Evidence map›Paper›PMID 32653026›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2020

The role of resting-state functional MRI for clinical preoperative language mapping.

Vinodh A Kumar, Islam M Heiba, Sujit S Prabhu, Melissa M Chen, Rivka R Colen, Angela L Young, Jason M Johnson, Ping Hou, Kyle Noll, Sherise D Ferguson and 4 more

Abstract readEvaluation Study
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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

14 authors.

Vinodh A KumarDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. vakumar@mdanderson.org.ORCID http://orcid.org/0000-0002-8322-1233
Islam M HeibaDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Sujit S PrabhuDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Melissa M ChenDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Rivka R ColenDepartment of Diagnostic Radiology, The University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Angela L YoungDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jason M JohnsonDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ping HouDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Kyle NollDepartment of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Sherise D FergusonDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ganesh RaoDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Frederick F LangDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Donald F SchomerDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ho-Ling LiuDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTask-based functional MRI (tb-fMRI) is a well-established technique used to identify eloquent cortex, but has limitations, particularly in cognitively impaired patients who cannot perform language paradigms. Resting-state functional MRI (rs-fMRI) is a potential alternative modality for presurgical mapping of language networks that does not require task performance. The purpose of our study is to determine the utility of rs-fMRI for clinical preoperative language mapping when tb-fMRI is limited.

methodsWe retrospectively reviewed 134 brain tumor patients who underwent preoperative fMRI language mapping. rs-fMRI was post-processed with seed-based correlation (SBC) analysis, when language tb-fMRI was limited. Two neuroradiologists reviewed both the tb-fMRI and rs-fMRI results. Six neurosurgeons retrospectively rated the usefulness of rs-fMRI for language mapping in their patients.

resultsOf the 134 patients, 49 cases had limited tb-fMRI and rs-fMRI was post-processed. Two neuroradiologists found rs-fMRI beneficial for functional language mapping in 41(84%) and 43 (88%) cases respectively; Cohen's kappa is 0.83, with a 95% confidence interval (0.61, 1.00). The neurosurgeons found rs-fMRI "definitely" useful in 26 cases (60%) and "somewhat" useful in 13 cases (30%) in locating potential eloquent language centers of clinical interest. Six unsuccessful rs-fMRI cases were due to: head motion (2 cases), nonspecific functionality connectivity outside the posterior language network (1 case), and an unknown system instability (3 cases).

conclusionsThis study is a proof of concept that shows SBC rs-fMRI may be a viable alternative for clinical language mapping when tb-fMRI is limited.

Indexed as

LanguageAdolescentAdultBrain MappingBrain NeoplasmsFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPreoperative PeriodFunctional connectivityRegional homogeneityResting-state fMRISeed-based correlation

Identifiers

PMID32653026
PMCPMC7353792

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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.