International hermelin brain tumor symposium on matricellular proteins in normal and cancer cell-matrix interactions

The second of the Hermelin Brain Tumor Center Symposia was held once again at Henry Ford Hospital in Detroit, Michigan on October 24th and 25th, 2003. A public conference was held on the 24th while a closed-door session took place on the 25th. The purpose of these symposia is to bring together experts in a particular field of study with the aim to share information with each other and the public, but then to meet privately to present novel data, hold discussions, and share concepts. While the interaction is intended to benefit all involved, the incentive is the expectation that the shared information will aid researchers at the Hermelin Brain Tumor Center in their quest to identify potential therapeutic targets and explore translational therapeutic strategies for the treatment of patients suffering nervous system tumors...

Primary brain tumor patients’ supportive care needs and multidisciplinary rehabilitation, community and psychosocial support services: Awareness, referral and utilization

Primary brain tumors are associated with significant physical, cognitive and psychosocial changes. Although treatment guidelines recommend offering multidisciplinary rehabilitation and support services to address patients’ residual deficits, the extent to which patients access such services is unclear. This study aimed to assess patients’ supportive care needs early after diagnosis, and quantify service awareness, referral and utilization. A population-based sample of 40 adults recently diagnosed with primary brain tumors was recruited through the Queensland Cancer Registry, representing 18.9% of the eligible population of 203 patients. Patients or carer proxies completed surveys of supportive care needs at baseline (approximately three months after diagnosis) and three months later. Descriptive statistics summarized needs and service utilization, and linear regression identified predictors of service use. Unmet supportive care needs were highest at baseline for all domains, and highest for the physical and psychological needs domains at each time point. At follow-up, participants reported awareness of, referral to, and use of 32 informational, support, health professional or practical services. All or almost all participants were aware of at least one informational (100%), health professional (100%), support (97%) or practical service (94%). Participants were most commonly aware of speech therapists (97%), physiotherapists (94%) and diagnostic information from the internet (88%). Clinician referrals were most commonly made to physiotherapists (53%), speech therapists (50%) and diagnostic information booklets (44%), and accordingly, participants most commonly used physiotherapists (56%), diagnostic information booklets (47%), diagnostic information from the internet (47%), and speech therapists (43%). Comparatively low referral to and use of psychosocial services may limit patients’ abilities to cope with their condition and the changes they experience.

Brain tumor and brain endothelial cells' response to ionizing radiation and phytochemical treatments

