Brain tumours

The bio-medical image processing is the application of image processing to process medical data. The techniques of feature extraction and machine learning are efficient techniques brain tumor detection. In this paper, various brain tumor detection techniques are reviewed analyzed in terms of certain parameters. It is analyzed that textual feature extraction and classification techniques give maximum accuracy for the brain tumor detection.

Adults diagnosed with primary brain tumours often experience physical, cognitive and neuropsychiatric impairments and decline in quality of life. Although disease and treatment-related information is commonly provided to cancer patients and carers, newly diagnosed brain tumour patients and their carers report unmet information needs. Few interventions have been designed or proven to address these information needs. Accordingly, a three-study research program, that incorporated both qualitative and quantitative research methods, was designed to: 1) identify and select an intervention to improve the provision of information, and meet the needs of patients with a brain tumour; 2) use an evidence-based approach to establish the content, language and format for the intervention; and 3) assess the acceptability of the intervention, and the feasibility of evaluation, with newly diagnosed brain tumour patients.

Objectives. Prognosis for glioblastoma multiforme (GBM) has remained poor. Th ere is almost always recurrence postresection and adjuvant treatment, the majority of which is local. Several preclinical models exist that recapitulate the essential features of GBM. Th e majority of these models treat GBM in the neoadjuvant setting. Here, we describe an imageable intracranial surgical resection model of GBM in the rodent. Methods . We implanted 106 U87 luciferase-expressing GBM cells into the right hemisphere of 6-week-old female rats at predefined stereotactic coordinates ( n ϭ 10). When the bioluminescence signal of tumours were in the exponential growth phase, the animals were randomised into surgical ( n ϭ 4) and non-surgical groups ( n ϭ 4). Under parenterally delivered anaesthesia, the animals were fixed in a stereotactic frame. A 4.5 mm craniectomy was performed with resection of the tumour using microsurgical techniques. Haemostasis was ensured. The cranial defect was repaired using a modified cranial window technique. No antibiotics were administered.

Engineers have been actively developing tools to detect tumors and to process medical images. Medical image segmentation is a powerful tool that is often used to detect tumors. Many scientists and researchers are working to develop and add more features to this tool. This project is about detecting Brain tumors from MRI images using an interface of GUI in Matlab. Using the GUI, this program can use various combinations of segmentation, filters, and other image processing algorithms to achieve the best results. We start with filtering the image using Prewitt horizontal edge-emphasizing filter. The next step for detecting tumor is "watershed pixels." The most important part of this project is that all the Matlab programs work with GUI “Matlab guide”. This allows us to use various combinations of filters, and other image processing techniques to arrive at the best result that can help us detect brain tumors in their early stages.

"This chapter presents findings of ethnographic work in a neuro-oncology
clinic in Israel. It is claimed that patients, close-ones and physicians
engage in creating metaphorical visions of the brain and brain tumours
that reaffirm Cartesian dualism. The ‘brain talk’ involved visible and
spatial terms and results in a particular kind of objectification of the
organ of the self. The overbearing presence of visual media (i.e., magnetic
resonance imaging, computed tomography, angiographic studies) further
gave rise to particular forms of interactions with patients and physicians
where the ‘imageable’ (i.e., the image on the screen) became the
‘imaginable’ (i.e., the metaphor). The images mostly referred to a domain
of mundane objects: a meatball in a dish of spaghetti, a topping of olives
over a pizza, the surface of the moon, a stone, an egg, an animal, a dark
cloud. Furthermore, conversations with family members showed that
formal facts and informed compassion were substituted by concrete
representations. For them, and especially for the patient, these
representations redefined an ungraspable situation, where a tumour – an object – can so easily affect the organ of their subjectivity, into something
comprehensible through the materialistic, often mechanistic actions of
most mundane objects. This, however, also created alienated objects
within the boundaries of their own embodied selves. Patients, on the one
hand, did not reject their own sense of ‘own-ness’, of having a lifeworld
(lebenswelt) as subjective agents, but on the other, did talk about their
own interiors as being an ‘other’: an object visible, observable and
imaginable from a third-person standpoint – a standpoint drawing its
authority from biomedical epistemology and practice."

