Evidence map›Paper›PMID 38889968›Full record

ArticleAJNR. American journal of neuroradiology2024

Probabilistic Presurgical Language fMRI Atlas of Patients with Brain Tumors.

Jian Ming Teo, Vinodh A Kumar, Jina Lee, Rami W Eldaya, Ping Hou, Mu-Lan Jen, Kyle R Noll, Peng Wei, Sherise D Ferguson, Sujit S Prabhu and 2 more

Abstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

12 authors.

Jian Ming TeoFrom the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0003-3543-1719
Vinodh A KumarDepartment of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-8322-1233
Jina LeeDepartment of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0009-0003-1350-4419
Rami W EldayaDepartment of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-7801-1015
Ping HouFrom the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-1518-571X
Mu-Lan JenFrom the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas.
Kyle R NollDepartment of Neuro-Oncology (K.R.N.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-7105-1900
Peng WeiDepartment of Biostatistics (P.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas.
Sherise D FergusonDepartment of Neurosurgery (S.D.F., S.S.P.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-6344-0615
Sujit S PrabhuDepartment of Neurosurgery (S.D.F., S.S.P.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-8155-0623
Max WintermarkDepartment of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-6726-3951
Ho-Ling LiuFrom the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas HLALiu@mdanderson.org.ORCID 0000-0002-0284-5889

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
A Comprehensive Clinical fMRI Software Solution to Enable Mapping of Critical Functional Networks and Cerebrovascular Reactivity in the BrainR01CA258788 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CATHERINE L ELSINGER, Ho-Ling Anthony Liu · 2022 to 2026
$2.2M
NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA258788
6 · The paper itself

Abstract

background and purposePatients with brain tumors have high intersubject variation in putative language regions, which may limit the utility of straightforward application of healthy subject brain atlases in clinical scenarios. The purpose of this study was to develop a probabilistic functional brain atlas that consolidates language functional activations of sentence completion and Silent Word Generation language paradigms using a large sample of patients with brain tumors. MATERIALS AND

methodsThe atlas was developed using retrospectively collected fMRI data from patients with brain tumors who underwent their first standard-of-care presurgical language fMRI scan at our institution between July 18, 2015, and May 13, 2022. Three hundred seventeen patients (861 fMRI scans) were used to develop the language functional atlas. An independent presurgical language fMRI data set of 39 patients with brain tumors from a previous study was used to evaluate our atlas. Family-wise error-corrected binary functional activation maps from sentence completion, letter fluency, and category fluency presurgical fMRI were used to create probability overlap maps and pooled probabilistic overlap maps in Montreal Neurological Institute standard space. The Wilcoxon signed-rank test was used to determine a significant difference in the maximum Dice coefficient for our atlas compared with a meta-analysis-based template with respect to expert-delineated primary language area activations.

resultsProbabilities of activating the left anterior primary language area and left posterior primary language area in the temporal lobe were 87.9% and 91.5%, respectively, for sentence completion, 88.5% and 74.2%, respectively, for letter fluency, and 83.6% and 67.6%, respectively, for category fluency. Maximum Dice coefficients for templates derived from our language atlas were significantly higher than the meta-analysis-based template in the left anterior primary language area (0.351 and 0.326, respectively,

conclusionsBrain tumor patient- and paradigm-specific probabilistic language atlases were developed. These atlases had superior spatial agreement with fMRI activations in individual patients compared with the meta-analysis-based template.

Indexed as

Brain MappingBrain NeoplasmsLanguageMagnetic Resonance ImagingAdultAgedAtlases as TopicFemaleHumansMaleMiddle AgedPreoperative CareRetrospective StudiesYoung Adult

Identifiers

PMID38889968
PMCPMC11543082

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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.