Evidence map›Paper›PMID 31692177›Full record

ArticleHuman brain mapping2020

Real-time presurgical resting-state fMRI in patients with brain tumors: Quality control and comparison with task-fMRI and intraoperative mapping.

Kishore Vakamudi, Stefan Posse, Rex Jung, Brad Cushnyr, Muhammad O Chohan

Open access · hybridAbstract readComparative Study
In one paragraph

Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

21 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
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  8. NF-GAT: A Node Feature-Based Graph Attention Network for ASD Classification.IEEE open journal of engineering in medicine and biology · 2024
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  9. Review
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  15. Functional Approaches to the Surgery of Brain Gliomas.Advances and technical standards in neurosurgery · 2022
    Review
  16. Article
  17. Article
  18. 15 Years MR-encephalography.Magma (New York, N.Y.) · 2021
    Review
  19. 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

5 authors at 1 institution in 1 country.

Kishore VakamudiDepartment of Neurology, University of New Mexico, Albuquerque, New Mexico.ORCID 0000-0002-4518-2173
Stefan PosseDepartment of Neurology, University of New Mexico, Albuquerque, New Mexico.ORCID 0000-0002-4816-080X
Rex JungDepartment of Neurosurgery, University of New Mexico, Albuquerque, New Mexico.
Brad CushnyrDepartment of Radiology, University of New Mexico, Albuquerque, New Mexico.
Muhammad O ChohanDepartment of Neurosurgery, University of New Mexico, Albuquerque, New Mexico.
University of New Mexico · US

Funding

High-Speed fMRI of Resting State ConnectivityR21EB018494 · NIBIB · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI POSSE, STEFAN · 2015 to 2016
$459k
Clinical real-time resting state fMRIR41NS090691 · NINDS · NEURINSIGHT, LLC · PI POSSE, STEFAN · 2016 to 2016
$150k
NIBIB NIH HHS R21 EB018494NINDS NIH HHS R41 NS090691
6 · The paper itself

Abstract

Resting-state functional magnetic resonance imaging (rsfMRI) is a promising task-free functional imaging approach, which may complement or replace task-based fMRI (tfMRI) in patients who have difficulties performing required tasks. However, rsfMRI is highly sensitive to head movement and physiological noise, and validation relative to tfMRI and intraoperative electrocortical mapping is still necessary. In this study, we investigate (a) the feasibility of real-time rsfMRI for presurgical mapping of eloquent networks with monitoring of data quality in patients with brain tumors and (b) rsfMRI localization of eloquent cortex compared with tfMRI and intraoperative electrocortical stimulation (ECS) in retrospective analysis. Five brain tumor patients were studied with rsfMRI and tfMRI on a clinical 3T scanner using MultiBand(8)-echo planar imaging (EPI) with repetition time: 400 ms. Moving-averaged sliding-window correlation analysis with regression of motion parameters and signals from white matter and cerebrospinal fluid was used to map sensorimotor and language resting-state networks. Data quality monitoring enabled rapid optimization of scan protocols, early identification of task noncompliance, and head movement-related false-positive connectivity to determine scan continuation or repetition. Sensorimotor and language resting-state networks were identifiable within 1 min of scan time. The Euclidean distance between ECS and rsfMRI connectivity and task-activation in motor cortex, Broca's, and Wernicke's areas was 5-10 mm, with the exception of discordant rsfMRI and ECS localization of Wernicke's area in one patient due to possible cortical reorganization and/or altered neurovascular coupling. This study demonstrates the potential of real-time high-speed rsfMRI for presurgical mapping of eloquent cortex with real-time data quality control, and clinically acceptable concordance of rsfMRI with tfMRI and ECS localization.

Indexed as

Preoperative CareAdultBrain MappingBrain NeoplasmsCerebral CortexDiffusion Tensor ImagingEcho-Planar ImagingElectric StimulationElectrocorticographyFeasibility StudiesFemaleHumansIntraoperative Neurophysiological MonitoringLanguageMaleMiddle Agedelectrocortical mappingfunctional MRIhigh-speed fMRIpresurgical mappingreal-time fMRIresting-state fMRItask-based fMRI

Identifiers

PMID31692177
PMCPMC7268088
OpenAlexW2987090675

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.