[Awake craniotomy for brain tumours].

PubMed

Milos, Peter; Metcalf, Kerstin; Vigren, Patrick; Lindehammar, Hans; Nilsson, Malin; Boström, Sverre

2016-10-11

Awake craniotomy for brain tumours  Awake neurosurgery is a useful method in lesions near eloquent brain areas, particularly low-grade gliomas.The aim is to maximise tumour resection and preserve neurological function. We performed 40 primary awake surgeries and 8 residual surgeries. Patients were operated awake throughout the procedure or with a laryngeal mask and general anaesthesia during the opening stage and then awake during intracerebral surgery. Language and motor function were mapped with direct cortical stimulation, motor evoked potential and standardised neurological testing. Radiologically, complete resection was achieved in 18 out of 40 patients in the primary surgeries. Full neurological recovery at three months was observed in 29 patients. Of the 11 patients with persisting neurological deficits at three months, symptoms were present preoperatively in 9 patients. We conclude that awake surgery, combined with intraoperative neurophysiological methods, is a safe method to improve treatment for low-grade gliomas.

Objectivity in the classification of tumours of the nasal epithelium

PubMed Central

Michaels, L.; Hyams, V. J.

1975-01-01

A survey of tumours derived from each of the four cell types of nasal epithelium is presented. Criticism is levelled at the adoption of additional terms for tissue types such as lympho-epithelium and transitional cell epithelium and tumours said to be derived from them. Electron microscopy is of assistance in classification particularly in the detection of evidence of keratin synthesis. The proposed classification of tumours of the nasal epithelium is: (1) Pseudostratified columnar epithelium: (a) papillary adenoma, (b) papillary carcinoma. (2) Squamous epithelium: (a) everted squamous papilloma, (b) inverted papilloma, (c) squamous carcinoma of any grade of differentiation from well differentiated to undifferentiated. (3) Melanocyte: malignant melanoma. (4) Olfactory neuroepithelium: olfactory neuroblastoma. ImagesFig. 1Fig. 2Fig. 3Fig. 4Fig. 5Fig. 6Fig. 7Fig. 8Fig. 9Fig. 10Fig. 11Fig. 12Fig. 13Fig. 14Fig. 15Fig. 16Fig. 17Fig. 18Fig. 19Fig. 21Fig. 20 PMID:1197175

DNA methylation-based classification of central nervous system tumours.

PubMed

Capper, David; Jones, David T W; Sill, Martin; Hovestadt, Volker; Schrimpf, Daniel; Sturm, Dominik; Koelsche, Christian; Sahm, Felix; Chavez, Lukas; Reuss, David E; Kratz, Annekathrin; Wefers, Annika K; Huang, Kristin; Pajtler, Kristian W; Schweizer, Leonille; Stichel, Damian; Olar, Adriana; Engel, Nils W; Lindenberg, Kerstin; Harter, Patrick N; Braczynski, Anne K; Plate, Karl H; Dohmen, Hildegard; Garvalov, Boyan K; Coras, Roland; Hölsken, Annett; Hewer, Ekkehard; Bewerunge-Hudler, Melanie; Schick, Matthias; Fischer, Roger; Beschorner, Rudi; Schittenhelm, Jens; Staszewski, Ori; Wani, Khalida; Varlet, Pascale; Pages, Melanie; Temming, Petra; Lohmann, Dietmar; Selt, Florian; Witt, Hendrik; Milde, Till; Witt, Olaf; Aronica, Eleonora; Giangaspero, Felice; Rushing, Elisabeth; Scheurlen, Wolfram; Geisenberger, Christoph; Rodriguez, Fausto J; Becker, Albert; Preusser, Matthias; Haberler, Christine; Bjerkvig, Rolf; Cryan, Jane; Farrell, Michael; Deckert, Martina; Hench, Jürgen; Frank, Stephan; Serrano, Jonathan; Kannan, Kasthuri; Tsirigos, Aristotelis; Brück, Wolfgang; Hofer, Silvia; Brehmer, Stefanie; Seiz-Rosenhagen, Marcel; Hänggi, Daniel; Hans, Volkmar; Rozsnoki, Stephanie; Hansford, Jordan R; Kohlhof, Patricia; Kristensen, Bjarne W; Lechner, Matt; Lopes, Beatriz; Mawrin, Christian; Ketter, Ralf; Kulozik, Andreas; Khatib, Ziad; Heppner, Frank; Koch, Arend; Jouvet, Anne; Keohane, Catherine; Mühleisen, Helmut; Mueller, Wolf; Pohl, Ute; Prinz, Marco; Benner, Axel; Zapatka, Marc; Gottardo, Nicholas G; Driever, Pablo Hernáiz; Kramm, Christof M; Müller, Hermann L; Rutkowski, Stefan; von Hoff, Katja; Frühwald, Michael C; Gnekow, Astrid; Fleischhack, Gudrun; Tippelt, Stephan; Calaminus, Gabriele; Monoranu, Camelia-Maria; Perry, Arie; Jones, Chris; Jacques, Thomas S; Radlwimmer, Bernhard; Gessi, Marco; Pietsch, Torsten; Schramm, Johannes; Schackert, Gabriele; Westphal, Manfred; Reifenberger, Guido; Wesseling, Pieter; Weller, Michael; Collins, Vincent Peter; Blümcke, Ingmar; Bendszus, Martin; Debus, Jürgen; Huang, Annie; Jabado, Nada; Northcott, Paul A; Paulus, Werner; Gajjar, Amar; Robinson, Giles W; Taylor, Michael D; Jaunmuktane, Zane; Ryzhova, Marina; Platten, Michael; Unterberg, Andreas; Wick, Wolfgang; Karajannis, Matthias A; Mittelbronn, Michel; Acker, Till; Hartmann, Christian; Aldape, Kenneth; Schüller, Ulrich; Buslei, Rolf; Lichter, Peter; Kool, Marcel; Herold-Mende, Christel; Ellison, David W; Hasselblatt, Martin; Snuderl, Matija; Brandner, Sebastian; Korshunov, Andrey; von Deimling, Andreas; Pfister, Stefan M

2018-03-22

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

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

PubMed

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

2013-01-01

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

Endometrial stromal tumours revisited: an update based on the 2014 WHO classification.

PubMed

Ali, Rola H; Rouzbahman, Marjan

2015-05-01

Endometrial stromal tumours (EST) are rare tumours of endometrial stromal origin that account for less than 2% of all uterine tumours. Recent cytogenetic and molecular advances in this area have improved our understanding of ESTs and helped refine their classification into more meaningful categories. Accordingly, the newly released 2014 WHO classification system recognises four categories: endometrial stromal nodule (ESN), low-grade endometrial stromal sarcoma (LGESS), high-grade endometrial stromal sarcoma (HGESS) and undifferentiated uterine sarcoma (UUS). At the molecular level, these tumours may demonstrate a relatively simple karyotype with a defining chromosomal rearrangement (as in the majority of ESNs, LGESSs and YWHAE-rearranged HGESS) or demonstrate complex cytogenetic aberrations lacking specific rearrangements (as in UUSs). Herein we provide an update on this topic aimed at the practicing pathologist. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Current approaches to the treatment of metastatic brain tumours

PubMed Central

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

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. PMID:24569448

Assessment of a brain-tumour-specific Patient Concerns Inventory in the neuro-oncology clinic.

PubMed

Rooney, Alasdair G; Netten, Anouk; McNamara, Shanne; Erridge, Sara; Peoples, Sharon; Whittle, Ian; Hacking, Belinda; Grant, Robin

2014-04-01

Brain tumour patients may struggle to express their concerns in the outpatient clinic, creating a physician-focused rather than a shared agenda. We created a simple, practical brain-tumour-specific holistic needs assessment (HNA) tool for use in the neuro-oncology outpatient clinic. We posted the brain tumour Patient Concerns Inventory (PCI) to a consecutive sample of adult brain tumour attendees to a neuro-oncology outpatient clinic. Participants brought the completed PCI to their clinic consultation. Patients and staff provided feedback. Seventy seven patients were eligible and 53 participated (response rate = 68%). The PCI captured many problems absent from general cancer checklists. The five most frequent concerns were fatigue, fear of tumour coming back, memory, concentration, and low mood. Respondents used the PCI to formulate 105 specific questions, usually about the meaning of physical or psychological symptoms. Patients and staff found the PCI to be useful, and satisfaction with the instrument was high. This study demonstrates the clinical utility of the brain tumour PCI in a neuro-oncology clinic. The combination of a brain-tumour-specific concerns checklist and an intervention to focus patient agenda creates a simple and efficient HNA tool.

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

PubMed

Soltaninejad, Mohammadreza; Yang, Guang; Lambrou, Tryphon; Allinson, Nigel; Jones, Timothy L; Barrick, Thomas R; Howe, Franklyn A; Ye, Xujiong

2018-04-01

Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management. Copyright © 2018 Elsevier B.V. All rights reserved.

Phase congruency map driven brain tumour segmentation

NASA Astrophysics Data System (ADS)

Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

2015-03-01

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

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

PubMed Central

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

2000-01-01

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

 PMID:10990503

Role of intraoperative ultrasound in achieving complete resection of intra-axial solid brain tumours.

PubMed

Mari, Abdul Razaque; Shah, Irfanullah; Imran, Muhammed; Ashraf, Junaid

2014-12-01

To determine the frequency of completeness of resection for intra-axial solid brain tumours with the help of intra-operative ultrasound to detect residual brain tumour. The cross-sectional study was conducted at the Department of Neurosurgery, Dow University of Health Sciences and Civil Hospital Karachi, from September 2009 to June 2010 and comprised patients with intra-axial solid brain lesion. During operation following standard craniotomy, multi-plane sonographic examination was performed using intra-operative ultrasound for tumour localisation and calculation of dimension, followed by tumour resection in the standard fashion. At the end of tumour resection ultrasound was again used for the detection of any residual tumour. Results of intra-operative ultrasound were compared with post-operative contrast magnetic resonance imaging. Of the 39 cases in which intra-operative ultrasound was performed, 32(82.1%) were males and 7(17.9%) were females, with an overall mean age of 42.6±19.7 years. Intra-operative ultrasonography was able to localise and delineate the tumour in all 39 (100%) cases. It showed no residual tumour in 36 (92.3%) cases, but in 3(7.7%) cases residual tumour was detected. Post-operative contrast enhancing magnetic resonance imaging showed no residual tumour in 35(89.7%) cases and in 4(10.3%) cases residual tumour was detected. The frequency of completely resected intra-axial solid brain tumour was 35(89.7%), while in 4(10.3%) cases incomplete resection was observed. The study concluded that intra-operative ultrasonography has an important role in achieving increased frequency of completely resected intra-axial solid brain tumours.

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

PubMed

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

2016-05-31

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

Targeting breast to brain metastatic tumours with death receptor ligand expressing therapeutic stem cells

PubMed Central

Bagci-Onder, Tugba; Du, Wanlu; Figueiredo, Jose-Luiz; Martinez-Quintanilla, Jordi

2015-01-01

Characterizing clinically relevant brain metastasis models and assessing the therapeutic efficacy in such models are fundamental for the development of novel therapies for metastatic brain cancers. In this study, we have developed an in vivo imageable breast-to-brain metastasis mouse model. Using real time in vivo imaging and subsequent composite fluorescence imaging, we show a widespread distribution of micro- and macro-metastasis in different stages of metastatic progression. We also show extravasation of tumour cells and the close association of tumour cells with blood vessels in the brain thus mimicking the multi-foci metastases observed in the clinics. Next, we explored the ability of engineered adult stem cells to track metastatic deposits in this model and show that engineered stem cells either implanted or injected via circulation efficiently home to metastatic tumour deposits in the brain. Based on the recent findings that metastatic tumour cells adopt unique mechanisms of evading apoptosis to successfully colonize in the brain, we reasoned that TNF receptor superfamily member 10A/10B apoptosis-inducing ligand (TRAIL) based pro-apoptotic therapies that induce death receptor signalling within the metastatic tumour cells might be a favourable therapeutic approach. We engineered stem cells to express a tumour selective, potent and secretable variant of a TRAIL, S-TRAIL, and show that these cells significantly suppressed metastatic tumour growth and prolonged the survival of mice bearing metastatic breast tumours. Furthermore, the incorporation of pro-drug converting enzyme, herpes simplex virus thymidine kinase, into therapeutic S-TRAIL secreting stem cells allowed their eradication post-tumour treatment. These studies are the first of their kind that provide insight into targeting brain metastasis with stem-cell mediated delivery of pro-apoptotic ligands and have important clinical implications. PMID:25910782

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

PubMed Central

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

2016-01-01

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

Long-term exposure to ambient air pollution and incidence of brain tumours: The Danish Nurse Cohort.

PubMed

Jørgensen, Jeanette Therming; Johansen, Martin Søes; Ravnskjær, Line; Andersen, Klaus Kaae; Bräuner, Elvira Vaclavik; Loft, Steffen; Ketzel, Matthias; Becker, Thomas; Brandt, Jørgen; Hertel, Ole; Andersen, Zorana Jovanovic

2016-07-01

Air pollution has been considered a potent environmental risk factor for neuropathology through neuroinflammation and oxidative stress, which might also cause brain tumour formation. However, epidemiological evidence on the association between air pollution and brain tumours in humans is sparse, with no data on exposure to particles. In this study we aim to examine associations between long-term exposure to ambient air pollution and risk for development of brain tumours. We used the Danish Nurse Cohort with 28,731 female nurses (age≥44years) recruited in 1993 or 1999 when self-reported information on lifestyle was collected. We obtained data on the incidence of brain tumours until 2013 from the Danish Cancer Register, and estimated annual mean concentrations of particulate matter with diameter<2.5μm (PM2.5), particulate matter with diameter<10μm (PM10), nitrogen oxides (NOx) and nitrogen dioxide (NO2) at the residence since 1990 using an atmospheric integrated chemistry-transport models system, and examined the association between the 3-year running mean of pollutants and brain tumour incidence using time-varying Cox regression, separately for total brain tumours, and for tumour subtypes by location (brain or meninges), and by malignancy (malignant or benign), and estimated hazard ratios and 95% confidence intervals per increase in interquartile range of exposure. Of 25,143 tumour-free nurses at recruitment, 121 developed brain cancer during 15.7 years of follow-up. We found a weak positive association between total brain tumours and PM2.5 (1.06; 0.80-1.40 per 3.37μg/m(3)), NO2 (1.09; 0.91-1.29) per 7.5μg/m(3), and NOx (1.02; 0.93-1.12 per 10.22μg/m(3)), and none with PM10 (0.93; 0.70-1.23 per 3.31μg/m(3)). Associations with PM2.5 and NO2 were stronger for tumours located in meninges than in brain, and for benign than for malignant tumours. Finally, association of total brain tumours with PM2.5 was modified by BMI, and was statistically significantly

Brain tumours and exposure to pesticides: a case–control study in southwestern France

PubMed Central

Provost, Dorothée; Cantagrel, Anne; Lebailly, Pierre; Jaffré, Anne; Loyant, Véronique; Loiseau, Hugues; Vital, Anne; Brochard, Patrick; Baldi, Isabelle

2007-01-01

Background Brain tumours are often disabling and rapidly lethal; their aetiology is largely unknown. Among potential risk factors, pesticides are suspected. Objective To examine the relationship between exposure to pesticides and brain tumours in adults in a population‐based case–control study in southwestern France. Methods Between May 1999 and April 2001, 221 incident cases of brain tumours and 442 individually matched controls selected from the general population were enrolled. Histories of occupational and environmental exposures, medical and lifestyle information were collected. A cumulative index of occupational exposure to pesticides was created, based on expert review of lifelong jobs and tasks. Separate analyses were performed for gliomas and meningiomas. Results A non‐statistically significant increase in risk was found for brain tumours when all types of occupational exposure to pesticides were considered (OR = 1.29, 95% CI 0.87 to 1.91) and slightly higher but still non‐statistically significant when gliomas were considered separately (OR = 1.47, 95% CI 0.81 to 2.66). In the highest quartile of the cumulative index, a significant association was found for brain tumours (OR = 2.16, 95% CI 1.10 to 4.23) and for gliomas (OR = 3.21, 95% CI 1.13 to 9.11), but not for meningiomas. A significant increase in risk was also seen for the treatment of home plants (OR = 2.24, 95% CI 1.16 to 4.30) owing to environmental exposure to pesticides. Conclusions These data suggest that a high level of occupational exposure to pesticides might be associated with an excess risk of brain tumours, and especially of gliomas. PMID:17537748

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

PubMed Central

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

2013-01-01

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

The developmental origin of brain tumours: a cellular and molecular framework.

PubMed

Azzarelli, Roberta; Simons, Benjamin D; Philpott, Anna

2018-05-14

The development of the nervous system relies on the coordinated regulation of stem cell self-renewal and differentiation. The discovery that brain tumours contain a subpopulation of cells with stem/progenitor characteristics that are capable of sustaining tumour growth has emphasized the importance of understanding the cellular dynamics and the molecular pathways regulating neural stem cell behaviour. By focusing on recent work on glioma and medulloblastoma, we review how lineage tracing contributed to dissecting the embryonic origin of brain tumours and how lineage-specific mechanisms that regulate stem cell behaviour in the embryo may be subverted in cancer to achieve uncontrolled proliferation and suppression of differentiation. © 2018. Published by The Company of Biologists Ltd.

Predicting parenting stress in caregivers of children with brain tumours.

PubMed

Bennett, Emily; English, Martin William; Rennoldson, Michael; Starza-Smith, Arleta

2013-03-01

The purpose of the study was to identify factors that contribute to parenting stress in caregivers of children diagnosed with brain tumours. The study was cross-sectional and recruited 37 participants from a clinical database at a specialist children's hospital. Parents were sent questionnaires, which were used to measure factors related to stress in caregivers of children diagnosed with a brain tumour. Stress levels were measured using the Parenting Stress Index-Short Form (PSI/SF). Correlation analysis and multiple linear regression were used to examine the associations between parenting stress and coping styles, locus of control, parent-perceived child disability and time since diagnosis. Results revealed that 51% of parents were experiencing clinically significant levels of stress. The mean stress level of parents in the study was significantly higher than the PSI/SF norms (t = 4.7, p < .001). Regression analysis revealed that external locus of control and coping by accepting responsibility accounted for 67% of the variance in parenting stress. Other styles of coping, child behaviour problems and the amount of time since diagnosis were not found to be predictive of levels of parenting stress. There was a high prevalence of parenting stress in caregivers of children with a brain tumour. An external locus of control and coping by accepting responsibility increased the likelihood of elevated levels of stress. Results emphasised the importance of ongoing support for parents of children with brain tumours. Intervention might helpfully be centred on strategies to increase parents' internal locus of control. Copyright © 2012 John Wiley & Sons, Ltd.

Further aspects on cellular and cordless telephones and brain tumours.

PubMed

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

2003-02-01

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

Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification.

PubMed

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

2015-01-01

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

Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

PubMed Central

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

2015-01-01

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

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

PubMed

de Ridder, L

1999-01-01

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

Brain tumour stem cells: implications for cancer therapy and regenerative medicine.

PubMed

Sanchez-Martin, Manuel

2008-09-01

The cancer relapse and mortality rate suggest that current therapies do not eradicate all malignant cells. Currently, it is accepted that tumorigenesis and organogenesis are similar in many respects, as for example, homeostasis is governed by a distinct sub-population of stem cells in both situations. There is increasing evidence that many types of cancer contain their own stem cells: cancer stem cells (CSC), which are characterized by their self-renewing capacity and differentiation ability. The investigation of solid tumour stem cells has gained momentum particularly in the area of brain tumours. Gliomas are the most common type of primary brain tumours. Nearly two-thirds of gliomas are highly malignant lesions with fast progression and unfortunate prognosis. Despite recent advances, two-year survival for glioblastoma (GBM) with optimal therapy is less than 30%. Even among patients with low-grade gliomas that confer a relatively good prognosis, treatment is almost never curative. Recent studies have demonstrated the existence of a small fraction of glioma cells endowed with features of primitive neural progenitor cells and a tumour-initiating function. In general, this fraction is characterized for forming neurospheres, being endowed with drug resistance properties and often, we can isolate some of them using sorting methods with specific antibodies. The molecular characterization of these stem populations will be critical to developing an effective therapy for these tumours with very dismal prognosis. To achieve this aim, the development of a mouse model which recapitulates the nature of these tumours is essential. This review will focus on glioma stem cell knowledge and discuss future implications in brain cancer therapy and regenerative medicine.

Depression in adult patients with primary brain tumours: a review of independent risk factors.

PubMed

Pidani, Anum Sadruddin; Rao, Aaida Mumtaz; Shamim, Muhammad Shahzad

2018-04-01

Depression is considered an under-diagnosed problem, especially in patients with malignancies. Patients with brain tumours in particular, have a relatively higher risk of developing depression, which is multifactorial. Herein, the authors review the recent literature on the prevalence of depression in patients with brain tumours, and explore the various risk factors involved. .

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

PubMed

Hardell, Lennart; Carlberg, Michael

2009-07-01

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

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

PubMed

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

2017-02-01

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

Three validation metrics for automated probabilistic image segmentation of brain tumours

PubMed Central

Zou, Kelly H.; Wells, William M.; Kikinis, Ron; Warfield, Simon K.

2005-01-01

SUMMARY The validity of brain tumour segmentation is an important issue in image processing because it has a direct impact on surgical planning. We examined the segmentation accuracy based on three two-sample validation metrics against the estimated composite latent gold standard, which was derived from several experts’ manual segmentations by an EM algorithm. The distribution functions of the tumour and control pixel data were parametrically assumed to be a mixture of two beta distributions with different shape parameters. We estimated the corresponding receiver operating characteristic curve, Dice similarity coefficient, and mutual information, over all possible decision thresholds. Based on each validation metric, an optimal threshold was then computed via maximization. We illustrated these methods on MR imaging data from nine brain tumour cases of three different tumour types, each consisting of a large number of pixels. The automated segmentation yielded satisfactory accuracy with varied optimal thresholds. The performances of these validation metrics were also investigated via Monte Carlo simulation. Extensions of incorporating spatial correlation structures using a Markov random field model were considered. PMID:15083482

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

A qualitative assessment of the supportive care and resource needs of patients undergoing craniotomy for benign brain tumours.

PubMed

Wong, Janice; Mendelsohn, Daniel; Nyhof-Young, Joyce; Bernstein, Mark

2011-11-01

As past literature has focused on support needs of patients with malignant brain tumours, the support needs of patients with benign brain tumours have largely been overlooked. The purpose of this study was to evaluate the supportive care and resource needs of patients undergoing craniotomy for benign brain tumours. Individual, semi-structured interviews were conducted with patients who had undergone craniotomy for a benign brain tumour within the past 2 years. Interviews were audio-recorded, transcribed, anonymized and subjected to descriptive thematic analysis by multiple investigators in the grounded theory tradition. Twenty-nine patients (20 women, 20-88 years of age) with World Health Organization grade I brain tumours (25 meningioma) were interviewed. Five overarching themes emerged: (1) need for formal support from diagnosis onwards; (2) complexity of supportive needs during postoperative recovery; (3) importance of regular long-term monitoring by physicians; (4) influence of psychosocial factors on supportive needs; and (5) existence of barriers to equal access to available supports. Patients' supportive care needs are temporally dependent on disease course and treatment, and modifiable by demographic and psychosocial factors. Findings of this study show that patients with benign tumours lacked but needed many supportive care resources currently available to cancer patients. Many of the potential solutions to this current gap in supportive care involve extending support resources already available for cancer patients to patients with benign brain tumours. We thus suggest recommendations to improve service gaps and reduce disparities in supportive care for patients with benign brain tumours.

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

PubMed Central

2012-01-01

The first case–control study on mobile phone use and brain tumour risk among children and adolescents (CEFALO study) has recently been published. In a commentary published in Environmental Health, Söderqvist and colleagues argued that CEFALO suggests an increased brain tumour risk in relation to wireless phone use. In this article, we respond and show why consistency checks of case–control study results with observed time trends of incidence rates are essential, given the well described limitations of case–control studies and the steep increase of mobile phone use among children and adolescents during the last decade. There is no plausible explanation of how a notably increased risk from use of wireless phones would correspond to the relatively stable incidence time trends for brain tumours among children and adolescents observed in the Nordic countries. Nevertheless, an increased risk restricted to heavy mobile phone use, to very early life exposure, or to rare subtypes of brain tumours may be compatible with stable incidence trends at this time and thus further monitoring of childhood brain tumour incidence rate time trends is warranted. PMID:22607537

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

PubMed

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

2012-05-20

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

Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

PubMed

Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

2018-06-01

There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

Medical exposure to ionising radiation and the risk of brain tumours: Interphone study group, Germany.

PubMed

Blettner, Maria; Schlehofer, Brigitte; Samkange-Zeeb, Florence; Berg, Gabriele; Schlaefer, Klaus; Schüz, Joachim

2007-09-01

The role of exposure to low doses of ionising radiation in the aetiology of brain tumours has yet to be clarified. The objective of this study was to investigate the association between medically or occupationally related exposure to ionising radiation and brain tumours. We used self-reported medical and occupational data collected during the German part of a multinational case-control study on mobile phone use and the risk of brain tumours (Interphone study) for the analyses. For any exposure to medical ionising radiation we found odds ratios (ORs) of 0.63 (95% confidence interval (CI)=0.48-0.83), 1.08 (95% CI=0.80-1.45) and 0.97 (95% CI=0.54-1.75) for glioma, meningioma and acoustic neuroma, respectively. Elevated ORs were found for meningioma (OR 2.32, 95% CI: 0.90-5.96) and acoustic neuroma (OR 6.45, 95% CI: 0.62-67.16) for radiotherapy to the head and neck regions. We did not find any significant increased risk of brain tumours for exposure to medical ionising radiation.

A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread.

PubMed

Swan, Amanda; Hillen, Thomas; Bowman, John C; Murtha, Albert D

2018-05-01

Gliomas are primary brain tumours arising from the glial cells of the nervous system. The diffuse nature of spread, coupled with proximity to critical brain structures, makes treatment a challenge. Pathological analysis confirms that the extent of glioma spread exceeds the extent of the grossly visible mass, seen on conventional magnetic resonance imaging (MRI) scans. Gliomas show faster spread along white matter tracts than in grey matter, leading to irregular patterns of spread. We propose a mathematical model based on Diffusion Tensor Imaging, a new MRI imaging technique that offers a methodology to delineate the major white matter tracts in the brain. We apply the anisotropic diffusion model of Painter and Hillen (J Thoer Biol 323:25-39, 2013) to data from 10 patients with gliomas. Moreover, we compare the anisotropic model to the state-of-the-art Proliferation-Infiltration (PI) model of Swanson et al. (Cell Prolif 33:317-329, 2000). We find that the anisotropic model offers a slight improvement over the standard PI model. For tumours with low anisotropy, the predictions of the two models are virtually identical, but for patients whose tumours show higher anisotropy, the results differ. We also suggest using the data from the contralateral hemisphere to further improve the model fit. Finally, we discuss the potential use of this model in clinical treatment planning.

Active video gaming improves body coordination in survivors of childhood brain tumours.

PubMed

Sabel, Magnus; Sjölund, Anette; Broeren, Jürgen; Arvidsson, Daniel; Saury, Jean-Michel; Blomgren, Klas; Lannering, Birgitta; Emanuelson, Ingrid

2016-10-01

We investigated whether active video gaming (AVG) could bring about regular, enjoyable, physical exercise in children treated for brain tumours, what level of physical activity could be reached and if the children's physical functioning improved. Thirteen children, aged 7-17 years, were randomised to either AVG or waiting-list. After 10-12 weeks they crossed-over. Weekly Internet coaching sessions were used to sustain motivation and evaluate enjoyment. Energy expenditure (EE) levels were measured as Metabolic Equivalent of Task (MET), using a multisensory activity monitor. Single-blinded assessments of physical functioning were done, using the Bruininks-Osteretsky Test of Motor Performance, second edition, evaluating participants before and after the intervention period, as well as comparing the randomisation groups after the first period. All patients completed the study. AVG sessions (mean duration 47 minutes) were performed on 72% of all days. Mean EE level during AVG sessions was 3.0 MET, corresponding to moderate physical activity. The Body Coordination score improved by 15% (p = 0.021) over the intervention period. In this group of childhood brain tumour survivors, home-based AVG, supported by a coach, was a feasible, enjoyable and moderately intense form of exercise that improved Body Coordination. Implications for Rehabilitation Childhood brain tumour survivors frequently have cognitive problems, inferior physical functioning and are less physically active compared to their healthy peers. Active video gaming (AVG), supported by Internet coaching, is a feasible home-based intervention in children treated for brain tumours, promoting enjoyable, regular physical exercise of moderate intensity. In this pilot study, AVG with Nintendo Wii improved Body Coordination.

Preprocessing and meta-classification for brain-computer interfaces.

PubMed

Hammon, Paul S; de Sa, Virginia R

2007-03-01

A brain-computer interface (BCI) is a system which allows direct translation of brain states into actions, bypassing the usual muscular pathways. A BCI system works by extracting user brain signals, applying machine learning algorithms to classify the user's brain state, and performing a computer-controlled action. Our goal is to improve brain state classification. Perhaps the most obvious way to improve classification performance is the selection of an advanced learning algorithm. However, it is now well known in the BCI community that careful selection of preprocessing steps is crucial to the success of any classification scheme. Furthermore, recent work indicates that combining the output of multiple classifiers (meta-classification) leads to improved classification rates relative to single classifiers (Dornhege et al., 2004). In this paper, we develop an automated approach which systematically analyzes the relative contributions of different preprocessing and meta-classification approaches. We apply this procedure to three data sets drawn from BCI Competition 2003 (Blankertz et al., 2004) and BCI Competition III (Blankertz et al., 2006), each of which exhibit very different characteristics. Our final classification results compare favorably with those from past BCI competitions. Additionally, we analyze the relative contributions of individual preprocessing and meta-classification choices and discuss which types of BCI data benefit most from specific algorithms.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Information needs and requirements in patients with brain tumours and their relatives.

PubMed

Reinert, Christiane; Rathberger, Katharina; Klinkhammer-Schalke, Monika; Kölbl, Oliver; Proescholdt, Martin; Riemenschneider, Markus J; Schuierer, Gerhard; Hutterer, Markus; Gerken, Michael; Hau, Peter

2018-06-01

Patients with brain tumours face a number of medical and social challenges. Previous studies have shown that these patients and their relatives need a high level of patient-oriented information and counselling. However, these needs are often underestimated. In this single-centre cross-sectional study, we evaluated, for the first time, the information needs of patients with brain tumours and their relatives depending on diagnosis, age and level of education. The participants were interviewed using pre-specified questionnaires. Answers were evaluated descriptively using standard statistical methods. A total of 888 questionnaires were sent out. The return rate was 50.7%. The majority of patients (nP = 103; 59.9%) and a higher proportion of relatives (nR = 103; 72.5%; p = 0.019) wished to receive a maximum of information. The majority (79.7% of patients; 83.1% of relatives) also stated that they preferred a personal, face-to-face meeting as primary source of information. The need for information increased with education (p = 0.015), and decreased with tumour grade (p = 0.025) and age (p = 0.118). Our data indicate that patients with brain tumours and their relatives have high information needs throughout their disease and continuously require information and counselling. Optimal provision of information is based on personal preferences, which needs to be evaluated appropriately. Patient-oriented information and counselling are parts of a successful communication strategy that can improve cancer care significantly.

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

PubMed

Brandão, S F; Campos, T P R

2015-07-01

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

Mobile phone use and brain tumours in the CERENAT case-control study.

PubMed

Coureau, Gaëlle; Bouvier, Ghislaine; Lebailly, Pierre; Fabbro-Peray, Pascale; Gruber, Anne; Leffondre, Karen; Guillamo, Jean-Sebastien; Loiseau, Hugues; Mathoulin-Pélissier, Simone; Salamon, Roger; Baldi, Isabelle

2014-07-01

The carcinogenic effect of radiofrequency electromagnetic fields in humans remains controversial. However, it has been suggested that they could be involved in the aetiology of some types of brain tumours. The objective was to analyse the association between mobile phone exposure and primary central nervous system tumours (gliomas and meningiomas) in adults. CERENAT is a multicenter case-control study carried out in four areas in France in 2004-2006. Data about mobile phone use were collected through a detailed questionnaire delivered in a face-to-face manner. Conditional logistic regression for matched sets was used to estimate adjusted ORs and 95% CIs. A total of 253 gliomas, 194 meningiomas and 892 matched controls selected from the local electoral rolls were analysed. No association with brain tumours was observed when comparing regular mobile phone users with non-users (OR=1.24; 95% CI 0.86 to 1.77 for gliomas, OR=0.90; 95% CI 0.61 to 1.34 for meningiomas). However, the positive association was statistically significant in the heaviest users when considering life-long cumulative duration (≥896 h, OR=2.89; 95% CI 1.41 to 5.93 for gliomas; OR=2.57; 95% CI 1.02 to 6.44 for meningiomas) and number of calls for gliomas (≥18,360 calls, OR=2.10, 95% CI 1.03 to 4.31). Risks were higher for gliomas, temporal tumours, occupational and urban mobile phone use. These additional data support previous findings concerning a possible association between heavy mobile phone use and brain tumours. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Changes in Cognition and Decision Making Capacity Following Brain Tumour Resection: Illustrated with Two Cases.

PubMed

Veretennikoff, Katie; Walker, David; Biggs, Vivien; Robinson, Gail

2017-09-24

Changes in cognition, behaviour and emotion frequently occur in patients with primary and secondary brain tumours. This impacts the ability to make considered decisions, especially following surgical resection, which is often overlooked in the management of patients. Moreover, the impact of cognitive deficits on decision making ability affects activities of daily living and functional independence. The assessment process to ascertain decision making capacity remains a matter of debate. One avenue for evaluating a patient's ability to make informed decisions in the context of brain tumour resection is neuropsychological assessment. This involves the assessment of a wide range of cognitive abilities on standard measurement tools, providing a robust approach to ascertaining capacity. Evidence has shown that a comprehensive and tailored neuropsychological assessment has greater sensitivity than brief cognitive screening tools to detect subtle and/or specific cognitive deficits in brain tumours. It is the precise nature and severity of any cognitive deficits that determines any implications for decision making capacity. This paper focuses on cognitive deficits and decision making capacity following surgical resection of both benign and malignant, and primary and secondary brain tumours in adult patients, and the implications for patients' ability to consent to future medical treatment and make decisions related to everyday activities.

Changes in Cognition and Decision Making Capacity Following Brain Tumour Resection: Illustrated with Two Cases

PubMed Central

Veretennikoff, Katie; Walker, David; Biggs, Vivien; Robinson, Gail

2017-01-01

Changes in cognition, behaviour and emotion frequently occur in patients with primary and secondary brain tumours. This impacts the ability to make considered decisions, especially following surgical resection, which is often overlooked in the management of patients. Moreover, the impact of cognitive deficits on decision making ability affects activities of daily living and functional independence. The assessment process to ascertain decision making capacity remains a matter of debate. One avenue for evaluating a patient’s ability to make informed decisions in the context of brain tumour resection is neuropsychological assessment. This involves the assessment of a wide range of cognitive abilities on standard measurement tools, providing a robust approach to ascertaining capacity. Evidence has shown that a comprehensive and tailored neuropsychological assessment has greater sensitivity than brief cognitive screening tools to detect subtle and/or specific cognitive deficits in brain tumours. It is the precise nature and severity of any cognitive deficits that determines any implications for decision making capacity. This paper focuses on cognitive deficits and decision making capacity following surgical resection of both benign and malignant, and primary and secondary brain tumours in adult patients, and the implications for patients’ ability to consent to future medical treatment and make decisions related to everyday activities. PMID:28946652

Machine learning based brain tumour segmentation on limited data using local texture and abnormality.

PubMed

Bonte, Stijn; Goethals, Ingeborg; Van Holen, Roel

2018-05-07

Brain tumour segmentation in medical images is a very challenging task due to the large variety in tumour shape, position, appearance, scanning modalities and scanning parameters. Most existing segmentation algorithms use information from four different MRI-sequences, but since this is often not available, there is need for a method able to delineate the different tumour tissues based on a minimal amount of data. We present a novel approach using a Random Forests model combining voxelwise texture and abnormality features on a contrast-enhanced T1 and FLAIR MRI. We transform the two scans into 275 feature maps. A random forest model next calculates the probability to belong to 4 tumour classes or 5 normal classes. Afterwards, a dedicated voxel clustering algorithm provides the final tumour segmentation. We trained our method on the BraTS 2013 database and validated it on the larger BraTS 2017 dataset. We achieve median Dice scores of 40.9% (low-grade glioma) and 75.0% (high-grade glioma) to delineate the active tumour, and 68.4%/80.1% for the total abnormal region including edema. Our fully automated brain tumour segmentation algorithm is able to delineate contrast enhancing tissue and oedema with high accuracy based only on post-contrast T1-weighted and FLAIR MRI, whereas for non-enhancing tumour tissue and necrosis only moderate results are obtained. This makes the method especially suitable for high-grade glioma. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed

Wright, John M; Vered, Marilena

2017-03-01

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

Case-control study on the use of cellular and cordless phones and the risk for malignant brain tumours.

PubMed

Hardell, L; Mild, K H; Carlberg, M

2002-10-01

To investigate the use of cellular and cordless phones and the risk for malignant brain tumours. A case-control study was performed on 649 patients aged 20-80 years of both sexes with malignant brain tumour diagnosed from 1 January 1997 to 30 June 2000. All patients were alive during the time of the study and had histopathology verified brain tumours. One matched control to each case was selected from the Swedish Population Register. The study area was the Uppsala-Orebro, Stockholm, Linköping and Göteborg medical regions of Sweden. Exposure was assessed by a questionnaire answered by 588 (91%) cases and 581 (90%) controls. Phone usage was defined as 'ever use' and usage starting within 1 year before diagnosis was disregarded. Overall, no significantly increased risks were found: analogue cellular phones yielded an odds ratio (OR)=1.13, 95% confidence interval (CI)=0.82-1.57, digital cellular phones OR=1.13, CI=0.86-1.48, and cordless phones OR=1.13, CI=0.85-1.50. For ipsilateral (same side) radiofrequency exposure, analogue mobile phones gave OR=1.85, CI=1.16-2.96, for all malignant brain tumours. For astrocytoma, this risk was OR=1.95, CI=1.12-3.39. For all malignant brain tumours, digital mobile phones yielded OR=1.59, CI=1.05-2.41, and cordless phones yielded OR=1.46, CI=0.96-2.23, in the analysis of ipsilateral exposure. The ipsilateral use of an analogue cellular phone yielded a significantly increased risk for malignant brain tumours.

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

PubMed Central

2011-01-01

Case-control studies on adults point to an increased risk of brain tumours (glioma and acoustic neuroma) associated with the long-term use of mobile phones. Recently, the first study on mobile phone use and the risk of brain tumours in children and adolescents, CEFALO, was published. It has been claimed that this relatively small study yielded reassuring results of no increased risk. We do not agree. We consider that the data contain several indications of increased risk, despite low exposure, short latency period, and limitations in the study design, analyses and interpretation. The information certainly cannot be used as reassuring evidence against an association, for reasons that we discuss in this commentary. PMID:22182218

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

PubMed

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

2011-12-19

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

In-vivo imaging of the morphology and blood perfusion of brain tumours in rats with UHR-OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bizheva, Kostadinka; Tan, Bingyao; Fisher, Carl J.; Mason, Erik; Lilge, Lothar D.

2017-02-01

Brain tumors are characterized with morphological changes at cellular level such as enlarged, non-spherical nuclei, microcalcifications, cysts, etc., and are highly vascularized. In this study, two research-grade optical coherence tomography (OCT) systems operating at 800 nm and 1060 nm with axial resolution of 0.95 µm and 3.5 µm in biological tissue respectively, were used to image in vivo and ex vivo the structure of brain tumours in rats. Female Fischer 344 rats were used for this study, which has received ethics clearance by the Animal Research Ethics Committees of the University of Waterloo and the University Health Network, Toronto. Brain tumours were induced by injection of rat brain cancer cell line (RG2 glioma) through a small craniotomy. Presence of brain tumours was verified by MRI imaging on day 7 post tumour cells injection. The in vivo OCT imaging session was conducted on day 14 of the study with the 1060 nm OCT system and both morphological OCT, Doppler OCT and OMAG images were acquired from the brain tumour and the surrounding healthy brain tissue. After completion of the imaging procedure, the brains were harvested, fixed in formalin and reimaged after 2 weeks with the 800 nm OCT system. The in vivo and ex vivo OCT morphological images were correlated with H and E histology. Results from this study demonstrate that UHR-OCT can distinguish between healthy and cancerous brain tissue based on differences in structural and vascular pattern.

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

PubMed

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

2014-06-01

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.

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

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

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

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

PubMed Central

Brandão, S F

2015-01-01

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

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

New technologies to combat malignant tumours of the brain.

PubMed

Heppner, F

1982-01-01

1. The primary problem in an effective treatment of a glioblastoma is the prevention of a recurrence. 2. For that purpose were the following therapeutical procedures undertaken: (a) Temporary implantation of radio cobalt in the brain itself (1957): (b) Clostridium butyricum M 55 was used to render the centre of the tumour fluid (1967): (c) Podophyllin was used to destroy the border of the tumour (1980); (d) The CO2 Laser beam (1975); (e) The electromagnetic heat induction deep in the brain (1973-1978). 3. In order to make the operation and postoperative phase safer for the patient, the following precautions were drawn upon or employed: (a) Hyperbaric oxygenisation in the pressure chamber (1971); (b) The anti-G-suit (1974); (c) the computer controlled automatic infusion pump (1980), and (d) the telemetric measurement of intra-cranial pressure (1975). 4. Apart from the pressure chamber, the mentioned devices were all supervised and developed in the department of the author. 5. The first successful means in the prevention of the recurrence of a glioblastoma multiform seems to be the telethermic method mentioned in 2 (e) above.

The 2016 revision of the WHO Classification of Central Nervous System Tumours: retrospective application to a cohort of diffuse gliomas.

PubMed

Rogers, Te Whiti; Toor, Gurvinder; Drummond, Katharine; Love, Craig; Field, Kathryn; Asher, Rebecca; Tsui, Alpha; Buckland, Michael; Gonzales, Michael

2018-03-01

The classification of central nervous system tumours has more recently been shaped by a focus on molecular pathology rather than histopathology. We re-classified 82 glial tumours according to the molecular-genetic criteria of the 2016 revision of the World Health Organization (WHO) Classification of Tumours of the Central Nervous System. Initial diagnoses and grading were based on the morphological criteria of the 2007 WHO scheme. Because of the impression of an oligodendroglial component on initial histological assessment, each tumour was tested for co-deletion of chromosomes 1p and 19q and mutations of isocitrate dehydrogenase (IDH-1 and 2) genes. Additionally, expression of proteins encoded by alpha-thalassemia X-linked mental retardation (ATRX) and TP53 genes was assessed by immunohistochemistry. We found that all but two tumours could be assigned to a specific category in the 2016 revision. The most common change in diagnosis was from oligoastrocytoma to specifically astrocytoma or oligodendroglioma. Analysis of progression free survival (PFS) for WHO grade II and III tumours showed that the objective criteria of the 2016 revision separated diffuse gliomas into three distinct molecular categories: chromosome 1p/19q co-deleted/IDH mutant, intact 1p/19q/IDH mutant and IDH wild type. No significant difference in PFS was found when comparing IDH mutant grade II and III tumours suggesting that IDH status is more informative than tumour grade. The segregation into distinct molecular sub-types that is achieved by the 2016 revision provides an objective evidence base for managing patients with grade II and III diffuse gliomas based on prognosis.

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

PubMed

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

2015-08-01

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

Ethics roundtable debate: Child with severe brain damage and an underlying brain tumour

PubMed Central

Gunn, Scott; Hashimoto, Satoru; Karakozov, Michael; Marx, Thomas; Tan, Ian KS; Thompson, Dan R; Vincent, Jean-Louis

2004-01-01

A young person presents with a highly malignant brain tumour with hemiparesis and limited prognosis after resection. She then suffers an iatrogenic cardiac and respiratory arrest that results in profound anoxic encephalopathy. A difference in opinion between the treatment team and the parent is based on a question of futile therapy. Opinions from five intensivists from around the world explore the differences in ethical and legal issues. A Physician-ethicist comments on the various approaches. PMID:15312199

Hybrid MR-PET of brain tumours using amino acid PET and chemical exchange saturation transfer MRI.