Apopleksi pituitari ditandai dengan peningkatan mendadak volume kelenjar pituitari akibat iskemia, nekrosis, perdarahan, dan/atau infark, yang biasanya disebabkan oleh adenoma pituitari. Teori terjadinya apopleksi pituitari salah satunya adalah pertumbuhan tumor yang melebihi suplai arteri sehingga memicu terjadinya pendesakan pada ruang pituitari yang berakibat pada iskemia, nekrosis, dan perdarahan. Peningkatan akut tekanan darah, penurunan tekanan darah secara cepat, dan stimulasi kelenjar pituitari itu sendiri dapat memicu terjadinya apopleksi pituitiari. Diagnosis klinis apopleksi pituitari sulit untuk dilakukan karena gejalanya mirip dengan gejala peningkatan tekanan pada struktur neural lainnya. Diagnosis radiologis dapat dilakukan baik menggunakan CT Scan maupun MRI. Tatalaksana umum apopleksi pituitari melibatkan stabilisasi hemodinamik, koreksi elektrolit, dan pemberian kortikosteroid. Indikasi pembedahan pada apopleksi pituitari dilakukan pada pasien dengan penurunan kesadaran dan defek penglihatan yang menyebabkan efek massa pada otak. Kata Kunci: Apopleksi Pituitari, Pembedahan, Medikamentosa, Pertumbuhan Tumor Pendahuluan Apopleksi pituitari pertama kali dideskripsikan pada tahun 1898 sebagai "pituitary tumor-associated hemorrhage". Terminologi apopleksi pituitari pertama kali digunakan pada tahun 1950. Apopleksi berasal dari kata "serangan mendadak". Terminologi ini menggambarkan peningkatan volume dari regio sellar yang dapat menimbulkan sakit kepala mendadak,

Brain tumour segmentation can improve diagnostics efficiency, rise the prediction rate and treatment planning. This will help the doctors and experts in their work. Where many types of brain tumour may be classified easily, the gliomas tumour is challenging to be segmented because of the diffusion between the tumour and the surrounding edema. Another important challenge with this type of brain tumour is that the tumour may grow anywhere in the brain with different shape and size. Brain cancer presents one of the most famous diseases over the world, which encourage the researchers to find a high-throughput system for tumour detection and classification. Several approaches have been proposed to design automatic detection and classification systems. This paper presents an integrated framework to segment the gliomas brain tumour automatically using pixel clustering for the MRI images foreground and background and classify its type based on deep learning mechanism, which is the convoluti...

To builds the endurance pace of the brain tumor patients and to have an improved treatment system in restorative picture preparing, brain tumor segmentation is basic technique for finding. The early and right conclusion of brain tumours assumes a significant job. Magnetic Resonance Imaging (MRI) method is the most famous non-intrusive strategy; in nowadays imaging of organic structures by MRI is a typical exploring system. For malignant growth determination the brain tumours segmentation should be possible physically from MRI, which gives the poor degree of exactness and identification. The classification of variations from the norm isn't unsurprising and clear however it is a tedious errand for doctor. These days, the issue of programmed segmentation and examination of brain tumours are significant research region. Anyway the recognition of tumor is a difficult assignment since tumor has complex qualities in appearance and limits. Manual segmentation of brain tumor for disease conclusion, from enormous measure of MR pictures created in clinical daily schedule, is a troublesome and tedious errand. There is a requirement for programmed brain tumor picture segmentation. This paper does the audit of various writings of brain tumor segmentation. For segmentation, generally utilized clustering calculation like fluffy c-means, k-means a few specialists utilized convolution neural system approach and GPM. The motivation behind each segmentation calculation is to accomplish precise and proficient framework grew, so that to discover tumor in least time with most extreme exactness. I. INTRODUCTION The focal point of human central sensory system is Brain. Brain is an intricate organ and it comprises of enormous system shaping because of quality of 50-100 billion neurons. Brain tumor is only irregular development of set of cells that develop inside or around the brain wildly. The dangerous a kind are sorts of brain tumours. The non-carcinogenic tumor is benevolent. It is less hurtful, by and large limited and it doesn't spread to different pieces of the body and very much treated because of its appropriate reaction. Favourable tumour is less hurtful than harmful tumor. Harmful tumours are dangerous developments. They are frequently impervious to treatment and it might spread to different pieces of the body. Harmful tumours are ordered into essential and optional tumours. The threatening tumor spreads exceptionally quick and assaults other brain tissues and debilitates the wellbeing condition which more often than not causes even demise. The recognition of Brain tumor is testing issue for fundamental judgment on analysis, because of complex structure of brain [1]-[4]. The magnetic resonance imaging (MRI) pictures are utilized in medicinal imaging procedure, to give point by point data about the interior tissue of particular picture. In the analysis of brain tumor, assurance of the careful area is a significant undertaking which discovers the shape and size of tumor. In brain tumor discovery systems, picture segmentation assumes a vivacious job. So as to extricate tumor from MRI pictures of brain distinctive picture segmentation procedures are utilized. For the explanation that segmentation of MRI gives the itemized data about the delicate brain tissues, for example, dark issue (GM), white issue (WM), cerebral spinal liquid (CSF) and so forth.

