Spatial Consistency in 3D Tract-Based Clustering Statistics

Authors:
Matthan Caan;Lucas Vliet;Charles Majoie;Eline Aukema;Kees Grimbergen;Frans Vos
Affiliations:
Department of Radiology, Academic Medical Center, University of Amsterdam, and Quantitative Imaging Group, Delft University of Technology,;Quantitative Imaging Group, Delft University of Technology,;Department of Radiology, Academic Medical Center, University of Amsterdam,;Department of Radiology, Academic Medical Center, University of Amsterdam,;Department of Radiology, Academic Medical Center, University of Amsterdam,;Department of Radiology, Academic Medical Center, University of Amsterdam, and Quantitative Imaging Group, Delft University of Technology,
Venue:
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Year:
2008

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Abstract

We propose a novel technique for tract-based comparison of DTI-indices between groups, based on a representation that is estimated while matching fiber tracts. The method involves a non-rigid registration based on a joint clustering and matching approach, after which a 3D-atlas of cluster center points is used as a frame of reference for statistics. Patient and control FA-distributions are compared per cluster. Spatial consistency is taken to reflect a significant difference between groups. Accordingly, a non-parametric classification is performed to assess the continuity of pathology over larger tract regions. In a study to infant survivors treated for medulloblastoma with intravenous methotrexate and cranial radiotherapy, significant decreases in FA in major parts of the corpus callosum were found.