenotype', was developed to categorize the specific differences between individual knees.
Results: There were four primary knee malalignments identified: varus deformity; valgus deformity; and two deformities in the sagittal plane. These malalignments were further categorized based on the degrees of deviation, creating groups with 5° coronal and sagittal ranges. A total of 77 phenotypic alignment patterns were found based on the analyzed cohort. In the coronal plane, varus HKA deformity between 6 and 10° was the most common, with 36.9% of the cases, followed by varus HKA alignment, which was between 0 and 5°, representing 34.3% of the cases. In the sagittal plane, neutral and flexion contracture deformities between 0 and 5° were the most common, with 32.6% of the cases, followed by a fixed flexion contracture alignment, which was between 6 and 10°, representing 28.7% of the cases. When combining coronal and sagittal planes, the most common alignment was the varus between 0 and 5° with a flexion contracture between 0 and 5° (12.5% of cases), closely followed by the varus between 6 and 10° with a flexion contracture between 6 and 10° (12.4% of cases).
Conclusion: The Native Alignment Phenotype classification system offers a nuanced understanding of knee deformities based on three-dimensional (CT scan) assessments, potentially leading to improved surgical outcomes in TKA. By leveraging the detailed data from the CT scans, this system provides a more comprehensive view of the knee's anatomy, emphasizing the importance of individualized, data-driven approaches in knee surgery.
© 2024 Professor P K Surendran Memorial Education Foundation. Published by Elsevier B.V. All rights reserved.