Evidence map›Paper›PMID 42908281›Full record

ArticleHuman brain mapping2026

Charting Cervical Spinal Cord Morphometry Across the Lifespan.

Kurt G Schilling, Michael E Kim, Matthew Amandola, Chenyu Gao, Karthik Ramadass, Praitayini Kanakaraj, Sam Bogdanov, Gaurav Rudravaram, Nancy R Newlin, Derek Archer and 31 more

Abstract read
In one paragraph

Article in Human brain mapping, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

41 authors.

Kurt G SchillingDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0003-3686-7645
Michael E KimDepartment of Computer Science, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0009-0006-3562-2688
Matthew AmandolaDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0009-0005-3445-6326
Chenyu GaoDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0003-2098-3035
Karthik RamadassDepartment of Computer Science, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-4610-3860
Praitayini KanakarajDepartment of Computer Science, Vanderbilt University, Nashville, Tennessee, USA.
Sam BogdanovMedical Scientist Training Program, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0001-7766-4217
Gaurav RudravaramDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA.
Nancy R NewlinDepartment of Computer Science, Vanderbilt University, Nashville, Tennessee, USA.
Derek ArcherVanderbilt University Medical Center, Vanderbilt Memory and Alzheimer's Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0001-8638-0785
Timothy J HohmanVanderbilt University Medical Center, Vanderbilt Memory and Alzheimer's Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-3377-7014
Angela L JeffersonVanderbilt University Medical Center, Vanderbilt Memory and Alzheimer's Center, Nashville, Tennessee, USA.
Victoria L MorganDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0001-8263-2324
Alexandra RocheVanderbilt University Institute of Imaging Science, Nashville, Tennessee, USA.
Dario J EnglotDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Murat BilgelLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0001-5042-7422
Lori L Beason HeldLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.
Luigi FerrucciLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0002-6273-1613
Laurie E CuttingVanderbilt University, Vanderbilt Brain Institute, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-2362-6028
Laura A BarqueroDepartment of Special Education, Peabody College of Education and Human Development, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-4279-3745
Micah A D'archangelDepartment of Special Education, Peabody College of Education and Human Development, Nashville, Tennessee, USA.
Tin Q NguyenVanderbilt University Institute of Imaging Science, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-0240-133X
Kathryn L HumphreysDepartment of Psychology and Human Development, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-5715-6597
Yanbin NiuDepartment of Psychology and Human Development, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0009-0005-1199-4033
Sophia Vinci-BooherDepartment of Psychology and Human Development, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-3626-146X
Carissa J CascioLife Span Institute and Department of Psychology, University of Kansas, Lawrence, Kansas, USA.
HABS‐HD Study Team
Alzheimer's Disease Neuroimaging Initiative
BIOCARD Study Team
Zhiyuan LiDepartment of Computer Science, Park University, Parkville, Missouri, USA.
Daniel MoyerDepartment of Computer Science, Vanderbilt University, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0003-4428-5012
Simon N VandekarDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Panpan ZhangVanderbilt University Medical Center, Vanderbilt Memory and Alzheimer's Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-8211-5930
Samuelle St-OngeNeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.ORCID https://orcid.org/0000-0001-7572-8504
Sandrine BédardNeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.ORCID https://orcid.org/0000-0001-9859-1133
Jan ValošekNeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.
Benjamin De LeenerNeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.ORCID https://orcid.org/0000-0002-1378-2756
Julien Cohen-AdadNeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.
John C GoreDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-9480-0900
Seth SmithDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0002-4168-562X
Bennett A LandmanDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID https://orcid.org/0000-0001-5733-2127

Funding

NIH HHS 1R01EB017230-01A1NIH HHS K01-AG073584NIH HHS K01-EB032898NIH HHS K24-AG046373NIH HHS R01-AG034962NIH HHS R01-AG056534NIH HHS R01-AG062826NIH HHS R01-HD114489NIH HHS UL1-TR000445NIH HHS UL1-TR002243
6 · The paper itself

Abstract

Spinal cord morphometry provides essential biomarkers of neurological health, but clinical interpretations are confounded by inter-subject variability and a lack of normative references across the full human lifespan. We address this gap by generating the first comprehensive lifespan charts for cervical spinal cord morphometry. From 78,269 T1-weighted brain MRI sessions, we identified a final cross-sectional cohort of 24,251 healthy or cognitively normal controls from 33 datasets (ages 0-100 years) with cervical cord coverage. To overcome contrast variability, we employed a state-of-the-art contrast-agnostic deep learning segmentation method, extracting cross-sectional area (CSA), anteroposterior (AP) and right-left (RL/transverse), and shape indices (AP/RL ratio, eccentricity, and solidity) from C1 to C7. Normative trajectories were modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS). The resulting charts reveal distinct non-linear lifespan changes: rapid growth through childhood and adolescence, peak maturation occurring in early-to-mid adulthood (e.g., mid-30s for CSA), followed by gradual decreases. Significant regional variations along the cervical cord and consistent sex differences (males > females for size metrics) were quantified. Spinal cord trajectories showed strong temporal coupling with brain white matter and brainstem volumes, suggesting integrated CNS development and aging. These lifespan charts provide a robust normative framework, enabling age- and sex-specific centile scoring of individual spinal cord morphometry. This resource offers a critical tool for differentiating typical variation from pathological changes, enhancing the clinical utility of spinal cord MRI in studies of development and neurodegeneration.

Indexed as

AgingCervical CordLongevityNeuroimagingAdolescentAdultAgedAged, 80 and overChildChild, PreschoolCross-Sectional StudiesDeep LearningFemaleHumansInfantInfant, Newborn

Identifiers

PMID42908281
PMCPMC13687786

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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.