Login Register Cart 0
Generic placeholder image

Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

An Automatic Method Framework for Personalized Knee Prosthetic Modeling Based on Kinematic Geometry

Author(s): Pengxi Li, Hui Liu, Bocheng Zhang, Dongpei Liu, Liang Yang* and Bin Liu*

Volume 20, 2024

Published on: 02 October, 2023

Article ID: e150823219726 Pages: 13

DOI: 10.2174/1573405620666230815142639

open_access

Open Access Journals Promotions 2
Abstract

The shape of a knee prosthesis has an important impact on the effect of total knee arthroplasty. Comparing to a standard common prosthesis, the personalized prosthesis has inherent advantages. However, how to construct a personalized knee prosthesis has not been studied deeply. In this paper, we present an automatic method framework of modeling personalized knee prostheses based on shape statistics and kinematic geometry. Firstly, the average healthy knee model is established through an unsupervised process. Secondly, the sTEA (Surgical Transecpicondylar Axis) is calculated, and the average healthy knee model is resized according to it. Thirdly, the resized model is used to simulate the knee’s motion in a healthy state. Fourthly, according to the target patient's condition, an excising operation is simulated on both patient's knee model and the resized model to generate an initial knee prosthesis model. Finally, the initial prosthesis model is adjusted according to the simulated motion results. The average maximum error between the resized healthy knee model and the patient's own knee model is less than 2 mm, and the average maximum error between the motion simulation results and actual motion results is less than 3 mm. This framework can generate personalized knee prosthesis models according to the patient’s different conditions, which makes up for the deficiencies of standard common prostheses.

Keywords: Knee motion simulation, Average knee modeling, Personalized prosthesis modeling, Total knee arthroplasty, Kinematic geometry, Automatic method framework.

