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1

[Revised WHO classification of brain tumours].  

PubMed

The WHO classification of brain tumours has been widely accepted and used in daily medical practice for more than 25 years since the first edition was published in 1979. In 2007, WHO revised the former classification, and published the newest one, the 4th edition of WHO classification. This revision updated the concept of grading, added several new entities and variants, modified and reclassified tumours, and changed the terminology. Newly codified entities include atypical choroid plexus papilloma, angiocentric glioma, extraventricular neurocytoma, papillary glioneuronal tumour, rosette-forming glioneuronal tumour of the fourth ventricle, papillary tumour of the pineal region, anaplastic hemangiopericytoma, Ewing sarcoma - PNET, pituicytoma, and spindle cell oncocytoma of the adenohypophysis. If a given tumour has an evidence of a different clinical features, genetic profile or prognostic behavior, it was considered to be histological variants; these included pilomyxoid astrocytoma, medulloblastoma with extensive nodularity, and anaplastic medulloblastoma. An overview of the 4th edition of WHO classification and short comments for each major point of alterations will be provided in this review. PMID:18232334

Nakazato, Yoichi

2008-01-01

2

Brain tumour segmentation and tumour tissue classification based on multiple MR protocols  

NASA Astrophysics Data System (ADS)

Segmentation of brain tumours in Magnetic Resonance (MR) images and classification of the tumour tissue into vital, necrotic, and perifocal edematous areas is required in a variety of clinical applications. Manual delineation of the tumour tissue boundaries is a tedious and error-prone task, and the results are not reproducible. Furthermore, tissue classification mostly requires information of several MR protocols and contrasts. Here we present a nearly automatic segmentation and classification algorithm for brain tumour tissue working on a combination of T1 weighted contrast enhanced (T1CE) images and fluid attenuated inversion recovery (FLAIR) images. Both image types are included in MR brain tumour protocols that are used in clinical routine. The algorithm is based on a region growing technique, hence it is fast (ten seconds on a standard personal computer). The only required user interaction is a mouse click for providing the starting point. The region growing parameters are automatically adapted in the course of growing, and if a new maximum image intensity is found, the region growing is restarted. This makes the algorithm robust, i.e. independent of the given starting point in a certain capture range. Furthermore, we use a lossless coarse-to-fine approach, which, together with the automatic adaptation of the parameters, can avoid leakage of the region growing procedure. We tested our algorithm on 20 cases of human glioblastoma and meningioma. In the majority of the test cases we got satisfactory results.

Franz, Astrid; Remmele, Stefanie; Keupp, Jochen

2011-03-01

3

Classification of single-voxel 1H spectra of brain tumours using LCModel.  

PubMed

This study presents a novel method for the direct classification of (1)H single-voxel MR brain tumour spectra using the widespread analysis tool LCModel. LCModel is designed to estimate individual metabolite proportions by fitting a linear combination of in?vitro metabolite spectra to an in?vivo MR spectrum. In this study, it is used to fit representations of complete tumour spectra and to perform a classification according to the highest estimated tissue proportion. Each tumour type is represented by two spectra, a mean component and a variability term, as calculated using a principal component analysis of a training dataset. In the same manner, a mean component and a variability term for normal white matter are also added into the analysis to allow a mixed tissue approach. An unbiased evaluation of the method is carried out through the automatic selection of training and test sets using the Kennard and Stone algorithm, and a comparison of LCModel classification results with those of the INTERPRET Decision Support System (IDSS) which incorporates an advanced pattern recognition method. In a test set of 46 spectra comprising glioblastoma multiforme, low-grade gliomas and meningiomas, LCModel gives a classification accuracy of 90% compared with an accuracy of 95% by IDSS. PMID:21796709

Raschke, F; Fuster-Garcia, E; Opstad, K S; Howe, F A

2012-02-01

4

Classification of brain tumours using short echo time 1H MR spectra.  

PubMed

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas (n = 87), meningiomas (n = 57), metastases (n = 39), and astrocytomas grade II (n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing. PMID:15324770

Devos, A; Lukas, L; Suykens, J A K; Vanhamme, L; Tate, A R; Howe, F A; Majós, C; Moreno-Torres, A; van der Graaf, M; Arús, C; Van Huffel, S

2004-09-01

5

Classification of brain tumours using short echo time 1H MR spectra  

NASA Astrophysics Data System (ADS)

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas ( n = 87), meningiomas ( n = 57), metastases ( n = 39), and astrocytomas grade II ( n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing.

Devos, A.; Lukas, L.; Suykens, J. A. K.; Vanhamme, L.; Tate, A. R.; Howe, F. A.; Majós, C.; Moreno-Torres, A.; van der Graaf, M.; Arús, C.; Van Huffel, S.

2004-09-01

6

MRS quality assessment in a multicentre study on MRS-based classification of brain tumours.  

PubMed

This paper reports on quality assessment of MRS in the European Union-funded multicentre project INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance; http://azizu.uab.es/INTERPRET), which has developed brain tumour classification software using in vivo proton MR spectra. The quality assessment consisted of both MR system quality assurance (SQA) and quality control (QC) of spectral data acquired from patients and healthy volunteers. The system performance of the MR spectrometers at all participating centres was checked bimonthly by a short measurement protocol using a specially designed INTERPRET phantom. In addition, a more extended SQA protocol was performed yearly and after each hardware or software upgrade. To compare the system performance for in vivo measurements, each centre acquired MR spectra from the brain of five healthy volunteers. All MR systems fulfilled generally accepted minimal system performance for brain MRS during the entire data acquisition period. The QC procedure of the MR spectra in the database comprised automatic determination of the signal-to-noise ratio (SNR) in a water-suppressed spectrum and of the line width of the water resonance (water band width, WBW) in the corresponding non-suppressed spectrum. Values of SNR > 10 and WBW < 8 Hz at 1.5 T were determined empirically as conservative threshold levels required for spectra to be of acceptable quality. These thresholds only hold for SNR and WBW values using the definitions and data processing described in this article. A final QC check consisted of visual inspection of each clinically validated water-suppressed metabolite spectrum by two, or, in the case of disagreement, three, experienced MR spectroscopists, to detect artefacts such as large baseline distortions, exceptionally broadened metabolite peaks, insufficient removal of the water line, large phase errors, and signals originating from outside the voxel. In the end, 10% of 889 spectra with completed spectroscopic judgement were discarded. PMID:17458918

van der Graaf, Marinette; Julià-Sapé, Margarida; Howe, Franklyn A; Ziegler, Anne; Majós, Carles; Moreno-Torres, Angel; Rijpkema, Mark; Acosta, Dionisio; Opstad, Kirstie S; van der Meulen, Yvonne M; Arús, Carles; Heerschap, Arend

2008-02-01

7

Classification of tumours  

PubMed Central

Tumours are classified according to the most differentiated cells with the exception of carcinomas where a few tumour cells show neuroendocrine differentiation. In this case these cells are regarded as redifferentiated tumour cells, and the tumour is not classified as neuroendocrine. However, it is now clear that normal neuroendocrine cells can divide, and that continuous stimulation of such cells results in tumour formation, which during time becomes increasingly malignant. To understand tumourigenesis, it is of utmost importance to recognize the cell of origin of the tumour since knowledge of the growth regulation of that cell may give information about development and thus possible prevention and prophylaxis of the tumour. It may also have implications for the treatment. The successful treatment of gastrointestinal stromal tumours by a tyrosine kinase inhibitor is an example of the importance of a correct cellular classification of a tumour. In the future tumours should not just be classified as for instance adenocarcinomas of an organ, but more precisely as a carcinoma originating from a certain cell type of that organ.

Waldum, Helge L; Sandvik, Arne K; Brenna, Eiliv; Fossmark, Reidar; Qvigstad, Gunnar; Soga, Jun

2008-01-01

8

Brain tumour stem cells  

Microsoft Academic Search

The dogma that the genesis of new cells is a negligible event in the adult mammalian brain has long influenced our perception and understanding of the origin and development of CNS tumours. The discovery that new neurons and glia are produced throughout life from neural stem cells provides new possibilities for the candidate cells of origin of CNS neoplasias. The

Rossella Galli; Brent A. Reynolds; Angelo L. Vescovi

2006-01-01

9

Brain Tumours Simulating Psychiatric Disease  

PubMed Central

Brain tumours may present with symptoms indistinguishable from psychiatric disease. The impression of most psychiatrists is that individuals suffering from brain tumour rarely appear among their patients. A priori reasoning based on evidence from neurological, neurosurgical and pathological sources suggests the contrary. The present study is a frequency analysis of cases of previously undiagnosed brain tumours admitted to either an open psychoneurotic ward or a mental hospital over a period of 15 years. The results support the impression held by psychiatrists that brain tumours are uncommon among psychiatric patients.

Hobbs, G. E.

1963-01-01

10

Tuberculosis simulating brain tumour.  

PubMed

The purpose of the study is to highlight the varied presentation of tuberculosis (TB) simulating a brain tumour. Headache and seizures are becoming frequent presenting complaints without any history of tuberculosis. The study comprises 1200 patients of both sexes with ages ranging from ten to sixty years. CT scan and MRI brain control with and without contrast medium were the investigations performed in these cases. In some patients Electroencephalography (EEG), cerebral angiography (DSA) and spectroscopy were also performed. The final diagnosis of tuberculosis was made on the basis of craniotomy, stereotactic and burr hole biopsies with histopathology in most of the cases. Forty per cent of the patients were followed up for eight months. They were put on anti-tuberculosis treatment with symptomatic and anti-epileptic drugs. The incidence was 544 and 757 per 100,000 in Africa and Indo Pakistan respectively. The male to female ratio was 1:1. Tuberculosis, especially with CNS involvement, is not only common in immunosuppressed patients in our setting, but TB has been and remains an important public health problem. TB may involve the CNS either as meningitis or as parenchymal granulomas or abscesses. Patients with brain TB usually present with fever, multiple cranial nerve involvement and occasional behavioural changes. CSF findings remain non specific in most cases. The most common sites are the cerebral hemisphere and basal ganglion in adults and the cerebellum in children. Tuberculosis has unique findings on brain CT and MRI. Cortical and subcortical locations are typical whereas the brain stem is a less common site. Tuberculosis lesions are usually solitary but multiple in 10% to 35% of cases. In spite of all these facts some cases of brain TB still need aggressive neurointervention to reach the final diagnosis of brain TB. Tuberculosis in the CNS may manifest in many different ways. So one should always include tuberculosis in the differential diagnosis in the etiology of delayed onset epilepsy and acute on chronic headache. In case of a discrepancy between clinical manifestations and CT/MRI findings, one can always anticipate tuberculous lesion in the brain. PMID:24059657

Chaudhry, U R; Farooq, M; Rauf, F; Bhatti, S K

2011-06-30

11

Negative Brain Scintiscan in Brain Tumours.  

National Technical Information Service (NTIS)

On the basis of 53 histologically verified and two histologically unidentified brain tumours, the author examined the reasons for these wrongly negative scintiscans. EEGs and angiographies carried out at about the same time were taken into account and com...

K. G. Dalke

1978-01-01

12

Neurofibromatosis type 1: brain stem tumours  

Microsoft Academic Search

We describe the clinical and imaging findings of brain stem tumours in patients with neurofibromatosis type 1 (NF1). The\\u000a NF1 patients imaged between January 1984 and January 1996 were reviewed and 25 patients were identified with a brain stem\\u000a tumour. Clinical, radiographical and pathological results were obtained by review of records and images. Brain stem tumour\\u000a identification occurred much later

L. T. Bilaniuk; P. T. Molloy; R. A. Zimmerman; P. C. Phillips; S. N. Vaughan; G. T. Liu; L. N. Sutton; M. Needle

1997-01-01

13

A second brain tumour and irradiation.  

PubMed Central

Three patients are described in whom irradiation of 2750 rad or more was used in the management of primary brain tumours, and 21 years or more later a second brain tumour of a different type occurred. One of the new tumours was a meningioma and the other two were cerebral astrocytomas. There is evidence to show that moderate doses of ionising radiations given in childhood for tinea capitis are associated with a late risk of developing a meningioma. Higher doses of radiation used for tumours in childhood are followed also by a late hazard of meningioma. There is insufficient evidence to implicate ionising radiations in the aetiology of gliomas. The oncogenic hazards of radiotherapy to the brain do not outweigh its therapeutic value in brain tumour. Images

Robinson, R G

1978-01-01

14

Identification of human brain tumour initiating cells  

Microsoft Academic Search

The cancer stem cell (CSC) hypothesis suggests that neoplastic clones are maintained exclusively by a rare fraction of cells with stem cell properties. Although the existence of CSCs in human leukaemia is established, little evidence exists for CSCs in solid tumours, except for breast cancer. Recently, we prospectively isolated a CD133+ cell subpopulation from human brain tumours that exhibited stem

Sheila K. Singh; Cynthia Hawkins; Ian D. Clarke; Jeremy A. Squire; Jane Bayani; Takuichiro Hide; R. Mark Henkelman; Michael D. Cusimano; Peter B. Dirks

2004-01-01

15

The 2007 WHO Classification of Tumours of the Central Nervous System  

PubMed Central

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.

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

2007-01-01

16

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

PubMed

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. PMID:17618441

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

2007-08-01

17

Neuropsychological Differences between Survivors of Supratentorial and Infratentorial Brain Tumours  

ERIC Educational Resources Information Center

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…

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

2011-01-01

18

Expression of thyroid transcription factor 1 in primary brain tumours  

PubMed Central

Background: Thyroid transcription factor 1 (TTF-1) is expressed in a proportion of carcinomas derived from follicular thyroid cells and respiratory epithelium. Immunohistochemical detection of this protein was shown previously to be a helpful aid in tumour diagnosis, specifically in deciding whether a tumour is primary to the lung/thyroid gland or metastatic. Recently, TTF-1 expression was also observed in certain areas of postnatal brain. Aim/Method: To investigate the expression of TTF-1 protein in a spectrum of 73 primary brain tumours including astrocytomas, glioblastomas, ependymomas, oligodendrogliomas, medulloblastomas, and gangliogliomas of different sites. Results: All the tumours were negative for TTF-1 except for two ependymomas of the third ventricle. Conclusions: The expression of TTF-1 in brain tumours appears to be site specific rather than associated with tumour dedifferentiation. The presented expression of TTF-1 protein in certain primary brain tumours should be taken into consideration when interpreting the immunohistochemical staining of brain tumours of uncertain primary site.

Zamecnik, J; Chanova, M; Kodet, R

2004-01-01

19

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

PubMed

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. PMID:23094909

Padma, A; Sukanesh, R

2013-01-01

20

Automated EEG signal analysis for identification of epilepsy seizures and brain tumour.  

PubMed

Abstract Electroencephalography (EEG) is a clinical test which records neuro-electrical activities generated by brain structures. EEG test results used to monitor brain diseases such as epilepsy seizure, brain tumours, toxic encephalopathies infections and cerebrovascular disorders. Due to the extreme variation in the EEG morphologies, manual analysis of the EEG signal is laborious, time consuming and requires skilled interpreters, who by the nature of the task are prone to subjective judegment and error. Further, manual analysis of the EEG results often fails to detect and uncover subtle features. This paper proposes an automated EEG analysis method by combining digital signal processing and neural network techniques, which will remove error and subjectivity associated with manual analysis and identifies the existence of epilepsy seizure and brain tumour diseases. The system uses multi-wavelet transform for feature extraction in which an input EEG signal is decomposed in a sub-signal. Irregularities and unpredictable fluctuations present in the decomposed signal are measured using approximate entropy. A feed-forward neural network is used to classify the EEG signal as a normal, epilepsy or brain tumour signal. The proposed technique is implemented and tested on data of 500 EEG signals for each disease. Results are promising, with classification accuracy of 98% for normal, 93% for epilepsy and 87% for brain tumour. Along with classification, the paper also highlights the EEG abnormalities associated with brain tumour and epilepsy seizure. PMID:24116656

Sharanreddy, M; Kulkarni, P K

2013-11-01

21

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

PubMed Central

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.

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

2003-01-01

22

Osteopenia in children surviving brain tumours.  

PubMed

Osteopenia has been reported in children surviving acute lymphoblastic leukaemia, apparently as a consequence of therapy. It has been suggested that cranial irradiation may play a crucial role in this disorder. To explore that possibility, survivors of brain tumours in childhood, all of whom had received radiotherapy, were examined for evidence of bone mineral loss. 19 children were assessed, on average at 7 years after treatment. Measurements of growth velocities, plain radiography of the skeleton, bone densitometry, health-related quality of life and physical activity were undertaken. Growth hormone (GH) deficiency had been detected in 6 children and 5 had received GH replacement, for a minimum of more than 3 years. 9 children were radiographically osteopenic (including the 5 who had received GH). Z scores for bone mineral density (BMD) were negative in the majority of children. Health-related quality of life was less and pain more frequent in those with low BMD scores. Pain was correlated negatively with both free-time activity and seasonal activity (P < 0.01). Osteopenia is a common sequel of therapy in children with brain tumours. Those with osteopenia have more pain and more compromised, health-related quality of life than those who are not osteopenic, and pain significantly limits physical activity. The pathogenesis of osteopenia in these children is still uncertain, but is likely to be multifactorial. PMID:9797700

Barr, R D; Simpson, T; Webber, C E; Gill, G J; Hay, J; Eves, M; Whitton, A C

1998-05-01

23

Expression of growth factor receptors in human brain tumours.  

PubMed Central

The expression of the EGF receptor, c-erbB-2 and PDGF receptor proteins has been studied in a series of human brain tumour biopsies and cell lines. Western blotting was used to determine the amount of protein present and their intrinsic and ligand promoted enzyme activities were studied by immunoprecipitation followed by autophosphorylation. EGF receptors were found to be expressed at very high levels in 40% of primary tumour biopsies, but at uniformly low levels in tumour derived cell lines. The c-erbB-2 protein was not detected in tumour biopsies, but was present at variable, but low levels in extracts of tumour cell lines. PDGF receptors were also found at moderate to low levels in both primary tumours and cell lines. The EGF receptor gene was amplified in four out of 14 primary tumours and this generally correlated with high levels of protein expression. The c-erbB-2 gene was not amplified. Employing the polymerase chain reaction and sequence specific oligonucleotides as probes there was no evidence of mutations in the c-erbB-2 gene transmembrane region. These results suggest that alterations of expression of the EGF receptor may play a role in human brain tumours. There was however no evidence for aberrant expression of the c-erbB-2 protein. Additional experiments are required to assess the influence of PDGF receptor expression in brain tumour cells. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6

Tuzi, N. L.; Venter, D. J.; Kumar, S.; Staddon, S. L.; Lemoine, N. R.; Gullick, W. J.

1991-01-01

24

Spectral and lifetime domain measurements of rat brain tumours  

NASA Astrophysics Data System (ADS)

During glioblastoma surgery, delineation of the brain tumour margins remains difficult especially since infiltrated and normal tissues have the same visual appearance. This problematic constitutes our research interest. We developed a fibre-optical fluorescence probe for spectroscopic and time domain measurements. First measurements of endogenous tissue fluorescence were performed on fresh and fixed rat tumour brain slices. Spectral characteristics, fluorescence redox ratios and fluorescence lifetime measurements were analysed. Fluorescence information collected from both, lifetime and spectroscopic experiments, appeared promising for tumour tissue discrimination. Two photon measurements were performed on the same fixed tissue. Different wavelengths are used to acquire two-photon excitation-fluorescence of tumorous and healthy sites.

Abi Haidar, D.; Leh, B.; Allaoua, K.; Genoux, A.; Siebert, R.; Steffenhagen, M.; Peyrot, D.; Sandeau, N.; Vever-Bizet, C.; Bourg-Heckly, G.; Chebbi, I.; Collado-Hilly, M.

2012-02-01

25

[The 2007 World Health Organisation classification of tumours of the central nervous system, comparison with 2000 classification].  

PubMed

WHO Classification of Tumours of the Central Nervous System from the 2007 is distinguished from the previous 2000 classification by a few conceptual modifications, changes in the terminology and seven newly codified tumour entities. The text shows a short comparison of both classifications emphasising the most important changes from the surgical neuropathology point of view. The newly codified entities are: angiocentric glioma, pilomyxoid astrocytoma, papillary glioneuronal tumor, rosette-forming glioneuronal tumor of the 4th ventricle, papillary tumour of the pineal region, spindle cell oncocytoma and pituicytoma. Mostly, they are rare tumours already known from the literature. Based on new knowledge from the molecular pathology the paragraphs about tumour genetics were markedly changed. The complexity and diversity of tumours of the nervous system is enormous, and, not surprisingly, some problematic questions of classification and grading remain unresolved. PMID:18819324

Rychlý, B; Sidlová, H; Dani?, D

2008-04-01

26

Development of luciferase tagged brain tumour models in mice for chemotherapy intervention studies  

Microsoft Academic Search

The blood–brain barrier (BBB) is considered one of the major causes for the low efficacy of cytotoxic compounds against primary brain tumours. The aim of this study was to develop intracranial tumour models in mice featuring intact or locally disrupted BBB properties, which can be used in testing chemotherapy against brain tumours. These tumours were established by intracranial injection of

E. M. Kemper; W. P. J. Leenders; B. Küsters; S. Lyons; T. Buckle; A. Heerschap; W. Boogerd; J. H. Beijnen; O. van Tellingen

2006-01-01

27

[Rare brain tumour in 6-month-old girl].  

PubMed

A six-month old girl presented with repetitive episodes of vomiting. Soon after admission to hospital she had convulsions. Computertomography showed a tumour in the third ventricle. She was non-radically operated. Histology showed an atypical teratoid/rhabdoid tumour (AT/RT). No active treatment was initiated, and the patient died three months later. AT/RT is a very rare tumor of the brain. It occurs primarily in early childhood. AT/RT is a very aggressive and rapidly progressing tumour. PMID:19208337

Handrup, Mette Møller; Schrøder, Henrik

2009-02-01

28

Cytokine Patterns in Brain Tumour Progression  

PubMed Central

Inflammation represents the immune system response to external or internal aggressors such as injury or infection in certain tissues. The body's response to cancer has many parallels with inflammation and repair; the inflammatory cells and cytokines present in tumours are more likely to contribute to tumour growth, progression, and immunosuppression, rather than in building an effective antitumour defence. Using new proteomic technology, we have investigated serum profile of pro- (IL-1?, IL-6, IL-8, IL-12, GM-CSF, and TNF-?) and anti-inflammatory cytokines (IL-4, IL-10), along with angiogenic factors (VEGF, bFGF) in order to assess tumoural aggressiveness. Our results indicate significant dysregulation in serum levels of cytokines and angiogenic factors, with over threefold upregulation of IL-6, IL-1?, TNF-?, and IL-10 and up to twofold upregulation of VEGF, FGF-2, IL-8, IL-2, and GM-CSF. These molecules are involved in tumour progression and aggressiveness, and are also involved in a generation of disease associated pain.

Albulescu, Radu; Codrici, Elena; Popescu, Ionela Daniela; Mihai, Simona; Necula, Laura Georgiana; Petrescu, Daniel; Teodoru, Mihaela; Tanase, Cristiana Pistol

2013-01-01

29

Immunocytochemical evaluation of proliferative activity in human brain tumours.  

PubMed

The immunocytochemical expression of the antigen reacting with the monoclonal antibody Ki-67 (Ki-67 positivity) was investigated in 50 imprint preparations from human brain tumours. Data were related to tumour proliferative activity, as determined from in vivo bromodeoxyuridine (BrdU) incorporation (BrdU-labelling index, BrdU-LI) and histology. The percentage of Ki-67-positive cells was greater than the corresponding BrdU-LI value in all tumours, and the differences in Ki-67 positivity among tumour subtypes paralleled the BrdU-LI differences. Both the BrdU-LI and the percentage of Ki-67 positive cells were significantly greater (P less than 0.005) in the group of clinically aggressive adult tumours, histologically identified as anaplastic astrocytomas and glioblastomas, than in the less aggressive ones (oligodendroglioma, meningiomas, schwannomas, pituitary adenomas, dermoid cyst) and in the cerebral metastatic localizations. These data suggest that Ki-67 positivity, which is easily evaluated with immunocytochemistry, is related to the proliferative activity of brain tumours and that this parameter is endowed with clinical significance. PMID:2275874

Girino, M; Riccardi, A; Danova, M; Gaetani, P; Butti, G; Giordano, M; Cuomo, A

1990-09-01

30

[WHO classification of tumours of the CNS: revised edition of 2007 with critical comments on the typing und grading of common-type diffuse gliomas].  

PubMed

The fourth edition of the WHO classification of tumours of the CNS was published in 2007. Six new entities were codified: angiocentric glioma (AG); papillary glioneuronal tumour (PGNT); rosette-forming glioneuronal tumour of the fourth ventricle (RGNT); papillary tumour of the pineal region (PTPR); spindle cell oncocytoma of the adenohypophysis (SCO); and pituicytoma. Furthermore, six histological variants of well-known brain tumours have been added, partially because they show different biological behaviour and/or prognosis: pilomyxoid astrocytoma; atypical choroid plexus papilloma; medulloblastoma with extensive nodularity; anaplastic medulloblastoma; extraventricular neurocytoma; non-specific variant of dysembryoplastic neuroepithelial tumour (DNT). The new entities and variants are discussed in this review. Moreover, the typing und grading of common-type diffuse gliomas, as well as the WHO grading system, are critically reviewed, particularly with regard to the prognostically important differential diagnosis of diffuse astrocytomas und oligodendrogliomas. PMID:18820922

Feiden, S; Feiden, W

2008-11-01

31

Current approaches to the treatment of metastatic brain tumours  

PubMed Central

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.

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.

2014-01-01

32

Molecular approaches to brain tumour invasion.  

PubMed

In glioma cells, the stimulatory input of extracellular matrix components and an increased sensitivity to growth factors result in a high proliferative and migratory behaviour. Cell surface receptor interactions play pivotal roles in converging information about conditions in the environment immediately outside the cell. The transduced signal, in turn induces a response within the cell that provokes a specific behaviour. Cellular migration and cell proliferation are interwoven processes that share several common intracellular pathways. The major cross-links are the phosphoinositol phosphate regulating enzymes, PI-3 kinase and PTEN, the focal adhesion kinase (FAK) and the tumour suppressor p53. An understanding of the interaction between the molecular participants involved in migration and proliferation will promote the design of new treatments. A full understanding of the basis of the invasiveness of tumour cells remains elusive. Gene and protein expression are being studied, using modern techniques such as microarray analysis, SAGE and 2-D protein gels. Transient and permanent protein-protein interactions and recruitment of proteins to specialised cellular domains are equally important in regulating cellular invasion and presumably will attract more attention in future. PMID:14663559

Günther, W; Skaftnesmo, K-O; Arnold, H; Terzis, A J A

2003-12-01

33

Value of 11C-methionine PET in imaging brain tumours and metastases.  

PubMed

(11)C-methionine (MET) is the most popular amino acid tracer used in PET imaging of brain tumours. Because of its characteristics, MET PET provides a high detection rate of brain tumours and good lesion delineation. This review focuses on the role of MET PET in imaging cerebral gliomas. The Introduction provides a clinical overview of what is important in primary brain tumours, recurrent brain tumours and brain metastases. The indications for radiotherapy and the results and problems arising after chemoradiotherapy in relation to imaging (pseudoprogression or radionecrosis) are discussed. The working mechanism, scan interpretation and quantification possibilities of MET PET are then explained. A literature overview is given of the role of MET PET in primary gliomas (diagnostic accuracy, grading, prognosis, assessment of tumour extent, biopsy and radiotherapy planning), in brain metastases, and in the differentiation between tumour recurrence and radiation necrosis. Finally, MET PET is compared to other nuclear imaging possibilities in brain tumour imaging. PMID:23232505

Glaudemans, Andor W J M; Enting, Roelien H; Heesters, Mart A A M; Dierckx, Rudi A J O; van Rheenen, Ronald W J; Walenkamp, Annemiek M E; Slart, Riemer H J A

2013-04-01

34

Brain MRI in fetuses with cardiac tumours.  

PubMed

Tuberous sclerosis complex (TSC) is an autosomal dominant multisystem disorder which affects the skin, brain, heart and other organs. It is caused by mutations of two genes: TSC1 (on chromosome 9q34) or TSC2 (on 16p13.3). 70% of cases are sporadic with new mutations. This study aimed to highlight the utility of prenatal MRI as an adjunct imaging modality in the diagnosis and prognosis of tuberous sclerosis complex. Prenatal ultrasound and magnetic resonance imaging were performed in seven fetuses at a gestational age of 30, 32, 34 and 35 weeks using a 1.5 T MRI scanner. SSFSE,T2- and FGRE/T1-weighted images were obtained in axial, coronal and sagittal planes. Postnatal MRI was performed in two cases. Intracardiac tumors (rhabdomyomas) were revealed on ultrasound in all fetuses. On sonographic examination the brain tissue appeared normal in all cases. Brain MRI revealed focal low-signal-intensity lesions, localized along the walls of the lateral ventricles of five fetuses. Another hypointense lesion was seen at the grey/white matter junction in one case. Brain MRI of two fetuses was normal. The diagnosis of TSC was established in five cases. Postnatal MRI in two cases confirmed prenatal findings. MRI allows more complete evaluation of the fetus and helps to determine the diagnosis and prognosis in cases of TSC. The use of prenatal MR imaging in addition to prenatal sonography has the potential to improve genetic counseling and prenatal diagnosis of patients with tuberous sclerosis. PMID:24299935

Jurkiewicz, E; Bekiesi?ska-Figatowska, M; Romaniuk-Doroszewska, A; Dangel, J

2007-10-31

35

Primary pulmonary solitary fibrous tumour with brain metastases.  

PubMed

Solitary fibrous tumour (SFT) is a mesenchymal neoplasm of subendothelial origin that can be found in all anatomical locations, but rarely in the lungs. A 71-year old female was referred to our hospital because of the increase in size of a solitary pulmonary mass. Chest contrast-enhanced dynamic computed tomography showed a well-circumscribed lobulated mass measuring 3.1×1.6 cm in the posterior segment of the right upper lobe of the lung. Positron emission tomography with 18F-fluorodeoxyglucose (FDG) demonstrated that the mass had high FDG uptake. A right upper lobectomy of the lung and mediastinal lymphadenectomy were performed. The tumour was pathologically diagnosed as an SFT. Seven months later, the patient was found to have brain metastases of the tumour, which led to dizziness. A craniotomy and successive radiosurgery with a gamma knife were performed for the metastatic tumours. She is still alive without evidence of disease 12 months after the treatment of the metastases. Pulmonary SFT seldom behaves aggressively, and only two previous cases of primary pulmonary SFT with brain metastases have been reported. Local therapy including surgery and radiotherapy against metastases from SFT could help improve the survival of such patients. PMID:23711464

Ozeki, Naoki; Kawaguchi, Koji; Taniguchi, Tetsuo; Yokoi, Kohei

2014-02-01

36

Brain tumours in Sweden 1996: care and costs  

PubMed Central

OBJECTIVES—Brain tumours cause considerable concern due to a high mortality and there are increasing efforts to provide adequate care, sometimes outside hospitals. Health care utilisation, direct costs of care, and the indirect social cost of morbidity and early mortality caused by brain tumours in Sweden in the year 1996 was analysed.?METHODS—Quantification of ambulatory care, care in hospital, long term and palliative/terminal care, drug consumption, temporary as well as long term morbidity, and mortality from comprehensive national data sources. Direct costs were calculated using 1996charges. Indirect costs were calculated by sex and age specific salaries. A sensitivity analysis considered the impact of alternative estimates of each item.?RESULTS—Indirect costs were 75% of the total and were caused mainly by early mortality. Direct costs were predominantly for care in hospital, long term care, and home health care. Among direct costs, astrocytomas III-IV and meningiomas accounted for 42% and 30% respectively.?CONCLUSIONS—The cost of illness from brain tumours reflects the characteristics of these malignancies. Despite their low incidence rate, the economic impact caused by high mortality among young persons is a predominant trait. Costs of acute hospital care and also long term care and home care are considerable.??

Blomqvist, P; Lycke, J; Strang, P; Tornqvist, H; Ekbom, A

2000-01-01

37

Operative Classification of Brain Arteriovenous Malformation  

PubMed Central

Summary The most important issue when dealing with a patient with a brain AVM is the decision whether to treat or not. Only after this decision has been made, taking into consideration a number of factors depending on both the patient and the specific type of AVM, can the best option for treatment be chosen. An operative classification of brain AVMs, previously adopted in the Department of Neuroradiology and Neurosurgery of Verona (Italy) and published in this journal, was subjected to validation in a consecutive group of 104 patients clinically followed for at least three years after completion of treatment. This classification, slightly modified from the original version concerning the importance of some specific items, allowed us to assess the indication to treat in each case, whatever type of treatment was offered to the patient.

Beltramello, A.; Ricciardi, G.K.; Piovan, E.; Zampieri, P.; Pasqualin, A.; Nicolato, A.; Foroni, R.; Sala, F.; Bassi, L.; Gerosa, M.

2009-01-01

38

LDH isoenzymes in cerebrospinal fluid in various brain tumours.  

PubMed Central

This study examined the isoenzymatic pattern of LDH in the cerebrospinal fluid (CSF) as well as the ratio between the five fractions of LDH among patients with various brain tumours, carcinomatous meningitis and control groups. LDH 1/LDH 2 less than 1 was found significant for carcinomatous meningitis (p less than 0.001) and brain metastases (p less than 0.001). LDH 1/LDH 2 ratio was found to be significantly lower in carcinomatous meningitis than in brain metastases (p less than 0.05). No LDH 1/LDH 2 ratios smaller than 1 were found in the other groups. The LDH 1/LDH 2 ratio smaller than 1 was found in the early stage of carcinomatous meningitis without other evidences of the involvement of the leptomeninges. Examination of LDH 1/LDH 2 can be found as an adjunctive method to identify brain metastases and carcinomatous meningitis at the initial stage.

Lampl, Y; Paniri, Y; Eshel, Y; Sarova-Pinhas, I

1990-01-01

39

MSSA brain abscess and pyomyositis presenting as brain tumour and DVT.  

PubMed

A 66-year-old man with a recent radiographic diagnosis of a parietal brain tumour presented with severe left thigh pain that prevented ambulation. On examination, his left anterior thigh was mildly swollen without erythema. Initial concern was for deep vein thrombosis in the setting of brain malignancy or necrotising soft tissue infection. Subsequent imaging and biopsies revealed methicillin sensitive Staphylococcus aureus (MSSA) pyomyositis of the left thigh and MSSA brain abscess. PMID:23997073

Narayanan, Maya; Mookherjee, Somnath; Spector, Tara B; White, Andrew Austin

2013-01-01

40

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

PubMed

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

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

1991-09-01

41

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

PubMed Central

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.

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

1991-01-01

42

Neuropsychometric evaluation of long-term survivors of adult brain tumours: relationship with tumour and treatment parameters  

Microsoft Academic Search

Background: Cognitive deficits are the hallmark of dose limiting late radiation morbidity in the CNS. Little is known about the neuropsychometric morbidity of treatment in adults with primary brain tumours. We set out to evaluate systematically the neuropsychometric function of all long-term survivors in order to document the frequency and severity of impairment and study its relationship with tumour and

A. Gregor; A. Cull; E. Traynor; M. Stewart; F. Lander; S. Love

1996-01-01

43

Adaptive multiclass classification for brain computer interfaces.  

PubMed

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. PMID:24684452

Llera, A; Gómez, V; Kappen, H J

2014-06-01

44

Endocrine disorders following treatment of childhood brain tumours.  

PubMed Central

We have studied the long-term endocrine effects of treatment on 144 children treated for brain tumours. All received cranial irradiation, 86 also received spinal irradiation and 34 chemotherapy. Almost all patients (140 of 144) had evidence of growth hormone insufficiency. Treatment with growth hormone was effective in maintaining normal growth but could not restore a deficit incurred by delay in instituting treatment. The effect of spinal irradiation on spinal growth was not corrected by growth hormone. As spinal growth makes the major contribution to the pubertal growth spurt and limb length the major contribution to childhood growth, treatment with GH will have maximal effect on leg length if instituted before the onset of puberty. Primary thyroid dysfunction was found in 11 of 47 children (23%) treated with craniospinal irradiation but in none treated with cranial irradiation alone. The incidence rose to 69% of 29 children treated with spinal irradiation and chemotherapy and to 50% of four children treated with cranial irradiation and chemotherapy. This effect of chemotherapy has not previously been reported and was detected by us through measurement of serum TSH concentration. Primary thyroid dysfunction requires treatment with thyroxine to prevent increasing the risk of secondary thyroid tumours. Seven of 20 girls (35%) treated with spinal irradiation had primary ovarian dysfunction as determined by raised gonadotrophin levels. Chemotherapy increased this, but not significantly. Three of 15 boys (20%) treated with chemotherapy had primary testicular dysfunction. Gonadotrophin deficiency occurred in seven boys. Four of 90 children had deficiency of cortisol secretion in response to hypoglycaemia. These results confirm the requirement for long-term follow-up of children treated for brain tumours from the endocrine point of view. Anticipation of hormone deficiencies and replacement treatment can improve the quality of life of survivors.

Livesey, E. A.; Hindmarsh, P. C.; Brook, C. G.; Whitton, A. C.; Bloom, H. J.; Tobias, J. S.; Godlee, J. N.; Britton, J.

1990-01-01

45

Identification of brain tumour initiating cells using the stem cell marker aldehyde dehydrogenase.  

PubMed

Aldehyde dehydrogenase (ALDH) has been identified in stem cells from both normal and cancerous tissues. This study aimed to evaluate the potential of ALDH as a universal brain tumour initiating cell (BTIC) marker applicable to primary brain tumours and their biological role in maintaining stem cell status. Cells from various primary brain tumours (24paediatric and 6 adult brain tumours) were stained with Aldefluor and sorted by flow cytometry. We investigated the impact of ALDH expression on BTIC characteristics in vitro and on tumourigenic potential in vivo. Primary brain tumours showed universal expression of ALDH, with 0.3-28.9% of the cells in various tumours identified as ALDH(+). The proportion of CD133(+) cells within ALDH(+) is higher than ALDH cells. ALDH(+) cells generate neurospheres with high proliferative potential, express neural stem cell markers and differentiate into multiple nervous system lineages. ALDH(+) cells tend to show high expression of induced pluripotent stem cell-related genes. Notably, targeted knockdown of ALDH1 by shRNA interference in BTICs potently disturbed their self-renewing ability. After 3months, ALDH(+) cells gave rise to tumours in 93% of mice whereas ALDH cells did not. The characteristic pathology of mice brain tumours from ALDH(+) cells was similar to that of human brain tumours, and these cells are highly proliferative in vivo. Our data suggest that primary brain tumours contain distinct subpopulations of cells that have high expression levels of ALDH and BTIC characteristics. ALDH might be a potential therapeutic target applicable to primary brain tumours. PMID:24103144

Choi, Seung Ah; Lee, Ji Yeoun; Phi, Ji Hoon; Wang, Kyu-Chang; Park, Chul-Kee; Park, Sung-Hye; Kim, Seung-Ki

2014-01-01

46

Classification trees for fast segmentation of DTI brain fiber tracts  

Microsoft Academic Search

A method is proposed for modeling and classification of White Matter fiber tracts in the brain. The presented scheme uses classification trees in conjunction with spatial representation of the individual fibers, in order to capture the characteristic behavior of fibers belonging to a specific anatomical structure. The method is characterized by high classification speed, under 3 seconds for all the

Gali Zimmerman-Moreno; Arnaldo Mayer; Hayit Greenspan

2008-01-01

47

Distinguishing Among 3-D Distributions for Brain Image Data Classification  

Microsoft Academic Search

To facilitate the process of discovering brain structure-function associations from image and clinical data, we have developed classification tools for brain image data that are based on measures of dissimilarity between probability distributions. We propose statistical as well as non-statistical methods for classifying three dimensional probability distributions of regions of interest (ROIs) in brain images. The statistical methods are based

A. Lazarevic; D. Pokrajac; V. Megalooikonomou; Z. Obradovic

2001-01-01

48

Combinations of genetic mutations in the adult neural stem cell compartment determine brain tumour phenotypes  

PubMed Central

It has been suggested that intrinsic brain tumours originate from a neural stem/progenitor cell population in the subventricular zone of the post-natal brain. However, the influence of the initial genetic mutation on the phenotype as well as the contribution of mature astrocytes to the formation of brain tumours is still not understood. We deleted Rb/p53, Rb/p53/PTEN or PTEN/p53 in adult subventricular stem cells; in ectopically neurografted stem cells; in mature parenchymal astrocytes and in transplanted astrocytes. We found that only stem cells, but not astrocytes, gave rise to brain tumours, independent of their location. This suggests a cell autonomous mechanism that enables stem cells to generate brain tumours, whereas mature astrocytes do not form brain tumours in adults. Recombination of PTEN/p53 gave rise to gliomas whereas deletion of Rb/p53 or Rb/p53/PTEN generated primitive neuroectodermal tumours (PNET), indicating an important role of an initial Rb loss in driving the PNET phenotype. Our study underlines an important role of stem cells and the relevance of initial genetic mutations in the pathogenesis and phenotype of brain tumours.

Jacques, Thomas S; Swales, Alexander; Brzozowski, Monika J; Henriquez, Nico V; Linehan, Jacqueline M; Mirzadeh, Zaman; O' Malley, Catherine; Naumann, Heike; Alvarez-Buylla, Arturo; Brandner, Sebastian

2010-01-01

49

Brain extraction based on locally linear representation-based classification.  

