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Sample records for brain tumour classification

  1. Brain tumour classification using Gaussian decomposition and neural networks.

    PubMed

    Arizmendi, Carlos; Sierra, Daniel A; Vellido, Alfredo; Romero, Enrique

    2011-01-01

    The development, implementation and use of computer-based medical decision support systems (MDSS) based on pattern recognition techniques holds the promise of substantially improving the quality of medical practice in diagnostic and prognostic tasks. In this study, the core of a decision support system for brain tumour classification from magnetic resonance spectroscopy (MRS) data is presented. It combines data pre-processing using Gaussian decomposition, dimensionality reduction using moving window with variance analysis, and classification using artificial neural networks (ANN). This combination of techniques is shown to yield high diagnostic classification accuracy in problems concerning diverse brain tumour pathologies, some of which have received little attention in the literature.

  2. Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

    PubMed

    Renjith, Arokia; Manjula, P; Mohan Kumar, P

    2015-01-01

    Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

  3. An Improved Brain Tumour Classification System using Wavelet Transform and Neural Network.

    PubMed

    Dhas, DAS; Madheswaran, M

    2015-06-09

    An improved brain tumour classification system using wavelet transform and neural network is developed and presented in this paper. The anisotropic diffusion filter is used for image denoising and the performance of oriented rician noise reducing anisotropic diffusion (ORNRAD) filter is validated. The segmentation of the denoised image is carried out by Fuzzy C-means clustering. The features are extracted using Symlet and Coiflet Wavelet transform and Levenberg Marquardt algorithm based neural network is used to classify the magnetic resonance imaging (MRI) images. This MRI classification technique is tested and analysed with the existing methodologies and its performance is found to be satisfactory with a classification accuracy of 93.02%. The developed system can assist the physicians for classifying the MRI images for better decision-making.

  4. Primary brain tumours in adults.

    PubMed

    Ricard, Damien; Idbaih, Ahmed; Ducray, François; Lahutte, Marion; Hoang-Xuan, Khê; Delattre, Jean-Yves

    2012-05-26

    Important advances have been made in the understanding and management of adult gliomas and primary CNS lymphomas--the two most common primary brain tumours. Progress in imaging has led to a better analysis of the nature and grade of these tumours. Findings from large phase 3 studies have yielded some standard treatments for gliomas, and have confirmed the prognostic value of specific molecular alterations. High-throughput methods that enable genome-wide analysis of tumours have improved the knowledge of tumour biology, which should lead to a better classification of gliomas and pave the way for so-called targeted therapy trials. Primary CNS lymphomas are a group of rare non-Hodgkin lymphomas. High-dose methotrexate-based regimens increase survival, but the standards of care and the place of whole-brain radiotherapy remain unclear, and are likely to depend on the age of the patient. The focus now is on the development of new polychemotherapy regimens to reduce or defer whole-brain radiotherapy and its delayed complications.

  5. Classification of odontogenic tumours. A historical review.

    PubMed

    Philipsen, Hans Peter; Reichart, Peter A

    2006-10-01

    Using the term odontome for any tumour arising from the dental formative tissues, Broca suggested a classification of odontogenic tumours (OTs) in 1869. From 1888 to 1914, Bland-Sutton and Gabell, James and Payne modified tumour terminology, while maintaining Broca's odontome concept. Thoma and Goldman's classification (1946) divided the OTs into tumours of ectodermal, mesodermal and mixed origin and abolished the general term odontome. The Pindborg and Clausen classification (1958) based on the idea that the reciprocal epithelial-mesenchymal tissue interactions were also operating in the pathogenesis of OTs. In 1966, WHO established a Collaborating Centre for the Histological Classification of Odontogenic Tumours and Allied Lesions (including jaw cysts) headed by Dr Jens Pindborg. In 1971, the first authoritative WHO guide to the classification of OTs and cysts appeared followed in 1992 by a second edition. In 2002, Philipsen and Reichart produced a revision of the 1992-edition and in 2003, the editors of the WHO Blue Book series: 'WHO Classification of Tumours' decided to produce a volume on the Head and Neck Tumours including a chapter on Odontogenic Tumours and Bone Related Lesions. In July of 2005 this volume was published by IARC, Lyon.

  6. [New TNM classification of malignant lung tumours].

    PubMed

    Wohlschläger, J; Wittekind, C; Theegarten, D

    2010-09-01

    The staging system for lung tumours is now recommended for the classification of both non-small-cell and small-cell lung cancer as well as for carcinoid tumours of the lung. The T classifications have been redefined: T1 has been subclassified as T1a (≤ 2 cm in size) and T1b (> 2-3 cm in size). T2 has been subclassified as T2a (> 3-5 cm in size) and T2b (> 5-7 cm in size). T2 (> 7 cm in size) has been reclassified as T3. Multiple tumour nodules in the same lobe have been reclassified from T4 to T3. Multiple tumour nodules in the same lung but a different lobe have been reclassified from M1 to T4. No changes have been made in the N classification. The M classification has been redefined: M1 has been subdivided into M1a and M1b. Malignant pleural and pericardial effusions have been reclassified from T4 to M1a. Separate tumour nodules in the contralateral lung have been reclassified from T4 to M1a. M1b designates distant metastasis.

  7. Imaging biomarkers of brain tumour margin and tumour invasion.

    PubMed

    Price, S J; Gillard, J H

    2011-12-01

    Invasion of tumour cells into the normal brain is one of the major reasons of treatment failure for gliomas. Although there is a good understanding of the molecular and cellular processes that occur during this invasion, it is not possible to detect the extent of the tumour with conventional imaging. However, there is an understanding that the degree of invasion differs with individual tumours, and yet they are all treated the same. Newer imaging techniques that probe the pathological changes within tumours may be suitable biomarkers for invasion. Imaging methods are now available that can detect subtle changes in white matter organisation (diffusion tensor imaging), tumour metabolism and cellular proliferation (using MR spectroscopy and positron emission tomography) occurring in regions of tumour that cannot be detected by conventional imaging. The role of such biomarkers of invasion should allow better delineation of tumour margins, which should improve treatment planning (especially surgery and radiotherapy) and provide information on the invasiveness of an individual tumour to help select the most appropriate therapy and help stratify patients for clinical trials.

  8. Molecular classification of urothelial carcinoma: global mRNA classification versus tumour-cell phenotype classification.

    PubMed

    Sjödahl, Gottfrid; Eriksson, Pontus; Liedberg, Fredrik; Höglund, Mattias

    2017-02-13

    Global mRNA expression analysis is efficient for phenotypic profiling of tumours and has been used to define molecular subtypes for almost every major tumour type. A key limitation is that most tumours are communities of both tumour and non-tumour cells. This problem is particularly pertinent when analysing advanced invasive tumours, known to induce major changes and responses in both the tumour and the surrounding tissue. To identify bladder cancer tumour-cell phenotypes and compare classification by tumour-cell phenotype with classification by global gene expression analysis, we analysed 307 advanced bladder cancers (cystectomised) both by genome gene expression analysis and by immunohistochemistry using antibodies for 28 proteins. By systematic analysis of gene and protein expression data, focusing on key molecular processes, we describe five tumour-cell phenotypes of advanced urothelial carcinoma; Urothelial-like, Genomically Unstable, Basal/SCC-like, Mesenchymal-like, and Small cell/Neuroendocrine like. We provide molecular pathological definitions for each subtype. Tumours expressing urothelial differentiation factors show inconsistent and abnormal protein expression of terminal differentiation markers, suggesting pseudo-differentiation. Cancers with different tumour-cell phenotypes may co-cluster (converge), and cases with identical tumour-cell phenotypes may cluster apart (diverge) in global mRNA analyses. This divergence/convergence suggests that broad global commonalities related to the invasive process may exist between muscle-invasive tumours regardless of specific tumour-cell phenotype. Hence, there is a systematic disagreement in subtype classification determined by global mRNA profiling and by IHC profiling at the tumour-cell level. We suggest that a combination of molecular pathology (tumour cell phenotype) and global mRNA profiling (context) is required for adequate subtype classification of muscle-invasive bladder cancer.

  9. Phase congruency map driven brain tumour segmentation

    NASA Astrophysics Data System (ADS)

    Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

    2015-03-01

    Computer Aided Diagnostic (CAD) systems are already of proven value in healthcare, especially for surgical planning, nevertheless much remains to be done. Gliomas are the most common brain tumours (70%) in adults, with a survival time of just 2-3 months if detected at WHO grades III or higher. Such tumours are extremely variable, necessitating multi-modal Magnetic Resonance Images (MRI). The use of Gadolinium-based contrast agents is only relevant at later stages of the disease where it highlights the enhancing rim of the tumour. Currently, there is no single accepted method that can be used as a reference. There are three main challenges with such images: to decide whether there is tumour present and is so localize it; to construct a mask that separates healthy and diseased tissue; and to differentiate between the tumour core and the surrounding oedema. This paper presents two contributions. First, we develop tumour seed selection based on multiscale multi-modal texture feature vectors. Second, we develop a method based on a local phase congruency based feature map to drive level-set segmentation. The segmentations achieved with our method are more accurate than previously presented methods, particularly for challenging low grade tumours.

  10. The 2007 WHO classification of tumours of the central nervous system.

    PubMed

    Louis, David N; Ohgaki, Hiroko; Wiestler, Otmar D; Cavenee, Webster K; Burger, Peter C; Jouvet, Anne; Scheithauer, Bernd W; Kleihues, Paul

    2007-08-01

    The fourth edition of the World Health Organization (WHO) classification of tumours of the central nervous system, published in 2007, lists several new entities, including angiocentric glioma, papillary glioneuronal tumour, rosette-forming glioneuronal tumour of the fourth ventricle, papillary tumour of the pineal region, pituicytoma and spindle cell oncocytoma of the adenohypophysis. Histological variants were added if there was evidence of a different age distribution, location, genetic profile or clinical behaviour; these included pilomyxoid astrocytoma, anaplastic medulloblastoma and medulloblastoma with extensive nodularity. The WHO grading scheme and the sections on genetic profiles were updated and the rhabdoid tumour predisposition syndrome was added to the list of familial tumour syndromes typically involving the nervous system. As in the previous, 2000 edition of the WHO 'Blue Book', the classification is accompanied by a concise commentary on clinico-pathological characteristics of each tumour type. The 2007 WHO classification is based on the consensus of an international Working Group of 25 pathologists and geneticists, as well as contributions from more than 70 international experts overall, and is presented as the standard for the definition of brain tumours to the clinical oncology and cancer research communities world-wide.

  11. Neuropsychological Differences between Survivors of Supratentorial and Infratentorial Brain Tumours

    ERIC Educational Resources Information Center

    Patel, S. K.; Mullins, W. A.; O'Neil, S. H.; Wilson, K.

    2011-01-01

    Background: The purpose of this study is to evaluate the relationship between brain tumour location and core areas of cognitive and behavioural functioning for paediatric brain tumour survivors. The extant literature both supports and refutes an association between paediatric brain tumour location and neurocognitive outcomes. We examined…

  12. Epilepsy-associated tumours: what epileptologists should know about neuropathology, terminology, and classification systems.

    PubMed

    Holthausen, Hans; Blümcke, Ingmar

    2016-09-01

    Brain tumours are an ever-challenging issue in neurology and related medical disciplines. This applies in particular to brain tumours associated with childhood-onset epilepsies, in which seizures are the presenting and only neurological symptom, as our current understanding of the biology and clinical behaviour of an individual tumour is far from being evidence-based. Prospective and randomized clinical trials are lacking in the field of epilepsy-associated tumours and a review of the current literature evokes more questions than provides answers. In this review, current areas of controversy in neuropathology, as well as terminology and classification, are discussed from an epileptologist's perspective. An illustrative case report exemplifies this controversy to further promote interdisciplinary discussion and novel research avenues towards comprehensive patient management in the near future.

  13. Combined texture feature analysis of segmentation and classification of benign and malignant tumour CT slices.

    PubMed

    Padma, A; Sukanesh, R

    2013-01-01

    A computer software system is designed for the segmentation and classification of benign from malignant tumour slices in brain computed tomography (CT) images. This paper presents a method to find and select both the dominant run length and co-occurrence texture features of region of interest (ROI) of the tumour region of each slice to be segmented by Fuzzy c means clustering (FCM) and evaluate the performance of support vector machine (SVM)-based classifiers in classifying benign and malignant tumour slices. Two hundred and six tumour confirmed CT slices are considered in this study. A total of 17 texture features are extracted by a feature extraction procedure, and six features are selected using Principal Component Analysis (PCA). This study constructed the SVM-based classifier with the selected features and by comparing the segmentation results with the experienced radiologist labelled ground truth (target). Quantitative analysis between ground truth and segmented tumour is presented in terms of segmentation accuracy, segmentation error and overlap similarity measures such as the Jaccard index. The classification performance of the SVM-based classifier with the same selected features is also evaluated using a 10-fold cross-validation method. The proposed system provides some newly found texture features have an important contribution in classifying benign and malignant tumour slices efficiently and accurately with less computational time. The experimental results showed that the proposed system is able to achieve the highest segmentation and classification accuracy effectiveness as measured by jaccard index and sensitivity and specificity.

  14. The effect of brain tumour laterality on anxiety levels among neurosurgical patients

    PubMed Central

    Mainio, A; Hakko, H; Niemela, A; Tuurinkoski, T; Koivukangas, J; Rasanen, P

    2003-01-01

    Objectives: The aim of this study was to investigate the level of anxiety in patients with a primary brain tumour and to analyse the effect of tumour laterality and histology on the level of anxiety. Recurrent measurements were assessed preoperatively, three months, and one year after operation. Methods: The study population consisted of 101 patients with a primary brain tumour from unselected and homogeneous population in northern Finland. The patients were studied preoperatively with CT or MRI to determine the location of the tumour. The histology of the tumour was defined according to WHO classification. The level of anxiety was obtained by Crown-Crisp Experiential Index (CCEI) scale. Results: The patients with a tumour in the right hemisphere had statistically significantly higher mean anxiety scores compared to the patients with a tumour in the left hemisphere before surgery of the tumour. By three months and by one year after surgical resection of the tumour, the level of anxiety declined in patients with a tumour in the right hemisphere. A corresponding decline was not found in patients with a tumour in the left hemisphere. According to laterality by tumour histology, the level of anxiety decreased significantly in male and female patients with a glioma in the right hemisphere, but a corresponding decline was not significant in the female patients with a meningioma in the right hemisphere. Decreased level of anxiety was not found in patients with gliomas or meningiomas in the left hemisphere by follow up measurements. Conclusions: Primary brain tumour in right hemisphere is associated with anxiety symptoms. The laterality of anxiety seems to reflect the differentiation of the two hemispheres. The level of anxiety declined after operation of right tumour, approaching that of the general population. The effect of right hemisphere gliomas on anxiety symptoms deserves special attention in future research. PMID:12933936

  15. Melanotic neuroectodermal tumour of infancy: a rare brain tumour of childhood.

    PubMed

    Khan, Muhammad Babar; Soares, Delvene; Tahir, Muhammad Zubair; Kumar, Rajesh; Minhas, Khurram; Bari, Muhammad Ehsan

    2013-05-01

    Melanotic neuroectodermal tumour of infancy is a rare, mostly benign but locally aggressive tumour of neural crest cell origin occurring in infants. The most commonly affected anatomic site is the maxilla. Such tumours of the brain and skull are very rare. We present the case of an 8 months old baby girl whose presenting complaint was a swelling in the scalp for 6 months. She was otherwise asymptomatic. CT imaging confirmed the presence of an osteolytic tumour in the anterior parasagittal skull with dural involvement. The tumour was surgically excised enbloc. The patient has been well at 2 years follow-up without any evidence of recurrence.

  16. Generating prior probabilities for classifiers of brain tumours using belief networks

    PubMed Central

    Reynolds, Greg M; Peet, Andrew C; Arvanitis, Theodoros N

    2007-01-01

    Background Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. Methods The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. Results Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET), germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. Conclusion Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods. PMID:17877822

  17. The evolving classification of soft tissue tumours - an update based on the new 2013 WHO classification.

    PubMed

    Fletcher, Christopher D M

    2014-01-01

    The new World Health Organization (WHO) classification of soft tissue tumours was published in early 2013, almost 11 years after the previous edition. While the number of newly recognized entities included for the first time is fewer than that in 2002, there have instead been substantial steps forward in molecular genetic and cytogenetic characterization of this family of tumours, leading to more reproducible diagnosis, a more meaningful classification scheme and providing new insights regarding pathogenesis, which previously has been obscure in most of these lesions. This brief overview summarizes changes in the classification in each of the broad categories of soft tissue tumour (adipocytic, fibroblastic, etc.) and also provides a short summary of newer genetic data which have been incorporated in the WHO classification.

  18. Canine brain tumours: a model for the human disease?

    PubMed

    Hicks, J; Platt, S; Kent, M; Haley, A

    2017-03-01

    Canine brain tumours are becoming established as naturally occurring models of disease to advance diagnostic and therapeutic understanding successfully. The size and structure of the dog's brain, histopathology and molecular characteristics of canine brain tumours, as well as the presence of an intact immune system, all support the potential success of this model. The limited success of current therapeutic regimens such as surgery and radiation for dogs with intracranial tumours means that there can be tremendous mutual benefit from collaboration with our human counterparts resulting in the development of new treatments. The similarities and differences between the canine and human diseases are described in this article, emphasizing both the importance and limitations of canines in brain tumour research. Recent clinical veterinary therapeutic trials are also described to demonstrate the areas of research in which canines have already been utilized and to highlight the important potential benefits of translational research to companion dogs.

  19. Low-grade epilepsy-associated neuroepithelial tumours - the 2016 WHO classification.

    PubMed

    Blümcke, Ingmar; Aronica, Eleonora; Becker, Albert; Capper, David; Coras, Roland; Honavar, Mrinalini; Jacques, Thomas S; Kobow, Katja; Miyata, Hajime; Mühlebner, Angelika; Pimentel, José; Söylemezoğlu, Figen; Thom, Maria

    2016-12-01

    Rapid developments in molecular genetic technology and research have swiftly advanced our understanding of neuro-oncology. As a consequence, the WHO invited their expert panels to revise the current classification system of brain tumours and to introduce, for the first time, a molecular genetic approach for selected tumour entities, thus setting a new gold standard in histopathology. The revised 5th edition of the 'blue book' was released in May 2016 and will have a major impact in stratifying diagnosis and treatment. However, low-grade neuroepithelial tumours that present with early-onset focal epilepsy and are mostly seen in children and young adults (previously designated as long-term epilepsy-associated neuroepithelial tumours, LEAT) lack such innovative clinicopathological and molecular genetic tools. The Neuropathology Task Force of the International League against Epilepsy will critically discuss this issue, and will offer perspectives on how to decipher and validate clinically meaningful LEAT entities using the current WHO approach that integrates clinicopathological and genetic classification systems.

  20. Cellular and cordless telephones and the risk for brain tumours.

    PubMed

    Hardell, L; Hallquist, A; Mild, K Hansson; Carlberg, M; Påhlson, A; Lilja, A

    2002-08-01

    Microwave exposure from the use of cellular telephones has been discussed in recent years as a potential risk factor for brain tumours. We included in a case-control study 1617 patients aged 20-80 years of both sexes with brain tumour diagnosed between 1 January 1997 and 30 June 2000. They were alive at the study time and had histopathologically verified brain tumour. One matched control to each case was selected from the Swedish Population Register. The study area was the Uppsala-Orebro, Stockholm, Linköping and Göteborg medical regions of Sweden. Exposure was assessed by a questionnaire that was answered by 1429 (88%) cases and 1470 (91%) controls. In total, use of analogue cellular telephones gave an increased risk with an odds ratio (OR) of 1.3 (95% confidence interval (CI) 1.02-1.6). With a tumour induction period of >10 years the risk increased further: OR 1.8 (95% CI 1.1-2.9). No clear association was found for digital or cordless telephones. With regard to the anatomical area of the tumour and exposure to microwaves, the risk was increased for tumours located in the temporal area on the same side of the brain that was used during phone calls; for analogue cellular telephones the OR was 2.5 (95% CI 1.3-4.9). Use of a telephone on the opposite side of the brain was not associated with an increased risk for brain tumours. With regard to different tumour types, the highest risk was for acoustic neurinoma (OR 3.5, 95% CI 1.8-6.8) among analogue cellular telephone users.

  1. Residential Radon and Brain Tumour Incidence in a Danish Cohort

    PubMed Central

    Bräuner, Elvira V.; Andersen, Zorana J.; Andersen, Claus E.; Pedersen, Camilla; Gravesen, Peter; Ulbak, Kaare; Hertel, Ole; Loft, Steffen; Raaschou-Nielsen, Ole

    2013-01-01

    Background Increased brain tumour incidence over recent decades may reflect improved diagnostic methods and clinical practice, but remain unexplained. Although estimated doses are low a relationship between radon and brain tumours may exist. Objective To investigate the long-term effect of exposure to residential radon on the risk of primary brain tumour in a prospective Danish cohort. Methods During 1993–1997 we recruited 57,053 persons. We followed each cohort member for cancer occurrence from enrolment until 31 December 2009, identifying 121 primary brain tumour cases. We traced residential addresses from 1 January 1971 until 31 December 2009 and calculated radon concentrations at each address using information from central databases regarding geology and house construction. Cox proportional hazards models were used to estimate incidence rate-ratios (IRR) and 95% confidence intervals (CI) for the risk of primary brain tumours associated with residential radon exposure with adjustment for age, sex, occupation, fruit and vegetable consumption and traffic-related air pollution. Effect modification by air pollution was assessed. Results Median estimated radon was 40.5 Bq/m3. The adjusted IRR for primary brain tumour associated with each 100 Bq/m3 increment in average residential radon levels was 1.96 (95% CI: 1.07; 3.58) and this was exposure-dependently higher over the four radon exposure quartiles. This association was not modified by air pollution. Conclusions We found significant associations and exposure-response patterns between long-term residential radon exposure radon in a general population and risk of primary brain tumours, adding new knowledge to this field. This finding could be chance and needs to be challenged in future studies. PMID:24066143

  2. Epstein-Barr virus-associated smooth muscle tumour presenting as a parasagittal brain tumour.

    PubMed

    Ibebuike, K E; Pather, S; Emereole, O; Ndolo, P; Kajee, A; Gopal, R; Naidoo, S

    2012-11-01

    Dural-based brain tumours, apart from meningiomas, are rare. Epstein-Barr virus (EBV)-associated smooth muscle tumor (SMT) is a documented but rare disease that occurs in immunocompromized patients. These tumours may be located at unusual sites including the brain. We present a 37-year-old patient, positive for the human immunodeficiency virus (HIV), who was admitted after generalized tonic-clonic seizures. MRI and CT scan revealed a dural-based brain tumour, intraoperatively thought to be a meningioma, but with an eventual histological diagnosis of EBV-SMT. Clinically the patient was well postoperatively with a Glasgow coma scale score of 15/15 and no focal neurologic deficit. This case confirms the association between EBV and SMT in patients with HIV/acquired immunodeficiency syndrome (AIDS). It also highlights the need to include EBV-SMT in the differential diagnosis of intracranial mass lesions in patients with HIV/AIDS.

  3. WHO classification of soft tissue tumours: an update based on the 2013 (4th) edition.

    PubMed

    Jo, Vickie Y; Fletcher, Christopher D M

    2014-02-01

    The fourth edition of the World Health Organization (WHO) Classification of Tumours of Soft Tissue and Bone was published in February 2013, and serves to provide an updated classification scheme and reproducible diagnostic criteria for pathologists. Given the relative rarity of soft tissue tumours and the rapid rate of immunohistochemical and genetic/molecular developments (not infrequently facilitating recognition of new tumour entities), this updated text edited by a consensus group is important for both practising pathologists and oncologists. The 2013 WHO classification includes several changes in soft tissue tumour classification, including several new entities (e.g., pseudomyogenic haemangioendothelioma, haemosiderotic fibrolipomatous tumour, and acral fibromyxoma), three newly included sections for gastrointestinal stromal tumours, nerve sheath tumours, and undifferentiated/unclassified soft tissue tumours, respectively, various 'reclassified' tumours, and a plethora of new genetic and molecular data for established tumour types that facilitate better definition and are useful as diagnostic tools. This article briefly outlines these updates based on the 2013 WHO classification of soft tissue tumours.

  4. Semi-supervised analysis of human brain tumours from partially labeled MRS information, using manifold learning models.

    PubMed

    Cruz-Barbosa, Raúl; Vellido, Alfredo

    2011-02-01

    Medical diagnosis can often be understood as a classification problem. In oncology, this typically involves differentiating between tumour types and grades, or some type of discrete outcome prediction. From the viewpoint of computer-based medical decision support, this classification requires the availability of accurate diagnoses of past cases as training target examples. The availability of such labeled databases is scarce in most areas of oncology, and especially so in neuro-oncology. In such context, semi-supervised learning oriented towards classification can be a sensible data modeling choice. In this study, semi-supervised variants of Generative Topographic Mapping, a model of the manifold learning family, are applied to two neuro-oncology problems: the diagnostic discrimination between different brain tumour pathologies, and the prediction of outcomes for a specific type of aggressive brain tumours. Their performance compared favorably with those of the alternative Laplacian Eigenmaps and Semi-Supervised SVM for Manifold Learning models in most of the experiments.

  5. Current approaches to the treatment of metastatic brain tumours.

    PubMed

    Owonikoko, Taofeek K; Arbiser, Jack; Zelnak, Amelia; Shu, Hui-Kuo G; Shim, Hyunsuk; Robin, Adam M; Kalkanis, Steven N; Whitsett, Timothy G; Salhia, Bodour; Tran, Nhan L; Ryken, Timothy; Moore, Michael K; Egan, Kathleen M; Olson, Jeffrey J

    2014-04-01

    Metastatic tumours involving the brain overshadow primary brain neoplasms in frequency and are an important complication in the overall management of many cancers. Importantly, advances are being made in understanding the molecular biology underlying the initial development and eventual proliferation of brain metastases. Surgery and radiation remain the cornerstones of the therapy for symptomatic lesions; however, image-based guidance is improving surgical technique to maximize the preservation of normal tissue, while more sophisticated approaches to radiation therapy are being used to minimize the long-standing concerns over the toxicity of whole-brain radiation protocols used in the past. Furthermore, the burgeoning knowledge of tumour biology has facilitated the entry of systemically administered therapies into the clinic. Responses to these targeted interventions have ranged from substantial toxicity with no control of disease to periods of useful tumour control with no decrement in performance status of the treated individual. This experience enables recognition of the limits of targeted therapy, but has also informed methods to optimize this approach. This Review focuses on the clinically relevant molecular biology of brain metastases, and summarizes the current applications of these data to imaging, surgery, radiation therapy, cytotoxic chemotherapy and targeted therapy.

  6. Further aspects on cellular and cordless telephones and brain tumours.

    PubMed

    Hardell, Lennart; Mild, Kjell Hansson; Carlberg, Michael

    2003-02-01

    We included in a case-control study on brain tumours and mobile and cordless telephones 1,617 patients aged 20-80 years of both sexes diagnosed during January 1, 1997 to June 30, 2000. They were alive at the study time and had histopathology verified brain tumour. One matched control to each case was selected from the Swedish Population Register. The study area was the Uppsala-Orebro, Stockholm, Linköping and Göteborg medical regions of Sweden. Exposure was assessed by a questionnaire that was answered by 1,429 (88%) cases and 1,470 (91%) controls. In total use of analogue cellular telephones gave an increased risk with odds ratio (OR)=1.3, 95% confidence interval (CI)=1.04-1.6, whereas digital and cordless phones did not overall increase the risk significantly. Ipsilateral use of analogue phones gave OR=1.7, 95% CI=1.2-2.3, digital phones OR=1.3, 95% CI=1.02-1.8 and cordless phones OR=1.2, 95% CI=0.9-1.6. The risk for ipsilateral use was significantly increased for astrocytoma for all studied phone types, analogue phones OR=1.8,95% CI=1.1-3.2, digital phones OR=1.8, 95% CI=1.1-2.8, cordless phones OR=1.8, 95% CI=1.1-2.9. Use of a telephone on the opposite side of the brain was not associated with a significantly increased risk for brain tumours. Regarding anatomical area of the tumour and exposure to microwaves, the risk was increased for tumours located in the temporal area on the same side of the brain that was used during phone calls, significantly so for analogue cellular telephones OR=2.3, 95% CI=1.2-4.1. For acoustic neurinoma OR=4.4, 95% CI=2.1-9.2 was calculated among analogue cellular telephone users. When duration of use was analysed as a continuous variable in the total material, the risk increased per year for analogue phones with OR=1.04, 95% CI=1.01-1.08. For astrocytoma and ipsilateral use the trend was for analogue phones OR=1.10, 95% CI=1.02-1.19, digital phones OR=1.11, 95% CI=1.01-1.22, and cordless phones OR=1.09, 95% CI=1.01-1.19. There was

  7. Mobile phones, cordless phones and the risk for brain tumours.

    PubMed

    Hardell, Lennart; Carlberg, Michael

    2009-07-01

    The Hardell-group conducted during 1997-2003 two case control studies on brain tumours including assessment of use of mobile phones and cordless phones. The questionnaire was answered by 905 (90%) cases with malignant brain tumours, 1,254 (88%) cases with benign tumours and 2,162 (89%) population-based controls. Cases were reported from the Swedish Cancer Registries. Anatomical area in the brain for the tumour was assessed and related to side of the head used for both types of wireless phones. In the current analysis we defined ipsilateral use (same side as the tumour) as >or=50% of the use and contralateral use (opposite side) as <50% of the calling time. We report now further results for use of mobile and cordless phones. Regarding astrocytoma we found highest risk for ipsilateral mobile phone use in the >10 year latency group, OR=3.3, 95% CI=2.0-5.4 and for cordless phone use OR=5.0, 95% CI=2.3-11. In total, the risk was highest for cases with first use <20 years age, for mobile phone OR=5.2, 95% CI=2.2-12 and for cordless phone OR=4.4, 95% CI=1.9-10. For acoustic neuroma, the highest OR was found for ipsilateral use and >10 year latency, for mobile phone OR=3.0, 95% CI=1.4-6.2 and cordless phone OR=2.3, 95% CI=0.6-8.8. Overall highest OR for mobile phone use was found in subjects with first use at age <20 years, OR=5.0, 95% CI 1.5-16 whereas no association was found for cordless phone in that group, but based on only one exposed case. The annual age-adjusted incidence of astrocytoma for the age group >19 years increased significantly by +2.16%, 95% CI +0.25 to +4.10 during 2000-2007 in Sweden in spite of seemingly underreporting of cases to the Swedish Cancer Registry. A decreasing incidence was found for acoustic neuroma during the same period. However, the medical diagnosis and treatment of this tumour type has changed during recent years and underreporting from a single center would have a large impact for such a rare tumour.

  8. Incidence of leukaemia and brain tumours in some "electrical occupations".

    PubMed Central

    Törnqvist, S; Knave, B; Ahlbom, A; Persson, T

    1991-01-01

    A 19 year follow up study was conducted to explore the association between occupations expected to be exposed to electromagnetic fields and the occurrence of leukaemia and brain tumours. Incidence of cancer between 1961-79 was calculated and the standardised morbidity ratio (SMR) with a 95% confidence interval (95% CI) was related to that of all Swedish working men. For all the selected "electrical occupations" the SMRs for total leukaemia and brain tumours were near unity. Increased risks were noted for all leukaemia among electrical/electronic engineers and technicians, (SMR 1.3; 95% CI 1.0-1.7) as well as in the sub-groups of telegraph/telephone (2.1; 1.1-3.6) and machine (2.6; 1.0-5.8) industries. Risk for chronic lymphoid leukaemia was increased in the same occupational category (1.7; 1.1-2.5) and in the sub-group of machine industry (4.8; 1.0-14.0), as well as for all linesmen (2.0; 1.0-3.5) and power linesmen (2.8; 1.1-5.7). Risk for acute myeloid leukaemia was increased among all miners (2.2; 1.0-4.1) and miners working in iron/ore mines (5.7; 2.1-12.4). Increased risk for all brain tumours (2.9; 1.2-5.9) and glioblastomas (3.4; 1.1-8.0) appeared among assemblers and repairmen in radio and TV industry. Raised risk for all brain tumours was seen for all welders (1.3; 1.0-1.7) and welders in iron/steel works (3.2; 1.0-7.4) and risk for glioblastomas was also increased for all welders (1.5; 1.1-2.1). No major changes in relative risk estimates were noted after the exclusion of persons who were over 65 at the time of diagnosis. Although a homogeneous pattern of increased risks of leukaemia or brain tumour was not noted, the hypothesis that magnetic fields might play a part in the origin of cancer cannot be rejected. PMID:1911402

  9. Gene selection approach based on improved swarm intelligent optimisation algorithm for tumour classification.

    PubMed

    Jin, Cong; Jin, Shu-Wei

    2016-06-01

    A number of different gene selection approaches based on gene expression profiles (GEP) have been developed for tumour classification. A gene selection approach selects the most informative genes from the whole gene space, which is an important process for tumour classification using GEP. This study presents an improved swarm intelligent optimisation algorithm to select genes for maintaining the diversity of the population. The most essential characteristic of the proposed approach is that it can automatically determine the number of the selected genes. On the basis of the gene selection, the authors construct a variety of the tumour classifiers, including the ensemble classifiers. Four gene datasets are used to evaluate the performance of the proposed approach. The experimental results confirm that the proposed classifiers for tumour classification are indeed effective.

  10. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Hematolymphoid Tumours.

    PubMed

    Brown, Noah A; Elenitoba-Johnson, Kojo S J

    2017-03-01

    In 2017, the latest revision to the WHO Classification of Head and Neck Tumours will be released. Similar to the 2005 WHO, the codification of hematopoietic and lymphoid neoplasms of the head and neck is included within chapters pertaining to the nasal cavity and paranasal sinuses, the nasopharynx, the larynx, the oral cavity and oropharynx, the neck and the salivary glands. Herein, we describe both changes to the classification of hematolymphoid neoplasms of the head and neck since the 2005 WHO, as well as recent advances in our understanding of the underlying pathogenesis and molecular pathology of these neoplasms.

  11. Hierarchical probabilistic Gabor and MRF segmentation of brain tumours in MRI volumes.

    PubMed

    Subbanna, Nagesh K; Precup, Doina; Collins, D Louis; Arbel, Tal

    2013-01-01

    In this paper, we present a fully automated hierarchical probabilistic framework for segmenting brain tumours from multispectral human brain magnetic resonance images (MRIs) using multiwindow Gabor filters and an adapted Markov Random Field (MRF) framework. In the first stage, a customised Gabor decomposition is developed, based on the combined-space characteristics of the two classes (tumour and non-tumour) in multispectral brain MRIs in order to optimally separate tumour (including edema) from healthy brain tissues. A Bayesian framework then provides a coarse probabilistic texture-based segmentation of tumours (including edema) whose boundaries are then refined at the voxel level through a modified MRF framework that carefully separates the edema from the main tumour. This customised MRF is not only built on the voxel intensities and class labels as in traditional MRFs, but also models the intensity differences between neighbouring voxels in the likelihood model, along with employing a prior based on local tissue class transition probabilities. The second inference stage is shown to resolve local inhomogeneities and impose a smoothing constraint, while also maintaining the appropriate boundaries as supported by the local intensity difference observations. The method was trained and tested on the publicly available MICCAI 2012 Brain Tumour Segmentation Challenge (BRATS) Database [1] on both synthetic and clinical volumes (low grade and high grade tumours). Our method performs well compared to state-of-the-art techniques, outperforming the results of the top methods in cases of clinical high grade and low grade tumour core segmentation by 40% and 45% respectively.

  12. Brain tumour and infiltrations dosimetry of boron neutron capture therapy combined with 252Cf brachytherapy.

    PubMed

    Brandão, Sâmia F; Campos, Tarcísio P R

    2012-04-01

    This article presents a dosimetric investigation of boron neutron capture therapy (BNCT) combined with (252)Cf brachytherapy for brain tumour control. The study was conducted through computational simulation in MCNP5 code, using a precise and discrete voxel model of a human head, in which a hypothetical brain tumour was incorporated. A boron concentration ratio of 1:5 for healthy-tissue: tumour was considered. Absorbed and biologically weighted dose rates and neutron fluency in the voxel model were evaluated. The absorbed dose rate results were exported to SISCODES software, which generates the isodose surfaces on the brain. Analyses were performed to clarify the relevance of boron concentrations in occult infiltrations far from the target tumour, with boron concentration ratios of 1:1 up to 1:50 for healthy-tissue:infiltrations and healthy-tissue:tumour. The average biologically weighted dose rates at tumour area exceed up to 40 times the surrounding healthy tissue dose rates. In addition, the biologically weighted dose rates from boron have the main contribution at the infiltrations, especially far from primary tumour. In conclusion, BNCT combined with (252)Cf brachytherapy is an alternative technique for brain tumour treatment because it intensifies dose deposition at the tumour and at infiltrations, sparing healthy brain tissue.

  13. Molecular crosstalk between tumour and brain parenchyma instructs histopathological features in glioblastoma

    PubMed Central

    Bougnaud, Sébastien; Golebiewska, Anna; Oudin, Anaïs; Keunen, Olivier; Harter, Patrick N.; Mäder, Lisa; Azuaje, Francisco; Fritah, Sabrina; Stieber, Daniel; Kaoma, Tony; Vallar, Laurent; Brons, Nicolaas H.C.; Daubon, Thomas; Miletic, Hrvoje; Sundstrøm, Terje; Herold-Mende, Christel; Mittelbronn, Michel; Bjerkvig, Rolf; Niclou, Simone P.

    2016-01-01

    The histopathological and molecular heterogeneity of glioblastomas represents a major obstacle for effective therapies. Glioblastomas do not develop autonomously, but evolve in a unique environment that adapts to the growing tumour mass and contributes to the malignancy of these neoplasms. Here, we show that patient-derived glioblastoma xenografts generated in the mouse brain from organotypic spheroids reproducibly give rise to three different histological phenotypes: (i) a highly invasive phenotype with an apparent normal brain vasculature, (ii) a highly angiogenic phenotype displaying microvascular proliferation and necrosis and (iii) an intermediate phenotype combining features of invasion and vessel abnormalities. These phenotypic differences were visible during early phases of tumour development suggesting an early instructive role of tumour cells on the brain parenchyma. Conversely, we found that tumour-instructed stromal cells differentially influenced tumour cell proliferation and migration in vitro, indicating a reciprocal crosstalk between neoplastic and non-neoplastic cells. We did not detect any transdifferentiation of tumour cells into endothelial cells. Cell type-specific transcriptomic analysis of tumour and endothelial cells revealed a strong phenotype-specific molecular conversion between the two cell types, suggesting co-evolution of tumour and endothelial cells. Integrative bioinformatic analysis confirmed the reciprocal crosstalk between tumour and microenvironment and suggested a key role for TGFβ1 and extracellular matrix proteins as major interaction modules that shape glioblastoma progression. These data provide novel insight into tumour-host interactions and identify novel stroma-specific targets that may play a role in combinatorial treatment strategies against glioblastoma. PMID:27049916

  14. Guiding intracortical brain tumour cells to an extracortical cytotoxic hydrogel using aligned polymeric nanofibres

    NASA Astrophysics Data System (ADS)

    Jain, Anjana; Betancur, Martha; Patel, Gaurangkumar D.; Valmikinathan, Chandra M.; Mukhatyar, Vivek J.; Vakharia, Ajit; Pai, S. Balakrishna; Brahma, Barunashish; MacDonald, Tobey J.; Bellamkonda, Ravi V.

    2014-03-01

    Glioblastoma multiforme is an aggressive, invasive brain tumour with a poor survival rate. Available treatments are ineffective and some tumours remain inoperable because of their size or location. The tumours are known to invade and migrate along white matter tracts and blood vessels. Here, we exploit this characteristic of glioblastoma multiforme by engineering aligned polycaprolactone (PCL)-based nanofibres for tumour cells to invade and, hence, guide cells away from the primary tumour site to an extracortical location. This extracortial sink is a cyclopamine drug-conjugated, collagen-based hydrogel. When aligned PCL-nanofibre films in a PCL/polyurethane carrier conduit were inserted in the vicinity of an intracortical human U87MG glioblastoma xenograft, a significant number of human glioblastoma cells migrated along the aligned nanofibre films and underwent apoptosis in the extracortical hydrogel. Tumour volume in the brain was significantly lower following insertion of aligned nanofibre implants compared with the application of smooth fibres or no implants.

  15. Combined radiotherapy and chemotherapy for high-grade brain tumours

    NASA Astrophysics Data System (ADS)

    Barazzuol, Lara

    Glioblastoma (GBM) is the most common primary brain tumour in adults and among the most aggressive of all tumours. For several decades, the standard care of GBM was surgical resection followed by radiotherapy alone. In 2005, a landmark phase III clinical trial coordinated by the European Organization for Research and Treatment of Cancer (EORTC) and the National Cancer Institute of Canada (NCIC) demonstrated the benefit of radiotherapy with concomitant and adjuvant temozolomide (TMZ) chemotherapy. With TMZ, the median life expectancy in optimally managed patients is still only 12-14 months, with only 25% surviving 24 months. There is an urgent need for new therapies in particular in those patients whose tumour has an unmethylated methylguanine methyltransferase gene (MGMT) promoter, which is a predictive factor of benefit from TMZ. In this dissertation, the nature of the interaction between TMZ and radiation is investigated using both a mathematical model, based on in vivo population statistics of survival, and in vitro experimentation on a panel of human GBM cell lines. The results show that TMZ has an additive effect in vitro and that the population-based model may be insufficient in predicting TMZ response. The combination of TMZ with particle therapy is also investigated. Very little preclinical data exists on the effects of charged particles on GBM cell lines as well as on the concomitant application of chemotherapy. In this study, human GBM cells are exposed to 3 MeV protons and 6 MeV alpha particles in concomitance with TMZ. The results suggest that the radiation quality does not affect the nature of the interaction between TMZ and radiation, showing reproducible additive cytotoxicity. Since TMZ and radiation cause DNA damage in cancer cells, there has been increased attention to the use of poly(ADP-ribose) polymerase (PARP) inhibitors. PARP is a family of enzymes that play a key role in the repair of DNA breaks. In this study, a novel PARP inhibitor, ABT-888

  16. Screening for invasion of the individual human brain tumour in an autologous confrontation system in vitro.

    PubMed

    de Ridder, L

    1999-01-01

    Invasiveness is the major cause of death in patients bearing a brain tumour. The invasiveness or infiltrative capacity of a primary brain tumour has a prognostic value for the evaluation of the process in vivo. So a model to imitate invasion might give information on the in vivo behaviour and outcome of the disease for the individual patient. The developed in vitro model represents an assay in which the patients' brain tumour-derived cells are confronted with connective tissue from the patient himself, i.e. an autologous system to evaluate the individual behaviour of the tumour, in contrast to other invasion models. The test can be applied with tumour-derived material collected by a stereotactic biopsy.

  17. Cellular immortality in brain tumours: an integration of the cancer stem cell paradigm.

    PubMed

    Rahman, Ruman; Heath, Rachel; Grundy, Richard

    2009-04-01

    Brain tumours are a diverse group of neoplasms that continue to present a formidable challenge in our attempt to achieve curable intervention. Our conceptual framework of human brain cancer has been redrawn in the current decade. There is a gathering acceptance that brain tumour formation is a phenotypic outcome of dysregulated neurogenesis, with tumours viewed as abnormally differentiated neural tissue. In relation, there is accumulating evidence that brain tumours, similar to leukaemia and many solid tumours, are organized as a developmental hierarchy which is maintained by a small fraction of cells endowed with many shared properties of tissue stem cells. Proof that neurogenesis persists throughout adult life, compliments this concept. Although the cancer cell of origin is unclear, the proliferative zones that harbour stem cells in the embryonic, post-natal and adult brain are attractive candidates within which tumour-initiation may ensue. Dysregulated, unlimited proliferation and an ability to bypass senescence are acquired capabilities of cancerous cells. These abilities in part require the establishment of a telomere maintenance mechanism for counteracting the shortening of chromosomal termini. A strategy based upon the synthesis of telomeric repeat sequences by the ribonucleoprotein telomerase, is prevalent in approximately 90% of human tumours studied, including the majority of brain tumours. This review will provide a developmental perspective with respect to normal (neurogenesis) and aberrant (tumourigenesis) cellular turnover, differentiation and function. Within this context our current knowledge of brain tumour telomere/telomerase biology will be discussed with respect to both its developmental and therapeutic relevance to the hierarchical model of brain tumourigenesis presented by the cancer stem cell paradigm.

  18. Glioblastoma brain tumours: estimating the time from brain tumour initiation and resolution of a patient survival anomaly after similar treatment protocols.

    PubMed

    Murray, J D

    2012-01-01

    A practical mathematical model for glioblastomas (brain tumours), which incorporates the two key parameters of tumour growth, namely the cancer cell diffusion and the cell proliferation rate, has been shown to be clinically useful and predictive. Previous studies explain why multifocal recurrence is inevitable and show how various treatment scenarios have been incorporated in the model. In most tumours, it is not known when the cancer started. Based on patient in vivo parameters, obtained from two brain scans, it is shown how to estimate the time, after initial detection, when the tumour started. This is an input of potential importance in any future controlled clinical study of any connection between cell phone radiation and brain tumour incidence. It is also used to estimate more accurately survival times from detection. Finally, based on patient parameters, the solution of the model equation of the tumour growth helps to explain why certain patients live longer than others after similar treatment protocols specifically surgical resection (removal) and irradiation.

  19. Functional MRI and intraoperative brain mapping to evaluate brain plasticity in patients with brain tumours and hemiparesis

    PubMed Central

    Roux, F; Boulanouar, K; Ibarrola, D; Tremoulet, M; Chollet, F; Berry, I

    2000-01-01

    OBJECTIVE—To support the hypothesis about the potential compensatory role of ipsilateral corticofugal pathways when the contralateral pathways are impaired by brain tumours.
METHODS—Retrospective analysis was carried out on the results of functional MRI (fMRI) of a selected group of five paretic patients with Rolandic brain tumours who exhibited an abnormally high ipsilateral/contralateral ratio of activation—that is, movements of the paretic hand activated predominately the ipsilateral cortex. Brain activation was achieved with a flexion extension of the fingers. Statistical parametric activation was obtained using a t test and a threshold of p<0.001. These patients, candidates for tumour resection, also underwent cortical intraoperative stimulation that was correlated to the fMRI spatial data using three dimensional reconstructions of the brain. Three patients also had postoperative control fMRI.
RESULTS—The absence of fMRI activation of the primary sensorimotor cortex normally innervating the paretic hand for the threshold chosen, was correlated with completely negative cortical responses of the cortical hand area during the operation. The preoperative fMRI activation of these patients predominantly found in the ipsilateral frontal and primary sensorimotor cortices could be related to the residual ipsilateral hand function. Postoperatively, the fMRI activation returned to more classic patterns of activation, reflecting the consequences of therapy.
CONCLUSION—In paretic patients with brain tumours, ipsilateral control could be implicated in the residual hand function, when the normal primary pathways are impaired. The possibility that functional tissue still remains in the peritumorous sensorimotor cortex even when the preoperative fMRI and the cortical intraoperative stimulations are negative, should be taken into account when planning the tumour resection and during the operation.

 PMID:10990503

  20. Non-negative matrix factorisation methods for the spectral decomposition of MRS data from human brain tumours

    PubMed Central

    2012-01-01

    Background In-vivo single voxel proton magnetic resonance spectroscopy (SV 1H-MRS), coupled with supervised pattern recognition (PR) methods, has been widely used in clinical studies of discrimination of brain tumour types and follow-up of patients bearing abnormal brain masses. SV 1H-MRS provides useful biochemical information about the metabolic state of tumours and can be performed at short (< 45 ms) or long (> 45 ms) echo time (TE), each with particular advantages. Short-TE spectra are more adequate for detecting lipids, while the long-TE provides a much flatter signal baseline in between peaks but also negative signals for metabolites such as lactate. Both, lipids and lactate, are respectively indicative of specific metabolic processes taking place. Ideally, the information provided by both TE should be of use for clinical purposes. In this study, we characterise the performance of a range of Non-negative Matrix Factorisation (NMF) methods in two respects: first, to derive sources correlated with the mean spectra of known tissue types (tumours and normal tissue); second, taking the best performing NMF method for source separation, we compare its accuracy for class assignment when using the mixing matrix directly as a basis for classification, as against using the method for dimensionality reduction (DR). For this, we used SV 1H-MRS data with positive and negative peaks, from a widely tested SV 1H-MRS human brain tumour database. Results The results reported in this paper reveal the advantage of using a recently described variant of NMF, namely Convex-NMF, as an unsupervised method of source extraction from SV1H-MRS. Most of the sources extracted in our experiments closely correspond to the mean spectra of some of the analysed tumour types. This similarity allows accurate diagnostic predictions to be made both in fully unsupervised mode and using Convex-NMF as a DR step previous to standard supervised classification. The obtained results are comparable to, or

  1. SMART syndrome: a late reversible complication after radiation therapy for brain tumours.

    PubMed

    Kerklaan, Joost P; Lycklama á Nijeholt, Geert J; Wiggenraad, Ruud G J; Berghuis, Bianca; Postma, Tjeerd J; Taphoorn, Martin J B

    2011-06-01

    With intensified treatment leading to longer survival, complications of therapy for brain tumours are more frequently observed. Regarding radiation therapy, progressive and irreversible white matter disease with cognitive decline is most feared. We report on four patients with reversible clinical and radiological features occurring years after radiation for brain tumours, suggestive for the so called SMART syndrome (stroke-like migraine attacks after radiation therapy). All four patients (males, age 36-60 years) had been treated with focal brain radiation for a primary brain tumour or with whole-brain radiation therapy for brain metastases. Ranging from 2 to 10 years following radiation therapy patients presented with headache and focal neurological deficits, suggestive for tumour recurrence. Two patients also presented with focal seizures. MRI demonstrated typical cortical swelling and contrast enhancement, primarily in the parieto-occipital region. On follow-up both clinical and MRI features improved spontaneously. Three patients eventually proved to have tumour recurrence. The clinical and radiological picture of these patients is compatible with the SMART syndrome, a rare complication of radiation therapy which is probably under recognized in brain tumour patients. The pathophysiology of the SMART syndrome is poorly understood but bears similarities with the posterior reversible encephalopathy syndrome (PRES). These four cases underline that the SMART syndrome should be considered in patients formerly treated with radiation therapy for brain tumours, who present with new neurologic deficits. Before the diagnosis of SMART syndrome can be established other causes, such as local tumour recurrence, leptomeningeal disease or ischemic disease should be ruled out.

  2. Human Cytomegalovirus Tegument Protein pp65 Is Detected in All Intra- and Extra-Axial Brain Tumours Independent of the Tumour Type or Grade

    PubMed Central

    Libard, Sylwia; Popova, Svetlana N.; Amini, Rose-Marie; Kärjä, Vesa; Pietiläinen, Timo; Hämäläinen, Kirsi M.; Sundström, Christer; Hesselager, Göran; Bergqvist, Michael; Ekman, Simon; Zetterling, Maria; Smits, Anja; Nilsson, Pelle; Pfeifer, Susan; de Ståhl, Teresita Diaz; Enblad, Gunilla; Ponten, Fredrik; Alafuzoff, Irina

    2014-01-01

    Human cytomegalovirus (HCMV) has been indicated being a significant oncomodulator. Recent reports have suggested that an antiviral treatment alters the outcome of a glioblastoma. We analysed the performance of commercial HCMV-antibodies applying the immunohistochemical (IHC) methods on brain sample obtained from a subject with a verified HCMV infection, on samples obtained from 14 control subjects, and on a tissue microarray block containing cores of various brain tumours. Based on these trials, we selected the best performing antibody and analysed a cohort of 417 extra- and intra-axial brain tumours such as gliomas, medulloblastomas, primary diffuse large B-cell lymphomas, and meningiomas. HCMV protein pp65 immunoreactivity was observed in all types of tumours analysed, and the IHC expression did not depend on the patient's age, gender, tumour type, or grade. The labelling pattern observed in the tumours differed from the labelling pattern observed in the tissue with an active HCMV infection. The HCMV protein was expressed in up to 90% of all the tumours investigated. Our results are in accordance with previous reports regarding the HCMV protein expression in glioblastomas and medulloblastomas. In addition, the HCMV protein expression was seen in primary brain lymphomas, low-grade gliomas, and in meningiomas. Our results indicate that the HCMV protein pp65 expression is common in intra- and extra-axial brain tumours. Thus, the assessment of the HCMV expression in tumours of various origins and pathologically altered tissue in conditions such as inflammation, infection, and even degeneration should certainly be facilitated. PMID:25268364

  3. The 2016 World Health Organization Classification of tumours of the Central Nervous System: what the paediatric neuroradiologist needs to know

    PubMed Central

    Chhabda, Sahil; Carney, Olivia; D’Arco, Felice; Jacques, Thomas S.

    2016-01-01

    The recently published 2016 World Health Organization (WHO) classification of tumours of the Central Nervous System (CNS) introduces a number of significant changes from the previous edition. Based on an improved understanding of the genetic and molecular basis of tumorigenesis there has been a shift towards defining tumours by means of these characteristics in addition to their histological features, thus providing an integrated diagnosis. In this article, we will provide a concise overview of the salient changes in the 2016 WHO classification of tumours of the CNS that are of relevance to the paediatric neuroradiologist when it comes to day-to-day reporting. PMID:27942466

  4. The 2016 World Health Organization Classification of tumours of the Central Nervous System: what the paediatric neuroradiologist needs to know.

    PubMed

    Chhabda, Sahil; Carney, Olivia; D'Arco, Felice; Jacques, Thomas S; Mankad, Kshitij

    2016-10-01

    The recently published 2016 World Health Organization (WHO) classification of tumours of the Central Nervous System (CNS) introduces a number of significant changes from the previous edition. Based on an improved understanding of the genetic and molecular basis of tumorigenesis there has been a shift towards defining tumours by means of these characteristics in addition to their histological features, thus providing an integrated diagnosis. In this article, we will provide a concise overview of the salient changes in the 2016 WHO classification of tumours of the CNS that are of relevance to the paediatric neuroradiologist when it comes to day-to-day reporting.

  5. MRS water resonance frequency in childhood brain tumours: a novel potential biomarker of temperature and tumour environment.

    PubMed

    Babourina-Brooks, Ben; Wilson, Martin; Arvanitis, Theodoros N; Peet, Andrew C; Davies, Nigel P

    2014-10-01

    (1)H MRS thermometry has been investigated for brain trauma and hypothermia monitoring applications but has not been explored in brain tumours. The proton resonance frequency (PRF) of water is dependent on temperature but is also influenced by microenvironment factors, such as fast proton exchange with macromolecules, ionic concentration and magnetic susceptibility. (1)H MRS has been utilized for brain tumour diagnostic and prognostic purposes in children; however, the water PRF measure may provide complementary information to further improve characterization. Water PRF values were investigated from a repository of MRS data acquired from childhood brain tumours and children with apparently normal brains. The cohort consisted of histologically proven glioma (22), medulloblastoma (19) and control groups (28, MRS in both the basal ganglia and parietal white matter regions). All data were acquired at 1.5 T using a short TE (30 ms) single voxel spectroscopy (PRESS) protocol. Water PRF values were calculated using methyl creatine and total choline. Spectral peak amplitude weighted averaging was used to improve the accuracy of the measurements. Mean PRF values were significantly larger for medulloblastoma compared with glioma, with a difference in the means of 0.0147 ppm (p < 0.05), while the mean PRF for glioma was significantly lower than for the healthy cohort, with a difference in the means of 0.0061 ppm (p < 0.05). This would suggest the apparent temperature of the glioma group was ~1.5 °C higher than the medulloblastomas and ~0.7 °C higher than a healthy brain. However, the PRF shift may not reflect a change in temperature, given that alterations in protein content, microstructure and ionic concentration contribute to PRF shifts. Measurement of these effects could also be used as a supplementary biomarker, and further investigation is required. This study has shown that the water PRF value has the potential to be used for characterizing

  6. [WHO classification of tumours of soft tissue and bone 2013: the main changes compared to the 3rd edition].

    PubMed

    Zambo, Iva; Veselý, Karel

    2014-04-01

    In early 2013, the new classification of tumours of soft tissue and bones was released. This edition belongs to the fourth series of so-called Blue Books published under the auspices of the World Health Organisation (WHO). The current classification follows the previous third edition, from which it differs in several aspects. The vast majority of changes are related to the soft tissue tumour section, which was enriched with three new chapters, some entities or terms were removed, new diagnoses were introduced, and several tumours were reallocated to other categories. Albeit to a lesser extent, similar changes have occurred also in the classification of bone tumours. Compared to the previous edition, more detailed molecular and cytogenetic data were incorporated in the current issue. The rapidly increasing knowledge of the genetics of mesenchymal tumours allows us to make more accurate diagnoses as well as to better understand of the pathogenesis of these lesions. However, abundant molecular and cytogenetic data highlight an increasing problem of growing numbers of genetic overlaps even among quite different tumours. The coexistence of several grading systems of soft tissue tumours is another controversial issue mentioned in the recent WHO classification. The main advantages and limitations of the two most widely used grading systems are also discussed.

  7. MicroRNA-based molecular classification of non-BRCA1/2 hereditary breast tumours

    PubMed Central

    Tanic, M; Andrés, E; M Rodriguez-Pinilla, S; Marquez-Rodas, I; Cebollero-Presmanes, M; Fernandez, V; Osorio, A; Benítez, J; Martinez-Delgado, B

    2013-01-01

    Background: Hereditary breast cancer comprises 5–10% of all breast cancers. Mutations in two high-risk susceptibility genes, BRCA1 and BRCA2, along with rare intermediate-risk genes and common low-penetrance alleles identified, altogether explain no more than 45% of the high-risk breast cancer families, although the majority of cases are unaccounted for and are designated as BRCAX tumours. Micro RNAs have called great attention for classification of different cancer types and have been implicated in a range of important biological processes and are deregulated in cancer pathogenesis. Methods: Here we have performed an exploratory hypothesis-generating study of miRNA expression profiles in a large series of 66 primary hereditary breast tumours by microarray analysis. Results: Unsupervised clustering analysis of miRNA molecular profiles revealed distinct subgroups of BRCAX tumours, ‘normal-like' BRCAX-A, ‘proliferative' BRCAX-B, ‘BRCA1/2-like' BRCAX-C and ‘undefined' BRCAX-D subgroup. These findings introduce a new insight in the biology of hereditary breast cancer, defining specific BRCAX subgroups, which could help in the search for novel susceptibility pathways in hereditary breast cancer. Conclusion: Our data demonstrate that BRCAX hereditary breast tumours can be sub-classified into four previously unknown homogenous groups characterised by specific miRNA expression signatures and histopathological features. PMID:24104964

  8. Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis†

    PubMed Central

    Gajjar, Ketan; Heppenstall, Lara D.; Pang, Weiyi; Ashton, Katherine M.; Trevisan, Júlio; Patel, Imran I.; Llabjani, Valon; Stringfellow, Helen F.; Martin-Hirsch, Pierre L.; Dawson, Timothy; Martin, Francis L.

    2013-01-01

    The most common initial treatment received by patients with a brain tumour is surgical removal of the growth. Precise histopathological diagnosis of brain tumours is to some extent subjective. Furthermore, currently available diagnostic imaging techniques to delineate the excision border during cytoreductive surgery lack the required spatial precision to aid surgeons. We set out to determine whether infrared (IR) and/or Raman spectroscopy combined with multivariate analysis could be applied to discriminate between normal brain tissue and different tumour types (meningioma, glioma and brain metastasis) based on the unique spectral “fingerprints” of their biochemical composition. Formalin-fixed paraffin-embedded tissue blocks of normal brain and different brain tumours were de-waxed, mounted on low-E slides and desiccated before being analyzed using attenuated total reflection Fourier-transform IR (ATR-FTIR) and Raman spectroscopy. ATR-FTIR spectroscopy showed a clear segregation between normal and different tumour subtypes. Discrimination of tumour classes was also apparent with Raman spectroscopy. Further analysis of spectral data revealed changes in brain biochemical structure associated with different tumours. Decreased tentatively-assigned lipid-to-protein ratio was associated with increased tumour progression. Alteration in cholesterol esters-to-phenylalanine ratio was evident in grade IV glioma and metastatic tumours. The current study indicates that IR and/or Raman spectroscopy have the potential to provide a novel diagnostic approach in the accurate diagnosis of brain tumours and have potential for application in intra-operative diagnosis. PMID:24098310

  9. Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis.

    PubMed

    Gajjar, Ketan; Heppenstall, Lara D; Pang, Weiyi; Ashton, Katherine M; Trevisan, Júlio; Patel, Imran I; Llabjani, Valon; Stringfellow, Helen F; Martin-Hirsch, Pierre L; Dawson, Timothy; Martin, Francis L

    2012-09-06

    The most common initial treatment received by patients with a brain tumour is surgical removal of the growth. Precise histopathological diagnosis of brain tumours is to some extent subjective. Furthermore, currently available diagnostic imaging techniques to delineate the excision border during cytoreductive surgery lack the required spatial precision to aid surgeons. We set out to determine whether infrared (IR) and/or Raman spectroscopy combined with multivariate analysis could be applied to discriminate between normal brain tissue and different tumour types (meningioma, glioma and brain metastasis) based on the unique spectral "fingerprints" of their biochemical composition. Formalin-fixed paraffin-embedded tissue blocks of normal brain and different brain tumours were de-waxed, mounted on low-E slides and desiccated before being analyzed using attenuated total reflection Fourier-transform IR (ATR-FTIR) and Raman spectroscopy. ATR-FTIR spectroscopy showed a clear segregation between normal and different tumour subtypes. Discrimination of tumour classes was also apparent with Raman spectroscopy. Further analysis of spectral data revealed changes in brain biochemical structure associated with different tumours. Decreased tentatively-assigned lipid-to-protein ratio was associated with increased tumour progression. Alteration in cholesterol esters-to-phenylalanine ratio was evident in grade IV glioma and metastatic tumours. The current study indicates that IR and/or Raman spectroscopy have the potential to provide a novel diagnostic approach in the accurate diagnosis of brain tumours and have potential for application in intra-operative diagnosis.

  10. Highlights of Children with Cancer UK’s Workshop on Drug Delivery in Paediatric Brain Tumours

    PubMed Central

    Nailor, Audrey; Walker, David A; Jacques, Thomas S; Warren, Kathy E; Brem, Henry; Kearns, Pamela R; Greenwood, John; Penny, Jeffrey I; Pilkington, Geoffrey J; Carcaboso, Angel M; Fleischhack, Gudrun; Macarthur, Donald; Slavc, Irene; Meijer, Lisethe; Gill, Steven; Lowis, Stephen; van Vuurden, Dannis G; Pearl, Monica S; Clifford, Steven C; Morrissy, Sorana; Ivanov, Delyan P; Beccaria, Kévin; Gilbertson, Richard J; Straathof, Karin; Green, Jordan J; Smith, Stuart; Rahman, Ruman; Kilday, John-Paul

    2016-01-01

    The first Workshop on Drug Delivery in Paediatric Brain Tumours was hosted in London by the charity Children with Cancer UK. The goals of the workshop were to break down the barriers to treating central nervous system (CNS) tumours in children, leading to new collaborations and further innovations in this under-represented and emotive field. These barriers include the physical delivery challenges presented by the blood–brain barrier, the underpinning reasons for the intractability of CNS cancers, and the practical difficulties of delivering cancer treatment to the brains of children. Novel techniques for overcoming these problems were discussed, new models brought forth, and experiences compared. PMID:27110286

  11. Linear accelerator radiosurgery in the management of brain tumours.

    PubMed

    Friedman, W A; Foote, K D

    2000-02-01

    Radiosurgery is an increasingly popular method for treating a variety of intracranial tumours. A great deal of treatment data has been accumulated suggesting that radiosurgery may be the treatment of choice for small acoustic schwannomas. Moreover, radiosurgery promises excellent tumour control and minimal risk in the treatment of small meningiomas in risky surgical locations such as the cavernous sinus. Radiosurgery offers superior local control rates for many metastatic neoplasms and has promise as an adjuvant 'boost' technique in certain malignant gliomas. This article presents a brief description of the linear accelerator, LINAC, radiosurgical technique, followed by a review of the more common applications of stereotactic radiosurgery in the treatment of intracranial neoplastic disease.

  12. Hormonal modulation of brain tumour growth: a cell culture study.

    PubMed

    Gibelli, N; Zibera, C; Butti, G; Assietti, R; Sica, G; Scerrati, M; Iacopino, F; Roselli, R; Paoletti, P; Robustelli della Cuna, G

    1989-01-01

    Tissue samples derived from two neuroepithelial tumours and five meningiomas were obtained at surgery from seven patients and cultured in order to study the effect of dexamethasone (DEX) and testosterone acetate (TA) on cell proliferation. Glucocorticoid and androgen receptors (GR, AR) were determined both on tissue samples (7 cases) and on five out of the seven cell cultures obtained by tumours. GR and AR were present respectively in 5 and in 4 out of the tumour specimens assayed and in 4/5 and 2/3 of the tested cell cultures. DEX activity on cell growth was tested on six cell cultures. Four of them showed a significant growth inhibition at the highest drug concentration. On the contrary, a significant growth stimulation was observed in four out of the five cultures, where GR were present, using low hormone concentrations. Treatment with pharmacological doses of TA caused a significant cytotoxicity in all the tested cultures. Low TA concentrations inhibited cell growth in one out of the two cell cultures which contained AR, but were ineffective in cultures lacking AR. Our preliminary results suggest a possible role in growth regulation by DEX and TA in intracranial tumours, on the basis of the presence of specific hormone receptors.

  13. Adaptive multiclass classification for brain computer interfaces.

    PubMed

    Llera, A; Gómez, V; Kappen, H J

    2014-06-01

    We consider the problem of multiclass adaptive classification for brain-computer interfaces and propose the use of multiclass pooled mean linear discriminant analysis (MPMLDA), a multiclass generalization of the adaptation rule introduced by Vidaurre, Kawanabe, von Bünau, Blankertz, and Müller (2010) for the binary class setting. Using publicly available EEG data sets and tangent space mapping (Barachant, Bonnet, Congedo, & Jutten, 2012) as a feature extractor, we demonstrate that MPMLDA can significantly outperform state-of-the-art multiclass static and adaptive methods. Furthermore, efficient learning rates can be achieved using data from different subjects.

  14. Mutation analysis of the p73 gene in nonastrocytic brain tumours

    PubMed Central

    Alonso, M E; Bello, M J; Gonzalez-Gomez, P; Lomas, J; Arjona, D; Campos, J M de; Kusak, M E; Sarasa, J L; Isla, A; Rey, J A

    2001-01-01

    Loss of heterozygosity (LOH) involving the distal chromosome 1p36region occurs frequently in nonastrocytic brain tumours, but the tumour suppressor gene targeted by this deletion is unknown. p73is a novel gene that has high sequence homology and similar gene structure to thep53 gene; it has been mapped to 1p36, and may thus represent a candidate for this tumour suppressor gene. To determine whether p73is involved in nonastrocytic brain tumour development, we analysed 65 tumour samples including 26 oligodendrogliomas, 4 ependymomas, 5 medulloblastomas, 10 meningiomas, 2 meningeal haemangiopericytomas, 2 neurofibrosarcomas, 3 primary lymphomas, 8 schwannomas and 5 metastatic tumours to the brain, for p73 alterations. Characterization of allelic loss at 1p36–p35 showed LOH in about 50% of cases, primarily involving oligodendroglial tumours (22 of 26 cases analysed; 85%) and meningiomas (4 of 10; 40%). PCR-SSCP and direct DNA sequencing of exons 2 to 14 of p73 revealed a missense mutation in one primary lymphoma: a G-to-A transition, with Glu291Lys change. 8 additional cases displayed no tumour-specific alterations, as 3 distinct polymorphic changes were identified: a double polymorphic change of exon 5 was found in one ependymoma and both samples derived from an oligodendroglioma, as follows: a G-to-A transition with no change in Pro 146, and a C-to-T variation with no change in Asn 204: a delG at exon 3/+12 position was identified in 4 samples corresponding to 2 oligodendrogliomas, 1 ependymoma and 1 meningioma, and a C-to-T change at exon 2/+10 position was present in a metastatic tumour. Although both LOH at 1p36 and p73 sequence changes were evidenced in 4 cases, it is difficult to establish a causal role of the p73 variations and nonastrocytic brain tumours development. © 2001 Cancer Research Campaign http://www.bjcancer.com PMID:11461077

  15. Outcomes of low-molecular-weight heparin treatment for venous thromboembolism in patients with primary and metastatic brain tumours.

