435
Views
13
CrossRef citations to date
0
Altmetric
Articles

Statistical shape model-based prediction of tibiofemoral cartilage

ORCID Icon, , &
Pages 568-578 | Received 26 May 2017, Accepted 26 Jun 2018, Published online: 26 Oct 2018

References

  • Albrecht T, Lüthi M, Gerig T, Vetter T. 2013. Posterior shape models. J Orthop Sci. 17(8):959–973.
  • An VV, Sivakumar BS, Phan K, Levy YD, Bruce WJ. 2017. Accuracy of MRI-based vs. CT-based patient-specific instrumentation in total knee arthroplasty: a meta-analysis. J Orthop Sci. 22(1):116–120.
  • Andriacchi TP, Koo S, Scanlan SF. 2009. Gait mechanics influence healthy cartilage morphology and osteoarthritis of the knee. J Bone Joint Surg Am. 91(Suppl 1):95–101.
  • Barr AJ, Dube B, Hensor EMA, Kingsbury SR, Peat G, Bowes MA, Sharples LD, Conaghan PG. 2016. The relationship between three-dimensional knee MRI bone shape and total knee replacement-A case control study: data from the Osteoarthritis Initiative. Rheumatology (Oxford). 55(9):1585–1593.
  • Bookstein FLF. 1989. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans Pattern Anal Mach Intell. 11(6):567–585.
  • Cerveri P, Sacco C, Olgiati G, Manzotti A, Baroni G. 2017. 2D/3D reconstruction of the distal femur using statistical shape models addressing personalized surgical instruments in knee arthroplasty: a feasibility analysis. Int J Med Robot Comput Assist Surg. 13:e1823.
  • Cootes TF, Taylor C, Cooper D, Graham J. 1995. Active shape models-their training and application. Comput Vis Image Understand. 61(1):38–59.
  • Courtis RP, Aram L, Stauffer C, Vincent G, Cyr AJ, Bowes M, Maletsky P. 2015. Active shape modelling accurately characterizes knee cartilage geometry in the design of CT-based patient-specific cutting guides for knee arthroplasty. Orthopaedic Research Society Annual Meeting; March 28-31; Las Vegas, Nevada, USA.
  • Danckaers F, Huysmans T, Lacko D, Ledda A, Verwulgent S, Van Dongen S, Sijbers J. 2014. Correspondence preserving elastic surface registration with shape model prior. Proceedings of the International Conference on Pattern Recognition; August; Stockholm, Sweden: IEEE. p. 2143–2148.
  • Davies R, Twining C, Taylor C. 2008. Statistical models of shape: optimization and evaluation. New York: Springer.
  • DiCiccio TJ, Efron B. 1996. Bootstrap confidence intervals. Stat Sci. 11(3):189–228.
  • Favre J, Erhart-Hledik JC, Chehab EF, Andriacchi TP. 2016. Baseline ambulatory knee kinematics are associated with changes in cartilage thickness in osteoarthritic patients over 5 years. J Biomech. 49(9):1859–1864.
  • Gower JC. 1975. Generalized procrustes analysis. Psychometrika. 40(1):33–51.
  • Heimann T, Meinzer HP. 2009. Statistical shape models for 3D medical image segmentation: a review. Med Image Anal. 13(4):543–563.
  • Heimann T, Morrison B. 2010. Segmentation of knee images: a grand challenge. In: Jiang, T, Navab, N, Pluim, JPW, Viergever, M, editors. Proceedings of MICCAI Workshop on Medical Image Analysis for the Clinic; September 20-24. Beijing, China: Springer, Berlin. p. 207–214.
  • Johnson JM. 2013. Analysis, segmentation and prediction of knee cartilage using statistical shape models [dissertation]. Knoxville (TN): University of Tennessee.
  • Jolliffe IT. 2002. Principal component analysis. 2nd ed. Springer.
