Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry

PubMed Central

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-01-01

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83–0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments. PMID:27001047

Brain tumor segmentation with Vander Lugt correlator based active contour.

PubMed

Essadike, Abdelaziz; Ouabida, Elhoussaine; Bouzid, Abdenbi

2018-07-01

The manual segmentation of brain tumors from medical images is an error-prone, sensitive, and time-absorbing process. This paper presents an automatic and fast method of brain tumor segmentation. In the proposed method, a numerical simulation of the optical Vander Lugt correlator is used for automatically detecting the abnormal tissue region. The tumor filter, used in the simulated optical correlation, is tailored to all the brain tumor types and especially to the Glioblastoma, which considered to be the most aggressive cancer. The simulated optical correlation, computed between Magnetic Resonance Images (MRI) and this filter, estimates precisely and automatically the initial contour inside the tumorous tissue. Further, in the segmentation part, the detected initial contour is used to define an active contour model and presenting the problematic as an energy minimization problem. As a result, this initial contour assists the algorithm to evolve an active contour model towards the exact tumor boundaries. Equally important, for a comparison purposes, we considered different active contour models and investigated their impact on the performance of the segmentation task. Several images from BRATS database with tumors anywhere in images and having different sizes, contrast, and shape, are used to test the proposed system. Furthermore, several performance metrics are computed to present an aggregate overview of the proposed method advantages. The proposed method achieves a high accuracy in detecting the tumorous tissue by a parameter returned by the simulated optical correlation. In addition, the proposed method yields better performance compared to the active contour based methods with the averages of Sensitivity=0.9733, Dice coefficient = 0.9663, Hausdroff distance = 2.6540, Specificity = 0.9994, and faster with a computational time average of 0.4119 s per image. Results reported on BRATS database reveal that our proposed system improves over the recently published state-of-the-art methods in brain tumor detection and segmentation. Copyright © 2018 Elsevier B.V. All rights reserved.

Computer assisted diagnostic system in tumor radiography.

PubMed

Faisal, Ahmed; Parveen, Sharmin; Badsha, Shahriar; Sarwar, Hasan; Reza, Ahmed Wasif

2013-06-01

An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.

Tumor growth model for atlas based registration of pathological brain MR images

NASA Astrophysics Data System (ADS)

Moualhi, Wafa; Ezzeddine, Zagrouba

2015-02-01

The motivation of this work is to register a tumor brain magnetic resonance (MR) image with a normal brain atlas. A normal brain atlas is deformed in order to take account of the presence of a large space occupying tumor. The method use a priori model of tumor growth assuming that the tumor grows in a radial way from a starting point. First, an affine transformation is used in order to bring the patient image and the brain atlas in a global correspondence. Second, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed combining a method derived from optical flow principles and a model for tumor growth (MTG). Results show that an automatic segmentation method of brain structures in the presence of large deformation can be provided.

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

PubMed

Pereira, Sergio; Pinto, Adriano; Alves, Victor; Silva, Carlos A

2016-05-01

Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3 ×3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0.88, 0.83, 0.77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0.78, 0.65, and 0.75 for the complete, core, and enhancing regions, respectively.

Patient-specific model-based segmentation of brain tumors in 3D intraoperative ultrasound images.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Lindner, Dirk; Arlt, Felix; Ituna-Yudonago, Jean Fulbert; Chalopin, Claire

2018-03-01

Intraoperative ultrasound (iUS) imaging is commonly used to support brain tumor operation. The tumor segmentation in the iUS images is a difficult task and still under improvement because of the low signal-to-noise ratio. The success of automatic methods is also limited due to the high noise sensibility. Therefore, an alternative brain tumor segmentation method in 3D-iUS data using a tumor model obtained from magnetic resonance (MR) data for local MR-iUS registration is presented in this paper. The aim is to enhance the visualization of the brain tumor contours in iUS. A multistep approach is proposed. First, a region of interest (ROI) based on the specific patient tumor model is defined. Second, hyperechogenic structures, mainly tumor tissues, are extracted from the ROI of both modalities by using automatic thresholding techniques. Third, the registration is performed over the extracted binary sub-volumes using a similarity measure based on gradient values, and rigid and affine transformations. Finally, the tumor model is aligned with the 3D-iUS data, and its contours are represented. Experiments were successfully conducted on a dataset of 33 patients. The method was evaluated by comparing the tumor segmentation with expert manual delineations using two binary metrics: contour mean distance and Dice index. The proposed segmentation method using local and binary registration was compared with two grayscale-based approaches. The outcomes showed that our approach reached better results in terms of computational time and accuracy than the comparative methods. The proposed approach requires limited interaction and reduced computation time, making it relevant for intraoperative use. Experimental results and evaluations were performed offline. The developed tool could be useful for brain tumor resection supporting neurosurgeons to improve tumor border visualization in the iUS volumes.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

PubMed

Cui, Shaoguo; Mao, Lei; Jiang, Jingfeng; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice.

Patient-specific semi-supervised learning for postoperative brain tumor segmentation.

PubMed

Meier, Raphael; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2014-01-01

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Multifractal modeling, segmentation, prediction, and statistical validation of posterior fossa tumors

NASA Astrophysics Data System (ADS)

Islam, Atiq; Iftekharuddin, Khan M.; Ogg, Robert J.; Laningham, Fred H.; Sivakumar, Bhuvaneswari

2008-03-01

In this paper, we characterize the tumor texture in pediatric brain magnetic resonance images (MRIs) and exploit these features for automatic segmentation of posterior fossa (PF) tumors. We focus on PF tumor because of the prevalence of such tumor in pediatric patients. Due to varying appearance in MRI, we propose to model the tumor texture with a multi-fractal process, such as a multi-fractional Brownian motion (mBm). In mBm, the time-varying Holder exponent provides flexibility in modeling irregular tumor texture. We develop a detailed mathematical framework for mBm in two-dimension and propose a novel algorithm to estimate the multi-fractal structure of tissue texture in brain MRI based on wavelet coefficients. This wavelet based multi-fractal feature along with MR image intensity and a regular fractal feature obtained using our existing piecewise-triangular-prism-surface-area (PTPSA) method, are fused in segmenting PF tumor and non-tumor regions in brain T1, T2, and FLAIR MR images respectively. We also demonstrate a non-patient-specific automated tumor prediction scheme based on these image features. We experimentally show the tumor discriminating power of our novel multi-fractal texture along with intensity and fractal features in automated tumor segmentation and statistical prediction. To evaluate the performance of our tumor prediction scheme, we obtain ROCs and demonstrate how sharply the curves reach the specificity of 1.0 sacrificing minimal sensitivity. Experimental results show the effectiveness of our proposed techniques in automatic detection of PF tumors in pediatric MRIs.

Brain's tumor image processing using shearlet transform

NASA Astrophysics Data System (ADS)

Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin; Korneeva, Anna; Kruglyakov, Alexey; Legalov, Alexander; Romanenko, Alexey; Zotin, Alexander

2017-09-01

Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

SU-C-BRA-06: Automatic Brain Tumor Segmentation for Stereotactic Radiosurgery Applications

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

Liu, Y; Stojadinovic, S; Jiang, S

Purpose: Stereotactic radiosurgery (SRS), which delivers a potent dose of highly conformal radiation to the target in a single fraction, requires accurate tumor delineation for treatment planning. We present an automatic segmentation strategy, that synergizes intensity histogram thresholding, super-voxel clustering, and level-set based contour evolving methods to efficiently and accurately delineate SRS brain tumors on contrast-enhance T1-weighted (T1c) Magnetic Resonance Images (MRI). Methods: The developed auto-segmentation strategy consists of three major steps. Firstly, tumor sites are localized through 2D slice intensity histogram scanning. Then, super voxels are obtained through clustering the corresponding voxels in 3D with reference to the similaritymore » metrics composited from spatial distance and intensity difference. The combination of the above two could generate the initial contour surface. Finally, a localized region active contour model is utilized to evolve the surface to achieve the accurate delineation of the tumors. The developed method was evaluated on numerical phantom data, synthetic BRATS (Multimodal Brain Tumor Image Segmentation challenge) data, and clinical patients’ data. The auto-segmentation results were quantitatively evaluated by comparing to ground truths with both volume and surface similarity metrics. Results: DICE coefficient (DC) was performed as a quantitative metric to evaluate the auto-segmentation in the numerical phantom with 8 tumors. DCs are 0.999±0.001 without noise, 0.969±0.065 with Rician noise and 0.976±0.038 with Gaussian noise. DC, NMI (Normalized Mutual Information), SSIM (Structural Similarity) and Hausdorff distance (HD) were calculated as the metrics for the BRATS and patients’ data. Assessment of BRATS data across 25 tumor segmentation yield DC 0.886±0.078, NMI 0.817±0.108, SSIM 0.997±0.002, and HD 6.483±4.079mm. Evaluation on 8 patients with total 14 tumor sites yield DC 0.872±0.070, NMI 0.824±0.078, SSIM 0.999±0.001, and HD 5.926±6.141mm. Conclusion: The developed automatic segmentation strategy, which yields accurate brain tumor delineation in evaluation cases, is promising for its application in SRS treatment planning.« less

Improved spatial coverage for brain 3D PRESS MRSI by automatic placement of outer-volume suppression saturation bands.

PubMed

Ozhinsky, Eugene; Vigneron, Daniel B; Nelson, Sarah J

2011-04-01

To develop a technique for optimizing coverage of brain 3D (1) H magnetic resonance spectroscopic imaging (MRSI) by automatic placement of outer-volume suppression (OVS) saturation bands (sat bands) and to compare the performance for point-resolved spectroscopic sequence (PRESS) MRSI protocols with manual and automatic placement of sat bands. The automated OVS procedure includes the acquisition of anatomic images from the head, obtaining brain and lipid tissue maps, calculating optimal sat band placement, and then using those optimized parameters during the MRSI acquisition. The data were analyzed to quantify brain coverage volume and data quality. 3D PRESS MRSI data were acquired from three healthy volunteers and 29 patients using protocols that included either manual or automatic sat band placement. On average, the automatic sat band placement allowed the acquisition of PRESS MRSI data from 2.7 times larger brain volumes than the conventional method while maintaining data quality. The technique developed helps solve two of the most significant problems with brain PRESS MRSI acquisitions: limited brain coverage and difficulty in prescription. This new method will facilitate routine clinical brain 3D MRSI exams and will be important for performing serial evaluation of response to therapy in patients with brain tumors and other neurological diseases. Copyright © 2011 Wiley-Liss, Inc.

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

Brain tumor locating in 3D MR volume using symmetry

NASA Astrophysics Data System (ADS)

Dvorak, Pavel; Bartusek, Karel

2014-03-01

This work deals with the automatic determination of a brain tumor location in 3D magnetic resonance volumes. The aim of this work is not the precise segmentation of the tumor and its parts but only the detection of its location. This work is the first step in the tumor segmentation process, an important topic in neuro-image processing. The algorithm expects 3D magnetic resonance volumes of brain containing a tumor. The detection is based on locating the area that breaks the left-right symmetry of the brain. This is done by multi-resolution comparing of corresponding regions in left and right hemisphere. The output of the computation is the probabilistic map of the tumor location. The created algorithm was tested on 80 volumes from publicly available BRATS databases containing 3D brain volumes afflicted by a brain tumor. These pathological structures had various sizes and shapes and were located in various parts of the brain. The locating performance of the algorithm was 85% for T1-weighted volumes, 91% for T1-weighted contrast enhanced volumes, 96% for FLAIR and T2-wieghted volumes and 95% for their combinations.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network

PubMed Central

Mao, Lei; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice. PMID:29755716

Automatic selection of localized region-based active contour models using image content analysis applied to brain tumor segmentation.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Cepeda-Negrete, Jonathan; Ibarra-Manzano, Mario Alberto; Chalopin, Claire

2017-12-01

Brain tumor segmentation is a routine process in a clinical setting and provides useful information for diagnosis and treatment planning. Manual segmentation, performed by physicians or radiologists, is a time-consuming task due to the large quantity of medical data generated presently. Hence, automatic segmentation methods are needed, and several approaches have been introduced in recent years including the Localized Region-based Active Contour Model (LRACM). There are many popular LRACM, but each of them presents strong and weak points. In this paper, the automatic selection of LRACM based on image content and its application on brain tumor segmentation is presented. Thereby, a framework to select one of three LRACM, i.e., Local Gaussian Distribution Fitting (LGDF), localized Chan-Vese (C-V) and Localized Active Contour Model with Background Intensity Compensation (LACM-BIC), is proposed. Twelve visual features are extracted to properly select the method that may process a given input image. The system is based on a supervised approach. Applied specifically to Magnetic Resonance Imaging (MRI) images, the experiments showed that the proposed system is able to correctly select the suitable LRACM to handle a specific image. Consequently, the selection framework achieves better accuracy performance than the three LRACM separately. Copyright © 2017 Elsevier Ltd. All rights reserved.

Deep learning and texture-based semantic label fusion for brain tumor segmentation

NASA Astrophysics Data System (ADS)

Vidyaratne, L.; Alam, M.; Shboul, Z.; Iftekharuddin, K. M.

2018-02-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Deep Learning and Texture-Based Semantic Label Fusion for Brain Tumor Segmentation.

PubMed

Vidyaratne, L; Alam, M; Shboul, Z; Iftekharuddin, K M

2018-01-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Brain Tumor Database, a free relational database for collection and analysis of brain tumor patient information.

PubMed

Bergamino, Maurizio; Hamilton, David J; Castelletti, Lara; Barletta, Laura; Castellan, Lucio

2015-03-01

In this study, we describe the development and utilization of a relational database designed to manage the clinical and radiological data of patients with brain tumors. The Brain Tumor Database was implemented using MySQL v.5.0, while the graphical user interface was created using PHP and HTML, thus making it easily accessible through a web browser. This web-based approach allows for multiple institutions to potentially access the database. The BT Database can record brain tumor patient information (e.g. clinical features, anatomical attributes, and radiological characteristics) and be used for clinical and research purposes. Analytic tools to automatically generate statistics and different plots are provided. The BT Database is a free and powerful user-friendly tool with a wide range of possible clinical and research applications in neurology and neurosurgery. The BT Database graphical user interface source code and manual are freely available at http://tumorsdatabase.altervista.org. © The Author(s) 2013.

Multifractal texture estimation for detection and segmentation of brain tumors.

PubMed

Islam, Atiq; Reza, Syed M S; Iftekharuddin, Khan M

2013-11-01

A stochastic model for characterizing tumor texture in brain magnetic resonance (MR) images is proposed. The efficacy of the model is demonstrated in patient-independent brain tumor texture feature extraction and tumor segmentation in magnetic resonance images (MRIs). Due to complex appearance in MRI, brain tumor texture is formulated using a multiresolution-fractal model known as multifractional Brownian motion (mBm). Detailed mathematical derivation for mBm model and corresponding novel algorithm to extract spatially varying multifractal features are proposed. A multifractal feature-based brain tumor segmentation method is developed next. To evaluate efficacy, tumor segmentation performance using proposed multifractal feature is compared with that using Gabor-like multiscale texton feature. Furthermore, novel patient-independent tumor segmentation scheme is proposed by extending the well-known AdaBoost algorithm. The modification of AdaBoost algorithm involves assigning weights to component classifiers based on their ability to classify difficult samples and confidence in such classification. Experimental results for 14 patients with over 300 MRIs show the efficacy of the proposed technique in automatic segmentation of tumors in brain MRIs. Finally, comparison with other state-of-the art brain tumor segmentation works with publicly available low-grade glioma BRATS2012 dataset show that our segmentation results are more consistent and on the average outperforms these methods for the patients where ground truth is made available.

Multifractal Texture Estimation for Detection and Segmentation of Brain Tumors

PubMed Central

Islam, Atiq; Reza, Syed M. S.

2016-01-01

A stochastic model for characterizing tumor texture in brain magnetic resonance (MR) images is proposed. The efficacy of the model is demonstrated in patient-independent brain tumor texture feature extraction and tumor segmentation in magnetic resonance images (MRIs). Due to complex appearance in MRI, brain tumor texture is formulated using a multiresolution-fractal model known as multifractional Brownian motion (mBm). Detailed mathematical derivation for mBm model and corresponding novel algorithm to extract spatially varying multifractal features are proposed. A multifractal feature-based brain tumor segmentation method is developed next. To evaluate efficacy, tumor segmentation performance using proposed multifractal feature is compared with that using Gabor-like multiscale texton feature. Furthermore, novel patient-independent tumor segmentation scheme is proposed by extending the well-known AdaBoost algorithm. The modification of AdaBoost algorithm involves assigning weights to component classifiers based on their ability to classify difficult samples and confidence in such classification. Experimental results for 14 patients with over 300 MRIs show the efficacy of the proposed technique in automatic segmentation of tumors in brain MRIs. Finally, comparison with other state-of-the art brain tumor segmentation works with publicly available low-grade glioma BRATS2012 dataset show that our segmentation results are more consistent and on the average outperforms these methods for the patients where ground truth is made available. PMID:23807424

Multi-Modal Glioblastoma Segmentation: Man versus Machine

PubMed Central

Pica, Alessia; Schucht, Philippe; Beck, Jürgen; Verma, Rajeev Kumar; Slotboom, Johannes; Reyes, Mauricio; Wiest, Roland

2014-01-01

Background and Purpose Reproducible segmentation of brain tumors on magnetic resonance images is an important clinical need. This study was designed to evaluate the reliability of a novel fully automated segmentation tool for brain tumor image analysis in comparison to manually defined tumor segmentations. Methods We prospectively evaluated preoperative MR Images from 25 glioblastoma patients. Two independent expert raters performed manual segmentations. Automatic segmentations were performed using the Brain Tumor Image Analysis software (BraTumIA). In order to study the different tumor compartments, the complete tumor volume TV (enhancing part plus non-enhancing part plus necrotic core of the tumor), the TV+ (TV plus edema) and the contrast enhancing tumor volume CETV were identified. We quantified the overlap between manual and automated segmentation by calculation of diameter measurements as well as the Dice coefficients, the positive predictive values, sensitivity, relative volume error and absolute volume error. Results Comparison of automated versus manual extraction of 2-dimensional diameter measurements showed no significant difference (p = 0.29). Comparison of automated versus manual segmentation of volumetric segmentations showed significant differences for TV+ and TV (p<0.05) but no significant differences for CETV (p>0.05) with regard to the Dice overlap coefficients. Spearman's rank correlation coefficients (ρ) of TV+, TV and CETV showed highly significant correlations between automatic and manual segmentations. Tumor localization did not influence the accuracy of segmentation. Conclusions In summary, we demonstrated that BraTumIA supports radiologists and clinicians by providing accurate measures of cross-sectional diameter-based tumor extensions. The automated volume measurements were comparable to manual tumor delineation for CETV tumor volumes, and outperformed inter-rater variability for overlap and sensitivity. PMID:24804720

Research of the multimodal brain-tumor segmentation algorithm

NASA Astrophysics Data System (ADS)

Lu, Yisu; Chen, Wufan

2015-12-01

It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. A new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain tumor images, we developed the algorithm to segment multimodal brain tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated and compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance.

Automatic metastatic brain tumor segmentation for stereotactic radiosurgery applications.

PubMed

Liu, Yan; Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lu, Weiguo; Yan, Yulong; Jiang, Steve B; Timmerman, Robert; Abdulrahman, Ramzi; Nedzi, Lucien; Gu, Xuejun

2016-12-21

The objective of this study is to develop an automatic segmentation strategy for efficient and accurate metastatic brain tumor delineation on contrast-enhanced T1-weighted (T1c) magnetic resonance images (MRI) for stereotactic radiosurgery (SRS) applications. The proposed four-step automatic brain metastases segmentation strategy is comprised of pre-processing, initial contouring, contour evolution, and contour triage. First, T1c brain images are preprocessed to remove the skull. Second, an initial tumor contour is created using a multi-scaled adaptive threshold-based bounding box and a super-voxel clustering technique. Third, the initial contours are evolved to the tumor boundary using a regional active contour technique. Fourth, all detected false-positive contours are removed with geometric characterization. The segmentation process was validated on a realistic virtual phantom containing Gaussian or Rician noise. For each type of noise distribution, five different noise levels were tested. Twenty-one cases from the multimodal brain tumor image segmentation (BRATS) challenge dataset and fifteen clinical metastases cases were also included in validation. Segmentation performance was quantified by the Dice coefficient (DC), normalized mutual information (NMI), structural similarity (SSIM), Hausdorff distance (HD), mean value of surface-to-surface distance (MSSD) and standard deviation of surface-to-surface distance (SDSSD). In the numerical phantom study, the evaluation yielded a DC of 0.98  ±  0.01, an NMI of 0.97  ±  0.01, an SSIM of 0.999  ±  0.001, an HD of 2.2  ±  0.8 mm, an MSSD of 0.1  ±  0.1 mm, and an SDSSD of 0.3  ±  0.1 mm. The validation on the BRATS data resulted in a DC of 0.89  ±  0.08, which outperform the BRATS challenge algorithms. Evaluation on clinical datasets gave a DC of 0.86  ±  0.09, an NMI of 0.80  ±  0.11, an SSIM of 0.999  ±  0.001, an HD of 8.8  ±  12.6 mm, an MSSD of 1.5  ±  3.2 mm, and an SDSSD of 1.8  ±  3.4 mm when comparing to the physician drawn ground truth. The result indicated that the developed automatic segmentation strategy yielded accurate brain tumor delineation and presented as a useful clinical tool for SRS applications.

Automatic metastatic brain tumor segmentation for stereotactic radiosurgery applications

NASA Astrophysics Data System (ADS)

Liu, Yan; Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lu, Weiguo; Yan, Yulong; Jiang, Steve B.; Timmerman, Robert; Abdulrahman, Ramzi; Nedzi, Lucien; Gu, Xuejun

2016-12-01

The objective of this study is to develop an automatic segmentation strategy for efficient and accurate metastatic brain tumor delineation on contrast-enhanced T1-weighted (T1c) magnetic resonance images (MRI) for stereotactic radiosurgery (SRS) applications. The proposed four-step automatic brain metastases segmentation strategy is comprised of pre-processing, initial contouring, contour evolution, and contour triage. First, T1c brain images are preprocessed to remove the skull. Second, an initial tumor contour is created using a multi-scaled adaptive threshold-based bounding box and a super-voxel clustering technique. Third, the initial contours are evolved to the tumor boundary using a regional active contour technique. Fourth, all detected false-positive contours are removed with geometric characterization. The segmentation process was validated on a realistic virtual phantom containing Gaussian or Rician noise. For each type of noise distribution, five different noise levels were tested. Twenty-one cases from the multimodal brain tumor image segmentation (BRATS) challenge dataset and fifteen clinical metastases cases were also included in validation. Segmentation performance was quantified by the Dice coefficient (DC), normalized mutual information (NMI), structural similarity (SSIM), Hausdorff distance (HD), mean value of surface-to-surface distance (MSSD) and standard deviation of surface-to-surface distance (SDSSD). In the numerical phantom study, the evaluation yielded a DC of 0.98  ±  0.01, an NMI of 0.97  ±  0.01, an SSIM of 0.999  ±  0.001, an HD of 2.2  ±  0.8 mm, an MSSD of 0.1  ±  0.1 mm, and an SDSSD of 0.3  ±  0.1 mm. The validation on the BRATS data resulted in a DC of 0.89  ±  0.08, which outperform the BRATS challenge algorithms. Evaluation on clinical datasets gave a DC of 0.86  ±  0.09, an NMI of 0.80  ±  0.11, an SSIM of 0.999  ±  0.001, an HD of 8.8  ±  12.6 mm, an MSSD of 1.5  ±  3.2 mm, and an SDSSD of 1.8  ±  3.4 mm when comparing to the physician drawn ground truth. The result indicated that the developed automatic segmentation strategy yielded accurate brain tumor delineation and presented as a useful clinical tool for SRS applications.

Semi-Automatic Segmentation Software for Quantitative Clinical Brain Glioblastoma Evaluation

PubMed Central

Zhu, Y; Young, G; Xue, Z; Huang, R; You, H; Setayesh, K; Hatabu, H; Cao, F; Wong, S.T.

2012-01-01

Rationale and Objectives Quantitative measurement provides essential information about disease progression and treatment response in patients with Glioblastoma multiforme (GBM). The goal of this paper is to present and validate a software pipeline for semi-automatic GBM segmentation, called AFINITI (Assisted Follow-up in NeuroImaging of Therapeutic Intervention), using clinical data from GBM patients. Materials and Methods Our software adopts the current state-of-the-art tumor segmentation algorithms and combines them into one clinically usable pipeline. Both the advantages of the traditional voxel-based and the deformable shape-based segmentation are embedded into the software pipeline. The former provides an automatic tumor segmentation scheme based on T1- and T2-weighted MR brain data, and the latter refines the segmentation results with minimal manual input. Results Twenty six clinical MR brain images of GBM patients were processed and compared with manual results. The results can be visualized using the embedded graphic user interface (GUI). Conclusion Validation results using clinical GBM data showed high correlation between the AFINITI results and manual annotation. Compared to the voxel-wise segmentation, AFINITI yielded more accurate results in segmenting the enhanced GBM from multimodality MRI data. The proposed pipeline could be used as additional information to interpret MR brain images in neuroradiology. PMID:22591720

Automatic brain tumor segmentation with a fast Mumford-Shah algorithm

NASA Astrophysics Data System (ADS)

Müller, Sabine; Weickert, Joachim; Graf, Norbert

2016-03-01

We propose a fully-automatic method for brain tumor segmentation that does not require any training phase. Our approach is based on a sequence of segmentations using the Mumford-Shah cartoon model with varying parameters. In order to come up with a very fast implementation, we extend the recent primal-dual algorithm of Strekalovskiy et al. (2014) from the 2D to the medically relevant 3D setting. Moreover, we suggest a new confidence refinement and show that it can increase the precision of our segmentations substantially. Our method is evaluated on 188 data sets with high-grade gliomas and 25 with low-grade gliomas from the BraTS14 database. Within a computation time of only three minutes, we achieve Dice scores that are comparable to state-of-the-art methods.

A semi-automated volumetric software for segmentation and perfusion parameter quantification of brain tumors using 320-row multidetector computed tomography: a validation study.

PubMed

Chae, Soo Young; Suh, Sangil; Ryoo, Inseon; Park, Arim; Noh, Kyoung Jin; Shim, Hackjoon; Seol, Hae Young

2017-05-01

We developed a semi-automated volumetric software, NPerfusion, to segment brain tumors and quantify perfusion parameters on whole-brain CT perfusion (WBCTP) images. The purpose of this study was to assess the feasibility of the software and to validate its performance compared with manual segmentation. Twenty-nine patients with pathologically proven brain tumors who underwent preoperative WBCTP between August 2012 and February 2015 were included. Three perfusion parameters, arterial flow (AF), equivalent blood volume (EBV), and Patlak flow (PF, which is a measure of permeability of capillaries), of brain tumors were generated by a commercial software and then quantified volumetrically by NPerfusion, which also semi-automatically segmented tumor boundaries. The quantification was validated by comparison with that of manual segmentation in terms of the concordance correlation coefficient and Bland-Altman analysis. With NPerfusion, we successfully performed segmentation and quantified whole volumetric perfusion parameters of all 29 brain tumors that showed consistent perfusion trends with previous studies. The validation of the perfusion parameter quantification exhibited almost perfect agreement with manual segmentation, with Lin concordance correlation coefficients (ρ c ) for AF, EBV, and PF of 0.9988, 0.9994, and 0.9976, respectively. On Bland-Altman analysis, most differences between this software and manual segmentation on the commercial software were within the limit of agreement. NPerfusion successfully performs segmentation of brain tumors and calculates perfusion parameters of brain tumors. We validated this semi-automated segmentation software by comparing it with manual segmentation. NPerfusion can be used to calculate volumetric perfusion parameters of brain tumors from WBCTP.

Prioritization of brain MRI volumes using medical image perception model and tumor region segmentation.

PubMed

Mehmood, Irfan; Ejaz, Naveed; Sajjad, Muhammad; Baik, Sung Wook

2013-10-01

The objective of the present study is to explore prioritization methods in diagnostic imaging modalities to automatically determine the contents of medical images. In this paper, we propose an efficient prioritization of brain MRI. First, the visual perception of the radiologists is adapted to identify salient regions. Then this saliency information is used as an automatic label for accurate segmentation of brain lesion to determine the scientific value of that image. The qualitative and quantitative results prove that the rankings generated by the proposed method are closer to the rankings created by radiologists. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi-fractal texture features for brain tumor and edema segmentation

NASA Astrophysics Data System (ADS)

Reza, S.; Iftekharuddin, K. M.

2014-03-01

In this work, we propose a fully automatic brain tumor and edema segmentation technique in brain magnetic resonance (MR) images. Different brain tissues are characterized using the novel texture features such as piece-wise triangular prism surface area (PTPSA), multi-fractional Brownian motion (mBm) and Gabor-like textons, along with regular intensity and intensity difference features. Classical Random Forest (RF) classifier is used to formulate the segmentation task as classification of these features in multi-modal MRIs. The segmentation performance is compared with other state-of-art works using a publicly available dataset known as Brain Tumor Segmentation (BRATS) 2012 [1]. Quantitative evaluation is done using the online evaluation tool from Kitware/MIDAS website [2]. The results show that our segmentation performance is more consistent and, on the average, outperforms other state-of-the art works in both training and challenge cases in the BRATS competition.

Multimodal brain-tumor segmentation based on Dirichlet process mixture model with anisotropic diffusion and Markov random field prior.

PubMed

Lu, Yisu; Jiang, Jun; Yang, Wei; Feng, Qianjin; Chen, Wufan

2014-01-01

Brain-tumor segmentation is an important clinical requirement for brain-tumor diagnosis and radiotherapy planning. It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. Because the classical MDP segmentation cannot be applied for real-time diagnosis, a new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain-tumor images, we developed the algorithm to segment multimodal brain-tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated using 32 multimodal MR glioma image sequences, and the segmentation results are compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance and has a great potential for practical real-time clinical use.

Multimodal Brain-Tumor Segmentation Based on Dirichlet Process Mixture Model with Anisotropic Diffusion and Markov Random Field Prior

PubMed Central

Lu, Yisu; Jiang, Jun; Chen, Wufan

2014-01-01

Brain-tumor segmentation is an important clinical requirement for brain-tumor diagnosis and radiotherapy planning. It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. Because the classical MDP segmentation cannot be applied for real-time diagnosis, a new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain-tumor images, we developed the algorithm to segment multimodal brain-tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated using 32 multimodal MR glioma image sequences, and the segmentation results are compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance and has a great potential for practical real-time clinical use. PMID:25254064

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.

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.

A Patch-Based Approach for the Segmentation of Pathologies: Application to Glioma Labelling.

PubMed

Cordier, Nicolas; Delingette, Herve; Ayache, Nicholas

2016-04-01

In this paper, we describe a novel and generic approach to address fully-automatic segmentation of brain tumors by using multi-atlas patch-based voting techniques. In addition to avoiding the local search window assumption, the conventional patch-based framework is enhanced through several simple procedures: an improvement of the training dataset in terms of both label purity and intensity statistics, augmented features to implicitly guide the nearest-neighbor-search, multi-scale patches, invariance to cube isometries, stratification of the votes with respect to cases and labels. A probabilistic model automatically delineates regions of interest enclosing high-probability tumor volumes, which allows the algorithm to achieve highly competitive running time despite minimal processing power and resources. This method was evaluated on Multimodal Brain Tumor Image Segmentation challenge datasets. State-of-the-art results are achieved, with a limited learning stage thus restricting the risk of overfit. Moreover, segmentation smoothness does not involve any post-processing.

An accurate segmentation method for volumetry of brain tumor in 3D MRI

NASA Astrophysics Data System (ADS)

Wang, Jiahui; Li, Qiang; Hirai, Toshinori; Katsuragawa, Shigehiko; Li, Feng; Doi, Kunio

2008-03-01

Accurate volumetry of brain tumors in magnetic resonance imaging (MRI) is important for evaluating the interval changes in tumor volumes during and after treatment, and also for planning of radiation therapy. In this study, an automated volumetry method for brain tumors in MRI was developed by use of a new three-dimensional (3-D) image segmentation technique. First, the central location of a tumor was identified by a radiologist, and then a volume of interest (VOI) was determined automatically. To substantially simplify tumor segmentation, we transformed the 3-D image of the tumor into a two-dimensional (2-D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the tumor scanned the 3-D image spirally from the "north pole" to the "south pole". The voxels scanned by the radial line provided a transformed 2-D image. We employed dynamic programming to delineate an "optimal" outline of the tumor in the transformed 2-D image. We then transformed the optimal outline back into 3-D image space to determine the volume of the tumor. The volumetry method was trained and evaluated by use of 16 cases with 35 brain tumors. The agreement between tumor volumes provided by computer and a radiologist was employed as a performance metric. Our method provided relatively accurate results with a mean agreement value of 88%.

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.

Glial brain tumor detection by using symmetry analysis

NASA Astrophysics Data System (ADS)

Pedoia, Valentina; Binaghi, Elisabetta; Balbi, Sergio; De Benedictis, Alessandro; Monti, Emanuele; Minotto, Renzo

2012-02-01

In this work a fully automatic algorithm to detect brain tumors by using symmetry analysis is proposed. In recent years a great effort of the research in field of medical imaging was focused on brain tumors segmentation. The quantitative analysis of MRI brain tumor allows to obtain useful key indicators of disease progression. The complex problem of segmenting tumor in MRI can be successfully addressed by considering modular and multi-step approaches mimicking the human visual inspection process. The tumor detection is often an essential preliminary phase to solvethe segmentation problem successfully. In visual analysis of the MRI, the first step of the experts cognitive process, is the detection of an anomaly respect the normal tissue, whatever its nature. An healthy brain has a strong sagittal symmetry, that is weakened by the presence of tumor. The comparison between the healthy and ill hemisphere, considering that tumors are generally not symmetrically placed in both hemispheres, was used to detect the anomaly. A clustering method based on energy minimization through Graph-Cut is applied on the volume computed as a difference between the left hemisphere and the right hemisphere mirrored across the symmetry plane. Differential analysis involves the loss the knowledge of the tumor side. Through an histogram analysis the ill hemisphere is recognized. Many experiments are performed to assess the performance of the detection strategy on MRI volumes in presence of tumors varied in terms of shapes positions and intensity levels. The experiments showed good results also in complex situations.

A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain

PubMed Central

Baumann, Cédric; Zouaoui, Sonia; Yordanova, Yordanka; Blonski, Marie; Rigau, Valérie; Chemouny, Stéphane; Taillandier, Luc; Bauchet, Luc; Duffau, Hugues; Paragios, Nikos

2016-01-01

Diffuse WHO grade II gliomas are diffusively infiltrative brain tumors characterized by an unavoidable anaplastic transformation. Their management is strongly dependent on their location in the brain due to interactions with functional regions and potential differences in molecular biology. In this paper, we present the construction of a probabilistic atlas mapping the preferential locations of diffuse WHO grade II gliomas in the brain. This is carried out through a sparse graph whose nodes correspond to clusters of tumors clustered together based on their spatial proximity. The interest of such an atlas is illustrated via two applications. The first one correlates tumor location with the patient’s age via a statistical analysis, highlighting the interest of the atlas for studying the origins and behavior of the tumors. The second exploits the fact that the tumors have preferential locations for automatic segmentation. Through a coupled decomposed Markov Random Field model, the atlas guides the segmentation process, and characterizes which preferential location the tumor belongs to and consequently which behavior it could be associated to. Leave-one-out cross validation experiments on a large database highlight the robustness of the graph, and yield promising segmentation results. PMID:26751577

Validation tools for image segmentation

NASA Astrophysics Data System (ADS)

Padfield, Dirk; Ross, James

2009-02-01

A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.

Automatic estimation of extent of resection and residual tumor volume of patients with glioblastoma.

PubMed

Meier, Raphael; Porz, Nicole; Knecht, Urspeter; Loosli, Tina; Schucht, Philippe; Beck, Jürgen; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2017-10-01

OBJECTIVE In the treatment of glioblastoma, residual tumor burden is the only prognostic factor that can be actively influenced by therapy. Therefore, an accurate, reproducible, and objective measurement of residual tumor burden is necessary. This study aimed to evaluate the use of a fully automatic segmentation method-brain tumor image analysis (BraTumIA)-for estimating the extent of resection (EOR) and residual tumor volume (RTV) of contrast-enhancing tumor after surgery. METHODS The imaging data of 19 patients who underwent primary resection of histologically confirmed supratentorial glioblastoma were retrospectively reviewed. Contrast-enhancing tumors apparent on structural preoperative and immediate postoperative MR imaging in this patient cohort were segmented by 4 different raters and the automatic segmentation BraTumIA software. The manual and automatic results were quantitatively compared. RESULTS First, the interrater variabilities in the estimates of EOR and RTV were assessed for all human raters. Interrater agreement in terms of the coefficient of concordance (W) was higher for RTV (W = 0.812; p < 0.001) than for EOR (W = 0.775; p < 0.001). Second, the volumetric estimates of BraTumIA for all 19 patients were compared with the estimates of the human raters, which showed that for both EOR (W = 0.713; p < 0.001) and RTV (W = 0.693; p < 0.001) the estimates of BraTumIA were generally located close to or between the estimates of the human raters. No statistically significant differences were detected between the manual and automatic estimates. BraTumIA showed a tendency to overestimate contrast-enhancing tumors, leading to moderate agreement with expert raters with respect to the literature-based, survival-relevant threshold values for EOR. CONCLUSIONS BraTumIA can generate volumetric estimates of EOR and RTV, in a fully automatic fashion, which are comparable to the estimates of human experts. However, automated analysis showed a tendency to overestimate the volume of a contrast-enhancing tumor, whereas manual analysis is prone to subjectivity, thereby causing considerable interrater variability.

Brain Tumor Segmentation Using Deep Belief Networks and Pathological Knowledge.

PubMed

Zhan, Tianming; Chen, Yi; Hong, Xunning; Lu, Zhenyu; Chen, Yunjie

2017-01-01

In this paper, we propose an automatic brain tumor segmentation method based on Deep Belief Networks (DBNs) and pathological knowledge. The proposed method is targeted against gliomas (both low and high grade) obtained in multi-sequence magnetic resonance images (MRIs). Firstly, a novel deep architecture is proposed to combine the multi-sequences intensities feature extraction with classification to get the classification probabilities of each voxel. Then, graph cut based optimization is executed on the classification probabilities to strengthen the spatial relationships of voxels. At last, pathological knowledge of gliomas is applied to remove some false positives. Our method was validated in the Brain Tumor Segmentation Challenge 2012 and 2013 databases (BRATS 2012, 2013). The performance of segmentation results demonstrates our proposal providing a competitive solution with stateof- the-art methods. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Brain tumor segmentation from multimodal magnetic resonance images via sparse representation.