    PubMed

    Chai-Adisaksopha, Chatree; Linkins, Lori-Ann; ALKindi, Said Y; Cheah, Matthew; Crowther, Mark A; Iorio, Alfonso

    2017-02-28

    Venous thromboembolism (VTE) is one of the most common complications in patients with brain tumours. There is limited data available in the literature on VTE treatment in these patients. We conducted a matched retrospective cohort study of patients with primary or metastatic brain cancer who were diagnosed with cancer-associated VTE. Patients were selected after a retrospective chart review of consecutive patients who were diagnosed with cancer-associated VTE between January 2010 and January 2014 at the Juravinski Thrombosis Clinic, Hamilton, Canada. Controls were age- and gender-matched patients with cancer-associated VTE from the same cohort, but without known brain tumours. A total of 364 patients with cancer-associated VTE were included (182 with primary or metastatic brain tumours and 182 controls). The median follow-up duration was 6.7 (interquartile range 2.5-15.8) months. The incidence rate of recurrent VTE was 11.0 per 100 patient-years (95 % CI; 6.7-17.9) in patients with brain tumours and 13.5 per 100 patient-years (95 % CI; 9.3-19.7) in non-brain tumour group. The incidence of major bleeding was 8.6 per 100 (95 % CI; 4.8-14.7) patient-years in patients with brain tumours versus 5.0 per 100 patient-years (95 % CI; 2.8-9.2) in controls. Rate of intracranial bleeding was higher in brain tumour patients (4.4 % vs 0 %, p-value=0.004). In summary, rates of recurrent VTE and major bleeding were not significantly different in patients with cancer-associated VTE in the setting of primary or metastatic brain tumours compared those without known brain tumours. However, greater numbers of intracranial bleeds were observed in patients with brain tumours.

  16. The World Health Organization 2016 classification of testicular germ cell tumours: a review and update from the International Society of Urological Pathology Testis Consultation Panel.

    PubMed

    Williamson, Sean R; Delahunt, Brett; Magi-Galluzzi, Cristina; Algaba, Ferran; Egevad, Lars; Ulbright, Thomas M; Tickoo, Satish K; Srigley, John R; Epstein, Jonathan I; Berney, Daniel M

    2017-02-01

    Since the last World Health Organization (WHO) classification scheme for tumours of the urinary tract and male genital organs, there have been a number of advances in the understanding, classification, immunohistochemistry and genetics of testicular germ cell tumours. The updated 2016 draft classification was discussed at an International Society of Urological Pathology Consultation on Testicular and Penile Cancer. This review addresses the main updates to germ cell tumour classification. Major changes include a pathogenetically derived classification using germ cell neoplasia in situ (GCNIS) as a new name for the precursor lesion, and the distinction of prepubertal tumours (non-GCNIS-derived) from postpubertal-type tumours (GCNIS-derived), acknowledging the existence of rare benign prepubertal-type teratomas in the postpubertal testis. Spermatocytic tumour is adopted as a replacement for spermatocytic seminoma, to avoid potential confusion with the unrelated usual seminoma. The spectrum of trophoblastic tumours arising in the setting of testicular germ cell tumour continues to expand, to include epithelioid and placental site trophoblastic tumours analogous to those of the gynaecological tract. Currently, reporting of anaplasia (seminoma or spermatocytic tumour) or immaturity (teratoma) is not required, as these do not have demonstrable prognostic importance. In contrast, overgrowth of a teratomatous component (somatic-type malignancy) and sarcomatous change in spermatocytic tumour indicate more aggressive behaviour, and should be reported.

  17. Neuro-oncology: Under-recognized mental incapacity in brain tumour patients.

    PubMed

    Bernstein, Mark

    2014-09-01

    Many patients with brain tumours possess inadequate mental capacity to provide informed consent, but this situation often goes undetected because clinicians do not routinely conduct formal cognitive assessments. This oversight should be recognized and rectified to enable optimum ethical and medical care of these vulnerable individuals.

  18. X-ray fluorescence study of the concentration of selected trace and minor elements in human brain tumours

    NASA Astrophysics Data System (ADS)

    Wandzilak, Aleksandra; Czyzycki, Mateusz; Radwanska, Edyta; Adamek, Dariusz; Geraki, Kalotina; Lankosz, Marek

    2015-12-01

    Neoplastic and healthy brain tissues were analysed to discern the changes in the spatial distribution and overall concentration of elements using micro X-ray fluorescence spectroscopy. High-resolution distribution maps of minor and trace elements such as P, S, Cl, K, Ca, Fe, Cu and Zn made it possible to distinguish between homogeneous cancerous tissue and areas where some structures could be identified, such as blood vessels and calcifications. Concentrations of the elements in the selected homogeneous areas of brain tissue were compared between tumours with various malignancy grades and with the controls. The study showed a decrease in the average concentration of Fe, P, S and Ca in tissues with high grades of malignancy as compared to the control group, whereas the concentration of Zn in these tissues was increased. The changes in the concentration were found to be correlated with the tumour malignancy grade. The efficacy of micro X-ray fluorescence spectroscopy to distinguish between various types of cancer based on the concentrations of studied elements was confirmed by multivariate discriminant analysis. Our analysis showed that the most important elements for tissue classification are Cu, K, Fe, Ca, and Zn. This method made it possible to correctly classify histopathological types in 99.93% of the cases used to build the model and in as much as 99.16% of new cases.

  19. Local Kernel for Brains Classification in Schizophrenia

    NASA Astrophysics Data System (ADS)

    Castellani, U.; Rossato, E.; Murino, V.; Bellani, M.; Rambaldelli, G.; Tansella, M.; Brambilla, P.

    In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining local measurements with non linear Support Vector Machine. Instead of considering a voxel-by-voxel comparison between patients and controls, we focus on landmark points which are characterized by local region descriptors, namely Scale Invariance Feature Transform (SIFT). Then, matching is obtained by introducing the local kernel for which the samples are represented by unordered set of features. Moreover, a new weighting approach is proposed to take into account the discriminative relevance of the detected groups of features. Experiments have been performed including a set of 54 patients with schizophrenia and 54 normal controls on which region of interest (ROI) have been manually traced by experts. Preliminary results on Dorso-lateral PreFrontal Cortex (DLPFC) region are promising since up to 75% of successful classification rate has been obtained with this technique and the performance has improved up to 85% when the subjects have been stratified by sex.

  20. Transient Global Amnesia and Brain Tumour: Chance Concurrence or Aetiological Association? Case Report and Systematic Literature Review

    PubMed Central

    Milburn-McNulty, Phil; Larner, Andrew J.

    2015-01-01

    We report a patient presenting with episodes of transient amnesia, some with features suggestive of transient global amnesia (TGA), and some more reminiscent of transient epileptic amnesia. Investigation with neuroimaging revealed an intrinsic lesion in the right amygdala, with features suggestive of low-grade neoplasia. We undertook a systematic review of the literature on TGA and brain tumour. Fewer than 20 cases were identified, some of which did not conform to the clinical diagnostic criteria for TGA. Hence, the concurrence of brain tumour and TGA is very rare and of doubtful aetiological relevance. In some brain tumour-associated cases, epilepsy may be masquerading as TGA. PMID:25802501

  1. Development of a positron probe for localization and excision of brain tumours during surgery

    NASA Astrophysics Data System (ADS)

    Bogalhas, F.; Charon, Y.; Duval, M.-A.; Lefebvre, F.; Palfi, S.; Pinot, L.; Siebert, R.; Ménard, L.

    2009-07-01

    The survival outcome of patients suffering from gliomas is directly linked to the complete surgical resection of the tumour. To help the surgeons to delineate precisely the boundaries of the tumour, we developed an intraoperative positron probe with background noise rejection capability. The probe was designed to be directly coupled to the excision tool such that detection and removal of the radiolabelled tumours could be simultaneous. The device consists of two exchangeable detection heads composed of clear and plastic scintillating fibres. Each head is coupled to an optic fibre bundle that exports the scintillating light to a photodetection and processing electronic module placed outside the operative wound. The background rejection method is based on a real-time subtraction technique. The measured probe sensitivity for 18F was 1.1 cps kBq-1 ml-1 for the small head and 3.4 cps kBq-1 ml-1 for the large head. The mean spatial resolution was 1.6 mm FWHM on the detector surface. The γ-ray rejection efficiency measured by realistic brain phantom modelling of the surgical cavity was 99.4%. This phantom also demonstrated the ability of the probe to detect tumour discs as small as 5 mm in diameter (20 mg) for tumour-to-background ratios higher than 3:1 and with an acquisition time around 4 s at each scanning step. These results indicate that our detector could be a useful complement to existing techniques for the accurate excision of brain tumour tissue and more generally to improve the efficiency of radio-guided cancer surgery.

  2. The creation of protection and hope in patients with malignant brain tumours.

    PubMed

    Salander, P; Bergenheim, T; Henriksson, R

    1996-04-01

    The malignant brain tumour disease condenses much of the anguish of cancer diseases. The brain is a vital and delicate organ, and the prognosis is generally unfavourable. The patient is exposed and has to rely on cognitive manoeuvres to manage the mental stress. The purpose of this study was to generate new insights into how the patient constructs a new sense of reality when confronted with the malignant brain tumour diagnosis. Within grounded theory methodology, 30 patients with malignant gliomas were interviewed twice, in direct connection with diagnosis, surgery and radiotherapy. In addition, their partners were interviewed, and quantitative instruments (SMMSE, RDCQ) were used as additional references for assessing the patients cognitively and emotionally. Eleven patients were excluded from the final analysis because of cognitive impairment of personality change. Most of the patients were aware of the fact that the brain tumour exposed them to grave danger, but they were also able to use various cognitive manoeuvres to create protection and hope. This process originated from different sources: the body; helpful relations; cognitive schemata; and the handling of information. The importance of the body to raise hope is emphasized. In the discussion we consider this process as an expression of how the patient brings together reality and hope, thus creating her/his own illusion. These findings are also related to adjacent psychoanalytic theory, proposing a theoretical reference with clinical implications when discussing "What to tell cancer patients."

  3. Plumbagin alters telomere dynamics, induces DNA damage and cell death in human brain tumour cells.

    PubMed

    Khaw, Aik Kia; Sameni, Safoura; Venkatesan, Shriram; Kalthur, Guruprasad; Hande, M Prakash

    2015-11-01

    Natural plant products may possess much potential in palliative therapy and supportive strategies of current cancer treatments with lesser cytotoxicity to normal cells compared to conventional chemotherapy. In the current study, anti-cancer properties of plumbagin, a plant-derived naphthoquinone, on brain cancer cells were determined. Plumbagin treatment resulted in the induction of DNA damage, cell cycle arrest and apoptosis, followed by suppression of the colony forming ability of the brain tumour cells. These effects were substantiated by upregulation of PTEN, TNFRSF1A and downregulation of E2F1 genes, along with a drop in MDM2, cyclin B1, survivin and BCL2 protein expression. Plumbagin induced elevated levels of caspase-3/7 activity as well. For the first time, we show here that plumbagin inhibits telomerase in brain tumour cells and results in telomere shortening following chronic long-term treatment. This observation implies considerable cytotoxicity of plumbagin towards cancer cells with higher telomerase activity. Collectively, our findings suggest plumbagin as a potential chemotherapeutic phytochemical in brain tumour treatment modalities.

  4. Occupational exposure to extremely low frequency magnetic fields and brain tumour risks in the INTEROCC study

    PubMed Central

    Turner, Michelle C; Benke, Geza; Bowman, Joseph D; Figuerola, Jordi; Fleming, Sarah; Hours, Martine; Kincl, Laurel; Krewski, Daniel; McLean, Dave; Parent, Marie-Elise; Richardson, Lesley; Sadetzki, Siegal; Schlaefer, Klaus; Schlehofer, Brigitte; Schüz, Joachim; Siemiatycki, Jack; van Tongeren, Martie; Cardis, Elisabeth

    2014-01-01

    Background Occupational exposure to extremely low frequency magnetic fields (ELF) is a suspected risk factor for brain tumours, however the literature is inconsistent. Few studies have assessed whether ELF in different time windows of exposure may be associated with specific histologic types of brain tumours. This study examines the association between ELF and brain tumours in the large-scale INTEROCC study. Methods Cases of adult primary glioma and meningioma were recruited in seven countries (Australia, Canada, France, Germany, Israel, New Zealand, United Kingdom) between 2000 and 2004. Estimates of mean workday ELF exposure based on a job exposure matrix assigned. Estimates of cumulative exposure, average exposure, maximum exposure, and exposure duration were calculated for the lifetime, and 1–4, 5–9, and 10+ years prior to the diagnosis/reference date. Results There were 3,761 included brain tumour cases (1,939 glioma, 1,822 meningioma) and 5,404 population controls. There was no association between lifetime cumulative ELF exposure and glioma or meningioma risk. However, there were positive associations between cumulative ELF 1–4 years prior to the diagnosis/reference date and glioma (odds ratio (OR) ≥ 90th percentile vs < 25th percentile = 1.67, 95% confidence interval (CI) 1.36–2.07, p < 0.0001 linear trend), and, somewhat weaker associations with meningioma (OR ≥ 90th percentile vs < 25th percentile = 1.23, 95% CI 0.97–1.57, p = 0.02 linear trend). Conclusions Results showed positive associations between ELF in the recent past and glioma. Impact Occupational ELF exposure may play a role in the later stages (promotion and progression) of brain tumourigenesis. PMID:24935666

  5. Classification of CT brain images based on deep learning networks.

    PubMed

    Gao, Xiaohong W; Hui, Rui; Tian, Zengmin

    2017-01-01

    While computerised tomography (CT) may have been the first imaging tool to study human brain, it has not yet been implemented into clinical decision making process for diagnosis of Alzheimer's disease (AD). On the other hand, with the nature of being prevalent, inexpensive and non-invasive, CT does present diagnostic features of AD to a great extent. This study explores the significance and impact on the application of the burgeoning deep learning techniques to the task of classification of CT brain images, in particular utilising convolutional neural network (CNN), aiming at providing supplementary information for the early diagnosis of Alzheimer's disease. Towards this end, three categories of CT images (N = 285) are clustered into three groups, which are AD, lesion (e.g. tumour) and normal ageing. In addition, considering the characteristics of this collection with larger thickness along the direction of depth (z) (~3-5 mm), an advanced CNN architecture is established integrating both 2D and 3D CNN networks. The fusion of the two CNN networks is subsequently coordinated based on the average of Softmax scores obtained from both networks consolidating 2D images along spatial axial directions and 3D segmented blocks respectively. As a result, the classification accuracy rates rendered by this elaborated CNN architecture are 85.2%, 80% and 95.3% for classes of AD, lesion and normal respectively with an average of 87.6%. Additionally, this improved CNN network appears to outperform the others when in comparison with 2D version only of CNN network as well as a number of state of the art hand-crafted approaches. As a result, these approaches deliver accuracy rates in percentage of 86.3, 85.6 ± 1.10, 86.3 ± 1.04, 85.2 ± 1.60, 83.1 ± 0.35 for 2D CNN, 2D SIFT, 2D KAZE, 3D SIFT and 3D KAZE respectively. The two major contributions of the paper constitute a new 3-D approach while applying deep learning technique to extract signature information

  6. Childhood brain tumour risk and its association with wireless phones: a commentary.

    PubMed

    Söderqvist, Fredrik; Carlberg, Michael; Hansson Mild, Kjell; Hardell, Lennart

    2011-12-19

    Case-control studies on adults point to an increased risk of brain tumours (glioma and acoustic neuroma) associated with the long-term use of mobile phones. Recently, the first study on mobile phone use and the risk of brain tumours in children and adolescents, CEFALO, was published. It has been claimed that this relatively small study yielded reassuring results of no increased risk. We do not agree. We consider that the data contain several indications of increased risk, despite low exposure, short latency period, and limitations in the study design, analyses and interpretation. The information certainly cannot be used as reassuring evidence against an association, for reasons that we discuss in this commentary.

  7. Lessons from brain mapping in surgery for low-grade glioma: insights into associations between tumour and brain plasticity.

    PubMed

    Duffau, Hugues

    2005-08-01

    Surgical treatment of low-grade gliomas (LGGs) aims to maximise the amount of tumour tissue resected, while minimising the risk of functional sequelae. In this review I address the issue of how to reconcile these two conflicting goals. First, I review the natural history of LGG-growth, invasion, and anaplastic transformation. Second, I discuss the contribution of new techniques, such as functional mapping, to our understanding of brain reorganisation in response to progressive growth of LGG. Third, I consider the clinical implications of interactions between tumour progression and brain plasticity. In particular, I show how longitudinal studies (preoperative, intraoperative, and postoperative) could allow us to optimise the surgical risk-to-benefit ratios. I will also discuss controversial issues such as defining surgical indications for LGGs, predicting the risk of postoperative deficit, aspects of operative surgical neuro-oncology (eg, preoperative planning and preservation of functional areas and tracts), and postoperative functional recovery.

  8. Classification of CT-brain slices based on local histograms

    NASA Astrophysics Data System (ADS)

    Avrunin, Oleg G.; Tymkovych, Maksym Y.; Pavlov, Sergii V.; Timchik, Sergii V.; Kisała, Piotr; Orakbaev, Yerbol

    2015-12-01

    Neurosurgical intervention is a very complicated process. Modern operating procedures based on data such as CT, MRI, etc. Automated analysis of these data is an important task for researchers. Some modern methods of brain-slice segmentation use additional data to process these images. Classification can be used to obtain this information. To classify the CT images of the brain, we suggest using local histogram and features extracted from them. The paper shows the process of feature extraction and classification CT-slices of the brain. The process of feature extraction is specialized for axial cross-section of the brain. The work can be applied to medical neurosurgical systems.

  9. Profile of a Malignant Brain Tumour in Jamaica: An Eight-year Review, 2005 to 2012

    PubMed Central

    Johnson, P; Jaggon, JR; Campbell, J; Bruce, C; Ferron-Boothe, D; James, K; Crandon, I; Eldemire-Shearer, D

    2015-01-01

    ABSTRACT Objective: Glioblastoma multiforme (GBM) is the most malignant and most common primary brain tumour worldwide. This study was undertaken to investigate the demographics of this tumour in Jamaica as there is to date no such published data. Data from the recently started Intracranial Tumour Registry (ITR) at the University Hospital of the West Indies was used. Methods: All cases of GBM entered into the ITR between 2005 and 2012 were gathered. Of these, only patients with pathologically proven diagnoses were entered into the study. Demographic data, including age and gender, were recorded. The distribution of the tumours by anatomic location was also documented. Results: Of the 602 patients entered into the ITR up to that time, 42 were found to have histologically proven GBM with a male to female ratio of 2.2:1. There was an age range of 8–92 years with a mean age of diagnosis of 48 years. The majority of the tumours (66.7%) occurred in the left cerebral hemisphere with the most common lobe being the temporal lobe. Two patients (4.8%) had lesions spanning both hemispheres. Conclusions: This preliminary study reveals that there is a similar gender distribution of GBM within our population compared with the rest of the world. It, however, revealed that the mean age of diagnosis in our population (48 years) is lower than that quoted in the worldwide literature (53 to 64 years). One possible explanation for this is the possibility that many of our GBMs are actually secondary tumours which are thought to arise from less malignant, undiagnosed precursors. The percentage of GBMs occurring in the paediatric population was similar to the rest of the world. PMID:26624590

  10. A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

    PubMed

    Nanthagopal, A Padma; Rajamony, R Sukanesh

    2012-07-01

    The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

  11. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Paragangliomas.

    PubMed

    Williams, Michelle D; Tischler, Arthur S

    2017-03-01

    Updated editions of The World Health Organization Classification of Tumours Pathology & Genetics for both Head and Neck Tumours and Tumours of Endocrine Organs took place in 2016 based on consensus conferences. These editions present unification of concepts in paragangliomas and highlight expanding knowledge of their etiology. There is a major emphasis in the new bluebooks on familial/syndromic paragangliomas, representing ~40% of all head and neck paragangliomas. Ancillary use of immunohistochemical evaluation, specifically of SDHB, allows the pathologist to screen for a large subset of these potentially hereditary cases. In addition, similarly to other neuroendocrine tumors, paragangliomas are now considered to represent a continuum of risk, and are assessed in terms of risk stratification. Tumors with SDHB mutations pose the highest risk for metastasis. There is currently no validated or endorsed histologic grading system. Paragangliomas remain tumors of undetermined biologic potential and should not be termed benign.

  12. Intracavitary moderator balloon combined with 252Cf brachytherapy and boron neutron capture therapy, improving dosimetry in brain tumour and infiltrations

    PubMed Central

    Brandão, S F

    2015-01-01

    Objective: This article proposes a combination of californium-252 (252Cf) brachytherapy, boron neutron capture therapy (BNCT) and an intracavitary moderator balloon catheter applied to brain tumour and infiltrations. Methods: Dosimetric evaluations were performed on three protocol set-ups: 252Cf brachytherapy combined with BNCT (Cf-BNCT); Cf-BNCT with a balloon catheter filled with light water (LWB) and the same set-up with heavy water (HWB). Results: Cf-BNCT-HWB has presented dosimetric advantages to Cf-BNCT-LWB and Cf-BNCT in infiltrations at 2.0–5.0 cm from the balloon surface. However, Cf-BNCT-LWB has shown superior dosimetry up to 2.0 cm from the balloon surface. Conclusion: Cf-BNCT-HWB and Cf-BNCT-LWB protocols provide a selective dose distribution for brain tumour and infiltrations, mainly further from the 252Cf source, sparing the normal brain tissue. Advances in knowledge: Malignant brain tumours grow rapidly and often spread to adjacent brain tissues, leading to death. Improvements in brain radiation protocols have been continuously achieved; however, brain tumour recurrence is observed in most cases. Cf-BNCT-LWB and Cf-BNCT-HWB represent new modalities for selectively combating brain tumour infiltrations and metastasis. PMID:25927876

  13. Mobile phone use, exposure to radiofrequency electromagnetic field, and brain tumour: a case-control study.

    PubMed

    Takebayashi, T; Varsier, N; Kikuchi, Y; Wake, K; Taki, M; Watanabe, S; Akiba, S; Yamaguchi, N

    2008-02-12

    In a case-control study in Japan of brain tumours in relation to mobile phone use, we used a novel approach for estimating the specific absorption rate (SAR) inside the tumour, taking account of spatial relationships between tumour localisation and intracranial radiofrequency distribution. Personal interviews were carried out with 88 patients with glioma, 132 with meningioma, and 102 with pituitary adenoma (322 cases in total), and with 683 individually matched controls. All maximal SAR values were below 0.1 W kg(-1), far lower than the level at which thermal effects may occur, the adjusted odds ratios (ORs) for regular mobile phone users being 1.22 (95% confidence interval (CI): 0.63-2.37) for glioma and 0.70 (0.42-1.16) for meningioma. When the maximal SAR value inside the tumour tissue was accounted for in the exposure indices, the overall OR was again not increased and there was no significant trend towards an increasing OR in relation to SAR-derived exposure indices. A non-significant increase in OR among glioma patients in the heavily exposed group may reflect recall bias.

  14. Brain Tumour Segmentation based on Extremely Randomized Forest with high-level features.

    PubMed

    Pinto, Adriano; Pereira, Sergio; Correia, Higino; Oliveira, J; Rasteiro, Deolinda M L D; Silva, Carlos A

    2015-08-01

    Gliomas are among the most common and aggressive brain tumours. Segmentation of these tumours is important for surgery and treatment planning, but also for follow-up evaluations. However, it is a difficult task, given that its size and locations are variable, and the delineation of all tumour tissue is not trivial, even with all the different modalities of the Magnetic Resonance Imaging (MRI). We propose a discriminative and fully automatic method for the segmentation of gliomas, using appearance- and context-based features to feed an Extremely Randomized Forest (Extra-Trees). Some of these features are computed over a non-linear transformation of the image. The proposed method was evaluated using the publicly available Challenge database from BraTS 2013, having obtained a Dice score of 0.83, 0.78 and 0.73 for the complete tumour, and the core and the enhanced regions, respectively. Our results are competitive, when compared against other results reported using the same database.

  15. Relaxation time based classification of magnetic resonance brain images

    NASA Astrophysics Data System (ADS)

    Baselice, Fabio; Ferraioli, Giampaolo; Pascazio, Vito

    2015-03-01

    Brain tissue classification in Magnetic Resonance Imaging is useful for a wide range of applications. Within this manuscript a novel approach for brain tissue joint segmentation and classification is presented. Starting from the relaxation time estimation, we propose a novel method for identifying the optimal decision regions. The approach exploits the statistical distribution of the involved signals in the complex domain. The technique, compared to classical threshold based ones, is able to improve the correct classification rate. The effectiveness of the approach is evaluated on a simulated case study.

  16. Intraoperative probe detecting β- decays in brain tumour radio-guided surgery

    NASA Astrophysics Data System (ADS)

    Solfaroli Camillocci, E.; Bocci, V.; Chiodi, G.; Collamati, F.; Donnarumma, R.; Faccini, R.; Mancini Terracciano, C.; Marafini, M.; Mattei, I.; Muraro, S.; Recchia, L.; Rucinski, A.; Russomando, A.; Toppi, M.; Traini, G.; Morganti, S.

    2017-02-01

    Radio-guided surgery (RGS) is a technique to intraoperatively detect tumour remnants, favouring a radical resection. Exploiting β- emitting tracers provides a higher signal to background ratio compared to the established technique with γ radiation, allowing the extension of the RGS applicability range. We developed and tested a detector based on para-terphenyl scintillator with high sensitivity to low energy electrons and almost transparent to γs to be used as intraoperative probe for RGS with β- emitting tracer. Portable read out electronics was customised to match the surgeon needs. This probe was used for preclinical test on specific phantoms and a test on ;ex vivo; specimens from patients affected by meningioma showing very promising results for the application of this new technique on brain tumours. In this paper, the prototype of the intraoperative probe and the tests are discussed; then, the results on meningioma are used to make predictions on the performance of the probe detecting residuals of a more challenging and more interesting brain tumour: the glioma.

  17. Metastatic ovarian carcinoma to the brain: an approach to identification and classification for neuropathologists.

    PubMed

    Nafisi, Houman; Cesari, Matthew; Karamchandani, Jason; Balasubramaniam, Gayathiri; Keith, Julia Lee

    2015-04-01

    Brain metastasis is an uncommon but increasing manifestation of ovarian epithelial carcinoma and neuropathologists' collective experience with these tumors is limited. We present clinicopathological characteristics of 13 cases of brain metastases from ovarian epithelial carcinoma diagnosed at two academic institutions. The mean ages at diagnosis of the ovarian carcinoma and their subsequent brain metastases were 58.7 and 62.8 years, respectively. At the time of initial diagnosis of ovarian carcinoma the majority of patients had an advanced stage and none had brain metastases as their first manifestation of malignancy. Brain metastases tended to be multiple with ring-enhancing features on neuroimaging. Primary tumors and their brain metastases were all high-grade histologically and the histologic subtypes were: nine high-grade serous carcinoma (HGSC) cases, two clear cell carcinoma (CCC) cases and a single case each of carcinosarcoma and high-grade adenocarcinoma. A recommended histo- and immunopathological approach to these tumours are provided to aid neuropathologists in the recognition and classification of metastatic ovarian carcinoma to the brain.

  18. Gene expression-based classifications of fibroadenomas and phyllodes tumours of the breast.

    PubMed

    Vidal, Maria; Peg, Vicente; Galván, Patricia; Tres, Alejandro; Cortés, Javier; Ramón y Cajal, Santiago; Rubio, Isabel T; Prat, Aleix

    2015-06-01

    Fibroepithelial tumors (FTs) of the breast are a heterogeneous group of lesions ranging from fibroadenomas (FAD) to phyllodes tumors (PT) (benign, borderline, malignant). Further understanding of their molecular features and classification might be of clinical value. In this study, we analysed the expression of 105 breast cancer-related genes, including the 50 genes of the PAM50 intrinsic subtype predictor and 12 genes of the Claudin-low subtype predictor, in a panel of 75 FTs (34 FADs, 5 juvenile FADs, 20 benign PTs, 5 borderline PTs and 11 malignant PTs) with clinical follow-up. In addition, we compared the expression profiles of FTs with those of 14 normal breast tissues and 49 primary invasive ductal carcinomas (IDCs). Our results revealed that the levels of expression of all breast cancer-related genes can discriminate the various groups of FTs, together with normal breast tissues and IDCs (False Discovery Rate < 5%). Among FTs, the levels expression of proliferation-related genes (e.g. CCNB1 and MKI67) and mesenchymal/epithelial-related (e.g. CLDN3 and EPCAM) genes were found to be most discriminative. As expected, FADs showed the highest and lowest expression of epithelial- and proliferation-related genes, respectively, whereas malignant PTs showed the opposite expression pattern. Interestingly, the overall profile of benign PTs was found more similar to FADs and normal breast tissues than the rest of tumours, including juvenile FADs. Within the dataset of IDCs and normal breast tissues, the vast majority of FADs, juvenile FADs, benign PTs and borderline PTs were identified as Normal-like by intrinsic breast cancer subtyping, whereas 7 (63.6%) and 3 (27.3%) malignant PTs were identified as Claudin-low and Basal-like, respectively. Finally, we observed that the previously described PAM50 risk of relapse prognostic score better predicted outcome in FTs than the morphological classification, even within PTs-only. Our results suggest that classification of FTs

  19. Walker 256 tumour cells increase substance P immunoreactivity locally and modify the properties of the blood-brain barrier during extravasation and brain invasion.

    PubMed

    Lewis, Kate M; Harford-Wright, Elizabeth; Vink, Robert; Nimmo, Alan J; Ghabriel, Mounir N

    2013-01-01

    It is not yet known how tumour cells traverse the blood-brain barrier (BBB) to form brain metastases. Substance P (SP) release is a key component of neurogenic inflammation which has been recently shown to increase the permeability of the BBB following CNS insults, making it a possible candidate as a mediator of tumour cell extravasation into the brain. This study investigated the properties of the BBB in the early stages of tumour cell invasion into the brain, and the possible involvement of SP. Male Wistar rats were injected with Walker 256 breast carcinoma cells via the internal carotid artery and euthanised at 1, 3, 6 and 9 days post tumour inoculation. Culture medium-injected animals served as controls at 1 and 9 days. Evidence of tumour cell extravasation across the BBB was first observed at 3 days post-inoculation, which corresponded with significantly increased albumin (p < 0.05) and SP immunoreactivity (p < 0.01) and significantly reduced endothelial barrier antigen labelling of microvessels when compared to culture medium control animals (p < 0.001). By day 9 after tumour cell inoculation, 100 % of animals developed large intracranial neoplasms that had significantly increased albumin in the peri-tumoral area (p < 0.001). The increased SP immunoreactivity and altered BBB properties at 3 days post-inoculation that coincided with early tumour invasion may be indicative of a mechanism for tumour cell extravasation into the brain. Thus, extravasation of tumour cells into the brain to form cerebral metastases may be a SP-mediated process.

  20. Clinical application of event related potentials in patients with brain tumours and traumatic head injuries.

    PubMed

    Olbrich, H M; Nau, H E; Zerbin, D; Lanczos, L; Lodemann, E; Engelmeier, M P; Grote, W

    1986-01-01

    Event related potential recording and psychometric evaluation of cognitive impairment were carried out on 21 patients with brain tumours, 21 patients with severe head injuries and 24 controls. The tumour and trauma patients who met the psychometric inclusion criteria for dementia, but not the non-demented patients, had significantly longer N2 and P3 latencies than the controls. In assessing individual patients P3 latency correctly differentiated between demented and non-demented patients in 81% of cases (for N2 latency 77%). Particularly P3 latency may provide a practical and objective measure of mental impairment in neurosurgical disorders producing dementia. Marked asymmetry in N2 and P3 amplitudes between hemispheres was observed in a number of cases. No significant relationship was found between diminution of N2 and P3 components and side of lesion.

  1. Update From the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Tumours of the Ear.

    PubMed

    Thompson, Lester D R

    2017-03-01

    The 2017 fourth edition of the World Health Organization Classification of Tumours, specifically as it relates to the ear (Chap. 9), has several changes. Importantly, the number of entities has been significantly reduced by omitting tumors or lesions if they do not occur exclusively or predominantly at this site or if they are discussed in detail elsewhere in the book. These entities include: embryonal rhabdomyosarcoma, osteoma, exostosis, angiolymphoid hyperplasia with eosinophilia, Schneiderian papilloma, inverted papilloma, lipoma of the internal auditory canal, hemangioma, hematolymphoid tumors, and secondary tumors. Paraganglioma was included in the neck chapter. New entries include otosclerosis and cholesteatoma, while refinements to nomenclature, classification and criteria were incorporated into the ceruminous gland tumors and epithelial tumors of the middle and inner ear. Specifically, the middle and inner ear were combined, as practical limitations of origin and imaging make a definitive separation artificial. The classification reflects the state of current understanding for these uncommon entities, with this update only highlighting selected entities that were the most significantly changed.

  2. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Odontogenic and Maxillofacial Bone Tumors.

    PubMed

    Wright, John M; Vered, Marilena

    2017-03-01

    The 4th edition of the World Health Organization's Classification of Head and Neck Tumours was published in January of 2017. This article provides a summary of the changes to Chapter 4 Tumours of the oral cavity and mobile tongue and Chapter 8 Odontogenic and maxillofacial bone tumours. Odontogenic cysts which were eliminated from the 3rd 2005 edition were included in the 4th edition as well as other unique allied conditons of the jaws. Many new tumors published since 2005 have been included in the 2017 classification.

  3. Tissue Tracking: Applications for Brain MRI Classification

    DTIC Science & Technology

    2007-01-01

    previous work on Bayesian classification algorithms. First, we present work by Haker et al.4 which outlines the general structure of Bayesian...groups have previously proposed Bayesian classification algorithms. Most relevant to our work is the work by Haker et al. on the tracking of objects in 2D...Segmentation,” Massachusetts Institute of Technology , 1999. 4. S. Haker , G. Sapiro, and A. Tannenbaum, “Knowledge-based segmentation of SAR data with

  4. Childhood brain tumours and use of mobile phones: comparison of a case-control study with incidence data.

    PubMed

    Aydin, Denis; Feychting, Maria; Schüz, Joachim; Röösli, Martin

    2012-05-20

    The first case-control study on mobile phone use and brain tumour risk among children and adolescents (CEFALO study) has recently been published. In a commentary published in Environmental Health, Söderqvist and colleagues argued that CEFALO suggests an increased brain tumour risk in relation to wireless phone use. In this article, we respond and show why consistency checks of case-control study results with observed time trends of incidence rates are essential, given the well described limitations of case-control studies and the steep increase of mobile phone use among children and adolescents during the last decade. There is no plausible explanation of how a notably increased risk from use of wireless phones would correspond to the relatively stable incidence time trends for brain tumours among children and adolescents observed in the Nordic countries. Nevertheless, an increased risk restricted to heavy mobile phone use, to very early life exposure, or to rare subtypes of brain tumours may be compatible with stable incidence trends at this time and thus further monitoring of childhood brain tumour incidence rate time trends is warranted.

  5. The World Health Organization 2016 classification of testicular non-germ cell tumours: a review and update from the International Society of Urological Pathology Testis Consultation Panel.

    PubMed

    Idrees, Muhammad T; Ulbright, Thomas M; Oliva, Esther; Young, Robert H; Montironi, Rodolfo; Egevad, Lars; Berney, Daniel; Srigley, John R; Epstein, Jonathan I; Tickoo, Satish K

    2017-03-01

    The World Health Organization (WHO) released a new tumour classification for the genitourinary system in early 2016 after consensus by pathologists with expertise in these organs. It utilized the framework of the 2004 classification, and incorporated the most up-to-date information concerning these tumours. In testicular tumours, the majority of the changes occurred in the nomenclature and classification of germ cell tumours; however, several modifications were also made for non-germ cell tumours. Among sex cord-stromal tumours, sclerosing Sertoli cell tumour (SCT) is no longer recognized as a separate entity but as a morphological variant of SCT not otherwise specified (NOS), as CTNNB1 gene mutations have been noted in both neoplasms but not in the other forms of SCT. Similarly, the lipid cell variant is not separately classified, but is considered to be a morphological variant of SCT NOS. Large-cell calcifying SCT is recognized as a distinct entity that occurs either sporadically or in association with Carney complex, with the latter patients having a distinct germline PRKAR1A gene mutation. Intratubular large-cell hyalinizing Sertoli cell neoplasia is also accepted as a separate entity linked with Peutz-Jeghers syndrome. The subcategories of 'mixed' and 'incompletely differentiated' forms of sex cord/gonadal stromal tumours have been replaced by 'mixed and unclassified sex cord-stromal tumours'. New entities introduced in the latest WHO revision include: myoid gonadal stromal tumour and 'undifferentiated gonadal tissue', a putative precursor lesion of gonadoblastoma, whereas juvenile xanthogranuloma and haemangioma are included in the miscellaneous category of tumours.

  6. Simple Fully Automated Group Classification on Brain fMRI

    SciTech Connect

    Honorio, J.; Goldstein, R.; Honorio, J.; Samaras, D.; Tomasi, D.; Goldstein, R.Z.

    2010-04-14

    We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statistical theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.

  7. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Oropharynx.

    PubMed

    Westra, William H; Lewis, James S

    2017-03-01

    The changes for oropharyngeal lesions in the 2017 edition of the WHO/IARC Classification of Head and Neck Tumours reference book are dramatic and significant, largely due to the growing impact of high risk human papillomavirus (HPV). The upcoming edition divides tumours of the oral cavity and oropharynx into separate chapters, classifies squamous cell carcinomas (SCC) of the oropharynx on the basis of HPV status, abandons the practice of histologic grading for oropharyngeal SCCs that are HPV positive, recognizes small cell carcinoma of the oropharynx, and combines polymorphous low grade adenocarcinoma and cribriform adenocarcinoma of tongue and minor salivary glands under the single term "polymorphous adenocarcinoma." This review not only calls attention to these changes, but describes the rationale driving these changes and highlights their implications for routine clinical practice.

  8. Validation of IR-spectroscopic brain tumor classification

    NASA Astrophysics Data System (ADS)

    Beleites, C.; Steiner, G.; Sobottka, S.; Schackert, G.; Salzer, R.

    2006-02-01

    As a molecular probe of tissue composition, infrared spectroscopic imaging serves as an adjunct to histopathology in detecting and diagnosing disease. In the past it was demonstrated that the IR spectra of brain tumors can be discriminated from one another according to their grade of malignancy. Although classification success rates up to 93% were observed one problem consists in the variation of the models depending on the number of samples used for the development of the classification model. In order to open the path for clinical trials the classification has to be validated. A series of classification models were built using a k-fold cross validation scheme and the classification predictions from the various models were combined to provide an aggregated prediction. The validation highlights instabilities in the models, error rates, sensitivity as well as specificity of the classification and allows the determination of confidence intervals. Better classification models could be achieved by an aggregated prediction. The validation shows that brain tumors can be classified by infrared spectroscopy and the grade of malignancy corresponds reasonably to the histopathological assignment.

  9. Image-guided microbeam irradiation to brain tumour bearing mice using a carbon nanotube x-ray source array

    NASA Astrophysics Data System (ADS)

    Zhang, Lei; Yuan, Hong; Burk, Laurel M.; Inscoe, Christy R.; Hadsell, Michael J.; Chtcheprov, Pavel; Lee, Yueh Z.; Lu, Jianping; Chang, Sha; Zhou, Otto

    2014-03-01

    Microbeam radiation therapy (MRT) is a promising experimental and preclinical radiotherapy method for cancer treatment. Synchrotron based MRT experiments have shown that spatially fractionated microbeam radiation has the unique capability of preferentially eradicating tumour cells while sparing normal tissue in brain tumour bearing animal models. We recently demonstrated the feasibility of generating orthovoltage microbeam radiation with an adjustable microbeam width using a carbon nanotube based x-ray source array. Here we report the preliminary results from our efforts in developing an image guidance procedure for the targeted delivery of the narrow microbeams to the small tumour region in the mouse brain. Magnetic resonance imaging was used for tumour identification, and on-board x-ray radiography was used for imaging of landmarks without contrast agents. The two images were aligned using 2D rigid body image registration to determine the relative position of the tumour with respect to a landmark. The targeting accuracy and consistency were evaluated by first irradiating a group of mice inoculated with U87 human glioma brain tumours using the present protocol and then determining the locations of the microbeam radiation tracks using γ-H2AX immunofluorescence staining. The histology results showed that among 14 mice irradiated, 11 received the prescribed number of microbeams on the targeted tumour, with an average localization accuracy of 454 µm measured directly from the histology (537 µm if measured from the registered histological images). Two mice received one of the three prescribed microbeams on the tumour site. One mouse was excluded from the analysis due to tissue staining errors.

  10. Image-guided microbeam irradiation to brain tumour bearing mice using a carbon nanotube x-ray source array.

    PubMed

    Zhang, Lei; Yuan, Hong; Burk, Laurel M; Inscoe, Christy R; Hadsell, Michael J; Chtcheprov, Pavel; Lee, Yueh Z; Lu, Jianping; Chang, Sha; Zhou, Otto

    2014-03-07

    Microbeam radiation therapy (MRT) is a promising experimental and preclinical radiotherapy method for cancer treatment. Synchrotron based MRT experiments have shown that spatially fractionated microbeam radiation has the unique capability of preferentially eradicating tumour cells while sparing normal tissue in brain tumour bearing animal models. We recently demonstrated the feasibility of generating orthovoltage microbeam radiation with an adjustable microbeam width using a carbon nanotube based x-ray source array. Here we report the preliminary results from our efforts in developing an image guidance procedure for the targeted delivery of the narrow microbeams to the small tumour region in the mouse brain. Magnetic resonance imaging was used for tumour identification, and on-board x-ray radiography was used for imaging of landmarks without contrast agents. The two images were aligned using 2D rigid body image registration to determine the relative position of the tumour with respect to a landmark. The targeting accuracy and consistency were evaluated by first irradiating a group of mice inoculated with U87 human glioma brain tumours using the present protocol and then determining the locations of the microbeam radiation tracks using γ-H2AX immunofluorescence staining. The histology results showed that among 14 mice irradiated, 11 received the prescribed number of microbeams on the targeted tumour, with an average localization accuracy of 454 µm measured directly from the histology (537 µm if measured from the registered histological images). Two mice received one of the three prescribed microbeams on the tumour site. One mouse was excluded from the analysis due to tissue staining errors.

  11. Image-guided microbeam irradiation to brain tumour bearing mice using a carbon nanotube X-ray source array

    PubMed Central

    Zhang, Lei; Yuan, Hong; Burk, Laurel M; Inscoe, Christy R; Hadsell, Michael J; Chtcheprov, Pavel; Lee, Yueh Z; Lu, Jianping; Chang, Sha; Zhou, Otto

    2014-01-01

    Microbeam radiation therapy (MRT) is a promising experimental and preclinical radiotherapy method for cancer treatment. Synchrotron based MRT experiments have shown that spatially fractionated microbeam radiation has the unique capability of preferentially eradicating tumour cells while sparing normal tissue in brain tumour bearing animal models. We recently demonstrated the feasibility of generating orthovoltage microbeam radiation with an adjustable microbeam width using a carbon nanotube based X-ray source array. Here we report the preliminary results from our efforts in developing an image guidance procedure for the targeted delivery of the narrow microbeams to the small tumour region in the mouse brain. Magnetic resonance imaging was used for tumour identification, and on-board X-ray radiography was used for imaging of landmarks without contrast agents. The two images were aligned using 2D rigid body image registration to determine the relative position of the tumour with respect to a landmark. The targeting accuracy and consistency were evaluated by first irradiating a group of mice inoculated with U87 human glioma brain tumours using the present protocol and then determining the locations of the microbeam radiation tracks using γ-H2AX immunofluorescence staining. The histology results showed that among 14 mice irradiated, 11 received the prescribed number of microbeams on the targeted tumour, with an average localization accuracy of 454 μm measured directly from the histology (537 μm if measured from the registered histological images). Two mice received one of the three prescribed microbeams on the tumour site. One mouse was excluded from the analysis due to tissue staining errors. PMID:24556798

  12. Brain tumor classification of microscopy images using deep residual learning

    NASA Astrophysics Data System (ADS)

    Ishikawa, Yota; Washiya, Kiyotada; Aoki, Kota; Nagahashi, Hiroshi

    2016-12-01

    The crisis rate of brain tumor is about one point four in ten thousands. In general, cytotechnologists take charge of cytologic diagnosis. However, the number of cytotechnologists who can diagnose brain tumors is not sufficient, because of the necessity of highly specialized skill. Computer-Aided Diagnosis by computational image analysis may dissolve the shortage of experts and support objective pathological examinations. Our purpose is to support a diagnosis from a microscopy image of brain cortex and to identify brain tumor by medical image processing. In this study, we analyze Astrocytes that is a type of glia cell of central nerve system. It is not easy for an expert to discriminate brain tumor correctly since the difference between astrocytes and low grade astrocytoma (tumors formed from Astrocyte) is very slight. In this study, we present a novel method to segment cell regions robustly using BING objectness estimation and to classify brain tumors using deep convolutional neural networks (CNNs) constructed by deep residual learning. BING is a fast object detection method and we use pretrained BING model to detect brain cells. After that, we apply a sequence of post-processing like Voronoi diagram, binarization, watershed transform to obtain fine segmentation. For classification using CNNs, a usual way of data argumentation is applied to brain cells database. Experimental results showed 98.5% accuracy of classification and 98.2% accuracy of segmentation.

  13. A novel brain tumour model in zebrafish reveals the role of YAP activation in MAPK- and PI3K-induced malignant growth

    PubMed Central

    Mayrhofer, Marie; Gourain, Victor; Reischl, Markus; Affaticati, Pierre; Jenett, Arnim; Joly, Jean-Stephane; Benelli, Matteo; Demichelis, Francesca; Poliani, Pietro Luigi; Sieger, Dirk

    2017-01-01

    ABSTRACT Somatic mutations activating MAPK and PI3K signalling play a pivotal role in both tumours and brain developmental disorders. We developed a zebrafish model of brain tumours based on somatic expression of oncogenes that activate MAPK and PI3K signalling in neural progenitor cells and found that HRASV12 was the most effective in inducing both heterotopia and invasive tumours. Tumours, but not heterotopias, require persistent activation of phospho (p)-ERK and express a gene signature similar to the mesenchymal glioblastoma subtype, with a strong YAP component. Application of an eight-gene signature to human brain tumours establishes that YAP activation distinguishes between mesenchymal glioblastoma and low grade glioma in a wide The Cancer Genome Atlas (TCGA) sample set including gliomas and glioblastomas (GBMs). This suggests that the activation of YAP might be an important event in brain tumour development, promoting malignant versus benign brain lesions. Indeed, co-expression of dominant-active YAP (YAPS5A) and HRASV12 abolishes the development of heterotopias and leads to the sole development of aggressive tumours. Thus, we have developed a model proving that neurodevelopmental disorders and brain tumours might originate from the same activation of oncogenes through somatic mutations, and established that YAP activation is a hallmark of malignant brain tumours. PMID:27935819

  14. Long-term supratentorial brain structure and cognitive function following cerebellar tumour resections in childhood.

    PubMed

    Moberget, T; Andersson, S; Lundar, T; Due-Tønnessen, B J; Heldal, A; Endestad, T; Westlye, L T

    2015-03-01

    The cerebellum is connected to extensive regions of the cerebrum, and cognitive deficits following cerebellar lesions may thus be related to disrupted cerebello-cerebral connectivity. Moreover, early cerebellar lesions could affect distal brain development, effectively inducing long-term changes in brain structure and cognitive function. Here, we characterize supratentorial brain structure and cognitive function in 20 adult patients treated for cerebellar tumours in childhood (mean age at surgery: 7.1 years) and 26 matched controls. Relative to controls, patients showed reduced cognitive function and increased grey matter density in bilateral cingulum, left orbitofrontal cortex and the left hippocampus. Within the patient group, increased grey matter density in these regions was associated with decreased performance on tests of processing speed and executive function. Further, diffusion tensor imaging revealed widespread alterations in white matter microstructure in patients. While current ventricle volume (an index of previous hydrocephalus severity it patients) was associated with grey matter density and white matter microstructure in patients, this could only partially account for the observed group differences in brain structure and cognitive function. In conclusion, our results show distal effects of cerebellar lesions on cerebral integrity and wiring, likely caused by a combination of neurodegenerative processes and perturbed neurodevelopment.

  15. [Ovarian tumor in a koi carp (Cyprinus carpio): Diagnosis, surgery, postoperative care and tumour classification].

    PubMed

    Lewisch, E; Reifinger, M; Schmidt, P; El-Matbouli, M

    2014-01-01

    Although ovarian tumour in the koi (Cyprinus carpio) does not appear to be an uncommon condition, its occurrence and therapy has rarely been reported. In the present case, the decision for surgery was based on clinical and sonographic findings of an intracoelomic mass. We used tricaine methansulfonate for the anaesthesia. Laparotomy was performed by ventral access and an ovarian tumour of 12-cm diameter was removed. The wound was sutured in two layers using Vicryl®. In addition to the application of an analgesic, an antibiotic and vitamins, the postoperative conditions the patient was kept under were adapted to support wound healing. The fish recovered uneventfully and was clinically healthy during the 16-month observation period. Based on the histological findings, the tumour was diagnosed as a thecoma. Investigations using antibodies against vimentin, cytokeratin, S 100 and glial fibrillary acidic protein (GFAP) failed to provide reliable results.

  16. Registration quality and descriptive epidemiology of childhood brain tumours in Scotland 1975-90.

    PubMed Central

    McKinney, P. A.; Ironside, J. W.; Harkness, E. F.; Arango, J. C.; Doyle, D.; Black, R. J.

    1994-01-01

    Children (0-14 years) with malignant brain and central nervous system (CNS) tumours (ICD9 191 and 192) were listed from the Scottish Cancer Registration Scheme for the years 1975-90. These cases formed the basis for validation and verification procedures aimed at providing a complete and accurate data set for epidemiological analyses. A variety of data sources were cross-checked to optimise ascertainment, and resulting from this 5.7% of validated cases were found on the cancer registry with diagnostic codes outside the ICD-9 range 191-192. A further 8.4% were newly registered cases. Analyses were conducted on the validated data set showing a significant temporal increase in incidence rates over the 16 year study period with an average annual percentage change of +2.6%. Large-scale geographical heterogeneity was also found, with a particularly high incidence in the Fife and Lothian areas and a low incidence in Grampian. Examination of associations with socioeconomic status, using the Carstairs deprivation index, revealed a rising trend in incidence strongly linked to areas with increasing levels of affluence. Our results suggest that for studies of childhood CNS tumours validation of cancer registry data is necessary and large-scale geographical variation and socioeconomic factors should be taken into account in any investigation of distribution in small geographical areas. PMID:7947107

  17. Natural image classification driven by human brain activity

    NASA Astrophysics Data System (ADS)

    Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

    2016-03-01

    Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

  18. Perimetric visual field and functional MRI correlation: implications for image-guided surgery in occipital brain tumours

    PubMed Central

    Roux, F; Ibarrola, D; Lotterie, J; Chollet, F; Berry, I

    2001-01-01

    OBJECTIVE—To compare the results of visual functional MRI with those of perimetric evaluation in patients with visual field defects and retrochiasmastic tumours and in normal subjects without visual field defect. The potential clinical usefulness of visual functional MRI data during resective surgery was evaluated in patients with occipital lobe tumours.
METHODS—Eleven patients with various tumours and visual field defects and 12 normal subjects were studied by fMRI using bimonocular or monocular repetitive photic stimulation (8 Hz). The data obtained were analyzed with the statistical parametric maps software (p<10-8) and were compared with the results of Goldmann visual field perimetric evaluation. In patients with occipital brain tumours undergoing surgery, the functional data were registered in a frameless stereotactic device and the images fused into anatomical three standard planes and three dimensional reconstructions of the brain surface.
RESULTS—Two studies of patients were discarded, one because of head motion and the other because of badly followed instructions. On the remaining patients the functional activations found in the visual cortex were consistent with the results of perimetric evaluation in all but one of the patients and all the normal subjects although the results of fMRI were highly dependent on the choices of the analysis thresholds. Visual functional MRI image guided data were used in five patients with occipital brain tumours. No added postoperative functional field defect was detected.
CONCLUSIONS—There was a good correspondence between fMRI data and the results of perimetric evaluation although dependent on the analysis thresholds. Visual fMRI data registered into a frameless stereotactic device may be useful in surgical planning and tumour removal.

 PMID:11561035

  19. Unsupervised classification of operator workload from brain signals

    NASA Astrophysics Data System (ADS)

    Schultze-Kraft, Matthias; Dähne, Sven; Gugler, Manfred; Curio, Gabriel; Blankertz, Benjamin

    2016-06-01

    Objective. In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Approach. Subjects executed a task on a touch screen that required continuous effort of visual and motor processing with alternating difficulty. We first employed classical approaches for workload state classification that operate on the sensor space of EEG and compared those to the performance of three state-of-the-art spatial filtering methods: common spatial patterns (CSPs) analysis, which requires binary label information; source power co-modulation (SPoC) analysis, which uses the subjects’ error rate as a target function; and canonical SPoC (cSPoC) analysis, which solely makes use of cross-frequency power correlations induced by different states of workload and thus represents an unsupervised approach. Finally, we investigated the effects of fusing brain signals and peripheral physiological measures (PPMs) and examined the added value for improving classification performance. Main results. Mean classification accuracies of 94%, 92% and 82% were achieved with CSP, SPoC, cSPoC, respectively. These methods outperformed the approaches that did not use spatial filtering and they extracted physiologically plausible components. The performance of the unsupervised cSPoC is significantly increased by augmenting it with PPM features. Significance. Our analyses ensured that the signal sources used for classification were of cortical origin and not contaminated with artifacts. Our findings show that workload states can be successfully differentiated from brain signals, even when less and less information from the experimental paradigm is used, thus paving the way for real-world applications in which label information may be noisy or entirely unavailable.

  20. Surgeon volume and 30 day mortality for brain tumours in England

    PubMed Central

    Williams, Matt; Treasure, Peter; Greenberg, David; Brodbelt, Andrew; Collins, Peter

    2016-01-01

    Background: There is evidence that surgeons who perform more operations have better outcomes. However, in patients with brain tumours, all of the evidence comes from the USA. Methods: We examined all English patients with an intracranial neoplasm who had an intracranial resection in 2008–2010. We included surgeons who performed at least six operations over 3 years, and at least one operation in the first and last 6 months of the period. Results: The analysis data set comprised 9194 operations, 163 consultant neurosurgeons and 30 centres. Individual surgeon volumes varied widely (7–272; median=46). 72% of operations were on the brain, and 30 day mortality was 3%. A doubling of surgeon load was associated with a 20% relative reduction in mortality. Thirty day mortality varied between centres (0·95–8·62%) but was not related to centre workload. Conclusions: Individual surgeon volumes correlated with patient 30 day mortality. Centres and surgeons in England are busier than surgeons and centres in the USA. There is no relationship between centre volume and 30 day mortality in England. Services in the UK appear to be adequately arranged at a centre level, but would benefit from further surgeon sub-specialisation. PMID:27764843

  1. Increasing rates of brain tumours in the Swedish national inpatient register and the causes of death register.

    PubMed

    Hardell, Lennart; Carlberg, Michael

    2015-04-03

    Radiofrequency emissions in the frequency range 30 kHz-300 GHz were evaluated to be Group 2B, i.e., "possibly", carcinogenic to humans by the International Agency for Research on Cancer (IARC) at WHO in May 2011. The Swedish Cancer Register has not shown increasing incidence of brain tumours in recent years and has been used to dismiss epidemiological evidence on a risk. In this study we used the Swedish National Inpatient Register (IPR) and Causes of Death Register (CDR) to further study the incidence comparing with the Cancer Register data for the time period 1998-2013 using joinpoint regression analysis. In the IPR we found a joinpoint in 2007 with Annual Percentage Change (APC) +4.25%, 95% CI +1.98, +6.57% during 2007-2013 for tumours of unknown type in the brain or CNS. In the CDR joinpoint regression found one joinpoint in 2008 with APC during 2008-2013 +22.60%, 95% CI +9.68, +37.03%. These tumour diagnoses would be based on clinical examination, mainly CT and/or MRI, but without histopathology or cytology. No statistically significant increasing incidence was found in the Swedish Cancer Register during these years. We postulate that a large part of brain tumours of unknown type are never reported to the Cancer Register. Furthermore, the frequency of diagnosis based on autopsy has declined substantially due to a general decline of autopsies in Sweden adding further to missing cases. We conclude that the Swedish Cancer Register is not reliable to be used to dismiss results in epidemiological studies on the use of wireless phones and brain tumour risk.

  2. Increasing Rates of Brain Tumours in the Swedish National Inpatient Register and the Causes of Death Register

    PubMed Central

    Hardell, Lennart; Carlberg, Michael

    2015-01-01

    Radiofrequency emissions in the frequency range 30 kHz–300 GHz were evaluated to be Group 2B, i.e., “possibly”, carcinogenic to humans by the International Agency for Research on Cancer (IARC) at WHO in May 2011. The Swedish Cancer Register has not shown increasing incidence of brain tumours in recent years and has been used to dismiss epidemiological evidence on a risk. In this study we used the Swedish National Inpatient Register (IPR) and Causes of Death Register (CDR) to further study the incidence comparing with the Cancer Register data for the time period 1998–2013 using joinpoint regression analysis. In the IPR we found a joinpoint in 2007 with Annual Percentage Change (APC) +4.25%, 95% CI +1.98, +6.57% during 2007–2013 for tumours of unknown type in the brain or CNS. In the CDR joinpoint regression found one joinpoint in 2008 with APC during 2008–2013 +22.60%, 95% CI +9.68, +37.03%. These tumour diagnoses would be based on clinical examination, mainly CT and/or MRI, but without histopathology or cytology. No statistically significant increasing incidence was found in the Swedish Cancer Register during these years. We postulate that a large part of brain tumours of unknown type are never reported to the Cancer Register. Furthermore, the frequency of diagnosis based on autopsy has declined substantially due to a general decline of autopsies in Sweden adding further to missing cases. We conclude that the Swedish Cancer Register is not reliable to be used to dismiss results in epidemiological studies on the use of wireless phones and brain tumour risk. PMID:25854296

  3. Meta-analysis of long-term mobile phone use and the association with brain tumours.

    PubMed

    Hardell, Lennart; Carlberg, Michael; Söderqvist, Fredrik; Hansson Mild, Kjell

    2008-05-01

    We evaluated long-term use of mobile phones and the risk for brain tumours in case-control studies published so far on this issue. We identified ten studies on glioma and meta-analysis yielded OR = 0.9, 95% CI = 0.8-1.1. Latency period of > or =10-years gave OR = 1.2, 95% CI = 0.8-1.9 based on six studies, for ipsilateral use (same side as tumour) OR = 2.0, 95% CI = 1.2-3.4 (four studies), but contralateral use did not increase the risk significantly, OR = 1.1, 95% CI = 0.6-2.0. Meta-analysis of nine studies on acoustic neuroma gave OR = 0.9, 95% CI = 0.7-1.1 increasing to OR = 1.3, 95% CI = 0.6-2.8 using > or =10-years latency period (four studies). Ipsilateral use gave OR = 2.4, 95% CI = 1.1-5.3 and contra-lateral OR = 1.2, 95% CI = 0.7-2.2 in the > or =10-years latency period group (three studies). Seven studies gave results for meningioma yielding overall OR = 0.8, 95% CI = 0.7-0.99. Using > or =10-years latency period OR = 1.3, 95% CI = 0.9-1.8 was calculated (four studies) increasing to OR = 1.7, 95% CI = 0.99-3.1 for ipsilateral use and OR = 1.0, 95% CI = 0.3-3.1 for contralateral use (two studies). We conclude that this meta-analysis gave a consistent pattern of an association between mobile phone use and ipsilateral glioma and acoustic neuroma using > or =10-years latency period.

  4. Disruption of tumour-host communication by downregulation of LFA-1 reduces COX-2 and e-NOS expression and inhibits brain metastasis growth

    PubMed Central

    Soto, Manuel Sarmiento; O'Brien, Emma R.; Andreou, Kleopatra; Scrace, Simon F.; Zakaria, Rasheed; Jenkinson, Michael D.; O'Neill, Eric; Sibson, Nicola R.

    2016-01-01

    Over 20% of cancer patients will suffer metastatic spread to the brain, and prognosis remains poor. Communication between tumour cells and host tissue is essential during metastasis, yet little is known of the processes underlying such interactions in the brain. Here we test the hypothesis that cross-talk between tumour cells and host brain cells, through tumour cell leukocyte function associated protein-1 (LFA-1), is critical in metastasis development. Temporal expression of LFA-1 and its major ligand intercellular adhesion molecule-1 (ICAM-1) was determined in two different mouse models of brain metastasis. Marked upregulation of both proteins was found, co-localising with astrocytes, microglia and tumour cells themselves. Silencing of LFA-1 expression in MDA231Br-GFP cells prior to intracerebral injection resulted in > 70% reduction in tumour burden compared to control MDA231Br-GFP cells (p < 0.005, n = 5). Subsequent qRT-PCR analysis of brain tissue revealed significant reductions in COX-2, VEGF and eNOS from host brain tissue, but not tumour cells, in mice injected with LFA-1 knockdown cells (p < 0.0001, n = 5). Finally, expression of both LFA-1 and ICAM-1 was demonstrated in human brain metastasis samples. The results of this study suggest LFA-1 as a new target in brain metastasis therapy and highlight the potential synergy with current anti-COX-2 and anti-NOS therapies. PMID:27447568

  5. Risk of brain tumours in relation to estimated RF dose from mobile phones: results from five Interphone countries

    PubMed Central

    Armstrong, B K; Bowman, J D; Giles, G G; Hours, M; Krewski, D; McBride, M; Parent, M E; Sadetzki, S; Woodward, A; Brown, J; Chetrit, A; Figuerola, J; Hoffmann, C; Jarus-Hakak, A; Montestruq, L; Nadon, L; Richardson, L; Villegas, R; Vrijheid, M

    2011-01-01

    Objectives The objective of this study was to examine the associations of brain tumours with radio frequency (RF) fields from mobile phones. Methods Patients with brain tumour from the Australian, Canadian, French, Israeli and New Zealand components of the Interphone Study, whose tumours were localised by neuroradiologists, were analysed. Controls were matched on age, sex and region and allocated the ‘tumour location’ of their matched case. Analyses included 553 glioma and 676 meningioma cases and 1762 and 1911 controls, respectively. RF dose was estimated as total cumulative specific energy (TCSE; J/kg) absorbed at the tumour's estimated centre taking into account multiple RF exposure determinants. Results ORs with ever having been a regular mobile phone user were 0.93 (95% CI 0.73 to 1.18) for glioma and 0.80 (95% CI 0.66 to 0.96) for meningioma. ORs for glioma were below 1 in the first four quintiles of TCSE but above 1 in the highest quintile, 1.35 (95% CI 0.96 to 1.90). The OR increased with increasing TCSE 7+ years before diagnosis (p-trend 0.01; OR 1.91, 95% CI 1.05 to 3.47 in the highest quintile). A complementary analysis in which 44 glioma and 135 meningioma cases in the most exposed area of the brain were compared with gliomas and meningiomas located elsewhere in the brain showed increased ORs for tumours in the most exposed part of the brain in those with 10+ years of mobile phone use (OR 2.80, 95% CI 1.13 to 6.94 for glioma). Patterns for meningioma were similar, but ORs were lower, many below 1.0. Conclusions There were suggestions of an increased risk of glioma in long-term mobile phone users with high RF exposure and of similar, but apparently much smaller, increases in meningioma risk. The uncertainty of these results requires that they be replicated before a causal interpretation can be made. PMID:21659469

  6. Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis

    PubMed Central

    Su, Zhengyu; Zeng, Wei; Wang, Yalin; Lu, Zhong-Lin; Gu, Xianfeng

    2015-01-01

    Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane. The uniformization map will distort the surface area elements. The area-distortion factor gives a probability measure on the canonical uniformization space. All the probability measures on a Riemannian manifold form the Wasserstein space. Given any 2 probability measures, there is a unique optimal mass transport map between them, the transportation cost defines the Wasserstein distance between them. Wasserstein distance gives a Riemannian metric for the Wasserstein space. It intrinsically measures the dissimilarities between shapes and thus has the potential for shape classification. To the best of our knowledge, this is the first work to introduce the optimal mass transport map to general Riemannian manifolds. The method is based on geodesic power Voronoi diagram. Comparing to the conventional methods, our approach solely depends on Riemannian metrics and is invariant under rigid motions and scalings, thus it intrinsically measures shape distance. Experimental results on classifying brain cortical surfaces with different intelligence quotients demonstrated the efficiency and efficacy of our method. PMID:26221691

  7. Relationship between paediatric CT scans and subsequent risk of leukaemia and brain tumours: assessment of the impact of underlying conditions

    PubMed Central

    de Gonzalez, Amy Berrington; Salotti, Jane A; McHugh, Kieran; Little, Mark P; Harbron, Richard W; Lee, Choonsik; Ntowe, Estelle; Braganza, Melissa Z; Parker, Louise; Rajaraman, Preetha; Stiller, Charles; Stewart, Douglas R; Craft, Alan W; Pearce, Mark S

    2016-01-01

    Background: We previously reported evidence of a dose–response relationship between ionising-radiation exposure from paediatric computed tomography (CT) scans and the risk of leukaemia and brain tumours in a large UK cohort. Underlying unreported conditions could have introduced bias into these findings. Methods: We collected and reviewed additional clinical information from radiology information systems (RIS) databases, underlying cause of death and pathology reports. We conducted sensitivity analyses excluding participants with cancer-predisposing conditions or previous unreported cancers and compared the dose–response analyses with our original results. Results: We obtained information from the RIS and death certificates for about 40% of the cohort (n∼180 000) and found cancer-predisposing conditions in 4 out of 74 leukaemia/myelodysplastic syndrome (MDS) cases and 13 out of 135 brain tumour cases. As these conditions were unrelated to CT exposure, exclusion of these participants did not alter the dose–response relationships. We found evidence of previous unreported cancers in 2 leukaemia/MDS cases, 7 brain tumour cases and 232 in non-cases. These previous cancers were related to increased number of CTs. Exclusion of these cancers reduced the excess relative risk per mGy by 15% from 0.036 to 0.033 for leukaemia/MDS (P-trend=0.02) and by 30% from 0.023 to 0.016 (P-trend<0.0001) for brain tumours. When we included pathology reports we had additional clinical information for 90% of the cases. Additional exclusions from these reports further reduced the risk estimates, but this sensitivity analysis may have underestimated risks as reports were only available for cases. Conclusions: Although there was evidence of some bias in our original risk estimates, re-analysis of the cohort with additional clinical data still showed an increased cancer risk after low-dose radiation exposure from CT scans in young patients. PMID:26882064

  8. Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

    PubMed Central

    Beare, Richard J.; Chen, Jian; Kelly, Claire E.; Alexopoulos, Dimitrios; Smyser, Christopher D.; Rogers, Cynthia E.; Loh, Wai Y.; Matthews, Lillian G.; Cheong, Jeanie L. Y.; Spittle, Alicia J.; Anderson, Peter J.; Doyle, Lex W.; Inder, Terrie E.; Seal, Marc L.; Thompson, Deanne K.

    2016-01-01

    Measuring the distribution of brain tissue types (tissue classification) in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation), which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM) software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF), hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks' gestation) acquired at 30 weeks' corrected gestational age (n = 5), coronal T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5) and axial T2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5). The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR) group, consisted of T2-weighted images of preterm infants (born <30 weeks' gestation) acquired shortly after birth (n = 12), preterm infants acquired at term-equivalent age (n = 12), and healthy term-born infants (born ≥38 weeks' gestation) acquired within the first 9 days of life (n = 12). For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for the cortical gray

  9. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: What is New in the 2017 WHO Blue Book for Tumours of the Hypopharynx, Larynx, Trachea and Parapharyngeal Space.

