4.2 Article

MRI Measurement of Upper Cervical Spinal Cord Cross-Sectional Area in Children

期刊

JOURNAL OF NEUROIMAGING
卷 30, 期 5, 页码 598-602

出版社

WILEY
DOI: 10.1111/jon.12758

关键词

Intersubject variability; magnetic resonance imaging; normalization strategies; pediatric; spinal cord

资金

  1. Charles and Helen Schwab Foundation
  2. National Institute of Health [NINDS R01 NS050915, NIDCD K24 DC015544, NIA P01 AG019724, NIA P50 AG023501]

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BACKGROUND AND PURPOSE Neurological and neurodegenerative diseases can affect the spinal cord (SC) of pediatric patients. Magnetic resonance imaging (MRI) allows for in vivo quantification of SC atrophy via cross-sectional area (CSA). The study of CSA values in the general population is important to disentangle disease-related changes from intersubject variability. This study aimed at providing normative values for cervical CSA in children, extending our previous work performed with adults. METHODS Seventy-eight children (age 7-17 years) were selected from a Developmental Dyslexia study. All subjects underwent a 3T brain MRI session and any incidental findings were reported on the scans. A sagittal 1 mm(3)3-dimensional T-1-weighted brain acquisition extended to the upper cervical cord was used to measure CSA at C2-C3, as well as spinal canal area and skull volume (V-scale). These three metrics were linearly fitted as a function of age to extract trends and percentage annual changes. Sex differences of CSA were assessed using least squares regression analyses, adjusting for age. We tested normalization strategies proven to be effective in reducing the intersubject variability of adults' CSA. RESULTS CSA changed as a function of age at a faster rate when compared with skull volume (CSA: 1.82% increase, V-scale: .60% reduction). Sex had a statistically significant effect on CSA. Normalization methods based on canal area and skull volume reduced the CSA intersubject variability up to 16.84%. CONCLUSIONS We present CSA normative values in a large cohort of children, reporting on sources of intersubject variability and how to reduce them applying normalization methods previously developed.

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