PubMed

Li, Yuhong; Jia, Fucang; Qin, Jing

2016-10-01

Accurately segmenting and quantifying brain gliomas from magnetic resonance (MR) images remains a challenging task because of the large spatial and structural variability among brain tumors. To develop a fully automatic and accurate brain tumor segmentation algorithm, we present a probabilistic model of multimodal MR brain tumor segmentation. This model combines sparse representation and the Markov random field (MRF) to solve the spatial and structural variability problem. We formulate the tumor segmentation problem as a multi-classification task by labeling each voxel as the maximum posterior probability. We estimate the maximum a posteriori (MAP) probability by introducing the sparse representation into a likelihood probability and a MRF into the prior probability. Considering the MAP as an NP-hard problem, we convert the maximum posterior probability estimation into a minimum energy optimization problem and employ graph cuts to find the solution to the MAP estimation. Our method is evaluated using the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013) and obtained Dice coefficient metric values of 0.85, 0.75, and 0.69 on the high-grade Challenge data set, 0.73, 0.56, and 0.54 on the high-grade Challenge LeaderBoard data set, and 0.84, 0.54, and 0.57 on the low-grade Challenge data set for the complete, core, and enhancing regions. The experimental results show that the proposed algorithm is valid and ranks 2nd compared with the state-of-the-art tumor segmentation algorithms in the MICCAI BRATS 2013 challenge. Copyright © 2016 Elsevier B.V. All rights reserved.

A novel fully automatic multilevel thresholding technique based on optimized intuitionistic fuzzy sets and tsallis entropy for MR brain tumor image segmentation.

PubMed

Kaur, Taranjit; Saini, Barjinder Singh; Gupta, Savita

2018-03-01

In the present paper, a hybrid multilevel thresholding technique that combines intuitionistic fuzzy sets and tsallis entropy has been proposed for the automatic delineation of the tumor from magnetic resonance images having vague boundaries and poor contrast. This novel technique takes into account both the image histogram and the uncertainty information for the computation of multiple thresholds. The benefit of the methodology is that it provides fast and improved segmentation for the complex tumorous images with imprecise gray levels. To further boost the computational speed, the mutation based particle swarm optimization is used that selects the most optimal threshold combination. The accuracy of the proposed segmentation approach has been validated on simulated, real low-grade glioma tumor volumes taken from MICCAI brain tumor segmentation (BRATS) challenge 2012 dataset and the clinical tumor images, so as to corroborate its generality and novelty. The designed technique achieves an average Dice overlap equal to 0.82010, 0.78610 and 0.94170 for three datasets. Further, a comparative analysis has also been made between the eight existing multilevel thresholding implementations so as to show the superiority of the designed technique. In comparison, the results indicate a mean improvement in Dice by an amount equal to 4.00% (p < 0.005), 9.60% (p < 0.005) and 3.58% (p < 0.005), respectively in contrast to the fuzzy tsallis approach.

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.

Automated detection and quantification of residual brain tumor using an interactive computer-aided detection scheme

NASA Astrophysics Data System (ADS)

Gaffney, Kevin P.; Aghaei, Faranak; Battiste, James; Zheng, Bin

2017-03-01

Detection of residual brain tumor is important to evaluate efficacy of brain cancer surgery, determine optimal strategy of further radiation therapy if needed, and assess ultimate prognosis of the patients. Brain MR is a commonly used imaging modality for this task. In order to distinguish between residual tumor and surgery induced scar tissues, two sets of MRI scans are conducted pre- and post-gadolinium contrast injection. The residual tumors are only enhanced in the post-contrast injection images. However, subjective reading and quantifying this type of brain MR images faces difficulty in detecting real residual tumor regions and measuring total volume of the residual tumor. In order to help solve this clinical difficulty, we developed and tested a new interactive computer-aided detection scheme, which consists of three consecutive image processing steps namely, 1) segmentation of the intracranial region, 2) image registration and subtraction, 3) tumor segmentation and refinement. The scheme also includes a specially designed and implemented graphical user interface (GUI) platform. When using this scheme, two sets of pre- and post-contrast injection images are first automatically processed to detect and quantify residual tumor volume. Then, a user can visually examine segmentation results and conveniently guide the scheme to correct any detection or segmentation errors if needed. The scheme has been repeatedly tested using five cases. Due to the observed high performance and robustness of the testing results, the scheme is currently ready for conducting clinical studies and helping clinicians investigate the association between this quantitative image marker and outcome of patients.

Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy.

PubMed

Yang, Guang; Nawaz, Tahir; Barrick, Thomas R; Howe, Franklyn A; Slabaugh, Greg

2015-12-01

Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

Improving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

NASA Astrophysics Data System (ADS)

Izadyyazdanabadi, Mohammadhassan; Belykh, Evgenii; Martirosyan, Nikolay; Eschbacher, Jennifer; Nakaji, Peter; Yang, Yezhou; Preul, Mark C.

2017-03-01

Confocal laser endomicroscopy (CLE), although capable of obtaining images at cellular resolution during surgery of brain tumors in real time, creates as many non-diagnostic as diagnostic images. Non-useful images are often distorted due to relative motion between probe and brain or blood artifacts. Many images, however, simply lack diagnostic features immediately informative to the physician. Examining all the hundreds or thousands of images from a single case to discriminate diagnostic images from nondiagnostic ones can be tedious. Providing a real time diagnostic value assessment of images (fast enough to be used during the surgical acquisition process and accurate enough for the pathologist to rely on) to automatically detect diagnostic frames would streamline the analysis of images and filter useful images for the pathologist/surgeon. We sought to automatically classify images as diagnostic or non-diagnostic. AlexNet, a deep-learning architecture, was used in a 4-fold cross validation manner. Our dataset includes 16,795 images (8572 nondiagnostic and 8223 diagnostic) from 74 CLE-aided brain tumor surgery patients. The ground truth for all the images is provided by the pathologist. Average model accuracy on test data was 91% overall (90.79 % accuracy, 90.94 % sensitivity and 90.87 % specificity). To evaluate the model reliability we also performed receiver operating characteristic (ROC) analysis yielding 0.958 average for area under ROC curve (AUC). These results demonstrate that a deeply trained AlexNet network can achieve a model that reliably and quickly recognizes diagnostic CLE images.

Automated identification of brain tumors from single MR images based on segmentation with refined patient-specific priors

PubMed Central

Sanjuán, Ana; Price, Cathy J.; Mancini, Laura; Josse, Goulven; Grogan, Alice; Yamamoto, Adam K.; Geva, Sharon; Leff, Alex P.; Yousry, Tarek A.; Seghier, Mohamed L.

2013-01-01

Brain tumors can have different shapes or locations, making their identification very challenging. In functional MRI, it is not unusual that patients have only one anatomical image due to time and financial constraints. Here, we provide a modified automatic lesion identification (ALI) procedure which enables brain tumor identification from single MR images. Our method rests on (A) a modified segmentation-normalization procedure with an explicit “extra prior” for the tumor and (B) an outlier detection procedure for abnormal voxel (i.e., tumor) classification. To minimize tissue misclassification, the segmentation-normalization procedure requires prior information of the tumor location and extent. We therefore propose that ALI is run iteratively so that the output of Step B is used as a patient-specific prior in Step A. We test this procedure on real T1-weighted images from 18 patients, and the results were validated in comparison to two independent observers' manual tracings. The automated procedure identified the tumors successfully with an excellent agreement with the manual segmentation (area under the ROC curve = 0.97 ± 0.03). The proposed procedure increases the flexibility and robustness of the ALI tool and will be particularly useful for lesion-behavior mapping studies, or when lesion identification and/or spatial normalization are problematic. PMID:24381535

Automated tumor volumetry using computer-aided image segmentation.

PubMed

Gaonkar, Bilwaj; Macyszyn, Luke; Bilello, Michel; Sadaghiani, Mohammed Salehi; Akbari, Hamed; Atthiah, Mark A; Ali, Zarina S; Da, Xiao; Zhan, Yiqang; O'Rourke, Donald; Grady, Sean M; Davatzikos, Christos

2015-05-01

Accurate segmentation of brain tumors, and quantification of tumor volume, is important for diagnosis, monitoring, and planning therapeutic intervention. Manual segmentation is not widely used because of time constraints. Previous efforts have mainly produced methods that are tailored to a particular type of tumor or acquisition protocol and have mostly failed to produce a method that functions on different tumor types and is robust to changes in scanning parameters, resolution, and image quality, thereby limiting their clinical value. Herein, we present a semiautomatic method for tumor segmentation that is fast, accurate, and robust to a wide variation in image quality and resolution. A semiautomatic segmentation method based on the geodesic distance transform was developed and validated by using it to segment 54 brain tumors. Glioblastomas, meningiomas, and brain metastases were segmented. Qualitative validation was based on physician ratings provided by three clinical experts. Quantitative validation was based on comparing semiautomatic and manual segmentations. Tumor segmentations obtained using manual and automatic methods were compared quantitatively using the Dice measure of overlap. Subjective evaluation was performed by having human experts rate the computerized segmentations on a 0-5 rating scale where 5 indicated perfect segmentation. The proposed method addresses a significant, unmet need in the field of neuro-oncology. Specifically, this method enables clinicians to obtain accurate and reproducible tumor volumes without the need for manual segmentation. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Automated Tumor Volumetry Using Computer-Aided Image Segmentation

PubMed Central

Bilello, Michel; Sadaghiani, Mohammed Salehi; Akbari, Hamed; Atthiah, Mark A.; Ali, Zarina S.; Da, Xiao; Zhan, Yiqang; O'Rourke, Donald; Grady, Sean M.; Davatzikos, Christos

2015-01-01

Rationale and Objectives Accurate segmentation of brain tumors, and quantification of tumor volume, is important for diagnosis, monitoring, and planning therapeutic intervention. Manual segmentation is not widely used because of time constraints. Previous efforts have mainly produced methods that are tailored to a particular type of tumor or acquisition protocol and have mostly failed to produce a method that functions on different tumor types and is robust to changes in scanning parameters, resolution, and image quality, thereby limiting their clinical value. Herein, we present a semiautomatic method for tumor segmentation that is fast, accurate, and robust to a wide variation in image quality and resolution. Materials and Methods A semiautomatic segmentation method based on the geodesic distance transform was developed and validated by using it to segment 54 brain tumors. Glioblastomas, meningiomas, and brain metastases were segmented. Qualitative validation was based on physician ratings provided by three clinical experts. Quantitative validation was based on comparing semiautomatic and manual segmentations. Results Tumor segmentations obtained using manual and automatic methods were compared quantitatively using the Dice measure of overlap. Subjective evaluation was performed by having human experts rate the computerized segmentations on a 0–5 rating scale where 5 indicated perfect segmentation. Conclusions The proposed method addresses a significant, unmet need in the field of neuro-oncology. Specifically, this method enables clinicians to obtain accurate and reproducible tumor volumes without the need for manual segmentation. PMID:25770633

[RSF model optimization and its application to brain tumor segmentation in MRI].

PubMed

Cheng, Zhaoning; Song, Zhijian

2013-04-01

Magnetic resonance imaging (MRI) is usually obscure and non-uniform in gray, and the tumors inside are poorly circumscribed, hence the automatic tumor segmentation in MRI is very difficult. Region-scalable fitting (RSF) energy model is a new segmentation approach for some uneven grayscale images. However, the level set formulation (LSF) of RSF model is not suitable for the environment with different grey level distribution inside and outside the intial contour, and the complex intensity environment of MRI always makes it hard to get ideal segmentation results. Therefore, we improved the model by a new LSF and combined it with the mean shift method, which can be helpful for tumor segmentation and has better convergence and target direction. The proposed method has been utilized in a series of studies for real MRI images, and the results showed that it could realize fast, accurate and robust segmentations for brain tumors in MRI, which has great clinical significance.

Confidence-based ensemble for GBM brain tumor segmentation

NASA Astrophysics Data System (ADS)

Huo, Jing; van Rikxoort, Eva M.; Okada, Kazunori; Kim, Hyun J.; Pope, Whitney; Goldin, Jonathan; Brown, Matthew

2011-03-01

It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images. A semi-automated system using fuzzy connectedness has recently been developed for computing the tumor volume that reduces the cost of manual annotation. In this study, we propose a an ensemble method that combines multiple segmentation results into a final ensemble one. The method is evaluated on a dataset of 20 cases from a multi-center pharmaceutical drug trial and compared to the fuzzy connectedness method. Three individual methods were used in the framework: fuzzy connectedness, GrowCut, and voxel classification. The combination method is a confidence map averaging (CMA) method. The CMA method shows an improved ROC curve compared to the fuzzy connectedness method (p < 0.001). The CMA ensemble result is more robust compared to the three individual methods.

Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection

PubMed Central

Su, Hai; Xing, Fuyong; Yang, Lin

2016-01-01

Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96. PMID:26812706

Brain tumor segmentation using holistically nested neural networks in MRI images.

PubMed

Zhuge, Ying; Krauze, Andra V; Ning, Holly; Cheng, Jason Y; Arora, Barbara C; Camphausen, Kevin; Miller, Robert W

2017-10-01

Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the standard imaging modality used to delineate the brain tumor target as part of treatment planning for the administration of radiation therapy. Despite more than 20 yr of research and development, computational brain tumor segmentation in MRI images remains a challenging task. We are presenting a novel method of automatic image segmentation based on holistically nested neural networks that could be employed for brain tumor segmentation of MRI images. Two preprocessing techniques were applied to MRI images. The N4ITK method was employed for correction of bias field distortion. A novel landmark-based intensity normalization method was developed so that tissue types have a similar intensity scale in images of different subjects for the same MRI protocol. The holistically nested neural networks (HNN), which extend from the convolutional neural networks (CNN) with a deep supervision through an additional weighted-fusion output layer, was trained to learn the multiscale and multilevel hierarchical appearance representation of the brain tumor in MRI images and was subsequently applied to produce a prediction map of the brain tumor on test images. Finally, the brain tumor was obtained through an optimum thresholding on the prediction map. The proposed method was evaluated on both the Multimodal Brain Tumor Image Segmentation (BRATS) Benchmark 2013 training datasets, and clinical data from our institute. A dice similarity coefficient (DSC) and sensitivity of 0.78 and 0.81 were achieved on 20 BRATS 2013 training datasets with high-grade gliomas (HGG), based on a two-fold cross-validation. The HNN model built on the BRATS 2013 training data was applied to ten clinical datasets with HGG from a locally developed database. DSC and sensitivity of 0.83 and 0.85 were achieved. A quantitative comparison indicated that the proposed method outperforms the popular fully convolutional network (FCN) method. In terms of efficiency, the proposed method took around 10 h for training with 50,000 iterations, and approximately 30 s for testing of a typical MRI image in the BRATS 2013 dataset with a size of 160 × 216 × 176, using a DELL PRECISION workstation T7400, with an NVIDIA Tesla K20c GPU. An effective brain tumor segmentation method for MRI images based on a HNN has been developed. The high level of accuracy and efficiency make this method practical in brain tumor segmentation. It may play a crucial role in both brain tumor diagnostic analysis and in the treatment planning of radiation therapy. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

MRI Brain Tumor Segmentation and Necrosis Detection Using Adaptive Sobolev Snakes.

PubMed

Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

2014-03-21

Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at different points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D diffusion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

MRI brain tumor segmentation and necrosis detection using adaptive Sobolev snakes

NASA Astrophysics Data System (ADS)

Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

2014-03-01

Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at di erent points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D di usion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

SU-E-T-213: Comparison of Treatment Efficiency of Gamma Knife SRS Plans for Brain Metastases with Different Planning Methods

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

Feng, Y; Huang, Z; Lo, S

2015-06-15

Purpose: To improve Gamma Knife SRS treatment efficiency for brain metastases and compare the differences of treatment time and radiobiological effects between two different planning methods of automatic filling and manual placement of shots with inverse planning. Methods: T1-weighted MRI images with gadolinium contrast from five patients with a single brain metastatic-lesion were used in this retrospective study. Among them, two were from primary breast cancer, two from primary melanoma cancer and one from primary prostate cancer. For each patient, two plans were generated in Leksell GammaPlan10.1.1 for radiosurgical treatment with a Leksell GammaKnife Perfexion machine: one with automatic filling,more » automatic sector configuration and inverse optimization (Method1); and the other with manual placement of shots, manual setup of collimator sizes, manual setup of sector blocking and inverse optimization (Method2). Dosimetric quality of the plans was evaluated with parameters of Coverage, Selectivity, Gradient-Index and DVH. Beam-on Time, Number-of-Shots and Tumor Control Probability(TCP) were compared for the two plans while keeping their dosimetric quality very similar. Relative reduction of Beam-on Time and Number-of-Shots were calculated as the ratios among the two plans and used for quantitative analysis. Results: With very similar dosimetric and radiobiological plan quality, plans created with Method 2 had significantly reduced treatment time. Relative reduction of Beam-on Time ranged from 20% to 51 % (median:29%,p=0.001), and reduction of Number-of-Shots ranged from 5% to 67% (median:40%,p=0.0002), respectively. Time of plan creation for Method1 and Method2 was similar, approximately 20 minutes, excluding the time for tumor delineation. TCP calculated for the tumors from differential DVHs did not show significant difference between the two plans (p=0.35). Conclusion: The method of manual setup combined with inverse optimization in LGP for treatment of brain metastatic lesions with the Perfexion can achieve significantly higher time efficiency without degrading treatment quality.« less

Automatic brain tumor detection in MRI: methodology and statistical validation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Islam, Mohammad A.; Shaik, Jahangheer; Parra, Carlos; Ogg, Robert

2005-04-01

Automated brain tumor segmentation and detection are immensely important in medical diagnostics because it provides information associated to anatomical structures as well as potential abnormal tissue necessary to delineate appropriate surgical planning. In this work, we propose a novel automated brain tumor segmentation technique based on multiresolution texture information that combines fractal Brownian motion (fBm) and wavelet multiresolution analysis. Our wavelet-fractal technique combines the excellent multiresolution localization property of wavelets to texture extraction of fractal. We prove the efficacy of our technique by successfully segmenting pediatric brain MR images (MRIs) from St. Jude Children"s Research Hospital. We use self-organizing map (SOM) as our clustering tool wherein we exploit both pixel intensity and multiresolution texture features to obtain segmented tumor. Our test results show that our technique successfully segments abnormal brain tissues in a set of T1 images. In the next step, we design a classifier using Feed-Forward (FF) neural network to statistically validate the presence of tumor in MRI using both the multiresolution texture and the pixel intensity features. We estimate the corresponding receiver operating curve (ROC) based on the findings of true positive fractions and false positive fractions estimated from our classifier at different threshold values. An ROC, which can be considered as a gold standard to prove the competence of a classifier, is obtained to ascertain the sensitivity and specificity of our classifier. We observe that at threshold 0.4 we achieve true positive value of 1.0 (100%) sacrificing only 0.16 (16%) false positive value for the set of 50 T1 MRI analyzed in this experiment.

Analysis of neoplastic lesions in magnetic resonance imaging using self-organizing maps.

PubMed

Mei, Paulo Afonso; de Carvalho Carneiro, Cleyton; Fraser, Stephen J; Min, Li Li; Reis, Fabiano

2015-12-15

To provide an improved method for the identification and analysis of brain tumors in MRI scans using a semi-automated computational approach, that has the potential to provide a more objective, precise and quantitatively rigorous analysis, compared to human visual analysis. Self-Organizing Maps (SOM) is an unsupervised, exploratory data analysis tool, which can automatically domain an image into selfsimilar regions or clusters, based on measures of similarity. It can be used to perform image-domain of brain tissue on MR images, without prior knowledge. We used SOM to analyze T1, T2 and FLAIR acquisitions from two MRI machines in our service from 14 patients with brain tumors confirmed by biopsies--three lymphomas, six glioblastomas, one meningioma, one ganglioglioma, two oligoastrocytomas and one astrocytoma. The SOM software was used to analyze the data from the three image acquisitions from each patient and generated a self-organized map for each containing 25 clusters. Damaged tissue was separated from the normal tissue using the SOM technique. Furthermore, in some cases it allowed to separate different areas from within the tumor--like edema/peritumoral infiltration and necrosis. In lesions with less precise boundaries in FLAIR, the estimated damaged tissue area in the resulting map appears bigger. Our results showed that SOM has the potential to be a powerful MR imaging analysis technique for the assessment of brain tumors. Copyright © 2015. Published by Elsevier B.V.

Automatic selection of arterial input function using tri-exponential models

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Chen, Jeremy; Castro, Marcelo; Thomasson, David

2009-02-01

Dynamic Contrast Enhanced MRI (DCE-MRI) is one method for drug and tumor assessment. Selecting a consistent arterial input function (AIF) is necessary to calculate tissue and tumor pharmacokinetic parameters in DCE-MRI. This paper presents an automatic and robust method to select the AIF. The first stage is artery detection and segmentation, where knowledge about artery structure and dynamic signal intensity temporal properties of DCE-MRI is employed. The second stage is AIF model fitting and selection. A tri-exponential model is fitted for every candidate AIF using the Levenberg-Marquardt method, and the best fitted AIF is selected. Our method has been applied in DCE-MRIs of four different body parts: breast, brain, liver and prostate. The success rates in artery segmentation for 19 cases are 89.6%+/-15.9%. The pharmacokinetic parameters computed from the automatically selected AIFs are highly correlated with those from manually determined AIFs (R2=0.946, P(T<=t)=0.09). Our imaging-based tri-exponential AIF model demonstrated significant improvement over a previously proposed bi-exponential model.

Smart cloud system with image processing server in diagnosing brain diseases dedicated for hospitals with limited resources.

PubMed

Fahmi, Fahmi; Nasution, Tigor H; Anggreiny, Anggreiny

2017-01-01

The use of medical imaging in diagnosing brain disease is growing. The challenges are related to the big size of data and complexity of the image processing. High standard of hardware and software are demanded, which can only be provided in big hospitals. Our purpose was to provide a smart cloud system to help diagnosing brain diseases for hospital with limited infrastructure. The expertise of neurologists was first implanted in cloud server to conduct an automatic diagnosis in real time using image processing technique developed based on ITK library and web service. Users upload images through website and the result, in this case the size of tumor was sent back immediately. A specific image compression technique was developed for this purpose. The smart cloud system was able to measure the area and location of tumors, with average size of 19.91 ± 2.38 cm2 and an average response time 7.0 ± 0.3 s. The capability of the server decreased when multiple clients accessed the system simultaneously: 14 ± 0 s (5 parallel clients) and 27 ± 0.2 s (10 parallel clients). The cloud system was successfully developed to process and analyze medical images for diagnosing brain diseases in this case for tumor.

PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI.

PubMed

Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng

2016-10-01

The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

Segmentation propagation for the automated quantification of ventricle volume from serial MRI

NASA Astrophysics Data System (ADS)

Linguraru, Marius George; Butman, John A.

2009-02-01

Accurate ventricle volume estimates could potentially improve the understanding and diagnosis of communicating hydrocephalus. Postoperative communicating hydrocephalus has been recognized in patients with brain tumors where the changes in ventricle volume can be difficult to identify, particularly over short time intervals. Because of the complex alterations of brain morphology in these patients, the segmentation of brain ventricles is challenging. Our method evaluates ventricle size from serial brain MRI examinations; we (i) combined serial images to increase SNR, (ii) automatically segmented this image to generate a ventricle template using fast marching methods and geodesic active contours, and (iii) propagated the segmentation using deformable registration of the original MRI datasets. By applying this deformation to the ventricle template, serial volume estimates were obtained in a robust manner from routine clinical images (0.93 overlap) and their variation analyzed.

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.

Detection of brain tumor margins using optical coherence tomography

NASA Astrophysics Data System (ADS)

Juarez-Chambi, Ronald M.; Kut, Carmen; Rico-Jimenez, Jesus; Campos-Delgado, Daniel U.; Quinones-Hinojosa, Alfredo; Li, Xingde; Jo, Javier

2018-02-01

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, noncancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancerinfiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End-Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

Detection of brain tumor margins using optical coherence tomography

NASA Astrophysics Data System (ADS)

Juarez-Chambi, Ronald M.; Kut, Carmen; Rico-Jimenez, Jesus; Campos-Delgado, Daniel U.; Quinones-Hinojosa, Alfredo; Li, Xingde; Jo, Javier

2018-02-01

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, non-cancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancer-infiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End- Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic stimulation.

PubMed

Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P

2015-09-30

The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

P04.19 Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardization.

PubMed Central

Molina, D.; Pérez-Beteta, J.; Martínez-González, A.; Velásquez, C.; Martino, J.; Luque, B.; Revert, A.; Herruzo, I.; Arana, E.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Textural analysis refers to a variety of mathematical methods used to quantify the spatial variations in grey levels within images. In brain tumors, textural features have a great potential as imaging biomarkers having been shown to correlate with survival, tumor grade, tumor type, etc. However, these measures should be reproducible under dynamic range and matrix size changes for their clinical use. Our aim is to study this robustness in brain tumors with 3D magnetic resonance imaging, not previously reported in the literature. Materials and methods: 3D T1-weighted images of 20 patients with glioblastoma (64.80 ± 9.12 years-old) obtained from a 3T scanner were analyzed. Tumors were segmented using an in-house semi-automatic 3D procedure. A set of 16 3D textural features of the most common types (co-occurrence and run-length matrices) were selected, providing regional (run-length based measures) and local information (co-ocurrence matrices) on the tumor heterogeneity. Feature robustness was assessed by means of the coefficient of variation (CV) under both dynamic range (16, 32 and 64 gray levels) and/or matrix size (256x256 and 432x432) changes. Results: None of the textural features considered were robust under dynamic range changes. The textural co-occurrence matrix feature Entropy was the only textural feature robust (CV < 10%) under spatial resolution changes. Conclusions: In general, textural measures of three-dimensional brain tumor images are neither robust under dynamic range nor under matrix size changes. Thus, it becomes mandatory to fix standards for image rescaling after acquisition before the textural features are computed if they are to be used as imaging biomarkers. For T1-weighted images a dynamic range of 16 grey levels and a matrix size of 256x256 (and isotropic voxel) is found to provide reliable and comparable results and is feasible with current MRI scanners. The implications of this work go beyond the specific tumor type and MRI sequence studied here and pose the need for standardization in textural feature calculation of oncological images. FUNDING: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

Brain Tumor Risk Factors

MedlinePlus

... Factors Brain Tumor Statistics ABTA Publications Brain Tumor Dictionary Upcoming Webinars Anytime Learning Brain Tumor Educational Presentations ... Factors Brain Tumor Statistics ABTA Publications Brain Tumor Dictionary Upcoming Webinars Anytime Learning Brain Tumor Educational Presentations ...

Glioblastoma Segmentation: Comparison of Three Different Software Packages.

PubMed

Fyllingen, Even Hovig; Stensjøen, Anne Line; Berntsen, Erik Magnus; Solheim, Ole; Reinertsen, Ingerid

2016-01-01

To facilitate a more widespread use of volumetric tumor segmentation in clinical studies, there is an urgent need for reliable, user-friendly segmentation software. The aim of this study was therefore to compare three different software packages for semi-automatic brain tumor segmentation of glioblastoma; namely BrainVoyagerTM QX, ITK-Snap and 3D Slicer, and to make data available for future reference. Pre-operative, contrast enhanced T1-weighted 1.5 or 3 Tesla Magnetic Resonance Imaging (MRI) scans were obtained in 20 consecutive patients who underwent surgery for glioblastoma. MRI scans were segmented twice in each software package by two investigators. Intra-rater, inter-rater and between-software agreement was compared by using differences of means with 95% limits of agreement (LoA), Dice's similarity coefficients (DSC) and Hausdorff distance (HD). Time expenditure of segmentations was measured using a stopwatch. Eighteen tumors were included in the analyses. Inter-rater agreement was highest for BrainVoyager with difference of means of 0.19 mL and 95% LoA from -2.42 mL to 2.81 mL. Between-software agreement and 95% LoA were very similar for the different software packages. Intra-rater, inter-rater and between-software DSC were ≥ 0.93 in all analyses. Time expenditure was approximately 41 min per segmentation in BrainVoyager, and 18 min per segmentation in both 3D Slicer and ITK-Snap. Our main findings were that there is a high agreement within and between the software packages in terms of small intra-rater, inter-rater and between-software differences of means and high Dice's similarity coefficients. Time expenditure was highest for BrainVoyager, but all software packages were relatively time-consuming, which may limit usability in an everyday clinical setting.

Brain tumor segmentation with Deep Neural Networks.

PubMed

Havaei, Mohammad; Davy, Axel; Warde-Farley, David; Biard, Antoine; Courville, Aaron; Bengio, Yoshua; Pal, Chris; Jodoin, Pierre-Marc; Larochelle, Hugo

2017-01-01

In this paper, we present a fully automatic brain tumor segmentation method based on Deep Neural Networks (DNNs). The proposed networks are tailored to glioblastomas (both low and high grade) pictured in MR images. By their very nature, these tumors can appear anywhere in the brain and have almost any kind of shape, size, and contrast. These reasons motivate our exploration of a machine learning solution that exploits a flexible, high capacity DNN while being extremely efficient. Here, we give a description of different model choices that we've found to be necessary for obtaining competitive performance. We explore in particular different architectures based on Convolutional Neural Networks (CNN), i.e. DNNs specifically adapted to image data. We present a novel CNN architecture which differs from those traditionally used in computer vision. Our CNN exploits both local features as well as more global contextual features simultaneously. Also, different from most traditional uses of CNNs, our networks use a final layer that is a convolutional implementation of a fully connected layer which allows a 40 fold speed up. We also describe a 2-phase training procedure that allows us to tackle difficulties related to the imbalance of tumor labels. Finally, we explore a cascade architecture in which the output of a basic CNN is treated as an additional source of information for a subsequent CNN. Results reported on the 2013 BRATS test data-set reveal that our architecture improves over the currently published state-of-the-art while being over 30 times faster. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Anatomy of the Brain

MedlinePlus

... Tumors Risk Factors Brain Tumor Statistics Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board ... Factors Brain Tumor Statistics ABTA Publications Brain Tumor Dictionary Upcoming Webinars Anytime Learning Brain Tumor Educational Presentations ...

Computerized Interpretation of Dynamic Breast MRI

DTIC Science & Technology

2006-05-01

correction, tumor segmentation , extraction of computerized features that help distinguish between benign and malignant lesions, and classification. Our...for assessing tumor extent in 3D. The primary feature used for 3D tumor segmentation is the postcontrast enhancement vector. Tumor segmentation is a...Appendix B. 4. Investigation of methods for automatic tumor segmentation We developed an automatic method for assessing tumor extent in 3D. The

Brain tumor - primary - adults

MedlinePlus

... Vestibular schwannoma (acoustic neuroma) - adults; Meningioma - adults; Cancer - brain tumor (adults) ... Primary brain tumors include any tumor that starts in the brain. Primary brain tumors can start from brain cells, ...

Oligoastrocytoma

MedlinePlus

... Pineal Tumor Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary ... Pineal Tumor Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary ...

Oligodendroglioma

MedlinePlus

... Pineal Tumor Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary ... Pineal Tumor Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary ...

Delineation and segmentation of cerebral tumors by mapping blood-brain barrier disruption with dynamic contrast-enhanced CT and tracer kinetics modeling-a feasibility study.

PubMed

Bisdas, S; Yang, X; Lim, C C T; Vogl, T J; Koh, T S

2008-01-01

Dynamic contrast-enhanced (DCE) imaging is a promising approach for in vivo assessment of tissue microcirculation. Twenty patients with clinical and routine computed tomography (CT) evidence of intracerebral neoplasm were examined with DCE-CT imaging. Using a distributed-parameter model for tracer kinetics modeling of DCE-CT data, voxel-level maps of cerebral blood flow (F), intravascular blood volume (vi) and intravascular mean transit time (t1) were generated. Permeability-surface area product (PS), extravascular extracellular blood volume (ve) and extraction ratio (E) maps were also calculated to reveal pathologic locations of tracer extravasation, which are indicative of disruptions in the blood-brain barrier (BBB). All maps were visually assessed for quality of tumor delineation and measurement of tumor extent by two radiologists. Kappa (kappa) coefficients and their 95% confidence intervals (CI) were calculated to determine the interobserver agreement for each DCE-CT map. There was a substantial agreement for the tumor delineation quality in the F, ve and t1 maps. The agreement for the quality of the tumor delineation was excellent for the vi, PS and E maps. Concerning the measurement of tumor extent, excellent and nearly excellent agreement was achieved only for E and PS maps, respectively. According to these results, we performed a segmentation of the cerebral tumors on the base of the E maps. The interobserver agreement for the tumor extent quantification based on manual segmentation of tumor in the E maps vs. the computer-assisted segmentation was excellent (kappa = 0.96, CI: 0.93-0.99). The interobserver agreement for the tumor extent quantification based on computer segmentation in the mean images and the E maps was substantial (kappa = 0.52, CI: 0.42-0.59). This study illustrates the diagnostic usefulness of parametric maps associated with BBB disruption on a physiology-based approach and highlights the feasibility for automatic segmentation of cerebral tumors.

Brain Tumor Symptoms

MedlinePlus

... Fatigue Other Symptoms Diagnosis Types of Tumors Risk Factors Brain Tumor Statistics Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board of Directors Staff Leadership Strategic Plan Financials News Careers Brain Tumor Information Brain Anatomy Brain ...

Brain tumor - children

MedlinePlus

... children; Neuroglioma - children; Oligodendroglioma - children; Meningioma - children; Cancer - brain tumor (children) ... The cause of primary brain tumors is unknown. Primary brain tumors may ... (spread to nearby areas) Cancerous (malignant) Brain tumors ...

Schwannoma

MedlinePlus

... Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board ... Factors Brain Tumor Statistics ABTA Publications Brain Tumor Dictionary Upcoming Webinars Anytime Learning Brain Tumor Educational Presentations ...

TU-AB-BRA-11: Evaluation of Fully Automatic Volumetric GBM Segmentation in the TCGA-GBM Dataset: Prognosis and Correlation with VASARI Features

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

Rios Velazquez, E; Meier, R; Dunn, W

Purpose: Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. Methods: MRI sets of 67 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA), including necrosis, edema, contrast enhancing and non-enhancing tumor. Spearman’s correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Results: Auto-segmented sub-volumes showedmore » high agreement with manually delineated volumes (range (r): 0.65 – 0.91). Also showed higher correlation with VASARI features (auto r = 0.35, 0.60 and 0.59; manual r = 0.29, 0.50, 0.43, for contrast-enhancing, necrosis and edema, respectively). The contrast-enhancing volume and post-contrast abnormal volume showed the highest C-index (0.73 and 0.72), comparable to manually defined volumes (p = 0.22 and p = 0.07, respectively). The non-enhancing region defined by BraTumIA showed a significantly higher prognostic value (CI = 0.71) than the edema (CI = 0.60), both of which could not be distinguished by manual delineation. Conclusion: BraTumIA tumor sub-compartments showed higher correlation with VASARI data, and equivalent performance in terms of prognosis compared to manual sub-volumes. This method can enable more reproducible definition and quantification of imaging based biomarkers and has a large potential in high-throughput medical imaging research.« less

Choroid Plexus

MedlinePlus

... Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board ... Factors Brain Tumor Statistics ABTA Publications Brain Tumor Dictionary Upcoming Webinars Anytime Learning Brain Tumor Educational Presentations ...

Understanding Brain Tumors

MedlinePlus

... to Know About Brain Tumors . What is a Brain Tumor? A brain tumor is an abnormal growth
 ... Tumors” from Frankly Speaking Frankly Speaking About Cancer: Brain Tumors Download the full book Questions to ask ...

Functional MRI in Medulloblastoma Survivors Supports Prophylactic Reading Intervention during Tumor Treatment

PubMed Central

Zou, Ping; Conklin, Heather M.; Scoggins, Matthew A.; Li, Yimei; Li, Xingyu; Jones, Melissa M.; Palmer, Shawna L.; Gajjar, Amar; Ogg, Robert J.

2015-01-01

Background Development of reading skills is vulnerable to disruption in children treated for brain tumors. Interventions, remedial and prophylactic, are needed to mitigate reading and other learning difficulties faced by survivors. A functional magnetic resonance imaging (fMRI) study was conducted to investigate long-term effects of a prophylactic reading intervention administered during radiation therapy in children treated for medulloblastoma. Methods The fMRI study included 19 reading-intervention (age 11.7±0.6 years) and 21 standard-of-care (age 12.1±0.6 years) medulloblastoma survivors, and 21 typically developing children (age 12.3±0.6 years). The survivors were 2.5 [1.2, 5.4] years after completion of tumor therapies and reading-intervention survivors were 2.9 [1.6, 5.9] years after intervention. Five fMRI tasks (Rapid Automatized Naming, Continuous Performance Test using faces and letters, orthographic and phonological processing of letter pairs, implicit word reading, and story reading) were used to probe reading-related neural activation. Woodcock-Johnson Reading Fluency, Word Attack, and Sound Awareness subtests were used to evaluate reading abilities. Results At the time of fMRI, Sound Awareness scores were significantly higher in the reading-intervention group than in the standard-of-care group (p = 0.046). Brain activation during the fMRI tasks was detected in left inferior frontal, temporal, ventral occipitotemporal, and subcortical regions, and differed among the groups (p<0.05, FWE). The pattern of group activation differences, across brain areas and tasks, was a normative trend in the reading-intervention group. Conclusions Standardized reading scores and patterns of brain activation provide evidence of long-term effects of prophylactic reading intervention in children treated for medulloblastoma. PMID:25967954

Recent Advancement of the Molecular Diagnosis in Pediatric Brain Tumor.

PubMed

Bae, Jeong-Mo; Won, Jae-Kyung; Park, Sung-Hye

2018-05-01

Recent discoveries of brain tumor-related genes and fast advances in genomic testing technologies have led to the era of molecular diagnosis of brain tumor. Molecular profiling of brain tumor became the significant step in the diagnosis, the prediction of prognosis and the treatment of brain tumor. Because traditional molecular testing methods have limitations in time and cost for multiple gene tests, next-generation sequencing technologies are rapidly introduced into clinical practice. Targeted sequencing panels using these technologies have been developed for brain tumors. In this article, focused on pediatric brain tumor, key discoveries of brain tumor-related genes are reviewed and cancer panels used in the molecular profiling of brain tumor are discussed.

Recent Advancement of the Molecular Diagnosis in Pediatric Brain Tumor

PubMed Central

Bae, Jeong-Mo; Won, Jae-Kyung; Park, Sung-Hye

2018-01-01

Recent discoveries of brain tumor-related genes and fast advances in genomic testing technologies have led to the era of molecular diagnosis of brain tumor. Molecular profiling of brain tumor became the significant step in the diagnosis, the prediction of prognosis and the treatment of brain tumor. Because traditional molecular testing methods have limitations in time and cost for multiple gene tests, next-generation sequencing technologies are rapidly introduced into clinical practice. Targeted sequencing panels using these technologies have been developed for brain tumors. In this article, focused on pediatric brain tumor, key discoveries of brain tumor-related genes are reviewed and cancer panels used in the molecular profiling of brain tumor are discussed. PMID:29742887

Brain Tumor Diagnosis

MedlinePlus

... updates Please leave this field empty Brain Tumor Diagnosis SHARE Home > Brain Tumor Information > Diagnosis Listen In cases where a brain tumor is ... to help the doctor reach a brain tumor diagnosis. These tests may also be able help the ...