PubMed

da Silva, N A; Lohmann, P; Fairney, J; Magill, A W; Oros Peusquens, A-M; Choi, C-H; Stirnberg, R; Stoffels, G; Galldiks, N; Golay, X; Langen, K-J; Jon Shah, N

2018-06-01

PET using radiolabelled amino acids has become a promising tool in the diagnostics of gliomas and brain metastasis. Current research is focused on the evaluation of amide proton transfer (APT) chemical exchange saturation transfer (CEST) MR imaging for brain tumour imaging. In this hybrid MR-PET study, brain tumours were compared using 3D data derived from APT-CEST MRI and amino acid PET using O-(2- 18 F-fluoroethyl)-L-tyrosine ( 18 F-FET). Eight patients with gliomas were investigated simultaneously with 18 F-FET PET and APT-CEST MRI using a 3-T MR-BrainPET scanner. CEST imaging was based on a steady-state approach using a B 1 average power of 1μT. B 0 field inhomogeneities were corrected a Prametric images of magnetisation transfer ratio asymmetry (MTR asym ) and differences to the extrapolated semi-solid magnetisation transfer reference method, APT# and nuclear Overhauser effect (NOE#), were calculated. Statistical analysis of the tumour-to-brain ratio of the CEST data was performed against PET data using the non-parametric Wilcoxon test. A tumour-to-brain ratio derived from APT# and 18 F-FET presented no significant differences, and no correlation was found between APT# and 18 F-FET PET data. The distance between local hot spot APT# and 18 F-FET were different (average 20 ± 13 mm, range 4-45 mm). For the first time, CEST images were compared with 18 F-FET in a simultaneous MR-PET measurement. Imaging findings derived from 18 F-FET PET and APT CEST MRI seem to provide different biological information. The validation of these imaging findings by histological confirmation is necessary, ideally using stereotactic biopsy.

Characterization of brain tumours with spin-spin relaxation: pilot case study reveals unique T 2 distribution profiles of glioblastoma, oligodendroglioma and meningioma.

PubMed

Laule, Cornelia; Bjarnason, Thorarin A; Vavasour, Irene M; Traboulsee, Anthony L; Wayne Moore, G R; Li, David K B; MacKay, Alex L

2017-11-01

Prolonged spin-spin relaxation times in tumour tissue have been observed since some of the earliest nuclear magnetic resonance investigations of the brain. Over the last three decades, numerous studies have sought to characterize tumour morphology and malignancy using quantitative assessment of T 2 relaxation times, although attempts to categorize and differentiate tumours have had limited success. However, previous work must be interpreted with caution as relaxation data were typically acquired using a variety of multiple echo sequences with a range of echoes and T 2 decay curves and were frequently fit with monoexponential analysis. We defined the distribution of T 2 components in three different human brain tumours (glioblastoma, oligodendroglioma, meningioma) using a multi-echo sequence with a greater number of echoes and a longer acquisition window than previously used (48 echoes, data collection out to 1120 ms) with no a priori assumptions about the number of exponential components contributing to the T 2 decay. T 2 relaxation times were increased in tumour tissue and each tumour showed a distinct T 2 distribution profile. Tumours have complex and unique compartmentalization characteristics. Quantitative assessment of T 2 relaxation in brain cancer may be useful in evaluating different grades of brain tumours on the basis of their T 2 distribution profile, and has the potential to be a non-invasive diagnostic tool which may also be useful in monitoring therapy. Further study with a larger sample size and varying grades of tumours is warranted.

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

PubMed Central

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

2014-01-01

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

Methylation of the TERT promoter and risk stratification of childhood brain tumours: an integrative genomic and molecular study.

PubMed

Castelo-Branco, Pedro; Choufani, Sanaa; Mack, Stephen; Gallagher, Denis; Zhang, Cindy; Lipman, Tatiana; Zhukova, Nataliya; Walker, Erin J; Martin, Dianna; Merino, Diana; Wasserman, Jonathan D; Elizabeth, Cynthia; Alon, Noa; Zhang, Libo; Hovestadt, Volker; Kool, Marcel; Jones, David T W; Zadeh, Gelareh; Croul, Sidney; Hawkins, Cynthia; Hitzler, Johann; Wang, Jean C Y; Baruchel, Sylvain; Dirks, Peter B; Malkin, David; Pfister, Stefan; Taylor, Michael D; Weksberg, Rosanna; Tabori, Uri

2013-05-01

Identification of robust biomarkers of malignancy and methods to establish disease progression is a major goal in paediatric neuro-oncology. We investigated whether methylation of the TERT promoter can be a biomarker for malignancy and patient outcome in paediatric brain tumours. For the discovery cohort, we used samples obtained from patients with paediatric brain tumours and individuals with normal brain tissues stored at the German Cancer Research Center (Heidelberg, Germany). We used methylation arrays for genome-wide assessment of DNA. For the validation cohort, we used samples obtained from several tissues for which full clinical and follow-up data were available from two hospitals in Toronto (ON, Canada). We did methylation analysis using quantitative Sequenom and pyrosequencing of an identified region of the TERT promoter. We assessed TERT expression by real-time PCR. To establish whether the biomarker could be used to assess and predict progression, we analysed methylation in paired samples of tumours that transformed from low to high grade and from localised to metastatic, and in choroid plexus tumours of different grades. Finally, we investigated overall survival in patients with posterior fossa ependymomas in which the identified region was hypermethylated or not. All individuals responsible for assays were masked to the outcome of the patients. Analysis of 280 samples in the discovery cohort identified one CpG site (cg11625005) in which 78 (99%) of 79 samples from normal brain tissues and low-grade tumours were not hypermethylated, but 145 (72%) of 201 samples from malignant tumours were hypermethylated (>15% methylated; p<0.0001). Analysis of 68 samples in the validation cohort identified a subset of five CpG sites (henceforth, upstream of the transcription start site [UTSS]) that was hypermethylated in all malignant paediatric brain tumours that expressed TERT but not in normal tissues that did not express TERT (p<0.0001). UTSS had a positive

Leukaemia, brain tumours and exposure to extremely low frequency magnetic fields: cohort study of Swiss railway employees

PubMed Central

Röösli, Martin; Lörtscher, Manfred; Egger, Matthias; Pfluger, Dominik; Schreier, Nadja; Lörtscher, Emanuel; Locher, Peter; Spoerri, Adrian; Minder, Christoph

2007-01-01

Aims To investigate the relationship between extremely low frequency magnetic field (ELF‐MF) exposure and mortality from leukaemia and brain tumour in a cohort of Swiss railway workers. Methods 20 141 Swiss railway employees with 464 129 person‐years of follow‐up between 1972 and 2002 were studied. Mortality rates for leukaemia and brain tumour of highly exposed train drivers (21 μT average annual exposure) were compared with medium and low exposed occupational groups (i.e. station masters with an average exposure of 1 μT). In addition, individual cumulative exposure was calculated from on‐site measurements and modelling of past exposures. Results The hazard ratio (HR) for leukaemia mortality of train drivers was 1.43 (95% CI 0.74 to 2.77) compared with station masters. For myeloid leukaemia the HR of train drivers was 4.74 (95% CI 1.04 to 21.60) and for Hodgkin's disease 3.29 (95% CI 0.69 to 15.63). Lymphoid leukaemia, non‐Hodgkin's disease and brain tumour mortality were not associated with magnetic field exposure. Concordant results were obtained from analyses based on individual cumulative exposure. Conclusions Some evidence of an exposure–response association was found for myeloid leukaemia and Hodgkin's disease, but not for other haematopoietic and lymphatic malignancies and brain tumours. PMID:17525094

Mutation and deletion analysis of GFRα-1, encoding the co-receptor for the GDNF/RET complex, in human brain tumours

PubMed Central

Gimm, O; Gössling, A; Marsh, D J; Dahia, P L M; Mulligan, L M; Deimling, A von; Eng, C

1999-01-01

Glial cell line-derived neurotrophic factor (GDNF) plays a key role in the control of vertebrate neuron survival and differentiation in both the central and peripheral nervous systems. GDNF preferentially binds to GFRα-1 which then interacts with the receptor tyrosine kinase RET. We investigated a panel of 36 independent cases of mainly advanced sporadic brain tumours for the presence of mutations in GDNF and GFRα-1. No mutations were found in the coding region of GDNF. We identified six previously described GFRα-1 polymorphisms, two of which lead to an amino acid change. In 15 of 36 brain tumours, all polymorphic variants appeared to be homozygous. Of these 15 tumours, one also had a rare, apparently homozygous, sequence variant at codon 361. Because of the rarity of the combination of homozygous sequence variants, analysis for hemizygous deletion was pursued in the 15 samples and loss of heterozygosity was found in 11 tumours. Our data suggest that intragenic point mutations of GDNF or GFRα-1 are not a common aetiologic event in brain tumours. However, either deletion of GFRα-1 and/or nearby genes may contribute to the pathogenesis of these tumours. © 1999 Cancer Research Campaign PMID:10408842

Histogram analysis of apparent diffusion coefficient maps for assessing thymic epithelial tumours: correlation with world health organization classification and clinical staging.

PubMed

Kong, Ling-Yan; Zhang, Wei; Zhou, Yue; Xu, Hai; Shi, Hai-Bin; Feng, Qing; Xu, Xiao-Quan; Yu, Tong-Fu

2018-04-01

To investigate the value of apparent diffusion coefficients (ADCs) histogram analysis for assessing World Health Organization (WHO) pathological classification and Masaoka clinical stages of thymic epithelial tumours. 37 patients with histologically confirmed thymic epithelial tumours were enrolled. ADC measurements were performed using hot-spot ROI (ADC HS-ROI ) and histogram-based approach. ADC histogram parameters included mean ADC (ADC mean ), median ADC (ADC median ), 10 and 90 percentile of ADC (ADC 10 and ADC 90 ), kurtosis and skewness. One-way ANOVA, independent-sample t-test, and receiver operating characteristic were used for statistical analyses. There were significant differences in ADC mean , ADC median , ADC 10 , ADC 90 and ADC HS-ROI among low-risk thymoma (type A, AB, B1; n = 14), high-risk thymoma (type B2, B3; n = 9) and thymic carcinoma (type C, n = 14) groups (all p-values <0.05), while no significant difference in skewness (p = 0.181) and kurtosis (p = 0.088). ADC 10 showed best differentiating ability (cut-off value, ≤0.689 × 10 -3 mm 2 s -1 ; AUC, 0.957; sensitivity, 95.65%; specificity, 92.86%) for discriminating low-risk thymoma from high-risk thymoma and thymic carcinoma. Advanced Masaoka stages (Stage III and IV; n = 24) tumours showed significant lower ADC parameters and higher kurtosis than early Masaoka stage (Stage I and II; n = 13) tumours (all p-values <0.05), while no significant difference on skewness (p = 0.063). ADC 10 showed best differentiating ability (cut-off value, ≤0.689 × 10 -3 mm 2 s -1 ; AUC, 0.913; sensitivity, 91.30%; specificity, 85.71%) for discriminating advanced and early Masaoka stage epithelial tumours. ADC histogram analysis may assist in assessing the WHO pathological classification and Masaoka clinical stages of thymic epithelial tumours. Advances in knowledge: 1. ADC histogram analysis could help to assess WHO pathological classification of thymic epithelial tumours. 2. ADC histogram analysis could

Motor deficits correlate with resting state motor network connectivity in patients with brain tumours

PubMed Central

Mikell, Charles B.; Youngerman, Brett E.; Liston, Conor; Sisti, Michael B.; Bruce, Jeffrey N.; Small, Scott A.; McKhann, Guy M.

2012-01-01

While a tumour in or abutting primary motor cortex leads to motor weakness, how tumours elsewhere in the frontal or parietal lobes affect functional connectivity in a weak patient is less clear. We hypothesized that diminished functional connectivity in a distributed network of motor centres would correlate with motor weakness in subjects with brain masses. Furthermore, we hypothesized that interhemispheric connections would be most vulnerable to subtle disruptions in functional connectivity. We used task-free functional magnetic resonance imaging connectivity to probe motor networks in control subjects and patients with brain tumours (n = 22). Using a control dataset, we developed a method for automated detection of key nodes in the motor network, including the primary motor cortex, supplementary motor area, premotor area and superior parietal lobule, based on the anatomic location of the hand-motor knob in the primary motor cortex. We then calculated functional connectivity between motor network nodes in control subjects, as well as patients with and without brain masses. We used this information to construct weighted, undirected graphs, which were then compared to variables of interest, including performance on a motor task, the grooved pegboard. Strong connectivity was observed within the identified motor networks between all nodes bilaterally, and especially between the primary motor cortex and supplementary motor area. Reduced connectivity was observed in subjects with motor weakness versus subjects with normal strength (P < 0.001). This difference was driven mostly by decreases in interhemispheric connectivity between the primary motor cortices (P < 0.05) and between the left primary motor cortex and the right premotor area (P < 0.05), as well as other premotor area connections. In the subjects without motor weakness, however, performance on the grooved pegboard did not relate to interhemispheric connectivity, but rather was inversely

The sensitivity of normal brain and intracranially implanted VX2 tumour to interstitial photodynamic therapy.

PubMed Central

Lilge, L.; Olivo, M. C.; Schatz, S. W.; MaGuire, J. A.; Patterson, M. S.; Wilson, B. C.

1996-01-01

The applicability and limitations of a photodynamic threshold model, used to describe quantitatively the in vivo response of tissues to photodynamic therapy, are currently being investigated in a variety of normal and malignant tumour tissues. The model states that tissue necrosis occurs when the number of photons absorbed by the photosensitiser per unit tissue volume exceeds a threshold. New Zealand White rabbits were sensitised with porphyrin-based photosensitisers. Normal brain or intracranially implanted VX2 tumours were illuminated via an optical fibre placed into the tissue at craniotomy. The light fluence distribution in the tissue was measured by multiple interstitial optical fibre detectors. The tissue concentration of the photosensitiser was determined post mortem by absorption spectroscopy. The derived photodynamic threshold values for normal brain are significantly lower than for VX2 tumour for all photosensitisers examined. Neuronal damage is evident beyond the zone of frank necrosis. For Photofrin the threshold decreases with time delay between photosensitiser administration and light treatment. No significant difference in threshold is found between Photofrin and haematoporphyrin derivative. The threshold in normal brain (grey matter) is lowest for sensitisation by 5 delta-aminolaevulinic acid. The results confirm the very high sensitivity of normal brain to porphyrin photodynamic therapy and show the importance of in situ light fluence monitoring during photodynamic irradiation. Images Figure 1 Figure 4 Figure 5 Figure 6 Figure 7 PMID:8562339

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

PubMed Central

Hardell, Lennart; Carlberg, Michael

2015-01-01

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

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

PubMed

Hardell, Lennart; Carlberg, Michael

2015-04-03

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

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

PubMed

Cardis, E; 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

2011-09-01

The objective of this study was to examine the associations of brain tumours with radio frequency (RF) fields from mobile phones. 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. 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. 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.

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

PubMed Central

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

2011-01-01

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

[WHO classification of head and neck tumours 2017: Main novelties and update of diagnostic methods].

PubMed

Sarradin, Victor; Siegfried, Aurore; Uro-Coste, Emmanuelle; Delord, Jean-Pierre

2018-06-01

The publication of the new WHO classification of head and neck tumours in 2017 brought major modifications. Especially, a new chapter is dedicated to the oropharynx, focusing on the description of squamous cell carcinoma induced by the virus Human Papilloma Virus (HPV), and new entities of tumors are described in nasal cavities and sinuses. In this article are presented the novelties and main changes of this new classification, as well as the updates of the diagnostic methods (immunohistochemistry, cytogenetics or molecular biology). Copyright © 2018 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

The carbon dioxide laser surgical unit as an instrument for surgery of brain tumours--its advantages and disadvantages.

PubMed

Takizawa, T

1984-01-01

The author started in 1969 his studies on developing the practical models of the carbon dioxide laser surgical units and produced Medilaser-S, Model MEL-42 and MEL-444. By the end of 1982 the author had operated on 143 cases of brain tumour with the laser. Most of those cases were brain tumours which were difficult or impossible to remove by conventional means. The major points of this paper are as follows: The principle of the laser, the mechanism of the CO2 laser, the biomedical features of the CO2 laser, the advantages and disadvantages of the CO2 laser, indications and contraindications for the use of the CO2 laser, development of the CO2 laser surgical units, surgical procedures and techniques of brain tumour laser surgery, adjuvant methods of laser surgery and comparison between the CO2 laser and the Nd-YAG laser.

A multinational case-control study on childhood brain tumours, anthropogenic factors, birth characteristics and prenatal exposures: A validation of interview data.

PubMed

Vienneau, Danielle; Infanger, Denis; Feychting, Maria; Schüz, Joachim; Schmidt, Lisbeth Samsø; Poulsen, Aslak Harbo; Tettamanti, Giorgio; Klæboe, Lars; Kuehni, Claudia E; Tynes, Tore; Von der Weid, Nicolas; Lannering, Birgitta; Röösli, Martin

2016-02-01

Little is known about the aetiology of childhood brain tumours. We investigated anthropometric factors (birth weight, length, maternal age), birth characteristics (e.g. vacuum extraction, preterm delivery, birth order) and exposures during pregnancy (e.g. maternal: smoking, working, dietary supplement intake) in relation to risk of brain tumour diagnosis among 7-19 year olds. The multinational case-control study in Denmark, Sweden, Norway and Switzerland (CEFALO) included interviews with 352 (participation rate=83.2%) eligible cases and 646 (71.1%) population-based controls. Interview data were complemented with data from birth registries and validated by assessing agreement (Cohen's Kappa). We used conditional logistic regression models matched on age, sex and geographical region (adjusted for maternal age and parental education) to explore associations between birth factors and childhood brain tumour risk. Agreement between interview and birth registry data ranged from moderate (Kappa=0.54; worked during pregnancy) to almost perfect (Kappa=0.98; birth weight). Neither anthropogenic factors nor birth characteristics were associated with childhood brain tumour risk. Maternal vitamin intake during pregnancy was indicative of a protective effect (OR 0.75, 95%-CI: 0.56-1.01). No association was seen for maternal smoking during pregnancy or working during pregnancy. We found little evidence that the considered birth factors were related to brain tumour risk among children and adolescents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Leptin concentration and nutritional status in the course of treatment in children with brain tumours--preliminary report.

PubMed

Musiol, Katarzyna; Sobol, Grazyna; Mizia-Malarz, Agnieszka; Wos, Halina

2014-01-01

To assess the nutritional status in children with central nervous system (CNS) tumours, including concentration of leptin, the neuropeptide responsible for regulation of energetic homeostasis in an organism. The studied group comprised 44 children with brain tumours, aged (4.02-18.7). In all children during the whole therapy (from the start to the period of 1 year and more after the end of therapy), a number of standard deviations (SDs) for the body mass index (SDS BMI) was derived from anthropometric measurements. Concentrations of leptin were assayed simultaneously. The lowest values of the anthropometric indices were found in children during the maintenance therapy. Concentrations of leptin in patients with malignant CNS tumours and significant undernutrition were slightly greater as compared to patients presenting normal nutritional status; however, without statistical significance. In children with tumours of the central nervous system, there are quantitative disorders of the nutritional status which correlate with the period of the treatment. The most significant disorders in the nutritional status are observed during maintenance chemotherapy. There was no statistically significant correlation between the concentration of leptin and nutritional status in children with malignant brain tumours during the course of treatment and after its completion.

Context aware decision support in neurosurgical oncology based on an efficient classification of endomicroscopic data.

PubMed

Li, Yachun; Charalampaki, Patra; Liu, Yong; Yang, Guang-Zhong; Giannarou, Stamatia

2018-06-13

Probe-based confocal laser endomicroscopy (pCLE) enables in vivo, in situ tissue characterisation without changes in the surgical setting and simplifies the oncological surgical workflow. The potential of this technique in identifying residual cancer tissue and improving resection rates of brain tumours has been recently verified in pilot studies. The interpretation of endomicroscopic information is challenging, particularly for surgeons who do not themselves routinely review histopathology. Also, the diagnosis can be examiner-dependent, leading to considerable inter-observer variability. Therefore, automatic tissue characterisation with pCLE would support the surgeon in establishing diagnosis as well as guide robot-assisted intervention procedures. The aim of this work is to propose a deep learning-based framework for brain tissue characterisation for context aware diagnosis support in neurosurgical oncology. An efficient representation of the context information of pCLE data is presented by exploring state-of-the-art CNN models with different tuning configurations. A novel video classification framework based on the combination of convolutional layers with long-range temporal recursion has been proposed to estimate the probability of each tumour class. The video classification accuracy is compared for different network architectures and data representation and video segmentation methods. We demonstrate the application of the proposed deep learning framework to classify Glioblastoma and Meningioma brain tumours based on endomicroscopic data. Results show significant improvement of our proposed image classification framework over state-of-the-art feature-based methods. The use of video data further improves the classification performance, achieving accuracy equal to 99.49%. This work demonstrates that deep learning can provide an efficient representation of pCLE data and accurately classify Glioblastoma and Meningioma tumours. The performance evaluation analysis

Isolating dividing neural and brain tumour cells for gene expression profiling.

PubMed

Endaya, Berwini; Cavanagh, Brenton; Alowaidi, Faisal; Walker, Tom; de Pennington, Nicholas; Ng, Jin-Ming A; Lam, Paula Y P; Mackay-Sim, Alan; Neuzil, Jiri; Meedeniya, Adrian C B

2016-01-15

The characterisation of dividing brain cells is fundamental for studies ranging from developmental and stem cell biology, to brain cancers. Whilst there is extensive anatomical data on these dividing cells, limited gene transcription data is available due to technical constraints. We focally isolated dividing cells whilst conserving RNA, from culture, primary neural tissue and xenografted glioma tumours, using a thymidine analogue that enables gene transcription analysis. 5-ethynyl-2-deoxyuridine labels the replicating DNA of dividing cells. Once labelled, cultured cells and tissues were dissociated, fluorescently tagged with a revised click chemistry technique and the dividing cells isolated using fluorescence-assisted cell sorting. RNA was extracted and analysed using real time PCR. Proliferation and maturation related gene expression in neurogenic tissues was demonstrated in acutely and 3 day old labelled cells, respectively. An elevated expression of marker and pathway genes was demonstrated in the dividing cells of xenografted brain tumours, with the non-dividing cells showing relatively low levels of expression. BrdU "immune-labelling", the most frequently used protocol for detecting cell proliferation, causes complete denaturation of RNA, precluding gene transcription analysis. This EdU labelling technique, maintained cell integrity during dissociation, minimized copper exposure during labelling and used a cell isolation protocol that avoided cell lysis, thus conserving RNA. The technique conserves RNA, enabling the definition of cell proliferation-related changes in gene transcription of neural and pathological brain cells in cells harvested immediately after division, or following a period of maturation. Copyright © 2015 Elsevier B.V. All rights reserved.

Known glioma risk loci are associated with glioma with a family history of brain tumours -- a case-control gene association study.

PubMed

Melin, Beatrice; Dahlin, Anna M; Andersson, Ulrika; Wang, Zhaoming; Henriksson, Roger; Hallmans, Göran; Bondy, Melissa L; Johansen, Christoffer; Feychting, Maria; Ahlbom, Anders; Kitahara, Cari M; Wang, Sophia S; Ruder, Avima M; Carreón, Tania; Butler, Mary Ann; Inskip, Peter D; Purdue, Mark; Hsing, Ann W; Mechanic, Leah; Gillanders, Elizabeth; Yeager, Meredith; Linet, Martha; Chanock, Stephen J; Hartge, Patricia; Rajaraman, Preetha

2013-05-15

Familial cancer can be used to leverage genetic association studies. Recent genome-wide association studies have reported independent associations between seven single nucleotide polymorphisms (SNPs) and risk of glioma. The aim of this study was to investigate whether glioma cases with a positive family history of brain tumours, defined as having at least one first- or second-degree relative with a history of brain tumour, are associated with known glioma risk loci. One thousand four hundred and thirty-one glioma cases and 2,868 cancer-free controls were identified from four case-control studies and two prospective cohorts from USA, Sweden and Denmark and genotyped for seven SNPs previously reported to be associated with glioma risk in case-control designed studies. Odds ratios were calculated by unconditional logistic regression. In analyses including glioma cases with a family history of brain tumours (n = 104) and control subjects free of glioma at baseline, three of seven SNPs were associated with glioma risk: rs2736100 (5p15.33, TERT), rs4977756 (9p21.3, CDKN2A-CDKN2B) and rs6010620 (20q13.33, RTEL1). After Bonferroni correction for multiple comparisons, only one marker was statistically significantly associated with glioma risk, rs6010620 (ORtrend for the minor (A) allele, 0.39; 95% CI: 0.25-0.61; Bonferroni adjusted ptrend , 1.7 × 10(-4) ). In conclusion, as previously shown for glioma regardless of family history of brain tumours, rs6010620 (RTEL1) was associated with an increased risk of glioma when restricting to cases with family history of brain tumours. These findings require confirmation in further studies with a larger number of glioma cases with a family history of brain tumours. Copyright © 2012 UICC.

Multiscale biomechanics of brain tumours favours cancer invasion by cell softening and tissue stiffening

NASA Astrophysics Data System (ADS)

Kas, Josef; Fritsch, Anatol; Grosser, Steffen; Friebe, Sabrina; Reiss-Zimmermann, Martin; Müller, Wolf; Hoffmann, Karl-Titus; Sack, Ingolf

Cancer progression needs two contradictory mechanical prerequisites. For metastasis individual cancer cells or small clusters have to flow through the microenvironment by overcoming the yield stress exerted by the surrounding. On the other hand a tumour has to behave as a solid to permit cell proliferation and spreading of the tumour mass against its surrounding. We determine that the high mechanical adaptability of cancer cells and the scale controlled viscoelastic properties of tissues reconcile both conflicting properties, fluid and solid, simultaneously in brain tumours. We resolve why different techniques that assess cell and tissue mechanics have produced apparently conflicting results by our finding that tumours generate different viscoelastic behaviours on different length scales, which are in concert optimal for tumour spreading and metastasis. Single cancer cells become very soft in their elastic behavior which promotes cell unjamming. On the level of direct cell-to-cell interactions cells feel their micro-environment as rigid elastic substrate that stimulates cancer on the molecular level. All over a tumour has predominately a stiff elastic character in terms of viscoelastic behaviour caused by a solid backbone. Simultaneously, the tumour mass is characterized by a large local variability in the storage and loss modulus that is caused by areas of a more fluid nature.

Volumetric brain tumour detection from MRI using visual saliency.

PubMed

Mitra, Somosmita; Banerjee, Subhashis; Hayashi, Yoichi

2017-01-01

Medical image processing has become a major player in the world of automatic tumour region detection and is tantamount to the incipient stages of computer aided design. Saliency detection is a crucial application of medical image processing, and serves in its potential aid to medical practitioners by making the affected area stand out in the foreground from the rest of the background image. The algorithm developed here is a new approach to the detection of saliency in a three dimensional multi channel MR image sequence for the glioblastoma multiforme (a form of malignant brain tumour). First we enhance the three channels, FLAIR (Fluid Attenuated Inversion Recovery), T2 and T1C (contrast enhanced with gadolinium) to generate a pseudo coloured RGB image. This is then converted to the CIE L*a*b* color space. Processing on cubes of sizes k = 4, 8, 16, the L*a*b* 3D image is then compressed into volumetric units; each representing the neighbourhood information of the surrounding 64 voxels for k = 4, 512 voxels for k = 8 and 4096 voxels for k = 16, respectively. The spatial distance of these voxels are then compared along the three major axes to generate the novel 3D saliency map of a 3D image, which unambiguously highlights the tumour region. The algorithm operates along the three major axes to maximise the computation efficiency while minimising loss of valuable 3D information. Thus the 3D multichannel MR image saliency detection algorithm is useful in generating a uniform and logistically correct 3D saliency map with pragmatic applicability in Computer Aided Detection (CADe). Assignment of uniform importance to all three axes proves to be an important factor in volumetric processing, which helps in noise reduction and reduces the possibility of compromising essential information. The effectiveness of the algorithm was evaluated over the BRATS MICCAI 2015 dataset having 274 glioma cases, consisting both of high grade and low grade GBM. The results were compared with

Within-brain classification for brain tumor segmentation.

PubMed

Havaei, Mohammad; Larochelle, Hugo; Poulin, Philippe; Jodoin, Pierre-Marc

2016-05-01

In this paper, we investigate a framework for interactive brain tumor segmentation which, at its core, treats the problem of interactive brain tumor segmentation as a machine learning problem. This method has an advantage over typical machine learning methods for this task where generalization is made across brains. The problem with these methods is that they need to deal with intensity bias correction and other MRI-specific noise. In this paper, we avoid these issues by approaching the problem as one of within brain generalization. Specifically, we propose a semi-automatic method that segments a brain tumor by training and generalizing within that brain only, based on some minimum user interaction. We investigate how adding spatial feature coordinates (i.e., i, j, k) to the intensity features can significantly improve the performance of different classification methods such as SVM, kNN and random forests. This would only be possible within an interactive framework. We also investigate the use of a more appropriate kernel and the adaptation of hyper-parameters specifically for each brain. As a result of these experiments, we obtain an interactive method whose results reported on the MICCAI-BRATS 2013 dataset are the second most accurate compared to published methods, while using significantly less memory and processing power than most state-of-the-art methods.

TNM-O: ontology support for staging of malignant tumours.

PubMed

Boeker, Martin; França, Fábio; Bronsert, Peter; Schulz, Stefan

2016-11-14

Objectives of this work are to (1) present an ontological framework for the TNM classification system, (2) exemplify this framework by an ontology for colon and rectum tumours, and (3) evaluate this ontology by assigning TNM classes to real world pathology data. The TNM ontology uses the Foundational Model of Anatomy for anatomical entities and BioTopLite 2 as a domain top-level ontology. General rules for the TNM classification system and the specific TNM classification for colorectal tumours were axiomatised in description logic. Case-based information was collected from tumour documentation practice in the Comprehensive Cancer Centre of a large university hospital. Based on the ontology, a module was developed that classifies pathology data. TNM was represented as an information artefact, which consists of single representational units. Corresponding to every representational unit, tumours and tumour aggregates were defined. Tumour aggregates consist of the primary tumour and, if existing, of infiltrated regional lymph nodes and distant metastases. TNM codes depend on the location and certain qualities of the primary tumour (T), the infiltrated regional lymph nodes (N) and the existence of distant metastases (M). Tumour data from clinical and pathological documentation were successfully classified with the ontology. A first version of the TNM Ontology represents the TNM system for the description of the anatomical extent of malignant tumours. The present work demonstrates its representational power and completeness as well as its applicability for classification of instance data.

CNS embryonal tumours: WHO 2016 and beyond.

PubMed

Pickles, J C; Hawkins, C; Pietsch, T; Jacques, T S

2018-02-01

Embryonal tumours of the central nervous system (CNS) present a significant clinical challenge. Many of these neoplasms affect young children, have a very high mortality and therapeutic strategies are often aggressive with poor long-term outcomes. There is a great need to accurately diagnose embryonal tumours, predict their outcome and adapt therapy to the individual patient's risk. For the first time in 2016, the WHO classification took into account molecular characteristics for the diagnosis of CNS tumours. This integration of histological features with genetic information has significantly changed the diagnostic work-up and reporting of tumours of the CNS. However, this remains challenging in embryonal tumours due to their previously unaccounted tumour heterogeneity. We describe the recent revisions made to the 4th edition of the WHO classification of CNS tumours and review the main changes, while highlighting some of the more common diagnostic testing strategies. © 2017 British Neuropathological Society.

Paediatric brain tumours: A review of radiotherapy, state of the art and challenges for the future regarding protontherapy and carbontherapy.

PubMed

Laprie, A; Hu, Y; Alapetite, C; Carrie, C; Habrand, J-L; Bolle, S; Bondiau, P-Y; Ducassou, A; Huchet, A; Bertozzi, A-I; Perel, Y; Moyal, É; Balosso, J

2015-12-01

Brain tumours are the most frequent solid tumours in children and the most frequent radiotherapy indications in paediatrics, with frequent late effects: cognitive, osseous, visual, auditory and hormonal. A better protection of healthy tissues by improved beam ballistics, with particle therapy, is expected to decrease significantly late effects without decreasing local control and survival. This article reviews the scientific literature to advocate indications of protontherapy and carbon ion therapy for childhood central nervous system cancer, and estimate the expected therapeutic benefits. A systematic review was performed on paediatric brain tumour treatments using Medline (from 1966 to March of 2014). To be included, clinical trials had to meet the following criteria: age of patients 18 years or younger, treated with radiation, and report of survival. Studies were also selected according to the evidence level. A secondary search of cited references found other studies about cognitive functions, quality of life, the comparison of photon and proton dosimetry showing potential dose escalation and/or sparing of organs at risk with protontherapy; and studies on dosimetric and technical issues related to protontherapy. A total of 7051 primary references published were retrieved, among which 40 clinical studies and 60 papers about quality of life, dose distribution and dosimetry were analysed, as well as the ongoing clinical trials. These papers have been summarized and reported in a specific document made available to the participants of a final 1-day workshop. Tumours of the meningeal envelop and bony cranial structures were excluded from the analysis. Protontherapy allows outstanding ballistics to target the tumour area, while substantially decreasing radiation dose to the normal tissues. There are many indications of protontherapy for paediatric brain tumours in curative intent, either for localized treatment of ependymomas, germ-cell tumours, craniopharyngiomas

Tumours of the soft (mesenchymal) tissues.

PubMed

Weiss, E

1974-01-01

This is a classification of tumours of fibrous tissue, fat, muscle, blood and lymph vessels, and mast cells, irrespective of the region of the body in which they arise. Tumours of fibrous tissue are divided into fibroma, fibrosarcoma (including "canine haemangiopericytoma"), other sarcomas, equine sarcoid, and various tumour-like lesions. The histological appearance of the tumours is described and illustrated with photographs.

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

PubMed

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

2016-01-01

Boron neutron capture therapy (BNCT) is a cellular-level particle radiation therapy that combines the selective delivery of boron compounds to tumour tissue with neutron irradiation. Previously, high doses of one of the boron compounds used for BNCT, L-BPA, were found to reduce the boron-derived irradiation dose to the central nervous system. However, injection with a high dose of L-BPA is not feasible in clinical settings. We aimed to find an alternative method to improve the therapeutic efficacy of this therapy. We examined the effects of oral preloading with various analogues of L-BPA in a xenograft tumour model and found that high-dose L-phenylalanine reduced the accumulation of L-BPA in the normal brain relative to tumour tissue. As a result, the maximum irradiation dose in the normal brain was 19.2% lower in the L-phenylalanine group relative to the control group. This study provides a simple strategy to improve the therapeutic efficacy of conventional boron compounds for BNCT for brain tumours and the possibility to widen the indication of BNCT to various kinds of other tumours. Copyright © 2015. Published by Elsevier Ireland Ltd.

Deep learning for brain tumor classification

NASA Astrophysics Data System (ADS)

Paul, Justin S.; Plassard, Andrew J.; Landman, Bennett A.; Fabbri, Daniel

2017-03-01

Recent research has shown that deep learning methods have performed well on supervised machine learning, image classification tasks. The purpose of this study is to apply deep learning methods to classify brain images with different tumor types: meningioma, glioma, and pituitary. A dataset was publicly released containing 3,064 T1-weighted contrast enhanced MRI (CE-MRI) brain images from 233 patients with either meningioma, glioma, or pituitary tumors split across axial, coronal, or sagittal planes. This research focuses on the 989 axial images from 191 patients in order to avoid confusing the neural networks with three different planes containing the same diagnosis. Two types of neural networks were used in classification: fully connected and convolutional neural networks. Within these two categories, further tests were computed via the augmentation of the original 512×512 axial images. Training neural networks over the axial data has proven to be accurate in its classifications with an average five-fold cross validation of 91.43% on the best trained neural network. This result demonstrates that a more general method (i.e. deep learning) can outperform specialized methods that require image dilation and ring-forming subregions on tumors.

Functional Magnetic Resonance Imaging for Preoperative Planning in Brain Tumour Surgery.

PubMed

Lau, Jonathan C; Kosteniuk, Suzanne E; Bihari, Frank; Megyesi, Joseph F

2017-01-01

Functional magnetic resonance imaging (fMRI) is being increasingly used for the preoperative evaluation of patients with brain tumours. The study is a retrospective chart review investigating the use of clinical fMRI from 2002 through 2013 in the preoperative evaluation of brain tumour patients. Baseline demographic and clinical data were collected. The specific fMRI protocols used for each patient were recorded. Sixty patients were identified over the 12-year period. The tumour types most commonly investigated were high-grade glioma (World Health Organization grade III or IV), low-grade glioma (World Health Organization grade II), and meningioma. Most common presenting symptoms were seizures (69.6%), language deficits (23.2%), and headache (19.6%). There was a predominance of left hemispheric lesions investigated with fMRI (76.8% vs 23.2% for right). The most commonly involved lobes were frontal (64.3%), temporal (33.9%), parietal (21.4%), and insular (7.1%). The most common fMRI paradigms were language (83.9%), motor (75.0%), sensory (16.1%), and memory (10.7%). The majority of patients ultimately underwent a craniotomy (75.0%), whereas smaller groups underwent stereotactic biopsy (8.9%) and nonsurgical management (16.1%). Time from request for fMRI to actual fMRI acquisition was 3.1±2.3 weeks. Time from fMRI acquisition to intervention was 4.9±5.5 weeks. We have characterized patient demographics in a retrospective single-surgeon cohort undergoing preoperative clinical fMRI at a Canadian centre. Our experience suggests an acceptable wait time from scan request to scan completion/analysis and from scan to intervention.

Odontogenic tumours: A review of 266 cases.

PubMed

Lawal, Ahmed O; Adisa, Akinyele O; Olusanya, Adeola A

2013-02-01

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. 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. 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. 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.

Brain tumor classification and segmentation using sparse coding and dictionary learning.

PubMed

Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

2016-08-01

This paper presents a novel fully automatic framework for multi-class brain tumor classification and segmentation using a sparse coding and dictionary learning method. The proposed framework consists of two steps: classification and segmentation. The classification of the brain tumors is based on brain topology and texture. The segmentation is based on voxel values of the image data. Using K-SVD, two types of dictionaries are learned from the training data and their associated ground truth segmentation: feature dictionary and voxel-wise coupled dictionaries. The feature dictionary consists of global image features (topological and texture features). The coupled dictionaries consist of coupled information: gray scale voxel values of the training image data and their associated label voxel values of the ground truth segmentation of the training data. For quantitative evaluation, the proposed framework is evaluated using different metrics. The segmentation results of the brain tumor segmentation (MICCAI-BraTS-2013) database are evaluated using five different metric scores, which are computed using the online evaluation tool provided by the BraTS-2013 challenge organizers. Experimental results demonstrate that the proposed approach achieves an accurate brain tumor classification and segmentation and outperforms the state-of-the-art methods.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-08-04

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. 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. 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). 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

P15.04DEVELOPMENT OF A NEW QUESTIONNAIRE TO MEASURE INSTRUMENTAL ACTIVITIES OF DAILY LIVING (I-ADL) IN PATIENTS WITH PRIMARY BRAIN TUMOURS: RESULTS OF PHASE 1

PubMed Central

Dirven, L.; Meijer, W.; Sikkes, S.A.M.; Reijneveld, J.C.; Aaronson, N.K.; Uitdehaag, B.M.J.; Taphoorn, M. J. B.

2014-01-01

BACKGROUND: Next to health-related quality of life, information on daily life functioning in brain tumour patients is essential. Instrumental Activities of Daily Living (I-ADL) are complex daily activities, such as food preparation and shopping. I-ADL may be negatively influenced by a cognitive decline, characteristic of brain tumor patients. OBJECTIVE: In the first phase of this project, we generated a provisional list of items measuring I-ADL that are relevant for primary brain tumour patients. METHODS: Questions from the Amsterdam IADL Questionnaire®, a 70-item questionnaire developed and validated to measure I-ADL in patients with dementia, were evaluated for relevance to brain tumour patients. In addition, new activities were generated. In the first step, 6 professional experts in neuro-oncology and 10 primary brain tumour patient-proxy dyads were asked to evaluate items in the Amsterdam IADL Questionnaire®. Experts had to indicate if these activities (1) could be considered as I-ADL, (2) were affected in brain tumour patients and (3) were clearly formulated. Patients and their proxies only needed to answer the latter two questions. In the second step, the same 6 experts, and in addition 6 other patient-proxy dyads were asked to generate new activities. To do so, in-depth interviews were conducted. Decision rules were determined to aid in deciding which items to retain (step 1) or to add (step 2). Activities that were indicated as IADL, affected and clearly formulated were retained. Activities that were considered as IADL and affected, but not clearly formulated, were rephrased. New activities that were frequently generated were added to the existing list of items. RESULTS: In step 1, experts indicated that 37% of the activities described in the Amsterdam IADL questionnaire® fulfilled all three criteria: conform the definition of IADL, clearly formulated and affected in brain tumour patients. Twenty-three per cent of the activities were affected and conform

Mobile phone use and risk of brain tumours: a systematic review of association between study quality, source of funding, and research outcomes.

PubMed

Prasad, Manya; Kathuria, Prachi; Nair, Pallavi; Kumar, Amit; Prasad, Kameshwar

2017-05-01

Mobile phones emit electromagnetic radiations that are classified as possibly carcinogenic to humans. Evidence for increased risk for brain tumours accumulated in parallel by epidemiologic investigations remains controversial. This paper aims to investigate whether methodological quality of studies and source of funding can explain the variation in results. PubMed and Cochrane CENTRAL searches were conducted from 1966 to December 2016, which was supplemented with relevant articles identified in the references. Twenty-two case control studies were included for systematic review. Meta-analysis of 14 case-control studies showed practically no increase in risk of brain tumour [OR 1.03 (95% CI 0.92-1.14)]. However, for mobile phone use of 10 years or longer (or >1640 h), the overall result of the meta-analysis showed a significant 1.33 times increase in risk. The summary estimate of government funded as well as phone industry funded studies showed 1.07 times increase in odds which was not significant, while mixed funded studies did not show any increase in risk of brain tumour. Metaregression analysis indicated that the association was significantly associated with methodological study quality (p < 0.019, 95% CI 0.009-0.09). Relationship between source of funding and log OR for each study was not statistically significant (p < 0.32, 95% CI 0.036-0.010). We found evidence linking mobile phone use and risk of brain tumours especially in long-term users (≥10 years). Studies with higher quality showed a trend towards high risk of brain tumour, while lower quality showed a trend towards lower risk/protection.

High field strength magnetic resonance imaging in paediatric brain tumour surgery--its role in prevention of early repeat resections.

PubMed

Avula, Shivaram; Pettorini, Benedetta; Abernethy, Laurence; Pizer, Barry; Williams, Dawn; Mallucci, Conor

2013-10-01

The purpose of this study is to compare the surgical and imaging outcome in children who underwent brain tumour surgery with intention of complete tumour resection, prior to and following the start of intra-operative MRI (ioMRI) service. ioMRI service for brain tumour resection commenced in October 2009. A cohort of patients operated between June 2007 and September 2009 with a pre-surgical intention of complete tumour resection were selected (Group A). A similar number of consecutive cases were selected from a prospective database of patients undergoing ioMRI (Group B). The demographics, imaging, pathology and surgical outcome of both groups were compared. Thirty-six of 47 cases from Group A met the inclusion criterion and 36 cases were selected from Group B; 7 of the 36 cases in Group A had unequivocal evidence of residual tumour on the post-operative scan; 5 (14%) of them underwent repeat resection within 6 months post-surgery. In Group B, ioMRI revealed unequivocal evidence of residual tumour in 11 of the 36 cases following initial resection. In 10 of these 11 cases, repeat resections were performed during the same surgical episode and none of these 11 cases required repeat surgery in the following 6 months. Early repeat resection rate was significantly different between both groups (p = 0.003). Following the advent of ioMRI at our institution, the need for repeat resection within 6 months has been prevented in cases where ioMRI revealed unequivocal evidence of residual tumour.

Detection of comorbidities and synchronous primary tumours via thoracic radiography and abdominal ultrasonography and their influence on treatment outcome in dogs with soft tissue sarcomas, primary brain tumours and intranasal tumours.

PubMed

Bigio Marcello, A; Gieger, T L; Jiménez, D A; Granger, L Abbigail

2015-12-01

Canine soft tissue sarcomas (STS), primary brain tumours and intranasal tumours are commonly treated with radiotherapy (RT). Given the low metastatic potential of these tumours, recommendations regarding imaging tests as staging are variable among institutions. The purpose of our study was to describe thoracic radiographic and abdominal ultrasonographic findings in dogs with these neoplasms and to investigate association of abnormal findings with alterations in recommended treatment. Medical records from 101 dogs, each having thoracic radiographs and abdominal ultrasound performed as part of their staging, were reviewed. In 98 of 101 (97%), imaging abnormalities were detected, 27% of which were further investigated with fine needle aspiration cytology or biopsy. Nine percent of the detected abnormalities were considered serious comorbidities that altered treatment recommendations, including 3 (3%) which were confirmed as synchronous primary neoplasms. These findings may influence recommendations regarding the decision to perform thoracic radiographs and abdominal ultrasound prior to initiation of RT. © 2013 John Wiley & Sons Ltd.

