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3D Models of Female Pelvis Structures Reconstructed and Represented in Combination with Anatomical and Radiological Sections

  • L. Asensio RomeroEmail author
  • M. Asensio Gómez
  • A. Prats-Galino
  • J. A. Juanes Méndez
Education & Training
  • 213 Downloads
Part of the following topical collections:
  1. Emergent Visualization Systems in Biomedical Sciences (TEEM 2017)

Abstract

We present a computer program designed to visualize and interact with three-dimensional models of the main anatomical structures of the female pelvis. They are reconstructed from serial sections of corpse, from the Visible Human project of the Medical Library of the United States and from serial sections of high-resolution magnetic resonance. It is possible to represent these three-dimensional structures in any spatial orientation, together with sectional images of corpse and magnetic resonance imaging, in the three planes of space (axial, coronal and sagittal) that facilitates the anatomical understanding and the identification of the set of visceral structures of this body region. Actually, there are few studies that analysze in detail the radiological anatomy of the female pelvis using three-dimensional models together with sectional images, making use of open applications for the representation of virtual scenes on low cost Windows® platforms. Our technological development allows the observation of the main female pelvis viscera in three dimensions with a very intuitive graphic interface. This computer application represents an important training tool for both medical students and specialists in gynecology and as a preliminary step in the planning of pelvic floor surgery.

Keywords

Three-dimensional models Corpse sections visible human project Radiological female pelvis anatomy Corpse female pelvis anatomy High resolution magnetic resonance Computer development 