Brain Cancer—Patient Version

Cancer.gov

Brain cancer refers to growths of malignant cells in tissues of the brain. Tumors that start in the brain are called primary brain tumors. Tumors that spread to the brain are called metastatic brain tumors. Start here to find information on brain cancer treatment, research, and statistics.

Brain Tumors

MedlinePlus

A brain tumor is a growth of abnormal cells in the tissues of the brain. Brain tumors can be benign, with no cancer cells, ... cancer cells that grow quickly. Some are primary brain tumors, which start in the brain. Others are ...

An algorithm for automatic parameter adjustment for brain extraction in BrainSuite

NASA Astrophysics Data System (ADS)

Rajagopal, Gautham; Joshi, Anand A.; Leahy, Richard M.

2017-02-01

Brain Extraction (classification of brain and non-brain tissue) of MRI brain images is a crucial pre-processing step necessary for imaging-based anatomical studies of the human brain. Several automated methods and software tools are available for performing this task, but differences in MR image parameters (pulse sequence, resolution) and instrumentand subject-dependent noise and artefacts affect the performance of these automated methods. We describe and evaluate a method that automatically adapts the default parameters of the Brain Surface Extraction (BSE) algorithm to optimize a cost function chosen to reflect accurate brain extraction. BSE uses a combination of anisotropic filtering, Marr-Hildreth edge detection, and binary morphology for brain extraction. Our algorithm automatically adapts four parameters associated with these steps to maximize the brain surface area to volume ratio. We evaluate the method on a total of 109 brain volumes with ground truth brain masks generated by an expert user. A quantitative evaluation of the performance of the proposed algorithm showed an improvement in the mean (s.d.) Dice coefficient from 0.8969 (0.0376) for default parameters to 0.9509 (0.0504) for the optimized case. These results indicate that automatic parameter optimization can result in significant improvements in definition of the brain mask.

Cysts

MedlinePlus

... Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board of Directors Staff Leadership Strategic Plan Financials News Careers Brain Tumor Information Brain Anatomy Brain ...

Astrocytoma

MedlinePlus

... Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board of Directors Staff Leadership Strategic Plan Financials News Careers Brain Tumor Information Brain Anatomy Brain ...

Chondrosarcoma

MedlinePlus

... Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board of Directors Staff Leadership Strategic Plan Financials News Careers Brain Tumor Information Brain Anatomy Brain ...

Ependymoma

MedlinePlus

... Pituitary Tumor PNET Schwannoma 2016 WHO Classification Risk Factors Brain Tumor Facts Brain Tumor Dictionary Webinars Anytime Learning About Us Our Founders Board of Directors Staff Leadership Strategic Plan Financials News Careers Brain Tumor Information Brain Anatomy Brain ...

Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

PubMed

Rios Velazquez, Emmanuel; Meier, Raphael; Dunn, William D; Alexander, Brian; Wiest, Roland; Bauer, Stefan; Gutman, David A; Reyes, Mauricio; Aerts, Hugo J W L

2015-11-18

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

Brain Tumors (For Parents)

MedlinePlus

... Staying Safe Videos for Educators Search English Español Brain Tumors KidsHealth / For Parents / Brain Tumors What's in ... radiation therapy or chemotherapy, or both. Types of Brain Tumors There are many different types of brain ...

Mutual-information-based image to patient re-registration using intraoperative ultrasound in image-guided neurosurgery

PubMed Central

Ji, Songbai; Wu, Ziji; Hartov, Alex; Roberts, David W.; Paulsen, Keith D.

2008-01-01

An image-based re-registration scheme has been developed and evaluated that uses fiducial registration as a starting point to maximize the normalized mutual information (nMI) between intraoperative ultrasound (iUS) and preoperative magnetic resonance images (pMR). We show that this scheme significantly (p⪡0.001) reduces tumor boundary misalignment between iUS pre-durotomy and pMR from an average of 2.5 mm to 1.0 mm in six resection surgeries. The corrected tumor alignment before dural opening provides a more accurate reference for assessing subsequent intraoperative tumor displacement, which is important for brain shift compensation as surgery progresses. In addition, we report the translational and rotational capture ranges necessary for successful convergence of the nMI registration technique (5.9 mm and 5.2 deg, respectively). The proposed scheme is automatic, sufficiently robust, and computationally efficient (<2 min), and holds promise for routine clinical use in the operating room during image-guided neurosurgical procedures. PMID:18975707

Registration uncertainties between 3D cone beam computed tomography and different reference CT datasets in lung stereotactic body radiation therapy.

PubMed

Oechsner, Markus; Chizzali, Barbara; Devecka, Michal; Combs, Stephanie Elisabeth; Wilkens, Jan Jakob; Duma, Marciana Nona

2016-10-26

The aim of this study was to analyze differences in couch shifts (setup errors) resulting from image registration of different CT datasets with free breathing cone beam CTs (FB-CBCT). As well automatic as manual image registrations were performed and registration results were correlated to tumor characteristics. FB-CBCT image registration was performed for 49 patients with lung lesions using slow planning CT (PCT), average intensity projection (AIP), maximum intensity projection (MIP) and mid-ventilation CTs (MidV) as reference images. Both, automatic and manual image registrations were applied. Shift differences were evaluated between the registered CT datasets for automatic and manual registration, respectively. Furthermore, differences between automatic and manual registration were analyzed for the same CT datasets. The registration results were statistically analyzed and correlated to tumor characteristics (3D tumor motion, tumor volume, superior-inferior (SI) distance, tumor environment). Median 3D shift differences over all patients were between 0.5 mm (AIPvsMIP) and 1.9 mm (MIPvsPCT and MidVvsPCT) for the automatic registration and between 1.8 mm (AIPvsPCT) and 2.8 mm (MIPvsPCT and MidVvsPCT) for the manual registration. For some patients, large shift differences (>5.0 mm) were found (maximum 10.5 mm, automatic registration). Comparing automatic vs manual registrations for the same reference CTs, ∆AIP achieved the smallest (1.1 mm) and ∆MIP the largest (1.9 mm) median 3D shift differences. The standard deviation (variability) for the 3D shift differences was also the smallest for ∆AIP (1.1 mm). Significant correlations (p < 0.01) between 3D shift difference and 3D tumor motion (AIPvsMIP, MIPvsMidV) and SI distance (AIPvsMIP) (automatic) and also for 3D tumor motion (∆PCT, ∆MidV; automatic vs manual) were found. Using different CT datasets for image registration with FB-CBCTs can result in different 3D couch shifts. Manual registrations achieved partly different 3D shifts than automatic registrations. AIP CTs yielded the smallest shift differences and might be the most appropriate CT dataset for registration with 3D FB-CBCTs.

Multifunctional Nanoparticles for Brain Tumor Diagnosis and Therapy

PubMed Central

Cheng, Yu; Morshed, Ramin; Auffinger, Brenda; Tobias, Alex L.; Lesniak, Maciej S.

2013-01-01

Brain tumors are a diverse group of neoplasms that often carry a poor prognosis for patients. Despite tremendous efforts to develop diagnostic tools and therapeutic avenues, the treatment of brain tumors remains a formidable challenge in the field of neuro-oncology. Physiological barriers including the blood-brain barrier result in insufficient accumulation of therapeutic agents at the site of a tumor, preventing adequate destruction of malignant cells. Furthermore, there is a need for improvements in brain tumor imaging to allow for better characterization and delineation of tumors, visualization of malignant tissue during surgery, and tracking of response to chemotherapy and radiotherapy. Multifunctional nanoparticles offer the potential to improve upon many of these issues and may lead to breakthroughs in brain tumor management. In this review, we discuss the diagnostic and therapeutic applications of nanoparticles for brain tumors with an emphasis on innovative approaches in tumor targeting, tumor imaging, and therapeutic agent delivery. Clinically feasible nanoparticle administration strategies for brain tumor patients are also examined. Furthermore, we address the barriers towards clinical implementation of multifunctional nanoparticles in the context of brain tumor management. PMID:24060923

Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.

PubMed

Pereira, Sérgio; Meier, Raphael; McKinley, Richard; Wiest, Roland; Alves, Victor; Silva, Carlos A; Reyes, Mauricio

2018-02-01

Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, they become less interpretable, which may cause some distrust by the end-user of the system. This is especially important as these systems are pervasively being introduced to critical domains, such as the medical field. Representation Learning techniques are general methods for automatic feature computation. Nevertheless, these techniques are regarded as uninterpretable "black boxes". In this paper, we propose a methodology to enhance the interpretability of automatically extracted machine learning features. The proposed system is composed of a Restricted Boltzmann Machine for unsupervised feature learning, and a Random Forest classifier, which are combined to jointly consider existing correlations between imaging data, features, and target variables. We define two levels of interpretation: global and local. The former is devoted to understanding if the system learned the relevant relations in the data correctly, while the later is focused on predictions performed on a voxel- and patient-level. In addition, we propose a novel feature importance strategy that considers both imaging data and target variables, and we demonstrate the ability of the approach to leverage the interpretability of the obtained representation for the task at hand. We evaluated the proposed methodology in brain tumor segmentation and penumbra estimation in ischemic stroke lesions. We show the ability of the proposed methodology to unveil information regarding relationships between imaging modalities and extracted features and their usefulness for the task at hand. In both clinical scenarios, we demonstrate that the proposed methodology enhances the interpretability of automatically learned features, highlighting specific learning patterns that resemble how an expert extracts relevant data from medical images. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring

PubMed Central

Moghbel, Mehrdad; Mashohor, Syamsiah; Mahmud, Rozi; Saripan, M. Iqbal Bin

2016-01-01

Segmentation of liver tumors from Computed Tomography (CT) and tumor burden analysis play an important role in the choice of therapeutic strategies for liver diseases and treatment monitoring. In this paper, a new segmentation method for liver tumors from contrast-enhanced CT imaging is proposed. As manual segmentation of tumors for liver treatment planning is both labor intensive and time-consuming, a highly accurate automatic tumor segmentation is desired. The proposed framework is fully automatic requiring no user interaction. The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. The accuracy of the proposed method was validated using a clinical liver dataset containing one of the highest numbers of tumors utilized for liver tumor segmentation containing 127 tumors in total with further validation of the results by a consultant radiologist. The proposed method was able to achieve one of the highest accuracies reported in the literature for liver tumor segmentation compared to other segmentation methods with a mean overlap error of 22.78 % and dice similarity coefficient of 0.75 in 3Dircadb dataset and a mean overlap error of 15.61 % and dice similarity coefficient of 0.81 in MIDAS dataset. The proposed method was able to outperform most other tumor segmentation methods reported in the literature while representing an overlap error improvement of 6 % compared to one of the best performing automatic methods in the literature. The proposed framework was able to provide consistently accurate results considering the number of tumors and the variations in tumor contrast enhancements and tumor appearances while the tumor burden was estimated with a mean error of 0.84 % in 3Dircadb dataset. PMID:27540353

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2012-01-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2011-12-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Pediatric Brain Tumor Foundation

MedlinePlus

... navigate their brain tumor diagnosis. WATCH AND SHARE Brain tumors and their treatment can be deadly so ... Pediatric Central Nervous System Cancers Read more >> Pediatric Brain Tumor Foundation 302 Ridgefield Court, Asheville, NC 28806 ...

Time-resolved fluorescence spectroscopy of human brain tumors

NASA Astrophysics Data System (ADS)

Marcu, Laura; Thompson, Reid C.; Garde, Smita; Sedrak, Mark; Black, Keith L.; Yong, William H.

2002-05-01

Fluorescence spectroscopy of the endogenous emission of brain tumors has been researched as a potentially important method for the intraoperative localization of brain tumor margins. In this study, we investigate the use of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) for demarcation of primary brain tumors by studying the time-resolved spectra of gliomas of different histologic grades. Time-resolved fluorescence (3 ns, 337 nm excitation) from excised human brain tumor show differences between the time-resolved emission of malignant glioma and normal brain tissue (gray and white matter). Our findings suggest that brain tumors can be differentiated from normal brain tissue based upon unique time-resolved fluorescence signature.

Quality of clinical brain tumor MR spectra judged by humans and machine learning tools.

PubMed

Kyathanahally, Sreenath P; Mocioiu, Victor; Pedrosa de Barros, Nuno; Slotboom, Johannes; Wright, Alan J; Julià-Sapé, Margarida; Arús, Carles; Kreis, Roland

2018-05-01

To investigate and compare human judgment and machine learning tools for quality assessment of clinical MR spectra of brain tumors. A very large set of 2574 single voxel spectra with short and long echo time from the eTUMOUR and INTERPRET databases were used for this analysis. Original human quality ratings from these studies as well as new human guidelines were used to train different machine learning algorithms for automatic quality control (AQC) based on various feature extraction methods and classification tools. The performance was compared with variance in human judgment. AQC built using the RUSBoost classifier that combats imbalanced training data performed best. When furnished with a large range of spectral and derived features where the most crucial ones had been selected by the TreeBagger algorithm it showed better specificity (98%) in judging spectra from an independent test-set than previously published methods. Optimal performance was reached with a virtual three-class ranking system. Our results suggest that feature space should be relatively large for the case of MR tumor spectra and that three-class labels may be beneficial for AQC. The best AQC algorithm showed a performance in rejecting spectra that was comparable to that of a panel of human expert spectroscopists. Magn Reson Med 79:2500-2510, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

An automatic rat brain extraction method based on a deformable surface model.

PubMed

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.

Hybrid Clustering And Boundary Value Refinement for Tumor Segmentation using Brain MRI

NASA Astrophysics Data System (ADS)

Gupta, Anjali; Pahuja, Gunjan

2017-08-01

The method of brain tumor segmentation is the separation of tumor area from Brain Magnetic Resonance (MR) images. There are number of methods already exist for segmentation of brain tumor efficiently. However it’s tedious task to identify the brain tumor from MR images. The segmentation process is extraction of different tumor tissues such as active, tumor, necrosis, and edema from the normal brain tissues such as gray matter (GM), white matter (WM), as well as cerebrospinal fluid (CSF). As per the survey study, most of time the brain tumors are detected easily from brain MR image using region based approach but required level of accuracy, abnormalities classification is not predictable. The segmentation of brain tumor consists of many stages. Manually segmenting the tumor from brain MR images is very time consuming hence there exist many challenges in manual segmentation. In this research paper, our main goal is to present the hybrid clustering which consists of Fuzzy C-Means Clustering (for accurate tumor detection) and level set method(for handling complex shapes) for the detection of exact shape of tumor in minimal computational time. using this approach we observe that for a certain set of images 0.9412 sec of time is taken to detect tumor which is very less in comparison to recent existing algorithm i.e. Hybrid clustering (Fuzzy C-Means and K Means clustering).

A New Way to Treat Brain Tumors: Targeting Proteins Coded by Microcephaly Genes?: Brain tumors and microcephaly arise from opposing derangements regulating progenitor growth. Drivers of microcephaly could be attractive brain tumor targets.

PubMed

Lang, Patrick Y; Gershon, Timothy R

2018-05-01

New targets for brain tumor therapies may be identified by mutations that cause hereditary microcephaly. Brain growth depends on the repeated proliferation of stem and progenitor cells. Microcephaly syndromes result from mutations that specifically impair the ability of brain progenitor or stem cells to proliferate, by inducing either premature differentiation or apoptosis. Brain tumors that derive from brain progenitor or stem cells may share many of the specific requirements of their cells of origin. These tumors may therefore be susceptible to disruptions of the protein products of genes that are mutated in microcephaly. The potential for the products of microcephaly genes to be therapeutic targets in brain tumors are highlighted hereby reviewing research on EG5, KIF14, ASPM, CDK6, and ATR. Treatments that disrupt these proteins may open new avenues for brain tumor therapy that have increased efficacy and decreased toxicity. © 2018 WILEY Periodicals, Inc.

Brain tumor modeling using the CRISPR/Cas9 system: state of the art and view to the future.

PubMed

Mao, Xiao-Yuan; Dai, Jin-Xiang; Zhou, Hong-Hao; Liu, Zhao-Qian; Jin, Wei-Lin

2016-05-31

Although brain tumors have been known tremendously over the past decade, there are still many problems to be solved. The etiology of brain tumors is not well understood and the treatment remains modest. There is in great need to develop a suitable brain tumor models that faithfully mirror the etiology of human brain neoplasm and subsequently get more efficient therapeutic approaches for these disorders. In this review, we described the current status of animal models of brain tumors and analyzed their advantages and disadvantages. Additionally, prokaryotic clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), a versatile genome editing technology for investigating the functions of target genes, and its application were also introduced in our present work. We firstly proposed that brain tumor modeling could be well established via CRISPR/Cas9 techniques. And CRISPR/Cas9-mediated brain tumor modeling was likely to be more suitable for figuring out the pathogenesis of brain tumors, as CRISPR/Cas9 platform was a simple and more efficient biological toolbox for implementing mutagenesis of oncogenes or tumor suppressors that were closely linked with brain tumors.

Brain tumor modeling using the CRISPR/Cas9 system: state of the art and view to the future

PubMed Central

Mao, Xiao-Yuan; Dai, Jin-Xiang; Zhou, Hong-Hao; Liu, Zhao-Qian; Jin, Wei-Lin

2016-01-01

Although brain tumors have been known tremendously over the past decade, there are still many problems to be solved. The etiology of brain tumors is not well understood and the treatment remains modest. There is in great need to develop a suitable brain tumor models that faithfully mirror the etiology of human brain neoplasm and subsequently get more efficient therapeutic approaches for these disorders. In this review, we described the current status of animal models of brain tumors and analyzed their advantages and disadvantages. Additionally, prokaryotic clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), a versatile genome editing technology for investigating the functions of target genes, and its application were also introduced in our present work. We firstly proposed that brain tumor modeling could be well established via CRISPR/Cas9 techniques. And CRISPR/Cas9-mediated brain tumor modeling was likely to be more suitable for figuring out the pathogenesis of brain tumors, as CRISPR/Cas9 platform was a simple and more efficient biological toolbox for implementing mutagenesis of oncogenes or tumor suppressors that were closely linked with brain tumors. PMID:26993776

Changes in Signal Intensity of the Dentate Nucleus and Globus Pallidus in Pediatric Patients: Impact of Brain Irradiation and Presence of Primary Brain Tumors Independent of Linear Gadolinium-based Contrast Agent Administration.

PubMed

Tamrazi, Benita; Nguyen, Binh; Liu, Chia-Shang J; Azen, Colleen G; Nelson, Mary B; Dhall, Girish; Nelson, Marvin D

2018-05-01

Purpose To determine whether whole-brain irradiation, chemotherapy, and primary brain pathologic conditions affect magnetic resonance (MR) imaging signal changes in pediatric patients independent of the administration of gadolinium-based contrast agents (GBCAs). Materials and Methods This institutional review board-approved, HIPAA-compliant study included 144 pediatric patients who underwent intravenous GBCA-enhanced MR imaging examinations (55 patients with primary brain tumors and whole-brain irradiation, 19 with primary brain tumors and chemotherapy only, 52 with primary brain tumors without any treatment, and 18 with neuroblastoma without brain metastatic disease). The signal intensities (SIs) in the globus pallidus (GP), thalamus (T), dentate nucleus (DN), and pons (P) were measured on unenhanced T1-weighted images. GP:T and DN:P SI ratios were compared between groups by using the analysis of variance and were analyzed relative to group, total cumulative number of doses of GBCA, age, and sex by using multivariable linear models. Results DN:P ratio for the radiation therapy group was greater than that for the other groups except for the group of brain tumors treated with chemotherapy (P < .05). The number of GBCA doses was correlated with the DN:P ratio for the nontreated brain tumor group (P < .0001). The radiation therapy-treated brain tumor group demonstrated higher DN:P ratios than the nontreated brain tumor group for number of doses less than or equal to 10 (P < .0001), whereas ratios in the nontreated brain tumor group were higher than those in the radiation therapy-treated brain tumor group for doses greater than 20 (P = .05). The GP:T ratios for the brain tumor groups were greater than that for the neuroblastoma group (P = .01). Conclusion Changes in SI of the DN and GP that are independent of the administration of GBCA occur in patients with brain tumors undergoing brain irradiation, as well as in patients with untreated primary brain tumors. © RSNA, 2017.

Development of a cerebral circulation model for the automatic control of brain physiology.

PubMed

Utsuki, T

2015-01-01

In various clinical guidelines of brain injury, intracranial pressure (ICP), cerebral blood flow (CBF) and brain temperature (BT) are essential targets for precise management for brain resuscitation. In addition, the integrated automatic control of BT, ICP, and CBF is required for improving therapeutic effects and reducing medical costs and staff burden. Thus, a new model of cerebral circulation was developed in this study for integrative automatic control. With this model, the CBF and cerebral perfusion pressure of a normal adult male were regionally calculated according to cerebrovascular structure, blood viscosity, blood distribution, CBF autoregulation, and ICP. The analysis results were consistent with physiological knowledge already obtained with conventional studies. Therefore, the developed model is potentially available for the integrative control of the physiological state of the brain as a reference model of an automatic control system, or as a controlled object in various control simulations.

Chemo brain or tumor brain - that is the question: the presence of extracranial tumors profoundly affects molecular processes in the prefrontal cortex of TumorGraft mice

PubMed Central

Kovalchuk, Anna; Ilnytskyy, Yaroslav; Rodriguez-Juarez, Rocio; Shpyleva, Svitlana; Melnyk, Stepan; Pogribny, Igor; Katz, Amanda; Sidransky, David; Kovalchuk, Olga; Kolb, Bryan

2017-01-01

Cancer chemotherapy causes numerous persistent central nervous system complications. This condition is known as chemo brain. Cognitive impairments occur even before treatment, and hence are referred to as cancer associated cognitive changes, or tumor brain. There is much yet to be learned about the mechanisms of both chemo brain and tumor brain. The frequency and timing of chemo brain and tumor brain occurrence and persistence strongly suggest they may be epigenetic in nature and associated with altered gene expression. Here we used TumorGraftTM models wherein part of a patient's tumor is removed and grafted into immune-deficient mice and conducted global gene expression and DNA methylation analysis. We show that malignant non-central nervous system tumor growth causes profound molecular alterations in the brain. Mice harbouring triple negative or progesterone positive breast cancer TumorGrafts exhibited altered gene expression, decreased levels of DNA methylation, increased levels of DNA hydroxymethylation, and oxidative stress in the prefrontal cortex. Interestingly, chemotherapy did not have any additional synergistic effects on the analyzed processes. The molecular changes observed in this study are known signs of neurodegeneration and brain aging. This study provides an important roadmap for future large-scale analysis of the molecular and cellular mechanisms of tumor brain. PMID:28758896

Spotlight on Brain Tumors: Do You Know the Symptoms?

MedlinePlus

... Subscribe October 2017 Print this issue Spotlight on Brain Tumors Do You Know the Symptoms? En español ... at Epilepsy Wise Choices Possible Symptoms of a Brain Tumor The symptoms of a brain tumor depend ...

SU-E-J-252: Reproducibility of Radiogenomic Image Features: Comparison of Two Semi-Automated Segmentation Methods

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

Lee, M; Woo, B; Kim, J

Purpose: Objective and reliable quantification of imaging phenotype is an essential part of radiogenomic studies. We compared the reproducibility of two semi-automatic segmentation methods for quantitative image phenotyping in magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM). Methods: MRI examinations with T1 post-gadolinium and FLAIR sequences of 10 GBM patients were downloaded from the Cancer Image Archive site. Two semi-automatic segmentation tools with different algorithms (deformable model and grow cut method) were used to segment contrast enhancement, necrosis and edema regions by two independent observers. A total of 21 imaging features consisting of area and edge groups were extracted automaticallymore » from the segmented tumor. The inter-observer variability and coefficient of variation (COV) were calculated to evaluate the reproducibility. Results: Inter-observer correlations and coefficient of variation of imaging features with the deformable model ranged from 0.953 to 0.999 and 2.1% to 9.2%, respectively, and the grow cut method ranged from 0.799 to 0.976 and 3.5% to 26.6%, respectively. Coefficient of variation for especially important features which were previously reported as predictive of patient survival were: 3.4% with deformable model and 7.4% with grow cut method for the proportion of contrast enhanced tumor region; 5.5% with deformable model and 25.7% with grow cut method for the proportion of necrosis; and 2.1% with deformable model and 4.4% with grow cut method for edge sharpness of tumor on CE-T1W1. Conclusion: Comparison of two semi-automated tumor segmentation techniques shows reliable image feature extraction for radiogenomic analysis of GBM patients with multiparametric Brain MRI.« less

Deregulated proliferation and differentiation in brain tumors

PubMed Central

Swartling, Fredrik J; Čančer, Matko; Frantz, Aaron; Weishaupt, Holger; Persson, Anders I

2014-01-01

Neurogenesis, the generation of new neurons, is deregulated in neural stem cell (NSC)- and progenitor-derived murine models of malignant medulloblastoma and glioma, the most common brain tumors of children and adults, respectively. Molecular characterization of human malignant brain tumors, and in particular brain tumor stem cells (BTSCs), has identified neurodevelopmental transcription factors, microRNAs, and epigenetic factors known to inhibit neuronal and glial differentiation. We are starting to understand how these factors are regulated by the major oncogenic drivers in malignant brain tumors. In this review, we will focus on the molecular switches that block normal neuronal differentiation and induce brain tumor formation. Genetic or pharmacological manipulation of these switches in BTSCs has been shown to restore the ability of tumor cells to differentiate. We will discuss potential brain tumor therapies that will promote differentiation in order to reduce treatment-resistance, suppress tumor growth, and prevent recurrence in patients. PMID:25416506

The busy social brain: evidence for automaticity and control in the neural systems supporting social cognition and action understanding.

PubMed

Spunt, Robert P; Lieberman, Matthew D

2013-01-01

Much social-cognitive processing is believed to occur automatically; however, the relative automaticity of the brain systems underlying social cognition remains largely undetermined. We used functional MRI to test for automaticity in the functioning of two brain systems that research has indicated are important for understanding other people's behavior: the mirror neuron system and the mentalizing system. Participants remembered either easy phone numbers (low cognitive load) or difficult phone numbers (high cognitive load) while observing actions after adopting one of four comprehension goals. For all four goals, mirror neuron system activation showed relatively little evidence of modulation by load; in contrast, the association of mentalizing system activation with the goal of inferring the actor's mental state was extinguished by increased cognitive load. These results support a dual-process model of the brain systems underlying action understanding and social cognition; the mirror neuron system supports automatic behavior identification, and the mentalizing system supports controlled social causal attribution.

Nano to micro delivery systems: targeting angiogenesis in brain tumors.

PubMed

Gilert, Ariel; Machluf, Marcelle

2010-10-08

Treating brain tumors using inhibitors of angiogenesis is extensively researched and tested in clinical trials. Although anti-angiogenic treatment holds a great potential for treating primary and secondary brain tumors, no clinical treatment is currently approved for brain tumor patients. One of the main hurdles in treating brain tumors is the blood brain barrier - a protective barrier of the brain, which prevents drugs from entering the brain parenchyma. As most therapeutics are excluded from the brain there is an urgent need to develop delivery platforms which will bypass such hurdles and enable the delivery of anti-angiogenic drugs into the tumor bed. Such delivery systems should be able to control release the drug or a combination of drugs at a therapeutic level for the desired time. In this mini-review we will discuss the latest improvements in nano and micro drug delivery platforms that were designed to deliver inhibitors of angiogenesis to the brain.

Nano to micro delivery systems: targeting angiogenesis in brain tumors

PubMed Central

2010-01-01

Treating brain tumors using inhibitors of angiogenesis is extensively researched and tested in clinical trials. Although anti-angiogenic treatment holds a great potential for treating primary and secondary brain tumors, no clinical treatment is currently approved for brain tumor patients. One of the main hurdles in treating brain tumors is the blood brain barrier - a protective barrier of the brain, which prevents drugs from entering the brain parenchyma. As most therapeutics are excluded from the brain there is an urgent need to develop delivery platforms which will bypass such hurdles and enable the delivery of anti-angiogenic drugs into the tumor bed. Such delivery systems should be able to control release the drug or a combination of drugs at a therapeutic level for the desired time. In this mini-review we will discuss the latest improvements in nano and micro drug delivery platforms that were designed to deliver inhibitors of angiogenesis to the brain. PMID:20932320

A validation framework for brain tumor segmentation.

PubMed

Archip, Neculai; Jolesz, Ferenc A; Warfield, Simon K

2007-10-01

We introduce a validation framework for the segmentation of brain tumors from magnetic resonance (MR) images. A novel unsupervised semiautomatic brain tumor segmentation algorithm is also presented. The proposed framework consists of 1) T1-weighted MR images of patients with brain tumors, 2) segmentation of brain tumors performed by four independent experts, 3) segmentation of brain tumors generated by a semiautomatic algorithm, and 4) a software tool that estimates the performance of segmentation algorithms. We demonstrate the validation of the novel segmentation algorithm within the proposed framework. We show its performance and compare it with existent segmentation. The image datasets and software are available at http://www.brain-tumor-repository.org/. We present an Internet resource that provides access to MR brain tumor image data and segmentation that can be openly used by the research community. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results.

Patients With Brain Tumors: Who Receives Postacute Occupational Therapy Services?

PubMed

Chan, Vincy; Xiong, Chen; Colantonio, Angela

2015-01-01

Data on the utilization of occupational therapy among patients with brain tumors have been limited to those with malignant tumors and small samples of patients outside North America in specialized palliative care settings. We built on this research by examining the characteristics of patients with brain tumors who received postacute occupational therapy services in Ontario, Canada, using health care administrative data. Between fiscal years 2004-2005 and 2008-2009, 3,199 patients with brain tumors received occupational therapy services in the home care setting after hospital discharge; 12.4% had benign brain tumors, 78.2% had malignant brain tumors, and 9.4% had unspecified brain tumors. However, patients with benign brain tumors were older (mean age=63.3 yr), and a higher percentage were female (65.2%). More than 90% of patients received in-home occupational therapy services. Additional research is needed to examine the significance of these differences and to identify factors that influence access to occupational therapy services in the home care setting. Copyright © 2015 by the American Occupational Therapy Association, Inc.

Automatic segmentation of cortical vessels in pre- and post-tumor resection laser range scan images

NASA Astrophysics Data System (ADS)

Ding, Siyi; Miga, Michael I.; Thompson, Reid C.; Garg, Ishita; Dawant, Benoit M.

2009-02-01

Measurement of intra-operative cortical brain movement is necessary to drive mechanical models developed to predict sub-cortical shift. At our institution, this is done with a tracked laser range scanner. This device acquires both 3D range data and 2D photographic images. 3D cortical brain movement can be estimated if 2D photographic images acquired over time can be registered. Previously, we have developed a method, which permits this registration using vessels visible in the images. But, vessel segmentation required the localization of starting and ending points for each vessel segment. Here, we propose a method, which automates the segmentation process further. This method involves several steps: (1) correction of lighting artifacts, (2) vessel enhancement, and (3) vessels' centerline extraction. Result obtained on 5 images obtained in the operating room suggests that our method is robust and is able to segment vessels reliably.

Faceted Visualization of Three Dimensional Neuroanatomy By Combining Ontology with Faceted Search

PubMed Central

Veeraraghavan, Harini; Miller, James V.

2013-01-01

In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset. PMID:24006207

Faceted visualization of three dimensional neuroanatomy by combining ontology with faceted search.

PubMed

Veeraraghavan, Harini; Miller, James V

2014-04-01

In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset.

Childhood Brain Tumors

MedlinePlus

Brain tumors are abnormal growths inside the skull. They are among the most common types of childhood ... still be serious. Malignant tumors are cancerous. Childhood brain and spinal cord tumors can cause headaches and ...

SU-E-T-587: Optimal Volumetric Modulated Arc Radiotherapy Treatment Planning Technique for Multiple Brain Metastases with Increasing Number of Arcs

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

Keeling, V; Hossain, S; Hildebrand, K

Purpose: To show improvements in dose conformity and normal brain tissue sparing using an optimal planning technique (OPT) against clinically acceptable planning technique (CAP) in the treatment of multiple brain metastases. Methods: A standardized international benchmark case with12 intracranial tumors was planned using two different VMAT optimization methods. Plans were split into four groups with 3, 6, 9, and 12 targets each planned with 3, 5, and 7 arcs using Eclipse TPS. The beam geometries were 1 full coplanar and half non-coplanar arcs. A prescription dose of 20Gy was used for all targets. The following optimization criteria was used (OPTmore » vs. CAP): (No upper limit vs.108% upper limit for target volume), (priority 140–150 vs. 75–85 for normal-brain-tissue), and (selection of automatic sparing Normal-Tissue-Objective (NTO) vs. Manual NTO). Both had priority 50 to critical structures such as brainstem and optic-chiasm, and both had an NTO priority 150. Normal-brain-tissue doses along with Paddick Conformity Index (PCI) were evaluated. Results: In all cases PCI was higher for OPT plans. The average PCI (OPT,CAP) for all targets was (0.81,0.64), (0.81,0.63), (0.79,0.57), and (0.72,0.55) for 3, 6, 9, and 12 target plans respectively. The percent decrease in normal brain tissue volume (OPT/CAP*100) achieved by OPT plans was (reported as follows: V4, V8, V12, V16, V20) (184, 343, 350, 294, 371%), (192, 417, 380, 299, 360%), and (235, 390, 299, 281, 502%) for the 3, 5, 7 arc 12 target plans, respectively. The maximum brainstem dose decreased for the OPT plan by 4.93, 4.89, and 5.30 Gy for 3, 5, 7 arc 12 target plans, respectively. Conclusion: Substantial increases in PCI, critical structure sparing, and decreases in normal brain tissue dose were achieved by eliminating upper limits from optimization, using automatic sparing of normal tissue function with high priority, and a high priority to normal brain tissue.« less

Plasma Levels of Glucose and Insulin in Patients with Brain Tumors

PubMed Central

ALEXANDRU, OANA; ENE, L.; PURCARU, OANA STEFANA; TACHE, DANIELA ELISE; POPESCU, ALISA; NEAMTU, OANA MARIA; TATARANU, LIGIA GABRIELA; GEORGESCU, ADA MARIA; TUDORICA, VALERICA; ZAHARIA, CORNELIA; DRICU, ANICA

2014-01-01

In the last years there were many authors that suggest the existence of an association between different components of metabolic syndrome and various cancers. Two important components of metabolic syndrome are hyperglycemia and hyperinsulinemia. Both of them had already been linked with the increased risk of pancreatic, breast, endometrial or prostate cancer. However the correlation of the level of the glucose and insulin with various types and grades of brain tumors remains unclear. In this article we have analysed the values of plasma glucose and insulin in 267 patients, consecutively diagnosed with various types of brain tumors. Our results showed no correlation between the glycemia and brain tumor types or grades. High plasma levels of insulin were found in brain metastasis and astrocytomas while the other types of brain tumors (meningiomas and glioblastomas) had lower levels of the peptide. The levels of insulin were also higher in brain metastasis and grade 3 brain tumors when compared with grade 1, grade 2 and grade 4 brain tumors. PMID:24791202

Cellular phone use and brain tumor: a meta-analysis.

PubMed

Kan, Peter; Simonsen, Sara E; Lyon, Joseph L; Kestle, John R W

2008-01-01

The dramatic increase in the use of cellular phones has generated concerns about potential adverse effects, especially the development of brain tumors. We conducted a meta-analysis to examine the effect of cellular phone use on the risk of brain tumor development. We searched the literature using MEDLINE to locate case-control studies on cellular phone use and brain tumors. Odds ratios (ORs) for overall effect and stratified ORs associated with specific brain tumors, long-term use, and analog/digital phones were calculated for each study using its original data. A pooled estimator of each OR was then calculated using a random-effects model. Nine case-control studies containing 5,259 cases of primary brain tumors and 12,074 controls were included. All studies reported ORs according to brain tumor subtypes, and five provided ORs on patients with > or =10 years of follow up. Pooled analysis showed an overall OR of 0.90 (95% confidence interval [CI] 0.81-0.99) for cellular phone use and brain tumor development. The pooled OR for long-term users of > or =10 years (5 studies) was 1.25 (95% CI 1.01-1.54). No increased risk was observed in analog or digital cellular phone users. We found no overall increased risk of brain tumors among cellular phone users. The potential elevated risk of brain tumors after long-term cellular phone use awaits confirmation by future studies.

Dynamic gamma knife radiosurgery

NASA Astrophysics Data System (ADS)

Luan, Shuang; Swanson, Nathan; Chen, Zhe; Ma, Lijun

2009-03-01

Gamma knife has been the treatment of choice for various brain tumors and functional disorders. Current gamma knife radiosurgery is planned in a 'ball-packing' approach and delivered in a 'step-and-shoot' manner, i.e. it aims to 'pack' the different sized spherical high-dose volumes (called 'shots') into a tumor volume. We have developed a dynamic scheme for gamma knife radiosurgery based on the concept of 'dose-painting' to take advantage of the new robotic patient positioning system on the latest Gamma Knife C™ and Perfexion™ units. In our scheme, the spherical high dose volume created by the gamma knife unit will be viewed as a 3D spherical 'paintbrush', and treatment planning reduces to finding the best route of this 'paintbrush' to 'paint' a 3D tumor volume. Under our dose-painting concept, gamma knife radiosurgery becomes dynamic, where the patient moves continuously under the robotic positioning system. We have implemented a fully automatic dynamic gamma knife radiosurgery treatment planning system, where the inverse planning problem is solved as a traveling salesman problem combined with constrained least-square optimizations. We have also carried out experimental studies of dynamic gamma knife radiosurgery and showed the following. (1) Dynamic gamma knife radiosurgery is ideally suited for fully automatic inverse planning, where high quality radiosurgery plans can be obtained in minutes of computation. (2) Dynamic radiosurgery plans are more conformal than step-and-shoot plans and can maintain a steep dose gradient (around 13% per mm) between the target tumor volume and the surrounding critical structures. (3) It is possible to prescribe multiple isodose lines with dynamic gamma knife radiosurgery, so that the treatment can cover the periphery of the target volume while escalating the dose for high tumor burden regions. (4) With dynamic gamma knife radiosurgery, one can obtain a family of plans representing a tradeoff between the delivery time and the dose distributions, thus giving the clinician one more dimension of flexibility of choosing a plan based on the clinical situations.

What underlies the diversity of brain tumors?

PubMed Central

Swartling, Fredrik J.; Hede, Sanna-Maria; Weiss, William A.

