Search results for: primary brain tumors

Authors: J. R. Ashrapov, G. A. Alihodzhaeva, D. E. Abdullaev, N. R. Kadirbekov

Abstract:

Diagnosis of brain tumors is one of the challenges, as several central nervous system diseases run the same symptoms. Modern diagnostic techniques such as CT, MRI helps to significantly improve the surgery in the operating period, after surgery, after allowing time to identify postoperative complications in neurosurgery. Purpose: To study the MRI characteristics and localization of brain tumors in children and to detect the postoperative complications in the postoperative period. Materials and methods: A retrospective study of treatment of 62 children with brain tumors in age from 2 to 5 years was performed. Results of the review: MRI scan of the brain of the 62 patients 52 (83.8%) case revealed a brain tumor. Distribution on MRI of brain tumors found in 15 (24.1%) - glioblastomas, 21 (33.8%) - astrocytomas, 7 (11.2%) - medulloblastomas, 9 (14.5%) - a tumor origin (craniopharyngiomas, chordoma of the skull base). MRI revealed the following characteristic features: an additional sign of the heterogeneous MRI signal of hyper and hypointensive T1 and T2 modes with a different perifocal swelling degree with involvement in the process of brain vessels. The main objectives of postoperative MRI study are the identification of early or late postoperative complications, evaluation of radical surgery, the identification of the extended-growing tumor that (in terms of 3-4 weeks). MRI performed in the following cases: 1. Suspicion of a hematoma (3 days or more) 2. Suspicion continued tumor growth (in terms of 3-4 weeks). Conclusions: Magnetic resonance tomography is a highly informative method of diagnostics of brain tumors in children. MRI also helps to determine the effectiveness and tactics of treatment and the follow up in the postoperative period.

Keywords: brain tumors, children, MRI, treatment

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Authors: Fumihiro Ima, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know growth rate of brain tumors before surgery because it influences treatment planning including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without administration of contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients and WHO grade 4 in 2 patients), meningioma WHO grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW-signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

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Authors: Fumihiro Imai, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

Abstract:

It is important to know the growth rate of brain tumors before surgery because it influences treatment planning, including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without the administration of a contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after a clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients, and WHO grade 4 in 2 patients), meningioma WHO grade 1 in 2 patients, and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW signals than that low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

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Authors: Mahmoodreza Tahamtan

Abstract:

Malignant surface epithelial ovarian tumors(SEOT) account for approximately 90% of primary ovarian cancer. We evaluate the immunohistochemical expression of WT1 protein among different histologic subtypes of SEOT. Immunohistochemistry for WT1 was done on 35 serous cystadenocarcinomas, 9 borderline serous tumors. A tumor was considered negative if < 1% of tumor cells were stained.Positive reactions were graded as follows:1+,1%-24%; 2+,25%-49%; 3+,50%-74%; 4+,75%-100%. Of the 35 cases of ovarian serous cystadenocarcinoma 30(85.7%)were diffusely positive(3+,4+),4 showed reactivity of < 50% of the tumor cells(1+,2+) and one were negative. All 9 borderline serous tumors showed immunoreactivity with WT1. WT1 is a good marker to distinguish primary ovarian serous carcinomas from other surface epithelial tumors.

Keywords: WT1, ovary, malignant, epithelial tumors

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Authors: Nitin Dwivedi, Jigna Shah

Abstract:

Brain tumor is metastatic neoplasm of central nervous system, in most of cases it is life threatening disease with low survival rate. Despite of enormous efforts in the development of therapeutics and diagnostic tools, the treatment of brain tumors and gliomas remain a considerable challenge in the area of neuro-oncology. The most reason behind of this the presence of physiological barriers including blood brain barrier and blood brain tumor barrier, lead to insufficient reach ability of therapeutic agents at the site of tumor, result of inadequate destruction of gliomas. So there is an indeed need empowerment of brain tumor imaging for better characterization and delineation of tumors, visualization of malignant tissue during surgery, and tracking of response to chemotherapy and radiotherapy. Multifunctional different generations of dendrimer offer an improved effort for potentiate drug delivery at the site of brain tumor and gliomas. So this article emphasizes the innovative dendrimer approaches in tumor targeting, tumor imaging and delivery of therapeutic agent.

