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Obtaining patient-specific point model of the human ilium bone in the case of incomplete volumetric data using the method of parametric regions

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Abstract

In this paper, we present the methodology for determining the point model of the ilium bone in cases when volumetric data of the whole bone are not available. An extreme traumatic bone damage, osteoporosis, destruction of bone tissue by malignant bone tumors or the existence of only 2D medical image (X-ray) can be the reason for the lack of complete volumetric data. Points on the bone surface were defined at the curves that run through 26 previously defined parameters, at the edges of anteroposterior (A–P) and lateral projections and at the parts of the surface between some parameters. Those parts of the surface, enclosed by parameters, represent ten parametric regions. The values of coordinates, which represent the input data in the statistical program, were measured in a uniquely defined coordinate system. After establishing the correlations between the values of coordinates, 8869 different linear and nonlinear regression models were obtained. The prediction values for point coordinates were calculated and exported to a CAD program. Results obtained were tested on a randomly chosen male right ilium bone, applying the methodology for creating the prediction model using the method of parametric regions, which allows creating a complete polygonal model, for each region separately or just for some parts of the region. Results obtained in the form of regression equations for the right ilium bone can be applied to the left ilium bone. The results of the research were verified using a comparative deviation and distance analysis between the initial and obtained polygonal models.

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Notes

  1. Total number of equations decreased by 8 from 8877, because the number of equations for Y and Z coordinates was lower than the number of equations for X coordinates due to the fact that regression models for point 3 were calculated in the equations for parameters d1, d3, d13 and d16, whose Y and Z coordinates equaled 0.

References

  1. Gomes GT, Cauter SV, Beule MD, Vigneron L, Pattyn C, Audenaert EA (2013) Patient-specific modelling in orthopedics: from image to surgery. In: Andreaus U, Iacoviello D (eds) Biomedical imaging and computational modeling in biomechanics. Springer, Dordrecht, pp 129–131

    Google Scholar 

  2. Styner MA, Rajamani KT, Nolte LP et al (2003) Evaluation of 3D correspondence methods for model building. Lect Notes Comput Sci 2732:63–75

    Article  Google Scholar 

  3. Chintalapani G, Ellingsen LM, Sadowsky O et al (2007) Statistical atlases of bone anatomy: construction, iterative improvement and validation. MICCAI 2007: Part I, LNCS, vol 4791. Springer, Heidelberg, pp 499–506

    Google Scholar 

  4. Aguirre MR, Linguraru MG, Ballester MAG (2007) Statistical bone shape analysis for image free surgery. Acta Universitatis Cibiniensis, Technical Series, LV, pp 121–129

  5. Erdem M, Gok K, Gokce B, Gok A (2017) Numerical analysis of temperature, screwing moment and thrust force using finite element method in bone screwing process. J Mech Med Biol 17(2):1750016-1–1750016-16. https://doi.org/10.1142/S0219519417500166

    Article  Google Scholar 

  6. Vitković N, Mitković MM, Mitković BM, Korunović N, Stevanović D, Veselinović M (2015) Reverse engineering of the Mitkovic type internal fixator for lateral tibial plateau. Facta Univ Ser: Mech Eng 13(3):259–268

    Google Scholar 

  7. Benameur S, Mignotte M, Parent S et al (2001) 3D biplanar reconstruction of scoliotic vertebrae using statistical models. In: Proceedings of the 2001 IEEE computer society conference on (Volume: 2), computer vision and pattern recognition 2, pp 577–582

  8. Fattah EDHAA (2013) Reconstruction of patient-specific bone models from X-ray radiography. Dissertation, University of Tennessee, Knoxville

  9. Lamecker H, Wenckebach TH, Hege HC (2006) Atlas-based 3D-shape reconstruction from X-ray images. In: Proceedings of the 2006 international conference on pattern recognition 2006 (ICPR 2006), vol I. IEEE Computer Society, pp 371–374

  10. Ristić M, Manić M, Mišić D, Kosanović M, Mitković M (2017) Implant material selection using expert system. Facta Univ Ser: Mech Eng 15(1):133–144

    Google Scholar 

  11. Baka N, Niessen WJ, Kaptein BL et al (2010) Correspondence free 3D statistical shape model fitting to sparse X-ray projections. In: Davant BM, Haynor DR (ed) Medical imaging 2010: image processing: proceedings of SPIE, vol 7623, p 76230D-1

  12. Lamecker H (2008) Variational and statistical shape modeling for 3D geometry reconstruction. Dissertation, Fachbereich Mathematik und Informatik der Freien Universitat Berlin

  13. Zheng G (2009) Statistical deformable model-based reconstruction of a patient-specific surface model from single standard X-ray radiograph. Comput Anal Images Patterns 57(2):672–679

    Article  Google Scholar 

  14. Schumann S, Sato Y, Yokota F, Nakanish Y, Takao M, Sugano N et al (2014) SSM-based 3D cup planning from two conventional X-ray images. In: Shape 2014: proceedings of symposium on statistical shape models & applications 2014; Delémont, p 21

  15. Gok K, Inal S (2015) Biomechanical comparison using finite element analysis of different screw configurations in the fixation of femoral neck fractures. Mech Sci 6(2):173–179. https://doi.org/10.5194/ms-6-173-2015

    Article  Google Scholar 

  16. Gok K, Inal S, Gok A, Gulbandilar E (2017) Comparison of effects of different screw materials in the triangle fixation of femoral neck fractures. J Mater Sci: Mater Med 28(5):81. https://doi.org/10.1007/s10856-017-5890-y