PubMed

Brain extraction is an important procedure in brain image analysis. Although numerous brain extraction methods have been presented, enhancing brain extraction methods remains challenging because brain MRI images exhibit complex characteristics, such as anatomical variability and intensity differences across different sequences and scanners. To address this problem, we present a Locally Linear Representation-based Classification (LLRC) method for brain extraction. A novel classification framework is derived by introducing the locally linear representation to the classical classification model. Under this classification framework, a common label fusion approach can be considered as a special case and thoroughly interpreted. Locality is important to calculate fusion weights for LLRC; this factor is also considered to determine that Local Anchor Embedding is more applicable in solving locally linear coefficients compared with other linear representation approaches. Moreover, LLRC supplies a way to learn the optimal classification scores of the training samples in the dictionary to obtain accurate classification. The International Consortium for Brain Mapping and the Alzheimer's Disease Neuroimaging Initiative databases were used to build a training dataset containing 70 scans. To evaluate the proposed method, we used four publicly available datasets (IBSR1, IBSR2, LPBA40, and ADNI3T, with a total of 241 scans). Experimental results demonstrate that the proposed method outperforms the four common brain extraction methods (BET, BSE, GCUT, and ROBEX), and is comparable to the performance of BEaST, while being more accurate on some datasets compared with BEaST. PMID:24525169

Huang, Meiyan; Yang, Wei; Jiang, Jun; Wu, Yao; Zhang, Yu; Chen, Wufan; Feng, Qianjin

2014-05-15

50

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

PubMed

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. Keywords: WHO classification - sarcoma - soft tissues - bones - tumour. PMID:24758500

Zambo, Iva; Veselý, Karel

2014-04-01

51

Combined radiotherapy and chemotherapy for high-grade brain tumours  

NASA Astrophysics Data System (ADS)

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, is used in combination with both TMZ and radiation. The results show that ABT-888 significantly enhances TMZ and radiation cell killing, regardless of the MGMT status. In summary, the findings of this research demonstrate that the use of particle therapy and PARP inhibitors are particularly promising and might improve the treatment outcome in patients with GBM.

Barazzuol, Lara

52

Primary malignant duodenal tumours: a point of view and a proposal of classification.  

PubMed

To date, malignant duodenal tumours have remained obscure subject-matter although they were first described in the eighteenth century. Recent development in technology and in anatomohistopathology makes it necessary to review the duodenal tumours classification, especially in relation to the progressive development of stromal and neuroendocrine forms. In the literature, precise epidemiological data are not reported and, as regards some duodenal tumours, simply do not exist. Series are generally either surgical, anatomopathological or gastroenterological. Hospital centres need to establish a collaboration which gathers new observed cases to avoid the dispersion of case series. Thus, a European Register will be established to report the real incidence by analyzing the specific differential elements. PMID:10568125

Testino, G; Cornaggia, M

1999-09-01

53

Cell proliferation in serial biopsies through human malignant brain tumours: measurement using Ki67 antibody labelling.  

PubMed

Cell proliferation was assessed in brain tumours using the monoclonal antibody Ki67 which recognizes a nuclear antigen expressed by proliferating cells. Using a novel stereotactic biopsy procedure, serial 1 cm biopsies were taken along a trajectory through six malignant brain tumours. Specimens were also obtained from 10 other brain tumours during conventional surgery. The percentage of Ki67 positive cells was determined as a fraction of the total number of tumour cells present. The Ki67 index for anaplastic astrocytomas and glioblastomas was significantly higher (Ki67 index range 11-18%) than that for benign or low grade tumours. Significant variation in proliferation was measured along the biopsy track through individual tumours (e.g. 0-12.3%) which correlated well with histological appearance. The Ki67 indices of normal brain were very low. In general the Ki67 indices increased with increasing histological grade and also appear to be a useful indicator of the active tumour volume and margin. This method provides spatial information about tumour proliferation which may be used to decide between different treatments and relate to prognosis. PMID:1892572

Parkins, C S; Darling, J L; Gill, S S; Revesz, T; Thomas, D G

1991-01-01

54

Elemental regional distribution in human brain tumours — PIXE analysis of biopsy and autopsy samples  

NASA Astrophysics Data System (ADS)

The elemental regional distribution in human brain tissue was obtained using PIXE analysis. A histo-pathological investigation was used to classify the samples into three different groups: (1) normal tissue, (2) tumour front and (3) tumour centre. Significant differences between the mean values of phosphorous, calcium, iron, zinc and selenium concentrations in each group are reported.

Tapper, U. A. S.; Malmqvist, K. G.; Brun, A.; Salford, L. G.

1987-03-01

55

Three-dimensional vasculature reconstruction of tumour microenvironment via local clustering and classification.  

PubMed

The vasculature inside breast cancers is one important component of the tumour microenvironment. The investigation of its spatial morphology, distribution and interactions with cancer cells, including cancer stem cells, is essential for elucidating mechanisms of tumour development and treatment response. Using confocal microscopy and fluorescent markers, we have acquired three-dimensional images of vasculature within mammary tumours and normal mammary gland of mouse models. However, it is difficult to segment and reconstruct complex vasculature accurately from the in vivo three-dimensional images owing to the existence of uneven intensity and regions with low signal-to-noise ratios (SNR). To overcome these challenges, we have developed a novel three-dimensional vasculature segmentation method based on local clustering and classification. First, images of vasculature are clustered into local regions, whose boundaries well delineate vasculature even in low SNR and uneven intensity regions. Then local regions belonging to vasculature are identified by applying a semi-supervised classification method based on three informative features of the local regions. Comparison of results using simulated and real vasculature images, from mouse mammary tumours and normal mammary gland, shows that the new method outperforms existing methods, and can be used for three-dimensional images with uneven background and low SNR to achieve accurate vasculature reconstruction. PMID:24511379

Zhu, Yanqiao; Li, Fuhai; Vadakkan, Tegy J; Zhang, Mei; Landua, John; Wei, Wei; Ma, Jinwen; Dickinson, Mary E; Rosen, Jeffrey M; Lewis, Michael T; Zhan, Ming; Wong, Stephen T C

2013-08-01

56

A case series discussing the anaesthetic management of pregnant patients with brain tumours  

PubMed Central

Pregnancy may aggravate the natural history of an intracranial tumour, and may even unmask a previously unknown diagnosis. Here we present a series of seven patients who had brain tumours during pregnancy. The aim of this case series is to characterize the current perioperative management and to suggest evidence based guidelines for the anaesthetic management of pregnant females with brain tumours. This is a retrospective study. Information on pregnant patients diagnosed with brain tumours that underwent caesarean section (CS) and/or brain tumour resection from May 2003 through June 2008 was obtained from the Department of General Anaesthesia and the Rose Ella Burkhardt Brain Tumour & Neuro-Oncology Centre (BBTC) at the Cleveland Clinic, OH, USA. The mean age was 34.5 years (range 29-40 years old). Six patients had glioma, two of whom had concomitant craniotomy and CS. Six cases had the tumour in the frontal lobe. Four cases were operated on under general anaesthesia and three underwent awake craniotomy. The neonatal outcomes of the six patients with elective or emergent delivery were six viable infants with normal Apgar scores. Pregnancy was terminated in the 7th patient. In conclusion, good knowledge of the variable anesthetic agents and their effects on the fetus is very important in managing those patients.

Farag, Ehab

2013-01-01

57

Incidence rates of the primary brain tumours in Georgia - a population-based study  

PubMed Central

Background To determine the incidence rate and to describe other basic epidemiological data of primary brain tumours in a population-based study in Georgia, performed between March 2009 and March 2011. Methods Active case ascertainment was used to identify brain tumour cases by searching neuroradiology scan reports and medical records from all participating medical institutions, covering almost 100% of the neurooncology patients in the country. Results A total of 980 new cases were identified during the two-year period. For a population of almost 4.5 million, the overall annual incidence rate was 10.62 per 100,000 person-years, age-standardized to the year 2000 US population (ASR). Non-malignant tumours constituted about 65.5% of all tumours. Males accounted for 44% and females for 56% of the cases. Among classified tumours, age-standardized incidence rates by histology were highest for meningiomas (2.65/100,000), pituitary adenoma (1.23/100,000) and glioblastomas (0.51/100,000). ASR were higher among females than males for all primary brain tumours (10.35 vs. 9.48/100,000) as well as for main histology groups except for neuroepithelial, lymphomas and germ cell tumours. Conclusions The annual incidence rate of all primary brain tumours in Georgia, though comparable with some European registry data, is low in comparison with the 2004–2005 Central Brain Tumor Registry of the United States (CBTRUS) database, which may reflect variations in reporting and methodology. The higher percentage of unclassified tumours (37.8%) probably also affects the discrepancies between our and CBTRUS findings. However, the most frequently reported tumour was meningioma with a significant predominance in females, which is consistent with CBTRUS data.

2014-01-01

58

Classification of breast tumour using electrical impedance and machine learning techniques.  

PubMed

When a breast lump is detected through palpation, mammography or ultrasonography, the final test for characterization of the tumour, whether it is malignant or benign, is biopsy. This is invasive and carries hazards associated with any surgical procedures. The present work was undertaken to study the feasibility for such characterization using non-invasive electrical impedance measurements and machine learning techniques. Because of changes in cell morphology of malignant and benign tumours, changes are expected in impedance at a fixed frequency, and versus frequency of measurement. Tetrapolar impedance measurement (TPIM) using four electrodes at the corners of a square region of sides 4 cm was used for zone localization. Data of impedance in two orthogonal directions, measured at 5 and 200 kHz from 19 subjects, and their respective slopes with frequency were subjected to machine learning procedures through the use of feature plots. These patients had single or multiple tumours of various types in one or both breasts, and four of them had malignant tumours, as diagnosed by core biopsy. Although size and depth of the tumours are expected to affect the measurements, this preliminary work ignored these effects. Selecting 12 features from the above measurements, feature plots were drawn for the 19 patients, which displayed considerable overlap between malignant and benign cases. However, based on observed qualitative trend of the measured values, when all the feature values were divided by respective ages, the two types of tumours separated out reasonably well. Using K-NN classification method the results obtained are, positive prediction value: 60%, negative prediction value: 93%, sensitivity: 75%, specificity: 87% and efficacy: 84%, which are very good for such a test on a small sample size. Study on a larger sample is expected to give confidence in this technique, and further improvement of the technique may have the ability to replace biopsy. PMID:24844143

Al Amin, Abdullah; Parvin, Shahnaj; Kadir, M A; Tahmid, Tasmia; Alam, S Kaisar; Siddique-e Rabbani, K

2014-06-01

59

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

PubMed Central

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.

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

2013-01-01

60

Simple Fully Automated Group Classification on Brain fMRI  

SciTech Connect

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.

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

2010-04-14

61

Bone morphogenetic proteins inhibit the tumorigenic potential of human brain tumour-initiating cells  

Microsoft Academic Search

Transformed, oncogenic precursors, possessing both defining neural-stem-cell properties and the ability to initiate intracerebral tumours, have been identified in human brain cancers. Here we report that bone morphogenetic proteins (BMPs), amongst which BMP4 elicits the strongest effect, trigger a significant reduction in the stem-like, tumour-initiating precursors of human glioblastomas (GBMs). Transient in vitro exposure to BMP4 abolishes the capacity of

S. G. M. Piccirillo; B. A. Reynolds; N. Zanetti; G. Lamorte; E. Binda; G. Broggi; H. Brem; A. Olivi; F. Dimeco; A. L. Vescovi

2006-01-01

62

Risk of second brain tumour after conservative surgery and radiotherapy for pituitary adenoma  

Microsoft Academic Search

OBJECTIVE--To assess the risk of second brain tumour in patients with pituitary adenoma treated with conservative surgery and external beam radiotherapy. DESIGN--Long term follow up of a cohort of patients with pituitary adenoma and comparison of tumour occurrence with population incidence rates. SETTING--The Royal Marsden Hospital. SUBJECTS--334 patients with pituitary adenoma treated with conservative surgery and radiotherapy (median dose 45

M. Brada; D. Ford; S. Ashley; J. M. Bliss; S. Crowley; M. Mason; B. Rajan; D. Traish

1992-01-01

63

Knowledge-Based Classification of Neuronal Fibers in Entire Brain  

Microsoft Academic Search

\\u000a This work presents a framework driven by parcellation of brain gray matter in standard normalized space to classify the neuronal\\u000a fibers obtained from diffusion tensor imaging (DTI) in entire human brain. Classification of fiber bundles into groups is\\u000a an important step for the interpretation of DTI data in terms of functional correlates of white matter structures. Connections\\u000a between anatomically delineated

Yan Xia; U. Turken; Susan L. Whitfield-gabrieli; John D. Gabrieli

2005-01-01

64

Nucleolar organizer region score and Ki-67 labelling index in high-grade gliomas and metastatic brain tumours.  

PubMed

Sixteen cases of malignant brain tumours comprising 6 anaplastic astrocytomas, 3 glioblastoma multiforme, 1 medulloblastoma and 6 metastatic brain tumours were investigated independently by a silver colloid method for nucleolar organizer regions (NORs) and an immunohistochemistry using a monoclonal antibody against a nuclear antigen. Ki-67, in proliferating cells. The correlation between the mean number of NORs and the percentage of Ki-67 labelled cells (Ki-67 labelling index) was examined. In addition, four normal brain tissue samples without neoplastic cells were stained for NOR. The mean number of NORs in these malignant brain tumours was significantly greater than that in normal astrocytes (p less than 0.001). Moreover, both the mean number of NORs and the Ki-67 labelling index in metastatic brain tumours were significantly greater than those in high-grade gliomas (p less than 0.001). The Ki-67 labelling index and the mean number of NORs in malignant brain tumours including metastatic brain tumours were found to be linearly related (r = 0.86). These results suggest that the proliferative potential of malignant brain tumours could be evaluated by NOR score as well as Ki-67 labelling index and that such indices provide clear discrimination between high-grade gliomas and metastatic brain tumours. PMID:1648862

Hara, A; Hirayama, H; Sakai, N; Yamada, H; Tanaka, T; Mori, H

1991-01-01

65

Targeting brain gliomas energy metabolism for classification purposes  

Microsoft Academic Search

The aim of this study is to reveal the discriminative potential of energy related metabolites in brain gliomas classification. The proposed analysis considers two aspects, the statistical and biological verification of metabolites' effects. In particular, Magnetic Resonance Spectroscopic Imaging (MRSI) is first employed for the statistical evaluation of metabolites. Five of the identified significant metabolites, namely glucose, pyruvate, lactate, alanine

M. G. Kounelakis; M. E. Zervakis; G. J. Postma; L. M. C. Buydens; G. C. Giakos; C. Narayan; S. Marotta; D. Natarajamani; X. Kotsiakis

2010-01-01

66

Feature selection and classification on brain computer interface (BCI) data  

Microsoft Academic Search

In this paper, a large number of features are extracted from raw EEG data and then feature selection and classification are performed ,for brain computer interface (BCI) applications using motor imaginary movements. As the feature selection method, mRMR (minimum Redundancy Maximum Relevance) method, which is a fast method to select relevant and non redundant feature set, is chosen. Using a

Davut Polat; Zehra Cataltepe

2012-01-01

67

AN APPRAISAL OF As74 FOR LOCALIZATION OF BRAIN TUMOURS  

Microsoft Academic Search

Arsenic-74 may be used to provide useful information in the diagnosis of ; intracranial space occupying lesions. the high degree of specificity for ; meningiomas may be put to good use in ruling out the likelihood of this ; particular type of neoplasm in certain patients. The overall successful ; localization of intracranial tumours and abscesses is discussed. Meningiomas are

W. Paul; E. H. Botterell

1963-01-01

68

Magnetic iron compounds in the human brain: a comparison of tumour and hippocampal tissue  

PubMed Central

Iron is a central element in the metabolism of normal and malignant cells. Abnormalities in iron and ferritin expression have been observed in many types of cancer. Interest in characterizing iron compounds in the human brain has increased due to advances in determining a relationship between excess iron accumulation and neurological and neurodegenerative diseases. In this work, four different magnetic methods have been employed to characterize the iron phases and magnetic properties of brain tumour (meningiomas) tissues and non-tumour hippocampal tissues. Four main magnetic components can be distinguished: the diamagnetic matrix, nearly paramagnetic blood, antiferromagnetic ferrihydrite cores of ferritin and ferrimagnetic magnetite and/or maghemite. For the first time, open hysteresis loops have been observed on human brain tissue at room temperature. The hysteresis properties indicate the presence of magnetite and/or maghemite particles that exhibit stable single-domain (SD) behaviour at room temperature. A significantly higher concentration of magnetically ordered magnetite and/or maghemite and a higher estimated concentration of heme iron was found in the meningioma samples. First-order reversal curve diagrams on meningioma tissue further show that the stable SD particles are magnetostatically interacting, implying high-local concentrations (clustering) of these particles in brain tumours. These findings suggest that brain tumour tissue contains an elevated amount of remanent iron oxide phases.

Brem, Franziska; Hirt, Ann M; Winklhofer, Michael; Frei, Karl; Yonekawa, Yasuhiro; Wieser, Heinz-Gregor; Dobson, Jon

2006-01-01

69

Characterisation of Walker 256 breast carcinoma cells from two tumour cell banks as assessed using two models of secondary brain tumours  

PubMed Central

Background Metastatic brain tumours are a common end stage of breast cancer progression, with significant associated morbidity and high mortality. Walker 256 is a rat breast carcinoma cell line syngeneic to Wistar rats and commonly used to induce secondary brain tumours. Previously there has been the assumption that the same cancer cell line from different cell banks behave in a similar manner, although recent studies have suggested that cell lines may change their characteristics over time in vitro. Methods In this study internal carotid artery injection and direct cerebral inoculation models of secondary brain tumours were used to determine the tumorigenicity of Walker 256 cells obtained from two cell banks, the American Type Culture Collection (ATCC), and the Cell Resource Centre for Medical Research at Tohoku University (CRCTU). Results Tumour incidence and volume, plus immunoreactivity to albumin, IBA1 and GFAP, were used as indicators of tumorigenicity and tumour interaction with the host brain microenvironment. CRCTU Walker 256 cells showed greater incidence, larger tumour volume, pronounced blood–brain barrier disruption and prominent glial response when compared to ATCC cell line. Conclusions These findings indicate that immortalised cancer cell lines obtained from different cell banks may have diverse characteristics and behaviour in vivo.

2013-01-01

70

Brain tumor classification based on long echo proton MRS signals.  

PubMed

There has been a growing research interest in brain tumor classification based on proton magnetic resonance spectroscopy (1H MRS) signals. Four research centers within the EU funded INTERPRET project have acquired a significant number of long echo 1H MRS signals for brain tumor classification. In this paper, we present an objective comparison of several classification techniques applied to the discrimination of four types of brain tumors: meningiomas, glioblastomas, astrocytomas grade II and metastases. Linear and non-linear classifiers are compared: linear discriminant analysis (LDA), support vector machines (SVM) and least squares SVM (LS-SVM) with a linear kernel as linear techniques and LS-SVM with a radial basis function (RBF) kernel as a non-linear technique. Kernel-based methods can perform well in processing high dimensional data. This motivates the inclusion of SVM and LS-SVM in this study. The analysis includes optimal input variable selection, (hyper-) parameter estimation, followed by performance evaluation. The classification performance is evaluated over 200 stratified random samplings of the dataset into training and test sets. Receiver operating characteristic (ROC) curve analysis measures the performance of binary classification, while for multiclass classification, we consider the accuracy as performance measure. Based on the complete magnitude spectra, automated binary classifiers are able to reach an area under the ROC curve (AUC) of more than 0.9 except for the hard case glioblastomas versus metastases. Although, based on the available long echo 1H MRS data, we did not find any statistically significant difference between the performances of LDA and the kernel-based methods, the latter have the strength that no dimensionality reduction is required to obtain such a high performance. PMID:15182848

Lukas, L; Devos, A; Suykens, J A K; Vanhamme, L; Howe, F A; Majós, C; Moreno-Torres, A; Van der Graaf, M; Tate, A R; Arús, C; Van Huffel, S

2004-05-01

71

Is Postoperative Deep Vein Thrombosis A Problem in Neurosurgical Patients with Brain Tumours in Singapore?  

Microsoft Academic Search

Aim: To prospectively establish the incidence of deep vein thrombosis (DVT) after cranial procedures in patients with brain tumour in Singapore. Methodology: Over a period of one year from June 1995 to May 1996, 106 consecutive patients were recruited into the study. All patients undergoing surgery within the period of study were included. Each patient underwent a preoperative and postoperative

K Kumar; K K Tang; J Thomas; C Chumpon

72

The level of MnSOD is directly correlated with grade of brain tumours of neuroepithelial origin.  

PubMed Central

The oxy-radical scavenger enzyme manganese superoxide dismutase (MnSOD) may act in the capacity of a tumour-suppressor gene. To address the issue of its role in tumour transformation and progression in vivo, we evaluated the content of this enzyme in 33 brain tumours of neuroepithelial origin with different degrees of differentiation (WHO grade II-IV) by means of Western blot and immunohistology. Our results show that immunoreactive MnSOD increases in a direct relationship with tumour grade and is therefore inversely correlated with differentiation. The increase in induced at a pretranscriptional level and is apparently specific to brain tumours of neuroepithelial origin. Approximately 30% of grade IV tumours display low levels of MnSOD content, and preoperative radiotherapy and brachytherapy result in low amounts of enzyme. Based upon these observations, we suggest that MnSOD cannot be considered a classical tumour-suppressor gene. Images Figure 1 Figure 2 Figure 5

Landriscina, M.; Remiddi, F.; Ria, F.; Palazzotti, B.; De Leo, M. E.; Iacoangeli, M.; Rosselli, R.; Scerrati, M.; Galeotti, T.

1996-01-01

73

Classification of Traumatic Brain Injury for Targeted Therapies  

PubMed Central

Abstract The heterogeneity of traumatic brain injury (TBI) is considered one of the most significant barriers to finding effective therapeutic interventions. In October, 2007, the National Institute of Neurological Disorders and Stroke, with support from the Brain Injury Association of America, the Defense and Veterans Brain Injury Center, and the National Institute of Disability and Rehabilitation Research, convened a workshop to outline the steps needed to develop a reliable, efficient and valid classification system for TBI that could be used to link specific patterns of brain and neurovascular injury with appropriate therapeutic interventions. Currently, the Glasgow Coma Scale (GCS) is the primary selection criterion for inclusion in most TBI clinical trials. While the GCS is extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms which are responsible for neurological deficits and targeted by interventions. On the premise that brain injuries with similar pathoanatomic features are likely to share common pathophysiologic mechanisms, participants proposed that a new, multidimensional classification system should be developed for TBI clinical trials. It was agreed that preclinical models were vital in establishing pathophysiologic mechanisms relevant to specific pathoanatomic types of TBI and verifying that a given therapeutic approach improves outcome in these targeted TBI types. In a clinical trial, patients with the targeted pathoanatomic injury type would be selected using an initial diagnostic entry criterion, including their severity of injury. Coexisting brain injury types would be identified and multivariate prognostic modeling used for refinement of inclusion/exclusion criteria and patient stratification. Outcome assessment would utilize endpoints relevant to the targeted injury type. Advantages and disadvantages of currently available diagnostic, monitoring, and assessment tools were discussed. Recommendations were made for enhancing the utility of available or emerging tools in order to facilitate implementation of a pathoanatomic classification approach for clinical trials.

Saatman, Kathryn E.; Duhaime, Ann-Christine; Bullock, Ross; Maas, Andrew I.R.; Valadka, Alex

2008-01-01

74

Multiple polymorphisms, but no mutations, in the WAF1/CIP1 gene in human brain tumours.  

PubMed Central

The cyclin kinase inhibitor WAF1/CIP1, also termed CDKN1, mediates p53-induced cell cycle arrest in response to DNA damage. This property makes it an attractive tumour-suppressor candidate for a p53-associated tumour-suppressor gene. In order to investigate the role of WAF1/CIP1 in the pathogenesis of primary human brain tumours we performed single-stranded conformation polymorphism (SSCP) analysis and direct sequencing of exon 2 of the gene in a representative series of 158 brain tumours and corresponding blood samples. In addition, all tumours were examined for mutations in exons 5-8 of the p53 gene. Analysis of WAF1/CIP1 revealed multiple polymorphisms, the most abundant being AGC-->AGA (Ser-->Arg) at codon 31 with an allele frequency of 8.5%. Less common polymorphisms included GTG-->GGG (Val-->Gly) at codon 25, GCC-->ACC (Ala-->Thr) at codon 64, CGC-->CTC (Arg-->Leu) at codon 32, GGC-->AGC (Gly-->Ser) at codon 14 and GCG-->GTG (Ala-->Val) at codon 39 each with an allele frequency of 0.3%. These polymorphisms were all located in a conserved region of exon 2. Two of the polymorphisms were also seen in a group of 157 healthy controls indicating that WAF1/CIP1 polymorphisms do not predispose to cancer. None of the tumours included in our series showed a somatic mutation in WAF1/CIP1. All samples were also analysed for loss of heterozygosity on the short arm of chromosome 6 in the region of the WAF1/CIP1 locus. Allelic loss was observed in only one patient with a glioblastoma. Mutations in the p53 gene were found in 22 of 158 tumours. No association was found between any polymorphism of the WAF1/CIP1 gene, p53 mutations and histopathological tumour type. Our data indicate that WAF1/CIP1 mutations are probably not involved in the formation of primary human brain tumours. Images Figure 1

Koopmann, J.; Maintz, D.; Schild, S.; Schramm, J.; Louis, D. N.; Wiestler, O. D.; von Deimling, A.

1995-01-01

75

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

NASA Astrophysics Data System (ADS)

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 ?-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.

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

2009-07-01

76

Diffusion tensor imaging demonstrates deviation of fibres in normal appearing white matter adjacent to a brain tumour  

Microsoft Academic Search

the objective was to study fibre orientation in the cerebral white matter of a patient with a brain tumour using diffusion tensor imaging (DTI). A patient with a mild left hemiparesis and a tumour in the right frontal lobe and 20 healthy volunteers were scanned with a DTI sequence. The scans were spatially normalised and the fibre orientation in the

U C Wieshmann; M R Symms; G J M Parker; C A Clark; L Lemieux; G J Barker; S D Shorvon

2000-01-01

77

[Differentiation from local tumour recurrence and radionecrosis after stereotactic radiosurgery for treatment of brain metastasis].  

PubMed

Magnetic resonance imaging (MRI) is a method of choice for follow-up of irradiated brain metastasis. It is difficult to differentiate local tumour recurrences from radiation induced-changes in case of suspicious contrast enhancement. New advanced MRI techniques (perfusion and spectrometry) and amino acid positron-emission tomography (PET) allow to be more accurate and could avoid a stereotactic biopsy for histological assessment, the only reliable but invasive method. We report the case of a patient who underwent surgery for a single, left frontal brain metastasis of a breast carcinoma, followed by adjuvant stereotactic radiotherapy in the operative bed. Seven months after, she presented a local change in the irradiated area on the perfusion-weighted MRI, for which the differentiation between a local tumour recurrence and radionecrosis was not possible. PET with 2-deoxy-((18)F)-fluoro-D-glucose (FDG) revealed a hypermetabolic lesion. After surgical resection, the histological assessment has mainly recovered radionecrosis with few carcinoma cells. The multimodal MRI has greatly contributed to refine the differential diagnosis between tumour recurrence and radionecrosis, which remains difficult. The FDG PET is helpful, in favour of the diagnosis of local tumour recurrence when a hypermetabolic lesion is found. Others tracers (such as carbon 11 or a fluoride isotope) deserve interest but are not available in all centres. Stereotactic biopsy should be discussed if any doubt remains. PMID:24433952

Patsouris, A; Augereau, P; Tanguy, J-Y; Morel, O; Menei, P; Rousseau, A; Paumier, A

2014-03-01

78

Li-Fraumeni syndrome: multiple distinct brain tumours in two brothers.  

PubMed

Li-Fraumeni syndrome is a rare autosomal dominant cancer-prone condition characterized by the occurrence of a large set of different types of cancer in a patient and their family. A germline disease-causing mutation of the gene encoding the p53 protein is associated with the syndrome. We report on a family in which segregation of a TP53 mutation in two generations was associated with two brain tumours, a leiomyosarcoma and a thyroid carcinoma in four male patients. The main patient presented with seizures revealing several primary brain tumours. We review recent views on its molecular basis and discuss management of the condition as well as a review of the literature. PMID:24636404

Lechien, J R; Brotchi, J; Van Maldergem, L; Costa de Araujo, P; Bruninx, G; Hilbert, P; Nubourgh, Y

2014-01-01

79

Magnetic fields and brain tumour risks in UK electricity supply workers.  

PubMed

Aims To investigate whether brain tumour risks are related to occupational exposure to low-frequency magnetic fields. Methods Brain tumour risks experienced by 73 051 employees of the former Central Electricity Generating Board of England and Wales were investigated for the period 1973-2010. All employees were hired in the period 1952-82 and were employed for at least 6 months with some employment in the period 1973-82. Detailed calculations had been performed by others to enable an assessment to be made of exposures to magnetic fields. Poisson regression was used to calculate relative risks (rate ratios) of developing a brain tumour (or glioma or meningioma) for categories of lifetime, distant (lagged) and recent (lugged) exposure. Results Findings for glioma and for the generality of all brain tumours were unexceptional; risks were close to (or below) unity for all exposure categories and there was no suggestion of risks increasing with cumulative (or recent or distant) magnetic field exposures. There were no statistically significant dose-response effects shown for meningioma, but there was some evidence of elevated risks in the three highest exposure categories for exposures received >10 years ago. Conclusions This study found no evidence to support the hypothesis that exposure to magnetic fields is a risk factor for gliomas, and the findings are consistent with the hypotheses that both distant and recent magnetic field exposures are not causally related to gliomas. The limited positive findings for meningioma may be chance findings; national comparisons argue against a causal interpretation. PMID:24562302

Sorahan, T

2014-04-01

80

Multiclass brain-computer interface classification by Riemannian geometry.  

PubMed

This paper presents a new classification framework for brain-computer interface (BCI) based on motor imagery. This framework involves the concept of Riemannian geometry in the manifold of covariance matrices. The main idea is to use spatial covariance matrices as EEG signal descriptors and to rely on Riemannian geometry to directly classify these matrices using the topology of the manifold of symmetric and positive definite (SPD) matrices. This framework allows to extract the spatial information contained in EEG signals without using spatial filtering. Two methods are proposed and compared with a reference method [multiclass Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA)] on the multiclass dataset IIa from the BCI Competition IV. The first method, named minimum distance to Riemannian mean (MDRM), is an implementation of the minimum distance to mean (MDM) classification algorithm using Riemannian distance and Riemannian mean. This simple method shows comparable results with the reference method. The second method, named tangent space LDA (TSLDA), maps the covariance matrices onto the Riemannian tangent space where matrices can be vectorized and treated as Euclidean objects. Then, a variable selection procedure is applied in order to decrease dimensionality and a classification by LDA is performed. This latter method outperforms the reference method increasing the mean classification accuracy from 65.1% to 70.2%. PMID:22010143

Barachant, Alexandre; Bonnet, Stéphane; Congedo, Marco; Jutten, Christian

2012-04-01

81

Health professionals' perspectives on information provision for patients with brain tumours and their families.  

PubMed

A significant number of patients diagnosed with primary brain tumours report unmet information needs. Using concept mapping methodology, this study aimed to identify strategies for improving information provision, and to describe factors that health professionals understood to influence their provision of information to patients with brain tumours and their families. Concept mapping is a mixed-methods approach that uses statistical methods to represent participants' perceived relationships between elements as conceptual maps. These maps, and results of associated data collection and analyses, are used to extract concepts involved in information provision to these patients. Thirty health professionals working across a range of neuro-oncology roles and settings participated in the concept mapping process. Participants rated a care coordinator as the most important strategy for improving brain tumour care, with psychological support as a whole rated as the most important element of care. Five major themes were identified as facilitating information provision: health professionals' communication skills, style and attitudes; patients' needs and preferences; perceptions of patients' need for protection and initiative; rapport and continuity between patients and health professionals; and the nature of the healthcare system. Overall, health professionals conceptualised information provision as 'individualised', dependent on these interconnected personal and environmental factors. PMID:22989208

Langbecker, D; Janda, M; Yates, P

2013-03-01

82

Multidisciplinary assessment of fitness to drive in brain tumour patients in southwestern Ontario: a grey matter  

PubMed Central

Background Neurocognitive impairments from brain tumours may interfere with the ability to drive safely. In 9 of 13 Canadian provinces and territories, physicians have a legal obligation to report patients who may be medically unfit to drive. To complicate matters, brain tumour patients are managed by a multidisciplinary team; the physician most responsible to make the report of unfitness is often not apparent. The objective of the present study was to determine the attitudes and reporting practices of physicians caring for these patients. Methods A 17-question survey distributed to physicians managing brain tumour patients elicited Respondent demographicsKnowledge about legislative requirementsExperience of reportingBarriers and attitudes to reporting Fisher exact tests were performed to assess differences in responses between family physicians (fps) and specialists. Results Of 467 physicians sent surveys, 194 responded (42%), among whom 81 (42%) were specialists and 113 (58%) were fps. Compared with the specialists, the fps were significantly less comfortable with reporting, less likely to consider reporting, less likely to have patients inquire about driving, and less likely to discuss driving implications. A lack of tools, concern for the patient–physician relationship, and a desire to preserve patient quality of life were the most commonly cited barriers in determining medical fitness of patients to drive. Conclusions Legal requirements to report medically unfit drivers put physicians in the difficult position of balancing patient autonomy and public safety. More comprehensive and definitive guidelines would be helpful in assisting physicians with this public health issue.

Chan, E.; Louie, A.V.; Hanna, M.; Bauman, G.S.; Fisher, B.J.; Palma, D.A.; Rodrigues, G.B.; Sathya, A.; D'Souza, D.P.

2013-01-01

83

Segmentation, feature extraction, and multiclass brain tumor classification.  

PubMed

Multiclass brain tumor classification is performed by using a diversified dataset of 428 post-contrast T1-weighted MR images from 55 patients. These images are of primary brain tumors namely astrocytoma (AS), glioblastoma multiforme (GBM), childhood tumor-medulloblastoma (MED), meningioma (MEN), secondary tumor-metastatic (MET), and normal regions (NR). Eight hundred fifty-six regions of interest (SROIs) are extracted by a content-based active contour model. Two hundred eighteen intensity and texture features are extracted from these SROIs. In this study, principal component analysis (PCA) is used for reduction of dimensionality of the feature space. These six classes are then classified by artificial neural network (ANN). Hence, this approach is named as PCA-ANN approach. Three sets of experiments have been performed. In the first experiment, classification accuracy by ANN approach is performed. In the second experiment, PCA-ANN approach with random sub-sampling has been used in which the SROIs from the same patient may get repeated during testing. It is observed that the classification accuracy has increased from 77 to 91 %. PCA-ANN has delivered high accuracy for each class: AS-90.74 %, GBM-88.46 %, MED-85 %, MEN-90.70 %, MET-96.67 %, and NR-93.78 %. In the third experiment, to remove bias and to test the robustness of the proposed system, data is partitioned in a manner such that the SROIs from the same patient are not common for training and testing sets. In this case also, the proposed system has performed well by delivering an overall accuracy of 85.23 %. The individual class accuracy for each class is: AS-86.15 %, GBM-65.1 %, MED-63.36 %, MEN-91.5 %, MET-65.21 %, and NR-93.3 %. A computer-aided diagnostic system comprising of developed methods for segmentation, feature extraction, and classification of brain tumors can be beneficial to radiologists for precise localization, diagnosis, and interpretation of brain tumors on MR images. PMID:23645344

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2013-12-01

84

Assessing fitness to drive in brain tumour patients: a grey matter of law, ethics, and medicine  

PubMed Central

Background Neurocognitive deficits from brain tumours may impair the ability to safely operate a motor vehicle. Although certain jurisdictions in Canada legally require that physicians report patients who are unfit to drive, criteria for determining fitness are not clearly defined for brain tumours. Methods Patients receiving brain radiotherapy at our institution from January to June 2009 were identified using the Oncology Patient Information System. In addition to descriptive statistics, details of driving assessment were reviewed retrospectively. The Fisher exact test was used to determine factors predictive of reporting a patient to the Ontario Ministry of Transportation (mto) as unfit to drive. A logistic regression model was constructed to further determine factors predictive of reporting. Results Of the 158 patients available for analysis, 48 (30%) were reported to the mto, and 64 (41%) were advised to stop driving. With respect to the 53 patients with seizures, a report was submitted to the mto for 30 (57%), and a documented discussion about the implications of driving was held with 35 (66%). On univariate analysis, younger age, a central nervous system primary, higher brain radiotherapy dose, unifocal disease, and the presence of seizures were predictive of physician reporting (p < 0.05). On logistic regression modelling, the presence of seizures (odds ratio: 3.9) and a higher radiotherapy dose (odds ratio: 1.3) remained predictive of reporting. Interpretation Physicians frequently do not discuss the implications of driving with brain tumour patients or are not properly documenting such advice (or both). Clear and concise reporting guidelines need to be drafted given the legal, medical, and ethical concerns surrounding this public health issue.

Louie, A.V.; Chan, E.; Hanna, M.; Bauman, G.S.; Fisher, B.J.; Palma, D.A.; Rodrigues, G.B.; Warner, A.; D'Souza, D.P.

2013-01-01

85

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

PubMed

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. PMID:22621242

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

86

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

PubMed

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. PMID:22610781

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

2013-01-01

87

Homozygous PMS2 germline mutations in two families with early-onset haematological malignancy, brain tumours, HNPCC-associated tumours, and signs of neurofibromatosis type 1  

Microsoft Academic Search

Heterozygous germline mutations in mismatch repair (MMR) genes MLH1, PMS2, MSH2, and MSH6 cause Lynch syndrome. New studies have indicated that biallelic mutations lead to a distinctive syndrome, childhood cancer syndrome (CCS), with haematological malignancies and tumours of brain and bowel early in childhood, often associated with signs of neurofibromatosis type 1. We provide further evidence for CCS reporting on

Stefan Krüger; Miriam Kinzel; Constanze Walldorf; Sven Gottschling; Andrea Bier; Sigrid Tinschert; Arend von Stackelberg; Wolfram Henn; Heike Görgens; Stephanie Boue; Konrad Kölble; Reinhard Büttner; Hans K Schackert

2008-01-01

88

Identification and Classification of Hubs in Brain Networks  

PubMed Central

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.

Sporns, Olaf; Honey, Christopher J.; Kotter, Rolf

2007-01-01

89

USP11 regulates PML stability to control Notch-induced malignancy in brain tumours.  

PubMed

The promyelocytic leukaemia (PML) protein controls multiple tumour suppressive functions and is downregulated in diverse types of human cancers through incompletely characterized post-translational mechanisms. Here we identify USP11 as a PML regulator by RNAi screening. USP11 deubiquitinates and stabilizes PML, thereby counteracting the functions of PML ubiquitin ligases RNF4 and the KLHL20-Cul3 (Cullin 3)-Roc1 complex. We find that USP11 is transcriptionally repressed through a Notch/Hey1-dependent mechanism, leading to PML destabilization. In human glioma, Hey1 upregulation correlates with USP11 and PML downregulation and with high-grade malignancy. The Notch/Hey1-induced downregulation of USP11 and PML not only confers multiple malignant characteristics of aggressive glioma, including proliferation, invasiveness and tumour growth in an orthotopic mouse model, but also potentiates self-renewal, tumour-forming capacity and therapeutic resistance of patient-derived glioma-initiating cells. Our study uncovers a PML degradation mechanism through Notch/Hey1-induced repression of the PML deubiquitinase USP11 and suggests an important role for this pathway in brain tumour pathogenesis. PMID:24487962

Wu, Hsin-Chieh; Lin, Yu-Ching; Liu, Cheng-Hsin; Chung, Hsiang-Ching; Wang, Ya-Ting; Lin, Ya-Wen; Ma, Hsin-I; Tu, Pang-Hsien; Lawler, Sean E; Chen, Ruey-Hwa

2014-01-01

90

Using neural networks to automatically detect brain tumours in MR images.  

PubMed

Computer vision has been applied to many medical imaging problems with the aim of providing clinical tools to aid medical professionals. We present work being carried out to develop one such system to automatically detect a specific type of brain tumour from head MR images. The tumour under consideration is an acoustic neuroma, which is a benign tumour occurring in the acoustic canals. The hybrid system developed integrates neural networks with more conventional techniques used for computer vision tasks. A database of MR images from 50 patients has been assembled and the acoustic neuromas present in the images have been labelled by hand. Using this data, neural networks (MLPs) have been developed to classify the images at the pixel level to achieve a targeted segmentation. The data used to train and test the MLPs developed, consists of the grey levels of a square of pixels, the pixel to be classified being the centre pixel, together with its global position in the image. The initial pixel level segmentation is refined by a series of conventional techniques. It is combined with an edge-region based segmentation and a morphological operation is applied to the result. This processing produces clusters of adjacent regions, which are considered to be candidate tumour regions. For each possible combination of these regions, features are measured and presented to neural networks which have been trained to identify structures corresponding to acoustic neuromas. Using this approach, all the acoustic neuromas are identified together with three false positive errors. PMID:9228581

Dickson, S; Thomas, B T; Goddard, P

1997-02-01

91

Clinical relevance of 201Tl-chloride SPET in the differential diagnosis of brain tumours.  

PubMed

Magnetic resonance imaging (MRI) and computed tomography (CT) may not be reliable in the differential diagnosis of tumour necrosis, scar and recurrent tumour. We compared 201Tl-chloride SPET with CT and MRI for the differential diagnosis of these cerebral lesions. Brain SPET was performed in 40 patients after the intravenous injection of 201Tl-chloride. All 40 patients also had a CT or MRI scan, and a histological diagnosis was available for 27 of the patients. For each patient, the ratio of counts in the lesion region of interest (ROI) to counts in the contralateral ROI was calculated and found to be between 0.58 and 9.60. The ratios for high-grade gliomas, metastases and meningiomas were high (> 2.7), especially in tumours with good vascularization. A low ratio (< 1.7) was noted in patients with low-grade astrocytoma, necrosis or ischaemic lesions. There were two exceptional cases of ischaemic lesions in the luxury perfusion stage (ratios of 3.61 and 3.87), as verified by HMPAO-SPET. We found that 201Tl-chloride SPET helps to differentiate between malignant tumours, poorly vascularized benign lesions and necrosis. Differentiation between low-grade astrocytoma and non-malignant lesions was not possible, but there was a trend towards differentiating between low-grade astrocytoma and ischaemic infarction. The timing of the investigation is important to avoid false-positive results in hyperperfused ischaemic tissue. PMID:9853323

Staffen, W; Hondl, N; Trinka, E; Iglseder, B; Unterrainer, J; Ladurner, G

1998-04-01

92

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

PubMed

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. PMID:3716890

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

1986-01-01

93

Flow cytometric analysis of DNA ploidy and proliferative potential in brain tumours.  