Le glioblastome multiforme (GBM) représente la tumeur cérébrale primaire la plus agressive et la plus vascularisée chez l’adulte. La survie médiane après le diagnostic est de moins d’un an en l’absence de traitement. Malheureusement, 90% des patients traités avec de la radiothérapie après la résection chirurgicale d’un GBM développent une récidive tumorale. Récemment, le traitement des GBM avec radiothérapie et témozolomide, un agent reconnu pour ses propriétés antiangiogéniques, a permis de prolonger la survie médiane à 14,6 mois. Des efforts sont déployés pour identifier des substances naturelles capables d’inhiber, de retarder ou de renverser le processus de carcinogenèse. Epigallocatechin-3-gallate (EGCG), un polyphénol retrouvé dans le thé vert, est reconnu pour ses propriétés anticancéreuses et antiangiogéniques. L’EGCG pourrait sensibiliser les cellules tumorales cérébrales et les cellules endothéliales dérivées des tumeurs aux traitements conventionnels. Le chapitre II décrit la première partie de ce projet de doctorat. Nous avons tenté de déterminer si l’EGCG pourrait sensibiliser la réponse des GBM à l’irradiation (IR) et si des marqueurs moléculaires spécifiques sont impliqués. Nous avons documenté que les cellules U-87 étaient relativement radiorésistantes et que Survivin, une protéine inhibitrice de l’apoptose, pourrait être impliquée dans la radiorésistance des GBM. Aussi, nous avons démontré que le pré-traitement des cellules U-87 avec de l’EGCG pourrait annuler l’effet cytoprotecteur d’une surexpression de Survivin et potentialiser l’effet cytoréducteur de l’IR. Au chapitre III, nous avons caractérisé l’impact de l’IR sur la survie de cellules endothéliales microvasculaires cérébrales humaines (HBMEC) et nous avons déterminé si l’EGCG pouvait optimiser cet effet. Bien que les traitements individuels avec l’EGCG et l’IR diminuaient la survie des HBMEC, le traitement combiné diminuait de façon synergique la survie cellulaire. Nous avons documenté que le traitement combiné augmentait la mort cellulaire, plus spécifiquement la nécrose. Au chapitre IV, nous avons investigué l’impact de l’IR sur les fonctions angiogéniques des HBMEC résistantes à l’IR, notamment la prolifération cellulaire, la migration cellulaire en présence de facteurs de croissance dérivés des tumeurs cérébrales, et la capacité de tubulogenèse. La voie de signalisation des Rho a aussi été étudiée en relation avec les propriétés angiogéniques des HBMEC radiorésistantes. Nos données suggèrent que l’IR altère significativement les propriétés angiogéniques des HBMEC. La réponse aux facteurs importants pour la croissance tumorale et l’angiogenèse ainsi que la tubulogenèse sont atténuées dans ces cellules. En conclusion, ce projet de doctorat confirme les propriétés cytoréductrices de l’IR sur les gliomes malins et propose un nouveau mécanisme pour expliquer la radiorésistance des GBM. Ce projet documente pour la première fois l’effet cytotoxique de l’IR sur les HBMEC. Aussi, ce projet reconnaît l’existence de HBMEC radiorésistantes et caractérise leurs fonctions angiogéniques altérées. La combinaison de molécules naturelles anticancéreuses et antiangiogéniques telles que l’EGCG avec de la radiothérapie pourrait améliorer l’effet de l’IR sur les cellules tumorales et sur les cellules endothéliales associées, possiblement en augmentant la mort cellulaire. Cette thèse supporte l’intégration de nutriments avec propriétés anticancéreuses et antiangiogéniques dans le traitement des gliomes malins pour sensibiliser les cellules tumorales et endothéliales aux traitements conventionnels.

Brain Tumor, Mood Disorder and Encephalopathy

Brain Tumor, Mood Disorder and EncephalopathyWe report a case of a patient was 65 years old, who was admitted with neurologic symptoms ill-defined by imaging findings that initial meningioma wing of the sphenoid, tumor resection, is performed. She presented torpid evolution, progressive neurological deterioration, until her death.

Antiproliferative activity of Eremanthus crotonoides extracts and centratherin demonstrated in brain tumor cell lines

The genus Eremanthus is recognized by the predominance of sesquiterpene lactones from the furanoheliangolide type, a class of substances extensively tested against cancer cell lines. Thus, the species E. crotonoides (DC.) Sch. Bip., Asteraceae, obtained on "restinga" vegetation was evaluated against U251 and U87-MG glioma cell lines using the MTT colorimetric assay. Dichloromethane fraction was cytotoxic to both glioblastoma multiforme cell lines. We then conducted UPLC-PDA-ESI-MS/MS analysis of the dichloromethane fraction, which allowed the identification of the sesquiterpene lactones centratherin and goyazensolide. The isolation of centratherin was performed using chromatographic techniques and the identification of this substance was confirmed according to NMR data. Cytotoxic activity of centratherin alone was also evaluated against both U251 and U87-MG cells, which showed IC50 values comparable with those obtained for the commercial anticancer drug doxorubicin. All the tested samples showed cytotoxic activity against glioblastoma multiforme cells which suggests that E. crotonoides extracts may be important sources of antiproliferative substances and that the centratherin may serve as prototype for developing new antiglioblastoma drugs.

