Intelligent Precision Knee Preservation System for Knee Osteoarthritis

The goal of this clinical trial is to verify whether the "dynamic dual-mode alignment optimization + intelligent precision knee-preserving system" (integrating static/kinematic target alignment, CT-based preoperative three-dimensional \[3D\] planning, 3D-printed guide plates, and intraoperative augmented reality \[AR\] real-time feedback) achieves a greater relative reduction in peak knee adduction moment (KAM) at 12 months postoperatively, while maintaining or improving knee clinical function and without increasing perioperative or long-term complication rates, compared with traditional knee-preserving strategies. The target population is patients aged 40-70 years with knee osteoarthritis (KOA; Kellgren-Lawrence grade II-III) who require high tibial osteotomy (HTO) for unilateral medial-compartment disease with mild-to-moderate varus deformity and who meet the inclusion and exclusion criteria. The main questions are: * Can the dynamic dual-mode alignment + intelligent precision system achieve a greater relative reduction in peak KAM at 12 months postoperatively than traditional knee-preserving strategies? * Can this system improve static alignment accuracy, dynamic load parameters (e.g., KAM impulse and varus thrust), and patient-reported outcome (PRO) scores without increasing complication rates? * Can 3D-printed patient-specific instrumentation (PSI) guide plates and real-time AR feedback reduce intraoperative radiation exposure and shorten operative time compared with traditional methods? Researchers will compare: Kinematic alignment (KA), traditional mechanical alignment (MA), and dynamic dual-mode alignment (DA) to evaluate the relative performance of alignment strategies; 3D-printed PSI-guided HTO versus traditional fluoroscopy-guided HTO to assess the efficacy of PSI; and AR-assisted intraoperative adjustment versus traditional fluoroscopy-based adjustment to evaluate the precision of AR navigation. Participants will: * Complete preoperative assessme