2012-01-01

Glioma and medulloblastoma represent the most commonly occurring malignant brain tumors in adults and in children respectively. Recent genomic and transcriptional approaches present a complex group of diseases, and delineate a number of molecular subgroups within tumors that share a common histopathology. Differences in cells of origin, regional niches, developmental timing and genetic events all contribute to this heterogeneity. In an attempt to recapitulate the diversity of brain tumors, an increasing array of genetically engineered mouse models (GEMMs) has been developed. These models often utilize promoters and genetic drivers from normal brain development, and can provide insight into specific cells from which these tumors originate. GEMMs show promise in both developmental biology and developmental therapeutics. This review describes numerous murine brain tumor models in the context of normal brain development, and the potential for these animals to impact brain tumor research. PMID:23085857

Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies.

PubMed

Vivanti, R; Szeskin, A; Lev-Cohain, N; Sosna, J; Joskowicz, L

2017-11-01

Radiological longitudinal follow-up of liver tumors in CT scans is the standard of care for disease progression assessment and for liver tumor therapy. Finding new tumors in the follow-up scan is essential to determine malignancy, to evaluate the total tumor burden, and to determine treatment efficacy. Since new tumors are typically small, they may be missed by examining radiologists. We describe a new method for the automatic detection and segmentation of new tumors in longitudinal liver CT studies and for liver tumors burden quantification. Its inputs are the baseline and follow-up CT scans, the baseline tumors delineation, and a tumor appearance prior model. Its outputs are the new tumors segmentations in the follow-up scan, the tumor burden quantification in both scans, and the tumor burden change. Our method is the first comprehensive method that is explicitly designed to find new liver tumors. It integrates information from the scans, the baseline known tumors delineations, and a tumor appearance prior model in the form of a global convolutional neural network classifier. Unlike other deep learning-based methods, it does not require large tagged training sets. Our experimental results on 246 tumors, of which 97 were new tumors, from 37 longitudinal liver CT studies with radiologist approved ground-truth segmentations, yields a true positive new tumors detection rate of 86 versus 72% with stand-alone detection, and a tumor burden volume overlap error of 16%. New tumors detection and tumor burden volumetry are important for diagnosis and treatment. Our new method enables a simplified radiologist-friendly workflow that is potentially more accurate and reliable than the existing one by automatically and accurately following known tumors and detecting new tumors in the follow-up scan.

Targeted delivery of antibody-based therapeutic and imaging agents to CNS tumors: Crossing the blood-brain-barrier divide

PubMed Central

Chacko, Ann-Marie; Li, Chunsheng; Pryma, Daniel A.; Brem, Steven; Coukos, George; Muzykantov, Vladimir R.

2014-01-01

Introduction Brain tumors are inherently difficult to treat in large part due to the cellular blood-brain barriers (BBB) that limit the delivery of therapeutics to the tumor tissue from the systemic circulation. Virtually no large-molecules, including antibody-based proteins, can penetrate the BBB. With antibodies fast becoming attractive ligands for highly specific molecular targeting to tumor antigens, a variety of methods are being investigated to enhance the access of these agents to intracranial tumors for imaging or therapeutic applications. Areas covered This review describes the characteristics of the BBB and the vasculature in brain tumors, described as the blood-brain tumor barrier (BBTB). Antibodies targeted to molecular markers of CNS tumors will be highlighted, and current strategies for enhancing the delivery of antibodies across these cellular barriers into the brain parenchyma to the tumor will be discussed. Non-invasive imaging approaches to assess BBB/BBTB permeability and/or antibody targeting will be presented as a means of guiding the optimal delivery of targeted agents to brain tumors. Expert Opinion Pre-clinical and clinical studies highlight the potential of several approaches in increasing brain tumor delivery across the blood-brain barrier divide. However, each carries its own risks and challenges. There is tremendous potential in using neuroimaging strategies to assist in understanding and defining the challenges to translating and optimizing molecularly-targeted antibody delivery to CNS tumors to improve clinical outcomes. PMID:23751126

Improvement of the matching speed of AIMS for development of an automatic totally tuning system for hyperthermia treatment using a resonant cavity applicator.

PubMed

Shindo, Y; Kato, K; Tsuchiya, K; Hirashima, T; Suzuki, M

2009-01-01

In this paper, we discuss the improvement of the speed of AIMS (Automatic Impedance Matching System) to automatically make impedance matching for a re-entrant resonant cavity applicator for non-invasive deep brain tumors hyperthermia treatments. We have already discussed the effectiveness of the heating method using the AIMS, with experiments of heating agar phantoms. However, the operating time of AIMS was about 30 minutes. To develop the ATT System (Automatic Totally Tuning System) including the automatic frequency tuning system, we must improve this problem. Because, when using the ATTS, the AIMS is used repeatedly to find the resonant frequency. In order to improve the speed of impedance matching, we developed the new automatic impedance matching system program (AIMS2). In AIMS, the stepping motors were connected to the impedance matching unit's dials. These dials were turned to reduce the reflected power. AIMS consists of two phases: all range searching and detailed searching. We focused on the three factors affecting the operating speed and improved them. The first factor is the interval put between the turning of the motors and AD converter. The second factor is how the steps of the motor when operating all range searching. The third factor is the starting position of the motor when detail searching. We developed the simple ATT System (ATT-beta) based on the AIMS2. To evaluate the developed AIMS2 and ATT- beta, experiments with an agar phantom were performed. From these results, we found that the operating time of the AIMS2 is about 4 minutes, which was approximately 12% of AIMS. From ATT-beta results, it was shown that it is possible to tune frequency and automatically match impedance with the program based on the AIMS2.

Find a Brain Tumor Center

MedlinePlus

... Ways to Give Charitable Shopping Close Find a Brain Tumor Center Below is a listing of brain ... center is in your insurance plan’s covered network Brain Tumor Treatment Centers: Filter: Mayo Clinic Arizona Mayo ...

Expression of hypoxia-inducible carbonic anhydrases in brain tumors

PubMed Central

Proescholdt, Martin A.; Mayer, Christina; Kubitza, Marion; Schubert, Thomas; Liao, Shu-Yuan; Stanbridge, Eric J.; Ivanov, Sergey; Oldfield, Edward H.; Brawanski, Alexander; Merrill, Marsha J.

2005-01-01

Malignant brain tumors exhibit distinct metabolic characteristics. Despite high levels of lactate, the intracellular pH of brain tumors is more alkaline than normal brain. Additionally, with increasing malignancy, brain tumors display intratumoral hypoxia. Carbonic anhydrase (CA) IX and XII are transmembrane isoenzymes that are induced by tissue hypoxia. They participate in regulation of pH homeostasis by catalyzing the reversible hydration of carbon dioxide. The aim of our study was to investigate whether brain tumors of different histology and grade of malignancy express elevated levels of CA IX and XII as compared to normal brain. We analyzed 120 tissue specimens from brain tumors (primary and metastatic) and normal brain for CA IX and XII expression by immunohistochemistry, Western blot, and in situ hybridization. Whereas normal brain tissue showed minimal levels of CA IX and XII expression, expression in tumors was found to be upregulated with increased level of malignancy. Hemangioblastomas, from patients with von Hippel–Lindau disease, also displayed high levels of CA IX and XII expression. Comparison of CA IX and XII staining with HIF-1α staining revealed a similar microanatomical distribution, indicating hypoxia as a major, but not the only, induction factor. The extent of CA IX and XII staining correlated with cell proliferation, as indicated by Ki67 labeling. The results demonstrate that CA IX and XII are upregulated in intrinsic and metastatic brain tumors as compared to normal brain tissue. This may contribute to the management of tumor-specific acid load and provide a therapeutic target. PMID:16212811

On the Automaticity of Emotion Processing in Words and Faces: Event-Related Brain Potentials Evidence from a Superficial Task

ERIC Educational Resources Information Center

Rellecke, Julian; Palazova, Marina; Sommer, Werner; Schacht, Annekathrin

2011-01-01

The degree to which emotional aspects of stimuli are processed automatically is controversial. Here, we assessed the automatic elicitation of emotion-related brain potentials (ERPs) to positive, negative, and neutral words and facial expressions in an easy and superficial face-word discrimination task, for which the emotional valence was…

Identification of early and distinct glioblastoma response patterns treated by boron neutron capture therapy not predicted by standard radiographic assessment using functional diffusion map

PubMed Central

2013-01-01

Background Radiologic response of brain tumors is traditionally assessed according to the Macdonald criteria 10 weeks from the start of therapy. Because glioblastoma (GB) responds in days rather than weeks after boron neutron capture therapy (BNCT) that is a form of tumor-selective particle radiation, it is inconvenient to use the Macdonald criteria to assess the therapeutic efficacy of BNCT by gadolinium-magnetic resonance imaging (Gd-MRI). Our study assessed the utility of functional diffusion map (fDM) for evaluating response patterns in GB treated by BNCT. Methods The fDM is an image assessment using time-dependent changes of apparent diffusion coefficient (ADC) in tumors on a voxel-by-voxel approach. Other than time-dependent changes of ADC, fDM can automatically assess minimum/maximum ADC, Response Evaluation Criteria In Solid Tumors (RECIST), and the volume of enhanced lesions on Gd-MRI over time. We assessed 17 GB patients treated by BNCT using fDM. Additionally, in order to verify our results, we performed a histopathological examination using F98 rat glioma models. Results Only the volume of tumor with decreased ADC by fDM at 2 days after BNCT was a good predictor for GB patients treated by BNCT (P value = 0.022 by log-rank test and 0.033 by wilcoxon test). In a histopathological examination, brain sections of F98 rat glioma models treated by BNCT showed cell swelling of both the nuclei and the cytoplasm compared with untreated rat glioma models. Conclusions The fDM could identify response patterns in BNCT-treated GB earlier than a standard radiographic assessment. Early detection of treatment failure can allow a change or supplementation before tumor progression and might lead to an improvement of GB patients’ prognosis. PMID:23915330

The modern brain tumor operating room: from standard essentials to current state-of-the-art.

PubMed

Barnett, Gene H; Nathoo, Narendra

2004-01-01

It is just over a century since successful brain tumor resection. Since then the diagnosis, imaging, and management of brain tumors have improved, in large part due to technological advances. Similarly, the operating room (OR) for brain tumor surgery has increased in complexity and specificity with multiple forms of equipment now considered necessary as technical adjuncts. It is evident that the theme of minimalism in combination with advanced image-guidance techniques and a cohort of sophisticated technologies (e.g., robotics and nanotechnology) will drive changes in the current OR environment for the foreseeable future. In this report we describe what may be regarded today as standard essentials in an operating room for the surgical management of brain tumors and what we believe to be the current 'state-of-the-art' brain tumor OR. Also, we speculate on the additional capabilities of the brain tumor OR of the near future.

Childhood Brain Tumor Epidemiology: A Brain Tumor Epidemiology Consortium Review

PubMed Central

Johnson, Kimberly J.; Cullen, Jennifer; Barnholtz-Sloan, Jill S.; Ostrom, Quinn T.; Langer, Chelsea E.; Turner, Michelle C.; McKean-Cowdin, Roberta; Fisher, James L.; Lupo, Philip J.; Partap, Sonia; Schwartzbaum, Judith A.; Scheurer, Michael E.

2014-01-01

Childhood brain tumors are the most common pediatric solid tumor and include several histological subtypes. Although progress has been made in improving survival rates for some subtypes, understanding of risk factors for childhood brain tumors remains limited to a few genetic syndromes and ionizing radiation to the head and neck. In this report, we review descriptive and analytical epidemiology childhood brain tumor studies from the past decade and highlight priority areas for future epidemiology investigations and methodological work that is needed to advance our understanding of childhood brain tumor causes. Specifically, we summarize the results of a review of studies published since 2004 that have analyzed incidence and survival in different international regions and that have examined potential genetic, immune system, developmental and birth characteristics, and environmental risk factors. PMID:25192704

Peri-tumoral leakage during intra-tumoral convection-enhanced delivery has implications for efficacy of peri-tumoral infusion before removal of tumor.

PubMed

Yang, Xiaoliang; Saito, Ryuta; Nakamura, Taigen; Zhang, Rong; Sonoda, Yukihiko; Kumabe, Toshihiro; Forsayeth, John; Bankiewicz, Krystof; Tominaga, Teiji

2016-01-01

In cases of malignant brain tumors, infiltrating tumor cells that exist at the tumor-surrounding brain tissue always escape from cytoreductive surgery and, protected by blood-brain barrier (BBB), survive the adjuvant chemoradiotherapy, eventually leading to tumor recurrence. Local interstitial delivery of chemotherapeutic agents is a promising strategy to target these cells. During our effort to develop effective drug delivery methods by intra-tumoral infusion of chemotherapeutic agents, we found consistent pattern of leakage from the tumor. Here we describe our findings and propose promising strategy to cover the brain tissue surrounding the tumor with therapeutic agents by means of convection-enhanced delivery. First, the intracranial tumor isograft model was used to define patterns of leakage from tumor mass after intra-tumoral infusion of the chemotherapeutic agents. Liposomal doxorubicin, although first distributed inside the tumor, distributed diffusely into the surrounding normal brain once the leakage happen. Trypan blue dye was used to evaluate the distribution pattern of peri-tumoral infusions. When infused intra- or peri-tumorally, infusates distributed robustly into the tumor border. Subsequently, volume of distributions with different infusion scheduling; including intra-tumoral infusion, peri-tumoral infusion after tumor resection, peri-tumoral infusion without tumor removal with or without systemic infusion of steroids, were compared with Evans-blue dye. Peri-tumoral infusion without tumor removal resulted in maximum volume of distribution. Prior use of steroids further increased the volume of distribution. Local interstitial drug delivery targeting tumor surrounding brain tissue before tumor removal should be more effective when targeting the invading cells.

INVITED REVIEW – NEUROIMAGING RESPONSE ASSESSMENT CRITERIA FOR BRAIN TUMORS IN VETERINARY PATIENTS

PubMed Central

Rossmeisl, John H.; Garcia, Paulo A.; Daniel, Gregory B.; Bourland, John Daniel; Debinski, Waldemar; Dervisis, Nikolaos; Klahn, Shawna

2013-01-01

The evaluation of therapeutic response using cross-sectional imaging techniques, particularly gadolinium-enhanced MRI, is an integral part of the clinical management of brain tumors in veterinary patients. Spontaneous canine brain tumors are increasingly recognized and utilized as a translational model for the study of human brain tumors. However, no standardized neuroimaging response assessment criteria have been formulated for use in veterinary clinical trials. Previous studies have found that the pathophysiologic features inherent to brain tumors and the surrounding brain complicate the use of the Response Evaluation Criteria in Solid Tumors (RECIST) assessment system. Objectives of this review are to describe strengths and limitations of published imaging-based brain tumor response criteria and propose a system for use in veterinary patients. The widely used human Macdonald and Response Assessment in Neuro-oncology (RANO) criteria are reviewed and described as to how they can be applied to veterinary brain tumors. Discussion points will include current challenges associated with the interpretation of brain tumor therapeutic responses such as imaging pseudophenomena and treatment-induced necrosis, and how advancements in perfusion imaging, positron emission tomography, and magnetic resonance spectroscopy have shown promise in differentiating tumor progression from therapy-induced changes. Finally, although objective endpoints such as MR-imaging and survival estimates will likely continue to comprise the foundations for outcome measures in veterinary brain tumor clinical trials, we propose that in order to provide a more relevant therapeutic response metric for veterinary patients, composite response systems should be formulated and validated that combine imaging and clinical assessment criteria. PMID:24219161

General Information about Childhood Brain and Spinal Cord Tumors

MedlinePlus

... Cord Tumors Treatment Overview (PDQ®)–Patient Version General Information About Childhood Brain and Spinal Cord Tumors Go ... types of brain and spinal cord tumors. The information from tests and procedures done to detect (find) ...

Lassa-Vesicular Stomatitis Chimeric Virus Safely Destroys Brain Tumors

PubMed Central

Wollmann, Guido; Drokhlyansky, Eugene; Davis, John N.; Cepko, Connie

2015-01-01

ABSTRACT High-grade tumors in the brain are among the deadliest of cancers. Here, we took a promising oncolytic virus, vesicular stomatitis virus (VSV), and tested the hypothesis that the neurotoxicity associated with the virus could be eliminated without blocking its oncolytic potential in the brain by replacing the neurotropic VSV glycoprotein with the glycoprotein from one of five different viruses, including Ebola virus, Marburg virus, lymphocytic choriomeningitis virus (LCMV), rabies virus, and Lassa virus. Based on in vitro infections of normal and tumor cells, we selected two viruses to test in vivo. Wild-type VSV was lethal when injected directly into the brain. In contrast, a novel chimeric virus (VSV-LASV-GPC) containing genes from both the Lassa virus glycoprotein precursor (GPC) and VSV showed no adverse actions within or outside the brain and targeted and completely destroyed brain cancer, including high-grade glioblastoma and melanoma, even in metastatic cancer models. When mice had two brain tumors, intratumoral VSV-LASV-GPC injection in one tumor (glioma or melanoma) led to complete tumor destruction; importantly, the virus moved contralaterally within the brain to selectively infect the second noninjected tumor. A chimeric virus combining VSV genes with the gene coding for the Ebola virus glycoprotein was safe in the brain and also selectively targeted brain tumors but was substantially less effective in destroying brain tumors and prolonging survival of tumor-bearing mice. A tropism for multiple cancer types combined with an exquisite tumor specificity opens a new door to widespread application of VSV-LASV-GPC as a safe and efficacious oncolytic chimeric virus within the brain. IMPORTANCE Many viruses have been tested for their ability to target and kill cancer cells. Vesicular stomatitis virus (VSV) has shown substantial promise, but a key problem is that if it enters the brain, it can generate adverse neurologic consequences, including death. We tested a series of chimeric viruses containing genes coding for VSV, together with a gene coding for the glycoprotein from other viruses, including Ebola virus, Lassa virus, LCMV, rabies virus, and Marburg virus, which was substituted for the VSV glycoprotein gene. Ebola and Lassa chimeric viruses were safe in the brain and targeted brain tumors. Lassa-VSV was particularly effective, showed no adverse side effects even when injected directly into the brain, and targeted and destroyed two different types of deadly brain cancer, including glioblastoma and melanoma. PMID:25878115

Metastasis Infiltration: An Investigation of the Postoperative Brain-Tumor Interface

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

Raore, Bethwel; Schniederjan, Matthew; Prabhu, Roshan

Purpose: This study aims to evaluate brain infiltration of metastatic tumor cells past the main tumor resection margin to assess the biological basis for the use of stereotactic radiosurgery treatment of the tumor resection cavity and visualized resection edge or clinical target volume. Methods and Materials: Resection margin tissue was obtained after gross total resection of a small group of metastatic lesions from a variety of primary sources. The tissue at the border of the tumor and brain tissue was carefully oriented and processed to evaluate the presence of tumor cells within brain tissue and their distance from the resectionmore » margin. Results: Microscopic assessment of the radially oriented tissue samples showed no tumor cells infiltrating the surrounding brain tissue. Among the positive findings were reactive astrocytosis observed on the brain tissue immediately adjacent to the tumor resection bed margin. Conclusions: The lack of evidence of metastatic tumor cell infiltration into surrounding brain suggests the need to target only a narrow depth of the resection cavity margin to minimize normal tissue injury and prevent treatment size-dependent stereotactic radiosurgery complications.« less

Adult Central Nervous System Tumors Treatment (PDQ®)—Health Professional Version

Cancer.gov

Most primary brain tumors are astrocytomas, glioblastomas, and meningiomas. Most primary spinal tumors are schwannomas, meningiomas, and ependymomas. Metastatic brain tumors have spread to the brain from other parts of the body. Get detailed information about CNS tumors and treatment in this summary for clinicians.

Half brain irradiation in a murine model of breast cancer brain metastasis: magnetic resonance imaging and histological assessments of dose-response.

PubMed

Zarghami, Niloufar; Murrell, Donna H; Jensen, Michael D; Dick, Frederick A; Chambers, Ann F; Foster, Paula J; Wong, Eugene

2018-06-01

Brain metastasis is becoming increasingly prevalent in breast cancer due to improved extra-cranial disease control. With emerging availability of modern image-guided radiation platforms, mouse models of brain metastases and small animal magnetic resonance imaging (MRI), we examined brain metastases' responses from radiotherapy in the pre-clinical setting. In this study, we employed half brain irradiation to reduce inter-subject variability in metastases dose-response evaluations. Half brain irradiation was performed on a micro-CT/RT system in a human breast cancer (MDA-MB-231-BR) brain metastasis mouse model. Radiation induced DNA double stranded breaks in tumors and normal mouse brain tissue were quantified using γ-H2AX immunohistochemistry at 30 min (acute) and 11 days (longitudinal) after half-brain treatment for doses of 8, 16 and 24 Gy. In addition, tumor responses were assessed volumetrically with in-vivo longitudinal MRI and histologically for tumor cell density and nuclear size. In the acute setting, γ-H2AX staining in tumors saturated at higher doses while normal mouse brain tissue continued to increase linearly in the phosphorylation of H2AX. While γ-H2AX fluorescence intensities returned to the background level in the brain 11 days after treatment, the residual γ-H2AX phosphorylation in the radiated tumors remained elevated compared to un-irradiated contralateral tumors. With radiation, MRI-derived relative tumor growth was significantly reduced compared to the un-irradiated side. While there was no difference in MRI tumor volume growth between 16 and 24 Gy, there was a significant reduction in tumor cell density from histology with increasing dose. In the longitudinal study, nuclear size in the residual tumor cells increased significantly as the radiation dose was increased. Radiation damages to the DNAs in the normal brain parenchyma are resolved over time, but remain unrepaired in the treated tumors. Furthermore, there is a radiation dose response in nuclear size of surviving tumor cells. Increase in nuclear size together with unrepaired DNA damage indicated that the surviving tumor cells post radiation had continued to progress in the cell cycle with DNA replication, but failed cytokinesis. Half brain irradiation provides efficient evaluation of dose-response for cancer cell lines, a pre-requisite to perform experiments to understand radio-resistance in brain metastases.

Examination of Blood-Brain Barrier (BBB) Integrity In A Mouse Brain Tumor Model

PubMed Central

On, Ngoc; Mitchell, Ryan; Savant, Sanjot D.; Bachmeier, Corbin. J.; Hatch, Grant M.; Miller, Donald W.

2013-01-01

The present study evaluates, both functionally and biochemically, brain tumor-induced alterations in brain capillary endothelial cells. Brain tumors were induced in Balb/c mice via intracranial injection of Lewis Lung carcinoma (3LL) cells into the right hemisphere of the mouse brain using stereotaxic apparatus. Blood-brain barrier (BBB) permeability was assessed at various stages of tumor development, using both radiolabeled tracer permeability and magnetic resonance imaging (MRI) with gadolinium diethylene-triamine-pentaacetate contrast enhancement (Gad-DTPA). The expression of the drug efflux transporter, P-glycoprotein (P-gp), in the BBB at various stages of tumor development was also evaluated by Western blot and immunohistochemistry. Median mouse survival following tumor cell injection was 17 days. The permeability of the BBB to 3H-mannitol was similar in both brain hemispheres at 7 and 10 days post-injection. By day 15, there was a 2-fold increase in 3H-mannitol permeability in the tumor bearing hemispheres compared to the non-tumor hemispheres. Examination of BBB permeability with Gad-DTPA contrast enhanced MRI indicated cerebral vascular permeability changes were confined to the tumor area. The permeability increase observed at the later stages of tumor development correlated with an increase in cerebral vascular volume suggesting angiogenesis within the tumor bearing hemisphere. Furthermore, the Gad-DPTA enhancement observed within the tumor area was significantly less than Gad-DPTA enhancement within the circumventricular organs not protected by the BBB. Expression of P-gp in both the tumor bearing and non-tumor bearing portions of the brain appeared similar at all time points examined. These studies suggest that although BBB integrity is altered within the tumor site at later stages of development, the BBB is still functional and limiting in terms of solute and drug permeability in and around the tumor. PMID:23184143

Quantitative imaging of magnesium distribution at single-cell resolution in brain tumors and infiltrating tumor cells with secondary ion mass spectrometry (SIMS)

PubMed Central

Chandra, Subhash; Parker, Dylan J.; Barth, Rolf F.; Pannullo, Susan C.

2016-01-01

Glioblastoma multiforme (GBM) is one of the deadliest forms of human brain tumors. The infiltrative pattern of growth of these tumors includes the spread of individual and/or clusters of tumor cells at some distance from the main tumor mass in parts of the brain protected by an intact blood-brain-barrier. Pathophysiological studies of GBM could be greatly enhanced by analytical techniques capable of in situ single-cell resolution measurements of infiltrating tumor cells. Magnesium homeostasis is an area of active investigation in high grade gliomas. In the present study, we have used the F98 rat glioma as a model of human GBM and an elemental/isotopic imaging technique of secondary ion mass spectrometry (SIMS), a CAMECA IMS-3f ion microscope, for studying Mg distributions with single-cell resolution in freeze-dried brain tissue cryosections. Quantitative observations were made on tumor cells in the main tumor mass, contiguous brain tissue, and infiltrating tumor cells in adjacent normal brain. The brain tissue contained a significantly lower total Mg concentration of 4.70 ± 0.93 mmol/Kg wet weight (mean ± SD) in comparison to 11.64 ± 1.96 mmol/Kg wet weight in tumor cells of the main tumor mass and 10.72 ± 1.76 mmol/Kg wet weight in infiltrating tumor cells (p<0.05). The nucleus of individual tumor cells contained elevated levels of bound Mg. These observations demonstrate enhanced Mg-influx and increased binding of Mg in tumor cells and provide strong support for further investigation of GBMs for altered Mg homeostasis and activation of Mg-transporting channels as possible therapeutic targets. PMID:26703785

Fluorescence Imaging/Agents in Tumor Resection.

PubMed

Stummer, Walter; Suero Molina, Eric

2017-10-01

Intraoperative fluorescence imaging allows real-time identification of diseased tissue during surgery without being influenced by brain shift and surgery interruption. 5-Aminolevulinic acid, useful for malignant gliomas and other tumors, is the most broadly explored compound approved for fluorescence-guided resection. Intravenous fluorescein sodium has recently received attention, highlighting tumor tissue based on extravasation at the blood-brain barrier (defective in many brain tumors). Fluorescein in perfused brain, unselective extravasation in brain perturbed by surgery, and propagation with edema are concerns. Fluorescein is not approved but targeted fluorochromes with affinity to brain tumor cells, in development, may offer future advantages. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Automatic Incubator-type Temperature Control System for Brain Hypothermia Treatment

NASA Astrophysics Data System (ADS)

Gaohua, Lu; Wakamatsu, Hidetoshi

An automatic air-cooling incubator is proposed to replace the manual water-cooling blanket to control the brain tissue temperature for brain hypothermia treatment. Its feasibility is theoretically discussed as follows: First, an adult patient with the cooling incubator is modeled as a linear dynamical patient-incubator biothermal system. The patient is represented by an 18-compartment structure and described by its state equations. The air-cooling incubator provides almost same cooling effect as the water-cooling blanket, if a light breeze of speed around 3 m/s is circulated in the incubator. Then, in order to control the brain temperature automatically, an adaptive-optimal control algorithm is adopted, while the patient-blanket therapeutic system is considered as a reference model. Finally, the brain temperature of the patient-incubator biothermal system is controlled to follow up the given reference temperature course, in which an adaptive algorithm is confirmed useful for unknown environmental change and/or metabolic rate change of the patient in the incubating system. Thus, the present work ensures the development of the automatic air-cooling incubator for a better temperature regulation of the brain hypothermia treatment in ICU.

Automatic MRI 2D brain segmentation using graph searching technique.

PubMed

Pedoia, Valentina; Binaghi, Elisabetta

2013-09-01

Accurate and efficient segmentation of the whole brain in magnetic resonance (MR) images is a key task in many neuroscience and medical studies either because the whole brain is the final anatomical structure of interest or because the automatic extraction facilitates further analysis. The problem of segmenting brain MRI images has been extensively addressed by many researchers. Despite the relevant achievements obtained, automated segmentation of brain MRI imagery is still a challenging problem whose solution has to cope with critical aspects such as anatomical variability and pathological deformation. In the present paper, we describe and experimentally evaluate a method for segmenting brain from MRI images basing on two-dimensional graph searching principles for border detection. The segmentation of the whole brain over the entire volume is accomplished slice by slice, automatically detecting frames including eyes. The method is fully automatic and easily reproducible by computing the internal main parameters directly from the image data. The segmentation procedure is conceived as a tool of general applicability, although design requirements are especially commensurate with the accuracy required in clinical tasks such as surgical planning and post-surgical assessment. Several experiments were performed to assess the performance of the algorithm on a varied set of MRI images obtaining good results in terms of accuracy and stability. Copyright © 2012 John Wiley & Sons, Ltd.

A multicenter study of primary brain tumor incidence in Australia (2000–2008)

PubMed Central

Dobes, Martin; Shadbolt, Bruce; Khurana, Vini G.; Jain, Sanjiv; Smith, Sarah F.; Smee, Robert; Dexter, Mark; Cook, Raymond

2011-01-01

There are conflicting reports from Europe and North America regarding trends in the incidence of primary brain tumor, whereas the incidence of primary brain tumors in Australia is currently unknown. We aimed to determine the incidence in Australia with age-, sex-, and benign-versus-malignant histology-specific analyses. A multicenter study was performed in the state of New South Wales (NSW) and the Australian Capital Territory (ACT), which has a combined population of >7 million with >97% rate of population retention for medical care. We retrospectively mined pathology databases servicing neurosurgical centers in NSW and ACT for histologically confirmed primary brain tumors diagnosed from January 2000 through December 2008. Data were weighted for patient outflow and data completeness. Incidence rates were age standardized and trends analyzed using joinpoint analysis. A weighted total of 7651 primary brain tumors were analyzed. The overall US-standardized incidence of primary brain tumors was 11.3 cases 100 000 person-years (±0.13; 95% confidence interval, 9.8–12.3) during the study period with no significant linear increase. A significant increase in primary malignant brain tumors from 2000 to 2008 was observed; this appears to be largely due to an increase in malignant tumor incidence in the ≥65-year age group. This collection represents the most contemporary data on primary brain tumor incidence in Australia. Whether the observed increase in malignant primary brain tumors, particularly in persons aged ≥65 years, is due to improved detection, diagnosis, and care delivery or a true change in incidence remains undetermined. We recommend a direct, uniform, and centralized approach to monitoring primary brain tumor incidence that can be independent of multiple interstate cancer registries. PMID:21727214

Inhibition of angiogenesis and tumor growth in the brain. Suppression of endothelial cell turnover by penicillamine and the depletion of copper, an angiogenic cofactor.

PubMed Central

Brem, S. S.; Zagzag, D.; Tsanaclis, A. M.; Gately, S.; Elkouby, M. P.; Brien, S. E.

1990-01-01

Microvascular proliferation, a hallmark of malignant brain tumors, represents an attractive target of anticancer research, especially because of the quiescent nonproliferative endothelium of the normal brain. Cerebral neoplasms sequester copper, a trace metal that modulates angiogenesis. Using a rabbit brain tumor model, normocupremic animals developed large vascularized VX2 carcinomas. By contrast, small, circumscribed, relatively avascular tumors were found in the brains of rabbits copper-depleted by diet and penicillamine treatment (CDPT). The CDPT rabbits showed a significant decrease in serum copper, copper staining of tumor cell nuclei, microvascular density, the tumor volume, endothelial cell turnover, and an increase in the vascular permeability (breakdown of the blood-brain barrier), as well as peritumoral brain edema. In non-tumor-bearing animals, CDPT did not alter the vascular permeability or the brain water content. CDPT also inhibited the intracerebral growth of the 9L gliosarcoma in F-344 rats, with a similar increase of the peritumoral vascular permeability and the brain water content. CDPT failed to inhibit tumor growth and the vascularization of the VX2 carcinoma in the thigh muscle or the metastases to the lung, findings that may reflect regional differences in the responsiveness of the endothelium, the distribution of copper, or the activity of cuproenzymes. Metabolic and pharmacologic withdrawal of copper suppresses intracerebral tumor angiogenesis; angiosuppression is a novel biologic response modifier for the in situ control of tumor growth in the brain. Images Figure 2 Figure 4 Figure 5 Figure 6 Figure 8 Figure 10 Figure 12 Figure 15 Figure 16 PMID:1700617

Targeting Brain Tumors with Nanomedicines: Overcoming Challenges of Blood Brain Barrier.

PubMed

Ningaraj, Nagendra S; Reddy, Polluru L; Khaitan, Divya

2018-04-12

This review elucidates ongoing research, which show improved delivery of anticancer drugs alone and/ or enclosed in carriers collectively called nanomedicines to cross the Blood brain barrier (BBB) / blood-brain tumor barrier (BTB) to kill tumor cells and impact patient survival. We highlighted various advances in understanding the mechanism of BTB function that impact on anticancer therapeutics delivery. We discussed latest breakthroughs in developing pharmaceutical strategies, including nanomedicines and delivering them across BTB for brain tumor management and treatment. We highlight various studies on regulation of BTB permeability regulation with respect to nanotech-based nanomedicines for targeted treatment of brain tumors. We have reviewed latest literature on development of specialized molecules and nanospheres for carrying pay load of anticancer agents to brain tumor cells across the BBB/ BTB and avoid drug efflux systems. We discuss identification and development of distinctive BTB biomarkers for targeted anti-cancer drug delivery to brain tumors. In addition, we discussed nanomedicines and multimeric molecular therapeutics that were encapsulated in nanospheres for treatment and monitoring of brain tumors. In this context, we highlight our research on calcium-activated potassium channels (KCa) and ATP-sensitive potassium channels (KATP) as portals of enhanced antineoplastic drugs delivery. This review might interest both academic and drug company scientists involved in drug delivery to brain tumors. We further seek to present evidence that BTB modulators can be clinically developed as combination drug or/ and as stand-alone anticancer drugs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Pediatric Brain Tumors: Genomics and Epigenomics Pave the Way.

PubMed

Fontebasso, Adam M; Jabado, Nada

2015-01-01

Primary malignant brain tumors remain a disproportionate cause of morbidity and mortality in humans. A number of studies exploring the cancer genome of brain tumors across ages using integrated genetics and epigenetics and next-generation sequencing technologies have recently emerged. This has led to considerable advances in the understanding of the basic biology and pathogenesis of brain tumors, including the most malignant and common variants in children: gliomas and medulloblastoma. Notably, studies of pediatric brain tumors have identified unexpected oncogenic pathways implicated in tumorigenesis. These range from a single pathway/molecule defect such as abnormalities of the mitogen-activated protein kinase pathway, considered to be a hallmark of pilocytic astrocytomas, to alterations in the epigenome as a critical component altered in many subgroups of high-grade brain tumors. Importantly, the type, timing, and spatial clustering of these molecular alterations provide a better understanding of the pathogenesis of the respective brain tumor they target and critical markers for therapy that will help refine pathological grading. We summarize these novel findings in pediatric brain tumors, which also are put in the context of the evolving notion of molecular pathology, now a mandated tool for proper classification and therapy assignment in the clinical setting.

Tumor segmentation of multi-echo MR T2-weighted images with morphological operators

NASA Astrophysics Data System (ADS)

Torres, W.; Martín-Landrove, M.; Paluszny, M.; Figueroa, G.; Padilla, G.

2009-02-01

In the present work an automatic brain tumor segmentation procedure based on mathematical morphology is proposed. The approach considers sequences of eight multi-echo MR T2-weighted images. The relaxation time T2 characterizes the relaxation of water protons in the brain tissue: white matter, gray matter, cerebrospinal fluid (CSF) or pathological tissue. Image data is initially regularized by the application of a log-convex filter in order to adjust its geometrical properties to those of noiseless data, which exhibits monotonously decreasing convex behavior. Finally the regularized data is analyzed by means of an 8-dimensional morphological eccentricity filter. In a first stage, the filter was used for the spatial homogenization of the tissues in the image, replacing each pixel by the most representative pixel within its structuring element, i.e. the one which exhibits the minimum total distance to all members in the structuring element. On the filtered images, the relaxation time T2 is estimated by means of least square regression algorithm and the histogram of T2 is determined. The T2 histogram was partitioned using the watershed morphological operator; relaxation time classes were established and used for tissue classification and segmentation of the image. The method was validated on 15 sets of MRI data with excellent results.

Penetration of intra-arterially administered vincristine in experimental brain tumor1,2

PubMed Central

Boyle, Frances M.; Eller, Susan L.; Grossman, Stuart A.

2004-01-01

Vincristine is an integral part of the “PCV” regimen that is commonly administered to treat primary brain tumors. The efficacy of vincristine as a single agent in these tumors has been poorly studied. This study was designed to determine whether vincristine enters normal rat brain or an intracranially or subcutaneously implanted glioma and to assess the presence of the efflux pump P-glycoprotein (P-gp) on tumor and vascular endothelial cells. The 9L rat gliosarcoma was implanted intracranially and subcutaneously in three Fischer 344 rats. On day 7, [3H]vincristine (50 μCi, 4.8 μg) was injected into the carotid artery, and the animals were euthanized 10 or 20 min later. Quantitative autoradiography revealed that vincristine levels in the liver were 6- to 11-fold greater than in the i.c. tumor, and 15- to 37-fold greater than in normal brain, the reverse of the expected pattern with intra-arterial delivery. Vincristine levels in the s.c. tumor were 2-fold higher than levels in the i.c. tumor. P-gp was detected with JSB1 antibody in vascular endothelium of both normal brain and the i.c. tumor, but not in the tumor cells in either location, or in endothelial cells in the s.c. tumor. These results demonstrate that vincristine has negligible penetration of normal rat brain or i.c. 9L glioma despite intra-arterial delivery and the presence of blood-brain barrier dysfunction as demonstrated by Evan’s blue. Furthermore, this study suggests that P-gp-mediated efflux from endothelium may explain these findings. The lack of penetration of vincristine into brain tumor and the paucity of single-agent activity studies suggest that vincristine should not be used in the treatment of primary brain tumors. PMID:15494097

Brain tumor initiating cells adapt to restricted nutrition through preferential glucose uptake.

PubMed

Flavahan, William A; Wu, Qiulian; Hitomi, Masahiro; Rahim, Nasiha; Kim, Youngmi; Sloan, Andrew E; Weil, Robert J; Nakano, Ichiro; Sarkaria, Jann N; Stringer, Brett W; Day, Bryan W; Li, Meizhang; Lathia, Justin D; Rich, Jeremy N; Hjelmeland, Anita B

2013-10-01

Like all cancers, brain tumors require a continuous source of energy and molecular resources for new cell production. In normal brain, glucose is an essential neuronal fuel, but the blood-brain barrier limits its delivery. We now report that nutrient restriction contributes to tumor progression by enriching for brain tumor initiating cells (BTICs) owing to preferential BTIC survival and to adaptation of non-BTICs through acquisition of BTIC features. BTICs outcompete for glucose uptake by co-opting the high affinity neuronal glucose transporter, type 3 (Glut3, SLC2A3). BTICs preferentially express Glut3, and targeting Glut3 inhibits BTIC growth and tumorigenic potential. Glut3, but not Glut1, correlates with poor survival in brain tumors and other cancers; thus, tumor initiating cells may extract nutrients with high affinity. As altered metabolism represents a cancer hallmark, metabolic reprogramming may maintain the tumor hierarchy and portend poor prognosis.