Keywords: blood brain barrier, dendrimer, gliomas, nanotechnology

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Authors: Sushila Jaiswal, Awadhesh Kumar Jaiswal

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Background: Primary melanocytic tumors of the central nervous system (CNS) are uncommon lesions and arise from the melanocytes located within the leptomeninges. Aim and objective: The aim of the study was to evaluate the clinical details, histomorphology of the primary melanocytic tumor of CNS. Method: The study was performed by the retrospective review of the case records of the primary melanocytic tumors of CNS diagnosed in our department. The formalin-fixed, paraffin embedded tissue blocks and tissue sections were retrieved and reviewed. Results: Seven cases (6 males, 1 female; age range- 16-40 years; mean age- 27 years) of primary melanocytic tumors of CNS were retrieved over last seven years. The tumor was intracranial (n=5; frontal – 1 case, parietal – 1 case, cerebello-pontine angle- 1 case, occipital -1 case, foramen magnum-1 case) and intra spinal (n=2; cervical – 2 cases). All patients presented with the neurological deficits related to the location of the tumor. Four cases were malignant melanoma; two were melanocytoma of intermediate grade and remaining one was melanocytoma. On histopathology, melanocytoma and melanoma both displayed sheets of well-differentiated melanocytes having round to oval nuclei with finely dispersed chromatin, occasional single eosinophilic nucleoli and a moderate amount of cytoplasm with abundant granular melanin pigment. The absence of mitosis and macronucleoli was noticed in melanocytoma while melanoma showed frequent mitosis and macronucleoli. On immunohistochemistry, both showed diffuse strong HMB45 and S-100 immunopositivity. Conclusion: Primary melanocytic tumors of CNS are rare and predominantly seen in males. It is important to differentiate melanoma from melanocytoma as prognosis of later is good.

Keywords: melanocytoma, melanoma, brain tumor, melanin

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Authors: Mutaz Dwairy

Abstract:

Solid tumors have high interstitial fluid pressure (IFP), high mechanical stress, and low oxygen levels. Solid stresses may induce apoptosis, stimulate the invasiveness and metastasis of cancer cells, and lower their proliferation rate, while oxygen concentration may affect the response of cancer cells to treatment. Although tumors grow in a nonhomogeneous environment, many existing theoretical models assume homogeneous growth and tissue has uniform mechanical properties. For example, the brain consists of three primary materials: white matter, gray matter, and cerebrospinal fluid (CSF). Therefore, tissue inhomogeneity should be considered in the analysis. This study established a physical model based on convection-diffusion equations and continuum mechanics principles. The model considers the geometrical inhomogeneity of the brain by including the three different matters in the analysis: white matter, gray matter, and CSF. The model also considers fluid-solid interaction and explicitly describes the effect of mechanical factors, e.g., solid stresses and IFP, chemical factors, e.g., oxygen concentration, and biological factors, e.g., cancer cell concentration, on growing tumors. In this article, we applied the model on a brain tumor positioned within the white matter, considering the brain inhomogeneity to estimate solid stresses, IFP, the cancer cell concentration, oxygen concentration, and the deformation of the tissues within the neoplasm and the surrounding. Tumor size was estimated at different time points. This model might be clinically crucial for cancer detection and treatment planning by measuring mechanical stresses, IFP, and oxygen levels in the tissue.

Keywords: biomechanical model, interstitial fluid pressure, solid stress, tumor microenvironment

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Authors: Ravi Kiran Pothamsetty, Radha Rani Ghosh, Baby Paul Thaliath

