PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space

Abstract : Template-based analysis of multi-parametric MRI data of the spinal cord sets the foundation for standardization and reproducibility, thereby helping the discovery of new biomarkers of spinal-related diseases. While MRI templates of the spinal cord have been recently introduced, none of them cover the entire spinal cord. In this study, we introduced an unbiased multimodal MRI template of the spinal cord and the brainstem, called PAM50, which is anatomically compatible with the ICBM152 brain template and uses the same coordinate system. The PAM50 template is based on 50 healthy subjects, covers the full spinal cord (C1 to L2 vertebral levels) and the brainstem, is available for T1-, T2-and T2*-weighted MRI contrasts and includes a probabilistic atlas of the gray matter and white matter tracts. Template creation accuracy was assessed by computing the mean and maximum distance error between each individual spinal cord centerline and the PAM50 centerline, after registration to the template. Results showed high accuracy for both T1- (mean = 0.37 ± 0.06 mm; max = 1.39 ± 0.58 mm) and T2-weighted (mean = 0.11 ± 0.03 mm; max = 0.71 ± 0.27 mm) contrasts. Additionally, the preservation of the spinal cord topology during the template creation process was verified by comparing the cross-sectional area (CSA) profile, averaged over all subjects, and the CSA profile of the PAM50 template. The fusion of the PAM50 and ICBM152 templates will facilitate group and multi-center studies of combined brain and spinal cord MRI, and enable the use of existing atlases of the brainstem compatible with the ICBM space.
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Submitted on : Thursday, December 7, 2017 - 11:31:07 AM
Last modification on : Wednesday, July 17, 2019 - 9:42:09 AM

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Benjamin de Leener, Vladimir S. Fonov, D. Louis Collins, Virginie Callot, Nikola Stikov, et al.. PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space. NeuroImage, Elsevier, 2017, ⟨10.1016/j.neuroimage.2017.10.041⟩. ⟨hal-01657949⟩

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