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Computerized Atlas-Guided Positioning of Deep Brain Stimulators: A Feasibility Study

  • Benoit M. Dawant
  • Rui Li
  • Ebru Cetinkaya
  • C. Kao
  • J. Michael Fitzpatrick
  • Peter E. Konrad
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2717)

Abstract

Optimal placement of a deep brain stimulator (DBS) is an iterative procedure. A target is chosen preoperatively based on anatomical landmarks identified on MR images. This point is used as an initial position that is refined intraoperatively using both micro-electrode recordings and macrostimulation. Because the length of the procedure increases with the time it takes to adjust the DBS to its final position, a good initial position is critical. In this work we ex- plore the possibility of using an atlas and non-rigid registration algorithms to select the initial position automatically. We compare the initial DBS position obtained with this approach and the initial position selected by a neurosurgeon with the final position for eight STN (subthalamic nucleus) cases. Our results show that the automatic method leads to initial positions that are closer to the final positions than the initial positions selected manually.

Keywords

Deep Brain Stimulator Final Position Essential Tremor Fiducial Marker Stereotactic Neurosurgery 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Deuschl, R.G., Volkmann, J., Krack, P.: Deep brain stimulation for movement disorders. Movement Disorders 17 (Suppl. 3), S1-S1 (2002)Google Scholar
  2. 2.
    Schrader, B., Hamel, W., Weinert, D., Mehdorn, H.M.: Documentation of electrode localization. Movement Disorders 17 (Suppl. 3), S167-S174 (2002)Google Scholar
  3. 3.
    Vitek, J.L.: Mechanisms of deep brain stimulation: excitation or inhibition. Mov Disord 17 (Suppl. 3), S69-S72 (2002)Google Scholar
  4. 4.
    Lozano, A.M.: Deep brain stimulation for Parkinson’s disease  7(3), 199–203 (2001)Google Scholar
  5. 5.
    Galloway, R.L., Maciunas, R.J.: Stereotactic neurosurgery. Crit. Rev. Biomed. Eng. 18(3), 181–205 (1990)Google Scholar
  6. 6.
    Franck, J., Konrad, P., Franklin, R., Haer, F., Hawksley, D.: STarFix: A Novel Approach to Frameless Stereotactic Neurosurgery Utilizing a Miniaturized Customized Pretargeted Cranial Platform Fixture – Technical Description, Unique Features, and Case Reports. In: Movement Disorders Society, 7th Intl. Congress of Parkinsons Disease & Movement Disorder, Miami, FL (November 2002)Google Scholar
  7. 7.
    Maurer Jr., C.R., Fitzpatrick, J.M., Wang, M.Y., Galloway Jr., R.L., Maciunas, R.J., Allen, G.S.: Registration of head volume images using implantable fiducial markers. IEEE Trans. Med. Imaging 16, 447–462 (1997)CrossRefGoogle Scholar
  8. 8.
    Thirion, J.-P.: “Image matching as a diffusion process: an analogy with Maxwell’s demons. Medical Image Analysis 2(3), 243–260 (1998)CrossRefGoogle Scholar
  9. 9.
    Rhode, G., Aldroubi, A., Dawant, B.M.: The Adaptive-bases algorithm for intensitybased nonrigid image registration. IEEE Transactions on Medical Imaging (2003) (in press)Google Scholar
  10. 10.
    Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L.G., Leach, M.O., Hawkes, D.J.: Nonrigid Registration Using Free-Form Deformations: Application to Breast MR Images. IEEE Transactions on Medical Imaging 18(8), 712–721 (1999)CrossRefGoogle Scholar
  11. 11.
    Meyer, C.R., et al.: Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate. Medical Image Analysis 3, 195–206 (1997)CrossRefGoogle Scholar
  12. 12.
    Maes, F., Collignon, A., Suetens, P.: Multimodality image registration by maximization of mutual information. IEEE Transaction on Medical Imaging 16(2), 187–198 (1997)CrossRefGoogle Scholar
  13. 13.
    Atkinson, J.D., Collins, D.L., Bertrand, G., Peters, T.M., Pike, G.B., Sadikot, A.F.: Optimal location of thalamotomy lesions for tremor associated with Parkinson Disease: a probabilistic analysis based on postoperative magnetic resonance imaging and an integrated digital atlas. J. Neurosurgery 96, 854–866 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Benoit M. Dawant
    • 1
  • Rui Li
    • 1
  • Ebru Cetinkaya
    • 1
  • C. Kao
    • 2
  • J. Michael Fitzpatrick
    • 1
  • Peter E. Konrad
    • 2
  1. 1.Department of Electrical Engineering and Computer ScienceVanderbilt UniversityNashville
  2. 2.Department of Neurological SurgeryVanderbilt UniversityNashville

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