• Brain Tumor Research and Treatment
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• v.6 no.2
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• pp.101-104
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• 2018

Pheochromocytoma (PCC) is a neuroendocrine tumor that mainly arises from the medulla of the adrenal gland. Some PCCs become malignant and metastasize to other organs. For example, it typically involves skeletal system, liver, lung, and regional lymph nodes. However, only a few cases of PCC with brain metastasis have been reported worldwide. We report a case of metastatic brain tumor from PCC in South Korea in 2016. A 52-year-old man presented with headache, dizziness and motor aphasia. He had a medical history of PCC with multi-organ metastasis, previously underwent several operations, and was treated with chemotherapy and radiotherapy. Brain MRIs showed a brain tumor on the left parietal lobe. Postoperative pathology confirmed that the metastatic brain tumor derived from malignant PCC. This is the first report PCC with brain metastasis in South Korea.

• Journal of Korean Neurosurgical Society
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• v.61 no.3
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• pp.376-385
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• 2018

Recent discoveries of brain tumor-related genes and fast advances in genomic testing technologies have led to the era of molecular diagnosis of brain tumor. Molecular profiling of brain tumor became the significant step in the diagnosis, the prediction of prognosis and the treatment of brain tumor. Because traditional molecular testing methods have limitations in time and cost for multiple gene tests, next-generation sequencing technologies are rapidly introduced into clinical practice. Targeted sequencing panels using these technologies have been developed for brain tumors. In this article, focused on pediatric brain tumor, key discoveries of brain tumor-related genes are reviewed and cancer panels used in the molecular profiling of brain tumor are discussed.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.143-148
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• 2022

Brain tumor classification is an important process that allows doctors to plan treatment for patients based on the stages of the tumor. To improve classification performance, various CNN-based architectures are used for brain tumor classification. Existing methods for brain tumor segmentation suffer from overfitting and poor efficiency when dealing with large datasets. The enhanced CNN architecture proposed in this study is based on U-Net for brain tumor segmentation, RefineNet for pattern analysis, and SegNet architecture for brain tumor classification. The brain tumor benchmark dataset was used to evaluate the enhanced CNN model's efficiency. Based on the local and context information of the MRI image, the U-Net provides good segmentation. SegNet selects the most important features for classification while also reducing the trainable parameters. In the classification of brain tumors, the enhanced CNN method outperforms the existing methods. The enhanced CNN model has an accuracy of 96.85 percent, while the existing CNN with transfer learning has an accuracy of 94.82 percent.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.30 no.1
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• pp.84-95
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• 2023

Purpose: This study aimed to clarify the concept of uncertainty in brain tumor patients. Methods: We used the Walker and Avant's concept analysis method. We searched RISS, MEDLINE, CINAHL, and EMBASE for published articles in Korean and English from January 2002 to December 2022. After applying the inclusion and exclusion criteria, 27 articles were selected for the final analysis. Result: "Uncertainty in brain tumor" was defined as a state in which related clues during the process of experiencing a disease after brain tumor diagnosis are unclear or difficult to understand, new experiences different from before, or a condition in which it is difficult to judge fragmentarily. Moreover, the empirical criteria for the attributes of uncertainty in brain tumor patients were ambiguity of the disease process, diversity of information, unpredictability of prognosis, and complexity of management. Conclusion: Brain tumor patients with uncertainty require strategic technology development so that brain tumor patients, their families, and health care providers can use reasonable coping methods.

• Journal of Korean Neurosurgical Society
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• v.61 no.5
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• pp.633-639
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• 2018

Objective : We investigated the outcomes of repeat stereotactic radiosurgery (SRS) for metastatic brain tumors that locally recurred despite previous SRS, focusing on the tumor control. Methods : A total of 114 patients with 176 locally recurring metastatic brain tumors underwent repeat SRS after previous SRS. The mean age was 59.4 years (range, 33 to 85), and there were 68 male and 46 female patients. The primary cancer types were non-small cell lung cancer (n=67), small cell lung cancer (n=12), gastrointestinal tract cancer (n=15), breast cancer (n=10), and others (n=10). The number of patients with a single recurring metastasis was 95 (79.8%), and another 19 had multiple recurrences. At the time of the repeat SRS, the mean volume of the locally recurring tumors was 5.94 mL (range, 0.42 to 29.94). We prescribed a mean margin dose of 17.04 Gy (range, 12 to 24) to the isodose line at the tumor border primarily using a 50% isodose line. Results : After the repeat SRS, we obtained clinical and magnetic resonance imaging follow-up data for 84 patients (73.7%) with a total of 108 tumors. The tumor control rate was 53.5% (58 of the 108), and the median and mean progression-free survival (PFS) periods were 246 and 383 days, respectively. The prognostic factors that were significantly related to better tumor control were prescription radiation dose of 16 Gy (p=0.000) and tumor volume less than both 4 mL (p=0.001) and 10 mL at the repeat SRS (p=0.008). The overall survival (OS) periods for all 114 patients after repeat SRS varied from 1 to 56 months, and median and mean OS periods were 229 and 404 days after the repeat SRS, respectively. The main cause of death was systemic problems including pulmonary dysfunction (n=58, 51%), and the identified direct or suspected brain-related death rate was around 20%. Conclusion : The tumor control following repeat SRS for locally recurring metastatic brain tumors after a previous SRS is relatively lower than that for primary SRS. However, both low tumor volume and high prescription radiation dose were significantly related to the tumor control following repeat SRS for these tumors after previous SRS, which is a general understanding of primary SRS for metastatic brain tumors.

