Evidence map›Paper›PMID 30919495›Full record

ArticleMovement disorders : official journal of the Movement Disorder Society2019

Morphometric MRI profiles of multiple system atrophy variants and implications for differential diagnosis.

Florian Krismer, Klaus Seppi, Georg Göbel, Ruth Steiger, Isabel Zucal, Sylvia Boesch, Elke R Gizewski, Gregor K Wenning, Werner Poewe, Christoph Scherfler

Open access · hybridAbstract read
In one paragraph

Article in Movement disorders : official journal of the Movement Disorder Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

27 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Article
  3. The role of neuro-imaging in multiple system atrophy.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Review
  4. Neuroimaging in multiple system atrophy: clinical implications and novel developments.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Imaging biomarkers for early multiple system atrophy.Parkinsonism & related disorders · 2022
    Article
  20. 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

10 authors at 1 institution in 1 country.

Florian KrismerDepartment of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Klaus SeppiDepartment of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Georg GöbelMedical Statistics, Informatics and Health Economics, Medical University Innsbruck, Innsbruck, Austria.
Ruth SteigerNeuroimaging Research Core Facility, Medical University Innsbruck, Innsbruck, Austria.
Isabel ZucalDepartment of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Sylvia BoeschDepartment of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Elke R GizewskiNeuroimaging Research Core Facility, Medical University Innsbruck, Innsbruck, Austria.
Gregor K WenningDepartment of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Werner PoeweDepartment of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Christoph ScherflerDepartment of Neurology, Medical University Innsbruck, Innsbruck, Austria.
Innsbruck Medical University · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundManual width measurements of the middle cerebellar peduncle on MRI were shown to improve the accuracy of an imaging-guided diagnosis of multiple system atrophy (MSA). Recently, automated volume segmentation algorithms were able to reliably differentiate patients with Parkinson's disease (PD) and the parkinsonian variant of MSA. The objective of the current study was to integrate probabilistic information of the middle cerebellar peduncle into an existing MRI atlas for automated subcortical segmentation and to evaluate the diagnostic properties of the novel atlas for the differential diagnosis of MSA (parkinsonian and cerebellar variant) versus PD.

methodsThree Tesla MRI scans of 48 healthy individuals were used to establish an automated whole-brain segmentation procedure that includes the volumes of the putamen, cerebellar gray and white matter, and the middle cerebellar peduncles. Classification accuracy of segmented volumes were tested in early-stage MSA patients (18 MSA-parkinsonism, 13 MSA-cerebellar) and 19 PD patients using a C4.5 classifier.

resultsPutaminal and infratentorial atrophy were present in 77.8% and 61.1% of MSA-parkinsonian patients, respectively. Four of 18 MSA-parkinsonian patients (22.2%) had infratentorial atrophy without evidence of putaminal atrophy. Infratentorial atrophy was present in all MSA-cerebellar patients, with concomitant putaminal atrophy in 46.2% of these cases. The diagnostic algorithm using putaminal and infratentorial volumetric information correctly classified all PD patients and 96.8% of MSA patients.

conclusionsThe middle cerebellar peduncle was successfully integrated into a subcortical segmentation atlas, and its excellent diagnostic accuracy outperformed existing volumetric MRI processing strategies in differentiating MSA patients with variable atrophy patterns from PD patients. © 2019 International Parkinson and Movement Disorder Society.

Indexed as

AgedAlgorithmsAtrophyBrainDiagnosis, DifferentialFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMultiple System AtrophyParkinson DiseaseParkinsonian DisordersPutamenatlasFreeSurferMRImultiple system atrophyParkinson's disease

Identifiers

PMID30919495
PMCPMC6767501
OpenAlexW2928359704

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.