T1 and ADC histogram parameters may be an in vivo biomarker for predicting the grade, subtype, and proliferative activity of meningioma

Differentiation of intracranial solitary fibrous tumor/hemangiopericytoma from atypical meningioma using apparent diffusion coefficient histogram analysis

Apparent Diffusion Coefficient Histogram Analysis for the Preoperative Evaluation of Ki-67 Expression in Pituitary Macroadenoma

Differentiating atypical meningioma from anaplastic meningioma using diffusion weighted imaging

Simple Summary The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. Analyses of the NEPA provide additional information to the magnetic resonance imaging (MRI) evaluation of the enhancing part of brain tumors. NEPA analyses of central nervous system malignancies with conventional and advanced MRI techniques give interesting highlights in the differential diagnosis of solid contrast-enhanced brain tumors regarding the prognostic stratification and treatment response. Considering the rapid technological changes in advanced MRI imaging, we assume that an update on this topic might be of interest. Abstract The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed.

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Conventional and Advanced Magnetic Resonance Imaging Assessment of Non-Enhancing Peritumoral Area in Brain Tumor

Microcystic meningioma (MCM) appears similar to atypical meningioma(AM) as per conventional diagnostic imaging. However, considering their different recurrence rate and prognosis, accurate differential diagnosis is essential for determine the appropriate treatment strategy. The aim of the study was to differentiate MCM from AM by diffusion-weighted imaging (DWI), in order to provide the basis for accurate preoperative diagnosis. The preoperative clinical data, conventional MRI and DWI data of 15 MCM and 30 AM cases were retrospectively analyzed. The average apparent diffusion coefficient (ADCmean), minimum ADC (ADCmin) and normalized ADC (nADC) between MCM and AM were compared using two sample t-tests. The value of ADCmean, ADCmin and nADC in the differential diagnosis of MCM and AM were calculated by the receiver operating curve (ROC) analysis. The ADCmean (1.06 ± 0.10 vs 0.80 ± 0.11 × 10−3 mm2/s; P < 0.001), ADCmin (0.99 ± 0.10 vs 0.74 ± 0.12 × 10−3 mm2/s; P < 0.001) and nADC (1.45 ± 0.17 vs 1.07 ± 0.17; P < .0001) were significantly higher in MCM compared to AM. ADCmean of 0.91 × 10−3 mm2/s showed an optimum area under the ROC curve of 0.967 ± 0.022, and distinguished between MCM and AM with 86.67% sensitivity, 100% specificity and 88.89% accuracy. In addition, its positive and negative predictive values were 96.29% and 77.78% respectively. DWI can differentially diagnose MCM and AM, and ADCmean is a potential quantitative tool that can improve preoperative diagnosis of both tumors.

Differentiating microcystic meningioma from atypical meningioma using diffusion-weighted imaging.

Nomogram for predicting early recurrence in patients with high-grade gliomas.

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Differentiating microcystic meningioma from atypical meningioma using diffusion-weighted imaging.

Nomogram for predicting early recurrence in patients with high-grade gliomas.