The tumour vasculature plays an important role in tumour growth and metastasis. Tumour angiogenesis provides more oxygen and nutrients to growing tumour cells, is not as tightly regulated as embryonic angiogenesis, and do not follow any hierarchically ordered pattern. The heterogeneity of the vasculature, high interstitial fluid pressure, poor extravasation due to sluggish blood flow, and larger distances between exchange vessels are potential barriers to the delivery of therapeutic agents to tumours. The prevention of angiogenesis, normalization of tumour vasculature, and enhancement of blood perfusion through the use of monoclonal antibodies against receptor proteins that are overexpressed on proangiogenic tumour cells, and improved, tumour-targeted delivery of therapeutic agents can all be achieved using nanocarriers of appropriate size. Nanomedicines such as polymeric nanoparticles, lipid nanoparticles, micelles, mesoporous silica particles, metal nanoparticles, noisomes, and liposomes have been developed for the delivery of anticancer drugs in combination with antiangiogenic agents. Amongst them, liposomal delivery systems are mostly approved by the FDA for clinical use. In this review, the molecular pathways of tumour angiogenesis, the physiology of tumour vasculature, barriers to tumour-targeted delivery of therapeutic agents, and the different strategies to overcome these barriers are discussed.

Meningioma brain tumour discrimination is challenging as many histological patterns are mixed between the different subtypes. In clinical practice, dominant patterns are investigated for signs of specific meningioma pathology; however the simple observation could result in inter- and intra-observer variation due to the complexity of the histopathological patterns. Also employing a computerised feature extraction approach applied at a single resolution scale might not suffice in accurately delineating the mixture of histopathological patterns. In this work we propose a novel multiresolution feature extraction approach for characterising the textural properties of the different pathological patterns (i.e. mainly cell nuclei shape, orientation and spatial arrangement within the cytoplasm). The pattern textural properties are characterised at various scales and orientations for an improved separability between the different extracted features. The Gabor filter energy output of each magnitude response was combined with four other fixed-resolution texture signatures (2 model-based and 2 statistical-based) with and without cell nuclei segmentation. The highest classification accuracy of 95% was reported when combining the Gabor filters energy and the meningioma subimage fractal signature as a feature vector without performing any prior cell nuceli segmentation. This indicates that characterising the cell-nuclei self-similarity properties via Gabor filters can assists in achieving an improved meningioma subtype classification, which can assist in overcoming variations in reported diagnosis.

