AIMC Topic: Meningeal Neoplasms
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Image-Guided Robotic Radiosurgery for Treatment of Recurrent Grade II and III Meningiomas. A Single-Center Study.
World neurosurgery
Jul 12, 2019
OBJECTIVE: Stereotactic radiosurgery (SRS) has been increasingly applied for malignant meningiomas as an alternative to conventionally fractioned radiation therapy. We performed a retrospective analysis of an institutional patient cohort with maligna...
Presurgical differentiation between malignant haemangiopericytoma and angiomatous meningioma by a radiomics approach based on texture analysis.
Journal of neuroradiology = Journal de neuroradiologie
Jun 18, 2019
PURPOSE: To assess whether a machine-learning model based on texture analysis (TA) could yield a more accurate diagnosis in differentiating malignant haemangiopericytoma (HPC) from angiomatous meningioma (AM).
A deep learning radiomics model for preoperative grading in meningioma.
European journal of radiology
May 1, 2019
OBJECTIVES: To noninvasively differentiate meningioma grades by deep learning radiomics (DLR) model based on routine post-contrast MRI.
Neoplasm Grading
Preoperative Care
Meningioma
Meningeal Neoplasms
Adolescent
Cohort Studies
Magnetic Resonance Imaging
Area Under Curve
Reproducibility of Results
Algorithms
Aged
Meninges
Prognosis
Young Adult
Sensitivity and Specificity
Retrospective Studies
Humans
Adult
Male
Female
Middle Aged
Deep Learning
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.
European radiology
Nov 15, 2018
OBJECTIVES: Preoperative, noninvasive prediction of the meningioma grade is important because it influences the treatment strategy. The purpose of this study was to evaluate the role of radiomics features of postcontrast T1-weighted images (T1C), app...
The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest.
European radiology
Aug 7, 2018
OBJECTIVES: The preoperative prediction of the WHO grade of a meningioma is important for further treatment plans. This study aimed to assess whether texture analysis (TA) based on apparent diffusion coefficient (ADC) maps could non-invasively classi...
Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI.
European radiology
Jun 25, 2018
OBJECTIVES: Magnetic resonance imaging (MRI) is the method of choice for imaging meningiomas. Volumetric assessment of meningiomas is highly relevant for therapy planning and monitoring. We used a multiparametric deep-learning model (DLM) on routine ...
Development of a deep convolutional neural network to predict grading of canine meningiomas from magnetic resonance images.
Veterinary journal (London, England : 1997)
Apr 4, 2018
An established deep neural network (DNN) based on transfer learning and a newly designed DNN were tested to predict the grade of meningiomas from magnetic resonance (MR) images in dogs and to determine the accuracy of classification of using pre- and...
eNAL++: a new and effective off-line correction protocol for rotational setup errors when using a robotic couch.
Journal of applied clinical medical physics
Nov 8, 2015
Cone-beam CTs (CBCTs) installed on a linear accelerator can be used to provide fast and accurate automatic six degrees of freedom (6DoF) vector displacement information of the patient position just prior to radiotherapy. These displacement correction...
A multiresolution clinical decision support system based on fractal model design for classification of histological brain tumours.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 7, 2014
Tissue texture is known to exhibit a heterogeneous or non-stationary nature; therefore using a single resolution approach for optimum classification might not suffice. A clinical decision support system that exploits the subbands' textural fractal ch...
Microscopy
Sensitivity and Specificity
Image Interpretation, Computer-Assisted
Brain Neoplasms
Pattern Recognition, Automated
Decision Support Systems, Clinical
Image Enhancement
Support Vector Machine
Meningioma
Humans
Fractals
Machine Learning
Meningeal Neoplasms
Algorithms
Reproducibility of Results
[Radiosurgery of benign intracranial lesions. Indications, results , and perspectives].
Revue medicale suisse
May 14, 2025
Stereotactic radiosurgery (SRS) is a non-invasive technique that is transforming the management of benign intracranial lesions through its precision and preservation of healthy tissues. It is effective for meningiomas, trigeminal neuralgia (TN), pitu...
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