Accuracy of Patient Specific Cutting Blocks in Total Knee Arthroplasty

Author:

Helmy Naeder1,Dao Trong Mai Lan1ORCID,Kühnel Stefanie P.1

Affiliation:

1. Abteilung für Orthopädie und Traumatologie des Bewegungsapparates, Bürgerspital Solothurn, Schöngrünstrasse 42, 4500 Solothurn, Switzerland

Abstract

Background.Long-term survival of total knee arthroplasty (TKA) is mainly determined by optimal positioning of the components and prosthesis alignment. Implant positioning can be optimized by computer assisted surgery (CAS). Patient specific cutting blocks (PSCB) seem to have the potential to improve component alignment compared to the conventional technique and to be comparable to CAS.Methods.113 knees were selected for PSI and included in this study. Pre- and postoperative mechanical axis, represented by the hip-knee-angle (HKA), the proximal tibial angle (PTA), the distal femoral angle (DFA), and the tibial slope (TS) were measured and the deviation from expected ideal values was calculated.Results.With a margin of error of ±3°, success rates were 81.4% for HKA, 92.0% for TPA, and 94.7% for DFA. With the margin of error for alignments extended to ±4°, we obtained a success rate of 92.9% for the HKA, 98.2% for the PTA, and 99.1% for the DFA. The TS showed postoperative results of 2.86 ± 2.02° (mean change 1.76 ± 2.85°).Conclusion.PSCBs for TKA seem to restore the overall leg alignment. Our data suggest that each individual component can be implanted accurately and the results are comparable to the ones in CAS.

Funder

Medacta Research Fund

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3