Brain tumor segmentation based on local independent projection-based classification.

PubMed

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

2014-10-01

Brain tumor segmentation is an important procedure for early tumor diagnosis and radiotherapy planning. Although numerous brain tumor segmentation methods have been presented, enhancing tumor segmentation methods is still challenging because brain tumor MRI images exhibit complex characteristics, such as high diversity in tumor appearance and ambiguous tumor boundaries. To address this problem, we propose a novel automatic tumor segmentation method for MRI images. This method treats tumor segmentation as a classification problem. Additionally, the local independent projection-based classification (LIPC) method is used to classify each voxel into different classes. A novel classification framework is derived by introducing the local independent projection into the classical classification model. Locality is important in the calculation of local independent projections for LIPC. Locality is also considered in determining whether local anchor embedding is more applicable in solving linear projection weights compared with other coding methods. Moreover, LIPC considers the data distribution of different classes by learning a softmax regression model, which can further improve classification performance. In this study, 80 brain tumor MRI images with ground truth data are used as training data and 40 images without ground truth data are used as testing data. The segmentation results of testing data are evaluated by an online evaluation tool. The average dice similarities of the proposed method for segmenting complete tumor, tumor core, and contrast-enhancing tumor on real patient data are 0.84, 0.685, and 0.585, respectively. These results are comparable to other state-of-the-art methods.

Evaluating the apparent diffusion coefficient in MRI studies as a means of determining paediatric brain tumour stages.

PubMed

Domínguez-Pinilla, N; Martínez de Aragón, A; Diéguez Tapias, S; Toldos, O; Hinojosa Bernal, J; Rigal Andrés, M; González-Granado, L I

2016-09-01

The apparent diffusion coefficient (ADC) in MRI seems to be related to cellularity in brain tumours. Its utility as a tool for distinguishing between histological types and tumour stages remains controversial. We retrospectively evaluated children diagnosed with CNS tumours between January 2008 and December 2013. Data collected were age, sex, histological diagnosis, and location of the tumour. We evaluated the ADC and ADC ratio and correlated those values with histological diagnoses. The study included 55 patients with a median age of 6 years. Histological diagnoses were pilocytic astrocytoma (40%), anaplastic ependymoma (16.4%), ganglioglioma (10.9%), glioblastoma (7.3%), medulloblastoma (5.5%), and other (20%). Tumours could also be classified as low-grade (64%) or high-grade (36%). Mean ADC was 1.3 for low-grade tumours and 0.9 for high-grade tumours (p=.004). Mean ADC ratios were 1.5 and 1.2 for low and high-grade tumours respectively (p=.025). There were no significant differences in ADC/ADC ratio between different histological types. ADC and ADC ratio may be useful in imaging-study based differential diagnosis of low and high-grade tumours, but they are not a substitute for an anatomical pathology study. Copyright © 2014 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Unsupervised classification of operator workload from brain signals.

PubMed

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

2016-06-01

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

Unsupervised classification of operator workload from brain signals

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Evidence for label-retaining tumour-initiating cells in human glioblastoma

PubMed Central

Deleyrolle, Loic P.; Harding, Angus; Cato, Kathleen; Siebzehnrubl, Florian A.; Rahman, Maryam; Azari, Hassan; Olson, Sarah; Gabrielli, Brian; Osborne, Geoffrey; Vescovi, Angelo

2011-01-01

Individual tumour cells display diverse functional behaviours in terms of proliferation rate, cell–cell interactions, metastatic potential and sensitivity to therapy. Moreover, sequencing studies have demonstrated surprising levels of genetic diversity between individual patient tumours of the same type. Tumour heterogeneity presents a significant therapeutic challenge as diverse cell types within a tumour can respond differently to therapies, and inter-patient heterogeneity may prevent the development of general treatments for cancer. One strategy that may help overcome tumour heterogeneity is the identification of tumour sub-populations that drive specific disease pathologies for the development of therapies targeting these clinically relevant sub-populations. Here, we have identified a dye-retaining brain tumour population that displays all the hallmarks of a tumour-initiating sub-population. Using a limiting dilution transplantation assay in immunocompromised mice, label-retaining brain tumour cells display elevated tumour-initiation properties relative to the bulk population. Importantly, tumours generated from these label-retaining cells exhibit all the pathological features of the primary disease. Together, these findings confirm dye-retaining brain tumour cells exhibit tumour-initiation ability and are therefore viable targets for the development of therapeutics targeting this sub-population. PMID:21515906

Phyllodes tumours of the breast: a consensus review

PubMed Central

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

2016-01-01

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

The occurrence of benign brain tumours in transgender individuals during cross-sex hormone treatment.

PubMed

Nota, Nienke M; Wiepjes, Chantal M; de Blok, Christel J M; Gooren, Louis J G; Peerdeman, Saskia M; Kreukels, Baudewijntje P C; den Heijer, Martin

2018-04-23

Benign brain tumours may be hormone sensitive. To induce physical characteristics of the desired gender, transgender individuals often receive cross-sex hormone treatment, sometimes in higher doses than hypogonadal individuals. To date, long-term (side) effects of cross-sex hormone treatment are largely unknown. In the present retrospective chart study we aimed to compare the incidence of common benign brain tumours: meningiomas, pituitary adenomas (non-secretive and secretive), and vestibular schwannomas in transgender individuals receiving cross-sex hormone treatment, with those reported in general Dutch or European populations. This study was performed at the VU University Medical Centre in the Netherlands and consisted of 2555 transwomen (median age at start of cross-sex hormone treatment: 31 years, interquartile range 23-41) and 1373 transmen (median age 23 years, interquartile range 18-31) who were followed for 23 935 and 11 212 person-years, respectively. For each separate brain tumour, standardized incidence ratios with 95% confidence intervals were calculated. In transwomen (male sex assigned at birth, female gender identity), eight meningiomas, one non-secretive pituitary adenoma, nine prolactinomas, and two vestibular schwannomas occurred. The incidence of meningiomas was higher in transwomen than in a general European female population (standardized incidence ratio 4.1, 95% confidence interval 1.9-7.7) and male population (11.9, 5.5-22.7). Similar to meningiomas, prolactinomas occurred more often in transwomen compared to general Dutch females (4.3, 2.1-7.9) and males (26.5, 12.9-48.6). Noteworthy, most transwomen had received orchiectomy but still used the progestogenic anti-androgen cyproterone acetate at time of diagnosis. In transmen (female sex assigned at birth, male gender identity), two cases of somatotrophinomas were observed, which was higher than expected based on the reported incidence rate in a general European population (incidence rate

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

PubMed

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

2008-02-12

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

Working plan for the use of patient-reported outcome measures in adults with brain tumours: a Response Assessment in Neuro-Oncology (RANO) initiative.

PubMed

Dirven, Linda; Armstrong, Terri S; Blakeley, Jaishri O; Brown, Paul D; Grant, Robin; Jalali, Rakesh; Leeper, Heather; Mendoza, Tito; Nayak, Lakshmi; Reijneveld, Jaap C; Le Rhun, Emilie; Walbert, Tobias; Weller, Michael; Wen, Patrick Y; Taphoorn, Martin J B

2018-03-01

The Response Assessment in Neuro-Oncology-Patient-Reported Outcome (RANO-PRO) working group is an international multidisciplinary collaboration that provides guidance on the use of patient-reported outcome (PRO) measures in clinical trials and practice for adult patients with brain tumours. Findings from both PROs and traditional outcome measures, such as survival, and clinical or radiological response, are essential to inform the research community, policy makers, physicians, and patients in the treatment decision-making process. Previous initiatives in oncology have focused on guidelines concerning the collection, analysis, interpretation, and reporting of PRO data. However, we recommend the application of appropriate PRO instruments, with respect to its content and measurement properties (ie, research question, content validity, and other measurement properties), in brain tumour research. PROs should be well defined and reliable to generate high-quality evidence, and our recommendations on the use of specific PRO measures could help to improve the quality of PRO evidence derived from neuro-oncological studies, and might add a new dimension in how the value of therapeutics is assessed in patients with brain tumours. In this Policy Review, we present the RANO-PRO working plan for the use of PROs in adults with brain tumours. Copyright © 2018 Elsevier Ltd. All rights reserved.

Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach.

PubMed

Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Amin, Hafeez Ullah; Hussain, Muhammad

2017-01-01

Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful. In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes. Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature. The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

Application of wavelet transformation and adaptive neighborhood based modified backpropagation (ANMBP) for classification of brain cancer

NASA Astrophysics Data System (ADS)

Werdiningsih, Indah; Zaman, Badrus; Nuqoba, Barry

2017-08-01

This paper presents classification of brain cancer using wavelet transformation and Adaptive Neighborhood Based Modified Backpropagation (ANMBP). Three stages of the processes, namely features extraction, features reduction, and classification process. Wavelet transformation is used for feature extraction and ANMBP is used for classification process. The result of features extraction is feature vectors. Features reduction used 100 energy values per feature and 10 energy values per feature. Classifications of brain cancer are normal, alzheimer, glioma, and carcinoma. Based on simulation results, 10 energy values per feature can be used to classify brain cancer correctly. The correct classification rate of proposed system is 95 %. This research demonstrated that wavelet transformation can be used for features extraction and ANMBP can be used for classification of brain cancer.

Segmentation, feature extraction, and multiclass brain tumor classification.

PubMed

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

2013-12-01

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.

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Efficacy and safety of prophylactic levetiracetam in supratentorial brain tumour surgery: a systematic review and meta‐analysis

PubMed Central

Tsaousi, Georgia; Apostolidou, Eirini; Karakoulas, Konstantinos; Kouvelas, Dimitrios; Amaniti, Ekaterini

2016-01-01

Aims The aim of this study was to perform an up‐to‐date systematic review and meta‐analysis on the efficacy and safety of prophylactic administration of levetiracetam in brain tumour patients. Method A systematic review of studies published until April 2015 was conducted using Scopus/Elsevier, EMBASE and MEDLINE. The search was limited to articles reporting results from adult patients, suffering from brain tumour, undergoing supratentorial craniotomy for tumour resection or biopsy and administered levetiracetam in the perioperative period for seizure prophylaxis. Outcomes included the efficacy and safety of levetiracetam, as well as the tolerability of the specific regimen, defined by the discontinuation of the treatment due to side effects. Results The systematic review included 1148 patients from 12 studies comparing levetiracetam with no treatment, phenytoin and valproate, while only 243 patients from three studies, comparing levetiracetam vs phenytoin efficacy and safety, were included in the meta‐analysis. The combined results from the meta‐analysis showed that levetiracetam administration was followed by significantly fewer seizures than treatment with phenytoin (OR = 0.12 [0.03–0.42]: χ2 = 1.76: I2 = 0%). Analysis also showed significantly fewer side effects in patients receiving levetiracetam, compared to other groups (P < 0.05). The combined results showed fewer side effects in the levetiracetam group compared to the phenytoin group (OR = 0.65 [0.14–2.99]: χ2 = 8.79: I2 = 77%). Conclusions The efficacy of prophylaxis with levetiracetam seems to be superior to that with phenytoin and valproate administration. Moreover, levetiracetam use demonstrates fewer side effects in brain tumour patients. Nevertheless, high risk of bias and moderate methodological quality must be taken into account when considering these results. PMID:26945547

EEG classification of emotions using emotion-specific brain functional network.

PubMed

Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

2015-08-01

The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.

The new WHO 2016 classification of brain tumors-what neurosurgeons need to know.

PubMed

Banan, Rouzbeh; Hartmann, Christian

2017-03-01

The understanding of molecular alterations of tumors has severely changed the concept of classification in all fields of pathology. The availability of high-throughput technologies such as next-generation sequencing allows for a much more precise definition of tumor entities. Also in the field of brain tumors a dramatic increase of knowledge has occurred over the last years partially calling into question the purely morphologically based concepts that were used as exclusive defining criteria in the WHO 2007 classification. Review of the WHO 2016 classification of brain tumors as well as a search and review of publications in the literature relevant for brain tumor classification from 2007 up to now. The idea of incorporating the molecular features in classifying tumors of the central nervous system led the authors of the new WHO 2016 classification to encounter inevitable conceptual problems, particularly with respect to linking morphology to molecular alterations. As a solution they introduced the concept of a "layered diagnosis" to the classification of brain tumors that still allows at a lower level a purely morphologically based diagnosis while partially forcing the incorporation of molecular characteristics for an "integrated diagnosis" at the highest diagnostic level. In this context the broad availability of molecular assays was debated. On the one hand molecular antibodies specifically targeting mutated proteins should be available in nearly all neuropathological laboratories. On the other hand, different high-throughput assays are accessible only in few first-world neuropathological institutions. As examples oligodendrogliomas are now primarily defined by molecular characteristics since the required assays are generally established, whereas molecular grouping of ependymomas, found to clearly outperform morphologically based tumor interpretation, was rejected from inclusion in the WHO 2016 classification because the required assays are currently only

Fitness to drive in patients with brain tumours: the influence of mandatory reporting legislation on radiation oncologists in Canada.

PubMed

Louie, A V; D'Souza, D P; Palma, D A; Bauman, G S; Lock, M; Fisher, B; Patil, N; Rodrigues, G B

2012-06-01

Certain jurisdictions in Canada legally require that physicians report unfit drivers. Physician attitudes and patterns of practice have yet to be evaluated in Canada for patients with brain tumours. We conducted a survey of 97 radiation oncologists, eliciting demographics, knowledge of reporting laws, and attitudes on reporting guidelines for unfit drivers. Eight scenarios with varying disability levels were presented to determine the likelihood of a patient being reported as unfit to drive. Statistical comparisons were made using the Fisher exact test. Of physicians approached, 99% responded, and 97 physicians participated. Most respondents (87%) felt that laws in their province governing the reporting of medically unfit drivers were unclear. Of the responding physicians, 23 (24%) were unable to correctly identify whether their province had mandatory reporting legislation. Physicians from provinces without mandatory reporting legislation were significantly less likely to consider reporting patients to provincial authorities (p = 0.001), and for all clinical scenarios, the likelihood of reporting significantly depended on the physician's provincial legal obligations. The presence of provincial legislation is of primary importance in determining whether physicians will report brain tumour patients to drivers' licensing authorities. In Canada, clear guidelines have to be developed to help in the assessment of whether brain tumour patients should drive.

Analysis of dual tree M-band wavelet transform based features for brain image classification.

PubMed

Ayalapogu, Ratna Raju; Pabboju, Suresh; Ramisetty, Rajeswara Rao

2018-04-29

The most complex organ in the human body is the brain. The unrestrained growth of cells in the brain is called a brain tumor. The cause of a brain tumor is still unknown and the survival rate is lower than other types of cancers. Hence, early detection is very important for proper treatment. In this study, an efficient computer-aided diagnosis (CAD) system is presented for brain image classification by analyzing MRI of the brain. At first, the MRI brain images of normal and abnormal categories are modeled by using the statistical features of dual tree m-band wavelet transform (DTMBWT). A maximum margin classifier, support vector machine (SVM) is then used for the classification and validated with k-fold approach. Results show that the system provides promising results on a repository of molecular brain neoplasia data (REMBRANDT) with 97.5% accuracy using 4 th level statistical features of DTMBWT. Viewing the experimental results, we conclude that the system gives a satisfactory performance for the brain image classification. © 2018 International Society for Magnetic Resonance in Medicine.

Long-term use of cellular phones and brain tumours: increased risk associated with use for > or =10 years.

PubMed

Hardell, Lennart; Carlberg, Michael; Söderqvist, Fredrik; Mild, Kjell Hansson; Morgan, L Lloyd

2007-09-01

To evaluate brain tumour risk among long-term users of cellular telephones. Two cohort studies and 16 case-control studies on this topic were identified. Data were scrutinised for use of mobile phone for > or =10 years and ipsilateral exposure if presented. The cohort study was of limited value due to methodological shortcomings in the study. Of the 16 case-control studies, 11 gave results for > or =10 years' use or latency period. Most of these results were based on low numbers. An association with acoustic neuroma was found in four studies in the group with at least 10 years' use of a mobile phone. No risk was found in one study, but the tumour size was significantly larger among users. Six studies gave results for malignant brain tumours in that latency group. All gave increased odd ratios (OR), especially for ipsilateral exposure. In a meta-analysis, ipsilateral cell phone use for acoustic neuroma was OR = 2.4 (95% CI 1.1 to 5.3) and OR = 2.0, (1.2 to 3.4) for glioma using a tumour latency period of > or =10 years. Results from present studies on use of mobile phones for > or =10 years give a consistent pattern of increased risk for acoustic neuroma and glioma. The risk is highest for ipsilateral exposure.

[Hepatocellular tumours in noncirrhotic liver tissue].

PubMed

Goltz, D; Fischer, H-P

2015-11-01

In recent years, the spectrum of tissue-based diagnostics of hepatocellular tumours has changed due to novel molecular pathological findings. Innovative radiographics filter out small lesions and ambiguous tumours for bioptical sampling. The spectrum of these tumours includes hepatocellular carcinoma, hepatocellular adenomas, focal nodular hyperplasia and macroregenerative nodules. Primarily, morphological analysis should identify the dignity of a lesion. After exclusion of HCC and reactive liver cell nodules, hepatocellular adenomas should be further subclassified based on immunohistochemical/molecular pathological criteria according to the WHO classification of liver tumours. This procedure provides significant additional information regarding the prognosis and therapeutic implications of hepatocellular adenomas.

MORPHOLOGICAL PATTERN AND FREQUENCY OF CENTRAL NERVOUS SYSTEM TUMOURS IN CHILDREN.

PubMed

Bilqees, Fatima; Samina, Khaleeq; Mohammad, Tahir; Khaleeq-uz-Zamaan

2016-01-01

Recent studies, including a comprehensive study by National Cancer Institute, have shown that a significant increase in the incidence of childhood brain tumours makes them the most common paediatric tumour. The objectives of this study were to determine the frequency of central nervous system tumours in paediatric age group (0-12 years), and to segregate various morphologic types according to WHO classification. The study included consecutive cases of central nervous system tumours diagnosed in children in the histopathology department at Federal Government Polyclinic, PGMI, Islamabad, during a period of 4.8 years (Jan 2009-Aug 2013). The initial histopathological evaluation of these lesions was performed on H&E stained sections of paraffin embedded tissues. Special stains and immunohistochemistry were performed whenever indicated. Out of 75 cases, 34 (45.3%) were astrocytic tumours, including 16 (47.1%) Pilocytic astrocytomas (WHO Grade-I), 1 (2.9%) diffuse fibrillary astrocytoma (WHO Grade-II), 1 (2.9%) anaplastic astrocytoma (WHO Grade-III) and 16(47.1%) glioblastoma multiforme (WHO Grade-IV); 18 (24%) were embryonal tumours including 17 (94.4%) medulloblastoma (WHO Grade-IV) and 1 (5.6%) neuroblastoma (WHO Grade IV); 10 (13.3%) were craniopharyngiomas (WHO Grade-I) and 5 (6.7%) were ependymal tumours including 1 (20%) myxopapillary ependymoma (WHO Grade-I) and 4 (80%) ependymomas (WHO Grade-II). Miscellaneous entities included 3 (4%) choroid plexus tumours; 1 (2%) anaplastic oligodendroglioma (WHO Grade-III); 1 (2%) atypical meningioma (WHO Grade-II); 1 (2%) schwannoma (WHO Grade-I); 1 (2%) neurofibroma (WHO Grade-I) and 1 (2%) lipoma (WHO Grade-I). Astrocytic tumours are the most common central nervous system tumours in paediatric age group and high grade lesions (WHO Grade-IV) constitute the largest category (45.3%).

Interactions between occupational exposure to extremely low frequency magnetic fields and chemicals for brain tumour risk in the INTEROCC study.

PubMed

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

2017-11-01

In absence of clear evidence regarding possible effects of occupational chemical exposures on brain tumour aetiology, it is worthwhile to explore the hypothesis that such exposures might act on brain tumour risk in interaction with occupational exposure to extremely low frequency magnetic fields (ELF). INTEROCC is a seven-country (Australia, Canada, France, Germany, Israel, New Zealand and UK), population-based, case-control study, based on the larger INTERPHONE study. Incident cases of primary glioma and meningioma were ascertained from 2000 to 2004. Job titles were coded into standard international occupational classifications and estimates of ELF and chemical exposures were assigned based on job-exposure matrices. Dichotomous indicators of cumulative ELF (≥50th vs <50th percentile, 1-4 year exposure time window) and chemical exposures (ever vs never, 5-year lag) were created. Interaction was assessed on both the additive and multiplicative scales. A total of 1939 glioma cases, 1822 meningioma cases and 5404 controls were included in the analysis, using conditional logistic regression. There was no clear evidence for interactions between ELF and any of the chemical exposures assessed for either glioma or meningioma risk. For glioma, subjects in the low ELF/metal exposed group had a lower risk than would be predicted from marginal effects. Results were similar according to different exposure time windows, to cut-points of exposure or in exposed-only analyses. There was no clear evidence for interactions between occupational ELF and chemical exposures in relation to glioma or meningioma risk observed. Further research with more refined estimates of occupational exposures is recommended. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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

PubMed Central

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

2016-01-01

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

Comparison of the prevalence of KRAS-LCS6 polymorphism (rs61764370) within different tumour types (colorectal, breast, non-small cell lung cancer and brain tumours). A study of the Czech population.

PubMed

Uvirova, Magdalena; Simova, Jarmila; Kubova, Barbora; Dvorackova, Nina; Tomaskova, Hana; Sedivcova, Monika; Dite, Petr

2015-09-01

A germline SNP (rs61764370) is located in a let-7 complementary site (LCS6) in the 3'UTR of KRAS oncogene, and it was found to alter the binding capability of the mature let-7 microRNA to the KRAS mRNA. The aim of the study was to evaluate the frequency of the KRAS-LCS6 variant allele in different cancer types that included patients with colorectal cancer (CRC), breast cancer (BC), non-small cell lung cancer (NSCLC) and brain tumour patient subgroups from the Czech Republic. The occurrence of this genetic variant was correlated with the presence of selected somatic mutations representing predictive biomarkers in the respective tumours. DNA of tumour tissues was isolated from 428 colorectal cancer samples, 311 non-small cell lung cancer samples, 195 breast cancer samples and 151 samples with brain tumour. Analysis of SNP (rs61764370) was performed by the PCR+RFLP method and direct sequencing. KRAS, BRAF and EGFR mutation status was assessed using real-time PCR. The status of the HER2 gene was assessed using the FISH method. The KRAS-LCS6 TG genotype has been detected in 16.4% (32/195) of breast cancer cases (in HER2 positive breast cancer 3.3%, in HER2 negative breast cancer 20.1%), in 12.4% (53/428) of CRC cases (KRAS/BRAF wild type CRC in 10.6%, KRAS mutant CRC in 10.1%, BRAF V600E mutant CRC in 18.5%), in 13.2% (41/311) of NSCLC samples, (EGFR mutant NSCLC patients in 8%, EGFR wild type NSCLC in 12.9%), and 17.9% (27/151) of brain tumour cases. The KRAS-LCS6 TG genotype was not significantly different across the studied tumours. In our study, the GG genotype has not been found among the cancer samples. Based on the findings, it is concluded that the occurrence of the KRAS-LCS6 TG genotype was statistically significantly different in association with status of the HER2 gene in breast cancer. Furthermore, significant association between the mutation status of analysed somatic variants in genes of the EGFR signalling pathway (KRAS, BRAF, EGFR) and the KRAS-LCS6

Brain tumor classification of microscopy images using deep residual learning

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

[Low field intra-operative magnetic resonance imaging for brain tumour surgery: preliminary experience].

PubMed

Roldán, Pedro; García, Sergio; González, Josep; Reyes, Luis Alberto; Torales, Jorge; Valero, Ricard; Oleaga, Laura; Enseñat, Joaquim

Intra-operative magnetic resonance imaging (iMRI) is a recently introduced tool in the most advanced neurosurgical operating rooms worldwide. We present our preliminary experience in brain tumour surgery with low field PoleStar N30® intraoperative MRI since its introduction in 2013 in the Barcelona Clinic Hospital. A prospective non-randomised study was conducted on cases operated on using iMRI and intention of complete removal up to October 2015. A record was made of the data as regards surgical times, resection rates, histological diagnosis, hospital stay, and survival rates during follow-up. The study included 50 patients, with a mean age of 55 years (±13.7), a preoperative mean Karnofsky of 92 (being 81 post-operatively), and a mean follow-up of 10.5 months (±6.5). There were 26% re-operations due to recurrence. High-grade gliomas were reported in 56%, low-grade gliomas in 24%, and 20% "Other" tumours. Overall hospital stay was 10 days (±4.5). Depending on the histologiacl diagnosis, the "Others" group had a longer hospital stay. Overall, there were 52% complete removal, 18% of maximum removals, and 30% of partial removals. The overall survival rates during follow-up was 84%. iMRI is a safe and effective tool for brain tumour surgery. Its use allows an increase in resection rates, and minimises post-operative complications. Its implementation involves an increase in surgical time, which improves with the characteristic learning curve. More studies are needed to establish its role in the long-term survival of patients. Copyright © 2016 Sociedad Española de Neurocirugía. Publicado por Elsevier España, S.L.U. All rights reserved.

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

PubMed

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

2016-02-16

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

Use of mobile phones and risk of brain tumours: update of Danish cohort study.

PubMed

Frei, Patrizia; Poulsen, Aslak H; Johansen, Christoffer; Olsen, Jørgen H; Steding-Jessen, Marianne; Schüz, Joachim

2011-10-19

To investigate the risk of tumours in the central nervous system among Danish mobile phone subscribers. Nationwide cohort study. Denmark. All Danes aged ≥ 30 and born in Denmark after 1925, subdivided into subscribers and non-subscribers of mobile phones before 1995. Risk of tumours of the central nervous system, identified from the complete Danish Cancer Register. Sex specific incidence rate ratios estimated with log linear Poisson regression models adjusted for age, calendar period, education, and disposable income. 358,403 subscription holders accrued 3.8 million person years. In the follow-up period 1990-2007, there were 10,729 cases of tumours of the central nervous system. The risk of such tumours was close to unity for both men and women. When restricted to individuals with the longest mobile phone use--that is, ≥ 13 years of subscription--the incidence rate ratio was 1.03 (95% confidence interval 0.83 to 1.27) in men and 0.91 (0.41 to 2.04) in women. Among those with subscriptions of ≥ 10 years, ratios were 1.04 (0.85 to 1.26) in men and 1.04 (0.56 to 1.95) in women for glioma and 0.90 (0.57 to 1.42) in men and 0.93 (0.46 to 1.87) in women for meningioma. There was no indication of dose-response relation either by years since first subscription for a mobile phone or by anatomical location of the tumour--that is, in regions of the brain closest to where the handset is usually held to the head. In this update of a large nationwide cohort study of mobile phone use, there were no increased risks of tumours of the central nervous system, providing little evidence for a causal association.

Evaluation of the effects of swainsonine, captopril, tangeretin and nobiletin on the biological behaviour of brain tumour cells in vitro.

PubMed

Rooprai, H K; Kandanearatchi, A; Maidment, S L; Christidou, M; Trillo-Pazos, G; Dexter, D T; Rucklidge, G J; Widmer, W; Pilkington, G J

2001-02-01

Although intrinsic tumours of the brain seldom metastasize to distant sites, their diffuse, infiltrative-invasive growth within the brain generally precludes successful surgical and adjuvant therapy. Hence, attention has now focused on novel therapeutic approaches to combat brain tumours that include the use of anti-invasive and anti-proliferative agents. The effect of four anti-invasive agents, swainsonine (a locoweed alkaloid), captopril (an anti-hypertensive drug), tangeretin and nobiletin (both citrus flavonoids), were investigated on various parameters of brain tumour invasion such as matrix metalloproteinase (MMP) secretion, migration, invasion and adhesion. A standard cytotoxicity assay was used to optimize working concentrations of the drugs on seven human brain tumour-derived cell lines of various histological type and grade of malignancy. A qualitative assessment by gelatin zymography revealed that the effect of these agents varied between the seven cell lines such that the low grade pilocytic astrocytoma was unaffected by three of the agents. In contrast, downregulation of the two gelatinases, MMP-2 and MMP-9 was seen in the grade 3 astrocytoma irrespective of which agent was used. Generally, swainsonine was the least effective whereas the citrus flavonoids, particularly nobiletin, showed the greatest downregulation of secretion of the MMPs. Furthermore, captopril and nobiletin were most efficient at inhibiting invasion, migration and adhesion in four representative cell lines (an ependymoma, a grade II oligoastrocytoma, an anaplastic astrocytoma and a glioblastoma multiforme). Yet again, the effects of the four agents varied between the four cell lines. Nobiletin was, nevertheless, the most effective agent used in these assays. In conclusion, the differential effects seen on the various parameters studied by these putative anti-invasive agents may be the result of interference with MMPs and other mechanisms underlying the invasive phenotype. From these

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

NASA Astrophysics Data System (ADS)

Kundi, Michael

2010-11-01

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.

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

Burke, Elinor; Grobler, Mariana; Elderfield, Kay; Bond, Frances; Crocker, Matthew; Taylor, Rohan; Bridges, Leslie R

2013-06-10

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). 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. 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.

DNA methylation-based classification and grading system for meningioma: a multicentre, retrospective analysis.

PubMed

Sahm, Felix; Schrimpf, Daniel; Stichel, Damian; Jones, David T W; Hielscher, Thomas; Schefzyk, Sebastian; Okonechnikov, Konstantin; Koelsche, Christian; Reuss, David E; Capper, David; Sturm, Dominik; Wirsching, Hans-Georg; Berghoff, Anna Sophie; Baumgarten, Peter; Kratz, Annekathrin; Huang, Kristin; Wefers, Annika K; Hovestadt, Volker; Sill, Martin; Ellis, Hayley P; Kurian, Kathreena M; Okuducu, Ali Fuat; Jungk, Christine; Drueschler, Katharina; Schick, Matthias; Bewerunge-Hudler, Melanie; Mawrin, Christian; Seiz-Rosenhagen, Marcel; Ketter, Ralf; Simon, Matthias; Westphal, Manfred; Lamszus, Katrin; Becker, Albert; Koch, Arend; Schittenhelm, Jens; Rushing, Elisabeth J; Collins, V Peter; Brehmer, Stefanie; Chavez, Lukas; Platten, Michael; Hänggi, Daniel; Unterberg, Andreas; Paulus, Werner; Wick, Wolfgang; Pfister, Stefan M; Mittelbronn, Michel; Preusser, Matthias; Herold-Mende, Christel; Weller, Michael; von Deimling, Andreas

2017-05-01

The WHO classification of brain tumours describes 15 subtypes of meningioma. Nine of these subtypes are allotted to WHO grade I, and three each to grade II and grade III. Grading is based solely on histology, with an absence of molecular markers. Although the existing classification and grading approach is of prognostic value, it harbours shortcomings such as ill-defined parameters for subtypes and grading criteria prone to arbitrary judgment. In this study, we aimed for a comprehensive characterisation of the entire molecular genetic landscape of meningioma to identify biologically and clinically relevant subgroups. In this multicentre, retrospective analysis, we investigated genome-wide DNA methylation patterns of meningiomas from ten European academic neuro-oncology centres to identify distinct methylation classes of meningiomas. The methylation classes were further characterised by DNA copy number analysis, mutational profiling, and RNA sequencing. Methylation classes were analysed for progression-free survival outcomes by the Kaplan-Meier method. The DNA methylation-based and WHO classification schema were compared using the Brier prediction score, analysed in an independent cohort with WHO grading, progression-free survival, and disease-specific survival data available, collected at the Medical University Vienna (Vienna, Austria), assessing methylation patterns with an alternative methylation chip. We retrospectively collected 497 meningiomas along with 309 samples of other extra-axial skull tumours that might histologically mimic meningioma variants. Unsupervised clustering of DNA methylation data clearly segregated all meningiomas from other skull tumours. We generated genome-wide DNA methylation profiles from all 497 meningioma samples. DNA methylation profiling distinguished six distinct clinically relevant methylation classes associated with typical mutational, cytogenetic, and gene expression patterns. Compared with WHO grading, classification by

Tumours of the soft (mesenchymal) tissues

PubMed Central

Weiss, E.

1974-01-01

This is a classification of tumours of fibrous tissue, fat, muscle, blood and lymph vessels, and mast cells, irrespective of the region of the body in which they arise. Tumours of fibrous tissue are divided into fibroma, fibrosarcoma (including “canine haemangiopericytoma”), other sarcomas, equine sarcoid, and various tumour-like lesions. The histological appearance of the tumours is described and illustrated with photographs. ImagesFig. 1Fig. 2Fig. 3Fig. 4Fig. 9Fig. 10Fig. 11Fig. 12Fig. 17Fig. 18Fig. 19Fig. 20Fig. 5Fig. 6Fig. 7Fig. 8Fig. 13Fig. 14Fig. 15Fig. 16 PMID:4371740

Pooled analysis of two Swedish case-control studies on the use of mobile and cordless telephones and the risk of brain tumours diagnosed during 1997-2003.

PubMed

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

2007-01-01

Here we present the pooled analysis of 2 case-control studies on the association of brain tumours with mobile phone use. Use of analogue cellular phones increased the risk for acoustic neuroma by 5%, 95% confidence interval (CI) = 2-9% per 100 hrs of use. The risk increased for astrocytoma grade III-IV with latency period with highest estimates using >10-year time period from first use of these phone types. The risk increased per one year of use of analogue phones by 10%, 95% CI = 6-14%, digital phones by 11%, 95% CI = 6-16%, and cordless phones by 8%, 95% CI = 5-12%. For all studied phone types OR for brain tumours, mainly acoustic neuroma and malignant brain tumours, increased with latency period, especially for astrocytoma grade III-IV.

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

NASA Astrophysics Data System (ADS)

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

2006-03-01

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

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

PubMed

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

2006-03-07

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

The brain MRI classification problem from wavelets perspective

NASA Astrophysics Data System (ADS)

Bendib, Mohamed M.; Merouani, Hayet F.; Diaba, Fatma

2015-02-01

Haar and Daubechies 4 (DB4) are the most used wavelets for brain MRI (Magnetic Resonance Imaging) classification. The former is simple and fast to compute while the latter is more complex and offers a better resolution. This paper explores the potential of both of them in performing Normal versus Pathological discrimination on the one hand, and Multiclassification on the other hand. The Whole Brain Atlas is used as a validation database, and the Random Forest (RF) algorithm is employed as a learning approach. The achieved results are discussed and statistically compared.

Classification of CT brain images based on deep learning networks.

PubMed

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

2017-01-01

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

Imaging biomarkers of angiogenesis and the microvascular environment in cerebral tumours

PubMed Central

Thompson, G; Mills, S J; Coope, D J; O’connor, J P B; Jackson, A

2011-01-01

Conventional contrast-enhanced CT and MRI are now in routine clinical use for the diagnosis, treatment and monitoring of diseases in the brain. The presence of contrast enhancement is a proxy for the pathological changes that occur in the normally highly regulated brain vasculature and blood-brain barrier. With recognition of the limitations of these techniques, and a greater appreciation for the nuanced mechanisms of microvascular change in a variety of pathological processes, novel techniques are under investigation for their utility in further interrogating the microvasculature of the brain. This is particularly important in tumours, where the reliance on angiogenesis (new vessel formation) is crucial for tumour growth, and the resulting microvascular configuration and derangement has profound implications for diagnosis, treatment and monitoring. In addition, novel therapeutic approaches that seek to directly modify the microvasculature require more sensitive and specific biological markers of baseline tumour behaviour and response. The currently used imaging biomarkers of angiogenesis and brain tumour microvascular environment are reviewed. PMID:22433824

Classification of MR brain images by combination of multi-CNNs for AD diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Danni; Liu, Manhua; Fu, Jianliang; Wang, Yaping

2017-07-01

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. Its early diagnosis is crucial for development of future treatment. Magnetic resonance images (MRI) play important role to help understand the brain anatomical changes related to AD. Conventional methods extract the hand-crafted features such as gray matter volumes and cortical thickness and train a classifier to distinguish AD from other groups. Different from these methods, this paper proposes to construct multiple deep 3D convolutional neural networks (3D-CNNs) to learn the various features from local brain images which are combined to make the final classification for AD diagnosis. First, a number of local image patches are extracted from the whole brain image and a 3D-CNN is built upon each local patch to transform the local image into more compact high-level features. Then, the upper convolution and fully connected layers are fine-tuned to combine the multiple 3D-CNNs for image classification. The proposed method can automatically learn the generic features from imaging data for classification. Our method is evaluated using T1-weighted structural MR brain images on 428 subjects including 199 AD patients and 229 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 87.15% and an AUC (area under the ROC curve) of 92.26% for AD classification, demonstrating the promising classification performances.

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

2013-01-01

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. PMID:24252243

Use of mobile phones and risk of brain tumours: update of Danish cohort study

PubMed Central

Poulsen, Aslak H; Johansen, Christoffer; Olsen, Jørgen H; Steding-Jessen, Marianne; Schüz, Joachim

2011-01-01

Objective To investigate the risk of tumours in the central nervous system among Danish mobile phone subscribers. Design Nationwide cohort study. Setting Denmark. Participants All Danes aged ≥30 and born in Denmark after 1925, subdivided into subscribers and non-subscribers of mobile phones before 1995. Main outcome measures Risk of tumours of the central nervous system, identified from the complete Danish Cancer Register. Sex specific incidence rate ratios estimated with log linear Poisson regression models adjusted for age, calendar period, education, and disposable income. Results 358 403 subscription holders accrued 3.8 million person years. In the follow-up period 1990-2007, there were 10 729 cases of tumours of the central nervous system. The risk of such tumours was close to unity for both men and women. When restricted to individuals with the longest mobile phone use—that is, ≥13 years of subscription—the incidence rate ratio was 1.03 (95% confidence interval 0.83 to 1.27) in men and 0.91 (0.41 to 2.04) in women. Among those with subscriptions of ≥10 years, ratios were 1.04 (0.85 to 1.26) in men and 1.04 (0.56 to 1.95) in women for glioma and 0.90 (0.57 to 1.42) in men and 0.93 (0.46 to 1.87) in women for meningioma. There was no indication of dose-response relation either by years since first subscription for a mobile phone or by anatomical location of the tumour—that is, in regions of the brain closest to where the handset is usually held to the head. Conclusions In this update of a large nationwide cohort study of mobile phone use, there were no increased risks of tumours of the central nervous system, providing little evidence for a causal association. PMID:22016439

Characterization and classification of zebrafish brain morphology mutants

PubMed Central

Lowery, Laura Anne; De Rienzo, Gianluca; Gutzman, Jennifer H.; Sive, Hazel

2010-01-01

The mechanisms by which the vertebrate brain achieves its three-dimensional structure are clearly complex, requiring the functions of many genes. Using the zebrafish as a model, we have begun to define genes required for brain morphogenesis, including brain ventricle formation, by studying 16 mutants previously identified as having embryonic brain morphology defects. We report the phenotypic characterization of these mutants at several time-points, using brain ventricle dye injection, imaging, and immunohistochemistry with neuronal markers. Most of these mutants display early phenotypes, affecting initial brain shaping, while others show later phenotypes, affecting brain ventricle expansion. In the early phenotype group, we further define four phenotypic classes and corresponding functions required for brain morphogenesis. Although we did not use known genotypes for this classification, basing it solely on phenotypes, many mutants with defects in functionally related genes clustered in a single class. In particular, class 1 mutants show midline separation defects, corresponding to epithelial junction defects; class 2 mutants show reduced brain ventricle size; class 3 mutants show midbrain-hindbrain abnormalities, corresponding to basement membrane defects; and class 4 mutants show absence of ventricle lumen inflation, corresponding to defective ion pumping. Later brain ventricle expansion requires the extracellular matrix, cardiovascular circulation, and transcription/splicing-dependent events. We suggest that these mutants define processes likely to be used during brain morphogenesis throughout the vertebrates. PMID:19051268

A review of classification algorithms for EEG-based brain-computer interfaces.

PubMed

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

2007-06-01

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.

Advanced soft computing diagnosis method for tumour grading.

PubMed

Papageorgiou, E I; Spyridonos, P P; Stylios, C D; Ravazoula, P; Groumpos, P P; Nikiforidis, G N

2006-01-01

To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.

Peculiarities of hyperlipidaemia in tumour patients.

PubMed Central

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

1981-01-01

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

Peculiarities of hyperlipidaemia in tumour patients.

PubMed

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

1981-05-01

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

Loss of the endothelial glycocalyx is associated with increased E-selectin mediated adhesion of lung tumour cells to the brain microvascular endothelium.

PubMed

Rai, Srijana; Nejadhamzeeigilani, Zaynab; Gutowski, Nicholas J; Whatmore, Jacqueline L

2015-09-25

Arrest of metastasising lung cancer cells to the brain microvasculature maybe mediated by interactions between ligands on circulating tumour cells and endothelial E-selectin adhesion molecules; a process likely to be regulated by the endothelial glycocalyx. Using human cerebral microvascular endothelial cells and non-small cell lung cancer (NSCLC) cell lines, we describe how factors secreted by NSCLC cells i.e. cystatin C, cathepsin L, insulin-like growth factor-binding protein 7 (IGFBP7), vascular endothelial growth factor (VEGF) and tumour necrosis factor-alpha (TNF-α), damage the glycocalyx and enhance initial contacts between lung tumour and cerebral endothelial cells. Endothelial cells were treated with tumour secreted-proteins or lung tumour conditioned medium (CM). Surface levels of E-selectin were quantified by ELISA. Adhesion of A549 and SK-MES-1 cells was examined under flow conditions (1 dyne/cm(2)). Alterations in the endothelial glycocalyx were quantified by binding of fluorescein isothiocyanate-linked wheat germ agglutinin (WGA-FITC). A549 and SK-MES-1 CM and secreted-proteins significantly enhanced endothelial surface E-selectin levels after 30 min and 4 h and tumour cell adhesion after 30 min, 4 and 24 h. Both coincided with significant glycocalyx degradation; A549 and SK-MES-1 CM removing 55 ± 12 % and 58 ± 18.7 % of WGA-FITC binding, respectively. Inhibition of E-selectin binding by monoclonal anti-E-selectin antibody completely attenuated tumour cell adhesion. These data suggest that metastasising lung cancer cells facilitate their own adhesion to the brain endothelium by secreting factors that damage the endothelial glycocalyx, resulting in exposure of the previously shielded adhesion molecules and engagement of the E-selectin-mediated adhesion axis.

Correlation between molecular analysis, diagnosis according to the 2015 WHO classification of unresected lung tumours and TTF1 expression in small biopsies and cytology specimens from 344 non-small cell lung carcinoma patients.

PubMed

Russell, Prudence A; Rogers, Toni-Maree; Solomon, Benjamin; Alam, Naveed; Barnett, Stephen A; Rathi, Vivek; Williams, Richard A; Wright, Gavin M; Conron, Matthew

2017-10-01

We investigated correlations between diagnosis according to the 2015 World Health Organization (WHO) classification of unresected lung tumours, molecular analysis and TTF1 expression in small biopsy and cytology specimens from 344 non-small cell lung carcinoma (NSCLC) patients. One case failed testing for EGFR, KRAS and ALK abnormalities and six had insufficient tumour for ALK testing. Overall mutation rate in 343 cases was 48% for the genes tested, with 19% EGFR, 33% KRAS and 4% BRAF mutations, and 5% ALK rearrangements detected. More EGFR-mutant (78%) and ALK-rearranged (75%) tumours had morphologic adenocarcinoma than KRAS-mutant (56%) tumours. Despite no significant difference in the overall rate of any molecular abnormality between morphologic adenocarcinoma (52%) and NSCLC, favour adenocarcinoma (47%) (p = 0.18), KRAS mutations were detected more frequently in the latter group. No significant difference in the overall rate of any molecular abnormality between TTF1 positive (49%) and TTF1 negative tumours (44%) (p = 0.92) was detected, but more EGFR-mutant (97%) and ALK-rearranged tumours (92%) were TTF1 positive than KRAS-mutant tumours (68%). Rates of EGFR, KRAS and BRAF mutations and ALK rearrangements in this Australian NSCLC patient population are consistent with the published international literature. Our findings suggest that 2015 WHO classification of unresected tumours may assist in identifying molecular subsets of advanced NSCLC. Copyright © 2017 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.