• Parasites, Hosts and Diseases
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• v.54 no.2
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• pp.201-204
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• 2016

Toxoplasma gondii is an intracellular protozoan that can modulate the environment of the infected host. An unfavorable environment modulated by T. gondii in the brain includes tumor microenvironment. Literature has suggested that T. gondii infection is associated with development of brain tumors. However, in Korea, epidemiological data regarding this correlation have been scarce. In this study, in order to investigate the relationship between T. gondii infection and brain tumor development, we investigated the seroprevalence of T. gondii among 93 confirmed brain tumor patients (various histological types, including meningioma and astrocytoma) in Korea using ELISA. The results revealed that T. gondii seropositivity among brain tumor patients (18.3%) was significantly (P<0.05) higher compared with that of healthy controls (8.6%). The seropositivity of brain tumor patients showed a significant age-tendency, i.e., higher in younger age group, compared with age-matched healthy controls (P<0.05). In conclusion, this study supports the close relationship between T. gondii infection and incidence of brain tumors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.105-125
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• 2024

Gliomas are the most common malignant brain tumor and cause the most deaths. Manual brain tumor segmentation is expensive, time-consuming, error-prone, and dependent on the radiologist's expertise and experience. Manual brain tumor segmentation outcomes by different radiologists for the same patient may differ. Thus, more robust, and dependable methods are needed. Medical imaging researchers produced numerous semi-automatic and fully automatic brain tumor segmentation algorithms using ML pipelines and accurate (handcrafted feature-based, etc.) or data-driven strategies. Current methods use CNN or handmade features such symmetry analysis, alignment-based features analysis, or textural qualities. CNN approaches provide unsupervised features, while manual features model domain knowledge. Cascaded algorithms may outperform feature-based or data-driven like CNN methods. A revolutionary cascaded strategy is presented that intelligently supplies CNN with past information from handmade feature-based ML algorithms. Each patient receives manual ground truth and four MRI modalities (T1, T1c, T2, and FLAIR). Handcrafted characteristics and deep learning are used to segment brain tumors in a Global Convolutional Neural Network (GCNN). The proposed GCNN architecture with two parallel CNNs, CSPathways CNN (CSPCNN) and MRI Pathways CNN (MRIPCNN), segmented BraTS brain tumors with high accuracy. The proposed model achieved a Dice score of 87% higher than the state of the art. This research could improve brain tumor segmentation, helping clinicians diagnose and treat patients.

• Journal of Korean Neurosurgical Society
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• v.42 no.2
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• pp.149-152
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• 2007

Authors report a very rare case of primary Hodgkin's lymphoma limited to the cerebellum. A 64-year-old female patient presented with headache, nausea, and vomiting. Magnetic resonance imaging of the brain revealed a nodular enhancing mass in the left cerebellar hemisphere. Tumor was removed totally with retromastoid suboccipital approach. Diagnosis was Hodgkin's lymphoma of mixed cellularity type, consisting of a dense mixed inflammatory infiltrate containing scattered large atypical mononuclear Hodgkin's cell and multinucleated Reed-Sternberg cells. Systemic work-up for the Hodgkin's lymphoma was followed with negative result. Postoperative radiation therapy was given and the patient is disease-free at 16 months after the operation.

• Journal of Korean Neurosurgical Society
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• v.63 no.1
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• pp.26-33
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• 2020

Glioblastoma (GBM) is a disease without any definite cure. Numerous approaches have been tested in efforts to conquer this brain disease, but patients invariably experience recurrence or develop resistance to treatment. New surgical tools, carefully chosen samples, and experimental methods are enabling discoveries at single-cell resolution. The present article reviews the cell-of-origin of isocitrate dehydrogenase (IDH)-wildtype GBM, beginning with the historical background for focusing on cellular origin and introducing the cancer genesis patterned on firework. The authors also review mutations associated with the senescence process in cells of the subventricular zone (SVZ), and biological validation of somatic mutations in a mouse SVZ model. Understanding GBM would facilitate research on the origin of other cancers and may catalyze the development of new management approaches or treatments against IDH-wildtype GBM.

• The Korean Journal of Nuclear Medicine
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• v.36 no.1
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• pp.19-27
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• 2002

The annual incidence of primary brain tumors is 7-19 cases per 100,000 people. The unique capacity of visualizing biochemical processes allows PET to determine functional metabolic activities of the brain tumors. Like other malignant tumors, F-18 FDG has been used commonly in the imaging of brain tumors. FDG PET is valuable in grading malignancy, predicting prognosis, monitoring treatment, differentiating tumor recurrence from radiation necrosis, and detecting primary lesion in metastatric brain tumors. Among amino acids labeled with positron emitters, C-11 methionine is used clinically. Tumor delineation is much better with methionine PET than with FDG PET. Low grade gliomas, in particular, are better evaluated with methionine than with FDG. PET opens another dimension in brain tumor imaging. PET imaging has clearly entered the clinical area with a profound impact on patient care in many indications.