Selective Targeting of Brain Tumors with Gold Nanoparticle-Induced Radiosensitization

PubMed Central

Joh, Daniel Y.; Sun, Lova; Stangl, Melissa; Al Zaki, Ajlan; Murty, Surya; Santoiemma, Phillip P.; Davis, James J.; Baumann, Brian C.; Alonso-Basanta, Michelle; Bhang, Dongha; Kao, Gary D.; Tsourkas, Andrew; Dorsey, Jay F.

2013-01-01

Successful treatment of brain tumors such as glioblastoma multiforme (GBM) is limited in large part by the cumulative dose of Radiation Therapy (RT) that can be safely given and the blood-brain barrier (BBB), which limits the delivery of systemic anticancer agents into tumor tissue. Consequently, the overall prognosis remains grim. Herein, we report our pilot studies in cell culture experiments and in an animal model of GBM in which RT is complemented by PEGylated-gold nanoparticles (GNPs). GNPs significantly increased cellular DNA damage inflicted by ionizing radiation in human GBM-derived cell lines and resulted in reduced clonogenic survival (with dose-enhancement ratio of ∼1.3). Intriguingly, combined GNP and RT also resulted in markedly increased DNA damage to brain blood vessels. Follow-up in vitro experiments confirmed that the combination of GNP and RT resulted in considerably increased DNA damage in brain-derived endothelial cells. Finally, the combination of GNP and RT increased survival of mice with orthotopic GBM tumors. Prior treatment of mice with brain tumors resulted in increased extravasation and in-tumor deposition of GNP, suggesting that RT-induced BBB disruption can be leveraged to improve the tumor-tissue targeting of GNP and thus further optimize the radiosensitization of brain tumors by GNP. These exciting results together suggest that GNP may be usefully integrated into the RT treatment of brain tumors, with potential benefits resulting from increased tumor cell radiosensitization to preferential targeting of tumor-associated vasculature. PMID:23638079

Biodegradable brain-penetrating DNA nanocomplexes and their use to treat malignant brain tumors

PubMed Central

Mastorakos, Panagiotis; Zhang, Clark; Song, Eric; Kim, Young Eun; Park, Hee Won; Berry, Sneha; Choi, Won Kyu; Hanes, Justin; Suk, Jung Soo

2018-01-01

The discovery of powerful genetic targets has spurred clinical development of gene therapy approaches to treat patients with malignant brain tumors. However, lack of success in the clinic has been attributed to the inability of conventional gene vectors to achieve gene transfer throughout highly disseminated primary brain tumors. Here, we demonstrate ex vivo that small nanocomplexes composed of DNA condensed by a blend of biodegradable polymer, poly(β-amino ester) (PBAE), with PBAE conjugated with 5 kDa polyethylene glycol (PEG) molecules (PBAE-PEG) rapidly penetrate healthy brain parenchyma and orthotopic brain tumor tissues in rats. Rapid diffusion of these DNA-loaded nanocomplexes observed in fresh tissues ex vivo demonstrated that they avoided adhesive trapping in the brain owing to their dense PEG coating, which was critical to achieving widespread transgene expression throughout orthotopic rat brain tumors in vivo following administration by convection enhanced delivery. Transgene expression with the PBAE/PBAE-PEG blended nanocomplexes (DNA-loaded brain-penetrating nanocomplexes, or DNA-BPN) was uniform throughout the tumor core compared to nanocomplexes composed of DNA with PBAE only (DNA-loaded conventional nanocomplexes, or DNA-CN), and transgene expression reached beyond the tumor edge, where infiltrative cancer cells are found, only for the DNA-BPN formulation. Finally, DNA-BPN loaded with anti-cancer plasmid DNA provided significantly enhanced survival compared to the same plasmid DNA loaded in DNA-CN in two aggressive orthotopic brain tumor models in rats. These findings underscore the importance of achieving widespread delivery of therapeutic nucleic acids within brain tumors and provide a promising new delivery platform for localized gene therapy in the brain. PMID:28694032

Stereotactic Radiosurgery in Treating Patients With Brain Tumors

ClinicalTrials.gov

2012-03-21

Adult Central Nervous System Germ Cell Tumor; Adult Malignant Meningioma; Adult Medulloblastoma; Adult Noninfiltrating Astrocytoma; Adult Oligodendroglioma; Adult Craniopharyngioma; Adult Meningioma; Brain Metastases; Adult Ependymoma; Adult Pineal Parenchymal Tumor; Adult Brain Stem Glioma; Adult Infiltrating Astrocytoma; Mixed Gliomas; Stage IV Peripheral Primitive Neuroectodermal Tumor

Clinical efficacy of positron emission tomography

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

Heiss, W.D.; Pawlick, G.; Herholz, K.

1987-01-01

The contents of this book are: Brain: Cerebral Vascular Disease; Brain: Movement Disorders; Brain: Epilepsy and Pediatric Neurology; Brain: Dementias; Brain: Schizophrenia; Heart: Angina Pectoris; Heart: Infarction; Lungs; Soft Tissue Tumors; and Brain Tumors.

Mechanical characterization of human brain tumors from patients and comparison to potential surgical phantoms.

PubMed

Stewart, Daniel C; Rubiano, Andrés; Dyson, Kyle; Simmons, Chelsey S

2017-01-01

While mechanical properties of the brain have been investigated thoroughly, the mechanical properties of human brain tumors rarely have been directly quantified due to the complexities of acquiring human tissue. Quantifying the mechanical properties of brain tumors is a necessary prerequisite, though, to identify appropriate materials for surgical tool testing and to define target parameters for cell biology and tissue engineering applications. Since characterization methods vary widely for soft biological and synthetic materials, here, we have developed a characterization method compatible with abnormally shaped human brain tumors, mouse tumors, animal tissue and common hydrogels, which enables direct comparison among samples. Samples were tested using a custom-built millimeter-scale indenter, and resulting force-displacement data is analyzed to quantify the steady-state modulus of each sample. We have directly quantified the quasi-static mechanical properties of human brain tumors with effective moduli ranging from 0.17-16.06 kPa for various pathologies. Of the readily available and inexpensive animal tissues tested, chicken liver (steady-state modulus 0.44 ± 0.13 kPa) has similar mechanical properties to normal human brain tissue while chicken crassus gizzard muscle (steady-state modulus 3.00 ± 0.65 kPa) has similar mechanical properties to human brain tumors. Other materials frequently used to mimic brain tissue in mechanical tests, like ballistic gel and chicken breast, were found to be significantly stiffer than both normal and diseased brain tissue. We have directly compared quasi-static properties of brain tissue, brain tumors, and common mechanical surrogates, though additional tests would be required to determine more complex constitutive models.

Drugs Approved for Brain Tumors

MedlinePlus

... Ask about Your Treatment Research Drugs Approved for Brain Tumors This page lists cancer drugs approved by ... that are not listed here. Drugs Approved for Brain Tumors Afinitor (Everolimus) Afinitor Disperz (Everolimus) Avastin (Bevacizumab) ...

Children's Brain Tumor Foundation

MedlinePlus

... 2 Family Donate Volunteer Justin's Hope Fund Children’s Brain Tumor Foundation, A non-profit organization, was founded ... and the long term outlook for children with brain and spinal cord tumors through research, support, education, ...

Novel strategies of Raman imaging for brain tumor research.

PubMed

Anna, Imiela; Bartosz, Polis; Lech, Polis; Halina, Abramczyk

2017-10-17

Raman diagnostics and imaging have been shown to be an effective tool for the analysis and discrimination of human brain tumors from normal structures. Raman spectroscopic methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n= 5), low-grade astrocytoma (grades I-II WHO) (n =4), ependymoma (n=3) and metastatic brain tumors (n= 1) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma, low grade astrocytoma and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational features and Raman images we provide a real-time feedback method that is label-free to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, proteins, DNA and RNA. Our results indicate marked metabolic differences between low and high grade brain tumors. We discuss molecular mechanisms causing these metabolic changes, particularly lipid alterations in malignant medulloblastoma and low grade gliomas that may shed light on the mechanisms driving tumor recurrence thereby revealing new approaches for the treatment of malignant glioma. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have found that almost all tumors studied in the paper have increased Raman signals of nucleic acids. This increase can be interpreted as increased DNA/RNA turnover in brain tumors. We have shown that the ratio of Raman intensities I 2930 /I 2845 at 2930 and 2845 cm -1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the different lipid and protein contents of cancerous brain tissue compared to the non-tumor tissue. We found that levels of the saturated fatty acids were significantly reduced in the high grade medulloblastoma samples compared with non-tumor brain samples and low grade astrocytoma. Differences were also noted in the n-6/n-3 polyunsaturated fatty acids (PUFA) content between medulloblastoma and non-tumor brain samples. The content of the oleic acid (OA) was significantly smaller in almost all brain high grade brain tumors than that observed in the control samples. It indicates that the fatty acid composition of human brain tumors differs from that found in non-tumor brain tissue. The iodine number N I for the normal brain tissue is 60. For comparison OA has 87, docosahexaenoic acid (DHA) 464, α-linolenic acid (ALA) 274. The high grade tumors have the iodine numbers between that for palmitic acid, stearic acid, arachidic acid (N I =0) and oleic acid (N I =87). Most low grade tumors have N I similar to that of OA. The iodine number for arachidonic acid (AA) (N I =334) is much higher than those observed for all studied samples.

Novel strategies of Raman imaging for brain tumor research

PubMed Central

Anna, Imiela; Bartosz, Polis; Lech, Polis; Halina, Abramczyk

2017-01-01

Raman diagnostics and imaging have been shown to be an effective tool for the analysis and discrimination of human brain tumors from normal structures. Raman spectroscopic methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n= 5), low-grade astrocytoma (grades I-II WHO) (n =4), ependymoma (n=3) and metastatic brain tumors (n= 1) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma, low grade astrocytoma and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational features and Raman images we provide a real–time feedback method that is label-free to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, proteins, DNA and RNA. Our results indicate marked metabolic differences between low and high grade brain tumors. We discuss molecular mechanisms causing these metabolic changes, particularly lipid alterations in malignant medulloblastoma and low grade gliomas that may shed light on the mechanisms driving tumor recurrence thereby revealing new approaches for the treatment of malignant glioma. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have found that almost all tumors studied in the paper have increased Raman signals of nucleic acids. This increase can be interpreted as increased DNA/RNA turnover in brain tumors. We have shown that the ratio of Raman intensities I2930/I2845 at 2930 and 2845 cm-1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the different lipid and protein contents of cancerous brain tissue compared to the non-tumor tissue. We found that levels of the saturated fatty acids were significantly reduced in the high grade medulloblastoma samples compared with non-tumor brain samples and low grade astrocytoma. Differences were also noted in the n-6/n-3 polyunsaturated fatty acids (PUFA) content between medulloblastoma and non-tumor brain samples. The content of the oleic acid (OA) was significantly smaller in almost all brain high grade brain tumors than that observed in the control samples. It indicates that the fatty acid composition of human brain tumors differs from that found in non-tumor brain tissue. The iodine number NI for the normal brain tissue is 60. For comparison OA has 87, docosahexaenoic acid (DHA) 464, α-linolenic acid (ALA) 274. The high grade tumors have the iodine numbers between that for palmitic acid, stearic acid, arachidic acid (NI=0) and oleic acid (NI=87). Most low grade tumors have NI similar to that of OA. The iodine number for arachidonic acid (AA) (NI=334) is much higher than those observed for all studied samples. PMID:29156720

Long-term exposure to ambient air pollution and incidence of brain tumor: the European Study of Cohorts for Air Pollution Effects (ESCAPE)

PubMed Central

Pedersen, Marie; Weinmayr, Gudrun; Stafoggia, Massimo; Galassi, Claudia; Jørgensen, Jeanette T; Sommar, Johan N; Forsberg, Bertil; Olsson, David; Oftedal, Bente; Aasvang, Gunn Marit; Schwarze, Per; Pyko, Andrei; Pershagen, Göran; Korek, Michal; Faire, Ulf De; Östenson, Claes-Göran; Fratiglioni, Laura; Eriksen, Kirsten T; Poulsen, Aslak H; Tjønneland, Anne; Bräuner, Elvira Vaclavik; Peeters, Petra H; Bueno-de-Mesquita, Bas; Jaensch, Andrea; Nagel, Gabriele; Lang, Alois; Wang, Meng; Tsai, Ming-Yi; Grioni, Sara; Marcon, Alessandro; Krogh, Vittorio; Ricceri, Fulvio; Sacerdote, Carlotta; Migliore, Enrica; Vermeulen, Roel; Sokhi, Ranjeet; Keuken, Menno; de Hoogh, Kees; Beelen, Rob; Vineis, Paolo; Cesaroni, Giulia; Brunekreef, Bert; Hoek, Gerard; Raaschou-Nielsen, Ole

2018-01-01

Abstract Background Epidemiological evidence on the association between ambient air pollution and brain tumor risk is sparse and inconsistent. Methods In 12 cohorts from 6 European countries, individual estimates of annual mean air pollution levels at the baseline residence were estimated by standardized land-use regression models developed within the ESCAPE and TRANSPHORM projects: particulate matter (PM) ≤2.5, ≤10, and 2.5–10 μm in diameter (PM2.5, PM10, and PMcoarse), PM2.5 absorbance, nitrogen oxides (NO2 and NOx) and elemental composition of PM. We estimated cohort-specific associations of air pollutant concentrations and traffic intensity with total, malignant, and nonmalignant brain tumor, in separate Cox regression models, adjusting for risk factors, and pooled cohort-specific estimates using random-effects meta-analyses. Results Of 282194 subjects from 12 cohorts, 466 developed malignant brain tumors during 12 years of follow-up. Six of the cohorts also had data on nonmalignant brain tumor, where among 106786 subjects, 366 developed brain tumor: 176 nonmalignant and 190 malignant. We found a positive, statistically nonsignificant association between malignant brain tumor and PM2.5 absorbance (hazard ratio and 95% CI: 1.67; 0.89–3.14 per 10–5/m3), and weak positive or null associations with the other pollutants. Hazard ratio for PM2.5 absorbance (1.01; 0.38–2.71 per 10–5/m3) and all other pollutants were lower for nonmalignant than for malignant brain tumors. Conclusion We found suggestive evidence of an association between long-term exposure to PM2.5 absorbance indicating traffic-related air pollution and malignant brain tumors, and no association with overall or nonmalignant brain tumors. PMID:29016987

Demeclocycline as a contrast agent for detecting brain neoplasms using confocal microscopy

NASA Astrophysics Data System (ADS)

Wirth, Dennis; Smith, Thomas W.; Moser, Richard; Yaroslavsky, Anna N.

2015-04-01

Complete resection of brain tumors improves life expectancy and quality. Thus, there is a strong need for high-resolution detection and microscopically controlled removal of brain neoplasms. The goal of this study was to test demeclocycline as a contrast enhancer for the intraoperative detection of brain tumors. We have imaged benign and cancerous brain tumors using multimodal confocal microscopy. The tumors investigated included pituitary adenoma, meningiomas, glioblastomas, and metastatic brain cancers. Freshly excised brain tissues were stained in 0.75 mg ml-1 aqueous solution of demeclocyline. Reflectance images were acquired at 402 nm. Fluorescence signals were excited at 402 nm and registered between 500 and 540 nm. After imaging, histological sections were processed from the imaged specimens and compared to the optical images. Fluorescence images highlighted normal and cancerous brain cells, while reflectance images emphasized the morphology of connective tissue. The optical and histological images were in accordance with each other for all types of tumors investigated. Demeclocyline shows promise as a contrast agent for intraoperative detection of brain tumors.

Emotion and sex of facial stimuli modulate conditional automaticity in behavioral and neuronal interference in healthy men.

PubMed

Kohn, Nils; Fernández, Guillén

2017-12-06

Our surrounding provides a host of sensory input, which we cannot fully process without streamlining and automatic processing. Levels of automaticity differ for different cognitive and affective processes. Situational and contextual interactions between cognitive and affective processes in turn influence the level of automaticity. Automaticity can be measured by interference in Stroop tasks. We applied an emotional version of the Stroop task to investigate how stress as a contextual factor influences the affective valence-dependent level of automaticity. 120 young, healthy men were investigated for behavioral and brain interference following a stress induction or control procedure in a counter-balanced cross-over-design. Although Stroop interference was always observed, sex and emotion of the face strongly modulated interference, which was larger for fearful and male faces. These effects suggest higher automaticity when processing happy and also female faces. Supporting behavioral patterns, brain data show lower interference related brain activity in executive control related regions in response to happy and female faces. In the absence of behavioral stress effects, congruent compared to incongruent trials (reverse interference) showed little to no deactivation under stress in response to happy female and fearful male trials. These congruency effects are potentially based on altered context- stress-related facial processing that interact with sex-emotion stereotypes. Results indicate that sex and facial emotion modulate Stroop interference in brain and behavior. These effects can be explained by altered response difficulty as a consequence of the contextual and stereotype related modulation of automaticity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Childhood Brain and Spinal Cord Tumors Treatment Overview (PDQ®)—Health Professional Version

Cancer.gov

Pediatric primary brain and CNS tumors are a diverse group of diseases that together constitute the most common solid tumor of childhood. Get detailed information about the diagnosis, classification, prognosis, and treatment of childhood brain and spinal cord tumors in this comprehensive summary for clinicians.

Growth of malignant extracranial tumors alters microRNAome in the prefrontal cortex of TumorGraft mice

PubMed Central

Kovalchuk, Anna; Ilnytskyy, Yaroslav; Rodriguez-Juarez, Rocio; Katz, Amanda; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

2017-01-01

A wide array of central nervous system complications, neurological deficits, and cognitive impairments occur and persist as a result of systemic cancer and cancer treatments. This condition is known as chemo brain and it affects over half of cancer survivors. Recent studies reported that cognitive impairments manifest before chemotherapy and are much broader than chemo brain alone, thereby adding in tumor brain as a component. The molecular mechanisms of chemo brain are under-investigated, and the mechanisms of tumor brain have not been analyzed at all. The frequency and timing, as well as the long-term persistence, of chemo brain and tumor brain suggest they may be epigenetic in nature. MicroRNAs, small, single-stranded non-coding RNAs, constitute an important part of the cellular epigenome and are potent regulators of gene expression. miRNAs are crucial for brain development and function, and are affected by a variety of different stresses, diseases and conditions. However, nothing is known about the effects of extracranial tumor growth or chemotherapy agents on the brain microRNAome. We used the well-established TumorGraft ™ mouse models of triple negative (TNBC) and progesterone receptor positive (PR+BC) breast cancer, and profiled global microRNAome changes in tumor-bearing mice upon chemotherapy, as compared to untreated tumor-bearing mice and intact mice. Our analysis focused on the prefrontal cortex (PFC), based on its roles in memory, learning, and executive functions, and on published data showing the PFC is a target in chemo brain. This is the first study showing that tumor presence alone significantly impacted the small RNAome of PFC tissues. Both tumor growth and chemotherapy treatment affected the small RNAome and altered levels of miRNAs, piRNAs, tRNAs, tRNA fragments and other molecules involved in post-transcriptional regulation of gene expression. Amongst those, miRNA changes were the most pronounced, involving several miRNA families, such as the miR-200 family and miR-183/96/182 cluster; both were deregulated in tumor-bearing and chemotherapy-treated animals. We saw that miRNA deregulation was associated with altered levels of brain-derived neurotrophic factor (BDNF), which plays an important role in cognition and memory and is one of the known miRNA targets. BDNF downregulation has been associated with an array of neurological conditions and could be one of the mechanisms underlying tumor brain and chemo brain. In the future our study could serve as a roadmap for further analysis of cancer and chemotherapy’s neural side effects, and differentially expressed miRNAs should be explored as potential tumor brain and chemo brain biomarkers. PMID:29179434

Employment status and termination among survivors of pediatric brain tumors: a cross-sectional survey.

PubMed

Sato, Iori; Higuchi, Akiko; Yanagisawa, Takaaki; Murayama, Shiho; Kumabe, Toshihiro; Sugiyama, Kazuhiko; Mukasa, Akitake; Saito, Nobuhito; Sawamura, Yutaka; Terasaki, Mizuhiko; Shibui, Soichiro; Takahashi, Jun; Nishikawa, Ryo; Ishida, Yasushi; Kamibeppu, Kiyoko

2018-04-30

Some childhood cancer survivors experience employment difficulties. This study aimed to describe pediatric brain-tumor survivors' employment status. A cross-sectional, observational study was conducted, with questionnaires distributed to 101 pediatric brain-tumor survivors (aged 15 years or older) and their attending physicians from nine institutions in Japan. We compared category and time-series histories for participants' first-time employment using national census information. Factors related to delayed employment or early employment termination were examined using survival-time analyses. Excluding students and homemakers, 38 brain-tumor survivors (median age 27 years, with 15 years since diagnosis) were of working age. Of these, 12 (32%) were unemployed and 9 (24%) had never been employed. First-time employment occurred later for brain-tumor survivors than the general population, particularly in those with lower educational levels. The number of brain-tumor survivors whose first job was terminated within the first year was higher than that for the general population, particularly in male survivors and germ cell-tumor survivors. Brain-tumor survivors described their working patterns (irregular), job types (specialist or professional), reasons for early termination (unsuitable job), and thoughts about working (they wished to serve their communities but lacked confidence). Brain-tumor survivors are associated with high unemployment rates and multiple unemployment-related factors. Education and welfare systems should identify individual methods of social participation for this group.

Brain Tumor Epidemiology – A Hub within Multidisciplinary Neuro-oncology. Report on the 15th Brain Tumor Epidemiology Consortium (BTEC) Annual Meeting, Vienna, 2014

PubMed Central

Woehrer, Adelheid; Lau, Ching C.; Prayer, Daniela; Bauchet, Luc; Rosenfeld, Myrna; Capper, David; Fisher, Paul G.; Kool, Marcel; Müller, Martin; Kros, Johan M.; Kruchko, Carol; Wiemels, Joseph; Wrensch, Margaret; Danysh, Heather E.; Zouaoui, Sonia; Heck, Julia E.; Johnson, Kimberly J.; Qi, Xiaoyang; O’Neill, Brian P.; Afzal, Samina; Scheurer, Michael E.; Bainbridge, Matthew N.; Nousome, Darryl; El Bahassi, Mustapha; Hainfellner, Johannes A.; Barnholtz-Sloan, Jill S.

2015-01-01

The Brain Tumor Epidemiology Consortium (BTEC) is an open scientific forum, which fosters the development of multi-center, international and inter-disciplinary collaborations. BTEC aims to develop a better understanding of the etiology, outcomes, and prevention of brain tumors (http://epi.grants.cancer.gov/btec/). The 15th annual Brain Tumor Epidemiology Consortium Meeting, hosted by the Austrian Societies of Neuropathology and Neuro-oncology, was held on September 9 – 11, 2014 in Vienna, Austria. The meeting focused on the central role of brain tumor epidemiology within multidisciplinary neuro-oncology. Knowledge of disease incidence, outcomes, as well as risk factors is fundamental to all fields involved in research and treatment of patients with brain tumors; thus, epidemiology constitutes an important link between disciplines, indeed the very hub. This was reflected by the scientific program, which included various sessions linking brain tumor epidemiology with clinical neuro-oncology, tissue-based research, and cancer registration. Renowned experts from Europe and the United States contributed their personal perspectives stimulating further group discussions. Several concrete action plans evolved for the group to move forward until next year’s meeting, which will be held at the Mayo Clinic at Rochester, MN, USA. PMID:25518914

Implications of neurovascular uncoupling in functional magnetic resonance imaging (fMRI) of brain tumors.

PubMed

Pak, Rebecca W; Hadjiabadi, Darian H; Senarathna, Janaka; Agarwal, Shruti; Thakor, Nitish V; Pillai, Jay J; Pathak, Arvind P

2017-11-01

Functional magnetic resonance imaging (fMRI) serves as a critical tool for presurgical mapping of eloquent cortex and changes in neurological function in patients diagnosed with brain tumors. However, the blood-oxygen-level-dependent (BOLD) contrast mechanism underlying fMRI assumes that neurovascular coupling remains intact during brain tumor progression, and that measured changes in cerebral blood flow (CBF) are correlated with neuronal function. Recent preclinical and clinical studies have demonstrated that even low-grade brain tumors can exhibit neurovascular uncoupling (NVU), which can confound interpretation of fMRI data. Therefore, to avoid neurosurgical complications, it is crucial to understand the biophysical basis of NVU and its impact on fMRI. Here we review the physiology of the neurovascular unit, how it is remodeled, and functionally altered by brain cancer cells. We first discuss the latest findings about the components of the neurovascular unit. Next, we synthesize results from preclinical and clinical studies to illustrate how brain tumor induced NVU affects fMRI data interpretation. We examine advances in functional imaging methods that permit the clinical evaluation of brain tumors with NVU. Finally, we discuss how the suppression of anomalous tumor blood vessel formation with antiangiogenic therapies can "normalize" the brain tumor vasculature, and potentially restore neurovascular coupling.

Stat3 orchestrates interaction between endothelial and tumor cells and inhibition of Stat3 suppresses brain metastasis of breast cancer cells.

PubMed

Lee, Hsueh-Te; Xue, Jianfei; Chou, Ping-Chieh; Zhou, Aidong; Yang, Phillip; Conrad, Charles A; Aldape, Kenneth D; Priebe, Waldemar; Patterson, Cam; Sawaya, Raymond; Xie, Keping; Huang, Suyun

2015-04-30

Brain metastasis is a major cause of morbidity and mortality in patients with breast cancer. Our previous studies indicated that Stat3 plays an important role in brain metastasis. Here, we present evidence that Stat3 functions at the level of the microenvironment of brain metastases. Stat3 controlled constitutive and inducible VEGFR2 expression in tumor-associated brain endothelial cells. Furthermore, inhibition of Stat3 by WP1066 decreased the incidence of brain metastases and increased survival in a preclinical model of breast cancer brain metastasis. WP1066 inhibited Stat3 activation in tumor-associated endothelial cells, reducing their infiltration and angiogenesis. WP1066 also inhibited breast cancer cell invasion. Our results indicate that WP1066 can inhibit tumor angiogenesis and brain metastasis mediated by Stat3 in endothelial and tumor cells.

Emergence of Convolutional Neural Network in Future Medicine: Why and How. A Review on Brain Tumor Segmentation

NASA Astrophysics Data System (ADS)

Alizadeh Savareh, Behrouz; Emami, Hassan; Hajiabadi, Mohamadreza; Ghafoori, Mahyar; Majid Azimi, Seyed

2018-03-01

Manual analysis of brain tumors magnetic resonance images is usually accompanied by some problem. Several techniques have been proposed for the brain tumor segmentation. This study will be focused on searching popular databases for related studies, theoretical and practical aspects of Convolutional Neural Network surveyed in brain tumor segmentation. Based on our findings, details about related studies including the datasets used, evaluation parameters, preferred architectures and complementary steps analyzed. Deep learning as a revolutionary idea in image processing, achieved brilliant results in brain tumor segmentation too. This can be continuing until the next revolutionary idea emerging.

Brain Tumor Epidemiology: Consensus from the Brain Tumor Epidemiology Consortium (BTEC)

PubMed Central

Bondy, Melissa L.; Scheurer, Michael E.; Malmer, Beatrice; Barnholtz-Sloan, Jill S.; Davis, Faith G.; Il’yasova, Dora; Kruchko, Carol; McCarthy, Bridget J.; Rajaraman, Preetha; Schwartzbaum, Judith A.; Sadetzki, Siegal; Schlehofer, Brigitte; Tihan, Tarik; Wiemels, Joseph L.; Wrensch, Margaret; Buffler, Patricia A.

2010-01-01

Epidemiologists in the Brain Tumor Epidemiology Consortium (BTEC) have prioritized areas for further research. Although many risk factors have been examined over the past several decades, there are few consistent findings possibly due to small sample sizes in individual studies and differences between studies in subjects, tumor types, and methods of classification. Individual studies have generally lacked sufficient sample size to examine interactions. A major priority based on available evidence and technologies includes expanding research in genetics and molecular epidemiology of brain tumors. BTEC has taken an active role in promoting understudied groups such as pediatric brain tumors, the etiology of rare glioma subtypes, such as oligodendroglioma, and meningioma, which not uncommon, has only recently been systematically registered in the US. There is also a pressing need to bring more researchers, especially junior investigators, to study brain tumor epidemiology. However, relatively poor funding for brain tumor research has made it difficult to encourage careers in this area. We review the group’s consensus on the current state of scientific findings and present a consensus on research priorities to identify the important areas the science should move to address. PMID:18798534

American Brain Tumor Association

MedlinePlus

... Brain Tumor Association Names Leslie M. Stokes Interim Chief Executive Officer and Begins Search for Permanent CEO September 7, ... American Brain Tumor Association Names Kelly Sitkin as Chief Advancement Officer Read More ABTA Live ABTA Facebook Follow @theabta ...

Gene expression changes in rat brain after short and long exposures to particulate matter in Los Angeles basin air: Comparison with human brain tumors.

PubMed

Ljubimova, Julia Y; Kleinman, Michael T; Karabalin, Natalya M; Inoue, Satoshi; Konda, Bindu; Gangalum, Pallavi; Markman, Janet L; Ljubimov, Alexander V; Black, Keith L

2013-11-01

Air pollution negatively impacts pulmonary, cardiovascular, and central nervous systems. Although its influence on brain cancer is unclear, toxic pollutants can cause blood-brain barrier disruption, enabling them to reach the brain and cause alterations leading to tumor development. By gene microarray analysis validated by quantitative RT-PCR and immunostaining we examined whether rat (n=104) inhalation exposure to air pollution particulate matter (PM) resulted in brain molecular changes similar to those associated with human brain tumors. Global brain gene expression was analyzed after exposure to PM (coarse, 2.5-10μm; fine, <2.5μm; or ultrafine, <0.15μm) and purified air for different times, short (0.5, 1, and 3 months) and chronic (10 months), for 5h per day, four days per week. Expression of select gene products was also studied in human brain (n=7) and in tumors (n=83). Arc/Arg3.1 and Rac1 genes, and their protein products were selected for further examination. Arc was elevated upon two-week to three-month exposure to coarse PM and declined after 10-month exposure. Rac1 was significantly elevated upon 10-month coarse PM exposure. On human brain tumor sections, Arc was expressed in benign meningiomas and low-grade gliomas but was much lower in high-grade tumors. Conversely, Rac1 was elevated in high-grade vs. low-grade gliomas. Arc is thus associated with early brain changes and low-grade tumors, whereas Rac1 is associated with long-term PM exposure and highly aggressive tumors. In summary, exposure to air PM leads to distinct changes in rodent brain gene expression similar to those observed in human brain tumors. Copyright © 2013 Elsevier GmbH. All rights reserved.

Distribution of polymer nanoparticles by convection-enhanced delivery to brain tumors.

PubMed

Saucier-Sawyer, Jennifer K; Seo, Young-Eun; Gaudin, Alice; Quijano, Elias; Song, Eric; Sawyer, Andrew J; Deng, Yang; Huttner, Anita; Saltzman, W Mark

2016-06-28

Glioblastoma multiforme (GBM) is a fatal brain tumor characterized by infiltration beyond the margins of the main tumor mass and local recurrence after surgery. The blood-brain barrier (BBB) poses the most significant hurdle to brain tumor treatment. Convection-enhanced delivery (CED) allows for local administration of agents, overcoming the restrictions of the BBB. Recently, polymer nanoparticles have been demonstrated to penetrate readily through the healthy brain when delivered by CED, and size has been shown to be a critical factor for nanoparticle penetration. Because these brain-penetrating nanoparticles (BPNPs) have high potential for treatment of intracranial tumors since they offer the potential for cell targeting and controlled drug release after administration, here we investigated the intratumoral CED infusions of PLGA BPNPs in animals bearing either U87 or RG2 intracranial tumors. We demonstrate that the overall volume of distribution of these BPNPs was similar to that observed in healthy brains; however, the presence of tumors resulted in asymmetric and heterogeneous distribution patterns, with substantial leakage into the peritumoral tissue. Together, our results suggest that CED of BPNPs should be optimized by accounting for tumor geometry, in terms of location, size and presence of necrotic regions, to determine the ideal infusion site and parameters for individual tumors. Copyright © 2016 Elsevier B.V. All rights reserved.

Improving Care in Pediatric Neuro-oncology Patients: An Overview of the Unique Needs of Children With Brain Tumors.

PubMed

Fischer, Cheryl; Petriccione, Mary; Donzelli, Maria; Pottenger, Elaine

2016-03-01

Brain tumors represent the most common solid tumors in childhood, accounting for almost 25% of all childhood cancer, second only to leukemia. Pediatric central nervous system tumors encompass a wide variety of diagnoses, from benign to malignant. Any brain tumor can be associated with significant morbidity, even when low grade, and mortality from pediatric central nervous system tumors is disproportionately high compared to other childhood malignancies. Management of children with central nervous system tumors requires knowledge of the unique aspects of care associated with this particular patient population, beyond general oncology care. Pediatric brain tumor patients have unique needs during treatment, as cancer survivors, and at end of life. A multidisciplinary team approach, including advanced practice nurses with a specialty in neuro-oncology, allows for better supportive care. Knowledge of the unique aspects of care for children with brain tumors, and the appropriate interventions required, allows for improved quality of life. © The Author(s) 2015.

Automated Voxel-Based Analysis of Volumetric Dynamic Contrast-Enhanced CT Data Improves Measurement of Serial Changes in Tumor Vascular Biomarkers

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

Coolens, Catherine, E-mail: catherine.coolens@rmp.uhn.on.ca; Department of Radiation Oncology, University of Toronto, Toronto, Ontario; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario

2015-01-01

Objectives: Development of perfusion imaging as a biomarker requires more robust methodologies for quantification of tumor physiology that allow assessment of volumetric tumor heterogeneity over time. This study proposes a parametric method for automatically analyzing perfused tissue from volumetric dynamic contrast-enhanced (DCE) computed tomography (CT) scans and assesses whether this 4-dimensional (4D) DCE approach is more robust and accurate than conventional, region-of-interest (ROI)-based CT methods in quantifying tumor perfusion with preliminary evaluation in metastatic brain cancer. Methods and Materials: Functional parameter reproducibility and analysis of sensitivity to imaging resolution and arterial input function were evaluated in image sets acquired from amore » 320-slice CT with a controlled flow phantom and patients with brain metastases, whose treatments were planned for stereotactic radiation surgery and who consented to a research ethics board-approved prospective imaging biomarker study. A voxel-based temporal dynamic analysis (TDA) methodology was used at baseline, at day 7, and at day 20 after treatment. The ability to detect changes in kinetic parameter maps in clinical data sets was investigated for both 4D TDA and conventional 2D ROI-based analysis methods. Results: A total of 7 brain metastases in 3 patients were evaluated over the 3 time points. The 4D TDA method showed improved spatial efficacy and accuracy of perfusion parameters compared to ROI-based DCE analysis (P<.005), with a reproducibility error of less than 2% when tested with DCE phantom data. Clinically, changes in transfer constant from the blood plasma into the extracellular extravascular space (K{sub trans}) were seen when using TDA, with substantially smaller errors than the 2D method on both day 7 post radiation surgery (±13%; P<.05) and by day 20 (±12%; P<.04). Standard methods showed a decrease in K{sub trans} but with large uncertainty (111.6 ± 150.5) %. Conclusions: Parametric voxel-based analysis of 4D DCE CT data resulted in greater accuracy and reliability in measuring changes in perfusion CT-based kinetic metrics, which have the potential to be used as biomarkers in patients with metastatic brain cancer.« less

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

NASA Astrophysics Data System (ADS)

Abdulbaqi, Hayder Saad; Jafri, Mohd Zubir Mat; Omar, Ahmad Fairuz; Mustafa, Iskandar Shahrim Bin; Abood, Loay Kadom

2015-04-01

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

Family History of Cancer in Benign Brain Tumor Subtypes Versus Gliomas

PubMed Central

Ostrom, Quinn T.; McCulloh, Christopher; Chen, Yanwen; Devine, Karen; Wolinsky, Yingli; Davitkov, Perica; Robbins, Sarah; Cherukuri, Rajesh; Patel, Ashokkumar; Gupta, Rajnish; Cohen, Mark; Barrios, Jaime Vengoechea; Brewer, Cathy; Schilero, Cathy; Smolenski, Kathy; McGraw, Mary; Denk, Barbara; Naska, Theresa; Laube, Frances; Steele, Ruth; Greene, Dale; Kastl, Alison; Bell, Susan; Aziz, Dina; Chiocca, E. A.; McPherson, Christopher; Warnick, Ronald; Barnett, Gene H.; Sloan, Andrew E.; Barnholtz-Sloan, Jill S.

2012-01-01

Purpose: Family history is associated with gliomas, but this association has not been established for benign brain tumors. Using information from newly diagnosed primary brain tumor patients, we describe patterns of family cancer histories in patients with benign brain tumors and compare those to patients with gliomas. Methods: Newly diagnosed primary brain tumor patients were identified as part of the Ohio Brain Tumor Study. Each patient was asked to participate in a telephone interview about personal medical history, family history of cancer, and other exposures. Information was available from 33 acoustic neuroma (65%), 78 meningioma (65%), 49 pituitary adenoma (73.1%), and 152 glioma patients (58.2%). The association between family history of cancer and each subtype was compared with gliomas using unconditional logistic regression models generating odds ratios (ORs) and 95% confidence intervals. Results: There was no significant difference in family history of cancer between patients with glioma and benign subtypes. Conclusion: The results suggest that benign brain tumor may have an association with family history of cancer. More studies are warranted to disentangle the potential genetic and/or environmental causes for these diseases. PMID:22649779

Social Competence in Childhood Brain Tumor Survivors: Feasibility and Preliminary Outcomes of a Peer-Mediated Intervention

PubMed Central

Devine, Katie A.; Bukowski, William M.; Sahler, Olle Jane Z.; Ohman-Strickland, Pamela; Smith, Tristram H.; Lown, E. Anne; Patenaude, Andrea Farkas; Korones, David N.; Noll, Robert B.