Classification of tumor based on magnetic resonance (MR) brain images using wavelet energy feature and neuro-fuzzy model

NASA Astrophysics Data System (ADS)

Damayanti, A.; Werdiningsih, I.

2018-03-01

The brain is the organ that coordinates all the activities that occur in our bodies. Small abnormalities in the brain will affect body activity. Tumor of the brain is a mass formed a result of cell growth not normal and unbridled in the brain. MRI is a non-invasive medical test that is useful for doctors in diagnosing and treating medical conditions. The process of classification of brain tumor can provide the right decision and correct treatment and right on the process of treatment of brain tumor. In this study, the classification process performed to determine the type of brain tumor disease, namely Alzheimer’s, Glioma, Carcinoma and normal, using energy coefficient and ANFIS. Process stages in the classification of images of MR brain are the extraction of a feature, reduction of a feature, and process of classification. The result of feature extraction is a vector approximation of each wavelet decomposition level. The feature reduction is a process of reducing the feature by using the energy coefficients of the vector approximation. The feature reduction result for energy coefficient of 100 per feature is 1 x 52 pixels. This vector will be the input on the classification using ANFIS with Fuzzy C-Means and FLVQ clustering process and LM back-propagation. Percentage of success rate of MR brain images recognition using ANFIS-FLVQ, ANFIS, and LM back-propagation was obtained at 100%.

Tumours of the upper alimentary tract

PubMed Central

Head, K. W.

1976-01-01

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

Heterogeneous data fusion for brain tumor classification.

PubMed

Metsis, Vangelis; Huang, Heng; Andronesi, Ovidiu C; Makedon, Fillia; Tzika, Aria

2012-10-01

Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this report, we present a novel machine learning framework for brain tumor classification based on heterogeneous data fusion of metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) magnetic resonance spectroscopy and gene transcriptome profiling, obtained from intact brain tumor biopsies. Our experimental results show that our novel framework outperforms any analysis using individual dataset.

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

NASA Astrophysics Data System (ADS)

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

2005-05-01

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

Comparative Approach of MRI-Based Brain Tumor Segmentation and Classification Using Genetic Algorithm.

PubMed

Bahadure, Nilesh Bhaskarrao; Ray, Arun Kumar; Thethi, Har Pal

2018-01-17

The detection of a brain tumor and its classification from modern imaging modalities is a primary concern, but a time-consuming and tedious work was performed by radiologists or clinical supervisors. The accuracy of detection and classification of tumor stages performed by radiologists is depended on their experience only, so the computer-aided technology is very important to aid with the diagnosis accuracy. In this study, to improve the performance of tumor detection, we investigated comparative approach of different segmentation techniques and selected the best one by comparing their segmentation score. Further, to improve the classification accuracy, the genetic algorithm is employed for the automatic classification of tumor stage. The decision of classification stage is supported by extracting relevant features and area calculation. The experimental results of proposed technique are evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on segmentation score, accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 92.03% accuracy, 91.42% specificity, 92.36% sensitivity, and an average segmentation score between 0.82 and 0.93 demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 93.79% dice similarity index coefficient, which indicates better overlap between the automated extracted tumor regions with manually extracted tumor region by radiologists.

Pooled analysis of two case-control studies on use of cellular and cordless telephones and the risk for malignant brain tumours diagnosed in 1997-2003.

PubMed

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

2006-09-01

To study the use of cellular and cordless telephones and the risk for malignant brain tumours. Two case-control studies on malignant brain tumours diagnosed during 1997-2003 included answers from 905 (90%) cases and 2,162 (89%) controls aged 20-80 years. We present pooled analysis of the results in the two studies. Cumulative lifetime use for >2,000 h yielded for analogue cellular phones odds ratio (OR)=5.9, 95% confidence interval (CI)=2.5-14, digital cellular phones OR=3.7, 95% CI=1.7-7.7, and for cordless phones OR=2.3, 95% CI=1.5-3.6. Ipsilateral exposure increased the risk for malignant brain tumours; analogue OR=2.1, 95% CI=1.5-2.9, digital OR=1.8, 95% CI=1.4-2.4, and cordless OR=1.7, 95% CI=1.3-2.2. For high-grade astrocytoma using >10 year latency period analogue phones yielded OR=2.7, 95% CI=1.8-4.2, digital phones OR=3.8, 95% CI=1.8-8.1, and cordless phones OR=2.2, 95% CI=1.3-3.9. In the multivariate analysis all phone types increased the risk. Regarding digital phones OR=3.7, 95% CI=1.5-9.1 and cordless phones OR=2.1, 95% CI=0.97-4.6 were calculated for malignant brain tumours for subjects with first use use <20 years of age, higher than in older persons. Increased risk was obtained for both cellular and cordless phones, highest in the group with >10 years latency period.

PERIVASCULAR EPITHELIOID TUMOURS (PEComas) OF THE GYNAECOLOGICAL TRACT

PubMed Central

Conlon, Niamh; Soslow, Robert A.; Murali, Rajmohan

2016-01-01

Perivascular epithelioid tumour (PEComas) of the gynaecological tract are rare tumours which were first recognised and diagnosed within the last twenty years. They represent a unique diagnostic challenge with regard to their accurate and reproducible distinction from more common entities such as smooth muscle tumours of the uterine corpus. In this review article we trace the development of the concept of the PEComa tumour family, highlight what is known about extra-gynaecological tract PEComa at an immunohistochemical, molecular and therapeutic level and then present a summary of all reported cases of gynaecological tract PEComa to date. In the summary, we highlight rare subtypes of gynaecological tract PEComa, and compare the performances of extant prognostic classification systems for malignancy in these tumours. PMID:25750268

Application of machine learning on brain cancer multiclass classification

NASA Astrophysics Data System (ADS)

Panca, V.; Rustam, Z.

2017-07-01

Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

The effect of combining two echo times in automatic brain tumor classification by MRS.

PubMed

García-Gómez, Juan M; Tortajada, Salvador; Vidal, César; Julià-Sapé, Margarida; Luts, Jan; Moreno-Torres, Angel; Van Huffel, Sabine; Arús, Carles; Robles, Montserrat

2008-11-01

(1)H MRS is becoming an accurate, non-invasive technique for initial examination of brain masses. We investigated if the combination of single-voxel (1)H MRS at 1.5 T at two different (TEs), short TE (PRESS or STEAM, 20-32 ms) and long TE (PRESS, 135-136 ms), improves the classification of brain tumors over using only one echo TE. A clinically validated dataset of 50 low-grade meningiomas, 105 aggressive tumors (glioblastoma and metastasis), and 30 low-grade glial tumors (astrocytomas grade II, oligodendrogliomas and oligoastrocytomas) was used to fit predictive models based on the combination of features from short-TEs and long-TE spectra. A new approach that combines the two consecutively was used to produce a single data vector from which relevant features of the two TE spectra could be extracted by means of three algorithms: stepwise, reliefF, and principal components analysis. Least squares support vector machines and linear discriminant analysis were applied to fit the pairwise and multiclass classifiers, respectively. Significant differences in performance were found when short-TE, long-TE or both spectra combined were used as input. In our dataset, to discriminate meningiomas, the combination of the two TE acquisitions produced optimal performance. To discriminate aggressive tumors from low-grade glial tumours, the use of short-TE acquisition alone was preferable. The classifier development strategy used here lends itself to automated learning and test performance processes, which may be of use for future web-based multicentric classifier development studies. Copyright (c) 2008 John Wiley & Sons, Ltd.

Germline PMS2 and somatic POLE exonuclease mutations cause hypermutability of the leading DNA strand in biallelic mismatch repair deficiency syndrome brain tumours.

PubMed

Andrianova, Maria A; Chetan, Ghati Kasturirangan; Sibin, Madathan Kandi; Mckee, Thomas; Merkler, Doron; Narasinga, Rao Kvl; Ribaux, Pascale; Blouin, Jean-Louis; Makrythanasis, Periklis; Seplyarskiy, Vladimir B; Antonarakis, Stylianos E; Nikolaev, Sergey I

2017-11-01

Biallelic mismatch repair deficiency (bMMRD) in tumours is frequently associated with somatic mutations in the exonuclease domains of DNA polymerases POLE or POLD1, and results in a characteristic mutational profile. In this article, we describe the genetic basis of ultramutated high-grade brain tumours in the context of bMMRD. We performed exome sequencing of two second-cousin patients from a large consanguineous family of Indian origin with early onset of high-grade glioblastoma and astrocytoma. We identified a germline homozygous nonsense variant, p.R802*, in the PMS2 gene. Additionally, by genome sequencing of these tumours, we found extremely high somatic mutation rates (237/Mb and 123/Mb), as well as somatic mutations in the proofreading domain of POLE polymerase (p.P436H and p.L424V), which replicates the leading DNA strand. Most interestingly, we found, in both cancers, that the vast majority of mutations were consistent with the signature of POLE exo - , i.e. an abundance of C>A and C>T mutations, particularly in special contexts, on the leading strand. We showed that the fraction of mutations under positive selection among mutations in tumour suppressor genes is more than two-fold lower in ultramutated tumours than in other glioblastomas. Genetic analyses enabled the diagnosis of the two consanguineous childhood brain tumours as being due to a combination of PMS2 germline and POLE somatic variants, and confirmed them as bMMRD/POLE exo - disorders. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Combined radiotherapy and chemotherapy for high-grade brain tumours

NASA Astrophysics Data System (ADS)

Barazzuol, Lara

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

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

PubMed

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

2015-01-01

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

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis

PubMed Central

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

2015-01-01

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

Pathology of Neuroendocrine Tumours of the Female Genital Tract.

PubMed

Howitt, Brooke E; Kelly, Paul; McCluggage, W Glenn

2017-09-01

Neuroendocrine tumours are uncommon or rare at all sites in the female genital tract. The 2014 World Health Organisation (WHO) Classification of neuroendocrine tumours of the endometrium, cervix, vagina and vulva has been updated with adoption of the terms low-grade neuroendocrine tumour and high-grade neuroendocrine carcinoma. In the endometrium and cervix, high-grade neoplasms are much more prevalent than low-grade and are more common in the cervix than the corpus. In the ovary, low-grade tumours are more common than high-grade carcinomas and the term carcinoid tumour is still used in WHO 2014. The term ovarian small-cell carcinoma of pulmonary type is included in WHO 2014 for a tumour which in other organs is termed high small-cell neuroendocrine carcinoma. Neuroendocrine tumours at various sites within the female genital tract often occur in association with other neoplasms and more uncommonly in pure form.

A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

PubMed

Shin, Jaeyoung; Kwon, Jinuk; Im, Chang-Hwan

2018-01-01

The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs ( p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

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

PubMed

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

2015-03-01

The cerebellum is connected to extensive regions of the cerebrum, and cognitive deficits following cerebellar lesions may thus be related to disrupted cerebello-cerebral connectivity. Moreover, early cerebellar lesions could affect distal brain development, effectively inducing long-term changes in brain structure and cognitive function. Here, we characterize supratentorial brain structure and cognitive function in 20 adult patients treated for cerebellar tumours in childhood (mean age at surgery: 7.1 years) and 26 matched controls. Relative to controls, patients showed reduced cognitive function and increased grey matter density in bilateral cingulum, left orbitofrontal cortex and the left hippocampus. Within the patient group, increased grey matter density in these regions was associated with decreased performance on tests of processing speed and executive function. Further, diffusion tensor imaging revealed widespread alterations in white matter microstructure in patients. While current ventricle volume (an index of previous hydrocephalus severity it patients) was associated with grey matter density and white matter microstructure in patients, this could only partially account for the observed group differences in brain structure and cognitive function. In conclusion, our results show distal effects of cerebellar lesions on cerebral integrity and wiring, likely caused by a combination of neurodegenerative processes and perturbed neurodevelopment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Seizure characteristics and the use of anti-epileptic drugs in children and young people with brain tumours and epileptic seizures: Analysis of regional paediatric cancer service population.

PubMed

Pilotto, Chiara; Liu, Jo-Fen; Walker, David A; Whitehouse, William P

2018-03-21

Epileptic seizures complicate the management of childhood brain tumours. There are no published standards for clinical practice concerning risk factors, treatment selection or strategies to withdraw treatment with antiepileptic drugs (AED). we undertook a case note review of 120 patients with newly diagnosed brain tumours, referred to a regional paediatric cancer service. data was available on 117/120 (98%) children <18 years: median age at tumour presentation was 8.1 years (IQR 25°-75° : 3.6-12.7), median follow up was 33 months (IQR 25°-75°: 24-56), and 35/117 (29%) experienced seizures. A cortical tumour location was associated with the highest risk of seizures (OR: 7.1; CI 95% 2.9-17.3). At a median follow up of 24 months (IQR 25°-75° : 15-48), 22/35 (63%) with seizures, had a single seizure episode, 15/35 (43%) were seizure free (SF) on AEDs, 13/35 (37%) were SF off AEDs, and 7/35 (20%) experienced continuing epileptic seizures. Overall 34/35 (97%) were treated with AEDs after a seizure, of whom 12/35 (35%) withdrew from AED medication, and although 4/35 (12%) had seizure relapse, all were after further acute events. The median duration of AED before withdrawal was 11 months (IQR 25°-75° 5-14 months), and the median follow up after withdrawal was 15 months (IQR 25°-75° 5-34 months). Seizures affect about 1/3rd of children and young people presenting with and being treated for brain tumours particularly when the tumour is in the cerebral cortex. The low risk of recurrent seizures after AED treatment justifies consideration of early withdrawal of AED after seizure control. Copyright © 2018. Published by Elsevier Ltd.

Long-term outcome in patients with germ cell tumours treated with POMB/ACE chemotherapy: comparison of commonly used classification systems of good and poor prognosis.

PubMed Central

Hitchins, R. N.; Newlands, E. S.; Smith, D. B.; Begent, R. H.; Rustin, G. J.; Bagshawe, K. D.

1989-01-01

We analysed outcome in 206 consecutive male patients treated for metastatic non-seminomatous germ cell tumour (NSGCT) of testicular or extragonadal origin treated with the POMB/ACE (cisplatin, vincristine, methotrexate, bleomycin, actinomycin D, cyclophosphamide, etoposide) regimen after division into prognostic groups by commonly used clinical classification systems and definitions of adverse prognosis. The adverse prognostic groups of all classification systems and definitions examined showed similar, but only moderate, sensitivity (71-81%) and specificity (52-56%) in predicting death. A simple definition of poor prognosis based on raised initial levels of serum tumour markers alpha fetoprotein (aFP) and human chorionic gonadotrophin (hCG) proved at least as useful (sensitivity 80%, specificity 55%) as other more complicated systems in predicting failure to achieve long-term survival. Comparison of survival between ultra-high dose cisplatin-based combination chemotherapy and patients treated with POMB/ACE shows no advantage from this more toxic approach. This suggests that good results in adverse prognosis patients can be achieved using conventional dose regimens administered intensively. PMID:2467682

Connectivity Strength-Weighted Sparse Group Representation-Based Brain Network Construction for MCI Classification

PubMed Central

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

2017-01-01

Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l1-norm penalty simply penalizes each edge of a brain network equally, without considering the original connectivity strength which is one of the most important inherent linkwise characters. Besides, based on the similarity of the linkwise connectivity, brain network shows prominent group structure (i.e., a set of edges sharing similar attributes). In this article, we propose a novel brain functional network modeling framework with a “connectivity strength-weighted sparse group constraint.” In particular, the network modeling can be optimized by considering both raw connectivity strength and its group structure, without losing the merit of sparsity. Our proposed method is applied to MCI classification, a challenging task for early AD diagnosis. Experimental results based on the resting-state functional MRI, from 50 MCI patients and 49 healthy controls, show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 84.8%) than other competing methods (e.g., sparse representation, accuracy = 65.6%). Post hoc inspection of the informative features further shows more biologically meaningful brain functional connectivities obtained by our proposed method. PMID:28150897

Patterns of relapse in poor-prognosis germ-cell tumours in the GETUG 13 trial: Implications for assessment of brain metastases.

PubMed

Loriot, Y; Pagliaro, L; Fléchon, A; Mardiak, J; Geoffrois, L; Kerbrat, P; Chevreau, C; Delva, R; Rolland, F; Theodore, C; Roubaud, G; Gravis, G; Eymard, J C; Malhaire, J P; Linassier, C; Habibian, M; Martin, A L; Journeau, F; Reckova, M; Logothetis, C; Laplanche, A; Le Teuff, G; Culine, S; Fizazi, K

2017-12-01

The GETUG 13 phase III trial tested personalised chemotherapy based on tumour marker decline in patients with poor-prognosis germ-cell tumour (GCT) and demonstrated that a dose-dense regimen improves progression-free survival in patients with an unfavourable decline. We investigated the pattern of relapse for patients included in GETUG 13. We conducted an analysis of relapse events in patients from GETUG 13. Baseline procedures before inclusion in the trial comprised a thoraco-abdomino-pelvic computed tomography scan and a magnetic resonance imaging of the brain. With a median follow-up of 4.1 years (0.3; 8.8 years), a progression event was observed in 109/254 patients (43%). First event consisted in a marker progression only in 47 patients (43%), a radiographic progression only in 35 patients (32%), a mix progression on both markers and imaging in 12 patients (11%) and death in 15 patients (14%). In patients with radiographic progression only, brain was the predominant site (n = 19/35, 54%). Among patients with unfavourable decline who experienced a radiographic progression (as first and subsequent progression event, n = 58), brain was a site of progression in 28 patients (48%): 12/30 (40%) in patients treated with cisplatin, bleomycin and etoposide and 16/28 (57%) in those treated with dose-dense chemotherapy. Brain metastases develop often, early and frequently as the only site of relapse in the course of poor-prognosis GCT. This raises the question of early detection and optimal treatment of brain metastases in these patients, e.g. by integrating a systematic brain MRI after 2-3 months of chemotherapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mechanisms of radiotherapy-associated cognitive disability in patients with brain tumours.

PubMed

Makale, Milan T; McDonald, Carrie R; Hattangadi-Gluth, Jona A; Kesari, Santosh

2017-01-01

Standard treatment of primary and metastatic brain tumours includes high-dose megavoltage-range radiation to the cranial vault. About half of patients survive >6 months, and many attain long-term control or cure. However, 50-90% of survivors exhibit disabling cognitive dysfunction. The radiation-associated cognitive syndrome is poorly understood and has no effective prevention or long-term treatment. Attention has primarily focused on mechanisms of disability that appear at 6 months to 1 year after radiotherapy. However, recent studies show that CNS alterations and dysfunction develop much earlier following radiation exposure. This finding has prompted the hypothesis that subtle early forms of radiation-induced CNS damage could drive chronic pathophysiological processes that lead to permanent cognitive decline. This Review presents evidence of acute radiation-triggered CNS inflammation, injury to neuronal lineages, accessory cells and their progenitors, and loss of supporting structure integrity. Moreover, injury-related processes initiated soon after irradiation could synergistically alter the signalling microenvironment in progenitor cell niches in the brain and the hippocampus, which is a structure critical to memory and cognition. Progenitor cell niche degradation could cause progressive neuronal loss and cognitive disability. The concluding discussion addresses future directions and potential early treatments that might reverse degenerative processes before they can cause permanent cognitive disability.

Do we need a new classification of parotid gland surgery?

PubMed

Wierzbicka, Małgorzata; Piwowarczyk, Krzysztof; Nogala, Hanna; Błaszczyńska, Marzena; Kosiedrowski, Michał; Mazurek, Cezary

2016-06-30

In February 2016 the European Salivary Gland Society (ESGS) presented and recommended classification of parotidectomies based on the anatomical I-V level division of parotid gland. The main goal of this paper is to present the new classification, and to answer the question if it is more precise compared to classic one. 607 patients (315 man, 292 women) operated on for parotid tumours in a tertiary referral centre, Department of Otolaryngology, Head and Neck Surgery, Medical University of Poznań (502 benign and 105 malignant tumours). Parotid surgery descriptions provided by retrospective analysis of all operating protocols covering the years 2006-2015 were "translated" into the new classification proposed by the ESGS. Analysis of operating protocols and fitting them into the new classification proposed by the ESGS show some discrepancies, in both benign and malignant tumours. Based on the re-evaluation of 607 cases, in 94 procedures for benign tumors the only information available was that "surgery was performed within the superficial lobe". Thus, the new classification forces the surgeon to be much more precise than previously. In 3 cases the whole superficial lobe was removed, together with the upper part of the deep lobe. Because the classification lacked parotidectomy I-II-IV, it indicated that the new classification was insufficient in the aforementioned three cases. In 6 cases of ECD more than one parotid gland tumour was removed. Among malignant tumours, total parotidectomy was the predominant procedure. In 3/13 cases of expanded parotidectomy the temporomandibular joint (TMJ) was additionally removed and it seems that the acronym TMJ should be included among the additional resected structures. It is also necessary to supplement the description of the treatment with casuistically resected anatomical structures for oncological purposes (RT planning) and follow-up imaging. Currently, since 2015 in Poland there has been the National Cancer Registry of benign

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

PubMed

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

2017-05-01

Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l 1 -norm penalty simply penalizes each edge of a brain network equally, without considering the original connectivity strength which is one of the most important inherent linkwise characters. Besides, based on the similarity of the linkwise connectivity, brain network shows prominent group structure (i.e., a set of edges sharing similar attributes). In this article, we propose a novel brain functional network modeling framework with a "connectivity strength-weighted sparse group constraint." In particular, the network modeling can be optimized by considering both raw connectivity strength and its group structure, without losing the merit of sparsity. Our proposed method is applied to MCI classification, a challenging task for early AD diagnosis. Experimental results based on the resting-state functional MRI, from 50 MCI patients and 49 healthy controls, show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 84.8%) than other competing methods (e.g., sparse representation, accuracy = 65.6%). Post hoc inspection of the informative features further shows more biologically meaningful brain functional connectivities obtained by our proposed method. Hum Brain Mapp 38:2370-2383, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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

PubMed

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

2015-01-01

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

Tumour exosome integrins determine organotropic metastasis.

PubMed

Hoshino, Ayuko; Costa-Silva, Bruno; Shen, Tang-Long; Rodrigues, Goncalo; Hashimoto, Ayako; Tesic Mark, Milica; Molina, Henrik; Kohsaka, Shinji; Di Giannatale, Angela; Ceder, Sophia; Singh, Swarnima; Williams, Caitlin; Soplop, Nadine; Uryu, Kunihiro; Pharmer, Lindsay; King, Tari; Bojmar, Linda; Davies, Alexander E; Ararso, Yonathan; Zhang, Tuo; Zhang, Haiying; Hernandez, Jonathan; Weiss, Joshua M; Dumont-Cole, Vanessa D; Kramer, Kimberly; Wexler, Leonard H; Narendran, Aru; Schwartz, Gary K; Healey, John H; Sandstrom, Per; Labori, Knut Jørgen; Kure, Elin H; Grandgenett, Paul M; Hollingsworth, Michael A; de Sousa, Maria; Kaur, Sukhwinder; Jain, Maneesh; Mallya, Kavita; Batra, Surinder K; Jarnagin, William R; Brady, Mary S; Fodstad, Oystein; Muller, Volkmar; Pantel, Klaus; Minn, Andy J; Bissell, Mina J; Garcia, Benjamin A; Kang, Yibin; Rajasekhar, Vinagolu K; Ghajar, Cyrus M; Matei, Irina; Peinado, Hector; Bromberg, Jacqueline; Lyden, David

2015-11-19

Ever since Stephen Paget's 1889 hypothesis, metastatic organotropism has remained one of cancer's greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.

Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients.

PubMed

Sevel, Landrew S; Boissoneault, Jeff; Letzen, Janelle E; Robinson, Michael E; Staud, Roland

2018-05-30

Chronic fatigue syndrome (CFS) is a disorder associated with fatigue, pain, and structural/functional abnormalities seen during magnetic resonance brain imaging (MRI). Therefore, we evaluated the performance of structural MRI (sMRI) abnormalities in the classification of CFS patients versus healthy controls and compared it to machine learning (ML) classification based upon self-report (SR). Participants included 18 CFS patients and 15 healthy controls (HC). All subjects underwent T1-weighted sMRI and provided visual analogue-scale ratings of fatigue, pain intensity, anxiety, depression, anger, and sleep quality. sMRI data were segmented using FreeSurfer and 61 regions based on functional and structural abnormalities previously reported in patients with CFS. Classification was performed in RapidMiner using a linear support vector machine and bootstrap optimism correction. We compared ML classifiers based on (1) 61 a priori sMRI regional estimates and (2) SR ratings. The sMRI model achieved 79.58% classification accuracy. The SR (accuracy = 95.95%) outperformed both sMRI models. Estimates from multiple brain areas related to cognition, emotion, and memory contributed strongly to group classification. This is the first ML-based group classification of CFS. Our findings suggest that sMRI abnormalities are useful for discriminating CFS patients from HC, but SR ratings remain most effective in classification tasks.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-12-01

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

Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.

PubMed

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations.

PubMed

Fabelo, Himar; Ortega, Samuel; Ravi, Daniele; Kiran, B Ravi; Sosa, Coralia; Bulters, Diederik; Callicó, Gustavo M; Bulstrode, Harry; Szolna, Adam; Piñeiro, Juan F; Kabwama, Silvester; Madroñal, Daniel; Lazcano, Raquel; J-O'Shanahan, Aruma; Bisshopp, Sara; Hernández, María; Báez, Abelardo; Yang, Guang-Zhong; Stanciulescu, Bogdan; Salvador, Rubén; Juárez, Eduardo; Sarmiento, Roberto

2018-01-01

Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal brain by these tumors makes their accurate identification by the naked eye difficult. Since surgery is the common treatment for brain cancer, an accurate radical resection of the tumor leads to improved survival rates for patients. However, the identification of the tumor boundaries during surgery is challenging. Hyperspectral imaging is a non-contact, non-ionizing and non-invasive technique suitable for medical diagnosis. This study presents the development of a novel classification method taking into account the spatial and spectral characteristics of the hyperspectral images to help neurosurgeons to accurately determine the tumor boundaries in surgical-time during the resection, avoiding excessive excision of normal tissue or unintentionally leaving residual tumor. The algorithm proposed in this study to approach an efficient solution consists of a hybrid framework that combines both supervised and unsupervised machine learning methods. Firstly, a supervised pixel-wise classification using a Support Vector Machine classifier is performed. The generated classification map is spatially homogenized using a one-band representation of the HS cube, employing the Fixed Reference t-Stochastic Neighbors Embedding dimensional reduction algorithm, and performing a K-Nearest Neighbors filtering. The information generated by the supervised stage is combined with a segmentation map obtained via unsupervised clustering employing a Hierarchical K-Means algorithm. The fusion is performed using a majority voting approach that associates each cluster with a certain class. To evaluate the proposed approach, five hyperspectral images of surface of the brain affected by glioblastoma tumor in vivo from five different patients have been used. The final classification maps obtained have been analyzed and validated by specialists. These preliminary results are promising

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations

PubMed Central

Kabwama, Silvester; Madroñal, Daniel; Lazcano, Raquel; J-O’Shanahan, Aruma; Bisshopp, Sara; Hernández, María; Báez, Abelardo; Yang, Guang-Zhong; Stanciulescu, Bogdan; Salvador, Rubén; Juárez, Eduardo; Sarmiento, Roberto

2018-01-01

Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal brain by these tumors makes their accurate identification by the naked eye difficult. Since surgery is the common treatment for brain cancer, an accurate radical resection of the tumor leads to improved survival rates for patients. However, the identification of the tumor boundaries during surgery is challenging. Hyperspectral imaging is a non-contact, non-ionizing and non-invasive technique suitable for medical diagnosis. This study presents the development of a novel classification method taking into account the spatial and spectral characteristics of the hyperspectral images to help neurosurgeons to accurately determine the tumor boundaries in surgical-time during the resection, avoiding excessive excision of normal tissue or unintentionally leaving residual tumor. The algorithm proposed in this study to approach an efficient solution consists of a hybrid framework that combines both supervised and unsupervised machine learning methods. Firstly, a supervised pixel-wise classification using a Support Vector Machine classifier is performed. The generated classification map is spatially homogenized using a one-band representation of the HS cube, employing the Fixed Reference t-Stochastic Neighbors Embedding dimensional reduction algorithm, and performing a K-Nearest Neighbors filtering. The information generated by the supervised stage is combined with a segmentation map obtained via unsupervised clustering employing a Hierarchical K-Means algorithm. The fusion is performed using a majority voting approach that associates each cluster with a certain class. To evaluate the proposed approach, five hyperspectral images of surface of the brain affected by glioblastoma tumor in vivo from five different patients have been used. The final classification maps obtained have been analyzed and validated by specialists. These preliminary results are promising

Multimodality cellular and molecular imaging of concomitant tumour enhancement in a syngeneic mouse model of breast cancer metastasis.

PubMed

Parkins, Katie M; Dubois, Veronica P; Hamilton, Amanda M; Makela, Ashley V; Ronald, John A; Foster, Paula J

2018-06-12

The mechanisms that influence metastatic growth rates are poorly understood. One mechanism of interest known as concomitant tumour resistance (CTR) can be defined as the inhibition of metastasis by existing tumour mass. Conversely, the presence of a primary tumour has also been shown to increase metastatic outgrowth, termed concomitant tumour enhancement (CTE). The majority of studies evaluating CTR/CTE in preclinical models have relied on endpoint histological evaluation of tumour burden. The goal of this research was to use conventional magnetic resonance imaging (MRI), cellular MRI, and bioluminescence imaging to study the impact of a primary tumour on the development of brain metastases in a syngeneic mouse model. Here, we report that the presence of a 4T1 primary tumour significantly enhances total brain tumour burden in Balb/C mice. Using in vivo BLI/MRI we could determine this was not related to differences in initial arrest or clearance of viable cells in the brain, which suggests that the presence of a primary tumour can increase the proliferative growth of brain metastases in this model. The continued application of our longitudinal cellular and molecular imaging tools will yield a better understanding of the mechanism(s) by which this physiological inhibition (CTR) and/or enhancement (CTE) occurs.

Role of surgery in brain metastases.

PubMed

Laghari, Altaf Ali; Ahmed, Syed Ijlal; Shamim, Muhammad Shahzad

2017-08-01

Brain metastases remain the commonest type of brain tumour, being four times more common than primary brain tumours. Although surgical intervention may be recommended for one of various reasons in the management of these tumours, including but not limited to conformation of diagnosis, relief of mass effect, improvement of neurological status and prolongation of survival, the guidelines for management of brain metastases remain largely subjective and therefore controversial. Herein the authors have attempted to review some of the existing evidence on role of surgery in the management of brain metastases and have presented their selected guidelines for the readers.

Recursive partitioning analysis (RPA) classification predicts survival in patients with brain metastases from sarcoma.

PubMed

Grossman, Rachel; Ram, Zvi

2014-12-01

Sarcoma rarely metastasizes to the brain, and there are no specific treatment guidelines for these tumors. The recursive partitioning analysis (RPA) classification is a well-established prognostic scale used in many malignancies. In this study we assessed the clinical characteristics of metastatic sarcoma to the brain and the validity of the RPA classification system in a subset of 21 patients who underwent surgical resection of metastatic sarcoma to the brain We retrospectively analyzed the medical, radiological, surgical, pathological, and follow-up clinical records of 21 patients who were operated for metastatic sarcoma to the brain between 1996 and 2012. Gliosarcomas, sarcomas of the head and neck with local extension into the brain, and metastatic sarcomas to the spine were excluded from this reported series. The patients' mean age was 49.6 ± 14.2 years (range, 25-75 years) at the time of diagnosis. Sixteen patients had a known history of systemic sarcoma, mostly in the extremities, and had previously received systemic chemotherapy and radiation therapy for their primary tumor. The mean maximal tumor diameter in the brain was 4.9 ± 1.7 cm (range 1.7-7.2 cm). The group's median preoperative Karnofsky Performance Scale was 80, with 14 patients presenting with Karnofsky Performance Scale of 70 or greater. The median overall survival was 7 months (range 0.2-204 months). The median survival time stratified by the Radiation Therapy Oncology Group RPA classes were 31, 7, and 2 months for RPA class I, II, and III, respectively (P = 0.0001). This analysis is the first to support the prognostic utility of the Radiation Therapy Oncology Group RPA classification for sarcoma brain metastases and may be used as a treatment guideline tool in this rare disease. Copyright © 2014 Elsevier Inc. All rights reserved.

Investigating intracranial tumour growth patterns with multiparametric MRI incorporating Gd‐DTPA and USPIO‐enhanced imaging

PubMed Central

Borri, Marco; Jury, Alexa; Popov, Sergey; Box, Gary; Perryman, Lara; Eccles, Suzanne A.; Jones, Chris; Robinson, Simon P.

2016-01-01

Abstract High grade and metastatic brain tumours exhibit considerable spatial variations in proliferation, angiogenesis, invasion, necrosis and oedema. Vascular heterogeneity arising from vascular co‐option in regions of invasive growth (in which the blood–brain barrier remains intact) and neoangiogenesis is a major challenge faced in the assessment of brain tumours by conventional MRI. A multiparametric MRI approach, incorporating native measurements and both Gd‐DTPA (Magnevist) and ultrasmall superparamagnetic iron oxide (P904)‐enhanced imaging, was used in combination with histogram and unsupervised cluster analysis using a k‐means algorithm to examine the spatial distribution of vascular parameters, water diffusion characteristics and invasion in intracranially propagated rat RG2 gliomas and human MDA‐MB‐231 LM2–4 breast adenocarcinomas in mice. Both tumour models presented with higher ΔR 1 (the change in transverse relaxation rate R 1 induced by Gd‐DTPA), fractional blood volume (fBV) and apparent diffusion coefficient than uninvolved regions of the brain. MDA‐MB‐231 LM2–4 tumours were less densely cellular than RG2 tumours and exhibited substantial local invasion, associated with oedema, whereas invasion in RG2 tumours was minimal. These additional features were reflected in the more heterogeneous appearance of MDA‐MB‐231 LM2–4 tumours on T 2‐weighted images and maps of functional MRI parameters. Unsupervised cluster analysis separated subregions with distinct functional properties; areas with a low fBV and relatively impermeable blood vessels (low ΔR 1) were predominantly located at the tumour margins, regions of MDA‐MB‐231 LM2–4 tumours with relatively high levels of water diffusion and low vascular permeability and/or fBV corresponded to histologically identified regions of invasion and oedema, and areas of mismatch between vascular permeability and blood volume were identified. We demonstrate that dual contrast MRI

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

PubMed

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

2016-10-01

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

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

PubMed Central

Lavender, J. P.

1973-01-01

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 PMID:4602127

Genotyping tumour DNA in cerebrospinal fluid and plasma of a HER2-positive breast cancer patient with brain metastases

PubMed Central

Siravegna, Giulia; Geuna, Elena; Mussolin, Benedetta; Crisafulli, Giovanni; Bartolini, Alice; Galizia, Danilo; Casorzo, Laura; Sarotto, Ivana; Scaltriti, Maurizio; Sapino, Anna; Bardelli, Alberto; Montemurro, Filippo

2017-01-01

Background Central nervous system (CNS) involvement contributes to significant morbidity and mortality in patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (mBC) and represents a major challenge for clinicians. Liquid biopsy of cerebrospinal fluid (CSF)-derived circulating tumour DNA (ctDNA) harbours clinically relevant genomic alterations in patients with CNS metastases and could be effective in tracking tumour evolution. Methods In a HER2-positive mBC patient with brain metastases, we applied droplet digital PCR (ddPCR) and next-generation whole exome sequencing (WES) analysis to measure ctDNA dynamic changes in CSF and plasma collected during treatment. Results Baseline CSF-derived ctDNA analysis revealed TP53 and PIK3CA mutations as well as ERBB2 and cMYC amplification. Post-treatment ctDNA analysis showed decreased markers level in plasma, consistent with extra-CNS disease control, while increased in the CSF, confirming poor treatment benefit in the CNS. Discussion Analysis of ctDNA in the CSF of HER2-positive mBC is feasible and could represent a useful companion for clinical management of brain metastases. PMID:29067216

Local Kernel for Brains Classification in Schizophrenia

NASA Astrophysics Data System (ADS)

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

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

[Neonatal tumours and congenital malformations].

PubMed

Berbel Tornero, O; Ortega García, J A; Ferrís i Tortajada, J; García Castell, J; Donat i Colomer, J; Soldin, O P; Fuster Soler, J L

2008-06-01

exist on the neonatal period and the majority are from medical institutions registers. The prevalence varies from 15 to 31.6%. To explain this association, the hypotheses are based on prenatal exposures (preconceptional and transplacental exposure), to mutagenic and carcinogenic risk factors. Neonatal tumours are more often associated to congenital abnormalities than other pediatric cancers. The inclusion and classification criteria needs to be unified to better understand the association between the neonatal tumours and congenital abnormalities. The environmental history in all neonatal tumours associated to congenital abnormalities, including the constitutional and environmental risk factors, will help to improve our knowledge of the underlying prenatal mechanisms and to an advance in its prevention.

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

PubMed Central

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

2013-01-01

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

Multi-fractal detrended texture feature for brain tumor classification

NASA Astrophysics Data System (ADS)

Reza, Syed M. S.; Mays, Randall; Iftekharuddin, Khan M.

2015-03-01

We propose a novel non-invasive brain tumor type classification using Multi-fractal Detrended Fluctuation Analysis (MFDFA) [1] in structural magnetic resonance (MR) images. This preliminary work investigates the efficacy of the MFDFA features along with our novel texture feature known as multifractional Brownian motion (mBm) [2] in classifying (grading) brain tumors as High Grade (HG) and Low Grade (LG). Based on prior performance, Random Forest (RF) [3] is employed for tumor grading using two different datasets such as BRATS-2013 [4] and BRATS-2014 [5]. Quantitative scores such as precision, recall, accuracy are obtained using the confusion matrix. On an average 90% precision and 85% recall from the inter-dataset cross-validation confirm the efficacy of the proposed method.

HELICoiD project: a new use of hyperspectral imaging for brain cancer detection in real-time during neurosurgical operations

NASA Astrophysics Data System (ADS)

Fabelo, Himar; Ortega, Samuel; Kabwama, Silvester; Callico, Gustavo M.; Bulters, Diederik; Szolna, Adam; Pineiro, Juan F.; Sarmiento, Roberto

2016-05-01

Hyperspectral images allow obtaining large amounts of information about the surface of the scene that is captured by the sensor. Using this information and a set of complex classification algorithms is possible to determine which material or substance is located in each pixel. The HELICoiD (HypErspectraL Imaging Cancer Detection) project is a European FET project that has the goal to develop a demonstrator capable to discriminate, with high precision, between normal and tumour tissues, operating in real-time, during neurosurgical operations. This demonstrator could help the neurosurgeons in the process of brain tumour resection, avoiding the excessive extraction of normal tissue and unintentionally leaving small remnants of tumour. Such precise delimitation of the tumour boundaries will improve the results of the surgery. The HELICoiD demonstrator is composed of two hyperspectral cameras obtained from Headwall. The first one in the spectral range from 400 to 1000 nm (visible and near infrared) and the second one in the spectral range from 900 to 1700 nm (near infrared). The demonstrator also includes an illumination system that covers the spectral range from 400 nm to 2200 nm. A data processing unit is in charge of managing all the parts of the demonstrator, and a high performance platform aims to accelerate the hyperspectral image classification process. Each one of these elements is installed in a customized structure specially designed for surgical environments. Preliminary results of the classification algorithms offer high accuracy (over 95%) in the discrimination between normal and tumour tissues.

Identification and classification of hubs in brain networks.

PubMed

Sporns, Olaf; Honey, Christopher J; Kötter, Rolf

2007-10-17

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.

Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification.

PubMed

Vrooman, Henri A; Cocosco, Chris A; van der Lijn, Fedde; Stokking, Rik; Ikram, M Arfan; Vernooij, Meike W; Breteler, Monique M B; Niessen, Wiro J

2007-08-01

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue in MR data, requires training on manually labeled subjects. This manual labeling is a laborious and time-consuming procedure. In this work, a new fully automated brain tissue classification procedure is presented, in which kNN training is automated. This is achieved by non-rigidly registering the MR data with a tissue probability atlas to automatically select training samples, followed by a post-processing step to keep the most reliable samples. The accuracy of the new method was compared to rigid registration-based training and to conventional kNN-based segmentation using training on manually labeled subjects for segmenting gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in 12 data sets. Furthermore, for all classification methods, the performance was assessed when varying the free parameters. Finally, the robustness of the fully automated procedure was evaluated on 59 subjects. The automated training method using non-rigid registration with a tissue probability atlas was significantly more accurate than rigid registration. For both automated training using non-rigid registration and for the manually trained kNN classifier, the difference with the manual labeling by observers was not significantly larger than inter-observer variability for all tissue types. From the robustness study, it was clear that, given an appropriate brain atlas and optimal parameters, our new fully automated, non-rigid registration-based method gives accurate and robust segmentation results. A similarity index was used for comparison with manually trained kNN. The similarity indices were 0.93, 0.92 and 0.92, for CSF, GM and WM, respectively. It can be concluded that our fully automated method using non-rigid registration may replace manual segmentation, and thus that automated brain tissue segmentation without laborious manual training is feasible.

Tumour exosome integrins determine organotropic metastasis

PubMed Central

Hoshino, Ayuko; Costa-Silva, Bruno; Shen, Tang-Long; Rodrigues, Goncalo; Hashimoto, Ayako; Mark, Milica Tesic; Molina, Henrik; Kohsaka, Shinji; Di Giannatale, Angela; Ceder, Sophia; Singh, Swarnima; Williams, Caitlin; Soplop, Nadine; Uryu, Kunihiro; Pharmer, Lindsay; King, Tari; Bojmar, Linda; Davies, Alexander E.; Ararso, Yonathan; Zhang, Tuo; Zhang, Haiying; Hernandez, Jonathan; Weiss, Joshua M.; Dumont-Cole, Vanessa D.; Kramer, Kimberly; Wexler, Leonard H.; Narendran, Aru; Schwartz, Gary K.; Healey, John H.; Sandstrom, Per; Labori, Knut Jørgen; Kure, Elin H.; Grandgenett, Paul M.; Hollingsworth, Michael A.; de Sousa, Maria; Kaur, Sukhwinder; Jain, Maneesh; Mallya, Kavita; Batra, Surinder K.; Jarnagin, William R.; Brady, Mary S.; Fodstad, Oystein; Muller, Volkmar; Pantel, Klaus; Minn, Andy J.; Bissell, Mina J.; Garcia, Benjamin A.; Kang, Yibin; Rajasekhar, Vinagolu K.; Ghajar, Cyrus M.; Matei, Irina; Peinado, Hector; Bromberg, Jacqueline; Lyden, David

2015-01-01

Ever since Stephen Paget’s 1889 hypothesis, metastatic organotropism has remained one of cancer’s greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis. PMID:26524530

Tumour exosome integrins determine organotropic metastasis

DOE PAGES

Hoshino, Ayuko; Costa-Silva, Bruno; Shen, Tang-Long; ...

2015-10-28

Ever since Stephen Paget’s 1889 hypothesis, metastatic organotropism has remained one of cancer’s greatest mysteries. In this paper, we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α 6β 4 and α 6β 1 weremore » associated with lung metastasis, while exosomal integrin α vβ 5 was linked to liver metastasis. Targeting the integrins α 6β 4 and α vβ 5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. In conclusion, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.« less

Tumour exosome integrins determine organotropic metastasis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoshino, Ayuko; Costa-Silva, Bruno; Shen, Tang-Long

Ever since Stephen Paget’s 1889 hypothesis, metastatic organotropism has remained one of cancer’s greatest mysteries. In this paper, we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α 6β 4 and α 6β 1 weremore » associated with lung metastasis, while exosomal integrin α vβ 5 was linked to liver metastasis. Targeting the integrins α 6β 4 and α vβ 5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. In conclusion, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.« less

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

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 functional magnetic resonance imaging (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. Copyright © 2013 Elsevier Inc. All rights reserved.

Occupational risk factors for low grade and high grade glioma: results from an international case control study of adult brain tumours.

