Back to Search Start Over

Bridging theory and practice: A comprehensive algorithm for imageless total knee arthroplasty.

Authors :
Sohail M
Kim HS
Source :
Computers in biology and medicine [Comput Biol Med] 2024 Jul; Vol. 177, pp. 108662. Date of Electronic Publication: 2024 May 27.
Publication Year :
2024

Abstract

Total knee arthroplasty (TKA) is a surgical procedure to treat severe knee osteoarthritis. Among several techniques available for performing TKA, imageless TKA is known for achieving precise alignment while minimizing invasiveness. This work proposes a comprehensive algorithm for imageless TKA device to calculate the varus/valgus and flexion/extension angles, as well as resection depths for cutting planes at distal femur and proximal tibia. Moreover, the algorithm calculates the hip-knee-ankle (HKA) and flexion angles of the leg. Initially, the proposed algorithm was validated in a virtual environment using a CT-scanned bone model in Solidworks. Subsequently, for the real-world validation, a SoftBone model was resected with conventional intra and extramedullary rods and cross-checked with the proposed algorithm. For the third validation, another SoftBone model was resected with the proposed algorithm and cuts were measured with a vernier caliper. During this experiment, there was an error of approximately 1 mm for both femoral and tibial resection cases when using an infrared camera with an accuracy of ±0.5 mm. However, this error could be reduced using an infrared camera with higher accuracy.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
177
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
38820780
Full Text :
https://doi.org/10.1016/j.compbiomed.2024.108662