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Astrocytoma

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Deep learning based on preoperative magnetic resonance (MR) images improves the predictive power of survival models in primary spinal cord astrocytomas.

Neuro-oncology
BACKGROUND: Prognostic models for spinal cord astrocytoma patients are lacking due to the low incidence of the disease. Here, we aim to develop a fully automated deep learning (DL) pipeline for stratified overall survival (OS) prediction based on pre...

Frameless robot-assisted stereotactic biopsy: an effective and minimally invasive technique for pediatric diffuse intrinsic pontine gliomas.

Journal of neuro-oncology
PURPOSE: Diffuse intrinsic pontine gliomas (DIPGs) are prone to high surgical risks, and they could even lead to death due to their specific sites. To determine the value of frameless robot-assisted stereotactic biopsies of DIPGs, when compared it wi...

Resection of Intracranial Tumors with a Robotic-Assisted Digital Microscope: A Preliminary Experience with Robotic Scope.

World neurosurgery
BACKGROUND: Magnified intraoperative visualization is of paramount importance during microsurgical procedures. Although the introduction of the operating microscope represented one of the most relevant innovations in modern neurosurgery, surgical vis...

Classification of paediatric brain tumours by diffusion weighted imaging and machine learning.

Scientific reports
To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocyt...

Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learning.

Scientific reports
Differentiating pseudoprogression from true tumor progression has become a significant challenge in follow-up of diffuse infiltrating gliomas, particularly high grade, which leads to a potential treatment delay for patients with early glioma recurren...

Improving the Reliability of Pharmacokinetic Parameters at Dynamic Contrast-enhanced MRI in Astrocytomas: A Deep Learning Approach.

Radiology
Background Pharmacokinetic (PK) parameters obtained from dynamic contrast agent-enhanced (DCE) MRI evaluates the microcirculation permeability of astrocytomas, but the unreliability from arterial input function (AIF) remains a challenge. Purpose To d...

Ependymoma and pilocytic astrocytoma: Differentiation using radiomics approach based on machine learning.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Mandatory accurate and specific diagnosis demands have brought about increased challenges for radiologists in pediatric posterior fossa tumor prediction and prognosis. With the development of high-performance computing and machine learning technologi...

Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging.

International journal of radiation oncology, biology, physics
PURPOSE: A noninvasive diagnostic method to predict the degree of malignancy accurately would be of great help in glioma management. This study aimed to create a highly accurate machine learning model to perform glioma grading.

Diffuse intrinsic pontine gliomas in children: Interest of robotic frameless assisted biopsy. A technical note.

Neuro-Chirurgie
INTRODUCTION: Diffuse intrinsic pontine gliomas (DIPG) constitute 10-15% of all brain tumors in the pediatric population; currently prognosis remains poor, with an overall survival of 7-14 months. Recently the indication of DIPG biopsy has been enlar...

Stereotactic robot-assisted MRI-guided laser thermal ablation of radiation necrosis in the posterior cranial fossa: technical note.

Neurosurgical focus
Laser interstitial thermal therapy (LITT) is a minimally invasive procedure used to treat a variety of intracranial lesions. Utilization of robotic assistance with stereotactic procedures has gained attention due to potential for advantages over conv...