Natural history of intraventricular meningiomas: systematic review

BJA Pereira, AN de Almeida, WS Paiva… - Neurosurgical …, 2020 - Springer
Review the data published on the subject to create a more comprehensive natural history of
intraventricular meningiomas (IVMs). A Medline search up to March 2018 using …

Prediction of high-grade histology and recurrence in meningiomas using routine preoperative magnetic resonance imaging: a systematic review

DC Spille, PB Sporns, K Hess, W Stummer… - World neurosurgery, 2019 - Elsevier
Objective Estimating the risk of recurrence after surgery remains crucial during care of
patients with meningioma. Numerous studies identified correlations of characteristics on …

Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI

J Hu, Y Zhao, M Li, J Liu, F Wang, Q Weng… - European Journal of …, 2020 - Elsevier
Purpose To investigate the prediction performance of radiomic models based on
multiparametric MRI in predicting the meningioma grade. Method In all, 229 low-grade …

Machine learning analyses can differentiate meningioma grade by features on magnetic resonance imaging

AT Hale, DP Stonko, L Wang, MK Strother… - Neurosurgical …, 2018 - thejns.org
OBJECTIVE Prognostication and surgical planning for WHO grade I versus grade II
meningioma requires thoughtful decision-making based on radiographic evidence, among …

WHO grade of intracranial meningiomas differs with respect to patient's age, location, tumor size and peritumoral edema

A Ressel, S Fichte, M Brodhun, SK Rosahl… - Journal of neuro …, 2019 - Springer
Purpose To analyse whether the WHO grade of intracranial meningiomas differs itself
depending on patients and meningioma characteristics at diagnosis. Methods Single center …

Multi-parametric MRI-based machine learning model for prediction of WHO grading in patients with meningiomas

Z Zhao, C Nie, L Zhao, D Xiao, J Zheng, H Zhang… - European …, 2024 - Springer
Objective The purpose of this study was to develop and validate a nomogram combined
multiparametric MRI and clinical indicators for identifying the WHO grade of meningioma …

WHO grade, proliferation index, and progesterone receptor expression are different according to the location of meningioma

F Maiuri, G Mariniello, E Guadagno, M Barbato… - Acta …, 2019 - Springer
Background Meningiomas may show a different WHO grade and variable biological and
clinical behaviors. The aim of the present study is to assess whether WHO grade …

Differentiation between benign and nonbenign meningiomas by using texture analysis from multiparametric MRI

C Ke, H Chen, X Lv, H Li, Y Zhang… - Journal of Magnetic …, 2020 - Wiley Online Library
Background It is difficult to prospectively differentiate between benign (World Health
Organization [WHO] I) and nonbenign (WHO II and III) meningiomas. Purpose To evaluate …

A novel framework for MR image segmentation and quantification by using MedGA

L Rundo, A Tangherloni, P Cazzaniga… - Computer methods and …, 2019 - Elsevier
Abstract Background and Objectives: Image segmentation represents one of the most
challenging issues in medical image analysis to distinguish among different adjacent tissues …

A practical overview on the molecular biology of meningioma

PD Delgado-López, E Cubo-Delgado… - Current Neurology and …, 2020 - Springer
Abstract Purpose of Review Meningioma is a common intracranial neoplasm currently
classified in 15 histologic subtypes across 3 grades of malignancy. First-choice therapy for …