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Radiation therapy has undergone many advancements and evloved from 2D to 3D. Recently, with rapid pace of drug discoveries, cutting edge technology, and clinical trials has made innovative advancements in computer technology and treatment planning and upgraded to intensity modulated radiotherapy (IMRT) which delivers in homogenous dose to tumor and normal tissues. The present study was a hospital-based experience comparing two different conformal radiotherapy techniques for brain tumors. This analytical study design has been conducted at Regional Cancer Centre, India from January 2014 to January 2015. Ten patients have been selected after inclusion and exclusion criteria. All the patients were treated on Artiste Siemens Linac Accelerator. The tolerance level for maximum dose was 6.0 Gyfor lenses and 54.0 Gy for brain stem, optic chiasm and optical nerves as per RTOG criteria. Mean and standard deviation values of PTV98%, PTV 95% and PTV 2% in IMRT were 93.16±2.9, 95.01±3.4 and 103.1±1.1 respectively; for 3DCRT were 91.4±4.7, 94.17±2.6 and 102.7±0.39 respectively. PTV max dose (%) in IMRT and 3D-CRT were 104.7±0.96 and 103.9±1.0 respectively. Maximum dose to the tumor can be delivered with IMRT with acceptable toxicity limits. Variables such as expertise, location of tumor, patient condition, and TPS influence the outcome of the treatment.

Keywords: brain tumors, intensity modulated radiotherapy (IMRT), three dimensional conformal radiotherapy (3D-CRT), radiation therapy oncology group (RTOG)

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Authors: Chung-Ming Lo, Kevin Li-Chun Hsieh

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The central nervous system in the World Health Organization defines grade 2, 3, 4 gliomas according to the aggressiveness. For brain tumors, using image examination would have a lower risk than biopsy. Besides, it is a challenge to extract relevant tissues from biopsy operation. Observing the whole tumor structure and composition can provide a more objective assessment. This study further proposed a computer-aided diagnosis (CAD) system based on a convolutional neural network to quantitatively evaluate a tumor's malignancy from brain magnetic resonance imaging. A total of 30 grade 2, 43 grade 3, and 57 grade 4 gliomas were collected in the experiment. Transferred parameters from AlexNet were fine-tuned to classify the target brain tumors and achieved an accuracy of 98% and an area under the receiver operating characteristics curve (Az) of 0.99. Without pre-trained features, only 61% of accuracy was obtained. The proposed convolutional neural network can accurately and efficiently classify grade 2, 3, and 4 gliomas. The promising accuracy can provide diagnostic suggestions to radiologists in the clinic.

Keywords: convolutional neural network, computer-aided diagnosis, glioblastoma, magnetic resonance imaging

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

Abstract:

The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Mahmoodreza Tahamtan

Abstract:

Background: Malignant surface epithelial ovarian tumors (SEOT) account for approximately 90% of primary ovarian cancer. Wilms tumor gene (WT1) product was defined as a tumor suppressor gene, but today it is considered capable of performing oncogenic functions. There seems to be differences in WT1 expression patterns among SEOT subtypes. We evaluate the immunohistochemical expression of WT1 protein among different histologic subtypes of SEOT. Materials and Methods: Immunohistochemistry for WT1 was done on 35 serous cystadenocarcinomas, 9 borderline serous tumors, 3 mucinous cystadenocarcinomas, 10 borderline mucinous tumors, 7 endometrioid ovarian carcinomas, 3 clear cell carcinomas, 1 malignant Brenner tumor, 2 metastatic adenocarcinomas, and 6 endometrial adenocarcinomas. A tumor was considered negative if < 1% of tumor cells were stained.Positive reactions were graded as follows:1+,1%-24%; 2+,25%-49%; 3+,50%-74%; 4+,75%-100%. Results: Of the 35 cases of ovarian serous cystadenocarcinoma, 30(85.7%) were diffusely positive (3+,4+),4 showed reactivity of < 50% of the tumor cells (1+,2+), and one were negative. All 9 borderline serous tumors showed immunoreactivity with WT1. All the mucinous tumors(n:13), endometrioid carcinomas (n: 7), clear cell carcinomas (n: 3), metastatic adenocarcinomas (n: 2) and primary endometrial carcinomas (n:6) were negative. The single malignant Brenner tumor showed a positive reaction for WT1(4+) Conclusion: WT1 is a good marker to distinguish primary ovarian serous carcinomas from other surface epithelial tumors (especially endometrioid subtype) and metastatic carcinomas (especially endometrial serous carcinoma), other than malignant mesothelioma. We cannot rely to the degree of expression inorder to separate high grade borderline serous tumors from low grade ones.

