ArticleThe British journal of radiology2018
The diagnostic value of using combined MR diffusion tensor imaging parameters to differentiate between low- and high-grade meningioma.
Article in The British journal of radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Diagnostic imaging and emerging image-guided neurointervention in brain tumors: a narrative review.Frontiers in radiology · 2026Review
- Diagnostic performance of amide proton transfer-weighted imaging and four advanced diffusion-weighted MRI models for meningioma grading and subtyping.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Meningioma: Molecular Updates from the 2021 World Health Organization Classification of CNS Tumors and Imaging Correlates.AJNR. American journal of neuroradiology · 2025Review
- Granulation Patterns of Functional Corticotroph Tumors Correlate with Tumor Size, Proliferative Activity, T2 Intensity-to-White Matter Ratio, and Postsurgical Early Biochemical Remission.Endocrine pathology · 2024Article
- Multi-parametric MRI-based machine learning model for prediction of WHO grading in patients with meningiomas.European radiology · 2024Article
- Post-chemo-radiotherapy response and pseudo-progression evaluation on glioma cell types by multi-parametric magnetic resonance imaging: a prospective study.BMC medical imaging · 2023Article
- Preoperative Apparent Diffusion Coefficient Values for Differentiation between Low and High Grade Meningiomas: An Updated Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2022Review
- Differentiation between various types and subtypes of intracranial meningiomas with advanced MRI.SA journal of radiology · 2022Article
- Evaluation of Magnetic Resonance Imaging for Microsurgical Efficacy and Relapse of Rolandic Meningioma.Computational intelligence and neuroscience · 2022Article
- Article
- Importance of Pre-treatment Fractional Anisotropy Value in Predicting Volumetric Response in Patients with Meningioma Treated with Gamma Knife Radiosurgery.Current medical imaging · 2021Article
- Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas.Neuroradiology · 2020Article
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4 authors.
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Abstract
objectiveThe purpose of this study was to examine whether the combined use of MR diffusion tensor imaging (DTI) parameters [DTI-apparent diffusion coefficient (ADC), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD)] could provide a more accurate diagnosis in differentiating between low-grade and atypical/anaplastic (high-grade) meningioma.
methodsPathologically proven 45 meningioma patients [32 low-grade, 13 high-grade (11 atypical and 2 anaplastic)] who had received DTI before surgery were assessed retrospectively by 2 independent observers. For each lesion, MR DTI parameters (ADCmin, ADCmax, ADCmean, FA, AD, and RD) and ratios (rADCmin, rADCmax, rADCmean, rFA, rAD, and rRD) were calculated. When differentiating between low- and high-grade meningioma, the optimum cutoff values of all MR DTI parameters were determined by using receiver operating characteristic (ROC) analysis. Area under the curve (AUC) was measured with combined ROC analysis for different combinations of MR DTI parameters in order to identify the model combination with the best diagnostic accuracy in differentiation between low and high-grade meningioma.
resultsAlthough the ADCmin, ADCmax, ADCmean, AD, RD, rADCmin, rADCmax, rADCmean, rAD, and rRD values of high-grade meningioma were significantly low (p = 0.007, p = 0.045, p = 0.035, p = 0.045, p = 0.003, p = 0.02, p = 0.03, p = 0.03, p = 0.045, and p = 0.01, respectively), when compared with low-grade meningioma, their FA and rFA values were significantly high (p = 0.007 and p = 0.01, respectively). For all MR DTI parameters, the highest individual distinctive power was RD with AUC of 0.778. The best diagnostic accuracy in differentiating between low- and high-grade meningioma was obtained by combining the ADCmin, RD, and FA parameters with 0.962 AUC.
conclusionThis study shows that combined MR DTI parameters consisting of ADCmin, RD, and FA can differentiate high-grade from low-grade meningioma with a diagnostic accuracy of 96.2%. Advances in knowledge: To the best of our knowledge, this is the first study reporting that a combined use of all MR DTI parameters provides higher diagnostic accuracy for the differentiation of low- from high-grade meningioma. Our study shows that any of the model combinations was superior to use of any individual MR DTI parameters for differentiation between low and high-grade meningioma. A combination of ADCmin, RD, and FA was found to be the best model for differentiating low-grade from high-grade meningioma and sensitivity, specificity, and AUC values were found to be 92.3%, 100%, and 0.96, respectively. Thus, a combination of MR DTI parameters can provide more accurate diagnostic information when differentiation between low and high-grade meningioma.
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