PubMed

The proliferative potential and DNA ploidy in 203 brain tumours (27 astrocytomas grade I, 37 grade II, 80 grade III, and 59 grade IV) were investigated using bromodeoxyuridine (BrdUrd) incorporation and flow cytometry. One to three tumour samples from each patient were incubated in vitro for one hour at 37 degrees C with bromodeoxyuridine (BrdUrd) using the high preasure oxygen method. After incubation, fixation and staining, the cell preparations were analysed by flow cytometry. The percentage of BrdUrd-labelled cells (BrdUrd Labelling Index, BrdUrdLI), the predicted potential doubling time (predTpot) and the total DNA content were evaluated. The percentage of unlabelled S-phase cells (SPF) and proliferative index (PI, the percentage of cells in S + G2 phases) were also estimated. DNA aneuploidy was found in 61.1% of high-grade (III-IV) and 50.0% of low-grade (I-II) astrocytomas. The tumours showed variability in the BrdUrdLI values which ranged from 0.2 to 15.8%. Significantly higher mean value for BrdUrdLI was shown in grade III-IV astrocytomas (3.4%), than in grade I-II astrocytomas (1.5%), p = 0.0068. Also significantly shorter mean predTpot was shown in high grade III-IV astrocytomas (28 days) than in low grade I-II tumours (51 days), p = 0.0096. However, no relationship was shown between other cell proliferation parameters and histological grade. The mean intratumoral variability calculated on the basis of BrdUrdLI values on 2-3 samples from each tumour amounted to 31.2% +/- SD 15.9%. PMID:9773297

Gasi?ska, A; Krzyszkowski, T; Sko?yszewski, J; Biesaga, B; Gli?ski, B; Pyrich, M

1998-01-01

94

Perinatal and early postnatal risk factors for malignant brain tumours in New South Wales children.  

PubMed

A population-based case-control study of incident primary malignant brain tumours diagnosed during 1985-1989 in children aged 0 to 14 years was carried out in the coastal conurbation of New South Wales comprising Sydney, Wollongong and Newcastle in the period 1988 to 1990. Personal interviews were conducted using a structured questionnaire with mothers of 82 cases and 164 control children individually matched to the cases by sex and age. Among the hypotheses examined were those related to: N-nitroso compounds (sources included diet, dummies, medications, tobacco smoke); factors associated with the birth of the child; trauma to the head; and irradiation (X-rays and electromagnetic radiation through electric blankets or water beds). Reported ever-use of a dummy increased the risk of childhood brain tumours (OR = 2.9, 95% CI 1.6 to 5.4), although there did not appear to be any consistent indication of rising risk with reported increased levels of use. Compared with children who had never used a dummy, categories of use during the first year of life of a maximum of "no more than 1 hour per day or night", "several hours per day or night", and "most of the day or night" had statistically significant odds ratios of 2.6, 3.4, and 2.7 respectively. Consumption of fruit by the child before the age of one appeared to be protective. No association was found between childhood brain tumours and birth weight, being the first-born child, or factors linked with the child's birth; head injuries; exposure to X-rays; contact with horses, or living on a farm; pesticide treatment of the house during the child's lifetime; or exposure to burning incense. PMID:8262665

McCredie, M; Maisonneuve, P; Boyle, P

1994-01-01

95

Brain tissue segmentation in 4D CT using voxel classification  

NASA Astrophysics Data System (ADS)

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.

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

96

DNA-microarray analysis of brain cancer: molecular classification for therapy  

Microsoft Academic Search

Primary brain tumours are among the most lethal of all cancers, largely as a result of their lack of responsiveness to current therapy. Numerous new therapies hold great promise for the treatment of patients with brain cancer, but the main challenge is to determine which treatment is most likely to benefit an individual patient. DNA-microarray-based technologies, which allow simultaneous analysis

Timothy F. Cloughesy; Stanley F. Nelson; Paul S. Mischel

2004-01-01

97

3- O Methyl6-[ 18 F]fluoro-l-DOPA and its evaluation in brain tumour imaging  

Microsoft Academic Search

3- O-Methyl-6-[ 18F]fluoro-l-DOPA (OMFD) is a major metabolite of 6-[ 18F]fluoro-L-DOPA. Although synthesis of OFMD was primarily established to study the dopaminergic system, as it is an amino acid analogue, uptake in experimental tumours has been found. The aim of this study was to evaluate the applicability of OMFD for brain tumour imaging and to obtain initial estimates of whole-body

B. Beuthien-Baumann; J. Bredow; W. Burchert; F. Füchtner; R. Bergmann; H.-D. Alheit; G. Reiss; R. Hliscs; R. Steinmeier; W.-G. Franke; B. Johannsen; J. Kotzerke

2003-01-01

98

Compatibility between 3T  1 H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1 H SV-MRS spectra  

Microsoft Academic Search

Object  This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers\\u000a which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.5T MRS data to be used\\u000a for diagnostic classification of 3T spectra, and perhaps also the combination of 1.5T and 3T databases.\\u000a \\u000a \\u000a \\u000a \\u000a Materials and methods  Brain

Elies Fuster-Garcia; Clara Navarro; Javier Vicente; Salvador Tortajada; Juan M. García-Gómez; Carlos Sáez; Jorge Calvar; John Griffiths; Margarida Julià-Sapé; Franklyn A. Howe; Jesús Pujol; Andrew C. Peet; Arend Heerschap; Àngel Moreno-Torres; M. C. Martínez-Bisbal; Beatriz Martínez-Granados; Pieter Wesseling; Wolfhard Semmler; Jaume Capellades; Carles Majós; Àngel Alberich-Bayarri; Antoni Capdevila; Daniel Monleón; Luis Martí-Bonmatí; Carles Arús; Bernardo Celda; Montserrat Robles

2011-01-01

99

Brain tumours and cigarette smoking: analysis of the INTERPHONE Canada case-control study  

PubMed Central

Background There is conflicting evidence regarding the associations between cigarette smoking and glioma or meningioma. Our purpose is to provide further evidence on these possible associations. Methods We conducted a set of case–control studies in three Canadian cities, Montreal, Ottawa and Vancouver. The study included 166 subjects with glioma, 93 subjects with meningioma, and 648 population-based controls. A lifetime history of cigarette smoking was collected and various smoking indices were computed. Multivariable logistic regression was used to estimate odds ratios (ORs) between smoking and each of the two types of brain tumours. Results Adjusted ORs between smoking and each type of brain tumour were not significantly elevated for all smokers combined or for smokers with over 15 pack-years ((packs / day) x years) accumulated. We tested for interactions between smoking and several sociodemographic variables; the interaction between smoking and education on glioma risk was significant, with smoking showing an elevated OR among subjects with lower education and an OR below unity among subjects with higher education. Conclusion Except for an unexplained and possibly artefactual excess risk in one population subgroup, we found little or no evidence of an association between smoking and either glioma or meningioma.

2014-01-01

100

Use of cellular telephones and brain tumour risk in urban and rural areas  

PubMed Central

Aims: To investigate the association between the use of cellular or cordless telephones and the risk for brain tumours in different geographical areas, urban and rural. Methods: Patients aged 20–80 years, living in the middle part of Sweden, and diagnosed between 1 January 1997 and 30 June 2000 were included. One control matched for sex and age in five year age groups was selected for each case. Use of different phone types was assessed by a questionnaire. Results: The number of participating cases was 1429; there were 1470 controls. An effect of rural living was most pronounced for digital cellular telephones. Living in rural areas yielded an odds ratio (OR) of 1.4 (95% CI 0.98 to 2.0), increasing to 3.2 (95% CI 1.2 to 8.4) with >5 year latency time for digital phones. The corresponding ORs for living in urban areas were 0.9 (95% CI 0.8 to 1.2) and 0.9 (95% CI 0.6 to 1.4), respectively. This effect was most obvious for malignant brain tumours. Conclusion: In future studies, place of residence should be considered in assessment of exposure to microwaves from cellular telephones, although the results in this study must be interpreted with caution due to low numbers in some of the calculations.

Hardell, L; Carlberg, M; Hansson, M

2005-01-01

101

Brain tumours in childhood in Bombay: I: Histopathology showing changing patterns; II: Tissue culture with light and electronmicroscopy, stressing ingestion & degradation of bacteria by glial cells in vitro  

Microsoft Academic Search

The pathological pattern of 86 braintumours’ in childhood during the years 1981–85 (out of a total of 586 for all ages), showed a higher proportion of neoplasms and a much lower of tuberculomas compared to the preceding three decades. A large number of histologically unusual cases was revealed. Through tissue culture of brain tumours we carried out morphological, histochemical

Darab K. Dastur; Sharda R. Kankonkar; Daya K. Manghani; Tanaaz H. Vakil; Usha P. Dave; Sanat N. Bhagwati

1989-01-01

102

Multiple instance learning for classification of dementia in brain MRI.  

PubMed

Machine learning techniques have been widely used to detect morphological abnormalities from structural brain magnetic resonance imaging data and to support the diagnosis of neurological diseases such as dementia. In this paper, we propose to use a multiple instance learning (MIL) method in an application for the detection of Alzheimer's disease (AD) and its prodromal stage mild cognitive impairment (MCI). In our work, local intensity patches are extracted as features. However, not all the patches extracted from patients with dementia are equally affected by the disease and some of them may not be characteristic of morphology associated with the disease. Therefore, there is some ambiguity in assigning disease labels to these patches. The problem of the ambiguous training labels can be addressed by weakly supervised learning techniques such as MIL. A graph is built for each image to exploit the relationships among the patches and then to solve the MIL problem. The constructed graphs contain information about the appearances of patches and the relationships among them, which can reflect the inherent structures of images and aids the classification. Using the baseline MR images of 834 subjects from the ADNI study, the proposed method can achieve a classification accuracy of 89% between AD patients and healthy controls, and 70% between patients defined as stable MCI and progressive MCI in a leave-one-out cross validation. Compared with two state-of-the-art methods using the same dataset, the proposed method can achieve similar or improved results, providing an alternative framework for the detection and prediction of neurodegenerative diseases. PMID:24858570

Tong, Tong; Wolz, Robin; Gao, Qinquan; Guerrero, Ricardo; Hajnal, Joseph V; Rueckert, Daniel

2014-07-01

103

Depth-dose evaluation and optimisation of the irradiation facility for boron neutron capture therapy of brain tumours.  

PubMed

Boron neutron capture therapy (BNCT) of brain tumours was investigated using thermal neutrons generated by a middle-power research reactor such as the TRIGA-II. The spatial distributions of neutrons and gamma rays were measured using a head phantom at different collimator apertures. Total depth-dose distributions were deduced from these results and were evaluated. We also obtained an optimum condition in terms of the collimator aperture, the 10B concentration in the tumour and the ratio of 10B concentration in the tumour to that in normal tissue. We found that, under this condition, BNCT using thermal neutrons from the TRIGA-II could be successfully used to treat a deep tumour. PMID:4048274

Matsumoto, T; Aizawa, O

1985-09-01

104

Cystic lesions of the brain. A classification based on pathogenesis, with consideration of histological and radiological features.  

PubMed

A classification of the existing multitude of cystic lesions of the brain is proposed, which allows an understanding of their genesis and consequent therapeutic implications, as well as their diagnostic characteristics. Essentially, cerebral cystic lesions may be classified into the following categories: Cysts containing CSF-like fluid, which include ex vacuo type cysts, such as leptomeningeal cysts, and cysts following surgical resection; cysts with fluid secreting walls and CSF-like content, such as arachnoid cysts; cysts associated with dysgenesis, for example Dandy-Walker cysts. The ex vacuo cysts increase craniospinal compliance, whereas the other cysts with CSF-like content do not; they are not per se expansive, however, although their occasional location along CSF pathways may cause obstruction and hydrocephalus. Another category includes cysts with a lining of non-neural epithelium like colloid cysts, epidermoid cysts, or craniopharyngiomas. They may increase in size and cause symptoms by compression, although not at the rate of tumour-associated cysts. The cysts associated with gliomas and other tumours have a pathogenesis bearing upon blood-brain barrier impairment and formation of vasogenic oedema. Finally, one may distinguish a category of cysts with infectious origin, such as brain abscesses and hydatid cysts. The cysts with CSF-like contents may be recognised by their magnetic resonance characteristics resembling those of CSF, whereas cysts containing proteinaceous fluid are associated with blood-brain barrier impairment and consequent contrast enhancement. The cysts with a lining of non-neural epithelium exhibit diverse properties of attenuation on computed tomography (CT) and magnetic resonance imaging (MRI), depending on the nature of their cyst contents. PMID:8223687

Go, K G; Hew, J M; Kamman, R L; Molenaar, W M; Pruim, J; Blaauw, E H

1993-09-01

105

Brain tumour surgery in the vicinity of short-term memory representation – results of neuronavigation using fMRI images  

Microsoft Academic Search

Summary  Objective. Functional information concerning the surrounding brain is mandatory for a good clinical outcome in brain tumour surgery.\\u000a The value of fMRI to detect the motorcortex and Broca’s area is widely accepted today. If an appropriate paradigm is used,\\u000a short-term memory areas can be visualized as well. Obviously this information must be integrated into cranial neuronavigation\\u000a for an appropriate intra-operative

V. Braun; A. Albrecht; T. Kretschmer; H.-P. Richter; A. Wunderlich

2006-01-01

106

Perfusion MRI of brain tumours: a comparative study of pseudo-continuous arterial spin labelling and dynamic susceptibility contrast imaging  

PubMed Central

Introduction The purpose of this study was to compare the non-invasive 3D pseudo-continuous arterial spin labelling (PC ASL) technique with the clinically established dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) for evaluation of brain tumours. Methods A prospective study of 28 patients with contrast-enhancing brain tumours was performed at 3 T using DSC-MRI and PC ASL with whole-brain coverage. The visual qualitative evaluation of signal enhancement in tumour was scored from 0 to 3 (0 = no signal enhancement compared with white matter, 3 = pronounced signal enhancement with equal or higher signal intensity than in grey matter/basal ganglia). The extent of susceptibility artefacts in the tumour was scored from 0 to 2 (0 = no susceptibility artefacts and 2 = extensive susceptibility artefacts (maximum diameter>2 cm)). A quantitative analysis was performed with normalised tumour blood flow values (ASL nTBF, DSC nTBF): mean value for region of interest (ROI) in an area with maximum signal enhancement/the mean value for ROIs in cerebellum. Results There was no difference in total visual score for signal enhancement between PC ASL and DSC relative cerebral blood flow (p=0.12). ASL had a lower susceptibility-artefact score than DSC-MRI (p=0.03). There was good correlation between DSC nTBF and ASL nTBF values with a correlation coefficient of 0.82. Conclusion PC ASL is an alternative to DSC-MRI for the evaluation of perfusion in brain tumours. The method has fewer susceptibility artefacts than DSC-MRI and can be used in patients with renal failure because no contrast injection is needed.

Jarnum, Hanna; Steffensen, Elena G.; Knutsson, Linda; Frund, Ernst-Torben; Simonsen, Carsten Wiberg; Lundbye-Christensen, S?ren; Shankaranarayanan, Ajit; Alsop, David C.; Jensen, Finn Taageh?j; Larsson, Elna-Marie

2010-01-01

107

An improved monomeric infrared fluorescent protein for neuronal and tumour brain imaging.  

PubMed

Infrared fluorescent proteins (IFPs) are ideal for in vivo imaging, and monomeric versions of these proteins can be advantageous as protein tags or for sensor development. In contrast to GFP, which requires only molecular oxygen for chromophore maturation, phytochrome-derived IFPs incorporate biliverdin (BV) as the chromophore. However, BV varies in concentration in different cells and organisms. Here we engineered cells to express the haeme oxygenase responsible for BV biosynthesis and a brighter monomeric IFP mutant (IFP2.0). Together, these tools improve the imaging capabilities of IFP2.0 compared with monomeric IFP1.4 and dimeric iRFP. By targeting IFP2.0 to the plasma membrane, we demonstrate robust labelling of neuronal processes in Drosophila larvae. We also show that this strategy improves the sensitivity when imaging brain tumours in whole mice. Our work shows promise in the application of IFPs for protein labelling and in vivo imaging. PMID:24832154

Yu, Dan; Gustafson, William Clay; Han, Chun; Lafaye, Céline; Noirclerc-Savoye, Marjolaine; Ge, Woo-Ping; Thayer, Desiree A; Huang, Hai; Kornberg, Thomas B; Royant, Antoine; Jan, Lily Yeh; Jan, Yuh Nung; Weiss, William A; Shu, Xiaokun

2014-01-01

108

An unusual presentation of an epidermoid brain tumour: a tale of two specialties.  

PubMed

A 33-year-old right-handed lady was referred to the psychiatry and neurology services by her general practitioner. Previously, she was under psychiatric care for bipolar affective disorder. Recently, her mood had deteriorated prompting the re-referral to the psychiatrists. In addition she had strange attacks. These strange attacks seemed to her like 'sensory overload' or that the 'brain just stops'. Other sensations throughout the attacks included feeling like she is in a 'fish bowl' and surrounding sights and sounds were distorted. She could not speak. After the attack she was hot and flustered, suffered memory loss and was tearful. Both the psychiatrist and the neurologist considered the possibility of these attacks being psychiatric in aetiology. However, the alternative possibility of a coexistence to epilepsy and depression was investigated and MRI demonstrated an epidermoid tumour with the supratentorial portion displacing the left temporal lobe. PMID:22967680

Wong, Jen-jou; Huda, Saif; Wieshmann, Udo Carl

2012-01-01

109

Diagnostic assessment of brain tumours and non-neoplastic brain disorders in vivo using proton nuclear magnetic resonance spectroscopy and artificial neural networks  

Microsoft Academic Search

Purpose\\u000a : Experiments were carried out to assess the potential of artificial neural network (ANN) analysis in the differential diagnosis\\u000a of brain tumours (low- and high-grade gliomas) from non-neoplastic focal brain lesions (tuberculomas and abscesses), using\\u000a proton magnetic resonance spectroscopy (1H MRS) as input data. Methods\\u000a : Single-voxel stimulated echo acquisition mode (STEAM) (echo time of 20?ms) spectra were acquired

Harish Poptani; Jouni Kaartinen; Rakesh K. Gupta; Matthias Niemitz; Yrjö Hiltunen; Risto A. Kauppinen

1999-01-01

110

Radioisotope scanning of brain, liver, lung and bone with a note on tumour localizing agents  

PubMed Central

Radioisotopic scanning of brain, liver, lungs and the skeleton is briefly reviewed with a survey of recent developments of clinical significance. In brain scanning neoplasm detection rates of greater than 90% are claimed. The true figure is probably 70-80%. Autopsy data shows a number of false negatives, particularly with vascular lesions. Attempts to make scanning more specific in differentiating neoplasm from vascular lesions by rapid sequence blood flow studies are reviewed. In liver scanning by means of colloids again high success rate is claimed but small metastases are frequently missed and the false negative scan rate is probably quite high. Lung scanning still has its main place in investigating pulmonary embolic disease. Ventilation studies using Xenon 133 are useful, particularly combined with perfusion studies. The various radiopharmaceuticals for use in bone scanning are reviewed. The appearance of technetium labelled phosphate compounds will probably allow much wider use of total skeletal scanning. Research into tumour localizing agents continues, the most recent and interesting being Gallium citrate and labelled bleomycin. Neither agent is predictable however although Gallium may have a place in Hodgkins disease and bronchogenic neoplasm and both may have a place in the detection of cerebral tumours. ImagesFig. 1Fig. 2Fig. 3p452-bFig. 3bFig. 4Fig. 5Fig. 5bFig. 6Fig. 7Fig. 8Fig. 9Fig. 10Fig. 11Fig. 12Fig. 12c & 12dFig. 13Fig. 13 b,c,dFig. 14Fig. 14bFig. 15Fig. 15bFig. 16Fig. 17Fig. 18

Lavender, J. P.

1973-01-01

111

TOPICAL REVIEW: A review of classification algorithms for EEG-based brain computer interfaces  

Microsoft Academic Search

In this paper we review classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.

F. Lotte; M. Congedo; A. Lécuyer; F. Lamarche; B. Arnaldi

2007-01-01

112

Sparse representation-based classification scheme for motor imagery-based brain-computer interface systems  

NASA Astrophysics Data System (ADS)

Motor imagery (MI)-based brain-computer interface systems (BCIs) normally use a powerful spatial filtering and classification method to maximize their performance. The common spatial pattern (CSP) algorithm is a widely used spatial filtering method for MI-based BCIs. In this work, we propose a new sparse representation-based classification (SRC) scheme for MI-based BCI applications. Sensorimotor rhythms are extracted from electroencephalograms and used for classification. The proposed SRC method utilizes the frequency band power and CSP algorithm to extract features for classification. We analyzed the performance of the new method using experimental datasets. The results showed that the SRC scheme provides highly accurate classification results, which were better than those obtained using the well-known linear discriminant analysis classification method. The enhancement of the proposed method in terms of the classification accuracy was verified using cross-validation and a statistical paired t-test (p < 0.001).

Shin, Younghak; Lee, Seungchan; Lee, Junho; Lee, Heung-No

2012-10-01

113

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

NASA Astrophysics Data System (ADS)

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.

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

2008-04-01

114

Brain–computer interfaces (BCIs): Detection instead of classification  

Microsoft Academic Search

Many studies over the past two decades have shown that people can use brain signals to convey their intent to a computer through brain–computer interfaces (BCIs). These devices operate by recording signals from the brain and translating these signals into device commands. They can be used by people who are severely paralyzed to communicate without any use of muscle activity.

G. Schalk; P. Brunner; L. A. Gerhardt; H. Bischof; J. R. Wolpaw

2008-01-01

115

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

PubMed Central

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.

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

116

Perioperative thromboprophylaxis in patients with craniotomy for brain tumours: a systematic review.  

PubMed

Venous thromboembolism (VTE) events are frequent in neurooncological patients in perioperative period thus increasing mortality and morbidity. The role of prophylaxis has not yet been established with certainty, and in various neurosurgery and intensive care units the practice is inconsistent. A better definition of the risk/cost/benefit ratio of the various methods, both mechanical (intermittent pneumatic compression-IPC, graduated compression stockings-GCS) and pharmacological (unfractionated heparin-UFH or low molecular weight heparin-LMWH), is warranted. We aim to define the optimal prophylactic treatment in the perioperative period in neurooncological patients. A systematic review of the literature was performed in Medline, Embase and Cochrane Library. Thirteen randomized controlled trials (RCTs) were identified, in which physical methods (IPC or GCS) and/or drugs (UFH or LMWHs) were evaluated in perioperative prophylaxis of neurological patients, mostly with brain cancer not treated with anticoagulants for other diseases. The analysis was conducted on a total of 1,932 randomized patients of whom 1,558 had brain tumours. Overall data show a trend of reduction of VTE in patients treated with mechanical methods (IPC or GCS) that should be initiated preoperatively and continued until discharge or longer in case of persistence of risk factors. The addition of enoxaparin starting the day after surgery, significantly reduces clinically manifest VTE, despite an increase in major bleeding events. Further studies are needed to delineate the types of patients with an increase of VTE risk and risk/benefits ratio of physical and pharmacological treatments in the perioperative period. PMID:23543244

Salmaggi, Andrea; Simonetti, Giorgia; Trevisan, Elisa; Beecher, Deirdre; Carapella, Carmine Maria; DiMeco, Francesco; Conti, Laura; Pace, Andrea; Filippini, Graziella

2013-06-01

117

LINT, a novel dL(3)mbt-containing complex, represses malignant brain tumour signature genes.  

PubMed

Mutations in the l(3)mbt tumour suppressor result in overproliferation of Drosophila larval brains. Recently, the derepression of different gene classes in l(3)mbt mutants was shown to be causal for transformation. However, the molecular mechanisms of dL(3)mbt-mediated gene repression are not understood. Here, we identify LINT, the major dL(3)mbt complex of Drosophila. LINT has three core subunits-dL(3)mbt, dCoREST, and dLint-1-and is expressed in cell lines, embryos, and larval brain. Using genome-wide ChIP-Seq analysis, we show that dLint-1 binds close to the TSS of tumour-relevant target genes. Depletion of the LINT core subunits results in derepression of these genes. By contrast, histone deacetylase, histone methylase, and histone demethylase activities are not required to maintain repression. Our results support a direct role of LINT in the repression of brain tumour-relevant target genes by restricting promoter access. PMID:22570633

Meier, Karin; Mathieu, Eve-Lyne; Finkernagel, Florian; Reuter, L Maximilian; Scharfe, Maren; Doehlemann, Gunther; Jarek, Michael; Brehm, Alexander

2012-01-01

118

LINT, a Novel dL(3)mbt-Containing Complex, Represses Malignant Brain Tumour Signature Genes  

PubMed Central

Mutations in the l(3)mbt tumour suppressor result in overproliferation of Drosophila larval brains. Recently, the derepression of different gene classes in l(3)mbt mutants was shown to be causal for transformation. However, the molecular mechanisms of dL(3)mbt-mediated gene repression are not understood. Here, we identify LINT, the major dL(3)mbt complex of Drosophila. LINT has three core subunits—dL(3)mbt, dCoREST, and dLint-1—and is expressed in cell lines, embryos, and larval brain. Using genome-wide ChIP–Seq analysis, we show that dLint-1 binds close to the TSS of tumour-relevant target genes. Depletion of the LINT core subunits results in derepression of these genes. By contrast, histone deacetylase, histone methylase, and histone demethylase activities are not required to maintain repression. Our results support a direct role of LINT in the repression of brain tumour-relevant target genes by restricting promoter access.

Meier, Karin; Mathieu, Eve-Lyne; Finkernagel, Florian; Reuter, L. Maximilian; Scharfe, Maren; Doehlemann, Gunther; Jarek, Michael; Brehm, Alexander

2012-01-01

119

Automated segmentation and classification of multispectral magnetic resonance images of brain using artificial neural networks  

Microsoft Academic Search

Presents a fully automated process for segmentation and classification of multispectral magnetic resonance (MR) images. This hybrid neural network method uses a Kohonen self-organizing neural network for segmentation and a multilayer backpropagation neural network for classification. To separate different tissue types, this process uses the standard T1-, T2-, and PD-weighted MR images acquired in clinical examinations. Volumetric measurements of brain

Wilburn E. Reddick; John O. Glass; Edwin N. Cook; T. David Elkin; Russell J. Deaton

1997-01-01

120

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

PubMed Central

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 cancer. Because these cancers are relatively rare, the cumulative absolute risks are small: in the 10 years after the first scan for patients younger than 10 years, one excess case of leukaemia and one excess case of brain tumour per 10?000 head CT scans is estimated to occur. Nevertheless, although clinical benefits should outweigh the small absolute risks, radiation doses from CT scans ought to be kept as low as possible and alternative procedures, which do not involve ionising radiation, should be considered if appropriate. Funding US National Cancer Institute and UK Department of Health.

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 Gonzalez, Amy Berrington

2012-01-01

121

A new approach to MRI brain images classification  

Microsoft Academic Search

The aim of this work is to present an automated method that assists diagnosis of normal and abnormal MR images. The diagnosis method consists of four stages, pre- processing of MR images, feature extraction, dimensionality reduction and classification. After histogram equalization of image, the features are extracted based on discrete wavelet transformation (DWT). Then the features are reduced using principal

Shahla Najafi; Mehdi Chehel Amirani; Zahra Sedghi

2011-01-01

122

Potential of anti-cancer therapy based on anti-miR-155 oligonucleotides in glioma and brain tumours.  

PubMed

MicroRNAs are aberrantly expressed in many cancers and can exert tumour-suppressive or oncogenic functions. As oncomirs promote growth of cancer cells and support survival during chemotherapy, thus microRNA-silencing therapies could be a valuable approach to be associated with anticancer drugs and chemotherapy treatments. miR-155 microRNA was found overexpressed in different types of cancer, such as leukaemias (PML, B-cell lymphomas), lung cancer and glioblastoma. GABA-A receptor downregulation was found correlated with glioma grading, with decreasing levels associated with higher grade of malignancies. A relationship between knock-down of miR-155 and re-expression of GABRA 1 protein in vivo was recently individuated. This finding has implication on the effectiveness of RNA-silencing approaches against miR-155 with the scope to control proliferation and signalling pathways regulated by GABA-A receptor. Applying microRNAs for treatment of brain tumours poses several problems, and fields to be solved are mainly the passage of the brain-blood barrier and the targeted delivery to specific cell types. Glioblastoma multiforme cells bud off microvesicles that deliver cytoplasmic contents to nearby cells. Thus, the exploitation of these mechanisms to deliver antagomir therapeutics targeting microvescicles in the brain could take the lead in the near future in the treatment for brain cancers in substitution of invasive surgical intervention. PMID:22834637

Poltronieri, Palmiro; D'Urso, Pietro I; Mezzolla, Valeria; D'Urso, Oscar F

2013-01-01

123

In vivo nuclear magnetic resonance spectroscopy of a transplanted brain tumour.  

PubMed Central

In vivo nuclear magnetic resonance 31P spectroscopy was used to demonstrate different patterns of high energy phosphate metabolism in a group of malignant tumours of glial origin. In some of the more malignant tumours a decrease in adenylate energy charge was found. This was associated with a decline in phosphocreatine and an increase in sugar phosphate and inorganic phosphorus.

Koeze, T. H.; Lantos, P. L.; Iles, R. A.; Gordon, R. E.

1984-01-01

124

Transient mutism and speech disorders after posterior fossa surgery in children with brain tumours  

Microsoft Academic Search

Summary Four patients aged 5 to 9 years with large tumours located in the posterior fossa (PNET, ependymoma or astrocytoma) are presented. Patients received standard neuropsychological assessments, including speech evaluation, prior to surgery. Following tumour resection, these 4 children developed transient mutism or different types of speech and cognitive disorders, associated with behavioural disturbances.

A. Kingma; J. J. A. Mooij; J. D. M. Metzemaekers; J. A. Leeuw

1994-01-01

125

Dietary restriction reduces angiogenesis and growth in an orthotopic mouse brain tumour model  

Microsoft Academic Search

Diet and lifestyle produce major effects on tumour incidence, prevalence, and natural history. Moderate dietary restriction has long been recognised as a natural therapy that improves health, promotes longevity, and reduces both the incidence and growth of many tumour types. Dietary restriction differs from fasting or starvation by reducing total food and caloric intake without causing nutritional deficiencies. No prior

P Mukherjee; M M El-Abbadi; J L Kasperzyk; M K Ranes; T N Seyfried

2002-01-01

126

Double-labelling immunohistochemistry for MGMT and a "cocktail" of non-tumourous elements is a reliable, quick and easy technique for inferring methylation status in glioblastomas and other primary brain tumours  

PubMed Central

Background Our aim was to develop a new protocol for MGMT immunohistochemistry with good agreement between observers and good correlation with molecular genetic tests of tumour methylation. We examined 40 primary brain tumours (30 glioblastomas and 10 oligodendroglial tumours) with our new technique, namely double-labelling immunohistochemistry for MGMT and a "cocktail" of non-tumour antigens (CD34, CD45 and CD68). We compared the results with single-labelling immunohistochemistry for MGMT and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA, a recognised molecular genetic technique which we applied as the gold-standard for the methylation status). Results Double-labelling immunohistochemistry for MGMT produced a visual separation of tumourous and non-tumourous elements on the same histological slide, making it quick and easy to determine whether tumour cell nuclei were MGMT-positive or MGMT-negative (and thereby infer the methylation status of the tumour). We found good agreement between observers (kappa 0.76) and within observer (kappa 0.84). Furthermore, double-labelling showed good specificity (80%), sensitivity (73.33%), positive predictive value (PPV, 83.33%) and negative predictive value (NPV, 68.75%) compared to MS-MLPA. Double-labelling was quicker and easier to assess than single-labelling and it outperformed quantitative computerised image analysis of MGMT single-labelling in terms of sensitivity, specificity, PPV and NPV. Conclusions Double-labelling immunohistochemistry for MGMT and a cocktail of non-tumourous elements provides a "one look" method for determining whether tumour cell nuclei are MGMT-positive or MGMT-negative. This can be used to infer the methylation status of the tumour. There is good observer agreement and good specificity, sensitivity, PPV and NPV compared to a molecular gold-standard.

2013-01-01

127

Essential problems in the interpretation of epidemiologic evidence for an association between mobile phone use and brain tumours  

NASA Astrophysics Data System (ADS)

Due to the close proximity of a mobile phone to the head when placing a call, concerns have been raised that exposure from microwaves during mobile phone use may exert adverse health effects and, in particular, may increase the risk of brain tumours. In response to these concerns epidemiological studies have been conducted, most applying the case-control design. While epidemiology can provide decisive evidence for an association between an exposure and a disease fundamental problems arise if exposure is short compared to the natural history of the disease. For brain tumours latencies of decades have been implicated making special considerations about potential effects of exposures necessary that commence during an already growing tumour. It is shown that measures of disease risk like odds ratios and relative risks can under such circumstances not be interpreted as indicators of a long term effect on incidences in the exposed population. Besides this problem, the issues of a suitable exposure metric and the selection of endpoints are unresolved. It is shown that the solution of these problems affords knowledge about the mechanism of action by which exposure increases the risk of manifest disease.

Kundi, Michael

2010-11-01

128

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)

In addition to its common usage as a tracer in metabolic and physiological studies, deuterium possesses anti-tumoural activity and confers protection against ?-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.

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

2005-05-01

129

Pattern Classification of Large-Scale Functional Brain Networks: Identification of Informative Neuroimaging Markers for Epilepsy  

PubMed Central

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 behind complex neuropsychiatric disorders. The systematic approaches we present here are expected to have wider applications in general neuropsychiatric disorders.

Zhang, ZhiQiang; Lu, WenLian; Lu, GuangMing; Feng, Jianfeng

2012-01-01

130

A multiscale and multiblock fuzzy C-means classification method for brain MR images  

PubMed Central

Purpose: Classification of magnetic resonance (MR) images has many clinical and research applications. Because of multiple factors such as noise, intensity inhomogeneity, and partial volume effects, MR image classification can be challenging. Noise in MRI can cause the classified regions to become disconnected. Partial volume effects make the assignment of a single class to one region difficult. Because of intensity inhomogeneity, the intensity of the same tissue can vary with respect to the location of the tissue within the same image. The conventional “hard” classification method restricts each pixel exclusively to one class and often results in crisp results. Fuzzy C-mean (FCM) classification or “soft” segmentation has been extensively applied to MR images, in which pixels are partially classified into multiple classes using varying memberships to the classes. Standard FCM, however, is sensitive to noise and cannot effectively compensate for intensity inhomogeneities. This paper presents a method to obtain accurate MR brain classification using a modified multiscale and multiblock FCM. Methods: An automatic, multiscale and multiblock fuzzy C-means (MsbFCM) classification method with MR intensity correction is presented in this paper. We use a bilateral filter to process MR images and to build a multiscale image series by increasing the standard deviation of spatial function and by reducing the standard deviation of range function. At each scale, we separate the image into multiple blocks and for every block a multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels in order to overcome the effect of intensity inhomogeneity. The result from a coarse scale supervises the classification in the next fine scale. The classification method is tested with noisy MR images with intensity inhomogeneity. Results: Our method was compared with the conventional FCM, a modified FCM (MFCM) and multiscale FCM (MsFCM) method. Validation studies were performed on synthesized images with various contrasts, on the simulated brain MR database, and on real MR images. Our MsbFCM method consistently performed better than the conventional FCM, MFCM, and MsFCM methods. The MsbFCM method achieved an overlap ratio of 91% or higher. Experimental results using real MR images demonstrate the effectiveness of the proposed method. Our MsbFCM classification method is accurate and robust for various MR images. Conclusions: As our classification method did not assume a Gaussian distribution of tissue intensity, it could be used on other image data for tissue classification and quantification. The automatic classification method can provide a useful quantification tool in neuroimaging and other applications.

Yang, Xiaofeng; Fei, Baowei

2011-01-01

131

Rarely metastasizing soft tissue tumours.  

PubMed

Soft tissue tumours that rarely metastasize have been afforded their own subcategory in recent WHO classifications. This review discusses the nature of these tumours and the difficulty in constructing usefully simple classifications for heterogeneous and complex groups of tumours. We also highlight the specific rarely metastasizing soft tissue tumours that have been recently added to the WHO classification (phosphaturic mesenchymal tumour, pseudomyogenic haemangioendothelioma) and those entities where there have been recent important defining genetic discoveries (myxoinflammatory fibroblastic sarcoma, solitary fibrous tumour, myoepitheliomas). PMID:24117966

Mangham, D Chas; Kindblom, Lars-Gunnar

2014-01-01

132

NK1 receptor antagonists and dexamethasone as anticancer agents in vitro and in a model of brain tumours secondary to breast cancer.  

PubMed

Emend, an NK1 antagonist, and dexamethasone are used to treat complications associated with metastatic brain tumours and their treatment. It has been suggested that these agents exert anticancer effects apart from their current use. The effects of the NK1 antagonists, Emend and N-acetyl-L-tryptophan, and dexamethasone on tumour growth were investigated in vitro and in vivo at clinically relevant doses. For animal experiments, a stereotaxic injection model of Walker 256 rat breast carcinoma cells into the striatum of Wistar rats was used. Emend treatment led to a decrease in tumour cell viability in vitro, although this effect was not replicated by N-acetyl-L-tryptophan. Dexamethasone did not decrease tumour cell viability in vitro but decreased tumour volume in vivo, likely to be through a reduction in tumour oedema, as indicated by the increase in tumour cell density. None of the agents investigated altered tumour cell replication or apoptosis in vivo. Inoculated animals showed increased glial fibrillary acidic protein and ionized calcium-binding adapter molecule 1 immunoreactivity indicative of astrocytes and microglia in the peritumoral area, whereas treatment with Emend and dexamethasone reduced the labelling for both glial cells. These results do not support the hypothesis that NK1 antagonists or dexamethasone exert a cytotoxic action on tumour cells, although these conclusions may be specific to this model and cell line. PMID:23407059

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

2013-04-01

133

Paediatric head CT scan and subsequent risk of malignancy and benign brain tumour: a nation-wide population-based cohort study.  

PubMed

Background:To evaluate the possible association between paediatric head computed tomography (CT) examination and increased subsequent risk of malignancy and benign brain tumour.Methods:In the exposed cohort, 24?418 participants under 18 years of age, who underwent head CT examination between 1998 and 2006, were identified from the Taiwan National Health Insurance Research Database (NHIRD). Patients were followed up until a diagnosis of malignant disease or benign brain tumour, withdrawal from the National Health Insurance (NHI) system, or at the end of 2008.Results:The overall risk was not significantly different in the two cohorts (incidence rate=36.72 per 100?000 person-years in the exposed cohort, 28.48 per 100?000 person-years in the unexposed cohort, hazard ratio (HR)=1.29, 95% confidence interval (CI)=0.90-1.85). The risk of benign brain tumour was significantly higher in the exposed cohort than in the unexposed cohort (HR=2.97, 95% CI=1.49-5.93). The frequency of CT examination showed strong correlation with the subsequent overall risk of malignancy and benign brain tumour.Conclusions:We found that paediatric head CT examination was associated with an increased incidence of benign brain tumour. A large-scale study with longer follow-up is necessary to confirm this result. PMID:24569470

Huang, W-Y; Muo, C-H; Lin, C-Y; Jen, Y-M; Yang, M-H; Lin, J-C; Sung, F-C; Kao, C-H

2014-04-29

134

Spatially Aggregated Multi-Class Pattern Classification in Functional MRI using Optimally Selected Functional Brain Areas  

PubMed Central

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality, and improve the robustness and accuracy of fMRI classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation.

Zheng, Weili; Ackley, Elena S.; Martinez-Ramon, Manel; Posse, Stefan

2012-01-01

135

Development of a new autofluorescence probe for the analysis of normal and tumour brain tissues  

Microsoft Academic Search

Fluorescence spectroscopy of endogenous emission of brain tumors, in particular glioblastoma multiforme, will be used for intraoperative localization of brain tumor margins. Our future surgeon's probe aims to discriminate tumor from normal brain tissues using beta and autofluorescence detection at the same time. Within this study we have implemented C6 glioma cells into rat brains to analyze the endogenous fluorescence

R. Siebert; M. H. Vu Thi; F. Jean; Y. Charon; M. Collado-Hilly; M. A. Duval; T. Mandat; L. Menard; S. Palfi; T. Tordjmann

2008-01-01

136

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

PubMed

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. PMID:24981017

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

2014-08-01

137

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

PubMed Central

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.

van Tongeren, Martie

2013-01-01

138

Radiobiological framework for the evaluation of stereotactic radiosurgery plans for invasive brain tumours.  

