Evidence map›Paper›PMID 40135019›Full record

ArticleCureus2025

Apparent Diffusion Coefficient (ADC) and Magnetic Resonance Imaging (MRI) Nomogram for Differentiating a Solitary Fibrous Tumor (World Health Organization Grade II) From an Angiomatous Meningioma.

Yu Ying, Noorazrul Yahya, Hanani Abdul Manan

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Yu YingDepartment of Interventional Radiology, University Kebangsaan Malaysia Medical Centre, Kuala Lumpur, MYS.
Noorazrul YahyaDepartment of Diagnostic Imaging and Radiotherapy, Centre for Diagnostic, Therapeutic and Investigative Sciences, Faculty of Health Sciences, National University of Malaysia, Kuala Lumpur, MYS.
Hanani Abdul MananFunctional Image Processing Laboratory, Department of Radiology, National University of Malaysia, Kuala Lumpur, MYS.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAccurate preoperative differentiation between intracranial solitary fibrous tumor (SFT, World Health Organization grade II) and angiomatous meningioma (AM) is crucial for surgical planning and prognosis prediction. While conventional magnetic resonance imaging (MRI) is widely used, distinguishing these tumors based on imaging alone remains challenging. This study aimed to evaluate clinical and MRI features to improve diagnostic accuracy between SFT and AM, focusing on the apparent diffusion coefficient (ADC) and conventional MRI parameters.

methodsA retrospective analysis was conducted on 51 patients (23 with SFT and 28 with AM) confirmed by pathology. Clinical and MRI characteristics were assessed using t-tests and chi-square tests. Logistic regression analysis was performed to identify independent predictors, and receiver operating characteristic (ROC) curve analysis evaluated diagnostic performance. A nomogram integrating ADC values with conventional MRI features was developed and validated using calibration curves.

resultsSignificant differences in tumor shape, cystic necrosis, T1-weighted imaging and T2-weighted imaging signal intensities, and ADC values were observed between SFT and AM (p < 0.05). Logistic regression analysis confirmed these factors as independent predictors, with ADC demonstrating the highest diagnostic performance at an optimal cutoff value of 1.08 × 10

conclusionIntegrating ADC values with clinical and MRI features provides a reliable method for differentiating intracranial SFT from AM. This approach enhances diagnostic precision, aiding in optimized clinical decision-making and surgical planning.

Indexed as

diffusion-weighted imagingmagnetic resonance imagingmeningiomanomogramsolitary fibrous tumor

Identifiers

PMID40135019
PMCPMC11933727

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