Advertisement

Annals of Biomedical Engineering

, Volume 46, Issue 11, pp 1951–1961 | Cite as

In Vivo Inspection of the Olfactory Epithelium: Feasibility of Robotized Optical Biopsy

  • Cédric Girerd
  • Thomas Lihoreau
  • Kanty Rabenorosoa
  • Brahim Tamadazte
  • Mourad Benassarou
  • Laurent Tavernier
  • Lionel Pazart
  • Emmanuel Haffen
  • Nicolas Andreff
  • Pierre Renaud
Article

Abstract

Inspecting the olfactory cleft can be of high interest, as it is an open access to neurons, and thus an opportunity to collect in situ related data in a non-invasive way. Also, recent studies show a strong link between olfactory deficiency and neurodegenerative diseases such as Alzheimer and Parkinson diseases. However, no inspection of this area is possible today, as it is very difficult to access. Only robot-assisted interventions seem viable to provide the required dexterity. The feasibility of this approach is demonstrated in this article, which shows that the path complexity to the olfactory cleft can be managed with a concentric tube robot (CTR), a particular type of continuum robot. First, new anatomical data are elaborated, in particular for the olfactory cleft, that remains hardly characterized. 3D reconstructions are conducted on the database of 20 subjects, using CT scan images. Measurements are performed to describe the anatomy, including metrics with inter-subject variability. Then, the existence of collision-free passageways for CTR is shown using the 3D reconstructions. Among the 20 subjects, 19 can be inspected using only 3 different robot geometries. This constitutes an essential step towards a robotic device to inspect subjects for clinical purposes.

Keywords

Olfactory epithelium ENT Robot-assisted intervention Continuum robot OCT 

Notes

Acknowledgments

This work was supported by the French National Agency for Research within the Biomedical Innovation program (NEMRO ANR-14-CE17-0013), and the Investissements d’Avenir (Robotex ANR-10-EQPX-44, Labex CAMI ANR-11-LABX-0004 and Labex ACTION ANR-11-LABX-0001-01).

Conflict of interest

No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this manuscript.

