• Annals of Clinical Neurophysiology
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• v.19 no.2
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• pp.93-100
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• 2017

In this article, we review the differences of the brain morphology according to age, sex, and handedness. Age is a well-known factor affecting brain morphology. With aging, progressive reduction of brain volume is driven. Sex also has great effects on brain morphology. Although there are some reports that the differences of brain morphology may originate from the differences of weight between the 2 sexes, studies have demonstrated that there are regional differences even after the correction for weight. Handedness has long been regarded as a behavioral marker of functional asymmetry. Although there have been debates about the effect of handedness on brain morphology, previous well-established studies suggest there are differences in some regions according to handedness. Even with the studies done so far, normal brain morphology is not fully understood. Therefore, studies specific for the each ethnic group and standardized methods are needed to establish a more reliable database of healthy subjects' brain morphology.

• Advances in biomechanics and applications
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• v.1 no.4
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• pp.253-267
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• 2014

The human head is identified as the body region most frequently involved in life-threatening injuries. Extensive research based on experimental, analytical and numerical methods has sought to quantify the response of the human head to blunt impact in an attempt to explain the likely injury process. Blunt head impact arising from vehicular collisions, sporting injuries, and falls leads to relative motion between the brain and skull and an increase in contact and shear stresses in the meningeal region, thereby leading to traumatic brain injuries. In this paper the properties and material modeling of the subarachnoid space (SAS) as it relates to Traumatic Brain Injuries (TBI) is investigated. This was accomplished using a simplified local model and a validated 3D finite element model. First the material modeling of the trabeculae in the Subarachnoid Space (SAS) was investigated and validated, then the validated material property was used in a 3D head model. In addition, the strain in the brain due to an impact was investigated. From this work it was determined that the material property of the SAS is approximately E = 1150 Pa and that the strain in the brain, and thus the severity of TBI, is proportional to the applied impact velocity and is approximately a quadratic function. This study reveals that the choice of material behavior and properties of the SAS are significant factors in determining the strain in the brain and therefore the understanding of different types of head/brain injuries.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5401-5406
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• 2015

Background: Brain metastases are the most common intra-cranial neoplasms. The incidence is on a rise due to advanced imaging techniques. Aims: The objective of the study was to analyse the clinical and demographic profile of patients with brain metastases from primary solid tumors. Materials and Methods: This is a retrospective single institutional study covering 130 consecutive patients with brain metastases from January 2007 to August 2014. Results: Some 64.6% of the patients were females. The majority were in the sixth decade of life. The site of the primary tumor was the lungs in 50.8% of the cases. The overall median time from the diagnosis of the primary malignancy to detection of brain metastases was 21.4 months. Survival was found to be significantly improved in patients with solitary brain lesions when compared to patients with multiple brain metastases, and in patients undergoing surgical excision with or without cranial irradiation when compared to whole brain irradiation alone. The majority of the cases belonged to the recursive partitioning analysis class II group. Whole brain radiation therapy was delivered to 79% of the patients. Conclusions: Most of the patients with brain metastases in the study belonged to recursive partitioning analysis classes II or III, and hence had poor prognosis. Most of the patients in the Indian context either do not satisfy the indications for surgical excision or are incapable of bearing the high cost associated with stereotactic radiosurgery. Treatment should be tailored on an individual basis to all these patients.

• Journal of Biomedical Engineering Research
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• v.26 no.3
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• pp.129-132
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• 2005

It is one of the most important issues to determine a target brain image that gives a common coordinate system for a constructing population-based brain atlas. The purpose of this study is to provide a simple and reliable procedure that determines the target brain image among the group based on the inherent structural information of three-dimensional magnetic resonance (MR) images. It uses only 11 lines defined automatically as a feature vector representing structural variations based on the Talairach coordinate system. Average characteristic vector of the group and the difference vectors of each one from the average vector were obtained. Finally, the individual data that had the minimum difference vector was determined as the target. We determined the target brain image by both our algorithm and conventional visual inspection for 20 healthy young volunteers. Eighteen fiducial points were marked independently for each data to evaluate the similarity. Target brain image obtained by our algorithm showed the best result, and the visual inspection determined the second one. We concluded that our method could be used to determine an appropriate target brain image in constructing brain atlases such as disease-specific ones.

• The Korean Journal of Nuclear Medicine
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• v.2 no.1
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• pp.59-66
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• 1968

Technetium 99m pertechnetate brain scanning were performed in 3 cases of head injury (2 chronic subdural hematomas and 1 acute epidural hematoma), 2 cases of brain abscess and I case of intracerebral hematoma associated with arteriovenous anomaly. In all the cases brain scintigrams showed "hot areas." Literatures on radioisotope scanning of intracranial lesions were briefly reviewed. With the improvement of radioisotope scanner and development of new radiopharmaceuticals brain scanning became a safe and useful screening test for diagnosis of intracranial lesions. Brain scanning can be easily performed even to a moribund patient without any discomfort and risk to the patient which are associated with cerebral angiography or pneumoencephalography. Brain scanning has been useful in diagnosis of brain tumor, brain abscess, subdural hematoma, and cerebral vascular diseases. In 80 to 90% of brain tumors positive scintigrams can be expected. Early studies were done with $^{203}Hg$-Neohydrin or $^{131}I$-serum albumin. With these agents, however, patients receive rather much radiation to the whole body and kidneys. In 1965 Harper introduced $^{99m}Tc$ to reduce radiation dose to the patient and improve statistical variation in isotope scanning.

