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Automatic string generation for estimating in vivo length changes of the medial patellofemoral ligament during knee flexion

  • Matthias Graf
  • Salomon Diether
  • Lazaros Vlachopoulos
  • Sandro Fucentese
  • Philipp Fürnstahl
Original Article

Abstract

Modeling ligaments as three-dimensional strings is a popular method for in vivo estimation of ligament length. The purpose of this study was to develop an algorithm for automated generation of non-penetrating strings between insertion points and to evaluate its feasibility for estimating length changes of the medial patellofemoral ligament during normal knee flexion. Three-dimensional knee models were generated from computed tomography (CT) scans of 10 healthy subjects. The knee joint under weight-bearing was acquired in four flexion positions (0°–120°). The path between insertion points was computed in each position to quantify string length and isometry. The average string length was maximal in 0° of flexion (64.5 ± 3.9 mm between femoral and proximal patellar point; 62.8 ± 4.0 mm between femoral and distal patellar point). It was minimal in 30° (60.0 ± 2.6 mm) for the proximal patellar string and in 120° (58.7 ± 4.3 mm) for the distal patellar string. The insertion points were considered to be isometric in 4 of the 10 subjects. The proposed algorithm appears to be feasible for estimating string lengths between insertion points in an automatic fashion. The length measurements based on CT images acquired under physiological loading conditions may give further insights into knee kinematics.

Keywords

Patellar ligament Three-dimensional imaging Computer-assisted surgery 

Notes

Conflict of interest

The authors declared that they have no conflicts of interests in the authorship and publication of this contribution.

