Evidence map›Paper›PMID 32163517›Full record

ArticlePloS one2020

Implementation of clinically relevant and robust fMRI-based language lateralization: Choosing the laterality index calculation method.

Irène Brumer, Enrico De Vita, Jonathan Ashmore, Jozef Jarosz, Marco Borri

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

12 citing papers in PubMed, 23 citations in OpenAlex.

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  11. Developing fMRI protocol for clinical useNeurosciences (Riyadh, Saudi Arabia) · 2021
    Article
  12. Power spectral analysis can determine language laterality from resting-state functional MRI data in healthy controls.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    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

5 authors at 3 institutions in 1 country.

Irène BrumerDepartment of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.ORCID 0000-0002-1936-8687
Enrico De VitaDepartment of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Jonathan AshmoreDepartment of Neuroradiology, King's College Hospital, London, United Kingdom.
Jozef JaroszDepartment of Neuroradiology, King's College Hospital, London, United Kingdom.
Marco BorriDepartment of Neuroradiology, King's College Hospital, London, United Kingdom.
King's College Hospital · GBKing's College London · GBNHS Highland · GB

Funding

Wellcome Trust 203148/Z/16/ZWellcome Trust WT 203148/Z/16/Z
6 · The paper itself

Abstract

The assessment of language lateralization has become widely used when planning neurosurgery close to language areas, due to individual specificities and potential influence of brain pathology. Functional magnetic resonance imaging (fMRI) allows non-invasive and quantitative assessment of language lateralization for presurgical planning using a laterality index (LI). However, the conventional method is limited by the dependence of the LI on the chosen activation threshold. To overcome this limitation, different threshold-independent LI calculations have been reported. The purpose of this study was to propose a simplified approach to threshold-independent LI calculation and compare it with three previously reported methods on the same cohort of subjects. Fifteen healthy subjects, who performed picture naming, verb generation, and word fluency tasks, were scanned. LI values were calculated for all subjects using four methods, and considering either the whole hemisphere or an atlas-defined language area. For each method, the subjects were ranked according to the calculated LI values, and the obtained rankings were compared. All LI calculation methods agreed in differentiating strong from weak lateralization on both hemispheric and regional scales (Spearman's correlation coefficients 0.59-1.00). In general, a more lateralized activation was found in the language area than in the whole hemisphere. The new method is well suited for application in the clinical practice as it is simple to implement, fast, and robust. The good agreement between LI calculation methods suggests that the choice of method is not key. Nevertheless, it should be consistent to allow a relative comparison of language lateralization between subjects.

Indexed as

AdultBrainBrain MappingCohort StudiesFemaleFunctional LateralityHumansLanguageMagnetic Resonance ImagingMaleMiddle AgedNeurosurgeryYoung Adult

Identifiers

PMID32163517
PMCPMC7067428
OpenAlexW3010907814

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.