PubMed

This study presents a radiobiological formalism for the evaluation of the treatment plans with respect to the probability of controlling tumours treated with stereotactic radiosurgery accounting for possible infiltrations of malignant cells beyond the margins of the delineated target. Treatments plans devised for three anaplastic astrocytoma cases were assumed for this study representing cases with different difficulties for target coverage. Several scenarios were considered regarding the infiltration patterns. Tumour response was described in terms of tumour control probability (TCP) assuming a Poisson model taking into account the initial number of clonogenic cells and the cell survival. The results showed the strong impact of the pattern of infiltration of tumour clonogens outside the delineated target on the outcome of the treatment. The treatment plan has to take into account the existence of the possible microscopic disease around the visible lesion; otherwise the high gradients around the target effectively prevent the sterilisation of the microscopic spread leading to low probability of control, in spite of the high dose delivered to the target. From this perspective, the proposed framework offers a further criterion for the evaluation of stereotactic radiosurgery plans taking into account the possible infiltration of tumour cells around the visible target. PMID:24490086

Sandström, Helena; Dasu, Alexandru; Toma-Dasu, Iuliana

2013-01-01

139

Radiobiological Framework for the Evaluation of Stereotactic Radiosurgery Plans for Invasive Brain Tumours  

PubMed Central

This study presents a radiobiological formalism for the evaluation of the treatment plans with respect to the probability of controlling tumours treated with stereotactic radiosurgery accounting for possible infiltrations of malignant cells beyond the margins of the delineated target. Treatments plans devised for three anaplastic astrocytoma cases were assumed for this study representing cases with different difficulties for target coverage. Several scenarios were considered regarding the infiltration patterns. Tumour response was described in terms of tumour control probability (TCP) assuming a Poisson model taking into account the initial number of clonogenic cells and the cell survival. The results showed the strong impact of the pattern of infiltration of tumour clonogens outside the delineated target on the outcome of the treatment. The treatment plan has to take into account the existence of the possible microscopic disease around the visible lesion; otherwise the high gradients around the target effectively prevent the sterilisation of the microscopic spread leading to low probability of control, in spite of the high dose delivered to the target. From this perspective, the proposed framework offers a further criterion for the evaluation of stereotactic radiosurgery plans taking into account the possible infiltration of tumour cells around the visible target.

Sandstrom, Helena; Dasu, Alexandru; Toma-Dasu, Iuliana

2013-01-01

140

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

PubMed

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. PMID:19162827

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

2008-01-01

141

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

NASA Astrophysics Data System (ADS)

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%.

Pulido, Andrea; Rueda, Andrea; Romero, Eduardo

2013-02-01

142

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

NASA Astrophysics Data System (ADS)

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.

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

2014-03-01

143

Lack of functional TSLP receptors mitigates Th2 polarization and the establishment and growth of 4T1 primary breast tumours but has different effects on tumour quantities in the lung and brain.  

PubMed

The 4T1 mammary carcinoma cell line produces TSLP. We had hypothesized that TSLP promotes the development of a permissive environment for the growth and metastasis of primary tumour and that this is associated with a Th2-polarized antitumour immune response. We found that, in Tslpr(-/-) mice, the mean tumour diameters were smaller from days 27 to 40, and relatively fewer tumour cells were present in the lung, compared with wild-type mice. Polarization of the Th2 cytokine profile was also diminished in Tslpr(-/-) mice. These findings confirmed those reported previously by others. Here, we further show that primary tumours are established less often in Tslpr(-/-) mice and that, unexpectedly, the relative number of tumour cells in the brain is greater in Tslpr(-/-) mice compared with wild-type mice. Findings from our cytotoxicity assays show that 4T1-directed lysis is undetectable in both WT and Tslpr(-/-) mice, ruling out the possibility that altered cytotoxic responses in Tslpr(-/-) mice are responsible for the differences we observed. In a human tissue microarray, positive staining for TSLP was seen in tumour cells from breast cancer tissue, but it was also seen in normal glandular epithelial cells from normal breast tissue, which has not been shown before. Thus, our findings provide new insight into the effects of TSLP in metastatic breast cancer. PMID:24033709

Erdmann, R B; Gartner, J G; Leonard, W J; Ellison, C A

2013-11-01

144

Motor imagery classification by means of source analysis for brain computer interface applications  

Microsoft Academic Search

We report a pilot study of performing classification of motor imagery for brain-computer interface applications, by means of source analysis of scalp-recorded EEGs. Independent component analysis (ICA) was used as a spatio-temporal filter extracting signal components relevant to left or right motor imagery (MI) tasks. Source analysis methods including equivalent dipole analysis and cortical current density imaging were applied to

Lei Qin; Lei Ding; Bin He

2004-01-01

145

Measuring brain lesion progression with a supervised tissue classification system.  

PubMed

Brain lesions, especially White Matter Lesions (WMLs), are associated with cardiac and vascular disease, but also with normal aging. Quantitative analysis of WML in large clinical trials is becoming more and more important. In this paper, we present a computer-assisted WML segmentation method, based on local features extracted from conventional multi-parametric Magnetic Resonance Imaging (MRI) sequences. A framework for preprocessing the temporal data by jointly equalizing histograms reduces the spatial and temporal variance of data, thereby improving the longitudinal stability of such measurements and hence the estimate of lesion progression. A Support Vector Machine (SVM) classifier trained on expert-defined WML's is applied for lesion segmentation on each scan using the AdaBoost algorithm. Validation on a population of 23 patients from 3 different imaging sites with follow-up studies and WMLs of varying sizes, shapes and locations tests the robustness and accuracy of the proposed segmentation method, compared to the manual segmentation results from an experienced neuroradiologist. The results show that our CAD-system achieves consistent lesion segmentation in the 4D data facilitating the disease monitoring. PMID:18979798

Zacharaki, Evangelia I; Kanterakis, Stathis; Bryan, R Nick; Davatzikos, Christos

2008-01-01

146

Evaluation of supervised methods for the classification of major tissues and subcortical structures in multispectral brain magnetic resonance images.  

PubMed

This work investigates the capability of supervised classification methods in detecting both major tissues and subcortical structures using multispectral brain magnetic resonance images. First, by means of a realistic digital brain phantom, we investigated the classification performance of various Discriminant Analysis methods, K-Nearest Neighbor and Support Vector Machine. Then, using phantom and real data, we quantitatively assessed the benefits of integrating anatomical information in the classification, in the form of voxels coordinates as additional features to the intensities or tissue probabilistic atlases as priors. In addition we tested the effect of spatial correlations between neighboring voxels and image denoising. For each brain tissue we measured the classification performance in terms of global agreement percentage, false positive and false negative rates and kappa coefficient. The effectiveness of integrating spatial information or a tissue probabilistic atlas has been demonstrated for the aim of accurately classifying brain magnetic resonance images. PMID:24702776

Murino, Loredana; Granata, Donatella; Carfora, Maria Francesca; Selvan, S Easter; Alfano, Bruno; Amato, Umberto; Larobina, Michele

2014-07-01

147

Feature Extraction from Subband Brain Signals and Its Classification  

NASA Astrophysics Data System (ADS)

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).

Mukul, Manoj Kumar; Matsuno, Fumitoshi

148

Embedding filtering criteria into a wrapper marker selection method for brain tumor classification: an application on metabolic peak area ratios  

Microsoft Academic Search

The purpose of this study is to identify reliable sets of metabolic markers that provide accurate classification of complex brain tumors and facilitate the process of clinical diagnosis. Several ratios of metabolites are tested alone or in combination with imaging markers. A wrapper feature selection and classification methodology is studied, employing Fisher's criterion for ranking the markers. The set of

M. G. Kounelakis; M. E. Zervakis; G. C. Giakos; G. J. Postma; L. M. C. Buydens; X. Kotsiakis

2011-01-01

149

CLASSIFICATION  

NSDL National Science Digital Library

Students will learn about classification Go into the Carnivorous Plant site and find 5 facts about carnivorous plants and write them in your science journal. Carnivorous Plants Using the animal classification site, click on the animals shown and write information about 2 of them in your journal. animal classification Use the animal diversity web page and write down ...

Kirby, Ms.

2009-09-23

150

Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra.  

PubMed

A computer-based decision support system to assist radiologists in diagnosing and grading brain tumours has been developed by the multi-centre INTERPRET project. Spectra from a database of 1H single-voxel spectra of different types of brain tumours, acquired in vivo from 334 patients at four different centres, are clustered according to their pathology, using automated pattern recognition techniques and the results are presented as a two-dimensional scatterplot using an intuitive graphical user interface (GUI). Formal quality control procedures were performed to standardize the performance of the instruments and check each spectrum, and teams of expert neuroradiologists, neurosurgeons, neurologists and neuropathologists clinically validated each case. The prototype decision support system (DSS) successfully classified 89% of the cases in an independent test set of 91 cases of the most frequent tumour types (meningiomas, low-grade gliomas and high-grade malignant tumours--glioblastomas and metastases). It also helps to resolve diagnostic difficulty in borderline cases. When the prototype was tested by radiologists and other clinicians it was favourably received. Results of the preliminary clinical analysis of the added value of using the DSS for brain tumour diagnosis with MRS showed a small but significant improvement over MRI used alone. In the comparison of individual pathologies, PNETs were significantly better diagnosed with the DSS than with MRI alone. PMID:16763971

Tate, Anne R; Underwood, Joshua; Acosta, Dionisio M; Julià-Sapé, Margarida; Majós, Carles; Moreno-Torres, Angel; Howe, Franklyn A; van der Graaf, Marinette; Lefournier, Virginie; Murphy, Mary M; Loosemore, Alison; Ladroue, Christophe; Wesseling, Pieter; Luc Bosson, Jean; Cabañas, Miquel E; Simonetti, Arjan W; Gajewicz, Witold; Calvar, Jorge; Capdevila, Antoni; Wilkins, Peter R; Bell, B Anthony; Rémy, Chantal; Heerschap, Arend; Watson, Des; Griffiths, John R; Arús, Carles

2006-06-01

151

Patterns of exposure to infectious diseases and social contacts in early life and risk of brain tumours in children and adolescents: an International Case-Control Study (CEFALO)  

PubMed Central

Background: Infectious diseases and social contacts in early life have been proposed to modulate brain tumour risk during late childhood and adolescence. Methods: CEFALO is an interview-based case–control study in Denmark, Norway, Sweden and Switzerland, including children and adolescents aged 7–19 years with primary intracranial brain tumours diagnosed between 2004 and 2008 and matched population controls. Results: The study included 352 cases (participation rate: 83%) and 646 controls (71%). There was no association with various measures of social contacts: daycare attendance, number of childhours at daycare, attending baby groups, birth order or living with other children. Cases of glioma and embryonal tumours had more frequent sick days with infections in the first 6 years of life compared with controls. In 7–19 year olds with 4+ monthly sick day, the respective odds ratios were 2.93 (95% confidence interval: 1.57–5.50) and 4.21 (95% confidence interval: 1.24–14.30). Interpretation: There was little support for the hypothesis that social contacts influence childhood and adolescent brain tumour risk. The association between reported sick days due to infections and risk of glioma and embryonal tumour may reflect involvement of immune functions, recall bias or inverse causality and deserve further attention.

Andersen, T V; Schmidt, L S; Poulsen, A H; Feychting, M; Roosli, M; Tynes, T; Aydin, D; Prochazka, M; Lannering, B; Klaeboe, L; Eggen, T; Kuehni, C E; Schmiegelow, K; Schuz, J

2013-01-01

152

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

NASA Astrophysics Data System (ADS)

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.

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

2012-03-01

153

CAVIAR: CLASSIFICATION VIA AGGREGATED REGRESSION AND ITS APPLICATION IN CLASSIFYING OASIS BRAIN DATABASE  

PubMed Central

This paper presents a novel classification via aggregated regression algorithm – dubbed CAVIAR – and its application to the OASIS MRI brain image database. The CAVIAR algorithm simultaneously combines a set of weak learners based on the assumption that the weight combination for the final strong hypothesis in CAVIAR depends on both the weak learners and the training data. A regularization scheme using the nearest neighbor method is imposed in the testing stage to avoid overfitting. A closed form solution to the cost function is derived for this algorithm. We use a novel feature – the histogram of the deformation field between the MRI brain scan and the atlas which captures the structural changes in the scan with respect to the atlas brain – and this allows us to automatically discriminate between various classes within OASIS [1] using CAVIAR. We empirically show that CAVIAR significantly increases the performance of the weak classifiers by showcasing the performance of our technique on OASIS.

Chen, Ting; Rangarajan, Anand; Vemuri, Baba C.

2010-01-01

154

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

NASA Astrophysics Data System (ADS)

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.

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

2014-01-01

155

[Molecular cytogenetic analysis of chromosomal aberrations in cells of low grade gliomas and its contribution for tumour classification].  

PubMed

Background: Low-grade gliomas represent a heterogeneous group of primary brain malignancies. The current dia-gnostics of these tumors rely strongly on histological classification. With the development of molecular cytogenetic methods several genetic markers were described, conributing to a better distinction of glial subtypes. The aim of this study was to assess the frequency of acquired chromosomal aberrations in low?grade gliomas and to search for new genomic changes associated with higher risk of tumor progression. Patients and Methods: We analysed bio-psy specimens from 41 patients with histological dia-gnosis of low-grade glioma using interphase fluorescence in situ hybridization (I?FISH) and single nucleotide polymorphism (SNP) array techniques (19 females and 22 males, medium age 42 years). Results: Besides notorious and most frequent finding of combined deletion of 1p/?19q (81.25% patients) several other recurrent aberrations were described in patients with oligodendrogliomas: deletions of p and q arms of chromosome 4 (25% patients), deletions of the short arms of chromosome 9 (18.75% patients), deletions of the long arms of chromosome 13 and monosomy of chromosome 18 (18.75% patients). In bio-psy specimens from patients with astrocytomas, we often observed deletion of 1p (24% patients), amplification of the long arms of chromosome 7 (16% patients), deletion of the long arm of chromosome 13 (20% patients), segmental uniparental disomy (UPD) of the short arms of chromosome 17 (60% patients) and deletion of the long arms of chromosome 19 (28% patients). In one patient we detected a shuttered chromosome 10 resulting from chromothripsis. Conclusion: Using a combination of I?FISH and SNP array, we detected not only known chromosomal changes but also new or less frequent recur-rent aberrations. Their role in cancer?cell progression and their impact on low?grade gliomas classification remains to be elucidated in a larger cohort of patients. Key words: oligodendroglioma -? astrocytoma -? SNP array -? interphase FISH - glioma This work was supported by grants of Internal Grant Agency of the Czech Ministry of Health No. NT/13212-4, PRVOUK-P27/LF1/1 a RVO-VFN64165. The authors declare they have no potential conflicts of interest concerning drugs, products, or?services used in the study. The Editorial Board declares that the manuscript met the ICMJE "uniform requirements" for biomedical papers.Submitted: 5. 11. 2013Accepted: 29. 1. 2014. PMID:24918277

Lhotská, H; Zemanová, Z; Kramá?, F; Lizcová, L; Svobodová, K; Ransdorfová, S; Byst?ická, D; Krej?ík, Z; Hrabal, P; Dohnalová, A; Kaiser, M; Michalová, K

2014-01-01

156

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

PubMed

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. PMID:23292152

Khan, Fary; Amatya, Bhasker

2013-02-01

157

Feed-forward hierarchical model of the ventral visual stream applied to functional brain image classification.  

PubMed

Functional brain imaging is a common tool in monitoring the progression of neurodegenerative and neurological disorders. Identifying functional brain imaging derived features that can accurately detect neurological disease is of primary importance to the medical community. Research in computer vision techniques to identify objects in photographs have reported high accuracies in that domain, but their direct applicability to identifying disease in functional imaging is still under investigation in the medical community. In particular, Serre et al. (: In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR-05). pp 994-1000) introduced a biophysically inspired filtering method emulating visual processing in striate cortex which they applied to perform object recognition in photographs. In this work, the model described by Serre et al. [2005] is extended to three-dimensional volumetric images to perform signal detection in functional brain imaging (PET, SPECT). The filter outputs are used to train both neural network and logistic regression classifiers and tested on two distinct datasets: ADNI Alzheimer's disease 2-deoxy-D-glucose (FDG) PET and National Football League players Tc99m HMPAO SPECT. The filtering pipeline is analyzed to identify which steps are most important for classification accuracy. Our results compare favorably with other published classification results and outperform those of a blinded expert human rater, suggesting the utility of this approach. PMID:22847891

Keator, David B; Fallon, James H; Lakatos, Anita; Fowlkes, Charless C; Potkin, Steven G; Ihler, Alexander

2014-01-01

158

Imaging of adult astrocytic brain tumours with 7 T MRI: preliminary results  

Microsoft Academic Search

Purpose  In this study tumour vascularity and necrosis of intracranial astrocytomas were compared using 7 T and 1.5 T magnetic resonance\\u000a imaging (MRI).\\u000a \\u000a \\u000a \\u000a \\u000a Methods  Fifteen patients with histologically proven astrocytomas (WHO grades II–IV) were prospectively examined at 1.5 T (Magnetom\\u000a Espree or Sonata) and 7 T (Magnetom 7 T, Siemens, Erlangen, Germany) with T2*-w (weighted), T1-w with (only a subset of five\\u000a patients at 7 T)

Christoph Moenninghoff; Stefan Maderwald; Jens M. Theysohn; Oliver Kraff; Mark E. Ladd; Nicolai El Hindy; Johannes van de Nes; Michael Forsting; Isabel Wanke

2010-01-01

159

Development of a new autofluorescence probe for the analysis of normal and tumour brain tissues  

NASA Astrophysics Data System (ADS)

Fluorescence spectroscopy of endogenous emission of brain tumors, in particular glioblastoma multiforme, will be used for intraoperative localization of brain tumor margins. Our future surgeon's probe aims to discriminate tumor from normal brain tissues using beta and autofluorescence detection at the same time. Within this study we have implemented C6 glioma cells into rat brains to analyze the endogenous fluorescence of tumor and normal rat brain tissue. Systematic differences have been observed when comparing the autofluorescence spectra obtained from white and grey matters: both the fluorescence intensity and the shape of the spectra differ. These results were obtained by means of a 2-fiber probe, one used to guide the laser to the tissue, the other for fluorescence light collection. Excitation light was delivered by a 405 nm picosecond laser and fluorescence detection was realized by a CCD-camera. In parallel we have developed brain phantoms allowing systematic analysis of fiber - sample geometries. Based on gelatin gels, they include silica particles with 235 and 329 nm diameters to simulate the diffusion characteristics of the tissue, ink for the absorption characteristics of the tissue and organic dyes like Rhodamin B to replace biofluorophores.

Siebert, R.; Vu Thi, M. H.; Jean, F.; Charon, Y.; Collado-Hilly, M.; Duval, M. A.; Mandat, T.; Menard, L.; Palfi, S.; Tordjmann, T.

2008-05-01

160

Real-time fMRI using brain-state classification.  

PubMed

We have implemented a real-time functional magnetic resonance imaging system based on multivariate classification. This approach is distinctly different from spatially localized real-time implementations, since it does not require prior assumptions about functional localization and individual performance strategies, and has the ability to provide feedback based on intuitive translations of brain state rather than localized fluctuations. Thus this approach provides the capability for a new class of experimental designs in which real-time feedback control of the stimulus is possible-rather than using a fixed paradigm, experiments can adaptively evolve as subjects receive brain-state feedback. In this report, we describe our implementation and characterize its performance capabilities. We observed approximately 80% classification accuracy using whole brain, block-design, motor data. Within both left and right motor task conditions, important differences exist between the initial transient period produced by task switching (changing between rapid left or right index finger button presses) and the subsequent stable period during sustained activity. Further analysis revealed that very high accuracy is achievable during stable task periods, and that the responsiveness of the classifier to changes in task condition can be much faster than signal time-to-peak rates. Finally, we demonstrate the versatility of this implementation with respect to behavioral task, suggesting that our results are applicable across a spectrum of cognitive domains. Beyond basic research, this technology can complement electroencephalography-based brain computer interface research, and has potential applications in the areas of biofeedback rehabilitation, lie detection, learning studies, virtual reality-based training, and enhanced conscious awareness. PMID:17133383

LaConte, Stephen M; Peltier, Scott J; Hu, Xiaoping P

2007-10-01

161

Localisation of motor areas in brain tumour patients: a comparison of preoperative [18F]FDG-PET and intraoperative cortical electrostimulation.  

PubMed

Assessment of the exact spatial relation between tumour and adjacent functionally relevant brain areas is a primary tool in the presurgical planning in brain tumour patients. The purpose of this study was to compare a preoperative fluorine-18 fluorodeoxyglucose positron emission tomography ([18F]FDG PET) activation protocol in patients with tumours near the central area with the results of intraoperative direct cortical electrostimulation, and to determine whether non-invasive preoperative PET imaging can provide results equivalent to those achieved with the invasive neurosurgical "gold standard". In this prospective study, we examined 20 patients with various tumours of the central area, performing two PET scans (each 30 min after i.v. injection of 134-341 MBq [18F]FDG) in each patient: (1) a resting baseline scan and (2) an activation scan using a standardised motor task (finger tapping, foot stretching). Following PET/MRI realignment and normalisation to the whole brain counts, parametric images of the activation versus the rest study were calculated and pixels above categorical threshold values were projected to the individual MRI for bimodal assessment of morphology and function (PET/MRI overlay). Intraoperative direct cortical electrostimulation was performed using a Viking IV probe (5 pulses, each of 100 micros) and documented using a dedicated neuro navigation system. Results were compared with the preoperative PET findings. PET revealed significant activation of the contralateral primary motor cortex in 95% (19/20) of the brain tumour patients (hand activation 13/13, foot activation 6/7), showing a mean increase in normalised [18F]FDG uptake of 20.5% +/- 5.2% (hand activation task) and 17.2% +/- 2.5% (foot activation task). Additionally detected activation of the ipsilateral primary motor cortex was interpreted as a metabolic indication for interhemispheric compensational processes. Evaluation of the PET findings by cortical stimulation yielded a 94% sensitivity and a 95% specificity for identification of motor-associated brain areas. In conclusion, the findings indicate that a relatively simple and clinically available [18F]FDG PET activation protocol enables a sufficiently precise assessment of the local relation between the intracranial tumour and the adjacent motor cortex areas and may facilitate the presurgical planning of tumour resection. PMID:11585300

Schreckenberger, M; Spetzger, U; Sabri, O; Meyer, P T; Zeggel, T; Zimny, M; Gilsbach, J; Buell, U

2001-09-01

162

Change detection and classification in brain MR images using change vector analysis.  

PubMed

The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases--such as Alzheimer's--focus on large-scale brain deformations. However, such patients often have other brain impairments, such as infarcts, white matter lesions and hemorrhages, which are typically overlooked by the deformation-based methods. Other unsupervised change detection algorithms have been proposed to detect tissue intensity changes. The outcome of these methods is typically a binary change map, which identifies changed brain regions. However, understanding what types of changes these regions underwent is likely to provide equally important information about lesion evolution. In this paper, we present an unsupervised 3D change detection method based on Change Vector Analysis. We compute and automatically threshold the Generalized Likelihood Ratio map to obtain a binary change map. Subsequently, we perform histogram-based clustering to classify the change vectors. We obtain a Kappa Index of 0.82 using various types of simulated lesions. The classification error is 2%. Finally, we are able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients. PMID:22256148

Simões, Rita; Slump, Cornelis

2011-01-01

163

Determination of metabolite concentrations in human brain tumour biopsy samples using HR-MAS and ERETIC measurements.  

PubMed

Accurate determination of the concentration of the metabolites contained in intact human biopsies of 10 glioblastoma multiforme samples was achieved using one-dimensional (1)H high-resolution magic angle spinning (HR-MAS) NMR combined with ERETIC (electronic reference to in vivo concentrations) measurements. The amount of sample used ranged from 6.8 to 12.9 mg. Metabolite concentrations were measured in each sample using two methods: with DSS (2,2-dimethyl-2-silapentane-5-sulfonate sodium salt) as an internal reference and with ERETIC as an external electronically generated reference. The ERETIC signal was shown to be highly reproducible and did not affect the spectral quality. The concentrations calculated by the ERETIC method in model solutions were shown to be independent of the salt concentration in the range typically found in biological samples (0-250 mM). The ERETIC method proved to be straightforward to use in tissues and much more robust than the internal standard method. The concentrations calculated using the internal DSS concentration were systematically found to be higher than those determined using the ERETIC technique. These results indicate a possible interaction of the DSS molecules with the biopsy sample. Moreover, variations in the sample preparation process, with possible loss of DSS solution, may hamper the quantification process, as happens in one of the ten samples analysed. In this study, the ERETIC method was validated on model solutions and used in brain tumour tissues. Calculated metabolite concentrations obtained with the ERETIC procedure matched the values determined in the same type of tumours by in vivo, ex vivo and in vitro methodologies. PMID:18833546

Martínez-Bisbal, M Carmen; Monleon, Daniel; Assemat, Olivier; Piotto, Martial; Piquer, José; Llácer, José Luis; Celda, Bernardo

2009-02-01

164

A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-means.  

PubMed

A fully automatic, multiscale and multiblock fuzzy C-means (MsbFCM) classification method with intensity correction for MR images is presented in this paper. We use a bilateral filter to process MR images and to build a multiscale image series by increasing the standard deviation of spatial function and reducing the standard deviation of range function. We separate every scale image into multiple blocks and for every block a multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels to overcome the effect of intensity inhomogeneity. The method is robust for noise MR images with intensity inhomogeneity because of its multiscale and multiblock bilateral filtering scheme. Our method was compared with the conventional FCM, a modified FCM (MFCM) and multiscale FCM (MsFCM) method on synthesized images, simulated brain MR images, and real MR images. The MsbFCM method achieved an overlap ratio of greater than 91% as validated by the ground truth even if original images have 9% noise and 40% intensity inhomogeneity. Experimental results using real MR images demonstrate the effectiveness of the proposed method. Our MsbFCM classification method is accurate and robust for various MR images. PMID:23358117

Yang, Xiaofeng; Fei, Baowei

2011-01-01

165

A MR Brain Classification Method Based on Multiscale and Multiblock Fuzzy C-means  

PubMed Central

A fully automatic, multiscale and multiblock fuzzy C-means (MsbFCM) classification method with intensity correction for MR images is presented in this paper. We use a bilateral filter to process MR images and to build a multiscale image series by increasing the standard deviation of spatial function and reducing the standard deviation of range function. We separate every scale image into multiple blocks and for every block a multiscale fuzzy C-means classification method is applied along the scales from the coarse to fine levels to overcome the effect of intensity inhomogeneity. The method is robust for noise MR images with intensity inhomogeneity because of its multiscale and multiblock bilateral filtering scheme. Our method was compared with the conventional FCM, a modified FCM (MFCM) and multiscale FCM (MsFCM) method on synthesized images, simulated brain MR images, and real MR images. The MsbFCM method achieved an overlap ratio of greater than 91% as validated by the ground truth even if original images have 9% noise and 40% intensity inhomogeneity. Experimental results using real MR images demonstrate the effectiveness of the proposed method. Our MsbFCM classification method is accurate and robust for various MR images.

Yang, Xiaofeng; Fei, Baowei

2013-01-01

166

Support vector machines for improving the classification of brain PET images  

NASA Astrophysics Data System (ADS)

The classification of brain PET volumes is carried out in three main steps: (1) registration, (2) feature extraction and (3) classification. The PET images were already smoothed with a 16 mm isotropic Gaussian kernel and registered within the Talairach and Tournoux reference system. To make the registration more accurate over a single reference, a method based on optical flow was applied. Feature extraction is carried out by principal component analysis (PCA). Support vector machines (SVM) are then used for classification, because they are better controlled than neural networks (NN) and well adapted to small sample size problems. SVM are constructed by a training algorithm that maximizes the margin between the training vectors and the decision boundary. The algorithm is simple quadratic programming under linear constraints, which leads to global optimum. The decision boundary is expressed as a linear combination of supporting vectors which are a subset of the training vectors closest to the decision boundary. After registration, NN and SVM were trained with the features extracted by PCA from the training set. The estimate error rate is 7.1% for SVM and 14.3% for NN.

Bonneville, Martin; Meunier, Jean; Bengio, Yoshua; Soucy, Jean-Paul

1998-06-01

167

A Role for the Malignant Brain Tumour (MBT) Domain Protein LIN-61 in DNA Double-Strand Break Repair by Homologous Recombination  

PubMed Central

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.

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

2013-01-01

168

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

NASA Astrophysics Data System (ADS)

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.

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

2009-02-01

169

Classification of motor imagery tasks for brain-computer interface applications by means of two equivalent dipoles analysis  

Microsoft Academic Search

We have developed a novel approach using source analysis for classifying motor imagery tasks. Two-equivalent-dipoles analysis was proposed to aid classification of motor imagery tasks for brain-computer interface (BCI) applications. By solving the electroencephalography (EEG) inverse problem of single trial data, it is found that the source analysis approach can aid classification of motor imagination of left- or right-hand movement

Baharan Kamousi; Zhongming Liu; Bin He

2005-01-01

170

Quantification of low-velocity motion using a navigator-echo supported MR velocity-mapping technique: application to intracranial dynamics in volunteers and patients with brain tumours.  

PubMed

Gradient-echo pulse sequences with velocity-encoding gradients of 22.5-25 mT/m, were used for brain-motion and CSF-flow studies. To reduce motion artifacts, a phase-correction technique based on navigator echoes was evaluated. Three patients with right-sided parietal tumours were investigated; one astrocytoma grade III-IV, one astrocytoma grade I-II and one benign meningioma. In healthy volunteers, a maximal brain-tissue velocity of (0.94 +/- 0.26) mm/s (mean +/- 1SD) was observed, which is consistent with previously presented results. The phase correction was proven useful for reduction of artifacts due to external head movements in modulus and phase images, without loss of phase information related to internal motion. The tissue velocity within the astrocytomas was low during the entire cardiac cycle. An abnormally high rostral velocity component was, however, observed in the brain tissue frontal to the astrocytomas. In all patients, an abnormal CSF flow pattern was observed. The study of brain motion may provide further understanding of the effects of tumours and other pathological conditions in the brain. When considering intracranial motion as a source of error in diffusion/perfusion MRI, the present study suggests that a pathology can alter the properties of brain motion and CSF flow considerably, leading to a more complex impact on diffusion/perfusion images. PMID:9084019

Wirestam, R; Salford, L G; Thomsen, C; Brockstedt, S; Persson, B R; Ståhlberg, F

1997-01-01

171

ADHD classification by a texture analysis of anatomical brain MRI data.  

PubMed

The ADHD-200 Global Competition provides an excellent opportunity for building diagnostic classifiers of Attention-Deficit/Hyperactivity Disorder (ADHD) based on resting-state functional MRI (rs-fMRI) and structural MRI data. Here, we introduce a simple method to classify ADHD based on morphological information without using functional data. Our test results show that the accuracy of this approach is competitive with methods based on rs-fMRI data. We used isotropic local binary patterns on three orthogonal planes (LBP-TOP) to extract features from MR brain images. Subsequently, support vector machines (SVM) were used to develop classification models based on the extracted features. In this study, a total of 436 male subjects (210 with ADHD and 226 controls) were analyzed to show the discriminative power of the method. To analyze the properties of this approach, we tested disparate LBP-TOP features from various parcellations and different image resolutions. Additionally, morphological information using a single brain tissue type (i.e., gray matter (GM), white matter (WM), and CSF) was tested. The highest accuracy we achieved was 0.6995. The LBP-TOP was found to provide better discriminative power using whole-brain data as the input. Datasets with higher resolution can train models with increased accuracy. The information from GM plays a more important role than that of other tissue types. These results and the properties of LBP-TOP suggest that most of the disparate feature distribution comes from different patterns of cortical folding. Using LBP-TOP, we provide an ADHD classification model based only on anatomical information, which is easier to obtain in the clinical environment and which is simpler to preprocess compared with rs-fMRI data. PMID:23024630

Chang, Che-Wei; Ho, Chien-Chang; Chen, Jyh-Horng

2012-01-01

172

A dual neural network ensemble approach for multiclass brain tumor classification.  

PubMed

The present study is conducted to develop an interactive computer aided diagnosis (CAD) system for assisting radiologists in multiclass classification of brain tumors. In this paper, primary brain tumors such as astrocytoma, glioblastoma multiforme, childhood tumor-medulloblastoma, meningioma and secondary tumor-metastases along with normal regions are classified by a dual level neural network ensemble. Two hundred eighteen texture and intensity features are extracted from 856 segmented regions of interest (SROIs) and are taken as input. PCA is used for reduction of dimensionality of the feature space. The study is performed on a diversified dataset of 428 post contrast T1-weighted magnetic resonance images of 55 patients. Two sets of experiments are performed. In the first experiment, random selection is used which may allow SROIs from the same patient having similar characteristics to appear in both training and testing simultaneously. In the second experiment, not even a single SROI from the same patient is common during training and testing. In the first experiment, it is observed that the dual level neural network ensemble has enhanced the overall accuracy to 95.85% compared with 91.97% of single level artificial neural network. The proposed method delivers high accuracy for each class. The accuracy obtained for each class is: astrocytoma 96.29%, glioblastoma multiforme 96.15%, childhood tumor-medulloblastoma 90%, meningioma 93.00%, secondary tumor-metastases 96.67% and normal regions 97.41%. This study reveals that dual level neural network ensemble provides better results than the single level artificial neural network. In the second experiment, overall classification accuracy of 90.4% was achieved. The generalization ability of this approach can be tested by analyzing larger datasets. The extensive training will also further improve the performance of the proposed dual network ensemble. Quantitative results obtained from the proposed method will assist the radiologist in forming a better decision for classifying brain tumors. PMID:23109381

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-11-01

173

Multivariate pattern classification reveals differential brain activation during emotional processing in individuals with psychosis proneness.  

PubMed

Among the general population, individuals with subthreshold psychotic-like experiences, or psychosis proneness (PP), can be psychometrically identified and are thought to have a 10-fold increased risk of psychosis. They also show impairments in measures of emotional functioning parallel to schizophrenia. Whilst previous studies have revealed altered brain activation in patients with schizophrenia during emotional processing, it is unclear whether these alterations are also expressed in individuals with high PP. Here we used Support Vector Machine (SVM) to perform multivariate pattern classification based on brain activation during emotional processing in 20 individuals with high PP and 20 comparison subjects (low PP). In addition, we performed a standard univariate analysis based on the General Linear Model (GLM) on the same data for comparison. The experimental task involved passively viewing negative and neutral pictures from the International Affective Picture System (IAPS). SVM allowed classification of the two groups with statistically significant accuracy (p=0.017) and identified group differences within an emotional circuitry including the amygdala, insula, anterior cingulate and medial prefrontal cortex. In contrast, the standard univariate analysis did not detect any significant between-group differences. Our results reveal a distributed and subtle set of alterations in brain function within the emotional circuitry of individuals with high PP, providing neurobiological support for the notion of dysfunctional emotional circuitry in this group. In addition, these alterations are best detected using a multivariate approach rather than standard univariate methods. Further application of this approach may aid in characterising people at clinical and genetic risk of developing psychosis. PMID:22036677

Modinos, Gemma; Pettersson-Yeo, William; Allen, Paul; McGuire, Philip K; Aleman, André; Mechelli, Andrea

2012-02-01

174

Epidemiology, severity classification, and outcome of moderate and severe traumatic brain injury: a prospective multicenter study.  

PubMed

Changes in the demographics, approach, and treatment of traumatic brain injury (TBI) patients require regular evaluation of epidemiological profiles, injury severity classification, and outcomes. This prospective multicenter study provides detailed information on TBI-related variables of 508 moderate-to-severe TBI patients. Variability in epidemiology and outcome is examined by comparing our cohort with previous multicenter studies. Additionally, the relation between outcome and injury severity classification assessed at different time points is studied. Based on the emergency department Glasgow Coma Scale (GCS), 339 patients were classified as having severe and 129 as having moderate TBI. In 15%, the diagnosis differed when the accident scene GCS was used for classification. In-hospital mortality was higher if severe TBI was diagnosed at both time points (44%) compared to moderate TBI at one or both time points (7-15%, p<0.001). Furthermore, 14% changed diagnosis when a threshold (?6?h) for impaired consciousness was used as a criterion for severe TBI: In-hospital mortality was<5% when impaired consciousness lasted for<6?h. This suggests that combining multiple clinical assessments and using a threshold for impaired consciousness may improve the classification of injury severity and prediction of outcome. Compared to earlier multicenter studies, our cohort demonstrates a different case mix that includes a higher age (mean=47.3 years), more diffuse (Traumatic Coma Databank [TCDB] I-II) injuries (58%), and more major extracranial injuries (40%), with relatively high 6 month mortality rates for both severe (46%) and moderate (21%) TBI. Our results confirm that TBI epidemiology and injury patterns have changed in recent years whereas case fatality rates remain high. PMID:21787177

Andriessen, Teuntje M J C; Horn, Janneke; Franschman, Gaby; van der Naalt, Joukje; Haitsma, Iain; Jacobs, Bram; Steyerberg, Ewout W; Vos, Pieter E

2011-10-01

175

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

PubMed Central

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 5 distinct isometric hand postures, as well as 4 distinct finger movements. Several control experiments were attempted in order to remove sensory information from the classification results. Online experiments were performed with 2 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, and characterization of non-stationarities such that ECoG could be a viable signal source for grasp control for amputees or individuals with paralysis.

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

2013-01-01

176

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

PubMed

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. PMID:24893256

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

2014-06-01

177

Multicentric extra-abdominal desmoid tumours  

Microsoft Academic Search

Despite their classification as benign, desmoid tumours are difficult to diagnose and manage. They are prone to recurrence and resection can be debilitating. Rarely, synchronous or metachronous multicentric desmoid tumours occur and may require further excision. Therefore, early detection of recurrence and multicentric tumours is vital. We present a case of metachronous desmoid tumours, and review the literature to propose

M. J. D Wagstaff; A Raurell; A. G. B Perks

2004-01-01

178

Assessing occupational and domestic ELF magnetic field exposure in the uk adult brain tumour study: results of a feasibility study.  

PubMed

The feasibility of measuring exposure to extremely low frequency magnetic fields (ELF MF) in the UK Adult Brain Tumour Study (UKABTS) was examined. During the study, 81 individuals and 30 companies were approached with 79 individuals and 25 companies agreeing to participate. Exposure data were collected using EMDEX II dosemeters worn by the participants for 3-4 consecutive days. Data were collected over a total of 321 d, including non-occupational periods. The results showed occupational exposure to be the main determinant of overall exposure. Moderate to strong correlations were found between arithmetic mean exposure and all other metrics with the possible exception of maximum exposure. Significant differences in exposure were found between job categories with large variability in certain categories. Highest average exposures were found for security officers (arithmetic mean, AM: 0.78 micro T), secretaries (AM: 0.48 micro T) and dentists (AM: 0.42 micro T). Welding and working near high-voltage power lines were associated with elevated exposure. In summary, acceptably precise measures of ELF MF exposure are feasible at relatively moderate cost. The results were used to develop a protocol for data collection from subjects in the UKABTS. PMID:15031444

van Tongeren, Martie; Mee, Terry; Whatmough, Pamela; Broad, Lisa; Maslanyj, Myron; Allen, Stuart; Muir, Ken; McKinney, Patricia

2004-01-01

179

A hybrid method of application of independent component analysis to in vivo 1H MR spectra of childhood brain tumours.  

PubMed

Independent component analysis (ICA) can automatically extract individual metabolite, macromolecular and lipid (MMLip) components from a series of in vivo MR spectra. The traditional feature extraction (FE)-based ICA approach is limited, in that a large sample size is required and a combination of metabolite and MMLip components can appear in the same independent component. The alternative ICA approach, based on blind source separation (BSS), is weak when dealing with overlapping peaks. Combining the advantages of both BSS and FE methods may lead to better results. Thus, we propose an ICA approach involving a hybrid of the BSS and FE techniques for the automated decomposition of a series of MR spectra. Experiments were performed on synthesised and patient in vivo childhood brain tumour MR spectra datasets. The hybrid ICA method showed an improvement in the decomposition ability compared with BSS-ICA or FE-ICA, with an increased correlation between the independent components and simulated metabolite and MMLip signals. Furthermore, we were able to automatically extract metabolites from the patient MR spectra dataset that were not in commonly used basis sets (e.g. guanidinoacetate). PMID:21960131

Hao, Jie; Zou, Xin; Wilson, Martin; Davies, Nigel P; Sun, Yu; Peet, Andrew C; Arvanitis, Theodoros N

2012-04-01

180

Adaptable fuzzy C-Means for improved classification as a preprocessing procedure of brain parcellation.  

PubMed

Parcellation, one of several brain analysis methods, is a procedure popular for subdividing the regions identified by segmentation into smaller topographically defined units. The fuzzy clustering algorithm is mainly used to preprocess parcellation into several segmentation methods, because it is very appropriate for the characteristics of magnetic resonance imaging (MRI), such as partial volume effect and intensity inhomogeneity. However, some gray matter, such as basal ganglia and thalamus, may be misclassified into the white matter class using the conventional fuzzy C-Means (FCM) algorithm. Parcellation has been nearly achieved through manual drawing, but it is a tedious and time-consuming process. We propose improved classification using successive fuzzy clustering and implementing the parcellation module with the modified graphic user interface (GUI) for the convenience of users. PMID:11442112

Yoon, U C; Kim, J S; Kim, J S; Kim, I Y; Kim, S I

2001-06-01

181

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

ERIC Educational Resources Information Center

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)…

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

2009-01-01

182

A framework to support automated classification and labeling of brain electromagnetic patterns.  

PubMed

This paper describes a framework for automated classification and labeling of patterns in electroencephalographic (EEG) and magnetoencephalographic (MEG) data. We describe recent progress on four goals: 1) specification of rules and concepts that capture expert knowledge of event-related potentials (ERP) patterns in visual word recognition; 2) implementation of rules in an automated data processing and labeling stream; 3) data mining techniques that lead to refinement of rules; and 4) iterative steps towards system evaluation and optimization. This process combines top-down, or knowledge-driven, methods with bottom-up, or data-driven, methods. As illustrated here, these methods are complementary and can lead to development of tools for pattern classification and labeling that are robust and conceptually transparent to researchers. The present application focuses on patterns in averaged EEG (ERP) data. We also describe efforts to extend our methods to represent patterns in MEG data, as well as EM patterns in source (anatomical) space. The broader aim of this work is to design an ontology-based system to support cross-laboratory, cross-paradigm, and cross-modal integration of brain functional data. Tools developed for this project are implemented in MATLAB and are freely available on request. PMID:18301711

Frishkoff, Gwen A; Frank, Robert M; Rong, Jiawei; Dou, Dejing; Dien, Joseph; Halderman, Laura K

2007-01-01

183

Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies.  

