Evidence map›Paper›PMID 41383241›Full record

ArticleFrontiers in neurology2025

Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.

Carsten Lukas, Barbara Bellenberg, Ferran Prados, Paola Valsasina, Katrin Parmar, Iman Brouwer, Deborah Pareto, Alex Rovira, Jaume Sastre-Garriga, Claudia A M Gandini Wheeler-Kingshott and 7 more

Abstract read
In one paragraph

Article in Frontiers in neurology, 2025. 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
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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

17 authors.

Carsten Lukas *Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Bochum, Germany.
Barbara Bellenberg *Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Bochum, Germany.
Ferran PradosDepartment of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), UCL, London, United Kingdom.
Paola ValsasinaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Katrin ParmarDepartment of Medicine, Neurological Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.
Iman BrouwerDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands.
Deborah ParetoSection of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Alex RoviraSection of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Jaume Sastre-GarrigaDepartment of Neurology, Multiple Sclerosis Center of Catalonia (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Claudia A M Gandini Wheeler-KingshottDepartment of Neuroinflammation, Faculty of Brain Sciences, UCL Queen Square Institute of Neurology, Queen Square MS Centre, University College London, London, United Kingdom.
Michael AmannDepartment of Medicine, Neurological Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.
Maria A RoccaNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Massimo FilippiNeuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Marios C YiannakasDepartment of Neuroinflammation, Faculty of Brain Sciences, UCL Queen Square Institute of Neurology, Queen Square MS Centre, University College London, London, United Kingdom.
Eva M M StrijbisDepartment of Neurology, Amsterdam UMC, Amsterdam, Netherlands.
Frederik BarkhofDepartment of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), UCL, London, United Kingdom.
Hugo VrenkenDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cervical cord atrophy is linked to disability in multiple sclerosis (MS). Cervical cord cross-sectional area (CSA) measurement for atrophy quantification using magnetic resonance imaging (MRI) has been technically validated, but information about effects of methodological choices on associations of CSA with clinical variables is lacking. Aim: Assessing how image acquisition, cord level selection, CSA normalization and segmentation software affect measurement variance, separation of clinical groups, correlations with clinical scores, and to formulate recommendations for future study designs. Methods: Head and neck 3D-T1-weighted MRI of people with MS (pwMS, Results: For all combinations of imaging, cord level, and segmentation software, unnormalized CSA differed between HC and pMS. CV in HC varied between 10.5 and 13.5% for unnormalized CSA and was lower for CSA normalized by C1-C2 (range: 9.4-12.0%) and C1-C3 vertebral height (8.6-12.6%). Unnormalized and normalized CSA correlated with EDSS scores for all measurement combinations (Spearman's rho between -0.646 and -0.372, all corrected Conclusion: Clinical performance of CSA quantification regarding discrimination between rMS and pMS and correlations with EDSS was better for whole cervical cord (C1-7) than for C1-2 measurements, and for normalization by C1-C2 or C1-C3 vertebral height. Based on the quantitative results of this exploratory multi-center study and on previous literature, we formulated recommendations to support future study design decisions.

Indexed as

atrophycervical cordcross-sectional areaCSAmultiple sclerosisoptimization MRIsegmentation software

Identifiers

PMID41383241
PMCPMC12689376

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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.