• Annals of Clinical Neurophysiology
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• v.22 no.2
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• pp.82-91
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• 2020

Electroencephalography (EEG) produces time-series data of neural oscillations in the brain, and is one of the most commonly used methods for investigating both normal brain functions and brain disorders. Quantitative EEG analysis enables identification of frequencies and brain activity that are activated or impaired. With studies on the structural and functional networks of the brain, the concept of the brain as a complex network has been fundamental to understand normal brain functions and the pathophysiology of various neurological disorders. Functional connectivity is a measure of neural synchrony in the brain network that refers to the statistical interdependency between neural oscillations over time. In this review, we first discuss the basic methods of EEG analysis, including preprocessing, spectral analysis, and functional-connectivity and graph-theory measures. We then review previous EEG studies of brain network characterization in several neurological disorders, including epilepsy, Alzheimer's disease, dementia with Lewy bodies, and idiopathic rapid eye movement sleep behavior disorder. Identifying the EEG-based network characteristics might improve the understanding of disease processes and aid the development of novel therapeutic approaches for various neurological disorders.

• Journal of Gastric Cancer
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• v.21 no.3
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• pp.319-324
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• 2021

The abscopal effect refers to the phenomenon in which local radiotherapy is associated with the regression of metastatic cancer that is distantly located from the irradiated site. Here, we present a case of a patient with advanced gastric cancer and brain metastases who was successfully treated with brain radiotherapy and anti-programmed death-1 (PD-1) therapy-induced abscopal effect. Although anti-PD-1 therapy alone could not prevent disease progression, the metastatic lesions in the brain and also in the abdominal lymph node showed a drastic response after brain radiotherapy and anti-PD-1 therapy. To our knowledge, this is the first reported case of successful treatment of advanced gastric cancer with multiple brain and abdominal lymph node metastases, possibly through anti-PD-1 therapy combined with brain radiotherapy-induced abscopal effect. We suggest that the combination of brain radiotherapy and anti-PD-1 therapy may be considered as a therapeutic option for advanced gastric cancer, especially when there is brain metastasis.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1233-1241
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• 2022

Tumors of the brain are the deadliest, with a life expectancy of only a few years for those with the most advanced forms. Diagnosing a brain tumor is critical to developing a treatment plan to help patients with the disease live longer. A misdiagnosis of brain tumors will lead to incorrect medical treatment, decreasing a patient's chance of survival. Radiologists classify brain tumors via biopsy, which takes a long time. As a result, the doctor will need an automatic classification system to identify brain tumors. Image classification is one application of the deep learning method in computer vision. One of the deep learning's most powerful algorithms is the convolutional neural network (CNN). This paper will introduce a novel deep learning structure and image gradient to classify brain tumors. Meningioma, glioma, and pituitary tumors are the three most popular forms of brain cancer represented in the Figshare dataset, which contains 3,064 T1-weighted brain images from 233 patients. According to the numerical results, our method is more accurate than other approaches.

• BMB Reports
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• v.57 no.7
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• pp.311-317
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• 2024

Brain organoid is a three-dimensional (3D) tissue derived from stem cells such as induced pluripotent stem cells (iPSCs) embryonic stem cells (ESCs) that reflect real human brain structure. It replicates the complexity and development of the human brain, enabling studies of the human brain in vitro. With emerging technologies, its application is various, including disease modeling and drug screening. A variety of experimental methods have been used to study structural and molecular characteristics of brain organoids. However, electrophysiological analysis is necessary to understand their functional characteristics and complexity. Although electrophysiological approaches have rapidly advanced for monolayered cells, there are some limitations in studying electrophysiological and neural network characteristics due to the lack of 3D characteristics. Herein, electrophysiological measurement and analytical methods related to neural complexity and 3D characteristics of brain organoids are reviewed. Overall, electrophysiological understanding of brain organoids allows us to overcome limitations of monolayer in vitro cell culture models, providing deep insights into the neural network complex of the real human brain and new ways of disease modeling.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.31-36
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• 1988

A personal computer-based brain map is described which will display a gray scale maps showing the distribution of signals derived from the electrical activity of the brain such as EEG or EP This topographic brain mapping system has a flexibility which describe the electrode number and placement mapping onto any shaped space and generate a brain maps by incoorporated the data acquisition and processing software with conventional EEG machine.