The occurrence of wide-scale neuroplasticity in the injured human brain raises hopes for biomarkers to guide personalised treatment. At the individual level, functional reorganisation has proven challenging to quantify using current techniques that are optimised for population-based analyses. In this cross-sectional study, we acquired functional MRI scans in 44 patients (22 men, 22 women, mean age: 39.4 ± 14 years) with a language-dominant hemisphere brain tumour prior to surgery and 23 healthy volunteers (11 men, 12 women, mean age: 36.3 ± 10.9 years) during performance of a verbal fluency task. We applied a recently developed approach to characterise the normal range of functional connectivity patterns during task performance in healthy controls. Next, we statistically quantified differences from the normal in individual patients and evaluated factors driving these differences. We show that the functional connectivity of brain regions involved in language fluency identifies "fingerprints" of brain plasticity in individual patients, not detected using standard task-evoked analyses. In contrast to healthy controls, patients with a tumour in their language dominant hemisphere showed highly variable fingerprints that uniquely distinguished individuals. Atypical fingerprints were influenced by tumour grade and tumour location relative to the typical fluency-activated network. Our findings show how alterations in brain networks can be visualised and statistically quantified from connectivity fingerprints in individual brains. We propose that connectivity fingerprints offer a statistical metric of individually-specific network organisation through which behaviourally-relevant adaptations could be formally quantified and monitored across individuals, treatments and time.

With the rapid development in serious games, health games have been demonstrated as a useful tool to enhance treatment effects with respect to some problematic behaviors. Every health game has its own game design which can affect the health in a positive manner. In this paper we fixed Imagery Psychotherapy into game design and then developed the 3D Graphical Imagery Psychotherapy video game with cognitive behavioral effects on the children suffering from brain tumor. This therapeutic game attempts to provide a new way to target the psychological illness related to this disease. Experimental user tests were conducted in three hospitals of Pakistan analyzing the different problematic behaviors of a cancer patient before and after the therapy application. The outcome of the study proved that 3D Graphical Imagery Therapy game has been effective in recovering from psychological illness related to brain tumor. The results showed a significant improvement regarding the behaviors, hence this game design found to be effective.

Meningiomas are one of the most prevalent primary brain tumors. Our study aims to obtain mechanistic insights of meningioma pathobiology using mass spectrometry-based label-free quantitative proteome analysis to identifying druggable targets and perturbed pathways for therapeutic intervention. Label-free based proteomics study was done from peptide samples of 21 patients and 8 non-tumor controls which were followed up with Phosphoproteomics to identify the kinases and phosphorylated components of the perturbed pathways. In silico approaches revealed perturbations in extracellular matrix remodeling and associated cascades. To assess the extent of influence of Integrin and PI3K-Akt pathways, we used an Integrin Linked Kinase inhibitor on patient-derived meningioma cell line and performed a transcriptomic analysis of the components. Furthermore, we designed a Targeted proteomics assay which to the best of our knowledge for very first-time enables identification of peptides from 54 meningioma patients via SRM assay to validate the key proteins emerging from our study. This resulted in the identification of peptides from CLIC1, ES8L2, and AHNK many of which are receptors and kinases and are difficult to be characterized using conventional approaches. Furthermore, we were also able to monitor transitions for proteins like NEK9 and CKAP4 which have been reported to be associated with meningioma pathobiology. We believe, this study can aid in designing peptide-based validation assays for meningioma patients as well as IHC studies for clinical applications.

The number of available breast cancer cell (BCC) lines is small, and only a very few of them have been extensively studied. Whether they are representative of the tumours from which they originated remains a matter of debate. Whether their diversity mirrors the well-known inter-tumoural heterogeneity is another essential question. While numerous similarities have long been found between cell lines and tumours, recent technical advances, including the use of micro-arrays and comparative genetic analysis, have brought new data to the discussion. This paper presents most of the BCC lines that have been described in some detail to date. It evaluates the accuracy of the few of them widely used (MCF-7, T-47D, BT-474, SK-BR-3, MDA-MB-231, Hs578T) as tumour models. It is concluded that BCC lines are likely to reflect, to a large extent, the features of cancer cells in vivo. The importance of oestrogen receptor-alpha (gene ESR1) and Her-2/neu (ERBB2) as classifiers for cell lines and tumours is underlined. The recourse to a larger set of cell lines is suggested since the exact origin of some of the widely used lines remains ambiguous. Investigations on additional specific lines are expected to improve our knowledge of BCC and of the dialogue that these maintain with their surrounding normal cells in vivo.

