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Record W2795110434 · doi:10.4103/1793-5482.228515

Meningioma consistency: Correlation between magnetic resonance imaging characteristics, operative findings, and histopathological features

2018· article· en· W2795110434 on OpenAlexaff
Mahmoud AlYamany, Mohammad Alshardan, Abdullah Abu Jamea, Nahid ElBakry, Lahbib Soualmi, Yasser Orz

Bibliographic record

VenueAsian Journal of Neurosurgery · 2018
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineMagnetic resonance imagingFluid-attenuated inversion recoveryMeningiomaRadiologyLesionHistopathologyBrain tumorNuclear medicinePathology

Abstract

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Introduction: Intracranial meningiomas account for 30% of all primary intracranial tumors. Surgical resection remains the mainstay of the treatment for meningiomas. The magnetic resonance of intracranial meningiomas has been largely discussed in many reports of the radiological and neurosurgical literature. To date, a few studies have been attempted to differentiate the tumor characteristics of meningiomas based on magnetic resonance imaging (MRI) studies. Objective: The objective of the study is to evaluate the relationship between MRI signal characteristics of intracranial meningiomas and consistency of tumor using objective measures. Materials and Methods: A prospective study included all the patients who were admitted for surgery with an MRI finding suggestive of meningioma. All patients were subjected to routine radiological investigations. Surgical resection was performed for patients eligible for surgery using cavitron ultrasonic aspirator (CUSA). The relationship and correlation between the radiological, intraoperative measurements and the histopathological diagnosis were studied. The tumor consistency was measured using mean CUSA level. Intensity on T2, fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging (DWI) was measured using circular regions of interest (ROI) on the MRI. Multiple ROIs were placed initially on the lesions avoiding the obvious blood vessels, if any, then on the brain cortex to avoid the vasogenic edema. The mean ROI (mROI) results from the lesion were subtracted from the mean ROI from the brain cortex for each lesion to achieve normalized ratio. The results of lesion mROI-cortex mROI were compared to the operative and histopathology results using Pearson's correlation test and linear regression test. Results: The total number of patients was seventy. The mean age of the patients was 51 ± 14.8, with 72% of them being females and 28% males. There was a strong statistically significant (P = 0.046) and (P = 0.003) correlation between mean CUSA and FLAIR mROI difference or T2 mROI difference, respectively. On the other hand, there was an inversely proportional relationship between mean CUSA and FLAIR mROI difference and mean CUSA and T2 mROI difference. The value of the regression test (r) shows that there was a slight linear relationship between FLAIR mROI difference or T2 mROI difference and mean CUSA values, in which the mean CUSA value = 50.1 + (−0.088) × FLAIR mROI difference (r = −0.273, P = 0.046) or mean CUSA value = 50.8 + (−0.055) × T2 mROI difference (r = 0.4, P = 0.003). There was no statistical significance in the relation between CUSA values and tumor histological subtypes, DWI values, age, or gender. Conclusion: This study presents a new objective method to measure the consistency of intracranial meningiomas based on a simple algorithmic formula. Such information will aid in planning surgery and assessing the resectability of the tumor. To date, this is the first objective measurement of meningioma consistency based on MRI studies and objective intraoperative evaluation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.264
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2018
Admission routes1
Has abstractyes

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