ArticleNeuroradiology2013
Brain size and white matter content of cerebrospinal tracts determine the upper cervical cord area: evidence from structural brain MRI.
Article in Neuroradiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 29 citations in OpenAlex.
- Charting Cervical Spinal Cord Morphometry Across the Lifespan.Human brain mapping · 2026Article
- Genetic architecture of MRI-derived cervical spinal cord morphology reveals sensory-motor axis and systemic disease associations.Nature communications · 2026Article
- Charting Cervical Spinal Cord Morphometry Across the Lifespan.bioRxiv : the preprint server for biology · 2026Article
- Article
- Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- A database of the healthy human spinal cord morphometry in the PAM50 template space.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Structural MRI Reveals Cervical Spinal Cord Atrophy in the P301L Mouse Model of Tauopathy: Gender and Transgene-Dosing Effects.Frontiers in aging neuroscience · 2022Article
- Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction.Frontiers in neuroimaging · 2022Article
- Normalization of Spinal Cord Total Cross-Sectional and Gray Matter Areas as Quantified With Radially Sampled Averaged Magnetization Inversion Recovery Acquisitions.Frontiers in neurology · 2021Article
- MRI Measurement of Upper Cervical Spinal Cord Cross-Sectional Area in Children.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2020Article
- Heritability of cervical spinal cord structure.Neurology. Genetics · 2020Article
- Intersubject Variability and Normalization Strategies for Spinal Cord Total Cross-Sectional and Gray Matter Areas.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2020Article
- Future Brain and Spinal Cord Volumetric Imaging in the Clinic for Monitoring Treatment Response in MS.Current treatment options in neurology · 2018Review
- Spinal Cord Gray Matter Atrophy in Amyotrophic Lateral Sclerosis.AJNR. American journal of neuroradiology · 2018Article
- Multicenter Validation of Mean Upper Cervical Cord Area Measurements from Head 3D T1-Weighted MR Imaging in Patients with Multiple Sclerosis.AJNR. American journal of neuroradiology · 2016Article
- Article
- Spinal cord atrophy in early Huntington's disease.Annals of clinical and translational neurology · 2014Article
- Biological variation in cervical spinal cord MRI morphometry in healthy individuals and people with multiple sclerosis.Journal of neuroimaging : official journal of the American Society of NeuroimagingArticle
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMeasurement of the upper cervical cord area (UCCA) from brain MRI may be an effective way to quantify spinal cord involvement in neurological disorders such as multiple sclerosis. However, knowledge on the determinants of UCCA in healthy controls (HCs) is limited.
methodsIn two cohorts of 133 and 285 HCs, we studied the influence of different demographic, body-related, and brain-related parameters on UCCA by simple and partial correlation analyses as well as by voxel-based morphometry (VBM) across both cerebral gray matter (GM) and white matter (WM).
resultsFirst, we confirmed the known but moderate effect of age on UCCA in the older cohort. Second, we studied the correlation of UCCA with sex, body height, and total intracranial volume (TIV). TIV was the only variable that correlated significantly with UCCA after correction for the other variables. Third, we studied the correlation of UCCA with brain-related parameters. Brain volume correlated stronger with UCCA than TIV. Both volumes of the brain tissue compartments GM and WM correlated with UCCA significantly. WM volume explained variance of UCCA after correction for GM volume, whilst the opposite was not observed. Correspondingly, VBM did not yield any brain region, whose GM content correlated significantly with UCCA, whilst cerebral WM content of cerebrospinal tracts strongly correlated with UCCA. This latter effect increased along a craniocaudal gradient.
conclusionUCCA is mainly determined by brain volume as well as by WM content of cerebrospinal tracts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.