scholarly journals Migraine as the First Symptom for Setting a Clinical Diagnosis

2020 ◽  
Vol 25 (1) ◽  
pp. 11-13
Author(s):  
Mariana-Alis Neagoe
Keyword(s):  
Brain Mri ◽  
Mass Effect ◽  
Local Relapse ◽  
Anaplastic Oligodendroglioma ◽  
Subtotal Resection ◽  
Hippocampal Region ◽  
Tumour Relapse ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain ◽  
Neurological State

AbstractThe migraine is among the most frequent complains of the patients requesting a medical consultation. I am presenting hereby the case of a 34-year old patient, who complained of diffuse migraine followed several weeks later by vomiting and seizures. The brain computed tomography (CT) and magnetic resonance imaging (MRI) examinations indicate an intracranial spread located in the left (temporal) hemisphere, which had a mass effect on the ventricular system. When performing the extemporaneous examination, it was found an anaplastic oligodendroglioma. Subtotal resection under microscopic guidance was performed, as well as radiotherapy and chemotherapy after the surgery. When discharged from hospital, the patient was surgically cured and had an improved neurological state. The repeated checkups (clinical and paraclinical) indicated no signs of local relapse. Approximately 8 years after the first surgery, the patient returned for a check-up, in view of investigations and treatment, while complaining of migraine and a nervousness state that was bothering his family. The brain MRI indicated a large tumour relapse located in the left temporal-hippocampal region. The histopathology examination indicated that it was an anaplastic oligodendroglioma relapse. Surgery was performed and the tumour relapse located in the left temporal-hippocampal region was completely ablated. After the surgery, the patient was conscious and had no movement dysfunctions.

scholarly journals Pelizaeus-Merzbacher Disease: A Case Report

2020 ◽  
Author(s):  
Ghazaleh Jamalipour Soufi ◽  
Siavash Iravan
Keyword(s):  
Case Report ◽  
White Matter ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Proteolipid Protein ◽  
Radiology Department ◽  
Magnetic Resonance Imaging Mri ◽  
Normal White Matter ◽  
Pelizaeus Merzbacher Disease ◽  
The Brain

Pelizaeus-Merzbacher Disease (PMD), as a rare genetically x-linked leukodystrophy, is a disorder of proteolipid protein expression in myelin formation. This disorder is clinically presented by neurodevelopmental delay and abnormal pendular eye movements. The responsible gene for this disorder is the proteolipid protein gene (PLP1). Our case was a oneyear-old boy referred to the radiology department for evaluating the Central Nervous System (CNS) development by brain Magnetic Resonance Imaging (MRI). Clinically, he demonstrated neuro-developmental delay symptoms. The brain MRI results indicated a diffuse lack of normal white matter myelination. This case report should be considered about the possibilityof PMD in the brain MRI of patients who present a diffuse arrest of normal white matter myelination.

scholarly journals A Review on Some Classification Methods of Brain Tumor MRI Datasets

2020 ◽  
pp. 421-424
Author(s):  
Nirmal Mungale ◽  
Snehal Kene ◽  
Amol Chaudhary
Keyword(s):  
Brain Tumor ◽  
Brain Mri ◽  
Mr Images ◽  
Classification Techniques ◽  
Abnormal Growth ◽  
Life Threatening ◽  
Magnetic Resonance Imaging Mri ◽  
Recent Classification ◽  
The Brain

Brain tumor is a life-threatening disease. Brain tumor is formed by the abnormal growth of cells inside and around the brain. Identification of the size and type of tumor is necessary for deciding the course of treatment of the patient. Magnetic Resonance Imaging (MRI) is one of the methods for detection of tumor in the brain. The classification of MR Images is a difficult task due to variety and complexity of brain tumors. Various classification techniques have been identified for brain MRI tumor images. This paper reviews some of these recent classification techniques.

scholarly journals Classification of Brain Tumors Using Hybridized Convolutional Neural Network in Brain MRI images

2022 ◽  
Vol 16 ◽  
pp. 561-570
Author(s):  
V Shwetha ◽  
C. H. Renu Madhavi ◽  
Kumar M. Nagendra
Keyword(s):  
Brain Mri ◽  
Morphological Operations ◽  
Hybrid Technique ◽  
Body Images ◽  
Anisotropic Diffusion Filter ◽  
Medical Disorders ◽  
Improved Performance ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain ◽  
Mri Image

In this research article, we have proposed a novel technique to operate on the Magnetic Resonance Imaging (MRI) data images which can be classified as image classification, segmentation and image denoising. With the efficient utilization of MRI images the medical experts are able to identify the medical disorders such as tumors which are correspondent to the brain. The prime agenda of the study is to organize brain into healthy and brain with tumor in brain with the test MRI data as considered. The MRI based technique is an methodology to study brain tumor based information for the better detailing of the internal body images when compared to other technique such as Computed Tomography (CT).Initially the MRI image is denoised using Anisotropic diffusion filter, then MRI image is segmented using Morphological operations, to classify the images for the disorder CNN based hybrid technique is incorporated, which is associated with five different set of layers with the pairing of pooling and convolution layers for the comparatively improved performance than other existing technique. The considered data base for the designed model is a publicly available and tested KAGGLE database for the brain MRI images which has resulted in the accuracy of 88.1%.

