Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Medical Imaging
  4. Volume 20, Issue 1
  5. Article
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
file format pdf download PDF
side by side viewer icon HTML

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.

© 2024 The Author(s). Published by Bentham Open.
© 2024 The Author(s). Published by Bentham Open. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
Loading

Article metrics loading...

/content/journals/cmir/10.2174/1573405620666230815142639
2023-10-02
2024-11-26

  • From This Site

    /content/journals/cmir/10.2174/1573405620666230815142639
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

/deliver/fulltext/cmir/20/1/CMIM-20-e150823219726.html?itemId=/content/journals/cmir/10.2174/1573405620666230815142639&mimeType=html&fmt=ahah

References

  1. AndriacchiT.P. StanwyckT.S. GalanteJ.O. Knee biomechanics and total knee replacement.J. Arthroplasty19861321121910.1016/S0883‑5403(86)80033‑X3559597
     [Google Scholar]
  2. PittaM. EspositoC.I. LiZ. LeeY. WrightT.M. PadgettD.E. Failure after modern total knee arthroplasty: A prospective study of 18,065 knees.J. Arthroplasty201833240741410.1016/j.arth.2017.09.04129079167
     [Google Scholar]
  3. SingariR.M. KankarP.K. Finite Element Modeling and Comparative Analysis of Multiple Biocompatible Titanium Alloys for Hip Prosthesis.Crossref2022
     [Google Scholar]
  4. KorezR. IbragimovB. LikarB. PernušF. VrtovecT. A framework for automated spine and vertebrae interpolation-based detection and model-based segmentation.IEEE Trans. Med. Imaging20153481649166210.1109/TMI.2015.238933425585415
     [Google Scholar]
  5. JoshiA.A. LeahyR.M. BadawiR.D. ChaudhariA.J. Registration-based morphometry for shape analysis of the bones of the human wrist.IEEE Trans. Med. Imaging201635241642610.1109/TMI.2015.247681726353369
     [Google Scholar]
  6. BryanR. Surya MohanP. HopkinsA. GallowayF. TaylorM. NairP.B. Statistical modelling of the whole human femur incorporating geometric and material properties.Med. Eng. Phys.2010321576510.1016/j.medengphy.2009.10.00819932044
     [Google Scholar]
  7. JungW. ParkS. ShinH. Combining volumetric dental CT and optical scan data for teeth modeling.Comput. Aided Des.201567-68243710.1016/j.cad.2015.04.008
     [Google Scholar]
  8. TsaiT.Y. LiJ.S. WangS. LiP. KwonY.M. LiG. Principal component analysis in construction of 3D human knee joint models using a statistical shape model method.Comput. Methods Biomech. Biomed. Engin.201518772172910.1080/10255842.2013.84367624156375
     [Google Scholar]
  9. CooganJ.S. KimD.G. BredbennerT.L. NicolellaD.P. Determination of sex differences of human cadaveric mandibular condyles using statistical shape and trait modeling.Bone2018106354110.1016/j.bone.2017.10.00328987286
     [Google Scholar]
  10. JoshiT. SharmaR. Kumar MittalV. GuptaV. Comparative investigation and analysis of hip prosthesis for different bio-compatible alloys.Mater. Today Proc.20214310511110.1016/j.matpr.2020.11.222
     [Google Scholar]
  11. JoshiT. SharmaR. MittalV.K. GuptaV. KrishanG. Dynamic analysis of hip prosthesis using different biocompatible alloys.ASME Open J. Engineering.20221011001
     [Google Scholar]
  12. MittalV. K. GuptaV. Homogeneous and heterogeneous modeling of patient-specific hip implant under static and dynamic loading condition using finite element analysis.J. Inst. Eng. (India): D2023
     [Google Scholar]
  13. ZachL. KunčickáL. RůžičkaP. KocichR. Design, analysis and verification of a knee joint oncological prosthesis finite element model.Comput. Biol. Med.201454536010.1016/j.compbiomed.2014.08.02125212118
     [Google Scholar]