    PubMed

    Gale, Nina; Poljak, Mario; Zidar, Nina

    2017-03-01

    Chapter 3 "Tumours of the hypopharynx, larynx, trachea, and parapharyngeal space" of the World Health Organization (WHO) Blue Book 2017 "Classification of Head and Neck Tumours" shows a shortened list of entities, especially due to reducing the number of benign and malignant soft tissue tumours, malignant melanoma and some others, which are transferred to more frequently affected regions of the head and neck. The basic concept of the new edition is to assimilate all advances concerning the discussed tumours in a shorter framework, appropriate for daily work. The main emphasis is on the most frequent lesions and tumors originating from the covering squamous epithelium. Laryngeal and hypopharyngeal conventional squamous cell carcinoma (CSCC), its variants and precursor lesions, occupy a major part of the chapter. New data on etiopathogenesis, with the focus on human papillomavirus (HPV) infection, are discussed in relation to the entities of the squamous epithelium. Although only a small fraction of these lesions are HPV-related, further studies are required for evaluation of the potential prognostic and therapeutic benefit of mRNA HPV determination. In contrast to earlier data, laryngeal and hypopharyngeal verrucous SCC, spindle cell SCC and basaloid SCC are not anymore considered as HPV-related tumours. New data on the pathogenesis of spindle cell SCC exhibiting divergent differentiation by epithelial-mesenchymal transition, are also briefly discussed. The most important innovation is brought by the section on precursor lesions, in which a unified two-tier classification, consisting of low- and high-grade dysplasia, is introduced. The proposed two-tier system can also be transformed into a three-tier classification for treatment purposes, with a distinction between carcinoma in situ and high-grade dysplasia. The reviewed morphological criteria of the proposed system are based on the amended Ljubljana classification. The section on laryngeal neuroendocrine

  10. Directed Progression Brain Networks in Alzheimer's Disease: Properties and Classification

    PubMed Central

    Young, Karl; Asif, Danial; Jutla, Inderjit; Liang, Michael; Wilson, Scott; Landsberg, Adam S.; Schuff, Norbert

    2014-01-01

    Abstract This article introduces a new approach in brain connectomics aimed at characterizing the temporal spread in the brain of pathologies like Alzheimer's disease (AD). The main instrument is the development of “directed progression networks” (DPNets), wherein one constructs directed edges between nodes based on (weakly) inferred directions of the temporal spreading of the pathology. This stands in contrast to many previously studied brain networks where edges represent correlations, physical connections, or functional progressions. In addition, this is one of a few studies showing the value of using directed networks in the study of AD. This article focuses on the construction of DPNets for AD using longitudinal cortical thickness measurements from magnetic resonance imaging data. The network properties are then characterized, providing new insights into AD progression, as well as novel markers for differentiating normal cognition (NC) and AD at the group level. It also demonstrates the important role of nodal variations for network classification (i.e., the significance of standard deviations, not just mean values of nodal properties). Finally, the DPNets are utilized to classify subjects based on their global network measures using a variety of data-mining methodologies. In contrast to most brain networks, these DPNets do not show high clustering and small-world properties. PMID:24901258

  11. Sparse Bayesian Classification of EEG for Brain-Computer Interface.

    PubMed

    Zhang, Yu; Zhou, Guoxu; Jin, Jing; Zhao, Qibin; Wang, Xingyu; Cichocki, Andrzej

    2016-11-01

    Regularization has been one of the most popular approaches to prevent overfitting in electroencephalogram (EEG) classification of brain-computer interfaces (BCIs). The effectiveness of regularization is often highly dependent on the selection of regularization parameters that are typically determined by cross-validation (CV). However, the CV imposes two main limitations on BCIs: 1) a large amount of training data is required from the user and 2) it takes a relatively long time to calibrate the classifier. These limitations substantially deteriorate the system's practicability and may cause a user to be reluctant to use BCIs. In this paper, we introduce a sparse Bayesian method by exploiting Laplace priors, namely, SBLaplace, for EEG classification. A sparse discriminant vector is learned with a Laplace prior in a hierarchical fashion under a Bayesian evidence framework. All required model parameters are automatically estimated from training data without the need of CV. Extensive comparisons are carried out between the SBLaplace algorithm and several other competing methods based on two EEG data sets. The experimental results demonstrate that the SBLaplace algorithm achieves better overall performance than the competing algorithms for EEG classification.

  12. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study

    PubMed Central

    Pearce, Mark S; Salotti, Jane A; Little, Mark P; McHugh, Kieran; Lee, Choonsik; Kim, Kwang Pyo; Howe, Nicola L; Ronckers, Cecile M; Rajaraman, Preetha; Craft, Alan W; Parker, Louise; de González, Amy Berrington

    2012-01-01

    Summary Background Although CT scans are very useful clinically, potential cancer risks exist from associated ionising radiation, in particular for children who are more radiosensitive than adults. We aimed to assess the excess risk of leukaemia and brain tumours after CT scans in a cohort of children and young adults. Methods In our retrospective cohort study, we included patients without previous cancer diagnoses who were first examined with CT in National Health Service (NHS) centres in England, Wales, or Scotland (Great Britain) between 1985 and 2002, when they were younger than 22 years of age. We obtained data for cancer incidence, mortality, and loss to follow-up from the NHS Central Registry from Jan 1, 1985, to Dec 31, 2008. We estimated absorbed brain and red bone marrow doses per CT scan in mGy and assessed excess incidence of leukaemia and brain tumours cancer with Poisson relative risk models. To avoid inclusion of CT scans related to cancer diagnosis, follow-up for leukaemia began 2 years after the first CT and for brain tumours 5 years after the first CT. Findings During follow-up, 74 of 178 604 patients were diagnosed with leukaemia and 135 of 176 587 patients were diagnosed with brain tumours. We noted a positive association between radiation dose from CT scans and leukaemia (excess relative risk [ERR] per mGy 0·036, 95% CI 0·005–0·120; p=0·0097) and brain tumours (0·023, 0·010–0·049; p<0·0001). Compared with patients who received a dose of less than 5 mGy, the relative risk of leukaemia for patients who received a cumulative dose of at least 30 mGy (mean dose 51·13 mGy) was 3·18 (95% CI 1·46–6·94) and the relative risk of brain cancer for patients who received a cumulative dose of 50–74 mGy (mean dose 60·42 mGy) was 2·82 (1·33–6·03). Interpretation Use of CT scans in children to deliver cumulative doses of about 50 mGy might almost triple the risk of leukaemia and doses of about 60 mGy might triple the risk of brain

  13. A systematic review of the risk factors associated with the onset and progression of primary brain tumours.

    PubMed

    Quach, Pauline; El Sherif, Reem; Gomes, James; Krewksi, Daniel

    2016-05-17

    The overall aim of this systematic review was to identify risk factors for onset and natural progression, which were shown to increase, decrease, or have a null association with risk of primary brain tumour. For onset, the project was separated into two phases. The first phase consisted of a systematic search of existing systematic reviews and meta-analyses. Moderate to high methodological quality reviews were incorporated and summarized with relevant observational studies published since 2010, identified from a systematic search performed in phase 2. For natural progression, only the first phase was conducted. Standard systematic review methodology was utilized. Based on this review, various genetic variants, pesticide exposures, occupational farming/hairdressing, cured meat consumption and personal hair dye use appear to be associated with increased risk of onset amongst adults. The specific EGF polymorphsm 61-A allele within Caucasian populations and having a history of allergy was associated with a decreased risk. For progression, M1B-1 antigen was shown to increase the risk. High birth weight, pesticide exposure (childhood exposure, and parental occupational exposure) and maternal consumption of cured meat during pregnancy may also increase the risk of onset of childhood brain tumours. Conversely, maternal intake of pre-natal supplements (folic acid) appeared to decrease risk. Children with neurofibromatosis 2 were considered to have worse overall and relapse free survival compared to neurofibromatosis 1, as were those children who had grade III tumours compared to lesser grades.

  14. Spectroscopic magnetic resonance imaging of the brain: voxel localisation and tissue segmentation in the follow up of brain tumour.

    PubMed

    Poloni, Guy; Bastianello, S; Vultaggio, Angela; Pozzi, S; Maccabelli, Gloria; Germani, Giancarlo; Chiarati, Patrizia; Pichiecchio, Anna

    2008-01-01

    The field of application of magnetic resonance spectroscopy (MRS) in biomedical research is expanding all the time and providing opportunities to investigate tissue metabolism and function. The data derived can be integrated with the information on tissue structure gained from conventional and non-conventional magnetic resonance imaging (MRI) techniques. Clinical MRS is also strongly expected to play an important role as a diagnostic tool. Essential for the future success of MRS as a clinical and research tool in biomedical sciences, both in vivo and in vitro, is the development of an accurate, biochemically relevant and physically consistent and reliable data analysis standard. Stable and well established analysis algorithms, in both the time and the frequency domain, are already available, as is free commercial software for implementing them. In this study, we propose an automatic algorithm that takes into account anatomical localisation, relative concentrations of white matter, grey matter, cerebrospinal fluid and signal abnormalities and inter-scan patient movement. The endpoint is the collection of a series of covariates that could be implemented in a multivariate analysis of covariance (MANCOVA) of the MRS data, as a tool for dealing with differences that may be ascribed to the anatomical variability of the subjects, to inaccuracies in the localisation of the voxel or slab, or to movement, rather than to the pathology under investigation. The aim was to develop an analysis procedure that can be consistently and reliably applied in the follow up of brain tumour. In this study, we demonstrate that the inclusion of such variables in the data analysis of quantitative MRS is fundamentally important (especially in view of the reduced accuracy typical of MRS measures compared to other MRI techniques), reducing the occurrence of false positives.

  15. Classification of types of stuttering symptoms based on brain activity.

    PubMed

    Jiang, Jing; Lu, Chunming; Peng, Danling; Zhu, Chaozhe; Howell, Peter

    2012-01-01

    Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type.

  16. Lost in laterality: interpreting ''preferred side of the head during mobile phone use and risk of brain tumour'' associations.

    PubMed

    Schüz, Joachim

    2009-08-01

    Due to the highly localized exposure from mobile phones, the preferred side of the head during their use is important information when investigating a possible link with brain tumour risk, but at the same time, error and bias hamper the assessment of this information in case-control studies. Current studies provide evidence of reporting bias insofar as cases appear to over-report the side of the head where the tumour occurred as the one that they preferred in the past when using mobile phones. More refined methods of analysis among only cases or prospective studies with an assessment of the laterality of mobile phone use before the diagnosis of disease are needed to evaluate whether associations seen in some studies are entirely due to reporting bias or a mixture of reporting bias and a causal effect.

  17. Prospective diagnostic performance evaluation of single-voxel 1H MRS for typing and grading of brain tumours.

    PubMed

    Julià-Sapé, Margarida; Coronel, Indira; Majós, Carles; Candiota, Ana Paula; Serrallonga, Marta; Cos, Mònica; Aguilera, Carles; Acebes, Juan José; Griffiths, John R; Arús, Carles

    2012-04-01

    The purpose of this study was to evaluate whether single-voxel (1)H MRS could add useful information to conventional MRI in the preoperative characterisation of the type and grade of brain tumours. MRI and MRS examinations from a prospective cohort of 40 consecutive patients were analysed double blind by radiologists and spectroscopists before the histological diagnosis was known. The spectroscopists had only the MR spectra, whereas the radiologists had both the MR images and basic clinical details (age, sex and presenting symptoms). Then, the radiologists and spectroscopists exchanged their predictions and re-evaluated their initial opinions, taking into account the new evidence. Spectroscopists used four different systems of analysis for (1)H MRS data, and the efficacy of each of these methods was also evaluated. Information extracted from (1)H MRS significantly improved the radiologists' MRI-based characterisation of grade IV tumours (glioblastomas, metastases, medulloblastomas and lymphomas) in the cohort [area under the curve (AUC) in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.85], and also of the less malignant glial tumours (AUC in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.81). One of the MRS analysis systems used, the INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance) decision support system, outperformed the others, as well as being better than the MRI evaluation for the characterisation of grade III astrocytomas. Thus, preoperative MRS data improve the radiologists' performance in diagnosing grade IV tumours and, for those of grade II-III, MRS data help them to recognise the glial lineage. Even in cases in which their diagnoses were not improved, the provision of MRS data to the radiologists had no negative influence on their predictions.

  18. 3-D brain MRI tissue classification on FPGAs.

    PubMed

    Koo, Jahyun J; Evans, Alan C; Gross, Warren J

    2009-12-01

    Many automatic algorithms have been proposed for analyzing magnetic resonance imaging (MRI) data sets. With the increasingly large data sets being used in brain mapping, there has been a significant rise in the need for accelerating these algorithms. Partial volume estimation (PVE), a brain tissue classification algorithm for MRI, was implemented on a field-programmable gate array (FPGA)-based high performance reconfigurable computer using the Mitrion-C high-level language (HLL). This work develops on prior work in which we conducted initial studies on accelerating the prior information estimation algorithm. In this paper, we extend the work to include probability density estimation and present new results and additional analysis. We used several simulated and real human brain MR images to evaluate the accuracy and performance improvement of the proposed algorithm. The FPGA-based probability density estimation and prior information estimation implementation achieved an average speedup over an Itanium 2 CPU of 2.5 x and 9.4 x , respectively. The overall performance improvement of the FPGA-based PVE algorithm was 5.1 x with four FPGAs.

  19. Overexpression of s6 kinase 1 in brain tumours is associated with induction of hypoxia-responsive genes and predicts patients' survival.

    PubMed

    Ismail, Heba M S

    2012-01-01

    mTOR/S6K pathway is a crucial regulator of cell growth and metabolism. Deregulated signalling via S6K has been linked to various human pathologies, including metabolic disorders and cancer. Many of the molecules signalling upstream of S6K have been shown to be either mutated or overexpressed in tumours, leading to S6K activation. The role of S6K1 in brain tumours is not fully investigated. In this study, we investigated the gene expression profile of S6 kinases in brain and CNS tumours using the publically available Cancer Microarray Database. We found that S6K1 but not S6K2 gene is overexpressed in brain tumours and this upregulation is associated with patients' poor survival. Furthermore, we interrogated Oncomine database for the expression profile of hypoxia-induced genes using a literature-defined concept. This gene list included HIF1A, VEGFA, SOX4, SOX9, MMP2, and NEDD9. We show that those genes are upregulated in all brain tumour studies investigated. Additionally, we analysed the coexpression profile of S6K1 and hypoxia responsive genes. The analysis was done across 4 different brain studies and showed that S6K1 is co-overexpressed with several hypoxia responsive genes. This study highlights the possible role of S6K1 in brain tumour progression and prediction of patients' survival. However, new epidemiological studies should be conducted in order to confirm these associations and to refine the role of S6K1 in brain tumours as a useful marker for patients' survival.

  20. Brain tissue segmentation in 4D CT using voxel classification

    NASA Astrophysics Data System (ADS)

    van den Boom, R.; Oei, M. T. H.; Lafebre, S.; Oostveen, L. J.; Meijer, F. J. A.; Steens, S. C. A.; Prokop, M.; van Ginneken, B.; Manniesing, R.

    2012-02-01

    A method is proposed to segment anatomical regions of the brain from 4D computer tomography (CT) patient data. The method consists of a three step voxel classification scheme, each step focusing on structures that are increasingly difficult to segment. The first step classifies air and bone, the second step classifies vessels and the third step classifies white matter, gray matter and cerebrospinal fluid. As features the time averaged intensity value and the temporal intensity change value were used. In each step, a k-Nearest-Neighbor classifier was used to classify the voxels. Training data was obtained by placing regions of interest in reconstructed 3D image data. The method has been applied to ten 4D CT cerebral patient data. A leave-one-out experiment showed consistent and accurate segmentation results.

  1. Penetration and intracellular uptake of poly(glycerol-adipate) nanoparticles into three-dimensional brain tumour cell culture models.

    PubMed

    Meng, Weina; Garnett, Martin C; Walker, David A; Parker, Terence L

    2016-03-01

    Nanoparticle (NP) drug delivery systems may potentially enhance the efficacy of therapeutic agents. It is difficult to characterize many important properties of NPs in vivo and therefore attempts have been made to use realistic in vitro multicellular spheroids instead. In this paper, we have evaluated poly(glycerol-adipate) (PGA) NPs as a potential drug carrier for local brain cancer therapy. Various three-dimensional (3-D) cell culture models have been used to investigate the delivery properties of PGA NPs. Tumour cells in 3-D culture showed a much higher level of endocytic uptake of NPs than a mixed normal neonatal brain cell population. Differences in endocytic uptake of NPs in 2-D and 3-D models strongly suggest that it is very important to use in vitro 3-D cell culture models for evaluating this parameter. Tumour penetration of NPs is another important parameter which could be studied in 3-D cell models. The penetration of PGA NPs through 3-D cell culture varied between models, which will therefore require further study to develop useful and realistic in vitro models. Further use of 3-D cell culture models will be of benefit in the future development of new drug delivery systems, particularly for brain cancers which are more difficult to study in vivo.

  2. Pharmaco-thermodynamics of deuterium-induced oedema in living rat brain via 1H2O MRI: implications for boron neutron capture therapy of malignant brain tumours.

    PubMed

    Medina, Daniel C; Li, Xin; Springer, Charles S

    2005-05-07

    In addition to its common usage as a tracer in metabolic and physiological studies, deuterium possesses anti-tumoural activity and confers protection against gamma-irradiation. A more recent interest in deuterium emanates from the search for alternatives capable of improving neutron penetrance whilst reducing healthy tissue radiation dose deposition in boron neutron capture therapy of malignant brain tumours. Despite this potential clinical application, deuterium induces brain oedema, which is detrimental to neutron capture therapy. In this study, five adult male rats were titrated with deuterated drinking water while brain oedema was monitored via water proton magnetic resonance imaging. This report concludes that deuterium, as well as deuterium-induced brain oedema, possesses a uniform brain bio-distribution. At a steady-state blood fluid deuteration value of 16%, when the deuterium isotope fraction in drinking water was 25%, a mean oedematous volume change of 9 +/- 2% (p-value <0.001) was observed in the rat brain-this may account for neurological and behavioural abnormalities found in mammals drinking highly deuterated water. In addition to characterizing the pharmaco-thermodynamics of deuterium-induced oedema, this report also estimates the impact of oedema on thermal neutron enhancement and effective dose reduction factors using simple linear transport calculations. While body fluid deuteration enhances thermal neutron flux penetrance and reduces dose deposition, oedema has the opposite effect because it increases the volume of interest, e.g., the brain volume. Thermal neutron enhancement and effective dose reduction factors could be reduced by as much as approximately 10% in the presence of a 9% water volume increase (oedema).

  3. Localisation of the sensorimotor cortex during surgery for brain tumours: feasibility and waveform patterns of somatosensory evoked potentials

    PubMed Central

    Romstock, J; Fahlbusch, R; Ganslandt, O; Nimsky, C; Strauss, C

    2002-01-01

    surgical planning and intraoperative use during surgery on perirolandic tumours, but compensation for brain shift, accuracy, and cost effectiveness are still a matter for discussion. PMID:11796773

  4. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Mucosal Melanomas.

    PubMed

    Williams, Michelle D

    2017-03-01

    The updated edition of The World Health Organization Classification of Tumours of the Head and Neck includes discussions on mucosal melanoma of both the sinonasal and oral cavity. Since the prior edition, sinonasal origin is now recognized as the most common site of occurrence of mucosal melanoma in the head and neck (66%) with oral cavity representing 25% of cases. Histologic features of mucosal melanomas vary widely from spindled, epithelioid, and pleomorphic to rhabdoid, plasmacytoid and undifferentiated. Additionally, mucosal melanomas are commonly amelanotic (or minimal pigmentation) (~50%) leading to overlapping features and diagnostic challenges in differentiating mucosal melanomas from other small cell/undifferentiated sinonasal tumors. Since the last edition, formal staging of head and neck mucosal melanomas was added to the American Joint Committee on Cancer entities, though the traditional histologic features that have prognostic significance in cutaneous melanomas fail to stratify mucosal melanomas (i.e. tumor thickness, ulceration). Interestingly, while melanomas of all sites are a malignancy derived from melanocytes, mucosal melanomas are now recognized to have distinct molecular alterations compared to cutaneous or uveal melanomas. BRAF V600E mutations are rare (<6%) in mucosally derived melanomas compared to a rate of 50% in cutaneous melanomas. CD117 (C-Kit) mutations are the most common alteration encountered (~25%) in mucosal sites with potential therapeutic targetability. The recognition of the distinct genetic changes in this subgroup of melanomas means that therapy advances in cutaneous melanomas may not translate to head and neck mucosal melanomas and clinical trials specific to this subgroup of patients are needed.

  5. Pharmaco-thermodynamics of deuterium-induced oedema in living rat brain via 1H2O MRI: implications for boron neutron capture therapy of malignant brain tumours

    NASA Astrophysics Data System (ADS)

    Medina, Daniel C.; Li, Xin; Springer, Charles S., Jr.

    2005-05-01

    In addition to its common usage as a tracer in metabolic and physiological studies, deuterium possesses anti-tumoural activity and confers protection against γ-irradiation. A more recent interest in deuterium emanates from the search for alternatives capable of improving neutron penetrance whilst reducing healthy tissue radiation dose deposition in boron neutron capture therapy of malignant brain tumours. Despite this potential clinical application, deuterium induces brain oedema, which is detrimental to neutron capture therapy. In this study, five adult male rats were titrated with deuterated drinking water while brain oedema was monitored via water proton magnetic resonance imaging. This report concludes that deuterium, as well as deuterium-induced brain oedema, possesses a uniform brain bio-distribution. At a steady-state blood fluid deuteration value of 16%, when the deuterium isotope fraction in drinking water was 25%, a mean oedematous volume change of 9 ± 2% (p-value <0.001) was observed in the rat brain—this may account for neurological and behavioural abnormalities found in mammals drinking highly deuterated water. In addition to characterizing the pharmaco-thermodynamics of deuterium-induced oedema, this report also estimates the impact of oedema on thermal neutron enhancement and effective dose reduction factors using simple linear transport calculations. While body fluid deuteration enhances thermal neutron flux penetrance and reduces dose deposition, oedema has the opposite effect because it increases the volume of interest, e.g., the brain volume. Thermal neutron enhancement and effective dose reduction factors could be reduced by as much as ~10% in the presence of a 9% water volume increase (oedema). All three authors have contributed equally to this work.

  6. 77 FR 16925 - Medical Devices; Neurological Devices; Classification of the Near Infrared Brain Hematoma Detector

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-23

    ...; Classification of the Near Infrared Brain Hematoma Detector AGENCY: Food and Drug Administration, HHS. ACTION: Final rule. SUMMARY: The Food and Drug Administration (FDA) is classifying the Near Infrared (NIR) Brain... generic name Near Infrared (NIR) Brain Hematoma Detector, and it is identified as a noninvasive...

  7. Assessing occupational exposure to chemicals in an international epidemiological study of brain tumours.

    PubMed

    van Tongeren, Martie; Kincl, Laurel; Richardson, Lesley; Benke, Geza; Figuerola, Jordi; Kauppinen, Timo; Lakhani, Ramzan; Lavoué, Jérôme; McLean, Dave; Plato, Nils; Cardis, Elisabeth

    2013-06-01

    The INTEROCC project is a multi-centre case-control study investigating the risk of developing brain cancer due to occupational chemical and electromagnetic field exposures. To estimate chemical exposures, the Finnish Job Exposure Matrix (FINJEM) was modified to improve its performance in the INTEROCC study and to address some of its limitations, resulting in the development of the INTEROCC JEM. An international team of occupational hygienists developed a crosswalk between the Finnish occupational codes used in FINJEM and the International Standard Classification of Occupations 1968 (ISCO68). For ISCO68 codes linked to multiple Finnish codes, weighted means of the exposure estimates were calculated. Similarly, multiple ISCO68 codes linked to a single Finnish code with evidence of heterogeneous exposure were refined. One of the key time periods in FINJEM (1960-1984) was split into two periods (1960-1974 and 1975-1984). Benzene exposure estimates in early periods were modified upwards. The internal consistency of hydrocarbon exposures and exposures to engine exhaust fumes was improved. Finally, exposure to polycyclic aromatic hydrocarbon and benzo(a)pyrene was modified to include the contribution from second-hand smoke. The crosswalk ensured that the FINJEM exposure estimates could be applied to the INTEROCC study subjects. The modifications generally resulted in an increased prevalence of exposure to chemical agents. This increased prevalence of exposure was not restricted to the lowest categories of cumulative exposure, but was seen across all levels for some agents. Although this work has produced a JEM with important improvements compared to FINJEM, further improvements are possible with the expansion of agents and additional external data.

  8. Assessing Occupational Exposure to Chemicals in an International Epidemiological Study of Brain Tumours

    PubMed Central

    van Tongeren, Martie

    2013-01-01

    The INTEROCC project is a multi-centre case–control study investigating the risk of developing brain cancer due to occupational chemical and electromagnetic field exposures. To estimate chemical exposures, the Finnish Job Exposure Matrix (FINJEM) was modified to improve its performance in the INTEROCC study and to address some of its limitations, resulting in the development of the INTEROCC JEM. An international team of occupational hygienists developed a crosswalk between the Finnish occupational codes used in FINJEM and the International Standard Classification of Occupations 1968 (ISCO68). For ISCO68 codes linked to multiple Finnish codes, weighted means of the exposure estimates were calculated. Similarly, multiple ISCO68 codes linked to a single Finnish code with evidence of heterogeneous exposure were refined. One of the key time periods in FINJEM (1960–1984) was split into two periods (1960–1974 and 1975–1984). Benzene exposure estimates in early periods were modified upwards. The internal consistency of hydrocarbon exposures and exposures to engine exhaust fumes was improved. Finally, exposure to polycyclic aromatic hydrocarbon and benzo(a)pyrene was modified to include the contribution from second-hand smoke. The crosswalk ensured that the FINJEM exposure estimates could be applied to the INTEROCC study subjects. The modifications generally resulted in an increased prevalence of exposure to chemical agents. This increased prevalence of exposure was not restricted to the lowest categories of cumulative exposure, but was seen across all levels for some agents. Although this work has produced a JEM with important improvements compared to FINJEM, further improvements are possible with the expansion of agents and additional external data. PMID:23467593

  9. Factors associated with long-term functional outcomes, psychological sequelae and quality of life in persons after primary brain tumour.

    PubMed

    Khan, Fary; Amatya, Bhasker

    2013-02-01

    To examine factors impacting long-term functional outcomes and psychological sequelae in persons with primary brain tumours (BT) in an Australian community cohort. Participants (n = 106) following definitive treatment for BT in the community were reviewed in rehabilitation clinics to assess impact on participants' current activity and restriction in participation, using validated questionnaires: Functional Independence Measure (FIM), Perceived Impact Problem Profile (PIPP), Depression Anxiety Stress Scale, Cancer Rehabilitation Evaluation System-Short Form and Cancer Survivor Unmet Needs Measure. Mean age of the participants was 51 years (range 21-77 years), majority were female (56 %) with median time since BT diagnosis 2.1 years and a third (39 %) had high grade tumours. Majority showed good functional recovery (median motor FIM score 75). Over half reported pain (56 %), of which 42 % had headaches. Other impairments included: ataxia (44 %), seizures (43 %); paresis (37 %), cognitive dysfunction (36 %) and visual impairment (35 %). About 20 % reported high levels of depression, compared with only 13 % in an Australian normative sample. Two-third (60 %) participants reported highest impact on the PIPP subscales for psychological wellbeing (scores of >3 on 6-point scale) and participation (45 %). Factors significantly associated with poorer current level of functioning and wellbeing included: younger participants (≤40 years), recent diagnoses, aggressive tumour types and presence of pain. No significant differences in scale scores were found across various treatments (surgery, chemotherapy or radiotherapy) on outcomes used. Rehabilitation for BT survivors is challenging and requires long-term management of psychological sequelae impacting activity and participation. More research into participatory limitation is needed to guide treating clinicians.

  10. In-phantom two-dimensional thermal neutron distribution for intraoperative boron neutron capture therapy of brain tumours

    NASA Astrophysics Data System (ADS)

    Yamamoto, T.; Matsumura, A.; Yamamoto, K.; Kumada, H.; Shibata, Y.; Nose, T.

    2002-07-01

    The aim of this study was to determine the in-phantom thermal neutron distribution derived from neutron beams for intraoperative boron neutron capture therapy (IOBNCT). Gold activation wires arranged in a cylindrical water phantom with (void-in-phantom) or without (standard phantom) a cylinder styrene form placed inside were irradiated by using the epithermal beam (ENB) and the mixed thermal-epithermal beam (TNB-1) at the Japan Research Reactor No 4. With ENB, we observed a flattened distribution of thermal neutron flux and a significantly enhanced thermal flux delivery at a depth compared with the results of using TNB-1. The thermal neutron distribution derived from both the ENB and TNB-1 was significantly improved in the void-in-phantom, and a double high dose area was formed lateral to the void. The flattened distribution in the circumference of the void was observed with the combination of ENB and the void-in-phantom. The measurement data suggest that the ENB may provide a clinical advantage in the form of an enhanced and flattened dose delivery to the marginal tissue of a post-operative cavity in which a residual and/or microscopically infiltrating tumour often occurs. The combination of the epithermal neutron beam and IOBNCT will improve the clinical results of BNCT for brain tumours.

  11. In-phantom two-dimensional thermal neutron distribution for intraoperative boron neutron capture therapy of brain tumours.

    PubMed

    Yamamoto, T; Matsumura, A; Yamamoto, K; Kumada, H; Shibata, Y; Nose, T

    2002-07-21

    The aim of this study was to determine the in-phantom thermal neutron distribution derived from neutron beams for intraoperative boron neutron capture therapy (IOBNCT). Gold activation wires arranged in a cylindrical water phantom with (void-in-phantom) or without (standard phantom) a cylinder styrene form placed inside were irradiated by using the epithermal beam (ENB) and the mixed thermal-epithermal beam (TNB-1) at the Japan Research Reactor No 4. With ENB, we observed a flattened distribution of thermal neutron flux and a significantly enhanced thermal flux delivery at a depth compared with the results of using TNB-1. The thermal neutron distribution derived from both the ENB and TNB-1 was significantly improved in the void-in-phantom, and a double high dose area was formed lateral to the void. The flattened distribution in the circumference of the void was observed with the combination of ENB and the void-in-phantom. The measurement data suggest that the ENB may provide a clinical advantage in the form of an enhanced and flattened dose delivery to the marginal tissue of a post-operative cavity in which a residual and/or microscopically infiltrating tumour often occurs. The combination of the epithermal neutron beam and IOBNCT will improve the clinical results of BNCT for brain tumours.

  12. The 'radiation vacation': Parents' experiences of travelling to have their children's brain tumours treated with proton beam therapy.

    PubMed

    Cockle, Sam G; Ogden, Jane

    2016-01-01

    Proton beam therapy is a new form of radiotherapy. Little is known about patients' experiences of proton beam therapy and less about parents' experiences of children receiving treatment. Semi-structured interviews explored 10 parents' experiences of travelling from the United Kingdom to the United States to have their children's brain tumours treated with proton beam therapy. Thematic analysis uncovered themes of 'adjusting to the PBT routine', 'finding benefit in the situation' and 'readjusting upon returning home'. Parents' initial worries were elevated by travel, but they found benefit in their experiences, describing them positively. The periods before and after treatment were most difficult, illustrating a cycle from upset to calm, back to upset upon their return home.

  13. Biodegradable interstitial release polymer loading a novel small molecule targeting Axl receptor tyrosine kinase and reducing brain tumour migration and invasion

    PubMed Central

    Yen, S-Y; Chen, S-R; Hsieh, J; Li, Y-S; Chuang, S-E; Chuang, H-M; Huang, M-H; Lin, S-Z; Harn, H-J; Chiou, T-W

    2016-01-01

    Glioblastoma multiforme (GBM) is the most common and aggressive brain tumour. The neoplasms are difficult to resect entirely because of their highly infiltration property and leading to the tumour edge is unclear. Gliadel wafer has been used as an intracerebral drug delivery system to eliminate the residual tumour. However, because of its local low concentration and short diffusion distance, patient survival improves non-significantly. Axl is an essential regulator in cancer metastasis and patient survival. In this study, we developed a controlled-release polyanhydride polymer loading a novel small molecule, n-butylidenephthalide (BP), which is not only increasing local drug concentration and extending its diffusion distance but also reducing tumour invasion, mediated by reducing Axl expression. First, we determined that BP inhibited the expression of Axl in a dose- and time-dependent manner and reduced the migratory and invasive capabilities of GBM cells. In addition, BP downregulated matrix metalloproteinase activity, which is involved in cancer cell invasion. Furthermore, we demonstrated that BP regulated Axl via the extracellular signal-regulated kinases pathway. Epithelial-to-mesenchymal transition (EMT) is related to epithelial cells in the invasive migratory mesenchymal cells that underlie cancer progression; we demonstrated that BP reduced the expression of EMT-related genes. Furthermore, we used the overexpression of Axl in GBM cells to prove that Axl is a crucial target in the inhibition of GBM EMT, migration and invasion. In an in vivo study, we demonstrated that BP inhibited tumour growth and suppressed Axl expression in a dose-dependent manner according to a subcutaneous tumour model. Most importantly, in an intracranial tumour model with BP wafer in situ treatment, we demonstrated that the BP wafer not only significantly increased the survival rate but also decreased Axl expression, and inhibited tumour invasion. These results contribute to the

  14. Improvement effect on the depth-dose distribution by CSF drainage and air infusion of a tumour-removed cavity in boron neutron capture therapy for malignant brain tumours.

    PubMed

    Sakurai, Yoshinori; Ono, Koji; Miyatake, Shin-Ichi; Maruhashi, Akira

    2006-03-07

    Boron neutron capture therapy (BNCT) without craniotomy for malignant brain tumours was started using an epi-thermal neutron beam at the Kyoto University Reactor in June 2002. We have tried some techniques to overcome the treatable-depth limit in BNCT. One of the effective techniques is void formation utilizing a tumour-removed cavity. The tumorous part is removed by craniotomy about 1 week before a BNCT treatment in our protocol. Just before the BNCT irradiation, the cerebro-spinal fluid (CSF) in the tumour-removed cavity is drained out, air is infused to the cavity and then the void is made. This void improves the neutron penetration, and the thermal neutron flux at depth increases. The phantom experiments and survey simulations modelling the CSF drainage and air infusion of the tumour-removed cavity were performed for the size and shape of the void. The advantage of the CSF drainage and air infusion is confirmed for the improvement in the depth-dose distribution. From the parametric surveys, it was confirmed that the cavity volume had good correlation with the improvement effect, and the larger effect was expected as the cavity volume was larger.

  15. Improvement effect on the depth-dose distribution by CSF drainage and air infusion of a tumour-removed cavity in boron neutron capture therapy for malignant brain tumours

    NASA Astrophysics Data System (ADS)

    Sakurai, Yoshinori; Ono, Koji; Miyatake, Shin-ichi; Maruhashi, Akira

    2006-03-01

    Boron neutron capture therapy (BNCT) without craniotomy for malignant brain tumours was started using an epi-thermal neutron beam at the Kyoto University Reactor in June 2002. We have tried some techniques to overcome the treatable-depth limit in BNCT. One of the effective techniques is void formation utilizing a tumour-removed cavity. The tumorous part is removed by craniotomy about 1 week before a BNCT treatment in our protocol. Just before the BNCT irradiation, the cerebro-spinal fluid (CSF) in the tumour-removed cavity is drained out, air is infused to the cavity and then the void is made. This void improves the neutron penetration, and the thermal neutron flux at depth increases. The phantom experiments and survey simulations modelling the CSF drainage and air infusion of the tumour-removed cavity were performed for the size and shape of the void. The advantage of the CSF drainage and air infusion is confirmed for the improvement in the depth-dose distribution. From the parametric surveys, it was confirmed that the cavity volume had good correlation with the improvement effect, and the larger effect was expected as the cavity volume was larger.

  16. An improved brain image classification technique with mining and shape prior segmentation procedure.

    PubMed

    Rajendran, P; Madheswaran, M

    2012-04-01

    The shape prior segmentation procedure and pruned association rule with ImageApriori algorithm has been used to develop an improved brain image classification system are presented in this paper. The CT scan brain images have been classified into three categories namely normal, benign and malignant, considering the low-level features extracted from the images and high level knowledge from specialists to enhance the accuracy in decision process. The experimental results on pre-diagnosed brain images showed 97% sensitivity, 91% specificity and 98.5% accuracy. The proposed algorithm is expected to assist the physicians for efficient classification with multiple key features per image.

  17. Computerised cognitive training in acquired brain injury: A systematic review of outcomes using the International Classification of Functioning (ICF).

    PubMed

    Sigmundsdottir, Linda; Longley, Wendy A; Tate, Robyn L

    2016-10-01

    Computerised cognitive training (CCT) is an increasingly popular intervention for people experiencing cognitive symptoms. This systematic review evaluated the evidence for CCT in adults with acquired brain injury (ABI), focusing on how outcome measures used reflect efficacy across components of the International Classification of Functioning, Disability and Health. Database searches were conducted of studies investigating CCT to treat cognitive symptoms in adult ABI. Scientific quality was rated using the PEDro-P and RoBiNT Scales. Ninety-six studies met the criteria. Most studies examined outcomes using measures of mental functions (93/96, 97%); fewer studies included measures of activities/participation (41/96, 43%) or body structures (8/96, 8%). Only 14 studies (15%) provided Level 1 evidence (randomised controlled trials with a PEDro-P score ≥ 6/10), with these studies suggesting strong evidence for CCT improving processing speed in multiple sclerosis (MS) and moderate evidence for improving memory in MS and brain tumour populations. There is a large body of research examining the efficacy of CCT, but relatively few Level 1 studies and evidence is largely limited to body function outcomes. The routine use of outcome measures of activities/participation would provide more meaningful evidence for the efficacy of CCT. The use of body structure outcome measures (e.g., neuroimaging) is a newly emerging area, with potential to increase understanding of mechanisms of action for CCT.

  18. Real-time classification of activated brain areas for fMRI-based human-brain-interfaces

    NASA Astrophysics Data System (ADS)

    Moench, Tobias; Hollmann, Maurice; Grzeschik, Ramona; Mueller, Charles; Luetzkendorf, Ralf; Baecke, Sebastian; Luchtmann, Michael; Wagegg, Daniela; Bernarding, Johannes

    2008-03-01

    Functional MR imaging (fMRI) enables to detect different activated brain areas according to the performed tasks. However, data are usually evaluated after the experiment, which prohibits intra-experiment optimization or more sophisticated applications such as biofeedback experiments. Using a human-brain-interface (HBI), subjects are able to communicate with external programs, e.g. to navigate through virtual scenes, or to experience and modify their own brain activation. These applications require the real-time analysis and classification of activated brain areas. Our paper presents first results of different strategies for real-time pattern analysis and classification realized within a flexible experiment control system that enables the volunteers to move through a 3D virtual scene in real-time using finger tapping tasks, and alternatively only thought-based tasks.

  19. OP04QUANTITATIVE MEASUREMENT OF BLOOD FLOW IN PAEDIATRIC BRAIN TUMOURS - A COMPARATIVE STUDY OF DYNAMIC SUSCEPTIBILITY CONTRAST AND MULTI-TIMEPOINT ARTERIAL SPIN LABEL IMAGING

    PubMed Central

    Abernethy, L.J.; Vidyasagar, R.; Pizer, B.L.; Mallucci, C.L.; Avula, S.; Parkes, L.M.

    2014-01-01

    INTRODUCTION: Arterial spin labeling (ASL) is a MR technique that allows for noninvasive quantification of cerebral blood flow (CBF). This technique, predominately used in research, has seen significant technical developments in the last few years that have led to more clinical applications. Currently, the main MR method used to provide perfusion measures in brain tumours is dynamic susceptibility contrast (DSC). DSC traces the signal changes caused by the transit of a bolus of gadolinium contrast agent. ASL has the advantage of not requiring bolus injection of contrast. We have performed a comparative study of DSC and multi-timepoint ASL in paediatric brain tumours (PBT). METHOD: Data from a total of 19 PBT patients (mean age: 9 ± 5 years; 10 females, 9 males) were included in the analyses for this study. Data used were from first presentation scans performed before any surgical intervention. Comparisons of the quantitative measures of CBF and blood arrival time between the two techniques were carried out to test the feasibility of ASL to provide useful quantification measures of CBF in PBT. RESULTS: DSC measurements of tumour blood flow showed a significant decrease in flow in comparison with normal brain, but this is not seen with ASL. There was a strong correlation between ASL and DSC measures of blood flow in normal brain (r = 0.65, p = 0.009), but not in tumour blood flow (r = 0.33, p = 0.2). CONCLUSION: This study demonstrates the feasibility and potential utility of ASL as a non-invasive technique for measuring blood flow in PBT. However, there is a discrepancy between ASL and DSC measures, that may be due to leakage of gadolinium contrast, reflecting the abnormal characteristics of tumour blood vessels in PBT.

  20. A role for the malignant brain tumour (MBT) domain protein LIN-61 in DNA double-strand break repair by homologous recombination.

    PubMed

    Johnson, Nicholas M; Lemmens, Bennie B L G; Tijsterman, Marcel

    2013-01-01

    Malignant brain tumour (MBT) domain proteins are transcriptional repressors that function within Polycomb complexes. Some MBT genes are tumour suppressors, but how they prevent tumourigenesis is unknown. The Caenorhabditis elegans MBT protein LIN-61 is a member of the synMuvB chromatin-remodelling proteins that control vulval development. Here we report a new role for LIN-61: it protects the genome by promoting homologous recombination (HR) for the repair of DNA double-strand breaks (DSBs). lin-61 mutants manifest numerous problems associated with defective HR in germ and somatic cells but remain proficient in meiotic recombination. They are hypersensitive to ionizing radiation and interstrand crosslinks but not UV light. Using a novel reporter system that monitors repair of a defined DSB in C. elegans somatic cells, we show that LIN-61 contributes to HR. The involvement of this MBT protein in HR raises the possibility that MBT-deficient tumours may also have defective DSB repair.

  1. L-Phenylalanine preloading reduces the (10)B(n, α)(7)Li dose to the normal brain by inhibiting the uptake of boronophenylalanine in boron neutron capture therapy for brain tumours.

    PubMed

    Watanabe, Tsubasa; Tanaka, Hiroki; Fukutani, Satoshi; Suzuki, Minoru; Hiraoka, Masahiro; Ono, Koji

    2016-01-01

    Boron neutron capture therapy (BNCT) is a cellular-level particle radiation therapy that combines the selective delivery of boron compounds to tumour tissue with neutron irradiation. Previously, high doses of one of the boron compounds used for BNCT, L-BPA, were found to reduce the boron-derived irradiation dose to the central nervous system. However, injection with a high dose of L-BPA is not feasible in clinical settings. We aimed to find an alternative method to improve the therapeutic efficacy of this therapy. We examined the effects of oral preloading with various analogues of L-BPA in a xenograft tumour model and found that high-dose L-phenylalanine reduced the accumulation of L-BPA in the normal brain relative to tumour tissue. As a result, the maximum irradiation dose in the normal brain was 19.2% lower in the L-phenylalanine group relative to the control group. This study provides a simple strategy to improve the therapeutic efficacy of conventional boron compounds for BNCT for brain tumours and the possibility to widen the indication of BNCT to various kinds of other tumours.

  2. Assessing the performance of four different categories of histological criteria in brain tumours grading by means of a computer-aided diagnosis image analysis system.

    PubMed

    Kostopoulos, S; Konstandinou, C; Sidiropoulos, K; Ravazoula, P; Kalatzis, I; Asvestas, P; Cavouras, D; Glotsos, D

    2015-10-01

    Brain tumours are considered one of the most lethal and difficult to treat forms of cancer, with unknown aetiology and lack of any realistic screening. In this study, we examine, whether the combination of descriptive criteria, used by expert histopathologists in assessing histologic tissue samples, and quantitative image analysis features may improve the diagnostic accuracy of brain tumour grading. Data comprised 61 cases of brain cancers (astrocytomas, oligodendrogliomas, meningiomas) collected from the archives of the University Hospital of Patras, Greece. Incorporating physician's descriptive criteria and image analysis's quantitative features into a discriminant function, a computer-aided diagnosis system was designed for discriminating low-grade from high-grade brain tumours. Physician's descriptive features, when solely used in the system, proved of high discrimination accuracy (93.4%). When verbal descriptive features were combined with quantitative image analysis features in the system, discrimination accuracy improved to 98.4%. The generalization of the proposed system to unseen data converged to an overall prediction accuracy of 86.7% ± 5.4%. Considering that histological grading affects treatment selection and diagnostic errors may be notable in clinical practice, the utilization of the proposed system may safeguard against diagnostic misinterpretations in every day clinical practice.

  3. Connectivity strength-weighted sparse group representation-based brain network construction for MCI classification.

    PubMed

    Yu, Renping; Zhang, Han; An, Le; Chen, Xiaobo; Wei, Zhihui; Shen, Dinggang

    2017-02-02

    Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l1 -norm penalty simply penalizes each edge of a brain network equally, without considering the original connectivity strength which is one of the most important inherent linkwise characters. Besides, based on the similarity of the linkwise connectivity, brain network shows prominent group structure (i.e., a set of edges sharing similar attributes). In this article, we propose a novel brain functional network modeling framework with a "connectivity strength-weighted sparse group constraint." In particular, the network modeling can be optimized by considering both raw connectivity strength and its group structure, without losing the merit of sparsity. Our proposed method is applied to MCI classification, a challenging task for early AD diagnosis. Experimental results based on the resting-state functional MRI, from 50 MCI patients and 49 healthy controls, show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 84.8%) than other competing methods (e.g., sparse representation, accuracy = 65.6%). Post hoc inspection of the informative features further shows more biologically meaningful brain functional connectivities obtained by our proposed method. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

  4. Word pair classification during imagined speech using direct brain recordings

    NASA Astrophysics Data System (ADS)

    Martin, Stephanie; Brunner, Peter; Iturrate, Iñaki; Millán, José Del R.; Schalk, Gerwin; Knight, Robert T.; Pasley, Brian N.

    2016-05-01

    People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70–150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58% p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications.

  5. Word pair classification during imagined speech using direct brain recordings

    PubMed Central

    Martin, Stephanie; Brunner, Peter; Iturrate, Iñaki; Millán, José del R.; Schalk, Gerwin; Knight, Robert T.; Pasley, Brian N.

    2016-01-01

    People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70–150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58%; p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications. PMID:27165452

  6. Survival analysis for apparent diffusion coefficient measures in children with embryonal brain tumours.

    PubMed

    Grech-Sollars, Matthew; Saunders, Dawn E; Phipps, Kim P; Clayden, Jonathan D; Clark, Chris A

    2012-10-01

    Embryonal brain tumors constitute a large and important subgroup of pediatric brain tumors. Apparent diffusion coefficient (ADC) measures have been previously used in the analysis of these tumors. We investigated a newly described ADC-derived parameter, the apparent transient coefficient in tumor (ATCT), a measure of the gradient change of ADC from the peri-tumoral edema into the tumor core, to study whether ATCT correlates with survival outcome. Sixty-one patients with histologically proven embryonal brain tumors and who had diffusion-weighted imaging (DWI) as part of their clinical imaging were enrolled in a retrospective study correlating ADC measures with survival. Kaplan-Meier survival curves were constructed for extent of surgical resection, age <3 years at diagnosis, tumor type, and metastasis at presentation. A multivariate survival analysis was performed that took into consideration ATCT and variables found to be significant in the Kaplan-Meier analysis as covariates. Results from the multivariate analysis showed that ATCT was the only significant covariate (P < .001). Survival analysis using Kaplan-Meier curves, dividing the patients into 4 groups of increasing values of ATCT, showed that more negative values of ATCT were significantly associated with a poorer prognosis (P < .001). A statistically significant difference was observed for survival data with respect to the change in ADC from edema into the tumor volume. Results show that more negative ATCT values are significantly associated with a poorer survival among children with embryonal brain tumors, irrespective of tumor type, extent of resection, age <3 years at diagnosis, and metastasis at presentation.

  7. Behavioral state classification in epileptic brain using intracranial electrophysiology

    NASA Astrophysics Data System (ADS)

    Kremen, Vaclav; Duque, Juliano J.; Brinkmann, Benjamin H.; Berry, Brent M.; Kucewicz, Michal T.; Khadjevand, Fatemeh; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Worrell, Gregory A.

    2017-04-01

    Objective. Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach. Data from seven patients (age 34+/- 12 , 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1–600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results. Classification accuracy of 97.8  ±  0.3% (normal tissue) and 89.4  ±  0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8  ±  0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1  ±  1.6%). Spectral power in high frequency band features (Ripple (80–250 Hz), Fast Ripple (250–600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy  ⩾90% using a single electrode contact and single spectral feature. Significance. Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.

  8. Brain Decoding-Classification of Hand Written Digits from fMRI Data Employing Bayesian Networks

    PubMed Central

    Yargholi, Elahe'; Hossein-Zadeh, Gholam-Ali

    2016-01-01

    We are frequently exposed to hand written digits 0–9 in today's modern life. Success in decoding-classification of hand written digits helps us understand the corresponding brain mechanisms and processes and assists seriously in designing more efficient brain–computer interfaces. However, all digits belong to the same semantic category and similarity in appearance of hand written digits makes this decoding-classification a challenging problem. In present study, for the first time, augmented naïve Bayes classifier is used for classification of functional Magnetic Resonance Imaging (fMRI) measurements to decode the hand written digits which took advantage of brain connectivity information in decoding-classification. fMRI was recorded from three healthy participants, with an age range of 25–30. Results in different brain lobes (frontal, occipital, parietal, and temporal) show that utilizing connectivity information significantly improves decoding-classification and capability of different brain lobes in decoding-classification of hand written digits were compared to each other. In addition, in each lobe the most contributing areas and brain connectivities were determined and connectivities with short distances between their endpoints were recognized to be more efficient. Moreover, data driven method was applied to investigate the similarity of brain areas in responding to stimuli and this revealed both similarly active areas and active mechanisms during this experiment. Interesting finding was that during the experiment of watching hand written digits, there were some active networks (visual, working memory, motor, and language processing), but the most relevant one to the task was language processing network according to the voxel selection. PMID:27468261

  9. Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification

    PubMed Central

    Rajesh Sharma, R.; Marikkannu, P.

    2015-01-01

    A novel hybrid approach for the identification of brain regions using magnetic resonance images accountable for brain tumor is presented in this paper. Classification of medical images is substantial in both clinical and research areas. Magnetic resonance imaging (MRI) modality outperforms towards diagnosing brain abnormalities like brain tumor, multiple sclerosis, hemorrhage, and many more. The primary objective of this work is to propose a three-dimensional (3D) novel brain tumor classification model using MRI images with both micro- and macroscale textures designed to differentiate the MRI of brain under two classes of lesion, benign and malignant. The design approach was initially preprocessed using 3D Gaussian filter. Based on VOI (volume of interest) of the image, features were extracted using 3D volumetric Square Centroid Lines Gray Level Distribution Method (SCLGM) along with 3D run length and cooccurrence matrix. The optimal features are selected using the proposed refined gravitational search algorithm (RGSA). Support vector machines, over backpropagation network, and k-nearest neighbor are used to evaluate the goodness of classifier approach. The preliminary evaluation of the system is performed using 320 real-time brain MRI images. The system is trained and tested by using a leave-one-case-out method. The performance of the classifier is tested using the receiver operating characteristic curve of 0.986 (±002). The experimental results demonstrate the systematic and efficient feature extraction and feature selection algorithm to the performance of state-of-the-art feature classification methods. PMID:26509188

  10. Integrative genomic analyses identify LIN28 and OLIG2 as markers of survival and metastatic potential in childhood central nervous system primitive neuro-ectodermal brain tumours

    PubMed Central

    Picard, Daniel; Miller, Suzanne; Hawkins, Cynthia E; Bouffet, Eric; Rogers, Hazel A; Chan, Tiffany SY; Kim, Seung-Ki; Ra, Young-Shin; Fangusaro, Jason; Korshunov, Andrey; Toledano, Helen; Nakamura, Hideo; Hayden, James T; Chan, Jennifer; Lafay-Cousin, Lucie; Hu, Ping X; Fan, Xing; Muraszko, Karin M; Pomeroy, Scott L; Lau, Ching C; Ng, Ho-Keung; Jones, Chris; Meter, Timothy Van; Clifford, Steven C; Eberhart, Charles; Gajjar, Amar; Pfister, Stefan M; Grundy, Richard G; Huang, Annie

    2013-01-01

    Background Childhood Central Nervous System Primitive Neuro-Ectodermal brain Tumours (CNS-PNETs) are highly aggressive brain tumours for which molecular features and best therapeutic strategy remains unknown. We interrogated a large cohort of these rare tumours in order to identify molecular markers that will enhance clinical management of CNS-PNET. Methods Transcriptional and copy number profiles from primary hemispheric CNS-PNETs were examined using clustering, gene and pathways enrichment analyses to discover tumour sub-groups and group-specific molecular markers. Immuno-histochemical and/or gene expression analyses were used to validate and examine the clinical significance of novel sub-group markers in 123 primary CNS-PNETs. Findings Three molecular sub-groups of CNS-PNETs distinguished by primitive neural (Group 1), oligo-neural (Group 2) and mesenchymal lineage (Group 3) gene expression signature were identified. Tumour sub-groups exhibited differential expression of cell lineage markers, LIN28 and OLIG2, and correlated with distinct demographics, survival and metastatic incidence. Group 1 tumours affected primarily younger females; male: female ratios were respectively 0.61 (median age 2.9 years; 95% CI: 2.4–5.2; p≤ 0.005), 1.25 (median age 7.9 years; 95% CI: 6–9.7) and 1.63 (median age 5.9 years; 95% CI: 4.9–7.8) for group 1, 2 and 3 patients. Overall outcome was poorest in group 1 patients which had a median survival of 0.8 years (95% CI: 0.47–1.2; p=0.019) as compared to 1.8 years (95% CI: 1.4–2.3) and 4.3 years; (95% CI: 0.82–7.8) respectively for group 2 and 3 patients. Group 3 tumours had the highest incidence of metastases at diagnosis; M0: M+ ratio were respectively 0.9 and 3.9 for group 3, versus group 1 and 2 tumours combined (p=0.037). Interpretation LIN28 and OLIG2 represent highly promising, novel diagnostic and prognostic molecular markers for CNS PNET that warrants further evaluation in prospective clinical trials. PMID:22691720

  11. Induction of HSP70 is associated with vincristine resistance in heat-shocked 9L rat brain tumour cells.

    PubMed Central

    Lee, W. C.; Lin, K. Y.; Chen, K. D.; Lai, Y. K.

    1992-01-01

    The most prominent cellular changes in heat-shock response are induction of HSPs synthesis and reorganisation of cytoskeleton. Vincristine was used as a tool to evaluate the integrity of microtubules in 9L rat brain tumour cells recovering from heat-shock treatment. Cells treated at 45 degrees C for 15 min and recovered under normal growing condition became resistant to vincristine-inflicted cytotoxicity and microtubule destruction. Among all HSPs, the level of HSP70 and the degree of vincristine resistance are best correlated. HSP70 and tubulin were found to be associated with each other as they were co-immunoprecipitated by either anti-HSP70 or anti-beta-tubulin monoclonal antibody. The current studies establish for the first time that HSP70 can complex with tubulin in cells and this association may stabilise the organisation of microtubules thus protect the heat-treated cells from vincristine damage. These findings are noteworthy in combining hyperthermia and chemotherapy in the management of malignant diseases. Images Figure 2 Figure 3 Figure 5 Figure 6 PMID:1419602

  12. Object categories specific brain activity classification with simultaneous EEG-fMRI.

    PubMed

    Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque

    2015-01-01

    Any kind of visual information is encoded in terms of patterns of neural activity occurring inside the brain. Decoding neural patterns or its classification is a challenging task. Functional magnetic resonance imaging (fMRI) and Electroencephalography (EEG) are non-invasive neuroimaging modalities to capture the brain activity pattern in term of images and electric potential respectively. To get higher spatiotemporal resolution of human brain from these two complementary neuroimaging modalities, simultaneous EEG-fMRI can be helpful. In this paper, we proposed a framework for classifying the brain activity patterns with simultaneous EEG-fMRI. We have acquired five human participants' data with simultaneous EEG-fMRI by showing different object categories. Further, combined analysis of EEG and fMRI data was carried out. Extracted information through combine analysis is passed to support vector machine (SVM) classifier for classification purpose. We have achieved better classification accuracy using simultaneous EEG-fMRI i.e., 81.8% as compared to fMRI data standalone. This shows that multimodal neuroimaging can improve the classification accuracy of brain activity patterns as compared to individual modalities reported in literature.

  13. Improved Grading and Survival Prediction of human astrocytic brain tumours by artificial neural network analysis of gene expression microarray data

    PubMed Central

    Petalidis, Lawrence P.; Oulas, Anastasis; Backlund, Magnus; Wayland, Matthew T.; Liu, Lu; Plant, Karen; Happerfield, Lisa; Freeman, Tom C.; Poirazi, Panayiota; Collins, V. Peter

    2010-01-01

    Histopathological grading of astrocytic tumours based on current WHO criteria offers a valuable but simplified representation of oncological reality and is often insufficient to predict clinical outcome. In this study we report a new astrocytic tumour microarray gene expression dataset (n=65). We have used a simple Artificial Neural Network (ANN) algorithm to address grading of human astrocytic tumours, derive specific transcriptional signatures from histopathological subtypes of astrocytic tumours and asses whether these molecular signatures define survival prognostic subclasses. 59 classifier genes were identified and found to fall within three distinct functional classes namely angiogenesis, cell differentiation and lower grade astrocytic tumour discrimination. These gene classes were found to characterize three molecular tumour subtypes denoted ANGIO, INTER and LOWER. Grading of samples using these subtypes agreed with prior histopathological grading both for our dataset (96.15%) as well as an independent dataset. Six tumours were particularly challenging to diagnose histopathologically. We present an ANN grading for these samples, and offer an evidence-based interpretation of grading results using clinical metadata to substantiate findings. The prognostic value of the three identified tumour subtypes was found to outperform histopathological grading as well as tumour subtypes reported in other studies, indicating a high survival prognostic potential for the 59 gene classifiers. Finally, 11 gene classifiers that differentiate between primary and secondary glioblastomas were also identified. PMID:18445660

  14. Automatic classification of lung tumour heterogeneity according to a visual-based score system in dynamic contrast enhanced CT sequences

    NASA Astrophysics Data System (ADS)

    Bevilacqua, Alessandro; Baiocco, Serena

    2016-03-01

    Computed tomography (CT) technologies have been considered for a long time as one of the most effective medical imaging tools for morphological analysis of body parts. Contrast Enhanced CT (CE-CT) also allows emphasising details of tissue structures whose heterogeneity, inspected through visual analysis, conveys crucial information regarding diagnosis and prognosis in several clinical pathologies. Recently, Dynamic CE-CT (DCE-CT) has emerged as a promising technique to perform also functional hemodynamic studies, with wide applications in the oncologic field. DCE-CT is based on repeated scans over time performed after intravenous administration of contrast agent, in order to study the temporal evolution of the tracer in 3D tumour tissue. DCE-CT pushes towards an intensive use of computers to provide automatically quantitative information to be used directly in clinical practice. This requires that visual analysis, representing the gold-standard for CT image interpretation, gains objectivity. This work presents the first automatic approach to quantify and classify the lung tumour heterogeneities based on DCE-CT image sequences, so as it is performed through visual analysis by experts. The approach developed relies on the spatio-temporal indices we devised, which also allow exploiting temporal data that enrich the knowledge of the tissue heterogeneity by providing information regarding the lesion status.

  15. Pattern classification of large-scale functional brain networks: identification of informative neuroimaging markers for epilepsy.

    PubMed

    Zhang, Jie; Cheng, Wei; Wang, ZhengGe; Zhang, ZhiQiang; Lu, WenLian; Lu, GuangMing; Feng, Jianfeng

    2012-01-01

    The accurate prediction of general neuropsychiatric disorders, on an individual basis, using resting-state functional magnetic resonance imaging (fMRI) is a challenging task of great clinical significance. Despite the progress to chart the differences between the healthy controls and patients at the group level, the pattern classification of functional brain networks across individuals is still less developed. In this paper we identify two novel neuroimaging measures that prove to be strongly predictive neuroimaging markers in pattern classification between healthy controls and general epileptic patients. These measures characterize two important aspects of the functional brain network in a quantitative manner: (i) coordinated operation among spatially distributed brain regions, and (ii) the asymmetry of bilaterally homologous brain regions, in terms of their global patterns of functional connectivity. This second measure offers a unique understanding of brain asymmetry at the network level, and, to the best of our knowledge, has not been previously used in pattern classification of functional brain networks. Using modern pattern-recognition approaches like sparse regression and support vector machine, we have achieved a cross-validated classification accuracy of 83.9% (specificity: 82.5%; sensitivity: 85%) across individuals from a large dataset consisting of 180 healthy controls and epileptic patients. We identified significantly changed functional pathways and subnetworks in epileptic patients that underlie the pathophysiological mechanism of the impaired cognitive functions. Specifically, we find that the asymmetry of brain operation for epileptic patients is markedly enhanced in temporal lobe and limbic system, in comparison with healthy individuals. The present study indicates that with specifically designed informative neuroimaging markers, resting-state fMRI can serve as a most promising tool for clinical diagnosis, and also shed light onto the physiology

  16. Brain tumour differentiation: rapid stratified serum diagnostics via attenuated total reflection Fourier-transform infrared spectroscopy.

    PubMed

    Hands, James R; Clemens, Graeme; Stables, Ryan; Ashton, Katherine; Brodbelt, Andrew; Davis, Charles; Dawson, Timothy P; Jenkinson, Michael D; Lea, Robert W; Walker, Carol; Baker, Matthew J

    2016-05-01

    The ability to diagnose cancer rapidly with high sensitivity and specificity is essential to exploit advances in new treatments to lead significant reductions in mortality and morbidity. Current cancer diagnostic tests observing tissue architecture and specific protein expression for specific cancers suffer from inter-observer variability, poor detection rates and occur when the patient is symptomatic. A new method for the detection of cancer using 1 μl of human serum, attenuated total reflection-Fourier transform infrared spectroscopy and pattern recognition algorithms is reported using a 433 patient dataset (3897 spectra). To the best of our knowledge, we present the largest study on serum mid-infrared spectroscopy for cancer research. We achieve optimum sensitivities and specificities using a Radial Basis Function Support Vector Machine of between 80.0 and 100 % for all strata and identify the major spectral features, hence biochemical components, responsible for the discrimination within each stratum. We assess feature fed-SVM analysis for our cancer versus non-cancer model and achieve 91.5 and 83.0 % sensitivity and specificity respectively. We demonstrate the use of infrared light to provide a spectral signature from human serum to detect, for the first time, cancer versus non-cancer, metastatic cancer versus organ confined, brain cancer severity and the organ of origin of metastatic disease from the same sample enabling stratified diagnostics depending upon the clinical question asked.

  17. Efficient multilevel brain tumor segmentation with integrated bayesian model classification.

    PubMed

    Corso, J J; Sharon, E; Dube, S; El-Saden, S; Sinha, U; Yuille, A

    2008-05-01

    We present a new method for automatic segmentation of heterogeneous image data that takes a step toward bridging the gap between bottom-up affinity-based segmentation methods and top-down generative model based approaches. The main contribution of the paper is a Bayesian formulation for incorporating soft model assignments into the calculation of affinities, which are conventionally model free. We integrate the resulting model-aware affinities into the multilevel segmentation by weighted aggregation algorithm, and apply the technique to the task of detecting and segmenting brain tumor and edema in multichannel magnetic resonance (MR) volumes. The computationally efficient method runs orders of magnitude faster than current state-of-the-art techniques giving comparable or improved results. Our quantitative results indicate the benefit of incorporating model-aware affinities into the segmentation process for the difficult case of glioblastoma multiforme brain tumor.

  18. Clinical features of gastroenteropancreatic tumours

    PubMed Central

    Czarnywojtek, Agata; Bączyk, Maciej; Ziemnicka, Katarzyna; Fischbach, Jakub; Wrotkowska, Elżbieta; Ruchała, Marek

    2015-01-01

    Gastroenteropancreatic (GEP) endocrine tumours (carcinoids and pancreatic islet cell tumours) are composed of multipotent neuroendocrine cells that exhibit a unique ability to produce, store, and secrete biologically active substances and cause distinct clinical syndromes. The classification of GEP tumours as functioning or non-functioning is based on the presence of symptoms that accompany these syndromes secondary to the secretion of hormones, neuropeptides and/or neurotransmitters (functioning tumours). Non-functioning tumours are considered to be neoplasms of neuroendocrine differentiation that are not associated with obvious symptoms attributed to the hypersecretion of metabolically active substances. However, a number of these tumours are either capable of producing low levels of such substances, which can be detected by immunohistochemistry but are insufficient to cause symptoms related to a clinical syndrome, or alternatively, they may secrete substances that are either metabolically inactive or inappropriately processed. In some cases, GEP tumours are not associated with the production of any hormone or neurotransmitter. Both functioning and non-functioning tumours can also produce symptoms due to mass effects compressing vital surrounding structures. Gastroenteropancreatic tumours are usually classified further according to the anatomic site of origin: foregut (including respiratory tract, thymus, stomach, duodenum, and pancreas), midgut (including small intestine, appendix, and right colon), and hindgut (including transverse colon, sigmoid, and rectum). Within these subgroups the biological and clinical characteristics of the tumours vary considerably, but this classification is still in use because a significant number of previous studies, mainly observational, have used it extensively. PMID:26516377

  19. The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain masses

    PubMed Central

    2010-01-01

    Background Proton Magnetic Resonance (MR) Spectroscopy (MRS) is a widely available technique for those clinical centres equipped with MR scanners. Unlike the rest of MR-based techniques, MRS yields not images but spectra of metabolites in the tissues. In pathological situations, the MRS profile changes and this has been particularly described for brain tumours. However, radiologists are frequently not familiar to the interpretation of MRS data and for this reason, the usefulness of decision-support systems (DSS) in MRS data analysis has been explored. Results This work presents the INTERPRET DSS version 3.0, analysing the improvements made from its first release in 2002. Version 3.0 is aimed to be a program that 1st, can be easily used with any new case from any MR scanner manufacturer and 2nd, improves the initial analysis capabilities of the first version. The main improvements are an embedded database, user accounts, more diagnostic discrimination capabilities and the possibility to analyse data acquired under additional data acquisition conditions. Other improvements include a customisable graphical user interface (GUI). Most diagnostic problems included have been addressed through a pattern-recognition based approach, in which classifiers based on linear discriminant analysis (LDA) were trained and tested. Conclusions The INTERPRET DSS 3.0 allows radiologists, medical physicists, biochemists or, generally speaking, any person with a minimum knowledge of what an MR spectrum is, to enter their own SV raw data, acquired at 1.5 T, and to analyse them. The system is expected to help in the categorisation of MR Spectra from abnormal brain masses. PMID:21114820

  20. Fast and accurate water content and T2* mapping in brain tumours localised with FET-PET

    NASA Astrophysics Data System (ADS)

    Oros-Peusquens, A.-M.; Keil, F.; Langen, K. J.; Herzog, H.; Stoffels, G.; Weiss, C.; Shah, N. J.

    2014-01-01

    The availability of combined MR-PET scanners opens new opportunities for the characterisation of tumour environment. In this study, water content and relaxation properties of glioblastoma were investigated in five patients using advanced MRI. The region containing metabolically active tumour tissue was defined by simultaneously measured FET-PET uptake. The mean value of water content in tumour tissue - obtained noninvasively with high precision and accuracy for the first time - amounted to 84.5%, similar to the value for normal grey matter. Constancy of water content contrasted with a large variability of T2* values in tumour tissue, qualitatively related to the magnetic inhomogeneity of tissue created by blood vessels and/or microbleeds. The quantitative MRI protocol takes 71/2 > min of measurement time and is proposed for extended clinical use.

  1. Preliminary structural MRI based brain classification of chronic pelvic pain: A MAPP network study.

    PubMed

    Bagarinao, Epifanio; Johnson, Kevin A; Martucci, Katherine T; Ichesco, Eric; Farmer, Melissa A; Labus, Jennifer; Ness, Timothy J; Harris, Richard; Deutsch, Georg; Apkarian, A Vania; Mayer, Emeran A; Clauw, Daniel J; Mackey, Sean

    2014-12-01

    Neuroimaging studies have shown that changes in brain morphology often accompany chronic pain conditions. However, brain biomarkers that are sensitive and specific to chronic pelvic pain (CPP) have not yet been adequately identified. Using data from the Trans-MAPP Research Network, we examined the changes in brain morphology associated with CPP. We used a multivariate pattern classification approach to detect these changes and to identify patterns that could be used to distinguish participants with CPP from age-matched healthy controls. In particular, we used a linear support vector machine (SVM) algorithm to differentiate gray matter images from the 2 groups. Regions of positive SVM weight included several regions within the primary somatosensory cortex, pre-supplementary motor area, hippocampus, and amygdala were identified as important drivers of the classification with 73% overall accuracy. Thus, we have identified a preliminary classifier based on brain structure that is able to predict the presence of CPP with a good degree of predictive power. Our regional findings suggest that in individuals with CPP, greater gray matter density may be found in the identified distributed brain regions, which are consistent with some previous investigations in visceral pain syndromes. Future studies are needed to improve upon our identified preliminary classifier with integration of additional variables and to assess whether the observed differences in brain structure are unique to CPP or generalizable to other chronic pain conditions.