PubMed

Quantitative multinuclear high-resolution magic angle spinning was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D (1)H and (31)P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. (1)H-(1)H homonuclear and (1)H-(31)P heteronuclear correlation experiments enabled the direct assessment of the (1)H-(31)P spin systems for signals that suffered from overlapping in the 1D (1)H spectra, and linked the information present in the 1D (1)H and (31)P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the (31)P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from (31)P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH(3))(3) signals of phosphocholine and choline in (1)H spectra of the tissue in these tumour samples. PMID:22552786

Esteve, Vicent; Celda, Bernardo; Martínez-Bisbal, M Carmen

2012-07-01

184

Classification  

NASA Astrophysics Data System (ADS)

A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. 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. 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. 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. The generalization performance of a learned model (how closely the target outputs and the model’s predicted outputs agree for patterns that have not been presented to the learning algorithm) would provide an indication of how well the model has learned the desired mapping. More formally, a classification learning algorithm L takes a training set T as its input. The training set consists of |T| examples or instances. It is assumed that there is a probability distribution D from which all training examples are drawn independently—that is, all the training examples are independently and identically distributed (i.i.d.). The ith training example is of the form (x_i, y_i), where x_i is a vector of values of several features and y_i represents the class to be predicted.* In the sunspot classification example given above, each training example would represent one sunspot’s classification (y_i) and the corresponding set of measurements (x_i). The output of a supervised learning algorithm is a model h that approximates the unknown mapping from the inputs to the outputs. In our example, h would map from the sunspot measurements to the type of sunspot. We may have a test set S—a set of examples not used in training that we use to test how well the model h predicts the outputs on new examples. Just as with the examples in T, the examples in S are assumed to be independent and identically distributed (i.i.d.) draws from the distribution D. We measure the error of h on the test set as the proportion of test cases that h misclassifies: 1/|S| Sigma(x,y union S)[I(h(x)!= y)] where I(v) is the indicator function—it returns 1 if v is true and 0 otherwise. In our sunspot classification example, we would identify additional examples of sunspots that were not used in generating the model, and use these to determine how accurate the model is—the fraction of the test samples that the model classifies correctly. An example of a classification model is the decision tree shown in Figure 23.1. We will discuss the decision tree learning algorithm in more detail later—for now, we assume that, given a training set with examples of sunspots, this decision tree is derived. This can be used to classify previously unseen examples of sunpots. For example, if a new sunspot’s inputs indicate that its "Group Length" is in the range 10-15, then the decision tree would classify the sunspot as being of type “E,” whereas if the "Group Length" is "NULL," the "Magnetic Type" is "bipolar," and the "Penumbra" is "rudimentary," then it would be classified as type "C." In this chapter, we will add to the above description of classification problems. We will discuss decision trees and several other classification models. In particular, we will discuss the learning algorithms that generate these classification models, how to use them to classify new

Oza, Nikunj

2012-03-01

185

A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals.  

PubMed

There is a recent increase in the use of multivariate analysis and pattern classification in prediction and real-time feedback of brain states from functional imaging signals and mapping of spatio-temporal patterns of brain activity. Here we present MANAS, a generalized software toolbox for performing online and offline classification of fMRI signals. MANAS has been developed using MATLAB, LIBSVM, and SVMlight packages to achieve a cross-platform environment. MANAS is targeted for neuroscience investigations and brain rehabilitation applications, based on neurofeedback and brain-computer interface (BCI) paradigms. MANAS provides two different approaches for real-time classification: subject dependent and subject independent classification. In this article, we present the methodology of real-time subject dependent and subject independent pattern classification of fMRI signals; the MANAS software architecture and subsystems; and finally demonstrate the use of the system with experimental results. PMID:24151454

Rana, Mohit; Gupta, Nalin; Dalboni Da Rocha, Josue L; Lee, Sangkyun; Sitaram, Ranganatha

2013-01-01

186

Classification  

NASA Technical Reports Server (NTRS)

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.

Oza, Nikunj C.

2011-01-01

187

CT-based quantitative SPECT for the radionuclide 201Tl: experimental validation and a standardized uptake value for brain tumour patients  

PubMed Central

Abstract We have previously reported on a method for reconstructing quantitative data from 99mTc single photon emission computed tomography (SPECT) images based on corrections derived from X-ray computed tomography, producing accurate results in both experimental and clinical studies. This has been extended for use with the radionuclide 201Tl. Accuracy was evaluated with experimental phantom studies, including corrections for partial volume effects where necessary. The quantitative technique was used to derive standardized uptake values (SUVs) for 201Tl evaluation of brain tumours. A preliminary study was performed on 26 patients using 201Tl SPECT scans to assess residual tumour after surgery and then to monitor response to treatment, with a follow-up time of 18 months. Measures of SUVmax were made following quantitative processing of the data and using a threshold grown volume of interest around the tumour. Phantom studies resulted in the calculation of concentration values consistently within 4% of true values. No continuous relation was found between SUVmax (post-resection) and patient survival. Choosing an SUVmax cut-off of 1.5 demonstrated a difference in survival between the 2 groups of patients after surgery. Patients with an SUVmax <1.5 had a 70% survival rate over the first 10 months, compared with a 47% survival rate for those with SUVmax >1.5. This difference did not achieve significance, most likely due to the small study numbers. By 18 months follow-up this difference had reduced, with corresponding survival rates of 40% and 27%, respectively. Although this study involves only a small cohort, it has succeeded in demonstrating the possibility of an SUV measure for SPECT to help monitor response to treatment of brain tumours and predict survival.

Bailey, Dale; Schembri, Geoff; Baldock, Clive

2012-01-01

188

Neural network classification of autoregressive features from electroencephalogram signals for brain computer interface design  

NASA Astrophysics Data System (ADS)

In this paper, we have designed a two-state brain-computer interface (BCI) using neural network (NN) classification of autoregressive (AR) features from electroencephalogram (EEG) signals extracted during mental tasks. The main purpose of the study is to use Keirn and Aunon's data to investigate the performance of different mental task combinations and different AR features for BCI design for individual subjects. In the experimental study, EEG signals from five mental tasks were recorded from four subjects. Different combinations of two mental tasks were studied for each subject. Six different feature extraction methods were used to extract the features from the EEG signals: AR coefficients computed with Burg's algorithm, AR coefficients computed with a least-squares (LS) algorithm and adaptive autoregressive (AAR) coefficients computed with a least-mean-square (LMS) algorithm. All the methods used order six applied to 125 data points and these three methods were repeated with the same data but with segmentation into five segments in increments of 25 data points. The multilayer perceptron NN trained by the back-propagation algorithm (MLP-BP) and linear discriminant analysis (LDA) were used to classify the computed features into different categories that represent the mental tasks. We compared the classification performances among the six different feature extraction methods. The results showed that sixth-order AR coefficients with the LS algorithm without segmentation gave the best performance (93.10%) using MLP-BP and (97.00%) using LDA. The results also showed that the segmentation and AAR methods are not suitable for this set of EEG signals. We conclude that, for different subjects, the best mental task combinations are different and proper selection of mental tasks and feature extraction methods are essential for the BCI design.

Huan, Nai-Jen; Palaniappan, Ramaswamy

2004-09-01

189

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

NASA Astrophysics Data System (ADS)

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 712min of measurement time and is proposed for extended clinical use.

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

2014-01-01

190

A comparative study of feature extraction and blind source separation of independent component analysis (ICA) on childhood brain tumour 1H magnetic resonance spectra.  

PubMed

Independent component analysis (ICA) has the potential of determining automatically the metabolite signals which make up MR spectra. However, the reliability with which this is accomplished and the optimal approach for investigating in vivo MRS have not been determined. Furthermore, the properties of ICA in brain tumour MRS with respect to dataset size and data quality have not been systematically explored. The two common techniques for applying ICA, blind source separation (BSS) and feature extraction (FE) were examined in this study using simulated data and the findings confirmed on patient data. Short echo time (TE 30 ms), low and high field (1.5 and 3 T) in vivo brain tumour MR spectra of childhood astrocytoma, ependymoma and medulloblastoma were generated by using a quantum mechanical simulator with ten metabolite and lipid components. Patient data (TE 30 ms, 1.5 T) were acquired from children with brain tumours. ICA of simulated data shows that individual metabolite components can be extracted from a set of MRS data. The BSS method generates independent components with a closer correlation to the original metabolite and lipid components than the FE method when the number of spectra in the dataset is small. The experiments also show that stable results are achieved with 300 MRS at an SNR equal to 10. The FE method is relatively insensitive to different ranges of full width at half maximum (FWHM) (from 0 to 3 Hz), whereas the BSS method degrades on increasing the range of FWHM. The peak frequency variations do not affect the results within the range of +/-0.08 ppm for the FE method, and +/-0.05 ppm for the BSS method. When the methods were applied to the patient dataset, results consistent with the synthesized experiments were obtained. PMID:19431141

Hao, Jie; Zou, Xin; Wilson, Martin P; Davies, Nigel P; Sun, Yu; Peet, Andrew C; Arvanitis, Theodoros N

2009-10-01

191

The Wechsler Adult Intelligence Scale—III and Malingering in Traumatic Brain InjuryClassification Accuracy in Known Groups  

Microsoft Academic Search

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) moderate\\/severe (M\\/S) TBI not-MND (n = 26). A

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

2009-01-01

192

Defining traumatic brain injury in children and youth using International Classification of Diseases version 10 codes: a systematic review protocol  

PubMed Central

Background Although healthcare administrative data are commonly used for traumatic brain injury research, there is currently no consensus or consistency on using the International Classification of Diseases version 10 codes to define traumatic brain injury among children and youth. This protocol is for a systematic review of the literature to explore the range of International Classification of Diseases version 10 codes that are used to define traumatic brain injury in this population. Methods/design The databases MEDLINE, MEDLINE In-Process, Embase, PsychINFO, CINAHL, SPORTDiscus, and Cochrane Database of Systematic Reviews will be systematically searched. Grey literature will be searched using Grey Matters and Google. Reference lists of included articles will also be searched. Articles will be screened using predefined inclusion and exclusion criteria and all full-text articles that meet the predefined inclusion criteria will be included for analysis. The study selection process and reasons for exclusion at the full-text level will be presented using a PRISMA study flow diagram. Information on the data source of included studies, year and location of study, age of study population, range of incidence, and study purpose will be abstracted into a separate table and synthesized for analysis. All International Classification of Diseases version 10 codes will be listed in tables and the codes that are used to define concussion, acquired traumatic brain injury, head injury, or head trauma will be identified. Discussion The identification of the optimal International Classification of Diseases version 10 codes to define this population in administrative data is crucial, as it has implications for policy, resource allocation, planning of healthcare services, and prevention strategies. It also allows for comparisons across countries and studies. This protocol is for a review that identifies the range and most common diagnoses used to conduct surveillance for traumatic brain injury in children and youth. This is an important first step in reaching an appropriate definition using International Classification of Diseases version 10 codes and can inform future work on reaching consensus on the codes to define traumatic brain injury for this vulnerable population.

2013-01-01

193

Imaging of sinonasal tumours  

PubMed Central

Abstract More than 70 benign and malignant sinonasal tumours and tumour-like conditions have been described. However, sinonasal tumours are rare, and sinonasal cancers comprise only 3% of all head and neck cancers and 1% of all malignancies, with a peak incidence in the 5th to 7th decades and with a male preponderance. The early symptoms and imaging findings of sinonasal tumours are similar to rhinosinusitis with runny and stuffy nose, lacrimation and epistaxis and therefore neglected both by the patients and doctors. When late symptoms such as anosmia, visual disturbances, cranial neuropathy (Cn II, IV, V, VI) or facial swelling appear, the patient is referred to sinonasal endoscopy or imaging. At the time of correct diagnosis more than half of the tumours have reached an advanced stage with a poor prognostic outcome. Even if imaging is performed in the early stages, a radiologist inexperienced with sinonasal anatomy and tumour features may easily interpret early signs of a malignant tumour as rhinosinusitis or a lesion that does not require follow-up. This article presents the imaging findings in some of the most common benign and malignant sinonasal tumours, and the TNM classification and staging of sinonasal carcinomas.

2012-01-01

194

Molecular classification of brain tumor biopsies using solid-state magic angle spinning proton magnetic resonance spectroscopy and robust classifiers.  

PubMed

Brain tumors are one of the leading causes of death in adults with cancer; however, molecular classification of these tumors with in vivo magnetic resonance spectroscopy (MRS) is limited because of the small number of metabolites detected. In vitro MRS provides highly informative biomarker profiles at higher fields, but also consumes the sample so that it is unavailable for subsequent analysis. In contrast, ex vivo high-resolution magic angle spinning (HRMAS) MRS conserves the sample but requires large samples and can pose technical challenges for producing accurate data, depending on the sample testing temperature. We developed a novel approach that combines a two-dimensional (2D), solid-state, HRMAS proton (1H) NMR method, TOBSY (total through-bond spectroscopy), which maximizes the advantages of HRMAS and a robust classification strategy. We used approximately 2 mg of tissue at -8 degrees C from each of 55 brain biopsies, and reliably detected 16 different biologically relevant molecular species. We compared two classification strategies, the support vector machine (SVM) classifier and a feed-forward neural network using the Levenberg-Marquardt back-propagation algorithm. We used the minimum redundancy/maximum relevance (MRMR) method as a powerful feature-selection scheme along with the SVM classifier. We suggest that molecular characterization of brain tumors based on highly informative 2D MRS should enable us to type and prognose even inoperable patients with high accuracy in vivo. PMID:18949365

Andronesi, Ovidiu C; Blekas, Konstantinos D; Mintzopoulos, Dionyssios; Astrakas, Loukas; Black, Peter M; Tzika, A Aria

2008-11-01

195

Aggregation of sparse linear discriminant analyses for event-related potential classification in brain-computer interface.  

PubMed

Two main issues for event-related potential (ERP) classification in brain-computer interface (BCI) application are curse-of-dimensionality and bias-variance tradeoff, which may deteriorate classification performance, especially with insufficient training samples resulted from limited calibration time. This study introduces an aggregation of sparse linear discriminant analyses (ASLDA) to overcome these problems. In the ASLDA, multiple sparse discriminant vectors are learned from differently l1-regularized least-squares regressions by exploiting the equivalence between LDA and least-squares regression, and are subsequently aggregated to form an ensemble classifier, which could not only implement automatic feature selection for dimensionality reduction to alleviate curse-of-dimensionality, but also decrease the variance to improve generalization capacity for new test samples. Extensive investigation and comparison are carried out among the ASLDA, the ordinary LDA and other competing ERP classification algorithms, based on different three ERP datasets. Experimental results indicate that the ASLDA yields better overall performance for single-trial ERP classification when insufficient training samples are available. This suggests the proposed ASLDA is promising for ERP classification in small sample size scenario to improve the practicability of BCI. PMID:24344691

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

2014-02-01

196

Physiological classification of sleep-wake states: based on tri-vesicular (3V) model of the brain.  

PubMed

A new physiological classification of sleep-wake states, based on a novel Tri-Vesicular (3V) model of the brain is proposed. The 3V model consists of an interconnected network of three primal brain vesicles, namely, right and left Arch-Encephalon (Mesencephalon + Diencephalon + Telencephalon) and one DeuterEncephalon (Metencephalon + Myelencephalon). Nine sleep-wake states are defined on the basis of the central activational index (activation and/or inhibition of the 3 brain vesicles), and the level of global arousal. Four sleep states I-IV, four wake states I-IV, and one transitional sleep-wake state, are characterized. The four sleep states correspond with the four non-REM sleep stages, the transitional sleep-wake state correlates with REM sleep, and four wake states are defined in terms of minimal, low, moderate, and high, global behavioral arousal. Three sets of data in the form of polysomnographic and aerobic exercise studies in five adult subjects, and 30 days' data of self-monitored arousal and oro-nasal breathing patterns, are provided in support of this physiological classification of sleep-wake states and the 3V brain model. PMID:1934520

Deshmukh, V D

1991-10-01

197

The safety and effectiveness of low field intraoperative MRI guidance in frameless stereotactic biopsies of brain tumours-design and interim analysis of a prospective randomized trial.  

PubMed

The aim of the study was to assess the safety and effectiveness of stereotactic brain tumour biopsy (STx biopsy) guided by low-field intraoperative magnetic resonance imaging (iMRI) in comparison with its frameless classic analogue based on a prospective randomized trial. A pilot group of 42 brain tumour patients was prospectively randomized into a low-field iMRI group and a control group that underwent a frameless STx biopsy. The primary endpoints of the analysis were postoperative complication rate and diagnostic yield, and the secondary endpoints were length of hospital stay and duration of operation. The iMRI group (21 patients) and the control group (21 patients) did not differ significantly according to demographic and epidemiological data. No major postoperative complications were noted in either group. In addition, no significant differences in the diagnostic yield (p?=?1.00) and length of hospital stay (p?=?0.16) were observed. The mean total OR time was 111?±?24 min in iMRI and 78?±?29 min in the control group (p?=?0.0001). Usage of iMRI may prolong the time of the procedure but seems to be comparable in safety and effectiveness to the standard frameless STx biopsy. PMID:23821131

Czy?, M; Tabakow, P; Weiser, A; Lechowicz-G?ogowska, B E; Zub, L W; Jarmundowicz, W

2014-01-01

198

Anti-tumour efficacy on glioma models of PHA-848125, a multi-kinase inhibitor able to cross the blood-brain barrier  

PubMed Central

Background and Purpose Malignant gliomas, the most common primary brain tumours, are highly invasive and neurologically destructive neoplasms with a very bad prognosis due to the difficulty in removing the mass completely by surgery and the limited activity of current therapeutic agents. PHA-848125 is a multi-kinase inhibitor with broad anti-tumour activity in pre-clinical studies and good tolerability in phase 1 studies, which could affect two main pathways involved in glioma pathogenesis, the G1-S phase progression control pathway through the inhibition of cyclin-dependent kinases and the signalling pathways mediated by tyrosine kinase growth factor receptors, such as tropomyosin receptors. For this reason, we tested PHA-848125 in glioma models. Experimental Approach PHA-848125 was tested on a panel of glioma cell lines in vitro to evaluate inhibition of proliferation and mechanism of action. In vivo efficacy was evaluated on two glioma models both as single agent and in combination with standard therapy. Key Results When tested on a subset of representative glioma cell lines, PHA-848125 blocked cell proliferation, DNA synthesis and inhibited both cell cycle and signal transduction markers. Relevantly, PHA-848125 was also able to induce cell death through autophagy in all cell lines. Good anti-tumour efficacy was observed by oral route in different glioma models both with s.c. and intracranial implantation. Indeed, we demonstrate that the drug is able to cross the blood–brain barrier. Moreover, the combination of PHA-848125 with temozolomide resulted in a synergistic effect, and a clear therapeutic gain was also observed with a triple treatment adding PHA-848125 to radiotherapy and temozolomide. Conclusions and Implications All the pre-clinical data obtained so far suggest that PHA-848125 may become a useful agent in chemotherapy regimens for glioma patients and support its evaluation in phase 2 trials for this indication.

Albanese, C; Alzani, R; Amboldi, N; Degrassi, A; Festuccia, C; Fiorentini, F; Gravina, GL; Mercurio, C; Pastori, W; Brasca, MG; Pesenti, E; Galvani, A; Ciomei, M

2013-01-01

199

Molecular classification of brain tumor biopsies using solid-state magic angle spinning proton magnetic resonance spectroscopy and robust classifiers  

PubMed Central

Brain tumors are one of the leading causes of death in adults with cancer; however, molecular classification of these tumors with in vivo magnetic resonance spectroscopy (MRS) is limited because of the small number of metabolites detected. In vitro MRS provides highly informative biomarker profiles at higher fields, but also consumes the sample so that it is unavailable for subsequent analysis. In contrast, ex vivo high-resolution magic angle spinning (HRMAS) MRS conserves the sample but requires large samples and can pose technical challenges for producing accurate data, depending on the sample testing temperature. We developed a novel approach that combines a two-dimensional (2D), solid-state, HRMAS proton (1H) NMR method, TOBSY (total through-bond spectroscopy), which maximizes the advantages of HRMAS and a robust classification strategy. We used 2 mg of tissue at -8°C from each of 55 brain biopsies, and reliably detected 16 different molecules. We compared two classification strategies, the support vector machine (SVM) classifier and a feed-forward neural network using the Levenberg-Marquardt back-propagation algorithm. We used the minimum redundancy/maximum relevance (MRMR) method as a powerful feature-selection scheme along with the SVM classifier. We also used the minimum redundancy/maximum relevance (MRMR) method as a powerful feature-selection scheme along with the SVM classifier.

Andronesi, Ovidiu C.; Blekas, Konstantinos D.; Mintzopoulos, Dionyssios; Astrakas, Loukas; Black, Peter M.; Tzika, A. Aria

2008-01-01

200

Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images  

Microsoft Academic Search

Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy

Christoph Krafft; Larysa Shapoval; Stephan B. Sobottka; Kathrin D. Geiger; Gabriele Schackert; Reiner Salzer

2006-01-01

201

A comparison of classification techniques for a gaze-independent P300-based brain-computer interface  

NASA Astrophysics Data System (ADS)

This off-line study aims to assess the performance of five classifiers commonly used in the brain-computer interface (BCI) community, when applied to a gaze-independent P300-based BCI. In particular, we compared the results of four linear classifiers and one nonlinear: Fisher's linear discriminant analysis (LDA), stepwise linear discriminant analysis (SWLDA), Bayesian linear discriminant analysis (BLDA), linear support vector machine (LSVM) and Gaussian supported vector machine (GSVM). Moreover, different values for the decimation of the training dataset were tested. The results were evaluated both in terms of accuracy and written symbol rate with the data of 19 healthy subjects. No significant differences among the considered classifiers were found. The optimal decimation factor spanned a range from 3 to 24 (12 to 94 ms long bins). Nevertheless, performance on individually optimized classification parameters is not significantly different from a classification with general parameters (i.e. using an LDA classifier, about 48 ms long bins).

Aloise, F.; Schettini, F.; Aricò, P.; Salinari, S.; Babiloni, F.; Cincotti, F.

2012-08-01

202

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

NASA Astrophysics Data System (ADS)

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%.

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

2012-02-01

203

Canadian Study of Determinants of Endometabolic Health in ChIlDrEn (CanDECIDE study): a cohort study protocol examining the mechanisms of obesity in survivors of childhood brain tumours  

PubMed Central

Background Childhood obesity has reached epidemic proportions and is impacting children's health globally. In adults, obesity is associated with chronic low-grade inflammation that leads to insulin resistance, which is one of the important mechanisms through which dysregulation of metabolism occurs. There is limited information available about the contribution of inflammation to metabolic health in obese children, and how individual and lifestyle factors impact this risk. One of the paediatric groups at risk of higher rates of obesity includes the survivors of childhood brain tumours. The aim of this study was to evaluate the mechanisms that contribute to inflammation in obese survivors of childhood brain tumours. Methods and analysis This is a prospective cohort study. We will recruit lean and obese survivors of childhood brain tumours, and a control group composed of lean and obese children with no history of tumours. We will measure circulating and urinary cytokine levels and cytokine gene expression in monocytes. In addition, the methylation patterns of cytokine genes and that of toll-like receptor genes will be evaluated. These will be correlated with individual and lifestyle factors including age, sex, ethnicity, puberty, body mass index, fasting lipid levels, insulin sensitivity, diet, exercise, sleep, stress and built environment. The sample size calculation showed that we need 25 participants per arm Ethics and dissemination This study has received ethics approval from the institutional review board. Once completed, we will publish this work in peer-reviewed journals and share the findings in presentations and posters in meetings. Discussion This study will permit the interrogation of inflammation as a contributor to obesity and its complications in obese survivors of childhood brain tumours and compare them with lean survivors and lean and obese controls with no history of tumours, which may help identify therapeutic and preventative interventions to combat the rising tide of obesity.

Samaan, M Constantine; Thabane, Lehana; Burrow, Sarah; Dillenburg, Rejane F; Scheinemann, Katrin

2013-01-01

204

Desmoid tumours  

Microsoft Academic Search

Desmoid tumours exhibit fibroblastic proliferation and arise from fascial or musculoaponeurotic structures. Despite their benign microscopic appearance, and their negligible metastatic potential, the propensity of desmoid tumours for local infiltration is potentially significant in terms of deformity, morbidity and mortality due to pressure effects and obstruction of vital structures and organs. The rarity of desmoid tumours, coupled with the variability

C. J Shields; D. C Winter; W. O Kirwan; H. P Redmond

2001-01-01

205

Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors  

PubMed Central

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of log BB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (log P), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental log BB data had been determined in vivo. In particular, since molecules with log BB > 0.3 cross the blood-brain barrier (BBB) readily while molecules with log BB < ?1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the log BB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings.

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-01-01

206

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

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 ?m 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(86.7%) malignant and 2(13.3%) benign tumors. The histological examination showed that the most common tumor types of mammary glands in bitches were: complex carcinoma, adenocarcinoma, malignant mixed tumour, benign mixed tumour, simple carcinoma– (5/15; 33.3%), (3/15; 20%), (3/15; 20%) and (2/15;13.3%), respectively. Simple carcinoma and cystic hyperplasia were less common - (1/15; 6.7%), and (1/15; 6.7%), respectively. Moreover, the most often tumors occur in inguinal mammary (60%) and abdominal (27%) glands. Conclusions Our results demonstrate that, because of the similarity of the cytohistopathological findings in the human and canine mammary gland tumours, it is possible to use the same cytopathological criteria applied in human pathology for the diagnosis of canine mammary gland tumours. Furthemoer, routine use of this human grading method would help the clinician to make a more accurate prognosis in the interests of post-surgical management in dogs with mammary carcinomas. Furthermore, this research will allow a more discriminating classification of mammary tumors and probably has a bearing on cytohistopathology, epidemiology, pathogenesis and prognosis. The most often tumors occur in inguinal mammary (60%) and abdominal (27%) glands. This interesting regional difference may be due to a) the duration of the growth before the diagnosis; b) the age of the dogs; and c) high prevelance of unspayed animals. Moreover, the most common type of tumor was complex carcinoma – 33.3% (5 cases).

2013-01-01

207

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

PubMed

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. PMID:22451316

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

2012-01-01

208

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

PubMed

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. PMID:24109856

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

2013-01-01

209

kNN-based multi-spectral MRI brain tissue classification: manual training versus automated atlas-based training  

NASA Astrophysics Data System (ADS)

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue, requires laborious training on manually labeled subjects. In this work, the performance of kNN-based segmentation of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) using manual training is compared with a new method, in which training is automated using an atlas. From 12 subjects, standard T2 and PD scans and a high-resolution, high-contrast scan (Siemens T1-weighted HASTE sequence with reverse contrast) were used as feature sets. For the conventional kNN method, manual segmentations were used for training, and classifications were evaluated in a leave-one-out study. The performance as a function of the number of samples per tissue, and k was studied. For fully automated training, scans were registered to a probabilistic brain atlas. Initial training samples were randomly selected per tissue based on a threshold on the tissue probability. These initials were processed to keep the most reliable samples. Performance of the method for varying the threshold on the tissue probability method was studied. By measuring the percentage overlap (SI), classification results of both methods were validated. For conventional kNN classification, varying the number of training samples did not result in significant differences, while increasing k gave significantly better results. In the method using automated training, there is an overestimation of GM at the expense of CSF at higher thresholds on the tissue probability maps. The difference between the conventional method (k=45) and the observers was not significantly larger than inter-observer variability for all tissue types. The automated method performed slightly worse and performed equal to the observers for WM, and less for CSF and GM. From these results it can be concluded that conventional kNN classification may replace manual segmentation, and that atlas-based kNN segmentation has strong potential for fully automated segmentation, without the need of laborious manual training.

Vrooman, Henri A.; Cocosco, Chris A.; Stokking, Rik; Ikram, M. Arfan; Vernooij, Meike W.; Breteler, Monique M.; Niessen, Wiro J.

2006-03-01

210

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

Federal Register 2010, 2011, 2012, 2013

...identified as a noninvasive device that employs near-infrared spectroscopy that is intended to be used to evaluate suspected brain hematomas...Detector is a noninvasive device that employs near-infrared spectroscopy that is intended to be used to evaluate suspected brain...

2012-03-23

211

Utility of post-traumatic amnesia in predicting 1-year productivity following traumatic brain injury: comparison of the Russell and Mississippi PTA classification intervals  

Microsoft Academic Search

BackgroundDuration of post-traumatic amnesia (PTA) correlates with global outcomes and functional disability. Russell proposed the use of PTA duration intervals as an index for classification of traumatic brain injury (TBI) severity. Alternative duration-based schemata have been recently proposed as better predictors of outcome to the commonly cited Russell intervals.ObjectiveValidate a TBI severity classification model (Mississippi intervals) of PTA duration anchored

R Nakase-Richardson; M Sherer; R T Seel; T Hart; R Hanks; J C Arango-Lasprilla; S A Yablon; A M Sander; S D Barnett; W C Walker; F Hammond

2011-01-01

212

Brain classification reveals the right cerebellum as the best biomarker of dyslexia  

PubMed Central

Background Developmental dyslexia is a specific cognitive disorder in reading acquisition that has genetic and neurological origins. Despite histological evidence for brain differences in dyslexia, we recently demonstrated that in large cohort of subjects, no differences between control and dyslexic readers can be found at the macroscopic level (MRI voxel), because of large variances in brain local volumes. In the present study, we aimed at finding brain areas that most discriminate dyslexic from control normal readers despite the large variance across subjects. After segmenting brain grey matter, normalizing brain size and shape and modulating the voxels' content, normal readers' brains were used to build a 'typical' brain via bootstrapped confidence intervals. Each dyslexic reader's brain was then classified independently at each voxel as being within or outside the normal range. We used this simple strategy to build a brain map showing regional percentages of differences between groups. The significance of this map was then assessed using a randomization technique. Results The right cerebellar declive and the right lentiform nucleus were the two areas that significantly differed the most between groups with 100% of the dyslexic subjects (N = 38) falling outside of the control group (N = 39) 95% confidence interval boundaries. The clinical relevance of this result was assessed by inquiring cognitive brain-based differences among dyslexic brain subgroups in comparison to normal readers' performances. The strongest difference between dyslexic subgroups was observed between subjects with lower cerebellar declive (LCD) grey matter volumes than controls and subjects with higher cerebellar declive (HCD) grey matter volumes than controls. Dyslexic subjects with LCD volumes performed worse than subjects with HCD volumes in phonologically and lexicon related tasks. Furthermore, cerebellar and lentiform grey matter volumes interacted in dyslexic subjects, so that lower and higher lentiform grey matter volumes compared to controls differently modulated the phonological and lexical performances. Best performances (observed in controls) corresponded to an optimal value of grey matter and they dropped for higher or lower volumes. Conclusion These results provide evidence for the existence of various subtypes of dyslexia characterized by different brain phenotypes. In addition, behavioural analyses suggest that these brain phenotypes relate to different deficits of automatization of language-based processes such as grapheme/phoneme correspondence and/or rapid access to lexicon entries.

Pernet, Cyril R; Poline, Jean Baptiste; Demonet, Jean Francois; Rousselet, Guillaume A

2009-01-01

213

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG).  

PubMed

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics. PMID:17156848

Lehmann, Christoph; Koenig, Thomas; Jelic, Vesna; Prichep, Leslie; John, Roy E; Wahlund, Lars-Olof; Dodge, Yadolah; Dierks, Thomas

2007-04-15

214

[Rhabdoid tumours].  

PubMed

Rhabdoid tumors (RT) are rare highly malignant tumors. They are part of the embryonic types of tumors and therefore occur in early childhood (between ages of 0-2 years). The most common locations are brain and kidney, but RTs arising usually from soft tissues have been reported widely at most anatomical sites in the body. These tumors are composed of rhabdoid cells alone or as a mixture with primitive neuroectodermal cells, mesenchymal cells and/or epithelial cells, commonly denoted as atypical teratoid/rhabdoid tumours (AT/RT). Based on extremely rare incidence and usually non-specific histological picture, molecular genetic studies are extremely helpful in confirming diagnosis of RT. Biallelic inactivation mutation of the SMARCB1 gene plays a crucial role in the pathogenesis of most RT. One third of mutations are germline mutations leading to the designation of the so-called rhabdoid predisposition syndrome. Molecular genetic analysis of the SMARCB1 gene might be beneficial in the establishment of correct diagnosis, genetic counselling and for epidemiologic studies. PMID:22920203

Vasov?ák, P; Puchmajerová, A; K?epelová, A

2012-01-01

215

Biophysical models of tumour growth  

NASA Astrophysics Data System (ADS)

Tumour growth is a multifactorial process, which has stimulated in recent decades the development of numerous models trying to figure out the mechanisms controlling solid tumours morphogenesis. While the earliest models were focusing on cell proliferation kinetics, modulated by the availability of supplied nutrients, new modelling approaches emphasize the crucial role of several biophysical processes, including local matrix remodelling, active cell migration and traction, and reshaping of host tissue vasculature. After a brief presentation of this experimental background, this review will outline a number of representative models describing, at different scales, the growth of avascular and vascularized tumours. Special attention will be paid to the formulation of tumour-host tissue interactions that selectively drive changes in tumour size and morphology, and which are notably mediated by the mechanical status and elasticity of the tumour microenvironment. Emergence of invasive behaviour through growth instabilities at the tumour-host interface will be presented considering both reaction-diffusion and mechano-cellular models. In the latter part of the review, patient-oriented implications of tumour growth modelling are outlined in the context of brain tumours. Some conceptual views of the adaptive strategies and selective barriers that govern tumour evolution are presented in conclusion as potential guidelines for the development of future models.

Tracqui, P.

2009-05-01

216

An Extended EM Algorithm for Joint Feature Extraction and Classification in Brain-Computer Interfaces  

Microsoft Academic Search

For many electroencephalogram (EEG)-based brain-computer interfaces (BCIs), a tedious and time-consuming training process is needed to set parameters. In BCI Competition 2005, reducing the training process was explicitly proposed as a task. Furthermore, an effective BCI system needs to be adaptive to dynamic variations of brain signals; that is, its parame- ters need to be adjusted online. In this article,

Yuanqing Li; Cuntai Guan

2006-01-01

217

Placental Tumour  

PubMed Central

Placental tumours include placental chorioangiomas, teratomas, haemangiomas, and haematomas. Placental chorioangiomas are benign vascular tumours and are the most common placental tumours, with a prevalence of 1%. Large placental chorioangiomas are rare and may lead to pregnancy complications and poor perinatal outcomes. These complications include fetal anaemia, hydrops fetalis, fetal growth restriction, polyhydramnios, and preterm delivery. We report a case of a large placental chorioangioma, the antenatal management and the maternal and fetal outcomes.

Al-Riyami, Nihal; Al-Hadabi, Rahma; Al-Dughaishi, Tamima; Al-Riyami, Marwa

2013-01-01

218

Classification of traumatic brain injury severity using informed data reduction in a series of binary classifier algorithms.  

PubMed

Assessment of medical disorders is often aided by objective diagnostic tests which can lead to early intervention and appropriate treatment. In the case of brain dysfunction caused by head injury, there is an urgent need for quantitative evaluation methods to aid in acute triage of those subjects who have sustained traumatic brain injury (TBI). Current clinical tools to detect mild TBI (mTBI/concussion) are limited to subjective reports of symptoms and short neurocognitive batteries, offering little objective evidence for clinical decisions; or computed tomography (CT) scans, with radiation-risk, that are most often negative in mTBI. This paper describes a novel methodology for the development of algorithms to provide multi-class classification in a substantial population of brain injured subjects, across a broad age range and representative subpopulations. The method is based on age-regressed quantitative features (linear and nonlinear) extracted from brain electrical activity recorded from a limited montage of scalp electrodes. These features are used as input to a unique "informed data reduction" method, maximizing confidence of prospective validation and minimizing over-fitting. A training set for supervised learning was used, including: "normal control," "concussed," and "structural injury/CT positive (CT+)." The classifier function separating CT+ from the other groups demonstrated a sensitivity of 96% and specificity of 78%; the classifier separating "normal controls" from the other groups demonstrated a sensitivity of 81% and specificity of 74%, suggesting high utility of such classifiers in acute clinical settings. The use of a sequence of classifiers where the desired risk can be stratified further supports clinical utility. PMID:22855231

Prichep, Leslie S; Jacquin, Arnaud; Filipenko, Julie; Dastidar, Samanwoy Ghosh; Zabele, Stephen; Vodencarevi?, Asmir; Rothman, Neil S

2012-11-01

219

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

PubMed Central

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 hypovolemic shock. This study underlines the role of BD as a relevant clinical indicator of hypovolaemic shock during the initial assessment in respect to haemostatic resuscitation and transfusion requirements.

2014-01-01

220

Case Identification of Work-Related Traumatic Brain Injury Using the Occupational Injury and Illness Classification System (OIICS)  

PubMed Central

Objective Traumatic brain injury (TBI) is one of the most common, costly, and disabling occupational injuries. Objectives included determining whether work-related TBI could be reliably identified using the Occupational Injury and Illness Classification System (OIICS) and describing challenges in developing an OIICS-based TBI case definition. Methods Washington State trauma registry reports and workers’ compensation claims were linked (1998–2008). Trauma registry diagnoses were used as the gold standard for six OIICS-based TBI case definitions. Results OIICS-based case definitions were highly specific but had low sensitivity, capturing less than a third of fatal and nonfatal TBI. Conclusions The use of OIICS versus ICD-9-CM codes underestimated TBI and changed the attributable cause distribution, with potential implications for prevention efforts. Surveillance methods that can more fully and accurately capture the impact of work-related TBI across the U.S are needed.

Graves, Janessa M.; Blanar, Laura; Bowman, Stephen M.

2013-01-01

221

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

NASA Astrophysics Data System (ADS)

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).

Salvaris, Mathew; Sepulveda, Francisco

2010-10-01

222

Real-time support vector classification and feedback of multiple emotional brain states  

Microsoft Academic Search

An important question that confronts current research in affective neuroscience as well as in the treatment of emotional disorders is whether it is possible to determine the emotional state of a person based on the measurement of brain activity alone. Here, we first show that an online support vector machine (SVM) can be built to recognize two discrete emotional states,

Ranganatha Sitaram; Sangkyun Lee; Sergio Ruiz; Mohit Rana; Ralf Veit; Niels Birbaumer

2011-01-01

223

Support vector machine classification and characterization of age-related reorganization of functional brain networks.  

PubMed

Most of what is known about the reorganization of functional brain networks that accompanies normal aging is based on neuroimaging studies in which participants perform specific tasks. In these studies, reorganization is defined by the differences in task activation between young and old adults. However, task activation differences could be the result of differences in task performance, strategy, or motivation, and not necessarily reflect reorganization. Resting-state fMRI provides a method of investigating functional brain networks without such confounds. Here, a support vector machine (SVM) classifier was used in an attempt to differentiate older adults from younger adults based on their resting-state functional connectivity. In addition, the information used by the SVM was investigated to see what functional connections best differentiated younger adult brains from older adult brains. Three separate resting-state scans from 26 younger adults (18-35 yrs) and 26 older adults (55-85) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available in the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 100 seed-regions from four functional networks with 5mm(3) radius were defined based on a recent study using machine learning classifiers on adolescent brains. Time-series for every seed-region were averaged and three matrices of z-transformed correlation coefficients were created for each subject corresponding to each individual's three resting-state scans. SVM was then applied using leave-one-out cross-validation. The SVM classifier was 84% accurate in classifying older and younger adult brains. The majority of the connections used by the classifier to distinguish subjects by age came from seed-regions belonging to the sensorimotor and cingulo-opercular networks. These results suggest that age-related decreases in positive correlations within the cingulo-opercular and default networks, and decreases in negative correlations between the default and sensorimotor networks, are the distinguishing characteristics of age-related reorganization. PMID:22227886

Meier, Timothy B; Desphande, Alok S; Vergun, Svyatoslav; Nair, Veena A; Song, Jie; Biswal, Bharat B; Meyerand, Mary E; Birn, Rasmus M; Prabhakaran, Vivek

2012-03-01

224

Occupational exposure to magnetic fields relative to mortality from brain tumours: updated and revised findings from a study of United Kingdom electricity generation and transmission workers, 1973–97  

Microsoft Academic Search

OBJECTIVETo investigate whether risk of brain tumour is related to occupational exposure to magnetic fields.METHODSThe mortality experienced by a cohort of 83 997 employees of the former Central Electricity Generating Board of England and Wales was investigated for the period 1973–97. All workers were employed for at least 6 months with some employment in the period 1973–82. Computerised work histories

T Sorahan; L Nichols; M van Tongeren; J M Harrington

2001-01-01

225

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

PubMed

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. PMID:23891435

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

2013-11-01

226

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

PubMed

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. PMID:23684862

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

2013-11-01

227

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

Microsoft Academic Search

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 Bereitschaftspotential (an event related potential

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

2005-01-01

228

Brain Tumor Classification Using AFM in Combination with Data Mining Techniques  

PubMed Central

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.

Huml, Marlene; Silye, Rene; Zauner, Gerald

2013-01-01

229

Classification of self-driven mental tasks from whole-brain activity patterns.  