  14. WatanabeK. IkedaY. SuzukiD. TeramotoA. KobayashiT. SuzukiT. YamashitaT. Three-dimensional analysis of tarsal bone response to axial loading in patients with hallux valgus and normal feet.Clin. Biomech.201742656910.1016/j.clinbiomech.2017.01.01228110242
     [Google Scholar]
  15. WhitesideL. A. ArimaJ. The anteroposterior axis for femoral rotational alignment in valgus total knee arthroplasty.Clin Orthop Relat Res199532116817210.1097/00003086‑199512000‑00026
     [Google Scholar]
  16. BergerR.A. RubashH.E. SeelM.J. ThompsonW.H. CrossettL.S. Determining the rotational alignment of the femoral component in total knee arthroplasty using the epicondylar axis.Clin. Orthop. Relat. Res.1993286404710.1097/00003086‑199301000‑00008
     [Google Scholar]
  17. MantasJ.P. BloebaumR.D. SkedrosJ.G. HofmannA.A. Implications of reference axes used for rotational alignment of the femoral component in primary and revision knee arthroplasty.J. Arthroplasty19927453153510.1016/S0883‑5403(06)80075‑61479373
     [Google Scholar]
  18. ChurchillD.L. IncavoS.J. JohnsonC.C. BeynnonB.D. The transepicondylar axis approximates the optimal flexion axis of the knee.Clin. Orthop. Relat. Res.199835635611111810.1097/00003086‑199811000‑000169917674
     [Google Scholar]
  19. KlatzowJ. DalmassoG. Martínez-AbadíasN. SharpeJ. UhlmannV. µMatch: 3D shape correspondence for biological image data.Front. Comput. Sci.202247
     [Google Scholar]
  20. SunJ. OvsjanikovM. GuibasL. A concise and provably informative multi‐scale signature based on heat diffusion.Comput. Graph. Forum200928513831392[). Oxford, UK: Blackwell Publishing Ltd. Crossref.].10.1111/j.1467‑8659.2009.01515.x
     [Google Scholar]
  21. AubryM. SchlickeweiU. CremersD. The wave kernel signature: A quantum mechanical approach to shape analysis.2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)06-13 November 2011Barcelona, Spain201110.1109/ICCVW.2011.6130444
     [Google Scholar]
  22. BeslP.J. McKayN.D. Method for registration of 3-D shapes.Sensor fusion IV: control paradigms and data structures.Spie. Crossref1992161158660610.1117/12.57955
     [Google Scholar]
  23. IwakiH. PinskerovaV. FreemanM.A.R. Tibiofemoral movement 1: The shapes and relative movements of the femur and tibia in the unloaded cadaver knee.J. Bone Joint Surg. Br.200082-B81189119510.1302/0301‑620X.82B8.082118911132285
     [Google Scholar]
  24. AsanoT. AkagiM. TanakaK. TamuraJ. NakamuraT. In vivo three-dimensional knee kinematics using a biplanar image-matching technique.Clin Orthop Relat Res.200138815716610.1097/00003086‑200107000‑00023
     [Google Scholar]
  25. GulanG. JurdanaH. GulanL. Personalized total knee arthroplasty: Better fit for better function.Personalized Medicine in Healthcare SystemsSpringer, Cham2019307314
     [Google Scholar]
  26. ChuiC.S. LeungK.S. QinJ. ShiD. AugatP. WongR.M.Y. ChowS.K.H. HuangX.Y. ChenC.Y. LaiY.X. YungP.S.H. QinL. CheungW.H. Population-based and personalized design of total knee replacement prosthesis for additive manufacturing based on Chinese anthropometric data.Engineering.20217338639410.1016/j.eng.2020.02.017
     [Google Scholar]
/content/journals/cmir/10.2174/1573405620666230815142639
Loading
An Automatic Method Framework for Personalized Knee Prosthetic Modeling Based on Kinematic Geometry
Curr. Med. Imaging 20, E110823219690 (2024); https://doi.org/10.2174/1573405620666230815142639
/content/journals/cmir/10.2174/1573405620666230815142639
/content/journals/cmir/10.2174/1573405620666230815142639
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Automatic method framework; Average knee modeling; Kinematic geometry; Knee motion simulation; Personalized prosthesis modeling; Total knee arthroplasty

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test