PubMed

Schlehofer, Brigitte; Hettinger, Iris; Ryan, Philip; Blettner, Maria; Preston-Martin, Susan; Little, Julian; Arslan, Annie; Ahlbom, Anders; Giles, Graham G; Howe, Geoffrey R; Ménégoz, Francoise; Rodvall, Ylva; Choi, Won N; Wahrendorf, Jürgen

2005-01-01

The majority of suspected occupational risk factors for adult brain tumours have yet to be confirmed as etiologically relevant. Within an international case-control study on brain tumours, lifelong occupational histories and information on exposures to specific substances were obtained by direct interviews to further investigate occupational risk factors for glioma. This is one of the largest studies of brain tumours in adults, including 1,178 cases and 1987 population controls from 8 collaborating study centres matched for age, gender and centre. All occupational information, was aggregated into 16 occupational categories. In a pooled analysis, odds ratios (OR), adjusted for education, were estimated separately for men and women and for high-grade glioma (HGG) and low-grade glioma (LGG), focusing especially on 6 categories defined a priori: agricultural, chemical, construction, metal, electrical/electronic and transport. For men, an elevated OR of glioma associated with the category "metal" (OR = 1.24, 95% CI 0.96-1.62) was seen, which appeared to be largely accounted for by LGG (OR = 1.59, 95% CI 1.00-2.52). For the other 5 occupational categories, no elevated risks for glioma were observed. For women the only noteworthy observation for the 6 a priori categories was an inverse association with the "agriculture" category (OR = 0.60, 95% CI 0.36-0.99). Apart from the 6 major categories, women working in food production or food processing (category "food") showed an increased OR of 1.95 (95% CI 1.04-3.68). None of the 20 substance groups was positively associated with glioma risk. Although some other point estimates were elevated, they lacked statistical significance. The results do not provide evidence of a strong association between occupational exposures and glioma development.

Tumours of the lower alimentary tract

PubMed Central

Head, K. W.

1976-01-01

This classification is presented in two parts: (a) tumours of the gastrointestinal tract; and (b) tumours of the anal canal and margin. In the gastrointestinal tract the tumours are classified as adenoma, adenocarcinoma, and undifferentiated carcinoma, with several subtypes. Most polyps prove to be non-neoplastic, hyperplastic, or regenerative rather than adenomatous. Carcinoma of the stomach occurs mainly in dogs, but is a rare tumour in all parts of the world. Moderately differentiated, tubular adenocarcinoma of the small intestine with excessive fibrosis occurs in all six species; in some geographical locations it may occur frequently in sheep and cattle. The adenoma/carcinoma sequence in the rectum of the dog is similar to that in man but is encountered less often. Carcinoid tumours are very rare in domestic animals. Among the soft tissue tumours, those of smooth muscle and adipose tissue are found fairly frequently and congenital mesothelioma in the peritoneum of calves occurs occasionally. Tumours of the haematopoietic and related tissues are the most common gastrointestinal neoplasms in all species and most belong to the lymphosarcoma group. Tumours of the anal canal and margin are common in the dog and 90% of these are tumours of the hepatoid (perianal) glands. ImagesFig. 1Fig. 2Fig. 3Fig. 4Fig. 29Fig. 30Fig. 31Fig. 32Fig. 33Fig. 34Fig. 35Fig. 36Fig. 13Fig. 14Fig. 15Fig. 16Fig. 9Fig. 10Fig. 11Fig. 12Fig. 5Fig. 6Fig. 7Fig. 8Fig. 37Fig. 38Fig. 39Fig. 40Fig. 25Fig. 26Fig. 27Fig. 28Fig. 17Fig. 18Fig. 19Fig. 20Fig. 21Fig. 22Fig. 23Fig. 24 PMID:1086148

[Acquired brain injury: a proposal for its definition, diagnostic criteria and classification].

PubMed

Castellanos-Pinedo, Fernando; Cid-Gala, Manuel; Duque, Pablo; Ramirez-Moreno, José M; Zurdo-Hernández, José M

2012-03-16

Acquired brain injury is a heterogeneous clinical concept that goes beyond the limits of the classical medical view, which tends to define processes and diseases on the grounds of a single causation. Although in the medical literature it appears fundamentally associated to traumatic brain injury, there are many other causes and management is similar in all of them, during the post-acute and chronic phases, as regards the measures to be taken concerning rehabilitation and attention to dependence. Yet, despite being an important health issue, today we do not have a set of diagnostic criteria or a classification for this condition. This is a serious handicap when it comes to carrying out epidemiological studies, designing specific care programmes and comparing results among different programmes and centres. Accordingly, the Extremadura Acquired Brain Injury Health Care Plan working group has drawn up these proposed diagnostic criteria, definition and classification. The proposal is intended to be essentially practical, its main purpose being to allow correct identification of the cases that must be attended to and to optimise the use of neurorehabilitation and attention to dependence resources, thereby ensuring attention is provided on a fair basis.

Short term outcomes following surgery in brain tumours sans neuronavigation.

PubMed

Rashid, Mamoon Ur; Junaid, Muhammad; Bukhari, Syed Sarmad; Afsheen, Afeera

2018-02-01

To determine the presentation and frequency of various intracranial neoplasms and assess outcomes for patients who underwent surgery without neuronavigation. This retrospective study was conducted at Combined Military Hospital, Peshawar, Pakistan, and comprised medical records related to the period from August 2011 to July 2014. Patient histories, examination reports and preoperative and post-operative radiological scans were reviewed and extent of excision was determined based on these coupled with recurrence rates. Intraoperatively, tumour excision was determined largely by the experience of the surgeon and preoperative planning using bony landmarks and radiological scans as an objective guide to resection. SPSS 21 was used for data analysis. Of the 143 patients, 83(57.9%) were males and 60(42.1%)were females. Gliomas were the most common tumours, occurring in 20(33.3%) females and 35(42.2%) males. One-year survival rate for grade 4 astrocytomas was poor (39.4%) and was excellent for meningiomas (100%) and pituitary tumours (100%). Time-tested methods of careful neurological examination and knowledge of neuroanatomy can allow a surgeon with limited resources to plan and accommodate for accurate tumour resection with adequate margins.

Genomic aberrations in spitzoid tumours and their implications for diagnosis, prognosis and therapy

PubMed Central

Wiesner, Thomas; Kutzner, Heinz; Cerroni, Lorenzo; Mihm, Martin J.; Busam, Klaus J.; Murali, Rajmohan

2016-01-01

Summary Histopathological evaluation of melanocytic tumours usually allows reliable distinction of benign melanocytic naevi from melanoma. More difficult is the histopathological classification of Spitz tumours, a heterogeneous group of tumours composed of large epithelioid or spindle-shaped melanocytes. Spitz tumours are biologically distinct from conventional melanocytic naevi and melanoma, as exemplified by their distinct patterns of genetic aberrations. Whereas conventional naevi and melanoma often harbour BRAF mutations, NRAS mutations, or inactivation of NF1, Spitz tumours show HRAS mutations, inactivation of BAP1 (often combined with BRAF mutations), or genomic rearrangements involving the kinases ALK, ROS1, NTRK1, BRAF, RET, and MET. In Spitz naevi, which lack significant histological atypia, all of these mitogenic driver aberrations trigger rapid cell proliferation, but after an initial growth phase, various tumour suppressive mechanisms stably block further growth. In some tumours, additional genomic aberrations may abrogate various tumour suppressive mechanisms, such as cell-cycle arrest, telomere shortening, or DNA damage response. The melanocytes then start to grow in a less organised fashion, may spread to regional lymph nodes, and are termed atypical Spitz tumours. Upon acquisition of even more aberrations, which often activate additional oncogenic pathways or reduce and alter cell differentiation, the neoplastic cells become entirely malignant and may colonise and take over distant organs (spitzoid melanoma). The sequential acquisition of genomic aberrations suggests that Spitz tumours represent a continuous biological spectrum, rather than a dichotomy of benign versus malignant, and that tumours with ambiguous histological features (atypical Spitz tumours) might be best classified as low-grade melanocytic tumours. The number of genetic aberrations usually correlates with the degree of histological atypia and explains why existing ancillary genetic

Investigating intracranial tumour growth patterns with multiparametric MRI incorporating Gd-DTPA and USPIO-enhanced imaging.

PubMed

Boult, Jessica K R; Borri, Marco; Jury, Alexa; Popov, Sergey; Box, Gary; Perryman, Lara; Eccles, Suzanne A; Jones, Chris; Robinson, Simon P

2016-11-01

High grade and metastatic brain tumours exhibit considerable spatial variations in proliferation, angiogenesis, invasion, necrosis and oedema. Vascular heterogeneity arising from vascular co-option in regions of invasive growth (in which the blood-brain barrier remains intact) and neoangiogenesis is a major challenge faced in the assessment of brain tumours by conventional MRI. A multiparametric MRI approach, incorporating native measurements and both Gd-DTPA (Magnevist) and ultrasmall superparamagnetic iron oxide (P904)-enhanced imaging, was used in combination with histogram and unsupervised cluster analysis using a k-means algorithm to examine the spatial distribution of vascular parameters, water diffusion characteristics and invasion in intracranially propagated rat RG2 gliomas and human MDA-MB-231 LM2-4 breast adenocarcinomas in mice. Both tumour models presented with higher ΔR 1 (the change in transverse relaxation rate R 1 induced by Gd-DTPA), fractional blood volume (fBV) and apparent diffusion coefficient than uninvolved regions of the brain. MDA-MB-231 LM2-4 tumours were less densely cellular than RG2 tumours and exhibited substantial local invasion, associated with oedema, whereas invasion in RG2 tumours was minimal. These additional features were reflected in the more heterogeneous appearance of MDA-MB-231 LM2-4 tumours on T 2 -weighted images and maps of functional MRI parameters. Unsupervised cluster analysis separated subregions with distinct functional properties; areas with a low fBV and relatively impermeable blood vessels (low ΔR 1 ) were predominantly located at the tumour margins, regions of MDA-MB-231 LM2-4 tumours with relatively high levels of water diffusion and low vascular permeability and/or fBV corresponded to histologically identified regions of invasion and oedema, and areas of mismatch between vascular permeability and blood volume were identified. We demonstrate that dual contrast MRI and evaluation of tissue diffusion properties

WHO is in and WHO is out of the mouth, salivary glands, and jaws sections of the 4th edition of the WHO classification of head and neck tumours.

PubMed

Kennedy, R A

2018-02-01

This review of changes to the 4th edition of the WHO classification of head and neck tumours focuses on their impact on the surgical care of diseases that affect the salivary glands, jaws, and oral cavity. Updates to the chapter on the salivary glands include the addition of secretory carcinoma and sclerosing polycystic adenosis. The odontogenic cysts are back, and the odontogenic keratocyst is listed among them, as it has now lost its brief and confusing designation as a neoplasm. The newly-defined sclerosing odontogenic carcinoma and primordial odontogenic tumour have been added. Oropharyngeal tumours have been separated from those of the oral cavity, which reflects the importance of HPV in carcinoma of the tonsils. The problems of grading oral epithelial dysplasia persist. Copyright © 2017 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Online EEG Classification of Covert Speech for Brain-Computer Interfacing.

PubMed

Sereshkeh, Alborz Rezazadeh; Trott, Robert; Bricout, Aurélien; Chau, Tom

2017-12-01

Brain-computer interfaces (BCIs) for communication can be nonintuitive, often requiring the performance of hand motor imagery or some other conversation-irrelevant task. In this paper, electroencephalography (EEG) was used to develop two intuitive online BCIs based solely on covert speech. The goal of the first BCI was to differentiate between 10[Formula: see text]s of mental repetitions of the word "no" and an equivalent duration of unconstrained rest. The second BCI was designed to discern between 10[Formula: see text]s each of covert repetition of the words "yes" and "no". Twelve participants used these two BCIs to answer yes or no questions. Each participant completed four sessions, comprising two offline training sessions and two online sessions, one for testing each of the BCIs. With a support vector machine and a combination of spectral and time-frequency features, an average accuracy of [Formula: see text] was reached across participants in the online classification of no versus rest, with 10 out of 12 participants surpassing the chance level (60.0% for [Formula: see text]). The online classification of yes versus no yielded an average accuracy of [Formula: see text], with eight participants exceeding the chance level. Task-specific changes in EEG beta and gamma power in language-related brain areas tended to provide discriminatory information. To our knowledge, this is the first report of online EEG classification of covert speech. Our findings support further study of covert speech as a BCI activation task, potentially leading to the development of more intuitive BCIs for communication.

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

PubMed

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

2014-05-15

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.

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

PubMed

Schüz, Joachim

2009-08-01

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

Mobile phones and brain tumours: a review of epidemiological research.

PubMed

Croft, R J; McKenzie, R J; Inyang, I; Benke, G P; Anderson, V; Abramson, M J

2008-12-01

There has been a great deal of public concern regarding the possibility that the use of mobile phone-related technologies might result in adverse health effects. Corresponding to this, there has been substantial epidemiological research designed to determine whether the use of mobile phones (MP) has any effect on health, and in particular whether it increases the risk of developing head and neck tumours. Such literature is particularly heterogeneous, which makes it difficult to pool in a meta-analysis. This paper thus reviews the epidemiological literature pertaining to the use of mobile phones and mobile phone-related technologies, and head and neck tumours, in an attempt to consolidate the various reports. Although there have been individual reports of associations between MP-use and tumours, this research is not consistent and on balance does not provide evidence of an association. There are reports of small associations between MP-use ipsilateral to the tumour for greater than 10 years, for both acoustic neuroma and glioma, but the present paper argues that these are especially prone to confounding by recall bias. The reported associations are in need of replication with methods designed to minimise such bias before they can be treated as more than suggestive.

Hybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review.

PubMed

Hong, Keum-Shik; Khan, Muhammad Jawad

2017-01-01

In this article, non-invasive hybrid brain-computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain-computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

Medulloblastoma genotype dictates blood brain barrier phenotype

PubMed Central

Phoenix, Timothy N.; Patmore, Deanna M.; Boop, Scott; Boulos, Nidal; Jacus, Megan O.; Patel, Yogesh T.; Roussel, Martine F; Finkelstein, David; Goumnerova, Lilian; Perreault, Sebastien; Wadhwa, Elizabeth; Cho, Yoon-Jae; Stewart, Clinton F.; Gilbertson, Richard J.

2016-01-01

SUMMARY The childhood brain tumour medulloblastoma includes four subtypes with very different prognoses. Here, we show that paracrine signals driven by mutant Beta-Catenin in WNT-medulloblastoma – an essentially curable form of the disease – induce an aberrant fenestrated vasculature that permits the accumulation of high levels of intra-tumoural chemotherapy and a robust therapeutic response. In contrast, SHH-medulloblastoma – a less curable disease subtype – contains an intact blood brain barrier, rendering this tumour impermeable and resistant to chemotherapy. The medulloblastoma-endothelial cell paracrine axis can be manipulated in vivo, altering chemotherapy permeability and clinical response. Thus, medulloblastoma genotype dictates tumour vessel phenotype, explaining in part the disparate prognoses among medulloblastoma subtypes and suggesting an approach to enhance the chemoresponsiveness of other brain tumours. PMID:27050100

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

Optical spectroscopy techniques can accurately distinguish benign and malignant renal tumours.

PubMed

Couapel, Jean-Philippe; Senhadji, Lotfi; Rioux-Leclercq, Nathalie; Verhoest, Grégory; Lavastre, Olivier; de Crevoisier, Renaud; Bensalah, Karim

2013-05-01

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: There is little known about optical spectroscopy techniques ability to evaluate renal tumours. This study shows for the first time the ability of Raman and optical reflectance spectroscopy to distinguish benign and malignant renal tumours in an ex vivo environment. We plan to develop this optical assistance in the operating room in the near future. To evaluate the ability of Raman spectroscopy (RS) and optical reflectance spectroscopy (ORS) to distinguish benign and malignant renal tumours at surgery. Between March and October 2011, RS and ORS spectra were prospectively acquired on surgical renal specimens removed for suspicion of renal cell carcinoma (RCC). Optical measurements were done immediately after surgery. Optical signals were normalised to ensure comparison between spectra. Initial and final portions of each spectrum were removed to avoid artefacts. A support vector machine (SVM) was built and tested using a leave-one-out cross-validation. Classification scores, including accuracy, sensitivity and specificity were calculated on the entire population and in patients with tumours of <4 cm. In all, 60 nephrectomies were performed for 53 malignant tumours (41 clear-cell, eight papillary and four chromophobe carcinomas) and seven benign tumours (four oncocytomas, two angiomyolipomas and a haemorrhagic cyst). In all, >700 optical spectra were obtained and submitted to SVM classification. The SVM could recognise benign and malignant renal tumours with an accuracy of 96% (RS) and 88% (ORS) in the whole population and with an accuracy of 93% (RS) and 95% (ORS) in the present subset of small renal tumours (<4 cm). Histological subtype could be determined in 80% and 88% of the cases with RS and ORS, respectively. The SVM was able to differentiate chromophobe carcinomas and benign lesions with an accuracy of 96% in RS and 98% in ORS. Benign and malignant renal tumours can be accurately discriminated by a

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition

PubMed Central

Zhan, Liang; Liu, Yashu; Wang, Yalin; Zhou, Jiayu; Jahanshad, Neda; Ye, Jieping; Thompson, Paul M.

2015-01-01

Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying brain imaging biomarkers that help to automatically differentiate stages of Alzheimer's disease. Here, we focused on brain structural networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying different stages of Alzheimer's disease. PMID:26257601

Mucinous tumours of appendix and ovary: an overview and evaluation of current practice.

PubMed

Rouzbahman, Marjan; Chetty, Runjan

2014-03-01

Mucinous lesions of the appendix and ovary are commonly encountered in routine practice. There are several published classification schemes for appendiceal mucinous neoplasms with resultant inconsistent use of terms and clinical doubt. While nomenclature is more settled with regards to ovarian mucinous neoplasms, the difficulty here lies with distinguishing primary from secondary mucinous tumours. This review highlights the terminology and nomenclature for appendiceal mucinous tumours, the relationship with ovarian mucinous neoplasms and pseudomyxoma peritonei, and the features that assist in separating primary from secondary ovarian mucinous tumours.

Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline

PubMed Central

Fan, Yong; Batmanghelich, Nematollah; Clark, Chris M.; Davatzikos, Christos

2010-01-01

Spatial patterns of brain atrophy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were measured via methods of computational neuroanatomy. These patterns were spatially complex and involved many brain regions. In addition to the hippocampus and the medial temporal lobe gray matter, a number of other regions displayed significant atrophy, including orbitofrontal and medial-prefrontal grey matter, cingulate (mainly posterior), insula, uncus, and temporal lobe white matter. Approximately 2/3 of the MCI group presented patterns of atrophy that overlapped with AD, whereas the remaining 1/3 overlapped with cognitively normal individuals, thereby indicating that some, but not all, MCI patients have significant and extensive brain atrophy in this cohort of MCI patients. Importantly, the group with AD-like patterns presented much higher rate of MMSE decline in follow-up visits; conversely, pattern classification provided relatively high classification accuracy (87%) of the individuals that presented relatively higher MMSE decline within a year from baseline. High-dimensional pattern classification, a nonlinear multivariate analysis, provided measures of structural abnormality that can potentially be useful for individual patient classification, as well as for predicting progression and examining multivariate relationships in group analyses. PMID:18053747

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

PubMed

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

2014-01-01

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

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

PubMed

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

2015-03-01

There is an increasing demand for noninvasive brain tumor biomarkers to guide surgery and subsequent oncotherapy. We present a novel whole-brain diffusion tensor imaging (DTI) segmentation (D-SEG) to delineate tumor volumes of interest (VOIs) for subsequent classification of tumor type. D-SEG uses isotropic (p) and anisotropic (q) components of the diffusion tensor to segment regions with similar diffusion characteristics. DTI scans were acquired from 95 patients with low- and high-grade glioma, metastases, and meningioma and from 29 healthy subjects. D-SEG uses k-means clustering of the 2D (p,q) space to generate segments with different isotropic and anisotropic diffusion characteristics. Our results are visualized using a novel RGB color scheme incorporating p, q and T2-weighted information within each segment. The volumetric contribution of each segment to gray matter, white matter, and cerebrospinal fluid spaces was used to generate healthy tissue D-SEG spectra. Tumor VOIs were extracted using a semiautomated flood-filling technique and D-SEG spectra were computed within the VOI. Classification of tumor type using D-SEG spectra was performed using support vector machines. D-SEG was computationally fast and stable and delineated regions of healthy tissue from tumor and edema. D-SEG spectra were consistent for each tumor type, with constituent diffusion characteristics potentially reflecting regional differences in tissue microstructure. Support vector machines classified tumor type with an overall accuracy of 94.7%, providing better classification than previously reported. D-SEG presents a user-friendly, semiautomated biomarker that may provide a valuable adjunct in noninvasive brain tumor diagnosis and treatment planning. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.

On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.

PubMed

Pläschke, Rachel N; Cieslik, Edna C; Müller, Veronika I; Hoffstaedter, Felix; Plachti, Anna; Varikuti, Deepthi P; Goosses, Mareike; Latz, Anne; Caspers, Svenja; Jockwitz, Christiane; Moebus, Susanne; Gruber, Oliver; Eickhoff, Claudia R; Reetz, Kathrin; Heller, Julia; Südmeyer, Martin; Mathys, Christian; Caspers, Julian; Grefkes, Christian; Kalenscher, Tobias; Langner, Robert; Eickhoff, Simon B

2017-12-01

Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc. © 2017

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

PubMed Central

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

2016-01-01

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

Telomere sequence content can be used to determine ALT activity in tumours

PubMed Central

Lee, Michael; Teber, Erdahl T; Holmes, Oliver; Nones, Katia; Patch, Ann-Marie; Dagg, Rebecca A; Lau, Loretta M S; Lee, Joyce H; Napier, Christine E; Arthur, Jonathan W; Grimmond, Sean M; Hayward, Nicholas K; Johansson, Peter A; Mann, Graham J; Scolyer, Richard A; Wilmott, James S; Reddel, Roger R; Pearson, John V; Waddell, Nicola; Pickett, Hilda A

2018-01-01

Abstract The replicative immortality of human cancer cells is achieved by activation of a telomere maintenance mechanism (TMM). To achieve this, cancer cells utilise either the enzyme telomerase, or the Alternative Lengthening of Telomeres (ALT) pathway. These distinct molecular pathways are incompletely understood with respect to activation and propagation, as well as their associations with clinical outcomes. We have identified significant differences in the telomere repeat composition of tumours that use ALT compared to tumours that do not. We then employed a machine learning approach to stratify tumours according to telomere repeat content with an accuracy of 91.6%. Importantly, this classification approach is applicable across all tumour types. Analysis of pathway mutations that were under-represented in ALT tumours, across 1,075 tumour samples, revealed that the autophagy, cell cycle control of chromosomal replication, and transcriptional regulatory network in embryonic stem cells pathways are involved in the survival of ALT tumours. Overall, our approach demonstrates that telomere sequence content can be used to stratify ALT activity in cancers, and begin to define the molecular pathways involved in ALT activation. PMID:29718321

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

PubMed

Mete, Mutlu; Sakoglu, Unal; Spence, Jeffrey S; Devous, Michael D; Harris, Thomas S; Adinoff, Bryon

2016-10-06

Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2-4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations. The voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of

Identification of genes involved in the biology of atypical teratoid/rhabdoid tumours using Drosophila melanogaster

NASA Astrophysics Data System (ADS)

Jeibmann, Astrid; Eikmeier, Kristin; Linge, Anna; Kool, Marcel; Koos, Björn; Schulz, Jacqueline; Albrecht, Stefanie; Bartelheim, Kerstin; Frühwald, Michael C.; Pfister, Stefan M.; Paulus, Werner; Hasselblatt, Martin

2014-06-01

Atypical teratoid/rhabdoid tumours (AT/RT) are malignant brain tumours. Unlike most other human brain tumours, AT/RT are characterized by inactivation of one single gene, SMARCB1. SMARCB1 is a member of the evolutionarily conserved SWI/SNF chromatin remodelling complex, which has an important role in the control of cell differentiation and proliferation. Little is known, however, about the pathways involved in the oncogenic effects of SMARCB1 inactivation, which might also represent targets for treatment. Here we report a comprehensive genetic screen in the fruit fly that revealed several genes not yet associated with loss of snr1, the Drosophila homologue of SMARCB1. We confirm the functional role of identified genes (including merlin, kibra and expanded, known to regulate hippo signalling pathway activity) in human rhabdoid tumour cell lines and AT/RT tumour samples. These results demonstrate that fly models can be employed for the identification of clinically relevant pathways in human cancer.

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

PubMed

Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Classification of Types of Stuttering Symptoms Based on Brain Activity

PubMed Central

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

2012-01-01

Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type. PMID:22761887

Pairwise mixture model for unmixing partial volume effect in multi-voxel MR spectroscopy of brain tumour patients

NASA Astrophysics Data System (ADS)

Olliverre, Nathan; Asad, Muhammad; Yang, Guang; Howe, Franklyn; Slabaugh, Gregory

2017-03-01

Multi-Voxel Magnetic Resonance Spectroscopy (MV-MRS) provides an important and insightful technique for the examination of the chemical composition of brain tissue, making it an attractive medical imaging modality for the examination of brain tumours. MRS, however, is affected by the issue of the Partial Volume Effect (PVE), where the signals of multiple tissue types can be found within a single voxel and provides an obstacle to the interpretation of the data. The PVE results from the low resolution achieved in MV-MRS images relating to the signal to noise ratio (SNR). To counteract PVE, this paper proposes a novel Pairwise Mixture Model (PMM), that extends a recently reported Signal Mixture Model (SMM) for representing the MV-MRS signal as normal, low or high grade tissue types. Inspired by Conditional Random Field (CRF) and its continuous variant the PMM incorporates the surrounding voxel neighbourhood into an optimisation problem, the solution of which provides an estimation to a set of coefficients. The values of the estimated coefficients represents the amount of each tissue type (normal, low or high) found within a voxel. These coefficients can then be visualised as a nosological rendering using a coloured grid representing the MV-MRS image overlaid on top of a structural image, such as a Magnetic Resonance Image (MRI). Experimental results show an accuracy of 92.69% in classifying patient tumours as either low or high grade compared against the histopathology for each patient. Compared to 91.96% achieved by the SMM, the proposed PMM method demonstrates the importance of incorporating spatial coherence into the estimation as well as its potential clinical usage.

Prognostic factors and survival according to tumour subtype in women presenting with breast cancer brain metastases at initial diagnosis.

PubMed

Leone, José Pablo; Leone, Julieta; Zwenger, Ariel Osvaldo; Iturbe, Julián; Leone, Bernardo Amadeo; Vallejo, Carlos Teodoro

2017-03-01

The presence of brain metastases at the time of initial breast cancer diagnosis (BMIBCD) is uncommon. Hence, the prognostic assessment and management of these patients is very challenging. The aim of this study was to analyse the influence of tumour subtype compared with other prognostic factors in the survival of patients with BMIBCD. We evaluated women with BMIBCD, reported to Surveillance, Epidemiology and End Results program from 2010 to 2013. Patients with other primary malignancy were excluded. Univariate and multivariate analyses were performed to determine the effects of each variable on overall survival (OS). We included 740 patients. Median OS for the whole population was 10 months, and 20.7% of patients were alive at 36 months. Tumour subtype distribution was: 46.6% hormone receptor (HR)+/HER2-, 17% HR+/HER2+, 14.1% HR-/HER2+ and 22.3% triple-negative. Univariate analysis showed that the presence of liver metastases, lung metastases and triple-negative patients (median OS 6 months) had worse prognosis. The HR+/HER2+ subtype had the longest OS with a median of 22 months. In multivariate analysis, older age (hazard ratio 1.8), lobular histology (hazard ratio 2.08), triple-negative subtype (hazard ratio 2.25), liver metastases (hazard ratio 1.6) and unmarried patients (hazard ratio 1.39) had significantly shorter OS. Although the prognosis of patients with BMIBCD is generally poor, 20.7% were still alive 3 years after the diagnosis. There were substantial differences in OS according to tumour subtype. In addition to tumour subtype, other independent predictors of OS are age at diagnosis, marital status, histology and liver metastases. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2002-07-01

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

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

PubMed

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

2014-09-01

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

Modern radiosurgical and endovascular classification schemes for brain arteriovenous malformations.

PubMed

Tayebi Meybodi, Ali; Lawton, Michael T

2018-05-04

Stereotactic radiosurgery (SRS) and endovascular techniques are commonly used for treating brain arteriovenous malformations (bAVMs). They are usually used as ancillary techniques to microsurgery but may also be used as solitary treatment options. Careful patient selection requires a clear estimate of the treatment efficacy and complication rates for the individual patient. As such, classification schemes are an essential part of patient selection paradigm for each treatment modality. While the Spetzler-Martin grading system and its subsequent modifications are commonly used for microsurgical outcome prediction for bAVMs, the same system(s) may not be easily applicable to SRS and endovascular therapy. Several radiosurgical- and endovascular-based grading scales have been proposed for bAVMs. However, a comprehensive review of these systems including a discussion on their relative advantages and disadvantages is missing. This paper is dedicated to modern classification schemes designed for SRS and endovascular techniques.

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

NASA Astrophysics Data System (ADS)

Rusconi, Marco; Valleriani, Angelo

2016-06-01

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

Defining traumatic brain injury in children and youth using international classification of diseases version 10 codes: a systematic review protocol.

PubMed

Chan, Vincy; Thurairajah, Pravheen; Colantonio, Angela

2013-11-13

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. 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. 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

Iodine-123 alpha-methyl tyrosine single-photon emission tomography of cerebral gliomas: standardised evaluation of tumour uptake and extent.

PubMed

Weckesser, M; Griessmeier, M; Schmidt, D; Sonnenberg, F; Ziemons, K; Kemna, L; Holschbach, M; Langen, K; Müller-Gärtner, H

1998-02-01

Single-photon emission tomography (SPET) with the amino acid analogue l-3-[123I]iodo-alpha-methyl tyrosine (IMT) is helpful in the diagnosis and monitoring of cerebral gliomas. Radiolabelled amino acids seem to reflect tumour infiltration more specifically than conventional methods like magnetic resonance imaging and computed tomography. Automatic tumour delineation based on maximal tumour uptake may cause an overestimation of mean tumour uptake and an underestimation of tumour extension in tumours with circumscribed peaks. The aim of this study was to develop a program for tumour delineation and calculation of mean tumour uptake which takes into account the mean background activity and is thus optimised to the problem of tumour definition in IMT SPET. Using the frequency distribution of pixel intensities of the tomograms a program was developed which automatically detects a reference brain region and draws an isocontour region around the tumour taking into account mean brain radioactivity. Tumour area and tumour/brain ratios were calculated. A three-compartment phantom was simulated to test the program. The program was applied to IMT SPET studies of 20 patients with cerebral gliomas and was compared to the results of manual analysis by three different investigators. Activity ratios and chamber extension of the phantom were correctly calculated by the automatic analysis. A method based on image maxima alone failed to determine chamber extension correctly. Manual region of interest analysis in patient studies resulted in a mean inter-observer standard deviation of 8.7% +/ -6.1% (range 2.7% -25.0%). The mean value of the results of the manual analysis showed a significant correlation to the results of the automatic analysis (r = 0.91, P<0. 0001 for the uptake ratio; r = 0.87, P<0.0001 for the tumour area). We conclude that the algorithm proposed simplifies the calculation of uptake ratios and may be used for observer-independent evaluation of IMT SPET studies. Three

Segmentation and classification of brain images using firefly and hybrid kernel-based support vector machine

NASA Astrophysics Data System (ADS)

Selva Bhuvaneswari, K.; Geetha, P.

2017-05-01

Magnetic resonance imaging segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumour detection techniques are presented in the literature. The entire segmentation process of our proposed work comprises three phases: threshold generation with dynamic modified region growing phase, texture feature generation phase and region merging phase. by dynamically changing two thresholds in the modified region growing approach, the first phase of the given input image can be performed as dynamic modified region growing process, in which the optimisation algorithm, firefly algorithm help to optimise the two thresholds in modified region growing. After obtaining the region growth segmented image using modified region growing, the edges can be detected with edge detection algorithm. In the second phase, the texture feature can be extracted using entropy-based operation from the input image. In region merging phase, the results obtained from the texture feature-generation phase are combined with the results of dynamic modified region growing phase and similar regions are merged using a distance comparison between regions. After identifying the abnormal tissues, the classification can be done by hybrid kernel-based SVM (Support Vector Machine). The performance analysis of the proposed method will be carried by K-cross fold validation method. The proposed method will be implemented in MATLAB with various images.

Pooled analysis of two case-control studies on the use of cellular and cordless telephones and the risk of benign brain tumours diagnosed during 1997-2003.

PubMed

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

2006-02-01

The use of cellular and cordless telephones and the risk of brain tumours is of concern since the brain is a high exposure area. We present the results of a pooled analysis of two case-control studies on benign brain tumours diagnosed during 1997-2003 including answers from 1,254 (88%) cases and 2,162 (89%) controls aged 20-80 years. For acoustic neuroma, the use of analogue cellular phones gave an odds ratio (OR) of 2.9 and a 95% confidence interval (CI) of 2.0-4.3; for digital cellular phones, OR=1.5; 95% CI=1.1-2.1; and for cordless telephones, OR=1.5, 95% CI=1.04-2.0. The highest OR was found for analogue phones with a latency period of >15 years; OR=3.8, 95% CI=1.4-10. Regarding meningioma, the results were as follows: for analogue phones, OR=1.3, 95% CI=0.99-1.7; for digital phones, OR=1.1, 95% CI=0.9-1.3; and for cordless phones, OR=1.1, 95% CI=0.9-1.4. In the multivariate analysis, a significantly increased risk of acoustic neuroma was found with the use of analogue phones.

A clinical perspective on the 2016 WHO brain tumor classification and routine molecular diagnostics.

PubMed

van den Bent, Martin J; Weller, Michael; Wen, Patrick Y; Kros, Johan M; Aldape, Ken; Chang, Susan

2017-05-01

The 2007 World Health Organization (WHO) classification of brain tumors did not use molecular abnormalities as diagnostic criteria. Studies have shown that genotyping allows a better prognostic classification of diffuse glioma with improved treatment selection. This has resulted in a major revision of the WHO classification, which is now for adult diffuse glioma centered around isocitrate dehydrogenase (IDH) and 1p/19q diagnostics. This revised classification is reviewed with a focus on adult brain tumors, and includes a recommendation of genes of which routine testing is clinically useful. Apart from assessment of IDH mutational status including sequencing of R132H-immunohistochemistry negative cases and testing for 1p/19q, several other markers can be considered for routine testing, including assessment of copy number alterations of chromosome 7 and 10 and of TERT promoter, BRAF, and H3F3A mutations. For "glioblastoma, IDH mutated" the term "astrocytoma grade IV" could be considered. It should be considered to treat IDH wild-type grades II and III diffuse glioma with polysomy of chromosome 7 and loss of 10q as glioblastoma. New developments must be more quickly translated into further revised diagnostic categories. Quality control and rapid integration of molecular findings into the final diagnosis and the communication of the final diagnosis to clinicians require systematic attention. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Modern Management of Pancoast Tumour].

PubMed

Marra, Alessandro

2018-06-01

Pancoast or superior pulmonary sulcus tumour is a subset of lung carcinoma that invades the structures of the thoracic inlet - first ribs, distal roots of the brachial plexus, stellate ganglion, vertebrae, and subclavian vessels. The first symptom is usually shoulder pain; consequently, most patients are initially treated for osteoarthritis. Late diagnosis is common. Success of therapy depends on an accurate staging: standard imaging with CT scan of the chest, PET-CT scan, brain MRI are needed to rule out distant metastases, endobronchial ultrasound-guided needle biopsy (EBUS-TBNA) or mediastinoscopy are mandatory for reliable nodal staging. An MRI of the thoracic inlet allows to clearly define the boundaries of local invasion. Modern management of Pancoast tumour includes induction concurrent chemoradiotherapy followed by surgical resection. As compared with historical series treated by preoperative radiation, a trimodally approach did enhance complete resection rates and perhaps long-term survival - from about 30% 5-year survival rate to 60% in R0-resected patients. In patients who have unresectable but non-metastatic Pancoast tumours and appropriate performance status, definitive concurrent chemoradiotherapy and radiotherapy are recommended options. Georg Thieme Verlag KG Stuttgart · New York.

Calorie restriction as an anti-invasive therapy for malignant brain cancer in the VM mouse.

PubMed

Shelton, Laura M; Huysentruyt, Leanne C; Mukherjee, Purna; Seyfried, Thomas N

2010-07-23

GBM (glioblastoma multiforme) is the most aggressive and invasive form of primary human brain cancer. We recently developed a novel brain cancer model in the inbred VM mouse strain that shares several characteristics with human GBM. Using bioluminescence imaging, we tested the efficacy of CR (calorie restriction) for its ability to reduce tumour size and invasion. CR targets glycolysis and rapid tumour cell growth in part by lowering circulating glucose levels. The VM-M3 tumour cells were implanted intracerebrally in the syngeneic VM mouse host. Approx. 12-15 days post-implantation, brains were removed and both ipsilateral and contralateral hemispheres were imaged to measure bioluminescence of invading tumour cells. CR significantly reduced the invasion of tumour cells from the implanted ipsilateral hemisphere into the contralateral hemisphere. The total percentage of Ki-67-stained cells within the primary tumour and the total number of blood vessels was also significantly lower in the CR-treated mice than in the mice fed ad libitum, suggesting that CR is anti-proliferative and anti-angiogenic. Our findings indicate that the VM-M3 GBM model is a valuable tool for studying brain tumour cell invasion and for evaluating potential therapeutic approaches for managing invasive brain cancer. In addition, we show that CR can be effective in reducing malignant brain tumour growth and invasion.

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification

PubMed Central

Dai, Mengxi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods. PMID:29743934

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification.

PubMed

Dai, Mengxi; Zheng, Dezhi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods.

Modern classification and outcome predictors of surgery in patients with brain arteriovenous malformations.

PubMed

Tayebi Meybodi, Ali; Lawton, Michael T

2018-02-23

Brain arteriovenous malformations (bAVM) are challenging lesions. Part of this challenge stems from the infinite diversity of these lesions regarding shape, location, anatomy, and physiology. This diversity has called on a variety of treatment modalities for these lesions, of which microsurgical resection prevails as the mainstay of treatment. As such, outcome prediction and managing strategy mainly rely on unraveling the nature of these complex tangles and ways each lesion responds to various therapeutic modalities. This strategy needs the ability to decipher each lesion through accurate and efficient categorization. Therefore, classification schemes are essential parts of treatment planning and outcome prediction. This article summarizes different surgical classification schemes and outcome predictors proposed for bAVMs.

Tumour-associated glial host cells display a stem-like phenotype with a distinct gene expression profile and promote growth of GBM xenografts.

PubMed

Leiss, Lina; Mutlu, Ercan; Øyan, Anne; Yan, Tao; Tsinkalovsky, Oleg; Sleire, Linda; Petersen, Kjell; Rahman, Mohummad Aminur; Johannessen, Mireille; Mitra, Sidhartha S; Jacobsen, Hege K; Talasila, Krishna M; Miletic, Hrvoje; Jonassen, Inge; Li, Xingang; Brons, Nicolaas H; Kalland, Karl-Henning; Wang, Jian; Enger, Per Øyvind

2017-02-07

Little is known about the role of glial host cells in brain tumours. However, supporting stromal cells have been shown to foster tumour growth in other cancers. We isolated stromal cells from patient-derived glioblastoma (GBM) xenografts established in GFP-NOD/scid mice. With simultaneous removal of CD11b + immune and CD31 + endothelial cells by fluorescence activated cell sorting (FACS), we obtained a population of tumour-associated glial cells, TAGs, expressing markers of terminally differentiaed glial cell types or glial progenitors. This cell population was subsequently characterised using gene expression analyses and immunocytochemistry. Furthermore, sphere formation was assessed in vitro and their glioma growth-promoting ability was examined in vivo. Finally, the expression of TAG related markers was validated in human GBMs. TAGs were highly enriched for the expression of glial cell proteins including GFAP and myelin basic protein (MBP), and immature markers such as Nestin and O4. A fraction of TAGs displayed sphere formation in stem cell medium. Moreover, TAGs promoted brain tumour growth in vivo when co-implanted with glioma cells, compared to implanting only glioma cells, or glioma cells and unconditioned glial cells from mice without tumours. Genome-wide microarray analysis of TAGs showed an expression profile distinct from glial cells from healthy mice brains. Notably, TAGs upregulated genes associated with immature cell types and self-renewal, including Pou3f2 and Sox2. In addition, TAGs from highly angiogenic tumours showed upregulation of angiogenic factors, including Vegf and Angiopoietin 2. Immunohistochemistry of three GBMs, two patient biopsies and one GBM xenograft, confirmed that the expression of these genes was mainly confined to TAGs in the tumour bed. Furthermore, their expression profiles displayed a significant overlap with gene clusters defining prognostic subclasses of human GBMs. Our data demonstrate that glial host cells in brain

Quality and readability of information materials for people with brain tumours and their families.

PubMed

Langbecker, Danette; Janda, Monika

2012-12-01

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

Goseki grade and tumour location influence survival of patients with gastric cancer.

PubMed

Calik, Muhammet; Calik, Ilknur; Demirci, Elif; Altun, Eren; Gundogdu, Betul; Sipal, Sare; Gundogdu, Cemal

2014-01-01

Owing to the variability of histopathological features and biological behaviour in gastric carcinoma, a great number of categorisation methods such as classical histopathologic grading, Lauren classification, the TNM staging system and the newly presented Goseki grading method are used by pathologists and other scientists. In our study, we aimed to investigate whether Goseki grade and tumour location have an effects on survival of gastric cancer cases. Eighty-four patients with gastric adenocarcinoma were covered in the investigation. The importance of Goseki grading system and tumour location were analysed in addition to the TNM staging and other conventional prognostic parameters. The median survival time in our patients was 35 months (minimum: 5, maximum: 116). According to our findings, there was no relation between survival and tumour size (p=0.192) or classical histological type (p=0.270). In contrast, the Goseki grade and tumour location significantly correlated with survival (p=0.007 and p<0.001, respectively). Additionally, tumours of the intestinal type had a longer median survival time (60.0 months) than diffuse tumours (24.0 months). In addition to the TNM staging system, tumour location and the Goseki grading system may be used as significant prognostic parameters in patients with gastric cancer.

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

PubMed

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

2008-05-01

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

Gastrointestinal neuroendocrine (carcinoid) tumours: current diagnosis and management.

PubMed

Modlin, Irvin M; Moss, Steven F; Oberg, Kjell; Padbury, Robert; Hicks, Rodney J; Gustafsson, Bjorn I; Wright, Nicholas A; Kidd, Mark

2010-07-05

Neuroendocrine tumours (NETs) are increasing in both incidence and prevalence and, as a group, are more prevalent than either gastric, pancreatic, oesophageal or hepatobiliary adenocarcinomas, or any two of these cancers combined. Clinical awareness of the protean and intermittent symptoms of NETs (eg, sweating, flushing, diarrhoea, and bronchospasm) is critical for timely diagnosis; however, the classical carcinoid syndrome is relatively uncommon. The most useful diagnostic test for gastrointestinal NETs is measurement of plasma chromogranin A (CgA) levels. Disease extent is assessed by both anatomical imaging, and nuclear imaging with radiolabelled somatostatin analogues. Pathological evaluation comprises tumour-node-metastasis classification, a minimum pathological dataset, CgA and synaptophysin immunostaining, as well as mitotic count or Ki-67 index (a marker of cell proliferation) to define grading. Resection of the primary lesion and as much metastatic disease as possible increases the efficacy of medical therapy. Other management strategies include hepatic embolisation and peptide receptor radionuclide therapy. Patients with tumours expressing somatostatin receptors should be treated with somatostatin analogues. Depending on the tumour grade, other effective agents include cytotoxics, tyrosine kinase inhibitors, and antiangiogenics. The overarching requirement for best management of patients with NETs is to ensure that they have ready access to experienced multidisciplinary clinician groups located within centres of appropriate subspecialty expertise.

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

PubMed

Farquhar, J; Hill, N J

2013-04-01

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.

Gastric neuroendocrine tumours.

PubMed

Crosby, David A; Donohoe, Claire L; Fitzgerald, Louise; Muldoon, Cian; Hayes, Brian; O'Toole, Dermot; Reynolds, John V

2012-01-01

Gastric neuroendocrine tumours (NETs) are increasingly recognised, and management decisions may be difficult due to an incomplete understanding of aetiology, natural history and optimum therapy. This article presents a current understanding based on recent advances in epidemiology, classification, molecular profiling, and treatment. Relevant medical literature was identified from searches of PubMed and references cited in appropriate articles identified. Selection of articles was based on peer review, journal and relevance. Gastric NETs may be divided into three clinical prognostic groups: type I is associated with autoimmune atrophic gastritis and hypergastrinaemia, type II is associated with Zollinger-Ellison syndrome, and type III lesions are gastrin-independent, have the greatest metastatic potential and poorest prognosis. There has been an increased frequency of gastric NETs reported. Management approaches have evolved in parallel with advances in endoscopic staging and surgery, as well as improved understanding of the biology and natural history of NETs. Gastric NETs present a spectrum of activity from indolent tumours to metastatic malignancy. Treatment decisions for patients must be individualised and are best managed by a multidisciplinary team approach. The current evidence base is limited to small series and efforts to treat patients within clinical networks of expertise are warranted. Copyright © 2012 S. Karger AG, Basel.

