Brain Tumor
Recently Published Documents





2022 ◽  
Vol 8 (1) ◽  
pp. 333-340
Md. RashidoonNabi Khan

Background: Among the risk factors of cardiovascular diseases, hypertension is one of the major reason. Intracranial hypertension (IIH) is a pressure buildup around the brain. It can happen unexpectedly, as a result of a severe head injury, stroke, or brain abscess could be occurred. It could also be a chronic, long-term condition, known as IIH. It results in the signs and symptoms of a brain tumor. Which is also known as benign intracranial hypertension. Cerebrospinal fluid, or CSF, is the fluid that surrounds the spinal cord and brain. CSF can accumulate if too much fluid is produced or not enough is reabsorbed. This can induce symptoms similar to a brain tumor. Intracranial Hypertension can be classified into three categories, they are Acute, Chronic and Idiopathic. IIH is recognized when the increased intracranial pressure cannot be explained by any other underlying cause.Aim: The aim of the study was to observe idiopathic intracranial hypertension patients in a select tertiary care hospital of Bangladesh.Methods:This cross-sectional observational study was conducted at the Department of Neurosurgery, Sylhet M. A. G. Osmani Medical College Hospital, Sylhet, Bangladesh. The study duration was from January 2012 to December 2020. A total number of 47 participants had been recruited as study population.Results:Male: female ratio was 1:10.75, and 91% of the total participants were female. 40.43% of the participants were aged between 21-30 years. 46.81% were overweight and 34.04% were obese. Most common symptom was nausea, followed by visual impairment and double vision.Conclusion:The prevalence of Idiopathic Intracranial Hypertension is much higher among the female. Female and high BMI are significant risk factors of IIH. It is more prevalent among young adults, and results on various vision related symptoms.

Oliver Y. Tang ◽  
Ross A. Clarke ◽  
Krissia M. Rivera Perla ◽  
Kiara M. Corcoran Ruiz ◽  
Steven A. Toms ◽  

2022 ◽  
Vol 12 ◽  
Fedele Dono ◽  
Stefano Consoli ◽  
Giacomo Evangelista ◽  
Annalisa Ricci ◽  
Mirella Russo ◽  

Purpose: Brain tumor-related epilepsy (BTRE) is a condition characterized by the development of seizures in the context of an undergoing oncological background. Levetiracetam (LEV) is a third-generation anti-seizure medication (ASM) widely used in BTRE prophylaxis. The study evaluated LEV neuropsychiatric side effects (SEs) in BTRE prophylaxis.Method: Twenty-eight patients with brain tumors were retrospectively selected and divided into two groups. In one group, we evaluated patients with a BTRE diagnosis using LEV (BTRE-group). The other group included patients with brain tumors who never had epilepsy and used a prophylactic ASM regimen with LEV (PROPHYLAXIS-group). Neuropsychiatric SEs of LEV were monitored using the Neuropsychiatric Inventory Questionnaire (NPI-Q) at the baseline visit and the 6- and 12-month follow-up.Results: Eighteen patients of the BTRE-group and 10 patients of the PROPHYLAXIS-group were included. Compared to the BTRE-group, the PROPHYLAXIS-group showed a higher severity of neuropsychiatric symptoms. According to Linear Mixed Models (LMM), a multiplicative effect was observed for the interaction between group treatment and time. For the caregiver distress score (CDS), only a time-effect was observed.Conclusion: Prophylactic ASM with LEV is associated with an increased frequency of neuropsychiatric SE. Accurate epileptological evaluations in patients with brain tumors are mandatory to select who would benefit most from ASM.

2022 ◽  
Aurora Campo ◽  
Francisco Fernandez-Flores ◽  
Marti Pumarola

Background and objective: Glial fibrillar acid protein is a common marker for brain tumor because of its particular rearrangement during tumor development. It is commonly used in manually histological glioma detection and grading. An automatic pipeline for tumor diagnosis based on GFAP is proposed in the present manuscript for detecting and grading canine brain glioma in stages III and IV. Methods: The study was performed on canine brain tumor stages III and IV as well as healthy tissue immunohistochemically stained for gliofibrillar astroglial protein. Four stereological indexes were developed using the area of the image as reference unit: density of glioma protein, density of neuropil, density of astrocytes and the glioma nuclei number density. Images of the slides were subset for image analysis (n=1415) and indexed. The stereological indexes of each subset constituted an array of data describing the tumor phase of the subset. A 5% of these arrays were used as training set for decision tree classification with PCA. The other arrays were further classified in a supervised approach. ANOVA and PCA analysis were applied to the indexes. Results: The final pipeline is able to detect brain tumor and to grade it automatically. Added to it, the role the neuropil during tumor development has been quantified for the first time. While astroglial cells tend to disappear, glioma cells invade all the tumor area almost to a saturation in stage III before reducing the density in stage IV. The density of the neuropil is reduced during the tumour growth. Conclusions: The method validated ere allows the automated diagnosis and grading of glioma in dogs. This method opens the research of the role of the neuropil in tumor development.

2022 ◽  
Vol 2022 ◽  
pp. 1-18
Muhammad Arif ◽  
F. Ajesh ◽  
Shermin Shamsudheen ◽  
Oana Geman ◽  
Diana Izdrui ◽  

Radiology is a broad subject that needs more knowledge and understanding of medical science to identify tumors accurately. The need for a tumor detection program, thus, overcomes the lack of qualified radiologists. Using magnetic resonance imaging, biomedical image processing makes it easier to detect and locate brain tumors. In this study, a segmentation and detection method for brain tumors was developed using images from the MRI sequence as an input image to identify the tumor area. This process is difficult due to the wide variety of tumor tissues in the presence of different patients, and, in most cases, the similarity within normal tissues makes the task difficult. The main goal is to classify the brain in the presence of a brain tumor or a healthy brain. The proposed system has been researched based on Berkeley’s wavelet transformation (BWT) and deep learning classifier to improve performance and simplify the process of medical image segmentation. Significant features are extracted from each segmented tissue using the gray-level-co-occurrence matrix (GLCM) method, followed by a feature optimization using a genetic algorithm. The innovative final result of the approach implemented was assessed based on accuracy, sensitivity, specificity, coefficient of dice, Jaccard’s coefficient, spatial overlap, AVME, and FoM.

2022 ◽  
Vol 2022 ◽  
pp. 1-6
Lan Sook Chang ◽  
Youn Hwan Kim ◽  
Sang Wha Kim

Temporal hollowing deformity (THD) is a contour irregularity in the frontotemporal region, which results in facial asymmetry in the frontal view. Here, we present our clinical experience of correction of THD using serratus anterior (SA) muscle and fascia free flaps. Between March 2016 and December 2018, 13 patients presenting with THD were treated with SA free flap. The mean age of the patients was 47.8 years. The patients received craniectomy due to subarachnoid hemorrhage, epidural hematoma, or brain tumor. On average, correction of THD was performed 17 months after cranioplasty. The SA flap size ranged from 5 × 5   cm to 10 × 8   cm . The mean operation time was 107.3 minutes. All of the flaps survived without complications. The mean follow-up duration was 20.3 months. For correction of THD, the SA muscle and fascia flap is among the best candidates to permanently restore aesthetic form and symmetry.

Silvia Schiavolin ◽  
Arianna Mariniello ◽  
Morgan Broggi ◽  
Francesco DiMeco ◽  
Paolo Ferroli ◽  

Sign in / Sign up

Export Citation Format

Share Document