2016-01-01

Objective Evaluate the acceptability, feasibility, and preliminary outcomes of a peer-mediated intervention to improve social competence of brain tumor survivors and classmates. Methods Twelve childhood brain tumor survivors and 217 classroom peers in intervention (n = 8) or comparison (n = 4) classrooms completed measures of social acceptance and reputation at two time points in the year. The intervention (5–8 sessions over 4–6 weeks) taught peer leaders skills for engaging classmates. Individual and classroom outcomes were analyzed with ANCOVA. Results Recruitment rates of families of brain tumor survivors (81%) and schools (100%) were adequate. Peer leaders reported satisfaction with the intervention. Preliminary outcome data trended toward some benefit in increasing the number of friend nominations for survivors of brain tumors but no changes in other peer-reported metrics. Preliminary results also suggested some positive effects on classroom levels of victimization and rejection. Conclusions A peer-mediated intervention was acceptable to families of brain tumor survivors and feasible to implement in schools. Findings warrant a larger trial to evaluate improvements for children with brain tumors and their peers. PMID:27355881

SJDAWN: St. Jude Children's Research Hospital Phase 1 Study Evaluating Molecularly-Driven Doublet Therapies for Children and Young Adults With Recurrent Brain Tumors

ClinicalTrials.gov

2018-04-09

Anaplastic Astrocytoma; Anaplastic Ependymoma; Anaplastic Ganglioglioma; Anaplastic Meningioma; Anaplastic Oligodendroglioma; Pleomorphic Xanthoastrocytoma, Anaplastic; Atypical Teratoid/Rhabdoid Tumor; Brain Cancer; Brain Tumor; Central Nervous System Neoplasms; Choroid Plexus Carcinoma; CNS Embryonal Tumor With Rhabdoid Features; Ganglioneuroblastoma of Central Nervous System; CNS Tumor; Embryonal Tumor of CNS; Ependymoma; Glioblastoma; Glioma; Glioma, Malignant; Medulloblastoma; Medulloblastoma; Unspecified Site; Medulloepithelioma; Neuroepithelial Tumor; Neoplasms; Neoplasms, Neuroepithelial; Papillary Tumor of the Pineal Region (High-grade Only); Pediatric Brain Tumor; Pineal Parenchymal Tumor of Intermediate Differentiation (High-grade Only); Pineoblastoma; Primitive Neuroectodermal Tumor; Recurrent Medulloblastoma; Refractory Brain Tumor; Neuroblastoma. CNS; Glioblastoma, IDH-mutant; Glioblastoma, IDH-wildtype; Medulloblastoma, Group 3; Medulloblastoma, Group 4; Glioma, High Grade; Neuroepithelial Tumor, High Grade; Medulloblastoma, SHH-activated and TP53 Mutant; Medulloblastoma, SHH-activated and TP53 Wildtype; Medulloblastoma, Chromosome 9q Loss; Medulloblastoma, Non-WNT Non-SHH, NOS; Medulloblastoma, Non-WNT/Non-SHH; Medulloblastoma, PTCH1 Mutation; Medulloblastoma, WNT-activated; Ependymoma, Recurrent; Glioma, Recurrent High Grade; Glioma, Recurrent Malignant; Embryonal Tumor, NOS; Glioma, Diffuse Midline, H3K27M-mutant; Embryonal Tumor With Multilayered Rosettes (ETMR); Ependymoma, NOS, WHO Grade III; Ependymoma, NOS, WHO Grade II; Medulloblastoma, G3/G4; Ependymoma, RELA Fusion Positive

Vascular Gene Expression in Nonneoplastic and Malignant Brain

PubMed Central

Madden, Stephen L.; Cook, Brian P.; Nacht, Mariana; Weber, William D.; Callahan, Michelle R.; Jiang, Yide; Dufault, Michael R.; Zhang, Xiaoming; Zhang, Wen; Walter-Yohrling, Jennifer; Rouleau, Cecile; Akmaev, Viatcheslav R.; Wang, Clarence J.; Cao, Xiaohong; St. Martin, Thia B.; Roberts, Bruce L.; Teicher, Beverly A.; Klinger, Katherine W.; Stan, Radu-Virgil; Lucey, Brenden; Carson-Walter, Eleanor B.; Laterra, John; Walter, Kevin A.

2004-01-01

Malignant gliomas are uniformly lethal tumors whose morbidity is mediated in large part by the angiogenic response of the brain to the invading tumor. This profound angiogenic response leads to aggressive tumor invasion and destruction of surrounding brain tissue as well as blood-brain barrier breakdown and life-threatening cerebral edema. To investigate the molecular mechanisms governing the proliferation of abnormal microvasculature in malignant brain tumor patients, we have undertaken a cell-specific transcriptome analysis from surgically harvested nonneoplastic and tumor-associated endothelial cells. SAGE-derived endothelial cell gene expression patterns from glioma and nonneoplastic brain tissue reveal distinct gene expression patterns and consistent up-regulation of certain glioma endothelial marker genes across patient samples. We define the G-protein-coupled receptor RDC1 as a tumor endothelial marker whose expression is distinctly induced in tumor endothelial cells of both brain and peripheral vasculature. Further, we demonstrate that the glioma-induced gene, PV1, shows expression both restricted to endothelial cells and coincident with endothelial cell tube formation. As PV1 provides a framework for endothelial cell caveolar diaphragms, this protein may serve to enhance glioma-induced disruption of the blood-brain barrier and transendothelial exchange. Additional characterization of this extensive brain endothelial cell gene expression database will provide unique molecular insights into vascular gene expression. PMID:15277233

Dye-enhanced multimodal confocal imaging as a novel approach to intraoperative diagnosis of brain tumors.

PubMed

Snuderl, Matija; Wirth, Dennis; Sheth, Sameer A; Bourne, Sarah K; Kwon, Churl-Su; Ancukiewicz, Marek; Curry, William T; Frosch, Matthew P; Yaroslavsky, Anna N

2013-01-01

Intraoperative diagnosis plays an important role in accurate sampling of brain tumors, limiting the number of biopsies required and improving the distinction between brain and tumor. The goal of this study was to evaluate dye-enhanced multimodal confocal imaging for discriminating gliomas from nonglial brain tumors and from normal brain tissue for diagnostic use. We investigated a total of 37 samples including glioma (13), meningioma (7), metastatic tumors (9) and normal brain removed for nontumoral indications (8). Tissue was stained in 0.05 mg/mL aqueous solution of methylene blue (MB) for 2-5 minutes and multimodal confocal images were acquired using a custom-built microscope. After imaging, tissue was formalin fixed and paraffin embedded for standard neuropathologic evaluation. Thirteen pathologists provided diagnoses based on the multimodal confocal images. The investigated tumor types exhibited distinctive and complimentary characteristics in both the reflectance and fluorescence responses. Images showed distinct morphological features similar to standard histology. Pathologists were able to distinguish gliomas from normal brain tissue and nonglial brain tumors, and to render diagnoses from the images in a manner comparable to haematoxylin and eosin (H&E) slides. These results confirm the feasibility of multimodal confocal imaging for intravital intraoperative diagnosis. © 2012 The Authors; Brain Pathology © 2012 International Society of Neuropathology.

Automatic processing of political preferences in the human brain.

PubMed

Tusche, Anita; Kahnt, Thorsten; Wisniewski, David; Haynes, John-Dylan

2013-05-15

Individual political preferences as expressed, for instance, in votes or donations are fundamental to democratic societies. However, the relevance of deliberative processing for political preferences has been highly debated, putting automatic processes in the focus of attention. Based on this notion, the present study tested whether brain responses reflect participants' preferences for politicians and their associated political parties in the absence of explicit deliberation and attention. Participants were instructed to perform a demanding visual fixation task while their brain responses were measured using fMRI. Occasionally, task-irrelevant images of German politicians from two major competing parties were presented in the background while the distraction task was continued. Subsequent to scanning, participants' political preferences for these politicians and their affiliated parties were obtained. Brain responses in distinct brain areas predicted automatic political preferences at the different levels of abstraction: activation in the ventral striatum was positively correlated with preference ranks for unattended politicians, whereas participants' preferences for the affiliated political parties were reflected in activity in the insula and the cingulate cortex. Using an additional donation task, we showed that the automatic preference-related processing in the brain extended to real-world behavior that involved actual financial loss to participants. Together, these findings indicate that brain responses triggered by unattended and task-irrelevant political images reflect individual political preferences at different levels of abstraction. Copyright © 2013 Elsevier Inc. All rights reserved.

MRI to predict nipple-areola complex (NAC) involvement: An automatic method to compute the 3D distance between the NAC and tumor.

PubMed

Giannini, Valentina; Bianchi, Veronica; Carabalona, Silvia; Mazzetti, Simone; Maggiorotto, Furio; Kubatzki, Franziska; Regge, Daniele; Ponzone, Riccardo; Martincich, Laura

2017-12-01

To assess the role in predicting nipple-areola complex (NAC) involvement of a newly developed automatic method which computes the 3D tumor-NAC distance. Ninety-nine patients scheduled to nipple sparing mastectomy (NSM) underwent magnetic resonance (MR) examination at 1.5 T, including sagittal T2w and dynamic contrast enhanced (DCE)-MR imaging. An automatic method was developed to segment the NAC and the tumor and to compute the 3D distance between them. The automatic measurement was compared with manual axial and sagittal 2D measurements. NAC involvement was defined by the presence of invasive ductal or lobular carcinoma and/or ductal carcinoma in situ or ductal intraepithelial neoplasia (DIN1c - DIN3). Tumor-NAC distance was computed on 95/99 patients (25 NAC+), as three tumors were not correctly segmented (sensitivity = 97%), and 1 NAC was not detected (sensitivity = 99%). The automatic 3D distance reached the highest area under the receiver operating characteristic (ROC) curve (0.830) with respect to the manual axial (0.676), sagittal (0.664), and minimum distances (0.664). At the best cut-off point of 21 mm, the 3D distance obtained sensitivity = 72%, specificity = 80%, positive predictive value = 56%, and negative predictive value = 89%. This method could provide a reproducible biomarker to preoperatively select breast cancer patients candidates to NSM, thus helping surgical planning and intraoperative management of patients. © 2017 Wiley Periodicals, Inc.

Increasing the efficacy of antitumor glioma vaccines by photodynamic therapy and local injection of allogeneic glioma cells

NASA Astrophysics Data System (ADS)

Christie, Catherine E.; Peng, Qian; Madsen, Steen J.; Uzal, Francisco A.; Hirschberg, Henry

2016-03-01

Immunotherapy of brain tumors involves the stimulation of an antitumor immune response. This type of therapy can be targeted specifically to tumor cells thus sparing surrounding normal brain. Due to the presence of the blood-brain barrier, the brain is relatively isolated from the systemic circulation and, as such, the initiation of significant immune responses is more limited than other types of cancers. The purpose of this study was to show that the efficacy of tumor primed antigen presenting macrophage vaccines could be increased by: (1) PDT of the priming tumor cells, and (2) injection of allogeneic glioma cells directly into brain tumors. Experiments were conducted in an in vivo brain tumor model using Fisher rats and BT4C (allogeneic) and F98 (syngeneic) glioma cells. Preliminary results showed that vaccination alone had significantly less inhibitory effect on F98 tumor growth compared to the combination of vaccination and allogeneic cell (BT4C) injection.

Gold nanoparticle imaging and radiotherapy of brain tumors in mice

PubMed Central

Hainfeld, James F; Smilowitz, Henry M; O'Connor, Michael J; Dilmanian, Farrokh Avraham; Slatkin, Daniel N

2013-01-01

Aim To test intravenously injected gold nanoparticles for x-ray imaging and radiotherapy enhancement of large, imminently lethal, intracerebral malignant gliomas. Materials & methods Gold nanoparticles approximately 11 nm in size were injected intravenously and brains imaged using microcomputed tomography. A total of 15 h after an intravenous dose of 4 g Au/kg was administered, brains were irradiated with 30 Gy 100 kVp x-rays. Results Gold uptake gave a 19:1 tumor-to-normal brain ratio with 1.5% w/w gold in tumor, calculated to increase local radiation dose by approximately 300%. Mice receiving gold and radiation (30 Gy) demonstrated 50% long term (>1 year) tumor-free survival, whereas all mice receiving radiation only died. Conclusion Intravenously injected gold nanoparticles cross the blood–tumor barrier, but are largely blocked by the normal blood–brain barrier, enabling high-resolution computed tomography tumor imaging. Gold radiation enhancement significantly improved long-term survival compared with radiotherapy alone. This approach holds promise to improve therapy of human brain tumors and other cancers. PMID:23265347

Mechanical characterization of human brain tumors from patients and comparison to potential surgical phantoms

PubMed Central

Rubiano, Andrés; Dyson, Kyle; Simmons, Chelsey S.

2017-01-01

While mechanical properties of the brain have been investigated thoroughly, the mechanical properties of human brain tumors rarely have been directly quantified due to the complexities of acquiring human tissue. Quantifying the mechanical properties of brain tumors is a necessary prerequisite, though, to identify appropriate materials for surgical tool testing and to define target parameters for cell biology and tissue engineering applications. Since characterization methods vary widely for soft biological and synthetic materials, here, we have developed a characterization method compatible with abnormally shaped human brain tumors, mouse tumors, animal tissue and common hydrogels, which enables direct comparison among samples. Samples were tested using a custom-built millimeter-scale indenter, and resulting force-displacement data is analyzed to quantify the steady-state modulus of each sample. We have directly quantified the quasi-static mechanical properties of human brain tumors with effective moduli ranging from 0.17–16.06 kPa for various pathologies. Of the readily available and inexpensive animal tissues tested, chicken liver (steady-state modulus 0.44 ± 0.13 kPa) has similar mechanical properties to normal human brain tissue while chicken crassus gizzard muscle (steady-state modulus 3.00 ± 0.65 kPa) has similar mechanical properties to human brain tumors. Other materials frequently used to mimic brain tissue in mechanical tests, like ballistic gel and chicken breast, were found to be significantly stiffer than both normal and diseased brain tissue. We have directly compared quasi-static properties of brain tissue, brain tumors, and common mechanical surrogates, though additional tests would be required to determine more complex constitutive models. PMID:28582392

[An automatic system for anatomophysiological correlation in three planes simultaneously during functional neurosurgery].

PubMed

Teijeiro, E J; Macías, R J; Morales, J M; Guerra, E; López, G; Alvarez, L M; Fernández, F; Maragoto, C; Seijo, F; Alvarez, E

The Neurosurgical Deep Recording System (NDRS) using a personal computer takes the place of complex electronic equipment for recording and processing deep cerebral electrical activity, as a guide in stereotaxic functional neurosurgery. It also permits increased possibilities of presenting information in direct graphic form with automatic management and sufficient flexibility to implement different analyses. This paper describes the possibilities of automatic simultaneous graphic representation in three almost orthogonal planes, available with the new 5.1 version of NDRS so as to facilitate the analysis of anatomophysiological correlation in the localization of deep structures of the brain during minimal access surgery. This new version can automatically show the spatial behaviour of signals registered throughout the path of the electrode inside the brain, superimposed simultaneously on sagittal, coronal and axial sections of an anatomical atlas of the brain, after adjusting the scale automatically according to the dimensions of the brain of each individual patient. This may also be shown in a tridimensional representation of the different planes themselves intercepting. The NDRS system has been successfully used in Spain and Cuba in over 300 functional neurosurgery operations. The new version further facilitates analysis of spatial anatomophysiological correlation for the localization of brain structures. This system has contributed to increase the precision and safety in selecting surgical targets in the control of Parkinson s disease and other disorders of movement.

MicroRNAs in brain metastases: potential role as diagnostics and therapeutics.

PubMed

Alsidawi, Samer; Malek, Ehsan; Driscoll, James J

2014-06-11

Brain metastases remain a daunting adversary that negatively impact patient survival. Metastatic brain tumors affect up to 45% of all cancer patients with systemic cancer and account for ~20% of all cancer-related deaths. A complex network of non-coding RNA molecules, microRNAs (miRNAs), regulate tumor metastasis. The brain micro-environment modulates metastatic tumor growth; however, defining the precise genetic events that promote metastasis in the brain niche represents an important, unresolved problem. Understanding these events will reveal disease-based targets and offer effective strategies to treat brain metastases. Effective therapeutic strategies based upon the biology of brain metastases represent an urgent, unmet need with immediate potential for clinical impact. Studies have demonstrated the ability of miRNAs to distinguish normal from cancerous cells, primary from secondary brain tumors, and correctly categorize metastatic brain tumor tissue of origin based solely on miRNA profiles. Interestingly, manipulation of miRNAs has proven effective in cancer treatment. With the promise of reduced toxicity, increased efficacy and individually directed personalized anti-cancer therapy, using miRNA in the treatment of metastatic brain tumors may prove very useful and improve patient outcome. In this review, we focus on the potential of miRNAs as diagnostic and therapeutic targets for the treatment of metastatic brain lesions.

Childhood Brain and Spinal Cord Tumors Treatment Overview (PDQ®)—Health Professional Version

Cancer.gov

Treatment for children with brain and spinal cord tumors is based on histology and location within the brain. For most of these tumors, an optimal regimen has not been determined, and enrollment onto clinical trials is encouraged. Get detailed information about these tumors in this clinician summary.

Brain Tumor Epidemiology Consortium (BTEC)

Cancer.gov

The Brain Tumor Epidemiology Consortium is an open scientific forum organized to foster the development of multi-center, international and inter-disciplinary collaborations that will lead to a better understanding of the etiology, outcomes, and prevention of brain tumors.

Brain Tumor Initiating Cells Adapt to Restricted Nutrition through Preferential Glucose Uptake

PubMed Central

Flavahan, William A.; Wu, Qiulian; Hitomi, Masahiro; Rahim, Nasiha; Kim, Youngmi; Sloan, Andrew E.; Weil, Robert J.; Nakano, Ichiro; Sarkaria, Jann N.; Stringer, Brett W.; Day, Bryan W.; Li, Meizhang; Lathia, Justin D.; Rich, Jeremy N.; Hjelmeland, Anita B.

2013-01-01

Like all cancers, brain tumors require a continuous source of energy and molecular resources for new cell production. In normal brain, glucose is an essential neuronal fuel, but the blood-brain barrier limits its delivery. We now report that nutrient restriction contributes to tumor progression by enriching for brain tumor initiating cells (BTICs) due to preferential BTIC survival and adaptation of non-BTICs through acquisition of BTIC features. BTICs outcompete for glucose uptake by co-opting the high affinity neuronal glucose transporter, type 3 (Glut3, SLC2A3). BTICs preferentially express Glut3 and targeting Glut3 inhibits BTIC growth and tumorigenic potential. Glut3, but not Glut1, correlates with poor survival in brain tumors and other cancers; thus, TICs may extract nutrients with high affinity. As altered metabolism represents a cancer hallmark, metabolic reprogramming may instruct the tumor hierarchy and portend poor prognosis. PMID:23995067

Growth of Malignant Non-CNS Tumors Alters Brain Metabolome

PubMed Central

Kovalchuk, Anna; Nersisyan, Lilit; Mandal, Rupasri; Wishart, David; Mancini, Maria; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

2018-01-01

Cancer survivors experience numerous treatment side effects that negatively affect their quality of life. Cognitive side effects are especially insidious, as they affect memory, cognition, and learning. Neurocognitive deficits occur prior to cancer treatment, arising even before cancer diagnosis, and we refer to them as “tumor brain.” Metabolomics is a new area of research that focuses on metabolome profiles and provides important mechanistic insights into various human diseases, including cancer, neurodegenerative diseases, and aging. Many neurological diseases and conditions affect metabolic processes in the brain. However, the tumor brain metabolome has never been analyzed. In our study we used direct flow injection/mass spectrometry (DI-MS) analysis to establish the effects of the growth of lung cancer, pancreatic cancer, and sarcoma on the brain metabolome of TumorGraft™ mice. We found that the growth of malignant non-CNS tumors impacted metabolic processes in the brain, affecting protein biosynthesis, and amino acid and sphingolipid metabolism. The observed metabolic changes were similar to those reported for neurodegenerative diseases and brain aging, and may have potential mechanistic value for future analysis of the tumor brain phenomenon. PMID:29515623

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

NASA Astrophysics Data System (ADS)

Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P.; Reyes, Mauricio

2013-07-01

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.

Brain tumor recurrence in children treated with growth hormone: the National Cooperative Growth Study experience.

PubMed

Moshang, T; Rundle, A C; Graves, D A; Nickas, J; Johanson, A; Meadows, A

1996-05-01

As of October 1993 the National Cooperative Growth Study included 1262 children with brain tumor who were treated with growth hormone. The type of brain tumor was specified in 947 (75%) of these children. The most common types were glioma, medulloblastoma, and craniopharyngioma, accounting for 91.3% of all those for which type was specified. Brain tumor recurred in 83 (6.6%) of the 1262 children over a total of 6115 patient-years at risk. The frequencies of tumor recurrence in children with low-grade glioma (18.1%), medulloblastoma (7.2%), and craniopharyngioma (6.4%) are lower than those in published reports of tumor recurrence in the general pediatric population with the same types of tumors. The analysis cannot conclusively show that no increased risk of tumor recurrence exists, however, because of the potential incompleteness of data reporting in the National Cooperative Growth Study. Nevertheless the findings are reassuring that children with the more common types of brain tumor who are treated with growth hormone do not seem to be at excessive risk for tumor recurrence.

An Automatic Occlusion Device for Remote Control of Tumor Tissue Ischemia

PubMed Central

El-Dahdah, Hamid; Wang, Bei; He, Guanglong; Xu, Ronald X.

2015-01-01

We developed an automatic occlusion device for remote control of tumor tissue ischemia. The device consists of a flexible cannula encasing a shape memory alloy wire with its distal end connected to surgical suture. Regional tissue occlusion was tested on both the benchtop and the animal models. In the benchtop test, the occlusion device introduced quantitative and reproducible changes of blood flow in a tissue simulating phantom embedding a vessel simulator. In the animal test, the device generated a cyclic pattern of reversible ischemia in the right hinder leg tissue of a black male C57BL/6 mouse. We also developed a multimodal detector that integrates near infrared spectroscopy and electron paramagnetic resonance spectroscopy for continuous monitoring of tumor tissue oxygenation, blood content, and oxygen tension changes. The multimodal detector was tested on a cancer xenograft nude mouse undergoing reversible tumor ischemia. The automatic occlusion device and the multi-modal detector can be potentially integrated for closed-loop feedback control of tumor tissue ischemia. Such an integrated occlusion device may be used in multiple clinical applications such as regional hypoperfusion control in tumor resection surgeries and thermal ablation processes. In addition, the proposed occlusion device can also be used as a research tool to understand tumor oxygen transport and hemodynamic characteristics. PMID:20082532

Endothelial Cell Implantation and Survival within Experimental Gliomas

NASA Astrophysics Data System (ADS)

Lal, Bachchu; Indurti, Ravi R.; Couraud, Pierre-Olivier; Goldstein, Gary W.; Laterra, John

1994-10-01

The delivery of therapeutic genes to primary brain neoplasms opens new opportunities for treating these frequently fatal tumors. Efficient gene delivery to tissues remains an important obstacle to therapy, and this problem has unique characteristics in brain tumors due to the blood-brain and blood-tumor barriers. The presence of endothelial mitogens and vessel proliferation within solid tumors suggests that genetically modified endothelial cells might efficiently transplant to brain tumors. Rat brain endothelial cells immortalized with the adenovirus E1A gene and further modified to express the β-galactosidase reporter were examined for their ability to survive implantation to experimental rat gliomas. Rats received 9L, F98, or C6 glioma cells in combination with endothelial cells intracranially to caudate/putamen or subcutaneously to flank. Implanted endothelial cells were identified by β-galactosidase histochemistry or by polymerase chain reaction in all tumors up to 35 days postimplantation, the latest time examined. Implanted endothelial cells appeared to cooperate in tumor vessel formation and expressed the brain-specific endothelial glucose transporter type 1 as identified by immunohistochemistry. The proliferation of implanted endothelial cells was supported by their increased number within tumors between postimplantation days 14 and 21 (P = 0.015) and by their expression of the proliferation antigen Ki67. These findings establish that genetically modified endothelial cells can be stably engrafted to growing gliomas and suggest that endothelial cell implantation may provide a means of delivering therapeutic genes to brain neoplasms and other solid tumors. In addition, endothelial implantation to brain may be useful for defining mechanisms of brain-specific endothelial differentiation.

What Are the Key Statistics about Brain and Spinal Cord Cancers?

MedlinePlus

... Brain and Spinal Cord Tumors in Adults Key Statistics for Brain and Spinal Cord Tumors The American ... Cord Tumors . Visit the American Cancer Society’s Cancer Statistics Center for more key statistics. Written by References ...

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images.

PubMed

Hamoud Al-Tamimi, Mohammed Sabbih; Sulong, Ghazali; Shuaib, Ibrahim Lutfi

2015-07-01

Resection of brain tumors is a tricky task in surgery due to its direct influence on the patients' survival rate. Determining the tumor resection extent for its complete information via-à-vis volume and dimensions in pre- and post-operative Magnetic Resonance Images (MRI) requires accurate estimation and comparison. The active contour segmentation technique is used to segment brain tumors on pre-operative MR images using self-developed software. Tumor volume is acquired from its contours via alpha shape theory. The graphical user interface is developed for rendering, visualizing and estimating the volume of a brain tumor. Internet Brain Segmentation Repository dataset (IBSR) is employed to analyze and determine the repeatability and reproducibility of tumor volume. Accuracy of the method is validated by comparing the estimated volume using the proposed method with that of gold-standard. Segmentation by active contour technique is found to be capable of detecting the brain tumor boundaries. Furthermore, the volume description and visualization enable an interactive examination of tumor tissue and its surrounding. Admirable features of our results demonstrate that alpha shape theory in comparison to other existing standard methods is superior for precise volumetric measurement of tumor. Copyright © 2015 Elsevier Inc. All rights reserved.

Label-free imaging of brain and brain tumor specimens with combined two-photon excited fluorescence and second harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Jiang, Liwei; Wang, Xingfu; Wu, Zanyi; Du, Huiping; Wang, Shu; Li, Lianhuang; Fang, Na; Lin, Peihua; Chen, Jianxin; Kang, Dezhi; Zhuo, Shuangmu

2017-10-01

Label-free imaging techniques are gaining acceptance within the medical imaging field, including brain imaging, because they have the potential to be applied to intraoperative in situ identifications of pathological conditions. In this paper, we describe the use of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) microscopy in combination for the label-free detection of brain and brain tumor specimens; gliomas. Two independently detecting channels were chosen to subsequently collect TPEF/SHG signals from the specimen to increase TPEF/SHG image contrasts. Our results indicate that the combined TPEF/SHG microscopic techniques can provide similar rat brain structural information and produce a similar resolution like conventional H&E staining in neuropathology; including meninges, cerebral cortex, white-matter structure corpus callosum, choroid plexus, hippocampus, striatum, and cerebellar cortex. It can simultaneously detect infiltrating human brain tumor cells, the extracellular matrix collagen fiber of connective stroma within brain vessels and collagen depostion in tumor microenvironments. The nuclear-to-cytoplasmic ratio and collagen content can be extracted as quantitative indicators for differentiating brain gliomas from healthy brain tissues. With the development of two-photon fiberscopes and microendoscope probes and their clinical applications, the combined TPEF and SHG microcopy may become an important multimodal, nonlinear optical imaging approach for real-time intraoperative histological diagnostics of residual brain tumors. These occur in various brain regions during ongoing surgeries through the method of simultaneously identifying tumor cells, and the change of tumor microenvironments, without the need for the removal biopsies and without the need for tissue labelling or fluorescent markers.

Targeting BRAF V600E and Autophagy in Pediatric Brain Tumors

DTIC Science & Technology

2015-10-01

AWARD NUMBER: W81XWH-14-1-0414 TITLE: Targeting BRAF V600E and Autophagy in Pediatric Brain Tumors PRINCIPAL INVESTIGATOR: Jean Mulcahy...29 Sep 2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-14-1-0414 Targeting BRAF V600E and Autophagy in Pediatric Brain Tumors 5b. GRANT...ABSTRACT 200 words most significant findings 15. SUBJECT TERMS autophagy , BRAF, brain tumor. pediatric 16. SECURITY CLASSIFICATION OF: 17

Biomaterial-based technologies for brain anti-cancer therapeutics and imaging.

PubMed

Orive, G; Ali, O A; Anitua, E; Pedraz, J L; Emerich, D F

2010-08-01

Treating malignant brain tumors represents one of the most formidable challenges in oncology. Contemporary treatment of brain tumors has been hampered by limited drug delivery across the blood-brain barrier (BBB) to the tumor bed. Biomaterials are playing an increasingly important role in developing more effective brain tumor treatments. In particular, polymer (nano)particles can provide prolonged drug delivery directly to the tumor following direct intracerebral injection, by making them physiochemically able to cross the BBB to the tumor, or by functionalizing the material surface with peptides and ligands allowing the drug-loaded material to be systemically administered but still specifically target the tumor endothelium or tumor cells themselves. Biomaterials can also serve as targeted delivery devices for novel therapies including gene therapy, photodynamic therapy, anti-angiogenic and thermotherapy. Nanoparticles also have the potential to play key roles in the diagnosis and imaging of brain tumors by revolutionizing both preoperative and intraoperative brain tumor detection, allowing early detection of pre-cancerous cells, and providing real-time, longitudinal, non-invasive monitoring/imaging of the effects of treatment. Additional efforts are focused on developing biomaterial systems that are uniquely capable of delivering tumor-associated antigens, immunotherapeutic agents or programming immune cells in situ to identify and facilitate immune-mediated tumor cell killing. The continued translation of current research into clinical practice will rely on solving challenges relating to the pharmacology of nanoparticles but it is envisioned that novel biomaterials will ultimately allow clinicians to target tumors and introduce multiple, pharmaceutically relevant entities for simultaneous targeting, imaging, and therapy in a unique and unprecedented manner. Copyright 2010 Elsevier B.V. All rights reserved.

Advances in Targeted Drug Delivery Approaches for the Central Nervous System Tumors: The Inspiration of Nanobiotechnology.

PubMed

Meng, Jianing; Agrahari, Vivek; Youm, Ibrahima

2017-03-01

At present, brain tumor is among the most challenging diseases to treat and the therapy is limited by the lack of effective methods to deliver anticancer agents across the blood-brain barrier (BBB). BBB is a selective barrier that separates the circulating blood from the brain extracellular fluid. In its neuroprotective function, BBB prevents the entry of toxins, as well as most of anticancer agents and is the main impediment for brain targeted drug delivery approaches. Nanotechnology-based delivery systems provide an attractive strategy to cross the BBB and reach the central nervous system (CNS). The incorporation of anticancer agents in various nanovehicles facilitates their delivery across the BBB. Moreover, a more powerful tool in brain tumor therapy has relied surface modifications of nanovehicles with specific ligands that can promote their passage through the BBB and favor the accumulation of the drug in CNS tumors. This review describes the physiological and anatomical features of the brain tumor and the BBB, and summarizes the recent advanced approaches to deliver anticancer drugs into brain tumor using nanobiotechnology-based drug carrier systems. The role of specific ligands in the design of functionalized nanovehicles for targeted delivery to brain tumor is reviewed. The current trends and future approaches in the CNS delivery of therapeutic molecules to tumors are also discussed.

Blood brain barrier: a challenge for effectual therapy of brain tumors.

PubMed

Bhowmik, Arijit; Khan, Rajni; Ghosh, Mrinal Kanti

2015-01-01

Brain tumors are one of the most formidable diseases of mankind. They have only a fair to poor prognosis and high relapse rate. One of the major causes of extreme difficulty in brain tumor treatment is the presence of blood brain barrier (BBB). BBB comprises different molecular components and transport systems, which in turn create efflux machinery or hindrance for the entry of several drugs in brain. Thus, along with the conventional techniques, successful modification of drug delivery and novel therapeutic strategies are needed to overcome this obstacle for treatment of brain tumors. In this review, we have elucidated some critical insights into the composition and function of BBB and along with it we have discussed the effective methods for delivery of drugs to the brain and therapeutic strategies overcoming the barrier.

GLISTR: Glioma Image Segmentation and Registration

PubMed Central

Pohl, Kilian M.; Bilello, Michel; Cirillo, Luigi; Biros, George; Melhem, Elias R.; Davatzikos, Christos

2015-01-01

We present a generative approach for simultaneously registering a probabilistic atlas of a healthy population to brain magnetic resonance (MR) scans showing glioma and segmenting the scans into tumor as well as healthy tissue labels. The proposed method is based on the expectation maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the original atlas into one with tumor and edema adapted to best match a given set of patient’s images. The modified atlas is registered into the patient space and utilized for estimating the posterior probabilities of various tissue labels. EM iteratively refines the estimates of the posterior probabilities of tissue labels, the deformation field and the tumor growth model parameters. Hence, in addition to segmentation, the proposed method results in atlas registration and a low-dimensional description of the patient scans through estimation of tumor model parameters. We validate the method by automatically segmenting 10 MR scans and comparing the results to those produced by clinical experts and two state-of-the-art methods. The resulting segmentations of tumor and edema outperform the results of the reference methods, and achieve a similar accuracy from a second human rater. We additionally apply the method to 122 patients scans and report the estimated tumor model parameters and their relations with segmentation and registration results. Based on the results from this patient population, we construct a statistical atlas of the glioma by inverting the estimated deformation fields to warp the tumor segmentations of patients scans into a common space. PMID:22907965

Presurgical localization and spatial shift of resting state networks in patients with brain metastases.

PubMed

Ding, Ju-Rong; Zhu, Fangmei; Hua, Bo; Xiong, Xingzhong; Wen, Yuqiao; Ding, Zhongxiang; Thompson, Paul M

2018-04-02

Brain metastases are the most prevalent cerebral tumors. Resting state networks (RSNs) are involved in multiple perceptual and cognitive functions. Therefore, precisely localizing multiple RSNs may be extremely valuable before surgical resection of metastases, to minimize neurocognitive impairments. Here we aimed to investigate the reliability of independent component analysis (ICA) for localizing multiple RSNs from resting-state functional MRI (rs-fMRI) data in individual patients, and further evaluate lesion-related spatial shifts of the RSNs. Twelve patients with brain metastases and 14 healthy controls were recruited. Using an improved automatic component identification method, we successfully identified seven common RSNs, including: the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN), language network (LN), sensorimotor network (SMN), auditory network (AN) and visual network (VN), in both individual patients and controls. Moreover, the RSNs in the patients showed a visible spatial shift compared to those in the controls, and the spatial shift of some regions was related to the tumor location, which may reflect a complicated functional mechanism - functional disruptions and reorganizations - caused by metastases. Besides, higher cognitive networks (DMN, ECN, DAN and LN) showed significantly larger spatial shifts than perceptual networks (SMN, AN and VN), supporting a functional dichotomy between the two network groups even in pathologic alterations associated with metastases. Overall, our findings provide evidence that ICA is a promising approach for presurgical localization of multiple RSNs from rs-fMRI data in individual patients. More attention should be paid to the spatial shifts of the RSNs before surgical resection.

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.

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

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

Abdulbaqi, Hayder Saad; Department of Physics, College of Education, University of Al-Qadisiya, Al-Qadisiya; Jafri, Mohd Zubir Mat

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introducemore » a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.« less

Molecular neuro-oncology and development of targeted therapeutic strategies for brain tumors. Part 1: Growth factor and Ras signaling pathways.

PubMed

Newton, Herbert B

2003-10-01

Brain tumors are a diverse group of malignancies that remain refractory to conventional treatment approaches, including radiotherapy and cytotoxic chemotherapy. Molecular neuro-oncology has now begun to clarify the transformed phenotype of brain tumors and identify oncogenic pathways that may be amenable to targeted therapy. Growth factor signaling pathways are often upregulated in brain tumors and may contribute to oncogenesis through autocrine and paracrine mechanisms. Excessive growth factor receptor stimulation can also lead to overactivity of the Ras signaling pathway, which is frequently aberrant in brain tumors. Receptor tyrosine kinase inhibitors, antireceptor monoclonal antibodies and antisense oligonucleotides are targeted approaches under investigation as methods to regulate aberrant growth factor signaling pathways in brain tumors. Several receptor tyrosine kinase inhibitors, including imatinib mesylate (Gleevec), gefitinib (Iressa) and erlotinib (Tarceva), have entered clinical trials for high-grade glioma patients. Farnesyl transferase inhibitors, such as tipifarnib (Zarnestra), which impair processing of proRas and inhibit the Ras signaling pathway, have also entered clinical trials for patients with malignant gliomas. Further development of targeted therapies and evaluation of these new agents in clinical trials will be needed to improve survival and quality of life of patients with brain tumors.

Combination of isocitrate dehydrogenase 1 (IDH1) mutation and podoplanin expression in brain tumors identifies patients at high or low risk of venous thromboembolism.

PubMed

Mir Seyed Nazari, P; Riedl, J; Preusser, M; Posch, F; Thaler, J; Marosi, C; Birner, P; Ricken, G; Hainfellner, J A; Pabinger, I; Ay, C

2018-06-01

Essentials Risk stratification for venous thromboembolism (VTE) in patients with brain tumors is challenging. Patients with IDH1 wildtype and high podoplanin expression have a 6-month VTE risk of 18.2%. Patients with IDH1 mutation and no podoplanin expression have a 6-month VTE risk of 0%. IDH1 mutation and podoplanin overexpression in primary brain tumors appear to be exclusive. Background Venous thromboembolism (VTE) is a frequent complication in primary brain tumor patients. Independent studies revealed that podoplanin expression in brain tumors is associated with increased VTE risk, whereas the isocitrate dehydrogenase 1 (IDH1) mutation is associated with very low VTE risk. Objectives To investigate the interrelation between intratumoral podoplanin expression and IDH1 mutation, and their mutual impact on VTE development. Patients/Methods In a prospective cohort study, intratumoral IDH1 R132H mutation and podoplanin were determined in brain tumor specimens (mainly glioma) by immunohistochemistry. The primary endpoint of the study was symptomatic VTE during a 2-year follow-up. Results All brain tumors that expressed podoplanin to a medium-high extent showed also an IDH1 wild-type status. A score based on IDH1 status and podoplanin expression levels allowed prediction of the risk of VTE. Patients with wild-type IDH1 brain tumors and high podoplanin expression had a significantly increased VTE risk compared with those with mutant IDH1 tumors and no podoplanin expression (6-month risk 18.2% vs. 0%). Conclusions IDH1 mutation and podoplanin overexpression seem to be exclusive. Although brain tumor patients with IDH1 mutation are at very low risk of VTE, the risk of VTE in patients with IDH1 wild-type tumors is strongly linked to podoplanin expression levels. © 2018 International Society on Thrombosis and Haemostasis.

Methionine PET/CT Studies In Patients With Cancer

ClinicalTrials.gov

2018-06-15

Brain Tumors and/or Solid Tumors Including; Brain Stem Glioma; High Grade CNS Tumors; Ependymoma; Medulloblastoma; Craniopharyngioma; Low Grade CNS Tumors; Hodgkin Lymphoma; Non Hodgkin Lymphoma; Ewing Sarcoma; Osteosarcoma; Rhabdomyosarcoma; Neuroblastoma; Other

Origins of Brain Tumor Macrophages.

PubMed

De Palma, Michele

2016-12-12

The ontogeny of brain-tumor-associated macrophages is poorly understood. New findings indicate that both resident microglia and blood-derived monocytes generate the pool of macrophages that infiltrate brain tumors of either primary or metastatic origin. Copyright © 2016 Elsevier Inc. All rights reserved.

