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Demonstrates real-time augmentation of tibial resection in TKA, suggesting improved soft tissue balance.
Purpose Kinematic alignment (KA) total knee arthroplasty (TKA) aims to restore native knee kinematics by aligning prosthetic components with each patient's constitutional anatomy. While femoral resurfacing is well established, tibial resection in KA‐TKA remains largely subjective, particularly in cases with advanced deformity or bone loss. This study introduces a novel augmented reality (AR)–based technique for tibial resection that utilises real‐time ligament elongation patterns to support personalised alignment. Methods More than 200 consecutive KA‐TKA procedures were performed using an AR navigation system (NextAR, Medacta) with medial‐stabilised implants (GMK Sphere). After femoral resurfacing and osteophyte removal, trial femoral components were inserted to restore functional intraoperative reference configuration, thereby defining a ‘zero‐position’ baseline. Real‐time elongation data of the medial and lateral collateral ligaments were visualised throughout the full range of motion via AR smart glasses. Tibial resection parameters—including varus/valgus angle and posterior slope—were quantitatively adjusted according to elongation patterns to replicate physiological soft‐tissue tension. Spacer blocks were used intraoperatively to verify bone‐gap balance. Results Intraoperative tibial adjustments guided by ligament elongation patterns enabled patient‐specific resection strategies without reliance on ambiguous osseous landmarks or purely subjective gap assessments. This approach facilitated consistent intraoperative evaluation of medial and lateral soft‐tissue behaviour in both extension and flexion. Conclusion This AR‐based KA‐TKA technique enables individualised tibial resection guided by real‐time ligament behaviour. It provides a reproducible and objective framework to support soft‐tissue‐informed intraoperative decision‐making, particularly in patients with complex deformities. This approach may complement existing KA principles and serve as a foundation for future outcome‐based investigations. Level of Evidence NA.
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Sato et al. (2026) studied this question.
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