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Multivariate Hippocampal Subfield Analysis of Local MRI Intensity and Volume: Application to Temporal Lobe Epilepsy

  • Hosung Kim
  • Boris C. Bernhardt
  • Jessie Kulaga-Yoskovitz
  • Benoit Caldairou
  • Andrea Bernasconi
  • Neda Bernasconi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8674)

Abstract

We propose a multispectral MRI-based clinical decision support approach to carry out automated seizure focus lateralization in patients with temporal lobe epilepsy (TLE). Based on high-resolution T1- and T2-weighted MRI with hippocampal subfield segmentations, our approach samples MRI features along the medial sheet of each subfield to minimize partial volume effects. To establish correspondence of sampling points across subjects, we propagate a spherical harmonic parameterization derived from the hippocampal boundary along a Laplacian gradient field towards the medial sheet. Volume and intensity data sampled on the medial sheet are finally fed into a supervised classifier. Testing our approach in TLE patients in whom the seizure focus could not be lateralized using conventional MR volumetry, the proposed approach correctly lateralized all patients and outperformed classification performance based on global subfield volumes or mean T2-intensity (100% vs. 68%). Moreover, statistical group-level comparisons revealed patterns of subfield abnormalities that were not evident in the global measurements and that largely agree with known histopathological changes.

Keywords

multispectral MRI computerized clinical decision support system hippocampal subfield analysis epilepsy 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Hosung Kim
    • 1
  • Boris C. Bernhardt
    • 1
  • Jessie Kulaga-Yoskovitz
    • 1
  • Benoit Caldairou
    • 1
  • Andrea Bernasconi
    • 1
  • Neda Bernasconi
    • 1
  1. 1.Department of Neurology and McConnell Brain Imaging Center, Montreal Neurological Institute and HospitalMcGill University, MontrealQuebecCanada

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