Notes

Compliance with Ethical Standards

Conflict of Interest

L. Asensio Romero declares that she has no conflict of interest. M. Asensio Gómez declares that he has no conflict of interest. A. Prats-Galino declares that he has no conflict of interest. J. A. Juanes Méndez declares that he has no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    Pujol, S., Baldwin, M., Nassiri, J., Kikinis, R., and Shaffer, K., Using 3D modeling techniques to enhance teaching of difficult anatomical concepts. Acad. Radiol. 23(4):507–516, 2016.  https://doi.org/10.1016/j.acra.2015.12.012.CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Legendre, G., Sahmoune Rachedi, L., Descamps, P., and Fernandez, H., Providing of a virtual simulator perineal anatomy (pelvic mentor®) in learning pelvic perineology: Results of a preliminary study. J. Gynecol. Obstet. Biol. Reprod. 44(1):72–77, 2014.  https://doi.org/10.1016/j.jgyn.2014.04.004.CrossRefGoogle Scholar
  3. 3.
    Fang, B., Wu, Y., Chu, C., Li, Y., Luo, N., Liu, K., Tan, L., and Zhang, S., Creation of a virtual anatomy system based on Chinese visible human data sets. Surg. Radiol. Anat. 39(4):441–449, 2017.  https://doi.org/10.1007/s00276-016-1741-7.CrossRefPubMedGoogle Scholar
  4. 4.
    Ghosh, S.K., Evolution of illustrations in anatomy: A study from the classical period in Europe to modern times. Anat. Sci. Educ. 8(2):175–188, 2015.  https://doi.org/10.1002/ase.1479.CrossRefPubMedGoogle Scholar
  5. 5.
    Abdulaziz, M., Deegan, E.G., Kavanagh, A., Stothers, L., Pugash, D., and Macnab, A., Advances in basic science methodologies for clinical diagnosis in female stress urinary incontinence. Can. Urol. Assoc. J. 11(6,2):117–120, 2017.  https://doi.org/10.5489/cuaj.4583.CrossRefGoogle Scholar
  6. 6.
    Balaya, V., Uhl, J.F., Lanore, A., Salachas, C., Samoyeau, T., Ngo, C., Bensaid, C., Cornou, C., Rossi, L., Douard, R., Bats, A.S., Lecuru, F., and Delmas, V., 3D modeling of the female pelvis by computer-assisted anatomical dissection: Applications and perspectives. J. Gynecol. Obstet. Biol. Reprod. 45(5):467–477, 2016.  https://doi.org/10.1016/j.jgyn.2016.01.006.CrossRefGoogle Scholar
  7. 7.
    Shin, D.S., Jang, H.G., Hwang, S.B., Har, D.H., Moon, Y.L., and Chung, M.S., Two-dimensional sectioned images and three-dimensional surface models for learning the anatomy of the female pelvis. Am. Assoc. Anatomists. 6:316–323, 2013.  https://doi.org/10.1002/ase.1342.Google Scholar
  8. 8.
    Kraima, A.C., Smit, N.N., Jansma, D., Wallner, C., Bleys, R.L., van de Velde, C.J., Botha, C.P., and DeRuiter, M.C., Toward a highly-detailed 3D pelvic model: Approaching an ultra-specific level for surgical simulation and anatomical education. Clin. Anat. 26(3):333–338, 2013.  https://doi.org/10.1002/ca.22207.CrossRefPubMedGoogle Scholar
  9. 9.
    Ackerman, M.J., The visible human project®: From body to bits. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2016:3338–3341, 2016.  https://doi.org/10.1109/EMBC.2016.7591442.PubMedGoogle Scholar
  10. 10.
    Noetscher, G.M., Yanamadala, J., Tankaria, H., Louie, S., Prokop, A., Nazarian, A., and Makarov, S.N., Computational human model VHP-FEMALE derived from datasets of the national library of medicine. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2016:3350–3353, 2016.  https://doi.org/10.1109/EMBC.2016.7591445.PubMedGoogle Scholar
  11. 11.
    Yanamadala, J., Noetscher, G.M., Louie, S., Prokop, A., Kozlov, M., Nazarian, A., and Makarov, S.N., Multi-purpose VHP-female version 3.0 cross-platform computational human model. Conf. Proc. IEEE Antennas Propag. (EuCAP). 2016:1–5, 2016.  https://doi.org/10.1109/EuCAP.2016.7481298.Google Scholar
  12. 12.
    Rea P.M., Advances in anatomical and medical visualisation. In Pinheiro MM, Simões D (ed) Handbook of Research on Engaging Digital Natives in Higher Education Settings. Aveiro, pp 244–264, 2016.  https://doi.org/10.4018/978-1-5225-0039-1.ch011
  13. 13.
    Berney, S., Bétrancourt, M., Molinari, G., and Hoyek, N., How spatial abilities and dynamic visualizations interplay when learning functional anatomy with 3D anatomical models. Anat. Sci. Educ. 8(5):452–462, 2015.  https://doi.org/10.1002/ase.1524.CrossRefPubMedGoogle Scholar
  14. 14.
    Tabernero Rico, R.D., Juanes Méndez, J.A., and Prats Galino, A., New generation of three-dimensional tools to learn anatomy. J. Med. Syst. 41(5):88, 2017.  https://doi.org/10.1007/s10916-017-0725-4.CrossRefPubMedGoogle Scholar
  15. 15.
    An, G., Hong, L., Zhou, X.B., Yang, Q., Li, M.Q., and Tang, X.Y., Accuracy and efficiency of computer-aided anatomical analysis using 3D visualization software based on semi-automated and automated segmentations. Ann. Anat. 210:76–83, 2017.  https://doi.org/10.1016/j.aanat.2016.11.009.CrossRefPubMedGoogle Scholar
  16. 16.