Keywords: WT1, ovary, epithelial tumors, malignant

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Authors: Nan Deng, Zhenqiu Liu

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Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

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Authors: Chih Jou Hsiao, Chung Ming Lo, Li Chun Hsieh

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Brain tumor is not the cancer having high incidence rate, but its high mortality rate and poor prognosis still make it as a big concern. On clinical examination, the grading of brain tumors depends on pathological features. However, there are some weak points of histopathological analysis which can cause misgrading. For example, the interpretations can be various without a well-known definition. Furthermore, the heterogeneity of malignant tumors is a challenge to extract meaningful tissues under surgical biopsy. With the development of magnetic resonance imaging (MRI), tumor grading can be accomplished by a noninvasive procedure. To improve the diagnostic accuracy further, this study proposed a computer-aided diagnosis (CAD) system based on MRI features to provide suggestions of tumor grading. Gliomas are the most common type of malignant brain tumors (about 70%). This study collected 34 glioblastomas (GBMs) and 73 lower-grade gliomas (LGGs) from The Cancer Imaging Archive. After defining the region-of-interests in MRI images, multiple quantitative morphological features such as region perimeter, region area, compactness, the mean and standard deviation of the normalized radial length, and moment features were extracted from the tumors for classification. As results, two of five morphological features and three of four image moment features achieved p values of <0.001, and the remaining moment feature had p value <0.05. Performance of the CAD system using the combination of all features achieved the accuracy of 83.18% in classifying the gliomas into LGG and GBM. The sensitivity is 70.59% and the specificity is 89.04%. The proposed system can become a second viewer on clinical examinations for radiologists.

Keywords: brain tumor, computer-aided diagnosis, gliomas, magnetic resonance imaging

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Authors: Ghada Esheba, Ghadeer Aldoobi, Salwa Almalk, Abrar Alshareef, Eman Al-khairi, Eman Yaseen

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Background: In Saudi Arabia, ovarian cancer ranked seventh among female population and is the most common female genital tract malignancy after endometrial cancer. A slight increase in the incidence of ovarian cancer was observed from 2001–2008. Makkah, Riyadh, and the eastern region of Saudi Arabia had the highest incidence rate ratio for the number of ovarian cancer cases (1). Differentiating metastatic adenocarcinomas from primary ovarian carcinomas, especially those of endometrioid and mucinous type is clinically significant and a challenge for clinicians and pathologists, yet the distinction has important therapeutic and prognostic implications. Aim: To clarify the most important histopathological criteria to differentiate between primary ovarian surface epithelial tumors especially mucinous and endometrioid subtypes, and metastatic adenocarcinoma and to evaluate the value of a panel of antibodies consisting of CK7, CK20, and CDX-2 in the distinction between primary ovarian surface epithelial tumors and metastatic adenocarcinoma. Material and methods: This study was carried out on 26 cases of primary ovarian surface epithelial neoplasms and 14 cases of metastatic ovarian adenocarcinoma. All cases were studied immunohistochemically using CK7, CK20, and CDX-2. Results: All cases of primary ovarian adenocarcinoma were positive for CK7. 25% and 58% of mucinous borderline mucinous tumor and mucinous carcinoma respectively were positive for CK20. Only 42% of mucinous carcinoma were positive for CDX-2. All cases of endometrioid carcinomas were negative for both CK20 and CDX-2. All cases of metastatic adenocarcinoma from the colon were negative for CK7 and positive for CK20 and CDX-2. Conclusions: CK7 is an important positive marker for primary ovarian tumors, while CK20 and CDX-2 are useful markers for colorectal carcinoma metastatic to the ovary. Caution should be taken as primary ovarian mucinous tumors may stain positive for CK20, CDX-2, or both, however, they usually exhibit a focal pattern of reactivity.

