Evidence map›Paper›PMID 27873040›Full record

SynthesisNeurosurgical review2018

Can MRI predict meningioma consistency?: a correlation with tumor pathology and systematic review.

Amy Yao, Margaret Pain, Priti Balchandani, Raj K Shrivastava

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Neurosurgical review, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
3.1field-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.

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

37 citing papers in PubMed, 86 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Amy YaoDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, Annenberg 8, One Gustave L Levy Pl, New York, NY, 10029, USA. amy.yao@icahn.mssm.edu.ORCID http://orcid.org/0000-0003-1751-9901
Margaret PainDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, Annenberg 8, One Gustave L Levy Pl, New York, NY, 10029, USA.
Priti BalchandaniDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, Annenberg 8, One Gustave L Levy Pl, New York, NY, 10029, USA.
Raj K ShrivastavaDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, Annenberg 8, One Gustave L Levy Pl, New York, NY, 10029, USA.
Icahn School of Medicine at Mount Sinai · US

Funding

7T Neurosurgical Mapping Protocol for Endoscopic Resection of Skull Base TumorsR01CA202911 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BALCHANDANI, PRITI · 2016 to 2020
$2.1M
NCI NIH HHS R01 CA202911
6 · The paper itself

Abstract

Tumor consistency is a critical factor that influences operative strategy and patient counseling. Magnetic resonance imaging (MRI) describes the concentration of water within living tissues and as such, is hypothesized to predict aspects of their biomechanical behavior. In meningiomas, MRI signal intensity has been used to predict the consistency of the tumor and its histopathological subtype, though its predictive capacity is debated in the literature. We performed a systematic review of the PubMed database since 1990 concerning MRI appearance and tumor consistency to assess whether or not MRI can be used reliably to predict tumor firmness. The inclusion criteria were case series and clinical studies that described attempts to correlate preoperative MRI findings with tumor consistency. The relationship between the pre-operative imaging characteristics, intraoperative findings, and World Health Organization (WHO) histopathological subtype is described. While T2 signal intensity and MR elastography provide a useful predictive measure of tumor consistency, other techniques have not been validated. T1-weighted imaging was not found to offer any diagnostic or predictive value. A quantitative assessment of T2 signal intensity more reliably predicts consistency than inherently variable qualitative analyses. Preoperative knowledge of tumor firmness affords the neurosurgeon substantial benefit when planning surgical techniques. Based upon our review of the literature, we currently recommend the use of T2-weighted MRI for predicting consistency, which has been shown to correlate well with analysis of tumor histological subtype. Development of standard measures of tumor consistency, standard MRI quantification metrics, and further exploration of MRI technique may improve the predictive ability of neuroimaging for meningiomas.

Indexed as

Elasticity Imaging TechniquesHumansMagnetic Resonance ImagingMeningiomaMagnetic resonance imagingMeningiomaPathologyTumor consistency

Identifiers

PMID27873040
PMCPMC5438899
OpenAlexW2550609160

What OpenQuestion holds

Textmetadata
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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.