Evidence map›Paper›PMID 32006951›Full record

Trial reportNeurosurgical focus2020

Accuracy analysis of fMRI and MEG activations determined by intraoperative mapping.

David G Ellis, Matthew L White, Satoru Hayasaka, David E Warren, Tony W Wilson, Michele R Aizenberg

Registry-linked trialOpen access · diamondAbstract readClinical Trial
In one paragraph

Trial report in Neurosurgical focus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01535430 (Assessment of Reorganization and Plasticity of Eloquent Function in Patients With Brain Tumors), which is not on this map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.8field-weighted citation impact, top 8% 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.

NCT01535430 recruitingnot on this map

Assessment of Reorganization and Plasticity of Eloquent Function in Patients With Brain Tumors

TypeobservationalSponsorUniversity of NebraskaRan2012 to 2027Enrolled75ConditionsPrimary Brain Tumor, Metastatic Brain TumorArmsBrain mapping
3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
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  7. Treatment Options for IDH-Mutant Malignant Gliomas.Current treatment options in oncology · 2024
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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

6 authors at 2 institutions in 1 country.

David G EllisDepartments of1Neurosurgery and.
Matthew L White2Radiology, University of Nebraska Medical Center, Omaha, Nebraska.
Satoru Hayasaka3Department of Psychology, University of Texas at Austin, Texas; and.
David E Warren4Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska.
Tony W Wilson4Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska.
Michele R AizenbergDepartments of1Neurosurgery and.
University of Nebraska Medical Center · USThe University of Texas at Austin · US

Funding

Tracking and Evaluation CoreU54GM115458 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI GUDA, CHITTIBABU · 2016 to 2025
$42.8M
NIGMS NIH HHS U54 GM115458
6 · The paper itself

Abstract

objectiveBy looking at how the accuracy of preoperative brain mapping methods vary according to differences in the distance from the activation clusters used for the analysis, the present study aimed to elucidate how preoperative functional neuroimaging may be used in such a way that maximizes the mapping accuracy.

methodsThe eloquent function of 19 patients with a brain tumor or cavernoma was mapped prior to resection with both functional MRI (fMRI) and magnetoencephalography (MEG). The mapping results were then validated using direct cortical stimulation mapping performed immediately after craniotomy and prior to resection. The subset of patients with equivalent MEG and fMRI tasks performed for motor (n = 14) and language (n = 12) were evaluated as both individual and combined predictions. Furthermore, the distance resulting in the maximum accuracy, as evaluated by the J statistic, was determined by plotting the sensitivities and specificities against a linearly increasing distance threshold.

resultsfMRI showed a maximum mapping accuracy at 5 mm for both motor and language mapping. MEG showed a maximum mapping accuracy at 40 mm for motor and 15 mm for language mapping. At the standard 10-mm distance used in the literature, MEG showed a greater specificity than fMRI for both motor and language mapping but a lower sensitivity for motor mapping. Combining MEG and fMRI showed a maximum accuracy at 15 mm and 5 mm-MEG and fMRI distances, respectively-for motor mapping and at a 10-mm distance for both MEG and fMRI for language mapping. For motor mapping, combining MEG and fMRI at the optimal distances resulted in a greater accuracy than the maximum accuracy of the individual predictions.

conclusionsThis study demonstrates that the accuracy of language and motor mapping for both fMRI and MEG is heavily dependent on the distance threshold used in the analysis. Furthermore, combining MEG and fMRI showed the potential for increased motor mapping accuracy compared to when using the modalities separately.Clinical trial registration no.: NCT01535430 (clinicaltrials.gov).

Indexed as

Brain MappingBrain NeoplasmsHumansIntraoperative Neurophysiological MonitoringLanguageMagnetic Resonance ImagingMagnetoencephalographyMotor Cortexbrain mappingbrain tumorBVS = blood vessel segmentationDCS = direct cortical stimulationeloquentfMRIfMRI = functional MRIMEGMEG = magnetoencephalographyT1W = T1-weighted

Identifiers

PMID32006951
PMCPMC8186296
OpenAlexW3004149242

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

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.