Keywords: adenoma, endometrioid, malignancy, ovarian

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Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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Authors: O. Yu Shchelkova, E. B. Usmanova

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Introduction: Last decades scientific research of quality of life (QoL) is developing fast worldwide. QoL concept pays attention to emotional experience of disease in patients, particularly to personal sense of possibility to satisfy actual needs and possibility of full social functioning in spite of disease limitations. QoL in oncological patients is studied intensively. Nevertheless, the issue of QoL in patients with bone tumors focused on psychological factors of QoL and relation to disease impact on QoL is not discussed. The aim of the study was to reveal the basic aspects and personality factors of QoL in patients with bone tumor. Results: Study participants were 139 patients with bone tumors. The diagnoses were osteosarcoma (n=42), giant cell tumor (n=32), chondrosarcoma (n=32), Ewing sarcoma (n=10) and bone metastases (n=23). The study revealed that patients with bone metastases assess their health significantly worse than other patients. Besides patients with osteosarcoma evaluate their general health higher than patients with giant cell tumors. Social functioning in patients with chondrosarcoma is higher than in patients with bone metastases and patients with giant cell tumor. Patients with chondrosarcoma have higher physical functioning and less restricted in daily activities than patients with bone metastases. Patients with bone metastases characterize their pain as more widespread than patients with primary bone tumors and have more functional restrictions due to bone incision. Moreover, the study revealed personality significant influence on QoL related to bone tumors. Such characteristics in structure of personality as high degree of self-consciousness, personal resources, cooperation and disposition to positive reappraisal in difficult situation correspond to higher QoL. Otherwise low personal resources and slight problem solving behaviour, low degree of self-consciousness and high social dependence correspond to decrease of QoL in patients with bone tumors. Conclusion: Patients with bone metastasis have lower QoL compared to patients with primary bone tumors. Patients with giant cell tumor have the worth quality of life among patients with primary bone tumors. Furthermore, the results revealed differences in QoL parameters associated with personality characteristics in patients with bone tumors. Such psychological factors as future goals, interest in life and emotional saturation, besides high degree of personal resources and cooperation influence on increasing QoL in patients with bone tumors.

Keywords: quality of life, psychological factors, bone tumor, personality

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Authors: Naim Izet Kajtazi

Abstract:

Context: Frequently, the cause of raised intracranial pressure remains unresolved and rarely is related to spinal tumors, moreover less to spinal medulloblastoma without primary brain focus. Process: An 18-year-old woman had a 3-month history of headaches and impaired vision. Neurological examination revealed bilateral sixth cranial nerve palsies with bilateral papilloedema of grade III. No focal brain or spine lesion was found on imaging. Consecutive lumbar punctures showed high opening pressure and subsequent increasing protein level. The meningeal biopsy was negative. At one point, she developed an increasing headache, vomiting and back pain. Spine MRI showed diffuse nodular leptomeningeal enhancement with the largest nodule at T6–T7. Malignant cells were detected in cerebrospinal fluid. She underwent laminectomy with excisional biopsy, and pathology showed medulloblastoma WHO grade IV. Outcome: She was treated with chemotherapy and craniospinal irradiation and made a good recovery. Relevance: Primary spinal leptomeningeal medulloblastoma is extremely rare, especially without primary brain focus, but may cause increased intracranial pressure, even in the early microscopic phases, and it should be considered in the differential diagnosis if conventional and aggressive treatment of idiopathic intracranial hypertension fails. We assume that arachnoiditis from tumor seeding caused increased intracranial pressure. Appropriate neurosurgical intervention and surgical biopsy are mandated if a suspicious lesion is detected. Consider proper rescreening of the whole neuroaxis in refractory cases of intracranial hypertension.

Keywords: CNS infection, IIH, headache, primary spinal leptomeningeal medulloblastoma