  2. Classification of autism spectrum disorder using supervised learning of brain connectivity measures extracted from synchrostates

    NASA Astrophysics Data System (ADS)

    Jamal, Wasifa; Das, Saptarshi; Oprescu, Ioana-Anastasia; Maharatna, Koushik; Apicella, Fabio; Sicca, Federico

    2014-08-01

    Objective. The paper investigates the presence of autism using the functional brain connectivity measures derived from electro-encephalogram (EEG) of children during face perception tasks. Approach. Phase synchronized patterns from 128-channel EEG signals are obtained for typical children and children with autism spectrum disorder (ASD). The phase synchronized states or synchrostates temporally switch amongst themselves as an underlying process for the completion of a particular cognitive task. We used 12 subjects in each group (ASD and typical) for analyzing their EEG while processing fearful, happy and neutral faces. The minimal and maximally occurring synchrostates for each subject are chosen for extraction of brain connectivity features, which are used for classification between these two groups of subjects. Among different supervised learning techniques, we here explored the discriminant analysis and support vector machine both with polynomial kernels for the classification task. Main results. The leave one out cross-validation of the classification algorithm gives 94.7% accuracy as the best performance with corresponding sensitivity and specificity values as 85.7% and 100% respectively. Significance. The proposed method gives high classification accuracies and outperforms other contemporary research results. The effectiveness of the proposed method for classification of autistic and typical children suggests the possibility of using it on a larger population to validate it for clinical practice.

  3. Window classification of brain CT images in biomedical articles.

    PubMed

    Xue, Zhiyun; Antani, Sameer; Long, L Rodney; Demner-Fushman, Dina; Thoma, George R

    2012-01-01

    Effective capability to search biomedical articles based on visual properties of article images may significantly augment information retrieval in the future. In this paper, we present a new method to classify the window setting types of brain CT images. Windowing is a technique frequently used in the evaluation of CT scans, and is used to enhance contrast for the particular tissue or abnormality type being evaluated. In particular, it provides radiologists with an enhanced view of certain types of cranial abnormalities, such as the skull lesions and bone dysplasia which are usually examined using the " bone window" setting and illustrated in biomedical articles using "bone window images". Due to the inherent large variations of images among articles, it is important that the proposed method is robust. Our algorithm attained 90% accuracy in classifying images as bone window or non-bone window in a 210 image data set.

  4. An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

    PubMed

    Siddiqui, Muhammad Faisal; Reza, Ahmed Wasif; Kanesan, Jeevan

    2015-01-01

    A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the

  5. Classification of EEG with structural feature dictionaries in a brain computer interface.

    PubMed

    Göksu, Fikri; Ince, Nuri Firat; Tadipatri, Vijay Aditya; Tewfik, Ahmed H

    2008-01-01

    We present a new method for the classification of EEG in a brain computer interface by adapting subject specific features in spectral, temporal and spatial domain. For this particular purpose we extend our previous work on ECoG classification based on structural feature dictionary and apply it to extract the spectro-temporal patterns of multichannel EEG recordings related to a motor imagery task. The construction of the feature dictionary based on undecimated wavelet packet transform is extended to block FFT. We evaluate several subset selection algorithms to select a small number of features for final classification. We tested our proposed approach on five subjects of BCI Competition 2005 dataset- IVa. By adapting the wavelet filter for each subject, the algorithm achieved an average classification accuracy of 91.4% The classification results and characteristic of selected features indicate that the proposed algorithm can jointly adapt to EEG patterns in spectro-spatio-temporal domain and provide classification accuracies as good as existing methods used in the literature.

  6. Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface

    NASA Astrophysics Data System (ADS)

    Ceballos, G. A.; Hernández, L. F.

    2015-04-01

    Objective. The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. Approach. Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). Main results. The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. Significance. We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.

  7. Classification of Alzheimer's disease using regional saliency maps from brain MR volumes

    NASA Astrophysics Data System (ADS)

    Pulido, Andrea; Rueda, Andrea; Romero, Eduardo

    2013-02-01

    Accurate diagnosis of Alzheimer's disease (AD) from structural Magnetic Resonance (MR) images is difficult due to the complex alteration of patterns in brain anatomy that could indicate the presence or absence of the pathology. Currently, an effective approach that allows to interpret the disease in terms of global and local changes is not available in the clinical practice. In this paper, we propose an approach for classification of brain MR images, based on finding pathology-related patterns through the identification of regional structural changes. The approach combines a probabilistic Latent Semantic Analysis (pLSA) technique, which allows to identify image regions through latent topics inferred from the brain MR slices, with a bottom-up Graph-Based Visual Saliency (GBVS) model, which calculates maps of relevant information per region. Regional saliency maps are finally combined into a single map on each slice, obtaining a master saliency map of each brain volume. The proposed approach includes a one-to-one comparison of the saliency maps which feeds a Support Vector Machine (SVM) classifier, to group test subjects into normal or probable AD subjects. A set of 156 brain MR images from healthy (76) and pathological (80) subjects, splitted into a training set (10 non-demented and 10 demented subjects) and one testing set (136 subjects), was used to evaluate the performance of the proposed approach. Preliminary results show that the proposed method reaches a maximum classification accuracy of 87.21%.

  8. Classification of normal and pathological aging processes based on brain MRI morphology measures

    NASA Astrophysics Data System (ADS)

    Perez-Gonzalez, J. L.; Yanez-Suarez, O.; Medina-Bañuelos, V.

    2014-03-01

    Reported studies describing normal and abnormal aging based on anatomical MRI analysis do not consider morphological brain changes, but only volumetric measures to distinguish among these processes. This work presents a classification scheme, based both on size and shape features extracted from brain volumes, to determine different aging stages: healthy control (HC) adults, mild cognitive impairment (MCI), and Alzheimer's disease (AD). Three support vector machines were optimized and validated for the pair-wise separation of these three classes, using selected features from a set of 3D discrete compactness measures and normalized volumes of several global and local anatomical structures. Our analysis show classification rates of up to 98.3% between HC and AD; of 85% between HC and MCI and of 93.3% for MCI and AD separation. These results outperform those reported in the literature and demonstrate the viability of the proposed morphological indexes to classify different aging stages.

  9. Feature Extraction from Subband Brain Signals and Its Classification

    NASA Astrophysics Data System (ADS)

    Mukul, Manoj Kumar; Matsuno, Fumitoshi

    This paper considers both the non-stationarity as well as independence/uncorrelated criteria along with the asymmetry ratio over the electroencephalogram (EEG) signals and proposes a hybrid approach of the signal preprocessing methods before the feature extraction. A filter bank approach of the discrete wavelet transform (DWT) is used to exploit the non-stationary characteristics of the EEG signals and it decomposes the raw EEG signals into the subbands of different center frequencies called as rhythm. A post processing of the selected subband by the AMUSE algorithm (a second order statistics based ICA/BSS algorithm) provides the separating matrix for each class of the movement imagery. In the subband domain the orthogonality as well as orthonormality criteria over the whitening matrix and separating matrix do not come respectively. The human brain has an asymmetrical structure. It has been observed that the ratio between the norms of the left and right class separating matrices should be different for better discrimination between these two classes. The alpha/beta band asymmetry ratio between the separating matrices of the left and right classes will provide the condition to select an appropriate multiplier. So we modify the estimated separating matrix by an appropriate multiplier in order to get the required asymmetry and extend the AMUSE algorithm in the subband domain. The desired subband is further subjected to the updated separating matrix to extract subband sub-components from each class. The extracted subband sub-components sources are further subjected to the feature extraction (power spectral density) step followed by the linear discriminant analysis (LDA).

  10. Enhanced Performance of Brain Tumor Classification via Tumor Region Augmentation and Partition.

    PubMed

    Cheng, Jun; Huang, Wei; Cao, Shuangliang; Yang, Ru; Yang, Wei; Yun, Zhaoqiang; Wang, Zhijian; Feng, Qianjin

    2015-01-01

    Automatic classification of tissue types of region of interest (ROI) plays an important role in computer-aided diagnosis. In the current study, we focus on the classification of three types of brain tumors (i.e., meningioma, glioma, and pituitary tumor) in T1-weighted contrast-enhanced MRI (CE-MRI) images. Spatial pyramid matching (SPM), which splits the image into increasingly fine rectangular subregions and computes histograms of local features from each subregion, exhibits excellent results for natural scene classification. However, this approach is not applicable for brain tumors, because of the great variations in tumor shape and size. In this paper, we propose a method to enhance the classification performance. First, the augmented tumor region via image dilation is used as the ROI instead of the original tumor region because tumor surrounding tissues can also offer important clues for tumor types. Second, the augmented tumor region is split into increasingly fine ring-form subregions. We evaluate the efficacy of the proposed method on a large dataset with three feature extraction methods, namely, intensity histogram, gray level co-occurrence matrix (GLCM), and bag-of-words (BoW) model. Compared with using tumor region as ROI, using augmented tumor region as ROI improves the accuracies to 82.31% from 71.39%, 84.75% from 78.18%, and 88.19% from 83.54% for intensity histogram, GLCM, and BoW model, respectively. In addition to region augmentation, ring-form partition can further improve the accuracies up to 87.54%, 89.72%, and 91.28%. These experimental results demonstrate that the proposed method is feasible and effective for the classification of brain tumors in T1-weighted CE-MRI.

  11. Enhanced Performance of Brain Tumor Classification via Tumor Region Augmentation and Partition

    PubMed Central

    Cheng, Jun; Huang, Wei; Cao, Shuangliang; Yang, Ru; Yang, Wei; Yun, Zhaoqiang; Wang, Zhijian; Feng, Qianjin

    2015-01-01

    Automatic classification of tissue types of region of interest (ROI) plays an important role in computer-aided diagnosis. In the current study, we focus on the classification of three types of brain tumors (i.e., meningioma, glioma, and pituitary tumor) in T1-weighted contrast-enhanced MRI (CE-MRI) images. Spatial pyramid matching (SPM), which splits the image into increasingly fine rectangular subregions and computes histograms of local features from each subregion, exhibits excellent results for natural scene classification. However, this approach is not applicable for brain tumors, because of the great variations in tumor shape and size. In this paper, we propose a method to enhance the classification performance. First, the augmented tumor region via image dilation is used as the ROI instead of the original tumor region because tumor surrounding tissues can also offer important clues for tumor types. Second, the augmented tumor region is split into increasingly fine ring-form subregions. We evaluate the efficacy of the proposed method on a large dataset with three feature extraction methods, namely, intensity histogram, gray level co-occurrence matrix (GLCM), and bag-of-words (BoW) model. Compared with using tumor region as ROI, using augmented tumor region as ROI improves the accuracies to 82.31% from 71.39%, 84.75% from 78.18%, and 88.19% from 83.54% for intensity histogram, GLCM, and BoW model, respectively. In addition to region augmentation, ring-form partition can further improve the accuracies up to 87.54%, 89.72%, and 91.28%. These experimental results demonstrate that the proposed method is feasible and effective for the classification of brain tumors in T1-weighted CE-MRI. PMID:26447861

  12. Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards

    PubMed Central

    Plitt, Mark; Barnes, Kelly Anne; Martin, Alex

    2014-01-01

    Objectives Autism spectrum disorders (ASD) are diagnosed based on early-manifesting clinical symptoms, including markedly impaired social communication. We assessed the viability of resting-state functional MRI (rs-fMRI) connectivity measures as diagnostic biomarkers for ASD and investigated which connectivity features are predictive of a diagnosis. Methods Rs-fMRI scans from 59 high functioning males with ASD and 59 age- and IQ-matched typically developing (TD) males were used to build a series of machine learning classifiers. Classification features were obtained using 3 sets of brain regions. Another set of classifiers was built from participants' scores on behavioral metrics. An additional age and IQ-matched cohort of 178 individuals (89 ASD; 89 TD) from the Autism Brain Imaging Data Exchange (ABIDE) open-access dataset (http://fcon_1000.projects.nitrc.org/indi/abide/) were included for replication. Results High classification accuracy was achieved through several rs-fMRI methods (peak accuracy 76.67%). However, classification via behavioral measures consistently surpassed rs-fMRI classifiers (peak accuracy 95.19%). The class probability estimates, P(ASD|fMRI data), from brain-based classifiers significantly correlated with scores on a measure of social functioning, the Social Responsiveness Scale (SRS), as did the most informative features from 2 of the 3 sets of brain-based features. The most informative connections predominantly originated from regions strongly associated with social functioning. Conclusions While individuals can be classified as having ASD with statistically significant accuracy from their rs-fMRI scans alone, this method falls short of biomarker standards. Classification methods provided further evidence that ASD functional connectivity is characterized by dysfunction of large-scale functional networks, particularly those involved in social information processing. PMID:25685703

  13. Automatic and adaptive classification of electroencephalographic signals for brain computer interfaces.

    PubMed

    Rodríguez-Bermúdez, Germán; García-Laencina, Pedro J

    2012-11-01

    Extracting knowledge from electroencephalographic (EEG) signals has become an increasingly important research area in biomedical engineering. In addition to its clinical diagnostic purposes, in recent years there have been many efforts to develop brain computer interface (BCI) systems, which allow users to control external devices only by using their brain activity. Once the EEG signals have been acquired, it is necessary to use appropriate feature extraction and classification methods adapted to the user in order to improve the performance of the BCI system and, also, to make its design stage easier. This work introduces a novel fast adaptive BCI system for automatic feature extraction and classification of EEG signals. The proposed system efficiently combines several well-known feature extraction procedures and automatically chooses the most useful features for performing the classification task. Three different feature extraction techniques are applied: power spectral density, Hjorth parameters and autoregressive modelling. The most relevant features for linear discrimination are selected using a fast and robust wrapper methodology. The proposed method is evaluated using EEG signals from nine subjects during motor imagery tasks. Obtained experimental results show its advantages over the state-of-the-art methods, especially in terms of classification accuracy and computational cost.

  14. Wireless brain-machine interface using EEG and EOG: brain wave classification and robot control

    NASA Astrophysics Data System (ADS)

    Oh, Sechang; Kumar, Prashanth S.; Kwon, Hyeokjun; Varadan, Vijay K.

    2012-04-01

    A brain-machine interface (BMI) links a user's brain activity directly to an external device. It enables a person to control devices using only thought. Hence, it has gained significant interest in the design of assistive devices and systems for people with disabilities. In addition, BMI has also been proposed to replace humans with robots in the performance of dangerous tasks like explosives handling/diffusing, hazardous materials handling, fire fighting etc. There are mainly two types of BMI based on the measurement method of brain activity; invasive and non-invasive. Invasive BMI can provide pristine signals but it is expensive and surgery may lead to undesirable side effects. Recent advances in non-invasive BMI have opened the possibility of generating robust control signals from noisy brain activity signals like EEG and EOG. A practical implementation of a non-invasive BMI such as robot control requires: acquisition of brain signals with a robust wearable unit, noise filtering and signal processing, identification and extraction of relevant brain wave features and finally, an algorithm to determine control signals based on the wave features. In this work, we developed a wireless brain-machine interface with a small platform and established a BMI that can be used to control the movement of a robot by using the extracted features of the EEG and EOG signals. The system records and classifies EEG as alpha, beta, delta, and theta waves. The classified brain waves are then used to define the level of attention. The acceleration and deceleration or stopping of the robot is controlled based on the attention level of the wearer. In addition, the left and right movements of eye ball control the direction of the robot.

  15. New KF-PP-SVM classification method for EEG in brain-computer interfaces.

    PubMed

    Yang, Banghua; Han, Zhijun; Zan, Peng; Wang, Qian

    2014-01-01

    Classification methods are a crucial direction in the current study of brain-computer interfaces (BCIs). To improve the classification accuracy for electroencephalogram (EEG) signals, a novel KF-PP-SVM (kernel fisher, posterior probability, and support vector machine) classification method is developed. Its detailed process entails the use of common spatial patterns to obtain features, based on which the within-class scatter is calculated. Then the scatter is added into the kernel function of a radial basis function to construct a new kernel function. This new kernel is integrated into the SVM to obtain a new classification model. Finally, the output of SVM is calculated based on posterior probability and the final recognition result is obtained. To evaluate the effectiveness of the proposed KF-PP-SVM method, EEG data collected from laboratory are processed with four different classification schemes (KF-PP-SVM, KF-SVM, PP-SVM, and SVM). The results showed that the overall average improvements arising from the use of the KF-PP-SVM scheme as opposed to KF-SVM, PP-SVM and SVM schemes are 2.49%, 5.83 % and 6.49 % respectively.

  16. Supervised, Multivariate, Whole-Brain Reduction Did Not Help to Achieve High Classification Performance in Schizophrenia Research

    PubMed Central

    Janousova, Eva; Montana, Giovanni; Kasparek, Tomas; Schwarz, Daniel

    2016-01-01

    We examined how penalized linear discriminant analysis with resampling, which is a supervised, multivariate, whole-brain reduction technique, can help schizophrenia diagnostics and research. In an experiment with magnetic resonance brain images of 52 first-episode schizophrenia patients and 52 healthy controls, this method allowed us to select brain areas relevant to schizophrenia, such as the left prefrontal cortex, the anterior cingulum, the right anterior insula, the thalamus, and the hippocampus. Nevertheless, the classification performance based on such reduced data was not significantly better than the classification of data reduced by mass univariate selection using a t-test or unsupervised multivariate reduction using principal component analysis. Moreover, we found no important influence of the type of imaging features, namely local deformations or gray matter volumes, and the classification method, specifically linear discriminant analysis or linear support vector machines, on the classification results. However, we ascertained significant effect of a cross-validation setting on classification performance as classification results were overestimated even though the resampling was performed during the selection of brain imaging features. Therefore, it is critically important to perform cross-validation in all steps of the analysis (not only during classification) in case there is no external validation set to avoid optimistically biasing the results of classification studies. PMID:27610072

  17. Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

    NASA Astrophysics Data System (ADS)

    Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

    2014-01-01

    We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

  18. Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue.

    PubMed

    Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

    2014-01-01

    We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

  19. Generation of brain tumours in mice by Cre-mediated recombination of neural progenitors in situ with the tamoxifen metabolite endoxifen.

    PubMed

    Benedykcinska, Anna; Ferreira, Andreia; Lau, Joanne; Broni, Jessica; Richard-Loendt, Angela; Henriquez, Nico V; Brandner, Sebastian

    2016-02-01

    Targeted cell- or region-specific gene recombination is widely used in the functional analysis of genes implicated in development and disease. In the brain, targeted gene recombination has become a mainstream approach to study neurodegeneration or tumorigenesis. The use of the Cre-loxP system to study tumorigenesis in the adult central nervous system (CNS) can be limited, when the promoter (such as GFAP) is also transiently expressed during development, which can result in the recombination of progenies of different lineages. Engineering of transgenic mice expressing Cre recombinase fused to a mutant of the human oestrogen receptor (ER) allows the circumvention of transient developmental Cre expression by inducing recombination in the adult organism. The recombination of loxP sequences occurs only in the presence of tamoxifen. Systemic administration of tamoxifen can, however, exhibit toxicity and might also recombine unwanted cell populations if the promoter driving Cre expression is active at the time of tamoxifen administration. Here, we report that a single site-specific injection of an active derivative of tamoxifen successfully activates Cre recombinase and selectively recombines tumour suppressor genes in neural progenitor cells of the subventricular zone in mice, and we demonstrate its application in a model for the generation of intrinsic brain tumours.

  20. Case-control study of the association between malignant brain tumours diagnosed between 2007 and 2009 and mobile and cordless phone use

    PubMed Central

    HARDELL, LENNART; CARLBERG, MICHAEL; SÖDERQVIST, FREDRIK; MILD, KJELL HANSSON

    2013-01-01

    Previous studies have shown a consistent association between long-term use of mobile and cordless phones and glioma and acoustic neuroma, but not for meningioma. When used these phones emit radiofrequency electromagnetic fields (RF-EMFs) and the brain is the main target organ for the hand-held phone. The International Agency for Research on Cancer (IARC) classified in May, 2011 RF-EMF as a group 2B, i.e. a ‘possible’ human carcinogen. The aim of this study was to further explore the relationship between especially long-term (>10 years) use of wireless phones and the development of malignant brain tumours. We conducted a new case-control study of brain tumour cases of both genders aged 18–75 years and diagnosed during 2007–2009. One population-based control matched on gender and age (within 5 years) was used to each case. Here, we report on malignant cases including all available controls. Exposures on e.g. use of mobile phones and cordless phones were assessed by a self-administered questionnaire. Unconditional logistic regression analysis was performed, adjusting for age, gender, year of diagnosis and socio-economic index using the whole control sample. Of the cases with a malignant brain tumour, 87% (n=593) participated, and 85% (n=1,368) of controls in the whole study answered the questionnaire. The odds ratio (OR) for mobile phone use of the analogue type was 1.8, 95% confidence interval (CI)=1.04–3.3, increasing with >25 years of latency (time since first exposure) to an OR=3.3, 95% CI=1.6–6.9. Digital 2G mobile phone use rendered an OR=1.6, 95% CI=0.996–2.7, increasing with latency >15–20 years to an OR=2.1, 95% CI=1.2–3.6. The results for cordless phone use were OR=1.7, 95% CI=1.1–2.9, and, for latency of 15–20 years, the OR=2.1, 95% CI=1.2–3.8. Few participants had used a cordless phone for >20–25 years. Digital type of wireless phones (2G and 3G mobile phones, cordless phones) gave increased risk with latency >1–5 years, then a

  1. Case-control study of the association between malignant brain tumours diagnosed between 2007 and 2009 and mobile and cordless phone use.

    PubMed

    Hardell, Lennart; Carlberg, Michael; Söderqvist, Fredrik; Mild, Kjell Hansson

    2013-12-01

    Previous studies have shown a consistent association between long-term use of mobile and cordless phones and glioma and acoustic neuroma, but not for meningioma. When used these phones emit radiofrequency electromagnetic fields (RF-EMFs) and the brain is the main target organ for the handheld phone. The International Agency for Research on Cancer (IARC) classified in May, 2011 RF-EMF as a group 2B, i.e. a 'possible' human carcinogen. The aim of this study was to further explore the relationship between especially long-term (>10 years) use of wireless phones and the development of malignant brain tumours. We conducted a new case-control study of brain tumour cases of both genders aged 18-75 years and diagnosed during 2007-2009. One population-based control matched on gender and age (within 5 years) was used to each case. Here, we report on malignant cases including all available controls. Exposures on e.g. use of mobile phones and cordless phones were assessed by a self-administered questionnaire. Unconditional logistic regression analysis was performed, adjusting for age, gender, year of diagnosis and socio-economic index using the whole control sample. Of the cases with a malignant brain tumour, 87% (n=593) participated, and 85% (n=1,368) of controls in the whole study answered the questionnaire. The odds ratio (OR) for mobile phone use of the analogue type was 1.8, 95% confidence interval (CI)=1.04‑3.3, increasing with >25 years of latency (time since first exposure) to an OR=3.3, 95% CI=1.6-6.9. Digital 2G mobile phone use rendered an OR=1.6, 95% CI=0.996-2.7, increasing with latency >15-20 years to an OR=2.1, 95% CI=1.2-3.6. The results for cordless phone use were OR=1.7, 95% CI=1.1-2.9, and, for latency of 15-20 years, the OR=2.1, 95% CI=1.2-3.8. Few participants had used a cordless phone for >20-25 years. Digital type of wireless phones (2G and 3G mobile phones, cordless phones) gave increased risk with latency >1-5 years, then a lower risk in the following

  2. Correlation of tumour BRAF mutations and MLH1 methylation with germline mismatch repair (MMR) gene mutation status: a literature review assessing utility of tumour features for MMR variant classification.

    PubMed

    Parsons, Michael T; Buchanan, Daniel D; Thompson, Bryony; Young, Joanne P; Spurdle, Amanda B

    2012-03-01

    Colorectal cancer (CRC) that demonstrates microsatellite instability (MSI) is caused by either germline mismatch repair (MMR) gene mutations, or 'sporadic' somatic tumour MLH1 promoter methylation. MLH1 promoter methylation is reportedly correlated with tumour BRAF V600E mutation status. No systematic review has been undertaken to assess the value of BRAF V600E mutation and MLH1 promoter methylation tumour markers as negative predictors of germline MMR mutation status. A literature review of CRC cohorts tested for MMR mutations, and tumour BRAF V600E mutation and/or MLH1 promoter methylation was conducted using PubMed. Studies were assessed for tumour features, stratified by tumour MMR status based on immunohistochemistry or MSI where possible. Pooled frequencies and 95% CIs were calculated using a random effects model. BRAF V600E results for 4562 tumours from 35 studies, and MLH1 promoter methylation results for 2975 tumours from 43 studies, were assessed. In 550 MMR mutation carriers, the BRAF V600E mutation frequency was 1.40% (95% CI 0.06% to 3%). In MMR mutation-negative cases, the BRAF V600E mutation frequency was 5.00% (95% CI 4% to 7%) in 1623 microsatellite stable (MSS) cases and 63.50% (95% CI 47% to 79%) in 332 cases demonstrating MLH1 methylation or MLH1 expression loss. MLH1 promoter methylation of the 'A region' was reported more frequently than the 'C region' in MSS CRCs (17% vs 0.06%, p<0.0001) and in MLH1 mutation carriers (42% vs 6%, p<0.0001), but not in MMR mutation-negative MSI-H CRCs (40% vs 47%, p=0.12). Methylation of the 'C region' was a predictor of MMR mutation-negative status in MSI-H CRC cases (47% vs 6% in MLH1 mutation carriers, p<0.0001). This review demonstrates that tumour BRAF V600E mutation, and MLH1 promoter 'C region' methylation specifically, are strong predictors of negative MMR mutation status. It is important to incorporate these features in multifactorial models aimed at predicting MMR mutation status.

  3. Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

    PubMed Central

    Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V.; Robles, Montserrat; Aparici, F.; Martí-Bonmatí, L.; García-Gómez, Juan M.

    2015-01-01

    Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation. PMID:25978453

  4. Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification.

    PubMed

    Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V; Robles, Montserrat; Aparici, F; Martí-Bonmatí, L; García-Gómez, Juan M

    2015-01-01

    Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.

  5. Predict or classify: The deceptive role of time-locking in brain signal classification

    PubMed Central

    Rusconi, Marco; Valleriani, Angelo

    2016-01-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal. PMID:27320688

  6. Predict or classify: The deceptive role of time-locking in brain signal classification

    NASA Astrophysics Data System (ADS)

    Rusconi, Marco; Valleriani, Angelo

    2016-06-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.

  7. Predict or classify: The deceptive role of time-locking in brain signal classification.

    PubMed

    Rusconi, Marco; Valleriani, Angelo

    2016-06-20

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.

  8. Classification of mathematics deficiency using shape and scale analysis of 3D brain structures

    NASA Astrophysics Data System (ADS)

    Kurtek, Sebastian; Klassen, Eric; Gore, John C.; Ding, Zhaohua; Srivastava, Anuj

    2011-03-01

    We investigate the use of a recent technique for shape analysis of brain substructures in identifying learning disabilities in third-grade children. This Riemannian technique provides a quantification of differences in shapes of parameterized surfaces, using a distance that is invariant to rigid motions and re-parameterizations. Additionally, it provides an optimal registration across surfaces for improved matching and comparisons. We utilize an efficient gradient based method to obtain the optimal re-parameterizations of surfaces. In this study we consider 20 different substructures in the human brain and correlate the differences in their shapes with abnormalities manifested in deficiency of mathematical skills in 106 subjects. The selection of these structures is motivated in part by the past links between their shapes and cognitive skills, albeit in broader contexts. We have studied the use of both individual substructures and multiple structures jointly for disease classification. Using a leave-one-out nearest neighbor classifier, we obtained a 62.3% classification rate based on the shape of the left hippocampus. The use of multiple structures resulted in an improved classification rate of 71.4%.

  9. Brain Network Activation Analysis Utilizing Spatiotemporal Features for Event Related Potentials Classification

    PubMed Central

    Stern, Yaki; Reches, Amit; Geva, Amir B.

    2016-01-01

    The purpose of this study was to introduce an improved tool for automated classification of event-related potentials (ERPs) using spatiotemporally parcellated events incorporated into a functional brain network activation (BNA) analysis. The auditory oddball ERP paradigm was selected to demonstrate and evaluate the improved tool. Methods: The ERPs of each subject were decomposed into major dynamic spatiotemporal events. Then, a set of spatiotemporal events representing the group was generated by aligning and clustering the spatiotemporal events of all individual subjects. The temporal relationship between the common group events generated a network, which is the spatiotemporal reference BNA model. Scores were derived by comparing each subject's spatiotemporal events to the reference BNA model and were then entered into a support vector machine classifier to classify subjects into relevant subgroups. The reliability of the BNA scores (test-retest repeatability using intraclass correlation) and their utility as a classification tool were examined in the context of Target-Novel classification. Results: BNA intraclass correlation values of repeatability ranged between 0.51 and 0.82 for the known ERP components N100, P200, and P300. Classification accuracy was high when the trained data were validated on the same subjects for different visits (AUCs 0.93 and 0.95). The classification accuracy remained high for a test group recorded at a different clinical center with a different recording system (AUCs 0.81, 0.85 for 2 visits). Conclusion: The improved spatiotemporal BNA analysis demonstrates high classification accuracy. The BNA analysis method holds promise as a tool for diagnosis, follow-up and drug development associated with different neurological conditions. PMID:28066224

  10. Computational Classification Approach to Profile Neuron Subtypes from Brain Activity Mapping Data.

    PubMed

    Li, Meng; Zhao, Fang; Lee, Jason; Wang, Dong; Kuang, Hui; Tsien, Joe Z

    2015-07-27

    The analysis of cell type-specific activity patterns during behaviors is important for better understanding of how neural circuits generate cognition, but has not been well explored from in vivo neurophysiological datasets. Here, we describe a computational approach to uncover distinct cell subpopulations from in vivo neural spike datasets. This method, termed "inter-spike-interval classification-analysis" (ISICA), is comprised of four major steps: spike pattern feature-extraction, pre-clustering analysis, clustering classification, and unbiased classification-dimensionality selection. By using two key features of spike dynamic - namely, gamma distribution shape factors and a coefficient of variation of inter-spike interval - we show that this ISICA method provides invariant classification for dopaminergic neurons or CA1 pyramidal cell subtypes regardless of the brain states from which spike data were collected. Moreover, we show that these ISICA-classified neuron subtypes underlie distinct physiological functions. We demonstrate that the uncovered dopaminergic neuron subtypes encoded distinct aspects of fearful experiences such as valence or value, whereas distinct hippocampal CA1 pyramidal cells responded differentially to ketamine-induced anesthesia. This ISICA method should be useful to better data mining of large-scale in vivo neural datasets, leading to novel insights into circuit dynamics associated with cognitions.

  11. Computational Classification Approach to Profile Neuron Subtypes from Brain Activity Mapping Data

    PubMed Central

    Li, Meng; Zhao, Fang; Lee, Jason; Wang, Dong; Kuang, Hui; Tsien, Joe Z.

    2015-01-01

    The analysis of cell type-specific activity patterns during behaviors is important for better understanding of how neural circuits generate cognition, but has not been well explored from in vivo neurophysiological datasets. Here, we describe a computational approach to uncover distinct cell subpopulations from in vivo neural spike datasets. This method, termed “inter-spike-interval classification-analysis” (ISICA), is comprised of four major steps: spike pattern feature-extraction, pre-clustering analysis, clustering classification, and unbiased classification-dimensionality selection. By using two key features of spike dynamic - namely, gamma distribution shape factors and a coefficient of variation of inter-spike interval - we show that this ISICA method provides invariant classification for dopaminergic neurons or CA1 pyramidal cell subtypes regardless of the brain states from which spike data were collected. Moreover, we show that these ISICA-classified neuron subtypes underlie distinct physiological functions. We demonstrate that the uncovered dopaminergic neuron subtypes encoded distinct aspects of fearful experiences such as valence or value, whereas distinct hippocampal CA1 pyramidal cells responded differentially to ketamine-induced anesthesia. This ISICA method should be useful to better data mining of large-scale in vivo neural datasets, leading to novel insights into circuit dynamics associated with cognitions. PMID:26212360

  12. Asynchronous P300 classification in a reactive brain-computer interface during an outlier detection task

    NASA Astrophysics Data System (ADS)

    Krumpe, Tanja; Walter, Carina; Rosenstiel, Wolfgang; Spüler, Martin

    2016-08-01

    Objective. In this study, the feasibility of detecting a P300 via an asynchronous classification mode in a reactive EEG-based brain-computer interface (BCI) was evaluated. The P300 is one of the most popular BCI control signals and therefore used in many applications, mostly for active communication purposes (e.g. P300 speller). As the majority of all systems work with a stimulus-locked mode of classification (synchronous), the field of applications is limited. A new approach needs to be applied in a setting in which a stimulus-locked classification cannot be used due to the fact that the presented stimuli cannot be controlled or predicted by the system. Approach. A continuous observation task requiring the detection of outliers was implemented to test such an approach. The study was divided into an offline and an online part. Main results. Both parts of the study revealed that an asynchronous detection of the P300 can successfully be used to detect single events with high specificity. It also revealed that no significant difference in performance was found between the synchronous and the asynchronous approach. Significance. The results encourage the use of an asynchronous classification approach in suitable applications without a potential loss in performance.

  13. Classification

    ERIC Educational Resources Information Center

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  14. Computerized “Learn-As-You-Go” Classification of Traumatic Brain Injuries Using NEISS Narrative Data

    PubMed Central

    Chen, Wei; Wheeler, Krista K; Lin, Simon; Huang, Yungui; Xiang, Huiyun

    2016-01-01

    One important routine task in injury research is to effectively classify injury circumstances into user-defined categories when using narrative text. However, traditional manual processes can be time consuming, and existing batch learning systems can be difficult to utilize by novice users. This study evaluates a “learn-as-you-go” machine-learning program. When using this program, the user trains classification models and interactively checks on accuracy until a desired threshold is reached. We examined the narrative text of traumatic brain injuries (TBIs) in the National Electronic Injury Surveillance System (NEISS) and classified TBIs into sport and non-sport categories. Our results suggest that the DUALIST “Learn-As-You-Go” program, which features a user-friendly online interface, is effective in injury narrative classification. In our study, the time frame to classify tens of thousands of narratives was reduced from a few days to minutes after approximately sixty minutes of training. PMID:26851618

  15. Brain tumor classification using the diffusion tensor image segmentation (D-SEG) technique

    PubMed Central

    Jones, Timothy L.; Byrnes, Tiernan J.; Yang, Guang; Howe, Franklyn A.; Bell, B. Anthony; Barrick, Thomas R.

    2015-01-01

    Background There is an increasing demand for noninvasive brain tumor biomarkers to guide surgery and subsequent oncotherapy. We present a novel whole-brain diffusion tensor imaging (DTI) segmentation (D-SEG) to delineate tumor volumes of interest (VOIs) for subsequent classification of tumor type. D-SEG uses isotropic (p) and anisotropic (q) components of the diffusion tensor to segment regions with similar diffusion characteristics. Methods DTI scans were acquired from 95 patients with low- and high-grade glioma, metastases, and meningioma and from 29 healthy subjects. D-SEG uses k-means clustering of the 2D (p,q) space to generate segments with different isotropic and anisotropic diffusion characteristics. Results Our results are visualized using a novel RGB color scheme incorporating p, q and T2-weighted information within each segment. The volumetric contribution of each segment to gray matter, white matter, and cerebrospinal fluid spaces was used to generate healthy tissue D-SEG spectra. Tumor VOIs were extracted using a semiautomated flood-filling technique and D-SEG spectra were computed within the VOI. Classification of tumor type using D-SEG spectra was performed using support vector machines. D-SEG was computationally fast and stable and delineated regions of healthy tissue from tumor and edema. D-SEG spectra were consistent for each tumor type, with constituent diffusion characteristics potentially reflecting regional differences in tissue microstructure. Support vector machines classified tumor type with an overall accuracy of 94.7%, providing better classification than previously reported. Conclusions D-SEG presents a user-friendly, semiautomated biomarker that may provide a valuable adjunct in noninvasive brain tumor diagnosis and treatment planning. PMID:25121771

  16. The ‘radiation vacation’: Parents’ experiences of travelling to have their children’s brain tumours treated with proton beam therapy

    PubMed Central

    Cockle, Sam G; Ogden, Jane

    2016-01-01

    Proton beam therapy is a new form of radiotherapy. Little is known about patients’ experiences of proton beam therapy and less about parents’ experiences of children receiving treatment. Semi-structured interviews explored 10 parents’ experiences of travelling from the United Kingdom to the United States to have their children’s brain tumours treated with proton beam therapy. Thematic analysis uncovered themes of ‘adjusting to the PBT routine’, ‘finding benefit in the situation’ and ‘readjusting upon returning home’. Parents’ initial worries were elevated by travel, but they found benefit in their experiences, describing them positively. The periods before and after treatment were most difficult, illustrating a cycle from upset to calm, back to upset upon their return home. PMID:28070403

  17. New Zealand adolescents’ cellphone and cordless phone user-habits: are they at increased risk of brain tumours already? A cross-sectional study

    PubMed Central

    2013-01-01

    Background Cellphone and cordless phone use is very prevalent among early adolescents, but the extent and types of use is not well documented. This paper explores how, and to what extent, New Zealand adolescents are typically using and exposed to active cellphones and cordless phones, and considers implications of this in relation to brain tumour risk, with reference to current research findings. Methods This cross-sectional study recruited 373 Year 7 and 8 school students with a mean age of 12.3 years (range 10.3-13.7 years) from the Wellington region of New Zealand. Participants completed a questionnaire and measured their normal body-to-phone texting distances. Main exposure-metrics included self-reported time spent with an active cellphone close to the body, estimated time and number of calls on both phone types, estimated and actual extent of SMS text-messaging, cellphone functions used and people texted. Statistical analyses used Pearson Chi2 tests and Pearson’s correlation coefficient (r). Analyses were undertaken using SPSS version 19.0. Results Both cellphones and cordless phones were used by approximately 90% of students. A third of participants had already used a cordless phone for ≥ 7 years. In 4 years from the survey to mid-2013, the cordless phone use of 6% of participants would equal that of the highest Interphone decile (≥ 1640 hours), at the surveyed rate of use. High cellphone use was related to cellphone location at night, being woken regularly, and being tired at school. More than a third of parents thought cellphones carried a moderate-to-high health risk for their child. Conclusions While cellphones were very popular for entertainment and social interaction via texting, cordless phones were most popular for calls. If their use continued at the reported rate, many would be at increased risk of specific brain tumours by their mid-teens, based on findings of the Interphone and Hardell-group studies. PMID:23302218

  18. Pooled analysis of case-control studies on malignant brain tumours and the use of mobile and cordless phones including living and deceased subjects.

    PubMed

    Hardell, Lennart; Carlberg, Michael; Hansson Mild, Kjell

    2011-05-01

    We studied the association between use of mobile and cordless phones and malignant brain tumours. Pooled analysis was performed of two case-control studies on patients with malignant brain tumours diagnosed during 1997-2003 and matched controls alive at the time of study inclusion and one case-control study on deceased patients and controls diagnosed during the same time period. Cases and controls or relatives to deceased subjects were interviewed using a structured questionnaire. Replies were obtained for 1,251 (85%) cases and 2,438 (84%) controls. The risk increased with latency period and cumulative use in hours for both mobile and cordless phones. Highest risk was found for the most common type of glioma, astrocytoma, yielding in the >10 year latency group for mobile phone use odds ratio (OR) = 2.7, 95% confidence interval (CI) = 1.9-3.7 and cordless phone use OR = 1.8, 95% CI = 1.2-2.9. In a separate analysis, these phone types were independent risk factors for glioma. The risk for astrocytoma was highest in the group with first use of a wireless phone before the age of 20; mobile phone use OR = 4.9, 95% CI = 2.2-11, cordless phone use OR = 3.9, 95% CI = 1.7-8.7. In conclusion, an increased risk was found for glioma and use of mobile or cordless phone. The risk increased with latency time and cumulative use in hours and was highest in subjects with first use before the age of 20.

  19. Threshold selection for classification of MR brain images by clustering method

    NASA Astrophysics Data System (ADS)

    Moldovanu, Simona; Obreja, Cristian; Moraru, Luminita

    2015-12-01

    Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

  20. Threshold selection for classification of MR brain images by clustering method

    SciTech Connect

    Moldovanu, Simona; Obreja, Cristian; Moraru, Luminita

    2015-12-07

    Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

  1. Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity.

    PubMed

    Rashid, Barnaly; Arbabshirani, Mohammad R; Damaraju, Eswar; Cetin, Mustafa S; Miller, Robyn; Pearlson, Godfrey D; Calhoun, Vince D

    2016-07-01

    Recently, functional network connectivity (FNC, defined as the temporal correlation among spatially distant brain networks) has been used to examine the functional organization of brain networks in various psychiatric illnesses. Dynamic FNC is a recent extension of the conventional FNC analysis that takes into account FNC changes over short periods of time. While such dynamic FNC measures may be more informative about various aspects of connectivity, there has been no detailed head-to-head comparison of the ability of static and dynamic FNC to perform classification in complex mental illnesses. This paper proposes a framework for automatic classification of schizophrenia, bipolar and healthy subjects based on their static and dynamic FNC features. Also, we compare cross-validated classification performance between static and dynamic FNC. Results show that the dynamic FNC significantly outperforms the static FNC in terms of predictive accuracy, indicating that features from dynamic FNC have distinct advantages over static FNC for classification purposes. Moreover, combining static and dynamic FNC features does not significantly improve the classification performance over the dynamic FNC features alone, suggesting that static FNC does not add any significant information when combined with dynamic FNC for classification purposes. A three-way classification methodology based on static and dynamic FNC features discriminates individual subjects into appropriate diagnostic groups with high accuracy. Our proposed classification framework is potentially applicable to additional mental disorders.

  2. Classification of brain disease in magnetic resonance images using two-stage local feature fusion

    PubMed Central

    Li, Tao; Li, Wu; Yang, Yehui

    2017-01-01

    Background Many classification methods have been proposed based on magnetic resonance images. Most methods rely on measures such as volume, the cerebral cortical thickness and grey matter density. These measures are susceptible to the performance of registration and limited in representation of anatomical structure. This paper proposes a two-stage local feature fusion method, in which deformable registration is not desired and anatomical information is represented from moderate scale. Methods Keypoints are firstly extracted from scale-space to represent anatomical structure. Then, two kinds of local features are calculated around the keypoints, one for correspondence and the other for representation. Scores are assigned for keypoints to quantify their effect in classification. The sum of scores for all effective keypoints is used to determine which group the test subject belongs to. Results We apply this method to magnetic resonance images of Alzheimer's disease and Parkinson's disease. The advantage of local feature in correspondence and representation contributes to the final classification. With the help of local feature (Scale Invariant Feature Transform, SIFT) in correspondence, the performance becomes better. Local feature (Histogram of Oriented Gradient, HOG) extracted from 16×16 cell block obtains better results compared with 4×4 and 8×8 cell block. Discussion This paper presents a method which combines the effect of SIFT descriptor in correspondence and the representation ability of HOG descriptor in anatomical structure. This method has the potential in distinguishing patients with brain disease from controls. PMID:28207873

  3. Diagnosis, classification and grading of canine mammary tumours as a model to study human breast cancer: an Clinico-Cytohistopathological study with environmental factors influencing public health and medicine

    PubMed Central

    2013-01-01

    Background The human “Elston and Ellis grading method” was utilized in dogs with mammary tumor to examine its relation to prognosis in this species, based on a 2-year follow-up period. Although cytopathology is widely used for early diagnosis of human neoplasms, it is not commonly performed in veterinary medicine. Our objectives in this study were to identify cytopathology criteria of malignancy for canine mammary tumors and the frequency of different types of mammary lesions and their relationship with histologic grade was investigated. Another aim of this study was to differentiate the simple and adenocarcinoma tumors from the complex or mixed tumor described by Elston and Ellis grading method. Methods The study was performed in 15 pure or mixed-breed female dogs submitted to surgical resections of mammary tumours. The mammary tumours were excised by simple mastectomy or regional mastectomy, with or without the superficial inguinal lymph nodes. Female dogs were mainly terriers (9 dogs) or mixed (3 dogs), the 3 other animals were a German shepherd, Dachshund and Pekingese. Before surgical excision of the tumour, FNAC was performed using a 0.6 mm diameter needle attached to a 10 ml syringe held in a standard metal syringe holder. The cytological sample was smeared onto a glass slide and either air-dried for May-Grünwald-stain, or ethanol-fixed for Papanicolaou stain and masses were surgically removed, the tumours were grossly examined and tissue samples were fixed in 10%-buffered-formalin and embedded in paraffin. Sections 4 μm thick were obtained from each sample and H&E stained. Results We obtained a correct cytohistological correlation in 14/15 cases (93.3%) when all cytopathological examinations were considered. Of the 15 cases examined, 2(13.3%) had well-differentiated (grade I), 6(40%) had moderately differentiated (grade II) and 7(46.7%) had poorly differentiated (grade III) tumours. Classification of all canine mammary gland lesions revealed 13

  4. Impact of brain tumour location on emotion and personality: a voxel-based lesion-symptom mapping study on mentalization processes.

    PubMed

    Campanella, Fabio; Shallice, Tim; Ius, Tamara; Fabbro, Franco; Skrap, Miran

    2014-09-01

    Patients affected by brain tumours may show behavioural and emotional regulation deficits, sometimes showing flattened affect and sometimes experiencing a true 'change' in personality. However, little evidence is available to the surgeon as to what changes are likely to occur with damage at specific sites, as previous studies have either relied on single cases or provided only limited anatomical specificity, mostly reporting associations rather than dissociations of symptoms. We investigated these aspects in patients undergoing surgery for the removal of cerebral tumours. We argued that many of the problems described can be ascribed to the onset of difficulties in one or more of the different levels of the process of mentalizing (i.e. abstracting and reflecting upon) emotion and intentions, which impacts on everyday behaviour. These were investigated in terms of (i) emotion recognition; (ii) Theory of Mind; (iii) alexithymia; and (iv) self-maturity (personality disorder). We hypothesized that temporo/limbic areas would be critical for processing emotion and intentions at a more perceptual level, while frontal lobe structures would be more critical when higher levels of mentalization/abstraction are required. We administered four different tasks, Task 1: emotion recognition of Ekman faces; Task 2: the Eyes Test (Theory of Mind); Task 3: Toronto Alexithymia Scale; and Task 4: Temperament and Character Inventory (a personality inventory), both immediately before and few days after the operation for the removal of brain tumours in a series of 71 patients (age range: 18-75 years; 33 female) with lesions located in the left or right frontal, temporal and parietal lobes. Lobe-based and voxel-based analysis confirmed that tasks requiring interpretation of emotions and intentions at more basic (less mentalized) levels (Tasks 1 and 2) were more affected by temporo/insular lesions, with emotion recognition (Task 1) being maximally impaired by anterior temporal and amygdala

  5. Voxel-based discriminant map classification on brain ventricles for Alzheimer's disease

    NASA Astrophysics Data System (ADS)

    Wang, Jingnan; de Haan, Gerard; Unay, Devrim; Soldea, Octavian; Ekin, Ahmet

    2009-02-01

    One major hallmark of the Alzheimer's disease (AD) is the loss of neurons in the brain. In many cases, medical experts use magnetic resonance imaging (MRI) to qualitatively measure the neuronal loss by the shrinkage or enlargement of the structures-of-interest. Brain ventricle is one of the popular choices. It is easily detectable in clinical MR images due to the high contrast of the cerebro-spinal fluid (CSF) with the rest of the parenchyma. Moreover, atrophy in any periventricular structure will directly lead to ventricle enlargement. For quantitative analysis, volume is the common choice. However, volume is a gross measure and it cannot capture the entire complexity of the anatomical shape. Since most existing shape descriptors are complex and difficult-to-reproduce, more straightforward and robust ways to extract ventricle shape features are preferred in the diagnosis. In this paper, a novel ventricle shape based classification method for Alzheimer's disease has been proposed. Training process is carried out to generate two probability maps for two training classes: healthy controls (HC) and AD patients. By subtracting the HC probability map from the AD probability map, we get a 3D ventricle discriminant map. Then a matching coefficient has been calculated between each training subject and the discriminant map. An adjustable cut-off point of the matching coefficients has been drawn for the two classes. Generally, the higher the cut-off point that has been drawn, the higher specificity can be achieved. However, it will result in relatively lower sensitivity and vice versa. The benchmarked results against volume based classification show that the area under the ROC curves for our proposed method is as high as 0.86 compared with only 0.71 for volume based classification method.

  6. New tissue priors for improved automated classification of subcortical brain structures on MRI☆

    PubMed Central

    Lorio, S.; Fresard, S.; Adaszewski, S.; Kherif, F.; Chowdhury, R.; Frackowiak, R.S.; Ashburner, J.; Helms, G.; Weiskopf, N.; Lutti, A.; Draganski, B.

    2016-01-01

    Despite the constant improvement of algorithms for automated brain tissue classification, the accurate delineation of subcortical structures using magnetic resonance images (MRI) data remains challenging. The main difficulties arise from the low gray-white matter contrast of iron rich areas in T1-weighted (T1w) MRI data and from the lack of adequate priors for basal ganglia and thalamus. The most recent attempts to obtain such priors were based on cohorts with limited size that included subjects in a narrow age range, failing to account for age-related gray-white matter contrast changes. Aiming to improve the anatomical plausibility of automated brain tissue classification from T1w data, we have created new tissue probability maps for subcortical gray matter regions. Supported by atlas-derived spatial information, raters manually labeled subcortical structures in a cohort of healthy subjects using magnetization transfer saturation and R2* MRI maps, which feature optimal gray-white matter contrast in these areas. After assessment of inter-rater variability, the new tissue priors were tested on T1w data within the framework of voxel-based morphometry. The automated detection of gray matter in subcortical areas with our new probability maps was more anatomically plausible compared to the one derived with currently available priors. We provide evidence that the improved delineation compensates age-related bias in the segmentation of iron rich subcortical regions. The new tissue priors, allowing robust detection of basal ganglia and thalamus, have the potential to enhance the sensitivity of voxel-based morphometry in both healthy and diseased brains. PMID:26854557

  7. Graph Theory-Based Brain Connectivity for Automatic Classification of Multiple Sclerosis Clinical Courses

    PubMed Central

    Kocevar, Gabriel; Stamile, Claudio; Hannoun, Salem; Cotton, François; Vukusic, Sandra; Durand-Dubief, Françoise; Sappey-Marinier, Dominique

    2016-01-01

    Purpose: In this work, we introduce a method to classify Multiple Sclerosis (MS) patients into four clinical profiles using structural connectivity information. For the first time, we try to solve this question in a fully automated way using a computer-based method. The main goal is to show how the combination of graph-derived metrics with machine learning techniques constitutes a powerful tool for a better characterization and classification of MS clinical profiles. Materials and Methods: Sixty-four MS patients [12 Clinical Isolated Syndrome (CIS), 24 Relapsing Remitting (RR), 24 Secondary Progressive (SP), and 17 Primary Progressive (PP)] along with 26 healthy controls (HC) underwent MR examination. T1 and diffusion tensor imaging (DTI) were used to obtain structural connectivity matrices for each subject. Global graph metrics, such as density and modularity, were estimated and compared between subjects' groups. These metrics were further used to classify patients using tuned Support Vector Machine (SVM) combined with Radial Basic Function (RBF) kernel. Results: When comparing MS patients to HC subjects, a greater assortativity, transitivity, and characteristic path length as well as a lower global efficiency were found. Using all graph metrics, the best F-Measures (91.8, 91.8, 75.6, and 70.6%) were obtained for binary (HC-CIS, CIS-RR, RR-PP) and multi-class (CIS-RR-SP) classification tasks, respectively. When using only one graph metric, the best F-Measures (83.6, 88.9, and 70.7%) were achieved for modularity with previous binary classification tasks. Conclusion: Based on a simple DTI acquisition associated with structural brain connectivity analysis, this automatic method allowed an accurate classification of different MS patients' clinical profiles. PMID:27826224

  8. Graph Theory-Based Brain Connectivity for Automatic Classification of Multiple Sclerosis Clinical Courses.

    PubMed

    Kocevar, Gabriel; Stamile, Claudio; Hannoun, Salem; Cotton, François; Vukusic, Sandra; Durand-Dubief, Françoise; Sappey-Marinier, Dominique

    2016-01-01

    Purpose: In this work, we introduce a method to classify Multiple Sclerosis (MS) patients into four clinical profiles using structural connectivity information. For the first time, we try to solve this question in a fully automated way using a computer-based method. The main goal is to show how the combination of graph-derived metrics with machine learning techniques constitutes a powerful tool for a better characterization and classification of MS clinical profiles. Materials and Methods: Sixty-four MS patients [12 Clinical Isolated Syndrome (CIS), 24 Relapsing Remitting (RR), 24 Secondary Progressive (SP), and 17 Primary Progressive (PP)] along with 26 healthy controls (HC) underwent MR examination. T1 and diffusion tensor imaging (DTI) were used to obtain structural connectivity matrices for each subject. Global graph metrics, such as density and modularity, were estimated and compared between subjects' groups. These metrics were further used to classify patients using tuned Support Vector Machine (SVM) combined with Radial Basic Function (RBF) kernel. Results: When comparing MS patients to HC subjects, a greater assortativity, transitivity, and characteristic path length as well as a lower global efficiency were found. Using all graph metrics, the best F-Measures (91.8, 91.8, 75.6, and 70.6%) were obtained for binary (HC-CIS, CIS-RR, RR-PP) and multi-class (CIS-RR-SP) classification tasks, respectively. When using only one graph metric, the best F-Measures (83.6, 88.9, and 70.7%) were achieved for modularity with previous binary classification tasks. Conclusion: Based on a simple DTI acquisition associated with structural brain connectivity analysis, this automatic method allowed an accurate classification of different MS patients' clinical profiles.

  9. Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas

    NASA Astrophysics Data System (ADS)

    Chestek, Cynthia A.; Gilja, Vikash; Blabe, Christine H.; Foster, Brett L.; Shenoy, Krishna V.; Parvizi, Josef; Henderson, Jaimie M.

    2013-04-01

    Objective. Brain-machine interface systems translate recorded neural signals into command signals for assistive technology. In individuals with upper limb amputation or cervical spinal cord injury, the restoration of a useful hand grasp could significantly improve daily function. We sought to determine if electrocorticographic (ECoG) signals contain sufficient information to select among multiple hand postures for a prosthetic hand, orthotic, or functional electrical stimulation system.Approach. We recorded ECoG signals from subdural macro- and microelectrodes implanted in motor areas of three participants who were undergoing inpatient monitoring for diagnosis and treatment of intractable epilepsy. Participants performed five distinct isometric hand postures, as well as four distinct finger movements. Several control experiments were attempted in order to remove sensory information from the classification results. Online experiments were performed with two participants. Main results. Classification rates were 68%, 84% and 81% for correct identification of 5 isometric hand postures offline. Using 3 potential controls for removing sensory signals, error rates were approximately doubled on average (2.1×). A similar increase in errors (2.6×) was noted when the participant was asked to make simultaneous wrist movements along with the hand postures. In online experiments, fist versus rest was successfully classified on 97% of trials; the classification output drove a prosthetic hand. Online classification performance for a larger number of hand postures remained above chance, but substantially below offline performance. In addition, the long integration windows used would preclude the use of decoded signals for control of a BCI system. Significance. These results suggest that ECoG is a plausible source of command signals for prosthetic grasp selection. Overall, avenues remain for improvement through better electrode designs and placement, better participant training

  10. EEG Subspace Analysis and Classification Using Principal Angles for Brain-Computer Interfaces

    NASA Astrophysics Data System (ADS)

    Ashari, Rehab Bahaaddin

    Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all of their ability to communicate and control the outside environment from loss of voluntary muscle control. Most BCIs are based on the classification of multichannel electroencephalography (EEG) signals recorded from users as they respond to external stimuli or perform various mental activities. The classification process is fraught with difficulties caused by electrical noise, signal artifacts, and nonstationarity. One approach to reducing the effects of similar difficulties in other domains is the use of principal angles between subspaces, which has been applied mostly to video sequences. This dissertation studies and examines different ideas using principal angles and subspaces concepts. It introduces a novel mathematical approach for comparing sets of EEG signals for use in new BCI technology. The success of the presented results show that principal angles are also a useful approach to the classification of EEG signals that are recorded during a BCI typing application. In this application, the appearance of a subject's desired letter is detected by identifying a P300-wave within a one-second window of EEG following the flash of a letter. Smoothing the signals before using them is the only preprocessing step that was implemented in this study. The smoothing process based on minimizing the second derivative in time is implemented to increase the classification accuracy instead of using the bandpass filter that relies on assumptions on the frequency content of EEG. This study examines four different ways of removing outliers that are based on the principal angles and shows that the outlier removal methods did not help in the presented situations. One of the concepts that this dissertation focused on is the effect of the number of trials on the classification accuracies. The achievement of the good classification results by using a small number of trials starting from two trials only

  11. EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme

    PubMed Central

    Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

    2016-01-01

    Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI. PMID:26880873

  12. Extracting salient brain patterns for imaging-based classification of neurodegenerative diseases.

    PubMed

    Rueda, Andrea; González, Fabio A; Romero, Eduardo

    2014-06-01

    Neurodegenerative diseases comprise a wide variety of mental symptoms whose evolution is not directly related to the visual analysis made by radiologists, who can hardly quantify systematic differences. Moreover, automatic brain morphometric analyses, that do perform this quantification, contribute very little to the comprehension of the disease, i.e., many of these methods classify but they do not produce useful anatomo-functional correlations. This paper presents a new fully automatic image analysis method that reveals discriminative brain patterns associated to the presence of neurodegenerative diseases, mining systematic differences and therefore grading objectively any neurological disorder. This is accomplished by a fusion strategy that mixes together bottom-up and top-down information flows. Bottom-up information comes from a multiscale analysis of different image features, while the top-down stage includes learning and fusion strategies formulated as a max-margin multiple-kernel optimization problem. The capacity of finding discriminative anatomic patterns was evaluated using the Alzheimer's disease (AD) as the use case. The classification performance was assessed under different configurations of the proposed approach in two public brain magnetic resonance datasets (OASIS-MIRIAD) with patients diagnosed with AD, showing an improvement varying from 6.2% to 13% in the equal error rate measure, with respect to what has been reported by the feature-based morphometry strategy. In terms of the anatomical analysis, discriminant regions found by the proposed approach highly correlates to what has been reported in clinical studies of AD.

  13. Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury

    PubMed Central

    Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong-Ah; Cartwright, Walter B.; Hinds, Pamela S.; Chamberlain, James M.

    2016-01-01

    Background The authors have previously demonstrated highly reliable automated classification of free text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. Objectives To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). Methods This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then de-identified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The dataset was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based upon the National Institute of Neurological Disorders and Stroke Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford

  14. RPA classification has prognostic significance for surgically resected single brain metastasis

    SciTech Connect

    Tendulkar, Rahul D.; Liu, Stephanie W.; Barnett, Gene H.; Vogelbaum, Michael A.; Toms, Steven A.; Jin Tao; Suh, John H.

    2006-11-01

    Purpose: To retrospectively evaluate prognostic factors that correlate with overall survival among patients with a surgically resected single brain metastasis. Methods and Materials: An Institutional Review Board-approved database of Cleveland Clinic Brain Tumor Institute was queried for patients with a single brain metastasis treated by surgical resection between February 1984 and January 2004. The primary endpoint was overall survival from the date of surgery by the Kaplan-Meier method. Results: A total of 271 patients were included. Statistically significant variables for improved survival on multivariate analysis included age <65 years, lack of extracranial metastases, control of primary tumor, histology (non-small-cell lung carcinoma), and use of stereotactic radiosurgery. The median survival for all patients was 10.2 months. Survival of patients in recursive partitioning analysis (RPA) class 1 was better (21.4 months) than those in RPA class 2 (9.0 months, p < 0.001), RPA class 3 (8.9 months, p = 0.15), or the combined group of RPA classes 2 and 3 (9.0 months, p < 0.001). Patients had a median survival of 10.6 months after documented gross total resection and 8.7 months after subtotal resection, which approached statistical significance (p 0.07). Those who were treated with stereotactic radiosurgery had a median survival of 17.1 months, which was greater than patients who were not treated with stereotactic radiosurgery (8.9 months, p = 0.006). Conclusions: This analysis supports the prognostic significance of the RPA classification in patients with a single brain metastasis who undergo surgical resection and adjuvant therapy. RPA class 1 patients have a very favorable prognosis with a median survival of 21.4 months.

  15. 3D texture-based classification applied on brain white matter lesions on MR images

    NASA Astrophysics Data System (ADS)

    Leite, Mariana; Gobbi, David; Salluzi, Marina; Frayne, Richard; Lotufo, Roberto; Rittner, Letícia

    2016-03-01

    Lesions in the brain white matter are among the most frequently observed incidental findings on MR images. This paper presents a 3D texture-based classification to distinguish normal appearing white matter from white matter containing lesions, and compares it with the 2D approach. Texture analysis were based on 55 texture attributes extracted from gray-level histogram, gray-level co-occurrence matrix, run-length matrix and gradient. The results show that the 3D approach achieves an accuracy rate of 99.28%, against 97.41% of the 2D approach by using a support vector machine classifier. Furthermore, the most discriminating texture attributes on both 2D and 3D cases were obtained from the image histogram and co-occurrence matrix.

  16. Comparison of classification methods for P300 brain-computer interface on disabled subjects.

    PubMed

    Manyakov, Nikolay V; Chumerin, Nikolay; Combaz, Adrien; Van Hulle, Marc M

    2011-01-01

    We report on tests with a mind typing paradigm based on a P300 brain-computer interface (BCI) on a group of amyotrophic lateral sclerosis (ALS), middle cerebral artery (MCA) stroke, and subarachnoid hemorrhage (SAH) patients, suffering from motor and speech disabilities. We investigate the achieved typing accuracy given the individual patient's disorder, and how it correlates with the type of classifier used. We considered 7 types of classifiers, linear as well as nonlinear ones, and found that, overall, one type of linear classifier yielded a higher classification accuracy. In addition to the selection of the classifier, we also suggest and discuss a number of recommendations to be considered when building a P300-based typing system for disabled subjects.

  17. Tumour angiogenesis.

    PubMed Central

    Arnold, F.

    1985-01-01

    Tumours induce the growth of host blood vessels to support their proliferation. This process of angiogenesis is evoked by specific chemical signals. Recognition of these angiogenic factors has led to experimental methods for cancer diagnosis and for inhibiting malignant growth by specifically blocking neovascularisation. The clinical potential of these techniques is discussed. PMID:2413796

  18. Oral Tumours

    PubMed Central

    Lecavalier, D.R.; Main, J.H.P.

    1988-01-01

    The authors of this article review briefly the anatomy of the oral soft tissues and describe the more common benign and malignant tumours of the mouth, giving emphasis to their clinical features. ImagesFigure 1Figure 2Figure 3Figure 4Figure 5Figure 6Figure 7Figure 8 PMID:21253197

  19. Brain fingerprinting classification concealed information test detects US Navy military medical information with P300

    PubMed Central

    Farwell, Lawrence A.; Richardson, Drew C.; Richardson, Graham M.; Furedy, John J.

    2014-01-01

    A classification concealed information test (CIT) used the “brain fingerprinting” method of applying P300 event-related potential (ERP) in detecting information that is (1) acquired in real life and (2) unique to US Navy experts in military medicine. Military medicine experts and non-experts were asked to push buttons in response to three types of text stimuli. Targets contain known information relevant to military medicine, are identified to subjects as relevant, and require pushing one button. Subjects are told to push another button to all other stimuli. Probes contain concealed information relevant to military medicine, and are not identified to subjects. Irrelevants contain equally plausible, but incorrect/irrelevant information. Error rate was 0%. Median and mean statistical confidences for individual determinations were 99.9% with no indeterminates (results lacking sufficiently high statistical confidence to be classified). We compared error rate and statistical confidence for determinations of both information present and information absent produced by classification CIT (Is a probe ERP more similar to a target or to an irrelevant ERP?) vs. comparison CIT (Does a probe produce a larger ERP than an irrelevant?) using P300 plus the late negative component (LNP; together, P300-MERMER). Comparison CIT produced a significantly higher error rate (20%) and lower statistical confidences: mean 67%; information-absent mean was 28.9%, less than chance (50%). We compared analysis using P300 alone with the P300 + LNP. P300 alone produced the same 0% error rate but significantly lower statistical confidences. These findings add to the evidence that the brain fingerprinting methods as described here provide sufficient conditions to produce less than 1% error rate and greater than 95% median statistical confidence in a CIT on information obtained in the course of real life that is characteristic of individuals with specific training, expertise, or organizational

  20. Brain fingerprinting classification concealed information test detects US Navy military medical information with P300.

    PubMed

    Farwell, Lawrence A; Richardson, Drew C; Richardson, Graham M; Furedy, John J

    2014-01-01

    A classification concealed information test (CIT) used the "brain fingerprinting" method of applying P300 event-related potential (ERP) in detecting information that is (1) acquired in real life and (2) unique to US Navy experts in military medicine. Military medicine experts and non-experts were asked to push buttons in response to three types of text stimuli. Targets contain known information relevant to military medicine, are identified to subjects as relevant, and require pushing one button. Subjects are told to push another button to all other stimuli. Probes contain concealed information relevant to military medicine, and are not identified to subjects. Irrelevants contain equally plausible, but incorrect/irrelevant information. Error rate was 0%. Median and mean statistical confidences for individual determinations were 99.9% with no indeterminates (results lacking sufficiently high statistical confidence to be classified). We compared error rate and statistical confidence for determinations of both information present and information absent produced by classification CIT (Is a probe ERP more similar to a target or to an irrelevant ERP?) vs. comparison CIT (Does a probe produce a larger ERP than an irrelevant?) using P300 plus the late negative component (LNP; together, P300-MERMER). Comparison CIT produced a significantly higher error rate (20%) and lower statistical confidences: mean 67%; information-absent mean was 28.9%, less than chance (50%). We compared analysis using P300 alone with the P300 + LNP. P300 alone produced the same 0% error rate but significantly lower statistical confidences. These findings add to the evidence that the brain fingerprinting methods as described here provide sufficient conditions to produce less than 1% error rate and greater than 95% median statistical confidence in a CIT on information obtained in the course of real life that is characteristic of individuals with specific training, expertise, or organizational

  1. The Wechsler Adult Intelligence Scale-III and Malingering in Traumatic Brain Injury: Classification Accuracy in Known Groups

    ERIC Educational Resources Information Center

    Curtis, Kelly L.; Greve, Kevin W.; Bianchini, Kevin J.

    2009-01-01

    A known-groups design was used to determine the classification accuracy of Wechsler Adult Intelligence Scale-III (WAIS-III) variables in detecting malingered neurocognitive dysfunction (MND) in traumatic brain injury (TBI). TBI patients were classified into the following groups: (a) mild TBI not-MND (n = 26), (b) mild TBI MND (n = 31), and (c)…

  2. New approach for automatic classification of Alzheimer's disease, mild cognitive impairment and healthy brain magnetic resonance images.

    PubMed

    Lahmiri, Salim; Boukadoum, Mounir

    2014-01-01

    Explored is the utility of modelling brain magnetic resonance images as a fractal object for the classification of healthy brain images against those with Alzheimer's disease (AD) or mild cognitive impairment (MCI). More precisely, fractal multi-scale analysis is used to build feature vectors from the derived Hurst's exponents. These are then classified by support vector machines (SVMs). Three experiments were conducted: in the first the SVM was trained to classify AD against healthy images. In the second experiment, the SVM was trained to classify AD against MCI and, in the third experiment, a multiclass SVM was trained to classify all three types of images. The experimental results, using the 10-fold cross-validation technique, indicate that the SVM achieved 97.08% ± 0.05 correct classification rate, 98.09% ± 0.04 sensitivity and 96.07% ± 0.07 specificity for the classification of healthy against MCI images, thus outperforming recent works found in the literature. For the classification of MCI against AD, the SVM achieved 97.5% ± 0.04 correct classification rate, 100% sensitivity and 94.93% ± 0.08 specificity. The third experiment also showed that the multiclass SVM provided highly accurate classification results. The processing time for a given image was 25 s. These findings suggest that this approach is efficient and may be promising for clinical applications.

