Evidence map›Paper›PMID 39113151›Full record

ArticleNeurological research and practice2024

Real-world analysis of brain atrophy in multiple sclerosis patients with an artificial intelligence based software tool.

Caroline Reinhardt, Klemens Angstwurm, David Freudenstein, De-Hyung Lee, Christina Wendl, Ralf A Linker

Abstract read
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Article in Neurological research and practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. From lesion detection to outcome prediction: artificial intelligence and deep learning applications in multiple sclerosis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
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

6 authors.

Caroline ReinhardtDepartment of Neurology, University of Regensburg, Universitätsstr. 84, 93053, Regensburg, Germany.ORCID http://orcid.org/0009-0005-2471-8222
Klemens AngstwurmDepartment of Neurology, University of Regensburg, Universitätsstr. 84, 93053, Regensburg, Germany.
David FreudensteinDepartment of Neurology, University of Regensburg, Universitätsstr. 84, 93053, Regensburg, Germany.
De-Hyung LeeDepartment of Neurology, University of Regensburg, Universitätsstr. 84, 93053, Regensburg, Germany.
Christina WendlDepartment of Neuroradiology, University of Regensburg, Regensburg, Germany.
Ralf A LinkerDepartment of Neurology, University of Regensburg, Universitätsstr. 84, 93053, Regensburg, Germany. ralf.linker@ukr.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAtrophy of white and grey matter volumes occurs early in the brains of people with multiple sclerosis (pwMS) and has great clinical relevance. In clinical trials, brain atrophy can be quantified by magnetic resonance imaging (MRI) with automated software tools.

methodsIn this study, we analyze volumes of various brain regions with the software "md brain" based on routine MRI scans of 53 pwMS in a real-world setting. We compare brain volumes of pwMS with an EDSS ≥ 3.5 and a disease duration ≥ 10 years to the brain volumes of pwMS with an EDSS < 3.5 and a disease duration < 10 years as well as with or without immunotherapy.

resultspwMS with an EDSS ≥ 3.5 and a disease duration ≥ 10 years had significantly lower volumes of the total brain, the grey matter and of the frontal, temporal, parietal and occipital lobe regions as compared to pwMS with an EDSS < 3.5 and a disease duration < 10 years. Regional brain volumes were significantly lower in pwMS without immunotherapy.

conclusionsThe study showed that higher EDSS, longer disease duration and absence of immunotherapy was associated with lower volumes in a number of brain regions. Further real-world studies may include larger patient cohorts in longitudinal analyses.

Indexed as

Brain atrophyMagnetic resonance imagingMR volumetryMultiple sclerosis

Identifiers

PMID39113151
PMCPMC11308334

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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.