With the rapid development in serious games, health games have been demonstrated as a useful tool to enhance treatment effects with respect to some problematic behaviors. Every health game has its own game design which can affect the health in a positive manner. In this paper we fixed Imagery Psychotherapy into game design and then developed the 3D Graphical Imagery Psychotherapy video game with cognitive behavioral effects on the children suffering from brain tumor. This therapeutic game attempts to provide a new way to target the psychological illness related to this disease. Experimental user tests were conducted in three hospitals of Pakistan analyzing the different problematic behaviors of a cancer patient before and after the therapy application. The outcome of the study proved that 3D Graphical Imagery Therapy game has been effective in recovering from psychological illness related to brain tumor. The results showed a significant improvement regarding the behaviors, hence this game design found to be effective.

Pasien dikeluhkan mengalami penurunan kesadaran sejak 2 hari yang lalu. Pasien tidak bisa dibangunkan keluarga sejak 2 hari yang lalu. Sebelumnya pasien memiliki riwayat nyeri kepala kronis sejak dan pandangan kabur sejak 1 tahun yang lalu. Pasien biasanya meminum bodrex untuk meredakan pusing. Pusing dikeluhka hilang timbul. Pasien sempat berobat ke dokter mata dan di sarankan memakai kacamata untuk pengelohatan kaburnya namun masih tidak membaik. Demam (-), muntah (-), kejang (-), riwayat trauma (-).

Background: Pituitary tumor-transforming gene (PTTG1) has been implicated in several oncogenic processes. The aim of this study was to determine PTTG expression in brain tumors. Materials and Methods: We investigated 88 benign and malignant brain tumors. PTTG immunoexpression was evaluated using a scale of 0 to 3. PTTG immunoexpression was nuclear and cytoplasmic in most tumors, except for medulloblastomas and hemangiopericytomas. Expression was highest in medulloblastomas. Higher grade gliomas including glioblastoma multiforme (GBM) IV and astrocytoma III had the highest level of PTTG expression, whereas low-grade gliomas had the lowest levels of PTTG expression. Hemangiopericytomas had the lowest levels of PTTG immunoreactivity, with meningiomas and schwannomas exhibiting similarly low PTTG levels. Nuclear PTTG immunoreactivity was higher than cytoplasmic in highergrade tumors. Conclusion: Our results indicate that PTTG immunoexpression is higher in aggressive brain tumors including medulloblastomas, GBM IV, and astrocytoma III, whereas in more benign tumors, PTTG immunoexpression is lower.

A significant number of patients diagnosed with primary brain tumours report unmet information needs. Using concept mapping methodology, this study aimed to identify strategies for improving information provision, and to describe factors that health professionals understood to influence their provision of information to patients with brain tumours and their families. Concept mapping is a mixed-methods approach that uses statistical methods to represent participants' perceived relationships between elements as conceptual maps. These maps, and results of associated data collection and analyses, are used to extract concepts involved in information provision to these patients. Thirty health professionals working across a range of neurooncology roles and settings participated in the concept mapping process. Participants rated a care coordinator as the most important strategy for improving brain tumour care, with psychological support as a whole rated as the most important element of care. Five major themes were identified as facilitating information provision: health professionals' communication skills, style and attitudes; patients' needs and preferences; perceptions of patients' need for protection and initiative; rapport and continuity between patients and health professionals; and the nature of the healthcare system. Overall, health professionals conceptualised information provision as 'individualised', dependent on these interconnected personal and environmental factors.

The objective of this research was to develop a question prompt list aimed at increasing question asking and reducing the unmet information needs of adults with primary brain tumours, and to pilot the question prompt list to determine its suitability for the intended population. Thematic analysis of existing resources was used to create a draft which was refined via interviews with 12 brain tumour patients and 6 relatives, readability testing, and review by health professionals. A non-randomised before-after pilot study with 20 brain tumour patients was used to assess the acceptability and usefulness of the question prompt list, compared with a 'standard brochure', and the feasibility of evaluation strategies. The question prompt list developed covered seven main topics (diagnosis, prognosis, symptoms and changes, treatment, support, after treatment finishes, and the health professional team). Pilot study participants provided with the question prompt list agreed that it was helpful (7/7), contained questions that were useful to them (7/7), and prompted them to ask their medical oncologist questions (5/7). The question prompt list is acceptable to patients, and contains questions relevant to them. Research is now needed to assess its effectiveness in increasing question asking and reducing unmet information needs.

