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Validation of Experts versus Atlas-based and Automatic Registration Methods for Subthalamic Nucleus Targeting on MRI

Castro, F. ; Pollo, Claudio ; Cuisenaire, Olivier ; Villemure, Jean-Guy ; Thiran, Jean-Philippe

In: International Journal of Computer Assisted Radiology and Surgery, 2006, vol. 1, no. 1, p. 5-12

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    Titre
    • Validation of Experts versus Atlas-based and Automatic Registration Methods for Subthalamic Nucleus Targeting on MRI
    Auteur
    • Castro, F.. Signal Processing Institute, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
    • Pollo, Claudio. Signal Processing Institute, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
    • Cuisenaire, Olivier. Signal Processing Institute, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
    • Villemure, Jean-Guy. Signal Processing Institute, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
    • Thiran, Jean-Philippe. Department of Neurosurgery, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • International Journal of Computer Assisted Radiology and Surgery, 2006, vol. 1, no. 1, p. 5-12. Springer-Verlag
    Autre version électronique
    Classification
    • Santé
    Identifiant OAI-PMH
    • oai:doc.rero.ch:319671
    Summary
    Objects In functional stereotactic neurosurgery, one of the cornerstones upon which the success and the operating time depends is an accurate targeting. The subthalamic nucleus (STN) is the usual target involved when applying deep brain stimulation for Parkinson's disease (PD). Unfortunately, STN is usually not clearly visible in common medical imaging modalities, which justifies the use of atlas-based segmentation techniques to infer the STN location. Materials and methods Eight bilaterally implanted PD patients were included in this study. A three-dimensional T1-weighted sequence and inversion recovery T2-weighted coronal slices were acquired pre-operatively. We propose a methodology for the construction of a ground truth of the STN location and a scheme that allows both, to perform a comparison between different non-rigid registration algorithms and to evaluate their usability to locate the STN automatically. Results The intra-expert variability in identifying the STN location is 1.06±0.61mm while the best non-rigid registration method gives an error of 1.80±0.62mm. On the other hand, statistical tests show that an affine registration with only 12 degrees of freedom is not enough for this application. Conclusions Using our validation-evaluation scheme, we demonstrate that automatic STN localization is possible and accurate with non-rigid registration algorithms