Evidence map›Paper›PMID 22435076›Full record

ArticleTherapeutic advances in neurological disorders2012

Neuroimaging of motor neuron diseases.

Jan Kassubek, Albert C Ludolph, Hans-Peter Müller

Open access · bronzeAbstract read
In one paragraph

Article in Therapeutic advances in neurological disorders, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.1field-weighted citation impact, top 14% of its field
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

13 citing papers in PubMed, 31 citations in OpenAlex.

  1. Potential Roles of Neuroimaging in Motor Neuron Disease.Current neurology and neuroscience reports · 2026
    Review
  2. Article
  3. Article
  4. Review
  5. Segmental involvement of the corpus callosum inTherapeutic advances in chronic disease · 2021
    Article
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  7. Review
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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

3 authors.

Jan Kassubek
Albert C Ludolph
Hans-Peter Müller

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is agreed that conventional magnetic resonance imaging (MRI) of the brain and spine is one of the core elements in the differential diagnostic work up of patients with clinical signs of motor neuron diseases (MNDs), for example amyotrophic lateral sclerosis (ALS), to exclude MND mimics. However, the sensitivity and specificity of MRI signs in these disorders are moderate to low and do not have an evidence level higher than class IV (good clinical practice point). Currently computerized MRI analyses in ALS and other MNDs are not techniques used for individual diagnosis. However, they have improved the anatomical understanding of pathomorphological alterations in gray and white matter in various MNDs and the changes in functional networks by quantitative comparisons between patients with MND and controls at group level. For multiparametric MRI protocols, including T1-weighted three-dimensional datasets, diffusion-weighted imaging and functional MRI, the potential as a 'dry' surrogate marker is a subject of investigation in natural history studies with well defined patients. The additional value of MRI with respect to early diagnosis at an individual level and for future disease-modifying multicentre trials remains to be defined. There is still the need for more longitudinal studies in the very early stages of disease or when there is clinical uncertainty and for better standardization in the acquisition and postprocessing of computer-based MRI data. These requirements are to be addressed by establishing quality-controlled multicentre neuroimaging databases.

Indexed as

amyotrophic lateral sclerosisDTImotor neuron diseasesMRIT1-weighted imaging

Identifiers

PMID22435076
PMCPMC3302203
OpenAlexW2115342939

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.