Aneuploidy with chromosome instability is a cancer hallmark. We studied chromosome 7 (Chr7) copy number variation (CNV) in gliomas and in primary cultures derived from them. We found tumor heterogeneity with cells having Chr7-CNV commonly occurs in gliomas, with a higher percentage of cells in high-grade gliomas carrying more than 2 copies of Chr7, as compared to low-grade gliomas. Interestingly, all Chr7-aneuploid cell types in the parental culture of established glioma cell lines reappeared in single-cell-derived subcultures. We then characterized the biology of three syngeneic glioma cultures dominated by different Chr7-aneuploid cell types. We found phenotypic divergence for cells following Chr7 missegregation, which benefited overall tumor growth in vitro and in vivo. Mathematical modeling suggested the involvement of chromosome instability and interactions among cell subpopulations in restoring the optimal equilibrium of tumor cell types. Both our experimental data and mathematical modeling demonstrated that the complexity of tumor heterogeneity could be enhanced by the existence of chromosomes with structural abnormality, in addition to their mis-segregations. Overall, our findings show, for the first time, the involvement of chromosome instability in maintaining tumor heterogeneity, which underlies the enhanced growth, persistence and treatment resistance of cancers.

Prostate Cancer is one of the common cancers in the world. It could primarily disseminate to the bone and can lead to death. In order to address its life-threatening distant metastasis, it is important to diagnose it earlier for timely treatment. Bone metastasis is usually diagnosed deploying bone scan imaging. However, interpretation of the bone scans is a tedious procedure for the physicians and often leads to misinterpretation either as overestimation or underestimation of the metastasis. To minimize the risk of misinterpretation, one of the accurate methods is quantitative analysis of the bone scans in order to ascertain, whether a metastatic lesion is present or not. There are several methods to-date which can be used to analyze the extent of such lesions. The aim of this study is to use %PAB (quantitative parameter) on a baseline bone scans. Moreover, an improved methodology is introduced by comparing the results with PSA levels. 141 patients with histopathologically proved prostate cancer were chosen to implement the % PAB on individual baseline bone scans. After which, for the calculation of risk of progression or regression of disease and survival rate, 40 patients were chosen from the same dataset. A serial follows up scan was performed to calculate 2-years survival rate. The dataset was again analyzed using the same quantitative parameter and the cut off were calculated as % PAB: 0.5. It was found out that the % PAB method is a good prognostic indicator in baseline scans. Moreover, the prostate cancer patients with the cut off % PAB > 0.5 showed increase risk of disease progression and less survival..

• Mencakup 36,6% dari keseluruhan tumor otak primer dan 53,2% dari tumor otak primer jinak, meningioma merupakan jenis tumor primer pada otak yang paling sering ditemui di Amerika • Fakhri et al. dari data register tumor di RSUD Dr. Soetomo Surabaya didapatkan meningioma menempati urutan pertama dari semua jenis tumor otak (39,2%).

Brain tumour segmentation can improve diagnostics efficiency, rise the prediction rate and treatment planning. This will help the doctors and experts in their work. Where many types of brain tumour may be classified easily, the gliomas tumour is challenging to be segmented because of the diffusion between the tumour and the surrounding edema. Another important challenge with this type of brain tumour is that the tumour may grow anywhere in the brain with different shape and size. Brain cancer presents one of the most famous diseases over the world, which encourage the researchers to find a high-throughput system for tumour detection and classification. Several approaches have been proposed to design automatic detection and classification systems. This paper presents an integrated framework to segment the gliomas brain tumour automatically using pixel clustering for the MRI images foreground and background and classify its type based on deep learning mechanism, which is the convolutional neural network. In this work, a novel segmentation and classification system is proposed to detect the tumour cells and classify the brain image if it is healthy or not. After collecting data for healthy and non-healthy brain images, satisfactory results are found and registered using computer vision approaches. This approach can be used as a part of a bigger diagnosis system for breast tumour detection and manipulation.

