Evidence map›Paper›PMID 42251620›Full record

ArticleJournal of neurology2026

Tongue volume in spinal and bulbar muscular atrophy (SBMA): an AI-assisted automatic MRI analysis.

Angela Rosenbohm, Ina Vernikouskaya, Anastasia Nosanova, Nam Nguyen-Younossi, Karl Georg Haeusler, Jochen Weishaupt, Volker Rasche, Hans-Peter Müller, Jan Kassubek

Abstract read
In one paragraph

Article in Journal of neurology, 2026. 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. Potential Roles of Neuroimaging in Motor Neuron Disease.Current neurology and neuroscience reports · 2026
    Review
  2. 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

9 authors.

Angela RosenbohmDepartment of Neurology, University Hospital Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany. angela.rosenbohm@uni-ulm.de.ORCID http://orcid.org/0000-0001-9700-0338
Ina VernikouskayaDepartment of Internal Medicine II, Ulm University Medical Center, Ulm, Germany.
Anastasia NosanovaDepartment of Neurology, University Hospital Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany.
Nam Nguyen-YounossiDepartment of Neurology, University Hospital Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany.
Karl Georg HaeuslerDepartment of Neurology, University Hospital Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany.
Jochen WeishauptDepartment of Neurology, University Hospital Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany.
Volker RascheDepartment of Internal Medicine II, Ulm University Medical Center, Ulm, Germany.
Hans-Peter Müller *Department of Neurology, University Hospital Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany.
Jan Kassubek *Department of Neurology, University Hospital Ulm, Oberer Eselsberg 45, 89081, Ulm, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atrophy of the tongue muscle without severe dysarthria is one of the clinical hallmarks of spinal and bulbar muscular atrophy (SBMA), a motor neuron disease caused by an androgene receptor defect. An operator-independent AI-based automatic segmentation of the tongue was applied to 3-D MRI data of the head in SBMA in order to quantify the tongue atrophy. Thirty-nine patients with SBMA and 51 age-matched healthy controls underwent MRI which were used for tongue volume quantification. A single triplanar convolutional neural network of U-Net architecture trained on axial, coronal, and sagittal planes was used for the segmentation of the tongue in MRI scans of the head, the resulting volumes were processed slice-wise across the three orientations and corrected for age. At the group level, a significant atrophy of the tongue was observed in SBMA when compared to controls (p < 0.05). Atrophy correlated well with total SBMA-functional rating scale and even more with bulbar subscores. In summary, the study employed an AI-assisted advanced imaging analysis to quantify the tongue morphology in individuals with SBMA in correlation to clinical bulbar function, suggesting this approach as a potential biomarker for disease assessment.

Indexed as

Artificial IntelligenceBulbo-Spinal Atrophy, X-LinkedMagnetic Resonance ImagingTongueAdultAgedConvolutional Neural NetworksFemaleHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMaleMiddle AgedOrgan SizeKennedy diseaseMagnetic resonance imagingMotor neuron diseaseMuscle volumeNeuroimagingTongueVolumetry

Identifiers

PMID42251620
PMCPMC13243324

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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.