Evidence map›Paper›PMID 40232308›Full record

Observational studyAnnals of medicine2025

Unveiling structural damage of the corpus callosum in amyotrophic lateral sclerosis through diffusion tensor imaging and spread direction perspectives.

Jieying Wu, Yingsheng Xu, Tielun Yin, Nan Zhang, Dongsheng Fan, Shan Ye

Abstract readObservational Study
In one paragraph

Observational study in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Jieying WuDepartment of Neurology, Peking University Third Hospital, Beijing, China.
Yingsheng XuDepartment of Neurology, Peking University Third Hospital, Beijing, China.
Tielun YinDepartment of Neurology, Peking University Third Hospital, Beijing, China.
Nan ZhangDepartment of Neurology, Peking University Third Hospital, Beijing, China.
Dongsheng FanDepartment of Neurology, Peking University Third Hospital, Beijing, China.
Shan YeDepartment of Neurology, Peking University Third Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDamage to the corpus callosum (CC) in amyotrophic lateral sclerosis (ALS) patients has been confirmed

methodsIn this observational study, diffusion tensor imaging (DTI) data were acquired from 45 individuals with the upper motor neuron-dominant (UMN-D) phenotype of ALS. The UMN-D ALS patients were categorized into two groups based on the direction of symptom spread, including 25 patients with horizontal spread (group H) and 20 patients with vertical spread (group V). Diffusivity indices were derived through whole-brain analysis and probabilistic fiber tracking.

resultsAccording to the voxel-based analysis and tract-based spatial statistics, differences in axial diffusivity (AD) in the CC were observed between disease subgroups, with patients in group H showing higher AD values than those in group V. Fiber tracking analysis revealed persistent differences in the AD indices of CC-primary motor cortex (PMC) fibers between the two disease subgroups.

conclusionIn UMN-D ALS patients, the direction of symptom spread may be related to the degree of CC involvement. The AD metric may be a more specific indicator of CC damage.

Indexed as

Amyotrophic Lateral SclerosisCorpus CallosumDiffusion Tensor ImagingAdultAgedFemaleHumansMaleMiddle AgedMotor CortexAxial diffusivityCorpus callosumHorizontal spreadUpper motor neuron-dominant amyotrophic lateral sclerosisVertical spread

Identifiers

PMID40232308
PMCPMC12001847

What OpenQuestion holds

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Registered trials

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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.