Magnetic resonance spectroscopy for detection of choline kinase inhibition in the treatment of brain tumors

PubMed Central

Kumar, Manoj; Arlauckas, Sean P.; Saksena, Sona; Verma, Gaurav; Ittyerah, Ranjit; Pickup, Stephen; Popov, Anatoliy V.; Delikatny, Edward J.; Poptani, Harish

2015-01-01

Abnormal choline metabolism is a hallmark of cancer and is associated with oncogenesis and tumor progression. Increased choline is consistently observed in both pre-clinical tumor models and in human brain tumors by proton magnetic resonance spectroscopy (MRS). Thus, inhibition of choline metabolism using specific choline kinase inhibitors such as MN58b may be a promising new strategy for treatment of brain tumors. We demonstrate the efficacy of MN58b in suppressing phosphocholine production in three brain tumor cell lines. In vivo MRS studies of rats with intra-cranial F98-derived brain tumors showed a significant decrease in tumor total choline concentration after treatment with MN58b. High resolution MRS of tissue extracts confirmed that this decrease was due to a significant reduction in phosphocholine. Concomitantly, a significant increase in poly-unsaturated lipid resonances was also observed in treated tumors, indicating apoptotic cell death. Magnetic resonance imaging (MRI) based volume measurements demonstrated a significant growth arrest in the MN58b-treated tumors in comparison to saline-treated controls. Histologically, MN58b-treated tumors showed decreased cell density, as well as increased apoptotic cells. These results suggest that inhibition of choline kinase can be used as an adjuvant to chemotherapy in the treatment of brain tumors and that decreases in total choline observed by MRS can be used as an effective phamacodynamic biomarker of treatment response. PMID:25657334

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

RNAi therapeutics for brain cancer: current advancements in RNAi delivery strategies.

PubMed

Malhotra, Meenakshi; Toulouse, André; Godinho, Bruno M D C; Mc Carthy, David John; Cryan, John F; O'Driscoll, Caitriona M

2015-10-01

Malignant primary brain tumors are aggressive cancerous cells that invade the surrounding tissues of the central nervous system. The current treatment options for malignant brain tumors are limited due to the inability to cross the blood-brain barrier. The advancements in current research has identified and characterized certain molecular markers that are essential for tumor survival, progression, metastasis and angiogenesis. These molecular markers have served as therapeutic targets for the RNAi based therapies, which enable site-specific silencing of the gene responsible for tumor proliferation. However, to bring about therapeutic success, an efficient delivery carrier that can cross the blood-brain barrier and reach the targeted site is essential. The current review focuses on the potential of targeted, non-viral and viral particles containing RNAi therapeutic molecules as delivery strategies specifically for brain tumors.

Coffee and green tea consumption in relation to brain tumor risk in a Japanese population.

PubMed

Ogawa, Takahiro; Sawada, Norie; Iwasaki, Motoki; Budhathoki, Sanjeev; Hidaka, Akihisa; Yamaji, Taiki; Shimazu, Taichi; Sasazuki, Shizuka; Narita, Yoshitaka; Tsugane, Shoichiro

2016-12-15

Few prospective studies have investigated the etiology of brain tumor, especially among Asian populations. Both coffee and green tea are popular beverages, but their relation with brain tumor risk, particularly with glioma, has been inconsistent in epidemiological studies. In this study, we evaluated the association between coffee and greed tea intake and brain tumor risk in a Japanese population. We evaluated a cohort of 106,324 subjects (50,438 men and 55,886 women) in the Japan Public Health Center-Based Prospective Study (JPHC Study). Subjects were followed from 1990 for Cohort I and 1993 for Cohort II until December 31, 2012. One hundred and fifty-seven (70 men and 87 women) newly diagnosed cases of brain tumor were identified during the study period. Hazard ratio (HR) and 95% confidence intervals (95%CIs) for the association between coffee or green tea consumption and brain tumor risk were assessed using a Cox proportional hazards regression model. We found a significant inverse association between coffee consumption and brain tumor risk in both total subjects (≥3 cups/day; HR = 0.47, 95%CI = 0.22-0.98) and in women (≥3 cups/day; HR = 0.24, 95%CI = 0.06-0.99), although the number of cases in the highest category was small. Furthermore, glioma risk tended to decrease with higher coffee consumption (≥3 cups/day; HR = 0.54, 95%CI = 0.16-1.80). No association was seen between green tea and brain tumor risk. In conclusion, our study suggested that coffee consumption might reduce the risk of brain tumor, including that of glioma, in the Japanese population. © 2016 UICC.

Geriatric neuro-oncology: from mythology to biology.

PubMed

Weller, Michael; Platten, Michael; Roth, Patrick; Wick, Wolfgang

2011-12-01

Age has remained one of the most important determinants of risk for the development of certain brain tumors, of benefit from and tolerance of brain tumor treatment, and overall outcome. Regarding these three aspects, there are major differences across the spectrum of primary brain tumors depending on specific histology. Here, we review recent advances in understanding the biological basis of the prognostic marker 'age' in neuro-oncology. Contemporary population-based studies confirm the strong prognostic impact of age in many brain tumors. Elderly patients continue to be treated less aggressively than younger patients with the same tumors. However, biological factors may contribute to the negative prognostic impact of age. For instance, among gliomas, mutations of the isocitrate dehydrogenase genes, which are prognostically favorable, are much more common in younger patients. Moreover, complete responses defined by neuroimaging were much less durable in elderly as opposed to younger patients with primary central nervous system lymphoma in the German Primary Central Nervous System Lymphoma Study Group trial. A combination of age-adapted patterns of care and treatment-independent, tumor-intrinsic factors contributes to the poorer outcome of elderly patients with brain tumors. These factors need to be better distinguished and understood in order to improve outcome in elderly brain tumor patients.

Lower gingival squamous cell carcinoma with brain metastasis during long-term cetuximab treatment: A case report.

PubMed

Naruse, Tomofumi; Tokuhisa, Mitsuko; Yanamoto, Souichi; Sakamoto, Yuki; Okuyama, Kohei; Tsuchihashi, Hiroki; Umeda, Masahiro

2018-05-01

Long-term cetuximab treatment can lead to acquired resistance, and tumor progression and/or new lesions often occur. The present report describes a case of lower gingival squamous cell carcinoma with brain metastasis during long-term cetuximab treatment in a 60-year-old man, including findings of an immunohistochemical study. The resected primary tumors, biopsy of the lung metastasis before administration of cetuximab, and brain metastasis specimens mediated by cetuximab were immunohistochemically examined. Histologically, the metastatic brain lesion showed hyperkeratinizing tumor cells with deeply stained irregular nuclei with necrotizing tumor cells, and a decrease in cell density was exhibited in part of the tumor nest. Moreover, the brain lesion was less malignant compared with the primary tumor and metastatic lung lesions. Immunohistochemically, the metastatic brain lesions showed low expression of epidermal growth factor receptor (EGFR) and high expression of N-cadherin compared with the primary tumor and metastatic lung lesions. These results suggest that acquired resistance to cetuximab may be associated with low EGFR expression and increased epithelial-to-mesenchymal transition potential.

Photodynamic therapy stimulates anti-tumor immune response in mouse models: the role of regulatory Tcells, anti-tumor antibodies, and immune attacks on brain metastases

NASA Astrophysics Data System (ADS)

Vatansever, Fatma; Kawakubo, Masayoshi; Chung, Hoon; Hamblin, Michael R.

2013-02-01

We have previously shown that photodynamic therapy mediated by a vascular regimen of benzoporphyrin derivative and 690nm light is capable of inducing a robust immune response in the mouse CT26.CL25 tumor model that contains a tumor-rejection antigen, beta-galactosidase (β-gal). For the first time we show that PDT can stimulate the production of serum IgG antibodies against the β-gal antigen. It is known that a common cause of death from cancer, particularly lung cancer, is brain metastases; especially the inoperable ones that do not respond to traditional cytotoxic therapies either. We asked whether PDT of a primary tumor could stimulate immune response that could attack the distant brain metastases. We have developed a mouse model of generating brain metastases by injecting CT26.CL25 tumor cells into the brain as well as injecting the same cancer cells under the skin at the same time. When the subcutaneous tumor was treated with PDT, we observed a survival advantage compared to mice that had untreated brain metastases alone.

Limiting glioma development by photodynamic therapy-generated macrophage vaccine and allo-stimulation: an in vivo histological study in rats

NASA Astrophysics Data System (ADS)

Madsen, Steen J.; Christie, Catherine; Huynh, Khoi; Peng, Qian; Uzal, Francisco A.; Krasieva, Tatiana B.; Hirschberg, Henry

2018-02-01

Immunotherapy of brain tumors involves the stimulation of an antitumor immune response. This type of therapy can be targeted specifically to tumor cells thus sparing surrounding normal brain. Due to the presence of the blood-brain barrier, the brain is relatively isolated from the systemic circulation and, as such, the initiation of significant immune responses is more limited than other types of cancers. The purpose of this study was to show that the efficacy of tumor primed antigen presenting macrophage (MaF98) vaccines can be increased by: (1) photodynamic therapy (PDT) of the priming tumor cells and (2) intracranial injection of allogeneic glioma cells directly into the tumor site. Experiments were conducted in an in vivo brain tumor development model using Fischer rats and F98 (syngeneic) and BT4C (allogeneic) glioma cells. The results showed that immunization with Ma (acting as antigen-presenting cells), primed with PDT-treated tumor cells (MaF98), significantly slowed but did not prevent the growth of F98-induced tumors in the brain. Complete suppression of tumor development was obtained via MaF98 inoculation combined with direct intracranial injection of allogeneic glioma cells. No deleterious effects were noted in any of the animals during the 14-day observation period.

Using Ferumoxytol-Enhanced MRI to Measure Inflammation in Patients With Brain Tumors or Other Conditions of the CNS

ClinicalTrials.gov

2017-08-30

Brain Injury; Central Nervous System Degenerative Disorder; Central Nervous System Infectious Disorder; Central Nervous System Vascular Malformation; Hemorrhagic Cerebrovascular Accident; Ischemic Cerebrovascular Accident; Primary Brain Neoplasm; Brain Cancer; Brain Tumors

Clinical presentation and epidemiology of brain tumors firstly diagnosed in adults in the Emergency Department: a 10-year, single center retrospective study.

PubMed

Comelli, Ivan; Lippi, Giuseppe; Campana, Valentina; Servadei, Franco; Cervellin, Gianfranco

2017-07-01

Several patients with new onset brain tumors present to the Emergency Department (ED) complaining for new symptoms. Although information exists on symptom prevalence in the entire population of patients with brain tumors, little is known about the clinical presentation in ED. This retrospective study was planned to investigate clinical presentation and epidemiology of brain tumors firstly diagnosed in a large urban ED throughout a 10-year period. All medical records of patients aged ≥18 years, discharged from our ED with a diagnosis of brain tumor were retrieved from the electronic hospital database during a 10-year period (2006 to 2015). The records were reassessed for selecting only brain tumors firstly diagnosed in the ED. The symptoms at presentation were divided in six categories: (I) headache; (II) seizures; (III) focal signs; (IV) altered mental status; (V) nausea/vomiting/dizziness; (VI) trauma. For all cases, the hospital record was retrieved, to obtain histologic classification of tumors. Patients with inflammatory neoformations were excluded from the study. Overall, 205 patients with firstly diagnosed brain tumor were identified among 870,135 ED visits (i.e., <1%). Glial tumors were the most frequent (50% of the entire sample). No significant differences were found between mean age of patients in the different histologically based groups (meningiomas 66±14; glioblastomas 65±16 years; metastases 66±13 years; other miscellaneous 66±19 years). Focal signs accounted for more than 50% of all presentation signs/symptoms. First presentation of brain tumor in the ED is not a rare occurrence, so that the emergency physicians should be aware of this possibility.

FDTD analysis of a noninvasive hyperthermia system for brain tumors.

PubMed

Yacoob, Sulafa M; Hassan, Noha S

2012-08-14

Hyperthermia is considered one of the new therapeutic modalities for cancer treatment and is based on the difference in thermal sensitivity between healthy tissues and tumors. During hyperthermia treatment, the temperature of the tumor is raised to 40-45°C for a definite period resulting in the destruction of cancer cells. This paper investigates design, modeling and simulation of a new non-invasive hyperthermia applicator system capable of effectively heating deep seated as well as superficial brain tumors using inexpensive, simple, and easy to fabricate components without harming surrounding healthy brain tissues. The proposed hyperthermia applicator system is composed of an air filled partial half ellipsoidal chamber, a patch antenna, and a head model with an embedded tumor at an arbitrary location. The irradiating antenna is placed at one of the foci of the hyperthermia chamber while the center of the brain tumor is placed at the other focus. The finite difference time domain (FDTD) method is used to compute both the SAR patterns and the temperature distribution in three different head models due to two different patch antennas at a frequency of 915 MHz. The obtained results suggest that by using the proposed noninvasive hyperthermia system it is feasible to achieve sufficient and focused energy deposition and temperature rise to therapeutic values in deep seated as well as superficial brain tumors without harming surrounding healthy tissue. The proposed noninvasive hyperthermia system proved suitable for raising the temperature in tumors embedded in the brain to therapeutic values by carefully selecting the systems components. The operator of the system only needs to place the center of the brain tumor at a pre-specified location and excite the antenna at a single frequency of 915 MHz. Our study may provide a basis for a clinical applicator prototype capable of heating brain tumors.

Toward real-time tumor margin identification in image-guided robotic brain tumor resection

NASA Astrophysics Data System (ADS)

Hu, Danying; Jiang, Yang; Belykh, Evgenii; Gong, Yuanzheng; Preul, Mark C.; Hannaford, Blake; Seibel, Eric J.

2017-03-01

For patients with malignant brain tumors (glioblastomas), a safe maximal resection of tumor is critical for an increased survival rate. However, complete resection of the cancer is hard to achieve due to the invasive nature of these tumors, where the margins of the tumors become blurred from frank tumor to more normal brain tissue, but in which single cells or clusters of malignant cells may have invaded. Recent developments in fluorescence imaging techniques have shown great potential for improved surgical outcomes by providing surgeons intraoperative contrast-enhanced visual information of tumor in neurosurgery. The current near-infrared (NIR) fluorophores, such as indocyanine green (ICG), cyanine5.5 (Cy5.5), 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX), are showing clinical potential to be useful in targeting and guiding resections of such tumors. Real-time tumor margin identification in NIR imaging could be helpful to both surgeons and patients by reducing the operation time and space required by other imaging modalities such as intraoperative MRI, and has the potential to integrate with robotically assisted surgery. In this paper, a segmentation method based on the Chan-Vese model was developed for identifying the tumor boundaries in an ex-vivo mouse brain from relatively noisy fluorescence images acquired by a multimodal scanning fiber endoscope (mmSFE). Tumor contours were achieved iteratively by minimizing an energy function formed by a level set function and the segmentation model. Quantitative segmentation metrics based on tumor-to-background (T/B) ratio were evaluated. Results demonstrated feasibility in detecting the brain tumor margins at quasi-real-time and has the potential to yield improved precision brain tumor resection techniques or even robotic interventions in the future.

Wild-Type Reovirus in Combination With Sargramostim in Treating Younger Patients With High-Grade Relapsed or Refractory Brain Tumors

ClinicalTrials.gov

2018-03-16

Childhood Astrocytoma; Childhood Atypical Teratoid/Rhabdoid Tumor; Diffuse Intrinsic Pontine Glioma; Glioma; Recurrent Childhood Anaplastic Oligodendroglioma; Recurrent Childhood Brain Neoplasm; Recurrent Childhood Glioblastoma; Recurrent Childhood Medulloblastoma; Recurrent Primitive Neuroectodermal Tumor; Refractory Brain Neoplasm

Assessing Amide Proton Transfer (APT) MRI Contrast Origins in 9 L Gliosarcoma in the Rat Brain Using Proteomic Analysis.

PubMed

Yan, Kun; Fu, Zongming; Yang, Chen; Zhang, Kai; Jiang, Shanshan; Lee, Dong-Hoon; Heo, Hye-Young; Zhang, Yi; Cole, Robert N; Van Eyk, Jennifer E; Zhou, Jinyuan

2015-08-01

To investigate the biochemical origin of the amide photon transfer (APT)-weighted hyperintensity in brain tumors. Seven 9 L gliosarcoma-bearing rats were imaged at 4.7 T. Tumor and normal brain tissue samples of equal volumes were prepared with a coronal rat brain matrix and a tissue biopsy punch. The total tissue protein and the cytosolic subproteome were extracted from both samples. Protein samples were analyzed using two-dimensional gel electrophoresis, and the proteins with significant abundance changes were identified by mass spectrometry. There was a significant increase in the cytosolic protein concentration in the tumor, compared to normal brain regions, but the total protein concentrations were comparable. The protein profiles of the tumor and normal brain tissue differed significantly. Six cytosolic proteins, four endoplasmic reticulum proteins, and five secreted proteins were considerably upregulated in the tumor. Our experiments confirmed an increase in the cytosolic protein concentration in tumors and identified several key proteins that may cause APT-weighted hyperintensity.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Automated brain tumor segmentation in magnetic resonance imaging based on sliding-window technique and symmetry analysis.

PubMed

Lian, Yanyun; Song, Zhijian

2014-01-01

Brain tumor segmentation from magnetic resonance imaging (MRI) is an important step toward surgical planning, treatment planning, monitoring of therapy. However, manual tumor segmentation commonly used in clinic is time-consuming and challenging, and none of the existed automated methods are highly robust, reliable and efficient in clinic application. An accurate and automated tumor segmentation method has been developed for brain tumor segmentation that will provide reproducible and objective results close to manual segmentation results. Based on the symmetry of human brain, we employed sliding-window technique and correlation coefficient to locate the tumor position. At first, the image to be segmented was normalized, rotated, denoised, and bisected. Subsequently, through vertical and horizontal sliding-windows technique in turn, that is, two windows in the left and the right part of brain image moving simultaneously pixel by pixel in two parts of brain image, along with calculating of correlation coefficient of two windows, two windows with minimal correlation coefficient were obtained, and the window with bigger average gray value is the location of tumor and the pixel with biggest gray value is the locating point of tumor. At last, the segmentation threshold was decided by the average gray value of the pixels in the square with center at the locating point and 10 pixels of side length, and threshold segmentation and morphological operations were used to acquire the final tumor region. The method was evaluated on 3D FSPGR brain MR images of 10 patients. As a result, the average ratio of correct location was 93.4% for 575 slices containing tumor, the average Dice similarity coefficient was 0.77 for one scan, and the average time spent on one scan was 40 seconds. An fully automated, simple and efficient segmentation method for brain tumor is proposed and promising for future clinic use. Correlation coefficient is a new and effective feature for tumor location.

The Long and Winding Road: From the High-Affinity Choline Uptake Site to Clinical Trials for Malignant Brain Tumors.

PubMed

Lowenstein, P R; Castro, M G

2016-01-01

Malignant brain tumors are one of the most lethal cancers. They originate from glial cells which infiltrate throughout the brain. Current standard of care involves surgical resection, radiotherapy, and chemotherapy; median survival is currently ~14-20 months postdiagnosis. Given that the brain immune system is deficient in priming systemic immune responses to glioma antigens, we proposed to reconstitute the brain immune system to achieve immunological priming from within the brain. Two adenoviral vectors are injected into the resection cavity or remaining tumor. One adenoviral vector expresses the HSV-1-derived thymidine kinase which converts ganciclovir into a compound only cytotoxic to dividing glioma cells. The second adenovirus expresses the cytokine fms-like tyrosine kinase 3 ligand (Flt3L). Flt3L differentiates precursors into dendritic cells and acts as a chemokine that attracts dendritic cells to the brain. HSV-1/ganciclovir killing of tumor cells releases tumor antigens that are taken up by dendritic cells within the brain tumor microenvironment. Tumor killing also releases HMGB1, an endogenous TLR2 agonist that activates dendritic cells. HMGB1-activated dendritic cells, loaded with glioma antigens, migrate to cervical lymph nodes to stimulate a systemic CD8+ T cells cytotoxic immune response against glioma. This immune response is specific to glioma tumors, induces immunological memory, and does neither cause brain toxicity nor autoimmune responses. An IND was granted by the FDA on 4/7/2011. A Phase I, first in person trial, to test whether reengineering the brain immune system is potentially therapeutic is ongoing. © 2016 Elsevier Inc. All rights reserved.

Emerging insights into barriers to effective brain tumor therapeutics.

PubMed

Woodworth, Graeme F; Dunn, Gavin P; Nance, Elizabeth A; Hanes, Justin; Brem, Henry

2014-01-01

There is great promise that ongoing advances in the delivery of therapeutics to the central nervous system (CNS) combined with rapidly expanding knowledge of brain tumor patho-biology will provide new, more effective therapies. Brain tumors that form from brain cells, as opposed to those that come from other parts of the body, rarely metastasize outside of the CNS. Instead, the tumor cells invade deep into the brain itself, causing disruption in brain circuits, blood vessel and blood flow changes, and tissue swelling. Patients with the most common and deadly form, glioblastoma (GBM) rarely live more than 2 years even with the most aggressive treatments and often with devastating neurological consequences. Current treatments include maximal safe surgical removal or biopsy followed by radiation and chemotherapy to address the residual tumor mass and invading tumor cells. However, delivering effective and sustained treatments to these invading cells without damaging healthy brain tissue is a major challenge and focus of the emerging fields of nanomedicine and viral and cell-based therapies. New treatment strategies, particularly those directed against the invasive component of this devastating CNS disease, are sorely needed. In this review, we (1) discuss the history and evolution of treatments for GBM, (2) define and explore three critical barriers to improving therapeutic delivery to invasive brain tumors, specifically, the neuro-vascular unit as it relates to the blood brain barrier, the extra-cellular space in regard to the brain penetration barrier, and the tumor genetic heterogeneity and instability in association with the treatment efficacy barrier, and (3) identify promising new therapeutic delivery approaches that have the potential to address these barriers and create sustained, meaningful efficacy against GBM.

Comparative expression analysis reveals lineage relationships between human and murine gliomas and a dominance of glial signatures during tumor propagation in vitro.

PubMed

Henriquez, Nico V; Forshew, Tim; Tatevossian, Ruth; Ellis, Matthew; Richard-Loendt, Angela; Rogers, Hazel; Jacques, Thomas S; Reitboeck, Pablo Garcia; Pearce, Kerra; Sheer, Denise; Grundy, Richard G; Brandner, Sebastian

2013-09-15

Brain tumors are thought to originate from stem/progenitor cell populations that acquire specific genetic mutations. Although current preclinical models have relevance to human pathogenesis, most do not recapitulate the histogenesis of the human disease. Recently, a large series of human gliomas and medulloblastomas were analyzed for genetic signatures of prognosis and therapeutic response. Using a mouse model system that generates three distinct types of intrinsic brain tumors, we correlated RNA and protein expression levels with human brain tumors. A combination of genetic mutations and cellular environment during tumor propagation defined the incidence and phenotype of intrinsic murine tumors. Importantly, in vitro passage of cancer stem cells uniformly promoted a glial expression profile in culture and in brain tumors. Gene expression profiling revealed that experimental gliomas corresponded to distinct subclasses of human glioblastoma, whereas experimental supratentorial primitive neuroectodermal tumors (sPNET) correspond to atypical teratoid/rhabdoid tumor (AT/RT), a rare childhood tumor. ©2013 AACR.

Trastuzumab uptake and its relation to efficacy in an animal model of HER2-positive breast cancer brain metastasis.

PubMed

Lewis Phillips, Gail D; Nishimura, Merry C; Lacap, Jennifer Arca; Kharbanda, Samir; Mai, Elaine; Tien, Janet; Malesky, Kimberly; Williams, Simon P; Marik, Jan; Phillips, Heidi S

2017-08-01

The extent to which efficacy of the HER2 antibody Trastuzumab in brain metastases is limited by access of antibody to brain lesions remains a question of significant clinical importance. We investigated the uptake and distribution of trastuzumab in brain and mammary fat pad grafts of HER2-positive breast cancer to evaluate the relationship of these parameters to the anti-tumor activity of trastuzumab and trastuzumab emtansine (T-DM1). Mouse transgenic breast tumor cells expressing human HER2 (Fo2-1282 or Fo5) were used to establish intracranial and orthotopic tumors. Tumor uptake and tissue distribution of systemically administered 89 Zr-trastuzumab or muMAb 4D5 (murine parent of trastuzumab) were measured by PET and ELISA. Efficacy of muMAb 4D5, the PI3K/mTOR inhibitor GNE-317, and T-DM1 was also assessed. 89 Zr-trastuzumab and muMAb 4D5 exhibited robust uptake into Fo2-1282 brain tumors, but not normal brains. Uptake into brain grafts was similar to mammary grafts. Despite this, muMAb 4D5 was less efficacious in brain grafts. Co-administration of muMAb 4D5 and GNE-317, a brain-penetrant PI3K/mTOR inhibitor, provided longer survival in mice with brain lesions than either agent alone. Moreover, T-DM1 increased survival in the Fo5 brain metastasis model. In models of HER2-positive breast cancer brain metastasis, trastuzumab efficacy does not appear to be limited by access to intracranial tumors. Anti-tumor activity improved with the addition of a brain-penetrant PI3K/mTOR inhibitor, suggesting that combining targeted therapies is a more effective strategy for treating HER2-positive breast cancer brain metastases. Survival was also extended in mice with Fo5 brain lesions treated with T-DM1.

Signals that regulate the oncogenic fate of neural stem cells and progenitors

PubMed Central

Swartling, Fredrik J.; Bolin, Sara; Phillips, Joanna J.; Persson, Anders I.

2013-01-01

Brain tumors have frequently been associated with a neural stem cell (NSC) origin and contain stem-like tumor cells, so-called brain tumor stem cells (BTSCs) that share many features with normal NSCs. A stem cell state of BTSCs confers resistance to radiotherapy and treatment with alkylating agents. It is also a hallmark of aggressive brain tumors and is maintained by transcriptional networks that are also active in embryonic stem cells. Advances in reprogramming of somatic cells into induced pluripotent stem (iPS) cells have further identified genes that drive stemness. In this review, we will highlight the possible drivers of stemness in medulloblastoma and glioma, the most frequent types of primary malignant brain cancer in children and adults, respectively. Signals that drive expansion of developmentally defined neural precursor cells are also active in corresponding brain tumors. Transcriptomal subgroups of human medulloblastoma and glioma match features of NSCs but also more restricted progenitors. Lessons from genetically-engineered mouse (GEM) models show that temporally and regionally defined NSCs can give rise to distinct subgroups of medulloblastoma and glioma. We will further discuss how acquisition of stem cell features may drive brain tumorigenesis from a non-NSC origin. Genetic alterations, signaling pathways, and therapy-induced changes in the tumor microenvironment can drive reprogramming networks and induce stemness in brain tumors. Finally, we propose a model where dysregulation of microRNAs (miRNAs) that normally provide barriers against reprogramming plays an integral role in promoting stemness in brain tumors. PMID:23376224

Brain extraction in partial volumes T2*@7T by using a quasi-anatomic segmentation with bias field correction.

PubMed

Valente, João; Vieira, Pedro M; Couto, Carlos; Lima, Carlos S

2018-02-01

Poor brain extraction in Magnetic Resonance Imaging (MRI) has negative consequences in several types of brain post-extraction such as tissue segmentation and related statistical measures or pattern recognition algorithms. Current state of the art algorithms for brain extraction work on weighted T1 and T2, being not adequate for non-whole brain images such as the case of T2*FLASH@7T partial volumes. This paper proposes two new methods that work directly in T2*FLASH@7T partial volumes. The first is an improvement of the semi-automatic threshold-with-morphology approach adapted to incomplete volumes. The second method uses an improved version of a current implementation of the fuzzy c-means algorithm with bias correction for brain segmentation. Under high inhomogeneity conditions the performance of the first method degrades, requiring user intervention which is unacceptable. The second method performed well for all volumes, being entirely automatic. State of the art algorithms for brain extraction are mainly semi-automatic, requiring a correct initialization by the user and knowledge of the software. These methods can't deal with partial volumes and/or need information from atlas which is not available in T2*FLASH@7T. Also, combined volumes suffer from manipulations such as re-sampling which deteriorates significantly voxel intensity structures making segmentation tasks difficult. The proposed method can overcome all these difficulties, reaching good results for brain extraction using only T2*FLASH@7T volumes. The development of this work will lead to an improvement of automatic brain lesions segmentation in T2*FLASH@7T volumes, becoming more important when lesions such as cortical Multiple-Sclerosis need to be detected. Copyright © 2017 Elsevier B.V. All rights reserved.

Quality of Life in Patients With Primary and Metastatic Brain Tumors in the Literature as Assessed by the FACT-Br.

PubMed

Chiu, Nicholas; Chiu, Leonard; Zeng, Liang; Zhang, Liying; Cella, David; Popovic, Marko; Chow, Ronald; Lam, Henry; Poon, Michael; Chow, Edward

2012-12-01

The Functional Assessment of Cancer Therapy-Brain (FACT-Br) is a quality of life (QOL) assessment tool that was originally developed for use in patients with primary brain tumors. However, the tool has also been used to assess QOL in patients with metastatic brain tumors. The purpose of this study is to compare the differences in QOL responses as assessed by the FACT-Br in patients with primary and metastatic brain neoplasms. A systematic literature search was conducted using the OvidSP platform in MEDLINE (1946 to July Week 2 2012) and EMBASE (1980 to 2012 Week 28). Articles in which the FACT-Br was used as a QOL assessment for patients with malignant brain tumors (both primary and metastatic) were included in the study. The weighted means of FACT-Br subscale and overall scores were calculated for the studies. To compare these scores, weighted analysis of variance was conducted and PROC GLM was performed for the data. A P-value of < 0.05 was considered statistically significant. A total of 23 studies (four in brain metastases, 18 in primary brain tumors and 1 in a mixed sample) using the FACT-Br for assessment of QOL were identified. Social and functional well-being were significantly better in patients with primary brain tumors (weighted mean score of 22.2 vs. 10.7, P = 0.0026, 16.9 vs. 6.2, P = 0.0025, respectively). No other scale of the FACT-Br was significantly different between the two groups and the performance status of patients included in both groups was similar. Patients with primary brain cancer seemed to have better social and functional well-being scores than those with metastatic brain tumors. Other QOL domains were similar between these two groups. However, the heterogeneity in the included studies and the low sample size of included samples in patients with metastatic brain tumors could have confounded our findings.

Gamma Knife Surgery for Metastatic Brain Tumors from Gynecologic Cancer.

PubMed

Matsunaga, Shigeo; Shuto, Takashi; Sato, Mitsuru

2016-05-01

The incidences of metastatic brain tumors from gynecologic cancer have increased. The results of Gamma Knife surgery (GKS) for the treatment of patients with brain metastases from gynecologic cancer (ovarian, endometrial, and uterine cervical cancers) were retrospectively analyzed to identify the efficacy and prognostic factors for local tumor control and survival. The medical records were retrospectively reviewed of 70 patients with 306 tumors who underwent GKS for brain metastases from gynecologic cancer between January 1995 and December 2013 in our institution. The primary cancers were ovarian in 33 patients with 147 tumors and uterine in 37 patients with 159 tumors. Median tumor volume was 0.3 cm(3). Median marginal prescription dose was 20 Gy. The local tumor control rates were 96.4% at 6 months and 89.9% at 1 year. There was no statistically significant difference between ovarian and uterine cancers. Higher prescription dose and smaller tumor volume were significantly correlated with local tumor control. Median overall survival time was 8 months. Primary ovarian cancer, controlled extracranial metastases, and solitary brain metastasis were significantly correlated with satisfactory overall survival. Median activities of daily living (ADL) preservation survival time was 8 months. Primary ovarian cancer, controlled extracranial metastases, and higher Karnofsky Performance Status score were significantly correlated with better ADL preservation. GKS is effective for control of tumor progression in patients with brain metastases from gynecologic cancer, and may provide neurologic benefits and preservation of the quality of life. Copyright © 2016 Elsevier Inc. All rights reserved.

Continuum of Care

MedlinePlus

... Brain Tumor Treatment Locations Treatment Side Effects & their Management Support and Resources Caregiver Resource Center Pediatric Caregiver Resource Center About Us Our Founders Board of Directors Staff Leadership Strategic Plan Financials News Careers Brain Tumor Information Brain Anatomy Brain ...

Clinical presentation, diagnosis, and pharmacotherapy of patients with primary brain tumors.

PubMed

Newton, H B; Turowski, R C; Stroup, T J; McCoy, L K

1999-01-01

To briefly review the clinical presentation and diagnosis of patients with primary brain tumors, followed by an in-depth survey of the pertinent pharmacotherapy. A detailed search of the neurologic, neurosurgical, and oncologic literature for basic science research, clinical studies, and review articles related to chemotherapy and pharmacotherapy of primary brain tumors. Relevant studies on tissue culture systems, animals, and humans examining the mechanisms of action, pharmacokinetics, clinical pharmacology, and treatment results of chemotherapeutic agents for primary brain tumors. In addition, studies of pharmacologic agents administered for supportive care and symptom control are reviewed. Primary brain tumors derive from cells within the intracranial cavity and generally present with headache, seizure activity, cognitive changes, and weakness. They are diagnosed most efficiently with magnetic resonance imaging. After diagnosis, the most common supportive medications include corticosteroids, gastric acid inhibitors, and anticonvulsants. Chemotherapy is adjunctive treatment for patients with malignant tumors and selected recurrent or progressive benign neoplasms. In general, the most effective chemotherapeutic drugs are alkylating agents such as the nitrosoureas, procarbazine, cisplatin, and carboplatin. Other agents used include cyclophosphamide, methotrexate, vincristine, and etoposide. Angiogenesis inhibitors and gene therapy comprise some of the novel therapeutic strategies under investigation. The efficacy of chemotherapy for primary brain tumors remains modest. Novel agents must be discovered that are more specific and attack tumor cells at the molecular level of tumorigenesis. Furthermore, strategies must be developed to counteract the pervasive problem of brain tumor chemoresistance.

Microglia and macrophages in malignant gliomas: recent discoveries and implications for promising therapies.

PubMed

da Fonseca, Anna Carolina Carvalho; Badie, Behnam

2013-01-01

Malignant gliomas are the most common primary brain tumors. Their deadliest manifestation, glioblastoma multiforme (GBM), accounts for 15% of all primary brain tumors and is associated with a median survival of only 15 months even after multimodal therapy. There is substantial presence of microglia and macrophages within and surrounding brain tumors. These immune cells acquire an alternatively activated phenotype with potent tumor-tropic functions that contribute to glioma growth and invasion. In this review, we briefly summarize recent data that has been reported on the interaction of microglia/macrophages with brain tumors and discuss potential application of these findings to the development of future antiglioma therapies.

Clinical applications of modern imaging technology: stereo image formation and location of brain cancer

NASA Astrophysics Data System (ADS)

Wang, Dezong; Wang, Jinxiang

1994-05-01

It is very important to locate the tumor for a patient, who has cancer in his brain. If he only gets X-CT or MRI pictures, the doctor does not know the size, shape location of the tumor and the relation between the tumor and other organs. This paper presents the formation of stereo images of cancer. On the basis of color code and color 3D reconstruction. The stereo images of tumor, brain and encephalic truncus are formed. The stereo image of cancer can be round on X, Y, Z-coordinates to show the shape from different directions. In order to show the location of tumor, stereo image of tumor and encephalic truncus are provided on different angles. The cross section pictures are also offered to indicate the relation of brain, tumor and encephalic truncus on cross sections. In this paper the calculating of areas, volume and the space between cancer and the side of the brain are also described.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI

NASA Astrophysics Data System (ADS)

Pei, Linmin; Reza, Syed M. S.; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M.

2017-03-01

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. To model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI.

PubMed

Pei, Linmin; Reza, Syed M S; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M

2017-02-11

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. In order to model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

A small-molecule antagonist of CXCR4 inhibits intracranial growth of primary brain tumors

NASA Astrophysics Data System (ADS)

Rubin, Joshua B.; Kung, Andrew L.; Klein, Robyn S.; Chan, Jennifer A.; Sun, Yanping; Schmidt, Karl; Kieran, Mark W.; Luster, Andrew D.; Segal, Rosalind A.

2003-11-01

The vast majority of brain tumors in adults exhibit glial characteristics. Brain tumors in children are diverse: Many have neuronal characteristics, whereas others have glial features. Here we show that activation of the Gi protein-coupled receptor CXCR4 is critical for the growth of both malignant neuronal and glial tumors. Systemic administration of CXCR4 antagonist AMD 3100 inhibits growth of intracranial glioblastoma and medulloblastoma xenografts by increasing apoptosis and decreasing the proliferation of tumor cells. This reflects the ability of AMD 3100 to reduce the activation of extracellular signal-regulated kinases 1 and 2 and Akt, all of which are pathways downstream of CXCR4 that promote survival, proliferation, and migration. These studies (i) demonstrate that CXCR4 is critical to the progression of diverse brain malignances and (ii) provide a scientific rationale for clinical evaluation of AMD 3100 in treating both adults and children with malignant brain tumors.

Quantitative assessment of Cerenkov luminescence for radioguided brain tumor resection surgery

NASA Astrophysics Data System (ADS)

Klein, Justin S.; Mitchell, Gregory S.; Cherry, Simon R.

2017-05-01

Cerenkov luminescence imaging (CLI) is a developing imaging modality that detects radiolabeled molecules via visible light emitted during the radioactive decay process. We used a Monte Carlo based computer simulation to quantitatively investigate CLI compared to direct detection of the ionizing radiation itself as an intraoperative imaging tool for assessment of brain tumor margins. Our brain tumor model consisted of a 1 mm spherical tumor remnant embedded up to 5 mm in depth below the surface of normal brain tissue. Tumor to background contrast ranging from 2:1 to 10:1 were considered. We quantified all decay signals (e±, gamma photon, Cerenkov photons) reaching the brain volume surface. CLI proved to be the most sensitive method for detecting the tumor volume in both imaging and non-imaging strategies as assessed by contrast-to-noise ratio and by receiver operating characteristic output of a channelized Hotelling observer.

Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software.

PubMed

Abdolmohammadi, Jamil; Shafiee, Mohsen; Faeghi, Fariborz; Arefan, Douman; Zali, Alireza; Motiei-Langroudi, Rouzbeh; Farshidfar, Zahra; Nazarlou, Ali Kiani; Tavakkoli, Ali; Yarham, Mohammad

2016-08-01

Timely diagnosis of brain tumors could considerably affect the process of patient treatment. To do so, para-clinical methods, particularly MRI, cannot be ignored. MRI has so far answered significant questions regarding tumor characteristics, as well as helping neurosurgeons. In order to detect the tumor cellularity, neuro-surgeons currently have to sample specimens by biopsy and then send them to the pathology unit. The aim of this study is to determine the tumor cellularity in the brain. In this cross-sectional study, 32 patients (18 males and 14 females from 18-77 y/o) were admitted to the neurosurgery department of Shohada-E Tajrish Hospital in Tehran, Iran from April 2012 to February 2014. In addition to routine pulse sequences, T2W Multi echo pulse sequences were taken and the images were analyzed using the MATLAB software to determine the brain tumor cellularity, compared with the biopsy. These findings illustrate the need for more T2 relaxation time decreases, the higher classes of tumors will stand out in the designed table. In this study, the results show T2 relaxation time with a 85% diagnostic weight, compared with the biopsy, to determine the brain tumor cellularity (p<0.05). Our results indicate that the T2 relaxation time feature is the best method to distinguish and present the degree of intra-axial brain tumors cellularity (85% accuracy compared to biopsy). The use of more data is recommended in order to increase the percent accuracy of this techniques.