  • Koo S, Andriacchi TP. 2007. A comparison of the influence of global functional loads vs. local contact anatomy on articular cartilage thickness at the knee. J Biomech. 40(13):2961–2966.
  • Koo S, Rylander JH, Andriacchi TP. 2011. Knee joint kinematics during walking influences the spatial cartilage thickness distribution in the knee. J Biomech. 44(7):1405–1409.
  • Lorensen WE, Cline HE. 1987. Marching cubes: a high resolution 3D surface construction algorithm. In: Maureen C. Stone, editor. Proceedings of the 14th annual conference on Computer graphics and interactive techniques - SIGGRAPH ’87; July 27-31; Anaheim, CA, USA. New York, USA: ACM. p. 163–169.
  • Mattei L, Pellegrino P, Calo M, Bistolfi A, Castoldi F. 2016. Patient specific instrumentation in total knee arthroplasty: a state of the art. Ann Transl Med. 4(7):126.
  • Plessers K, Vanden Berghe P, Van Dijck C, Wirix-Speetjens R, Debeer P, Jonkers I, Vander Sloten J. 2018. Virtual reconstruction of glenoid bone defects using a statistical shape model. J Shoulder Elbow Surg. 27(1):160–166.
  • Rodrigues AST, Gutierres MAP, Rodrigues AST, Gutierres MAP. 2017. Patient-specific instrumentation in total knee arthroplasty. Should we adopt it? Rev Brasil Ortop. 52(3):242–250.
  • Schotanus M, Sollie R, van Haaren E, Hendrickx R, Jansen E, Kort N. 2016. A radiological analysis of the difference between MRI- and CT-based patient-specific matched guides for total knee arthroplasty from the same manufacturer: a randomised controlled trial. J Am Coll Radiol. 98B(6):786–792.
  • Sistrom CL, McKay NL. 2005. Costs, charges, and revenues for hospital diagnostic imaging procedures: differences by modality and hospital characteristics. J Arthroplasty. 2(6):511–519.
  • Slover JD, Rubash HE, Malchau H, Bosco JA. 2012. Cost-effectiveness analysis of custom total knee cutting blocks. J Orthop Res. 27(2):180–185.
  • Smoger LM, Fitzpatrick CK, Clary CW, Cyr AJ, Maletsky LP, Rullkoetter PJ, Laz PJ. 2015. Statistical modeling to characterize relationships between knee anatomy and kinematics. J Orthop Res. 33(11):1620–1630.
  • Thienpont E, Schwab PE, Fennema P. 2017. Efficacy of patient-specific instruments in total knee arthroplasty: a systematic review and meta-analysis. J Bone Joint Surg Am. 99(6):521–530.
  • Valette S, Chassery JM, Prost R. 2008. Generic remeshing of 3D triangular meshes with metric-dependent discrete voronoi diagrams. Med Eng Phys. 14(2):369–381.
  • Van den Broeck J, Vereecke E, Wirix-Speetjens R, Vander Sloten J. 2014. Segmentation accuracy of long bones. Med Eng Phys. 36(7):949–53.
  • Van den Berghe P, Demol J, Gelaude F, Vander Sloten J. 2016. Virtual anatomical reconstruction of large acetabular bone defects using a statistical shape model. Comput Methods Biomech Biomed Engin. 5842(December):1–10.
  • Watters TS, Mather RC, Browne JA, Berend KR, Lombardi AV, Bolognesi MP. 2011. Analysis of procedure-related costs and proposed benefits of using patient-specific approach in total knee arthroplasty. J Surg Orthop Adv. 20(2):112–116.
  • Wu XD, Xiang BY, Schotanus MG, Liu ZH, Chen Y, Huang W. 2017. CT- versus MRI-based patient-specific instrumentation for total knee arthroplasty: a systematic review and meta-analysis. Surgeon. 15(6):336–348.
  • Yang YM, Rueckert D, Bull AMJ. 2008. Predicting the shapes of bones at a joint: application to the shoulder. Comput Methods Biomech Biomed Eng. 11(1):19–30.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.