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Authors: Jakkireddy Sravani

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Introduction: The maintenance of hemodynamic stability is of pivotal importance in supratentorial surgeries. Anesthesia for supratentorial tumors requires an understanding of localized or generalized rising ICP, regulation, and maintenance of intracerebral perfusion, and avoidance of secondary systemic ischemic insults. We aimed to compare the effects of the combination of ketamine and propofol with propofol alone when used as an induction and maintenance anesthetic agent during supratentorial tumors. Methodology: This prospective, randomized, double-blinded controlled study was conducted at AIIMS Raipur after obtaining the institute Ethics Committee approval (1212/IEC-AIIMSRPR/2022 dated 15/10/2022), CTRI/2023/01/049298 registration and written informed consent. Fifty-two supratentorial tumor patients posted for craniotomy and excision were included in the study. The patients were randomized into two groups. One group received a combination of ketamine and propofol, and the other group received propofol for induction and maintenance of anesthesia. Intraoperative hemodynamic stability and quality of brain relaxation were studied in both groups. Statistical analysis and technique: An MS Excel spreadsheet program was used to code and record the data. Data analysis was done using IBM Corp SPSS v23. The independent sample "t" test was applied for continuously dispersed data when two groups were compared, the chi-square test for categorical data, and the Wilcoxon test for not normally distributed data. Results: The patients were comparable in terms of demographic profile, duration of the surgery, and intraoperative input-output status. The trends in BIS over time were similar between the two groups (p-value = 1.00). Intraoperative hemodynamics (SBP, DBP, MAP) were better maintained in the ketamine and propofol combination group during induction and maintenance (p-value < 0.01). The quality of brain relaxation was comparable between the two groups (p-value = 0.364). Conclusion: Ketamine and propofol combination for the induction and maintenance of anesthesia was associated with superior hemodynamic stability, required fewer vasopressors during excision of supratentorial tumors, provided adequate brain relaxation, and some degree of neuroprotection compared to propofol alone.

Keywords: supratentorial tumors, hemodynamic stability, brain relaxation, ketamine, propofol

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Authors: Mouna Zitouni, Mariem Tounsi

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This research introduces an application of the Riesz mixture model for medical image segmentation for accurate diagnosis and treatment of brain tumors. We propose a pixel classification technique based on the Riesz distribution, derived from an extended Bartlett decomposition. To our knowledge, this is the first study addressing this approach. The Expectation-Maximization algorithm is implemented for parameter estimation. A comparative analysis, using both synthetic and real brain images, demonstrates the superiority of the Riesz model over a recent method based on the Wishart distribution.

Keywords: EM algorithm, segmentation, Riesz probability distribution, Wishart probability distribution

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Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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Authors: Sandeep Mohindra

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Since 2013, the authors have operated on 568 cases of pituitary tumors through the trans-sphenoidal route, using the binostril approach. The distribution included 486 cases of non-functioning pituitary tumors, 24 cases of Growth hormone(GH) secreting tumors(acromegaly), and 28 cases of adrenocorticotrophic(ACTH) secreting tumors(Cushing's Disease). The authors utilized neuro-navigation for 18 cases, and all belonged to the functional tumor category. Complications included ICA injury in 2 cases, fatal meningitis in 5 cases, while CSF leak required repair in 28 cases. Satisfactory excision was noted in 512 cases, while recurrence/residual required repeat surgery in 32 cases. Authors conclude that trans sphenoidal route remains the best and optimal way of managing sellar tumors, especially pituitary adenomas.

Keywords: pituitary, adenoma, trans-sphenoidal, endonasal, neuronavigation

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Authors: Mostafa El Khashab

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Our experience with 50 patients with metastatic tumors located in different locations of the brain by a stereotactic-guided craniotomy and total microsurgical resection. Patients ranged in age from 36 to 73 years. There were 28 women and 22 men. Thirty-four patients presented with hemiparesis and 6 with aphasia and the remaining presented with psychological manifestations and memory issues. Gross total resection was accomplished in all cases, with postoperative imaging confirmation of complete removal. Forty patients were subjected to whole brain irradiation. One patient developed a stroke postoperatively and another one had a flap infection. 4 patients developed different postoperative but unrelated morbidities, including pneumonia and DVT. No mortality was encountered. We believe that with the assistance of stereotactic localization, metastases in vital regions of the brain can be removed with very low neurologic morbidity and that, in comparison to other modalities, they fare better regarding their long-term outcome.

Keywords: stereotactic, craniotomy, radiosurgery, patient

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Authors: Angelis P. Barlampas

