Evidence map›Paper›PMID 42243882›Full record

ArticleArthroplasty (London, England)2026

Full-flexion gap balancing-driven personalized preoperative planning for TKA: biomechanical evidence of improved load symmetry in an in vitro model.

Zijun Tang, Diyang Zou, Yangyang Yang, Nan Zheng, Zhemin Zhu, Juan Wang, Pingyue Li, Rongshan Cheng, Guoqiang Zhang, Tsung-Yuan Tsai

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Article in Arthroplasty (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Zijun TangSchool of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, China.
Diyang ZouSchool of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, China.
Yangyang YangSchool of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, China.
Nan ZhengSchool of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, China.
Zhemin ZhuSchool of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, China.
Juan WangDepartment of Joint Surgery, Hebei Medical University Third Hospital, Shijiazhuang, 050051, China.
Pingyue LiGuangdong Key Lab of Orthopedic Technology and Implant, General Hospital of Southern Theater Command of PLA, Guangzhou, 510010, China.
Rongshan ChengSchool of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, China. chengrongshan@sjtu.edu.cn.
Guoqiang ZhangGeneral Hospital of People's Liberation Army, Beijing, 100141, China. gqzhang301orth@163.com.
Tsung-Yuan TsaiSchool of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, China. tytsai@sjtu.edu.cn.

Funding

Fundamental Research Funds for the Central Universities AF0820060Innovation Medical Device Application Demonstration Project supported by the Shanghai Municipal Commission of Economy and Informatization, Shanghai Municipal Health Commission, and Shanghai Municipal Medical Security Bureau 23SHS02800-06National Natural Science Foundation of China 32371367
6 · The paper itself

Abstract

purposeConventional morphology-based planning (MB) in total knee arthroplasty (TKA) often results in imbalanced medial-lateral loading, which is a major risk factor for prosthesis loosening. This study aimed to evaluate a full-flexion gap balance planning (GB) approach and compare its biomechanical performance with MB planning.

methodsTKA surgical planning was performed on eight subjects. In vivo knee kinematics were obtained using a dual X-ray imaging system. The implant position was optimized within an in silico surgical-planning framework by minimizing medial-lateral gap differences across the full flexion range using in vivo dynamic kinematics. Using 3D-printed in vitro models, joint contact forces were measured at various flexion angles to compare medial-lateral load distribution between GB and MB planning.

resultsGB planning optimized femoral varus/valgus by approximately 4° within anatomical constraints, significantly reducing the medial-lateral gap difference to a mean of < 1 mm across the entire flexion range (p < 0.05). In contrast, the medial-lateral gap difference exceeded 2 mm with MB planning. Furthermore, at mid-to-high flexion angles (30°-100°), GB planning reduced the medial-lateral load imbalance by approximately 38%-67% compared with MB planning (p < 0.05).

conclusionGB planning significantly improves medial-lateral load balance across the full range of flexion compared to conventional MB planning. This personalized planning optimizes joint loading patterns in vitro, which may theoretically align with principles aimed at reducing flexion-related adverse outcomes.

Indexed as

Dynamic dual X-rayGap-balancedIn vitro experimentPreoperative optimizationTotal knee arthroplasty

Identifiers

PMID42243882
PMCPMC13237995

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