Threshold selection for classification of MR brain images by clustering method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moldovanu, Simona; Dumitru Moţoc High School, 15 Milcov St., 800509, Galaţi; Obreja, Cristian

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

Threshold selection for classification of MR brain images by clustering method

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Obreja, Cristian; Moraru, Luminita

2015-12-01

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

Pattern classification of brain activation during emotional processing in subclinical depression: psychosis proneness as potential confounding factor.

PubMed

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

2013-01-01

We used Support Vector Machine (SVM) to perform multivariate pattern classification based on brain activation during emotional processing in healthy participants with subclinical depressive symptoms. Six-hundred undergraduate students completed the Beck Depression Inventory II (BDI-II). Two groups were subsequently formed: (i) subclinical (mild) mood disturbance (n = 17) and (ii) no mood disturbance (n = 17). Participants also completed a self-report questionnaire on subclinical psychotic symptoms, the Community Assessment of Psychic Experiences Questionnaire (CAPE) positive subscale. The functional magnetic resonance imaging (fMRI) paradigm entailed passive viewing of negative emotional and neutral scenes. The pattern of brain activity during emotional processing allowed correct group classification with an overall accuracy of 77% (p = 0.002), within a network of regions including the amygdala, insula, anterior cingulate cortex and medial prefrontal cortex. However, further analysis suggested that the classification accuracy could also be explained by subclinical psychotic symptom scores (correlation with SVM weights r = 0.459, p = 0.006). Psychosis proneness may thus be a confounding factor for neuroimaging studies in subclinical depression.

Reliability of a novel, semi-quantitative scale for classification of structural brain magnetic resonance imaging in children with cerebral palsy.

PubMed

Fiori, Simona; Cioni, Giovanni; Klingels, Katrjin; Ortibus, Els; Van Gestel, Leen; Rose, Stephen; Boyd, Roslyn N; Feys, Hilde; Guzzetta, Andrea

2014-09-01

To describe the development of a novel rating scale for classification of brain structural magnetic resonance imaging (MRI) in children with cerebral palsy (CP) and to assess its interrater and intrarater reliability. The scale consists of three sections. Section 1 contains descriptive information about the patient and MRI. Section 2 contains the graphical template of brain hemispheres onto which the lesion is transposed. Section 3 contains the scoring system for the quantitative analysis of the lesion characteristics, grouped into different global scores and subscores that assess separately side, regions, and depth. A larger interrater and intrarater reliability study was performed in 34 children with CP (22 males, 12 females; mean age at scan of 9 y 5 mo [SD 3 y 3 mo], range 4 y-16 y 11 mo; Gross Motor Function Classification System level I, [n=22], II [n=10], and level III [n=2]). Very high interrater and intrarater reliability of the total score was found with indices above 0.87. Reliability coefficients of the lobar and hemispheric subscores ranged between 0.53 and 0.95. Global scores for hemispheres, basal ganglia, brain stem, and corpus callosum showed reliability coefficients above 0.65. This study presents the first visual, semi-quantitative scale for classification of brain structural MRI in children with CP. The high degree of reliability of the scale supports its potential application for investigating the relationship between brain structure and function and examining treatment response according to brain lesion severity in children with CP. © 2014 Mac Keith Press.

The epidemiology of neonatal tumours. Report of an international working group.

PubMed

Moore, S W; Satgé, D; Sasco, A J; Zimmermann, A; Plaschkes, J

2003-09-01

Neonatal tumours occur every 12,500-27,500 live births and comprise 2% of childhood malignancies, but there is little clarity as to their real prevalence, sites of origin and pathological nature as reported series vary. As an entity, neonatal tumours provide a unique window of opportunity to study tumours in which minimal environmental interference has occurred. The majority of tumours present with a mass at birth (e.g., teratomas, neuroblastomas, mesoblastic nephroma, fibromatosis), which are not infrequently identified on antenatal ultrasound. Histologically, teratoma and neuroblastoma remain the two main tumour types encountered with soft tissue sarcoma, renal tumours, CNS tumours and leukaemia being the next most common tumour types identified. Malignant tumours are uncommon in the neonatal period per se and benign tumours may have malignant potential. A particular problem exists in clinical classification, as histological features of malignancy do not always correlate with clinical behaviour. Benign tumours may also be life threatening because of their size and location. Other tumours may demonstrate local invasiveness, but no metastatic potential, and tumours that are clearly malignant may demonstrate unpredictable or uncertain behaviour. Screening programmes have brought more tumours to light, but do not appear to affect the overall prognosis. They may provide clues to the stage at which tumours develop in foetu. The aetiology of cancer in children is multifactorial and includes both genetic and environmental factors. The association between congenital abnormalities and tumours is well established (15% of neonatal tumours). Genetic defects are highly likely in neonatal tumours and include those with a high risk of malignancy (e.g., retinoblastoma), but also genetically determined syndromes with an increased risk of malignancy and complex genetic rearrangements. Tumours are mostly genetically related at a cellular level and factors influencing cellular

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

PubMed Central

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

2016-01-01

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

Mild traumatic brain injury literature review and proposed changes to classification.

PubMed

Krainin, Benjamin M; Forsten, Robert D; Kotwal, Russ S; Lutz, Robert H; Guskiewicz, Kevin M

2011-01-01

Mild traumatic brain injury (mTBI) reportedly occurs in 8-22% of U.S. servicemembers who conduct combat operations in Afghanistan and Iraq. The current definition for mTBI found in the medical literature, to include the Department of Defense (DoD) and Veterans Administration (VA) clinical practice guidelines is limited by the parameters of loss of consciousness, altered consciousness, or post-traumatic amnesia, and does not account for other constellations of potential symptoms. Although mTBI symptoms typically resolve within seven days, some servicemembers experience symptoms that continue for weeks, months, or years following an injury. Mild TBI is one of few disorders in medicine where a benign and misleading diagnostic classification is bestowed on patients at the time of injury, yet still can be associated with lifelong complications. This article comprehensively reviews the clinical literature over the past 20 years and proposes a new classification for TBI that addresses acute, sub-acute, and chronic phases, and includes neurocognitive, somatic, and psychological symptom presentation. 2011.

Automatic segmentation of multimodal brain tumor images based on classification of super-voxels.

PubMed

Kadkhodaei, M; Samavi, S; Karimi, N; Mohaghegh, H; Soroushmehr, S M R; Ward, K; All, A; Najarian, K

2016-08-01

Despite the rapid growth in brain tumor segmentation approaches, there are still many challenges in this field. Automatic segmentation of brain images has a critical role in decreasing the burden of manual labeling and increasing robustness of brain tumor diagnosis. We consider segmentation of glioma tumors, which have a wide variation in size, shape and appearance properties. In this paper images are enhanced and normalized to same scale in a preprocessing step. The enhanced images are then segmented based on their intensities using 3D super-voxels. Usually in images a tumor region can be regarded as a salient object. Inspired by this observation, we propose a new feature which uses a saliency detection algorithm. An edge-aware filtering technique is employed to align edges of the original image to the saliency map which enhances the boundaries of the tumor. Then, for classification of tumors in brain images, a set of robust texture features are extracted from super-voxels. Experimental results indicate that our proposed method outperforms a comparable state-of-the-art algorithm in term of dice score.

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

Classification of Parkinsonian syndromes from FDG-PET brain data using decision trees with SSM/PCA features.

PubMed

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

2015-01-01

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

Identification of brain metastasis genes and therapeutic evaluation of histone deacetylase inhibitors in a clinically relevant model of breast cancer brain metastasis.

PubMed

Kim, Soo-Hyun; Redvers, Richard P; Chi, Lap Hing; Ling, Xiawei; Lucke, Andrew J; Reid, Robert C; Fairlie, David P; Baptista Moreno Martin, Ana Carolina; Anderson, Robin L; Denoyer, Delphine; Pouliot, Normand

2018-05-21

Breast cancer brain metastasis remains largely incurable. While several mouse models have been developed to investigate the genes and mechanisms regulating breast cancer brain metastasis, these models often lack clinical relevance since they require the use of immune-compromised mice and/or are poorly metastatic to brain from the mammary gland. We describe the development and characterisation of an aggressive brain metastatic variant of the 4T1 syngeneic model (4T1Br4) that spontaneously metastasises to multiple organs, but is selectively more metastatic to the brain from the mammary gland than parental 4T1 tumours. By immunohistochemistry, 4T1Br4 tumours and brain metastases display a triple negative phenotype, consistent with the high propensity of this breast cancer subtype to spread to brain. In vitro assays indicate that 4T1Br4 cells have an enhanced ability to adhere to or migrate across a brain-derived endothelial monolayer and greater invasive response to brain-derived soluble factors compared to 4T1 cells. These properties are likely to contribute to the brain-selectivity of 4T1Br4 tumours. Expression profiling and gene set enrichment analyses demonstrate the clinical relevance of the 4T1Br4 model at the transcriptomic level. Pathway analyses implicate tumour-intrinsic immune regulation and vascular interactions in successful brain colonisation, revealing potential therapeutic targets. Evaluation of two histone deacetylase inhibitors, SB939 and 1179.4b, shows partial efficacy against 4T1Br4 metastasis to brain and other sites in vivo and potent radio-sensitising properties in vitro The 4T1Br4 model provides a clinically relevant tool for mechanistic studies and to evaluate novel therapies against brain metastasis. © 2018. Published by The Company of Biologists Ltd.

Tumour suppressor TRIM33 targets nuclear β-catenin degradation

PubMed Central

Xue, Jianfei; Chen, Yaohui; Wu, Yamei; Wang, Zhongyong; Zhou, Aidong; Zhang, Sicong; Lin, Kangyu; Aldape, Kenneth; Majumder, Sadhan; Lu, Zhimin; Huang, Suyun

2014-01-01

Aberrant activation of β-catenin in the nucleus has been implicated in a variety of human cancers but the fate of nuclear β-catenin is unknown. Here we demonstrate that tripartite motif-containing protein 33 (TRIM33), acting as an E3 ubiquitin ligase, reduces the abundance of nuclear β-catenin protein. TRIM33-mediated β-catenin is destabilized and is GSK-3β or β-TrCP independent. TRIM33 interacts with and ubiquitylates nuclear β-catenin. Moreover, protein kinase Cδ, which directly phosphorylates β-catenin at Ser715, is required for the TRIM33–β-catenin interaction. The function of TRIM33 in suppressing tumour cell proliferation and brain tumour development depends on TRIM33-promoted β-catenin degradation. In human glioblastoma specimens, endogenous TRIM33 levels are inversely correlated with β-catenin. In summary, our findings identify TRIM33 as a tumour suppressor that can abolish tumour cell proliferation and tumorigenesis by degrading nuclear β-catenin. This work suggests a new therapeutic strategy against human cancers caused by aberrant activation of β-catenin. PMID:25639486

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2010-01-01

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. PMID:21151847

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

PubMed

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

2010-04-14

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.

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

PubMed

Simões, Rita; Slump, Cornelis

2011-01-01

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.

Dynamics of fertility impairment in childhood brain tumour survivors.

PubMed

Pfitzer, C; Chen, C-M; Wessel, T; Keil, T; Sörgel, A; Langer, T; Steinmann, D; Borgmann-Staudt, A

2014-10-01

Fertility impairment and recovery after chemo- and radiotherapy have been reported in both male and female childhood cancer survivors, but little is known about the dynamics. Our aim, therefore, was to describe the development of fertility impairment and possible recovery in childhood brain tumour survivors. In this longitudinal study, we included 144 survivors, who were treated in two German paediatric oncology centres between 2000 and 2005. Fertility parameters were retrieved from medical records up to 12 years after diagnosis. Participants with age ≥13 years and formerly cranial irradiation ≥30 Gray (n = 23), including 83 % (n = 19) with craniospinal irradiation ≥30 Gray, had a higher median FSH concentration compared to 29 patients without chemoradiotherapy: 8.3 IU/l (IQR 6.5-11.2) versus 4.1 IU/l (IQR 3.2-5.1) 2 years after initial treatment; 8.9 IU/l (IQR 8.5-10.8) versus 4.2 IU/l (IQR 2.4-6.7) after 8 years; and 7.1 IU/l (IQR 6.7-7.7) versus 3.5 IU/l (IQR 2.8-4.2) after 10 years. Altogether, 11/65 women reported the occurrence of amenorrhoea 6.0 years (range 1-10) after diagnosis. Five of these women later developed a regular menstrual cycle without hormone replacement therapy. Patients' chance of recovery from fertility impairment was increased with time since diagnosis (p = 0.074). Signs of fertility impairment such as amenorrhoea and elevated FSH levels were observed at variable time points between 1 and 12 years after chemoradiotherapy. Decreasing FSH levels were observed 1-7 years after elevation and were interpreted either as an atrophy of the pituitary gland or as recovery from fertility impairment.

Coupled modelling of tumour angiogenesis, tumour growth and blood perfusion.

PubMed

Cai, Yan; Xu, Shixiong; Wu, Jie; Long, Quan

2011-06-21

We propose a mathematical modelling system to investigate the dynamic process of tumour cell proliferation, death and tumour angiogenesis by fully coupling the vessel growth, tumour growth and blood perfusion. Tumour growth and angiogenesis are coupled by the chemical microenvironment and the cell-matrix interaction. The haemodynamic calculation is carried out on the updated vasculature. The domains of intravascular, transcapillary and interstitial fluid flow were coupled in the model to provide a comprehensive solution of blood perfusion variables. An estimation of vessel collapse is made according to the wall shear stress criterion to provide feedback on vasculature remodelling. The simulation can show the process of tumour angiogenesis and the spatial distribution of tumour cells for periods of up to 24 days. It can show the major features of tumour and tumour microvasculature during the period such as the formation of a large necrotic core in the tumour centre with few functional vessels passing through, and a well circulated tumour periphery regions in which the microvascular density is high and associated with more aggressive proliferating cells of the growing tumour which are all consistent with physiological observations. The study also demonstrated that the simulation results are not dependent on the initial tumour and networks, which further confirms the application of the coupled model feedback mechanisms. The model enables us to examine the interactions between angiogenesis and tumour growth, and to study the dynamic response of a solid tumour to the changes in the microenvironment. This simulation framework can be a foundation for further applications such as drug delivery and anti-angiogenic therapies. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

PubMed Central

Lancaster, Jenessa; Lorenz, Romy; Leech, Rob; Cole, James H.

2018-01-01

Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years). Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm). For predicting chronological age, a mean absolute error (MAE) of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm). This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian

Tumour location within the breast: Does tumour site have prognostic ability?

PubMed

Rummel, Seth; Hueman, Matthew T; Costantino, Nick; Shriver, Craig D; Ellsworth, Rachel E

2015-01-01

Tumour location within the breast varies with the highest frequency in the upper outer quadrant (UOQ) and lowest frequency in the lower inner quadrant (LIQ). Whether tumour location is prognostic is unclear. To determine whether tumour location is prognostic, associations between tumour site and clinicopathological characteristics were evaluated. All patients enrolled in the Clinical Breast Care Project whose tumour site-UOQ, upper inner quadrant (UIQ), central, LIQ, lower outer quadrant (LOQ)-was determined by a single, dedicated breast pathologist were included in this study. Patients with multicentric disease (n = 122) or tumours spanning multiple quadrants (n = 381) were excluded from further analysis. Clinicopathological characteristics were analysed using chi-square tests for univariate analysis with multivariate analysis performed using principal components analysis (PCA) and multiple logistic regression. Significance was defined as P < 0.05. Of the 980 patients with defined tumour location, 30 had bilateral disease. Tumour location in the UOQ (51.5%) was significantly higher than in the UIQ (15.6%), LOQ (14.2%), central (10.6%), or LIQ (8.1%). Tumours in the central quadrant were significantly more likely to have higher tumour stage (P = 0.003) and size (P < 0.001), metastatic lymph nodes (P < 0.001), and mortality (P = 0.011). After multivariate analysis, only tumour size and lymph node status remained significantly associated with survival. Evaluation of tumour location as a prognostic factor revealed that although tumours in the central region are associated with less favourable outcome, these associations are not independent of location but rather driven by larger tumour size. Tumours in the central region are more difficult to detect mammographically, resulting in larger tumour size at diagnosis and thus less favourable prognosis. Together, these data demonstrate that tumour location is not an independent prognostic factor.

Classification of brain MRI with big data and deep 3D convolutional neural networks

NASA Astrophysics Data System (ADS)

Wegmayr, Viktor; Aitharaju, Sai; Buhmann, Joachim

2018-02-01

Our ever-aging society faces the growing problem of neurodegenerative diseases, in particular dementia. Magnetic Resonance Imaging provides a unique tool for non-invasive investigation of these brain diseases. However, it is extremely difficult for neurologists to identify complex disease patterns from large amounts of three-dimensional images. In contrast, machine learning excels at automatic pattern recognition from large amounts of data. In particular, deep learning has achieved impressive results in image classification. Unfortunately, its application to medical image classification remains difficult. We consider two reasons for this difficulty: First, volumetric medical image data is considerably scarcer than natural images. Second, the complexity of 3D medical images is much higher compared to common 2D images. To address the problem of small data set size, we assemble the largest dataset ever used for training a deep 3D convolutional neural network to classify brain images as healthy (HC), mild cognitive impairment (MCI) or Alzheimers disease (AD). We use more than 20.000 images from subjects of these three classes, which is almost 9x the size of the previously largest data set. The problem of high dimensionality is addressed by using a deep 3D convolutional neural network, which is state-of-the-art in large-scale image classification. We exploit its ability to process the images directly, only with standard preprocessing, but without the need for elaborate feature engineering. Compared to other work, our workflow is considerably simpler, which increases clinical applicability. Accuracy is measured on the ADNI+AIBL data sets, and the independent CADDementia benchmark.

Sinonasal haemangiopericytoma-like tumour: a sinonasal glomus tumour or a haemangiopericytoma?

PubMed

Tse, L L Y; Chan, J K C

2002-06-01

Sinonasal haemangiopericytoma-like tumour is controversial with regard to its nosologic nature. This study aims to investigate its relationship with glomus tumour and haemangiopericytoma. Six cases of sinonasal haemangiopericytoma-like tumours identified in our files were reviewed for clinicopathological features, and compared with five cases each of soft tissue glomus tumour and meningeal haemangiopericytoma. Immunohistochemical studies for muscle-specific actin, smooth muscle actin, desmin and CD34 were performed. Sinonasal haemangiopericytoma-like tumour demonstrated a uniform histological appearance with bland-looking short, spindly cells forming sheets and short fascicles. The tumour cells were interspersed with slit-like, round and ectatic blood vessels. Actin immunoreactivity was demonstrated in all six cases, although occasionally patchy. The histological appearance and immunohistochemical phenotype of sinonasal haemangiopericytoma-like tumour were very similar to and focally indistinguishable from glomus tumour. Meningeal haemangiopericytoma, in contrast, was characterized by high tumour cellularity, random nuclear orientation, presence of staghorn vasculature and lack of immunohistochemical evidence of myogenic differentiation. We conclude that sinonasal haemangiopericytoma-like tumour is biologically close to or identical to glomus tumour, but is not related to haemangiopericytoma.

Continuous measurement of breast tumour hormone receptor expression: a comparison of two computational pathology platforms.

PubMed

Ahern, Thomas P; Beck, Andrew H; Rosner, Bernard A; Glass, Ben; Frieling, Gretchen; Collins, Laura C; Tamimi, Rulla M

2017-05-01

Computational pathology platforms incorporate digital microscopy with sophisticated image analysis to permit rapid, continuous measurement of protein expression. We compared two computational pathology platforms on their measurement of breast tumour oestrogen receptor (ER) and progesterone receptor (PR) expression. Breast tumour microarrays from the Nurses' Health Study were stained for ER (n=592) and PR (n=187). One expert pathologist scored cases as positive if ≥1% of tumour nuclei exhibited stain. ER and PR were then measured with the Definiens Tissue Studio (automated) and Aperio Digital Pathology (user-supervised) platforms. Platform-specific measurements were compared using boxplots, scatter plots and correlation statistics. Classification of ER and PR positivity by platform-specific measurements was evaluated with areas under receiver operating characteristic curves (AUC) from univariable logistic regression models, using expert pathologist classification as the standard. Both platforms showed considerable overlap in continuous measurements of ER and PR between positive and negative groups classified by expert pathologist. Platform-specific measurements were strongly and positively correlated with one another (r≥0.77). The user-supervised Aperio workflow performed slightly better than the automated Definiens workflow at classifying ER positivity (AUC Aperio =0.97; AUC Definiens =0.90; difference=0.07, 95% CI 0.05 to 0.09) and PR positivity (AUC Aperio =0.94; AUC Definiens =0.87; difference=0.07, 95% CI 0.03 to 0.12). Paired hormone receptor expression measurements from two different computational pathology platforms agreed well with one another. The user-supervised workflow yielded better classification accuracy than the automated workflow. Appropriately validated computational pathology algorithms enrich molecular epidemiology studies with continuous protein expression data and may accelerate tumour biomarker discovery. Published by the BMJ Publishing

The role of amino acid PET in the light of the new WHO classification 2016 for brain tumors.

PubMed

Suchorska, Bogdana; Albert, Nathalie L; Bauer, Elena K; Tonn, Jörg-Christian; Galldiks, Norbert

2018-04-26

Since its introduction in 2016, the revision of the World Health Organization (WHO) classification of central nervous system tumours has already changed the diagnostic and therapeutic approach in glial tumors. Blurring the lines between entities formerly labelled as "high-grade" or "low-grade", molecular markers define distinct biological subtypes with different clinical course. This new classification raises the demand for non-invasive imaging methods focussing on depicting metabolic processes. We performed a review of current literature on the use of amino acid PET (AA-PET) for obtaining diagnostic or prognostic information on glioma in the setting of the current WHO 2016 classification. So far, only a few studies have focussed on combining molecular genetic information and metabolic imaging using AA-PET. The current review summarizes the information available on "molecular grading" as well as prognostic information obtained from AA-PET and delivers an insight into a possible interrelation between metabolic imaging and glioma genetics. Within the framework of molecular characterization of gliomas, metabolic imaging using AA-PET is a promising tool for non-invasive characterisation of molecular features and to provide additional prognostic information. Further studies incorporating molecular and metabolic features are necessary to improve the explanatory power of AA-PET in glial tumors.

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method

PubMed Central

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions. PMID:28588470

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method.

PubMed

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.

Challenges in providing culturally-competent care to patients with metastatic brain tumours and their families.

PubMed

Longo, Lianne; Slater, Serena

2014-01-01

Being diagnosed with a metastatic brain tumour can be devastating as it is characterized by very low cure rates, as well as significant morbidity and mortality. Given the poor life expectancy and progressive disability that ensues, patients and family members experience much turmoil, which includes losses that bring about changes to family roles, routines and relationships. Crisis and conflict are common during such major disruptions to a family system, as individual members attempt to make sense of the illness experience based on cultural and spiritual beliefs, past experiences and personal philosophies. It is imperative health care providers strive towards increased awareness and knowledge of how culture affects the overall experience of illness and death in order to help create a mutually satisfactory care plan. Providing culturally-competent care entails the use of proper communication skills to facilitate the exploration of patient and family perspectives and allows for mutual decision making. A case study will illustrate the challenges encountered in providing culturally-competent care to a woman with brain cancer and her family. As the patient's health declined, the family entered into a state of crisis where communication between family members and health care professionals was strained; leading to conflict and sub-optimal outcomes. This paper will address the ethical dilemma of providing culturally-competent care when a patient's safety is at risk, and the nursing implications of upholding best practices in the context of differing beliefs and priorities.

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Ceballos, G. A.; Hernández, L. F.

2015-04-01

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

Audit of tumour histopathology reviewed by a regional oncology centre.

PubMed Central

Prescott, R J; Wells, S; Bisset, D L; Banerjee, S S; Harris, M

1995-01-01

AIMS--To analyse the diagnostic differences in reporting tumour histopathology between a district general hospital and a regional oncology centre. METHODS--Tumour histopathology reports (n = 227) extracted from Bolton General Hospital files between 1988 and 1992 were compared with the corresponding Christie Hospital (oncology centre) reports, the same material having been seen at both hospitals. RESULTS--Diagnostic agreement existed in 77% of all cases. The incidence of major discrepancies was 8.37%. Of the diagnoses, 19 (36%) cases involved major discrepancies and 34 (64%) cases minor discrepancies. Most discrepancies occurred in the lymphoma group and involved subclassification of Hodgkin's and non-Hodgkin's lymphoma. Ki1 anaplastic large cell lymphoma and T cell rich B cell lymphoma were problematic diagnoses. The correct grading of follicle centre cell lymphomas using the Kiel classification was another problem area. In 19 cases certain aspects of immunohistochemistry produced discrepancies. In one case an incorrect diagnosis was made at the oncology centre and in another both centres gave an incorrect diagnosis. CONCLUSIONS--Areas of diagnostic difficulty mainly involve the subclassification of lymphomas. Review of tumour pathology by experts is recommended, at least in certain categories, to ensure correct diagnosis and uniformity in subclassification of tumours. PMID:7730487

Concussion classification via deep learning using whole-brain white matter fiber strains

PubMed Central

Cai, Yunliang; Wu, Shaoju; Zhao, Wei; Li, Zhigang; Wu, Zheyang

2018-01-01

Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses explicitly pre-defined in a specific brain region of interest. They could suffer from loss of information. A single training dataset has also been used to evaluate performance but without cross-validation. In this study, we developed a deep learning approach for concussion classification using implicit features of the entire voxel-wise white matter fiber strains. Using reconstructed American National Football League (NFL) injury cases, leave-one-out cross-validation was employed to objectively compare injury prediction performances against two baseline machine learning classifiers (support vector machine (SVM) and random forest (RF)) and four scalar metrics via univariate logistic regression (Brain Injury Criterion (BrIC), cumulative strain damage measure of the whole brain (CSDM-WB) and the corpus callosum (CSDM-CC), and peak fiber strain in the CC). Feature-based machine learning classifiers including deep learning, SVM, and RF consistently outperformed all scalar injury metrics across all performance categories (e.g., leave-one-out accuracy of 0.828–0.862 vs. 0.690–0.776, and .632+ error of 0.148–0.176 vs. 0.207–0.292). Further, deep learning achieved the best cross-validation accuracy, sensitivity, AUC, and .632+ error. These findings demonstrate the superior performances of deep learning in concussion prediction and suggest its promise for future applications in biomechanical investigations of traumatic brain injury. PMID:29795640

Concussion classification via deep learning using whole-brain white matter fiber strains.

PubMed

Cai, Yunliang; Wu, Shaoju; Zhao, Wei; Li, Zhigang; Wu, Zheyang; Ji, Songbai

2018-01-01

Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses explicitly pre-defined in a specific brain region of interest. They could suffer from loss of information. A single training dataset has also been used to evaluate performance but without cross-validation. In this study, we developed a deep learning approach for concussion classification using implicit features of the entire voxel-wise white matter fiber strains. Using reconstructed American National Football League (NFL) injury cases, leave-one-out cross-validation was employed to objectively compare injury prediction performances against two baseline machine learning classifiers (support vector machine (SVM) and random forest (RF)) and four scalar metrics via univariate logistic regression (Brain Injury Criterion (BrIC), cumulative strain damage measure of the whole brain (CSDM-WB) and the corpus callosum (CSDM-CC), and peak fiber strain in the CC). Feature-based machine learning classifiers including deep learning, SVM, and RF consistently outperformed all scalar injury metrics across all performance categories (e.g., leave-one-out accuracy of 0.828-0.862 vs. 0.690-0.776, and .632+ error of 0.148-0.176 vs. 0.207-0.292). Further, deep learning achieved the best cross-validation accuracy, sensitivity, AUC, and .632+ error. These findings demonstrate the superior performances of deep learning in concussion prediction and suggest its promise for future applications in biomechanical investigations of traumatic brain injury.

Glioblastoma and ABO blood groups: further evidence of an association between the distribution of blood group antigens and brain tumours.

PubMed

Allouh, Mohammed Z; Al Barbarawi, Mohammed M; Hiasat, Mohammad Y; Al-Qaralleh, Mohammed A; Ababneh, Emad I

2017-10-01

Glioblastoma is a highly malignant brain tumour that usually leads to death. Several studies have reported a link between the distribution of ABO blood group antigens and a risk of developing specific types of cancer, although no consensus has been reached. This study aims to investigate the relationship between the distribution of ABO blood group antigens and the incidence of glioblastoma. The study cohort consisted of 115 glioblastoma patients who were diagnosed at King Abdullah University Hospital, Jordan, between 2004 and 2015. Three different patient populations made up three control groups and these were selected from among patients at the same institution between 2014 and 2015 as follows: 3,847 healthy blood donors, 654 accidental trauma patients admitted to the Departments of Neurosurgery and Orthopaedics, and 230 age- and sex-matched control subjects recruited blindly from the Departments of Paediatrics and Internal Medicine. There was a significant association between the distribution of ABO blood group antigens and the incidence of glioblastoma. Post hoc residual analysis revealed that individuals with group A had a higher than expected chance of developing glioblastoma, while individuals with group O had a lower than expected chance. Furthermore, individuals with group A were found to be at a 1.62- to 2.28-fold increased risk of developing glioblastoma compared to individuals with group O. In the present study, we demonstrate that, in Jordan, individuals with group A have an increased risk of developing glioblastoma, while individuals with group O have a reduced risk. These findings suggest that the distribution of ABO blood group antigens is associated with a risk of brain tumours and may play an important role in their development. However, further clinical and experimental investigations are required to confirm this association.

Using Fractal and Local Binary Pattern Features for Classification of ECOG Motor Imagery Tasks Obtained from the Right Brain Hemisphere.

PubMed

Xu, Fangzhou; Zhou, Weidong; Zhen, Yilin; Yuan, Qi; Wu, Qi

2016-09-01

The feature extraction and classification of brain signal is very significant in brain-computer interface (BCI). In this study, we describe an algorithm for motor imagery (MI) classification of electrocorticogram (ECoG)-based BCI. The proposed approach employs multi-resolution fractal measures and local binary pattern (LBP) operators to form a combined feature for characterizing an ECoG epoch recording from the right hemisphere of the brain. A classifier is trained by using the gradient boosting in conjunction with ordinary least squares (OLS) method. The fractal intercept, lacunarity and LBP features are extracted to classify imagined movements of either the left small finger or the tongue. Experimental results on dataset I of BCI competition III demonstrate the superior performance of our method. The cross-validation accuracy and accuracy is 90.6% and 95%, respectively. Furthermore, the low computational burden of this method makes it a promising candidate for real-time BCI systems.

Regularised extreme learning machine with misclassification cost and rejection cost for gene expression data classification.

PubMed

Lu, Huijuan; Wei, Shasha; Zhou, Zili; Miao, Yanzi; Lu, Yi

2015-01-01

The main purpose of traditional classification algorithms on bioinformatics application is to acquire better classification accuracy. However, these algorithms cannot meet the requirement that minimises the average misclassification cost. In this paper, a new algorithm of cost-sensitive regularised extreme learning machine (CS-RELM) was proposed by using probability estimation and misclassification cost to reconstruct the classification results. By improving the classification accuracy of a group of small sample which higher misclassification cost, the new CS-RELM can minimise the classification cost. The 'rejection cost' was integrated into CS-RELM algorithm to further reduce the average misclassification cost. By using Colon Tumour dataset and SRBCT (Small Round Blue Cells Tumour) dataset, CS-RELM was compared with other cost-sensitive algorithms such as extreme learning machine (ELM), cost-sensitive extreme learning machine, regularised extreme learning machine, cost-sensitive support vector machine (SVM). The results of experiments show that CS-RELM with embedded rejection cost could reduce the average cost of misclassification and made more credible classification decision than others.

Anti-tumour strategies aiming to target tumour-associated macrophages

PubMed Central

Tang, Xiaoqiang; Mo, Chunfen; Wang, Yongsheng; Wei, Dandan; Xiao, Hengyi

2013-01-01

Tumour-associated macrophages (TAMs) represent a predominant population of inflammatory cells that present in solid tumours. TAMs are mostly characterized as alternatively activated M2-like macrophages and are known to orchestrate nearly all stages of tumour progression. Experimental investigations indicate that TAMs contribute to drug-resistance and radio-protective effects, and clinical evidence shows that an elevated number of TAMs and their M2 profile are correlated with therapy failure and poor prognosis in cancer patients. Recently, many studies on TAM-targeted strategies have made significant progress and some pilot works have achieved encouraging results. Among these, connections between some anti-tumour drugs and their influence on TAMs have been suggested. In this review, we will summarize recent advances in TAM-targeted strategies for tumour therapy. Based on the proposed mechanisms, those strategies are grouped into four categories: (i) inhibiting macrophage recruitment; (ii) suppressing TAM survival; (iii) enhancing M1-like tumoricidal activity of TAMs; (iv) blocking M2-like tumour-promoting activity of TAMs. It is desired that further attention be drawn to this research field and more effort be made to promote TAM-targeted tumour therapy. PMID:23113570

ELUCIDATING BRAIN CONNECTIVITY NETWORKS IN MAJOR DEPRESSIVE DISORDER USING CLASSIFICATION-BASED SCORING.

PubMed

Sacchet, Matthew D; Prasad, Gautam; Foland-Ross, Lara C; Thompson, Paul M; Gotlib, Ian H

2014-04-01

Graph theory is increasingly used in the field of neuroscience to understand the large-scale network structure of the human brain. There is also considerable interest in applying machine learning techniques in clinical settings, for example, to make diagnoses or predict treatment outcomes. Here we used support-vector machines (SVMs), in conjunction with whole-brain tractography, to identify graph metrics that best differentiate individuals with Major Depressive Disorder (MDD) from nondepressed controls. To do this, we applied a novel feature-scoring procedure that incorporates iterative classifier performance to assess feature robustness. We found that small-worldness , a measure of the balance between global integration and local specialization, most reliably differentiated MDD from nondepressed individuals. Post-hoc regional analyses suggested that heightened connectivity of the subcallosal cingulate gyrus (SCG) in MDDs contributes to these differences. The current study provides a novel way to assess the robustness of classification features and reveals anomalies in large-scale neural networks in MDD.

[Liposomal cytarabine for the treatment of leptomeningeal dissemination of central nervous system tumours in children and adolescents].

PubMed

Moreno, Lucas; García Ariza, Miguel Angel; Cruz, Ofelia; Calvo, Carlota; Fuster, Jose Luis; Salinas, Jose Antonio; Moscardo, Cristina; Portugal, Raquel; Merino, Jose Manuel; Madero, Luis

2016-11-01

Leptomeningeal dissemination in paediatric central nervous system (CNS) tumours is associated with a poor outcome, and new therapeutic strategies are desperately needed. One of the main difficulties in the treatment of CNS tumours is blood brain barrier penetration. Intrathecal therapy has shown to be effective in several paediatric tumours. The aim of this article is to review the data available on the use of liposomal cytarabine for paediatric patients with leptomeningeal dissemination of CNS tumours, including the pharmacology, administration route, safety and efficacy data. Copyright © 2016 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

Mediastinal germ cell tumour causing superior vena cava tumour thrombosis.

PubMed

Karanth, Suman S; Vaid, Ashok K; Batra, Sandeep; Sharma, Devender

2015-03-25

We report a rare case of a 35-year-old man who presented with a 1-week history of retrosternal chest pain of moderate intensity. A positron emission tomography CT (PET-CT) showed a large fluorodeoxy-glucose (FDG)-avid heterogeneously enhancing necrotic mass in the anterosuperior mediastinum with a focal FDG-avid thrombosis of the superior vena cava (SVC) suggestive of tumour thrombus and vascular invasion. α-Fetoprotein levels were raised (5690 IU/L). Image guided biopsy of the mediastinal mass was suggestive of non-seminomatous germ cell tumour (NSGCT). The patient received four cycles of BEP (bleomycin, etoposide and cisplatin) along with therapeutic anticoagulation with low-molecular-weight heparin. Follow-up whole body PET-CT revealed complete resolution of mediastinal mass and SVC tumour thrombosis. The documentation of FDG-PET-avid tumour thrombus resolving with chemotherapy supports the concept of circulating tumour cells being important not only in common solid tumours such as breast and colon cancer but also in relatively less common tumours such as NSGCT. The detection of circulating tumour cells could help deploy aggressive regimens upfront. 2015 BMJ Publishing Group Ltd.

Evaluation of dissemination studies with FDG whole-body positron emission tomography in patients with suspected metastatic tumours of brain and spine.

PubMed

Go, K G; Pruim, J; Que, T H; Vaalburg, W; Haaxma-Reiche, H

2000-01-01

In the preoperative diagnosis of malignant brain tumours there is often uncertainty regarding their metastatic or primary nature, requiring dissemination studies. Currently FDG-wbPET is being used for the efficient detection of systemic tumours. It therefore may become a substitute for the conventional dissemination studies if it allows an earlier diagnosis. In this descriptive and preliminary study a population of 14 patients with suspected or proven metastatic lesions, [18F]-fluoro-2-deoxy-D-glucose whole body positron emission tomography (FDG-wbPET) was conducted and verified by additional conventional dissemination studies. FINDINGS AND THEIR INTERPRETATION: The entire series of dissemination studies required an average of 30 days with a range of 4-73 days. The FDG-wbPET was corroborated by the other dissemination studies in 10 of the 14 patients. In 7 of these 10 patients both PET and dissemination studies showed systemic abnormal findings, but in one case the presence of high pulmonary activity on the FDG-wbPET and the abnormal findings on the chest X-rays proved to be Aspergillus infection at autopsy. In the other 2 cases the negative PET findings corresponded to the absence of systemic dissemination. In 5 cases there was disagreement of the results of the FDG-wbPET with other evidence, among which there were 2 cases of glioblastoma in which systemic metastases were most unlikely, and the foci of activity on the FDG-wbPET had to be considered as false positives. In the remaining 3 cases the systemic presence of high activity on the FDG-wbPET indicated the systemic presence of tumour, whereas the other dissemination studies disclosed no tumour. The results warrant the use of FDG-wbPET as a screening method for the search of metastases, allowing other studies to be focussed on the lesion. But from the cost/benefit point of view this would make the method less suitable as a substitute for dissemination studies in general, although it may speed up the diagnostic

Breast Cancer Brain Metastases: Clonal Evolution in Clinical Context.

PubMed

Saunus, Jodi M; McCart Reed, Amy E; Lim, Zhun Leong; Lakhani, Sunil R

2017-01-13

Brain metastases are highly-evolved manifestations of breast cancer arising in a unique microenvironment, giving them exceptional adaptability in the face of new extrinsic pressures. The incidence is rising in line with population ageing, and use of newer therapies that stabilise metastatic disease burden with variable efficacy throughout the body. Historically, there has been a widely-held view that brain metastases do not respond to circulating therapeutics because the blood-brain-barrier (BBB) restricts their uptake. However, emerging data are beginning to paint a more complex picture where the brain acts as a sanctuary for dormant, subclinical proliferations that are initially protected by the BBB, but then exposed to dynamic selection pressures as tumours mature and vascular permeability increases. Here, we review key experimental approaches and landmark studies that have charted the genomic landscape of breast cancer brain metastases. These findings are contextualised with the factors impacting on clonal outgrowth in the brain: intrinsic breast tumour cell capabilities required for brain metastatic fitness, and the neural niche, which is initially hostile to invading cells but then engineered into a tumour-support vehicle by the successful minority. We also discuss how late detection, abnormal vascular perfusion and interstitial fluid dynamics underpin the recalcitrant clinical behaviour of brain metastases, and outline active clinical trials in the context of precision management.

The 2015 WHO Classification of Tumors of the Thymus: Continuity and Changes

PubMed Central

Marx, Alexander; Chan, John K.C.; Coindre, Jean-Michel; Detterbeck, Frank; Girard, Nicolas; Harris, Nancy L.; Jaffe, Elaine S.; Kurrer, Michael O.; Marom, Edith M.; Moreira, Andre L.; Mukai, Kiyoshi; Orazi, Attilio; Ströbel, Philipp

2015-01-01

This overview of the 4th edition of the WHO Classification of thymic tumors has two aims. First, to comprehensively list the established and new tumour entities and variants that are described in the new WHO Classification of thymic epithelial tumors, germ cell tumors, lymphomas, dendritic cell and myeloid neoplasms, and soft tissue tumors of the thymus and mediastinum; second, to highlight major differences in the new WHO Classification that result from the progress that has been made since the 3rd edition in 2004 at immunohistochemical, genetic and conceptual levels. Refined diagnostic criteria for type A, AB, B1–B3 thymomas and thymic squamous cell carcinoma are given and will hopefully improve the reproducibility of the classification and its clinical relevance. The clinical perspective of the classification has been strengthened by involving experts from radiology, thoracic surgery and oncology; by incorporating state-of-the-art PET/CT images; and by depicting prototypic cytological specimens. This makes the thymus section of the new WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart a valuable tool for pathologists, cytologists and clinicians alike. The impact of the new WHO Classification on therapeutic decisions is exemplified in this overview for thymic epithelial tumors and mediastinal lymphomas, and future perspectives and challenges are discussed. PMID:26295375

Connectome analysis for pre-operative brain mapping in neurosurgery

PubMed Central

Hart, Michael G.; Price, Stephen J.; Suckling, John

2016-01-01

Abstract Object: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains ‘wiring diagram’. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Methods: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal–parietal–occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Results: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Conclusions: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits. PMID:27447756

[Guideline on brain metastases: not a cookbook].

PubMed

Reijneveld, Jaap C

2011-01-01

The guideline 'Brain Metastases', which was revised on behalf of the Dutch Society for Neuro-Oncology (LWNO), provides an excellent overview of levels of scientific evidence on diagnosis and treatment of patients with parenchymal brain metastases of solid tumours. I would like to emphasize, however, that this guideline is not a cookbook for facilitating individual physicians to treat patients on their own. It is important that every patient suffering from brain metastases is discussed by a multidisciplinary tumour board consisting of at least a neurologist, a neurosurgeon, a medical oncologist, a radiation oncologist, a pathologist and a radiologist, and that several crucial questions need to be explicitly asked and answered about every single patient.

Single-Trial Classification of Multi-User P300-Based Brain-Computer Interface Using Riemannian Geometry.

PubMed

Korczowski, L; Congedo, M; Jutten, C

2015-08-01

The classification of electroencephalographic (EEG) data recorded from multiple users simultaneously is an important challenge in the field of Brain-Computer Interface (BCI). In this paper we compare different approaches for classification of single-trials Event-Related Potential (ERP) on two subjects playing a collaborative BCI game. The minimum distance to mean (MDM) classifier in a Riemannian framework is extended to use the diversity of the inter-subjects spatio-temporal statistics (MDM-hyper) or to merge multiple classifiers (MDM-multi). We show that both these classifiers outperform significantly the mean performance of the two users and analogous classifiers based on the step-wise linear discriminant analysis. More importantly, the MDM-multi outperforms the performance of the best player within the pair.

Mobile phones and head tumours. The discrepancies in cause-effect relationships in the epidemiological studies - how do they arise?

PubMed

Levis, Angelo G; Minicuci, Nadia; Ricci, Paolo; Gennaro, Valerio; Garbisa, Spiridione

2011-06-17

Whether or not there is a relationship between use of mobile phones (analogue and digital cellulars, and cordless) and head tumour risk (brain tumours, acoustic neuromas, and salivary gland tumours) is still a matter of debate; progress requires a critical analysis of the methodological elements necessary for an impartial evaluation of contradictory studies. A close examination of the protocols and results from all case-control and cohort studies, pooled- and meta-analyses on head tumour risk for mobile phone users was carried out, and for each study the elements necessary for evaluating its reliability were identified. In addition, new meta-analyses of the literature data were undertaken. These were limited to subjects with mobile phone latency time compatible with the progression of the examined tumours, and with analysis of the laterality of head tumour localisation corresponding to the habitual laterality of mobile phone use. Blind protocols, free from errors, bias, and financial conditioning factors, give positive results that reveal a cause-effect relationship between long-term mobile phone use or latency and statistically significant increase of ipsilateral head tumour risk, with biological plausibility. Non-blind protocols, which instead are affected by errors, bias, and financial conditioning factors, give negative results with systematic underestimate of such risk. However, also in these studies a statistically significant increase in risk of ipsilateral head tumours is quite common after more than 10 years of mobile phone use or latency. The meta-analyses, our included, examining only data on ipsilateral tumours in subjects using mobile phones since or for at least 10 years, show large and statistically significant increases in risk of ipsilateral brain gliomas and acoustic neuromas. Our analysis of the literature studies and of the results from meta-analyses of the significant data alone shows an almost doubling of the risk of head tumours induced by

Canine perineal tumours.