References

  1. 1.
    Aarli, J. A., T. Dua, A. Janca, and A. Muscetta. Neurological Disorders: Public Health Challenges. Geneva: World Health Organization, 2006, pp. 32.Google Scholar
  2. 2.
    Amorim, P., T. Moraes, J. Silva, and H. Pedrini. InVesalius: An interactive rendering framework for health care support. In: Advances in Visual Computing, 2015, vol. 9474, pp. 45–54.Google Scholar
  3. 3.
    AGILTRON. Miniature oct fiber probe. http://www.agiltron.com/PDFs/Miniature
  4. 4.
    Bergeles, C., A. H. Gosline, N. V. Vasilyev, P. J. Codd, P. J. del Nido, and P. E. Dupont. Concentric tube robot design and optimization based on task and anatomical constraints. IEEE Trans. Robot. 31(1):67–84, 2015.CrossRefGoogle Scholar
  5. 5.
    Bojsen-Moller, F. and J. Fahrenkrug. Nasal swell-bodies and cyclic changes in the air passage of the rat and rabbit nose. J. Anat. 110:25, 1971.Google Scholar
  6. 6.
    Bruyas, A., F. Geiskopf, and P. Renaud. Toward unibody robotic structures with integrated functions using multimaterial additive manufacturing: case study of an MRI-compatible interventional device. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, pp.1744–1750.Google Scholar
  7. 7.
    Bui, N. L., S. H. Ong, and K. W. C. Foong. Automatic segmentation of the nasal cavity and paranasal sinuses from cone-beam CT images.Int. J. Comput. Assist. Radiol. Surg. 10(8):1269–1277, 2015.CrossRefGoogle Scholar
  8. 8.
    Burgner-Kahrs, J., D. C. Rucker, and H. Choset. Continuum robots for medical applications: a survey. IEEE Trans. Robot. 31(6):1261–1280, 2015.CrossRefGoogle Scholar
  9. 9.
    Burgner, J., P. J. Swaney, R. Lathrop, K. D. Weaver, R. J. Webster et al. Debulking from within: a robotic steerable cannula for intracerebral hemorrhage evacuation. IEEE Trans. Biomed. Eng. 60(9):2567–2575, 2013.CrossRefGoogle Scholar
  10. 10.
    Butler, E. J., R. Hammond-Oakley, S. Chawarski, A. H. Gosline, P. Codd, T. Anor, J. R. Madsen, P. E. Dupont, and J. Lock. Robotic neuro-endoscope with concentric tube augmentation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012, pp.2941–2946.Google Scholar
  11. 11.
    Cignoni, P., M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, and G. Ranzuglia. MeshLab: an open-source mesh processing tool. In: Sixth Eurographics Italian Chapter Conference, 2008, pp.129–136.Google Scholar
  12. 12.
    Costanzo, R. M. Regeneration of olfactory receptor cells. Ciba Found. Symp. 160:233–248, 1991.Google Scholar
  13. 13.
    Doty, R. L. Olfactory dysfunction in Parkinson disease. Nat. Rev. Neurol. 8(6):329–339, 2012.CrossRefGoogle Scholar
  14. 14.
    Dryer, L. and P. Graziadei. Influence of the olfactory organ on brain development. Perspect. Dev. Neurobiol. 2(2):163–174, 1994.Google Scholar
  15. 15.
    Dupont, P. E., J. Lock, B. Itkowitz, and E. Butler. Design and control of concentric-tube robots. IEEE Trans. Robot. 26(2):209–225, 2010.CrossRefGoogle Scholar
  16. 16.
    Elwany, S., A. Medanni, M. Eid, A. Aly, A. El-Daly, and S. Ammar. Radiological observations on the olfactory fossa and ethmoid roof. J. Laryngol. Otol. 124(12):1251–1256, 2010.CrossRefGoogle Scholar
  17. 17.
    Escada, P. A., C. Lima, and J. M. da Silva. The human olfactory mucosa. Eur. Arch. Oto-Rhino-Laryngol. 124(12):1251–1256, 2010.Google Scholar
  18. 18.
    Flood, D. G. and P. D. Coleman. Neuron numbers and sizes in aging brain: comparisons of human, monkey, and rodent data. Neurobiol. Aging 9:453–463, 1988.CrossRefGoogle Scholar
  19. 19.
    Gilbert, H. B., J. Neimat, and R. J. Webster. Concentric tube robots as steerable needles: achieving follow-the-leader deployment. IEEE Trans. Robot. 31(2):246–258, 2015.CrossRefGoogle Scholar
  20. 20.
    Gladwin, K. and D. Choi. Olfactory ensheathing cells: part Icurrent concepts and experimental laboratory models. World Neurosurg. 83(1):114–119, 2015.CrossRefGoogle Scholar