PubMed

During wakefulness, a constant and continuous stream of complex stimuli and self-driven thoughts permeate the human mind. Here, eleven participants were asked to count down numbers and remember negative or positive autobiographical episodes of their personal lives, for 32 seconds at a time, during which they could freely engage in the execution of those tasks. We then examined the possibility of determining from a single whole-brain functional magnetic resonance imaging scan which one of the two mental tasks each participant was performing at a given point in time. Linear support-vector machines were used to build within-participant classifiers and across-participants classifiers. The within-participant classifiers could correctly discriminate scans with an average accuracy as high as 82%, when using data from all individual voxels in the brain. These results demonstrate that it is possible to accurately classify self-driven mental tasks from whole-brain activity patterns recorded in a time interval as short as 2 seconds. PMID:24824899

Nawa, Norberto Eiji; Ando, Hiroshi

2014-01-01

230

Classification of Self-Driven Mental Tasks from Whole-Brain Activity Patterns  

PubMed Central

During wakefulness, a constant and continuous stream of complex stimuli and self-driven thoughts permeate the human mind. Here, eleven participants were asked to count down numbers and remember negative or positive autobiographical episodes of their personal lives, for 32 seconds at a time, during which they could freely engage in the execution of those tasks. We then examined the possibility of determining from a single whole-brain functional magnetic resonance imaging scan which one of the two mental tasks each participant was performing at a given point in time. Linear support-vector machines were used to build within-participant classifiers and across-participants classifiers. The within-participant classifiers could correctly discriminate scans with an average accuracy as high as 82%, when using data from all individual voxels in the brain. These results demonstrate that it is possible to accurately classify self-driven mental tasks from whole-brain activity patterns recorded in a time interval as short as 2 seconds.

Nawa, Norberto Eiji; Ando, Hiroshi

2014-01-01

231

Unsupervised multiparametric classification of dynamic susceptibility contrast imaging: study of the healthy brain.  

PubMed

Characterization and quantification of magnetic resonance perfusion images is important for clinical interpretation, though this calls for a reproducible and accurate method of analysis and a robust healthy reference. The few studies which have examined the perfusion of the healthy brain using dynamic susceptibility contrast (DSC) imaging were largely limited to manual definition of the regions of interest (ROI) and results were dependent on the location of the ROI. The current study aimed to develop a methodology for DSC data analysis and to obtain reference values of healthy subjects. Twenty three healthy volunteers underwent DSC. An unsupervised multiparametric clustering method was applied to four perfusion parameters. Three clusters were defined and identified as: dura-blood-vessels, gray matter and white matter and their vascular characteristics were obtained. Additionally, regional perfusion differences were studied and revealed a prolonged mean transient time and a trend for higher vascularity in the posterior compared with the anterior and middle cerebral vascular territories. While additional studies are required to confirm our findings, this result may have important clinical implications. The proposed unsupervised multiparametric method enabled accurate tissue differentiation, is easy replicable and has a wide range of applications in both pathological and healthy brains. PMID:21419230

Artzi, M; Aizenstein, O; Hendler, T; Ben Bashat, D

2011-06-01

232

The IASLC Lung Cancer Staging Project: Proposals for the Revision of the TNM Stage Groupings in the Forthcoming (Seventh) Edition of the TNM Classification of Malignant Tumours  

Microsoft Academic Search

Introduction: The seventh edition of the TNM Classification of Malignant Tumors is due to be published early in 2009. In prepa- ration for this, the International Association for the Study of Lung Cancer established its Lung Cancer Staging Project in 1998. The recommendations of this committee for changes to the T, N, and M descriptors have been published. This report

Peter Goldstraw; John Crowley; Kari Chansky; Dorothy J. Giroux; Patti A. Groome; Ramon Rami-Porta; Pieter E. Postmus; Valerie Rusch; Leslie Sobin

2007-01-01

233

Ependymoma in children under the age of 3 years: a report from the Canadian Pediatric Brain Tumour Consortium.  

PubMed

The determination of optimal therapy for ependymoma (EP) in infants is ongoing. We describe the incidence, management and outcomes of Canadian infants with EP to discern potential future research questions. Of 579 cases registered in a national database of children <36 months of age diagnosed with a brain tumor from 1990 to 2005, inclusive, 75 (13 %) were EP. These cases were analyzed. A mean annual age-adjusted incidence rate of 4.6 per 100,000 children years was calculated. The male:female ratio was 1.77. Of the tumors, 80 % were infratentorial in location, 67 % were WHO grade II histology, and 29 % were metastatic at diagnosis. All patients underwent a surgical procedure. A complete resection of the tumor was achieved in 56 % of the cases; 43 % of these patients survive while 36 % of the patients with tumors less than completely resected survive. Initial therapy consisted of surgery alone in 23 % of patients, or surgery plus chemotherapy (37 %), radiation therapy (RT; 19 %), or both (21 %). Any use of RT increased with patient age. The 5-year EFS rates for patients in each of the four treatment groups was 22, 11.5, 46.2 and 64.8 %, respectively. For all patients the median survival was 63 ± 6 months and 5-year overall survival was 55 ± 6 %. Patients treated with surgery and chemotherapy alone were younger and had a lower rate of survival than older patients who were more often treated with radiation therapy containing regimens. Further study is needed to determine which patients are optimally served with these treatment modalities. PMID:24532240

Purdy, Eve; Johnston, Donna L; Bartels, Ute; Fryer, Chris; Carret, Anne-Sophie; Crooks, Bruce; Eisenstat, David D; Lafay-Cousin, Lucie; Larouche, Valerie; Wilson, Beverly; Zelcer, Shayna; Silva, Mariana; Bouffet, Eric; Keene, Daniel; Strother, Douglas R

2014-04-01

234

Matched signal detection on graphs: theory and application to brain network classification.  

PubMed

We develop a matched signal detection (MSD) theory for signals with an intrinsic structure described by a weighted graph. Hypothesis tests are formulated under different signal models. In the simplest scenario, we assume that the signal is deterministic with noise in a subspace spanned by a subset of eigenvectors of the graph Laplacian. The conventional matched subspace detection can be easily extended to this case. Furthermore, we study signals with certain level of smoothness. The test turns out to be a weighted energy detector, when the noise variance is negligible. More generally, we presume that the signal follows a prior distribution, which could be learnt from training data. The test statistic is then the difference of signal variations on associated graph structures, if an Ising model is adopted. Effectiveness of the MSD on graph is evaluated both by simulation and real data. We apply it to the network classification problem of Alzheimer's disease (AD) particularly. The preliminary results demonstrate that our approach is able to exploit the sub-manifold structure of the data, and therefore achieve a better performance than the traditional principle component analysis (PCA). PMID:24683953

Hu, Chenhui; Cheng, Lin; Sepulcre, Jorge; El Fakhri, Georges; Lu, Yue M; Lu, Yue M

2013-01-01

235

Extracting Multiscale Pattern Information of fMRI Based Functional Brain Connectivity with Application on Classification of Autism Spectrum Disorders  

PubMed Central

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 and specificity of . 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.

Wang, Hui; Chen, Chen; Fushing, Hsieh

2012-01-01

236

Observed versus estimated IQ as an index of malingering in traumatic brain injury: classification accuracy in known groups.  

PubMed

This study examined the classification accuracy of observed WAIS-III VIQ, PIQ, and FSIQ minus Barona-estimate differential scores in the detection of Malingered Neurocognitive Dysfunction (MND) in Traumatic Brain Injury (TBI) using a known-groups design. Two hundred eleven TBI patients were assigned to one of three groups: Not-MND (n = 87), Indeterminate (n = 68), and MND (n = 56). A General Clinical Sample of 93 no-incentive patients (e.g., CVA, memory disorder) was also included to better study specificity. The VIQ differential accurately differentiated MND from Not-MND TBI patients regardless of injury severity. The PIQ differential was only accurate in mild TBI and did not add incremental validity to the VIQ differential. This study indicates that VIQ declines of greater than 24 points are rare except in very severe TBI. Particularly in mild TBI, such differentials likely indicate intentional suppression of WAIS-III performance consistent with MND. Clinical application is discussed. PMID:18726736

Greve, Kevin W; Lotz, Kenni L; Bianchini, Kevin J

2008-01-01

237

The Wechsler Adult Intelligence Scale-III and malingering in traumatic brain injury: classification accuracy in known groups.  

PubMed

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) moderate/severe (M/S) TBI not-MND (n = 26). A sample of 80 general clinical patients was used for comparison. Verbal IQ, Verbal Comprehension Index, and Working Memory Index detected approximately 25% of malingerers with a false positive (FP) error rate of approximately 5% in the mild TBI group. Comparable FP rates were obtained in M/S TBI. FP rates for Performance IQ, Perceptual Organization Index, and Processing Speed Index were acceptable in mild TBI but too high in M/S TBI. Previously studied specialized indicators (Vocabulary minus Digit Span and the Mittenberg formula) failed to differentiate malingerers from nonmalingerers. The clinical application of these findings is discussed. PMID:19797328

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

2009-12-01

238

Phyllodes tumours  

PubMed Central

Phyllodes tumours are rare fibroepithelial lesions that account for less than 1% of all breast neoplasms. With the non-operative management of fibroadenomas widely adopted, the importance of phyllodes tumours today lies in the need to differentiate them from other benign breast lesions. All breast lumps should be triple assessed and the diagnosis of a phyllodes tumour considered in women, particularly over the age of 35 years, who present with a rapidly growing "benign" breast lump. Treatment can be by either wide excision or mastectomy provided histologically clear specimen margins are ensured. Nodal metastases are rare and routine axillary dissection is not recommended. Few reliable clinical and histological prognostic factors have been identified. Local recurrence occurs in approximately 15% of patients and is more common after incomplete excision. It can usually be controlled by further surgery. Repeated local recurrence has been reported without the development of distant metastases or reduced survival. Approximately 20% of patients with malignant phyllodes tumours develop distant metastases. Long term survival with distant metastases is rare. The role of chemotherapy, radiotherapy, and hormonal manipulation in both the adjuvant and palliative settings remain to be defined.???Keywords: benign breast disease; fibroadenoma; phyllodes tumour

Parker, S; Harries, S

2001-01-01

239

[Brain metastasis of breast tumors and blood brain barrier].  

PubMed

Brain metastases are prevalent in solid tumours and lymphomas. They are associated with poor survival. The brain is regarded as a sanctuary site for metastatic tumour cells where they exist partially protected from drugs by the blood brain barrier. Amongst the different molecular sub-types of breast cancer, HER2 positive tumours and triple negative tumours exhibit the highest incidence of brain metastasis. Specific strategies are needed to fight brain metastatic disease. Preclinical models for brain metastasis have been developed, yielding mechanistic molecular knowledge and new therapeutic approaches. PMID:21527366

Diéras, Véronique; Pierga, Jean-Yves

2011-04-01

240

Oral Tumours  

PubMed Central

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

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

1988-01-01

241

Multi-parametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images  

PubMed Central

Rationale and Objectives: Treatment of brain neoplasms can greatly benefit from better delineation of bulk neoplasm boundary and the extent and degree of more subtle neoplastic infiltration. MRI is the primary imaging modality for evaluation before and after therapy, typically combining conventional sequences with more advanced techniques like perfusion-weighted imaging and diffusion tensor imaging (DTI). The purpose of this study is to quantify the multi-parametric imaging profile of neoplasms by integrating structural MRI and DTI via statistical image analysis methods, in order to potentially capture complex and subtle tissue characteristics that are not obvious from any individual image or parameter. Materials and Methods: Five structural MR sequences, namely, B0, Diffusion Weighted Images, FLAIR, T1-weighted, and gadolinium-enhanced T1-weighted, and two scalar maps computed from DTI, i.e., fractional anisotropy and apparent diffusion coefficient, are used to create an intensity-based tissue profile. This is incorporated into a non-linear pattern classification technique to create a multi-parametric probabilistic tissue characterization, which is applied to data from 14 patients with newly diagnosed primary high grade neoplasms who have not received any therapy prior to imaging. Results: Preliminary results demonstrate that this multi-parametric tissue characterization helps to better differentiate between neoplasm, edema and healthy tissue, and to identify tissue that is likely progress to neoplasm in the future. This has been validated on expert assessed tissue. Conclusion: This approach has potential applications in treatment, aiding computer-assisted surgery by determining the spatial distributions of healthy and neoplastic tissue, as well as in identifying tissue that is relatively more prone to tumor recurrence.

Verma, Ragini; Zacharaki, Evangelia I.; Ou, Yangming; Cai, Hongmin; Chawla, Sanjeev; Lee, Seung-Koo; Melhem, Elias R.; Wolf, Ronald; Davatzikos, Christos

2008-01-01

242

Raman and FTIR microspectroscopy for detection of brain metastasis  

NASA Astrophysics Data System (ADS)

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.

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

2011-06-01

243

Classification of brain-stem trigeminal evoked potentials in multiple sclerosis, minor head injuries and post-concussion syndrome pathologies by similarity measurements.  

PubMed

In this study measurements obtained from brain-stem trigeminal evoked potentials (BTEP) are applied to the problem of diagnosing Multiple Sclerosis (MS) and Post-concussion syndrome (PCS). We present a simplistic model that depicts the BTEP waveform as the linear combination of a set of filters excited by a short stimulus. The relation between the BTEP latencies and the 1st to 4th harmonic components is shown. The performance of a fuzzy similarity measure based classifier is compared with that of human experts. The efficiency of the proposed classifier in conjunction with delay time and amplitude features is examined. Using this novel approach, a classification rate of 93.55% and 84.1% for MS and PCS pathologies, respectively, was achieved. This performance compares favorably to the classification rates of 84.28% for MS and 70.47% for PCS pathologies achieved by human experts. PMID:11137473

Guterman, H; Nehmadi, Y; Chistyakov, A; Soustiel, J; Hafner, H; Feinsod, M

2000-12-01

244

Tumours of the upper alimentary tract  

PubMed Central

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

Head, K. W.

1976-01-01

245

Prediction of central nervous system embryonal tumour outcome based on gene expression  

Microsoft Academic Search

Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients'

Scott L. Pomeroy; Pablo Tamayo; Michelle Gaasenbeek; Lisa M. Sturla; Michael Angelo; Margaret E. McLaughlin; John Y. H. Kim; Liliana C. Goumnerova; Peter M. Black; Ching Lau; Jeffrey C. Allen; David Zagzag; James M. Olson; Tom Curran; Cynthia Wetmore; Jaclyn A. Biegel; Tomaso Poggio; Shayan Mukherjee; Ryan Rifkin; Andrea Califano; Gustavo Stolovitzky; David N. Louis; Jill P. Mesirov; Eric S. Lander; Todd R. Golub

2002-01-01

246

Odontogenic tumours: A review of 266 cases  

PubMed Central

Objectives: The aim of this study was to examine the relative frequency of odontogenic tumours at a tertiary hospital in Ibadan, as well as to study the various histologic types based on WHO 2005 classification and to compare results from this study with those of previous studies. Study design: The records of the Oral Pathology Department of University College Hospital were reviewed. Lesions diagnosed as odontogenic tumours were categorized into four groups based on WHO 2005 classification and were analyzed for age, sex and site using SPSS for Window (version 18.0; SPSS Inc. Chicago, IL) and frequency tables were generated. Results: Two hundred and sixty six (41.7%) cases of odontogenic tumours were seen. The mean age of occurrence was 32.6 (±15.815) years (range3-82 years) and peak age was in the third decade of life. Eleven (4.1%) malignant odontogenic tumours were seen. Ameloblastoma with 65.4% of cases was the most common odontogenic tumour followed by fibromyxoma (14.7%), no case of odontoma was seen in this series. Conclusion: The findings were mostly similar to those of African and Asian series and showed variations from reports from the Americas. The reason for the disparity in African and American series needs further investigations. Key words:Odontogenic tumour, classification, Nigeria.

Adisa, Akinyele O.; Olusanya, Adeola A.

2013-01-01

247

Urogenital tumours in childhood.  

PubMed

The commonest urogenital tumours in childhood are Wilms tumour of the kidney and rhabdomyosarcoma in the pelvis. We review these tumours along with other primary renal tumours and less common ovarian and testicular tumours in childhood. Current clinical concepts, relevant staging investigations and imaging features are described. PMID:22187115

Swinson, S; McHugh, K

2011-01-01

248

Radiotherapy by particle beams (hadrontherapy) of intracranial tumours: a survey on pathology  

Microsoft Academic Search

A review of the principal contributions of radiotherapy 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 on tumours and on the normal nervous tissue,

2005-01-01

249

Tumours of the minor (oropharyngeal) salivary glands: a demographic study of 336 cases.  

PubMed

There are 2410 primary epithelial salivary gland tumours in the files of the British Salivary Gland Tumour Panel. Of these tumours, 336 (14%) involved the minor (oropharyngeal) salivary glands, and these were studied in the present investigation. Individual tumours were diagnosed according to the WHO Classification. The percentage of malignant or potentially malignant tumours (46%) was much higher than in major glands (18%), and in some of the less common intraoral sites all the tumours were malignant. The principal sites were the palate (54%), lips (21%) and buccal mucosa (11%), and, in these sites, pleomorphic adenoma was the most common tumour. Monomorphic adenomas accounted for 6% of palatal tumours, but 30% of lip salivary gland tumours. The most common malignant tumour was the adenoid cystic carcinoma. The results are compared with several other large surveys and with tumours of major salivary glands. PMID:2991488

Eveson, J W; Cawson, R A

1985-07-01

250

[Diagnosis and treatment options of neuroendocrine tumours].  

PubMed

Neuroendocrine neoplasms belong to the group of rare tumours. Their clinical importance may be highlighted by their high prevalence despite low incidence. Since survival rate is similar to other progressive neoplastic diseases in metastatic cases, early recognition and appropriate therapy of these neoplasms are equally important. Classification of neuroendocrine tumours is based on their pathologic characteristics according to the 2010 WHO recommendation. Non-functioning tumours cause local symptoms due to their mass effect, while functioning tumours produce well-defined endocrine syndromes. Among laboratory tests, serum chromogranin-A is considered the most important biomarker of both non-functioning and functioning neuroendocrine tumours. Localization of these tumours includes the use of conventional diagnostic imaging, endoscopic examinations, and functional imaging studies. With respect to treatment, elimination of the primary tumour remains one of the most important issues. In advanced cases of the disease metastasectomy, interventional radiologic methods, medical treatment and endoradiotherapy can be used. The aim of this review is to summarize briefly the symptoms, diagnostic methods and treatment options of neuroendocrine tumours. PMID:24058100

Uhlyarik, Andrea; Pápai, Zsuzsanna

2013-09-29

251

A Semi-supervised SVM Learning Algorithm for Joint Feature Extraction and Classification in Brain Computer Interfaces  

Microsoft Academic Search

In machine learning based Brain Computer Interfaces (BCIs), it is a challenge to use only a small amount of labelled data to build a classifier for a specific subject. This challenge was specifically addressed in BCI Competition 2005. Moreover, an effective BCI system should be adaptive to tackle the dynamic variations in brain signal. One of the solutions is to

Yuanqing Li; Cuntai Guan

2006-01-01

252

Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.  

PubMed

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. PMID:24440135

Siuly; Li, Yan; Paul Wen, Peng

2014-03-01

253

Prediction of passive blood–brain partitioning: Straightforward and effective classification models based on in silico derived physicochemical descriptors  

Microsoft Academic Search

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood–brain partitioning, expressed in terms of logBB values. The models are based on computationally derived physicochemical descriptors, namely the octanol\\/water partition coefficient (logP),

Santiago Vilar; Mayukh Chakrabarti; Stefano Costanzi

2010-01-01

254

The tumour-associated carbonic anhydrases CA II, CA IX and CA XII in a group of medulloblastomas and supratentorial primitive neuroectodermal tumours: an association of CA IX with poor prognosis  

Microsoft Academic Search

BACKGROUND: Medulloblastomas (MBs) and supratentorial primitive neuroectodermal tumours (PNETs) are the most common highly aggressive paediatric brain tumours. In spite of extensive research on these tumours, there are only few known biomarkers or therapeutic target proteins, and the prognosis of patients with these tumours remains poor. Our aim was to investigate whether carbonic anhydrases (CAs), enzymes commonly overexpressed in various

Kristiina Nordfors; Joonas Haapasalo; Miikka Korja; Anssi Niemelä; Jukka Laine; Anna-Kaisa Parkkila; Silvia Pastorekova; Jaromir Pastorek; Abdul Waheed; William S Sly; Seppo Parkkila; Hannu Haapasalo

2010-01-01

255

WAIS Digit Span-Based Indicators of Malingered Neurocognitive DysfunctionClassification Accuracy in Traumatic Brain Injury  

Microsoft Academic Search

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. Performance of 1,063 nonincentive patients (e.g., cerebrovascular accident, memory disorder) was

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

2005-01-01

256

Speeding up classification of multi-channel brain-computer interfaces: common spatial patterns for slow cortical potentials  

Microsoft Academic Search

During the last years interest has been growing to find an effective communication channel which translates human intentions into control signals for a computer, the so called brain-computer interface (BCI). One main goal of research is to help patients with severe neuromuscular disabilities by substituting normal motor outputs. Various cortical processes were identified which are suitable for implementing such a

Guido Dornhege; Benjamin Blankertz; Gabriel Curio

2003-01-01

257

Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain–computer interface  

Microsoft Academic Search

There has been an increase in research interest for brain–computer interface (BCI) technology as an alternate mode of communication and environmental control for the disabled, such as patients suffering from amyotrophic lateral sclerosis (ALS), brainstem stroke and spinal cord injury. Disabled patients with appropriate physical care and cognitive ability to communicate with their social environment continue to live with a

Ranganatha Sitaram; Haihong Zhang; Cuntai Guan; Manoj Thulasidas; Yoko Hoshi; Akihiro Ishikawa; Koji Shimizu; Niels Birbaumer

2007-01-01

258

Human Body Motions Classification  

Microsoft Academic Search

This paper deals with video based parameteriza- tion and classification of human body motions. The main task of this work is to develop and verify the procedures for observing of muscle and brain activity. The developed procedures have no negative impact to brain activity (the tracking does not affect the measured EEG signals). The procedures required only standard hardware equipment

J. Havlik; J. Uhlir; Z. Horcik

259

Congenital primitive neuroectodermal tumour presenting as obstructed labour  

PubMed Central

Brain tumours presenting at delivery are extremely rare. A case of primitive neuroectodermal tumour (PNET) that presented intrapartum with failure to progress due to hydrocephalus is reported. Diagnosis required imaging with magnetic resonance and computed tomography in addition to open biopsy.??

Inwald, D.; Kempley, S.; Hird, M.

1998-01-01

260

Gene expression profiling of gliomas: merging genomic and histopathological classification for personalised therapy  

PubMed Central

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.

Vitucci, M; Hayes, D N; Miller, C R

2011-01-01

261

Tumours of salivary tissue  

PubMed Central

A clinical study of 401 cases of tumour of salivary tissue has been made and the results reported, together with a review of the literature. The histological variations of such tumours are classified and discussed. Images

Cameron, J. Malcolm

1961-01-01

262

Synchronous cerebral and pleural solitary fibrous tumour.  

PubMed

Solitary fibrous tumours of the pleura (SFTPs) are rare mesenchymal neoplasms usually originating from the visceral pleura, but they have been reported in many other sites. To the best of our knowledge, this report describes the first known case of synchronous SFTP in the left visceral pleura and brain. The SFTP of the brain was resected via craniotomy, whereas the SFTP of the pleura, widely compressing and displacing the left lower lung lobe, was resected via left thoracotomy. PMID:24599838

Gómez Hernández, María Teresa; Rodríguez, María; Jiménez, Marcelo; Varela, Gonzalo

2014-06-01

263

Brain metastases as preventive and therapeutic targets  

Microsoft Academic Search

The incidence of metastasis to the brain is apparently rising in cancer patients and threatens to limit the gains that have been made by new systemic treatments. The brain is considered a 'sanctuary site' as the blood–tumour barrier limits the ability of drugs to enter and kill tumour cells. Translational research examining metastasis to the brain needs to be multi-disciplinary,

Kevin A. Camphausen; Quentin R. Smith; Patricia S. Steeg

2011-01-01

264

Disseminated tumour cells  

Microsoft Academic Search

Metastatic spread is a major factor in the prognosis of cancer patients. Early detection and eradication of circulating tumour cells prior to the development of metastases could help to improve the outcome of patients after tumour resection. Disseminated tumour cells have been detected in different compartments of the body using cytological and immunostaining methods and, more recently, using different molecular

Ilka Vogel; Holger Kalthoff

2001-01-01

265

Brain metastases.  

PubMed

Brain metastases are the most frequent neurological complication of cancer and the most common brain tumour type. Lung and breast cancers, and melanoma are responsible for up to three-quarters of metastatic brain lesions. Most patients exhibit either headache, seizures, focal deficits, cognitive or gait disorders, which severely impair the quality of life. Brain metastases are best demonstrated by MRI, which is sensitive but non-specific. The main differential diagnosis includes primary tumours, abscesses, vascular and inflammatory lesions. Overall prognosis is poor and depends on age, extent and activity of the systemic disease, number of brain metastases and performance status. In about half of the patients, especially those with widespread and uncontrolled systemic malignancy, death is heavily related to extra-neural lesions, and treatment of cerebral disease doesn't significantly improve survival. In such patients the aim is to improve or stabilize the neurological deficit and maintain quality of life. Corticosteroids and whole-brain radiotherapy usually fulfill this purpose. By contrast, patients with limited number of brain metastases, good performance status and controlled or limited systemic disease, may benefit from aggressive treatment as both quality of life and survival are primarily related to treatment of brain lesions. Several efficacious therapeutic options including surgery, radiotherapy and chemotherapy are available for these patients. PMID:24365409

Gállego Pérez-Larraya, Jaime; Hildebrand, Jerzy

2014-01-01

266

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

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. PMID:24619359

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

267

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 Central

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 WT1Wilms2 and WT1Wilms3 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.

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

2014-01-01

268

Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification.  

PubMed

This paper introduces a novel methodology for the segmentation of brain MS lesions in MRI volumes using a new clustering algorithm named SCPFCM. SCPFCM uses membership, typicality and spatial information to cluster each voxel. The proposed method relies on an initial segmentation of MS lesions in T1-w and T2-w images by applying SCPFCM algorithm, and the T1 image is then used as a mask and is compared with T2 image. The proposed method was applied to 10 clinical MRI datasets. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. PMID:22606670

Khotanlou, Hassan; Afrasiabi, Mahlagha

2011-07-01

269

Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification  

PubMed Central

This paper introduces a novel methodology for the segmentation of brain MS lesions in MRI volumes using a new clustering algorithm named SCPFCM. SCPFCM uses membership, typicality and spatial information to cluster each voxel. The proposed method relies on an initial segmentation of MS lesions in T1-w and T2-w images by applying SCPFCM algorithm, and the T1 image is then used as a mask and is compared with T2 image. The proposed method was applied to 10 clinical MRI datasets. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations.

Khotanlou, Hassan; Afrasiabi, Mahlagha

2011-01-01

270

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)

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 have a significant improvement compared to the classical MUSIC method, with a small margin of uncertainty about the exact location of the sources. In fact, the constraints of the spatial sparsity on the signal field allow to concentrate power in the directions of active sources, and consequently it is possible to calculate the position of the sources within the considered volume conductor. Later, the method is tested on the real EEG data too. The result is in accordance with the clinical report even if improvements are necessary to have further accurate estimates of the positions of the sources.

Vergallo, P.; Lay-Ekuakille, A.

2013-08-01

271

Multi-frequency electrical impedance tomography (EIT) of the adult human head: initial findings in brain tumours, arteriovenous malformations and chronic stroke, development of an analysis method and calibration.  

PubMed

MFEIT (multi-frequency electrical impedance tomography) could distinguish between ischaemic and haemorrhagic stroke and permit the urgent use of thrombolytic drugs in patients with ischaemic stroke. The purpose of this study was to characterize the UCLH Mk 2 MFEIT system, designed for this purpose, with 32 electrodes and a multiplexed 2 kHz to 1.6 MHz single impedance measuring circuit. Data were collected in seven subjects with brain tumours, arteriovenous malformations or chronic stroke, as these resembled the changes in haemorrhagic or ischaemic stroke. Calibration studies indicated that the reliable bandwidth was only 16-64 kHz because of front-end components placed to permit simultaneous EEG recording. In raw in-phase component data, the SD of 16-64 kHz data for one electrode combination across subjects was 2.45 +/- 0.9%, compared to a largest predicted change of 0.35% estimated using the FEM of the head. Using newly developed methods of examining the most sensitive channels from the FEM, and nonlinear imaging constrained to the known site of the lesion, no reproducible changes between pathologies were observed. This study has identified a specification for accuracy in EITS in acute stroke, identified the size of variability in relation to this in human recordings, and presents new methods for analysis of data. Although no reproducible changes were identified, we hope this will provide a foundation for future studies in this demanding but potentially powerful novel application. PMID:16636407

Romsauerova, A; McEwan, A; Horesh, L; Yerworth, R; Bayford, R H; Holder, D S

2006-05-01

272

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

PubMed

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. PMID:20848106

Feiden, S; Sartorius, E; Feiden, W

2010-10-01

273

Melanotic neuroectodermal tumour of infancy.  

PubMed

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. PMID:22797196

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

2010-01-01

274

Circulating tumour cells: insights into tumour heterogeneity.  

PubMed

Tumour heterogeneity is a major barrier to cure breast cancer. It can exist between patients with different intrinsic subtypes of breast cancer or within an individual patient with breast cancer. In the latter case, heterogeneity has been observed between different metastatic sites, between metastatic sites and the original primary tumour, and even within a single tumour at either a metastatic or a primary site. Tumour heterogeneity is a function of two separate, although linked, processes. First, genetic instability is a hallmark of malignancy, and results in 'fixed' genetic changes that are almost certainly carried forward through progression of the cancer over time, with increasingly complex additional genetic changes in new metastases as they arise. The second type of heterogeneity is due to differential but 'plastic' expression of various genes important in the biology and response to various therapies. Together, these processes result in highly variable cancers with differential response, and resistance, to both targeted (e.g. endocrine or anti-human epithelial growth receptor type 2 (HER2) agents) and nontargeted therapies (e.g. chemotherapy). Ideally, tumour heterogeneity would be monitored over time, especially in relation to therapeutic strategies. However, biopsies of metastases require invasive and costly procedures, and biopsies of multiple metastases, or serially over time, are impractical. Circulating tumour cells (CTCs) represent a potential surrogate for tissue-based cancer and therefore might provide the opportunity to monitor serial changes in tumour biology. Recent advances have enabled accurate and reliable quantification and molecular characterization of CTCs with regard to a number of important biomarkers including oestrogen receptor alpha and HER2. Preliminary data have demonstrated that expression of these markers between CTCs in individual patients with metastatic breast cancer reflects the heterogeneity of the underlying tumours. Future studies are designed to determine the clinical utility of these novel technologies in either research or routine clinical settings. PMID:23844916

Hayes, D F; Paoletti, C

2013-08-01

275

The tumour suppressor L(3)mbt inhibits neuroepithelial proliferation and acts on insulator elements  

Microsoft Academic Search

In Drosophila, defects in asymmetric cell division often result in the formation of stem-cell-derived tumours. Here, we show that very similar terminal brain tumour phenotypes arise through a fundamentally different mechanism. We demonstrate that brain tumours in l(3)mbt mutants originate from overproliferation of neuroepithelial cells in the optic lobes caused by derepression of target genes in the Salvador–Warts–Hippo (SWH) pathway.

Constance Richter; Katarzyna Oktaba; Jonas Steinmann; Jürg Müller; Juergen A. Knoblich

2011-01-01

276

Bihemispheric brain stimulation facilitates motor recovery in chronic stroke patients(Podcast)(e–Pub ahead of print)(LOE Classification)  

PubMed Central

Objective: Motor recovery after stroke depends on the integrity of ipsilesional motor circuits and interactions between the ipsilesional and contralesional hemispheres. In this sham-controlled randomized trial, we investigated whether noninvasive modulation of regional excitability of bilateral motor cortices in combination with physical and occupational therapy improves motor outcome after stroke. Methods: Twenty chronic stroke patients were randomly assigned to receive 5 consecutive sessions of either 1) bihemispheric transcranial direct current stimulation (tDCS) (anodal tDCS to upregulate excitability of ipsilesional motor cortex and cathodal tDCS to downregulate excitability of contralesional motor cortex) with simultaneous physical/occupational therapy or 2) sham stimulation with simultaneous physical/occupational therapy. Changes in motor impairment (Upper Extremity Fugl-Meyer) and motor activity (Wolf Motor Function Test) assessments were outcome measures while functional imaging parameters were used to identify neural correlates of motor improvement. Results: The improvement of motor function was significantly greater in the real stimulation group (20.7% in Fugl-Meyer and 19.1% in Wolf Motor Function Test scores) when compared to the sham group (3.2% in Fugl-Meyer and 6.0% in Wolf Motor Function Test scores). The effects outlasted the stimulation by at least 1 week. In the real-stimulation group, stronger activation of intact ipsilesional motor regions during paced movements of the affected limb were found postintervention whereas no significant activation changes were seen in the control group. Conclusions: The combination of bihemispheric tDCS and peripheral sensorimotor activities improved motor functions in chronic stroke patients that outlasted the intervention period. This novel approach may potentiate cerebral adaptive processes that facilitate motor recovery after stroke. Classification of evidence: This study provides Class I evidence that for adult patients with ischemic stroke treated at least 5 months after their first and only stroke, bihemispheric tDCS and simultaneous physical/occupational therapy given over 5 consecutive sessions significantly improves motor function as measured by the Upper Extremity Fugl-Meyer assessment (raw change treated 6.1 ± 3.4, sham 1.2 ± 1.0). GLOSSARY CST = corticospinal tract; FLAIR = fluid-attenuated inversion recovery; LI = laterality index; MRC = Medical Research Council; PT/OT = physical/occupational therapy; rTMS = repetitive transcranial magnetic stimulation; tDCS = transcranial direct current stimulation; UE-FM = Upper Extremity Fugl-Meyer assessment; WMFT = Wolf Motor Function Test.

Lindenberg, R.; Renga, V.; Zhu, L.L.; Nair, D.; Schlaug, G.

2010-01-01

277

Unknown primary tumours  

PubMed Central

Unknown primary tumours (UPTs) are defined by the absence of a primary tumour in biopsy proved metastatic cancer. These tumours have a specific biology with clinical characteristics of rapid progression and random atypical metastases. Cytogenetic abnormalities have been demonstrated, particularly deletion of chromosome 1p. Diagnostic evaluation that includes pathology review, physical examination, chest radiography, computed tomography of the abdomen, and mammography is directed at the identification of treatable subsets. Based on clinicopathological criteria, therapy responsive subsets of patients with UPTs can be defined. These subsets have a better prognosis than the average median survival time of four months in patients with UPTs.???Keywords: unknown primary tumours; metastases

Hillen, H

2000-01-01

278

Malignant pancreatic carcinoid tumour.  

PubMed

Pancreatic carcinoid tumours are rare, particularly within the paediatric population. The clinical presentation is largely dependent on the functionality of the tumour. Although the tumour is generally slow-growing, surgical resection is still the mainstay of curative treatment. Morbidity is, however, significantly contributed by secretion of excess hormones; in view of this, biotherapy is an important treatment strategy. Octreotide, a somatostatin analogue, has been shown to be successful in both symptomatic control and stability of tumour progression. We report a 12-year-old girl, who presented with hypertensive crisis, and showed good response to a combination of chemotherapy and octreotide. PMID:18043827

Zarina, A L; Hamidah, A; Zulkifli, S Z; Zulfiqar, M A; Jamal, R

2007-12-01

279

Tumours of the skin*  

PubMed Central

Tumours occur more frequently in the skin than in any other part of the body. Epithelial tumours are described under the following headings: basal cell tumour, squamous cell carcinoma, papilloma, sebaceous gland tumour, tumour of hepatoid glands, sweat gland tumour, mixed tumour of apocrine sweat glands, carcinoma of apocrine sweat glands, tumour of hair follicle, and intracutaneous cornifying epithelioma. Tumours of the melanogenic system are divided into benign melanoma and malignant melanoma, the latter being subdivided into the following types: epithelioid, spindle cell, epithelioid and spindle cell, dendritic, and whorled. ImagesFig. 17Fig. 18Fig. 19Fig. 20Fig. 49Fig. 50Fig. 51Fig. 52Fig. 37Fig. 38Fig. 39Fig. 40Fig. 5Fig. 6Fig. 7Fig. 8Fig. 33Fig. 34Fig. 35Fig. 36Fig. 13Fig. 14Fig. 15Fig. 16Fig. 25Fig. 26Fig. 27Fig. 28Fig. 9Fig. 10Fig. 11Fig. 12Fig. 29Fig. 30Fig. 31Fig. 32Fig. 21Fig. 22Fig. 23Fig. 24Fig. 41Fig. 42Fig. 43Fig. 44Fig. 1Fig. 2Fig. 3Fig. 4Fig. 53Fig. 54Fig. 55Fig. 56Fig. 45Fig. 46Fig. 47Fig. 48

Weiss, E.; Frese, K.

1974-01-01

280

Malignant Dysembryoplastic Neuroepithelial Tumour in a Zebrafish (Danio rerio)  

PubMed Central

Summary Neuroectodermal tumours in man, including medulloblastoma, medulloepithelioma, neuroblastoma, esthesioneuroblastoma, primitive neuroectodermal tumour and dysembryoplastic neuroepithelial tumour, typically occur in children and young adults. These tumour types are occasionally observed in juvenile and adult zebrafish (Danio rerio), either as induced tumours in carcinogen-exposed zebrafish or as an incidental finding in zebrafish ? 2 years of age. An adult zebrafish submitted for routine histological examination was sent for a second opinion consultation after an uncharacteristic brain mass was identified. Microscopically, the expansile and infiltrative extracortical mass arising from the cerebellum had a diffuse microcystic pattern with solid hypercellular regions occupying 80% of the extrameningeal space and effacing the endomeninx and significantly displacing the metencephalon. The mass was composed of dense sheets of oligodendrocyte-like cells, random neurons and pseudocysts containing ‘floating neurons’ within a scant mucinous matrix. Neoplastic cells demonstrated positive perinuclear and intracytoplasmic expression of S-100. Malignant dysembryoplastic neuroepithelial tumour was diagnosed based upon the histologic features of the brain mass, which were indistinguishable from the human tumour. To our knowledge, this is the first report of a dysembryoplastic neuroepithelial tumour in a zebrafish.

Peterson, T. S.; Heidel, J. R.; Murray, K. N.; Sanders, J. L.; Anderson, W. I.; Kent, M. L.

2014-01-01

281

Recruitment feasibility to a cohort study of endocrine and metabolic health among survivors of childhood brain tumours: a report from the Canadian study of Determinants of Endometabolic Health in ChIlDrEn (CanDECIDE)  

PubMed Central

Objectives The aim of this study was to test the feasibility of recruitment and performance of study procedures of the Canadian Study of Determinants of Endometabolic Health in ChIlDrEn (CanDECIDE) study, which was designed to assess the determinants of endocrine and metabolic health in survivors of childhood brain tumours. Setting A single paediatric tertiary care centre in Hamilton, Ontario, Canada. Participants We included boys and girls, aged 5?years and older, who were lean (body mass index (BMI) below 85th centile for age and gender) or overweight/obese (BMI 85th centile or above for age and gender). We excluded children on steroids or immunosuppressant therapy, smokers and those who had an active infection for the 2?weeks prior to participation. Outcomes Feasibility targets included recruitment rate of at least 50%, the consenting of 80% of participants to provide biological samples, 90% questionnaire completion rate and the ability to process biological samples from at least 80% of participants. Results We approached 210 potential participants, and of the 112 (53%) who agreed to participate, 30 (26.8%) completed the study visit over 7?months. All participants agreed to fast, provide biological samples and complete the questionnaires. Sample collection was successful in 97% (29/30) of participants and laboratory procedures were feasible in 100% of collected samples. We also tested resources required for the conduct of the full study including personnel, space, laboratory equipment and procedures and determined that they are all feasible. Conclusions Recruitment and consenting of patients for the CanDECIDE study may be feasible. However, we are considering prolonging recruitment duration and collaboration with other centres to meet recruitment targets due to lower than expected recruitment rate. Completion of questionnaires and implementation of sample processing protocols are feasible.

Samaan, M Constantine; Scheinemann, Katrin; Burrow, Sarah; Dillenburg, Rejane F; Barr, Ronald D; Wang, Kuan-Wen; Valencia, Marlie; Thabane, Lehana

2014-01-01

282

Cancer imaging: Lighting up tumours  

NASA Astrophysics Data System (ADS)

Detection of a wide range of tumours remains a challenge in cancer diagnostics. By exploiting changes in the tumour microenvironment, a pH-responsive polymeric nanomaterial enables ultrasensitive tumour-specific imaging in many types of cancer.

Ling, Daishun; Hackett, Michael J.; Hyeon, Taeghwan

2014-02-01

283

Androgen secreting adrenocortical tumours  

PubMed Central

BACKGROUND—Androgen secreting adrenocortical tumours are rare in children and the determination of their malignant potential can be difficult.?OBJECTIVES—To assess the presentation, histology, and clinical behaviour of these tumours.?SETTING—Two tertiary referral centres. ?Study design—Retrospective analysis of children diagnosed with an androgen secreting adrenocortical tumour between 1976 and 1996.?PATIENTS—Twenty three girls and seven boys aged 0-14 years.?RESULTS—Pubic hair was observed in all children, clitoromegaly or growth of the phallus in 23 children, acceleration of linear growth in 22 children, and advanced bone age (> 1.5 years) in 18 children. Hypersecretion of androgens was detected by assessment of serum androgen concentrations alone in four patients and by 24 hour urine steroid excretion profiles in 22 patients. All 16 tumours measuring < 5 cm in diameter were benign. Of the tumours measuring 5-9 cm, three were malignant and seven were benign, whereas all four tumours > 10 cm were malignant. Histological slides were available for reassessment in 25 children. Although mitoses and necrosis were more characteristic of tumours with malignant behaviour, no exclusive histological features of malignancy were seen.?CONCLUSION—Histological criteria for malignancy are not reliable, whereas tumour size is important in assessing malignant potential.??

