Advertisement

3D Organ Motion Prediction for MR-Guided High Intensity Focused Ultrasound

  • Patrik Arnold
  • Frank Preiswerk
  • Beat Fasel
  • Rares Salomir
  • Klaus Scheffler
  • Philippe C. Cattin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6892)

Abstract

MR-guided High Intensity Focused Ultrasound is an emerging non-invasive technique capable of depositing sharply localised energy deep within the body, without affecting the surrounding tissues. This, however, implies exact knowledge of the target’s position when treating mobile organs. In this paper we present an atlas-based prediction technique that trains an atlas from time-resolved 3D volumes using 4DMRI, capturing the full patient specific motion of the organ. Based on a breathing signal, the respiratory state of the organ is then tracked and used to predict the target’s future position. To additionally compensate for the non-periodic slower organ drifts, the static motion atlas is combined with a population-based statistical exhalation drift model. The proposed method is validated on organ motion data of 12 healthy volunteers. Experiments estimating the future position of the entire liver result in an average prediction error of 1.1 mm over time intervals of up to 13 minutes.

Keywords

Motion Compensation Motion Prediction Organ Motion Drift Model Future Position 
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.

References

  1. 1.
    Keall, P., Mageras, G., Balter, J., Emery, R., Forster, K., Jliang, S., Kapatoes, J., Low, D., Murphy, M., Ramsey, B.M.C., Herk, M.V., Vedam, S., Wong, J., Yorke, E.: The management of respiratory motion in radiation oncology report of AAPM task group. Med. Phys. 33, 3874–3900 (2006)CrossRefGoogle Scholar
  2. 2.
    Webb, S.: Motion effects in (intensity modulated) radiation therapy. Phys. Med. Biol. 51, R403–R425 (2006)Google Scholar
  3. 3.
    Pernot, M., Tanter, M., Fink, M.: 3-D real-time motion correction in high-intensity focused ultrasound therapy. Ultrasound in Medicine and Biology 30(9), 1239–1249 (2004)CrossRefGoogle Scholar
  4. 4.
    Ries, M., de Senneville, B.D., Roujol, S., Berber, Y., Quesson, B., Moonen, C.: Real-time 3D target tracking in mri guided focused ultrasound ablations in moving tissues. Magnetic Resonance in Medicine 64, 1704–1712 (2010)CrossRefGoogle Scholar
  5. 5.
    von Siebenthal, M., Szekely, G., Gamper, U., Boesiger, P., Lomax, A., Cattin, P.: 4D MR imaging of respiratory organ motion and its variability. Phys. in Med. Biol. 52, 1547–1564 (2007)CrossRefGoogle Scholar
  6. 6.
    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. Transactions on Medical Imaging 18, 712–721 (1999)CrossRefGoogle Scholar
  7. 7.
    von Siebenthal, M., Szekely, G., Lomax, A.J., Cattin, P.C.: Systematic errors in respiratory gating due to intrafraction deformations of the liver. Med. Phys. 34, 3620–3629 (2007)CrossRefGoogle Scholar
  8. 8.
    von Siebenthal, M., Székely, G., Lomax, A., Cattin, P.C.: Inter-subject modelling of liver deformation during radiation therapy. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part I. LNCS, vol. 4791, pp. 659–666. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Blanz, V., Vetter, T.: Reconstructing the complete 3D shape of faces from partial information. Informationstechnik und Technische Informatik 44, 295–302 (2002)Google Scholar
  10. 10.
    Vedam, S., Kini, V.R., Keall, P.J., Ramakrishnan, V., Mostafavi, H., Mohan, R.: Quantifying the predictability of diaphragm motion during respiration with a noninvasive external marker. Med. Phys. 30, 505–513 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Patrik Arnold
    • 1
  • Frank Preiswerk
    • 1
  • Beat Fasel
    • 1
  • Rares Salomir
    • 1
  • Klaus Scheffler
    • 1
  • Philippe C. Cattin
    • 1
  1. 1.Medical Image Analysis CenterUniversity of BaselBaselSwitzerland

Personalised recommendations