  21. 21.
    Godoy, M. D. C. L., R. L. Voegels, F. de Rezende Pinna, R. Imamura, and J. M. Farfel. Olfaction in neurologic and neurodegenerative diseases: a literature review. Int. Arch. Otorhinolaryngol. 19(2):176–179, 2015.Google Scholar
  22. 22.
    Gopinath, B., K. J. Anstey, A. Kifley, and P. Mitchell. Olfactory impairment is associated with functional disability and reduced independence among older adults. Maturitas 72(1):50–55, 2012.CrossRefGoogle Scholar
  23. 23.
    Gosline, A. H., N. V. Vasilyev, E. J. Butler, C. Folk, A. Cohen, R. Chen, N. Lang, P. J. Del Nido, and P. E. Dupont. Percutaneous intracardiac beating-heart surgery using metal mems tissue approximation tools. Int. J. Robot. Res. 31(9):1081–1093, 2012.CrossRefGoogle Scholar
  24. 24.
    Hudson, T. C., M. C. Lin, J. Cohen, S. Gottschalk, and D. Manocha. V-COLLIDE: accelerated collision detection for VRML. In: Proceedings of the second symposium on Virtual reality modeling language, 1997, pp.117–123.Google Scholar
  25. 25.
    Jones, B. A. and I. D. Walker. Kinematics for multisection continuum robots. IEEE Trans. Robot. 22(1):43–55, 2006.CrossRefGoogle Scholar
  26. 26.
    Kalmey, J. K., J. Thewissen, and D. E. Dluzen. Age-related size reduction of foramina in the cribriform plate. Anat. Record 251(3):326–329, 1998.CrossRefGoogle Scholar
  27. 27.
    Kavoi, B. M. and H. Jameela. Comparative morphometry of the olfactory bulb, tract and stria in the human, dog and goat. Int. J. Morphol. 29(3):939–946, 2011.CrossRefGoogle Scholar
  28. 28.
    Lavoie, J., P. Gass Astorga, H. Segal-Gavish, Y. Wu, Y. Chung, N. Cascella, A. Sawa, and K. Ishizuka. The olfactory neural epithelium as a tool in neuroscience. Trends Mol. Med. 23(2):100–103, 2017.CrossRefGoogle Scholar
  29. 29.
    Lorensen, W. E. and H. E. Cline. Marching cubes: a high resolution 3D surface construction algorithm. SIGGRAPH Comput. Graph. 21(4):163–169, 1987.CrossRefGoogle Scholar
  30. 30.
    Moench, T., R. Gasteiger, G. Janiga, H. Theisel, and B. Preim. Context-aware mesh smoothing for biomedical applications. Comput. Graph. 35(4):755–767, 2011.CrossRefGoogle Scholar
  31. 31.
    Moon, C., S. J. Yoo, and H. S. Han. Smell, Encyclopedia of the Neurological Sciences, 2nd ed. Cambridge: Academic Press, 2014, pp. 216–220.Google Scholar
  32. 32.
    Renevier R., Tamadazte B., Rabenorosoa K., Tavernier L., and Andreff N. Endoscopic laser surgery: design, modeling and control. IEEE/ASME Trans. Mech. 22(1):99–106, 2017.CrossRefGoogle Scholar
  33. 33.
    Robert J. Webster, I. and B. A. Jones. Design and kinematic modeling of constant curvature continuum robots: a review. Int. J. Robot. Res. 29(13):1661–1683, 2010.CrossRefGoogle Scholar
  34. 34.
    Savvateeva, D. M., C. Güldner, T. Murthum, S. Bien, A. Teymoortash, J. A. Werner, and M. Bremke. Digital volume tomography (DVT) measurements of the olfactory cleft and olfactory fossa. Acta Oto-Laryngol. 130(3):398–404, 2010.CrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 2018

Authors and Affiliations

  • Cédric Girerd
    • 1
  • Thomas Lihoreau
    • 5
  • Kanty Rabenorosoa
    • 2
  • Brahim Tamadazte
    • 2
  • Mourad Benassarou
    • 4
  • Laurent Tavernier
    • 3
  • Lionel Pazart
    • 5
  • Emmanuel Haffen
    • 5
  • Nicolas Andreff
    • 2
  • Pierre Renaud
    • 1
  1. 1.AVR-ICube, CNRS, Université de Strasbourg, INSA StrasbourgStrasbourgFrance
  2. 2.FEMTO-ST InstituteUniv. Bourgogne Franche-Comté/CNRSBesançonFrance
  3. 3.Univ. Hospital of BesançonUniv. Bourgogne Franche-ComtéBesançonFrance
  4. 4.La Pitié Salpêtrière HospitalParisFrance
  5. 5.CIC Inserm 1431Univ. Hospital of Besançon, Univ. Bourgogne Franche-ComtéBesançonFrance

Personalised recommendations