Wolthers, O; Cameron, F; Scheimberg, I; Honour, J; Hindmarsh, P; Savage, M; Stanhope, R; Brook, C

1999-01-01

284

Breast tumour angiogenesis  

Microsoft Academic Search

The central importance of tumour neovascularization has been emphasized by clinical trials using antiangiogenic therapy in breast cancer. This review gives a background to breast tumour neovascularization in in situ and invasive breast cancer, outlines the mechanisms by which this is achieved and discusses the influence of the microenvironment, focusing on hypoxia. The regulation of angiogenesis and the antivascular agents

Stephen B Fox; Daniele G Generali; Adrian L Harris

2007-01-01

285

Classification of binary intentions for individuals with impaired oculomotor function: ‘eyes-closed’ SSVEP-based brain-computer interface (BCI)  

NASA Astrophysics Data System (ADS)

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 disabled individuals with impaired oculomotor function.

Lim, Jeong-Hwan; Hwang, Han-Jeong; Han, Chang-Hee; Jung, Ki-Young; Im, Chang-Hwan

2013-04-01

286

Odontogenic tumours in children and adolescents: a study of 78 Nigerian cases  

Microsoft Academic Search

Background: There is paucity of literature on odontogenic tumours in children and adolescents. Available records are difficult to compare due to differences in study criteria. To contribute to the records, a 20-year study of odontogenic tumours on the basis of the WHO classification (Kramer et al., 1992) in Nigerian African children and adolescents ?18 years of age was undertaken. Material:

Ezekiel Taiwo Adebayo; Sunday Olusegun Ajike; Emmanuel Oladepo Adekeye

2002-01-01

287

Inhibition in Multiclass Classification  

Microsoft Academic Search

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly,

Ramón Huerta; Shankar Vembu; José M. Amigó; Thomas Nowotny; Charles Elkan

288

Inhibition in Multiclass Classification  

Microsoft Academic Search

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect.

Ramón Huerta; Shankar Vembu; José M. Amigó; Thomas Nowotny; Charles Elkan

2012-01-01

289

Small Intestinal Tumours  

PubMed Central

Objective. Balloon enteroscopy (BE) and capsule enteroscopy (CE) are enteroscopy methods that allow examination and treatment of the small bowel. Before the CE and BE era, the small intestine was difficult to access for investigation. Small intestinal tumours are infrequent conditions, but about half of them are malignant. Materials and Methods. A total of 303 BEs were performed in 179 patients. Oral insertion was performed in 240 and anal in 63 BEs. Indications for the procedure in our patients with small bowel tumours were anaemia and/or bleeding, obstruction, suspicion of carcinoid tumour, or suspicion of Peutz-Jeghers syndrome. Results. In 50 of our 179 patients (28%), we diagnosed some small intestinal tumours: hamartomas in Peutz-Jeghers syndrome in 16 patients, adenocarcinoma in 7, lymphoma in 6, carcinoid tumour in 4, melanoma and stromal tumour in 3, adenoma, lipoma, and inflammatory polyps in 2, and granular cell tumour, cavernous lymphangioma, fibrolipoma, Cronkhite-Canada polyps, and metastatic involvement in individual cases. Conclusion. BE facilitates exploration and treatment of the small intestine. The procedure is generally safe and useful. BE and CE are essential modalities for the management of small intestinal diseases.

Kopacova, Marcela; Bures, Jan; Tacheci, Ilja

2013-01-01

290

Small intestinal tumours.  

PubMed

Objective. Balloon enteroscopy (BE) and capsule enteroscopy (CE) are enteroscopy methods that allow examination and treatment of the small bowel. Before the CE and BE era, the small intestine was difficult to access for investigation. Small intestinal tumours are infrequent conditions, but about half of them are malignant. Materials and Methods. A total of 303 BEs were performed in 179 patients. Oral insertion was performed in 240 and anal in 63 BEs. Indications for the procedure in our patients with small bowel tumours were anaemia and/or bleeding, obstruction, suspicion of carcinoid tumour, or suspicion of Peutz-Jeghers syndrome. Results. In 50 of our 179 patients (28%), we diagnosed some small intestinal tumours: hamartomas in Peutz-Jeghers syndrome in 16 patients, adenocarcinoma in 7, lymphoma in 6, carcinoid tumour in 4, melanoma and stromal tumour in 3, adenoma, lipoma, and inflammatory polyps in 2, and granular cell tumour, cavernous lymphangioma, fibrolipoma, Cronkhite-Canada polyps, and metastatic involvement in individual cases. Conclusion. BE facilitates exploration and treatment of the small intestine. The procedure is generally safe and useful. BE and CE are essential modalities for the management of small intestinal diseases. PMID:24348540

Kopá?ová, Marcela; Rejchrt, Stanislav; Bureš, Jan; Tachecí, Ilja

2013-01-01

291

Texture analysis of T1 - and T2 -weighted MR images and use of probabilistic neural network to discriminate posterior fossa tumours in children.  

PubMed

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 & Sons, Ltd. PMID:24729528

Orphanidou-Vlachou, Eleni; Vlachos, Nikolaos; Davies, Nigel P; Arvanitis, Theodoros N; Grundy, Richard G; Peet, Andrew C

2014-06-01

292

Anaplastic astroblastoma: a rare glial tumour  

PubMed Central

Astroblastoma is a rarely diagnosed primary brain neoplasm whose histogenesis has been clarified recently. It occurs in children and young adults and presents as a well-circumscribed, contrast enhancing lesion in the cerebral hemisphere. Here the authors present a case of 25-year-old woman with an astroblastoma in the left frontal convexity that was excised. The characteristic radiological and histopathological features of this case are described. An astroblastoma should be included in the differential of a localised brain tumour, especially in a young patient.

Binesh, Fariba; Akhavan, Ali; Navabii, Hossein; Mehrabaniyan, Mohammadreza

2011-01-01

293

Network-Based High Level Data Classification  

Microsoft Academic Search

Traditional supervised data classification considers only physical features (e.g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification

Thiago Christiano Silva; Liang Zhao

2012-01-01

294

Primary mediastinal tumours  

PubMed Central

Al-Naaman, Y. D., Al-Ani, M. S., and Al-Omeri, M. M. (1974).Thorax, 29, 475-481. Primary mediastinal tumours. A review of 28 patients with primary mediastinal tumours seen over a five-year period is presented. Clinical and pathological features of a heterogeneous group of tumours are emphasized. Since a number of patients presented with mild symptoms or were asymptomatic (especially adults), the importance of routine chest radiographs is stressed. Complete excision was accomplished in all patients with benign lesions. Malignant lesions were usually partially resectable and carried a poor prognosis. Images

Al-Naaman, Yousif D.; Al-Ani, Mohamad S.; Al-Omeri, Muayyad M.

1974-01-01

295

The determinants of tumour immunogenicity  

Microsoft Academic Search

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

Thomas Blankenstein; Pierre G. Coulie; Eli Gilboa; Elizabeth M. Jaffee

2012-01-01

296

Gastrointestinal stromal tumours (GIST)  

Microsoft Academic Search

Background-aim  Gastrointestinal stromal tumours (GIST) are the most common mesenchymal neoplasms of the gastrointestinal tract, yet extremely\\u000a rare since they account for less than 1% of all GI tumours, which may arise virtually in any part of the gastrointestinal\\u000a tract. GISTs are typically defined as a group of heterogeneous gastrointestinal mesenchymal neoplasms that are characterized\\u000a by the expression of c-KIT receptor

D. Skouteris; K. Biliri; S. Chranioti; M. Digalakis

2010-01-01

297

Breast tumour angiogenesis  

PubMed Central

The central importance of tumour neovascularization has been emphasized by clinical trials using antiangiogenic therapy in breast cancer. This review gives a background to breast tumour neovascularization in in situ and invasive breast cancer, outlines the mechanisms by which this is achieved and discusses the influence of the microenvironment, focusing on hypoxia. The regulation of angiogenesis and the antivascular agents that are used in an antiangiogenic dosing schedule, both novel and conventional, are also summarized.

Fox, Stephen B; Generali, Daniele G; Harris, Adrian L

2007-01-01

298

Disrupting tumour blood vessels  

Microsoft Academic Search

Low-molecular-weight vascular-disrupting agents (VDAs) cause a pronounced shutdown in blood flow to solid tumours, resulting in extensive tumour-cell necrosis, while they leave the blood flow in normal tissues relatively intact. The largest group of VDAs is the tubulin-binding combretastatins, several of which are now being tested in clinical trials. DMXAA (5,6-dimethylxanthenone-4-acetic acid) — one of a structurally distinct group of

Chryso Kanthou; Bruce C. Baguley; Gillian M. Tozer

2005-01-01

299

Management of central nervous system tumours in the elderly.  

PubMed

Brain tumours in the elderly show differences from the general population in their spectrum of incidence, their molecular profile and their response to treatment. Furthermore, this population also finds it more difficult to tolerate the treatments applied to younger patients. For these reasons it is justified to investigate older patients separately and to devise treatments applicable specifically to this population. In recent years important information has come from the research literature that allows us to make specific recommendations for the management of elderly patients with brain tumours. Here we review the important publications and document these recommendations. PMID:24703159

Rampling, R; Erridge, S

2014-07-01

300

Splenic tumour: a clinicopathological study.  

PubMed

Splenic tumours are occasionally found during routine physical check-ups or elective abdominal image studies. Histologically, most splenic tumours are of benign vascular origin. To avoid unnecessary surgery for asymptomatic patients with benign splenic tumours and clarify the clinicopathological features of spleen tumours, this study gathered 44 cases of primary or isolated metastatic spleen tumours confirmed by pathology from surgery specimens or biopsies. The differences in clinicopathological features and image presentations between benign and malignant spleen tumour were investigated. Thirty-two cases involved benign tumours while 12 cases were malignant. Among the benign tumours, vascular originating tumours were most common (with 14 cases of cavernous haemangiomas, 13 cases of lymphangioma, three cases of lymphangiohaemangioma and one case of Littoral cell angioma). Notably, one, case of inflammatory pseudotumour because of Schistosoma parasite infection was also noted. Among the malignant tumours, there were four cases of angiosarcomas with vascular endothelium origins, as well as lymphomas and six metastatic tumours. Image studies were non-specific. Image study alone is an inadequate basis for making differential diagnoses between benign and malignant tumours. Instead, pathological studies are required for a final diagnosis. Using previous studies and this investigation, fine needle aspiration biopsy of spleen tumours with the help of ultrasonic or computed tomography appears a safe and effective method for obtaining biopsy specimens. Splenectomy is recommended only for patients with malignancies or complications such as intractable abdominal pain, coagulopathy or tumour rupture with an unstable haemodynamic state. PMID:15587770

Chen, L W; Chien, R N; Yen, C L; Chang, L C

2004-10-01

301

Classification of chromosome segregation errors in cancer  

Microsoft Academic Search

Abnormal chromosome segregation at mitosis is one way by which neoplastic cells accumulate the many genetic abnormalities\\u000a required for tumour development. In this paper, a straightforward morphology-based classification of chromosome segregation\\u000a errors in cancer is suggested. This classification distinguishes between abnormalities in spindle symmetry (spindle multipolarity,\\u000a size-asymmetry of ana-telophase poles) and abnormalities in sister chromatid segregation (chromosome bridges, chromatid bridges,

David Gisselsson

2008-01-01

302

Spectral classification  

NASA Astrophysics Data System (ADS)

Taxonomic classification of astronomically observed stellar objects is described in terms of spectral properties. Stars receive a classification containing a letter, number, and a Roman numeral, which relates the star to other stars of higher or lower Roman numerals. The citation indicates the stellar chromatic emission in relation to the wavelengths of other stars. Standards are chosen from the available objects detected. Various classification schemes such as the MK, HD, and the Barbier-Chalonge-Divan systems are defined, including examples of indexing differences. Details delineating the separations between classifications are discussed with reference to the information content in spectral and in photometric classification schemes. The parameters usually used for classification include the temperature, luminosity, reddening, binarity, rotation, magnetic field, and elemental abundance or composition. The inclusion of recently discovered extended wavelength characteristics in nominal classifications is outlined, together with techniques involved in automated classification.

Jaschek, C.

303

Clinical management of brain metastasis  

Microsoft Academic Search

Brain metastasis is a common complication ocurring in about 15–20% of all cancer patients. For the initial management, distinguishing\\u000a between three types of presentation is essential: de novo brain metastasis, simultaneous presentation of both brain metastasis\\u000a and the primary tumour (usually lung carcinoma), and the presentation of a patient known to have systemic cancer developing\\u000a a brain metastasis. For de

Ch. J. Vecht; Daniel den Hoed

1998-01-01

304

Predicting tumour response.  

PubMed

Response prediction is an important emerging concept in oncologic imaging, with tailored, individualized treatment regimens increasingly becoming the standard of care. This review aims to define tumour response and illustrate the ways in which imaging techniques can demonstrate tumour biological characteristics that provide information on the likely benefit to be received by treatment. Two imaging approaches are described: identification of therapeutic targets and depiction of the treatment-resistant phenotype. The former approach is exemplified by the use of radionuclide imaging to confirm target expression before radionuclide therapy but with angiogenesis imaging and imaging correlates for genetic response predictors also demonstrating potential utility. Techniques to assess the treatment-resistant phenotype include demonstration of hypoperfusion with dynamic contrast-enhanced computed tomography and magnetic resonance imaging (MRI), depiction of necrosis with diffusion-weighted MRI, imaging of hypoxia and tumour adaption to hypoxia, and 99mTc-MIBI imaging of P-glycoprotein mediated drug resistance. To date, introduction of these techniques into clinical practice has often been constrained by inadequate cross-validation of predictive criteria and lack of verification against appropriate response end points such as survival. With further refinement, imaging predictors of response could play an important role in oncology, contributing to individualization of therapy based on the specific tumour phenotype. This ability to predict tumour response will have implications for improving efficacy of treatment, cost-effectiveness and omission of futile therapy. PMID:24061161

Kyle, Samuel D; Law, W Phillip; Miles, Kenneth A

2013-01-01

305

Predicting tumour response  

PubMed Central

Abstract Response prediction is an important emerging concept in oncologic imaging, with tailored, individualized treatment regimens increasingly becoming the standard of care. This review aims to define tumour response and illustrate the ways in which imaging techniques can demonstrate tumour biological characteristics that provide information on the likely benefit to be received by treatment. Two imaging approaches are described: identification of therapeutic targets and depiction of the treatment-resistant phenotype. The former approach is exemplified by the use of radionuclide imaging to confirm target expression before radionuclide therapy but with angiogenesis imaging and imaging correlates for genetic response predictors also demonstrating potential utility. Techniques to assess the treatment-resistant phenotype include demonstration of hypoperfusion with dynamic contrast-enhanced computed tomography and magnetic resonance imaging (MRI), depiction of necrosis with diffusion-weighted MRI, imaging of hypoxia and tumour adaption to hypoxia, and 99mTc-MIBI imaging of P-glycoprotein mediated drug resistance. To date, introduction of these techniques into clinical practice has often been constrained by inadequate cross-validation of predictive criteria and lack of verification against appropriate response end points such as survival. With further refinement, imaging predictors of response could play an important role in oncology, contributing to individualization of therapy based on the specific tumour phenotype. This ability to predict tumour response will have implications for improving efficacy of treatment, cost-effectiveness and omission of futile therapy.

Law, W. Phillip; Miles, Kenneth A.

2013-01-01

306

Subdural enhancement on postoperative spinal MRI after resection of posterior cranial fossa tumours  

Microsoft Academic Search

In malignant brain tumours which may disseminate staging, usually by cranial and spinal MRI is necessary. If MRI is performed in the postoperative period pitfalls should be considered. Nonspecific subdural contrast enhancement on spinal staging MRI is rarely reported after resection of posterior fossa tumours, which may be mistaken for dissemination of malignancy. We investigated the frequency of spinal subdural

M. Warmuth-Metz; J. Krauss; L. Solymosi

2004-01-01

307

Unusual presentation of a large pituitary tumour in relation to diving.  

PubMed Central

A case of necrosis of a pituitary tumour occurring in the context of diving is described. The presenting features and subsequent course suggested a brain stem vascular event. The tumour was not detected by routine computerized tomographic scanning, but was identified with magnetic resonance imaging. The possible pathophysiological mechanism is discussed. Images Figure 1 Figure 2 Figure 3

Bakheit, A. M.; Kennedy, P. G.

1989-01-01

308

ICA-based classification scheme for EEG-based brain-computer interface: the role of mental practice and concentration skills  

Microsoft Academic Search

This article explores the use of independent component analysis (ICA) approach to design a new EEG-based brain-computer interface (BCI) for natural control of prosthetic hand grasp. ICA is a useful technique that allows blind separation of sources, linearly mixed, assuming only the statistical independence of these sources. This suggests the possibility of using ICA to separate different independent brain activities

Abbas Erfanian; Ali Erfani

2004-01-01

309

Feature subset selection for classification of histological images  

Microsoft Academic Search

Classification of histological images is considered in this paper. The task is to distinguish different classes of tumours of the central nervous system on the basis of features extracted from microscopic slides. The number of extracted features is relatively high and some of them seem to be irrelevant for classification of the images. Thus, the main objective of this study

Jacek Jelonek; Jerzy Stefanowski

1997-01-01

310

Radiotherapy for ocular tumours  

PubMed Central

Ocular tumours present a therapeutic challenge because of the sensitive tissues involved and the necessity to destroy the tumour while minimising visual loss. Radiotherapy (RT) is one of several modalites used apart from surgery, laser, cryotherapy, and chemotherapy. Both external beam RT (EBRT) and brachytherapy are used. Tumours of the bulbar conjunctiva, squamous carcinoma and malignant melanoma, can be treated with a radioactive plaque: strontium-90, ruthenium-106 (Ru-106), or iodine-125 (I-125), after excision. If the tumour involves the fornix or tarsal conjunctiva, proton therapy can treat the conjunctiva and spare most of the eye. Alternatively, an I-125 interstitial implant can be used with shielding of the cornea and lens. Conjunctival mucosal-associated lymphoid tissue lymphoma can be treated with an anterior electron field with lens shielding and 25–30 Gray (Gy) in 2?Gy fractions. Discrete retinoblastoma (RB), too large for cryotherapy or thermolaser, or recurrent after these modalities, can be treated with plaque therapy, I-125, or Ru-106. For large RB, multiple tumours, or vitreous seeds the whole eye can be treated with an I-125 applicator, sparing the bony orbit, or with EBRT, under anaesthetic, using X-rays or proton therapy with vacuum contact lenses to fix the eyes in the required position. Post-enucleated orbits at risk for recurrent RB can be treated with an I-125 implant with shielding to reduce the dose to the bony orbit. Uveal malignant melanomas can be treated with plaque or proton therapy with excellent local control. Preservation of vision will depend on the initial size and location of the tumour.

Stannard, C; Sauerwein, W; Maree, G; Lecuona, K

2013-01-01

311

SEOM clinical guidelines for the diagnosis and treatment of gastroenteropancreatic neuroendocrine tumours (GEP NETS).  

PubMed

Gastroenteropancreatic neuroendocrine tumours (GEP NETs) represent a heterogenous family of tumours with growing incidence and challenging clinical management. Unlike other solid tumours, they have the ability to secrete different peptides and neuramines that cause distinct clinical syndromes. However, many are clinically silent until advanced disease. This guideline aims to provide practical recommendations for the diagnosis and treatment of GEP NETs. Most recent histological and staging classifications, as well as available therapeutic approaches, such as surgery, locoregional therapy, peptide receptor radionuclide therapy (PRRT) and hormonal or systemic therapy, are discussed in this manuscript, including some recent relevant achievements with novel targeted agents. Clinical presentation (with or without hormonal syndrome), histological tumour features (including proliferation index (Ki-67) and the presence or not of somatostatin receptors), tumour stage, and location of primary tumour and distant metastasis are all key issues that shall be taken into consideration to properly design and integrate the most adequate therapeutic strategy. PMID:21821488

García-Carbonero, Rocío; Salazar, Ramón; Sevilla, Isabel; Isla, Dolores

2011-08-01

312

Survival of patients with nonseminomatous germ cell cancer: a review of the IGCC classification by Cox regression and recursive partitioning  

Microsoft Academic Search

The International Germ Cell Consensus (IGCC) classification identifies good, intermediate and poor prognosis groups among patients with metastatic nonseminomatous germ cell tumours (NSGCT). It uses the risk factors primary site, presence of nonpulmonary visceral metastases and tumour markers alpha-fetoprotein (AFP), human chorionic gonadotrophin (HCG) and lactic dehydrogenase (LDH). The IGCC classification is easy to use and remember, but lacks flexibility.

M R van Dijk; E W Steyerberg; S P Stenning; E Dusseldorp; J D F Habbema; van Dijk

2004-01-01

313

Metastasising pilar tumour of scalp  

Microsoft Academic Search

A case of pilar tumour of the scalp, treated by local excision and radiotherapy, later metastasised to the neck. The variable histological growth patterns of the primary tumour and its metastases are described. It is concluded that the pilar tumour is a genuine neoplasm of the hair follicle that is occasionally capable of malignant behaviour.

P A Batman; H J Evans

1986-01-01

314

DESMOID TUMOURS OF THE HAND  

Microsoft Academic Search

We report a case of a 3-year-old child with a desmoid tumour of the hand, which is an exceedingly rare location. Desmoid tumours of the hand are difficult to treat because of the many important structures concentrated in the area as well as the infiltrative and recurrent character of these tumours.

F DUTEILLE; G DAUTEL; D SOMMELET

1999-01-01

315

PUTTING TUMOURS IN CONTEXT  

PubMed Central

The interactions between cancer cells and their micro- and macroenvironment create a context that promotes tumour growth and protects it from immune attack. The functional association of cancer cells with their surrounding tissues forms a new ‘organ’ that changes as malignancy progresses. Investigation of this process might provide new insights into the mechanisms of tumorigenesis and could also lead to new therapeutic targets.

Bissell, Mina J.; Radisky, Derek

2010-01-01

316

Graz brain-computer interface II: towards communication between humans and computers based on online classification of three different EEG patterns  

Microsoft Academic Search

The paper describes work on the brain-computer interface (BCI). The BCI is designed to help patients with severe motor impairment\\u000a (e.g. amyotropic lateral sclerosis) to communicate with their environment through wilful modification of their EEG. To establish\\u000a such a communication channel, two major prerequisites have to be fulfilled: features that reliably describe several distinctive\\u000a brain states have to be available,

J. Kalcher; D. Flotzinger; Ch. Neuper; S. Gölly; G. Pfurtscheller

1996-01-01

317

[Radiotherapy of brain tumors].  

PubMed

When radiotherapy is employed for central nervous system tumours, several clinical considerations relating to the special normal tissue environment in which they are located deserve recognition. First of all the radiosensitivity of normal brain is nearly equivalent to that of the majority of the primary tumours requiring irradiation. Secondly destroyed normal neural tissue never regenates, but partial recovery is possible following limited injury. Thirdly definition of the target volume is determined mostly by indirect means from a synthesis of neuroradiological findings (C.T. scans, M.R.I.). Finally the rigidity of the intact cranium confers greater clinical significance on mass effects including postradiotherapeutic edema. Most brain tumours respond to external irradiation which may be applied either postoperatively or definitively, e.g. gliomas, lymphomas, medulloblastomas, and metastases. New stereotactic techniques, including radiosurgery, interstitial brachytherapy, and proton beam radiotherapy allow the delivery of larger dose in a limited volume. PMID:8729350

Mazeron, J J; Boisserie, G

1996-02-15

318

Tumours in calves: comparative aspects.  

PubMed

In this paper, calf neoplasia is discussed in relation to a series of cases comprising (1). spontaneous congenital bovine tumours of fetuses and newborn animals, (2). spontaneous juvenile-type tumours in calves aged 2-12 months, and (3). iatrogenic tumours of calves. The congenital cases (n=14) consisted of tumours of a predominantly mesenchymal and malignant nature (malignant lymphoma, mesothelioma and mixed mesodermal tumour). In the juvenile cases (n=11), malignant lymphoma and sarcoma were the commonest forms. In comparing tumour patterns in calves with those reported in adult cattle, it was apparent that tumours were less common in the former (6 versus 60 per 100000) and that, with the exception of malignant lymphoma, the types of tumour differed. Carcinomas, which were virtually absent in calves, predominated in adults, probably due to the longer exposure of older animals to carcinogenic factors. In comparing tumour patterns in calves with those reported in pigs and children, it was clear that calf cases were mainly sporadic, with the notable exception of malignant lymphoma in twins. In young pigs, however, several types of tumour (some hereditary) were reported on a single farm as multiple cases. In children, tumours occurred more frequently than in calves, and many neoplasms in both children and calves could be regarded as embryonic tumours or hamartomas. Little is known about the pathogenetic pathways of tumours in calves, with the exception of congenital neuro-fibromatosis (hereditary) and possibly of mesotheliomatosis (due to asbestos). Modern methods of analysing chromosomal and gene aberrations may be helpful in clarifying the pathogenesis of congenital tumours. PMID:12354519

Misdorp, W

2002-01-01

319

Malignant primary cardiac tumours  

PubMed Central

OBJECTIVES Management of malignant tumours of the heart remains a poorly investigated clinical area due to the scarcity of presentations. The purpose of this series and review is to present an outline of the management emphasized by our personal experience in a regional cardiothoracic centre. METHODS We reviewed all cases presenting with primary cardiac tumours in our institution within the last 10 years, looking at presentation, management and outcomes. RESULTS Of these, the records of 3 patients, who attended the Royal Victoria Hospital in Belfast and were treated for a cardiac sarcoma, were fully evaluated. A review of current literature was conducted through a search of Pubmed and Medline databases. A review of the presentation of these patients and the generally accepted management deterioration of patients diagnosed with cardiac sarcoma is discussed. CONCLUSIONS With reference to our case series, we want to draw attention to the rapid deteriation of these patients following presentation.

Burnside, Nathan; MacGowan, Simon W.

2012-01-01

320

Tumours of the spleen.  

PubMed

The spleen has been considered a 'forgotten organ' even if it is included and well demonstrated on every CT and MRI of the abdomen. Tumours of the spleen are rare; however, radiologists need to be aware of the main tumoral features and patterns in order to try to distinguish between benign and malignant masses often discovered incidentally. The principal tumoral masses, benign (cysts, haemangiomas, litteral cell angioma, lymphangioma) and malignant (lymphoma, metastases haemangiosarcoma), are described. PMID:16154823

Giovagnoni, Andrea; Giorgi, Chiara; Goteri, Gaia

2005-01-01

321

Tumours of the spleen  

PubMed Central

The spleen has been considered a ‘forgotten organ’ even if it is included and well demonstrated on every CT and MRI of the abdomen. Tumours of the spleen are rare; however, radiologists need to be aware of the main tumoral features and patterns in order to try to distinguish between benign and malignant masses often discovered incidentally. The principal tumoral masses, benign (cysts, haemangiomas, litteral cell angioma, lymphangioma) and malignant (lymphoma, metastases haemagiosarcoma), are described.

Giovagnoni, Andrea; Giorgi, Chiara; Goteri, Gaia

2005-01-01

322

An unusual intracranial tumour presenting in pregnancy.  

PubMed

We describe a patient who presented in late pregnancy with deteriorating neurological status due to an intracranial capillary haemangioma causing mass effect and raised intracranial pressure. She became confused and uncooperative leading to practical difficulties in performing adequate radiological imaging. Decision regarding timing of delivery and craniotomy was not straightforward and required discussion between the neurosurgeon, obstetrician and anaesthetist based on assessment of fetal maturity and the need to perform a craniotomy to excise what was initially thought to be a meningioma. Caesarean section was performed under general anaesthesia. The tumour was resected three weeks later. Management of obstetric patients with brain tumours is complex, requiring knowledge of the physiological effects of pregnancy on tumour size and labour on intracranial pressure. Both of these may influence the choice of labour analgesia or anaesthesia for caesarean section. Anaesthetists must be aware of the difficulties of radiological imaging during pregnancy, particularly in confused patients. The conflicting requirements of general anaesthesia for craniotomy and caesarean section should be considered. PMID:17126003

Smith, I F; Skelton, V

2007-01-01

323

Multifocal Dysembryoplastic Neuroepithelial Tumour with Intradural Spinal Cord Lipomas: Report of a Case  

PubMed Central

We report a case of temporal lobe epilepsy and incomplete Brown-Sequard syndrome of the thoracic cord. Computed tomography and magnetic resonance (MR) imaging showed multiple supratentorial masses with the classical radiological appearances of multifocal dysembryoplastic neuroepithelial tumour (DNET). Spinal MR imaging revealed intradural lipomas, not previously reported in association with multifocal DNET. Presentation and imaging findings are discussed along with classification and natural history of the tumour.

White, Richard D.; Kanodia, Avinash K.; Sammler, Esther M.; Brunton, John N.; Heath, Craig A.

2011-01-01

324

Multifocal dysembryoplastic neuroepithelial tumour with intradural spinal cord lipomas: report of a case.  

PubMed

We report a case of temporal lobe epilepsy and incomplete Brown-Sequard syndrome of the thoracic cord. Computed tomography and magnetic resonance (MR) imaging showed multiple supratentorial masses with the classical radiological appearances of multifocal dysembryoplastic neuroepithelial tumour (DNET). Spinal MR imaging revealed intradural lipomas, not previously reported in association with multifocal DNET. Presentation and imaging findings are discussed along with classification and natural history of the tumour. PMID:22606558

White, Richard D; Kanodia, Avinash K; Sammler, Esther M; Brunton, John N; Heath, Craig A

2011-01-01

325

A brain–computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device  

Microsoft Academic Search

Objective: The Thought Translation Device (TTD) for brain–computer interaction was developed to enable totally paralyzed patients to communicate. Patients learn to regulate slow cortical potentials (SCPs) voluntarily with feedback training to select letters. This study reports the comparison of different methods of electroencephalographic (EEG) analysis to improve spelling accuracy with the TTD on a data set of 6650 trials of

Thilo Hinterberger; Andrea Kübler; Jochen Kaiser; Nicola Neumann; Niels Birbaumer

2003-01-01

326

Metabolic scaling in solid tumours  

PubMed Central

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.

Milotti, E.; Vyshemirsky, V.; Sega, M.; Stella, S.; Chignola, R.

2013-01-01

327

Metabolic scaling in solid tumours  

NASA Astrophysics Data System (ADS)

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.

Milotti, E.; Vyshemirsky, V.; Sega, M.; Stella, S.; Chignola, R.

2013-06-01

328

[Guideline for therapy of malignant thyroid tumours: pleading for an actualization].  

PubMed

Total (or near total) thyroidectomy (TE) followed by radioiodine ((131)I) ablation (RIA) of residual thyroid tissue is considered to be the ideal treatment for differentiated thyroid carcinoma. However, the actual guideline of the DGN (German Society of Nuclear Medicine) recommends for the so-called papillary micro-carcinoma of the thyroid (PMC) no further therapeutic strategy (no complete TE, no (131)I-ablation of the remaining lobe). PMC has been defined as papillary carcinoma measuring 1 cm (T1) in maximal diameter according to the World Health Organization classification system for thyroid tumours (1988). The new WHO-classification (starting in 2003) defines the T1-tumour measuring 2 cm in maximal diameter. The authors demand a new, modern guideline, following the new WHO classification. This includes, that despite the overall excellent prognosis for patients with PMC, the treatment of patients with T1-tumours of the new WHO-classification (including the "old" PMC) should be no different from the treatment of patients with conventional papillary thyroid carcinoma, i.e. complete surgery (TE and central lymph node dissection) followed by RIA of residual thyroid tissue. The authors argue that it is not appropriate to consider the tumour size as the single most important key factor for therapy and prognosis. Even small tumours may have poor prognostic factors, such as lymph node metastasis, multifocality or molecular characteristics (expression of oncogenes). PMID:15316578

Wieler, H; Bartenstein, P; Becker, H P; Bell, E; Decker, P; Jacob, R; Kirsch, C M; Musholt, T; Schwab, R; Schwerdtfeger, P; Trampert, L

2004-08-01

329

Primary mesenteric gastrointestinal stromal tumour.  

PubMed

Primary mesenteric gastrointestinal stromal tumours (GISTs) are rare tumours and can be included as a differential for an expanding intraabdominal mass. We present the case, in our institution, of a 72-year-old male who presented with non-specific symptoms and was diagnosed with a primary mesenteric GIST following resection. We report his follow-up and discuss the current theories as to the origins of these rare tumours and current treatment modalities. PMID:24876518

Kirby, R; Rajasagaram, N; Ghusn, M

2014-05-01

330

Primary mesenteric gastrointestinal stromal tumour  

PubMed Central

Primary mesenteric gastrointestinal stromal tumours (GISTs) are rare tumours and can be included as a differential for an expanding intraabdominal mass. We present the case, in our institution, of a 72-year-old male who presented with non-specific symptoms and was diagnosed with a primary mesenteric GIST following resection. We report his follow-up and discuss the current theories as to the origins of these rare tumours and current treatment modalities.

Kirby, R.; Rajasagaram, N.; Ghusn, M.

2014-01-01

331

Classification accuracy of serum Apo A-I and S100B for the diagnosis of mild traumatic brain injury and prediction of abnormal initial head computed tomography scan.  

PubMed

The objective of the current study was to determine the classification accuracy of serum S100B and apolipoprotein (apoA-I) for mild traumatic brain injury (mTBI) and abnormal initial head computed tomography (CT) scan, and to identify ethnic, racial, age, and sex variation in classification accuracy. We performed a prospective, multi-centered study of 787 patients with mTBI who presented to the emergency department within 6 h of injury and 467 controls who presented to the outpatient laboratory for routine blood work. Serum was analyzed for S100B and apoA-I. The outcomes were disease status (mTBI or control) and initial head CT scan. At cutoff values defined by 90% of controls, the specificity for mTBI using S100B (0.899 [95% confidence interval (CI): 0.78-0.92]) was similar to that using apoA-I (0.902 [0.87-0.93]), and the sensitivity using S100B (0.252 [0.22-0.28]) was similar to that using apoA-I (0.249 [0.22-0.28]). The area under the receiver operating characteristic curve (AUC) for the combination of S100B and apoA-I (0.738, 95% CI: 0.71, 0.77), however, was significantly higher than the AUC for S100B alone (0.709, 95% CI: 0.68, 0.74, p=0.001) and higher than the AUC for apoA-I alone (0.645, 95% CI: 0.61, 0.68, p<0.0001). The AUC for prediction of abnormal initial head CT scan using S100B was 0.694 (95%CI: 0.62, 0.77) and not significant for apoA-I. At a S100B cutoff of <0.060 ?g/L, the sensitivity for abnormal head CT was 98%, and 22.9% of CT scans could have been avoided. There was significant age and race-related variation in the accuracy of S100B for the diagnosis of mTBI. The combined use of serum S100B and apoA-I maximizes classification accuracy for mTBI, but only S100B is needed to classify abnormal head CT scan. Because of significant subgroup variation in classification accuracy, age and race need to be considered when using S100B to classify subjects for mTBI. PMID:23758329

Bazarian, Jeffrey J; Blyth, Brian J; He, Hua; Mookerjee, Sohug; Jones, Courtney; Kiechle, Karin; Moynihan, Ryan; Wojcik, Susan M; Grant, William D; Secreti, LaLainia M; Triner, Wayne; Moscati, Ronald; Leinhart, August; Ellis, George L; Khan, Jawwad

2013-10-15

332

Brain drug delivery technologies: novel approaches for transporting therapeutics  

Microsoft Academic Search

The blood–brain barrier (BBB) denies many therapeutic agents access to brain tumours and other diseases of the central nervous system (CNS). Despite remarkable advances in our understanding of the mechanisms involved in the development of the brain diseases and the actions of neuroactive agents, drug delivery to the brain remains a challenge. For more than 20 years, extensive efforts have

Jamal Temsamani; Jean-Michel Scherrmann; Anthony R Rees; Michel Kaczorek

2000-01-01

333

Immunohistochemistry of ovarian granulosa cell tumours  

Microsoft Academic Search

Paraffin-embedded material of 47 ovarian tumours primarily diagnosed as granulosa cell tumours, including 2 cases of juvenile granulosa cell tumour, were studied immunohistochemically for the presence of intermediate filament proteins, epithelial membrane antigen and tumour markers. Forty-one lesions, including the 2 juvenile granulosa cell tumours, were vimentin positive, while keratin and epithelial membrane antigen expression could not be detected. Six

S. Chadha; Th. H. Kwast

1989-01-01

334

VEGF targets the tumour cell  

PubMed Central

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.

Goel, Hira Lal; Mercurio, Arthur M.

2014-01-01

335

Molecular Classifications  

Microsoft Academic Search

The field of glioma classification is currently entering a new era with the introduction of paradigms based on molecular information.\\u000a Rather than supplanting traditional morphology-based classification schemes, it is anticipated that emerging molecular biologic,\\u000a genomic, transcriptomic, and proteomic data will complement and augment existing morphologic and immunophenotypic data, providing\\u000a for a more accurate and refined stratification of glioma patients for

Gregory N. Fuller

336

Tumour Suppressor Genes in the Pathogenesis of Human Pituitary Tumours  

Microsoft Academic Search

Abnormal cell proliferation is controlled by opposing actions of oncogene products (stimulatory) and tumour suppressor gene (TSG) products (inhibitory). The former are dominantly acting, i.e. only one copy needed for tumorigenesis, whilst for TSG both copies of the gene must be inactivated so these are recessive at a cellular level. For anterior pituitary tumours only one oncogene (Gsp) has been

R. N. Clayton; M. Boggild; A. S. Bates; J. Bicknell; D. Simpson; W. Farrell

1997-01-01

337

Association of tumour vasculature with tumour progression and overall survival of patients with non-early gastric carcinomas.  

PubMed Central

In order to investigate the relationship between intratumoral vasculature and progression of gastric carcinomas and between vessel counts and survival of patients with non-early gastric carcinoma, we counted the intratumoral microvessels and compared their numbers with clinicopathological parameters, as well as with the patients' survival. Microvessels were stained with anti-CD34 monoclonal antibody before counting by microscopy (x200). In a group of 181 patients who had undergone tumour resection and were followed for more than 24 months the vessel counts for 83 patients with stage IV disease were significantly higher than those for patients with any other stage of disease. Among various clinicopathological variables, haematogenous metastasis, lymph node metastasis, peritoneal metastasis, stage IV disease and non-curative resection were more frequent in the patients with highly vascularized tumours (intratumoral vessel count > 155) than in those with less vascularized tumours. As a classification of stage IV disease such as haematogenous or peritoneal metastasis generally indicates non-curative resection, it can be considered that the development of stage IV disease is associated with the increase in tumour angiogenesis. Both univariate and multivariate analyses showed that the intratumoral vessel count was significantly predictive of overall survival, when tested as either a continuous or dichotomous variable. Cox hazards model analysis showed that the vessel count was one of the significant and independent prognostic variables. Patients with highly vascularized tumours were significantly more likely to die than those with less vascularized tumours. Assessment of tumour vasculature may therefore be important, not only for its prognostic value, but also as it may help to predict responses to angiogenesis-inhibiting agents.

Tanigawa, N.; Amaya, H.; Matsumura, M.; Shimomatsuya, T.

1997-01-01

338

Classification of histopathologic changes following chemotherapy in Ewing's sarcoma of bone  

Microsoft Academic Search

A uniform classification of response to chemotherapy is essential to allow comparison of local effect and ultimate prognosis between different therapy schedules. We define a histological grading system for assessment of the response to chemotherapy in Ewing's sarcoma, based on the amount and architectural pattern of residual histologically viable-appearing tumour, the preferential sites of minimal residual tumour and the amount

H. J. Woude; J. L. Bloem; A. H. M. Taminiau; M. A. Nooy; P. C. W. Hogendoorn

1994-01-01

339

Brain metastasis from medullary thyroid carcinoma  

PubMed Central

The brain is an exceedingly rare site of metastasis in medullary thyroid carcinoma (MTC). A 50-year-old female who had a history of micro-MTC 11 years prior developed a cerebellar metastasis which was incidentally discovered. Imaging revealed a right cerebellar hemispheric mass with contrast enhancement on CT scans. Histopathologic exam demonstrated a metastatic tumour composed of nodules and sheets of large tumour cells with abundant cytoplasm. Immunohistochemistry confirmed the origin from a MTC. This case report highlights the unique features of an unusual metastatic brain tumour, which followed an indolent course for a long time despite multiple distant metastases.

Borcek, P; Asa, S L; Gentili, F; Ezzat, S; Kiehl, T-R

2010-01-01

340

Brain metastasis from medullary thyroid carcinoma.  

PubMed

The brain is an exceedingly rare site of metastasis in medullary thyroid carcinoma (MTC). A 50-year-old female who had a history of micro-MTC 11 years prior developed a cerebellar metastasis which was incidentally discovered. Imaging revealed a right cerebellar hemispheric mass with contrast enhancement on CT scans. Histopathologic exam demonstrated a metastatic tumour composed of nodules and sheets of large tumour cells with abundant cytoplasm. Immunohistochemistry confirmed the origin from a MTC. This case report highlights the unique features of an unusual metastatic brain tumour, which followed an indolent course for a long time despite multiple distant metastases. PMID:22802478

Börcek, P; Asa, S L; Gentili, F; Ezzat, S; Kiehl, T-R

2010-01-01

341

Recognising Individuals Using Their Brain Patterns  

Microsoft Academic Search

In this paper, a novel method to recognise persons using their brain patterns is proposed. These brain patterns are obtained when the individuals perceive a picture. High frequency brain energy is used as features that are classified by Elman backpropagation neural network. The experimental results using 1600 brain signals from 40 individuals give average classification rate of 96.63%. This pilot

K. V. R. Ravi; Ramaswamy Palaniappan

2005-01-01

342

[Fractionated stereotactic irradiation of skull-base related tumours].  

