Rootlets-based registration to the PAM50 spinal cord template.

Imaging neuroscience (Cambridge, Mass.) Pub Date : 2025-08-26 eCollection Date: 2025-01-01 DOI:10.1162/IMAG.a.123
Sandrine Bédard, Jan Valošek, Valeria Oliva, Kenneth A Weber Ii, Julien Cohen-Adad
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Abstract

Spinal cord functional MRI studies require precise localization of spinal levels for reliable voxel-wise group analyses. Traditional template-based registration of the spinal cord uses intervertebral discs for alignment. However, substantial anatomical variability across individuals exists between vertebral and spinal levels. This study proposes a novel registration approach that leverages spinal nerve rootlets to improve alignment accuracy and reproducibility across individuals. We developed a registration method leveraging dorsal cervical rootlets segmentation and aligning them non-linearly with the PAM50 spinal cord template. Validation was performed on a multi-subject, multi-site dataset (n = 267, 44 sites) and a multi-subject dataset with various neck positions (n = 10, 3 sessions). We further validated the method on task-based functional MRI (n = 23) to compare group-level activation maps using rootlet-based registration to traditional disc-based methods. Rootlet-based registration showed superior alignment across individuals compared with the traditional disc-based method on n = 226 individuals, and on n = 176 individuals for morphological analyses. Notably, rootlet positions were more stable across neck positions. Group-level analysis of task-based functional MRI using rootlet-based registration increased Z scores and activation cluster size compared with disc-based registration (number of active voxels from 3292 to 7978). Rootlet-based registration enhances both inter- and intra-subject anatomical alignment and yields better spatial normalization for group-level fMRI analyses. Our findings highlight the potential of rootlet-based registration to improve the precision and reliability of spinal cord neuroimaging group analysis.

基于rootlets的PAM50脊髓模板注册。
脊髓功能MRI研究需要精确定位脊髓水平,以进行可靠的体素组分析。传统的基于模板的脊髓注册使用椎间盘对齐。然而,在个体之间存在椎体和脊柱水平的大量解剖学差异。本研究提出了一种新的定位方法,利用脊神经根来提高个体间的对准精度和可重复性。我们开发了一种利用颈背根分割并将其与PAM50脊髓模板非线性对齐的配准方法。在多受试者、多站点数据集(n = 267,44个站点)和不同颈部位置的多受试者数据集(n = 10,3次)上进行验证。我们进一步在基于任务的功能MRI上验证了该方法(n = 23),比较了使用基于根的配准方法和传统的基于磁盘的方法的组级激活图。在n = 226个个体和n = 176个个体的形态分析中,基于根茎的配准结果优于传统的基于圆盘的配准方法。值得注意的是,根茎位置在颈部位置上更加稳定。与基于磁盘的配准(活动体素数从3292到7978)相比,使用基于根块的配准的基于任务的功能MRI组水平分析增加了Z分数和激活簇大小。基于根茎的配准增强了受试者之间和受试者内部的解剖对齐,并为群体水平的fMRI分析提供了更好的空间归一化。我们的研究结果强调了基于根的配准在提高脊髓神经影像学组分析的准确性和可靠性方面的潜力。
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