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Purpose: A 29 years old woman presented in the emergency department with psychiatric symptoms. The psychiatrist ordered a computed tomography scan as part of a general examination. Material and methods: The CT showed bilateral enlarged choroid plexus structures mimicking papillomata and situated in the trigones of the lateral ventricles. The left choroid plexus was heavily calcified, but the right one has no any obvious calcifications. Results: It is well kown that any brain mass can present with behavioral changes and even psychiatric symptomatology. Papillomata of the ventricular system have been described to cause psychotic episodes. According to literature, choroid plexus papillomas are seldom neuroepithelial intraventricular tumors, which are benign and categorized as WHO grade 1 tumors. They are more common in the pediatric population, but they can occur in the adults, too1. In addition, the distinction between choroid plexus papilloma and carcinoma is very difficult and impossible by imagine alone. It can only be implied with more advanced imaging, such as arterial spin labeling and MRI. The final diagnosis is, of course, after surgical excision. The usual location in adults is the fourth ventricle, but in children, it is the lateral ventricles. Their imaging appearance is that of a solid vascular tumor, which enhances intensely after the intravenous administration of contrast material. One out of fourth tumors presents speckled calcifications1. In our case, there are symmetrically sized masses at the trigones, and there are no calcifications in one of them, whereas the other one is grossly calcified. Also, there is no obvious hydrocephalus or any other evidence of increased intracranial pressure. General conclusions: When there is a new psychiatric patient, someone must undergo any possible examination, and of course, a brain CT study should be done to exclude any rare organic causes that may be responsible for the disease.

Keywords: phycosis, intraventricular masses, CT, brain calcifications

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Authors: Jin Hwan Cheong, Mina Hwang, Myung Hoon Han, Je Il Ryu, Young ha Oh, Seong Ho Koh, Wu Duck Won, Byung Jin Ha

Abstract:

Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been reported to play critical roles in the proliferation of various cancer cells. However, the roles of LGR5 in brain tumors and the specific intracellular signaling proteins directly associated with it remain unknown. Expression of LGR5 was first measured in normal brain tissue, meningioma, and pituitary adenoma of humans. To identify the downstream signaling pathways of LGR5, siRNA-mediated knockdown of LGR5 was performed in SH-SY5Y neuroblastoma cells followed by proteomics analysis with 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In addition, the expression of LGR5-associated proteins was evaluated in LGR5-inꠓhibited neuroblastoma cells and in human normal brain, meningioma, and pituitary adenoma tissue. Proteomics analysis showed 12 protein spots were significantly different in expression level (more than two-fold change) and subsequently identified by peptide mass fingerprinting. A protein association network was constructed from the 12 identified proteins altered by LGR5 knockdown. Direct and indirect interactions were identified among the 12 proteins. HSP 90-beta was one of the proteins whose expression was altered by LGR5 knockdown. Likewise, we observed decreased expression of proteins in the hnRNP subfamily following LGR5 knockdown. In addition, we have for the first time identified significantly higher hnRNP family expression in meningioma and pituitary adenoma compared to normal brain tissue. Taken together, LGR5 and its downstream sigꠓnaling play critical roles in neuroblastoma and brain tumors such as meningioma and pituitary adenoma.

Keywords: LGR5, neuroblastoma, meningioma, pituitary adenoma, hnRNP

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Authors: Sona Babu Rathinam, Lavanya Dharmendran, Therraddi Mutthu

Abstract:

Objectives: The purpose of this paper is to provides an overview of the neuroendocrine tumors that arise in the oral cavity. Material and Methods: An overview of the relevant papers on neuroendocrine tumors of the oral cavity by various authors was studied and summarized. Results: On the basis of the relevant studies, this paper provides an overview of the classification and histological differentiation of the neuroendocrine tumors that arise in the oral cavity. Conclusions: The basis of classification of neuroendocrine tumors is largely determined by their histologic differentiation. Though they reveal biologic heterogeneity, there should be an awareness of the occurrence of such lesions in the oral cavity to enable them to be detected and treated early.

Keywords: malignant peripheral nerve sheath tumor, olfactory neuroblastoma, paraganglioma, schwannoma

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Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi

Abstract:

In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.

Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture

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Authors: Ghada Esheba, Ebtisam Aljerayan, Afnan Al-Ghamdi, Atheer Alsharif, Hanan alzahrani

Abstract:

Background: Primary ovarian neoplasms comprise a heterogeneous group of tumors of three main subtypes: surface epithelial, germ cell, and sex cord-stromal. The wide morphological variation within and between these groups can result in diagnostic difficulties. Gonadal sex cord-stromal tumors (SCST) represent one of the most heterogeneous categories of human neoplasms, because they may contain various combinations of different gonadal sex cord and stromal element. Aim: The aim of this work is to highlight the clinicopathological characteristics of SCST and to assess the value of alpha-inhibin and calretinin in the distinction between SCST and their mimics. Material and methods: This study was carried out on 100 cases using full tissue sections; 70 cases were SCST and 30 cases were histological mimics of SCST. The cases were studied using immunohistochemically using alpha-inhibin. In addition, an ovarian tissue microarray containing 170 benign and malignant ovarian neoplasms was also studied immunohistochemically for calretinin expression. The ovarian microarray included 14 SCST, 59 ovarian serous borderline tumors, 17 mucinous borderline tumors, 10 mucinous adenocarcinomas, 32 endometrioid adenocarcinomas, 34 clear cell carcinomas, and 4 germ cell tumors. Results: 99% of SCST examined using full tissue sections exhibited positive cytoplasmic staining for inhibin. On the contrary, only 7% of the histological mimics (P value < 0.0001). 86% of SCST in the tissue microarray were positive for calretinin with nuclear and/or cytoplasmic staining compared to only 7% of the other tumor types (P value < 0.0001). Conclusions: SCST have characteristic clinicopathological and immunohistochemical features and their recognition is crucial for proper diagnosis and treatment. Alpha-inhibin and calretinin are of great help in the diagnosis of sex cord-stromal tumors.

Keywords: calretinin, granulosa cell tumor, inhibin, sex cord-stromal tumors

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Authors: Nur Sofi Hidayah, Ratih Tri Purwatiningsih

Abstract:

Learning is a process attempts person to obtain a new behavior changes as a whole, as a result of his own experience in the interaction with the environment. Learning involves our brain to think, while the ability of the brain to each student's performance is different. To obtain optimal learning results then need time to learn the exact hour that the brain's performance is not too heavy. Referring to the learning system in Finland which apply 45 minutes to learn and a 15-minute break is expected to be the brain work better, with the rest of the brain, the brain will be more focused and lessons can be absorbed well. It can be concluded that learning in this way students learn with brain always fresh and the best possible use of the time, but it can make students not saturated in a lesson.

Keywords: learning, working hours brain, time efficient learning, working hours in the brain receive stimulus.

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Authors: Ghada E. Esheba, Ghufran Kheshaifaty, Kholoud Al-Harbi, Wafa'a Al-Harbi, Ala'a Al-Orabi, Moayad Turkistani

Abstract:

Krukenberg tumor is a rare metastatic ovarian carcinoma that usually occurs in female between 30 - 40 year old and rarely seen after menopause. Stomach is the most common primary site. Histopathological features of krukenberg tumors appear as diffuse stromal proliferation, mucus-production, and numerous signet-cells and these tumors spread mostly by lymphatic route. Treatment and prognostic factors are not well established. This study describes a 34 year old female with a unilateral ovarian mass discovered accidentally during cesarean section delivery and it was misdiagnosed as luteoma of pregnancy, but histopathological examination showed a diffuse infiltration of the ovary and omentum by signet ring cells. These findings were not correlated with luteoma of pregnancy or any other types of primary ovarian tumors like surface epithelial tumor, sex cord stromal tumor or germ cell tumor. However, after the analysis of immunohistochemical results (negative CK7, positive CK20 and CDX-2), the finding was the diagnostic of metastatic krukenberg tumor. Two weeks later, the patient was evaluated and a large gastric tumor was found in her stomach and she underwent gastrectomy.

Keywords: CK7, CK20, CDX-2, Krukenburg tumor, metastatic ovarian tumor

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Authors: Ibtihal D. Mustafa, Mawia A. Hassan

Abstract:

Tumor segmentation from MRI image is important part of medical images experts. This is particularly a challenging task because of the high assorting appearance of tumor tissue among different patients. MRI images are advance of medical imaging because it is give richer information about human soft tissue. There are different segmentation techniques to detect MRI brain tumor. In this paper, different procedure segmentation methods are used to segment brain tumors and compare the result of segmentations by using correlation and structural similarity index (SSIM) to analysis and see the best technique that could be applied to MRI image.

Keywords: MRI, segmentation, correlation, structural similarity

Procedia PDF Downloads 407