PubMed

Berrocal, A; Vos, J H; van den Ingh, T S; Molenbeek, R F; van Sluijs, F J

1989-12-01

One hundred and thirty nine canine perineal tumours were histologically evaluated. The vast majority (134 tumours = 96.4%) appeared to originate from the characteristic glandular structures of this region. They were classified as well differentiated perianal gland tumours (58.3%), as moderately or poorly differentiated perianal gland tumours (21.6%) and as carcinomas without perianal gland differentiation (16.5%). Only 5 tumours (3.6%) appeared to originate from non-characteristic perineal structures. A prominent male predominance was found with respect to the perianal gland tumours, whereas the carcinomas showed a distinct female predisposition. Tumours showing perianal gland differentiation almost invariably will have a benign behaviour. The carcinomas lacking any perianal gland differentiation often show a distinct malignant behaviour with metastases to regional lymph nodes and internal organs. These malignant neoplasms showed morphological and clinical features comparable to canine anal sac gland adenocarcinomas and carcinoids in man and animals.

Brain tissue segmentation in 4D CT using voxel classification

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

Low tumour cell content in a lung tumour bank: implications for molecular characterisation.

PubMed

Goh, Felicia; Duhig, Edwina E; Clarke, Belinda E; McCaul, Elizabeth; Passmore, Linda; Courtney, Deborah; Windsor, Morgan; Naidoo, Rishendren; Franz, Louise; Parsonson, Kylie; Yang, Ian A; Bowman, Rayleen V; Fong, Kwun M

2017-10-01

Lung cancer encompasses multiple malignant epithelial tumour types, each with specific targetable, potentially actionable mutations, such that precision management mandates accurate tumour typing. Molecular characterisation studies require high tumour cell content and low necrosis content, yet lung cancers are frequently a heterogeneous mixture of tumour and stromal cells. We hypothesised that there may be systematic differences in tumour cell content according to histological subtype, and that this may have implications for tumour banks as a resource for comprehensive molecular characterisation studies in lung cancer. To investigate this, we estimated tumour cell and necrosis content of 4267 samples resected from 752 primary lung tumour specimens contributed to a lung tissue bank. We found that banked lung cancer samples had low tumour cell content (33%) generally, although it was higher in carcinoids (77.5%) than other lung cancer subtypes. Tumour cells comprise a variable and often small component of banked resected tumour samples, and are accompanied by stromal reaction, inflammation, fibrosis, and normal structures. This has implications for the adequacy of unselected tumour bank samples for diagnostic and molecular investigations, and further research is needed to determine whether tumour cell content has a significant impact on analytical results in studies using tissue from tumour bank resources. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Intraoperative β{sup -} detecting probe for radio-guided surgery in tumour resection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solfaroli Camillocci, Elena; Bellini, Fabio; Bocciy, Valerio

The development of the β{sup -} based radio-guided surgery aims to extend the technique to those tumours where surgery is the only possible treatment and the assessment of the resection would most profit from the low background around the lesion, as for brain tumours. Feasibility studies on meningioma and gliomas already estimated the potentiality of this new treatment. To validate the technique, a prototype of the intraoperative probe detecting β{sup -} decays and specific phantoms simulating tumour remnant patterns embedded in healthy tissue have been realized. The response of the probe in this simulated environment is tested with dedicated procedures.more » This document discusses the innovative aspects of the method, the status of the developed intraoperative β{sup -} detecting probe and the results of the preclinical tests. (authors)« less

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

PubMed

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

2011-05-01

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

Immunity to tumour antigens.

PubMed

Li, Geng; Ali, Selman A; McArdle, Stephanie E B; Mian, Shahid; Ahmad, Murrium; Miles, Amanda; Rees, Robert C

2005-01-01

During the last decade, a large number of human tumour antigens have been identified. These antigens are classified as tumour-specific shared antigens, tissue-specific differentiation antigens, overexpressed antigens, tumour antigens resulting from mutations, viral antigens and fusion proteins. Antigens recognised by effectors of immune system are potential targets for antigen-specific cancer immunotherapy. However, most tumour antigens are self-proteins and are generally of low immunogenicity and the immune response elicited towards these tumour antigens is not always effective. Strategies to induce and enhance the tumour antigen-specific response are needed. This review will summarise the approaches to discovery of tumour antigens, the current status of tumour antigens, and their potential application to cancer treatment.

Prognostic value of two tumour staging classifications in patients with sinonasal mucosal melanoma.

PubMed

Houette, A; Gilain, L; Mulliez, A; Mom, T; Saroul, N

2016-11-01

Sinonasal mucosal melanoma is a rare disease associated with a very poor prognosis. The purpose of this study was to assess the prognostic value of the 2 staging systems published in the literature for these tumours: the American Joint Committee on Cancer (AJCC) Cancer Staging Manual for mucosal melanoma of the head and neck published in 2009 (7th edition) and the AJCC Cancer Staging Manual for cancers of the nasal cavity and paranasal sinuses published in 2002 (6th edition) and the prognostic value of tumour site, either limited to the nasal cavities or with paranasal sinus invasion. A retrospective study was conducted on 18 patients treated between August 1998 and June 2014. Each lesion was staged according to the AJCC Cancer Staging Manual 2002 and 2009 and the following data were collected: age, sex, tumour site, initial symptoms, treatment modalities, follow-up, recurrences and overall survival. Patient survival, from the date of discovery of the melanoma until death, was analysed by Kaplan-Meier survival curves and between-group comparison of survival was performed with a log rank test. The mean age at diagnosis was 72 years (range: 54-94) and the cohort comprised 11 women and 7 men. The median overall survival was 80 months, the 1-year overall survival was 82.6% and the 5-year overall survival was 54.5%. The AJCC 2002 staging system presented a statistically significant prognostic value (P=0.0476), while no statistically significant prognostic value was observed for the AJCC 2009 staging system (P=0.108). Paranasal sinus invasion was significantly associated with a poor prognosis (P=0.0039). This study demonstrates the superiority of the non-specific AJCC 2002 Cancer Staging Manual. Medical and surgical management must take paranasal sinus invasion into account, as it constitutes a major prognostic factor. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Automating Cell Detection and Classification in Human Brain Fluorescent Microscopy Images Using Dictionary Learning and Sparse Coding

PubMed Central

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A.; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M.

2017-01-01

Background Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. New method Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Results Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. Comparison with existing methods We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. Conclusion The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. PMID:28267565

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.

PubMed

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M; Grinberg, Lea T

2017-04-15

Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. Copyright © 2017 Elsevier B.V. All rights reserved.

Lesser-known myelin-related disorders: focal tumour-like demyelinating lesions.

PubMed

Jiménez Arango, J A; Uribe Uribe, C S; Toro González, G

2015-03-01

Focal tumour-like demyelinating lesions are defined as solitary demyelinating lesions with a diameter greater than 2 cm. In imaging studies, these lesions may mimic a neoplasm or brain abscess; as a result, invasive diagnostic and therapeutic measures may be performed that will in some cases increase morbidity. Our aim was to analyse and characterise these lesions according to their clinical, radiological, and pathological characteristics, and this data in addition to our literature review will contribute to a better understanding of these lesions. This descriptive study includes 5 cases with pathological diagnoses. We provide subject characteristics gathered through reviewing their clinical, radiology, and pathology reports. Patients' ages ranged from 12 to 60 years; 3 patients were female. The time delay between symptom onset and hospital admission was 3 to 120 days. Clinical manifestations were diverse and dependent on the location of the lesion, pyramidal signs were found in 80% of patients, there were no clinical or radiological signs of spinal cord involvement, and follow-up times ranged from 1 to 15 years. Brain biopsy is the gold standard for the diagnosis of demyelinating tumour-like lesions; however, their clinical features, along with several magnetic resonance imaging features such as open ring enhancement, venular enhancement, the presence of glutamate in spectroscopy, and others, may be sufficient to differentiate neoplastic lesions from focal tumour-like demyelinating lesions. Copyright © 2012 Sociedad Española de Neurología. Published by Elsevier Espana. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

In vivo PET evaluation in tumour-bearing rats of 2-[ 18F]fluoromethyl- L-phenylalanine as a new potential tracer for molecular imaging of brain and extra-cranial tumours in humans with PET

NASA Astrophysics Data System (ADS)

Kersemans, Ken; Bauwens, Matthias; Lahoutte, Tony; Bossuyt, Axel; Mertens, John

2007-02-01

The Na +-independent L-type LAT1 amino acid transport system for large and neutral amino acids has been shown to be expressed higher in tumour tissue relative to normal tissue and has been regarded as a key point for the development of new amino acid based tumour tracers for molecular imaging. We developed a new fluorinated phenylalanine analogue, 2-[ 18F]fluoromethyl- L-phenylalanine, considering that the spatial volume of FCH 3 is comparable with that of the iodine atom in 2-I- L-phenylalanine, of which we have proven that it is taken up excellently in tumours by the LAT1 system. The substrate molecule for radiolabeling, Boc-2-bromomethyl- L-phenylalanine- tButylester, was prepared by radical bromination of Boc-2-methyl- L-phenylalanine- tButylester. [ 18F -] for bromine exchange is performed within 3 min in conditions comparable to the [ 18F]FDG synthesis with a radiochemical yield of at least 85%. After deprotection and semi-preparative HPLC purification, the 2-[ 18F]fluoromethyl- L-phenylalanine is recovered n.c.a. (57%) with a high purity and 3.7 MBq were injected into R1M rhabdomyosarcoma tumour-bearing rats. Imaging was performed with a human PET camera from 5 to 45 min p.i. The tumour/background and tumour/blood ratios obtained from PET acquisition were at least 2.5. DUR values for the tumours were at least about 5. Furthermore, a small tumour implanted near a kidney could be well visualized completely separated from this kidney. Moreover in all tumours the "active" tumour tissue can clearly be differentiated from less active tumour tissue. This proves that 2-[ 18F]fluoromethyl- L-phenylalanine has a great potential as a new tracer for specific tumour diagnosis with PET.

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

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

Microenvironmental autophagy promotes tumour growth.

PubMed

Katheder, Nadja S; Khezri, Rojyar; O'Farrell, Fergal; Schultz, Sebastian W; Jain, Ashish; Rahman, Mohammed M; Schink, Kay O; Theodossiou, Theodossis A; Johansen, Terje; Juhász, Gábor; Bilder, David; Brech, Andreas; Stenmark, Harald; Rusten, Tor Erik

2017-01-19

As malignant tumours develop, they interact intimately with their microenvironment and can activate autophagy, a catabolic process which provides nutrients during starvation. How tumours regulate autophagy in vivo and whether autophagy affects tumour growth is controversial. Here we demonstrate, using a well characterized Drosophila melanogaster malignant tumour model, that non-cell-autonomous autophagy is induced both in the tumour microenvironment and systemically in distant tissues. Tumour growth can be pharmacologically restrained using autophagy inhibitors, and early-stage tumour growth and invasion are genetically dependent on autophagy within the local tumour microenvironment. Induction of autophagy is mediated by Drosophila tumour necrosis factor and interleukin-6-like signalling from metabolically stressed tumour cells, whereas tumour growth depends on active amino acid transport. We show that dormant growth-impaired tumours from autophagy-deficient animals reactivate tumorous growth when transplanted into autophagy-proficient hosts. We conclude that transformed cells engage surrounding normal cells as active and essential microenvironmental contributors to early tumour growth through nutrient-generating autophagy.

Tumour-induced osteomalacia.

PubMed

Minisola, Salvatore; Peacock, Munro; Fukumoto, Seijii; Cipriani, Cristiana; Pepe, Jessica; Tella, Sri Harsha; Collins, Michael T

2017-07-13

Tumour-induced osteomalacia (TIO), also known as oncogenic osteomalacia, is a rare paraneoplastic disorder caused by tumours that secrete fibroblast growth factor 23 (FGF23). Owing to the role of FGF23 in renal phosphate handling and vitamin D synthesis, TIO is characterized by decreased renal tubular reabsorption of phosphate, by hypophosphataemia and by low levels of active vitamin D. Chronic hypophosphataemia ultimately results in osteomalacia (that is, inadequate bone mineralization). The diagnosis of TIO is usually suspected when serum phosphate levels are chronically low in the setting of bone pain, fragility fractures and muscle weakness. Locating the offending tumour can be very difficult, as the tumour is often very small and can be anywhere in the body. Surgical removal of the tumour is the only definitive treatment. When the tumour cannot be located or when complete resection is not possible, medical treatment with phosphate salts or active vitamin D is necessary. One of the most promising emerging treatments for unresectable tumours that cause TIO is the anti-FGF23 monoclonal antibody KRN23. The recent identification of a fusion of fibronectin and fibroblast growth factor receptor 1 (FGFR1) as a molecular driver in some tumours not only sheds light on the pathophysiology of TIO but also opens the door to a better understanding of the transcription, translocation, post-translational modification and secretion of FGF23, as well as suggesting approaches to targeted therapy. Further study will reveal if the FGFR1 pathway is also involved in tumours that do not harbour the translocation.

ICGC PedBrain: Dissecting the genomic complexity underlying medulloblastoma

PubMed Central

Jones, David TW; Jäger, Natalie; Kool, Marcel; Zichner, Thomas; Hutter, Barbara; Sultan, Marc; Cho, Yoon-Jae; Pugh, Trevor J; Hovestadt, Volker; Stütz, Adrian M; Rausch, Tobias; Warnatz, Hans-Jörg; Ryzhova, Marina; Bender, Sebastian; Sturm, Dominik; Pleier, Sabrina; Cin, Huriye; Pfaff, Elke; Sieber, Laura; Wittmann, Andrea; Remke, Marc; Witt, Hendrik; Hutter, Sonja; Tzaridis, Theophilos; Weischenfeldt, Joachim; Raeder, Benjamin; Avci, Meryem; Amstislavskiy, Vyacheslav; Zapatka, Marc; Weber, Ursula D; Wang, Qi; Lasitschka, Bärbel; Bartholomae, Cynthia C; Schmidt, Manfred; von Kalle, Christof; Ast, Volker; Lawerenz, Chris; Eils, Jürgen; Kabbe, Rolf; Benes, Vladimir; van Sluis, Peter; Koster, Jan; Volckmann, Richard; Shih, David; Betts, Matthew J; Russell, Robert B; Coco, Simona; Tonini, Gian Paolo; Schüller, Ulrich; Hans, Volkmar; Graf, Norbert; Kim, Yoo-Jin; Monoranu, Camelia; Roggendorf, Wolfgang; Unterberg, Andreas; Herold-Mende, Christel; Milde, Till; Kulozik, Andreas E; von Deimling, Andreas; Witt, Olaf; Maass, Eberhard; Rössler, Jochen; Ebinger, Martin; Schuhmann, Martin U; Frühwald, Michael C; Hasselblatt, Martin; Jabado, Nada; Rutkowski, Stefan; von Bueren, André O; Williamson, Dan; Clifford, Steven C; McCabe, Martin G; Collins, V. Peter; Wolf, Stephan; Wiemann, Stefan; Lehrach, Hans; Brors, Benedikt; Scheurlen, Wolfram; Felsberg, Jörg; Reifenberger, Guido; Northcott, Paul A; Taylor, Michael D; Meyerson, Matthew; Pomeroy, Scott L; Yaspo, Marie-Laure; Korbel, Jan O; Korshunov, Andrey; Eils, Roland; Pfister, Stefan M; Lichter, Peter

2013-01-01

Summary Medulloblastoma is an aggressively-growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and displays tremendous biological and clinical heterogeneity1. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life. Four tumour subgroups with distinct clinical, biological and genetic profiles are currently discriminated2,3. WNT tumours, displaying activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens4. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis2. Group 3 & 4 tumours are molecularly less well-characterised, and also present the greatest clinical challenges2,3,5. The full repertoire of genetic events driving this distinction, however, remains unclear. Here we describe an integrative deep-sequencing analysis of 125 tumour-normal pairs. Tetraploidy was identified as a frequent early event in Group 3 & 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA-sequencing confirmed these alterations, and revealed the expression of the first medulloblastoma fusion genes. Chromatin modifiers were frequently altered across all subgroups. These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 & 4 patients. PMID:22832583

Regional brain volumetry and brain function in severely brain-injured patients.

PubMed

Annen, Jitka; Frasso, Gianluca; Crone, Julia Sophia; Heine, Lizette; Di Perri, Carol; Martial, Charlotte; Cassol, Helena; Demertzi, Athena; Naccache, Lionel; Laureys, Steven

2018-04-01

The relationship between residual brain tissue in patients with disorders of consciousness (DOC) and the clinical condition is unclear. This observational study aimed to quantify gray (GM) and white matter (WM) atrophy in states of (altered) consciousness. Structural T1-weighted magnetic resonance images were processed for 102 severely brain-injured and 52 healthy subjects. Regional brain volume was quantified for 158 (sub)cortical regions using Freesurfer. The relationship between regional brain volume and clinical characteristics of patients with DOC and conscious brain-injured patients was assessed using a linear mixed-effects model. Classification of patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) using regional volumetric information was performed and compared to classification using cerebral glucose uptake from fluorodeoxyglucose positron emission tomography. For validation, the T1-based classifier was tested on independent datasets. Patients were characterized by smaller regional brain volumes than healthy subjects. Atrophy occurred faster in UWS compared to MCS (GM) and conscious (GM and WM) patients. Classification was successful (misclassification with leave-one-out cross-validation between 2% and 13%) and generalized to the independent data set with an area under the receiver operator curve of 79% (95% confidence interval [CI; 67-91.5]) for GM and 70% (95% CI [55.6-85.4]) for WM. Brain volumetry at the single-subject level reveals that regions in the default mode network and subcortical gray matter regions, as well as white matter regions involved in long range connectivity, are most important to distinguish levels of consciousness. Our findings suggest that changes of brain structure provide information in addition to the assessment of functional neuroimaging and thus should be evaluated as well. Ann Neurol 2018;83:842-853. © 2018 American Neurological Association.

Mobile phones and head tumours. The discrepancies in cause-effect relationships in the epidemiological studies - how do they arise?

PubMed Central

2011-01-01

Background Whether or not there is a relationship between use of mobile phones (analogue and digital cellulars, and cordless) and head tumour risk (brain tumours, acoustic neuromas, and salivary gland tumours) is still a matter of debate; progress requires a critical analysis of the methodological elements necessary for an impartial evaluation of contradictory studies. Methods A close examination of the protocols and results from all case-control and cohort studies, pooled- and meta-analyses on head tumour risk for mobile phone users was carried out, and for each study the elements necessary for evaluating its reliability were identified. In addition, new meta-analyses of the literature data were undertaken. These were limited to subjects with mobile phone latency time compatible with the progression of the examined tumours, and with analysis of the laterality of head tumour localisation corresponding to the habitual laterality of mobile phone use. Results Blind protocols, free from errors, bias, and financial conditioning factors, give positive results that reveal a cause-effect relationship between long-term mobile phone use or latency and statistically significant increase of ipsilateral head tumour risk, with biological plausibility. Non-blind protocols, which instead are affected by errors, bias, and financial conditioning factors, give negative results with systematic underestimate of such risk. However, also in these studies a statistically significant increase in risk of ipsilateral head tumours is quite common after more than 10 years of mobile phone use or latency. The meta-analyses, our included, examining only data on ipsilateral tumours in subjects using mobile phones since or for at least 10 years, show large and statistically significant increases in risk of ipsilateral brain gliomas and acoustic neuromas. Conclusions Our analysis of the literature studies and of the results from meta-analyses of the significant data alone shows an almost doubling of

Tumour-on-a-chip: microfluidic models of tumour morphology, growth and microenvironment

PubMed Central

Trubelja, Alen

2017-01-01

Cancer remains one of the leading causes of death, albeit enormous efforts to cure the disease. To overcome the major challenges in cancer therapy, we need to have a better understanding of the tumour microenvironment (TME), as well as a more effective means to screen anti-cancer drug leads; both can be achieved using advanced technologies, including the emerging tumour-on-a-chip technology. Here, we review the recent development of the tumour-on-a-chip technology, which integrates microfluidics, microfabrication, tissue engineering and biomaterials research, and offers new opportunities for building and applying functional three-dimensional in vitro human tumour models for oncology research, immunotherapy studies and drug screening. In particular, tumour-on-a-chip microdevices allow well-controlled microscopic studies of the interaction among tumour cells, immune cells and cells in the TME, of which simple tissue cultures and animal models are not amenable to do. The challenges in developing the next-generation tumour-on-a-chip technology are also discussed. PMID:28637915

Updated Histologic Classification of Adenomas and Carcinomas in the Colon of Carcinogen-treated Sprague-Dawley Rats.

PubMed

Rubio, Carlos A

2017-12-01

Recent studies have disclosed novel histological phenotypes of colon tumours in carcinogen-treated rats. The aim of this study was to update the current histological classification of colonic neoplasias in Sprague-Dawley (SD) rats. Archival sections from 398 SD rats having 408 neoplasias in previous experiments were re-evaluated. Of the 408 colonic neoplasias, 11% (44/408) were adenomas without invasive growth and 89% (364/408) invasive carcinomas. Out of the 44 adenomas, 82% were conventional (tubular or villous), 14% traditional serrated (TSA; with unlocked serrations or with closed microtubules) and 5% gut-associated lymphoid tissue (GALT)-associated adenomas. Out of 364 carcinomas, 57% were conventional carcinomas, 26% GALT carcinomas, 8% undifferentiated, 6% signet-ring cell carcinomas, and 4% traditional serrated carcinomas (TSC). Thus, conventional adenomas, conventional carcinomas and GALT-associated carcinomas predominated (p<0.05). The updated classification of colonic tumours in SD rats includes conventional adenomas, TSA, GALT-associated adenomas, conventional carcinomas, TSC, GALT-associated carcinomas, signet-ring cell carcinomas and undifferentiated carcinomas. Several of the histological phenotypes reported here are not included in any of the current classifications of colonic tumours in rodents. This updated classification fulfils the requirements for an animal model of human disease, inasmuch as similar histological phenotypes of colon neoplasias have been documented in humans. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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

PubMed

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

2016-01-01

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

Rebound nystagmus: EOG analysis of a case with a floccular tumour.

PubMed Central

Yamazaki, A; Zee, D S

1979-01-01

Eye movements were recorded and quantitatively analysed in a patient with a tumour initially involving the cerebellar flocculus. Ocular motor abnormalities included (1) impaired smooth pursuit, (2) impaired cancellation of the vestibulo-ocular reflex when fixating an object rotating with the head, and (3) gaze paretic and rebound nystagmus. Comparable findings have been reported in monkeys with experimental floccular lesions. The rebound nystagmus (but not the other ocular motor abnormalities) disappeared when the tumour appeared to invade the brain stem in the region near the vestibular nuclei. This finding suggests that the floccular lesion unmasked a bias which created rebound nystagmus and that the bias probably arose in the vestibular nuclei. PMID:508695

Somatostatin Analogues according to Ki67 index in neuroendocrine tumours: an observational retrospective-prospective analysis from real life

PubMed Central

Faggiano, Antongiulio; Carratù, Anna Chiara; Guadagno, Elia; Tafuto, Salvatore; Tatangelo, Fabiana; Riccardi, Ferdinando; Mocerino, Carmela; Palmieri, Giovannella; Damiano, Vincenzo; Siciliano, Roberta; Leo, Silvana; Mauro, Annamaria; Tozzi, Lucia Franca; Battista, Claudia; De Rosa, Gaetano; Colao, Annamaria

2016-01-01

Somatostatin analogues (SSAs) have shown limited and variable antiproliferative effects in neuroendocrine tumours (NETs). Whether tumour control by SSAs depends on grading based on the 2010 WHO NET classification is still unclear. The aim of this study is to evaluate the efficacy of long-acting SSAs in NETs according to Ki67 index. An observational Italian multicentre study was designed to collect data in patients with gastro-entero-pancreatic or thoracic NETs under SSA treatment. Both retrospective and prospective data were included and they were analysed in line with Ki67 index, immunohistochemically evaluated in tumour samples and graded according to WHO classification (G1 = Ki67 index 0-2%, G2 = Ki67 index 3-20%, G3 = Ki67 index > 20%). Among 601 patients with NET, 140 with a histologically confirmed gastro-entero-pancreatic or thoracic NET or NET with unknown primary were treated with lanreotide autogel or octreotide LAR. An objective tumour response was observed in 11%, stability in 58% and progression in 31%. Objective response and tumour stability were not significantly different between G1 and G2 NETs. Progression free survival was longer but not significantly different in G1 than G2 NETs (median: 89 vs 43 months, p = 0.15). The median PFS was significantly longer in NETs showing Ki67 < 5% than in those showing Ki67 ≥5% (89 vs 35 months, p = 0.005). SSA therapy shows significant antiproliferative effects in well differentiated low/intermediate-proliferating NETs, not only G1 but also in G2 type. A Ki67 index of 5% seems to work better than 3% to select the best candidates for SSA therapy. PMID:26701729

Somatostatin analogues according to Ki67 index in neuroendocrine tumours: an observational retrospective-prospective analysis from real life.

PubMed

Faggiano, Antongiulio; Carratù, Anna Chiara; Guadagno, Elia; Tafuto, Salvatore; Tatangelo, Fabiana; Riccardi, Ferdinando; Mocerino, Carmela; Palmieri, Giovannella; Damiano, Vincenzo; Siciliano, Roberta; Leo, Silvana; Mauro, Annamaria; Tozzi, Lucia Franca; Battista, Claudia; De Rosa, Gaetano; Colao, Annamaria

2016-02-02

Somatostatin analogues (SSAs) have shown limited and variable antiproliferative effects in neuroendocrine tumours (NETs). Whether tumour control by SSAs depends on grading based on the 2010 WHO NET classification is still unclear. The aim of this study is to evaluate the efficacy of long-acting SSAs in NETs according to Ki67 index. An observational Italian multicentre study was designed to collect data in patients with gastro-entero-pancreatic or thoracic NETs under SSA treatment. Both retrospective and prospective data were included and they were analysed in line with Ki67 index, immunohistochemically evaluated in tumour samples and graded according to WHO classification (G1 = Ki67 index 0-2%, G2 = Ki67 index 3-20%, G3 = Ki67 index > 20%). Among 601 patients with NET, 140 with a histologically confirmed gastro-entero-pancreatic or thoracic NET or NET with unknown primary were treated with lanreotide autogel or octreotide LAR. An objective tumour response was observed in 11%, stability in 58% and progression in 31%. Objective response and tumour stability were not significantly different between G1 and G2 NETs. Progression free survival was longer but not significantly different in G1 than G2 NETs (median: 89 vs 43 months, p = 0.15). The median PFS was significantly longer in NETs showing Ki67 < 5% than in those showing Ki67 ≥ 5% (89 vs 35 months, p = 0.005). SSA therapy shows significant antiproliferative effects in well differentiated low/intermediate-proliferating NETs, not only G1 but also in G2 type. A Ki67 index of 5% seems to work better than 3% to select the best candidates for SSA therapy.

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

NASA Astrophysics Data System (ADS)

Ashari, Rehab Bahaaddin

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

Hyaluronan and hyaluronectin in the extracellular matrix of human brain tumour stroma.

PubMed

Delpech, B; Maingonnat, C; Girard, N; Chauzy, C; Maunoury, R; Olivier, A; Tayot, J; Creissard, P

1993-01-01

Hyaluronan (HA) and the hyaluronan-binding glycoprotein hyaluronectin (HN) were measured in 23 gliomas and 8 meningiomas and their location was revisited in 35 tumours. A clear-cut difference was found in the HN/HA ratio values of glioblastomas (below 0.5) and that of astrocytomas (above 0.5 P < 0.001). Besides their location in the intercellular part of gliomas, HA and HN displayed a perivascular location in 1/3 astrocytomas, 17/24 glioblastomas, and 3/7 meningiomas, suggesting they could be produced also by the vascular stroma of tumours and that they would characterise the neoangiogenesis. All cultivated glioma cells tested produced HA in vitro, whereas only 1/11 cell lines produced HN, at a low level. The results obtained suggest that glioma HA and HN are produced by both cancer cells and vascular stroma cells, which contribute to the edification of the extracellular matrix. In meningiomas only the stroma would be responsible for HA and HN production.

Side population in human glioblastoma is non-tumorigenic and characterizes brain endothelial cells

PubMed Central

Golebiewska, Anna; Bougnaud, Sébastien; Stieber, Daniel; Brons, Nicolaas H. C.; Vallar, Laurent; Hertel, Frank; Klink, Barbara; Schröck, Evelin; Bjerkvig, Rolf

2013-01-01

The identification and significance of cancer stem-like cells in malignant gliomas remains controversial. It has been proposed that cancer stem-like cells display increased drug resistance, through the expression of ATP-binding cassette transporters that detoxify cells by effluxing exogenous compounds. Here, we investigated the ‘side population’ phenotype based on efflux properties of ATP-binding cassette transporters in freshly isolated human glioblastoma samples and intracranial xenografts derived thereof. Using fluorescence in situ hybridization analysis on sorted cells obtained from glioblastoma biopsies, as well as human tumour xenografts developed in immunodeficient enhanced green fluorescence protein-expressing mice that allow an unequivocal tumour-stroma discrimination, we show that side population cells in human glioblastoma are non-neoplastic and exclusively stroma-derived. Tumour cells were consistently devoid of efflux properties regardless of their genetic background, tumour ploidy or stem cell associated marker expression. Using multi-parameter flow cytometry we identified the stromal side population in human glioblastoma to be brain-derived endothelial cells with a minor contribution of astrocytes. In contrast with their foetal counterpart, neural stem/progenitor cells in the adult brain did not display the side population phenotype. Of note, we show that CD133-positive cells often associated with cancer stem-like cells in glioblastoma biopsies, do not represent a homogenous cell population and include CD31-positive endothelial cells. Interestingly, treatment of brain tumours with the anti-angiogenic agent bevacizumab reduced total vessel density, but did not affect the efflux properties of endothelial cells. In conclusion our findings contribute to an unbiased identification of cancer stem-like cells and stromal cells in brain neoplasms, and provide novel insight into the complex issue of drug delivery to the brain. Since efflux properties of

Improving fMRI reliability in presurgical mapping for brain tumours.

PubMed

Stevens, M Tynan R; Clarke, David B; Stroink, Gerhard; Beyea, Steven D; D'Arcy, Ryan Cn

2016-03-01

Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence

MHC class I antigens and tumour-infiltrating leucocytes in laryngeal cancer: long-term follow-up.

PubMed Central

Esteban, F.; Redondo, M.; Delgado, M.; Garrido, F.; Ruiz-Cabello, F.

1996-01-01

Alteration in MHC class I expression may be used by cancer cells to avoid immune destruction. Much experimental evidence supports this idea, although survival studies are very scarce. To investigate whether the presence or absence of HLA-A, -B and -C antigens in laryngeal carcinoma influences survival, a series of 60 primary laryngeal tumours treated surgically and normal tissues were evaluated in frozen sections for the expression of MHC class I antigens and tumour-infiltrating leucocytes (CD3, CD4, CD8, CD11b, CD1, CD20 and CD16), using monoclonal antibodies and the APAAP, technique. Long-term follow-up from the patients is available, ranging from 6 to 10 years. Thirteen tumours presented total HLA-ABC loss, five selective losses of HLA-A antigens and one absence of HLA-B antigens. Total losses were statistically associated with several clinical and pathological parameters, but there were no differences regarding tumour-infiltrating leucocytes. After conducting a prospective study, only T and N staging and scoring according to Glanz's malignancy classification were found to be independently related to patients' outcome. From our data, we conclude that neither complete loss of HLA class I antigens nor tumour-infiltrating leucocytes appear to influence survival in squamous cell carcinoma of the larynx. PMID:8956796

Resistance to tumour challenge after tumour laser thermotherapy is associated with a cellular immune response

PubMed Central

Ivarsson, K; Myllymäki, L; Jansner, K; Stenram, U; Tranberg, K-G

2005-01-01

Previous studies in our laboratory have shown that interstitial laser thermotherapy (ILT) of an experimental liver tumour is superior to surgical excision, at least partly due to a laser-induced immunological effect. The aim of the present study was to investigate the time–response relationship of the ILT-induced immunisation and the cellular response of macrophages and lymphocytes. A dimethylhydrazine-induced adenocarcinoma was transplanted into the liver of syngeneic rats. Rats with tumour were treated 6–8 days later (tumour size 0.25–0.40 cm3) with ILT of tumour or resection of the tumour-bearing lobe. Two groups of rats without tumour were treated with resection of a normal liver lobe or ILT of normal liver. A challenging tumour was implanted into the liver of each rat 2, 5 or 10 weeks after primary treatment. Rats were killed 6, 12 and 48 days (or earlier due to their condition) after challenge (n=8 in all groups). Immunohistochemical techniques were used to determine lymphocytes (CD8, CD4) and macrophages (ED1, ED2) in rats having had treatment of a primary tumour. Interstitial laser thermotherapy of the first tumour was followed by eradication of challenging tumour and absence of tumour spread. This contrasted with rapid growth and spread of challenging tumour in the other groups. In the challenging vital tumour tissue and in the interface between the tumour and surroundings, the number of ED1 macrophages and CD8 lymphocytes was higher in rats having been treated with the ILT of tumour than in those having undergone resection of the tumour-bearing lobe. The number of ED2 macrophages and CD4 lymphocytes was low and did not vary between these two groups. Interstitial laser thermotherapy elicited an immune response that eradicated a challenging tumour and was associated with increased numbers of tumour-infiltrating macrophages and CD8 lymphocytes. PMID:16091763

[Prevalence of central nervous system tumours and histological identification in the operated patient: 20 years of experience].

PubMed

Anaya-Delgadillo, Gustavo; de Juambelz-Cisneros, Pedro Pablo; Fernández-Alvarado, Basilio; Pazos-Gómez, Fernando; Velasco-Torre, Andrea; Revuelta-Gutiérrez, Rogelio

Central nervous system tumours comprise a heterogeneous group of neoplasms with great histological diversity. Despite the rising prevalence of these tumours in developing countries, some places like Mexico and Latin America have no representative studies that show the real impact of these tumours in our population. To describe the characteristics of the primary and secondary tumours of the central nervous system in the last 20 years in a Mexican institution. Patients with histopathological diagnosis from 1993 to 2013 in our institution, grouping them according to WHO classification 2007, characterising them by age group, gender, and anatomical location. There were a total of 511 tumours of the central nervous system. Of those, 292 were women and 219 men, with a ratio 1.3: 1, and a mean age of 49.3 years. Tumours with higher prevalence were: Meningeal tumours, 171 (33%), followed by neuroepithelial, 121 (24%). Astrocytoma had the highest prevalence in paediatric patients, whereas in those older than 20 years it was the meningioma. The supratentorial location was the most involved. This is the first study of a series of cases in Mexico that is performed by taking into account benign and malignant tumours of the central nervous system, with patients of all age groups with a range of 20 years. While this work only represents a retrospective analysis of an institution, it can be a strong indication of the epidemiology of these tumours in our environment. Copyright © 2016. Publicado por Masson Doyma México S.A.

[Mobile phones and head tumours: it is time to read and highlight data in a proper way].

PubMed

Levis, Angelo G; Minicucci, Nadia; Ricci, Paolo; Gennaro, Valerio; Garbisa, Spiridione

2011-01-01

The uncertainty about the relationship between the use of mobile phones (MPs: analogue and digital cellulars, and cordless) and the increase of head tumour risk can be solved by a critical analysis of the methodological elements of both the positive and the negative studies. Results by Hardell indicate a cause/effect relationship: exposures for or latencies from ≥ 10 years to MPs increase by up to 100% the risk of tumour on the same side of the head preferred for phone use (ipsilateral tumours) - which is the only one significantly irradiated - with statistical significance for brain gliomas, meningiomas and acoustic neuromas. On the contrary, studies published under the Interphone project and others produced negative results and are characterised by the substantial underestimation of the risk of tumour. However, also in the Interphone studies a clear and statistically significant increase of ipsilateral head tumours (gliomas, neuromas and parotid gland tumours) is quite common in people having used MPs since or for ≥ 10 years. And also the metaanalyses by Hardell and other Authors, including only the literature data on ipsilateral tumours in people having used MPs since or for ≥ 10 years - and so also part of the Interphone data - still show statistically significant increases of head tumours.

Neutron medical treatment of tumours — a survey of facilities

NASA Astrophysics Data System (ADS)

Wagner, F. M.; Loeper-Kabasakal, B.; Breitkreutz, H.

2012-03-01

Neutron therapy has two branches: Fast Neutron Therapy (FNT) and Boron Neutron Capture Therapy (BNCT). The mean neutron energies used for FNT range from 2 MeV to 25 MeV whereas the maximum energy for BNCT is about 10 keV. Neutron generators for FNT have been cyclotrons, accelerators and reactors, whereas BNCT is so far bound to reactors. Both therapies use the effects of high-LET radiation (secondary recoil protons and alpha particles, respectively) and can attack otherwise radioresistant tumours, however, with the hazard of adverse effects for irradiated healthy tissue. FNT has been administered to about 30,000 patients world-wide. From formerly 40 facilities, only eight are operational or stand-by today. The reasons for this development have been, on the one hand, related to technical and economical conditions; on the other hand, strong side effects and insufficient proof of clinical results in the early years as well as increasing competition with new clinical methods have reduced patient numbers. In fact, strict observations of indications, appropriate therapy-planning including low-LET radiation, and consequent treatment of side effects have lead to remarkable results in the meantime. BNCT initially was developed for the treatment of extremely aggressive forms of brain tumour, taking advantage of the action of the blood-brain-barrier which allows for a boronated compound to be selectively enriched in tumour cells. Meanwhile, also malignant melanoma (MM) and Head-and-Neck (H&T) tumours are treated because of their relative radioresistance. At present, epithermal beams with sufficient flux are available only at two facilities. Existing research reactors were indispensable in the development of BNCT, but are to be replaced by hospital-based epithermal neutron sources. Clinical results indicate significantly increased survival times, but the number of patients ever treated is still below 1,000. 3D-dose calculation systems have been developed at several facilities

Novel somatic and germline mutations in intracranial germ cell tumours.

PubMed

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

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.

Effects of childhood body size on breast cancer tumour characteristics

PubMed Central

2010-01-01

Introduction Although a role of childhood body size in postmenopausal breast cancer risk has been established, less is known about its influence on tumour characteristics. Methods We studied the relationships between childhood body size and tumour characteristics in a Swedish population-based case-control study consisting of 2,818 breast cancer cases and 3,111 controls. Our classification of childhood body size was derived from a nine-level somatotype. Relative risks were estimated by odds ratios with 95% confidence intervals, derived from fitting unconditional logistic regression models. Association between somatotype at age 7 and tumour characteristics were evaluated in a case-only analysis where P values for heterogeneity were obtained by performing one degree of freedom trend tests. Results A large somatotype at age 7 was found to be associated with decreased postmenopausal breast cancer risk. Although strongly associated with other risk factors such as age of menarche, adult body mass index and mammographic density, somatotype at age 7 remained a significant protective factor (odds ratio (OR) comparing large to lean somatotype at age 7 = 0.73, 95% confidence interval (CI) = 0.58-0.91, P trend = 0.004) after adjustment. The significant protective effect was observed within all subgroups defined by estrogen receptor (ER) and progesterone receptor (PR) status, with a stronger effect for ER-negative (0.40, 95% CI = 0.21-0.75, P trend = 0.002), than for ER-positive (0.80, 95% CI = 0.62-1.05, P trend = 0.062), tumours (P heterogeneity = 0.046). Somatotype at age 7 was not associated with tumour size, histology, grade or the presence or absence of metastatic nodes. Conclusions Greater body size at age 7 is associated with a decreased risk of postmenopausal breast cancer, and the associated protective effect is stronger for the ER-negative breast cancer subtype than for the ER-positive subtype. PMID:20398298

Phyllodes tumours

PubMed Central

Parker, S; Harries, S

2001-01-01

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 PMID:11423590

Descriptive epidemiology of childhood central nervous system tumours in Tunisia. experience of a single institution over a 15-year period (1990-2004).

PubMed

Bellil, Salma; Limaiem, Faten; Mahfoudhi, Houaïda; Bellil, Khadija; Chelly, Inès; Mekni, Amina; Jemel, Hafedh; Khaldi, Moncef; Haouet, Slim; Zitouna, Moncef; Kchir, Nidhameddine

2008-01-01

Central nervous system tumours represent 20% of all childhood cancers, and are the second most common group of neoplasms after leukaemias. To describe epidemiological characteristics of central nervous system tumours in a paediatric Tunisian population. A retrospective study of 492 childhood central nervous system tumours operated between 1990 and 2004 was undertaken. We investigated the age-related location, gender distribution and the histology of all tumours, and adopted the latest WHO classification (2007) in grouping all the tumours. There were 488 primary and 4 secondary tumours; 426 (86.6%) were intracranial and 66 (13.4%) were intraspinal. Of the 426 intracranial tumours, 214 (50.24%) were supratentorial and 212 (49.76%) were infratentorial. The median age at diagnosis was 8 years, with a male:female ratio of 1.14:1. Low-grade tumours (WHO I/II) constituted 67.3% of all lesions and the rest (32.7%) were high-grade tumours (WHO III/IV). The most common tumour found in our series was astrocytoma (38%), followed by medulloblastoma (16.2%), then ependymoma (6.9%), cystic tumours (6.3%) and craniopharyngioma (5.3%). The overall 5-year survival rate was 45% with a mean follow-up period of 36 months. In our patient population, the incidence and distribution of central nervous system tumours were similar to those reported in literature. Overall survival rates varied according to tumour location and histopathology. (c) 2008 S. Karger AG, Basel.

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

PubMed Central

2010-01-01

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

[Postchemotherapy residual tumour resection in complex metastatic sites of advanced testicular germ cell tumours].

PubMed

Paffenholz, P; Pfister, D; Heidenreich, A

2016-05-01

Postchemotherapy residual tumour resection (PC-RTR) is an integral part of the multimodal therapy for advanced testicular germ cell tumours. Depending on the extent and localisation of the residual mass, PC-RTR may necessitate a multidisciplinary procedure (which should be planned preoperatively), to resolve even complex situations in an oncologically sound manner, with lower treatment-related morbidity The aim of article is to report on the interdisciplinary management of complex residual masses. Of a total of 162 patients who underwent PC-RTR, 24 (17.8 %) patients underwent, in addition to a bilateral postchemotherapy retroperitoneal lymphadenectomy (PC-RPLND), complex adjunctive resections including the abdominal aorta, the inferior vena cava, or the thoracic/lumbar spine, and the neighbouring vessels (n = 15). We performed a retrospective analysis of treatment-associated complications according to the Clavien-Dindo classification and of progression-free, cancer-specific and overall survival. Median patient age was 24.5 (18-52) years. All patients had an intermediate or poor prognosis according to the International Germ Cell Cancer Collaboration Group (IGCCCG). Median tumour diameter at the time of surgery was 18.6 (9.0-35) cm. In 5 patients 1-2 metastatic lumbar vertebral bodies were completely resected, stabilised and replaced by means of a cage. In 6 patients resection of the abdominal aorta/inferior vena cava with vascular prosthesis replacement was required owing to infiltration. In 2 patients the common iliac artery or vein was resected and replaced. In addition, retrocrural lymph nodes had to be resected in 5 patients and 3 patients required adjunctive nephrectomy. In another 4 patients the Whipple procedure was required owing to infiltration into the pancreas and/or duodenum. The median operating time was 7.8 (6-15) h, the median blood loss was around 1,450 (900-3,400) ml, and 2 Clavien-Dindo grade IVa complications occurred. Pathohistology

Immunohistochemical expression of p53 proteins in Wilms' tumour: a possible association with the histological prognostic parameter of anaplasia.