References

  1. 1.
    Bentley JL (1975) Multidimensional binary search trees used for associative searching. Commun ACM 18(9):509–517CrossRefGoogle Scholar
  2. 2.
    Besl PJ, McKay ND (1992) A method for registration of 3-D shapes. Pattern Anal Mach Intell IEEE Trans 14(2):239–256CrossRefGoogle Scholar
  3. 3.
    Bollier M, Fulkerson J, Cosgarea A, Tanaka M (2011) Technical failure of medial patellofemoral ligament reconstruction. Arthroscopy 27(8):1153–1159PubMedCrossRefGoogle Scholar
  4. 4.
    Burks RT, Desio SM, Bachus KN, Tyson L, Springer K (1998) Biomechanical evaluation of lateral patellar dislocations. Am J Knee Surg 11(1):24–31PubMedGoogle Scholar
  5. 5.
    Crisco JJ, Moore DC, Marai GE, Laidlaw DH, Akelman E, Weiss AP et al (2007) Effects of distal radius malunion on distal radioulnar joint mechanics—an in vivo study. J Orthop Res 25(4):547–555PubMedCrossRefGoogle Scholar
  6. 6.
    Deie M, Ochi M, Sumen Y, Yasumoto M, Kobayashi K, Kimura H (2003) Reconstruction of the medial patellofemoral ligament for the treatment of habitual or recurrent dislocation of the patella in children. J Bone Joint Surg Br 85(6):887–890PubMedGoogle Scholar
  7. 7.
    Desio SM, Burks RT, Bachus KN (1998) Soft tissue restraints to lateral patellar translation in the human knee. Am J Sports Med 26(1):59–65PubMedGoogle Scholar
  8. 8.
    Hautamaa PV, Fithian DC, Kaufman KR, Daniel DM, Pohlmeyer AM (1998) Medial soft tissue restraints in lateral patellar instability and repair. Clin Orthop Relat Res 349:174–182PubMedCrossRefGoogle Scholar
  9. 9.
    Kobayashi K, Sakamoto M, Hosseini A, Rubash HE, Li G (2012) In-vivo patellar tendon kinematics during weight-bearing deep knee flexion. J Orthop Res 30(10):1596–1603PubMedCrossRefGoogle Scholar
  10. 10.
    Lorensen WE, Cline HE (1987) Marching cubes: a high resolution 3D surface construction algorithm. SIGGRAPH Comput Graph 21(4):163–169CrossRefGoogle Scholar
  11. 11.
    Marai GE, Laidlaw DH, Demiralp C, Andrews S, Grimm CM, Crisco JJ (2004) Estimating joint contact areas and ligament lengths from bone kinematics and surfaces. IEEE Trans Biomed Eng 51(5):790–799PubMedCrossRefGoogle Scholar
  12. 12.
    Matthews JJ, Schranz P (2010) Reconstruction of the medial patellofemoral ligament using a longitudinal patellar tunnel technique. Int Orthop 34(8):1321–1325PubMedCentralPubMedCrossRefGoogle Scholar
  13. 13.
    Montgomery DC, Runger GC (2010) Applied statistics and probability for engineers. Wiley. ISBN: 9780470053041Google Scholar
  14. 14.
    Moritomo H, Murase T, Arimitsu S, Oka K, Yoshikawa H, Sugamoto K (2008) Change in the length of the ulnocarpal ligaments during radiocarpal motion: possible impact on triangular fibrocartilage complex foveal tears. J Hand Surg Am 33(8):1278–1286PubMedCrossRefGoogle Scholar
  15. 15.
    Moritomo H, Noda K, Goto A, Murase T, Yoshikawa H, Sugamoto K (2009) Interosseous membrane of the forearm: length change of ligaments during forearm rotation. J Hand Surg Am 34(4):685–691PubMedCrossRefGoogle Scholar
  16. 16.
    Mountney J, Senavongse W, Amis AA, Thomas NP (2005) Tensile strength of the medial patellofemoral ligament before and after repair or reconstruction. J Bone Joint Surg Br 87(1):36–40PubMedGoogle Scholar
  17. 17.
    Nomura E, Inoue M, Osada N (2005) Anatomical analysis of the medial patellofemoral ligament of the knee, especially the femoral attachment. Knee Surg Sports Traumatol Arthrosc 13(7):510–515PubMedCrossRefGoogle Scholar
  18. 18.
    Oka K, Murase T, Moritomo H, Goto A, Sugamoto K, Yoshikawa H (2009) Accuracy analysis of three-dimensional bone surface models of the forearm constructed from multidetector computed tomography data. Int J Med Robot 5(4):452–457PubMedCrossRefGoogle Scholar
  19. 19.
    Omori S, Moritomo H, Murase T, Miyake J, Kataoka T, Kawanishi Y et al (2013) Changes in length of the radioulnar ligament and distal oblique bundle after Colles’ fracture. J Plast Surg Hand Surg 47(5):409–414PubMedCrossRefGoogle Scholar
  20. 20.
    Philippot R, Chouteau J, Wegrzyn J, Testa R, Fessy MH, Moyen B (2009) Medial patellofemoral ligament anatomy: implications for its surgical reconstruction. Knee Surg Sports Traumatol Arthrosc 17(5):475–479PubMedCrossRefGoogle Scholar
  21. 21.
    Powell MJD (1994) A direct search optimization method that models the objective and constraint functions by linear interpolation. In: Gomez S, Hennart J-P (eds) Advances in optimization and numerical analysis. Mathematics and Its applications, vol 275. Springer, Netherlands, pp 51–67CrossRefGoogle Scholar
  22. 22.
    Schottle PB, Fucentese SF, Romero J (2005) Clinical and radiological outcome of medial patellofemoral ligament reconstruction with a semitendinosus autograft for patella instability. Knee Surg Sports Traumatol Arthrosc 13(7):516–521PubMedCrossRefGoogle Scholar
  23. 23.
    Schottle PB, Schmeling A, Rosenstiel N, Weiler A (2007) Radiographic landmarks for femoral tunnel placement in medial patellofemoral ligament reconstruction. Am J Sports Med 35(5):801–804PubMedCrossRefGoogle Scholar
  24. 24.
    Schroeder W, Martin K, Lorensen B (2006) Visualization toolkit: an object-oriented approach to 3D graphics, 4th edn. Kitware, ISBN: 193093419XGoogle Scholar
  25. 25.
    Smirk C, Morris H (2003) The anatomy and reconstruction of the medial patellofemoral ligament. Knee 10(3):221–227PubMedCrossRefGoogle Scholar
  26. 26.
    Steensen RN, Dopirak RM, McDonald WG 3rd (2004) The anatomy and isometry of the medial patellofemoral ligament: implications for reconstruction. Am J Sports Med 32(6):1509–1513PubMedCrossRefGoogle Scholar
  27. 27.
    Yoo YS, Chang HG, Seo YJ, Byun JC, Lee GK, Im H et al (2012) Changes in the length of the medial patellofemoral ligament: an in vivo analysis using 3-dimensional computed tomography. Am J Sports Med 40(9):2142–2148PubMedCrossRefGoogle Scholar
  28. 28.
    Zhu Z, Ding H, Dang X, Tang J, Zhou Y, Wang G (2010) In vitro kinematic measurements of the patellar tendon in two different types of posterior-stabilized total knee arthroplasties. Conf Proc IEEE Eng Med Biol Soc 2010:3938–3941PubMedGoogle Scholar

Copyright information

© International Federation for Medical and Biological Engineering 2014

Authors and Affiliations

  • Matthias Graf
    • 1
  • Salomon Diether
    • 2
  • Lazaros Vlachopoulos
    • 1
  • Sandro Fucentese
    • 3
  • Philipp Fürnstahl
    • 1
  1. 1.Computer Assisted Research and Development Group, University Hospital BalgristUniversity of ZurichZurichSwitzerland
  2. 2.Computer Vision LaboratoryETH ZurichZurichSwitzerland
  3. 3.Department of Orthopedic Surgery, University Hospital BalgristUniversity of ZurichZurichSwitzerland

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