Simultaneous voxel-wise analysis of brain and spinal cord morphometry and microstructure within the SPM framework

Area of Science:

• Neuroimaging
• Biomedical Engineering
• Radiology

Background:

• Assessing brain and spinal cord changes requires separate analytical tools.
• Spinal cord injury (SCI) research needs integrated neuroimaging analysis for comprehensive understanding.
• Existing methods lack simultaneous analysis across the entire neuraxis.

Purpose of the Study:

• To validate a novel simultaneous analysis tool for brain and cervical spinal cord within the Statistical Parametric Mapping (SPM) framework.
• To compare trauma-induced neurostructural changes in SCI patients using the new tool versus separate analysis methods.
• To assess the consistency and accuracy of MRI measures using intraclass correlation coefficients (ICC).

Main Methods:

• Developed a probabilistic brain-spinal cord (BSC) template using generative semi-supervised modeling.
• Integrated the BSC template into SPM for voxel-based morphometry and quantification analyses.
• Validated the approach on T1-weighted scans and multiparameter maps in SCI patients and controls.

Main Results:

• The SPM approach with the BSC template identified trauma-induced changes in the sensorimotor system of both the brain and spinal cord in SCI patients.
• Findings were consistent with established, separate brain and spinal cord analysis tools.
• High intraclass correlation coefficients (ICC) were observed in key brain regions like sensorimotor cortices, corticospinal tracts, and thalamus.

Conclusions:

• The simultaneous voxel-wise analysis of brain and cervical spinal cord in SPM offers a unified framework.
• This new processing approach is comparable to existing tools for SCI neuroimaging analysis.
• The primary advantage is the ability to perform simultaneous analysis across the entire neuraxis, enhancing research efficiency.