Intersubject Variability and Normalization Strategies for Spinal Cord Total Cross-Sectional and Gray Matter Areas

Abstract

Background and purpose: The 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.

Methods: One 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.

Results: The 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.

Conclusions: The 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.

Keywords: Intersubject variability; magnetic resonance imaging; morphometry; normalization strategies; spinal cord.

Figure 1

Segmentation examples of A: TCA (purple) and GMA (white); B: axial_canal_area (green), ap_canal_diameter (blue) and lat_canal_diameter (orange); C: axial_vertebra_area (red), ap_vertebra_axial (black) and lat_vertebra_axial (pink) and D: height of the anterior (AH) and posterior (PH) vertebral walls (yellow) and ap_vertebra_diameter (cyan). ap: anterior-posterior; lat: lateral.

Figure 2

TCA plotted in function of V-scale (left) and axial_canal_product (right). Linear regression fit lines and 95% confidence intervals are reported in red.

Figure 3

Total brain and GM volumes, SC TCA and GMA as a function of age (stratified by sex: women (blue), men (red)). A: linear fit of data; B: quadratic fit. The r² for the fits (men and women together) are reported in the graph.

Figure 3

Total brain and GM volumes, SC TCA and GMA as a function of age (stratified by sex: women (blue), men (red)). A: linear fit of data; B: quadratic fit. The r² for the fits (men and women together) are reported in the graph.