PubMed

The prognosis of the treatment of brain tumours depends on two main factors: biological nature and localisation of the neoplasm. Requirements of oncologic surgery can be met only partially if at all in neurological surgery of brain tumours. Resectability depends primarily on localisation of the neoplasms. The leading principle is preservation of fine neural structures, minimising morbidity from tissue resection with the goal of maximal tumour resection. As nervous structures and the target volume do not move in the intracranial space, large radiation doses unusual in traditional radiotherapy can be given either in one or in fractionated sessions to small targets (point-radiation) and a well-controlled radiation necrosis of the pathological tissue can be achieved. Management principles of treatment of skull-base related tumours are very similar due to high risks of functional morbidity evoked by surgical injury to the cranial nerves, brainstem structures, vessels of the Willis circle and those of the substantia perforata anterior and posterior, etc. Such tumours are neoplasms arising from the skull base, those infiltrating the cavernous sinuses, invasive pituitary tumours, those arising from the glomus jugulare, or located within the cerebello-pontine angle, etc. This manuscript intends to illustrate and prove the hypothesis by means of 4 cases that fractionated stereotactic radiotherapy (fSRT) is an important part of treatment armamentarium in the latter cases, as it is capable of exploiting both the advantages of traditional fractionated irradiation and that of the high conformality and selectivity of radiosurgery. It is capable of administering appropriate quantity of total target dose with a lower than limit dose on surrounding structures. The presentation proves that fSRT can be planned already in the phase of surgical indication as a "microsurgery-assisted radiotherapy". PMID:24353990

Horváth, Zsolt; Bellyei, Szabolcs; Farkas, Róbert; Mangel, László; Kovács, Péter; Sebestyén, Zsolt; Dóczi, Tamás

2013-12-01

343

Tumours of the cauda equina.  

PubMed Central

A retrospective study of 70 consecutive patients with a cauda equina tumour who were admitted to Neurosurgical Department at the Radcliffe Infirmary, Oxford is presented. The diagnosis of these tumours is often difficult and delayed. The quality of life largely depends upon the neurological disability at presentation. The diagnostic features and investigations are discussed together with the treatment and prognosis.

Fearnside, M R; Adams, C B

1978-01-01

344

Desmoid tumours of the extremities  

Microsoft Academic Search

The authors report seven cases of desmoid tumors of the extremities. A tumour less than a few centimetres in size is best removed by wide local excision. Large growths should also be excised, but efforts should be made to preserve the vessels and nerves, since malignant transformation and metastases do not occur. Irradiation therapy should be considered for tumours which

T. Vizkelety; M. Szendriii

1988-01-01

345

Interleukin-2 and histamine in combination inhibit tumour growth and angiogenesis in malignant glioma  

PubMed Central

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

Johansson, M; Henriksson, R; Bergenheim, A T; Koskinen, L-O D

2000-01-01

346

Classification of spatiotemporal hemodynamics from brain perfusion MR images using expectation-maximization estimation with finite mixture of multivariate gaussian distributions.  

PubMed

The ability to cluster different perfusion compartments in the brain is critical for analyzing brain perfusion. This study presents a method based on a mixture of multivariate Gaussians (MoMG) and the expectation-maximization (EM) algorithm to dissect various perfusion compartments from dynamic susceptibility contrast (DSC) MR images so that each compartment comprises pixels of similar signal-time curves. This EM-based method provides an objective way to 1) delineate an area to serve as the in-plane arterial input function (AIF) of the feeding artery for adjacent tissues to better quantify the relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), and mean transit time (MTT); 2) demarcate regions with abnormal perfusion derangement to facilitate diagnosis; and 3) obtain parametric maps with supplementary information, such as temporal scenarios and recirculation of contrast agent. Results from normal subjects show that perfusion cascade manifests (in order of appearance) the arteries, gray matter (GM), white matter (WM), veins and sinuses, and choroid plexus mixed with cerebrospinal fluid (CSF). The averaged rCBV, rCBF, and MTT ratios between GM and WM are in good agreement with those in the literature. Results from a patient with cerebral arteriovenous malformation (CAVM) showed distinct spatiotemporal characteristics between perfusion patterns, which allowed differentiation between pathological and nonpathological areas. PMID:17191233

Wu, Yu-Te; Chou, Yen-Chun; Guo, Wan-Yuo; Yeh, Tzu-Chen; Hsieh, Jen-Chuen

2007-01-01

347

Targeting the erythropoietin receptor on glioma cells reduces tumour growth  

SciTech Connect

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.

Peres, Elodie A.; Valable, Samuel [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France)] [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France); Guillamo, Jean-Sebastien [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France) [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France); Departement de Neurologie, CHU de Caen (France); Marteau, Lena [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France)] [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France); Bernaudin, Jean-Francois [Service d'Histologie-Biologie Tumorale, ER2UPMC, Universite Paris 6, Hopital Tenon, Paris (France)] [Service d'Histologie-Biologie Tumorale, ER2UPMC, Universite Paris 6, Hopital Tenon, Paris (France); Roussel, Simon [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France)] [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France); Lechapt-Zalcman, Emmanuele [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France) [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France); Service d'Anatomie Pathologique, CHU de Caen (France); Bernaudin, Myriam [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France)] [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France); Petit, Edwige, E-mail: epetit@cyceron.fr [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France)] [CERVOxy team 'Hypoxia and cerebrovascular pathophysiology', UMR 6232 CI-NAPS, Universite de Caen Basse-Normandie, Universite Paris-Descartes, CNRS, CEA. G.I.P. CYCERON, Caen (France)

2011-10-01

348

MGMT expression and pituitary tumours: relationship to tumour biology.  

PubMed

Over the past half decade, temozolomide, an oral akylating chemotherapeutic agent, has been shown to have significant activity in the management of aggressive pituitary tumours. The expression of 06-methylguanine-DNA methyltransferase (MGMT), a DNA repair enzyme, is an important predictor of response to therapy. Low MGMT expression has been reported with a higher frequency amongst more aggressive pituitary tumours, suggesting MGMT may play a role in pituitary tumour progression. In this study, we performed a microarray analysis to determine whether there was a distinct gene expression profile between tumours with low MGMT and high MGMT expression. Overall, 1,403 differentially expressed genes were identified with raw p values less than 0.05. Gene set enrichment analysis (GSEA) revealed significant differences in the gene expression profile between high and low MGMT expressing pituitary tumours. High MGMT expressing pituitary tumours were found to have upregulation of components of the FGFR family and downstream signaling cascades such as PI3 K/Akt and MAPK pathways. Activation of genes involved in the DNA damage response and DNA repair pathways, as well as genes involved in transcription, were identified in pituitary tumours with low MGMT expression. These results form the basis of our proposed model to describe the role of MGMT in pituitary tumorigenesis. PMID:22797801

McCormack, Ann; Kaplan, Warren; Gill, Anthony J; Little, Nicholas; Cook, Raymond; Robinson, Bruce; Clifton-Bligh, Roderick

2013-06-01

349

SKIN-TUMOUR CLASSIFICATION WITH FUNCTIONAL INFRARED IMAGING  

Microsoft Academic Search

The number of skin-cancer cases has dramatically increased during the last decades. Generally, an early diagnosis is the key for successful treatment. However, a first diagnosis is always done with Stolz's traditional (subjective) ABCD rule of dermatoscopy based on the four main criteria or lesion parameters: Asymmetry, Border, Colour and Diameter. Unfortunately, a sound decision if a skin tumor is

Thorsten M. Buzug; Steffen Schumann; Lucas Pfaffmann; Uwe Reinhold; Jürgen Ruhlmann

2006-01-01

350

'Tumour-induced osteomalacia'  

PubMed Central

A 60-year-old man presented 2 years before his diagnosis with long-standing muscle cramping, progressive generalised weakness and chronic hip pain. The patient was found to have bilateral femoral neck pathologic fractures therefore, underwent reamed intramedullary nailing of both femurs. Laboratory studies showed hypophosphataemia. Bone marrow biopsy was negative for malignancy. Positron emission tomography demonstrated fludeoxyglucose uptake only in the posterior neck. Bone scan showed innumerable foci of increased activity throughout the skeleton consistent with pseudofractures seen in osteomalacia. Fine needle aspiration from the mass in the neck revealed a phosphaturic mesenchymal tumour of mixed connective tissue type. Resection of the mass in the neck resulted in resolution of generalised complaints with no evidence of recurrence with a follow-up of 12 months.

Munoz, Javier; Michel Ortega, Rosa; Celzo, Florence; Donthireddy, Vijayalakshmi

2012-01-01

351

Recurrent hyperphosphatemic tumoural calcinosis.  

PubMed

Tumoural calcinosis (TC) is a benign gradually developing disorder that can occur in a variety of clinical settings, characterised by subcutaneous deposition of calcium phosphate with or without giant cell reaction. We describe a case of 11-year-old girl presenting with recurrent hard swellings in the vicinity of shoulder and hip joints associated with elevated serum phosphate and normal serum calcium levels. TC has been mainly reported from Africa, with very few cases reported from India. After the diagnosis of hyperphosphatemic TC was established, the patient was treated with oral sevelamer and is under constant follow-up to detect recurrence, if any. The present case highlights the fact that although an uncommon lesion, TC must be considered in the differential diagnosis of subcutaneous hard lump in the vicinity of a joint. PMID:23010461

Amit, Sonal; Agarwal, Asha; Nigam, Anand; Rao, Yashwant Kumar

2012-01-01

352

Form classification  

NASA Astrophysics Data System (ADS)

The problem of form classification is to assign a single-page form image to one of a set of predefined form types or classes. We classify the form images using low level pixel density information from the binary images of the documents. In this paper, we solve the form classification problem with a classifier based on the k-means algorithm, supported by adaptive boosting. Our classification method is tested on the NIST scanned tax forms data bases (special forms databases 2 and 6) which include machine-typed and handwritten documents. Our method improves the performance over published results on the same databases, while still using a simple set of image features.

Reddy, K. V. Umamaheswara; Govindaraju, Venu

2008-01-01

353

Classification Fun  

NSDL National Science Digital Library

Taxonomic information shows the evolutionary relationships between organisms. In this lesson plan, students will classify organisms by kingdom and apply their own understanding of classification to identify organisms. The students should already have an understanding of the basics of the five kindoms and the seven categories of classification. The document includes a pre-test on the topic to gauge student understanding and two classroom activities. The activity is intended for sixth grade students, and should take three to four class periods to complete.

Shubinski, Carol

2012-06-11

354

Isolated cerebellar tuberculoma mimicking posterior cranial fossa tumour.  

PubMed

Isolated central nervous system (CNS) tuberculoma is a rare disease. This disease is associated with high morbidity and mortality, despite modern methods of detection and treatment. CNS tuberculosis can present as meningitis, arachnoiditis, tuberculomas or the uncommon form of tuberculous subdural empyema and brain abscess. We present the clinical, radiological and pathological findings of cerebellar tuberculoma in an Iranian immunocompetent patient mimicking a malignant tumour. PMID:23966456

Binesh, Fariba; Zahir, Shokouh Taghipour; Bovanlu, Taghi Roshan

2013-01-01

355

CT appearances of pleural tumours.  

PubMed

Computed tomography (CT) is the imaging technique of choice for characterizing pleural masses with respect to their location, composition, and extent. CT also provides important information regarding invasion of the chest wall and surrounding structures. A spectrum of tumours can affect the pleura of which metastatic adenocarcinoma is the commonest cause of malignant pleural disease, while malignant mesothelioma is the most common primary pleural tumour. Certain CT features help differentiate benign from malignant processes. This pictorial review highlights the salient CT appearances of a range of tumours that may affect the pleura. PMID:19664483

Salahudeen, H M; Hoey, E T D; Robertson, R J; Darby, M J

2009-09-01

356

Low-level and high-level modulations of fixational saccades and high frequency oscillatory brain activity in a visual object classification task  

PubMed Central

Until recently induced gamma-band activity (GBA) was considered a neural marker of cortical object representation. However, induced GBA in the electroencephalogram (EEG) is susceptible to artifacts caused by miniature fixational saccades. Recent studies have demonstrated that fixational saccades also reflect high-level representational processes. Do high-level as opposed to low-level factors influence fixational saccades? What is the effect of these factors on artifact-free GBA? To investigate this, we conducted separate eye tracking and EEG experiments using identical designs. Participants classified line drawings as objects or non-objects. To introduce low-level differences, contours were defined along different directions in cardinal color space: S-cone-isolating, intermediate isoluminant, or a full-color stimulus, the latter containing an additional achromatic component. Prior to the classification task, object discrimination thresholds were measured and stimuli were scaled to matching suprathreshold levels for each participant. In both experiments, behavioral performance was best for full-color stimuli and worst for S-cone isolating stimuli. Saccade rates 200–700 ms after stimulus onset were modulated independently by low and high-level factors, being higher for full-color stimuli than for S-cone isolating stimuli and higher for objects. Low-amplitude evoked GBA and total GBA were observed in very few conditions, showing that paradigms with isoluminant stimuli may not be ideal for eliciting such responses. We conclude that cortical loops involved in the processing of objects are preferentially excited by stimuli that contain achromatic information. Their activation can lead to relatively early exploratory eye movements even for foveally-presented stimuli.

Kosilo, Maciej; Wuerger, Sophie M.; Craddock, Matt; Jennings, Ben J.; Hunt, Amelia R.; Martinovic, Jasna

2013-01-01

357

Image Classification  

NSDL National Science Digital Library

In this exercise, students get experience with image classification. Images are an increasingly important source of information about land cover and land use over time because comparisons of historic and current images can provide an estimate of change in the landscape.

Cote, Paul; Welch, Brian C.

2008-10-14

358

Classifying Classification  

ERIC Educational Resources Information Center

This article describes the experience of a group of first-grade teachers as they tackled the science process of classification, a targeted learning objective for the first grade. While the two-year process was not easy and required teachers to teach in a new, more investigation-oriented way, the benefits were great. The project helped teachers and…

Novakowski, Janice

2009-01-01

359

Orthotopic human melanoma xenograft model systems for studies of tumour angiogenesis, pathophysiology, treatment sensitivity and metastatic pattern.  

PubMed Central

Adequate tumour models are a prerequisite in experimental cancer research. The purpose of the present work was to establish and assess the validity of four new orthotopic human melanoma xenograft model systems (A-07, D-12, R-18, U-25). Permanent cell lines were established in monolayer culture from subcutaneous metastases of four different melanoma patients by using an in vivo-in vitro procedure, and cells from these lines were inoculated intradermally in Balb/c nu/nu mice to form tumours. Individual xenografted tumours of the same line differed substantially in growth and pathophysiological parameters, probably as a consequence of differences between inoculation sites in host factors which influence tumour angiogenesis. Nevertheless, xenografted tumours of different lines showed distinctly different biological characteristics. Several biological characteristics of the donor patients' tumours were retained in the xenografted tumours, including angiogenic potential; growth, histopathological and pathophysiological parameters; and sensitivity to radiation, heat and dacarbazine treatment. Moreover, the organ-specific metastatic pattern of the xenografted tumours reflected the pattern of distant metastases in the donor patients. The organs of preference for distant metastases were lungs (A-07, D-12), lymph nodes (R-18) and brain (U-25). R-18 lymph node metastases and U-25 brain metastases developed in the absence of lung involvement. The four orthotopic human melanoma xenograft model systems show great promise for future studies of tumour angiogenesis, pathophysiology, treatment sensitivity and metastatic pattern. Images Figure 1 Figure 4 Figure 5 Figure 7

Rofstad, E. K.

1994-01-01

360

Sampled sinusoidal stimulation profile and multichannel fuzzy logic classification for monitor-based phase-coded SSVEP brain-computer interfacing  

NASA Astrophysics Data System (ADS)

Objective. The performance and usability of brain-computer interfaces (BCIs) can be improved by new paradigms, stimulation methods, decoding strategies, sensor technology etc. In this study we introduce new stimulation and decoding methods for electroencephalogram (EEG)-based BCIs that have targets flickering at the same frequency but with different phases. Approach. The phase information is estimated from the EEG data, and used for target command decoding. All visual stimulation is done on a conventional (60-Hz) LCD screen. Instead of the ‘on/off’ visual stimulation, commonly used in phase-coded BCI, we propose one based on a sampled sinusoidal intensity profile. In order to fully exploit the circular nature of the evoked phase response, we introduce a filter feature selection procedure based on circular statistics and propose a fuzzy logic classifier designed to cope with circular information from multiple channels jointly. Main results. We show that the proposed visual stimulation enables us not only to encode more commands under the same conditions, but also to obtain EEG responses with a more stable phase. We also demonstrate that the proposed decoding approach outperforms existing ones, especially for the short time windows used. Significance. The work presented here shows how to overcome some of the limitations of screen-based visual stimulation. The superiority of the proposed decoding approach demonstrates the importance of preserving the circularity of the data during the decoding stage.

Manyakov, Nikolay V.; Chumerin, Nikolay; Robben, Arne; Combaz, Adrien; van Vliet, Marijn; Van Hulle, Marc M.

2013-06-01

361

The cytological diagnosis of paediatric renal tumours  

Microsoft Academic Search

Fine needle aspiration cytology (FNAC) is used for preoperative diagnosis of paediatric renal tumours, especially in centres where preoperative chemotherapy is advocated in Wilms’ tumour. This review focuses on salient cytological features in specific paediatric renal tumours, the approach to resolving a differential diagnosis and the role of ancillary methods in diagnosis of paediatric renal tumours. Crucial differential diagnoses include

T Shet; S Viswanathan

2009-01-01

362

The Role of Copper in Tumour Angiogenesis  

Microsoft Academic Search

Copper stimulates the proliferation and migration of endothelial cells and is required for the secretion of several angiogenic factors by tumour cells. Copper chelation decreases the secretion of many of these factors. Serum copper levels are upregulated in many human tumours and correlate with tumour burden and prognosis. Copper chelators reduce tumour growth and microvascular density in animal models. New

Sarah A. Lowndes; Adrian L. Harris

2005-01-01

363

Classification in Australia.  

National Technical Information Service (NTIS)

Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local need...

J. McKinlay

1980-01-01

364

Surgical management of adrenocortical tumours.  

PubMed

The surgical treatment of adrenal tumours has evolved over the past century, as has our understanding of which hormones are secreted by the adrenal glands and what these hormones do. This article reviews the preoperative evaluation of patients with adrenal tumours that could be benign or malignant, including metastases. The biochemical evaluation of excess levels of hormones is discussed, as are imaging characteristics that differentiate benign tumours from malignant tumours. The options for surgical management are outlined, including the advantages and disadvantages of various open and laparoscopic approaches. The surgical management of adrenocortical carcinoma is specifically reviewed, including controversies in operative approaches as well as surgical management of invasive or recurrent disease. PMID:24637859

Miller, Barbra S; Doherty, Gerard M

2014-05-01

365

Quantifying tumour heterogeneity with CT  

PubMed Central

Abstract Heterogeneity is a key feature of malignancy associated with adverse tumour biology. Quantifying heterogeneity could provide a useful non-invasive imaging biomarker. Heterogeneity on computed tomography (CT) can be quantified using texture analysis which extracts spatial information from CT images (unenhanced, contrast-enhanced and derived images such as CT perfusion) that may not be perceptible to the naked eye. The main components of texture analysis can be categorized into image transformation and quantification. Image transformation filters the conventional image into its basic components (spatial, frequency, etc.) to produce derived subimages. Texture quantification techniques include structural-, model- (fractal dimensions), statistical- and frequency-based methods. The underlying tumour biology that CT texture analysis may reflect includes (but is not limited to) tumour hypoxia and angiogenesis. Emerging studies show that CT texture analysis has the potential to be a useful adjunct in clinical oncologic imaging, providing important information about tumour characterization, prognosis and treatment prediction and response.

Miles, Kenneth A.

2013-01-01

366

Quantifying tumour heterogeneity with CT.  

PubMed

Heterogeneity is a key feature of malignancy associated with adverse tumour biology. Quantifying heterogeneity could provide a useful non-invasive imaging biomarker. Heterogeneity on computed tomography (CT) can be quantified using texture analysis which extracts spatial information from CT images (unenhanced, contrast-enhanced and derived images such as CT perfusion) that may not be perceptible to the naked eye. The main components of texture analysis can be categorized into image transformation and quantification. Image transformation filters the conventional image into its basic components (spatial, frequency, etc.) to produce derived subimages. Texture quantification techniques include structural-, model- (fractal dimensions), statistical- and frequency-based methods. The underlying tumour biology that CT texture analysis may reflect includes (but is not limited to) tumour hypoxia and angiogenesis. Emerging studies show that CT texture analysis has the potential to be a useful adjunct in clinical oncologic imaging, providing important information about tumour characterization, prognosis and treatment prediction and response. PMID:23545171

Ganeshan, Balaji; Miles, Kenneth A

2013-01-01

367

Imaging oxygenation of human tumours  

PubMed Central

Tumour hypoxia represents a significant challenge to the curability of human tumours leading to treatment resistance and enhanced tumour progression. Tumour hypoxia can be detected by non-invasive and invasive techniques but the inter-relationships between these remains largely undefined. 18F-MISO and Cu-ATSM-PET, and BOLD-MRI are the lead contenders for human application based on their non-invasive nature, ease of use and robustness, measurement of hypoxia status, validity, ability to demonstrate heterogeneity and general availability, these techniques are the primary focus of this review. We discuss where developments are required for hypoxia imaging to become clinically useful and explore potential new uses for hypoxia imaging techniques including biological conformal radiotherapy.

Krohn, Kenneth A.; Lewis, Jason S.; Alber, Markus

2006-01-01

368

Contemporary methods of therapy and follow-up of neuroendocrine tumours of the gastrointestinal tract and the pancreas  

PubMed Central

The growing interest in neuroendocrine tumours is due to the dynamic growth of detection of this type of cancer. Neuroendocrine tumours (neuroendocrine neoplasms – NENs / neuroendocrine tumours – NETs) derive from glands, groups of endocrine cells and diffuse neuroendocrine system cells. Mainly they derive from the gastrointestinal tract (gastroenteropancreatic-neuroendocrine tumours – GEP-NETs). Currently the modified WHO classification from 2010 is widely used. An important element in the choice of treatment is histological maturity based on mitotic activity and on assessment of proliferation activity (Ki-67). The treatment of choice is surgery. In most cases, complete surgical removal is impossible because of the advanced staging at the time of diagnosis. In well-differentiated neoplasms where the expression of somatostatin receptors is expected, patients are qualified for somatostatin analogues therapy. Poorly differentiated lesions are qualified for chemotherapy. In the guidelines of ENETS (European Neuroendocrine Tumor Society) from 2007 the rules concerning monitoring depending on the WHO classification were specified.

Fischbach, Jakub; Kaminski, Grzegorz; Ruchala, Marek

2012-01-01

369

The classification of lymphomas: a new beginning or the end of an era?  

Microsoft Academic Search

The World Health Organisation Classification of Tumours of the Haematopoietic and Lymphoid Tissues has recently been published. This is the latest in a long line of classifications of haematological malignancies and will be the international standard. It is now possible to achieve high levels of diagnostic accuracy for the main types of lymphoma. However, many of the entities encompass a

A. S. Jack; Algernon Firth

2003-01-01

370

New Ensemble Machine Learning Method for Classification and Prediction on Gene Expression Data  

Microsoft Academic Search

A reliable and precise classification of tumours is essential for successful treatment of cancer. Recent researches have confirmed the utility of ensemble machine learning algorithms for gene expression data analysis. In this paper, a new ensemble machine learning algorithm is proposed for classification and prediction on gene expression data. The algorithm is tested and compared with three popular adopted ensembles,

Ching Wei Wang

2006-01-01

371

Ablative therapy for liver tumours  

PubMed Central

Established ablative therapies for the treatment of primary and secondary liver tumours, including percutaneous ethanol injection, cryotherapy, and radiofrequency ablation, are discussed. Newer techniques such as magnetic resonance imaging guided laser interstitial thermal therapy of liver tumours has produced a median survival rate of 40.8 months after treatment. The merits of this newly emerging technique are discussed, together with future developments, such as focused ultrasound therapy, which holds the promise of non-invasive thermoablation treatment on an outpatient basis.

Dick, E A; Taylor-Robinson, S D; Thomas, H C; Gedroyc, W M W

2002-01-01

372

Desmoid tumour: a pleomorphic lesion  

Microsoft Academic Search

Background: Desmoid tumour (DT) is an uncommon locally invasive non-metastasizing neoplastic lesion. The aetiology of this tumour is unknown and its treatment is controversial. Twelve cases of DT are presented and the literature is reviewed. Methods: Twelve cases of DT treated at our institution during a 3.5-year period are analysed and the literature reviewed. Ten patients were referred with a

M. N. Kulaylat; C. P. Karakousis; C. M. Keaney; D. McCorvey; J. Bem

1999-01-01

373

The role of claudin-5 in blood-brain barrier (BBB) and brain metastases (review).  

PubMed

Metastatic brain tumours are frequently observed in patients with lung, breast and malignant melanoma and a severe complication of metastatic cancers. With improved primary cancer treatments, including surgery, radiation therapy and chemotherapy, patients are now living longer following initial treatment, compared with previous treatments. Brain metastasis (BM) remains a significant clinical issue. Since BM represents a major therapeutic challenge, it is vital that the mechanisms of interaction between tumour cells and the blood?brain barrier (BBB), as well as the method by which tumour cells establish metastatic tumours in the brain, are understood. A key step in BM is the interaction and penetration of the BBB by cancer cells. The BBB consists of endothelial cells, pericytes, astrocytes and a number of molecular structures between these cells. The BBB relies on the tight junctions (TJs) that are present between the endothelial cells of the brain capillaries to provide a closed environment for the brain. TJs comprise a number of proteins, including occludin, claudins and junctional adhesion molecules (JAMs). Among them, claudins are the key integral proteins that regulate BBB permeability. It has previously been shown that claudin?5, not only regulates paracellular ionic selectivity, but also plays a role in the regulation of tumour cell motility, suggesting that TJs and claudin?5 contribute to the control of BM. This study reviews the role of claudin?5 in the regulation of BBB permeability during the brain metastatic process. PMID:24366267

Jia, Wang; Lu, Runchun; Martin, Tracey A; Jiang, Wen G

2014-03-01

374

The tumour-associated carbonic anhydrases CA II, CA IX and CA XII in a group of medulloblastomas and supratentorial primitive neuroectodermal tumours: an association of CA IX with poor prognosis  

PubMed Central

Background Medulloblastomas (MBs) and supratentorial primitive neuroectodermal tumours (PNETs) are the most common highly aggressive paediatric brain tumours. In spite of extensive research on these tumours, there are only few known biomarkers or therapeutic target proteins, and the prognosis of patients with these tumours remains poor. Our aim was to investigate whether carbonic anhydrases (CAs), enzymes commonly overexpressed in various tumours including glioblastomas and oligodendrogliomas, are present in MBs and PNETs, and whether their expression can be correlated with patient prognosis. Methods We determined the expression of the tumour-associated carbonic anhydrases CA II, CA IX and CA XII in a series of MB/PNET specimens (n = 39) using immunohistochemistry. Results Endothelial CA II, cytoplasmic CA II, CA IX and CA XII were expressed in 49%, 73%, 23% and 11% of the tumours, respectively. CA II was detected in the neovessel endothelium and the tumour cell cytoplasm. CA IX was mainly expressed in the tumour cells located in perinecrotic areas. CA XII showed the most homogenous distribution within the tumours. Importantly, CA IX expression predicted poor prognosis in both univariate (p = 0.041) and multivariate analyses (p = 0.016). Conclusions We suggest that CA IX should be considered a potential prognostic and therapeutic target in MBs and PNETs.

2010-01-01

375

Classification of endometrial carcinoma: more than two types.  

PubMed

Endometrial cancer is the most common gynaecological malignancy in Europe and North America. Traditional classification of endometrial carcinoma is based either on clinical and endocrine features (eg, types I and II) or on histopathological characteristics (eg, endometrioid, serous, or clear-cell adenocarcinoma). Subtypes defined by the different classification systems correlate to some extent, but there is substantial heterogeneity in biological, pathological, and molecular features within tumour types from both classification systems. In this Review we provide an overview of traditional and newer genomic classifications of endometrial cancer. We discuss how a classification system that incorporates genomic and histopathological features to define biologically and clinically relevant subsets of the disease would be useful. Such integrated classification might facilitate development of treatments tailored to specific disease subgroups and could potentially enable delivery of precision medicine to patients with endometrial cancer. PMID:24872110

Murali, Rajmohan; Soslow, Robert A; Weigelt, Britta

2014-06-01

376

Giant phyllodes tumour of the breast.  

PubMed

Phyllodes tumours are fibroepithelial lesions and count for 0.4% of breast tumours. Telling the difference between phyllodes tumours and fibroadenomas is sometimes difficult but of importance because wide resection is the mainstay of treatment for phyllodes tumours. We present a female patient, 55 years old with a giant phyllodes tumour (38 x 31 x 23 cm) of the breast. The breast reconstruction was done using a pedicled transverse rectus abdominis myocutaneous (TRAM) flap. PMID:18042445

Walravens, C; De Greef, C

2008-10-01

377

[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

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. PMID:22279776

Grigor'ev, Iu G

2011-01-01

378

Novel somatic and germline mutations in intracranial germ cell tumours.  

PubMed

Intracranial germ cell tumours (IGCTs) are a group of rare heterogeneous brain tumours that are clinically and histologically similar to the more common gonadal GCTs. IGCTs show great variation in their geographical and gender distribution, histological composition and treatment outcomes. The incidence of IGCTs is historically five- to eightfold greater in Japan and other East Asian countries than in Western countries, with peak incidence near the time of puberty. About half of the tumours are located in the pineal region. The male-to-female incidence ratio is approximately 3-4:1 overall, but is even higher for tumours located in the pineal region. Owing to the scarcity of tumour specimens available for research, little is currently known about this rare disease. Here we report the analysis of 62 cases by next-generation sequencing, single nucleotide polymorphism array and expression array. We find the KIT/RAS signalling pathway frequently mutated in more than 50% of IGCTs, including novel recurrent somatic mutations in KIT, its downstream mediators KRAS and NRAS, and its negative regulator CBL. Novel somatic alterations in the AKT/mTOR pathway included copy number gains of the AKT1 locus at 14q32.33 in 19% of patients, with corresponding upregulation of AKT1 expression. We identified loss-of-function mutations in BCORL1, a transcriptional co-repressor and tumour suppressor. We report significant enrichment of novel and rare germline variants in JMJD1C, which codes for a histone demethylase and is a coactivator of the androgen receptor, among Japanese IGCT patients. This study establishes a molecular foundation for understanding the biology of IGCTs and suggests potentially promising therapeutic strategies focusing on the inhibition of KIT/RAS activation and the AKT1/mTOR pathway. PMID:24896186

Wang, Linghua; Yamaguchi, Shigeru; Burstein, Matthew D; Terashima, Keita; Chang, Kyle; Ng, Ho-Keung; Nakamura, Hideo; He, Zongxiao; Doddapaneni, Harshavardhan; Lewis, Lora; Wang, Mark; Suzuki, Tomonari; Nishikawa, Ryo; Natsume, Atsushi; Terasaka, Shunsuke; Dauser, Robert; Whitehead, William; Adekunle, Adesina; Sun, Jiayi; Qiao, Yi; Marth, Gábor; Muzny, Donna M; Gibbs, Richard A; Leal, Suzanne M; Wheeler, David A; Lau, Ching C

2014-07-10

379

Cellular automata coupled with steady-state nutrient solution permit simulation of large-scale growth of tumours.  

PubMed

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. PMID:23382053

Shrestha, Sachin Man Bajimaya; Joldes, Grand Roman; Wittek, Adam; Miller, Karol

2013-04-01

380

Triangle Classification  

NSDL National Science Digital Library

This geometry lesson from Illuminations presents the Triangle Classification problem. Students will attempt to classify the triangles formed in a plane when a randomly selected point is connected to the endpoints of a given line segment. Students should have access to a computer with internet access for the lesson. The material is intended for grades 9-12 and should require 1 class period to complete.

2010-12-29

381

Primate Classification  

NSDL National Science Digital Library

In this lesson students learn how classification of organisms is based on evolutionary relationships. They will also learn how primates are categorized, and how they are related. Students transfer examples (names) of primates from their location in an outline hierarchy of primate groups into a set of nested boxes reflecting that same hierarchy. A cladogram can then be drawn illustrating how these groups are related in an evolutionary way.

382

Genes that mediate breast cancer metastasis to the brain  

Microsoft Academic Search

The molecular basis for breast cancer metastasis to the brain is largely unknown. Brain relapse typically occurs years after the removal of a breast tumour, suggesting that disseminated cancer cells must acquire specialized functions to take over this organ. Here we show that breast cancer metastasis to the brain involves mediators of extravasation through non-fenestrated capillaries, complemented by specific enhancers

Paula D. Bos; Xiang H.-F. Zhang; Cristina Nadal; Weiping Shu; Roger R. Gomis; Don X. Nguyen; Andy J. Minn; Marc J. van de Vijver; William L. Gerald; John A. Foekens; Joan Massagué

2009-01-01

383

Reappraisal of the so-called 'villous tumours' of the rectosigmoid, based on histological, immunohistochemical and genotypic features  

PubMed Central

Background Villous tumours of the rectosigmoid are historically defined as broad-based lesions associated with secretory diarrhoea. Objective This study aimed to perform a reappraisal of these tumours, on the basis of newly introduced histological, immunohistochemical and molecular parameters. Methods For this study, 22 villous tumours, diagnosed by endoscopic criteria (19 Paris 0–IIa, three Paris 0–Is), were evaluated according to WHO classification. Microsatellite instability status, KRAS and BRAF mutations, MGMT status of villous tumours and associated invasive carcinoma were determined. Results The 22 villous tumours fell into four groups: 1) nine villous adenomas, 2) six tubulovillous adenomas, 3) three filiform traditional serrated adenomas, and 4) four traditional serrated adenomas with conventional dysplasia. Filiform serrated adenomas displayed a distinctive endoscopic protruding pattern (Paris 0-Is). Villous adenomas were strongly associated with secretory diarrhoea. All the villous tumours were microsatellite stable. Five tumours exhibited MGMT abnormalities. KRAS mutations were frequent in villous adenomas, whereas BRAF mutations were essentially detected in serrated lesions. Invasive carcinomas (n?=?7) maintained the histopathological and molecular imprint of the prior villous tumour. Conclusion The rectosigmoid villous tumours are histologically and molecularly heterogeneous, including serrated neoplasias. Endoscopic and clinical findings are predictive of the histopathological diagnosis of some of these distinct entities.

Kury, Sebastien; Coron, Emmanuel; Bezieau, Stephane; Laboisse, Christian L; Mosnier, Jean-Francois

2014-01-01

384

A model for intratumoural chemotherapy in the rat brain  

Microsoft Academic Search

Summary To achieve the best reproducibility in rat brain tumour models several injection techniques have been used. Although stereotactic cell injections have proved to be effective and reliable, they are expensive and time consuming. A new permanently implanted device is presented here. It allows precise cell delivery for best tumour reproducibility, and it can be left in place for future

M. Saini; F. Roser; M. Samii; M. Bellinzona

2004-01-01

385

A Cross-Sectional Survey of Prevalence of Odontogenic Tumours  

Microsoft Academic Search

Aim  To analyze the relative frequency of different types of odontogenic tumors based on the WHO 2005 histopathological classification\\u000a of odontogenic tumours and to compare the data with published literature.\\u000a \\u000a \\u000a \\u000a \\u000a Methods  Data collected from seven different hospitals in the same region of the city (south Chennai) were systematically searched\\u000a for all cases of odontogenic tumors operated on between the years 2005–2010. The

Vijay Ebenezer; Balakrishnan Ramalingam

2010-01-01

386

Drug-induced alterations in tumour perfusion yield increases in tumour cell radiosensitivity  

PubMed Central

The perfusion of human tumour xenografts was manipulated by administration of diltiazem and pentoxifylline, and the extent that observed changes in tumour perfusion altered tumour radiosensitivity was determined. 2 tumour systems having intrinsically different types of hypoxia were studied. The responses of SiHa tumours, which have essentially no transient hypoxia, were compared to the responses of WiDr tumours, which contain chronically and transiently hypoxic cells. We found that relatively modest increases in net tumour perfusion increased tumour cell radiosensitivity in WiDr tumours to a greater extent than in SiHa tumours. Moreover, redistribution of blood flow within WiDr tumours was observed on a micro-regional level that was largely independent of changes in net tumour perfusion. Through fluorescence-activated cell sorting coupled with an in vivo–in vitro cloning assay, increases in the radiosensitivity of WiDr tumour cells at intermediate levels of oxygenation were observed, consistent with the expectation that a redistribution of tumour blood flow had increased oxygen delivery to transiently hypoxic tumour cells. Our data therefore suggest that drug-induced changes in tumour micro-perfusion can alter the radiosensitivity of transiently hypoxic tumour cells, and that increasing the radiosensitivity of tumour cells at intermediate levels of oxygenation is therapeutically relevant. © 2001 Cancer Research Campaign ??http://www.bjcancer.com

Bennewith, K L; Durand, R E

2001-01-01

387

Constraint Classification for Multiclass Classification and Ranking  

Microsoft Academic Search

The constraint classification framework captures many flavors of mul- ticlass classification including winner-take-all multiclass classification, multilabel classification and ranking. We present a meta-algorithm for learning in this framework that learns via a single linear classifier in high dimension. We discuss distribution independent as well as margin-based generalization bounds and present empirical and theoretical evidence showing that constraint classification benefits over

Sariel Har-peled; Dan Roth; Dav Zimak

2002-01-01

388

Beach Classification  

NSDL National Science Digital Library

This activity provides students with an in-class practice of landscape interpretation using slides of beaches shown by the instructor. Students view a select number of slides and are asked to classify each beach shown using the Wright and Short Beach Classification: dissipative, reflexive, and intermediate by visually identifying landforms and processes of each beach type. The outcome of this activity is that students have practice identifying landforms and processes and applying their observations and interpretations of geomorphic features and processes for an applied purpose. Designed for a geomorphology course Has minimal/no quantitative component

Davis, Lisa

389

Genetic disparity between primary tumours, disseminated tumour cells, and manifest metastasis.  

PubMed

Recent genetic analyses of paired samples from primary tumours and disseminated tumour cells have uncovered a bewildering genetic disparity. It was therefore proposed that ectopically residing tumour cells disseminate early and develop independently into metastases parallel to the primary tumour. Alternatively, these cells may represent an irrelevant cell population unable to spawn metastases whereas only cells that disseminated late in primary tumour development (which therefore are similar to the primary tumour) will form manifest metastasis. Here, we review comparative analyses of paired samples from primary tumours and disseminated tumour cells or primary tumours and metastases. The data demonstrate a striking disparity, questioning the use of primary tumours as surrogate for the genetics of systemic cancer. In the era of molecular therapies that build upon genetic defects of tumour cells, these data call for a direct diagnostic pathology of systemic cancer. PMID:19795462

Stoecklein, Nikolas H; Klein, Christoph A

2010-02-01

390

Solid pseudopapillary tumour of pancreas.  

PubMed

Solid pseudopapillary tumour of pancreas (SPT) is an extremely rare pancreatic tumour, which has a low malignant potential and occurs mainly in young women. Pathologic and imaging findings include a well defined encapsulated pancreatic mass with cystic and solid components with evidence of haemorrhage. This is a case of a 16 years old girl who presented with upper abdominal pain of long duration and epigastric mass on palpation. Computed Tomography (CT) scan demonstrated a large well defined heterogenous attenuation mass of solid enhancing and cystic non enhancing areas, arising from the head of the pancreas. Radiologically it was diagnosed as a case of pancreatic neoplasm. Fine needle aspiration cytology (FNAC) and histopathology of the biopsy material diagnosed as solid pseudopapillary tumour of pancreas. PMID:24858174

Bose, B; Majumder, S; Khan, A U

2014-04-01

391

Lymphocytic tumours of the conjunctiva  

PubMed Central

Twenty-six cases of lymphocytic tumour of the conjunctiva, which were originally classified as benign lymphoma and lymphosarcoma, were followed up for more than five years, They were then reclassified into non-disseminating and disseminating groups. Only when germinal follicles are present can a histological diagnosis of benign lymphoma be made. Moreover, it is only when lymphoblasts are seen to be infiltrating the tissues that a definitive diagnosis of lymphosarcoma can be made. The remaining tumours, which represent the large majority of lesions, show a very similar or identical histological picture, and a diagnosis of benignity or malignancy can only be made after a prolonged follow up. The possible nature of the non-disseminating lymphocytic tumours is briefly discussed. Images

Morgan, Gwyn

1971-01-01

392

Classification in Australia.  

ERIC Educational Resources Information Center

Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

McKinlay, John

393

Fluorescence-guided surgical sampling of glioblastoma identifies phenotypically distinct tumour-initiating cell populations in the tumour mass and margin  

PubMed Central

Background: Acquiring clinically annotated, spatially stratified tissue samples from human glioblastoma (GBM) is compromised by haemorrhage, brain shift and subjective identification of ‘normal' brain. We tested the use of 5-aminolevulinic acid (5-ALA) fluorescence to objective tissue sampling and to derive tumour-initiating cells (TICs) from mass and margin. Methods: The 5-ALA was administered to 30 GBM patients. Samples were taken from the non-fluorescent necrotic core, fluorescent tumour mass and non-fluorescent margin. We compared the efficiency of isolating TICs from these areas in 5-ALA versus control patients. HRMAS 1H NMR was used to reveal metabolic alterations due to 5-ALA. We then characterised TICs for self-renewal in vitro and tumorigenicity in vivo. Results: The derivation of TICs was not compromised by 5-ALA and the metabolic profile was similar between tumours from 5-ALA patients and controls. The TICs from the fluorescent mass were self-renewing in vitro and tumour-forming in vivo, whereas TICs from non-fluorescent margin did not self-renew in vitro but did form tumours in vivo. Conclusion: Our data show that 5-ALA does not compromise the derivation of TICs. It also reveals that the margin contains TICs, which are phenotypically different from those isolated from the corresponding mass.

Piccirillo, S G M; Dietz, S; Madhu, B; Griffiths, J; Price, S J; Collins, V P; Watts, C

2012-01-01

394