scholarly journals 3D U-Net for Skull Stripping in Brain MRI

2019 ◽  
Vol 9 (3) ◽  
pp. 569 ◽  
Author(s):  
Hyunho Hwang ◽  
Hafiz Zia Ur Rehman ◽  
Sungon Lee
Keyword(s):  
Deep Learning ◽  
Automatic Segmentation ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Brain Extraction ◽  
Skull Stripping ◽  
Segmentation Algorithms ◽  
Magnetic Resonance Imaging Mri ◽  
Deep Learning Network ◽  
The Brain

Skull stripping in brain magnetic resonance imaging (MRI) is an essential step to analyze images of the brain. Although manual segmentation has the highest accuracy, it is a time-consuming task. Therefore, various automatic segmentation algorithms of the brain in MRI have been devised and proposed previously. However, there is still no method that solves the entire brain extraction problem satisfactorily for diverse datasets in a generic and robust way. To address these shortcomings of existing methods, we propose the use of a 3D-UNet for skull stripping in brain MRI. The 3D-UNet was recently proposed and has been widely used for volumetric segmentation in medical images due to its outstanding performance. It is an extended version of the previously proposed 2D-UNet, which is based on a deep learning network, specifically, the convolutional neural network. We evaluated 3D-UNet skull-stripping using a publicly available brain MRI dataset and compared the results with three existing methods (BSE, ROBEX, and Kleesiek’s method; BSE and ROBEX are two conventional methods, and Kleesiek’s method is based on deep learning). The 3D-UNet outperforms two typical methods and shows comparable results with the specific deep learning-based algorithm, exhibiting a mean Dice coefficient of 0.9903, a sensitivity of 0.9853, and a specificity of 0.9953.

scholarly journals Concurrence of Juvenile Idiopathic Arthritis and Multiple Sclerosis

2011 ◽  
Vol 2011 ◽  
pp. 1-2
Author(s):  
Ben Abdelghani Kaouther ◽  
Souabni Leila ◽  
Belhadj Salwa ◽  
Zakraoui Leith
Keyword(s):  
Multiple Sclerosis ◽  
Juvenile Idiopathic Arthritis ◽  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Brain Mri ◽  
Resonance Imaging ◽  
Cerebral Magnetic Resonance Imaging ◽  
Need To Evaluate ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

We report a 21-year-old female patient known to have Juvenile idiopathic arthritis (JIA) who later developed multiple sclerosis (MS). The disease was documented on the brain and cerebral magnetic resonance imaging (MRI) and the visual evoked potential. Our case emphasizes the need to evaluate the symptoms and brain MRI carefully. The concurrence of MS and JIA is uncommon. The possible relationship between the 2 diseases was discussed.

scholarly journals Early signs of damage to the brain as a target organ in hypertension

2019 ◽  
Vol 11 (3S) ◽  
pp. 32-37 ◽  
Author(s):  
T. M. Ostroumova ◽  
O. D. Ostroumova ◽  
V. A. Parfenov
Keyword(s):  
Brain Damage ◽  
Diffusion Tensor ◽  
Brain Mri ◽  
Hypertensive Patients ◽  
Early Stages ◽  
Cerebrovascular Complications ◽  
Control Functions ◽  
Magnetic Resonance Imaging Mri ◽  
Function Testing ◽  
The Brain

The paper reviews the data available in the literature on and the results of the authors' own investigations of the signs of brain damage in hypertension in its early stages. The signs of early brain damage in hypertension can be considered as deteriorated control functions, white matter hyperintensities (WMH), as evidenced by the standard modes of magnetic resonance imaging (MRI), decreased fractional anisotropy in the frontal lobes, as shown by diffusion tensor MRI, and reduced cerebral perfusion. The latter two signs are detected even in hypertensive patients without WMH. Cognitive function testing and brain MRI using special regimens make it possible to identify a group of hypertensive patients at higher risk for cerebrovascular complications just in the early stages of the disease.

