3Dプリント患者特異的インプラント・AI仮想術前計画支援内側固定支持型単顆置換術

Unicompartmental knee arthroplasty (UKA) is widely recognized as an effective treatment for advanced knee osteoarthritis. However, its dependency on surgical experience and two-dimensional (2D) radiographs introduces significant challenges for less-experienced surgeons and for patients with femoral or tibial bone deformities. To enhance surgical precision and reduce prosthesis malposition-related complications, our team integrated three-dimensional (3D) printing technology for patient-specific instrumentation (PSI) with artificial intelligence (AI)-based preoperative simulation planning, thereby addressing the limitations of traditional approaches. This study presents a comprehensive digital workflow for fixed-bearing UKA that aims to achieve precise prosthetic alignment, improve surgical efficiency and safety, reduce operative time, and enable personalized prosthesis positioning with consistent and reproducible outcomes. The protocol consists of five critical steps: 1. Strict patient selection based on fixed-bearing UKA indications; 2. Comprehensive imaging acquisition, including CT scans of the affected knee, anteroposterior and lateral radiographs, and full-length weight-bearing X-rays in DICOM format; 3. AI-assisted preoperative planning with detailed surgical simulation reports; 4. Fabrication of customized 3D-printed cutting guides; 5. Precise osteotomy execution with intraoperative verification. By implementing this standardized digital approach, we demonstrate how integrating AI and 3D printing can optimize UKA outcomes through enhanced reproducibility, accuracy, and patient-specific customization.