  3. New approach for automatic classification of Alzheimer's disease, mild cognitive impairment and healthy brain magnetic resonance images

    PubMed Central

    Boukadoum, Mounir

    2014-01-01

    Explored is the utility of modelling brain magnetic resonance images as a fractal object for the classification of healthy brain images against those with Alzheimer's disease (AD) or mild cognitive impairment (MCI). More precisely, fractal multi-scale analysis is used to build feature vectors from the derived Hurst's exponents. These are then classified by support vector machines (SVMs). Three experiments were conducted: in the first the SVM was trained to classify AD against healthy images. In the second experiment, the SVM was trained to classify AD against MCI and, in the third experiment, a multiclass SVM was trained to classify all three types of images. The experimental results, using the 10-fold cross-validation technique, indicate that the SVM achieved 97.08% ± 0.05 correct classification rate, 98.09% ± 0.04 sensitivity and 96.07% ± 0.07 specificity for the classification of healthy against MCI images, thus outperforming recent works found in the literature. For the classification of MCI against AD, the SVM achieved 97.5% ± 0.04 correct classification rate, 100% sensitivity and 94.93% ± 0.08 specificity. The third experiment also showed that the multiclass SVM provided highly accurate classification results. The processing time for a given image was 25 s. These findings suggest that this approach is efficient and may be promising for clinical applications. PMID:26609373

  4. Brain tissue classification from MRI data by means of texture analysis

    NASA Astrophysics Data System (ADS)

    Lachmann, Frederic; Barillot, Christian

    1992-06-01

    The new magnetic resonance imaging systems (MRI) are able to perform a brain scan with fairly good three-dimensional resolution. In order to allow the physician, and especially the neuroanatomist, to deal with the prime information borne by the images, the prevalent data have to be enhanced with regards to the medical objective. The aim of the work presented in this paper is to recognize and to label the head structures from MR images. This is done by computing probabilities for a pixel to belong to pre-specified head structures (i.e., skin, bone, CSF, ventricular system, grey and white matter, and brain). Several ways are presented and discussed in this paper, including the computation of statistical properties like `Markov parameters' and `fractal dimension.' From these statistical parameters, computed from a single MR image or a 3-D isotropic MR database, clustering and classification processes are used to issue fuzzy membership coefficients representing the probabilities for a pixel to belong to a particular structure. Improvements are proposed with regard to the expressed choices and examples are presented.

  5. Classification.

    PubMed

    Tuxhorn, Ingrid; Kotagal, Prakash

    2008-07-01

    In this article, we review the practical approach and diagnostic relevance of current seizure and epilepsy classification concepts and principles as a basic framework for good management of patients with epileptic seizures and epilepsy. Inaccurate generalizations about terminology, diagnosis, and treatment may be the single most important factor, next to an inadequately obtained history, that determines the misdiagnosis and mismanagement of patients with epilepsy. A stepwise signs and symptoms approach for diagnosis, evaluation, and management along the guidelines of the International League Against Epilepsy and definitions of epileptic seizures and epilepsy syndromes offers a state-of-the-art clinical approach to managing patients with epilepsy.

  6. Classification

    NASA Technical Reports Server (NTRS)

    Oza, Nikunj C.

    2011-01-01

    A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. In supervised learning, a set of training examples---examples with known output values---is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate's measurements. This chapter discusses methods to perform machine learning, with examples involving astronomy.

  7. MRI Brain Images Healthy and Pathological Tissues Classification with the Aid of Improved Particle Swarm Optimization and Neural Network

    PubMed Central

    Sheejakumari, V.; Sankara Gomathi, B.

    2015-01-01

    The advantages of magnetic resonance imaging (MRI) over other diagnostic imaging modalities are its higher spatial resolution and its better discrimination of soft tissue. In the previous tissues classification method, the healthy and pathological tissues are classified from the MRI brain images using HGANN. But the method lacks sensitivity and accuracy measures. The classification method is inadequate in its performance in terms of these two parameters. So, to avoid these drawbacks, a new classification method is proposed in this paper. Here, new tissues classification method is proposed with improved particle swarm optimization (IPSO) technique to classify the healthy and pathological tissues from the given MRI images. Our proposed classification method includes the same four stages, namely, tissue segmentation, feature extraction, heuristic feature selection, and tissue classification. The method is implemented and the results are analyzed in terms of various statistical performance measures. The results show the effectiveness of the proposed classification method in classifying the tissues and the achieved improvement in sensitivity and accuracy measures. Furthermore, the performance of the proposed technique is evaluated by comparing it with the other segmentation methods. PMID:25977706

  8. Estimating associations of mobile phone use and brain tumours taking into account laterality: a comparison and theoretical evaluation of applied methods.

    PubMed

    Frederiksen, Kirsten; Deltour, Isabelle; Schüz, Joachim

    2012-12-10

    Estimating exposure-outcome associations using laterality information on exposure and on outcome is an issue, when estimating associations of mobile phone use and brain tumour risk. The exposure is localized; therefore, a potential risk is expected to exist primarily on the side of the head, where the phone is usually held (ipsilateral exposure), and to a lesser extent at the opposite side of the head (contralateral exposure). Several measures of the associations with ipsilateral and contralateral exposure, dealing with different sampling designs, have been presented in the literature. This paper presents a general framework for the analysis of such studies using a likelihood-based approach in a competing risks model setting. The approach clarifies the implicit assumptions required for the validity of the presented estimators, particularly that in some approaches the risk with contralateral exposure is assumed to be zero. The performance of the estimators is illustrated in a simulation study showing for instance that while in some scenarios there is a loss of statistical power, others - in case of a positive ipsilateral exposure-outcome association - would result in a negatively biased estimate of the contralateral exposure parameter, irrespective of any additional recall bias. In conclusion, our theoretical evaluations and results from the simulation study emphasize the importance of setting up a formal model, which furthermore allows for estimation in more complicated and perhaps more realistic exposure settings, such as taking into account exposure to both sides of the head.

  9. Radiological aspects of gamma knife radiosurgery for arteriovenous malformations and other non-tumoural disorders of the brain.

    PubMed

    Guo, W Y

    1993-01-01

    The aims of the thesis were to investigate stereotaxic procedures in radiosurgery for cerebral arteriovenous malformations (AVMs) and radiation effects of single session high-dose irradiation delivered by gamma knife on the human brain. Investigation of gamma knife radiosurgery in 1,464 patients constitutes the data base of this thesis. High quality stereotaxic angiography is the gold standard targeting imaging in radiosurgery for cerebral AVMs, particularly for small AVMs or residual AVMs after other treatments. For medium and large size AVMs, stereotaxic MR techniques can improve targeting precision and decrease irradiation volume as compared to stereotaxic angiography in selected cases provided that proper pulse sequences are used. Combined treatments, where embolization precedes radiosurgery, can improve amenability of the treatment for large AVMs. This is on condition that the partially embolized nidi are well delineated and the volume of the residual nidi has been decreased to a level where an optimum irradiation can be safely prescribed. Radiologically, adverse radiation effects (ARE) of gamma knife radiosurgery for cerebral AVMs are observed in 16% (131/816) of the patients. The ARE are observed as a focal low attenuation on CT or as a focal high signal on MR image without enhancement in 47% (61/131), and as a peripheral or homogeneous enhancing lesion in 48% (63/131). MR imaging is more sensitive than CT in detecting the ARE. 91% of the ARE are observed within 18 months after radiosurgery and 89% are seen to regress within 18 months. Clinically, symptomatic ARE are only observed in 6% (51/816) and only in half of them, i.e. 3%, are the symptoms permanent. The risk of ARE in radiosurgery for venous angiomas is higher as compared to AVMs. Other mechanisms have probably been employed. In gamma capsulotomy, the necrotic lesions and reaction volumes created by using multiple isocentres of 4 mm collimators are less predictable as compared to that by single

  10. How well does the Oxfordshire Community Stroke Project classification predict the site and size of the infarct on brain imaging?

    PubMed Central

    Mead, G; Lewis, S; Wardlaw, J; Dennis, M; Warlow, C

    2000-01-01

    OBJECTIVES—The Oxfordshire Community Stroke Project (OCSP) classification is a simple clinical scheme for subdividing first ever acute stroke. Several small studies have shown that when an infarct is visible on CT or MRI, the classification predicts its site in about three quarters of patients. The aim was to further investigate this relation in a much larger cohort of patients in hospital with ischaemic stroke.
METHODS—Between 1994 and 1997, inpatients and outpatients with ischaemic stroke were assessed by one of several stroke physicians who noted the OCSP classification. A neuroradiologist classified the site and extent of recent infarction on CT or MRI.
RESULTS—Of 1012 patients with ischaemic stroke, 655 (65%) had recent visible infarcts. These radiological lesions were appropriate to the clinical classification in 69/87 (79%) patients with a total anterior circulation syndrome, 213/298 (71%) with a partial anterior circulation syndrome, 105/144 (73%) with a lacunar syndrome, and 105/126 (83%) with a posterior circulation syndrome. Overall, 75% of patients with visible infarcts were correctly classified clinically. If patients without a visible infarct did have an appropriate lesion in the brain (best case), the classification would have correctly predicted its site and size in 849/1012 (84%) patients, compared with only 492/1012 (49%) in the worst case scenario.
CONCLUSION—The OCSP classification predicted the site of infarct in three quarters of patients. When an infarct is visible on brain imaging, the site of the infarct should guide the use of further investigations, but if an infarct is not seen, the OCSP classification could be used to predict its likely size and site.

 PMID:10766882

  11. Classification of multi-class motor imagery with a novel hierarchical SVM algorithm for brain-computer interfaces.

    PubMed

    Dong, Enzeng; Li, Changhai; Li, Liting; Du, Shengzhi; Belkacem, Abdelkader Nasreddine; Chen, Chao

    2017-02-25

    Pattern classification algorithm is the crucial step in developing brain-computer interface (BCI) applications. In this paper, a hierarchical support vector machine (HSVM) algorithm is proposed to address an EEG-based four-class motor imagery classification task. Wavelet packet transform is employed to decompose raw EEG signals. Thereafter, EEG signals with effective frequency sub-bands are grouped and reconstructed. EEG feature vectors are extracted from the reconstructed EEG signals with one versus the rest common spatial patterns (OVR-CSP) and one versus one common spatial patterns (OVO-CSP). Then, a two-layer HSVM algorithm is designed for the classification of these EEG feature vectors, where "OVO" classifiers are used in the first layer and "OVR" in the second layer. A public dataset (BCI Competition IV-II-a)is employed to validate the proposed method. Fivefold cross-validation results demonstrate that the average accuracy of classification in the first layer and the second layer is 67.5 ± 17.7% and 60.3 ± 14.7%, respectively. The average accuracy of the classification is 64.4 ± 16.7% overall. These results show that the proposed method is effective for four-class motor imagery classification.

  12. Automatic classification of sulcal regions of the human brain cortex using pattern recognition

    NASA Astrophysics Data System (ADS)

    Behnke, Kirsten J.; Rettmann, Maryam E.; Pham, Dzung L.; Shen, Dinggang; Resnick, Susan M.; Davatzikos, Christos; Prince, Jerry L.

    2003-05-01

    Parcellation of the cortex has received a great deal of attention in magnetic resonance (MR) image analysis, but its usefulness has been limited by time-consuming algorithms that require manual labeling. An automatic labeling scheme is necessary to accurately and consistently parcellate a large number of brains. The large variation of cortical folding patterns makes automatic labeling a challenging problem, which cannot be solved by deformable atlas registration alone. In this work, an automated classification scheme that consists of a mix of both atlas driven and data driven methods is proposed to label the sulcal regions, which are defined as the gray matter regions of the cortical surface surrounding each sulcus. The premise for this algorithm is that sulcal regions can be classified according to the pattern of anatomical features (e.g. supramarginal gyrus, cuneus, etc.) associated with each region. Using a nearest-neighbor approach, a sulcal region is classified as being in the same class as the sulcus from a set of training data which has the nearest pattern of anatomical features. Using just one subject as training data, the algorithm correctly labeled 83% of the regions that make up the main sulci of the cortex.

  13. Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

    PubMed

    Sauwen, N; Acou, M; Van Cauter, S; Sima, D M; Veraart, J; Maes, F; Himmelreich, U; Achten, E; Van Huffel, S

    2016-01-01

    Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

  14. A parametric feature extraction and classification strategy for brain-computer interfacing.

    PubMed

    Burke, Dave P; Kelly, Simon P; de Chazal, Philip; Reilly, Richard B; Finucane, Ciarán

    2005-03-01

    Parametric modeling strategies are explored in conjunction with linear discriminant analysis for use in an electroencephalogram (EEG)-based brain-computer interface (BCI). A left/right self-paced typing exercise is analyzed by extending the usual autoregressive (AR) model for EEG feature extraction with an AR with exogenous input (ARX) model for combined filtering and feature extraction. The ensemble averaged Bereitschafts potential (an event related potential preceding the onset of movement) forms the exogenous signal input to the ARX model. Based on trials with six subjects, the ARX case of modeling both the signal and noise was found to be considerably more effective than modeling the noise alone (common in BCI systems) with the AR method yielding a classification accuracy of 52.8+/-4.8% and the ARX method an accuracy of 79.1+/-3.9 % across subjects. The results suggest a role for ARX-based feature extraction in BCIs based on evoked and event-related potentials.

  15. Automated Classification to Predict the Progression of Alzheimer's Disease Using Whole-Brain Volumetry and DTI

    PubMed Central

    Jung, Won Beom; Lee, Young Min; Kim, Young Hoon

    2015-01-01

    Objective This study proposes an automated diagnostic method to classify patients with Alzheimer's disease (AD) of degenerative etiology using magnetic resonance imaging (MRI) markers. Methods Twenty-seven patients with subjective memory impairment (SMI), 18 patients with mild cognitive impairment (MCI), and 27 patients with AD participated. MRI protocols included three dimensional brain structural imaging and diffusion tensor imaging to assess the cortical thickness, subcortical volume and white matter integrity. Recursive feature elimination based on support vector machine (SVM) was conducted to determine the most relevant features for classifying abnormal regions and imaging parameters, and then a factor analysis for the top-ranked factors was performed. Subjects were classified using nonlinear SVM. Results Medial temporal regions in AD patients were dominantly detected with cortical thinning and volume atrophy compared with SMI and MCI patients. Damage to white matter integrity was also accredited with decreased fractional anisotropy and increased mean diffusivity (MD) across the three groups. The microscopic damage in the subcortical gray matter was reflected in increased MD. Classification accuracy between pairs of groups (SMI vs. MCI, MCI vs. AD, SMI vs. AD) and among all three groups were 84.4% (±13.8), 86.9% (±10.5), 96.3% (±4.6), and 70.5% (±11.5), respectively. Conclusion This proposed method may be a potential tool to diagnose AD pathology with the current clinical criteria. PMID:25670951

  16. Segmentation and classification of normal-appearing brain: how much is enough?

    NASA Astrophysics Data System (ADS)

    Glass, John O.; Reddick, Wilburn E.; Ji, Qing; Glas, Lauren S.

    2002-05-01

    In this study, subsets of MR slices were examined to assess their ability to optimally predict the total cerebral volume of gray matter, white matter and CSF. Patients underwent a clinical imaging protocol consisting of T1-, T2-, PD-, and FLAIR-weighted images after obtaining informed consent. MR imaging sets were registered, RF-corrected, and then analyzed with a hybrid neural network segmentation and classification algorithm to identify normal brain parenchyma. After processing the data, the correlation between the image subsets and the total cerebral volumes of gray matter, white matter and CSF were examined. The 29 subjects (18F, 11M) assessed in this study were 1.7 ? 18.7 (median = 5.2) years of age. The five subsets accounted for 5%, 15%, 24%, 56%, and 79% of the total cerebral volume. The predictive correlation for gray matter, white matter, and CSF in each of these subsets were: 5% (R= 0.94, 0.92, 0.91), 15% (R= 0.93, 0.95, 0.94), 24% (R= 0.92, 0.95, 0.94), 56% (R= 0.75, 0.95, 0.89), and 79% (R= 0.89, 0.98, 0.99) respectively. All subsets of slices examined were significantly correlated (p<0.001) with the total cerebral volume of gray matter, white matter, and CSF.

  17. Automatic segmentation of MR brain images of preterm infants using supervised classification.

    PubMed

    Moeskops, Pim; Benders, Manon J N L; Chiţ, Sabina M; Kersbergen, Karina J; Groenendaal, Floris; de Vries, Linda S; Viergever, Max A; Išgum, Ivana

    2015-09-01

    Preterm birth is often associated with impaired brain development. The state and expected progression of preterm brain development can be evaluated using quantitative assessment of MR images. Such measurements require accurate segmentation of different tissue types in those images. This paper presents an algorithm for the automatic segmentation of unmyelinated white matter (WM), cortical grey matter (GM), and cerebrospinal fluid in the extracerebral space (CSF). The algorithm uses supervised voxel classification in three subsequent stages. In the first stage, voxels that can easily be assigned to one of the three tissue types are labelled. In the second stage, dedicated analysis of the remaining voxels is performed. The first and the second stages both use two-class classification for each tissue type separately. Possible inconsistencies that could result from these tissue-specific segmentation stages are resolved in the third stage, which performs multi-class classification. A set of T1- and T2-weighted images was analysed, but the optimised system performs automatic segmentation using a T2-weighted image only. We have investigated the performance of the algorithm when using training data randomly selected from completely annotated images as well as when using training data from only partially annotated images. The method was evaluated on images of preterm infants acquired at 30 and 40weeks postmenstrual age (PMA). When the method was trained using random selection from the completely annotated images, the average Dice coefficients were 0.95 for WM, 0.81 for GM, and 0.89 for CSF on an independent set of images acquired at 30weeks PMA. When the method was trained using only the partially annotated images, the average Dice coefficients were 0.95 for WM, 0.78 for GM and 0.87 for CSF for the images acquired at 30weeks PMA, and 0.92 for WM, 0.80 for GM and 0.85 for CSF for the images acquired at 40weeks PMA. Even though the segmentations obtained using training data

  18. Factors related to pregnancy and birth and the risk of childhood brain tumours: The ESTELLE and ESCALE studies (SFCE, France).

    PubMed

    Bailey, Helen D; Rios, Paula; Lacour, Brigitte; Guerrini-Rousseau, Léa; Bertozzi, Anne-Isabelle; Leblond, Pierre; Faure-Conter, Cécile; Pellier, Isabelle; Freycon, Claire; Michon, Jean; Puget, Stéphanie; Ducassou, Stéphane; Orsi, Laurent; Clavel, Jacqueline

    2017-04-15

    Little is known of the causes of childhood brain tumors (CBT). The aims of this study were to investigate whether extremes of birth weight were associated with increased risk of CBT and whether maternal preconceptional folic acid supplementation or breastfeeding reduced the risk. In addition, other maternal characteristics and birth related factors were also investigated. We pooled data from two French national population-based case-control studies with similar designs conducted in 2003-2004 and 2010-2011. The mothers of 510 CBT cases (directly recruited from the national childhood cancer register) and 3,102 controls aged under 15 years, frequency matched by age and gender did a telephone interview, which focussed on demographic and perinatal characteristics, and maternal life style habits and reproductive history. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression, adjusted for age, sex, study of origin and relevant confounders. No association was found between CBT and birth weight or fetal growth. The use of preconceptional folic acid supplementation was rare (5.3% in cases and 7.8% in controls) and the OR was 0.8 (95% CI 0.5, 1.4). There was no association with breastfeeding, even prolonged (six months or more; OR 1.0, 95% CI 0.8, 1.4). Neither was there any association between CBT and other investigated factors (maternal body mass index, gestational weight gain, congenital abnormality, maternal reproductive history or use of fertility treatments. Although large, this study was underpowered for subtype analyses. Pooling data with other population-based studies may provide further insight into findings by CBT subtypes.

  19. Tumours of the upper alimentary tract

    PubMed Central

    Head, K. W.

    1976-01-01

    Tumours of the oropharynx of domestic animals are common in most parts of the world, but squamous cell carcinoma of the upper alimentary tract shows differences in prevalence in different geographical areas and occurs at different sites in the various species. Oral tumours of the melanogenic system are more common in dogs than in man. The following main histological categories, which broadly correspond to those used in the classification of tumours of man, are described: papilloma; squamous cell carcinoma; salivary gland tumours; malignant melanoma; tumours of soft (mesenchymal) tissues; tumours of the facial bones; tumours of haematopoietic and related tissues; and odontogenic tumours and jaw cysts. Papilloma, squamous cell carcinoma, malignant melanoma, fibroma, and fibrosarcoma account for about 80% of the tumours that occur in the upper alimentary tract of domestic animals. ImagesFig. 6Fig. 7Fig. 8Fig. 9Fig. 34Fig. 35Fig. 36Fig. 37Fig. 2Fig. 3Fig. 4Fig. 5Fig. 22Fig. 23Fig. 24Fig. 25Fig. 26Fig. 27Fig. 28Fig. 29Fig. 14Fig. 15Fig. 16Fig. 17Fig. 30Fig. 31Fig. 32Fig. 33Fig. 18Fig. 19Fig. 20Fig. 21Fig. 10Fig. 11Fig. 12Fig. 13Fig. 1 PMID:1086147

  20. Analysis of Different Classification Techniques for Two-Class Functional Near-Infrared Spectroscopy-Based Brain-Computer Interface

    PubMed Central

    Qureshi, Nauman Khalid; Noori, Farzan Majeed; Hong, Keum-Shik

    2016-01-01

    We analyse and compare the classification accuracies of six different classifiers for a two-class mental task (mental arithmetic and rest) using functional near-infrared spectroscopy (fNIRS) signals. The signals of the mental arithmetic and rest tasks from the prefrontal cortex region of the brain for seven healthy subjects were acquired using a multichannel continuous-wave imaging system. After removal of the physiological noises, six features were extracted from the oxygenated hemoglobin (HbO) signals. Two- and three-dimensional combinations of those features were used for classification of mental tasks. In the classification, six different modalities, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbour (kNN), the Naïve Bayes approach, support vector machine (SVM), and artificial neural networks (ANN), were utilized. With these classifiers, the average classification accuracies among the seven subjects for the 2- and 3-dimensional combinations of features were 71.6, 90.0, 69.7, 89.8, 89.5, and 91.4% and 79.6, 95.2, 64.5, 94.8, 95.2, and 96.3%, respectively. ANN showed the maximum classification accuracies: 91.4 and 96.3%. In order to validate the results, a statistical significance test was performed, which confirmed that the p values were statistically significant relative to all of the other classifiers (p < 0.005) using HbO signals. PMID:27725827

  1. Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

    PubMed

    Cuadra, Meritxell Bach; Cammoun, Leila; Butz, Torsten; Cuisenaire, Olivier; Thiran, Jean-Philippe

    2005-12-01

    This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

  2. Matched signal detection on graphs: Theory and application to brain imaging data classification.

    PubMed

    Hu, Chenhui; Sepulcre, Jorge; Johnson, Keith A; Fakhri, Georges E; Lu, Yue M; Li, Quanzheng

    2016-01-15

    Motivated by recent progress in signal processing on graphs, we have developed a matched signal detection (MSD) theory for signals with intrinsic structures described by weighted graphs. First, we regard graph Laplacian eigenvalues as frequencies of graph-signals and assume that the signal is in a subspace spanned by the first few graph Laplacian eigenvectors associated with lower eigenvalues. The conventional matched subspace detector can be applied to this case. Furthermore, we study signals that may not merely live in a subspace. Concretely, we consider signals with bounded variation on graphs and more general signals that are randomly drawn from a prior distribution. For bounded variation signals, the test is a weighted energy detector. For the random signals, the test statistic is the difference of signal variations on associated graphs, if a degenerate Gaussian distribution specified by the graph Laplacian is adopted. We evaluate the effectiveness of the MSD on graphs both with simulated and real data sets. Specifically, we apply MSD to the brain imaging data classification problem of Alzheimer's disease (AD) based on two independent data sets: 1) positron emission tomography data with Pittsburgh compound-B tracer of 30 AD and 40 normal control (NC) subjects, and 2) resting-state functional magnetic resonance imaging (R-fMRI) data of 30 early mild cognitive impairment and 20 NC subjects. Our results demonstrate that the MSD approach is able to outperform the traditional methods and help detect AD at an early stage, probably due to the success of exploiting the manifold structure of the data.

  3. Melanotic neuroectodermal tumour of infancy.

    PubMed

    Siddiqui, T H; Amin, M R; Bashar, M A; Ahmed, Z; Matin, A; Hasan, G Z; Islam, M D; Hossain, M Z

    2011-04-01

    Melanotic neuroectodermal tumour in infancy is rare, mainly benign with little tendency to recur after excision or effective curettage. This pigmented neoplasm of neural crest origin occurring in infants before 1 year of age. The most common site of occurrence is the anterior maxillary alveolar ridge (70%), following by the skull, brain and mandible. The genital organ is the most frequent extra cranial site. We report a 6 months old male baby with a similar tumour arising from right half of cheek involving the maxilla. We diagnosed the case after histological report. We remove the tumour through a sub-labial incision. The mass was blackish in colour, and was mobilized from all side including from the maxillary sinuses. The author thought that this should be reported for improving the clinical awareness and treatment of pigmented soft tissue mass in children. Almost one year follow up of the patients showed no recurrence.

  4. Malignant sweat gland tumours: an update.

    PubMed

    Cardoso, José C; Calonje, Eduardo

    2015-11-01

    Cutaneous adnexal tumours can be a diagnostic challenge for the pathologist. This is particularly true in the case of tumours with sweat gland differentiation, due to a large number of rare entities, a multiplicity of names to designate the same neoplasms and consequent lack of consensus regarding their classification and nomenclature. In the traditional view, sweat gland tumours were divided into eccrine and apocrine. However, this has been challenged in recent years, and in fact many of these tumours may have both eccrine and apocrine variants. Some display more complex features and defy classification, due to the presence of other lines of differentiation, namely follicular and/or sebaceous (in the case of apocrine tumours, due to the close embryological relationship between apocrine glands, hair follicles and sebaceous glands). The present paper reviews and updates the basic concepts regarding the following malignant sweat gland tumours: apocrine carcinoma, porocarcinoma, hidradenocarcinoma, spiradenocarcinoma, cylindrocarcinoma, microcystic adnexal carcinoma and related entities, squamoid eccrine ductal carcinoma, digital papillary adenocarcinoma, primary cutaneous mucinous carcinoma, endocrine mucin-producing sweat gland carcinoma and primary cutaneous signet ring cell carcinoma. Particular emphasis is put in recent findings that may have implications in the diagnosis and management of these tumours.

  5. A new clinical guideline from the Royal College of Paediatrics and Child Health with a national awareness campaign accelerates brain tumor diagnosis in UK children—“HeadSmart: Be Brain Tumour Aware”

    PubMed Central

    2016-01-01

    Background A national survey in 2006 identified that UK referral practice for pediatric CNS tumors ranked poorly in international comparisons, which led to new National Health Service (NHS) Evidence accredited referral guidelines published in 2008 by the Royal College of Paediatrics and Child Health and a campaign to raise awareness of early features of CNS tumors and the need for timely imaging. Methods The “HeadSmart: Be Brain Tumour Aware” campaign was launched in June 2011 across the UK as a quality improvement strategy directed at reducing the total diagnostic interval (TDI) from a pre-campaign (2006) median of 14 (mean, 35.4) weeks to a target of 5 weeks in order to equal the best reported internationally. Professional and public awareness was measured by questionnaire surveys. TDI was collected by clinical champions in 18 regional children's cancer centers and the public campaign was coordinated by a national charity, working with a network of community champions. Results The guidelines and campaign raised awareness among pediatricians and were associated with reduction in TDI to a median of 6.7 (mean, 21.3) weeks by May 2013. This change in referral practice was most pronounced in the time from first medical contact to CNS imaging, for which the median was reduced from 3.3 to 1.4 weeks between January 2011 and May 2013 (P = .009). Conclusion This strategy to accelerate brain tumor diagnosis by the NHS using a public and professional awareness campaign is a “world first” in pediatric cancer and is being emulated internationally and acknowledged by a series of NHS and charity awards for excellence. PMID:26523066

  6. Classification of Parkinsonian Syndromes from FDG-PET Brain Data Using Decision Trees with SSM/PCA Features

    PubMed Central

    Mudali, D.; Teune, L. K.; Renken, R. J.; Leenders, K. L.; Roerdink, J. B. T. M.

    2015-01-01

    Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data. PMID:25918550

  7. Peculiarities of hyperlipidaemia in tumour patients.

    PubMed Central

    Dilman, V. M.; Berstein, L. M.; Ostroumova, M. N.; Tsyrlina, Y. V.; Golubev, A. G.

    1981-01-01

    The study group included 684 cases: 258 patients with breast carcinoma, 113 males with lung cancer, 42 patients with rectal tumours, 42 patients with stomach tumours, 59 patients with fibroadenomatosis, and 170 healthy subjects of varying age (male and female). A relatively high blood triglyceride level was found in patients with breast, lung, rectal (females), and stomach (female) tumours. The blood concentration of high-density lipoprotein-cholesterol in patients with breast, lung, and stomach (female) tumours was relatively low. The elimination of tumour (breast carcinoma) did not lead to significant changes in lipid metabolism. There was no correlation between degree of lipidaemia and stage of tumour progression except in the cases of rectal cancer. Preliminary results are presented on the tentative classification of hyperlipoproteinaemia in tumour patients, using the lipid concentration threshold values advocated by Carlson et al. (1977); an increased frequency of Type IV hyperlipoproteinaemia proved to be the most characteristic feature of tumour patients. The results are discussed in terms of the concept of the importance of lipid metabolic disturbances, primarily those due to ageing, in the genesis of the syndrome of "cancerophilia" (predisposition to cancer). PMID:7248149

  8. Supervised classification of brain tissues through local multi-scale texture analysis by coupling DIR and FLAIR MR sequences

    NASA Astrophysics Data System (ADS)

    Poletti, Enea; Veronese, Elisa; Calabrese, Massimiliano; Bertoldo, Alessandra; Grisan, Enrico

    2012-02-01

    The automatic segmentation of brain tissues in magnetic resonance (MR) is usually performed on T1-weighted images, due to their high spatial resolution. T1w sequence, however, has some major downsides when brain lesions are present: the altered appearance of diseased tissues causes errors in tissues classification. In order to overcome these drawbacks, we employed two different MR sequences: fluid attenuated inversion recovery (FLAIR) and double inversion recovery (DIR). The former highlights both gray matter (GM) and white matter (WM), the latter highlights GM alone. We propose here a supervised classification scheme that does not require any anatomical a priori information to identify the 3 classes, "GM", "WM", and "background". Features are extracted by means of a local multi-scale texture analysis, computed for each pixel of the DIR and FLAIR sequences. The 9 textures considered are average, standard deviation, kurtosis, entropy, contrast, correlation, energy, homogeneity, and skewness, evaluated on a neighborhood of 3x3, 5x5, and 7x7 pixels. Hence, the total number of features associated to a pixel is 56 (9 textures x3 scales x2 sequences +2 original pixel values). The classifier employed is a Support Vector Machine with Radial Basis Function as kernel. From each of the 4 brain volumes evaluated, a DIR and a FLAIR slice have been selected and manually segmented by 2 expert neurologists, providing 1st and 2nd human reference observations which agree with an average accuracy of 99.03%. SVM performances have been assessed with a 4-fold cross-validation, yielding an average classification accuracy of 98.79%.

  9. Individual 3D region-of-interest atlas of the human brain: automatic training point extraction for neural-network-based classification of brain tissue types

    NASA Astrophysics Data System (ADS)

    Wagenknecht, Gudrun; Kaiser, Hans-Juergen; Obladen, Thorsten; Sabri, Osama; Buell, Udalrich

    2000-04-01

    Individual region-of-interest atlas extraction consists of two main parts: T1-weighted MRI grayscale images are classified into brain tissues types (gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), scalp/bone (SB), background (BG)), followed by class image analysis to define automatically meaningful ROIs (e.g., cerebellum, cerebral lobes, etc.). The purpose of this algorithm is the automatic detection of training points for neural network-based classification of brain tissue types. One transaxial slice of the patient data set is analyzed. Background separation is done by simple region growing. A random generator extracts spatially uniformly distributed training points of class BG from that region. For WM training point extraction (TPE), the homogeneity operator is the most important. The most homogeneous voxels define the region for WM TPE. They are extracted by analyzing the cumulative histogram of the homogeneity operator response. Assuming a Gaussian gray value distribution in WM, a random number is used as a probabilistic threshold for TPE. Similarly, non-white matter and non-background regions are analyzed for GM and CSF training points. For SB TPE, the distance from the BG region is an additional feature. Simulated and real 3D MRI images are analyzed and error rates for TPE and classification calculated.

  10. Toward FRP-Based Brain-Machine Interfaces-Single-Trial Classification of Fixation-Related Potentials.

    PubMed

    Finke, Andrea; Essig, Kai; Marchioro, Giuseppe; Ritter, Helge

    2016-01-01

    The co-registration of eye tracking and electroencephalography provides a holistic measure of ongoing cognitive processes. Recently, fixation-related potentials have been introduced to quantify the neural activity in such bi-modal recordings. Fixation-related potentials are time-locked to fixation onsets, just like event-related potentials are locked to stimulus onsets. Compared to existing electroencephalography-based brain-machine interfaces that depend on visual stimuli, fixation-related potentials have the advantages that they can be used in free, unconstrained viewing conditions and can also be classified on a single-trial level. Thus, fixation-related potentials have the potential to allow for conceptually different brain-machine interfaces that directly interpret cortical activity related to the visual processing of specific objects. However, existing research has investigated fixation-related potentials only with very restricted and highly unnatural stimuli in simple search tasks while participant's body movements were restricted. We present a study where we relieved many of these restrictions while retaining some control by using a gaze-contingent visual search task. In our study, participants had to find a target object out of 12 complex and everyday objects presented on a screen while the electrical activity of the brain and eye movements were recorded simultaneously. Our results show that our proposed method for the classification of fixation-related potentials can clearly discriminate between fixations on relevant, non-relevant and background areas. Furthermore, we show that our classification approach generalizes not only to different test sets from the same participant, but also across participants. These results promise to open novel avenues for exploiting fixation-related potentials in electroencephalography-based brain-machine interfaces and thus providing a novel means for intuitive human-machine interaction.

  11. Toward FRP-Based Brain-Machine Interfaces—Single-Trial Classification of Fixation-Related Potentials

    PubMed Central

    Finke, Andrea; Essig, Kai; Marchioro, Giuseppe; Ritter, Helge

    2016-01-01

    The co-registration of eye tracking and electroencephalography provides a holistic measure of ongoing cognitive processes. Recently, fixation-related potentials have been introduced to quantify the neural activity in such bi-modal recordings. Fixation-related potentials are time-locked to fixation onsets, just like event-related potentials are locked to stimulus onsets. Compared to existing electroencephalography-based brain-machine interfaces that depend on visual stimuli, fixation-related potentials have the advantages that they can be used in free, unconstrained viewing conditions and can also be classified on a single-trial level. Thus, fixation-related potentials have the potential to allow for conceptually different brain-machine interfaces that directly interpret cortical activity related to the visual processing of specific objects. However, existing research has investigated fixation-related potentials only with very restricted and highly unnatural stimuli in simple search tasks while participant’s body movements were restricted. We present a study where we relieved many of these restrictions while retaining some control by using a gaze-contingent visual search task. In our study, participants had to find a target object out of 12 complex and everyday objects presented on a screen while the electrical activity of the brain and eye movements were recorded simultaneously. Our results show that our proposed method for the classification of fixation-related potentials can clearly discriminate between fixations on relevant, non-relevant and background areas. Furthermore, we show that our classification approach generalizes not only to different test sets from the same participant, but also across participants. These results promise to open novel avenues for exploiting fixation-related potentials in electroencephalography-based brain-machine interfaces and thus providing a novel means for intuitive human-machine interaction. PMID:26812487

  12. Magnetic resonance imaging findings in 40 dogs with histologically confirmed intracranial tumours.

    PubMed

    Ródenas, Sergio; Pumarola, Marti; Gaitero, Lluís; Zamora, Angels; Añor, Sònia

    2011-01-01

    Magnetic resonance (MR) images of 40 dogs with histologically confirmed primary and secondary intracranial tumours were reviewed. Forty-one tumours were diagnosed by means of MR imaging (MRI). MRI findings allowed diagnosis of a neoplastic lesion in 37/41 cases. Based on MRI features, differentiation between neoplastic and non-neoplastic lesions was possible in 24/27 (89%) primary brain tumours and in 13/14 (92%) secondary brain tumours. Diagnosis of tumour type based on MRI features was correct in 19/27 (70%) primary tumours and in 13/14 secondary tumours. The results of this study show that MRI is a good diagnostic imaging modality to detect neoplastic lesions and to diagnose tumour type in dogs. However, as some neoplasms show equivocal MRI features the technique has limitations in the detection of some intracranial tumours and in predicting tumour type.

  13. Toward a brain-computer interface for Alzheimer's disease patients by combining classical conditioning and brain state classification.

    PubMed

    Liberati, Giulia; Dalboni da Rocha, Josué Luiz; van der Heiden, Linda; Raffone, Antonino; Birbaumer, Niels; Olivetti Belardinelli, Marta; Sitaram, Ranganatha

    2012-01-01

    Brain-computer interfaces (BCIs) provide alternative methods for communicating and acting on the world, since messages or commands are conveyed from the brain to an external device without using the normal output pathways of peripheral nerves and muscles. Alzheimer's disease (AD) patients in the most advanced stages, who have lost the ability to communicate verbally, could benefit from a BCI that may allow them to convey basic thoughts (e.g., "yes" and "no") and emotions. There is currently no report of such research, mostly because the cognitive deficits in AD patients pose serious limitations to the use of traditional BCIs, which are normally based on instrumental learning and require users to self-regulate their brain activation. Recent studies suggest that not only self-regulated brain signals, but also involuntary signals, for instance related to emotional states, may provide useful information about the user, opening up the path for so-called "affective BCIs". These interfaces do not necessarily require users to actively perform a cognitive task, and may therefore be used with patients who are cognitively challenged. In the present hypothesis paper, we propose a paradigm shift from instrumental learning to classical conditioning, with the aim of discriminating "yes" and "no" thoughts after associating them to positive and negative emotional stimuli respectively. This would represent a first step in the development of a BCI that could be used by AD patients, lending a new direction not only for communication, but also for rehabilitation and diagnosis.

  14. Classification of wheelchair commands using brain computer interface: comparison between able-bodied persons and patients with tetraplegia.

    PubMed

    Chai, Rifai; Ling, Sai Ho; Hunter, Gregory P; Tran, Yvonne; Nguyen, Hung T

    2013-01-01

    This paper presents a three-class mental task classification for an electroencephalography based brain computer interface. Experiments were conducted with patients with tetraplegia and able bodied controls. In addition, comparisons with different time-windows of data were examined to find the time window with the highest classification accuracy. The three mental tasks used were letter composing, arithmetic and imagery of a Rubik's cube rolling forward; these tasks were associated with three wheelchair commands: left, right and forward, respectively. An eyes closed task was also recorded for the algorithms testing and used as an additional on/off command. The features extraction method was based on the spectrum from a Hilbert-Huang transform and the classification algorithm was based on an artificial neural network with a fuzzy particle swarm optimization with cross-mutated operation. The results show a strong eyes closed detection for both groups with average accuracy at above 90%. The overall result for the combined groups shows an improved average accuracy of 70.6% at 1s, 74.8% at 2s, 77.8% at 3s, 79.6% at 4s and 81.4% at 5s. The accuracy for individual groups were lower for patients with tetraplegia compared to the able-bodied group, however, does improve with increased duration of the time-window.

  15. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Tumors of the Salivary Gland.

    PubMed

    Seethala, Raja R; Stenman, Göran

    2017-03-01

    The salivary gland section in the 4th edition of the World Health Organization classification of head and neck tumors features the description and inclusion of several entities, the most significant of which is represented by (mammary analogue) secretory carcinoma. This entity was extracted mainly from acinic cell carcinoma based on recapitulation of breast secretory carcinoma and a shared ETV6-NTRK3 gene fusion. Also new is the subsection of "Other epithelial lesions," for which key entities include sclerosing polycystic adenosis and intercalated duct hyperplasia. Many entities have been compressed into their broader categories given clinical and morphologic similarities, or transitioned to a different grouping as was the case with low-grade cribriform cystadenocarcinoma reclassified as intraductal carcinoma (with the applied qualifier of low-grade). Specific grade has been removed from the names of the salivary gland entities such as polymorphous adenocarcinoma, providing pathologists flexibility in assigning grade and allowing for recognition of a broader spectrum within an entity. Cribriform adenocarcinoma of (minor) salivary gland origin continues to be divisive in terms of whether it should be recognized as a distinct category. This chapter also features new key concepts such as high-grade transformation. The new paradigm of translocations and gene fusions being common in salivary gland tumors is featured heavily in this chapter.

  16. [Malignant phyllodes tumour : a case report].

    PubMed

    Radermacher, J; Burlet, O; Sylvestre, R M; Wetz, P; Delvenne, Ph

    2016-11-01

    A 28 year old woman has suffered over the previous month from a post-traumatic swelling sensation of the left breast. Ultrasonography demonstrates a 9 cm, sharply-cut, rounded, hypo-echogenic lesion. Surgery is performed, with the hypothesis of an haematoma. The pathological analysis of the lesion shows a malignant phyllodes tumour with heterologous rhabdomyosarcomatous features. No metastasis is found. A radical mastectomy is performed and the patient benefits from an adjuvant radio-chemotherapy. Phyllodes tumours represent up to 1 % of all mammary cancers, with 10-20 % of malignant lesions. These tumours behave differently from usual breast cancers. This atypical case, arising in a traumatic context, provides the opportunity to discuss the treatment and classification of phyllodes tumours of the breast.

  17. Response conflict processes' classification in 7 and 9 year old children using EEG brain connectivity measures.

    PubMed

    Almabruk, T; Iyer, K; Girdler, S; Khan, M M; Tan, T

    2016-08-01

    Investigating cognitive development of children poses interesting challenges pertaining to emergence of children's' ability to think and understand. Psychological tasks that involve conflict, like the Flanker task, are widely used to understand development of response conflict processes. In this study, EEG signals were used to examine the coherence and imaginary part of coherency within the delta, theta, alpha and beta bands across different conditions of the Flanker task. Longitudinal data were collected from a group of typically developing children at ages of seven and nine. We found that the imaginary part of coherency was more helpful in distinguishing between stimuli - alpha and beta bands resulted in 90.90% classification rate in seven year old children. The beta and theta bands were found to be more effective for stimuli classification in nine year old children - more than 84.09% classification accuracy was achieved.

  18. Partial volume effect modeling for segmentation and tissue classification of brain magnetic resonance images: A review.

    PubMed

    Tohka, Jussi

    2014-11-28

    Quantitative analysis of magnetic resonance (MR) brain images are facilitated by the development of automated segmentation algorithms. A single image voxel may contain of several types of tissues due to the finite spatial resolution of the imaging device. This phenomenon, termed partial volume effect (PVE), complicates the segmentation process, and, due to the complexity of human brain anatomy, the PVE is an important factor for accurate brain structure quantification. Partial volume estimation refers to a generalized segmentation task where the amount of each tissue type within each voxel is solved. This review aims to provide a systematic, tutorial-like overview and categorization of methods for partial volume estimation in brain MRI. The review concentrates on the statistically based approaches for partial volume estimation and also explains differences to other, similar image segmentation approaches.

  19. Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease

    PubMed Central

    Wang, Zhengxia; Zhu, Xiaofeng; Adeli, Ehsan; Zhu, Yingying; Zu, Chen; Nie, Feiping; Shen, Dinggang; Wu, Guorong

    2017-01-01

    Graph-based Transductive Learning (GTL) is a powerful tool in computer-assisted diagnosis, especially when the training data is not sufficient to build reliable classifiers. Conventional GTL approaches first construct a fixed subject-wise graph based on the similarities of observed features (i.e., extracted from imaging data) in the feature domain, and then follow the established graph to propagate the existing labels from training to testing data in the label domain. However, such a graph is exclusively learned in the feature domain and may not be necessarily optimal in the label domain. This may eventually undermine the classification accuracy. To address this issue, we propose a progressive GTL (pGTL) method to progressively find an intrinsic data representation. To achieve this, our pGTL method iteratively (1) refines the subject-wise relationships observed in the feature domain using the learned intrinsic data representation in the label domain, (2) updates the intrinsic data representation from the refined subject-wise relationships, and (3) verifies the intrinsic data representation on the training data, in order to guarantee an optimal classification on the new testing data. Furthermore, we extend our pGTL to incorporate multi-modal imaging data, to improve the classification accuracy and robustness as multi-modal imaging data can provide complementary information. Promising classification results in identifying Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal Control (NC) subjects are achieved using MRI and PET data.

  20. Extracellular vesicles in the biology of brain tumour stem cells--Implications for inter-cellular communication, therapy and biomarker development.

    PubMed

    Nakano, Ichiro; Garnier, Delphine; Minata, Mutsuko; Rak, Janusz

    2015-04-01

    Extracellular vesicles (EVs) act as carriers of molecular and oncogenic signatures present in subsets of tumour cells and tumour-associated stroma, and as mediators of intercellular communication. These processes likely involve cancer stem cells (CSCs). EVs represent a unique pathway of cellular export and cell-to-cell transfer of insoluble molecular regulators such as membrane receptors, signalling proteins and metabolites, thereby influencing the functional integration of cancer cell populations. While mechanisms that control biogenesis, cargo and uptake of different classes of EVs (exosomes, microvesicles, ectosomes, large oncosomes) are poorly understood, they likely remain under the influence of stress-responses, microenvironment and oncogenic processes that define the biology and heterogeneity of human cancers. In glioblastoma (GBM), recent molecular profiling approaches distinguished several disease subtypes driven by distinct molecular, epigenetic and mutational mechanisms, leading to formation of proneural, neural, classical and mesenchymal tumours. Moreover, molecularly distinct clonal cellular lineages co-exist within individual GBM lesions, where they differentiate according to distinct stem cell hierarchies resulting in several facets of tumour heterogeneity and the related potential for intercellular interactions. Glioma stem cells (GSCs) may carry signatures of either proneural or mesenchymal GBM subtypes and differ in several biological characteristics that are, at least in part, represented by the output and repertoire of EV production (vesiculome). We report that vesiculomes differ between known GBM subtypes. EVs may also reflect and influence the equilibrium of the stem cell hierarchy, contain oncogenic drivers and modulate the microenvironment (vascular niche). The GBM/GSC subtype-specific differentials in EV cargo of proteins, transcripts, microRNA and DNA may enable detection of the dynamics of the stem cell compartment and result in

  1. Mathematical Modelling of a Brain Tumour Initiation and Early Development: A Coupled Model of Glioblastoma Growth, Pre-Existing Vessel Co-Option, Angiogenesis and Blood Perfusion

    PubMed Central

    Cai, Yan; Wu, Jie; Li, Zhiyong; Long, Quan

    2016-01-01

    We propose a coupled mathematical modelling system to investigate glioblastoma growth in response to dynamic changes in chemical and haemodynamic microenvironments caused by pre-existing vessel co-option, remodelling, collapse and angiogenesis. A typical tree-like architecture network with different orders for vessel diameter is designed to model pre-existing vasculature in host tissue. The chemical substances including oxygen, vascular endothelial growth factor, extra-cellular matrix and matrix degradation enzymes are calculated based on the haemodynamic environment which is obtained by coupled modelling of intravascular blood flow with interstitial fluid flow. The haemodynamic changes, including vessel diameter and permeability, are introduced to reflect a series of pathological characteristics of abnormal tumour vessels including vessel dilation, leakage, angiogenesis, regression and collapse. Migrating cells are included as a new phenotype to describe the migration behaviour of malignant tumour cells. The simulation focuses on the avascular phase of tumour development and stops at an early phase of angiogenesis. The model is able to demonstrate the main features of glioblastoma growth in this phase such as the formation of pseudopalisades, cell migration along the host vessels, the pre-existing vasculature co-option, angiogenesis and remodelling. The model also enables us to examine the influence of initial conditions and local environment on the early phase of glioblastoma growth. PMID:26934465

  2. Mathematical Modelling of a Brain Tumour Initiation and Early Development: A Coupled Model of Glioblastoma Growth, Pre-Existing Vessel Co-Option, Angiogenesis and Blood Perfusion.

    PubMed

    Cai, Yan; Wu, Jie; Li, Zhiyong; Long, Quan

    2016-01-01

    We propose a coupled mathematical modelling system to investigate glioblastoma growth in response to dynamic changes in chemical and haemodynamic microenvironments caused by pre-existing vessel co-option, remodelling, collapse and angiogenesis. A typical tree-like architecture network with different orders for vessel diameter is designed to model pre-existing vasculature in host tissue. The chemical substances including oxygen, vascular endothelial growth factor, extra-cellular matrix and matrix degradation enzymes are calculated based on the haemodynamic environment which is obtained by coupled modelling of intravascular blood flow with interstitial fluid flow. The haemodynamic changes, including vessel diameter and permeability, are introduced to reflect a series of pathological characteristics of abnormal tumour vessels including vessel dilation, leakage, angiogenesis, regression and collapse. Migrating cells are included as a new phenotype to describe the migration behaviour of malignant tumour cells. The simulation focuses on the avascular phase of tumour development and stops at an early phase of angiogenesis. The model is able to demonstrate the main features of glioblastoma growth in this phase such as the formation of pseudopalisades, cell migration along the host vessels, the pre-existing vasculature co-option, angiogenesis and remodelling. The model also enables us to examine the influence of initial conditions and local environment on the early phase of glioblastoma growth.

  3. The neurosurgical aspects in the treatment of cerebral tumours.

    PubMed

    Czirják, S; Bábel, B

    1994-01-01

    Experience with more than 500 tumour cases operated in one year in the National Institute of Neurosurgery and the relevant oncological literature point to an important role of neurosurgery in the treatment of cerebral tumours. After reviewing the dramatic advances of neuroimaging and neurosurgical methods the main problems of neuro-oncology will be brought to light and the new directions of brain tumour research will be shown.

  4. Extrarenal teratoid Wilms' tumour.

    PubMed

    Chowhan, A K; Reddy, M K; Javvadi, V; Kannan, T

    2011-06-01

    We report an unusual case of extrarenal teratoid Wilms' tumour in a 15-month-old male child. The tumour was retroperitoneal in location and consisted of triphasic Wilms' tumour elements, along with the presence of heterologous components. The heterologous teratoid elements were composed of predominantly glandular epithelium with the presence of focal skeletal muscle, adipose and neuroglial tissues. Although extrarenal Wilms' tumours have been documented in the literature, only a few cases have been noted to date. We present the relevant clinical, radiological, histomorphological, histochemical and immunohistochemical features of this rare tumour, and discuss the various theories of its histogenesis.

  5. The impact of severe traumatic brain injury on a novel base deficit- based classification of hypovolemic shock

    PubMed Central

    2014-01-01

    Background Recently, our group has proposed a new classification of hypovolemic shock based on the physiological shock marker base deficit (BD). The classification consists of four groups of worsening BD and correlates with the extent of hypovolemic shock in severely injured patients. The aim of this study was to test the applicability of our recently proposed classification of hypovolemic shock in the context of severe traumatic brain injury (TBI). Methods Between 2002 and 2011, patients ≥16 years in age with an AIShead ≥ 3 have been retrieved from the German TraumaRegister DGU® database. Patients were classified into four strata of worsening BD [(class I (BD ≤ 2 mmol/l), class II (BD > 2.0 to 6.0 mmol/l), class III (BD > 6.0 to 10 mmol/l) and class IV (BD > 10 mmol/l)] and assessed for demographic and injury characteristics as well as blood product transfusions and outcomes. The cohort of severely injured patients with TBI was compared to a population of all trauma patients to assess possible differences in the applicability of the BD based classification of hypovolemic shock. Results From a total of 23,496 patients, 10,201 multiply injured patients with TBI (AIShead ≥ 3) could be identified. With worsening of BD, a consecutive increase of mortality rate from 15.9% in class I to 61.4% in class IV patients was observed. Simultaneously, injury severity scores increased from 20.8 (±11.9) to 41.6 (±17). Increments in BD paralleled decreasing hemoglobin, platelet counts and Quick’s values. The number of blood units transfused correlated with worsening of BD. Massive transfusion rates increased from 5% in class I to 47% in class IV. Between multiply injured patients with TBI and all trauma patients, no clinically relevant differences in transfusion requirement or massive transfusion rates were observed. Conclusion The presence of TBI has no relevant impact on the applicability of the recently proposed BD-based classification of

  6. Multilevel segmentation and integrated bayesian model classification with an application to brain tumor segmentation.

    PubMed

    Corso, Jason J; Sharon, Eitan; Yuille, Alan

    2006-01-01

    We present a new method for automatic segmentation of heterogeneous image data, which is very common in medical image analysis. The main contribution of the paper is a mathematical formulation for incorporating soft model assignments into the calculation of affinities, which are traditionally model free. We integrate the resulting model-aware affinities into the multilevel segmentation by weighted aggregation algorithm. We apply the technique to the task of detecting and segmenting brain tumor and edema in multimodal MR volumes. Our results indicate the benefit of incorporating model-aware affinities into the segmentation process for the difficult case of brain tumor.

  7. Detection and classification of tastants in vivo using a novel bioelectronic tongue in combination with brain-machine interface.

    PubMed

    Zhen Qin; Bin Zhang; Ning Hu; Ping Wang

    2015-01-01

    The mammalian gustatory system is acknowledged as one of the most valid chemosensing systems. The sense of taste particularly provides critical information about ingestion of toxic and noxious chemicals. Thus the potential of utilizing rats' gustatory system is investigated in detecting sapid substances. By recording electrical activities of neurons in gustatory cortex, a novel bioelectronic tongue system is developed in combination with brain-machine interface technology. Features are extracted in both spikes and local field potentials. By visualizing these features, classification is performed and the responses to different tastants can be prominently separated from each other. The results suggest that this in vivo bioelectronic tongue is capable of detecting tastants and will provide a promising platform for potential applications in evaluating palatability of food and beverages.

  8. Outcome Classification of Preschool Children with Autism Spectrum Disorders Using Mri Brain Measures.

    ERIC Educational Resources Information Center

    Akshoomoff, Natacha; Lord, Catherine; Lincoln, Alan J.; Courchesne, Rachel Y.; Carper, Ruth A.; Townsend, Jeanne; Courchesne, Eric

    2004-01-01

    Objective: To test the hypothesis that a combination of magnetic resonance imaging (MRI) brain measures obtained during early childhood distinguish children with autism spectrum disorders (ASD) from typically developing children and is associated with functional outcome. Method: Quantitative MRI technology was used to measure gray and white matter…

  9. WAIS Digit Span-Based Indicators of Malingered Neurocognitive Dysfunction: Classification Accuracy in Traumatic Brain Injury

    ERIC Educational Resources Information Center

    Heinly, Matthew T.; Greve, Kevin W.; Bianchini, Kevin J.; Love, Jeffrey M.; Brennan, Adrianne

    2005-01-01

    The present study determined specificity and sensitivity to malingered neurocognitive dysfunction (MND) in traumatic brain injury (TBI) for several Wechsler Adult Intelligence Scale (WAIS) Digit Span scores. TBI patients (n = 344) were categorized into one of five groups: no incentive, incentive only, suspect, probable MND, and definite MND.…

  10. Classification effects of real and imaginary movement selective attention tasks on a P300-based brain-computer interface

    NASA Astrophysics Data System (ADS)

    Salvaris, Mathew; Sepulveda, Francisco

    2010-10-01

    Brain-computer interfaces (BCIs) rely on various electroencephalography methodologies that allow the user to convey their desired control to the machine. Common approaches include the use of event-related potentials (ERPs) such as the P300 and modulation of the beta and mu rhythms. All of these methods have their benefits and drawbacks. In this paper, three different selective attention tasks were tested in conjunction with a P300-based protocol (i.e. the standard counting of target stimuli as well as the conduction of real and imaginary movements in sync with the target stimuli). The three tasks were performed by a total of 10 participants, with the majority (7 out of 10) of the participants having never before participated in imaginary movement BCI experiments. Channels and methods used were optimized for the P300 ERP and no sensory-motor rhythms were explicitly used. The classifier used was a simple Fisher's linear discriminant. Results were encouraging, showing that on average the imaginary movement achieved a P300 versus No-P300 classification accuracy of 84.53%. In comparison, mental counting, the standard selective attention task used in previous studies, achieved 78.9% and real movement 90.3%. Furthermore, multiple trial classification results were recorded and compared, with real movement reaching 99.5% accuracy after four trials (12.8 s), imaginary movement reaching 99.5% accuracy after five trials (16 s) and counting reaching 98.2% accuracy after ten trials (32 s).

  11. Detection of Mild Traumatic Brain Injury by Machine Learning Classification Using Resting State Functional Network Connectivity and Fractional Anisotropy.

    PubMed

    Vergara, Victor M; Mayer, Andrew R; Damaraju, Eswar; Kiehl, Kent A; Calhoun, Vince

    2017-03-01

    Traumatic brain injury (TBI) may adversely affect a person's thinking, memory, personality, and behavior. While mild TBI (mTBI) diagnosis is challenging, there is a risk for long-term psychiatric, neurologic, and psychosocial problems in some patients that motivates the search for new and better biomarkers. Recently, diffusion magnetic resonance imaging (dMRI) has shown promise in detecting mTBI, but its validity is still being investigated. Resting state functional network connectivity (rsFNC) is another approach that is emerging as a promising option for the diagnosis of mTBI. The present work investigated the use of rsFNC for mTBI detection compared with dMRI results on the same cohort. Fifty patients with mTBI (25 males) and age-sex matched healthy controls were recruited. Features from dMRI were obtained using all voxels, the enhanced Z-score microstructural assessment for pathology, and the distribution corrected Z-score. Features based on rsFNC were obtained through group independent component analysis and correlation between pairs of resting state networks. A linear support vector machine was used for classification and validated using leave-one-out cross validation. Classification achieved a maximum accuracy of 84.1% for rsFNC and 75.5% for dMRI and 74.5% for both combined. A t test analysis revealed significant increase in rsFNC between cerebellum versus sensorimotor networks and between left angular gyrus versus precuneus in subjects with mTBI. These outcomes suggest that inclusion of both common and unique information is important for classification of mTBI. Results also suggest that rsFNC can yield viable biomarkers that might outperform dMRI and points to connectivity to the cerebellum as an important region for the detection of mTBI.

  12. Randomized pilot study and qualitative evaluation of a clinical decision support system for brain tumour diagnosis based on SV ¹H MRS: evaluation as an additional information procedure for novice radiologists.

    PubMed

    Sáez, Carlos; Martí-Bonmatí, Luis; Alberich-Bayarri, Angel; Robles, Montserrat; García-Gómez, Juan M

    2014-02-01

    The results of a randomized pilot study and qualitative evaluation of the clinical decision support system Curiam BT are reported. We evaluated the system's feasibility and potential value as a radiological information procedure complementary to magnetic resonance (MR) imaging to assist novice radiologists in diagnosing brain tumours using MR spectroscopy (1.5 and 3.0T). Fifty-five cases were analysed at three hospitals according to four non-exclusive diagnostic questions. Our results show that Curiam BT improved the diagnostic accuracy in all the four questions. Additionally, we discuss the findings of the users' feedback about the system, and the further work to optimize it for real environments and to conduct a large clinical trial.

  13. Malignant tumours after renal transplantation.

    PubMed

    Fahlenkamp, D; Reinke, P; Kirchner, S; Schnorr, D; Lindeke, A; Loening, S A

    1996-10-01

    In 1243 patients after renal transplantation, 39 malignant tumours were detected in 37 patients. The average latency period between transplantation and tumour disease was 72 months. Tumours included 8 malignant lymphomas, 7 dermatomas and 24 visceral tumours. The patients who developed a tumour had received fewer blood transfusions before transplantation than a tumour-free control group of 60 patients with renal transplants. Rejection crises occurred in a significantly smaller number of tumour patients compared with the control group.

  14. Automatic brain caudate nuclei segmentation and classification in diagnostic of Attention-Deficit/Hyperactivity Disorder.

    PubMed

    Igual, Laura; Soliva, Joan Carles; Escalera, Sergio; Gimeno, Roger; Vilarroya, Oscar; Radeva, Petia

    2012-12-01

    We present a fully automatic diagnostic imaging test for Attention-Deficit/Hyperactivity Disorder diagnosis assistance based on previously found evidences of caudate nucleus volumetric abnormalities. The proposed method consists of different steps: a new automatic method for external and internal segmentation of caudate based on Machine Learning methodologies; the definition of a set of new volume relation features, 3D Dissociated Dipoles, used for caudate representation and classification. We separately validate the contributions using real data from a pediatric population and show precise internal caudate segmentation and discrimination power of the diagnostic test, showing significant performance improvements in comparison to other state-of-the-art methods.

  15. Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis.

    PubMed

    Sripada, Chandra Sekhar; Kessler, Daniel; Welsh, Robert; Angstadt, Michael; Liberzon, Israel; Phan, K Luan; Scott, Clayton

    2013-11-01

    Methylphenidate is a psychostimulant medication that produces improvements in functions associated with multiple neurocognitive systems. To investigate the potentially distributed effects of methylphenidate on the brain's intrinsic network architecture, we coupled resting state imaging with multivariate pattern classification. In a within-subject, double-blind, placebo-controlled, randomized, counterbalanced, cross-over design, 32 healthy human volunteers received either methylphenidate or placebo prior to two fMRI resting state scans separated by approximately one week. Resting state connectomes were generated by placing regions of interest at regular intervals throughout the brain, and these connectomes were submitted for support vector machine analysis. We found that methylphenidate produces a distributed, reliably detected, multivariate neural signature. Methylphenidate effects were evident across multiple resting state networks, especially visual, somatomotor, and default networks. Methylphenidate reduced coupling within visual and somatomotor networks. In addition, default network exhibited decoupling with several task positive networks, consistent with methylphenidate modulation of the competitive relationship between these networks. These results suggest that connectivity changes within and between large-scale networks are potentially involved in the mechanisms by which methylphenidate improves attention functioning.

  16. Brain networks involved in tactile speed classification of moving dot patterns: the effects of speed and dot periodicity

    PubMed Central

    Yang, Jiajia; Kitada, Ryo; Kochiyama, Takanori; Yu, Yinghua; Makita, Kai; Araki, Yuta; Wu, Jinglong; Sadato, Norihiro

    2017-01-01

    Humans are able to judge the speed of an object’s motion by touch. Research has suggested that tactile judgment of speed is influenced by physical properties of the moving object, though the neural mechanisms underlying this process remain poorly understood. In the present study, functional magnetic resonance imaging was used to investigate brain networks that may be involved in tactile speed classification and how such networks may be affected by an object’s texture. Participants were asked to classify the speed of 2-D raised dot patterns passing under their right middle finger. Activity in the parietal operculum, insula, and inferior and superior frontal gyri was positively related to the motion speed of dot patterns. Activity in the postcentral gyrus and superior parietal lobule was sensitive to dot periodicity. Psycho-physiological interaction (PPI) analysis revealed that dot periodicity modulated functional connectivity between the parietal operculum (related to speed) and postcentral gyrus (related to dot periodicity). These results suggest that texture-sensitive activity in the primary somatosensory cortex and superior parietal lobule influences brain networks associated with tactually-extracted motion speed. Such effects may be related to the influence of surface texture on tactile speed judgment. PMID:28145505

  17. Brain tissue classification based on DTI using an improved fuzzy C-means algorithm with spatial constraints.

    PubMed

    Wen, Ying; He, Lianghua; von Deneen, Karen M; Lu, Yue

    2013-11-01

    We present an effective method for brain tissue classification based on diffusion tensor imaging (DTI) data. The method accounts for two main DTI segmentation obstacles: random noise and magnetic field inhomogeneities. In the proposed method, DTI parametric maps were used to resolve intensity inhomogeneities of brain tissue segmentation because they could provide complementary information for tissues and define accurate tissue maps. An improved fuzzy c-means with spatial constraints proposal was used to enhance the noise and artifact robustness of DTI segmentation. Fuzzy c-means clustering with spatial constraints (FCM_S) could effectively segment images corrupted by noise, outliers, and other imaging artifacts. Its effectiveness contributes not only to the introduction of fuzziness for belongingness of each pixel but also to the exploitation of spatial contextual information. We proposed an improved FCM_S applied on DTI parametric maps, which explores the mean and covariance of the feature spatial information for automated segmentation of DTI. The experiments on synthetic images and real-world datasets showed that our proposed algorithms, especially with new spatial constraints, were more effective.

  18. Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification

    PubMed Central

    Desroches, Joannie; Jermyn, Michael; Mok, Kelvin; Lemieux-Leduc, Cédric; Mercier, Jeanne; St-Arnaud, Karl; Urmey, Kirk; Guiot, Marie-Christine; Marple, Eric; Petrecca, Kevin; Leblond, Frédéric

    2015-01-01

    A detailed characterization study is presented of a Raman spectroscopy system designed to maximize the volume of resected cancer tissue in glioma surgery based on in vivo molecular tissue characterization. It consists of a hand-held probe system measuring spectrally resolved inelastically scattered light interacting with tissue, designed and optimized for in vivo measurements. Factors such as linearity of the signal with integration time and laser power, and their impact on signal to noise ratio, are studied leading to optimal data acquisition parameters. The impact of ambient light sources in the operating room is assessed and recommendations made for optimal operating conditions. In vivo Raman spectra of normal brain, cancer and necrotic tissue were measured in 10 patients, demonstrating that real-time inelastic scattering measurements can distinguish necrosis from vital tissue (including tumor and normal brain tissue) with an accuracy of 87%, a sensitivity of 84% and a specificity of 89%. PMID:26203368

  19. Brain tumor classification using AFM in combination with data mining techniques.

    PubMed

    Huml, Marlene; Silye, René; Zauner, Gerald; Hutterer, Stephan; Schilcher, Kurt

    2013-01-01

    Although classification of astrocytic tumors is standardized by the WHO grading system, which is mainly based on microscopy-derived, histomorphological features, there is great interobserver variability. The main causes are thought to be the complexity of morphological details varying from tumor to tumor and from patient to patient, variations in the technical histopathological procedures like staining protocols, and finally the individual experience of the diagnosing pathologist. Thus, to raise astrocytoma grading to a more objective standard, this paper proposes a methodology based on atomic force microscopy (AFM) derived images made from histopathological samples in combination with data mining techniques. By comparing AFM images with corresponding light microscopy images of the same area, the progressive formation of cavities due to cell necrosis was identified as a typical morphological marker for a computer-assisted analysis. Using genetic programming as a tool for feature analysis, a best model was created that achieved 94.74% classification accuracy in distinguishing grade II tumors from grade IV ones. While utilizing modern image analysis techniques, AFM may become an important tool in astrocytic tumor diagnosis. By this way patients suffering from grade II tumors are identified unambiguously, having a less risk for malignant transformation. They would benefit from early adjuvant therapies.

  20. Toward more intuitive brain-computer interfacing: classification of binary covert intentions using functional near-infrared spectroscopy

    NASA Astrophysics Data System (ADS)

    Hwang, Han-Jeong; Choi, Han; Kim, Jeong-Youn; Chang, Won-Du; Kim, Do-Won; Kim, Kiwoong; Jo, Sungho; Im, Chang-Hwan

    2016-09-01

    In traditional brain-computer interface (BCI) studies, binary communication systems have generally been implemented using two mental tasks arbitrarily assigned to "yes" or "no" intentions (e.g., mental arithmetic calculation for "yes"). A recent pilot study performed with one paralyzed patient showed the possibility of a more intuitive paradigm for binary BCI communications, in which the patient's internal yes/no intentions were directly decoded from functional near-infrared spectroscopy (fNIRS). We investigated whether such an "fNIRS-based direct intention decoding" paradigm can be reliably used for practical BCI communications. Eight healthy subjects participated in this study, and each participant was administered 70 disjunctive questions. Brain hemodynamic responses were recorded using a multichannel fNIRS device, while the participants were internally expressing "yes" or "no" intentions to each question. Different feature types, feature numbers, and time window sizes were tested to investigate optimal conditions for classifying the internal binary intentions. About 75% of the answers were correctly classified when the individual best feature set was employed (75.89% ±1.39 and 74.08% ±2.87 for oxygenated and deoxygenated hemoglobin responses, respectively), which was significantly higher than a random chance level (68.57% for p<0.001). The kurtosis feature showed the highest mean classification accuracy among all feature types. The grand-averaged hemodynamic responses showed that wide brain regions are associated with the processing of binary implicit intentions. Our experimental results demonstrated that direct decoding of internal binary intention has the potential to be used for implementing more intuitive and user-friendly communication systems for patients with motor disabilities.

