Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
Hum Brain Mapp. 2021 Jan;42(1):220-232. doi: 10.1002/hbm.25218. Epub 2020 Sep 29.
To validate a simultaneous analysis tool for the brain and cervical cord embedded in the statistical parametric mapping (SPM) framework, we compared trauma-induced macro- and microstructural changes in spinal cord injury (SCI) patients to controls. The findings were compared with results obtained from existing processing tools that assess the brain and spinal cord separately. A probabilistic brain-spinal cord template (BSC) was generated using a generative semi-supervised modelling approach. The template was incorporated into the pre-processing pipeline of voxel-based morphometry and voxel-based quantification analyses in SPM. This approach was validated on T1-weighted scans and multiparameter maps, by assessing trauma-induced changes in SCI patients relative to controls and comparing the findings with the outcome from existing analytical tools. Consistency of the MRI measures was assessed using intraclass correlation coefficients (ICC). The SPM approach using the BSC template revealed trauma-induced changes across the sensorimotor system in the cord and brain in SCI patients. These changes were confirmed with established approaches covering brain or cord, separately. The ICC in the brain was high within regions of interest, such as the sensorimotor cortices, corticospinal tracts and thalamus. The simultaneous voxel-wise analysis of brain and cervical spinal cord was performed in a unique SPM-based framework incorporating pre-processing and statistical analysis in the same environment. Validation based on a SCI cohort demonstrated that the new processing approach based on the brain and cord is comparable to available processing tools, while offering the advantage of performing the analysis simultaneously across the neuraxis.
为了验证嵌入统计参数映射（SPM）框架中的大脑和颈椎脊髓的同步分析工具，我们将脊髓损伤（SCI）患者的创伤引起的宏观和微观结构变化与对照组进行了比较。将这些发现与分别评估大脑和脊髓的现有处理工具的结果进行了比较。使用生成式半监督建模方法生成了概率性的脑-脊髓模板（BSC）。该模板被纳入 SPM 中的基于体素的形态测量学和基于体素的定量分析的预处理流水线。通过评估相对于对照组的 SCI 患者的创伤引起的变化，并将结果与现有分析工具的结果进行比较，对 T1 加权扫描和多参数图上的这种方法进行了验证。使用组内相关系数（ICC）评估 MRI 测量的一致性。使用 BSC 模板的 SPM 方法揭示了 SCI 患者脊髓和大脑中感觉运动系统的创伤后变化。这些变化与涵盖大脑或脊髓的现有方法得到了证实。在感兴趣的区域，如感觉运动皮质、皮质脊髓束和丘脑内，大脑的 ICC 很高。大脑和颈椎脊髓的同时体素分析是在一个独特的基于 SPM 的框架中进行的，该框架在同一环境中进行预处理和统计分析。基于 SCI 队列的验证表明，基于大脑和脊髓的新处理方法与现有的处理工具相当，同时具有在整个神经轴上同时进行分析的优势。