Computerized brain tumor segmentation in magnetic resonance imaging

OBJECTIVE: To propose an automatic brain tumor segmentation system. METHODS: The system used texture characteristics as its main source of information for segmentation. RESULTS: The mean correct match was 94% of correspondence between the segmented areas and ground truth. CONCLUSION: Final results showed that the proposed system was able to find and delimit tumor areas without requiring any user interaction.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

New-onset epilepsy: considerations for initial and follow-up MRI to detect brain tumor

Seizures are often the presenting symptoms of a cerebral tumor and may precede its diagnosis by many years. The article under evaluation searched two large English registries for patients admitted for new-onset epilepsy. The risk of subsequently being diagnosed with a malignant brain tumor was found to be 26-fold higher compared with controls, persisted over many years and was accentuated in young patients. Recently, surgical advances have led to a significant decrease in surgical morbidities, making surgery the first treatment option for gliomas, especially low-grade gliomas. This paradigm shift warrants a consequent diagnostic workup (MRI) in patients at risk for low-grade glioma - that is, patients with new-onset epilepsy. The study is discussed in the context of the ongoing debate on neuroimaging after new-onset epilepsy.

A survey of MRI-based medical image analysis for brain tumor studies

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Characterization of the 9L gliosarcoma implanted in the Fischer rat: an orthotopic model for a grade IV brain tumor.

Among rodent models for brain tumors, the 9L gliosarcoma is one of the most widely used. Our 9L-European Synchrotron Radiation Facility (ESRF) model was developed from cells acquired at the Brookhaven National Laboratory (NY, USA) in 1997 and implanted in the right caudate nucleus of syngeneic Fisher rats. It has been largely used by the user community of the ESRF during the last decade, for imaging, radiotherapy, and chemotherapy, including innovative treatments based on particular irradiation techniques and/or use of new drugs. This work presents a detailed study of its characteristics, assessed by magnetic resonance imaging (MRI), histology, immunohistochemistry, and cytogenetic analysis. The data used for this work were from rats sampled in six experiments carried out over a 3-year period in our lab (total number of rats = 142). The 9L-ESRF tumors were induced by a stereotactic inoculation of 10(4) 9L cells in the right caudate nucleus of the brain. The assessment of vascular parameters was performed by MRI (blood volume fraction and vascular size index) and by immunostaining of vessels (rat endothelial cell antigen-1 and type IV collagen). Immunohistochemistry and regular histology were used to describe features such as tumor cell infiltration, necrosis area, nuclear pleomorphism, cellularity, mitotic characteristics, leukocytic infiltration, proliferation, and inflammation. Moreover, for each of the six experiments, the survival of the animals was assessed and related to the tumor growth observed by MRI or histology. Additionally, the cytogenetic status of the 9L cells used at ESRF lab was investigated by comparative genomics hybridization analysis. Finally, the response of the 9L-ESRF tumor to radiotherapy was estimated by plotting the survival curves after irradiation. The median survival time of 9L-ESRF tumor-bearing rats was highly reproducible (19-20 days). The 9L-ESRF tumors presented a quasi-exponential growth, were highly vascularized with a high cellular density and a high proliferative index, accompanied by signs of inflammatory responses. We also report an infiltrative pattern which is poorly observed on conventional 9 L tumor. The 9L-ESRF cells presented some cytogenetic specificities such as altered regions including CDK4, CDKN2A, CDKN2B, and MDM2 genes. Finally, the lifespan of 9L-ESRF tumor-bearing rats was enhanced up to 28, 35, and 45 days for single doses of 10, 20, and 2 × 20 Gy, respectively. First, this report describes an animal model that is used worldwide. Second, we describe few features typical of our model if compared to other 9L models worldwide. Altogether, the 9L-ESRF tumor model presents characteristics close to the human high-grade gliomas such as high proliferative capability, high vascularization and a high infiltrative pattern. Its response to radiotherapy demonstrates its potential as a tool for innovative radiotherapy protocols.