  1. Endolymphatic sac tumour.

    PubMed

    Zulkarnaen, Mohammad; Tang, Ing Ping; Wong, Siong Lung

    2012-06-01

    We present a case of a papillary tumour at the cerebellopontine angle in a 41-year-old man. He presented with left-sided facial and ear pain associated with dizziness, nystagmus and hearing loss. CT scan of the temporal bone showed a destructive tumour at the left cerebellopontine angle. Surgical excision was performed and the diagnosis of the endolymphatic sac tumour was made. Endolymphatic tumour is a low grade adenocarcinoma that originates from the endolymphatic sac. The definitive diagnosis requires a combination of clinical features, radiological finding and pathological correlation.

  2. Tumour progression and metastasis

    PubMed Central

    Arvelo, Francisco; Sojo, Felipe; Cotte, Carlos

    2016-01-01

    The two biological mechanisms that determine types of malignancy are infiltration and metastasis, for which tumour microenvironment plays a key role in developing and establishing the morphology, growth and invasiveness of a malignancy. The microenvironment is formed by complex tissue containing the extracellular matrix, tumour and non-tumour cells, a signalling network of cytokines, chemokines, growth factors, and proteases that control autocrine and paracrine communication among individual cells, facilitating tumour progression. During the development of the primary tumour, the tumour stroma and continuous genetic changes within the cells makes it possible for them to migrate, having to count on a pre-metastatic niche receptor that allows the tumour’s survival and distant growth. These niches are induced by factors produced by the primary tumour; if it is eradicated, the active niches become responsible for activating the latent disseminated cells. Due to the importance of these mechanisms, the strategies that develop tumour cells during tumour progression and the way in which the microenvironment influences the formation of metastasis are reviewed. It also suggests that the metastatic niche can be an ideal target for new treatments that make controlling metastasis possible. PMID:26913068

  3. New frontiers for astrocytic tumours.

    PubMed

    Nano, Rosanna; Lascialfari, Alessandro; Corti, Maurizio; Paolini, Alessandro; Pasi, Francesca; Corbella, Franco; DI Liberto, Riccardo

    2012-07-01

    Glioblastoma multiforme, the most common type of primary brain tumour, remains an unsolved clinical problem. A great deal of work has been done in an effort to understand the biology and genetics of glioblastoma multiforme, but clinically effective treatments remain elusive. It is well known that malignant gliomas develop resistance to chemo- and radiotherapy. In this review we evaluated the literature data regarding therapeutic progress for the treatment of astrocytic tumours, focusing our attention on new frontiers for glioblastoma. The research studies performed in in vitro and in vivo models show that the application of hyperthermia using magnetic nanoparticles is safe and could be a promising tool in the treatment of glioblastoma patients. Our efforts are focused towards new fields of research, for example nanomedicine and the study of the uptake and cytotoxic effects of magnetic nanoparticles. The improvement of the quality of life of patients, by increasing their survival rate is the best result to be pursued, since these tumours are considered as ineradicable.

  4. Melanotic neuroectodermal tumour of infancy.

    PubMed

    Pattanayak Mohanty, Sweta; Ray, Jay Gopal; Richa; Mukherjee, Sanjit; Mandal, Chitra; Chaudhuri, Keya

    2010-11-23

    Melanotic neuroectodermal tumour of infancy (MNTI) is a rare benign tumour of neural crest origin that was first described by Krompecher in 1918.1 It is predominantly found in infancy, with about 92% of cases below the age of 12 months and 82% below the age of 6 months. The predominant site of origin is in the premaxilla though it is reported at other sites also including the skull, the mandible, the epididymis and the brain.2 The lesions often have areas of bluish discolouration on the surface and are characterised by displacement of the involved tooth bud and local aggressiveness. The present report deals with two cases of MNTI, a 5-month-old baby girl and a 6-month-old baby boy who reported to the Department of Oral and Maxillofacial Pathology, Dr R Ahmed Dental College and Hospital, Kolkata, India. The clinical, radiological, histological and immunohistochemical findings, confirmed the diagnosis of MNTI. Flow cytometry was performed to analyse aneuploidy. The tumours were treated surgically with no history of recurrence to date.

  5. [The role of diagnostic neuropathology in familial tumour syndromes].

    PubMed

    Feiden, S; Sartorius, E; Feiden, W

    2010-10-01

    Inherited cancer syndromes often involve the central and peripheral nervous system. For the surgical neuropathologist the possibility in individual patients of a familial tumour syndrome needs to be considered in the case of special tumours such as malignant peripheral nerve sheath tumour (MPNST), medulloblastoma with extensive nodularity (MBEN) or even atypical teratoid/rhabdoid tumour (AT/RT) of the brain. Furthermore, tumour location and patient age may point to a familial tumour syndrome as in the case of neurofibromatosis type 2 (NF2) with typical bilateral vestibular schwannoma in young age. This short review discusses some of the diagnostic aspects in this field relating to neurofibromatosis type 1 and 2 (NF1, NF2), as well as the two rare tumors MBEN in Gorlin-Goltz syndrome and AT/RT in particular.

  6. The classification of microglial activation phenotypes on neurodegeneration and regeneration in Alzheimer’s disease brain

    PubMed Central

    Varnum, Megan M.; Ikezu, Tsuneya

    2015-01-01

    Alzheimer’s disease (AD) is a neurodegenerative disease characterized by progressive decline of cognitive function and memory formation. There is no therapeutic that can halt or reverse its progression. Contemporary research suggests that age-dependent neuroinflammatory changes may play a significant role in the decreased neurogenesis and cognitive impairments in AD. The innate immune response is characterized by pro-inflammatory (M1) activation of macrophages and subsequent production of specific cytokines, chemokines, and reactive intermediates, followed by resolution and alternative activation for anti-inflammatory signaling (M2a) and wound healing (M2c). We propose that microglial activation phenotypes are analogous to those of macrophages and that their activation plays a significant role in regulating neurogenesis in the brain. Microglia undergo a switch from an M2- to an M1-skewed activation phenotype during aging. This review will assess the neuroimmunological studies that led to characterization of the different microglial activation states using AD mouse models. It will also discuss the roles of microglial activation on neurogenesis in AD and propose anti-inflammatory molecules as exciting therapeutic targets for research. Molecules like interleukin-4 and CD200 have proven to be important anti-inflammatory molecules in the regulation of neuroinflammation in the brain, and they will be discussed in detail for their therapeutic potential. PMID:22710659

  7. The classification of microglial activation phenotypes on neurodegeneration and regeneration in Alzheimer's disease brain.

    PubMed

    Varnum, Megan M; Ikezu, Tsuneya

    2012-08-01

    Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive decline of cognitive function. There is no therapy that can halt or reverse its progression. Contemporary research suggests that age-dependent neuroinflammatory changes may play a significant role in the decreased neurogenesis and cognitive impairments in AD. The innate immune response is characterized by pro-inflammatory (M1) activation of macrophages and subsequent production of specific cytokines, chemokines, and reactive intermediates, followed by resolution and alternative activation for anti-inflammatory signaling (M2a) and wound healing (M2c). We propose that microglial activation phenotypes are analogous to those of macrophages and that their activation plays a significant role in regulating neurogenesis in the brain. Microglia undergo a switch from an M2- to an M1-skewed activation phenotype during aging. This review will assess the neuroimmunological studies that led to characterization of the different microglial activation states in AD mouse models. It will also discuss the roles of microglial activation on neurogenesis in AD and propose anti-inflammatory molecules as exciting therapeutic targets for research. Molecules such as interleukin-4 and CD200 have proven to be important anti-inflammatory mediators in the regulation of neuroinflammation in the brain, which will be discussed in detail for their therapeutic potential.

  8. A discriminative model-constrained EM approach to 3D MRI brain tissue classification and intensity non-uniformity correction

    NASA Astrophysics Data System (ADS)

    Wels, Michael; Zheng, Yefeng; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

    2011-06-01

    We describe a fully automated method for tissue classification, which is the segmentation into cerebral gray matter (GM), cerebral white matter (WM), and cerebral spinal fluid (CSF), and intensity non-uniformity (INU) correction in brain magnetic resonance imaging (MRI) volumes. It combines supervised MRI modality-specific discriminative modeling and unsupervised statistical expectation maximization (EM) segmentation into an integrated Bayesian framework. While both the parametric observation models and the non-parametrically modeled INUs are estimated via EM during segmentation itself, a Markov random field (MRF) prior model regularizes segmentation and parameter estimation. Firstly, the regularization takes into account knowledge about spatial and appearance-related homogeneity of segments in terms of pairwise clique potentials of adjacent voxels. Secondly and more importantly, patient-specific knowledge about the global spatial distribution of brain tissue is incorporated into the segmentation process via unary clique potentials. They are based on a strong discriminative model provided by a probabilistic boosting tree (PBT) for classifying image voxels. It relies on the surrounding context and alignment-based features derived from a probabilistic anatomical atlas. The context considered is encoded by 3D Haar-like features of reduced INU sensitivity. Alignment is carried out fully automatically by means of an affine registration algorithm minimizing cross-correlation. Both types of features do not immediately use the observed intensities provided by the MRI modality but instead rely on specifically transformed features, which are less sensitive to MRI artifacts. Detailed quantitative evaluations on standard phantom scans and standard real-world data show the accuracy and robustness of the proposed method. They also demonstrate relative superiority in comparison to other state-of-the-art approaches to this kind of computational task: our method achieves average

  9. Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles.

    PubMed

    Barker, Jocelyn; Hoogi, Assaf; Depeursinge, Adrien; Rubin, Daniel L

    2016-05-01

    Computerized analysis of digital pathology images offers the potential of improving clinical care (e.g. automated diagnosis) and catalyzing research (e.g. discovering disease subtypes). There are two key challenges thwarting computerized analysis of digital pathology images: first, whole slide pathology images are massive, making computerized analysis inefficient, and second, diverse tissue regions in whole slide images that are not directly relevant to the disease may mislead computerized diagnosis algorithms. We propose a method to overcome both of these challenges that utilizes a coarse-to-fine analysis of the localized characteristics in pathology images. An initial surveying stage analyzes the diversity of coarse regions in the whole slide image. This includes extraction of spatially localized features of shape, color and texture from tiled regions covering the slide. Dimensionality reduction of the features assesses the image diversity in the tiled regions and clustering creates representative groups. A second stage provides a detailed analysis of a single representative tile from each group. An Elastic Net classifier produces a diagnostic decision value for each representative tile. A weighted voting scheme aggregates the decision values from these tiles to obtain a diagnosis at the whole slide level. We evaluated our method by automatically classifying 302 brain cancer cases into two possible diagnoses (glioblastoma multiforme (N = 182) versus lower grade glioma (N = 120)) with an accuracy of 93.1% (p < 0.001). We also evaluated our method in the dataset provided for the 2014 MICCAI Pathology Classification Challenge, in which our method, trained and tested using 5-fold cross validation, produced a classification accuracy of 100% (p < 0.001). Our method showed high stability and robustness to parameter variation, with accuracy varying between 95.5% and 100% when evaluated for a wide range of parameters. Our approach may be useful to automatically

  10. EEG brain mapping and brain connectivity index for subtypes classification of attention deficit hyperactivity disorder children during the eye-opened period.

    PubMed

    Rodrak, Supassorn; Wongsawat, Yodchanan

    2013-01-01

    Attention deficit hyperactivity disorder (ADHD) is one of the most prevalent neurological disorders. It is classified by the DSM-IV into three subtypes, i.e. 1) predominately inattentive type, 2) predominately hyperactive-impulsive type, and (3) combined type. In order to make the treatment via the neurofeedback or the occupational therapy, quantitative evaluations as well as ADHD subtype classification are the important problems to be solved to enhance an alternative way to treat ADHD. Hence, in this paper, we systematically classify all of these three subtypes by the 19-channel EEG data. Three brain mapping (QEEG) techniques, i.e. absolute power of frequency bands, coherence, and phase lag, are employed to visualize each type of the ADHD. ADHD children with combined type have deficit in delta theta and alpha activity. For the inattentive type, there are excessive delta and theta absolute power in the frontal area as well as the excessive coherence in beta and high beta frequency bands. For the hyperactivity and impulsive type, the behavior is dominated by the slow wave. This information will give benefits to the psychiatrist, psychologist, neurofeedback therapist as well as the occupational therapist for quantitatively planning and analyzing the treatment.

  11. Progressive dysembryoplastic neuroepithelial tumour.

    PubMed

    Alexander, Hamish; Tannenburg, Anthony; Walker, David G; Coyne, Terry

    2015-01-01

    Dysembryoplastic neuroepithelial tumour (DNET) is a benign tumour characterised by cortical location and presentation with drug resistant partial seizures in children. Recently the potential for malignant transformation has been reported, however progression without malignant transformation remains rare. We report a case of clinical and radiologic progression of a DNET in a girl 10 years after initial biopsy.

  12. A Knowledge Discovery Approach to Diagnosing Intracranial Hematomas on Brain CT: Recognition, Measurement and Classification

    NASA Astrophysics Data System (ADS)

    Liao, Chun-Chih; Xiao, Furen; Wong, Jau-Min; Chiang, I.-Jen

    Computed tomography (CT) of the brain is preferred study on neurological emergencies. Physicians use CT to diagnose various types of intracranial hematomas, including epidural, subdural and intracerebral hematomas according to their locations and shapes. We propose a novel method that can automatically diagnose intracranial hematomas by combining machine vision and knowledge discovery techniques. The skull on the CT slice is located and the depth of each intracranial pixel is labeled. After normalization of the pixel intensities by their depth, the hyperdense area of intracranial hematoma is segmented with multi-resolution thresholding and region-growing. We then apply C4.5 algorithm to construct a decision tree using the features of the segmented hematoma and the diagnoses made by physicians. The algorithm was evaluated on 48 pathological images treated in a single institute. The two discovered rules closely resemble those used by human experts, and are able to make correct diagnoses in all cases.

  13. Raman and FTIR microspectroscopy for detection of brain metastasis

    NASA Astrophysics Data System (ADS)

    Bergner, Norbert; Romeike, Bernd F. M.; Reichart, Rupert; Kalff, Rolf; Krafft, Christoph; Popp, Jürgen

    2011-07-01

    Vibrational spectroscopic imaging methods are novel tools to visualise chemical component in tissue without staining. Fourier transform infrared (FTIR) imaging is more frequently applied than Raman imaging so far. FTIR images recorded with a FPA detector have been demonstrated to identify the primary tumours of brain metastases. However, the strong absorption of water makes it difficult to transfer the results to non-dried tissues. Raman spectroscopy with near infrared excitation can be used instead and allows collecting the chemical fingerprint of native specimens. Therefore, Raman spectroscopy is a promising tool for tumour diagnosis in neurosurgery. Scope of the study is to compare FTIR and Raman images to visualize the tumour border and identify spectral features for classification. Brain metastases were obtained from patients undergoing surgery at the university hospital. Brain tissue sections were shock frozen, cryosectioned, dried and the same areas were imaged with both spectroscopic method. To visualise the chemical components, multivariate statistical algorithms were applied for data analysis. Furthermore classification models were trained using supervised algorithms to predict the primary tumor of brain metastases. Principal component regression (PCR) was used for prediction based on FTIR images. Support vector machines (SVM) were used for prediction based on Raman images. The principles are shown for two specimens. In the future, the study will be extended to larger data sets.

  14. Sonic Hedgehog promotes proliferation of Notch-dependent monociliated choroid plexus tumour cells

    PubMed Central

    Li, Li; Grausam, Katie B.; Wang, Jun; Lun, Melody P.; Ohli, Jasmin; Lidov, Hart G. W.; Calicchio, Monica L.; Zeng, Erliang; Salisbury, Jeffrey L.; Wechsler-Reya, Robert J.; Lehtinen, Maria K.; Schüller, Ulrich; Zhao, Haotian

    2016-01-01

    Aberrant Notch signaling has been linked to many cancers including choroid plexus (CP) tumours, a group of rare and predominantly pediatric brain neoplasms. We developed animal models of CP tumours by inducing sustained expression of Notch1 that recapitulate properties of human CP tumours with aberrant NOTCH signaling. Whole transcriptome and functional analyses showed that tumour cell proliferation is associated with Sonic Hedgehog (Shh) in the tumour microenvironment. Unlike CP epithelial cells, which have multiple primary cilia, tumour cells possess a solitary primary cilium as a result of Notch-mediated suppression of multiciliate diffferentiation. A Shh-driven signaling cascade in the primary cilium occurs in tumour cells but not in epithelial cells. Lineage studies show that CP tumours arise from mono-ciliated progenitors in the roof plate characterized by elevated Notch signaling. Abnormal SHH signaling and distinct ciliogenesis are detected in human CP tumours, suggesting SHH pathway and cilia differentiation as potential therapeutic avenues. PMID:26999738

  15. Clustering-initiated factor analysis application for tissue classification in dynamic brain positron emission tomography.

    PubMed

    Boutchko, Rostyslav; Mitra, Debasis; Baker, Suzanne L; Jagust, William J; Gullberg, Grant T

    2015-07-01

    The goal is to quantify the fraction of tissues that exhibit specific tracer binding in dynamic brain positron emission tomography (PET). It is achieved using a new method of dynamic image processing: clustering-initiated factor analysis (CIFA). Standard processing of such data relies on region of interest analysis and approximate models of the tracer kinetics and of tissue properties, which can degrade accuracy and reproducibility of the analysis. Clustering-initiated factor analysis allows accurate determination of the time-activity curves and spatial distributions for tissues that exhibit significant radiotracer concentration at any stage of the emission scan, including the arterial input function. We used this approach in the analysis of PET images obtained using (11)C-Pittsburgh Compound B in which specific binding reflects the presence of β-amyloid. The fraction of the specific binding tissues determined using our approach correlated with that computed using the Logan graphical analysis. We believe that CIFA can be an accurate and convenient tool for measuring specific binding tissue concentration and for analyzing tracer kinetics from dynamic images for a variety of PET tracers. As an illustration, we show that four-factor CIFA allows extraction of two blood curves and the corresponding distributions of arterial and venous blood from PET images even with a coarse temporal resolution.

  16. Comparing implementations of magnetic-resonance-guided fluorescence molecular tomography for diagnostic classification of brain tumors

    NASA Astrophysics Data System (ADS)

    Davis, Scott C.; Samkoe, Kimberley S.; O'Hara, Julia A.; Gibbs-Strauss, Summer L.; Paulsen, Keith D.; Pogue, Brian W.

    2010-09-01

    Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT scanner. All data were spectrally unmixed to extract the dye fluorescence from the tissue autofluorescence. Methods to combine the two data sets were compared using student's t-tests and receiver operating characteristic analysis. Bulk fluorescence measurements that made up the optical imaging data set were also considered in the comparison. While most techniques were able to distinguish EGFR(+) tumors from EGFR(-) tumors and control animals, with area-under-the-curve values=1, only a handful were able to distinguish EGFR(-) tumors from controls. Bulk fluorescence spectroscopy techniques performed as well as most imaging techniques, suggesting that complex imaging algorithms may be unnecessary to diagnose EGFR status in these tissue volumes.

  17. Automatic Region-Based Brain Classification of MRI-T1 Data

    PubMed Central

    Yusof, Rubiyah

    2016-01-01

    Image segmentation of medical images is a challenging problem with several still not totally solved issues, such as noise interference and image artifacts. Region-based and histogram-based segmentation methods have been widely used in image segmentation. Problems arise when we use these methods, such as the selection of a suitable threshold value for the histogram-based method and the over-segmentation followed by the time-consuming merge processing in the region-based algorithm. To provide an efficient approach that not only produce better results, but also maintain low computational complexity, a new region dividing based technique is developed for image segmentation, which combines the advantages of both regions-based and histogram-based methods. The proposed method is applied to the challenging applications: Gray matter (GM), White matter (WM) and cerebro-spinal fluid (CSF) segmentation in brain MR Images. The method is evaluated on both simulated and real data, and compared with other segmentation techniques. The obtained results have demonstrated its improved performance and robustness. PMID:27096925

  18. Image Data Mining for Pattern Classification and Visualization of Morphological Changes in Brain MR Images.

    PubMed

    Murakawa, Saki; Ikuta, Rie; Uchiyama, Yoshikazu; Shiraishi, Junji

    2016-02-01

    Hospital information systems (HISs) and picture archiving and communication systems (PACSs) are archiving large amounts of data (i.e., "big data") that are not being used. Therefore, many research projects in progress are trying to use "big data" for the development of early diagnosis, prediction of disease onset, and personalized therapies. In this study, we propose a new method for image data mining to identify regularities and abnormalities in the large image data sets. We used 70 archived magnetic resonance (MR) images that were acquired using three-dimensional magnetization-prepared rapid acquisition with gradient echo (3D MP-RAGE). These images were obtained from the Alzheimer's disease neuroimaging initiative (ADNI) database. For anatomical standardization of the data, we used the statistical parametric mapping (SPM) software. Using a similarity matrix based on cross-correlation coefficients (CCs) calculated from an anatomical region and a hierarchical clustering technique, we classified all the abnormal cases into five groups. The Z score map identified the difference between a standard normal brain and each of those from the Alzheimer's groups. In addition, the scatter plot obtained from two similarity matrixes visualized the regularities and abnormalities in the image data sets. Image features identified using our method could be useful for understanding of image findings associated with Alzheimer's disease.

  19. Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders.

    PubMed

    Wang, Hui; Chen, Chen; Fushing, Hsieh

    2012-01-01

    We employed a multi-scale clustering methodology known as "data cloud geometry" to extract functional connectivity patterns derived from functional magnetic resonance imaging (fMRI) protocol. The method was applied to correlation matrices of 106 regions of interest (ROIs) in 29 individuals with autism spectrum disorders (ASD), and 29 individuals with typical development (TD) while they completed a cognitive control task. Connectivity clustering geometry was examined at both "fine" and "coarse" scales. At the coarse scale, the connectivity clustering geometry produced 10 valid clusters with a coherent relationship to neural anatomy. A supervised learning algorithm employed fine scale information about clustering motif configurations and prevalence, and coarse scale information about intra- and inter-regional connectivity; the algorithm correctly classified ASD and TD participants with sensitivity of 82.8% and specificity of 82.8%. Most of the predictive power of the logistic regression model resided at the level of the fine-scale clustering geometry, suggesting that cellular versus systems level disturbances are more prominent in individuals with ASD. This article provides validation for this multi-scale geometric approach to extracting brain functional connectivity pattern information and for its use in classification of ASD.

  20. Possible Roles of the Dominant Uncinate Fasciculus in Naming Objects: A Case Report of Intraoperative Electrical Stimulation on a Patient with a Brain Tumour

    PubMed Central

    Nomura, Keiko; Kazui, Hiroaki; Tokunaga, Hiromasa; Hirata, Masayuki; Goto, Tetsu; Goto, Yuko; Hashimoto, Naoya; Yoshimine, Toshiki; Takeda, Masatoshi

    2013-01-01

    How the dominant uncinate fasciculus (UF) contributes to naming performance is uncertain. In this case report, a patient with an astrocytoma near the dominant UF was given a picture-naming task during intraoperative electrical stimulation in order to resect as much tumourous tissues as possible without impairing the dominant UF function. Here we report that the stimulations with the picture-naming task also provided some insights into how the dominant UF contributes to naming performance. The stimulation induced naming difficulty, verbal paraphasia, and recurrent and continuous perseveration. Moreover, just after producing the incorrect responses, the patient displayed continuous perseveration even though the stimulation had ended. The left UF connects to the inferior frontal lobe, which is necessary for word production, so that the naming difficulty appears to be the result of disrupted word production caused by electrical stimulation of the dominant UF. The verbal paraphasia appears to be due to the failure to select the correct word from semantic memory and the failure to suppress the incorrect word. The left UF is associated with working memory, which plays an important role in recurrent perseveration. The continuous perseveration appears to be due to disturbances in word production and a failure to inhibit an appropriate response. These findings in this case suggest that the dominant UF has multiple roles in the naming of objects. PMID:23242348

  1. Classification of a frameshift/extended and a stop mutation in WT1 as gain-of-function mutations that activate cell cycle genes and promote Wilms tumour cell proliferation.

    PubMed

    Busch, Maike; Schwindt, Heinrich; Brandt, Artur; Beier, Manfred; Görldt, Nicole; Romaniuk, Paul; Toska, Eneda; Roberts, Stefan; Royer, Hans-Dieter; Royer-Pokora, Brigitte

    2014-08-01

    The WT1 gene encodes a zinc finger transcription factor important for normal kidney development. WT1 is a suppressor for Wilms tumour development and an oncogene for diverse malignant tumours. We recently established cell lines from primary Wilms tumours with different WT1 mutations. To investigate the function of mutant WT1 proteins, we performed WT1 knockdown experiments in cell lines with a frameshift/extension (p.V432fsX87 = Wilms3) and a stop mutation (p.P362X = Wilms2) of WT1, followed by genome-wide gene expression analysis. We also expressed wild-type and mutant WT1 proteins in human mesenchymal stem cells and established gene expression profiles. A detailed analysis of gene expression data enabled us to classify the WT1 mutations as gain-of-function mutations. The mutant WT1(Wilms2) and WT1(Wilms3) proteins acquired an ability to modulate the expression of a highly significant number of genes from the G2/M phase of the cell cycle, and WT1 knockdown experiments showed that they are required for Wilms tumour cell proliferation. p53 negatively regulates the activity of a large number of these genes that are also part of a core proliferation cluster in diverse human cancers. Our data strongly suggest that mutant WT1 proteins facilitate expression of these cell cycle genes by antagonizing transcriptional repression mediated by p53. We show that mutant WT1 can physically interact with p53. Together the findings show for the first time that mutant WT1 proteins have a gain-of-function and act as oncogenes for Wilms tumour development by regulating Wilms tumour cell proliferation.

  2. Investigation of the trade-off between time window length, classifier update rate and classification accuracy for restorative brain-computer interfaces.

    PubMed

    Darvishi, Sam; Ridding, Michael C; Abbott, Derek; Baumert, Mathias

    2013-01-01

    Recently, the application of restorative brain-computer interfaces (BCIs) has received significant interest in many BCI labs. However, there are a number of challenges, that need to be tackled to achieve efficient performance of such systems. For instance, any restorative BCI needs an optimum trade-off between time window length, classification accuracy and classifier update rate. In this study, we have investigated possible solutions to these problems by using a dataset provided by the University of Graz, Austria. We have used a continuous wavelet transform and the Student t-test for feature extraction and a support vector machine (SVM) for classification. We find that improved results, for restorative BCIs for rehabilitation, may be achieved by using a 750 milliseconds time window with an average classification accuracy of 67% that updates every 32 milliseconds.

  3. Phyllodes tumours of the breast: a consensus review

    PubMed Central

    Tan, Benjamin Y; Acs, Geza; Apple, Sophia K; Badve, Sunil; Bleiweiss, Ira J; Brogi, Edi; Calvo, José P; Dabbs, David J; Ellis, Ian O; Eusebi, Vincenzo; Farshid, Gelareh; Fox, Stephen B; Ichihara, Shu; Lakhani, Sunil R; Rakha, Emad A; Reis-Filho, Jorge S; Richardson, Andrea L; Sahin, Aysegul; Schmitt, Fernando C; Schnitt, Stuart J; Siziopikou, Kalliopi P; Soares, Fernando A; Tse, Gary M; Vincent-Salomon, Anne; Tan, Puay Hoon

    2016-01-01

    Phyllodes tumours constitute an uncommon but complex group of mammary fibroepithelial lesions. Accurate and reproducible grading of these tumours has long been challenging, owing to the need to assess multiple stratified histological parameters, which may be weighted differently by individual pathologists. Distinction of benign phyllodes tumours from cellular fibroadenomas is fraught with difficulty, due to overlapping microscopic features. Similarly, separation of the malignant phyllodes tumour from spindle cell metaplastic carcinoma and primary breast sarcoma can be problematic. Phyllodes tumours are treated by surgical excision. However, there is no consensus on the definition of an appropriate surgical margin to ensure completeness of excision and reduction of recurrence risk. Interpretive subjectivity, overlapping histological diagnostic criteria, suboptimal correlation between histological classification and clinical behaviour and the lack of robust molecular predictors of outcome make further investigation of the pathogenesis of these fascinating tumours a matter of active research. This review consolidates the current understanding of their pathobiology and clinical behaviour, and includes proposals for a rational approach to the classification and management of phyllodes tumours. PMID:26768026

  4. Gender, Race, and Survival: A Study in Non-Small-Cell Lung Cancer Brain Metastases Patients Utilizing the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification

    SciTech Connect

    Videtic, Gregory M.M.; Reddy, Chandana A.; Chao, Samuel T.; Rice, Thomas W.; Adelstein, David J.; Barnett, Gene H.; Mekhail, Tarek M.; Vogelbaum, Michael A.; Suh, John H.

    2009-11-15

    Purpose: To explore whether gender and race influence survival in non-small-cell lung cancer (NSCLC) in patients with brain metastases, using our large single-institution brain tumor database and the Radiation Therapy Oncology Group recursive partitioning analysis (RPA) brain metastases classification. Methods and materials: A retrospective review of a single-institution brain metastasis database for the interval January 1982 to September 2004 yielded 835 NSCLC patients with brain metastases for analysis. Patient subsets based on combinations of gender, race, and RPA class were then analyzed for survival differences. Results: Median follow-up was 5.4 months (range, 0-122.9 months). There were 485 male patients (M) (58.4%) and 346 female patients (F) (41.6%). Of the 828 evaluable patients (99%), 143 (17%) were black/African American (B) and 685 (83%) were white/Caucasian (W). Median survival time (MST) from time of brain metastasis diagnosis for all patients was 5.8 months. Median survival time by gender (F vs. M) and race (W vs. B) was 6.3 months vs. 5.5 months (p = 0.013) and 6.0 months vs. 5.2 months (p = 0.08), respectively. For patients stratified by RPA class, gender, and race, MST significantly favored BFs over BMs in Class II: 11.2 months vs. 4.6 months (p = 0.021). On multivariable analysis, significant variables were gender (p = 0.041, relative risk [RR] 0.83) and RPA class (p < 0.0001, RR 0.28 for I vs. III; p < 0.0001, RR 0.51 for II vs. III) but not race. Conclusions: Gender significantly influences NSCLC brain metastasis survival. Race trended to significance in overall survival but was not significant on multivariable analysis. Multivariable analysis identified gender and RPA classification as significant variables with respect to survival.

  5. Factors affecting platinum concentrations in human surgical tumour specimens after cisplatin.

    PubMed Central

    Stewart, D. J.; Molepo, J. M.; Green, R. M.; Montpetit, V. A.; Hugenholtz, H.; Lamothe, A.; Mikhael, N. Z.; Redmond, M. D.; Gadia, M.; Goel, R.

    1995-01-01

    We assessed factors which affect cisplatin concentrations in human surgical tumour specimens. Cisplatin 10 mg m-2 was given i.v. to 45 consenting patients undergoing surgical resection of neoplasms, and platinum was assayed in resected tumour and in deproteinated plasma by flameless atomic absorption spectrophotometry. By multiple stepwise regression analysis of normalised data, patient characteristics that emerged as being most closely associated (P < 0.05) with tumour platinum concentrations (after correcting for associations with other variables) were tumour 'source' [primary brain lymphomas, medulloblastomas and meningiomas ('type LMM') > 'others' > lung cancer > head/neck cancer > gliomas) or tumour 'type' (LMM > brain metastases > extracerebral tumours > gliomas), serum calcium and chloride (positive correlations) and bilirubin (negative). Tumour location (intracranial vs extracranial) did not correlate with platinum concentrations. If values for a single outlier were omitted, high-grade gliomas had significantly higher platinum concentrations (P < 0.003) than low-grade gliomas. For intracranial tumours, the computerised tomographic scan feature that correlated most closely with platinum concentrations in multivariate analysis was the darkness of peritumoral oedema. Tumour source or type is a much more important correlate of human tumour cisplatin concentrations than is intracranial vs extracranial location. Serum calcium, chloride and bilirubin levels may affect tumour cisplatin uptake or retention. CT scan characteristics may help predict cisplatin concentrations in intracranial tumours. PMID:7880744

  6. Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

    PubMed

    Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

    2016-10-01

    Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

  7. Neonatal exposure to estradiol-17β modulates tumour necrosis factor alpha and cyclooxygenase-2 expression in brain and also in ovaries of adult female rats.

    PubMed

    Shridharan, Radhika Nagamangalam; Krishnagiri, Harshini; Govindaraj, Vijayakumar; Sarangi, SitiKantha; Rao, Addicam Jagannadha

    2016-02-01

    The sexually dimorphic organization in perinatal rat brain is influenced by steroid hormones. Exposure to high levels of estrogen or endocrine-disrupting compounds during perinatal period may perturb this process, resulting in compromised reproductive physiology and behavior as observed in adult In our recent observation neonatal exposure of the female rats to estradiol-17β resulted in down-regulation of TNF-α, up-regulation of COX-2 and increase in SDN-POA size in pre-optic area in the adulthood. It is known that the control of reproductive performance in female involves a complex interplay of the hypothalamus, pituitary, and ovary. The present study was undertaken to understand the possible molecular mechanism involved in changes observed in the ovarian morphology and expression of selected genes in the ovary. Administration of estradiol-17β (100 μg) on day 2 and 3 after birth revealed up-regulation of ER-α, ER-β, COX-2 and down-regulation of TNF-α expression. Also the decrease in the ovarian weight, altered ovarian morphology and changes in the 2D protein profiles were also seen. This is apparently the first report documenting that neonatal estradiol exposure modulates TNF-α and COX-2 expression in the ovary as seen during adult stage. Our results permit us to suggest that cues originating from the modified brain structure due to neonatal exposure of estradiol-17β remodel the ovary at the molecular level in such a way that there is a disharmony in the reproductive function during adulthood and these changes are perennial and can lead to infertility and changes of reproductive behavior.

  8. The determinants of tumour immunogenicity

    PubMed Central

    Blankenstein, Thomas; Coulie, Pierre G.; Gilboa, Eli; Jaffee, Elizabeth M.

    2013-01-01

    Many standard and targeted therapies, as well as radiotherapy, have been shown to induce an anti-tumour immune response, and immunotherapies rely on modulating the host immune system to induce an anti-tumour immune response. However, the immune response to such therapies is often reliant on the immunogenicity of a tumour. Tumour immunogenicity varies greatly between cancers of the same type in different individuals and between different types of cancer. So, what do we know about tumour immunogenicity and how might we therapeutically improve tumour immunogenicity? We asked four leading cancer immunologists around the world for their opinions on this important issue. PMID:22378190

  9. Coexistent dysembryoplastic neuroepithelial tumour and pilocytic astrocytoma

    PubMed Central

    Nasit, Jitendra G.; Shah, Payal; Zalawadia, Himanshu

    2016-01-01

    Dysembryoplastic neuroepithelial tumour (DNET) is an uncommon mixed glioneuronal tumour. DNET is classified as Grade I neoplasm in revised World Health Organization classification of tumors of the nervous system. DNET is commonly seen in the temporal lobe of children and young adults with features of pharmacoresistant complex partial seizures. Tumors arising in association with DNETs are rare. Only two cases of pilocytic astrocytoma (PA) arising in DNETs are reported. Surgical excision is the only successful management with favourable prognosis. The development of recurrence and malignancy after subtotal or even after complete excision challenges the premise of stability and highlights the importance of close clinical follow up. Here, a case of DNET with area of PA is described which helps in understanding the pathogenesis and biological behavior of DNET. PMID:27695565

  10. A Study on the Effect of Electrical Stimulation as a User Stimuli for Motor Imagery Classification in Brain-Machine Interface

    PubMed Central

    Bhattacharyya, Saugat; Clerc, Maureen; Hayashibe, Mitsuhiro

    2016-01-01

    Functional Electrical Stimulation (FES) provides a neuroprosthetic interface to non-recovered muscle groups by stimulating the affected region of the human body. FES in combination with Brain-machine interfacing (BMI) has a wide scope in rehabilitation because this system directly links the cerebral motor intention of the users with its corresponding peripheral muscle activations. In this paper, we examine the effect of FES on the electroencephalography (EEG) during motor imagery (left- and right-hand movement) training of the users. Results suggest a significant improvement in the classification accuracy when the subject was induced with FES stimuli as compared to the standard visual one. PMID:27478573

  11. A Study on the Effect of Electrical Stimulation as a User Stimuli for Motor Imagery Classification in Brain-Machine Interface.

    PubMed

    Bhattacharyya, Saugat; Clerc, Maureen; Hayashibe, Mitsuhiro

    2016-06-13

    Functional Electrical Stimulation (FES) provides a neuroprosthetic interface to non-recovered muscle groups by stimulating the affected region of the human body. FES in combination with Brain-machine interfacing (BMI) has a wide scope in rehabilitation because this system directly links the cerebral motor intention of the users with its corresponding peripheral muscle activations. In this paper, we examine the effect of FES on the electroencephalography (EEG) during motor imagery (left- and right-hand movement) training of the users. Results suggest a significant improvement in the classification accuracy when the subject was induced with FES stimuli as compared to the standard visual one.

  12. Tumour Cell Heterogeneity

    PubMed Central

    Gay, Laura; Baker, Ann-Marie; Graham, Trevor A.

    2016-01-01

    The population of cells that make up a cancer are manifestly heterogeneous at the genetic, epigenetic, and phenotypic levels. In this mini-review, we summarise the extent of intra-tumour heterogeneity (ITH) across human malignancies, review the mechanisms that are responsible for generating and maintaining ITH, and discuss the ramifications and opportunities that ITH presents for cancer prognostication and treatment. PMID:26973786

  13. Investigating the use of support vector machine classification on structural brain images of preterm-born teenagers as a biological marker.

    PubMed

    Chu, Carlton; Lagercrantz, Hugo; Forssberg, Hans; Nagy, Zoltan

    2015-01-01

    Preterm birth has been shown to induce an altered developmental trajectory of brain structure and function. With the aid support vector machine (SVM) classification methods we aimed to investigate whether MRI data, collected in adolescence, could be used to predict whether an individual had been born preterm or at term. To this end we collected T1-weighted anatomical MRI data from 143 individuals (69 controls, mean age 14.6y). The inclusion criteria for those born preterm were birth weight ≤ 1500g and gestational age < 37w. A linear SVM was trained on the grey matter segment of MR images in two different ways. First, all the individuals were used for training and classification was performed by the leave-one-out method, yielding 93% correct classification (sensitivity = 0.905, specificity = 0.942). Separately, a random half of the available data were used for training twice and each time the other, unseen, half of the data was classified, resulting 86% and 91% accurate classifications. Both gestational age (R = -0.24, p<0.04) and birth weight (R = -0.51, p < 0.001) correlated with the distance to decision boundary within the group of individuals born preterm. Statistically significant correlations were also found between IQ (R = -0.30, p < 0.001) and the distance to decision boundary. Those born small for gestational age did not form a separate subgroup in these analyses. The high rate of correct classification by the SVM motivates further investigation. The long-term goal is to automatically and non-invasively predict the outcome of preterm-born individuals on an individual basis using as early a scan as possible.

  14. Vascular endothelial growth factor is a potential tumour angiogenesis factor in human gliomas in vivo

    NASA Astrophysics Data System (ADS)

    Plate, Karl H.; Breier, Georg; Weich, Herbert A.; Risau, Werner

    1992-10-01

    CLINICAL and experimental studies suggest that angiogenesis is a prerequisite for solid tumour growth1,2. Several growth factors with mitogenic or chemotactic activity for endothelial cells in vitro have been described, but it is not known whether these mediate tumour vascularization in vivo3,4. Glioblastoma, the most common and most malignant brain tumour in humans, is distinguished from astrocytoma by the presence of necroses and vascular prolifer-ations5'6. Here we show that expression of an endothelial cell-specific mitogen, vascular endothelial growth factor (VEGF), is induced in astrocytoma cells but is dramatically upregulated in two apparently different subsets of glioblastoma cells. The high-affinity tyrosine kinase receptor for VEGF, flt, although not expressed in normal brain endothelium, is upregulated in tumour endothelial cells in vivo. These observations strongly support the concept that tumour angiogenesis is regulated by paracrine mechanisms and identify VEGF as a potential tumour angiogenesis factor in vivo.

  15. Texture analysis of T1- and T2-weighted MR images and use of probabilistic neural network to discriminate posterior fossa tumours in children

    PubMed Central

    Orphanidou-Vlachou, Eleni; Vlachos, Nikolaos; Davies, Nigel P; Arvanitis, Theodoros N; Grundy, Richard G; Peet, Andrew C

    2014-01-01

    Brain tumours are the most common solid tumours in children, representing 20% of all cancers. The most frequent posterior fossa tumours are medulloblastomas, pilocytic astrocytomas and ependymomas. Texture analysis (TA) of MR images can be used to support the diagnosis of these tumours by providing additional quantitative information. MaZda software was used to perform TA on T1- and T2-weighted images of children with pilocytic astrocytomas, medulloblastomas and ependymomas of the posterior fossa, who had MRI at Birmingham Children's Hospital prior to treatment. The region of interest was selected on three slices per patient in Image J, using thresholding and manual outlining. TA produced 279 features, which were reduced using principal component analysis (PCA). The principal components (PCs) explaining 95% of the variance were used in a linear discriminant analysis (LDA) and a probabilistic neural network (PNN) to classify the cases, using DTREG statistics software. PCA of texture features from both T1- and T2-weighted images yielded 13 PCs to explain >95% of the variance. The PNN classifier for T1-weighted images achieved 100% accuracy on training the data and 90% on leave-one-out cross-validation (LOOCV); for T2-weighted images, the accuracy was 100% on training the data and 93.3% on LOOCV. A PNN classifier with T1 and T2 PCs achieved 100% accuracy on training the data and 85.8% on LOOCV. LDA classification accuracies were noticeably poorer. The features found to hold the highest discriminating potential were all co-occurrence matrix derived, where adjacent pixels had highly correlated intensities. This study shows that TA can be performed on standard T1- and T2-weighted images of childhood posterior fossa tumours using readily available software to provide high diagnostic accuracy. Discriminatory features do not correspond to those used in the clinical interpretation of the images and therefore provide novel tumour information. Copyright © 2014 John Wiley

  16. A Method for Automated Classification of Parkinson’s Disease Diagnosis Using an Ensemble Average Propagator Template Brain Map Estimated from Diffusion MRI

    PubMed Central

    Banerjee, Monami; Okun, Michael S.; Vaillancourt, David E.; Vemuri, Baba C.

    2016-01-01

    Parkinson’s disease (PD) is a common and debilitating neurodegenerative disorder that affects patients in all countries and of all nationalities. Magnetic resonance imaging (MRI) is currently one of the most widely used diagnostic imaging techniques utilized for detection of neurologic diseases. Changes in structural biomarkers will likely play an important future role in assessing progression of many neurological diseases inclusive of PD. In this paper, we derived structural biomarkers from diffusion MRI (dMRI), a structural modality that allows for non-invasive inference of neuronal fiber connectivity patterns. The structural biomarker we use is the ensemble average propagator (EAP), a probability density function fully characterizing the diffusion locally at a voxel level. To assess changes with respect to a normal anatomy, we construct an unbiased template brain map from the EAP fields of a control population. Use of an EAP captures both orientation and shape information of the diffusion process at each voxel in the dMRI data, and this feature can be a powerful representation to achieve enhanced PD brain mapping. This template brain map construction method is applicable to small animal models as well as to human brains. The differences between the control template brain map and novel patient data can then be assessed via a nonrigid warping algorithm that transforms the novel data into correspondence with the template brain map, thereby capturing the amount of elastic deformation needed to achieve this correspondence. We present the use of a manifold-valued feature called the Cauchy deformation tensor (CDT), which facilitates morphometric analysis and automated classification of a PD versus a control population. Finally, we present preliminary results of automated discrimination between a group of 22 controls and 46 PD patients using CDT. This method may be possibly applied to larger population sizes and other parkinsonian syndromes in the near future. PMID

  17. Tumour exosome integrins determine organotropic metastasis.

    PubMed

    Hoshino, Ayuko; Costa-Silva, Bruno; Shen, Tang-Long; Rodrigues, Goncalo; Hashimoto, Ayako; Tesic Mark, Milica; Molina, Henrik; Kohsaka, Shinji; Di Giannatale, Angela; Ceder, Sophia; Singh, Swarnima; Williams, Caitlin; Soplop, Nadine; Uryu, Kunihiro; Pharmer, Lindsay; King, Tari; Bojmar, Linda; Davies, Alexander E; Ararso, Yonathan; Zhang, Tuo; Zhang, Haiying; Hernandez, Jonathan; Weiss, Joshua M; Dumont-Cole, Vanessa D; Kramer, Kimberly; Wexler, Leonard H; Narendran, Aru; Schwartz, Gary K; Healey, John H; Sandstrom, Per; Labori, Knut Jørgen; Kure, Elin H; Grandgenett, Paul M; Hollingsworth, Michael A; de Sousa, Maria; Kaur, Sukhwinder; Jain, Maneesh; Mallya, Kavita; Batra, Surinder K; Jarnagin, William R; Brady, Mary S; Fodstad, Oystein; Muller, Volkmar; Pantel, Klaus; Minn, Andy J; Bissell, Mina J; Garcia, Benjamin A; Kang, Yibin; Rajasekhar, Vinagolu K; Ghajar, Cyrus M; Matei, Irina; Peinado, Hector; Bromberg, Jacqueline; Lyden, David

    2015-11-19

    Ever since Stephen Paget's 1889 hypothesis, metastatic organotropism has remained one of cancer's greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.

  18. Tumour exosome integrins determine organotropic metastasis

    PubMed Central

    Hoshino, Ayuko; Costa-Silva, Bruno; Shen, Tang-Long; Rodrigues, Goncalo; Hashimoto, Ayako; Mark, Milica Tesic; Molina, Henrik; Kohsaka, Shinji; Di Giannatale, Angela; Ceder, Sophia; Singh, Swarnima; Williams, Caitlin; Soplop, Nadine; Uryu, Kunihiro; Pharmer, Lindsay; King, Tari; Bojmar, Linda; Davies, Alexander E.; Ararso, Yonathan; Zhang, Tuo; Zhang, Haiying; Hernandez, Jonathan; Weiss, Joshua M.; Dumont-Cole, Vanessa D.; Kramer, Kimberly; Wexler, Leonard H.; Narendran, Aru; Schwartz, Gary K.; Healey, John H.; Sandstrom, Per; Labori, Knut Jørgen; Kure, Elin H.; Grandgenett, Paul M.; Hollingsworth, Michael A.; de Sousa, Maria; Kaur, Sukhwinder; Jain, Maneesh; Mallya, Kavita; Batra, Surinder K.; Jarnagin, William R.; Brady, Mary S.; Fodstad, Oystein; Muller, Volkmar; Pantel, Klaus; Minn, Andy J.; Bissell, Mina J.; Garcia, Benjamin A.; Kang, Yibin; Rajasekhar, Vinagolu K.; Ghajar, Cyrus M.; Matei, Irina; Peinado, Hector; Bromberg, Jacqueline; Lyden, David

    2015-01-01

    Ever since Stephen Paget’s 1889 hypothesis, metastatic organotropism has remained one of cancer’s greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis. PMID:26524530

  19. P17.35GEINO-10: A PROSPECTIVE OBSERVATIONAL MULTICENTER STUDY OF THE CHARACTERISTICS OF PATIENTS WITH INTRA-AXIAL BRAIN TUMOURS AND THEIR THERAPEUTIC MANAGEMENT IN SPANISH HOSPITALS

    PubMed Central

    Gil-Gil, M.J.; Sepúlveda, J.M.; Vieitez, J.M.; Peñas, R. de las; Fernández-Pérez, I.; Pérez-Segura, P.; Fuster, P.; Martinez-García, M.; Quintanar, T.; del Barco, S.

    2014-01-01

    INTRODUCTION: Primitive brain tumours (BT) represent 2% of adult malignancies. BT patients are treated by different clinical specialists in Spanish hospitals. This means that we did not know with certainty how these patients are treated in Spain. To improve this knowledge the Neuro-Oncology Investigation Spanish Group (GEINO) designed this prospective observational multicenter study. OBJECTIVE: Describe the clinical and pathological characteristics and therapeutic management of intra-axial BT patients diagnosed after January 2010 in Spain. PATIENTS AND METHODS: Patients >18 years old, diagnosed after January 2010 of a intra-axial BT, treated or not, and gave written informed consent. RESULTS: 397 patients from 22 hospitals were enrolled between 08/01/2012 and 12/03/2013. The median age was 56.9 (18-83) years. 58% were male and 42% female. 87% had ECOG ≤2. 48.5% had comorbidity. 9% had previous history of cancer (2% BT). Symptoms at diagnoses: seizures 30%, epilepsy 25%, cognitive impairment 23.5%, ataxia 7.5%. BT was located in frontal lobe in 33.5%, temporal 29%, parietal 13%, posterior fosse or brainstem 5%. By histology Glioblastoma (GBM) were 67%, anaplastic astrocytoma (AA) 12%, oligodendroglioma or oligoastrocytoma grade 2-3 were 11%, low-grade astrocytoma 6%, medulloblastoma 2% and ependymoma 1%. Of the 313 patients with GBM or AA 98% underwent surgery (SR): 40% complete resection, 41% partial, 11% stereotactic biopsy and 7% open biopsy. 8% of patients received neoadjuvant temozolomide (TMZ) + /- bevacizumab (BV) into a clinical trial. 94% of patients received radiotherapy (RT): 72% focal, 21% whole-brain and 6% hemi-brain. 83% of patients received adjuvant chemotherapy (QT): 99% TMZ with a median of 5 cycles (1-18) and 1% PCV (all were AA). Median Progression Free survival was 10.4 months (95%CI: 9-11.8) for GBM and 31.1 months (95%CI: 12.2-49.9) for AA. 130/167 (78%) of GBM or AA patients received treatment at 1st relapse: 14% SR, 8% RT and 96% QT (CPT11

  20. HELICoiD project: a new use of hyperspectral imaging for brain cancer detection in real-time during neurosurgical operations

    NASA Astrophysics Data System (ADS)

    Fabelo, Himar; Ortega, Samuel; Kabwama, Silvester; Callico, Gustavo M.; Bulters, Diederik; Szolna, Adam; Pineiro, Juan F.; Sarmiento, Roberto

    2016-05-01

    Hyperspectral images allow obtaining large amounts of information about the surface of the scene that is captured by the sensor. Using this information and a set of complex classification algorithms is possible to determine which material or substance is located in each pixel. The HELICoiD (HypErspectraL Imaging Cancer Detection) project is a European FET project that has the goal to develop a demonstrator capable to discriminate, with high precision, between normal and tumour tissues, operating in real-time, during neurosurgical operations. This demonstrator could help the neurosurgeons in the process of brain tumour resection, avoiding the excessive extraction of normal tissue and unintentionally leaving small remnants of tumour. Such precise delimitation of the tumour boundaries will improve the results of the surgery. The HELICoiD demonstrator is composed of two hyperspectral cameras obtained from Headwall. The first one in the spectral range from 400 to 1000 nm (visible and near infrared) and the second one in the spectral range from 900 to 1700 nm (near infrared). The demonstrator also includes an illumination system that covers the spectral range from 400 nm to 2200 nm. A data processing unit is in charge of managing all the parts of the demonstrator, and a high performance platform aims to accelerate the hyperspectral image classification process. Each one of these elements is installed in a customized structure specially designed for surgical environments. Preliminary results of the classification algorithms offer high accuracy (over 95%) in the discrimination between normal and tumour tissues.

  1. Radiotherapy in Phyllodes Tumour

    PubMed Central

    Sasidharan, Balukrishna; Manipadam, Marie Therese; Paul, M J; Backianathan, Selvamani

    2017-01-01

    Introduction Phyllodes Tumour (PT) of the breast is a relatively rare breast neoplasm (<1%) with diverse range of pathology and biological behaviour. Aim To describe the clinical course of PT and to define the role of Radiotherapy (RT) in PT of the breast. Materials and Methods Retrospective analysis of hospital data of patients with PT presented from 2005 to 2014 was done. Descriptive statistics was used to analyze the results. Simple description of data was done in this study. Age and duration of symptoms were expressed in median and range. Percentages, tables and general discussions were used to understand the meaning of the data analyzed. Results Out of the 98 patients, 92 were eligible for analysis. The median age of presentation was 43 years. A total of 64/92 patients were premenopausal. There was no side predilection for this tumour but 57/92 patients presented as an upper outer quadrant lump. Fifty percent of the patients presented as giant (10 cm) PT. The median duration of symptoms was 12 months (range: 1-168 months). A 60% of patients had Benign (B), 23% had Borderline (BL) and 17% had malignant (M) tumours. The surgical treatment for benign histology included Lumpectomy (L) for 15%, Wide Local Excision (WLE) for 48%, and Simple Mastectomy (SM) for 37%. All BL and M tumours were treated with WLE or SM. There was no recurrence in B and BL group when the margin was ≥1 cm. All non-metastatic M tumours received adjuvant RT irrespective of their margin status. Total 3/16 patients with M developed local recurrence. Total 6/16 M patients had distant metastases (lung or bone). Our median duration of follow up was 20 months (range: 1-120 months). Conclusion Surgical resection with adequate margins (>1 cm) gave excellent local control in B and BL tumours. For patients with BL PT, local radiotherapy is useful, if margins are close or positive even after the best surgical resection. There is a trend towards improved local control with adjuvant radiotherapy for

  2. Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.

    PubMed

    Siuly; Li, Yan; Paul Wen, Peng

    2014-03-01

    Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested.

  3. Diagnosing Musculoskeletal Tumours

    PubMed Central

    Carter, Simon R.; Spooner, David; Sneath, Rodney S.

    2001-01-01

    In 1993 we became aware of a worrying increase in apparent errors in the histopathological diagnosis of musculoskeletal tumours in our Unit. As a result all cases seen over the past 8 years were reviewed by an independent panel. Of the 1996 cases reviewed there was an error in 87. In 54 cases (2.7%) this had led to some significant change in the active management of the patient. The main areas where errors arose were in those very cases where clinical and radiological features were not helpful in confirming or refuting the diagnosis. The incidence of errors rose with the passage of time, possibly related to a deterioration in the pathologist’s health. The error rate in diagnosing bone tumours in previously published series ranges from 9 to 40%. To ensure as accurate a rate of diagnosis as possible multidisciplinary working and regular audit are essential. PMID:18521309

  4. [Adrenal tumours in childhood].

    PubMed

    Martos-Moreno, G A; Pozo-Román, J; Argente, J

    2013-09-01

    This special article aims to summarise the current knowledge regarding the two groups of tumours with their origin in the adrenal gland: 1) adrenocortical tumours, derived from the cortex of the adrenal gland and 2) phaeochromocytomas and paragangliomas, neuroendocrine tumours derived from nodes of neural crest derived cells symmetrically distributed at both sides of the entire spine (paragangliomas [PG]). These PGs can be functioning tumors that secrete catecholamines, which confers their typical dark colour after staining with chromium salts (chromaffin tumors). Among these, the term phaeochromocytoma (PC) is restricted to those PGs derived from the chromaffin cells in the adrenal medulla (intra-adrenal PGs), whereas the term PG is used for those sympathetic or parasympathetic ones in an extra-adrenal location. We analyse the state of the art of their pathogenic and genetic bases, as well as their clinical signs and symptoms, the tests currently available for performing their diagnosis (biochemical, hormonal, imaging and molecular studies) and management (surgery, pre- and post-surgical medical treatment), considering the current and developing strategies in chemo- and radiotherapy.

  5. Tumours of the kidney

    PubMed Central

    Nielsen, Svend W.; Mackey, L. J.; Misdorp, W.

    1976-01-01

    The most frequent renal tumours of animals are renal cell carcinoma and nephroblastoma. Renal cell carcinomas are seen mainly in dogs and cattle and nephroblastoma is encountered in pigs, puppies, and calves. Renal cell carcinomas are usually papillary in the dog. They show a marked propensity for vascular invasion, penetration of the posterior vena cava, and subsequent pulmonary metastasis. Nephroblastoma, which is morphologically identical to Wilms' tumour of children, is almost always a benign tumour in animals. It is one of the most frequent neoplasms of pigs, possibly owing to the fact that most pigs are slaughtered (and examined) when a few months old. Lymphosarcoma involving the kidney is particularly frequent in the cat, but is also seen in other species as part of a generalized disease. ImagesFig. 5,6Fig. 7Fig. 8Fig. 1,2Fig. 3,4Fig. 16,17,18,19Fig. 9,10Fig. 11Fig. 12Fig. 13Fig. 14,15 PMID:1086154

  6. [New WHO-classification of lung and pleural tumors].

    PubMed

    Wagenaar, S S

    1999-05-08

    A new classification of the World Health Organization (WHO) of lung and pleural tumours will be published presently. Compared with the previous edition of 1981 the changed parts more accurately reflect the available therapeutic choices and the prognostic characteristics of the different tumour types. The classification is based on conventional light-microscopical typing. Additional techniques (from histochemistry, immune histochemistry, electron microscopy and molecular biology) have not yet decisive influence on tumour typing. The dichotomy between small-cell and large-cell carcinomas is too simplistic, as the group of large-cell carcinomas is heterogeneous, and further differentiation leads to identification of tumour types with distinct therapeutic options and prognostic characteristics. There are new criteria for the classification of neuroendocrine tumours, such as the mitotic index. It is recommended to use the newly revised classification for diagnostic purposes, epidemiology and biologic studies.

  7. Gating and tracking, 4D in thoracic tumours.

    PubMed

    Verellen, D; Depuydt, T; Gevaert, T; Linthout, N; Tournel, K; Duchateau, M; Reynders, T; Storme, G; De Ridder, M

    2010-10-01

    The limited ability to control for a tumour's location compromises the accuracy with which radiation can be delivered to tumour-bearing tissue. The resultant requirement for larger treatment volumes to accommodate target uncertainty restricts the radiation dose because more surrounding normal tissue is exposed. With image-guided radiation therapy (IGRT), these volumes can be optimized and tumouricidal doses may be delivered, achieving maximum tumour control with minimal complications. Moreover, with the ability of high precision dose delivery and real-time knowledge of the target volume location, IGRT has initiated the exploration of new indications in radiotherapy such as hypofractionated radiotherapy (or stereotactic body radiotherapy), deliberate inhomogeneous dose distributions coping with tumour heterogeneity (dose painting by numbers and biologically conformal radiation therapy), and adaptive radiotherapy. In short: "individualized radiotherapy". Tumour motion management, especially for thoracic tumours, is a particular problem in this context both for the delineation of tumours and organs at risk as well as during the actual treatment delivery. The latter will be covered in this paper with some examples based on the experience of the UZ Brussel. With the introduction of the NOVALIS system (BrainLAB, Feldkirchen, Germany) in 2000 and consecutive prototypes of the ExacTrac IGRT system, gradually a hypofractionation treatment protocol was introduced for the treatment of lung tumours and liver metastases evolving from motion-encompassing techniques towards respiratory-gated radiation therapy with audio-visual feedback and most recently dynamic tracking using the VERO system (BrainLAB, Feldkirchen, Germany). This evolution will be used to illustrate the recent developments in this particular field of research.

  8. Genomic aberrations in spitzoid tumours and their implications for diagnosis, prognosis and therapy

    PubMed Central

    Wiesner, Thomas; Kutzner, Heinz; Cerroni, Lorenzo; Mihm, Martin J.; Busam, Klaus J.; Murali, Rajmohan

    2016-01-01

    Summary Histopathological evaluation of melanocytic tumours usually allows reliable distinction of benign melanocytic naevi from melanoma. More difficult is the histopathological classification of Spitz tumours, a heterogeneous group of tumours composed of large epithelioid or spindle-shaped melanocytes. Spitz tumours are biologically distinct from conventional melanocytic naevi and melanoma, as exemplified by their distinct patterns of genetic aberrations. Whereas conventional naevi and melanoma often harbour BRAF mutations, NRAS mutations, or inactivation of NF1, Spitz tumours show HRAS mutations, inactivation of BAP1 (often combined with BRAF mutations), or genomic rearrangements involving the kinases ALK, ROS1, NTRK1, BRAF, RET, and MET. In Spitz naevi, which lack significant histological atypia, all of these mitogenic driver aberrations trigger rapid cell proliferation, but after an initial growth phase, various tumour suppressive mechanisms stably block further growth. In some tumours, additional genomic aberrations may abrogate various tumour suppressive mechanisms, such as cell-cycle arrest, telomere shortening, or DNA damage response. The melanocytes then start to grow in a less organised fashion, may spread to regional lymph nodes, and are termed atypical Spitz tumours. Upon acquisition of even more aberrations, which often activate additional oncogenic pathways or reduce and alter cell differentiation, the neoplastic cells become entirely malignant and may colonise and take over distant organs (spitzoid melanoma). The sequential acquisition of genomic aberrations suggests that Spitz tumours represent a continuous biological spectrum, rather than a dichotomy of benign versus malignant, and that tumours with ambiguous histological features (atypical Spitz tumours) might be best classified as low-grade melanocytic tumours. The number of genetic aberrations usually correlates with the degree of histological atypia and explains why existing ancillary genetic

  9. Gene expression profiling of gliomas: merging genomic and histopathological classification for personalised therapy.

    PubMed

    Vitucci, M; Hayes, D N; Miller, C R

    2011-02-15

    The development of DNA microarray technologies over the past decade has revolutionised translational cancer research. These technologies were originally hailed as more objective, comprehensive replacements for traditional histopathological cancer classification systems, based on microscopic morphology. Although DNA microarray-based gene expression profiling (GEP) remains unlikely in the near term to completely replace morphological classification of primary brain tumours, specifically the diffuse gliomas, GEP has confirmed that significant molecular heterogeneity exists within the various morphologically defined gliomas, particularly glioblastoma (GBM). Herein, we provide a 10-year progress report on human glioma GEP, with focus on development of clinical diagnostic tests to identify molecular subtypes, uniquely responsive to adjuvant therapies. Such progress may lead to a more precise classification system that accurately reflects the cellular, genetic, and molecular basis of gliomagenesis, a prerequisite for identifying subsets uniquely responsive to specific adjuvant therapies, and ultimately in achieving individualised clinical care of glioma patients.

  10. [Phyllodes tumour: a rare, rapidly growing breast tumour].

    PubMed

    den Exter, Paul L; Hornstra, Bonne J; Vree, Robbert

    2009-01-01

    A 40-year-old woman presented at the breast outpatient clinic with a giant tumour of her left breast. The size, rapid growth and radiological characteristics of the lesion led us to suspect a phyllodes tumour. A histological examination of a needle biopsy confirmed this diagnosis. An additional CT scan revealed no signs of metastases. We performed a mastectomy during which a tumour measuring 48 x 33 x 25 cm was resected. Histological examination revealed a borderline phyllodes tumour. Phyllodes tumours are rare fibroepithelial neoplasms of the breast and pre-operatively these are often difficult to differentiate from fibroadenomas. Phyllodes tumours have a variable clinical course with the ability to metastasize and a propensity to recur locally. Complete excision with wide margins is essential to prevent local recurrence. In our case, the surgical margins were limited and our patient was therefore treated with postoperative radiation therapy.

  11. Clinicopathological Study of Surface Epithelial Tumours of the Ovary: An Institutional Study

    PubMed Central

    Venugopal, Suguna Belur

    2016-01-01

    Introduction It is an established fact that tumours of ovary inherit a spectrum of histogenetic background, the variety being more than any other organ. Surface epithelial stromal tumours of ovary being the most common type of ovarian tumours form a complicating and baffling subject in the history of oncology and hence, are an interesting topic for study. Aim The aim of this study was to categorize the surface epithelial tumours of ovary into benign, borderline and malignant, to study their clinical and histopathological pattern and to compare their incidences with other studies. Materials and Methods This is a 5 year (3years of retrospective + 2 years of prospective) study conducted during the period of June 2006 to May 2011. It consisted of 139 cases (141 tumours/ lesions). The relevant clinical details about the patient were retrieved from hospital data. Results The 141 surface epithelial tumours from 139 cases accounted for 66.2% of all the ovarian tumours encountered during the study period. The mean age of diagnosis in our study was 42.4 years. The most common clinical presentation was mass in abdomen. 90.6% of tumours were unilateral and 9.4% cases were bilateral. Right sided tumours (59.8%) were more common than left sided tumours (40.14%). 82.3% were benign tumours, 12.1% were malignant and 5.7% tumours belonged to the borderline category. Conclusion Surface epithelial tumours present a great challenge to the gynecologic oncologist because non-neoplastic ovarian lesions can form a pelvic mass and potentially mimic a neoplasm. Their proper recognition and histopathologic classification is essential for appropriate management as malignant tumours are usually picked up at an advanced stage owing to their asymptomatic nature and inaccessible site for aspiration cytology and biopsy. Histopathological examination still remains the mainstay in diagnosis of these neoplasms. PMID:27891341

  12. Metabolic substrate utilization by tumour and host tissues in cancer cachexia.

    PubMed Central

    Mulligan, H D; Tisdale, M J

    1991-01-01

    Utilization of metabolic substrates in tumour and host tissues was determined in the presence or absence of two colonic tumours, the MAC16, which is capable of inducing cachexia in recipient animals, and the MAC13, which is of the same histological type, but without the effect on host body composition. Glucose utilization by different tissues was determined in vivo by the 2-deoxyglucose tracer technique. Glucose utilization by the MAC13 tumour was significantly higher than by the MAC16 tumour, and in animals bearing tumours of either type the tumour was the second major consumer of glucose after the brain. This extra demand for glucose was accompanied by a marked decrease in glucose utilization by the epididymal fat-pads, testes, colon, spleen, kidney and, in particular, the brain, in tumour-bearing animals irrespective of cachexia. The decrease in glucose consumption by the brain was at least as high as the metabolic demand by the tumour. This suggests that the tissues of tumour-bearing animals adapt to use substrates other than glucose and that alterations in glucose utilization are not responsible for the cachexia. Studies in vitro showed that brain metabolism in the tumour-bearing state was maintained by an increased use of lactate and 3-hydroxybutyrate, accompanied by a 50% increase in 3-oxoacid CoA-transferase. This was supported by studies in vivo which showed an increased metabolism of 3-hydroxybutyrate in tumour-bearing animals. Thus ketone bodies may be utilized as a metabolic fuel during the cancer-bearing state, even though the nutritional conditions mimic the fed state. PMID:1859359

  13. Odontogenic tumours in children and adolescents: a collaborative study of 431 cases.

    PubMed

    Servato, J P S; de Souza, P E A; Horta, M C R; Ribeiro, D C; de Aguiar, M C F; de Faria, P R; Cardoso, S V; Loyola, Adriano Mota

    2012-06-01

    This study describes the oral and maxillofacial pathological characteristics of a series of odontogenic tumours in children and adolescents from three Brazilian reference centres. The records were reviewed for all odontogenic tumours in patients up to 18 years old based on criteria proposed by the World Health Organization (WHO) in 2005. Data concerning sex, age, skin colour and tumour location were collected and plotted. Four hundred and thirty one odontogenic tumours in children and adolescents were found, accounting for 37.5% of the total number of odontogenic tumours diagnosed. Benign tumours were predominant (99.8% of the cases), and odontoma was the most frequent type (41.4%), followed by keratocystic odontogenic tumours (25.5%) and ameloblastoma (14.6%). Odontogenic tumours were rarely detected in early childhood, and their prevalence increased with age. An almost equal distribution was observed with respect to sex and the site of the lesions. This study is the largest reported retrospective analysis describing odontogenic tumours in children and adolescents to date. The authors detected some variation in the relative frequency of odontogenic tumours compared with similar reports. Additional studies should be conducted based on the new WHO classification and predetermined age parameters to enable comparative analysis among different worldwide populations.

  14. Metabolic scaling in solid tumours

    NASA Astrophysics Data System (ADS)

    Milotti, E.; Vyshemirsky, V.; Sega, M.; Stella, S.; Chignola, R.

    2013-06-01

    Tumour metabolism is an outstanding topic of cancer research, as it determines the growth rate and the global activity of tumours. Recently, by combining the diffusion of oxygen, nutrients, and metabolites in the extracellular environment, and the internal motions that mix live and dead cells, we derived a growth law of solid tumours which is linked to parameters at the cellular level. Here we use this growth law to obtain a metabolic scaling law for solid tumours, which is obeyed by tumours of different histotypes both in vitro and in vivo, and we display its relation with the fractal dimension of the distribution of live cells in the tumour mass. The scaling behaviour is related to measurable parameters, with potential applications in the clinical practice.

