• Nico Papinutto, Carlo Asteggiano, Antje Bischof, Tristan J Gundel, Eduardo Caverzasi, William A Stern, Stefano Bastianello, Stephen L Hauser, and Roland G Henry.
• Department of Neurology, University of California, San Francisco, CA.
• J Neuroimaging. 2020 Jan 1; 30 (1): 110-118.

Background And PurposeThe quantification of spinal cord (SC) atrophy by MRI has assumed an important role in assessment of neuroinflammatory/neurodegenerative diseases and traumatic SC injury. Recent technical advances make possible the quantification of gray matter (GM) and white matter tissues in clinical settings. However, the goal of a reliable diagnostic, prognostic or predictive marker is still elusive, in part due to large intersubject variability of SC areas. Here, we investigated the sources of this variability and explored effective strategies to reduce it.MethodsOne hundred twenty-nine healthy subjects (mean age: 41.0 ± 15.9) underwent MRI on a Siemens 3T Skyra scanner. Two-dimensional PSIR at the C2-C3 vertebral level and a sagittal 1 mm3 3D T1-weighted brain acquisition extended to the upper cervical cord were acquired. Total cross-sectional area and GM area were measured at C2-C3, as well as measures of the vertebra, spinal canal and the skull. Correlations between the different metrics were explored using Pearson product-moment coefficients. The most promising metrics were used to normalize cord areas using multiple regression analyses.ResultsThe most effective normalization metrics were the V-scale (from SienaX) and the product of the C2-C3 spinal canal diameters. Normalization methods based on these metrics reduced the intersubject variability of cord areas of up to 17.74%. The measured cord areas had a statistically significant sex difference, while the effect of age was moderate.ConclusionsThe present work explored in a large cohort of healthy subjects the source of intersubject variability of SC areas and proposes effective normalization methods for its reduction.© 2019 by the American Society of Neuroimaging.

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