Background: Glial tumors are most common brain tumors in our population. While the exact etiology and pathogenesis is unknown, the evaluation of current trends in the frequency and morphology of glial tumors is imperative to constitute better diagnostic and treatment protocols. Data pertaining to frequency and spectrum of glial tumors is scarcely available in our population. The aim of this study was to determine the morphologic spectrum of glial tumors prevalent in our population.
Method: 126 cases of glial tumors were retrospectively analyzed over a period of 5 years. Patients from all age groups and both genders were included in this study. Glial tumors were classified and graded according to WHO classification.
Results: Glial tumors were more common in males with a sex ratio of 2:1 and mean age of 38.26 years. Astrocytomas were most common glial tumors (51.6%) followed by oligodendrogliomas (23%). Glioblastoma was the most frequent astrocytic tumor and was incomparably frequent in older age group.
Conclusion: In our study, Oligodendrogliomas and mixed oligoastrocytomas represent major pattern of disease in comparison with available regional data. Knowledge of these changing trends and patterns of glial tumor morphology and frequency can help in improvements and applications of newly emerging diagnostic and treatment modalities.
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http://dx.doi.org/10.1186/1755-7682-7-33 | DOI Listing |
Aim: St. John\'s Wort Oil (JWO) has a sedative property and it is used traditionally for the treatment of depression, neuralgia and excitability. JWO has been shown to have anticancer activity via apoptosis in glioblastoma cells.
View Article and Find Full Text PDFAim: Many combinations of inflammation-based markers have been reported their prognostic ability. The prognostic value of albumin-to-gama-glutamyltransferase ratio (AGR), an inflammation-related index, has been identified for several cancers. However, the predictive value of AGR for high-grade glioma patients remains unclear.
View Article and Find Full Text PDFAim: This study aims to assess the clinicopathological and prognostic significance of Tim-3, an immune checkpoint molecule, and Rel-B, an NF-κB subunit, in grade 4 diffuse glioma samples and their relationship with each other.
Material And Methods: The demographic, radiologic, prognostic, and treatment data of patients diagnosed with grade 4 diffuse glioma between 2016 and 2019 were reviewed and recorded. Tim-3 and Rel-B were applied to the paraffin-embedded tissues by immunohistochemistry method.
Objective: To assist in the rapid clinical identification of brain tumor types while achieving segmentation detection, this study investigates the feasibility of applying the deep learning YOLOv5s algorithm model to the segmentation of brain tumor magnetic resonance images and optimizes and upgrades it on this basis.
Methods: The research institute utilized two public datasets of meningioma and glioma magnetic resonance imaging from Kaggle. Dataset 1 contains a total of 3,223 images, and Dataset 2 contains 216 images.
F1000Res
January 2025
Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Introduction: Magnetic resonance imaging (MRI) is essential for brain imaging, but conventional methods rely on qualitative contrast, are time-intensive, and prone to variability. Magnetic resonance finger printing (MRF) addresses these limitations by enabling fast, simultaneous mapping of multiple tissue properties like T1, T2. Using dynamic acquisition parameters and a precomputed signal dictionary, MRF provides robust, qualitative maps, improving diagnostic precision and expanding clinical and research applications in brain imaging.
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