Evaluation of cervical spinal cord atrophy using a modified SIENA approach

Area of Science:

• Neuroimaging
• Neurology
• Biomedical Engineering

Background:

• Spinal cord (SC) atrophy is a key indicator of neurodegeneration in neurological disorders.
• Current methods for assessing SC atrophy, like cross-sectional area (CSA) changes, suffer from significant variability.
• Registration-based techniques offer a more accurate approach to SC atrophy assessment.

Purpose of the Study:

• Introduce Structural Image Evaluation using Normalization of Atrophy on the Spinal Cord (SIENA-SC), an adapted method for direct SC volume change calculation.
• Compare the performance of SIENA-SC against the Generalized Boundary Shift Integral (GBSI) and CSA change methods.
• Evaluate SIENA-SC's robustness, reproducibility, and sensitivity in detecting SC atrophy.

Main Methods:

• Adapted the original SIENA method for SC analysis (SIENA-SC) using clinical brain MRI with extended field of view.
• Compared SIENA-SC with GBSI and CSA change on a scan-rescan dataset.
• Applied SIENA-SC to compare SC atrophy rates between 190 healthy controls and 65 multiple sclerosis patients.

Main Results:

• SIENA-SC demonstrated the lowest measurement error on a scan-rescan dataset compared to GBSI and CSA change.
• SIENA-SC revealed significantly higher yearly SC atrophy rates in multiple sclerosis patients versus healthy controls.
• SIENA-SC required a smaller sample size to detect treatment effects, indicating higher sensitivity.

Conclusions:

• SIENA-SC is a robust, reproducible, and sensitive method for assessing longitudinal SC volume changes.
• SIENA-SC provides an accessible, automated tool for neuroscientists, minimizing manual intervention and measurement variability.
• This method enhances the study of neurodegeneration through more accurate SC atrophy quantification.