    Article  CAS  Google Scholar 

  17. Phillips ATM, Pankaj P, Howie CR, Usmani AS, Simpson AHRW (2007) Finite element modelling of the pelvis: inclusion of muscular and ligamentous boundary conditions. Med Eng Phys 29(7):739–748

    Article  CAS  Google Scholar 

  18. Popov I, Onuh SO SO (2009) Reverse engineering of pelvic bone for hip joint replacement. J Med Eng Technol 33(6):454–459

    Article  CAS  Google Scholar 

  19. Trajanović M, Tufegdžić M, Arsić S, Ilić D (2013) Toward reverse engineering of the hip bone. In: Proceedings of the 35th international conference on production engineering (ICPE 2013), Kraljevo-Kopaonik, pp 319–324

  20. Traub F, Andreou D, Niethard M, Tiedke C, Werner M, Tunn PU (2013) Biological reconstruction following the resection of malignant bone tumors of the pelvis. Hindawi Publishing Corporation, Sarcoma, New York. https://doi.org/10.1155/2013/745360

    Book  Google Scholar 

  21. Criteria for palliation of bone metastases - clinical applications (2007) IAEA-TECDOC-1549. IAEA, Vienna

  22. Cartiaux O, Banse X, Paul L, Francq BG, Aubin CE´R, Docquier PL (2012) Computer-assisted planning and navigation improves cutting accuracy during simulated bone tumor surgery of the pelvis. Comput Aided Surg 18:19–26

    Article  Google Scholar 

  23. Natarajan MV, Sameer MM, Bose JC, Dheep K (2010) Surgical management of pelvic Ewing’s sarcoma. Indian J Orthop 44(4):397–401

    Article  Google Scholar 

  24. Tufegdzic M, Arsic S, Trajanovic M (2015) Parameter-based morphometry of the wing of ilium. Ј Anat Soc India 64:129–135. https://doi.org/10.1016/j.jasi.2015.10.008

    Article  Google Scholar 

  25. Fukuchi RK, Arakaki C, Orselli MIV, Marcos Duarte M (2010) Evaluation of alternative technical markers for the pelvis coordinate system. J Biomech 43:592–594

    Article  Google Scholar 

  26. Nikou C, Jaramaz B, DiGioia AM, Levison TJ (2000) Description of anatomic coordinate systems and rationale for use in an image-guided total hip replacement system. In: Delp SL, DiGoia AM, Jaramaz B (eds) Medical image computing and computer-assisted intervention MICCAI 2000, lecture notes in computer science 1935. Springer, Berlin, pp 1188–1194

    Google Scholar 

  27. Tannast M, Kubiak-Langer M, Murphy SB et al (2006) Computer-assisted simulation of femoro-acetabular impingement surgery. In: Stiehl JB, Konermann WH, Haaker RG, DiGioia AM (eds) Navigation and MIS in orthopedic surgery. Springer, Berlin, pp 448–455

    Google Scholar 

  28. Hakki S, Bilotta V, Oliveira JD, Luis Dordelly L (2010) Comparative study of acetabular center axis vs anterior pelvis plane registration technique in navigated hip arthroplasty. Orthopedics 33(10):43–47

    Article  Google Scholar 

  29. Vandenbussche E, Saffarini M, Taillieu F, Céline Mutschler C (2008) The asymmetric profile of the acetabulum. Clin Orthop Relat Res 466:417–423

    Article  Google Scholar 

  30. Hsu JT, Tsai MT, Chang CH, Huang HL, Kuo-An Lai KA (2011) Computer-assisted navigation for acetabular cup placement: a single image guiding system. In: Proceedings of the World Congress on Engineering 2011 (WCE 2011), vol III, London

  31. Köhnlein W, Ganz RD, Impellizzeri FM, Michael Leunig M (2009) Acetabular morphology implications for joint-preserving surgery. Clin Orthop Relat Res 467:682–691

    Article  Google Scholar 

  32. Lubovsky O, Peleg E, Joskowicz L, Liebergall M, Khoury A (2010) Acetabular orientation variability and symmetry based on CT scans of adults. Int J Cars 5:449–454

    Article  Google Scholar 

  33. Fieten L, Eschweiler J, Heger S, Fuente MDL, Radermacher K (2009) Surface based determination of the pelvis coordinate system. In: Proceeding of SPIE 7261, medical imaging 2009: visualization, image-guided procedures, and modeling, p 726138. https://doi.org/10.1117/12.812321

  34. Hilal I, Van Sint Jan S, Leardini A, Della Croce U (2002) Technical report on data collection procedure—annex i, project number: 10954. Project title: virtual animation of the kinematics of the human for industrial, educational and research purposes

  35. Majstorovic V, Trajanovic M, Vitkovic N, Stojkovic M (2013) Reverse engineering of human bones by using method of anatomical features. CIRP Ann Manuf Technol 62(2013):167–170

    Article  Google Scholar 

  36. Tufegdzic M, Arsic S, Trajanovic M (2016) Predictive geometrical model of the upper extremity of human fibula. Biocybern Biomed Eng 36(1):172–181. https://doi.org/10.1016/j.bbe.2015.12.003

    Article  Google Scholar 

Download references

Acknowledgements

The paper is part of the project III41017 - Virtual human osteoarticular system and its application in preclinical and clinical practice, sponsored by the Ministry of Education, Science and Technology development of the Republic of Serbia for the period 2011–2017.

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Correspondence to Milica Tufegdzic.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the Medical University of Warsaw and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Trajanovic, M., Tufegdzic, M. & Arsic, S. Obtaining patient-specific point model of the human ilium bone in the case of incomplete volumetric data using the method of parametric regions. Australas Phys Eng Sci Med 41, 931–944 (2018). https://doi.org/10.1007/s13246-018-0689-9

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