    Fenesi, B., Mackinnon, C., Cheng, L., Kim, J.A., and Wainman, B.C., The effect of image quality, repeated study, and assessment method on anatomy learning. Anat. Sci. Educ. 10(3):249–261, 2017.  https://doi.org/10.1002/ase.1657.CrossRefPubMedGoogle Scholar
  17. 17.
    Preece, D., Williams, S., Lam, R., and Weller, R., Let's get physical: Advantages of a physical model over 3D computer models and textbooks in learning imaging anatomy. Anat. Sci. Educ. 6(4):216–224, 2013.  https://doi.org/10.1002/ase.1345.CrossRefPubMedGoogle Scholar
  18. 18.
    Estai, M., and Bunt, S., Best teaching practices in anatomy education: A critical review. Ann. Anat. -Anatomischer Anzeiger. 208:151–157, 2016.  https://doi.org/10.1016/j.aanat.2016.02.010.CrossRefPubMedGoogle Scholar
  19. 19.
    Peterson, D.C., and Mlynarczyk, G.S., Analysis of traditional versus three-dimensional augmented curriculum on anatomical learning outcome measures. Anat. Sci. Educ. 9(6):529–536, 2016.  https://doi.org/10.1002/ase.1612.CrossRefPubMedGoogle Scholar
  20. 20.
    Trelease, R.B., From chalkboard, slides, and paper to e-learning: How computing technologies have transformed anatomical sciences education. Anat. Sci. Educ. 9(6):583–602, 2016.  https://doi.org/10.1002/ase.1620.CrossRefPubMedGoogle Scholar
  21. 21.
    Wohlrab, K., Jelovsek, E., and Myers, D., Incorporating simulation into gynecologic surgical training. Am. J. Obstet. Gynecol. 217(5):522–526, 2017.  https://doi.org/10.1016/j.ajog.2017.05.017.CrossRefPubMedGoogle Scholar
  22. 22.
    Barbeito, A., Painho, M., Cabral, P., and O'Neill, J.G., Beyond digital human body atlases: Segmenting an integrated 3D topological model of the human body. Int. J. E-Health Med. Commun. (IJEHMC). 8(1):19–36, 2017.  https://doi.org/10.4018/IJEHMC.2017010102.CrossRefGoogle Scholar
  23. 23.
    Brown, K., Handa, V., Macura, K., and DeLeon, V., Three-dimensional shape differences in the bony pelvis of women with pelvic floor disorders. Int. Urogynecol. J.: Including Pelvic Floor Dysfunction. 24(3):431–439, 2013.  https://doi.org/10.1007/s00192-012-1876-y.CrossRefGoogle Scholar
  24. 24.
    Moore, C.W., Wilson, T.D., and Rice, C.L., Digital preservation of anatomical variation: 3D-modeling of embalmed and plastinated cadaveric specimens using μCT and MRI. Ann. Anat. -Anatomischer Anzeiger. 209:69–75, 2017.  https://doi.org/10.1016/j.aanat.2016.09.010.CrossRefPubMedGoogle Scholar
  25. 25.
    Bertrand, M., Macri, F., Mazars, R., Droupy, S., Beregi, J., and Prudhomme, M., MRI-based 3D pelvic autonomous innervation: A first step towards image-guided pelvic surgery. Eur. Radiol. 24(8):1989–1997, 2014.  https://doi.org/10.1007/s00330-014-3211-0.CrossRefPubMedGoogle Scholar
  26. 26.
    Yiasemidou, M., Glassman, D., Mushtaq, F., Athanasiou, C., Williams, M.M., Jayne, D., and Miskovic, D., Mental practice with interactive 3D visual aids enhances surgical performance. Surg. Endosc. Interventional Techniques. 31(10):4111–4117, 2017.  https://doi.org/10.1007/s00464-017-5459-3.CrossRefGoogle Scholar
  27. 27.
    Peng, Y., Khavari, R., Nakib, N.A., Boone, T.B., and Zhang, Y., Assessment of urethral support using mRI-derived computational modeling of the female pelvis. Int. Urogynecol. J. 27(2):205–212, 2016.  https://doi.org/10.1007/s00192-015-2804-8.CrossRefPubMedGoogle Scholar
  28. 28.
    Chen, L., Lenz, F., Alt, C.D., Sohn, C., De Lancey, J.O., and Brocker, K.A., MRI visible Fe3O4 polypropylene mesh: 3D reconstruction of spatial relation to bony pelvis and neurovascular structures. Int. Urogynecol. J. Pelvic Floor Dysfunct. 28(8):1131–1138, 2017.  https://doi.org/10.1007/s00192-017-3263-1.CrossRefGoogle Scholar
  29. 29.
    Doumouchtsis, S.K., Nazarian, D.A., Gauthaman, N., Durnea, C.M., and Munneke, G., Three-dimensional volume rendering of pelvic models and paraurethral masses based on MRI cross-sectional images. Int. Urogynecol. J. 28:1–9, 2017.  https://doi.org/10.1007/s00192-017-3317-4.CrossRefGoogle Scholar
  30. 30.
    Giannini, A., Iodice, V., Picano, E., Russo, E., Zampa, V., Ferrari, V., and Simoncini, T., Magnetic resonance imaging–based three dimensional patient-specific reconstruction of uterine fibromatosis: Impact on surgery. J. Gynecol. Surg. 33(4):138–144, 2017.  https://doi.org/10.1089/gyn.2016.0119.CrossRefGoogle Scholar
  31. 31.
    Smit, N., Lawonn, K., Kraima, A., DeRuiter, M., Sokooti, H., Bruckner, S., Eisemann, E., and Vilanova, A., PelVis: Atlas-based surgical planning for oncological pelvic surgery. IEEE Trans. Vis. Comput. Graph. 23(1):741–750, 2017.  https://doi.org/10.1109/TVCG.2016.2598826.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Human Anatomy and Histology, School of MedicineUniversity of SalamancaSalamancaSpain
  2. 2.Department of Human Anatomy and Embryology, School of MedicineUniversity of BarcelonaBarcelonaSpain

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