[1]
Andriacchi TP, Stanwyck TS, Galante JO. Knee biomechanics and total knee replacement. J Arthroplasty 1986; 1(3): 211-9.
[http://dx.doi.org/10.1016/S0883-5403(86)80033-X] [PMID: 3559597]
[2]
Pitta M, Esposito CI, Li Z, Lee Y, Wright TM, Padgett DE. Failure after modern total knee arthroplasty: A prospective study of 18,065 knees. J Arthroplasty 2018; 33(2): 407-14.
[http://dx.doi.org/10.1016/j.arth.2017.09.041] [PMID: 29079167]
[3]
Singari RM, Kankar PK. Finite Element Modeling and Comparative Analysis of Multiple Biocompatible Titanium Alloys for Hip Prosthesis. Crossref 2022.
[4]
Korez R, Ibragimov B, Likar B, Pernuš F, Vrtovec T. A framework for automated spine and vertebrae interpolation-based detection and model-based segmentation. IEEE Trans Med Imaging 2015; 34(8): 1649-62.
[http://dx.doi.org/10.1109/TMI.2015.2389334] [PMID: 25585415]
[5]
Joshi AA, Leahy RM, Badawi RD, Chaudhari AJ. Registration-based morphometry for shape analysis of the bones of the human wrist. IEEE Trans Med Imaging 2016; 35(2): 416-26.
[http://dx.doi.org/10.1109/TMI.2015.2476817] [PMID: 26353369]
[6]
Bryan R, Surya Mohan P, Hopkins A, Galloway F, Taylor M, Nair PB. Statistical modelling of the whole human femur incorporating geometric and material properties. Med Eng Phys 2010; 32(1): 57-65.
[http://dx.doi.org/10.1016/j.medengphy.2009.10.008] [PMID: 19932044]
[7]
Jung W, Park S, Shin H. Combining volumetric dental CT and optical scan data for teeth modeling. Comput Aided Des 2015; 67-68: 24-37.
[http://dx.doi.org/10.1016/j.cad.2015.04.008]
[8]
Tsai TY, Li JS, Wang S, Li P, Kwon YM, Li G. Principal component analysis in construction of 3D human knee joint models using a statistical shape model method. Comput Methods Biomech Biomed Engin 2015; 18(7): 721-9.
[http://dx.doi.org/10.1080/10255842.2013.843676] [PMID: 24156375]
[9]
Coogan JS, Kim DG, Bredbenner TL, Nicolella DP. Determination of sex differences of human cadaveric mandibular condyles using statistical shape and trait modeling. Bone 2018; 106: 35-41.
[http://dx.doi.org/10.1016/j.bone.2017.10.003] [PMID: 28987286]
[10]
Joshi T, Sharma R, Kumar Mittal V, Gupta V. Comparative investigation and analysis of hip prosthesis for different bio-compatible alloys. Mater Today Proc 2021; 43: 105-11.
[http://dx.doi.org/10.1016/j.matpr.2020.11.222]
[11]
Joshi T, Sharma R, Mittal VK, Gupta V, Krishan G. Dynamic analysis of hip prosthesis using different biocompatible alloys. ASME Open J Engineering 2022; 1: 011001.
[12]
Mittal V K, Gupta V. Homogeneous and heterogeneous modeling of patient-specific hip implant under static and dynamic loading condition using finite element analysis. J Inst Eng (India): D 2023.
[13]
Zach L, Kunčická L, Růžička P, Kocich R. Design, analysis and verification of a knee joint oncological prosthesis finite element model. Comput Biol Med 2014; 54: 53-60.
[http://dx.doi.org/10.1016/j.compbiomed.2014.08.021] [PMID: 25212118]
[14]
Watanabe K, Ikeda Y, Suzuki D, et al. Three-dimensional analysis of tarsal bone response to axial loading in patients with hallux valgus and normal feet. Clin Biomech 2017; 42: 65-9.
[http://dx.doi.org/10.1016/j.clinbiomech.2017.01.012] [PMID: 28110242]
[15]
Whiteside L A, Arima J. The anteroposterior axis for femoral rotational alignment in valgus total knee arthroplasty. Clin Orthop Relat Res 1995; 321: 168-72.
[http://dx.doi.org/10.1097/00003086-199512000-00026]
[16]
Berger RA, Rubash HE, Seel MJ, Thompson WH, Crossett LS. Determining the rotational alignment of the femoral component in total knee arthroplasty using the epicondylar axis. Clin Orthop Relat Res 1993; 286: 40-7.
[http://dx.doi.org/10.1097/00003086-199301000-00008]
[17]
Mantas JP, Bloebaum RD, Skedros JG, Hofmann AA. Implications of reference axes used for rotational alignment of the femoral component in primary and revision knee arthroplasty. J Arthroplasty 1992; 7(4): 531-5.
[http://dx.doi.org/10.1016/S0883-5403(06)80075-6] [PMID: 1479373]
[18]
Churchill DL, Incavo SJ, Johnson CC, Beynnon BD. The transepicondylar axis approximates the optimal flexion axis of the knee. Clin Orthop Relat Res 1998; 356(356): 111-8.
[http://dx.doi.org/10.1097/00003086-199811000-00016] [PMID: 9917674]
[19]
Klatzow J, Dalmasso G, Martínez-Abadías N, Sharpe J, Uhlmann V. µMatch: 3D shape correspondence for biological image data. Front Comput Sci 2022; 4: 7.
[20]
Sun J, Ovsjanikov M, Guibas L. A concise and provably informative multi‐scale signature based on heat diffusion. Comput Graph Forum 2009; 28(5): 1383-92. [). Oxford, UK: Blackwell Publishing Ltd. Crossref.].
[http://dx.doi.org/10.1111/j.1467-8659.2009.01515.x]
[21]
Aubry M, Schlickewei U, Cremers D. The wave kernel signature: A quantum mechanical approach to shape analysis. 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops). 06-13 November 2011; Barcelona, Spain. 2011.
[http://dx.doi.org/10.1109/ICCVW.2011.6130444]
[22]
Besl PJ, McKay ND. Method for registration of 3-D shapes. Sensor fusion IV: control paradigms and data structures. Spie. Crossref 1992; 1611: pp. 586-606.
[http://dx.doi.org/10.1117/12.57955]
[23]
Iwaki H, Pinskerova V, Freeman MAR. Tibiofemoral movement 1: The shapes and relative movements of the femur and tibia in the unloaded cadaver knee. J Bone Joint Surg Br 2000; 82-B(8): 1189-95.
[http://dx.doi.org/10.1302/0301-620X.82B8.0821189] [PMID: 11132285]
[24]
Asano T, Akagi M, Tanaka K, Tamura J, Nakamura T. In vivo three-dimensional knee kinematics using a biplanar image-matching technique. Clin Orthop Relat Res 2001; (388): 157-66.
[http://dx.doi.org/10.1097/00003086-200107000-00023]
[25]
Gulan G, Jurdana H, Gulan L. Personalized total knee arthroplasty: Better fit for better function. Personalized Medicine in Healthcare Systems. Springer, Cham 2019; pp. 307-14.
[26]
Chui CS, Leung KS, Qin J, et al. Population-based and personalized design of total knee replacement prosthesis for additive manufacturing based on Chinese anthropometric data. Engineering 2021; 7(3): 386-94.
[http://dx.doi.org/10.1016/j.eng.2020.02.017]

Rights & Permissions Print Cite
Article Metrics
15
2
Wayfinder Image
Open Access Journals Promotions
© 2024 Bentham Science Publishers | Privacy Policy