PubMed

Cheah, P L; Looi, L M; Chan, L L

1996-01-01

Wilms' tumour (nephroblastoma) has been associated with chromosomal abnormalities at the 11p13, 11p15 and 16q regions. A study into the possibility of mutations occurring within p53, the ubiquitous adult tumour suppressor gene, in Wilms' tumour was carried out. Thirty-eight cases were studied. Of these 36 were categorised into the favourable histology group and two into the unfavourable histology group based on the National Wilms' Tumour Study criteria. Archival formalin-fixed, paraffin-embedded tissue sections from each case were stained with a polyclonal (AB565:Chemicon) and a monoclonal (DO7:Dako) antibody raised against p53 protein using a peroxidase-labelled streptavidin biotin kit (Dako). 'Cure' (disease-free survival of 60 months or longer) was documented in 39% of cases with favourable histology tumours. Eleven percent in this group succumbed to the disease. Both cases with unfavourable histology died. Four out of 36 (11%) tumours with favourable histology demonstrated weak to moderate staining with both AB565 and DO7 in more than 75% of tumour cells. In contrast, p53 protein expression in unfavourable histology tumours was significantly increased compared with the favourable histology group (P = 0.021) with both cases demonstrating immunopositivity in > 75% of tumour cells when stained with AB565 and DO7. The intensity of staining ranged from moderate to strong in both cases. It appears from this preliminary study that the immunohistochemical expression of p53 protein in Wilms' tumour, presumably a result of mutation in the p53 tumour suppressor gene, correlates with histological classification, histological categorisation being one of the useful features in the prognostic assessment of Wilms' tumours.

Inter-hemispheric language functional reorganization in low-grade glioma patients after tumour surgery.

PubMed

Kristo, Gert; Raemaekers, Mathijs; Rutten, Geert-Jan; de Gelder, Beatrice; Ramsey, Nick F

2015-03-01

Despite many claims of functional reorganization following tumour surgery, empirical studies that investigate changes in functional activation patterns are rare. This study investigates whether functional recovery following surgical treatment in patients with a low-grade glioma in the left hemisphere is linked to inter-hemispheric reorganization. Based on literature, we hypothesized that reorganization would induce changes in the spatial pattern of activation specifically in tumour homologue brain areas in the healthy right hemisphere. An experimental group (EG) of 14 patients with a glioma in the left hemisphere near language related brain areas, and a control group of 6 patients with a glioma in the right, non-language dominant hemisphere were scanned before and after resection. In addition, an age and gender matched second control group of 18 healthy volunteers was scanned twice. A verb generation task was used to map language related areas and a novel technique was used for data analysis. Contrary to our hypothesis, we found that functional recovery following surgery of low-grade gliomas cannot be linked to functional reorganization in language homologue brain areas in the healthy, right hemisphere. Although elevated changes in the activation pattern were found in patients after surgery, these were largest in brain areas in proximity to the surgical resection, and were very similar to the spatial pattern of the brain shift following surgery. This suggests that the apparent perilesional functional reorganization is mostly caused by the brain shift as a consequence of surgery. Perilesional functional reorganization can however not be excluded. The study suggests that language recovery after transient post-surgical language deficits involves recovery of functioning of the presurgical language system. Copyright © 2014 Elsevier Ltd. All rights reserved.

Effect of tertiary multileaf collimator (MLC) on foetal dose during three-dimensional conformal radiation therapy (3DCRT) of a brain tumour during pregnancy.

PubMed

Sharma, Dayananda S; Jalali, Rakesh; Tambe, Chandrashekhar M; Animesh; Deshpande, Deepak D

2004-01-01

The aim of this work was to measure the dose to foetus both in vivo and in vitro during three-dimensional conformal radiation therapy (3DCRT) in a pregnant patient with a pituitary adenoma. The study was then extended to assess the components contributing to the foetal dose such as collimator scatter, internal scatter, head leakage, wedge scatter and multileaf collimator (MLC) effect. A 30-year-old pregnant woman with a non-functioning pituitary macroadenoma was planned for 3DCRT with 6MV X-ray using four equally weighted MLC-shaped non-coplanar wedged portals. In vivo dosimetry was carried out using thermoluminescent (TL) phosphor powder, which was placed at different positions on the patient, corresponding to different locations in the uterus and also at external os. In vitro measurements were also performed on a simulated phantom using the same set-up parameters and beam arrangement to verify the in vivo measured dose. Experiments were carried out to measure the respective contributions of different components towards peripheral dose. In vitro measured dose to foetus was found to be slightly more than that of in vivo measurement with a maximum of 0.044% of the prescribed dose of 45Gy, which corresponded to 0.0199+/-0.0008Gy. Thermoluminescence dosimeter (TLD) kept at the external os of the patient showed a dose of 0.031% of the prescribed dose. Among the various components of the peripheral dose (foetal dose) measured, head leakage was found to be the leading cause contributing 52%, followed by wedge scatter (31%), collimator scatter (14%) and internal scatter (13%). The use of MLC reduced not only the volume of normal brain irradiation as compared to open fields but also the peripheral dose by 10%. Radiotherapy of brain tumours during pregnancy poses a unique clinical situation and decisions to deliver radiotherapy should be taken after detailed in vitro and in vivo dosimetric measurements. Our findings suggest that the beam arrangement using 3-4-fields

Robust Averaging of Covariances for EEG Recordings Classification in Motor Imagery Brain-Computer Interfaces.

PubMed

Uehara, Takashi; Sartori, Matteo; Tanaka, Toshihisa; Fiori, Simone

2017-06-01

The estimation of covariance matrices is of prime importance to analyze the distribution of multivariate signals. In motor imagery-based brain-computer interfaces (MI-BCI), covariance matrices play a central role in the extraction of features from recorded electroencephalograms (EEGs); therefore, correctly estimating covariance is crucial for EEG classification. This letter discusses algorithms to average sample covariance matrices (SCMs) for the selection of the reference matrix in tangent space mapping (TSM)-based MI-BCI. Tangent space mapping is a powerful method of feature extraction and strongly depends on the selection of a reference covariance matrix. In general, the observed signals may include outliers; therefore, taking the geometric mean of SCMs as the reference matrix may not be the best choice. In order to deal with the effects of outliers, robust estimators have to be used. In particular, we discuss and test the use of geometric medians and trimmed averages (defined on the basis of several metrics) as robust estimators. The main idea behind trimmed averages is to eliminate data that exhibit the largest distance from the average covariance calculated on the basis of all available data. The results of the experiments show that while the geometric medians show little differences from conventional methods in terms of classification accuracy in the classification of electroencephalographic recordings, the trimmed averages show significant improvement for all subjects.

Multifocal multi-site Warthin tumour.

PubMed

Hilton, Jennifer M; Phillips, John S; Hellquist, Henrik B; Premachandra, Don J

2008-12-01

The unique case of a 55-year-old man with multifocal adenolymphoma (Warthin's tumour) of both parotid glands, the neck and post-nasal space is presented. Warthin tumour is almost exclusively a parotid tumour but is known to be bilateral in 7-10% of cases and multifocal in 2% of cases. Most extraglandular Warthin tumours have been located in neck lymph nodes and only a few cases have been reported from other sites. The presented case is unique in having synchronous and metachronous Warthin tumours, as well as one of the tumours being neither truly parotid, nor within a lymph node.

Which method of posttraumatic stress disorder classification best predicts psychosocial function in children with traumatic brain injury?

PubMed

Iselin, Greg; Le Brocque, Robyne; Kenardy, Justin; Anderson, Vicki; McKinlay, Lynne

2010-10-01

Controversy surrounds the classification of posttraumatic stress disorder (PTSD), particularly in children and adolescents with traumatic brain injury (TBI). In these populations, it is difficult to differentiate TBI-related organic memory loss from dissociative amnesia. Several alternative PTSD classification algorithms have been proposed for use with children. This paper investigates DSM-IV-TR and alternative PTSD classification algorithms, including and excluding the dissociative amnesia item, in terms of their ability to predict psychosocial function following pediatric TBI. A sample of 184 children aged 6-14 years were recruited following emergency department presentation and/or hospital admission for TBI. PTSD was assessed via semi-structured clinical interview (CAPS-CA) with the child at 3 months post-injury. Psychosocial function was assessed using the parent report CHQ-PF50. Two alternative classification algorithms, the PTSD-AA and 2 of 3 algorithms, reached statistical significance. While the inclusion of the dissociative amnesia item increased prevalence rates across algorithms, it generally resulted in weaker associations with psychosocial function. The PTSD-AA algorithm appears to have the strongest association with psychosocial function following TBI in children and adolescents. Removing the dissociative amnesia item from the diagnostic algorithm generally results in improved validity. Copyright 2010 Elsevier Ltd. All rights reserved.

Significance of perivascular tumour cells defined by CD109 expression in progression of glioma.

PubMed

Shiraki, Yukihiro; Mii, Shinji; Enomoto, Atsushi; Momota, Hiroyuki; Han, Yi-Peng; Kato, Takuya; Ushida, Kaori; Kato, Akira; Asai, Naoya; Murakumo, Yoshiki; Aoki, Kosuke; Suzuki, Hiromichi; Ohka, Fumiharu; Wakabayashi, Toshihiko; Todo, Tomoki; Ogawa, Seishi; Natsume, Atsushi; Takahashi, Masahide

2017-12-01

In the progression of glioma, tumour cells often exploit the perivascular microenvironment to promote their survival and resistance to conventional therapies. Some of these cells are considered to be brain tumour stem cells (BTSCs); however, the molecular nature of perivascular tumour cells has not been specifically clarified because of the complexity of glioma. Here, we identified CD109, a glycosylphosphatidylinositol-anchored protein and regulator of multiple signalling pathways, as a critical regulator of the progression of lower-grade glioma (World Health Organization grade II/III) by clinicopathological and whole-genome sequencing analysis of tissues from human glioma. The importance of CD109-positive perivascular tumour cells was confirmed not only in human lower-grade glioma tissues but also in a mouse model that recapitulated human glioma. Intriguingly, BTSCs isolated from mouse glioma expressed high levels of CD109. CD109-positive BTSCs exerted a proliferative effect on differentiated glioma cells treated with temozolomide. These data reveal the significance of tumour cells that populate perivascular regions during glioma progression, and indicate that CD109 is a potential therapeutic target for the disease. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Lomustine Nanoparticles Enable Both Bone Marrow Sparing and High Brain Drug Levels - A Strategy for Brain Cancer Treatments.

PubMed

Fisusi, Funmilola A; Siew, Adeline; Chooi, Kar Wai; Okubanjo, Omotunde; Garrett, Natalie; Lalatsa, Katerina; Serrano, Dolores; Summers, Ian; Moger, Julian; Stapleton, Paul; Satchi-Fainaro, Ronit; Schätzlein, Andreas G; Uchegbu, Ijeoma F

2016-05-01

The blood brain barrier compromises glioblastoma chemotherapy. However high blood concentrations of lipophilic, alkylating drugs result in brain uptake, but cause myelosuppression. We hypothesised that nanoparticles could achieve therapeutic brain concentrations without dose-limiting myelosuppression. Mice were dosed with either intravenous lomustine Molecular Envelope Technology (MET) nanoparticles (13 mg kg(-1)) or ethanolic lomustine (6.5 mg kg(-1)) and tissues analysed. Efficacy was assessed in an orthotopic U-87 MG glioblastoma model, following intravenous MET lomustine (daily 13 mg kg(-1)) or ethanolic lomustine (daily 1.2 mg kg(-1) - the highest repeated dose possible). Myelosuppression and MET particle macrophage uptake were also investigated. The MET formulation resulted in modest brain targeting (brain/ bone AUC0-4h ratios for MET and ethanolic lomustine = 0.90 and 0.53 respectively and brain/ liver AUC0-4h ratios for MET and ethanolic lomustine = 0.24 and 0.15 respectively). The MET formulation significantly increased mice (U-87 MG tumours) survival times; with MET lomustine, ethanolic lomustine and untreated mean survival times of 33.2, 22.5 and 21.3 days respectively and there were no material treatment-related differences in blood and femoral cell counts. Macrophage uptake is slower for MET nanoparticles than for liposomes. Particulate drug formulations improved brain tumour therapy without major bone marrow toxicity.

Prognostication in eye cancer: the latest tumor, node, metastasis classification and beyond

PubMed Central

Kivelä, T; Kujala, E

2013-01-01

The tumour, node, metastasis (TNM) classification is a universal cancer staging system, which has been used for five decades. The current seventh edition became effective in 2010 and covers six ophthalmic sites: eyelids, conjunctiva, uvea, retina, orbit, and lacrimal gland; and five cancer types: carcinoma, sarcoma, melanoma, retinoblastoma, and lymphoma. The TNM categories are based on the anatomic extent of the primary tumour (T), regional lymph node metastases (N), and systemic metastases (M). The T categories of ophthalmic cancers are based on the size of the primary tumour and any invasion of periocular structures. The anatomic category is used to determine the TNM stage that correlates with survival. Such staging is currently implemented only for carcinoma of the eyelid and melanoma of the uvea. The classification of ciliary body and choroidal melanoma is the only one based on clinical evidence so far: a database of 7369 patients analysed by the European Ophthalmic Oncology Group. It spans a prognosis from 96% 5-year survival for stage I to 97% 5-year mortality for stage IV. The most accurate criterion for prognostication in uveal melanoma is, however, analysis of chromosomal alterations and gene expression. When such data are available, the TNM stage may be used for further stratification. Prognosis in retinoblastoma is frequently assigned by using an international classification, which predicts conservation of the eye and vision, and an international staging separate from the TNM system, which predicts survival. The TNM cancer staging manual is a useful tool for all ophthalmologists managing eye cancer. PMID:23258307

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

PubMed

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

2016-02-01

The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then deidentified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The data set was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based on the National Institute of Neurological Disorders and Stroke (NINDS) Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7

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

PubMed Central

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

2016-01-01

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

[Combined palliative hypofractionated radiation and carboplatin chemotherapy of intranasal tumours in dogs].

PubMed

Schwietzer, A; Kessler, M; Kandel-Tschiederer, B

2012-10-17

Combination therapy of intranasal tumours in dogs with palliative 60 cobalt radiation and carboplatin chemotherapy. Twenty-five dogs with intranasal tumours were treated in the Hofheim Veterinary Hospital (Germany) from 2004 to 2006 with a total radiation dose of 24Gy (3 fractions of 8 Gy on days 0, 7 and 21) and five doses of Carboplatin (270-300 mg/m² BSA i.v. every 21-28 days). In 88% patients, clinical symptoms subsided partially or completely resulting in improvement in quality of life. Computed tomography revealed partial (5/25) or complete (5/25) tumour remissions. Chemotherapy was well tolerated. Radiation therapy caused no or minimal side effects except for 3 dogs (12%), which experienced serious ocular side effects resulting in loss of vision of the affected eye and one dog with epileptic seizures. Survival times ranged from 10-639 days with a median of 156 days. There was no statistically significant correlation between the parameters breed, age, sex, brain invasion or tumour stage and survival time or progression free interval. Survival time and progression free interval were significantly correlated with the degree of tumour remission. It can be concluded from this study that palliative radiation therapy combined with chemotherapy results in excellent palliation of clinical symptoms and acceptable survival times. There was no advantage of combined therapy (radiation with carboplatin) when compared to literature data on results of radiation therapy alone.

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

PubMed

Redmayne, Mary

2013-01-10

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

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

PubMed Central

2013-01-01

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

Adapting radiotherapy to hypoxic tumours

NASA Astrophysics Data System (ADS)

Malinen, Eirik; Søvik, Åste; Hristov, Dimitre; Bruland, Øyvind S.; Rune Olsen, Dag

2006-10-01

In the current work, the concepts of biologically adapted radiotherapy of hypoxic tumours in a framework encompassing functional tumour imaging, tumour control predictions, inverse treatment planning and intensity modulated radiotherapy (IMRT) were presented. Dynamic contrast enhanced magnetic resonance imaging (DCEMRI) of a spontaneous sarcoma in the nasal region of a dog was employed. The tracer concentration in the tumour was assumed related to the oxygen tension and compared to Eppendorf histograph measurements. Based on the pO2-related images derived from the MR analysis, the tumour was divided into four compartments by a segmentation procedure. DICOM structure sets for IMRT planning could be derived thereof. In order to display the possible advantages of non-uniform tumour doses, dose redistribution among the four tumour compartments was introduced. The dose redistribution was constrained by keeping the average dose to the tumour equal to a conventional target dose. The compartmental doses yielding optimum tumour control probability (TCP) were used as input in an inverse planning system, where the planning basis was the pO2-related tumour images from the MR analysis. Uniform (conventional) and non-uniform IMRT plans were scored both physically and biologically. The consequences of random and systematic errors in the compartmental images were evaluated. The normalized frequency distributions of the tracer concentration and the pO2 Eppendorf measurements were not significantly different. 28% of the tumour had, according to the MR analysis, pO2 values of less than 5 mm Hg. The optimum TCP following a non-uniform dose prescription was about four times higher than that following a uniform dose prescription. The non-uniform IMRT dose distribution resulting from the inverse planning gave a three times higher TCP than that of the uniform distribution. The TCP and the dose-based plan quality depended on IMRT parameters defined in the inverse planning procedure (fields

Platelet-activating factor receptor (PAF-R)-dependent pathways control tumour growth and tumour response to chemotherapy

PubMed Central

2010-01-01

Background Phagocytosis of apoptotic cells by macrophages induces a suppressor phenotype. Previous data from our group suggested that this occurs via Platelet-activating factor receptor (PAF-R)-mediated pathways. In the present study, we investigated the impact of apoptotic cell inoculation or induction by a chemotherapeutic agent (dacarbazine, DTIC) on tumour growth, microenvironmental parameters and survival, and the effect of treatment with a PAF-R antagonist (WEB2170). These studies were performed in murine tumours: Ehrlich Ascitis Tumour (EAT) and B16F10 melanoma. Methods Tumour growth was assessed by direct counting of EAT cells in the ascitis or by measuring the volume of the solid tumour. Parameters of the tumour microenvironment, such as the frequency of cells expressing cyclo-oxygenase-2 (COX-2), caspase-3 and galectin-3, and microvascular density, were determined by immunohistochemistry. Levels of vascular endothelium growth factor (VEGF) and prostaglandin E2 (PGE2) were determined by ELISA, and levels of nitric oxide (NO) by Griess reaction. PAF-R expression was analysed by immunohistochemistry and flow cytometry. Results Inoculation of apoptotic cells before EAT implantation stimulated tumour growth. This effect was reversed by in vivo pre-treatment with WEB2170. This treatment also reduced tumour growth and modified the microenvironment by reducing PGE2, VEGF and NO production. In B16F10 melanoma, WEB2170 alone or in association with DTIC significantly reduced tumour volume. Survival of the tumour-bearing mice was not affected by WEB2170 treatment but was significantly improved by the combination of DTIC with WEB2170. Tumour microenvironment elements were among the targets of the combination therapy since the relative frequency of COX-2 and galectin-3 positive cells and the microvascular density within the tumour mass were significantly reduced by treatment with WEB2170 or DTIC alone or in combination. Antibodies to PAF-R stained the cells from inside

O6-Methylguanine-DNA methyltransferase protein expression by immunohistochemistry in brain and non-brain systemic tumours: systematic review and meta-analysis of correlation with methylation-specific polymerase chain reaction.

PubMed

Brell, Marta; Ibáñez, Javier; Tortosa, Avelina

2011-01-26

The DNA repair protein O6-Methylguanine-DNA methyltransferase (MGMT) confers resistance to alkylating agents. Several methods have been applied to its analysis, with methylation-specific polymerase chain reaction (MSP) the most commonly used for promoter methylation study, while immunohistochemistry (IHC) has become the most frequently used for the detection of MGMT protein expression. Agreement on the best and most reliable technique for evaluating MGMT status remains unsettled. The aim of this study was to perform a systematic review and meta-analysis of the correlation between IHC and MSP. A computer-aided search of MEDLINE (1950-October 2009), EBSCO (1966-October 2009) and EMBASE (1974-October 2009) was performed for relevant publications. Studies meeting inclusion criteria were those comparing MGMT protein expression by IHC with MGMT promoter methylation by MSP in the same cohort of patients. Methodological quality was assessed by using the QUADAS and STARD instruments. Previously published guidelines were followed for meta-analysis performance. Of 254 studies identified as eligible for full-text review, 52 (20.5%) met the inclusion criteria. The review showed that results of MGMT protein expression by IHC are not in close agreement with those obtained with MSP. Moreover, type of tumour (primary brain tumour vs others) was an independent covariate of accuracy estimates in the meta-regression analysis beyond the cut-off value. Protein expression assessed by IHC alone fails to reflect the promoter methylation status of MGMT. Thus, in attempts at clinical diagnosis the two methods seem to select different groups of patients and should not be used interchangeably.

[Surgical Management of Peritoneal Surface Malignancy with Respect to Tumour Type, Tumour Stage and Individual Tumour Biology].

PubMed

Beckert, S; Struller, F; Grischke, E-M; Glatzle, J; Zieker, D; Königsrainer, A; Königsrainer, I

2016-08-01

Peritoneal tumour dissemination is still considered as a terminal disease. For the last two decades, cytoreductive surgery (CRS) combined with intraoperative hyperthermic chemotherapy (HIPEC) has been popularised by Paul Sugarbaker almost doubling survival in selected patients compared with systemic chemotherapy alone. Nowadays, this particular treatment protocol is available in comprehensive cancer centres with reasonable mortality and morbidity. However, patient selection is still challenging. In general, CRS and HIPEC is indicated in primary peritoneal tumours such as mesothelioma and pseudomyxoma peritonei as well as in peritoneal metastases derived from gastrointestinal malignancies and ovarian cancers. Since systemic tumour spread is uncommon in patients with peritoneal metastases, peritoneal tumour dissemination was defined as localised disease within the "compartment abdomen". However, CRS and HIPEC are only beneficial as long as complete cytoreduction is achieved (CC-0 or CC-1). Histopathological parameters, the Sugarbaker peritoneal carcinomatosis index (PCI) and general condition of the patient have been established as patient selection criteria. In primary peritoneal cancers, individual tumour biology is the predominant criterium for patient selection as opposed to intraabdominal tumour load in peritoneal metastases derived from gastrointestinal cancers. In gastric cancer, CRS and HIPEC should be restricted to synchronous limited disease because of its biological aggressiveness. In patients with free floating cancer cells without macroscopic signs of peritoneal spread, however, CRS and HIPEC following preoperative "neoadjuvant" chemotherapy preserves chances for cure. So far, there is no general recommendation for CRS and HIPEC by clinical practice guidelines. In the recent S3 guideline for treatment of colorectal cancer, however, CRS and HIPEC have been included as possible treatment options. Georg Thieme Verlag KG Stuttgart · New York.

Lysyl oxidase-like-2 promotes tumour angiogenesis and is a potential therapeutic target in angiogenic tumours.

PubMed

Zaffryar-Eilot, Shelly; Marshall, Derek; Voloshin, Tali; Bar-Zion, Avinoam; Spangler, Rhyannon; Kessler, Ofra; Ghermazien, Haben; Brekhman, Vera; Suss-Toby, Edith; Adam, Dan; Shaked, Yuval; Smith, Victoria; Neufeld, Gera

2013-10-01

Lysyl oxidase-like 2 (LOXL2), a secreted enzyme that catalyzes the cross-linking of collagen, plays an essential role in developmental angiogenesis. We found that administration of the LOXL2-neutralizing antibody AB0023 inhibited bFGF-induced angiogenesis in Matrigel plug assays and suppressed recruitment of angiogenesis promoting bone marrow cells. Small hairpin RNA-mediated inhibition of LOXL2 expression or inhibition of LOXL2 using AB0023 reduced the migration and network-forming ability of endothelial cells, suggesting that the inhibition of angiogenesis results from a direct effect on endothelial cells. To examine the effects of AB0023 on tumour angiogenesis, AB0023 was administered to mice bearing tumours derived from SKOV-3 ovarian carcinoma or Lewis lung carcinoma (LLC) cells. AB0023 treatment significantly reduced the microvascular density in these tumours but did not inhibit tumour growth. However, treatment of mice bearing SKOV-3-derived tumours with AB0023 also promoted increased coverage of tumour vessels with pericytes and reduced tumour hypoxia, providing evidence that anti-LOXL2 therapy results in the normalization of tumour blood vessels. In agreement with these data, treatment of mice bearing LLC-derived tumours with AB0023 improved the perfusion of the tumour-associated vessels as determined by ultrasonography. Improved perfusion and normalization of tumour vessels after treatment with anti-angiogenic agents were previously found to improve the delivery of chemotherapeutic agents into tumours and to result in an enhancement of chemotherapeutic efficiency. Indeed, treatment with AB0023 significantly enhanced the anti-tumourigenic effects of taxol. Our results suggest that inhibition of LOXL2 may prove beneficial for the treatment of angiogenic tumours.

Advanced typical and atypical carcinoid tumours of the lung: management recommendations

PubMed Central

Melosky, B.

2018-01-01

Background Neuroendocrine tumours (nets) are classified by site of origin, with lung being the second most common primary site after the gastrointestinal tract. Lung nets are rare and heterogeneous, with varied pathologic and clinical features. Typical and atypical carcinoid tumours are low-grade lung nets which, compared with the more common high-grade nets, are associated with a more favourable prognosis. Still, optimal treatment strategies are lacking. Methods This review concentrates on classification and treatment strategies for metastatic low-grade lung nets, considering both typical and atypical carcinoids. The terminology can be confusing, and an attempt is made to simplify it. Promising results from recent trials that included lung nets are presented and discussed. Finally, guidelines from Europe and North America are discussed, and differences are noted. Results Even within the group of patients with low-grade nets, the presentation, the locations of metastasis, and the speed of progression can be very different. The initial work-up and an understanding of the tumour’s biology are key in making management decisions. Various treatment options—including somatostatin analogs, peptide receptor radioligand therapy, and biologic systemic therapy, specifically with the mtor (mechanistic target of rapamycin) inhibitor everolimus—are now available and are presented in a treatment algorithm. Summary Although lung nets are rare and evidence supporting optimal treatment strategies is lacking, the recent publication of trials that have included patients with lung nets advances evidence-based therapy for these tumours. Many variables have to be considered in managing these tumours that have received little attention. Education for treating physicians is needed.

Comparison of Classification Methods for P300 Brain-Computer Interface on Disabled Subjects

PubMed Central

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

2011-01-01

We report on tests with a mind typing paradigm based on a P300 brain-computer interface (BCI) on a group of amyotrophic lateral sclerosis (ALS), middle cerebral artery (MCA) stroke, and subarachnoid hemorrhage (SAH) patients, suffering from motor and speech disabilities. We investigate the achieved typing accuracy given the individual patient's disorder, and how it correlates with the type of classifier used. We considered 7 types of classifiers, linear as well as nonlinear ones, and found that, overall, one type of linear classifier yielded a higher classification accuracy. In addition to the selection of the classifier, we also suggest and discuss a number of recommendations to be considered when building a P300-based typing system for disabled subjects. PMID:21941530

Deep 3D convolution neural network for CT brain hemorrhage classification

NASA Astrophysics Data System (ADS)

Jnawali, Kamal; Arbabshirani, Mohammad R.; Rao, Navalgund; Patel, Alpen A.

2018-02-01

Intracranial hemorrhage is a critical conditional with the high mortality rate that is typically diagnosed based on head computer tomography (CT) images. Deep learning algorithms, in particular, convolution neural networks (CNN), are becoming the methodology of choice in medical image analysis for a variety of applications such as computer-aided diagnosis, and segmentation. In this study, we propose a fully automated deep learning framework which learns to detect brain hemorrhage based on cross sectional CT images. The dataset for this work consists of 40,367 3D head CT studies (over 1.5 million 2D images) acquired retrospectively over a decade from multiple radiology facilities at Geisinger Health System. The proposed algorithm first extracts features using 3D CNN and then detects brain hemorrhage using the logistic function as the last layer of the network. Finally, we created an ensemble of three different 3D CNN architectures to improve the classification accuracy. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve of the ensemble of three architectures was 0.87. Their results are very promising considering the fact that the head CT studies were not controlled for slice thickness, scanner type, study protocol or any other settings. Moreover, the proposed algorithm reliably detected various types of hemorrhage within the skull. This work is one of the first applications of 3D CNN trained on a large dataset of cross sectional medical images for detection of a critical radiological condition

Infective complications following tumour endoprosthesis surgery for bone and soft tissue tumours.

PubMed

Peel, T; May, D; Buising, K; Thursky, K; Slavin, M; Choong, P

2014-09-01

This study aims to describe the incidence of infective complications, including tumour endoprosthesis infection, in a cohort of patients undergoing tumour endoprosthesis surgery in Victoria, Australia. This retrospective cohort study was performed over 15 years (January 1996-December 2010). 121 patients underwent tumour endoprosthesis surgery during the study period. Patients were followed for a median of 34 months (interquartile range [IQR] 17, 80). Overall, 34 patients (28%) experienced infective complications including: bacteraemia in 19 patients (16%) and tumour endoprosthesis infection in 17 (14%). The majority of patients with early and late acute infections (haematogenous) were managed with debridement and retention of the prosthesis in addition to biofilm-active antibiotics. Late chronic infections were predominantly managed by exchange of the prosthesis. The overall success rate of treatment was 71%. The success rate for debridement and retention was 75% compared with 67% for exchange procedures. There is a significant rate of infective complications following tumour endoprosthesis surgery including 14% of patients experiencing infection involving the tumour endoprosthesis. This study is the first to report on outcomes from debridement and retention of the prosthesis; which had comparable success rates to other treatment modalities. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Id1 suppresses anti-tumour immune responses and promotes tumour progression by impairing myeloid cell maturation.

PubMed

Papaspyridonos, Marianna; Matei, Irina; Huang, Yujie; do Rosario Andre, Maria; Brazier-Mitouart, Helene; Waite, Janelle C; Chan, April S; Kalter, Julie; Ramos, Ilyssa; Wu, Qi; Williams, Caitlin; Wolchok, Jedd D; Chapman, Paul B; Peinado, Hector; Anandasabapathy, Niroshana; Ocean, Allyson J; Kaplan, Rosandra N; Greenfield, Jeffrey P; Bromberg, Jacqueline; Skokos, Dimitris; Lyden, David

2015-04-29

A central mechanism of tumour progression and metastasis involves the generation of an immunosuppressive 'macroenvironment' mediated in part through tumour-secreted factors. Here we demonstrate that upregulation of the Inhibitor of Differentiation 1 (Id1), in response to tumour-derived factors, such as TGFβ, is responsible for the switch from dendritic cell (DC) differentiation to myeloid-derived suppressor cell expansion during tumour progression. Genetic inactivation of Id1 largely corrects the myeloid imbalance, whereas Id1 overexpression in the absence of tumour-derived factors re-creates it. Id1 overexpression leads to systemic immunosuppression by downregulation of key molecules involved in DC differentiation and suppression of CD8 T-cell proliferation, thus promoting primary tumour growth and metastatic progression. Furthermore, advanced melanoma patients have increased plasma TGFβ levels and express higher levels of ID1 in myeloid peripheral blood cells. This study reveals a critical role for Id1 in suppressing the anti-tumour immune response during tumour progression and metastasis.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Calcified miliary brain metastases with mitochondrial inclusion bodies.

PubMed Central

Yamazaki, T; Harigaya, Y; Noguchi, O; Okamoto, K; Hirai, S

1993-01-01

A patient with calcified miliary brain metastases from lung adenocarcinoma is reported. Electron microscopic study of the metastatic tumour cells showed membranous inclusion bodies in mitochondria. Images PMID:8429312

Effects of an alveolar recruitment maneuver on subdural pressure, brain swelling, and mean arterial pressure in patients undergoing supratentorial tumour resection: a randomized crossover study.

PubMed

Flexman, Alana M; Gooderham, Peter A; Griesdale, Donald E; Argue, Ruth; Toyota, Brian

2017-06-01

Although recruitment maneuvers have been advocated as part of a lung protective ventilation strategy, their effects on cerebral physiology during elective neurosurgery are unknown. Our objectives were to determine the effects of an alveolar recruitment maneuver on subdural pressure (SDP), brain relaxation score (BRS), and cerebral perfusion pressure among patients undergoing supratentorial tumour resection. In this prospective crossover study, patients scheduled for resection of a supratentorial brain tumour were randomized to undergo either a recruitment maneuver (30 cm of water for 30 sec) or a "sham" maneuver (5 cm of water for 30 sec), followed by the alternative intervention after a 90-sec equilibration period. Subdural pressure was measured through a dural perforation following opening of the cranium. Subdural pressure and mean arterial pressure (MAP) were recorded continuously. The blinded neurosurgeon provided a BRS at baseline and at the end of each intervention. During each treatment, the changes in SDP, BRS, and MAP were compared. Twenty-one patients underwent the study procedure. The increase in SDP was higher during the recruitment maneuver than during the sham maneuver (difference, 3.9 mmHg; 95% confidence interval [CI], 2.2 to 5.6; P < 0.001). Mean arterial pressure decreased further in the recruitment maneuver than in the sham maneuver (difference, -9.0 mmHg; 95% CI, -12.5 to -5.6; P < 0.001). Cerebral perfusion pressure decreased 14 mmHg (95% CI, 4 to 24) during the recruitment maneuver. The BRS did not change with either maneuver. Our results suggest that recruitment maneuvers increase subdural pressure and reduce cerebral perfusion pressure, although the clinical importance of these findings is thus far unknown. This trial was registered with ClinicalTrials.gov, NCT02093117.

[Why are carotid glomus tumours dangerous?].

PubMed

Certík, B; Třeška, V

2014-10-01

Carotid body tumours are rare, usually benign tumours. The dangerous nature of carotid body tumours is due to their hypervascularization and the intimate relationship to cervical arteries and cranial nerves. In a case report, the authors document that misdiagnosis and efforts to remove or obtain a biopsy of the tumour outside vascular centres can be more dangerous for the patient than the nature of the tumour itself.

Tumours of bones and joints

PubMed Central

Misdorp, W.; Van Der Heul, R. O.

1976-01-01

Tumours of bones and joints are not infrequent in dogs but are rare in other domestic animals. In the dog, most bone tumours are malignant; osteosarcomas are by far the most frequently encountered tumours, especially in giant breeds and boxers. The following main categories of bone tumour are described: bone-forming, cartilage-forming, giant cell, marrow, vascular, miscellaneous, metastatic, unclassified, and tumour-like lesions. The tumours of joints and related structures are classified as synovial sarcomas, fibroxanthomas, and malignant giant cell tumour of soft tissues. ImagesFig. 21Fig. 22Fig. 23Fig. 24Fig. 17Fig. 18Fig. 19Fig. 20Fig. 29Fig. 30Fig. 31Fig. 32Fig. 33Fig. 34Fig. 35Fig. 36Fig. 25Fig. 26Fig. 27Fig. 28Fig. 1Fig. 2Fig. 3Fig. 4Fig. 37Fig. 38Fig. 39Fig. 40Fig. 5Fig. 6Fig. 7Fig. 8Fig. 13Fig. 14Fig. 15Fig. 16Fig. 9Fig. 10Fig. 11Fig. 12 PMID:1086157

Training for planning tumour resection: augmented reality and human factors.

PubMed

Abhari, Kamyar; Baxter, John S H; Chen, Elvis C S; Khan, Ali R; Peters, Terry M; de Ribaupierre, Sandrine; Eagleson, Roy

2015-06-01

Planning surgical interventions is a complex task, demanding a high degree of perceptual, cognitive, and sensorimotor skills to reduce intra- and post-operative complications. This process requires spatial reasoning to coordinate between the preoperatively acquired medical images and patient reference frames. In the case of neurosurgical interventions, traditional approaches to planning tend to focus on providing a means for visualizing medical images, but rarely support transformation between different spatial reference frames. Thus, surgeons often rely on their previous experience and intuition as their sole guide is to perform mental transformation. In case of junior residents, this may lead to longer operation times or increased chance of error under additional cognitive demands. In this paper, we introduce a mixed augmented-/virtual-reality system to facilitate training for planning a common neurosurgical procedure, brain tumour resection. The proposed system is designed and evaluated with human factors explicitly in mind, alleviating the difficulty of mental transformation. Our results indicate that, compared to conventional planning environments, the proposed system greatly improves the nonclinicians' performance, independent of the sensorimotor tasks performed ( ). Furthermore, the use of the proposed system by clinicians resulted in a significant reduction in time to perform clinically relevant tasks ( ). These results demonstrate the role of mixed-reality systems in assisting residents to develop necessary spatial reasoning skills needed for planning brain tumour resection, improving patient outcomes.

MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets

PubMed Central

Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J.

2017-01-01

Abstract Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. PMID:28472340

Carcinoma-astrocyte gap junctions promote brain metastasis by cGAMP transfer.

PubMed

Chen, Qing; Boire, Adrienne; Jin, Xin; Valiente, Manuel; Er, Ekrem Emrah; Lopez-Soto, Alejandro; Jacob, Leni; Patwa, Ruzeen; Shah, Hardik; Xu, Ke; Cross, Justin R; Massagué, Joan

2016-05-26

Brain metastasis represents a substantial source of morbidity and mortality in various cancers, and is characterized by high resistance to chemotherapy. Here we define the role of the most abundant cell type in the brain, the astrocyte, in promoting brain metastasis. We show that human and mouse breast and lung cancer cells express protocadherin 7 (PCDH7), which promotes the assembly of carcinoma-astrocyte gap junctions composed of connexin 43 (Cx43). Once engaged with the astrocyte gap-junctional network, brain metastatic cancer cells use these channels to transfer the second messenger cGAMP to astrocytes, activating the STING pathway and production of inflammatory cytokines such as interferon-α (IFNα) and tumour necrosis factor (TNF). As paracrine signals, these factors activate the STAT1 and NF-κB pathways in brain metastatic cells, thereby supporting tumour growth and chemoresistance. The orally bioavailable modulators of gap junctions meclofenamate and tonabersat break this paracrine loop, and we provide proof-of-principle that these drugs could be used to treat established brain metastasis.

Role of 5-ALA in improving extent of tumour resection in patients with Glioblastoma Multiforme.

PubMed

Waqas, Muhammad; Khan, Inamullah; Shamim, Muhammad Shahzad

2017-10-01

Goal of surgery for patients with Glioblastoma Multiforme (GBM) is gross total resection with no new neurological deficits. Surgical resection is often restricted due the difficulty in differentiating the tumour from surrounding normal brain using either naked eye, or standard intra-operative white light microscopy. GBM uptakes orally administered 5-ALA becomes fluorescent when viewed by a special light, and this property has been used to improve intra-operative tumour identification. This technique should therefore allow better extent of tumour resection. The hypothesis has been tested through several studies and even though most studies are of low quality, they strongly favour the use of 5- ALA in improving the extent of resection when compared to white light microscopy. A systematic review on the topic had a similar conclusion. Few studies have also hinted on a high false negative rate with the use of this technique..

Bilateral multifocal Warthin tumours.

PubMed

Deveer, Mehmet; Sahan, Murat; Sivrioglu, Ali Kemal; Celik, Ozgür Ilhan

2013-05-22

Warthin tumour, also known as papillary cystadenoma lymphomatosum, is the second most frequent benign tumour of the parotid gland after pleomorphic adenoma. A 57-year-old man was referred to our hospital with bilateral buccal masses without pain. He presented with a 1-year history of the condition and stated that growth of the mass has accelerated during the last 6 months. Ultrasonography examination showed two heterogeneous solid masses. Axial contrast-enhanced CT image revealed bilateral heterogeneous solid masses. The masses showed enhancement after contrast administration (95 HU). Fine needle aspiration cytology was recommended for further analysis and typical benign features of Warthin tumour was obtained. Right parotid gland including the masses was resected completely. 5 weeks later superficial parotidectomy was performed to the left parotid gland. Histological examination revealed cystic tumour in the parenchyma of parotid gland, composed of prominent lymphoid stroma and large epithelial cells with oncocytic features covering it consistent with Warthin tumour.

Bilateral multifocal Warthin tumours

PubMed Central

Deveer, Mehmet; Sahan, Murat; Sivrioglu, Ali Kemal; İlhan Celik, Özgür

2013-01-01

Warthin tumour, also known as papillary cystadenoma lymphomatosum, is the second most frequent benign tumour of the parotid gland after pleomorphic adenoma. A 57-year-old man was referred to our hospital with bilateral buccal masses without pain. He presented with a 1-year history of the condition and stated that growth of the mass has accelerated during the last 6 months. Ultrasonography examination showed two heterogeneous solid masses. Axial contrast-enhanced CT image revealed bilateral heterogeneous solid masses. The masses showed enhancement after contrast administration (95 HU). Fine needle aspiration cytology was recommended for further analysis and typical benign features of Warthin tumour was obtained. Right parotid gland including the masses was resected completely. 5 weeks later superficial parotidectomy was performed to the left parotid gland. Histological examination revealed cystic tumour in the parenchyma of parotid gland, composed of prominent lymphoid stroma and large epithelial cells with oncocytic features covering it consistent with Warthin tumour. PMID:23704438

Boosting Classification Accuracy of Diffusion MRI Derived Brain Networks for the Subtypes of Mild Cognitive Impairment Using Higher Order Singular Value Decomposition

PubMed Central

Zhan, L.; Liu, Y.; Zhou, J.; Ye, J.; Thompson, P.M.

2015-01-01

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and Alzheimer's disease (AD), and around 10-15% of people with MCI develop AD each year. More recently, MCI has been further subdivided into early and late stages, and there is interest in identifying sensitive brain imaging biomarkers that help to differentiate stages of MCI. Here, we focused on anatomical brain networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying early versus late MCI. PMID:26413202

Supervised novelty detection in brain tissue classification with an application to white matter hyperintensities

NASA Astrophysics Data System (ADS)

Kuijf, Hugo J.; Moeskops, Pim; de Vos, Bob D.; Bouvy, Willem H.; de Bresser, Jeroen; Biessels, Geert Jan; Viergever, Max A.; Vincken, Koen L.

2016-03-01

Novelty detection is concerned with identifying test data that differs from the training data of a classifier. In the case of brain MR images, pathology or imaging artefacts are examples of untrained data. In this proof-of-principle study, we measure the behaviour of a classifier during the classification of trained labels (i.e. normal brain tissue). Next, we devise a measure that distinguishes normal classifier behaviour from abnormal behavior that occurs in the case of a novelty. This will be evaluated by training a kNN classifier on normal brain tissue, applying it to images with an untrained pathology (white matter hyperintensities (WMH)), and determine if our measure is able to identify abnormal classifier behaviour at WMH locations. For our kNN classifier, behaviour is modelled as the mean, median, or q1 distance to the k nearest points. Healthy tissue was trained on 15 images; classifier behaviour was trained/tested on 5 images with leave-one-out cross-validation. For each trained class, we measure the distribution of mean/median/q1 distances to the k nearest point. Next, for each test voxel, we compute its Z-score with respect to the measured distribution of its predicted label. We consider a Z-score >=4 abnormal behaviour of the classifier, having a probability due to chance of 0.000032. Our measure identified >90% of WMH volume and also highlighted other non-trained findings. The latter being predominantly vessels, cerebral falx, brain mask errors, choroid plexus. This measure is generalizable to other classifiers and might help in detecting unexpected findings or novelties by measuring classifier behaviour.

Suppression of tumour growth by orally administered osteopontin is accompanied by alterations in tumour blood vessels.

PubMed

Rittling, S R; Wejse, P L; Yagiz, K; Warot, G A; Hui, T

2014-03-04

The integrin-binding protein osteopontin is strongly associated with tumour development, yet is an abundant dietary component as a constituent of human and bovine milk. Therefore, we tested the effect of orally administered osteopontin (o-OPN) on the development of subcutaneous tumours in mice. Bovine milk osteopontin was administered in drinking water to tumour-bearing immune-competent mice. Tumour growth, proliferation, necrosis, apoptosis and blood vessel size and number were measured. Expression of the α₉ integrin was determined. o-OPN suppressed tumour growth, increased the extent of necrosis, and induced formation of abnormally large blood vessels. Anti-OPN reactivity detected in the plasma of OPN-null mice fed OPN suggested that tumour-blocking peptides were absorbed during digestion, but the o-OPN effect was likely distinct from that of an RGD peptide. Expression of the α₉ integrin was detected on both tumour cells and blood vessels. Potential active peptides from the α₉ binding site of OPN were identified by mass spectrometry following in vitro digestion, and injection of these peptides suppressed tumour growth. These results suggest that peptides derived from o-OPN are absorbed and interfere with tumour growth and normal vessel development. o-OPN-derived peptides that target the α₉ integrin are likely involved.

[From new genetic and histological classifications to direct treatment].

PubMed

Compérat, Eva; Furudoï, Adeline; Varinot, Justine; Rioux-Leclerq, Nathalie

2016-08-01

The most important criterion for optimal cancer treatment is a correct classification of the tumour. During the last three years, several very important progresses have been made with a better definition of urothelial carcinoma (UC), especially from a molecular point of view. We start having a global understanding of UC, although many details are still not completely understood. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Ciliated muconodular papillary tumour of the lung: a newly defined low-grade malignant tumour.