Accuracy considerations in navigated cup placement for total hip arthroplasty

被引:14
|
作者
Langlotz, U.
Gr tzner, P. A.
Bernsmann, K.
Kowal, J. H.
Tannast, M.
Caversaccio, M.
Nolte, L-P
机构
[1] Inst Surg Technol & Biomech, MEM Res Ctr, CH-3014 Bern, Switzerland
[2] mNemosci, Ubach Palenberg, Germany
[3] Katharinen Hosp, Stuttgart, Germany
[4] ViaSana Clin, AA Mill, Netherlands
[5] Univ Bern, Inselspital, Dept Orthopaed Surg, CH-3010 Bern, Switzerland
[6] Univ Bern, Inselspital, Dept ENT Surg, CH-3010 Bern, Switzerland
关键词
accuracy; cup placement; THR; navigation; CT-free; fluoroscopy;
D O I
10.1243/09544119JEIM280
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Computer assisted orthopaedic surgery (CAOS) technology has recently been introduced to overcome problems resulting from acetabular component malpositioning in total hip arthroplasty. Available navigation modules can conceptually be categorized as computer tomography (CT) based, fluoroscopy based, or image-free. The current study presents a comprehensive accuracy analysis on the computer assisted placement accuracy of acetabular cups. It combines analyses using mathematical approaches, in vitro testing environments, and an in vivo clinical trial. A hybrid navigation approach combining image-free with fluoroscopic technology was chosen as the best compromise to CT-based systems. It introduces pointer-based digitization for easily assessable points and bi-planar fluoroscopy for deep-seated landmarks. From the in vitro data maximum deviations were found to be 3.6 degrees for inclination and 3.8 degrees for anteversion relative to a pre-defined test position. The maximum difference between intraoperatively calculated cup inclination and anteversion with the postoperatively measured position was 4 degrees and 5 degrees, respectively. These data coincide with worst cases scenario predictions applying a statistical simulation model. The proper use of navigation technology can reduce variability of cup placement well within the surgical safe zone. Surgeons have to concentrate on a variety of error sources during the procedure, which may explain the reported strong learning curves for CAOS technologies.
引用
收藏
页码:739 / 753
页数:15
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