Jaume Sastre-Garriga , Deborah Pareto , Manel Alberich , Breogán Rodríguez-Acevedo , Àngela Vidal-Jordana , Juan Francisco Corral , Mar Tintoré , Jordi Río , Cristina Auger , Xavier Montalban , Àlex Rovira
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引用次数: 1
Abstract
Purpose
Several studies have indicated the relevance of spinal cord grey matter atrophy for Multiple Sclerosis (MS) related disability. This work aimed at evaluating feasibility and clinical relevance of MRI-derived estimations of spinal cord grey matter atrophy in clinical practice.
Methods
A convenience sample of MS patients (n=48) and healthy controls (HC, n=11) was scanned using brain sagittal 3D T1w (MPRAGE) and transverse T2w-FLAIR, and transverse single-slice spinal cord 2D heavily T1w (PSIR: phase-sensitive inversion recovery) sequences. An experienced technician with neuroradiological supervision used a semiautomated thresholding method implemented in JIM software on PSIR sequences to obtain cross-sectional area (CSA) of the spinal canal (CSAcanal), whole cord (CSAcord), grey (CSAgm) and white matter (CSAwm) at C2-C3. MPRAGE and T2w-FLAIR sequences were used to obtain brain parenchymal, grey and white matter fractions (BPF, GMF and WMF) using the Statistical Parametric Mapping software. Appropriate statistical tests were used before and after age and sex adjustment.
Results
CSAgm and CSAwm could be obtained in all HC, but only 18 patients (37.5%) due to presence of lesions at C2-C3. Significant univariate associations between EDSS and BPF (rho =−0.376, p=0.015), GMF (rho =−0.287, p=0.069), CSAcanal (rho =−0.310, p=0.049), CSAcord (rho =−0.533 p<0.001) and CSAgm (rho =−0.511, p=0.062) were detected. After age/sex adjustment trends were observed for CSAcanal and CSAcord.
Conclusion
In a clinical practice setting, relevance of spinal cord grey matter is confirmed, but cervical cord lesions could greatly hamper its application. Clinical associations with disability have been observed and seem stronger for spinal cord than for brain atrophy measures.
Neuroscience informaticsSurgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology