OBJECT: Our goal was to build a probabilistic atlas and anatomical template of the human cervical and thoracic spinal cord (SC) that could be used for segmentation algorithm improvement, parametric group studies, and enrichment of biomechanical modelling. MATERIALS AND METHODS: High-resolution axial T2*-weighted images were acquired at 3T on 15 healthy volunteers using a multi-echo-gradient-echo sequence (1 slice per vertebral level from C1 to L2). After manual segmentation, linear and affine co-registrations were performed providing either inter-individual morphometric variability maps, or substructure probabilistic maps [CSF, white and grey matter (WM/GM)] and anatomical SC template. RESULTS: The larger inter-individual morphometric variations were observed at the thoraco-lumbar levels and in the posterior GM. Mean SC diameters were in agreement with the literature and higher than post-mortem measurements. A representative SC MR template was generated and values up to 90 and 100% were observed on GM and WM-probability maps. CONCLUSION: This work provides a probabilistic SC atlas and a template that could offer great potentialities for parametrical MRI analysis (DTI/MTR/fMRI) and group studies, similar to what has already been performed using a brain atlas. It also offers great perspective for biomechanical models usually based on post-mortem or generic data. Further work will consider integration into an automated SC segmentation pipeline.
OBJECT: Our goal was to build a probabilistic atlas and anatomical template of the human cervical and thoracic spinal cord (SC) that could be used for segmentation algorithm improvement, parametric group studies, and enrichment of biomechanical modelling. MATERIALS AND METHODS: High-resolution axial T2*-weighted images were acquired at 3T on 15 healthy volunteers using a multi-echo-gradient-echo sequence (1 slice per vertebral level from C1 to L2). After manual segmentation, linear and affine co-registrations were performed providing either inter-individual morphometric variability maps, or substructure probabilistic maps [CSF, white and grey matter (WM/GM)] and anatomical SC template. RESULTS: The larger inter-individual morphometric variations were observed at the thoraco-lumbar levels and in the posterior GM. Mean SC diameters were in agreement with the literature and higher than post-mortem measurements. A representative SC MR template was generated and values up to 90 and 100% were observed on GM and WM-probability maps. CONCLUSION: This work provides a probabilistic SC atlas and a template that could offer great potentialities for parametrical MRI analysis (DTI/MTR/fMRI) and group studies, similar to what has already been performed using a brain atlas. It also offers great perspective for biomechanical models usually based on post-mortem or generic data. Further work will consider integration into an automated SC segmentation pipeline.
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Authors: Nico Papinutto; Regina Schlaeger; Valentina Panara; Eduardo Caverzasi; Sinyeob Ahn; Kevin J Johnson; Alyssa H Zhu; William A Stern; Gerhard Laub; Stephen L Hauser; Roland G Henry Journal: J Magn Reson Imaging Date: 2014-12-08 Impact factor: 4.813
Authors: Regina Schlaeger; Nico Papinutto; Valentina Panara; Carolyn Bevan; Iryna V Lobach; Monica Bucci; Eduardo Caverzasi; Jeffrey M Gelfand; Ari J Green; Kesshi M Jordan; William A Stern; H-Christian von Büdingen; Emmanuelle Waubant; Alyssa H Zhu; Douglas S Goodin; Bruce A C Cree; Stephen L Hauser; Roland G Henry Journal: Ann Neurol Date: 2014-08-21 Impact factor: 10.422
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