Background: The current standard of care for dif-fuse astrocytoma, specifically partial resection fol-lowed by chemotherapy and/or radiation, remains ineffec¬tive due to the infiltrative nature of the tu-mour, in addition to the detrimental secondary ef-fects of these existing treatments. Thus, the intrana-sal administra¬tion of a telomerase inhibitor (GRN163) is an appeal¬ing alternative as it would inhibit further tumour growth, post-surgery. By cir-cumventing the blood-brain barrier through the ol-factory pathway, the treatment would be more effec-tive in targeting can¬cerous cells and would reach the different brain re¬gions impacted by this widespread tumour.
Hypothesis: The administration of GRN163 by in-tranasal passageway would be an effective adjuvant treatment following surgical resection of a diffuse astrocytoma due to its ability to inhibit tumour growth, thus eventually increasing the overall sur-viv¬al rate of patients.
Aims: To design an effective method of reaching the diffuse astrocytoma, thus improving the progres-sion-free survival rate of the patient and providing them with safer alternatives.
Methods: Phase I clinical trial serving to evaluate the safety of the technique, find a recommended dosage specific to individual body weight and tu-mour size and look for signs of effectiveness.
Results: A reduction of the tumour size and inhibi-tion of the rate of growth will be observed following treatment.
Conclusion: This study will further elucidate the therapeutic potential of an intranasal administration of a telomerase inhibitor in humans. In addition, it will provide a direction for change towards improv-ing the care of patients suffering from brain tumours as it addresses a safer and non-invasive method of treatment.
Keywords: Astrocytoma, Resection, Telomerase, Trial

With the rapid development in serious games, health games have been demonstrated as a useful tool to enhance treatment effects with respect to some problematic behaviors. Every health game has its own game design which can affect the health in a positive manner. In this paper we fixed Imagery Psychotherapy into game design and then developed the 3D Graphical Imagery Psychotherapy video game with cognitive behavioral effects on the children suffering from brain tumor. This therapeutic game attempts to provide a new way to target the psychological illness related to this disease. Experimental user tests were conducted in three hospitals of Pakistan analyzing the different problematic behaviors of a cancer patient before and after the therapy application. The outcome of the study proved that 3D Graphical Imagery Therapy game has been effective in recovering from psychological illness related to brain tumor. The results showed a significant improvement regarding the behaviors, hence this game design found to be effective.

A significant number of patients diagnosed with primary brain tumours report unmet information needs. Using concept mapping methodology, this study aimed to identify strategies for improving information provision, and to describe factors that health professionals understood to influence their provision of information to patients with brain tumours and their families. Concept mapping is a mixed-methods approach that uses statistical methods to represent participants' perceived relationships between elements as conceptual maps. These maps, and results of associated data collection and analyses, are used to extract concepts involved in information provision to these patients. Thirty health professionals working across a range of neurooncology roles and settings participated in the concept mapping process. Participants rated a care coordinator as the most important strategy for improving brain tumour care, with psychological support as a whole rated as the most important element of care. Five major themes were identified as facilitating information provision: health professionals' communication skills, style and attitudes; patients' needs and preferences; perceptions of patients' need for protection and initiative; rapport and continuity between patients and health professionals; and the nature of the healthcare system. Overall, health professionals conceptualised information provision as 'individualised', dependent on these interconnected personal and environmental factors.

Written information is commonly used to inform patients about their disease and treatment but must be evidence-based and understandable to be useful. This study assessed the quality of the content and the readability of information brochures for people affected by brain tumours. We randomly selected 18 publicly available brochures. Brochures were assessed by criteria to assess the quality of content using the DISCERN instrument. Readability was tested using three commonly used formulas, which yield the reading grade level required to comprehend the brochure (sixth grade level recommended). The mean overall DISCERN score was 3.17 out of a maximum of 5 (moderate quality); only one achieved a rating greater than 4 (high quality). Only one brochure met the sixth grade readability criteria. Although brochures may have accurate content, few satisfied all of the recommended criteria to evaluate their content. Existing brochures need to be critically reviewed and simplified and consumer-focused brochures, produced.