  15. Metabolic scaling in solid tumours

    PubMed Central

    Milotti, E.; Vyshemirsky, V.; Sega, M.; Stella, S.; Chignola, R.

    2013-01-01

    Tumour metabolism is an outstanding topic of cancer research, as it determines the growth rate and the global activity of tumours. Recently, by combining the diffusion of oxygen, nutrients, and metabolites in the extracellular environment, and the internal motions that mix live and dead cells, we derived a growth law of solid tumours which is linked to parameters at the cellular level1. Here we use this growth law to obtain a metabolic scaling law for solid tumours, which is obeyed by tumours of different histotypes both in vitro and in vivo, and we display its relation with the fractal dimension of the distribution of live cells in the tumour mass. The scaling behaviour is related to measurable parameters, with potential applications in the clinical practice. PMID:23727729

  16. VEGF targets the tumour cell.

    PubMed

    Goel, Hira Lal; Mercurio, Arthur M

    2013-12-01

    The function of vascular endothelial growth factor (VEGF) in cancer is not limited to angiogenesis and vascular permeability. VEGF-mediated signalling occurs in tumour cells, and this signalling contributes to key aspects of tumorigenesis, including the function of cancer stem cells and tumour initiation. In addition to VEGF receptor tyrosine kinases, the neuropilins are crucial for mediating the effects of VEGF on tumour cells, primarily because of their ability to regulate the function and the trafficking of growth factor receptors and integrins. This has important implications for our understanding of tumour biology and for the development of more effective therapeutic approaches.

  17. Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive Impairment

    PubMed Central

    Wen, Dong; Jia, Peilei; Lian, Qiusheng; Zhou, Yanhong; Lu, Chengbiao

    2016-01-01

    At present, the sparse representation-based classification (SRC) has become an important approach in electroencephalograph (EEG) signal analysis, by which the data is sparsely represented on the basis of a fixed dictionary or learned dictionary and classified based on the reconstruction criteria. SRC methods have been used to analyze the EEG signals of epilepsy, cognitive impairment and brain computer interface (BCI), which made rapid progress including the improvement in computational accuracy, efficiency and robustness. However, these methods have deficiencies in real-time performance, generalization ability and the dependence of labeled sample in the analysis of the EEG signals. This mini review described the advantages and disadvantages of the SRC methods in the EEG signal analysis with the expectation that these methods can provide the better tools for analyzing EEG signals. PMID:27458376

  18. Brain Metastases From Breast Carcinoma: Validation of the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification and Proposition of a New Prognostic Score

    SciTech Connect

    Le Scodan, Romuald Massard, Christophe; Mouret-Fourme, Emmanuelle; Guinebretierre, Jean Marc; Cohen-Solal, Christine; De Lalande, Brigitte; Moisson, Patricia; Breton-Callu, Christelle; Gardner, Miriam; Goupil, Alain; Renody, Nicole; Floiras, Jean Louis; Labib, Alain

    2007-11-01

    Purpose: To validate the Radiation Therapy Oncology Group Recursive Partitioning Analysis (RTOG RPA) classification and determine independent prognostic factors, to create a simple and specific prognostic score for patients with brain metastases (BM) from breast carcinoma treated with whole-brain radiotherapy (WBRT). Methods and Materials: From January 1998 through December 2003, 132 patients with BM from breast carcinoma were treated with WBRT. We analyzed several potential predictors of survival after WBRT: age, Karnofsky performance status, RTOG-RPA class, number of BM, presence and site of other systemic metastases, interval between primary tumor and BM, tumor hormone receptor (HR) status, lymphocyte count, and HER-2 overexpression. Results: A total of 117 patients received exclusive WBRT and were analyzed. Median survival with BM was 5 months. One-year and 2-year survival rates were 27.6% (95% confidence interval [CI] 19.9-36.8%) and 12% (95% CI 6.5-21.2%), respectively. In multivariate analysis, RTOG RPA Class III, lymphopenia ({<=}0.7 x 10{sup 9}/L) and HR negative status were independent prognostic factors for poor survival. We constructed a three-factor prognostic scoring system that predicts 6-month and 1-year rates of overall survival in the range of 76.1-29.5% (p = 0.00033) and 60.9-15.9% (p = 0.0011), respectively, with median survival of 15 months, 5 months, or 3 months for patients with none, one, or more than one adverse prognostic factor(s), respectively. Conclusions: This study confirms the prognostic value of the RTOG RPA classification, lymphopenia, and tumor HR status, which can be used to form a prognostic score for patients with BM from breast carcinoma.

  19. Classification of functional near-infrared spectroscopy signals corresponding to the right- and left-wrist motor imagery for development of a brain-computer interface.

    PubMed

    Naseer, Noman; Hong, Keum-Shik

    2013-10-11

    This paper presents a study on functional near-infrared spectroscopy (fNIRS) indicating that the hemodynamic responses of the right- and left-wrist motor imageries have distinct patterns that can be classified using a linear classifier for the purpose of developing a brain-computer interface (BCI). Ten healthy participants were instructed to imagine kinesthetically the right- or left-wrist flexion indicated on a computer screen. Signals from the right and left primary motor cortices were acquired simultaneously using a multi-channel continuous-wave fNIRS system. Using two distinct features (the mean and the slope of change in the oxygenated hemoglobin concentration), the linear discriminant analysis classifier was used to classify the right- and left-wrist motor imageries resulting in average classification accuracies of 73.35% and 83.0%, respectively, during the 10s task period. Moreover, when the analysis time was confined to the 2-7s span within the overall 10s task period, the average classification accuracies were improved to 77.56% and 87.28%, respectively. These results demonstrate the feasibility of an fNIRS-based BCI and the enhanced performance of the classifier by removing the initial 2s span and/or the time span after the peak value.

  20. A short history of neuroendocrine tumours and their peptide hormones.

    PubMed

    de Herder, Wouter W; Rehfeld, Jens F; Kidd, Mark; Modlin, Irvin M

    2016-01-01

    The discovery of neuroendocrine tumours of the gastrointestinal tract and pancreas started in 1870, when Rudolf Heidenhain discovered the neuroendocrine cells, which can lead to the development of these tumours. Siegfried Oberndorfer was the first to introduce the term carcinoid in 1907. The pancreatic islet cells were first described in 1869 by Paul Langerhans. In 1924, Seale Harris was the first to describe endogenous hyperinsulinism/insulinoma. In 1942 William Becker and colleagues were the first to describe the glucagonoma syndrome. The first description of gastrinoma by Robert Zollinger and Edwin Ellison dates from 1955. The first description of the VIPoma syndrome by John Verner and Ashton Morrison dates from 1958. In 1977, the groups of Lars-Inge Larsson and Jens Rehfeld, and of Om Ganda reported the first cases of somatostatinoma. But only in 2013, Jens Rehfeld and colleagues described the CCK-oma syndrome. The most recently updated WHO classification for gastrointestinal neuroendocrine tumours dates from 2010.

  1. Friend or foe?: The tumour microenvironment dilemma in colorectal cancer.

    PubMed

    Colangelo, Tommaso; Polcaro, Giovanna; Muccillo, Livio; D'Agostino, Giovanna; Rosato, Valeria; Ziccardi, Pamela; Lupo, Angelo; Mazzoccoli, Gianluigi; Sabatino, Lina; Colantuoni, Vittorio

    2017-01-01

    The network of bidirectional homotypic and heterotypic interactions established among parenchymal tumour cells and surrounding mesenchymal stromal cells generates the tumour microenvironment (TME). These intricate crosstalks elicit both beneficial and adverse effects on tumour initiation and progression unbalancing the signals and responses from the neighbouring cells. Here, we highlight the structure, activities and evolution of TME cells considering a novel colorectal cancer (CRC) classification based on differential stromal composition and gene expression profiles. In this scenario, we scrutinise the molecular pathways that either change or become corrupted during CRC development and their relative prognostic value. Finally, we survey the therapeutic molecules directed against TME components currently available in clinical trials as well as those with stronger potential in preclinical studies. Elucidation of dynamic variations in the CRC TME cell composition and their relative contribution could provide novel diagnostic or prognostic biomarkers and allow more personalised therapeutic strategies.

  2. Identification of genes involved in the biology of atypical teratoid/rhabdoid tumours using Drosophila melanogaster

    NASA Astrophysics Data System (ADS)

    Jeibmann, Astrid; Eikmeier, Kristin; Linge, Anna; Kool, Marcel; Koos, Björn; Schulz, Jacqueline; Albrecht, Stefanie; Bartelheim, Kerstin; Frühwald, Michael C.; Pfister, Stefan M.; Paulus, Werner; Hasselblatt, Martin

    2014-06-01

    Atypical teratoid/rhabdoid tumours (AT/RT) are malignant brain tumours. Unlike most other human brain tumours, AT/RT are characterized by inactivation of one single gene, SMARCB1. SMARCB1 is a member of the evolutionarily conserved SWI/SNF chromatin remodelling complex, which has an important role in the control of cell differentiation and proliferation. Little is known, however, about the pathways involved in the oncogenic effects of SMARCB1 inactivation, which might also represent targets for treatment. Here we report a comprehensive genetic screen in the fruit fly that revealed several genes not yet associated with loss of snr1, the Drosophila homologue of SMARCB1. We confirm the functional role of identified genes (including merlin, kibra and expanded, known to regulate hippo signalling pathway activity) in human rhabdoid tumour cell lines and AT/RT tumour samples. These results demonstrate that fly models can be employed for the identification of clinically relevant pathways in human cancer.

  3. Radiotherapy by particle beams (hadrontherapy) of intracranial tumours: a survey on pathology.

    PubMed

    Schiffer, D

    2005-04-01

    A review of the principal contributions of radio-therapy of brain tumours by beam particles is carried out. Neutrons, protons and light ions are considered along with their pros and cons in relation to types and locations of brain tumours. A particular emphasis is given to the pathologic studies of their effects directly o n tumours and on the normal nervous tissue, considering mainly the relevant action mechanisms of the radiation types and the requirements of the clinical therapeutic strategies. For comparison the main features of the pathologic effects of radiotherapy by photons are described. From the review it emerges that the new modality of radiation by protons and light ions, because of their peculiar physical characteristics, may represent a new way of destroying the tumour and sparing normal nervous tissue, especially when deeply located and irregularly shaped tumours are concerned. More neuropathological studies are needed in order to better understand the potentiality of the new treatment of modalities.

  4. Uterine Tumour Resembling Ovarian Sex Cord Tumour- A Rare Entity

    PubMed Central

    Ilhan, Tolgay Tuyan; Gül, Ayhan; Ugurluoglu, Ceyhan; Çelik, Çetin

    2016-01-01

    Uterine Tumour Resembling Ovarian Sex-Cord Tumours (UTROSCTs) are an extremely rare type of uterine body tumours arising from the endometrial stroma. Epidemiology, aetiology, pathogenesis, management and natural history of UTROSCTs are still a question of debate, as there is little available data in the literature. Although rare, the possibility of UTROSCTs should be kept in mind, when a patient presents with abnormal bleeding and an enlarged uterus. UTROSCTs appear dirty white/cream-coloured, gelatinous, well-circumscribed mass with smooth surface on macroscopic examination. We present a rare case of endometrial stromal tumour with sex-cord-like differentiation which was successfully treated by hysterectomy with bilateral salpingo-oophorectomy. The clinical manifestations, pathologic characteristics, diagnosis and management of these tumours are reviewed here. PMID:28208949

  5. EEG-Based Classification of Motor Imagery Tasks Using Fractal Dimension and Neural Network for Brain-Computer Interface

    NASA Astrophysics Data System (ADS)

    Phothisonothai, Montri; Nakagawa, Masahiro

    In this study, we propose a method of classifying a spontaneous electroencephalogram (EEG) approach to a brain-computer interface. Ten subjects, aged 21-32 years, volunteered to imagine left-and right- hand movements. An independent component analysis based on a fixed-point algorithm is used to eliminate the activities found in the EEG signals. We use a fractal dimension value to reveal the embedded potential responses in the human brain. The different fractal dimension values between the relaxing and imaging periods are computed. Featured data is classified by a three-layer feed-forward neural network based on a simple backpropagation algorithm. Two conventional methods, namely, the use of the autoregressive (AR) model and the band power estimation (BPE) as features, and the linear discriminant analysis (LDA) as a classifier, are selected for comparison in this study. Experimental results show that the proposed method is more effective than the conventional methods.

  6. Adapting radiotherapy to hypoxic tumours

    NASA Astrophysics Data System (ADS)

    Malinen, Eirik; Søvik, Åste; Hristov, Dimitre; Bruland, Øyvind S.; Rune Olsen, Dag

    2006-10-01

    In the current work, the concepts of biologically adapted radiotherapy of hypoxic tumours in a framework encompassing functional tumour imaging, tumour control predictions, inverse treatment planning and intensity modulated radiotherapy (IMRT) were presented. Dynamic contrast enhanced magnetic resonance imaging (DCEMRI) of a spontaneous sarcoma in the nasal region of a dog was employed. The tracer concentration in the tumour was assumed related to the oxygen tension and compared to Eppendorf histograph measurements. Based on the pO2-related images derived from the MR analysis, the tumour was divided into four compartments by a segmentation procedure. DICOM structure sets for IMRT planning could be derived thereof. In order to display the possible advantages of non-uniform tumour doses, dose redistribution among the four tumour compartments was introduced. The dose redistribution was constrained by keeping the average dose to the tumour equal to a conventional target dose. The compartmental doses yielding optimum tumour control probability (TCP) were used as input in an inverse planning system, where the planning basis was the pO2-related tumour images from the MR analysis. Uniform (conventional) and non-uniform IMRT plans were scored both physically and biologically. The consequences of random and systematic errors in the compartmental images were evaluated. The normalized frequency distributions of the tracer concentration and the pO2 Eppendorf measurements were not significantly different. 28% of the tumour had, according to the MR analysis, pO2 values of less than 5 mm Hg. The optimum TCP following a non-uniform dose prescription was about four times higher than that following a uniform dose prescription. The non-uniform IMRT dose distribution resulting from the inverse planning gave a three times higher TCP than that of the uniform distribution. The TCP and the dose-based plan quality depended on IMRT parameters defined in the inverse planning procedure (fields

  7. Intraspinal tumours in the Kenya African.

    PubMed

    Ruberti, R F; Carmagnani, A L

    1976-06-01

    Thirty-one cases of intraspinal tumours in the African have been described, with age, sex incidence, frequency, site and histopathology shown. Intraspinal tumours in this series are compared with the larger series. Extradural and intramedullary tumours together with cervical spine tumours appear to be more frequent in this series. There is a high incidence of dumbell tumours in the neurinomas. Sarcomas are the most common type of tumours and mainly affect the thoracic spine.

  8. Strengths and weaknesses of 1.5T and 3T MRS data in brain glioma classification.

    PubMed

    Kounelakis, M G; Dimou, I N; Zervakis, M E; Tsougos, I; Tsolaki, E; Kousi, E; Kapsalaki, E; Theodorou, K

    2011-07-01

    Although magnetic resonance spectroscopy (MRS) methods of 1.5Tesla (T) and 3T have been widely applied during the last decade for noninvasive diagnostic purposes, only a few studies have been reported on the value of the information extracted in brain cancer discrimination. The purpose of this study is threefold. First, to show that the diagnostic value of the information extracted from two different MRS scanners of 1.5T and 3T is significantly influenced in terms of brain gliomas discrimination. Second, to statistically evaluate the discriminative potential of publicly known metabolic ratio markers, obtained from these two types of scanners in classifying low-, intermediate-, and high-grade gliomas. Finally, to examine the diagnostic value of new metabolic ratios in the discrimination of complex glioma cases where the diagnosis is both challenging and critical. Our analysis has shown that although the information extracted from 3T MRS scanner is expected to provide better brain gliomas discrimination; some factors like the features selected, the pulse-sequence parameters, and the spectroscopic data acquisition methods can influence the discrimination efficiency. Finally, it is shown that apart from the bibliographical known, new metabolic ratio features such as N-acetyl aspartate/ S, Choline/ S, Creatine/ S , and myo-Inositol/ S play significant role in gliomas grade discrimination.

  9. Benign hepatic tumours and tumour like conditions in men.

    PubMed Central

    Karhunen, P J

    1986-01-01

    In a consecutive medicolegal necropsy series benign hepatic tumours and tumour like conditions occurred in 52% of the 95 men aged 35-69 years. The incidence increased with age, mainly due to small bile duct tumours (n = 26; mean age 56.7 years; p less than 0.01; mean size 1.3 mm). The next most common tumours were cavernous hemangiomas (n = 19; mean age 53.9 years; mean size 5.2 mm) that were not related to age. Focal nodular hyperplasia (n = 3; mean size 8.0 mm) tended to occur in a younger age group (mean age 40.3 years; p less than 0.001). Multiple bile duct tumours were present in 46% and hemangiomas in 50% of the men studied. Liver cell adenoma, nodular regenerative hyperplasia, and peliosis hepatis were incidental findings (one case of each). Nodular regenerative hyperplasia was associated with the consumption of alcohol and a total dose of 21.5 g of testosterone. These results indicate that benign hepatic tumours and tumour like conditions are not rare in men but may remain undetected because of their small size. Images PMID:3950039

  10. Tumours of bones and joints

    PubMed Central

    Misdorp, W.; Van Der Heul, R. O.

    1976-01-01

    Tumours of bones and joints are not infrequent in dogs but are rare in other domestic animals. In the dog, most bone tumours are malignant; osteosarcomas are by far the most frequently encountered tumours, especially in giant breeds and boxers. The following main categories of bone tumour are described: bone-forming, cartilage-forming, giant cell, marrow, vascular, miscellaneous, metastatic, unclassified, and tumour-like lesions. The tumours of joints and related structures are classified as synovial sarcomas, fibroxanthomas, and malignant giant cell tumour of soft tissues. ImagesFig. 21Fig. 22Fig. 23Fig. 24Fig. 17Fig. 18Fig. 19Fig. 20Fig. 29Fig. 30Fig. 31Fig. 32Fig. 33Fig. 34Fig. 35Fig. 36Fig. 25Fig. 26Fig. 27Fig. 28Fig. 1Fig. 2Fig. 3Fig. 4Fig. 37Fig. 38Fig. 39Fig. 40Fig. 5Fig. 6Fig. 7Fig. 8Fig. 13Fig. 14Fig. 15Fig. 16Fig. 9Fig. 10Fig. 11Fig. 12 PMID:1086157

  11. Murine Bioluminescent Hepatic Tumour Model

    PubMed Central

    Rajendran, Simon; Salwa, Slawomir; Gao, Xuefeng; Tabirca, Sabin; O'Hanlon, Deirdre; O'Sullivan, Gerald C.; Tangney, Mark

    2010-01-01

    This video describes the establishment of liver metastases in a mouse model that can be subsequently analysed by bioluminescent imaging. Tumour cells are administered specifically to the liver to induce a localised liver tumour, via mobilisation of the spleen and splitting into two, leaving intact the vascular pedicle for each half of the spleen. Lewis lung carcinoma cells that constitutively express the firefly luciferase gene (luc1) are inoculated into one hemi-spleen which is then resected 10 minutes later. The other hemi-spleen is left intact and returned to the abdomen. Liver tumour growth can be monitored by bioluminescence imaging using the IVIS whole body imaging system. Quantitative imaging of tumour growth using IVIS provides precise quantitation of viable tumour cells. Tumour cell death and necrosis due to drug treatment is indicated early by a reduction in the bioluminescent signal. This mouse model allows for investigating the mechanisms underlying metastatic tumour-cell survival and growth and can be used for the evaluation of therapeutics of liver metastasis. PMID:20689502

  12. Brain source localization: A new method based on MUltiple SIgnal Classification algorithm and spatial sparsity of the field signal for electroencephalogram measurements

    NASA Astrophysics Data System (ADS)

    Vergallo, P.; Lay-Ekuakille, A.

    2013-08-01

    Brain activity can be recorded by means of EEG (Electroencephalogram) electrodes placed on the scalp of the patient. The EEG reflects the activity of groups of neurons located in the head, and the fundamental problem in neurophysiology is the identification of the sources responsible of brain activity, especially if a seizure occurs and in this case it is important to identify it. The studies conducted in order to formalize the relationship between the electromagnetic activity in the head and the recording of the generated external field allow to know pattern of brain activity. The inverse problem, that is given the sampling field at different electrodes the underlying asset must be determined, is more difficult because the problem may not have a unique solution, or the search for the solution is made difficult by a low spatial resolution which may not allow to distinguish between activities involving sources close to each other. Thus, sources of interest may be obscured or not detected and known method in source localization problem as MUSIC (MUltiple SIgnal Classification) could fail. Many advanced source localization techniques achieve a best resolution by exploiting sparsity: if the number of sources is small as a result, the neural power vs. location is sparse. In this work a solution based on the spatial sparsity of the field signal is presented and analyzed to improve MUSIC method. For this purpose, it is necessary to set a priori information of the sparsity in the signal. The problem is formulated and solved using a regularization method as Tikhonov, which calculates a solution that is the better compromise between two cost functions to minimize, one related to the fitting of the data, and another concerning the maintenance of the sparsity of the signal. At the first, the method is tested on simulated EEG signals obtained by the solution of the forward problem. Relatively to the model considered for the head and brain sources, the result obtained allows to

  13. Tumours of the nasal cavity*

    PubMed Central

    Stünzi, H.; Hauser, B.

    1976-01-01

    Tumours of the nasal cavity are rare in domestic animals, most cases occurring in the dog. Epithelial tumours are the most common type in carnivores (dogs and cats). In general, the same types of tumour occur in domestic animals as occur in man. There was no significant predisposition for breed in dogs, but in both dogs and cats far more males than females were affected. Metastases occurred only rarely. ImagesFig. 1Fig. 2Fig. 3Fig. 4Fig. 9Fig. 10Fig. 11Fig. 12Fig. 5Fig. 6Fig. 7Fig. 8 PMID:1086156

  14. Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: What Is New in the 2017 WHO Blue Book for Tumors and Tumor-Like Lesions of the Neck and Lymph Nodes.

    PubMed

    Katabi, Nora; Lewis, James S

    2017-03-01

    The World Health Organization (WHO) 2017 Classification of Head and Neck Tumors ("Blue Book") will now include a new chapter on tumors and tumor-like lesions of the neck and lymph nodes, which was not included in the previous edition. Tumors and tumor-like lesions, including a variety of cysts and metastases, can arise in any component in the neck, including soft tissue, lymph nodes, and developmental remnants. The pathology and clinical features of metastatic carcinoma of unknown primary in the head and neck has changed dramatically in the last several years. Many of these tumors which were previously diagnosed as unknown primary are now identified as oropharyngeal and nasopharyngeal carcinomas related to human papillomavirus (HPV), less commonly to Epstein-Barr virus (EBV) and occasionally even to Merkel cell polyomavirus. Many unusual features can arise in these metastases, such as undifferentiated morphology, extensive cystic change with central degeneration, gland formation, and even ciliated cells. Rarely, carcinoma in the neck can arise in association with a heterotopic tissue, primarily thyroid or salivary gland tissue. Tumor-like lesions include branchial cleft cysts, thyroglossal duct cyst, dermoid and teratoid cyst, and ranula. Pathologists should be familiar with the diagnostic features and clinicopathologic corrections of these neck lesions in order to correctly diagnosis them and to provide for proper clinical management. This article will briefly describe the pathologic and clinical features of these entities as they are covered in the new 2017 Blue Book.

  15. Interleukin-2 and histamine in combination inhibit tumour growth and angiogenesis in malignant glioma

    PubMed Central

    Johansson, M; Henriksson, R; Bergenheim, A T; Koskinen, L-O D

    2000-01-01

    Biotherapy including interleukin-2 (IL-2) treatment seems to be more effective outside the central nervous system when compared to the effects obtained when the same tumour is located intracerebrally. Recently published studies suggest that reduced activity of NK cells in tumour tissue can be increased by histamine. The present study was designed to determine whether IL-2 and histamine, alone or in combination, can induce anti-tumour effects in an orthotopic rat glioma model. One group of rats was treated with histamine alone (4 mg kg–1s.c. as daily injections from day 6 after intracranial tumour implantation), another group with IL-2 alone as a continuous subcutaneous infusion and a third group with both histamine and IL-2. The animals were sacrificed at day 24 after tumour implantation. IL-2 and histamine in combination significantly reduced tumour growth. The microvessel density was significantly reduced, an effect mainly affecting the small vessels. No obvious alteration in the pattern of VEGF mRNA expression was evident and no significant changes in apoptosis were observed. Neither IL-2 nor histamine alone caused any detectable effects on tumour growth. Histamine caused an early and pronounced decline in tumour blood flow compared to normal brain. The results indicate that the novel combination of IL-2 and histamine can be of value in reducing intracerebral tumour growth and, thus, it might be of interest to re-evaluate the therapeutic potential of biotherapy in malignant glioma. © 2000 Cancer Research Campaign PMID:10952789

  16. Brain-state classification and a dual-state decoder dramatically improve the control of cursor movement through a brain-machine interface

    NASA Astrophysics Data System (ADS)

    Sachs, Nicholas A.; Ruiz-Torres, Ricardo; Perreault, Eric J.; Miller, Lee E.

    2016-02-01

    Objective. It is quite remarkable that brain machine interfaces (BMIs) can be used to control complex movements with fewer than 100 neurons. Success may be due in part to the limited range of dynamical conditions under which most BMIs are tested. Achieving high-quality control that spans these conditions with a single linear mapping will be more challenging. Even for simple reaching movements, existing BMIs must reduce the stochastic noise of neurons by averaging the control signals over time, instead of over the many neurons that normally control movement. This forces a compromise between a decoder with dynamics allowing rapid movement and one that allows postures to be maintained with little jitter. Our current work presents a method for addressing this compromise, which may also generalize to more highly varied dynamical situations, including movements with more greatly varying speed. Approach. We have developed a system that uses two independent Wiener filters as individual components in a single decoder, one optimized for movement, and the other for postural control. We computed an LDA classifier using the same neural inputs. The decoder combined the outputs of the two filters in proportion to the likelihood assigned by the classifier to each state. Main results. We have performed online experiments with two monkeys using this neural-classifier, dual-state decoder, comparing it to a standard, single-state decoder as well as to a dual-state decoder that switched states automatically based on the cursor’s proximity to a target. The performance of both monkeys using the classifier decoder was markedly better than that of the single-state decoder and comparable to the proximity decoder. Significance. We have demonstrated a novel strategy for dealing with the need to make rapid movements while also maintaining precise cursor control when approaching and stabilizing within targets. Further gains can undoubtedly be realized by optimizing the performance of the

  17. Intracranial tumoural haemorrhage--a report of 58 cases.

    PubMed

    Yuguang, Liu; Meng, Liu; Shugan, Zhu; Yuquan, Jiang; Gang, Li; Xingang, Li; Chengyuan, Wu

    2002-11-01

    In order to study the computerized tomographic (CT) appearances and clinical characteristics of intracranial tumoural haemorrhage (ITH), we analyzed retrospectively fifty-eight patients with ITH and reviewed the literature. As a result, 91% patients had acute or subacute onset and 26% manifested haemorrhage as their first symptoms. CT scanning indicated that intratumoural bleeding occurred in 23 cases, bleeding into parenchyma 18 cases, subarachnoid space 6 cases, ventricle 3 cases and subdural space 8 cases. Thirty-eight patients had emergency operations and the others had selective operations. Both tumours and haematomas were removed all together in all patients. Fifty-five patients were cured or improved and three died during the perioperative stage in our series. Among the patients with ITH, there were 21 metastatic tumours, 19 gliomas, 10 meningiomas, 6 pituitary adenomas, 1 melanoma and 1 acoustic neurilemoma. The onset of most ITH resembled that of cerebrovascular diseases. The location of ITH and the CT appearances of ITH varied in different cerebral tumours. Radical removal of brain tumours with haemorrhage is an effective treatment for ITH, which can greatly decrease the perioperative mortality rate and improve the prognoses of patients.

  18. Multicellular Streaming in Solid Tumours

    NASA Astrophysics Data System (ADS)

    Kas, Josef

    As early as 400 BCE, the Roman medical encyclopaedist Celsus recognized that solid tumours are stiffer than surrounding tissue. However, cancer cell lines are softer, and softer cells facilitate invasion. This paradox raises several questions: Does softness emerge from adaptation to mechanical and chemical cues in the external microenvironment, or are soft cells already present inside a primary solid tumour? If the latter, how can a more rigid tissue contain more soft cells? Here we show that in primary tumour samples from patients with mammary and cervix carcinomas, cells do exhibit a broad distribution of rigidities, with a higher fraction of softer and more contractile cells compared to normal tissue. Mechanical modelling based on patient data reveals that, surprisingly, tumours with a significant fraction of very soft cells can still remain rigid. Moreover, in tissues with the observed distributions of cell stiffnesses, softer cells spontaneously self-organize into lines or streams, possibly facilitating cancer metastasis.

  19. Primitive neuroectodermal adrenal gland tumour.

    PubMed

    Tsang, Y P; Lang, Brian H H; Tam, S C; Wong, K P

    2014-10-01

    Ewing's sarcoma, also called primitive neuroectodermal tumour of the adrenal gland, is extremely rare. Only a few cases have been reported in the literature. We report on a woman with adult-onset primitive neuroectodermal tumour of the adrenal gland presenting with progressive flank pain. Computed tomography confirmed an adrenal tumour with invasion of the left diaphragm and kidney. Radical surgery was performed and the pain completely resolved; histology confirmed the presence of primitive neuroectodermal tumour, for which she was given chemotherapy. The clinical presentation of this condition is non-specific, and a definitive diagnosis is based on a combination of histology, as well as immunohistochemical and cytogenic analysis. According to the literature, these tumours demonstrate rapid growth and aggressive behaviour but there are no well-established guidelines or treatment strategies. Nevertheless, surgery remains the mainstay of local disease control; curative surgery can be performed in most patients. Adjuvant chemoirradiation has been advocated yet no consensus is available. The prognosis of patients with primitive neuroectodermal tumours remains poor.

  20. Targeting the erythropoietin receptor on glioma cells reduces tumour growth

    SciTech Connect

    Peres, Elodie A.; Valable, Samuel; Guillamo, Jean-Sebastien; Marteau, Lena; Bernaudin, Jean-Francois; Roussel, Simon; Lechapt-Zalcman, Emmanuele; Bernaudin, Myriam; Petit, Edwige

    2011-10-01

    Hypoxia has been shown to be one of the major events involved in EPO expression. Accordingly, EPO might be expressed by cerebral neoplastic cells, especially in glioblastoma, known to be highly hypoxic tumours. The expression of EPOR has been described in glioma cells. However, data from the literature remain descriptive and controversial. On the basis of an endogenous source of EPO in the brain, we have focused on a potential role of EPOR in brain tumour growth. In the present study, with complementary approaches to target EPO/EPOR signalling, we demonstrate the presence of a functional EPO/EPOR system on glioma cells leading to the activation of the ERK pathway. This EPO/EPOR system is involved in glioma cell proliferation in vitro. In vivo, we show that the down-regulation of EPOR expression on glioma cells reduces tumour growth and enhances animal survival. Our results support the hypothesis that EPOR signalling in tumour cells is involved in the control of glioma growth.

  1. A classification method of different motor imagery tasks based on fractal features for brain-machine interface.

    PubMed

    Phothisonothai, Montri; Nakagawa, Masahiro

    2009-03-01

    The objective of this study is to classify spontaneous electroencephalogram (EEG) signal on the basis of fractal concepts. Four motor imagery tasks (left hand movement, right hand movement, feet movement, and tongue movement) were investigated for each EEG recording session. Ten subjects volunteered to participate in this study. As we known, fractal geometry is a mathematical tool for dealing with complex systems like EEG signal. Therefore, we used the fractal dimension (FD) as feature for the application of brain-machine interface (BMI). Effective algorithm, namely, detrended fluctuation analysis (DFA) has been selected to estimate embedded FD values between relaxing and imaging states of the recorded EEG signal. To show the pattern of FDs, we propose a windowing-based method or also called time-dependent fractal dimension (TDFD) and the Kullback-Leibler (K-L) divergence. The K-L divergence and different expected values are employed as the input parameters of classifier. Finally, featured data are classified by a three-layer feed-forward neural network based on a simple backpropagation algorithm. Experimental results show that the proposed method is more effective than the conventional methods.

  2. EEG-Based Classification of New Imagery Tasks Using Three-Layer Feedforward Neural Network Classifier for Brain-Computer Interface

    NASA Astrophysics Data System (ADS)

    Phothisonothai, Montri; Nakagawa, Masahiro

    2006-10-01

    In this paper proposes the classification method of new imagery tasks for simple binary commands approach to a brain-computer interface (BCI). An analysis of imaginary tasks as “yes/no” have been proposed. Since BCI is very helpful technology for the patients who are suffering from severe motor disabilities. The BCI applications can be realized by using an electroencephalogram (EEG) signals recording at the scalp surface through the electrodes. Six healthy subjects (three males and three females), aged 23-30 years, were volunteered to participate in the experiment. During the experiment, 10-questions were used to be stimuli. The feature extraction of the event-related synchronization and event-related desynchronization (ERD/ERS) responses can be determined by the slope coefficient and Euclidian distance (SCED) method. The method uses the three-layer feedforward neural network based on a simple backpropagation algorithm to classify the two feature vectors. The experimental results of the proposed method show the average accuracy rates of 81.5 and 78.8% when the subjects imagine to “yes” and “no”, respectively.

  3. Classification of Salivary Gland Neoplasms.

    PubMed

    Bradley, Patrick J

    2016-01-01

    Presently, there is no universal 'working' classification system acceptable to all clinicians involved in the diagnosis and management of patients with salivary gland neoplasms. The most recent World Health Organization Classification of Tumours: Head and Neck Tumours (Salivary Glands) (2005) for benign and malignant neoplasms represents the consensus of current knowledge and is considered the standard pathological classification based on which series should be reported. The TNM classification of salivary gland malignancies has stood the test of time, and using the stage groupings remains the current standard for reporting treated patients' outcomes. Many developments in molecular and genetic methods in the meantime have identified a number of new entities, and new findings for several of the well-established salivary malignancies need to be considered for inclusion in any new classification system. All clinicians involved in the diagnosis, assessment and treatment of patients with salivary gland neoplasms must understand and respect the need for the various classification systems, enabling them to work within a multidisciplinary clinical team environment.

  4. Microsatellite instability in thyroid tumours and tumour-like lesions

    PubMed Central

    Lazzereschi, D; Palmirotta, R; Ranieri, A; Ottini, L; Verì, M C; Cama, A; Cetta, F; Nardi, F; Colletta, G; Mariani-Costantini, R

    1999-01-01

    Fifty-one thyroid tumours and tumour-like lesions were analysed for instability at ten dinucleotide microsatellite loci and at two coding mononucleotide repeats within the transforming growth factor β (TGF-β) type II receptor (TβRII) and insulin-like growth factor II (IGF-II) receptor (IGFIIR) genes respectively. Microsatellite instability (MI) was detected in 11 out of 51 cases (21.5%), including six (11.7%) with MI at one or two loci and five (9.8%) with Ml at three or more loci (RER+ phenotype). No mutations in the TβRII and IGFIIR repeats were observed. The overall frequency of MI did not significantly vary in relation to age, gender, benign versus malignant status and tumour size. However, widespread MI was significantly more frequent in follicular adenomas and carcinomas than in papillary and Hürthle cell tumours: three out of nine tumours of follicular type (33.3%) resulted in replication error positive (RER+), versus 1 out of 29 papillary carcinomas (3.4%, P = 0.01), and zero out of eight Hürthle cell neoplasms. Regional lymph node metastases were present in five MI-negative primary cancers and resulted in MI-positive in two cases. © 1999 Cancer Research Campaign PMID:9888478

  5. Therapy-induced tumour secretomes promote resistance and tumour progression

    PubMed Central

    Obenauf, Anna C.; Zou, Yilong; Ji, Andrew L.; Vanharanta, Sakari; Shu, Weiping; Shi, Hubing; Kong, Xiangju; Bosenberg, Marcus C.; Wiesner, Thomas; Rosen, Neal; Lo, Roger S.; Massagué, Joan

    2015-01-01

    Drug resistance invariably limits the clinical efficacy of targeted therapy with kinase inhibitors against cancer1,2. Here we show that targeted therapy with BRAF, ALK, or EGFR kinase inhibitors induces a complex network of secreted signals in drug-stressed melanoma and lung adenocarcinoma cells. This therapy-induced secretome (TIS) stimulates the outgrowth, dissemination, and metastasis of drug-resistant cancer cell clones and supports the survival of drug-sensitive cancer cells, contributing to incomplete tumour regression. The vemurafenib reactive secretome in melanoma is driven by down-regulation of the transcription factor FRA1. In situ transcriptome analysis of drug-resistant melanoma cells responding to the regressing tumour microenvironment revealed hyperactivation of multiple signalling pathways, most prominently the AKT pathway. Dual inhibition of RAF and PI3K/AKT/mTOR pathways blunted the outgrowth of the drug-resistant cell population in BRAF mutant melanoma tumours, suggesting this combination therapy as a strategy against tumour relapse. Thus, therapeutic inhibition of oncogenic drivers induces vast secretome changes in drug-sensitive cancer cells, paradoxically establishing a tumour microenvironment that supports the expansion of drug-resistant clones, but is susceptible to combination therapy. PMID:25807485

  6. Vasoproliferative tumours of the retina

    PubMed Central

    Heimann, H.; Bornfeld, N.; Vij, O.; Coupland, S.; Bechrakis, N.; Kellner, U.; Foerster, M.

    2000-01-01

    BACKGROUND—Vasoproliferative tumours of the retina (VPTR) are benign tumours of unknown origin, occurring mostly in otherwise healthy patients. VPTR may be associated with other chorioretinal diseases, such as uveitis. The tumours, which histologically represent reactive gliovascular proliferations, are characterised by a pink to yellow appearance on funduscopy and are accompanied by exudative and haemorrhagic changes of the retina.
METHODS—22 cases of VPTR in 21 patients were examined with a follow up period between 1 month and 6 years. Ophthalmological changes associated with VPTR were intraretinal and subretinal exudations (n=18), exudative detachments of the surrounding sensory retina (n=13), intraretinal and subretinal haemorrhages (n=10), exudative changes within the macula (n=10), hyperpigmentation of the retinal pigment epithelium at the border of the exudative retinal changes (n=9), and vitreous haemorrhages (n=4). Tumour biopsy was performed in two cases. Treatment consisted of plaque radiotherapy (n=14), plaque radiotherapy and cryotherapy (two), cryotherapy only (two), observation (three), and enucleation in one case of a blind and painful eye.
RESULTS—Regression of the tumour and the associated exudative changes could be observed in all treated cases. Visual acuity at last follow up improved two lines or more in two cases, remained within two lines of the initial visual acuity in 15 cases, and worsened in the remaining five. Histopathological examination of the biopsy specimens and the tumour of the enucleated eye showed massive capillary proliferation with perivascular spindle-shaped glial cells of retinal origin.
CONCLUSION—The correct diagnosis of VPTR is of importance as these lesions may lead to visual loss. Further, VPTR must be differentiated from angiomas associated with von Hippel-Lindau disease as well as from ocular and systemic malignancies. Regression of tumour thickness and associated retinal changes can be achieved with

  7. [Liposomal cytarabine for the treatment of leptomeningeal dissemination of central nervous system tumours in children and adolescents].

    PubMed

    Moreno, Lucas; García Ariza, Miguel Angel; Cruz, Ofelia; Calvo, Carlota; Fuster, Jose Luis; Salinas, Jose Antonio; Moscardo, Cristina; Portugal, Raquel; Merino, Jose Manuel; Madero, Luis

    2016-11-01

    Leptomeningeal dissemination in paediatric central nervous system (CNS) tumours is associated with a poor outcome, and new therapeutic strategies are desperately needed. One of the main difficulties in the treatment of CNS tumours is blood brain barrier penetration. Intrathecal therapy has shown to be effective in several paediatric tumours. The aim of this article is to review the data available on the use of liposomal cytarabine for paediatric patients with leptomeningeal dissemination of CNS tumours, including the pharmacology, administration route, safety and efficacy data.

  8. Nuclear expression of Survivin in paediatric ependymomas and choroid plexus tumours correlates with morphologic tumour grade.

    PubMed

    Altura, R A; Olshefski, R S; Jiang, Y; Boué, D R

    2003-11-03

    Survivin is a gene that is widely expressed throughout the development of the normal mammalian embryo. Subcellular localisation of Survivin to both the nucleus and cytoplasm has suggested multiple functional roles, including inhibition of cell death, especially as demonstrated within a variety of malignant cell types, as well as regulation of the mitotic spindle checkpoint. The expression of Survivin has been associated with an adverse clinical outcome in a large number of malignancies. However, nuclear Survivin expression has been described as an independent variable of favourable prognosis in two large clinical studies of breast and gastric carcinomas. Reports of Survivin expression in normal postnatal, differentiated tissues have been restricted to cell types with high proliferative capacities, including vascular endothelium, endometrium, colonic epithelium, and activated lymphocytes. Prior to this report, expression within the normal human brain had not been characterised. Here, we analyse the expression of Survivin in human brain sections obtained from perinatal and paediatric autopsy cases. We report a strikingly high level of expression of Survivin within normal ependyma and choroid plexus (CP). Analysis of corresponding neoplastic tissue in paediatric ependymomas and CP tumours shows that expression of the nuclear form of Survivin correlates with morphologic tumour grade, with a loss of nuclear expression associated with progressive cytologic anaplasia. This pattern of expression supports a hypothesis that Survivin plays a functional role in normal ependymal growth and/or neural stem cell differentiation, and that abnormally low levels of expression of the nuclear form of this protein may be a marker of more aggressive disease and/or higher morphologic grade in ependymal and CP tumours.

  9. Tumour banking: the Spanish design.

    PubMed

    Morente, M M; de Alava, E; Fernandez, P L

    2007-01-01

    In the last decade the technical advances in high throughput techniques to analyze DNA, RNA and proteins have had a potential major impact on prevention, diagnosis, prognosis and treatment of many human diseases. Key pieces in this process, mainly thinking about the future, are tumour banks and tumour bank networks. To face these challenges, diverse suitable models and designs can be developed. The current article presents the development of a nationwide design of tumour banks in Spain based on a network of networks, specially focusing on its harmonization efforts mainly regarding technical procedures, ethical requirements, unified quality control policy and unique sample identification. We also describe our most important goals for the next years. This model does not correspond to a central tumour bank, but to a cooperative and coordinated network of national and regional networks. Independently from the network in which it is included, sample collections reside in their original institution, where it can be used for further clinical diagnosis, teaching and research activities of each independent hospital. The herein described 'network of networks' functional model could be useful for other countries and/or international tumour bank activities.

  10. A Rare Collision Tumour of Uterus- Squamous Cell Carcinoma and Endometrial Stromal Sarcoma

    PubMed Central

    Gupta, Bindiya; Pathre, Abhishek; Rajaram, Shalini; Goyal, Neerja

    2017-01-01

    Collision tumours are defined by co-existence of two tumours in the same or adjacent organs which are topographically and histologically distinct with minimal or no histological admixture. Collision tumours have been described in many organs notably thyroid, brain, adrenal gland, stomach and rarely uterus. Most of the collision tumours reported in uterus have two components; an adenocarcinoma and a sarcoma. We report a case of a 60-year-old lady who presented with complaints of post-menopausal bleeding. A cervical biopsy was performed which showed a non-keratinizing squamous cell carcinoma of cervix. Intra-operatively the uterus was bulky with a 6 cm x 5 cm polypoidal mass in the endometrial canal along with a 2 cm friable cervical growth. The fleshy uterine cavity mass was a spindle cell tumour with moderate pleomorphism and frequent mitosis. It was immunopositive for CD10 and negative for smooth muscle actin and cytokeratin 5/6. The other growth showed non-keratinizing squamous cell carcinoma which was positive for cytokeratin 5/6. Based on the distinct topographical location and limited areas of tumour admixture of the two tumours, a diagnosis of collision tumour of uterus comprising of endometrial stromal sarcoma (high grade) uterus and squamous cell carcinoma cervix was made. PMID:28384878

  11. Tumour-associated eosinophilia in the bladder.

    PubMed Central

    Lowe, D; Fletcher, C D; Gower, R L

    1984-01-01

    Tumour eosinophilia is an uncommon but striking phenomenon which has been found in many tumours, mostly of large cell type or squamous differentiation. The incidence, appearance and importance of tumour eosinophilia in the bladder are described. Eosinophilia is commoner in deeply invasive tumours and in tumours showing squamous metaplasia. Transitional cell carcinomas with eosinophilia have a better prognosis than those without, but this improvement is not seen in squamous cell carcinomas of the bladder. When eosinophilia is found on superficial biopsies of a bladder tumour, the possibility of muscle invasion should be considered. PMID:6725595

  12. Pitfalls in colour photography of choroidal tumours.

    PubMed

    Schalenbourg, A; Zografos, L

    2013-02-01

    Colour imaging of fundus tumours has been transformed by the development of digital and confocal scanning laser photography. These advances provide numerous benefits, such as panoramic images, increased contrast, non-contact wide-angle imaging, non-mydriatic photography, and simultaneous angiography. False tumour colour representation can, however, cause serious diagnostic errors. Large choroidal tumours can be totally invisible on angiography. Pseudogrowth can occur because of artefacts caused by different methods of fundus illumination, movement of reference blood vessels, and flattening of Bruch's membrane and sclera when tumour regression occurs. Awareness of these pitfalls should prevent the clinician from misdiagnosing tumours and wrongfully concluding that a tumour has grown.

  13. PHD2 in tumour angiogenesis

    PubMed Central

    Chan, D A; Giaccia, A J

    2010-01-01

    Originally identified as the enzymes responsible for catalysing the oxidation of specific, conserved proline residues within hypoxia-inducible factor-1α (HIF-1α), the additional roles for the prolyl hydroxylase domain (PHD) proteins have remained elusive. Of the four identified PHD enzymes, PHD2 is considered to be the key oxygen sensor, as knockdown of PHD2 results in elevated HIF protein. Several recent studies have highlighted the importance of PHD2 in tumourigenesis. However, there is conflicting evidence as to the exact role of PHD2 in tumour angiogenesis. The divergence seems to be because of the contribution of stromal-derived PHD2, and in particular the involvement of endothelial cells, vs tumour-derived PHD2. This review summarises our current understanding of PHD2 and tumour angiogenesis, focusing on the influences of PHD2 on vascular normalisation and neovascularisation. PMID:20461086

  14. Tumour markers in breast cancer.

    PubMed Central

    Cove, D. H.; Woods, K. L.; Smith, S. C.; Burnett, D.; Leonard, J.; Grieve, R. J.; Howell, A.

    1979-01-01

    The clinical usefulness of 8 potential tumour markers has been evaluated in 69 patients with Stage I and II breast cancer and 57 patients with Stage III and IV. Serum CEA concentrations were raised in 13% of patients with local and 65% of those with advanced breast cancer. In patients with clinical evidence of progression or regression of tumour, serum CEA levels changed appropriately in 83% of cases. Taking 4 of the markers (carcinoembryonic antigen (CEA), lactalbumin, alpha subunit and haptoglobin) serum concentrations of one or more were raised in 33% of patients with local disease and 81% of those with advanced breast cancer. However, marker concentrations were often only marginally raised, and are unlikely to provide sensitive guide to tumour burden. CEA, lactalbumin and alpha subunit were detectable in 68%, 43% and 40% respectively of extracts of primary breast cancers. PMID:92331

  15. Impact of tumour volume on prediction of progression-free survival in sinonasal cancer

    PubMed Central

    Hennersdorf, Florian; Mauz, Paul-Stefan; Adam, Patrick; Welz, Stefan; Sievert, Anne; Ernemann, Ulrike; Bisdas, Sotirios

    2015-01-01

    Background The present study aimed to analyse potential prognostic factors, with emphasis on tumour volume, in determining progression free survival (PFS) for malignancies of the nasal cavity and the paranasal sinuses. Patients and methods Retrospective analysis of 106 patients with primary sinonasal malignancies treated and followed-up between March 2006 and October 2012. Possible predictive parameters for PFS were entered into univariate and multivariate Cox regression analysis. Kaplan-Meier curve analysis included age, sex, baseline tumour volume (based on MR imaging), histology type, TNM stage and prognostic groups according to the American Joint Committee on Cancer (AJCC) classification. Receiver operating characteristic (ROC) curve analysis concerning the predictive value of tumour volume for recurrence was also conducted. Results The main histological subgroup consisted of epithelial tumours (77%). The majority of the patients (68%) showed advanced tumour burden (AJCC stage III–IV). Lymph node involvement was present in 18 cases. The mean tumour volume was 26.6 ± 21.2 cm3. The median PFS for all patients was 24.9 months (range: 2.5–84.5 months). The ROC curve analysis for the tumour volume showed 58.1% sensitivity and 75.4% specificity for predicting recurrence. Tumour volume, AJCC staging, T- and N- stage were significant predictors in the univariate analysis. Positive lymph node status and tumour volume remained significant and independent predictors in the multivariate analysis. Conclusions Radiological tumour volume proofed to be a statistically reliable predictor of PFS. In the multivariate analysis, T-, N- and overall AJCC staging did not show significant prognostic value. PMID:26401135

  16. Tumour endothelial cells in high metastatic tumours promote metastasis via epigenetic dysregulation of biglycan

    PubMed Central

    Maishi, Nako; Ohba, Yusuke; Akiyama, Kosuke; Ohga, Noritaka; Hamada, Jun-ichi; Nagao-Kitamoto, Hiroko; Alam, Mohammad Towfik; Yamamoto, Kazuyuki; Kawamoto, Taisuke; Inoue, Nobuo; Taketomi, Akinobu; Shindoh, Masanobu; Hida, Yasuhiro; Hida, Kyoko

    2016-01-01

    Tumour blood vessels are gateways for distant metastasis. Recent studies have revealed that tumour endothelial cells (TECs) demonstrate distinct phenotypes from their normal counterparts. We have demonstrated that features of TECs are different depending on tumour malignancy, suggesting that TECs communicate with surrounding tumour cells. However, the contribution of TECs to metastasis has not been elucidated. Here, we show that TECs actively promote tumour metastasis through a bidirectional interaction between tumour cells and TECs. Co-implantation of TECs isolated from highly metastatic tumours accelerated lung metastases of low metastatic tumours. Biglycan, a small leucine-rich repeat proteoglycan secreted from TECs, activated tumour cell migration via nuclear factor-κB and extracellular signal–regulated kinase 1/2. Biglycan expression was upregulated by DNA demethylation in TECs. Collectively, our results demonstrate that TECs are altered in their microenvironment and, in turn, instigate tumour cells to metastasize, which is a novel mechanism for tumour metastasis. PMID:27295191

  17. Classification of binary intentions for individuals with impaired oculomotor function: ‘eyes-closed’ SSVEP-based brain-computer interface (BCI)

    NASA Astrophysics Data System (ADS)

    Lim, Jeong-Hwan; Hwang, Han-Jeong; Han, Chang-Hee; Jung, Ki-Young; Im, Chang-Hwan

    2013-04-01

    Objective. Some patients suffering from severe neuromuscular diseases have difficulty controlling not only their bodies but also their eyes. Since these patients have difficulty gazing at specific visual stimuli or keeping their eyes open for a long time, they are unable to use the typical steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems. In this study, we introduce a new paradigm for SSVEP-based BCI, which can be potentially suitable for disabled individuals with impaired oculomotor function. Approach. The proposed electroencephalography (EEG)-based BCI system allows users to express their binary intentions without needing to open their eyes. A pair of glasses with two light emitting diodes flickering at different frequencies was used to present visual stimuli to participants with their eyes closed, and we classified the recorded EEG patterns in the online experiments conducted with five healthy participants and one patient with severe amyotrophic lateral sclerosis (ALS). Main results. Through offline experiments performed with 11 participants, we confirmed that human SSVEP could be modulated by visual selective attention to a specific light stimulus penetrating through the eyelids. Furthermore, the recorded EEG patterns could be classified with accuracy high enough for use in a practical BCI system. After customizing the parameters of the proposed SSVEP-based BCI paradigm based on the offline analysis results, binary intentions of five healthy participants were classified in real time. The average information transfer rate of our online experiments reached 10.83 bits min-1. A preliminary online experiment conducted with an ALS patient showed a classification accuracy of 80%. Significance. The results of our offline and online experiments demonstrated the feasibility of our proposed SSVEP-based BCI paradigm. It is expected that our ‘eyes-closed’ SSVEP-based BCI system can be potentially used for communication of

  18. Cellular automata coupled with steady-state nutrient solution permit simulation of large-scale growth of tumours.

    PubMed

    Shrestha, Sachin Man Bajimaya; Joldes, Grand Roman; Wittek, Adam; Miller, Karol

    2013-04-01

    We model complete growth of an avascular tumour by employing cellular automata for the growth of cells and steady-state equation to solve for nutrient concentrations. Our modelling and computer simulation results show that, in the case of a brain tumour, oxygen distribution in the tumour volume may be sufficiently described by a time-independent steady-state equation without losing the characteristics of a time-dependent diffusion equation. This makes the solution of oxygen concentration in the tumour volume computationally more efficient, thus enabling simulation of tumour growth on a large scale. We solve this steady-state equation using a central difference method. We take into account the composition of cells and intercellular adhesion in addition to processes involved in cell cycle--proliferation, quiescence, apoptosis, and necrosis--in the tumour model. More importantly, we consider cell mutation that gives rise to different phenotypes and therefore a tumour with heterogeneous population of cells. A new phenotype is probabilistically chosen and has the ability to survive at lower levels of nutrient concentration and reproduce faster. We show that heterogeneity of cells that compose a tumour leads to its irregular growth and that avascular growth is not supported for tumours of diameter above 18 mm. We compare results from our growth simulation with existing experimental data on Ehrlich ascites carcinoma and tumour spheroid cultures and show that our results are in good agreement with the experimental findings.

  19. Update from the 4th Edition of the World Health Organization of Head and Neck Tumours: Tumours of the Oral Cavity and Mobile Tongue.

    PubMed

    Müller, Susan

    2017-03-01

    There have been several additions and deletions in Chapter 4 on Tumours of the oral cavity and mobile tongue in the 2017 fourth edition of the World Health Organization Classification of Tumours of the Head and Neck. This chapter excludes the oropharynx, which now is a stand-alone chapter acknowledging the uniqueness of the oropharynx from the oral cavity. New entries in Chapter 4 include rhabdomyoma, haemangioma, schwannoma, neurofibroma and myofibroblastic sarcoma in the section titled Soft tissue and neural tumours. Discussion of salivary gland entities have been reduced and includes mucoepidermoid carcinoma and pleomorphic adenoma as the other salivary gland types are discussed elsewhere. In the Haematolymphoid tumours section, like the salivary gland section, only tumors that commonly present in the oral cavity are discussed in Chapter 4. Excluded entities in the updated classification include papillary hyperplasia, median rhomboid glossitis, keratoacanthoma, focal oral mucinosis, and secondary tumors. This article will summarize the changes in the new classification since the 2005 edition focusing on selected entities that have had significant changes along with new entries.

  20. An Improved Tumour Temperature Measurement and Control Method for Superficial Tumour Ultrasound Hyperthermia Therapeutic System

    NASA Astrophysics Data System (ADS)

    Shen1, G. F.; Chen, Y. Z.; Ren, G. X.

    2006-10-01

    In tumour hyperthermia therapy, the research on measurement and control of tumour temperature is very important. Based on the hardware platform of superficial tumour ultrasound hyperthermia therapeutic system, an improved tumour temperature measurement and control method is presented in this paper. The experiment process, data and results are discussed in detail. The improved method will greatly reduce the pain and dread of the patients during the therapy period on the tumour temperature measurement and control by using the pinhead sensor.

  1. 'Primary extrarenal Wilms' tumour': rare presentation of a common paediatric tumour.

    PubMed

    Goel, Vandana; Verma, Amit Kumar; Batra, Vineeta; Puri, Sunil Kumar

    2014-06-06

    Wilms' tumour (nephroblastoma), the most common abdominal malignancy of childhood, occurs primarily as a malignant renal tumour. Extrarenal Wilms' tumour is rare with occasional reports from the Indian subcontinent. The various locations of extrarenal Wilms' tumour include retroperitoneum, uterus, skin and thorax. In this report we will discuss the imaging features highlighting the imaging differential diagnosis in a case of retroperitoneal (extrarenal) primary Wilms' tumour.

  2. Isolation of inflammatory cells from human tumours.

    PubMed

    Polak, Marta E

    2011-01-01

    Inflammatory cells are present in many tumours, and understanding their function is of increasing importance, particularly to studies of tumour immunology. The tumour-infiltrating leukocytes encompass a variety of cell types, e.g. T lymphocytes, macrophages, dendritic cells, NK cells, and mast cells. Choice of the isolation method greatly depends on the tumour type and the leukocyte subset of interest, but the protocol usually includes tissue disaggregation and cell enrichment. We recommend density centrifugation for initial enrichment, followed by specific magnetic bead negative or positive panning with leukocyte and tumour cell selective antibodies.

  3. [Malignant intracerebral nerve sheath tumours: Two case reports and complete review of the literature cases].

    PubMed

    Le Fèvre, C; Castelli, J; Perrin, C; Hénaux, P L; Noël, G

    2016-04-01

    Malignant peripheral nerve sheath tumours are extremely rare and can be associated with neurofibramatosis type 1. Their prognosis is poor and surgery remains the mainstay of therapy and should be the first line of treatment. Radiotherapy and chemotherapy are second line treatment and their effectiveness remains to demonstrate. The diagnosis is clinical, radiological, histological and immunohistochemical. Malignant peripheral nerve sheath tumours have a potential of local tumour recurrence very high and can metastasize. They often occur in extremity of the members but also rarely into brain. We report two cases of intracerebral nerve sheath tumour. The first was a 68-year-old woman who was admitted with progressive symptoms of headache and diplopia. A left frontotemporal malignant peripheral nerve sheath tumours was diagnosed and was treated by surgery and irradiation. Ten months later, she presented a local recurrence and spine bone's metastases were treated by vertebroplasty and irradiation. The patient died 15 months after the diagnosis. The second case was a 47-year-old woman who was referred because headache and vomiting symptoms. A right frontal malignant peripheral nerve sheath tumours was diagnosed and treated by surgery and irradiation. After that, the patient had three local recurrence operated and pulmonary and cranial bone's metastases. She was still alive after 20 months. We propose a literature review with 25 cases of intracerebral nerve sheath tumour identified, including the two current cases.

  4. Mesenteric gastrointestinal stromal tumour presenting as intracranial space occupying lesion

    PubMed Central

    Puri, Tarun; Gunabushanam, Gowthaman; Malik, Monica; Goyal, Shikha; Das, Anup K; Julka, Pramod K; Rath, Goura K

    2006-01-01

    Background Gastrointestinal stromal tumours (GIST) usually present with non-specific gastrointestinal symptoms such as abdominal mass, pain, anorexia and bowel obstruction. Methods We report a case of a 42 year old male who presented with a solitary intracranial space occupying lesion which was established as a metastasis from a mesenteric tumour. Results The patient was initially treated as a metastatic sarcoma, but a lack of response to chemotherapy prompted testing for CD117 which returned positive. A diagnosis of mesenteric GIST presenting as solitary brain metastasis was made, and the patient was treated with imatinib. Conclusion We recommend that all sarcomas with either an intraabdominal or unknown origin be routinely tested for CD117 to rule out GIST. PMID:17105654

  5. Hemi-dystonia secondary to localised basal ganglia tumour.

    PubMed Central

    Narbona, J; Obeso, J A; Tuñon, T; Martinez-Lage, J M; Marsden, C D

    1984-01-01

    An 8-year-old boy with an 18 month history of left limb hemi-dystonia due to a right lenticular nucleus astrocytoma originating in the putamen is reported. Subsequent neuropathological study demonstrated that the tumour was mainly localised to the right lenticular nucleus, with cystic necrosis in the infero-lateral putamen. Solid tumour also infiltrated the right hypothalamus, the anterior commisure and the optic chiasm, and there was perivascular spread into the globus pallidus, internal capsule and roof of the right lateral ventricle. This case, and the few other published reports of symptomatic dystonia due to focal brain lesions verified pathologically, indicate that damage to the lenticular nucleus, and to the putamen in particular, can cause limb dystonia in man. Images PMID:6747646

  6. A mechanically coupled reaction-diffusion model that incorporates intra-tumoural heterogeneity to predict in vivo glioma growth.

    PubMed

    Hormuth, David A; Weis, Jared A; Barnes, Stephanie L; Miga, Michael I; Rericha, Erin C; Quaranta, Vito; Yankeelov, Thomas E

    2017-03-01

    While gliomas have been extensively modelled with a reaction-diffusion (RD) type equation it is most likely an oversimplification. In this study, three mathematical models of glioma growth are developed and systematically investigated to establish a framework for accurate prediction of changes in tumour volume as well as intra-tumoural heterogeneity. Tumour cell movement was described by coupling movement to tissue stress, leading to a mechanically coupled (MC) RD model. Intra-tumour heterogeneity was described by including a voxel-specific carrying capacity (CC) to the RD model. The MC and CC models were also combined in a third model. To evaluate these models, rats (n = 14) with C6 gliomas were imaged with diffusion-weighted magnetic resonance imaging over 10 days to estimate tumour cellularity. Model parameters were estimated from the first three imaging time points and then used to predict tumour growth at the remaining time points which were then directly compared to experimental data. The results in this work demonstrate that mechanical-biological effects are a necessary component of brain tissue tumour modelling efforts. The results are suggestive that a variable tissue carrying capacity is a needed model component to capture tumour heterogeneity. Lastly, the results advocate the need for additional effort towards capturing tumour-to-tissue infiltration.

  7. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

    PubMed

    Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

    2016-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  8. Imaging biomarkers of angiogenesis and the microvascular environment in cerebral tumours

    PubMed Central

    Thompson, G; Mills, S J; Coope, D J; O’connor, J P B; Jackson, A

    2011-01-01

    Conventional contrast-enhanced CT and MRI are now in routine clinical use for the diagnosis, treatment and monitoring of diseases in the brain. The presence of contrast enhancement is a proxy for the pathological changes that occur in the normally highly regulated brain vasculature and blood-brain barrier. With recognition of the limitations of these techniques, and a greater appreciation for the nuanced mechanisms of microvascular change in a variety of pathological processes, novel techniques are under investigation for their utility in further interrogating the microvasculature of the brain. This is particularly important in tumours, where the reliance on angiogenesis (new vessel formation) is crucial for tumour growth, and the resulting microvascular configuration and derangement has profound implications for diagnosis, treatment and monitoring. In addition, novel therapeutic approaches that seek to directly modify the microvasculature require more sensitive and specific biological markers of baseline tumour behaviour and response. The currently used imaging biomarkers of angiogenesis and brain tumour microvascular environment are reviewed. PMID:22433824

  9. Notch as a tumour suppressor.

    PubMed

    Nowell, Craig S; Radtke, Freddy

    2017-03-01

    The Notch signalling cascade is an evolutionarily conserved pathway that has a crucial role in regulating development and homeostasis in various tissues. The cellular processes and events that it controls are diverse, and continued investigation over recent decades has revealed how the role of Notch signalling is multifaceted and highly context dependent. Consistent with the far-reaching impact that Notch has on development and homeostasis, aberrant activity of the pathway is also linked to the initiation and progression of several malignancies, and Notch can in fact be either oncogenic or tumour suppressive depending on the tissue and cellular context. The Notch pathway therefore represents an important target for therapeutic agents designed to treat many types of cancer. In this Review, we focus on the latest developments relating specifically to the tumour-suppressor activity of Notch signalling and discuss the potential mechanisms by which Notch can inhibit carcinogenesis in various tissues. Potential therapeutic strategies aimed at restoring or augmenting Notch-mediated tumour suppression will also be highlighted.

  10. Radiotherapy alone for local tumour control in esthesioneuroblastoma.

    PubMed

    Benfari, G; Fusconi, M; Ciofalo, A; Gallo, A; Altissimi, G; Celani, T; De Vincentiis, M

    2008-12-01

    Esthesioneuroblastoma is an uncommon tumour. Due to its low incidence, this neoplasm is difficult to evaluate and its treatment remains a matter of debate. Although the role of post-operative radiation is relatively well-defined, little is reported regarding the role of radiotherapy as the only treatment modality. A retrospective analysis of the literature has been conducted. With reference to the treatment of esthesioneuroblastoma, 55 patients submitted only to radiotherapy have been selected from publications of internationally indexed literature between 1979 and 2006. According to the Kadish classification, 6 patients were in stage A, 12 in stage B, and 37 in stage C. Response to therapy for each stage was assessed. There was no evidence of disease in: 6/6 stage A patients with a median follow-up period of 103.6 months, 7/12 stage B patients with a median followup period of 120 months, and 7/37 stage C patients with a median follow-up period of 77.3 months. A total of 27 patients died due to tumour-related causes and 5 due to intercurrent disease, while 3 patients were alive with disease (local recurrence and cervical lymph node metastasis). In conclusion, esthesioneuroblastoma is a malignant tumour which grows both locoregionally and distantly. For this reason, despite the satisfying results regarding response to radiotherapy alone in stage A patients, irradiation should be used only in early lesions arising below the cribriform plate, whereas all other cases require aggressive and multimodal therapy.

  11. Resistance to tumour challenge after tumour laser thermotherapy is associated with a cellular immune response

    PubMed Central

    Ivarsson, K; Myllymäki, L; Jansner, K; Stenram, U; Tranberg, K-G

    2005-01-01

    Previous studies in our laboratory have shown that interstitial laser thermotherapy (ILT) of an experimental liver tumour is superior to surgical excision, at least partly due to a laser-induced immunological effect. The aim of the present study was to investigate the time–response relationship of the ILT-induced immunisation and the cellular response of macrophages and lymphocytes. A dimethylhydrazine-induced adenocarcinoma was transplanted into the liver of syngeneic rats. Rats with tumour were treated 6–8 days later (tumour size 0.25–0.40 cm3) with ILT of tumour or resection of the tumour-bearing lobe. Two groups of rats without tumour were treated with resection of a normal liver lobe or ILT of normal liver. A challenging tumour was implanted into the liver of each rat 2, 5 or 10 weeks after primary treatment. Rats were killed 6, 12 and 48 days (or earlier due to their condition) after challenge (n=8 in all groups). Immunohistochemical techniques were used to determine lymphocytes (CD8, CD4) and macrophages (ED1, ED2) in rats having had treatment of a primary tumour. Interstitial laser thermotherapy of the first tumour was followed by eradication of challenging tumour and absence of tumour spread. This contrasted with rapid growth and spread of challenging tumour in the other groups. In the challenging vital tumour tissue and in the interface between the tumour and surroundings, the number of ED1 macrophages and CD8 lymphocytes was higher in rats having been treated with the ILT of tumour than in those having undergone resection of the tumour-bearing lobe. The number of ED2 macrophages and CD4 lymphocytes was low and did not vary between these two groups. Interstitial laser thermotherapy elicited an immune response that eradicated a challenging tumour and was associated with increased numbers of tumour-infiltrating macrophages and CD8 lymphocytes. PMID:16091763

  12. PET imaging of primary mediastinal tumours.

    PubMed Central

    Kubota, K.; Yamada, S.; Kondo, T.; Yamada, K.; Fukuda, H.; Fujiwara, T.; Ito, M.; Ido, T.