Outpatient Procedural Sedation of Patients With Autism Spectrum Disorders for Magnetic Resonance Imaging of the Brain Using Propofol

2018 ◽  
Vol 33 (5) ◽  
pp. 313-319 ◽  
Author(s):  
Pradip P. Kamat ◽  
Marie K. Karaga ◽  
Benjamin L. Wisniewski ◽  
Courtney E. McCracken ◽  
Harold K. Simon ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Mri ◽  
Autism Spectrum ◽  
Resonance Imaging ◽  
Serious Adverse Events ◽  
Children With Asd ◽  
Spectrum Disorders ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

Objective: To quantify the number of personnel, time to induce and complete sedation using propofol for outpatient magnetic resonance imaging (MRI) of the brain, and the frequency of serious adverse events (SAEs) in children with autism spectrum disorder (ASD) compared with children without ASD. Results: Baseline characteristics were the same between both groups. Overall sedation success was 99%. Although most children were sedated with ≤3 providers, 10% with ASD needed ≥4 providers (P = .005). The duration of sedation was less for the ASD group compared with the non-ASD group (49 minutes vs 56 minutes, P = .005). There was no difference in SAE frequency between groups (ASD 14% vs non-ASD 16%, P = .57). Conclusion: Children with ASD can be sedated for brain MRI using propofol with no increased frequency of SAEs compared with children without ASD. Sedation teams should anticipate that 10% of children with ASD may need additional personnel before propofol induction.

scholarly journals Systemic inflammatory response in infants with craniostenosis sedated with propofol

2021 ◽  
Vol 11 (3) ◽  
pp. 297-306
Author(s):  
Viktoriia I. Gurskaya ◽  
Vadim P. Ivanov ◽  
Vitalii Yu. Novikov ◽  
Natalia V. Draygina ◽  
Irina A. Savvina
Keyword(s):  
Blood Plasma ◽  
Brain Mri ◽  
Short Exposure ◽  
Intravenous Sedation ◽  
Resonance Imaging ◽  
Intravenous Anesthesia ◽  
Tumor Necrosis Factors ◽  
Before And After ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

AIM: This study aimed to investigate the possible effect of intravenous anesthesia (sedation) with propofol on the levels of several cytokines (interleukin [IL]-6, IL-8, IL-10, and tumor necrosis factors-) and S100B protein in the blood plasma of children aged 1 year with craniostenosis. MATERIALS AND METHODS: Twenty patients aged 112 months diagnosed with non-syndromic forms of craniosynostosis, who underwent magnetic resonance imaging (MRI) of the brain under propofol sedation, were classified according to ASA I-II class. Peripheral blood sampling was performed before and after the drug administration, followed by laboratory analysis. RESULTS: A significant increase was found in the serum level of IL-6 (p = 0.004) when intravenous sedation with propofol was used for 29 4.93 min. CONCLUSION: Short exposure of children aged 1 year with craniostenosis to hypnotic propofol during brain MRI significantly increased the level of the pro-inflammatory cytokine IL-6 in the blood plasma.

U-Net Model-Based Classification and Description of Brain Tumor in MRI Images

2021 ◽  
pp. 2140005
Author(s):  
P. Prakash Tunga ◽  
Vipula Singh ◽  
V. Sri Aditya ◽  
N. Subramanya
Keyword(s):  
Brain Tumor ◽  
Brain Mri ◽  
Ground Truth ◽  
Invasive Technique ◽  
Imaging Method ◽  
Non Invasive ◽  
Tissue Contrast ◽  
Tumor Region ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

In this paper, we discuss the classification of the brain tumor in Magnetic Resonance Imaging (MRI) images using the U-Net model, then evaluate parameters that indicate the performance of the model. We also discuss the extraction of the tumor region from brain image and description of the tumor regarding its position and size. Here, we consider the case of Gliomas, one of the types of brain tumors, which occur in common and can be fatal depending on their position and growth. U-Net is a model of Convolutional Neural Network (CNN) which has U-shaped architecture. MRI employs a non-invasive technique and can very well provide soft-tissue contrast and hence, for the detection and description of the brain tumor, this imaging method can be beneficial. Manual delineation of tumors from brain MRI is laborious, time-consuming and can vary from expert to expert. Our work forms a computer aided technique which is relatively faster and reproducible, and the accuracy is very much on par with ground truth. The results of the work can be used for treatment planning and further processing related to storage or transmission of images.

Co-occurrence of an intraventricular meningioma and cholesterol granuloma of the choroid plexus in a cat

2013 ◽  
Vol 41 (06) ◽  
pp. 408-412 ◽  
Author(s):  
M. Henrich ◽  
M. Kramer ◽  
M. J. Schmidt ◽  
N. Ondreka
Keyword(s):  
Choroid Plexus ◽  
Mass Effect ◽  
Cholesterol Granuloma ◽  
Resonance Imaging ◽  
The Third ◽  
Signal Characteristics ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain ◽  
Surrounding Parenchyma ◽  
Space Occupying Lesion

SummaryA 12-year-old domestic shorthair cat was presented with neurologic signs localized to the forebrain. Magnetic resonance imaging (MRI) of the brain revealed a space occupying lesion within the third and the lateral ventricles. The lesion had areas of disparate signal characteristics and exerted a mass effect on the surrounding parenchyma and ventricular system. The histologic examination identified the co-existence of two intraventricular masses: a meningioma and a choroid plexus cholesterol granuloma.

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