Evidence map›Paper›PMID 35299624›Full record

ArticleFrontiers in neuroscience2022

Validation of Non-invasive Language Mapping Modalities for Eloquent Tumor Resection: A Pilot Study.

Matthew Muir, Rajan Patel, Jeffrey Traylor, Dhiego Chaves de Almeida Bastos, Sarah Prinsloo, Ho-Ling Liu, Kyle Noll, Jeffrey Wefel, Sudhakar Tummala, Vinodh Kumar and 1 more

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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  6. Review
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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

11 authors.

Matthew MuirDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Rajan PatelDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Jeffrey TraylorDepartment of Neurological Surgery, The University of Texas Southwestern Medical Center, Dallas, TX, United States.
Dhiego Chaves de Almeida BastosDepartment of Neurosurgery, Cleveland Clinic, Cleveland, OH, United States.
Sarah PrinslooDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Ho-Ling LiuDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Kyle NollDepartment of Neuropsychology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Jeffrey WefelDepartment of Neuropsychology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Sudhakar TummalaDepartment of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Vinodh KumarDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Sujit PrabhuDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many studies have established a link between extent of resection and survival in patients with gliomas. Surgeons must optimize the oncofunctional balance by maximizing the extent of resection and minimizing postoperative neurological morbidity. Preoperative functional imaging modalities are important tools for optimizing the oncofunctional balance. Transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) are non-invasive imaging modalities that can be used for preoperative functional language mapping. Scarce data exist evaluating the accuracy of these preoperative modalities for language mapping compared with gold standard intraoperative data in the same cohort. This study compares the accuracy of fMRI and TMS for language mapping compared with intraoperative direct cortical stimulation (DCS). We also identified significant predictors of preoperative functional imaging accuracy, as well as significant predictors of functional outcomes. Evidence from this study could inform clinical judgment as well as provide neuroscientific insight. We used geometric distances to determine copositivity between preoperative data and intraoperative data. Twenty-eight patients were included who underwent both preoperative fMRI and TMS procedures, as well as an awake craniotomy and intraoperative language mapping. We found that TMS shows significantly superior correlation to intraoperative DCS compared with fMRI. TMS also showed significantly higher sensitivity and negative predictive value than specificity and positive predictive value. Poor cognitive baseline was associated with decreased TMS accuracy as well as increased risk for worsened aphasia postoperatively. TMS has emerged as a promising preoperative language mapping tool. Future work should be done to identify the proper role of each imaging modality in a comprehensive, multimodal approach to optimize the oncofunctional balance.

Indexed as

aphasiabrain mappingdirect cortical stimulationeloquentfunctional MRIgliomastranscranial magnetic stimulation

Identifiers

PMID35299624
PMCPMC8923233

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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.