    1996-01-01

    Mediastinal masses include a wide variety of tumours and remain an interesting diagnostic challenge for radiologist. We performed positron emission tomography (PET) studies of primary mediastinal tumours in order to predict the malignancy of these tumours preoperatively. Twenty-two patients with primary mediastinal tumours were studied with PET using 2-deoxy-2-[18F]fluoro-D-glucose (FDG). The histological findings of surgical pathology or biopsy, or mediastinoscopy were compared with those of computerised tomography (CT) and PET. PET images were evaluated semiquantitatively using the differential uptake ratio (DUR). Increased FDG uptake was observed in nine of ten patients with malignant tumours, including thymic carcinomas, lymphomas, invasive thymomas and a case of sarcoidosis. A moderate level of FDG uptake was found in a myeloma, non-invasive thymomas, and a schwannoma, whereas a low uptake was observed in a teratoma and various benign cysts. The mean FDG uptake of malignant tumours was significantly higher than that of benign tumours. Both thymic cancer and invasive thymoma showed a high FDG uptake. CT examination resulted in three false-negative and two false-positive cases when used in predicting tumour invasion, while PET was associated with a false-positive and a false-negative case. In conclusion, the use of FDG with PET is clinically helpful in evaluating the malignant nature of primary mediastinal tumours. Our results also suggest that a high FDG uptake reflects the invasiveness of malignant nature of thymic tumours. Images Figure 1 Figure 2 PMID:8611400

  13. Gene expression profiling of human ovarian tumours

    PubMed Central

    Biade, S; Marinucci, M; Schick, J; Roberts, D; Workman, G; Sage, E H; O'Dwyer, P J; LiVolsi, V A; Johnson, S W

    2006-01-01

    There is currently a lack of reliable diagnostic and prognostic markers for ovarian cancer. We established gene expression profiles for 120 human ovarian tumours to identify determinants of histologic subtype, grade and degree of malignancy. Unsupervised cluster analysis of the most variable set of expression data resulted in three major tumour groups. One consisted predominantly of benign tumours, one contained mostly malignant tumours, and one was comprised of a mixture of borderline and malignant tumours. Using two supervised approaches, we identified a set of genes that distinguished the benign, borderline and malignant phenotypes. These algorithms were unable to establish profiles for histologic subtype or grade. To validate these findings, the expression of 21 candidate genes selected from these analyses was measured by quantitative RT–PCR using an independent set of tumour samples. Hierarchical clustering of these data resulted in two major groups, one benign and one malignant, with the borderline tumours interspersed between the two groups. These results indicate that borderline ovarian tumours may be classified as either benign or malignant, and that this classifier could be useful for predicting the clinical course of borderline tumours. Immunohistochemical analysis also demonstrated increased expression of CD24 antigen in malignant versus benign tumour tissue. The data that we have generated will contribute to a growing body of expression data that more accurately define the biologic and clinical characteristics of ovarian cancers. PMID:16969345

  14. Gene expression profiling of human ovarian tumours.

    PubMed

    Biade, S; Marinucci, M; Schick, J; Roberts, D; Workman, G; Sage, E H; O'Dwyer, P J; Livolsi, V A; Johnson, S W

    2006-10-23

    There is currently a lack of reliable diagnostic and prognostic markers for ovarian cancer. We established gene expression profiles for 120 human ovarian tumours to identify determinants of histologic subtype, grade and degree of malignancy. Unsupervised cluster analysis of the most variable set of expression data resulted in three major tumour groups. One consisted predominantly of benign tumours, one contained mostly malignant tumours, and one was comprised of a mixture of borderline and malignant tumours. Using two supervised approaches, we identified a set of genes that distinguished the benign, borderline and malignant phenotypes. These algorithms were unable to establish profiles for histologic subtype or grade. To validate these findings, the expression of 21 candidate genes selected from these analyses was measured by quantitative RT-PCR using an independent set of tumour samples. Hierarchical clustering of these data resulted in two major groups, one benign and one malignant, with the borderline tumours interspersed between the two groups. These results indicate that borderline ovarian tumours may be classified as either benign or malignant, and that this classifier could be useful for predicting the clinical course of borderline tumours. Immunohistochemical analysis also demonstrated increased expression of CD24 antigen in malignant versus benign tumour tissue. The data that we have generated will contribute to a growing body of expression data that more accurately define the biologic and clinical characteristics of ovarian cancers.

  15. Diagnosing tumours on routine surgical sections by immunohistochemistry: use of cytokeratin, common leucocyte, and other markers.

    PubMed Central

    Poston, R N; Sidhu, Y S

    1986-01-01

    Tumours of uncertain tissue of origin were investigated by immunohistochemistry on formalin fixed paraffin embedded sections. Two antibodies--PD7/26, an anti common leucocyte antigen, and CAM5.2, an anticytokeratin--recognised most lymphomas and carcinomas, respectively: 88% of these tumours were identified by the two antibodies alone. These antibodies permitted the separation of the cases into groups: positive with CAM5.2, positive with PD7/26, and a third comprising those negative with both. The negative group contained other tumours and a small number of carcinomas and lymphomas; many of the lymphomas were, apparently, of histiocytic origin. Comparison of CAM5.2 with other epithelial markers showed that it was the most effective. Some further classification of the tumours was carried out with a panel of organ and cell specific antibodies: mesotheliomas were recognised by their pattern of reactivity with epithelial markers. Overall, the tumour type was determined in 90% of cases. Immunohistochemistry performed as described can be a potent aid to the diagnostic histopathology of tumours. Images PMID:2424934

  16. [The probability of developing brain tumours among users of cellular telephones (scientific information to the decision of the International Agency for Research on Cancer (IARC) announced on May 31, 2011)].

    PubMed

    Grigor'ev, Iu G

    2011-01-01

    The WHO's International Agency for Research on Cancer (IARC) has made May 31 2011 PRESS RELEASE No 208 which classifies radiofrequency electromagnetic fields as possibly carcinogenic to humans (Group 2B). The decision is based on an increased risk of glioma, i.e., a malignant type of brain cancer associated with the wireless phone use. This paper reports the analysis of the long-term research on the issue in question that had been carried out in many countries around the world before the decision was made.

  17. Mobile phones and head tumours. The discrepancies in cause-effect relationships in the epidemiological studies - how do they arise?

    PubMed Central

    2011-01-01

    Background Whether or not there is a relationship between use of mobile phones (analogue and digital cellulars, and cordless) and head tumour risk (brain tumours, acoustic neuromas, and salivary gland tumours) is still a matter of debate; progress requires a critical analysis of the methodological elements necessary for an impartial evaluation of contradictory studies. Methods A close examination of the protocols and results from all case-control and cohort studies, pooled- and meta-analyses on head tumour risk for mobile phone users was carried out, and for each study the elements necessary for evaluating its reliability were identified. In addition, new meta-analyses of the literature data were undertaken. These were limited to subjects with mobile phone latency time compatible with the progression of the examined tumours, and with analysis of the laterality of head tumour localisation corresponding to the habitual laterality of mobile phone use. Results Blind protocols, free from errors, bias, and financial conditioning factors, give positive results that reveal a cause-effect relationship between long-term mobile phone use or latency and statistically significant increase of ipsilateral head tumour risk, with biological plausibility. Non-blind protocols, which instead are affected by errors, bias, and financial conditioning factors, give negative results with systematic underestimate of such risk. However, also in these studies a statistically significant increase in risk of ipsilateral head tumours is quite common after more than 10 years of mobile phone use or latency. The meta-analyses, our included, examining only data on ipsilateral tumours in subjects using mobile phones since or for at least 10 years, show large and statistically significant increases in risk of ipsilateral brain gliomas and acoustic neuromas. Conclusions Our analysis of the literature studies and of the results from meta-analyses of the significant data alone shows an almost doubling of

  18. Expression of doublecortin in tumours of the central and peripheral nervous system and in human non-neuronal tissues.

    PubMed

    Bernreuther, Christian; Salein, Nora; Matschke, Jakob; Hagel, Christian

    2006-03-01

    Doublecortin is a microtubule-associated phosphoprotein involved in neuronal migration and differentiation expressed in migrating neuroblasts in the central nervous system. We systematically analysed doublecortin expression in 179 tumours of the central and 65 tumours of peripheral nervous system as well as in 74 different non-neuronal tissues to evaluate the specificity of doublecortin as a marker for neuronal differentiation in glioneuronal tumours. Glioneuronal tumours and oligodendrogliomas grade II and III uniformly showed a high intensity and frequency of doublecortin staining, whereas intermediate doublecortin expression was observed in astrocytic tumours of grade II-IV. In pilocytic astrocytomas and ependymomas only scattered doublecortin positive cells were detected. In the peripheral nervous system, doublecortin expression was found in neurofibroma but was absent in schwannoma. Double staining of tumour tissue revealed co-expression of doublecortin and neurofilament in cells of gangliocytomas and gangliogliomas and co-expression of doublecortin with S100 protein or GFAP in glial tumours, respectively. In a tissue array comprised of 74 different normal non-neuronal human tissues, doublecortin expression was demonstrated in epithelia of the kidney, liver, salivary glands and duodenum among others. Interestingly, doublecortin expression could not be shown in brain metastases of tumours originating from these tissues. Immunohistochemical data was further corroborated by Western blot analysis and reverse transcription polymerase chain reaction. In conclusion, doublecortin can be regarded as specific neuronal marker only in normal developing brain, but lacks specificity in glioneuronal and glial tumours and other non-neuronal human tissues where it is expressed in a wide variety of tumours and tissues.

  19. Surgical treatment of benign endobronchial tumours

    PubMed Central

    Halttunen, P; Meurala, H; Standertskjöld-Nordenstam, C-G

    1982-01-01

    Four cases of benign endobronchial tumour are reported which were successfully treated by bronchial resection. In two cases (of fibroma and leiomyoma respectively) a cylinder of bronchus alone was resected; in one case (lipoma) a healthy right upper lobe was preserved by a bronchoplastic procedure and in the other (chondroma) the tumour was removed with the right lower lobe, which was irreversibly damaged. It is important to recognise that such tumours are unsuitable for treatment by endoscopic means alone. Images PMID:7157223

  20. Tumour promotion versus tumour suppression in chronic hepatic iron overload.

    PubMed

    Bloomer, Steven A; Brown, Kyle E

    2015-06-01

    Although iron-catalysed oxidative damage is presumed to be a major mechanism of injury leading to cirrhosis and hepatocellular carcinoma in hemochromatosis, these events have been difficult to recapitulate in an animal model. In this study, we evaluated regulators of hepatocarcinogenesis in a rodent model of chronic iron overload. Sprague-Dawley rats were iron loaded with iron dextran over 6 months. Livers were harvested and analysed for markers of oxidative stress, as well as the following proteins: p53, murine double minute 2, the Shc proteins p66, p52, p46; β-catenin, CHOP, C/EBPα and Yes-associated protein. In this model, iron loading is associated with hepatocyte proliferation, and indices of oxidative damage are mildly increased in tandem with augmented antioxidant defenses. Alterations potentially favouring carcinogenesis included a modest but significant decrease in p53 levels and increases in p52, p46 and β-catenin levels compared with control livers. Countering these factors, the iron-loaded livers demonstrated a significant decrease in CHOP, which has recently been implicated in the development of hepatocellular carcinoma, as well as a reciprocal increase in C/EBPα and decrease in Yes-associated protein. Our results suggest that chronic iron overload elicits both tumour suppressive as well as tumour-promoting mechanisms in rodent liver.

  1. Endovascular treatment of primary hepatic tumours

    PubMed Central

    Popiel, M; Gulie, L; Turculeţ, C; Beuran, M

    2008-01-01

    First transcatheter embolization of hepatic artery has been materializing in 1974, in France, for unresectable hepatic tumours. Then, this treatment has become use enough in many countries, especially in Japan, where primary hepatic tumours are very frequent. In this article, we present procedures of interventional endovascular treatment for primary hepatic tumours: chemoembolization, intra–arterial chemotherapy. The study comprises patients with primary hepatic tumours investigated by hepatic–ultrasound and contrast–enhanced CT or MRI. DSA–hepatic angiography is very important to verify the accessory hepatic supply. It has been performed selective catheterization of right/left hepatic branches followed by cytostatics injection. Most of the patients have benefit by hepatic chemoembolization (cytostatics, Lipiodol and embolic materials). The selective intra–arterial chemotherapy (cytostatics without Lipiodol) was performing in cases with contraindications for Lipiodol or embolic materials injection (cirrhosis–Child C, thrombosis of portal vein, hepatic insufficiency). For treatment of primary hepatic tumours we use 5–F–Uracil, Farmarubicin and Mytomicin C. Less numbers of the reservoirs were placed because financial causes. Chemoembolization was better than procedures without Lipiodol or embolic materials. Lipiodol reached in tumoural tissue and the distribution of Lipiodol harmonises with degree of vascularisation. After the chemoembolization procedure, the diameter of tumours decreased gradually depending on the size of tumour. Effective alternative for unresectable primary hepatic tumours (big size, hepatic dysfunction, and other surgical risk factors) is endovascular interventional treatment. PMID:20108517

  2. Histogenesis of ovarian malignant mixed mesodermal tumours.

    PubMed Central

    Clarke, T J

    1990-01-01

    The histogenesis of ovarian malignant mixed mesodermal tumours, which includes the concept of metaplastic carcinoma, is controversial. Four such tumours were examined for evidence of metaplastic transition from carcinoma to sarcoma using morphology and reticulin stains. Consecutive sections were stained immunohistochemically using cytokeratin and vimentin to determine whether cells at the interface between carcinoma and sarcoma expressed both cytokeratin and vimentin. There was no evidence of morphological, architectural, or immunohistochemical transitions from carcinoma to sarcoma in the four tumours studied. This suggests that ovarian malignant mixed mesodermal tumours are not metaplastic carcinomas but are composed of histogenetically different elements. Images PMID:2160478

  3. [Mobile phones and head tumours: it is time to read and highlight data in a proper way].

    PubMed

    Levis, Angelo G; Minicucci, Nadia; Ricci, Paolo; Gennaro, Valerio; Garbisa, Spiridione

    2011-01-01

    The uncertainty about the relationship between the use of mobile phones (MPs: analogue and digital cellulars, and cordless) and the increase of head tumour risk can be solved by a critical analysis of the methodological elements of both the positive and the negative studies. Results by Hardell indicate a cause/effect relationship: exposures for or latencies from ≥ 10 years to MPs increase by up to 100% the risk of tumour on the same side of the head preferred for phone use (ipsilateral tumours) - which is the only one significantly irradiated - with statistical significance for brain gliomas, meningiomas and acoustic neuromas. On the contrary, studies published under the Interphone project and others produced negative results and are characterised by the substantial underestimation of the risk of tumour. However, also in the Interphone studies a clear and statistically significant increase of ipsilateral head tumours (gliomas, neuromas and parotid gland tumours) is quite common in people having used MPs since or for ≥ 10 years. And also the metaanalyses by Hardell and other Authors, including only the literature data on ipsilateral tumours in people having used MPs since or for ≥ 10 years - and so also part of the Interphone data - still show statistically significant increases of head tumours.

  4. Clinico-pathological characteristics of different types of immunodeficiency-associated smooth muscle tumours.

    PubMed

    Hussein, Kais; Rath, Berenice; Ludewig, Britta; Kreipe, Hans; Jonigk, Danny

    2014-09-01

    Rare Epstein-Barr virus (EBV)+ smooth muscle tumours (SMT) manifest typically under immunosuppression. Three major subtypes are known: human immunodeficiency virus-associated (HIV-SMT), after transplantation (PTSMT) or associated with congenital immunodeficiency syndromes (CI-SMT). So far, there are no analyses which compare the clinico-pathological characteristics of all three subtypes. Case reports and case series on these three tumour types were collected (1990-2012). Meta-data analysis was performed for identification of similarities and differences. A total of 73 HIV-SMT, 66 PTSMT and 9 CI-SMT were evaluated. There was a slight female predominance (55-67%). Children were affected nearly equally in HIV-SMT (33%) and PTSMT (35%), while all CI-SMT occurred in children. HIV-SMT manifested preferentially in the central nervous system, gut/liver, skin, lungs/larynx/pharynx and adrenal glands. PTSMT were predominantly found in the liver, lungs/larynx/pharynx, gut/spleen and brain. CI-SMT were often found in lungs/larynx, brain, liver, adrenal glands and spleen. Antecedent EBV+ lymphoproliferations manifested more often in PTSMT. In all three tumour subtypes, survival analyses did not show any significant differences regarding surgical therapeutic approaches, the occurrence of multiple tumours, tumour size or sarcoma-like histological features. HIV-SMT had the poorest overall survival, which might be attributed to HIV-associated infectious complications.

  5. Transillumination imaging of intraocular tumours.

    PubMed

    Kjersem, Bård; Krohn, Jørgen

    2013-06-01

    The purpose of this paper is to discuss a recently described modification of a standard photo slit lamp system for ocular transillumination, with special emphasis on the light transmission through the eye wall and the photographic technique. Transillumination photography was carried out with the Haag-Streit Photo-Slit Lamp BX 900 (Haag-Streit AG, Koeniz, Switzerland). After having released the background lighting optic fibre cable from its holder, the patient was positioned at the slit lamp, and the fibre tip was gently pressed against the sclera or the cornea of the patient's eye. During about 1/1000 of a second, the eye was illuminated by the flash and the scleral shadow of the tumour was exposed to the camera sensor. The images were of good diagnostic quality, making it easy to outline the tumours and to evaluate the involvement of intraocular structures. None of the examined patients experienced discomfort or negative side effects. The method is recommended in cases where photographic transillumination documentation of intraocular pathologies is considered important.

  6. Gastrointestinal Stromal Tumours: An Update

    PubMed Central

    Somerhausen, Nicolas De Saint Aubain

    1998-01-01

    Purpose. To study the evolution of concepts concerning gastrointestinal stromal tumours (GISTs) over 30 years. Discussion. GISTs have been, for more than 30 years, the subject of considerable controversy regarding their line of differentiation as well as the prediction of their behaviour. Furthermore, once they spread within the peritoneal cavity, they are extremely hard to control. The recent findings of c-Kit mutations and the immunohistochemical detection of the product of this gene, KIT or CD117, in the mainly non-myogenic subset of this family of tumours, has led to a reappraisal of this group of lesions, which, with some exceptions, is now thought to be derived from the interstitial cells of Cajal, and this has facilitated a clearer definition of their pathological spectrum. In this article, we review chronologically the evolution of the concept of GIST with the gradual application of electron microscopy, immunohistochemistry, DNA ploidy analysis. We discuss the impact of these techniques on the pathological assessment and clinical management of GISTs. PMID:18521245

  7. FDG uptake, a surrogate of tumour hypoxia?

    PubMed Central

    Van de Wiele, Christophe

    2008-01-01

    Introduction Tumour hyperglycolysis is driven by activation of hypoxia-inducible factor-1 (HIF-1) through tumour hypoxia. Accordingly, the degree of 2-fluro-2-deoxy-d-glucose (FDG) uptake by tumours might indirectly reflect the level of hypoxia, obviating the need for more specific radiopharmaceuticals for hypoxia imaging. Discussion In this paper, available data on the relationship between hypoxia and FDG uptake by tumour tissue in vitro and in vivo are reviewed. In pre-clinical in vitro studies, acute hypoxia was consistently shown to increase FDG uptake by normal and tumour cells within a couple of hours after onset with mobilisation or modification of glucose transporters optimising glucose uptake, followed by a delayed response with increased rates of transcription of GLUT mRNA. In pre-clinical imaging studies on chronic hypoxia that compared FDG uptake by tumours grown in rat or mice to uptake by FMISO, the pattern of normoxic and hypoxic regions within the human tumour xenografts, as imaged by FMISO, largely correlated with glucose metabolism although minor locoregional differences could not be excluded. In the clinical setting, data are limited and discordant. Conclusion Further evaluation of FDG uptake by various tumour types in relation to intrinsic and bioreductive markers of hypoxia and response to radiotherapy or hypoxia-dependent drugs is needed to fully assess its application as a marker of hypoxia in the clinical setting. PMID:18509637

  8. Cerebrospinal fluid rhinorrhoea in pituitary tumours1

    PubMed Central

    Cole, I E; Keene, Malcolm

    1980-01-01

    Three cases of CSF rhinorrhoea due to pituitary tumours are reported and the literature reviewed. The treatment of choice appears to be trans-sphenoidal exploration of the pituitary fossa with insertion of a free muscle graft followed by radiotherapy. The probability of the tumour being a prolactin-secreting adenoma is discussed. PMID:7017123

  9. Skull metastasis from rectal gastrointestinal stromal tumours.

    PubMed

    Gil-Arnaiz, Irene; Martínez-Trufero, Javier; Pazo-Cid, Roberto Antonio; Felipo, Francesc; Lecumberri, María José; Calderero, Verónica

    2009-09-01

    Gastrointestinal stromal tumours (GIST) are the most common mesenchymal neoplasm of the gastrointestinal tract. Rectum localisation is infrequent for these neoplasms, accounting for about 5% of all cases. Distant metastases of GIST are also rare. We present a patient with special features: the tumour is localised in rectum and it has an uncommon metastatic site, the skull, implying a complex differential diagnosis approach.

  10. [Single-cell sequencing and tumour heterogeneity].

    PubMed

    Jordan, Bertrand

    2014-12-01

    The heterogeneity of tumours is now beginning to be documented precisely by single-cell new-generation sequencing. Recently published results on breast tumours show that each of the cells analysed displays a unique pattern of point mutations. This extensive genetic diversity is present before any treatment, and is likely to cause resistance to initially successful targeted therapies.

  11. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

    PubMed

    Louis, David N; Perry, Arie; Reifenberger, Guido; von Deimling, Andreas; Figarella-Branger, Dominique; Cavenee, Webster K; Ohgaki, Hiroko; Wiestler, Otmar D; Kleihues, Paul; Ellison, David W

    2016-06-01

    The 2016 World Health Organization Classification of Tumors of the Central Nervous System is both a conceptual and practical advance over its 2007 predecessor. For the first time, the WHO classification of CNS tumors uses molecular parameters in addition to histology to define many tumor entities, thus formulating a concept for how CNS tumor diagnoses should be structured in the molecular era. As such, the 2016 CNS WHO presents major restructuring of the diffuse gliomas, medulloblastomas and other embryonal tumors, and incorporates new entities that are defined by both histology and molecular features, including glioblastoma, IDH-wildtype and glioblastoma, IDH-mutant; diffuse midline glioma, H3 K27M-mutant; RELA fusion-positive ependymoma; medulloblastoma, WNT-activated and medulloblastoma, SHH-activated; and embryonal tumour with multilayered rosettes, C19MC-altered. The 2016 edition has added newly recognized neoplasms, and has deleted some entities, variants and patterns that no longer have diagnostic and/or biological relevance. Other notable changes include the addition of brain invasion as a criterion for atypical meningioma and the introduction of a soft tissue-type grading system for the now combined entity of solitary fibrous tumor / hemangiopericytoma-a departure from the manner by which other CNS tumors are graded. Overall, it is hoped that the 2016 CNS WHO will facilitate clinical, experimental and epidemiological studies that will lead to improvements in the lives of patients with brain tumors.

  12. p53 tumour suppressor gene expression in pancreatic neuroendocrine tumour cells.

    PubMed Central

    Bartz, C; Ziske, C; Wiedenmann, B; Moelling, K

    1996-01-01

    Neuroendocrine pancreatic tumours grow slower and metastasise later than ductal and acinar carcinomas. The expression of the p53 tumour suppressor gene in pancreatic neuroendocrine tumour cells is unknown. Pancreatic neuroendocrine cell lines (n = 5) and human tumour tissues (n = 19) were studied for changed p53 coding sequence, transcription, and translation. Proliferative activity of tumour cells was determined analysing Ki-67 expression. No mutation in the p53 nucleotide sequence of neuroendocrine tumour cell was found. However, an overexpression of p53 could be detected in neuroendocrine pancreatic tumour cell lines at a protein level. As no p53 mutations were seen, it is suggested that post-translational events can also lead to an overexpression of p53. Images Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 PMID:8675094

  13. Training for planning tumour resection: augmented reality and human factors.

    PubMed

    Abhari, Kamyar; Baxter, John S H; Chen, Elvis C S; Khan, Ali R; Peters, Terry M; de Ribaupierre, Sandrine; Eagleson, Roy

    2015-06-01

    Planning surgical interventions is a complex task, demanding a high degree of perceptual, cognitive, and sensorimotor skills to reduce intra- and post-operative complications. This process requires spatial reasoning to coordinate between the preoperatively acquired medical images and patient reference frames. In the case of neurosurgical interventions, traditional approaches to planning tend to focus on providing a means for visualizing medical images, but rarely support transformation between different spatial reference frames. Thus, surgeons often rely on their previous experience and intuition as their sole guide is to perform mental transformation. In case of junior residents, this may lead to longer operation times or increased chance of error under additional cognitive demands. In this paper, we introduce a mixed augmented-/virtual-reality system to facilitate training for planning a common neurosurgical procedure, brain tumour resection. The proposed system is designed and evaluated with human factors explicitly in mind, alleviating the difficulty of mental transformation. Our results indicate that, compared to conventional planning environments, the proposed system greatly improves the nonclinicians' performance, independent of the sensorimotor tasks performed ( ). Furthermore, the use of the proposed system by clinicians resulted in a significant reduction in time to perform clinically relevant tasks ( ). These results demonstrate the role of mixed-reality systems in assisting residents to develop necessary spatial reasoning skills needed for planning brain tumour resection, improving patient outcomes.

  14. Canine mammary tumour cell lines established in vitro.

    PubMed

    Hellmén, E

    1993-01-01

    Mammary tumours are the most common tumours in the female dog. The tumours have a complex histology and exist in epithelial, mixed and mesenchymal forms. To study the biology of canine mammary tumours, five cell lines have been established and characterized. The results indicate that canine mammary tumours might be derived from mammary stem cells and that the tumour growth is independent of oestrogens. The established canine mammary tumour cell lines will be valuable tools in further studies of the histogenesis and pathogenesis of these tumours.

  15. Adult Wilms' Tumour: Case Report and Review of Literature.

    PubMed

    Modi, Sunny; Tiang, Kor Woi; Inglis, Po; Collins, Stuart

    2016-01-01

    Wilms' tumour (nephroblastoma) is the most common renal tumour in children. Wilms' tumour in adults is extremely rare and has a poorer prognosis than paediatric Wilms' tumour. It is difficult to differentiate adult Wilms' tumour from renal cell carcinoma based on radiological findings alone. The diagnosis in adults is often serendipitous following nephrectomy for presumed renal cell carcinoma. Because of the paucity of literature, there are no standard protocols for the management of adult Wilms' tumour, and therefore, it is managed as per paediatric Wilms' tumour. Herein, we report the case of adult Wilms' tumour in a 43-year-old man, which was diagnosed unexpectedly following nephrectomy for presumed renal cell carcinoma.

  16. Adamantinoma: an unusual bone tumour.

    PubMed

    Roque, Pedro; Mankin, Henry J; Rosenberg, Andrew

    2008-12-01

    Adamantinoma is a rare tumour, which most often affects the tibia and produces lytic and sometimes destructive lesions, which can cause fractures. The lesions occur principally in adults and are more common in males. A small percentage of the patients develop metastases, sometimes quite late in the course. Our institution has treated 42 patients with adamantinomas since 1972 and has evaluated them by imaging studies and histology. The majority of the patients were treated by resection of the lesion and insertion of an intercalary allograft. Only three of the patients died of disease with the time until death ranging from 10 to 17 years. Recurrence occurred in only three patients and the allograft success rate in terms of function was 71% at a mean time of 10 years.

  17. Overview and recent advances in neuropathology. Part 1: Central nervous system tumours.

    PubMed

    Robertson, Thomas; Koszyca, Barbara; Gonzales, Michael

    2011-02-01

    This review highlights the recent changes to the World Health Organization (WHO) 4th edition of the classification of central nervous system tumours. The mixed glial and neuronal tumour group continues to expand to encompass three new subtypes of glioneuronal tumours. The main diagnostic points differentiating these tumours are covered. Also covered is an update on issues relating to grading of astrocytic, oligodendroglial and pineal tumours and the recent molecular subtypes observed in medulloblastomas. The theme of molecular genetics is continued in the following section where the four subtypes in the molecular subclassification of glioblastoma; classical, mesenchymal, proneural and neural are outlined. The genetic profile of these subtypes is highlighted as is their varying biological responses to adjuvant therapies. The relationship between chromosome 1p and 19q deletions and treatment responsive oligodendrogliomas is discussed, as are the newer advances relating to silencing of the MGMT gene in astrocytomas and mutations in the IDH-1 gene in both astrocytomas and oligodendrogliomas. The final section in this article provides an update on the concept of glioma stem cells.

  18. Transsphenoidal surgery for pituitary tumours

    PubMed Central

    Massoud, A; Powell, M; Williams, R; Hindmarsh, P; Brook, C

    1997-01-01

    Accepted 29 January 1997
 OBJECTIVES—Transsphenoidal surgery (TSS) is the preferred method for the excision of pituitary microadenomas in adults. This study was carried out to establish the long term efficacy and safety of TSS in children.
STUDY DESIGN—A 14 year retrospective analysis was carried out on 23 children (16 boys and seven girls), all less than 18 years of age, who had undergone TSS at our centre.
RESULTS—Twenty nine transsphenoidal surgical procedures were carried out. The most common diagnosis was an adrenocorticotrophic hormone (ACTH) secreting adenoma (14 (61%) patients). The median length of follow up was 8.0 years (range 0.3-14.0 years). Eighteen (78%) patients were cured after the first procedure. No death was related to the operation. The most common postoperative complication was diabetes insipidus, which was transient in most patients. Other complications were headaches in two patients and cerebrospinal fluid leaks in two patients. De novo endocrine deficiencies after TSS in children were as follows: three (14%) patients developed panhypopituitarism, eight (73%) developed growth hormone insufficiency, three (14%) developed secondary hypothyroidism, and four (21%) developed gonadotrophin deficiency. Permanent ACTH deficiency occurred in five (24%) patients, though all patients received postoperative glucocorticoid treatment until dynamic pituitary tests were performed three months after TSS.
CONCLUSIONS—TSS in children is a safe and effective treatment for pituitary tumours, provided it is performed by surgeons with considerable experience and expertise. Surgical complications are minimal. Postoperative endocrine deficit is considerable, but is only permanent in a small proportion of patients.

 • Transsphenoidal surgery is a safe and effective treatment for pituitary tumours in children • Transsphenoidal surgery should be performed by surgeons with considerable experience and expertise • Surgical complications of

  19. Brain Tissue Classification Based on Diffusion Tensor Imaging: A Comparative Study Between Some Clustering Algorithms and Their Effect on Different Diffusion Tensor Imaging Scalar Indices

    PubMed Central

    Elaff, Ihab

    2016-01-01

    Background Brain segmentation from diffusion tensor imaging (DTI) into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) with acceptable results is subjected to many factors. Objectives The most important issue in brain segmentation from DTI images is the selection of suitable scalar indices that best describe the required tissue in the images. Specifying suitable clustering method and suitable number of clusters of the selected method are other factors which affects the segmentation process significantly. Materials and Methods The segmentation process is evaluated using four different clustering methods with different number of clusters where some DTI scalar indices for 10 human brains are processed. Results The aim was to produce results with less segmentation error and a lower computational cost while attempting to minimizing boundary overlapping and minimizing the effect of artifacts due to macroscale scanning. Conclusion The volume ratios of the best produced outputs with respect to the total brain size are 16.7% ± 3.53% for CSF, 35.05% ± 1.13% for WM, and 48.2% ± 2.88% for GM. PMID:27703655

  20. A model of vascular tumour growth in mice combining longitudinal tumour size data with histological biomarkers.

    PubMed

    Ribba, Benjamin; Watkin, Emmanuel; Tod, Michel; Girard, Pascal; Grenier, Emmanuel; You, Benoît; Giraudo, Enrico; Freyer, Gilles

    2011-02-01

    Optimising the delivery of antiangiogenic drugs requires the development of drug-disease models of vascular tumour growth that incorporate histological data indicative of cytostatic action. In this study, we formulated a model to analyse the dynamics of tumour progression in nude mice xenografted with HT29 or HCT116 colorectal cancer cells. In 30 mice, tumour size was periodically measured, and percentages of hypoxic and necrotic tissue were assessed using immunohistochemistry techniques on tumour samples after euthanasia. The simultaneous analysis of histological data together with longitudinal tumour size data prompted the development of a semi-mechanistic model integrating random effects of parameters. In this model, the peripheral non-hypoxic tissue proliferates according to a generalised-logistic equation where the maximal tumour size is represented by a variable called 'carrying capacity'. The ratio of the whole tumour size to the carrying capacity was used to define the hypoxic stress. As this stress increases, non-hypoxic tissue turns hypoxic. Hypoxic tissue does not stop proliferating, but hypoxia constitutes a transient stage before the tissue becomes necrotic. As the tumour grows, the carrying capacity increases owing to the process of angiogenesis. The model is shown to correctly predict tumour growth dynamics as well as percentages of necrotic and hypoxic tissues within the tumour. We show how the model can be used as a theoretical tool to investigate the effects of antiangiogenic treatments on tumour growth. This model provides a tool to analyse tumour size data in combination with histological biomarkers such as the percentages of hypoxic and necrotic tissue and is shown to be useful for gaining insight into the effects of antiangiogenic drugs on tumour growth and composition.

  1. Intraoperative β{sup -} detecting probe for radio-guided surgery in tumour resection

    SciTech Connect

    Solfaroli Camillocci, Elena; Bellini, Fabio; Bocciy, Valerio; Collamatiyz, Francesco; Faccini, Riccardo; Paramattiy, Riccardo; Paterayz, Vincenzo; Pinciy, Davide; Recchiay, Luigi; Sciubbayz, Adalberto; Senzacqua, Martina; Voenay, Cecilia; Morgantiy, Silvio; De Luciax, Erika; Matteixk, Ilaria; Sartizx, Alessio; Russomando, Aandrea; Marafiniy, Michela

    2015-07-01

    The development of the β{sup -} based radio-guided surgery aims to extend the technique to those tumours where surgery is the only possible treatment and the assessment of the resection would most profit from the low background around the lesion, as for brain tumours. Feasibility studies on meningioma and gliomas already estimated the potentiality of this new treatment. To validate the technique, a prototype of the intraoperative probe detecting β{sup -} decays and specific phantoms simulating tumour remnant patterns embedded in healthy tissue have been realized. The response of the probe in this simulated environment is tested with dedicated procedures. This document discusses the innovative aspects of the method, the status of the developed intraoperative β{sup -} detecting probe and the results of the preclinical tests. (authors)

  2. Contrast‐enhanced ultrasound of pancreatic tumours

    PubMed Central

    D'Onofrio, Mirko; Crosara, Stefano; Dal Corso, Flavia; Barbi, Emilio; Canestrini, Stefano; Mucelli, Roberto Pozzi

    2015-01-01

    Abstract Indication/purpose: To review contrast‐enhanced ultrasound features of the most common pancreatic tumours. Methods: Contrast‐enhanced ultrasound (CEUS) can provide distinctive features of pancreatic tumours that are reported in the present paper, providing radiologic‐pathological correlations and clarifying the main differential diagnosis. Conclusion: Contrast‐enhanced ultrasound plays a well‐established role in the evaluation of pancreatic tumours. When possible, CEUS should be always performed after the initial US diagnosis, in order to improve the accuracy of the first line examination. PMID:28191218

  3. Photodynamic therapy and anti-tumour immunity

    PubMed Central

    Castano, Ana P.; Mroz, Pawel; Hamblin, Michael R.

    2010-01-01

    Photodynamic therapy (PDT) uses non-toxic photosensitizers and harmless visible light in combination with oxygen to produce cytotoxic reactive oxygen species that kill malignant cells by apoptosis and/or necrosis, shut down the tumour microvasculature and stimulate the host immune system. In contrast to surgery, radiotherapy and chemotherapy that are mostly immunosuppressive, PDT causes acute inflammation, expression of heat-shock proteins, invasion and infiltration of the tumour by leukocytes, and might increase the presentation of tumour-derived antigens to T cells. PMID:16794636

  4. Transoral robotic surgery for retromolar trigone tumours.

    PubMed

    Durmus, K; Apuhan, T; Ozer, E

    2013-12-01

    The retromolar trigone is a challenging transoral surgical site due to the difficulty of visualization. Our aim is to report a new technique of transoral robotic resection of retromolar trigone tumours. We present three patients with retromolar trigone tumours with pathological diagnosis of squamous cell carcinoma who underwent successful transoral robotic resection. Robotic retromolar trigone resection and concurrent supraomohyoid neck dissections were performed in all patients without any complication. In conclusion, transoral robotic surgery is a safe and feasible technique for resection of malignant retromolar trigone tumours with minimal complications and favourable outcomes.

  5. Decrease in FOXJ1 expression and its ciliogenesis program in aggressive ependymoma and choroid plexus tumours

    PubMed Central

    Abedalthagafi, Malak S.; Wu, Michael P.; Merrill, Parker H.; Du, Ziming; Woo, Terri; Sheu, Shu-Hsien; Hurwitz, Shelley; Ligon, Keith L.; Santagata, Sandro

    2017-01-01

    Well-differentiated human cancers share transcriptional programs with the normal tissue counterparts from which they arise. These programs broadly influence cell behavior and function and are integral modulators of malignancy. Here, we show that the master regulator of motile ciliogenesis, FOXJ1, is highly expressed in cells along the ventricular surface of the human brain. Strong expression is present in cells of the ependyma and the choroid plexus as well as in a subset of cells residing in the subventricular zone. Expression of FOXJ1 and its transcriptional program is maintained in many well-differentiated human tumours that arise along the ventricle, including low-grade ependymal tumours and choroid plexus papilloma. Anaplastic ependymoma as well as choroid plexus carcinoma show decreased FOXJ1 expression and its associated ciliogenesis program genes. In ependymoma and choroid plexus tumours, reduced expression of FOXJ1 and its ciliogenesis program are markers of poor outcome and are therefore useful biomarkers for assessing these tumours. Transitions in ciliogenesis define distinct differentiation states in ependymal and choroid plexus tumours with important implications for patient care. PMID:26690880

  6. Peripheral primitive neuroectodermal tumour in a dog.

    PubMed

    Junginger, J; Röthlisberger, A; Lehmbecker, A; Stein, V M; Ludwig, D C; Baumgärtner, W; Seehusen, F

    2013-11-01

    A 1-year-old German shepherd dog was presented with paraparesis quickly progressing to paraplegia. Magnetic resonance imaging revealed a large mass beneath the thoracolumbar vertebral column infiltrating the spinal canal and resulting in severe extradural compression of the spinal cord. Microscopically, this comprised a cell-rich unencapsulated tumour supported by fine bands of a fibrovascular stroma and occasionally forming primitive rosettes. Immunohistochemistry showed the tumour cells to express synaptophysin and neuron-specific enolase. Ultrastructurally, the neoplastic cells had low to moderate numbers of intracytoplasmic neurosecretory granules. A peripheral primitive neuroectodermal tumour was diagnosed. This is a rare embryonal tumour of neural origin that may have arisen from adrenal medulla, autonomic ganglia or peripheral nerves.

  7. Heuristic Classification.

    DTIC Science & Technology

    1985-08-01

    34 Similarly, we draw causal nets linking abnormal states, saying that brain-hematoma (mass of blood in the brain) is caused by brain-hemorrhage (bleeding...possible solutions (restricted to abnormal findings that must be explained or "non-specific" findings not already explained by active solutions). In...solutions are abnormal processes causing the observed symptoms. We say that the inferred model of the device, the diagnosis, explains the symptoms. In

  8. Keratocystic odontogenic tumour: systematic review

    PubMed Central

    MacDonald-Jankowski, D S

    2011-01-01

    Objectives The aim of this review is to evaluate the principal clinical and conventional radiographic features of non-syndromic keratocystic odontogenic tumour (KCOT) by systematic review (SR), and to compare the frequencies between four global groups. Methods The databases searched were the PubMed interface of Medline and LILACS. Only those reports of KCOTs that occurred in a series of consecutive cases, in the reporting authors' caseload, were considered. Results 51 reports, of 49 series of cases, were included in the SR. 11 SR-included series were in languages other than English. KCOTs affected males more frequently and were three times more prevalent in the mandible. Although the mean age at first presentation was 37 years, the largest proportion of cases first presented in the third decade. The main symptom was swelling. Over a third were found incidentally. Nearly two-thirds displayed buccolingual expansion. Over a quarter of cases recurred. Only a quarter of all SR-included reported series of cases included details of at least one radiological feature. The East Asian global group presented significantly as well-defined, even corticated, multilocular radiolucencies with buccolingual expansion. The KCOTs affecting the Western global group significantly displayed an association with unerupted teeth. Conclusions Long-term follow-up of large series that would have revealed detailed radiographic description and long-term outcomes of non-syndromic KCOT was lacking. PMID:21159911

  9. Calcifying Epithelial Odontogenic Tumour of the Mandible: An Unusually Aggressive Presentation of an Indolent Tumour

    PubMed Central

    Dev, DP Arul; Michael, Manoj Joseph; Akhilesh, AV; Das, Bindu

    2016-01-01

    Calcifying Epithelial Odontogenic Tumour (CEOT) or Pindborg tumour is a rare odontogenic tumour of epithelial origin. They constitute less than 1% of odontogenic tumours. Intra-ossseous variant of CEOT are more common compared to extra-osseous variant. Although benign, these can exhibit deceptively aggressive presentation. Here we report a rare case of CEOT in a 36-year-old female patient who presented with aggressive intra-osseous lesion with cortical breach and exuberant soft tissue proliferation. The lesion was treated with resection and reconstructed with titanium reconstruction plate. PMID:27790590

  10. Primary primitive neuroectodermal tumour of the kidney in adults.

    PubMed

    Verma, Ritu; Singhal, Mitali; Pandey, Rakesh

    2013-03-04

    Primitive neuroectodermal tumour (PNET) is a neural crest tumour derived from neuroectoderm. Renal PNET is a very rare tumour occurring during childhood or adolescence. We report two cases of PNET involving kidney in adults. Presenting signs and symptoms include abdominal/flank pain and/or haematuria. Microscopy reveals the tumour consisted of small round cells with round nuclei and scant cytoplasm. Diagnosis was confirmed by immunohistochemistry with diffuse membranous positivity of tumour cells with CD99. As these tumours have an aggressive clinical course with rapid death in many reported cases, it is important to differentiate them from other small round-cell tumours.

  11. Tumour-targeted nanomedicines: principles and practice

    PubMed Central

    Lammers, T; Hennink, W E; Storm, G

    2008-01-01

    Drug targeting systems are nanometre-sized carrier materials designed for improving the biodistribution of systemically applied (chemo)therapeutics. Various different tumour-targeted nanomedicines have been evaluated over the years, and clear evidence is currently available for substantial improvement of the therapeutic index of anticancer agents. Here, we briefly summarise the most important targeting systems and strategies, and discuss recent advances and future directions in the development of tumour-targeted nanomedicines. PMID:18648371

  12. A dynamical model of tumour immunotherapy.

    PubMed

    Frascoli, Federico; Kim, Peter S; Hughes, Barry D; Landman, Kerry A

    2014-07-01

    A coupled ordinary differential equation model of tumour-immune dynamics is presented and analysed. The model accounts for biological and clinical factors which regulate the interaction rates of cytotoxic T lymphocytes on the surface of the tumour mass. A phase plane analysis demonstrates that competition between tumour cells and lymphocytes can result in tumour eradication, perpetual oscillations, or unbounded solutions. To investigate the dependence of the dynamic behaviour on model parameters, the equations are solved analytically and conditions for unbounded versus bounded solutions are discussed. An analytic characterisation of the basin of attraction for oscillatory orbits is given. It is also shown that the tumour shape, characterised by a surface area to volume scaling factor, influences the size of the basin, with significant consequences for therapy design. The findings reveal that the tumour volume must surpass a threshold size that depends on lymphocyte parameters for the cancer to be completely eliminated. A semi-analytic procedure to calculate oscillation periods and determine their sensitivity to model parameters is also presented. Numerical results show that the period of oscillations exhibits notable nonlinear dependence on biologically relevant conditions.

  13. Smooth muscle tumours of the alimentary tract.

    PubMed Central

    Diamond, T.; Danton, M. H.; Parks, T. G.

    1990-01-01

    Neoplasms arising from smooth muscle of the gastrointestinal (GI) tract are uncommon, comprising only 1% of gastrointestinal tumours. A total of 51 cases of smooth muscle tumour of the GI tract were analysed; 44 leiomyomas and 7 leiomyosarcomas. Lesions occurred in all areas from the oesophagus to the rectum, the stomach being the commonest site. Thirty-six patients had clinical features referable to the tumour. The tumour was detected during investigation or management of an unrelated disease process in 15 patients. The clinical presentation varied depending on tumour location, but abdominal pain and GI bleeding were the commonest presenting symptoms. The lesion was demonstrated preoperatively, mainly by endoscopy and barium studies, in 27 patients. Surgical excision was the treatment of choice, where possible. There was no recurrence in the leiomyoma group but four patients died in the leiomyosarcoma group. Although rare, smooth muscle tumours should be considered in situations where clinical presentation and investigations are not suggestive of any common GI disorder. The preoperative assessment and diagnosis is difficult because of the variability in clinical features and their inaccessibility to routine GI investigation. It is recommended that, where possible, the lesion, whether symptomatic or discovered incidentally, should be excised completely to achieve a cure and prevent future complications. Images Figure 3 Figure 4 PMID:2221768

  14. The Swiss Canine Cancer Registry: a retrospective study on the occurrence of tumours in dogs in Switzerland from 1955 to 2008.

    PubMed

    Grüntzig, K; Graf, R; Hässig, M; Welle, M; Meier, D; Lott, G; Erni, D; Schenker, N S; Guscetti, F; Boo, G; Axhausen, K; Fabrikant, S; Folkers, G; Pospischil, A

    2015-01-01

    Diagnostic records are a key feature of any cancer epidemiology, prevention or control strategy for man and animals. Therefore, the information stored in human and animal cancer registries is essential for undertaking comparative epidemiological, pathogenic and therapeutic research. This study presents the Swiss Canine Cancer Registry, containing case data compiled between 1955 and 2008. The data consist of pathology diagnostic records issued by three veterinary diagnostic laboratories in Switzerland. The tumours were classified according to the guidelines of the International Classification of Oncology for Humans on the basis of tumour type, malignancy and body location. The dogs were classified according to breed, age, sex, neuter status and place of residence. The diagnostic data were correlated with data on the Swiss general dog population and the incidence of cancer in dogs was thus investigated. A total of 67,943 tumours were diagnosed in 121,963 dogs and 47.07% of these were malignant. The most common tumour location was the skin (37.05%), followed by mammary glands (23.55%) and soft tissue (13.66%). The most common tumour diagnoses were epithelial (38.45%), mesenchymal (35.10%) and lymphoid tumours (13.23%). The results are compared with data in other canine registries and similarities in tumour distribution and incidence are noted. It is hoped that this study will mark the beginning of continuous registration of dog tumours in Switzerland, which, in turn, will serve as a reference for research in the fields of animal and human oncology.

  15. [An immobilising malignant phyllodes tumour of the breast].

    PubMed

    Fritsche, E; Hug, U; Winterholer, D

    2015-04-01

    Phyllodes tumours of the breast are rare occurrences, but they can reach huge dimensions. Descriptions of tumours whereby the women are immobilised as a consequence of the size of the tumour, are hard to find in the literature. In this presentation we show a case of a woman in otherwise healthy condition with a giant phyllodes tumour of her left breast. Because of the weight of the tumour, the patient could not leave her bed for more than 6 months.

  16. Accuracy of Various MRI Sequences in Determining the Tumour Margin in Musculoskeletal Tumours

    PubMed Central

    Putta, Tharani; Gibikote, Sridhar; Madhuri, Vrisha; Walter, Noel

    2016-01-01

    Summary Background It is imperative that bone tumour margin and extent of tumour involvement are accurately assessed pre-operatively in order for the surgeon to attain a safe surgical margin. In this study, we comprehensively assessed each of the findings that influence surgical planning, on various MRI sequences and compared them with the gold standard – pathology. Material/Methods In this prospective study including 21 patients with extremity bone tumours, margins as seen on various MRI sequences (T1, T2, STIR, DWI, post-gadolinium T1 FS) were measured and biopsies were obtained from each of these sites during the surgical resection. The resected tumour specimen and individual biopsy samples were studied to assess the true tumour margin. Margins on each of the MRI sequences were then compared with the gold standard – pathology. In addition to the intramedullary tumour margin, we also assessed the extent of soft tissue component, neurovascular bundle involvement, epiphyseal and joint involvement, and the presence or absence of skip lesions. Results T1-weighted imaging was the best sequence to measure tumour margin without resulting in clinically significant underestimation or overestimation of the tumour extent (mean difference of 0.8 mm; 95% confidence interval between −0.9 mm to 2.5 mm; inter-class correlation coefficient of 0.998). STIR and T1 FS post-gadolinium imaging grossly overestimated tumour extent by an average of 16.7 mm and 16.8 mm, respectively (P values <0.05). Post-gadolinium imaging was better to assess joint involvement while T1 and STIR were the best to assess epiphyseal involvement. Conclusions T1-weighted imaging was the best sequence to assess longitudinal intramedullary tumour extent. We suggest that osteotomy plane 1.5 cm beyond the T1 tumour margin is safe and also limits unwarranted surgical bone loss. However, this needs to be prospectively proven with a larger sample size. PMID:28058070

  17. Reaching a Moveable Visual Target: Dissociations in Brain Tumour Patients

    ERIC Educational Resources Information Center

    Buiatti, Tania; Skrap, Miran; Shallice, Tim

    2013-01-01

    Damage to the posterior parietal cortex (PPC) can lead to Optic Ataxia (OA), in which patients misreach to peripheral targets. Recent research suggested that the PPC might be involved not only in simple reaching tasks toward peripheral targets, but also in changing the hand movement trajectory in real time if the target moves. The present study…

  18. Tumour macrophages as potential targets of bisphosphonates

    PubMed Central

    2011-01-01

    Tumour cells communicate with the cells of their microenvironment via a series of molecular and cellular interactions to aid their progression to a malignant state and ultimately their metastatic spread. Of the cells in the microenvironment with a key role in cancer development, tumour associated macrophages (TAMs) are among the most notable. Tumour cells release a range of chemokines, cytokines and growth factors to attract macrophages, and these in turn release numerous factors (e.g. VEGF, MMP-9 and EGF) that are implicated in invasion-promoting processes such as tumour cell growth, flicking of the angiogenic switch and immunosuppression. TAM density has been shown to correlate with poor prognosis in breast cancer, suggesting that these cells may represent a potential therapeutic target. However, there are currently no agents that specifically target TAM's available for clinical use. Bisphosphonates (BPs), such as zoledronic acid, are anti-resorptive agents approved for treatment of skeletal complication associated with metastatic breast cancer and prostate cancer. These agents act on osteoclasts, key cells in the bone microenvironment, to inhibit bone resorption. Over the past 30 years this has led to a great reduction in skeletal-related events (SRE's) in patients with advanced cancer and improved the morbidity associated with cancer-induced bone disease. However, there is now a growing body of evidence, both from in vitro and in vivo models, showing that zoledronic acid can also target tumour cells to increase apoptotic cell death and decrease proliferation, migration and invasion, and that this effect is significantly enhanced in combination with chemotherapy agents. Whether macrophages in the peripheral tumour microenvironment are exposed to sufficient levels of bisphosphonate to be affected is currently unknown. Macrophages belong to the same cell lineage as osteoclasts, the major target of BPs, and are highly phagocytic cells shown to be sensitive to

  19. Novel use of Empirical Mode Decomposition in single-trial classification of motor imagery for use in brain-computer interfaces.

    PubMed

    Davies, Simon R H; James, Christopher J

    2013-01-01

    This paper presents a novel method, based on multi-channel Empirical Mode Decomposition (EMD), of classifying the electroencephalogram (EEG) recordings of imagined movement by a subject within a brain-computer interfacing (BCI) framework. EMD is a technique that divides any non-linear or non-stationary signal into groups of frequency harmonics, called Intrinsic Mode Functions (IMFs). As frequency is a key component of both IMFs and the μ rhythm (8-13 Hz brain activity generated during motor imagery), IMFs are then grouped by frequency. EMD is applied to the recordings from two electrodes for each trial and the resulting IMFs are grouped according to peak-frequency band via Hierarchical Clustering Analysis (HCA). The cluster containing the frequency band of the μ rhythm (8-13 Hz) is then selected and the sum-total of the IMFs from each electrode are summed together. A simple linear classifier is then sufficient to classify the motor-imagery with 89% sensitivity from a separate test set.

  20. Tumour-induced neoneurogenesis and perineural tumour growth: a mathematical approach

    NASA Astrophysics Data System (ADS)

    Lolas, Georgios; Bianchi, Arianna; Syrigos, Konstantinos N.

    2016-02-01

    It is well-known that tumours induce the formation of a lymphatic and a blood vasculature around themselves. A similar but far less studied process occurs in relation to the nervous system and is referred to as neoneurogenesis. The relationship between tumour progression and the nervous system is still poorly understood and is likely to involve a multitude of factors. It is therefore relevant to study tumour-nerve interactions through mathematical modelling: this may reveal the most significant factors of the plethora of interacting elements regulating neoneurogenesis. The present work is a first attempt to model the neurobiological aspect of cancer development through a system of differential equations. The model confirms the experimental observations that a tumour is able to promote nerve formation/elongation around itself, and that high levels of nerve growth factor and axon guidance molecules are recorded in the presence of a tumour. Our results also reflect the observation that high stress levels (represented by higher norepinephrine release by sympathetic nerves) contribute to tumour development and spread, indicating a mutually beneficial relationship between tumour cells and neurons. The model predictions suggest novel therapeutic strategies, aimed at blocking the stress effects on tumour growth and dissemination.

  1. Clinical management of tumours in geriatric dogs and cats: systemic effects of tumours and paraneoplastic syndromes.

    PubMed

    Gorman, N T

    1990-04-21

    There are many clinical presentations of neoplastic disease in the dog and cat. Some relate to the presence of a solid mass but many relate to the systemic effect that the tumour has on the animal. This paper covers the broad categories of the systemic metabolic and haematological effects that are associated with tumours in the dog and cat.

  2. Occurrence of tumours metastatic to bones and multicentric tumours with skeletal involvement in dogs.

    PubMed

    Trost, M E; Inkelmann, M A; Galiza, G J N; Silva, T M; Kommers, G D

    2014-01-01

    The skeletons of 110 dogs with malignant tumours of different origins were examined by necropsy examination over a 3-year period to identify bone metastases. Twenty-one cases of metastatic or multicentric tumours with bone involvement were recorded. In general, more female dogs presented with bony metastases; however, when the dogs with mammary tumours were omitted, the gender distribution of the cases was approximately equivalent. The mammary gland was the primary site of most of the metastatic bone lesions, followed by the musculoskeletal system and the respiratory system. The majority (77%) of metastases were grossly visible and present in multiple bones. However, in 23% of the cases, the metastases could be diagnosed only at the microscopical level. The vertebrae and the humerus were the most frequently affected bones regardless of the primary site and the histogenesis of the tumours. The results of this study revealed a high prevalence of bone metastases and/or bone involvement in dogs with multicentric tumours.

  3. Clinical relevance associated to the analysis of circulating tumour cells in patients with solid tumours.

    PubMed

    Serrano Fernádez, María José; Alvarez Merino, Juan Carlos; Martínez Zubiaurre, Iñigo; Fernández García, Ana; Sánchez Rovira, Pedro; Lorente Acosta, José Antonio

    2009-10-01

    The distant growth of tumour cells escaping from primary tumours, a process termed metastasis, represents the leading cause of death among patients affected by malignant neoplasias from breast and colon. During the metastasis process, cancer cells liberated from primary tumour tissue, also termed circulating tumour cells (CTCs), travel through the circulatory and/or lymphatic systems to reach distant organs. The early detection and the genotypic and phenotypic characterisation of such CTCs could represent a powerful diagnostic tool of the disease, and could also be considered an important predictive and prognostic marker of disease progression and treatment response. In this article we discuss the potential relevance in the clinic of monitoring CTCs from patients suffering from solid epithelial tumours, with emphasis on the impact of such analyses as a predictive marker for treatment response.

  4. Desmoplastic nested spindle cell tumours and nested stromal epithelial tumours of the liver.

    PubMed

    Misra, Sunayana; Bihari, Chhagan

    2016-04-01

    Desmoplastic nested spindle cell tumour of liver (DNSTL), nested stromal-epithelial tumour (NSET) and calcifying nested stromal-epithelial tumour (CNSET) are recently described entities with similar morphology, immunohistochemistry and molecular genetics. These are rare entities with only three large case series described till date. These tumours commonly present in the paediatric age group. NSETs, in addition have been described to be associated with ectopic adrenocorticotropic hormone (ACTH) production and Cushingoid features. It is important to discuss this rare group of tumours with a low malignant potential as the most common radiological differential diagnosis is hepatoblastoma, which has a relatively poorer prognosis. Thus, a pathologist needs to keep this entity in mind, so as to offer a correct histological diagnosis.

  5. Vascular tumours in infants. Part I: benign vascular tumours other than infantile haemangioma.

    PubMed

    Hoeger, P H; Colmenero, I

    2014-09-01

    Vascular anomalies can be subdivided into vascular tumours and vascular malformations (VMs). While most VMs are present at birth and do not exhibit significant postnatal growth, vascular tumours are characterized by their dynamics of growth and (sometimes) spontaneous regression. This review focuses on benign vascular tumours other than infantile haemangiomas (IHs), namely pyogenic granuloma, eruptive pseudoangiomatosis, glomangioma, rapidly involuting and noninvoluting congenital haemangioma, verrucous haemangioma and spindle cell haemangioma. While some of them bear clinical resemblance to IH, they can be separated by age of appearance, growth characteristics and/or negative staining for glucose transporter 1. Separation of these tumours from IH is necessary because their outcome and therapeutic options are different. Semimalignant and malignant vascular tumours will be addressed in a separate review.

  6. Gene expression biomarkers in the brain of a mouse model for Alzheimer's disease: mining of microarray data by logic classification and feature selection.

    PubMed

    Arisi, Ivan; D'Onofrio, Mara; Brandi, Rossella; Felsani, Armando; Capsoni, Simona; Drovandi, Guido; Felici, Giovanni; Weitschek, Emanuel; Bertolazzi, Paola; Cattaneo, Antonino

    2011-01-01

    The identification of early and stage-specific biomarkers for Alzheimer's disease (AD) is critical, as the development of disease-modification therapies may depend on the discovery and validation of such markers. The identification of early reliable biomarkers depends on the development of new diagnostic algorithms to computationally exploit the information in large biological datasets. To identify potential biomarkers from mRNA expression profile data, we used the Logic Mining method for the unbiased analysis of a large microarray expression dataset from the anti-NGF AD11 transgenic mouse model. The gene expression profile of AD11 brain regions was investigated at different neurodegeneration stages by whole genome microarrays. A new implementation of the Logic Mining method was applied both to early (1-3 months) and late stage (6-15 months) expression data, coupled to standard statistical methods. A small number of "fingerprinting" formulas was isolated, encompassing mRNAs whose expression levels were able to discriminate between diseased and control mice. We selected three differential "signature" genes specific for the early stage (Nudt19, Arl16, Aph1b), five common to both groups (Slc15a2, Agpat5, Sox2ot, 2210015, D19Rik, Wdfy1), and seven specific for late stage (D14Ertd449, Tia1, Txnl4, 1810014B01Rik, Snhg3, Actl6a, Rnf25). We suggest these genes as potential biomarkers for the early and late stage of AD-like neurodegeneration in this model and conclude that Logic Mining is a powerful and reliable approach for large scale expression data analysis. Its application to large expression datasets from brain or peripheral human samples may facilitate the discovery of early and stage-specific AD biomarkers.

  7. Whole-brain functional connectivity during emotional word classification in medication-free Major Depressive Disorder: Abnormal salience circuitry and relations to positive emotionality☆

    PubMed Central

    van Tol, Marie-José; Veer, Ilya M.; van der Wee, Nic J.A.; Aleman, André; van Buchem, Mark A.; Rombouts, Serge A.R.B.; Zitman, Frans G.; Veltman, Dick J.; Johnstone, Tom

    2013-01-01

    Major Depressive Disorder (MDD) has been associated with biased processing and abnormal regulation of negative and positive information, which may result from compromised coordinated activity of prefrontal and subcortical brain regions involved in evaluating emotional information. We tested whether patients with MDD show distributed changes in functional connectivity with a set of independently derived brain networks that have shown high correspondence with different task demands, including stimulus salience and emotional processing. We further explored if connectivity during emotional word processing related to the tendency to engage in positive or negative emotional states. In this study, 25 medication-free MDD patients without current or past comorbidity and matched controls (n = 25) performed an emotional word-evaluation task during functional MRI. Using a dual regression approach, individual spatial connectivity maps representing each subject's connectivity with each standard network were used to evaluate between-group differences and effects of positive and negative emotionality (extraversion and neuroticism, respectively, as measured with the NEO-FFI). Results showed decreased functional connectivity of the medial prefrontal cortex, ventrolateral prefrontal cortex, and ventral striatum with the fronto-opercular salience network in MDD patients compared to controls. In patients, abnormal connectivity was related to extraversion, but not neuroticism. These results confirm the hypothesis of a relative (para)limbic–cortical decoupling that may explain dysregulated affect in MDD. As connectivity of these regions with the salience network was related to extraversion, but not to general depression severity or negative emotionality, dysfunction of this network may be responsible for the failure to sustain engagement in rewarding behavior. PMID:24179829

  8. [Changes in the TNM classification of head and neck tumors].

    PubMed

    Weber, A; Schmid, K W; Tannapfel, A; Wittekind, C

    2010-09-01

    Only minor modifications were introduced in the classification of squamous cell carcinomas of the oro- and hypopharynx, namely in the definition of some T and N categories. A new TNM classification has been introduced for mucosal melanoma of the head and neck. Some proposals for ramification of the T1 categories of thyroid tumours have been adopted from the TNM Supplement, unfortunately not those proposed for the T3 categories. The new TNM classification of Merkel cell carcinomas, which frequently occur in the head and neck region, is also discussed.

  9. Approaches to paraspinal tumours - a technical note.

    PubMed

    Dhar, Arjun; Pawar, Sumeet; Prasad, Apurva; Ramani, P S

    2017-03-23

    Neurogenic tumours of the paraspinal space can occur in all age groups. It is common in adult population and relatively rare in elderly group. Usually they are benign, but in children, arising from the autonomic system, tends to be malignant in nature. Usually in adults, they arise from peripheral nerve sheath and are labelled as schwannomas. For a given tumour, determination of a correct surgical approach is mandatory to achieve a successful surgical outcome. Several factors like tumour size, histology, involvement of the bony spinal canal, etc. are some of the deciding factors for a correct surgical approach. Since many such tumours are benign, total excision is possible with a correct surgical approach. If the tumour involves the integrity of the spine then additionally a stabilization procedure may have to be carried out. Unfortunately, there are still no guidelines regarding the choice of surgical approach for the excision of such tumors. Presented here is a series of five patients managed by us over a period of 10 years. Four patients were adults and one female child was three years old. Four patients were operated upon successfully and the fifth one is waiting for surgery.

  10. The diagnosis of soft tissue tumours.

    PubMed Central

    Serpell, J. W.; Fish, S. H.; Fisher, C.; Thomas, J. M.

    1992-01-01

    We prospectively analysed methods of diagnosis in 118 patients referred for definitive treatment with documented or presumed soft tissue sarcoma (STS). Of 65 patients with primary STS, 54 were biopsied before referral. Of these, 5 (9%) were biopsied by Tru-cut biopsy, 17 (32%) by incisional biopsy and 32 (59%) by excisional biopsy. The remaining 11 patients with primary STS, referred without biopsy, were all diagnosed by Tru-cut biopsy. An additional eight patients suspected of having STS were referred without biopsy and were found to have malignant tumours other than STS involving soft tissue by Tru-cut biopsy. Nineteen patients were proved to have benign soft tissue tumours; in 13 presumed to have STS, the diagnosis was unknown at referral. In four of these, biopsy was inappropriate. Of nine submitted to Tru-cut biopsy, an unequivocal diagnosis was made in 5 (56%) and incisional biopsy was required in the other four. Therefore, paradoxically, benign soft tissue tumours may be more difficult to diagnose with Tru-cut biopsy than malignant tumours. This study confirms the high degree of accuracy of Tru-cut biopsy in diagnosing malignant soft tissue tumours and highlights the disadvantages of open biopsy techniques. PMID:1416683

  11. Imaging tumours of the ampulla of Vater.

    PubMed

    Zbar, Andrew P; Maor, Yaakov; Czerniak, Abraham

    2012-12-01

    Although comparatively rare, ampullary tumours tend to be more readily curable than periampullary lesions and pancreatic carcinomas, consequent upon an earlier presentation, a lower likelihood of involved lymph nodes or vascular infiltration and a less aggressive histology. Recently, selected early cases have been able to resected endoscopically making accurate preoperative tumour (T) staging critical in such decision making. The most commonly available imaging methods are endoscopic ultrasound (EUS) and CT scanning where in the former case there is variable accuracy for larger (T2/T3) ampullary tumours particularly where the patient has undergone preoperative common bile duct stenting. CT scanning has consistent shown inferior T staging of ampullary tumours when compared with EUS, although it provides information concerning visceral and nodal metastatic disease. Transpapillary intraductal ultrasound (where available) has shown high accuracy for early T1 tumours potentially suitable for endoscopic or local ampullary excision with the added advantage that it may be conducted without preliminary sphincterotomy. Recently, our group has been using intraoperative transduodenal ultrasound which assists surgical decision making concerning local excision or radical pancreaticoduodenal resection. Very recent images using 3-dimensional endoduodenal ultrasound has provided exquisite images of the ampulla and remain to be validated in ampullary neoplasms.

  12. Giant malignant phyllodes tumour of breast.

    PubMed

    Krishnamoorthy, Ramakrishnan; Savasere, Thejas; Prabhuswamy, Vinod Kumar; Babu, Rajashekhara; Shivaswamy, Sadashivaiah

    2014-01-01

    The term phyllodes tumour includes lesions ranging from completely benign tumours to malignant sarcomas. Clinically phyllodes tumours are smooth, rounded, and usually painless multinodular lesions indistinguishable from fibroadenomas. Percentage of phyllodes tumour classified as malignant ranges from 23% to 50%. We report a case of second largest phyllodes tumour in a 35-year-old lady who presented with swelling of right breast since 6 months, initially small in size, that progressed gradually to present size. Examination revealed mass in the right breast measuring 36×32 cms with lobulated firm surface and weighing 10 kgs. Fine needle aspiration cytology was reported as borderline phyllodes; however core biopsy examination showed biphasic neoplasm with malignant stromal component. Simple mastectomy was done and specimen was sent for histopathological examination which confirmed the core biopsy report. Postoperatively the patient received chemotherapy and radiotherapy. The patient is on follow-up for a year and has not shown any evidence of metastasis or recurrence.

  13. Constitutional ring chromosomes and tumour suppressor genes.

    PubMed Central

    Tommerup, N; Lothe, R

    1992-01-01

    The types of malignancy reported in carriers of constitutional ring chromosomes r(11), r(13), and r(22) are concordant with the chromosomal assignment of tumour suppressor loci associated with Wilms' tumour, retinoblastoma, and meningioma. It is suggested that the somatic instability of ring chromosomes may play a role in this association and that constitutional ring chromosomes may be a source for mapping of tumour suppressor loci with the potential for covering most or all of the human genome. The hypothesis predicts the presence of a locus on chromosome 10 associated with follicular carcinoma of the thyroid, in line with previous cytogenetic findings of rearrangements involving chromosome 10 in thyroid tumours, and a locus on chromosome 22 associated with testicular cancer. Development of neurofibromatoses (NF) that do not fulfil the clinical criteria of neurofibromatosis type 2 (NF2) in carriers with r(22) suggests either the presence of an additional NF locus on chromosome 22 or that ring chromosome mediated predisposition to somatic mutation of a specific tumour suppressor may be associated with atypical development of features usually associated with germline mutations. PMID:1336057

  14. Targeting the tumour microenvironment in ovarian cancer.

    PubMed

    Hansen, Jean M; Coleman, Robert L; Sood, Anil K

    2016-03-01

    The study of cancer initiation, growth, and metastasis has traditionally been focused on cancer cells, and the view that they proliferate due to uncontrolled growth signalling owing to genetic derangements. However, uncontrolled growth in tumours cannot be explained solely by aberrations in cancer cells themselves. To fully understand the biological behaviour of tumours, it is essential to understand the microenvironment in which cancer cells exist, and how they manipulate the surrounding stroma to promote the malignant phenotype. Ovarian cancer is the leading cause of death from gynaecologic cancer worldwide. The majority of patients will have objective responses to standard tumour debulking surgery and platinum-taxane doublet chemotherapy, but most will experience disease recurrence and chemotherapy resistance. As such, a great deal of effort has been put forth to develop therapies that target the tumour microenvironment in ovarian cancer. Herein, we review the key components of the tumour microenvironment as they pertain to this disease, outline targeting opportunities and supporting evidence thus far, and discuss resistance to therapy.

  15. Phylogenetic Quantification of Intra-tumour Heterogeneity

    PubMed Central

    Schwarz, Roland F.; Trinh, Anne; Sipos, Botond; Brenton, James D.; Goldman, Nick; Markowetz, Florian

    2014-01-01

    Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data. PMID:24743184

  16. Classification Analysis.

    ERIC Educational Resources Information Center

    Ball, Geoffrey H.

    Sorting things into groups is a basic intellectual task that allows people to simplify with minimal reduction in information. Classification techniques, which include both clu