A 3D Printed Mechanical Model of the Knee to Detect and Avoid Total Knee Replacement Surgery Errors

Alexandra Mercader, Timon Röttinger, Amir Bigdeli, Heinz Röttinger, Tim C. Lueth

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this article, a novel 3D printed knee model for detecting possible errors in the planning and treatment of total knee replacement surgery is presented. This method is a first step towards automation of prosthesis placement. Thanks to the mathematically computed four-bar mechanism, it is now possible to emulate the implant insertion before the operation. This model allows the surgeon to fit the prosthesis to the patient's knee and to verify if the mounted position is optimal. This process can be repeated until the ideal position is found. Exact copies of the bones are made from the CT images of the patient. These resin copies of the real bones are placed in the motion model, reproducing the real patient's knee flexion. The model shows the implantation result with respect to the operation plan and the patient's kinematics. The experiment carried out on a patient's model according to the standard implantation shows a lift-off and sliding effect of the femoral component outside the joint area. However, this phenomenon is easily resolved if the femoral component is implanted about half a centimeter lateral to the knee's coronal axis. Until now, no medical research had questioned the lateral positioning of the prosthesis. This knee model provides an understanding of the important biomechanical parameters for total knee replacement surgery. This model will have a significant contribution to secure the surgery's success, increase patient satisfaction and reduce the overall number of revisions.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Robotics and Automation, ICRA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages12501-12507
Number of pages7
ISBN (Electronic)9781728190778
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China
Duration: 30 May 20215 Jun 2021

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2021-May
ISSN (Print)1050-4729

Conference

Conference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Country/TerritoryChina
CityXi'an
Period30/05/215/06/21

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