[Positron emission tomography in the diagnosis of recurrent growth of brain tumors].

PubMed

Skvortsova, T Iu; Brodskaia, Z L; Rudas, M S; Mozhaev, S V; Gurchin, A F; Medvedev, S V

2005-01-01

The authors analyzed the results of 11C-methionine positron emission tomography (PET) in 101 patients with suspected recurrent brain tumor. The diagnosis was confirmed in 72 patients. The increased 11C-methionine uptake in the initial tumor area is considered to be a crucial PET evidence of a recurrent tumor. On the other hand, brain tissue histological changes associated with surgery, radiation, and chemotherapy were characterized by the low uptake of the tracer. The sensitivity and specificity of PET scanning in detecting tumor recurrence were found to be 95.8 and 96.5%, respectively. 11C-methionine PET is proposed as a reliable technique for early differentiating between a recurrent brain tumor and treatment-induced nonneoplastic changes.

Association between number of cell phone contracts and brain tumor incidence in nineteen U.S. States.

PubMed

Lehrer, Steven; Green, Sheryl; Stock, Richard G

2011-02-01

Some concern has arisen about adverse health effects of cell phones, especially the possibility that the low power microwave-frequency signal transmitted by the antennas on handsets might cause brain tumors or accelerate the growth of subclinical tumors. We analyzed data from the Statistical Report: Primary Brain Tumors in the United States, 2000-2004 and 2007 cell phone subscription data from the Governing State and Local Sourcebook. There was a significant correlation between number of cell phone subscriptions and brain tumors in nineteen US states (r = 0.950, P < 0.001). Because increased numbers of both cell phone subscriptions and brain tumors could be due solely to the fact that some states, such as New York, have much larger populations than other states, such as North Dakota, multiple linear regression was performed with number of brain tumors as the dependent variable, cell phone subscriptions, population, mean family income and mean age as independent variables. The effect of cell phone subscriptions was significant (P = 0.017), and independent of the effect of mean family income (P = 0.894), population (P = 0.003) and age (0.499). The very linear relationship between cell phone usage and brain tumor incidence is disturbing and certainly needs further epidemiological evaluation. In the meantime, it would be prudent to limit exposure to all sources of electro-magnetic radiation.

Towards tailored management of malignant brain tumors with nanotheranostics.

PubMed

Aparicio-Blanco, Juan; Torres-Suárez, Ana-Isabel

2018-06-01

Malignant brain tumors still represent an unmet medical need given their rapid progression and often fatal outcome within months of diagnosis. Given their extremely heterogeneous nature, the assumption that a single therapy could be beneficial for all patients is no longer plausible. Hence, early feedback on drug accumulation at the tumor site and on tumor response to treatment would help tailor therapies to each patient's individual needs for personalized medicine. In this context, at the intersection between imaging and therapy, theranostic nanomedicine is a promising new technique for individualized management of malignant brain tumors. Although brain nanotheranostics has yet to be translated into clinical practice, this field is now a research hotspot due to the growing demand for personalized therapies. In this review, the barriers to the clinical implementation of theranostic nanomedicine for tracking tumor responses to treatment and for guiding stimulus-activated therapies and surgical resection of malignant brain tumors are discussed. Likewise, the criteria that nanotheranostic systems need to fulfil to become clinically relevant formulations are analyzed in depth, focusing on theranostic agents already tested in vivo. Currently, magnetic nanoparticles exploiting brain targeting strategies represent the first generation of preclinical theranostic nanomedicines for the management of malignant brain tumors. The development of nanocarriers that can be used both in imaging studies and the treatment of brain tumors could help identify which patients are most and least likely to respond to a given treatment. This will enable clinicians to adapt the therapy to the needs of the patient and avoid overdosing non-responders. Given the many different approaches to non-invasive techniques for imaging and treating brain tumors, it is important to focus on the strategies most likely to be implemented and to design the most feasible theranostic biomaterials that will bring nanotheranostics one step closer to clinical practice. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

3-D in vivo brain tumor geometry study by scaling analysis

NASA Astrophysics Data System (ADS)

Torres Hoyos, F.; Martín-Landrove, M.

2012-02-01

A new method, based on scaling analysis, is used to calculate fractal dimension and local roughness exponents to characterize in vivo 3-D tumor growth in the brain. Image acquisition was made according to the standard protocol used for brain radiotherapy and radiosurgery, i.e., axial, coronal and sagittal magnetic resonance T1-weighted images, and comprising the brain volume for image registration. Image segmentation was performed by the application of the k-means procedure upon contrasted images. We analyzed glioblastomas, astrocytomas, metastases and benign brain tumors. The results show significant variations of the parameters depending on the tumor stage and histological origin.

Dynamic perfusion CT in brain tumors.

PubMed

Yeung, Timothy Pok Chi; Bauman, Glenn; Yartsev, Slav; Fainardi, Enrico; Macdonald, David; Lee, Ting-Yim

2015-12-01

Dynamic perfusion CT (PCT) is an imaging technique for assessing the vascular supply and hemodynamics of brain tumors by measuring blood flow, blood volume, and permeability-surface area product. These PCT parameters provide information complementary to histopathologic assessments and have been used for grading brain tumors, distinguishing high-grade gliomas from other brain lesions, differentiating true progression from post-treatment effects, and predicting prognosis after treatments. In this review, the basic principles of PCT are described, and applications of PCT of brain tumors are discussed. The advantages and current challenges, along with possible solutions, of PCT are presented. Copyright © 2015. Published by Elsevier Ireland Ltd.

Biothermal Model of Patient and Automatic Control System of Brain Temperature for Brain Hypothermia Treatment

NASA Astrophysics Data System (ADS)

Wakamatsu, Hidetoshi; Gaohua, Lu

Various surface-cooling apparatus such as the cooling cap, muffler and blankets have been commonly used for the cooling of the brain to provide hypothermic neuro-protection for patients of hypoxic-ischemic encephalopathy. The present paper is aimed at the brain temperature regulation from the viewpoint of automatic system control, in order to help clinicians decide an optimal temperature of the cooling fluid provided for these three types of apparatus. At first, a biothermal model characterized by dynamic ambient temperatures is constructed for adult patient, especially on account of the clinical practice of hypothermia and anesthesia in the brain hypothermia treatment. Secondly, the model is represented by the state equation as a lumped parameter linear dynamic system. The biothermal model is justified from their various responses corresponding to clinical phenomena and treatment. Finally, the optimal regulator is tentatively designed to give clinicians some suggestions on the optimal temperature regulation of the patient’s brain. It suggests the patient’s brain temperature could be optimally controlled to follow-up the temperature process prescribed by the clinicians. This study benefits us a great clinical possibility for the automatic hypothermia treatment.

Novel treatment strategies for brain tumors and metastases

PubMed Central

El-Habashy, Salma E.; Nazief, Alaa M.; Adkins, Chris E.; Wen, Ming Ming; El-Kamel, Amal H.; Hamdan, Ahmed M.; Hanafy, Amira S.; Terrell, Tori O.; Mohammad, Afroz S.; Lockman, Paul R.; Nounou, Mohamed Ismail

2015-01-01

This review summarizes patent applications in the past 5 years for the management of brain tumors and metastases. Most of the recent patents discuss one of the following strategies: the development of new drug entities that specifically target the brain cells, the blood–brain barrier and the tumor cells, tailor-designing a novel carrier system that is able to perform multitasks and multifunction as a drug carrier, targeting vehicle and even as a diagnostic tool, direct conjugation of a US FDA approved drug with a targeting moiety, diagnostic moiety or PK modifying moiety, or the use of innovative nontraditional approaches such as genetic engineering, stem cells and vaccinations. Until now, there has been no optimal strategy to deliver therapeutic agents to the CNS for the treatment of brain tumors and metastases. Intensive research efforts are actively ongoing to take brain tumor targeting, and novel and targeted CNS delivery systems to potential clinical application. PMID:24998288

Clinical study and numerical simulation of brain cancer dynamics under radiotherapy

NASA Astrophysics Data System (ADS)

Nawrocki, S.; Zubik-Kowal, B.

2015-05-01

We perform a clinical and numerical study of the progression of brain cancer tumor growth dynamics coupled with the effects of radiotherapy. We obtained clinical data from a sample of brain cancer patients undergoing radiotherapy and compare it to our numerical simulations to a mathematical model of brain tumor cell population growth influenced by radiation treatment. We model how the body biologically receives a physically delivered dose of radiation to the affected tumorous area in the form of a generalized LQ model, modified to account for the conversion process of sublethal lesions into lethal lesions at high radiation doses. We obtain good agreement between our clinical data and our numerical simulations of brain cancer progression given by the mathematical model, which couples tumor growth dynamics and the effect of irradiation. The correlation, spanning a wide dataset, demonstrates the potential of the mathematical model to describe the dynamics of brain tumor growth influenced by radiotherapy.

The isoform A of reticulon-4 (Nogo-A) in cerebrospinal fluid of primary brain tumor patients: influencing factors.

PubMed

Koper, Olga Martyna; Kamińska, Joanna; Milewska, Anna; Sawicki, Karol; Mariak, Zenon; Kemona, Halina; Matowicka-Karna, Joanna

2018-05-18

The influence of isoform A of reticulon-4 (Nogo-A), also known as neurite outgrowth inhibitor, on primary brain tumor development was reported. Therefore the aim was the evaluation of Nogo-A concentrations in cerebrospinal fluid (CSF) and serum of brain tumor patients compared with non-tumoral individuals. All serum results, except for two cases, obtained both in brain tumors and non-tumoral individuals, were below the lower limit of ELISA detection. Cerebrospinal fluid Nogo-A concentrations were significantly lower in primary brain tumor patients compared to non-tumoral individuals. The univariate linear regression analysis found that if white blood cell count increases by 1 × 10 3 /μL, the mean cerebrospinal fluid Nogo-A concentration value decreases 1.12 times. In the model of multiple linear regression analysis predictor variables influencing cerebrospinal fluid Nogo-A concentrations included: diagnosis, sex, and sodium level. The mean cerebrospinal fluid Nogo-A concentration value was 1.9 times higher for women in comparison to men. In the astrocytic brain tumor group higher sodium level occurs with lower cerebrospinal fluid Nogo-A concentrations. We found the opposite situation in non-tumoral individuals. Univariate linear regression analysis revealed, that cerebrospinal fluid Nogo-A concentrations change in relation to white blood cell count. In the created model of multiple linear regression analysis we found, that within predictor variables influencing CSF Nogo-A concentrations were diagnosis, sex, and sodium level. Results may be relevant to the search for cerebrospinal fluid biomarkers and potential therapeutic targets in primary brain tumor patients. Nogo-A concentrations were tested by means of enzyme-linked immunosorbent assay (ELISA).

Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

PubMed

Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

2014-01-01

The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Autophagy inhibition overcomes multiple mechanisms of resistance to BRAF inhibition in brain tumors

PubMed Central

Mulcahy Levy, Jean M; Zahedi, Shadi; Griesinger, Andrea M; Morin, Andrew; Davies, Kurtis D; Aisner, Dara L; Kleinschmidt-DeMasters, BK; Fitzwalter, Brent E; Goodall, Megan L; Thorburn, Jacqueline; Amani, Vladimir; Donson, Andrew M; Birks, Diane K; Mirsky, David M; Hankinson, Todd C; Handler, Michael H; Green, Adam L; Vibhakar, Rajeev; Foreman, Nicholas K; Thorburn, Andrew

2017-01-01

Kinase inhibitors are effective cancer therapies, but tumors frequently develop resistance. Current strategies to circumvent resistance target the same or parallel pathways. We report here that targeting a completely different process, autophagy, can overcome multiple BRAF inhibitor resistance mechanisms in brain tumors. BRAFV600Emutations occur in many pediatric brain tumors. We previously reported that these tumors are autophagy-dependent and a patient was successfully treated with the autophagy inhibitor chloroquine after failure of the BRAFV600E inhibitor vemurafenib, suggesting autophagy inhibition overcame the kinase inhibitor resistance. We tested this hypothesis in vemurafenib-resistant brain tumors. Genetic and pharmacological autophagy inhibition overcame molecularly distinct resistance mechanisms, inhibited tumor cell growth, and increased cell death. Patients with resistance had favorable clinical responses when chloroquine was added to vemurafenib. This provides a fundamentally different strategy to circumvent multiple mechanisms of kinase inhibitor resistance that could be rapidly tested in clinical trials in patients with BRAFV600E brain tumors. DOI: http://dx.doi.org/10.7554/eLife.19671.001 PMID:28094001

Phosphatidylserine-Targeted Nanotheranostics for Brain Tumor Imaging and Therapeutic Potential

PubMed Central

Wang, Lulu; Habib, Amyn A.; Mintz, Akiva; Li, King C.; Zhao, Dawen

2017-01-01

Phosphatidylserine (PS), the most abundant anionic phospholipid in cell membrane, is strictly confined to the inner leaflet in normal cells. However, this PS asymmetry is found disruptive in many tumor vascular endothelial cells. We discuss the underlying mechanisms for PS asymmetry maintenance in normal cells and its loss in tumor cells. The specificity of PS exposure in tumor vasculature but not normal blood vessels may establish it a useful biomarker for cancer molecular imaging. Indeed, utilizing PS-targeting antibodies, multiple imaging probes have been developed and multimodal imaging data have shown their high tumor-selective targeting in various cancers. There is a critical need for improved diagnosis and therapy for brain tumors. We have recently established PS-targeted nanoplatforms, aiming to enhance delivery of imaging contrast agents across the blood–brain barrier to facilitate imaging of brain tumors. Advantages of using the nanodelivery system, in particular, lipid-based nanocarriers, are discussed here. We also describe our recent research interest in developing PS-targeted nanotheranostics for potential image-guided drug delivery to treat brain tumors. PMID:28654387

Phosphatidylserine-Targeted Nanotheranostics for Brain Tumor Imaging and Therapeutic Potential.

PubMed

Wang, Lulu; Habib, Amyn A; Mintz, Akiva; Li, King C; Zhao, Dawen

2017-01-01

Phosphatidylserine (PS), the most abundant anionic phospholipid in cell membrane, is strictly confined to the inner leaflet in normal cells. However, this PS asymmetry is found disruptive in many tumor vascular endothelial cells. We discuss the underlying mechanisms for PS asymmetry maintenance in normal cells and its loss in tumor cells. The specificity of PS exposure in tumor vasculature but not normal blood vessels may establish it a useful biomarker for cancer molecular imaging. Indeed, utilizing PS-targeting antibodies, multiple imaging probes have been developed and multimodal imaging data have shown their high tumor-selective targeting in various cancers. There is a critical need for improved diagnosis and therapy for brain tumors. We have recently established PS-targeted nanoplatforms, aiming to enhance delivery of imaging contrast agents across the blood-brain barrier to facilitate imaging of brain tumors. Advantages of using the nanodelivery system, in particular, lipid-based nanocarriers, are discussed here. We also describe our recent research interest in developing PS-targeted nanotheranostics for potential image-guided drug delivery to treat brain tumors.

Micro-SPECT/CT-based pharmacokinetic analysis of 99mTc-diethylenetriaminepentaacetic acid in rats with blood-brain barrier disruption induced by focused ultrasound.

PubMed

Yang, Feng-Yi; Wang, Hsin-Ell; Lin, Guan-Liang; Teng, Ming-Che; Lin, Hui-Hsien; Wong, Tai-Tong; Liu, Ren-Shyan

2011-03-01

This study evaluated the pharmacokinetics of (99m)Tc-diethylenetriamine pentaacetate acid ((99m)Tc-DTPA) after intravenous administration in healthy and F98 glioma-bearing F344 rats in the presence of blood-brain barrier disruption (BBB-D) induced by focused ultrasound (FUS). The pharmacokinetics of the healthy and tumor-containing brains after BBB-D were compared to identify the optimal time period for combined treatment. Healthy and F98 glioma-bearing rats were injected intravenously with Evans blue (EB) and (99m)Tc-DTPA; these treatments took place with or without BBB-D induced by transcranial FUS of 1 hemisphere of the brain. The permeability of the BBB was quantified by EB extravasation. Twelve rats were scanned for 2 h to estimate uptake of (99m)Tc radioactivity with respect to time for the pharmacokinetic analysis. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining was performed to examine tissue damage. The accumulations of EB and (99m)Tc-DTPA in normal brains or brains with a tumor were significantly elevated after the intravenous injection when BBB-D was induced. The disruption-to-nondisruption ratio of the brains and the tumor-to-ipsilateral brain ratio of the tumors in terms of radioactivity reached a peak at 45 and 60 min, respectively. EB injection followed by sonication showed that there was an increase of about 2-fold in the tumor-to-ipsilateral brain EB ratio of the target tumors (7.36), compared with the control tumors (3.73). TUNEL staining showed no significant differences between the sonicated tumors and control tumors. This study demonstrates that (99m)Tc-DTPA micro-SPECT/CT can be used for the pharmacokinetic analysis of BBB-D induced by FUS. This method should be able to provide important information that will help with establishing an optimal treatment protocol for drug administration after FUS-induced BBB-D in clinical brain disease therapy.

Combination Adenovirus + Pembrolizumab to Trigger Immune Virus Effects

ClinicalTrials.gov

2018-06-20

Brain Cancer; Brain Neoplasm; Glioma; Glioblastoma; Gliosarcoma; Malignant Brain Tumor; Neoplasm, Neuroepithelial; Neuroectodermal Tumors; Neoplasm by Histologic Type; Neoplasm, Nerve Tissue; Nervous System Diseases

Childhood Brain and Spinal Cord Tumors Treatment Overview (PDQ®)—Patient Version

Cancer.gov

Brain and spinal cord tumors may be benign (not cancer) or malignant (cancer). Both types cause signs or symptoms and need treatment. Get information about the many kinds of brain and spinal cord tumors, signs and symptoms, tests to diagnose, and treatment in this expert-reviewed summary.

Brain Tumor Trials Collaborative | Center for Cancer Research

Cancer.gov

Brain Tumor Trials Collaborative In Pursuit of a Cure The mission of the BTTC is to develop and perform state-of-the-art clinical trials in a collaborative and collegial environment, advancing treatments for patients with brain tumors, merging good scientific method with concern for patient well-being and outcome.

Adult Brain and Spine Tumor Research - Facebook Live Event

Cancer.gov

Chief, Dr. Mark Gilbert and Senior Investigator, Dr. Terri Armstrong, of the NCI Center for Cancer Research, Neuro-Oncology Branch, will be joined by moderator and Chief Executive Officer, David Arons of the National Brain Tumor Society led a discussion on adult brain and spine tumor research and treatment.

Adult Brain and Spine Tumor Research and Development

Cancer.gov

Chief, Dr. Mark Gilbert and Senior Investigator, Dr. Terri Armstrong, of the NCI Center for Cancer Research, Neuro-Oncology Branch, will be joined by moderator and Chief Executive Officer, David Arons of the National Brain Tumor Society led a discussion on adult brain and spine tumor research and treatment.

Primary brain tumors, neural stem cell, and brain tumor cancer cells: where is the link?

PubMed Central

Germano, Isabelle; Swiss, Victoria; Casaccia, Patrizia

2010-01-01

The discovery of brain tumor-derived cells (BTSC) with the properties of stem cells has led to the formulation of the hypothesis that neural stem cells could be the cell of origin of primary brain tumors (PBT). In this review we present the most common molecular changes in PBT, define the criteria of identification of BTSC and discuss the similarities between the characteristics of these cells and those of the endogenous population of neural stem cells (NPCs) residing in germinal areas of the adult brain. Finally, we propose possible mechanisms of cancer initiation and progression and suggest a model of tumor initiation that includes intrinsic changes of resident NSC and potential changes in the microenvironment defining the niche where the NSC reside. PMID:20045420

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Breast Cancer Resistance Protein and P-glycoprotein in Brain Cancer: Two Gatekeepers Team Up

PubMed Central

Agarwal, Sagar; Hartz, Anika M.S.; Elmquist, William F.; Bauer, Björn

2012-01-01

Brain cancer is a devastating disease. Despite extensive research, treatment of brain tumors has been largely ineffective and the diagnosis of brain cancer remains uniformly fatal. Failure of brain cancer treatment may be in part due to limitations in drug delivery, influenced by the ABC drug efflux transporters P-gp and BCRP at the blood-brain and blood-tumor barriers, in brain tumor cells, as well as in brain tumor stem-like cells. P-gp and BCRP limit various anti-cancer drugs from entering the brain and tumor tissues, thus rendering chemotherapy ineffective. To overcome this obstacle, two strategies – targeting transporter regulation and direct transporter inhibition – have been proposed. In this review, we focus on these strategies. We first introduce the latest findings on signaling pathways that could potentially be targeted to down-regulate P-gp and BCRP expression and/or transport activity. We then highlight in detail the new paradigm of P-gp and BCRP working as a “cooperative team of gatekeepers” at the blood-brain barrier, discuss its ramifications for brain cancer therapy, and summarize the latest findings on dual P-gp/BCRP inhibitors. Finally, we provide a brief summary with conclusions and outline the perspectives for future research endeavors in this field. PMID:21827403

Yoga Therapy in Treating Patients With Malignant Brain Tumors

ClinicalTrials.gov

2017-07-27

Adult Anaplastic Astrocytoma; Adult Anaplastic Ependymoma; Adult Anaplastic Meningioma; Adult Anaplastic Oligodendroglioma; Adult Brain Stem Glioma; Adult Choroid Plexus Tumor; Adult Diffuse Astrocytoma; Adult Ependymoblastoma; Adult Ependymoma; Adult Giant Cell Glioblastoma; Adult Glioblastoma; Adult Gliosarcoma; Adult Grade II Meningioma; Adult Medulloblastoma; Adult Meningeal Hemangiopericytoma; Adult Mixed Glioma; Adult Oligodendroglioma; Adult Papillary Meningioma; Adult Pineal Gland Astrocytoma; Adult Pineoblastoma; Adult Pineocytoma; Adult Supratentorial Primitive Neuroectodermal Tumor (PNET); Recurrent Adult Brain Tumor

Atopic conditions and brain tumor risk in children and adolescents--an international case-control study (CEFALO).

PubMed

Shu, X; Prochazka, M; Lannering, B; Schüz, J; Röösli, M; Tynes, T; Kuehni, C E; Andersen, T V; Infanger, D; Schmidt, L S; Poulsen, A H; Klaeboe, L; Eggen, T; Feychting, M

2014-04-01

A number of epidemiological studies indicate an inverse association between atopy and brain tumors in adults, particularly gliomas. We investigated the association between atopic disorders and intracranial brain tumors in children and adolescents, using international collaborative CEFALO data. CEFALO is a population-based case-control study conducted in Denmark, Norway, Sweden, and Switzerland, including all children and adolescents in the age range 7-19 years diagnosed with a primary brain tumor between 2004 and 2008. Two controls per case were randomly selected from population registers matched on age, sex, and geographic region. Information about atopic conditions and potential confounders was collected through personal interviews. In total, 352 cases (83%) and 646 controls (71%) participated in the study. For all brain tumors combined, there was no association between ever having had an atopic disorder and brain tumor risk [odds ratio 1.03; 95% confidence interval (CI) 0.70-1.34]. The OR was 0.76 (95% CI 0.53-1.11) for a current atopic condition (in the year before diagnosis) and 1.22 (95% CI 0.86-1.74) for an atopic condition in the past. Similar results were observed for glioma. There was no association between atopic conditions and risk of all brain tumors combined or of glioma in particular. Stratification on current or past atopic conditions suggested the possibility of reverse causality, but may also the result of random variation because of small numbers in subgroups. In addition, an ongoing tumor treatment may affect the manifestation of atopic conditions, which could possibly affect recall when reporting about a history of atopic diseases. Only a few studies on atopic conditions and pediatric brain tumors are currently available, and the evidence is conflicting.

APPLICATION OF ISOTOPE ENCEPHALOGRAPHY AND ELECTROENCEPHALOSCOPY FOR LOCALIZATION OF BRAIN TUMOURS

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

Shamov, V.N.; Badmayev, C.N.; Bekhtereva, N.P.

1959-10-31

The problems of diagnosis and localization of brain tumors in some cases present many difficulities and make the neurosurgeon seek for additional methods of investigation. In such circumstances usage of the tracer technique in diagnostics is of considerable help, as it has obvious advantages compared with other methods of investigation, such as safety, painlessness, non-traumatism, absence of undesirable after effects, accuracy, and relative simplicity. The present communication is based on the results of clinical observations on 150 patients with verified brain tumors. Analyses of the data show that the accuracy of the brain tumor localizations vary, depending upon the depthmore » of the tumor site and conceniration of labelled material in the area of tumor growth. The diagnostic value of the method is doubtful in cases of tumors of posterior fossa, base of the brain, or the lesions of median line. The application of isotope encephalography is successfully supplemented by the new method of investigations, i.e., electroencephaloscopy, which allows the localization of deeply set tumors. Possibilities and limitations of the method are discussed. It is concluded that the isotope encephalography and electroencephaloscopy represent very valuable diagnostic methods which alongside with other auxiliary methods are widely used in diagnosis of brain tumors. (C.H.)« less

Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

NASA Astrophysics Data System (ADS)

Sadeghi-Goughari, M.; Mojra, A.; Sadeghi, S.

2016-02-01

Intraoperative Thermal Imaging (ITI) is a new minimally invasive diagnosis technique that can potentially locate margins of brain tumor in order to achieve maximum tumor resection with least morbidity. This study introduces a new approach to ITI based on artificial tactile sensing (ATS) technology in conjunction with artificial neural networks (ANN) and feasibility and applicability of this method in diagnosis and localization of brain tumors is investigated. In order to analyze validity and reliability of the proposed method, two simulations were performed. (i) An in vitro experimental setup was designed and fabricated using a resistance heater embedded in agar tissue phantom in order to simulate heat generation by a tumor in the brain tissue; and (ii) A case report patient with parafalcine meningioma was presented to simulate ITI in the neurosurgical procedure. In the case report, both brain and tumor geometries were constructed from MRI data and tumor temperature and depth of location were estimated. For experimental tests, a novel assisted surgery robot was developed to palpate the tissue phantom surface to measure temperature variations and ANN was trained to estimate the simulated tumor’s power and depth. Results affirm that ITI based ATS is a non-invasive method which can be useful to detect, localize and characterize brain tumors.

Mobile phone use and brain tumors in children and adolescents: a multicenter case-control study.

PubMed

Aydin, Denis; Feychting, Maria; Schüz, Joachim; Tynes, Tore; Andersen, Tina Veje; Schmidt, Lisbeth Samsø; Poulsen, Aslak Harbo; Johansen, Christoffer; Prochazka, Michaela; Lannering, Birgitta; Klæboe, Lars; Eggen, Tone; Jenni, Daniela; Grotzer, Michael; Von der Weid, Nicolas; Kuehni, Claudia E; Röösli, Martin

2011-08-17

It has been hypothesized that children and adolescents might be more vulnerable to possible health effects from mobile phone exposure than adults. We investigated whether mobile phone use is associated with brain tumor risk among children and adolescents. CEFALO is a multicenter case-control study conducted in Denmark, Sweden, Norway, and Switzerland that includes all children and adolescents aged 7-19 years who were diagnosed with a brain tumor between 2004 and 2008. We conducted interviews, in person, with 352 case patients (participation rate: 83%) and 646 control subjects (participation rate: 71%) and their parents. Control subjects were randomly selected from population registries and matched by age, sex, and geographical region. We asked about mobile phone use and included mobile phone operator records when available. Odds ratios (ORs) for brain tumor risk and 95% confidence intervals (CIs) were calculated using conditional logistic regression models. Regular users of mobile phones were not statistically significantly more likely to have been diagnosed with brain tumors compared with nonusers (OR = 1.36; 95% CI = 0.92 to 2.02). Children who started to use mobile phones at least 5 years ago were not at increased risk compared with those who had never regularly used mobile phones (OR = 1.26, 95% CI = 0.70 to 2.28). In a subset of study participants for whom operator recorded data were available, brain tumor risk was related to the time elapsed since the mobile phone subscription was started but not to amount of use. No increased risk of brain tumors was observed for brain areas receiving the highest amount of exposure. The absence of an exposure-response relationship either in terms of the amount of mobile phone use or by localization of the brain tumor argues against a causal association.

Detection of somatic mutations in the mitochondrial DNA control region D-loop in brain tumors: The first report in Malaysian patients.

PubMed

Mohamed Yusoff, Abdul Aziz; Mohd Nasir, Khairol Naaim; Haris, Khalilah; Mohd Khair, Siti Zulaikha Nashwa; Abdul Ghani, Abdul Rahman Izaini; Idris, Zamzuri; Abdullah, Jafri Malin

2017-11-01

Although the role of nuclear-encoded gene alterations has been well documented in brain tumor development, the involvement of the mitochondrial genome in brain tumorigenesis has not yet been fully elucidated and remains controversial. The present study aimed to identify mutations in the mitochondrial DNA (mtDNA) control region D-loop in patients with brain tumors in Malaysia. A mutation analysis was performed in which DNA was extracted from paired tumor tissue and blood samples obtained from 49 patients with brain tumors. The D-loop region DNA was amplified using the PCR technique, and genetic data from DNA sequencing analyses were compared with the published revised Cambridge sequence to identify somatic mutations. Among the 49 brain tumor tissue samples evaluated, 25 cases (51%) had somatic mutations of the mtDNA D-loop, with a total of 48 mutations. Novel mutations that had not previously been identified in the D-loop region (176 A-deletion, 476 C>A, 566 C>A and 16405 A-deletion) were also classified. No significant associations between the D-loop mutation status and the clinicopathological parameters were observed. To the best of our knowledge, the current study presents the first evidence of alterations in the mtDNA D-loop regions in the brain tumors of Malaysian patients. These results may provide an overview and data regarding the incidence of mitochondrial genome alterations in Malaysian patients with brain tumors. In addition to nuclear genome aberrations, these specific mitochondrial genome alterations may also be considered as potential cancer biomarkers for the diagnosis and staging of brain cancers.

Dynamic glucose enhanced (DGE) MRI for combined imaging of blood-brain barrier break down and increased blood volume in brain cancer.

PubMed

Xu, Xiang; Chan, Kannie W Y; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T; van Zijl, Peter C M

2015-12-01

Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared with contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (P < 0.005). Both CEST and relaxation effects contribute to the signal change. DGE MRI is a feasible technique for studying brain tumor enhancement reflecting differences in tumor blood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. © 2015 Wiley Periodicals, Inc.

Dynamic Glucose Enhanced (DGE) MRI for Combined Imaging of Blood Brain Barrier Break Down and Increased Blood Volume in Brain Cancer

PubMed Central

Xu, Xiang; Chan, Kannie WY; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T.; van Zijl, Peter C.M.

2015-01-01

Purpose Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Methods Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. Results DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared to contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (p<0.005). Both CEST and relaxation effects contribute to the signal change. Conclusion DGE MRI is a feasible technique for studying brain tumor enhancement reflecting differences in tumor blood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. PMID:26404120

The effect of mannitol on intraoperative brain relaxation in patients undergoing supratentorial tumor surgery: study protocol for a randomized controlled trial

PubMed Central

2014-01-01

Background The risk of brain swelling after dural opening is high in patients with midline shift undergoing supratentorial tumor surgery. Brain swelling may result in increased intracranial pressure, impeded tumor exposure, and adverse outcomes. Mannitol is recommended as a first-line dehydration treatment to reduce brain edema and enable brain relaxation during neurosurgery. Research has indicated that mannitol enhanced brain relaxation in patients undergoing supratentorial tumor surgery; however, these results need further confirmation, and the optimal mannitol dose has not yet been established. We propose to examine whether different doses of 20% mannitol improve brain relaxation in a dose-dependent manner when administered at the time of incision. We will examine patients with preexisting mass effects and midline shift undergoing elective supratentorial brain tumor surgery. Methods This is a single-center, randomized controlled, parallel group trial that will be carried out at Beijing Tiantan Hospital, Capital Medical University. Randomization will be achieved using a computer-generated table. The study will include 220 patients undergoing supratentorial tumor surgery whose preoperative computed tomography/magnetic resonance imaging results indicate a brain midline shift. Patients in group A, group B, and group C will receive dehydration treatment at incision with 20% mannitol solutions of 0.7, 1.0, and 1.4 g/kg, respectively, at a rate of 600 mL/h. The patients in the control group will not receive mannitol. The primary outcome is an improvement in intraoperative brain relaxation and dura tension after dehydration with mannitol. Secondary outcomes are postoperative outcomes and the incidence of mannitol side effects. Discussion The aim of this study is to determine the optimal dose of 20% mannitol for intraoperative infusion. We will examine brain relaxation and outcome in patients undergoing supratentorial tumor surgery. If our results are positive, the study will indicate the optimal dose of mannitol to improve brain relaxation and avoid side effects during brain tumor surgery. Trial registration The study is registered with the registry website http://www.chictr.org with the registration number ChiCTRTRC13003984 (17 December 2013). PMID:24884731

Surgical management of patients with primary brain tumors.

PubMed

Bohan, Eileen; Glass-Macenka, Deanna

2004-11-01

To provide an overview of the diagnostic work-up, intraoperative technologies, postoperative treatment options, and investigational new therapies in patients with malignant brain tumors. Published textbooks and articles and other reference materials. Recent improvements in diagnostic and surgical equipment have influenced outcomes and overall quality of life for patients with central nervous system tumors. The ability to more accurately target and more safely remove brain tumors has enhanced the postoperative period and decreased hospital stays. However, malignant neoplasms continue to be refractory to current treatments, necessitating innovative surgical approaches at the time of initial diagnosis and at tumor recurrence. Nurses with an understanding of current diagnostic and surgical treatment modalities for brain tumors are able to provide accurate patient education and comprehensive care, enhancing the overall hospital and outpatient experience.

Detection of experimental brain tumors using time-resolved laser-induced fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Thompson, Reid C.; Black, Keith L.; Kateb, Babak; Marcu, Laura

2002-05-01

Time-Resolved Laser-Induced Fluorescence Spectroscopy (TR-LIFS) has the potential to provide a non- invasive characterization and detection of tumors. We utilized TR-LIFS to detect gliomas in-vivo in the rat C6 glioma model. Time-resolved emission spectra of both normal brain and tumor were analyzed to determine if unique fluorescence signatures could be used to distinguish the two. Fluorescence parameters derived from both spectral and time domain were used for tissue characterization. Our results show that in the rat C6 glioma model, TR-LIFS can be used to differentiate brain tumors from normal tissue (gray and white mater) based upon time- resolved fluorescence signatures seen in brain tumors.

Microglia and Macrophages in Malignant Gliomas: Recent Discoveries and Implications for Promising Therapies

PubMed Central

Carvalho da Fonseca, Anna Carolina; Badie, Behnam

2013-01-01

Malignant gliomas are the most common primary brain tumors. Their deadliest manifestation, glioblastoma multiforme (GBM), accounts for 15% of all primary brain tumors and is associated with a median survival of only 15 months even after multimodal therapy. There is substantial presence of microglia and macrophages within and surrounding brain tumors. These immune cells acquire an alternatively activated phenotype with potent tumor-tropic functions that contribute to glioma growth and invasion. In this review, we briefly summarize recent data that has been reported on the interaction of microglia/macrophages with brain tumors and discuss potential application of these findings to the development of future antiglioma therapies. PMID:23864876

Diagnostic value of the fast-FLAIR sequence in MR imaging of intracranial tumors.

PubMed

Husstedt, H W; Sickert, M; Köstler, H; Haubitz, B; Becker, H

2000-01-01

The aim of this study was to quantify imaging characteristics of fast fluid-attenuated inversion recovery (FLAIR) sequence in brain tumors compared with T1-postcontrast- and T2-sequences. Fast-FLAIR-, T2 fast spin echo (FSE)-, and T1 SE postcontrast images of 74 patients with intracranial neoplasms were analyzed. Four neuroradiologists rated signal intensity and inhomogeneity of the tumor, rendering of cystic parts, demarcation of the tumor vs brain, of the tumor vs edema and of brain vs edema, as well as the presence of motion and of other artifacts. Data analysis was performed for histologically proven astrocytomas, glioblastomas, and meningiomas, for tumors with poor contrast enhancement, and for all patients pooled. Only for tumors with poor contrast enhancement (n = 12) did fast FLAIR provide additional information about the lesion. In these cases, signal intensity, demarcation of the tumor vs brain, and differentiation of the tumor vs edema were best using fast FLAIR. In all cases, rendering of the tumor's inner structure was poor. For all other tumor types, fast FLAIR did not give clinically relevant information, the only exception being a better demarcation of the edema from brain tissue. Artifacts rarely interfered with evaluation of fast-FLAIR images. Thus, fast FLAIR cannot replace T2-weighted series. It provides additional information only in tumors with poor contrast enhancement. It is helpful for defining the exact extent of the edema of any tumor but gives little information about their inner structure.

Label-Free Delineation of Brain Tumors by Coherent Anti-Stokes Raman Scattering Microscopy in an Orthotopic Mouse Model and Human Glioblastoma

PubMed Central

Tamosaityte, Sandra; Leipnitz, Elke; Geiger, Kathrin D.; Schackert, Gabriele; Koch, Edmund; Steiner, Gerald; Kirsch, Matthias

2014-01-01

Background Coherent anti-Stokes Raman scattering (CARS) microscopy provides fine resolution imaging and displays morphochemical properties of unstained tissue. Here, we evaluated this technique to delineate and identify brain tumors. Methods Different human tumors (glioblastoma, brain metastases of melanoma and breast cancer) were induced in an orthotopic mouse model. Cryosections were investigated by CARS imaging tuned to probe C-H molecular vibrations, thereby addressing the lipid content of the sample. Raman microspectroscopy was used as reference. Histopathology provided information about the tumor's localization, cell proliferation and vascularization. Results The morphochemical contrast of CARS images enabled identifying brain tumors irrespective of the tumor type and properties: All tumors were characterized by a lower CARS signal intensity than the normal parenchyma. On this basis, tumor borders and infiltrations could be identified with cellular resolution. Quantitative analysis revealed that the tumor-related reduction of CARS signal intensity was more pronounced in glioblastoma than in metastases. Raman spectroscopy enabled relating the CARS intensity variation to the decline of total lipid content in the tumors. The analysis of the immunohistochemical stainings revealed no correlation between tumor-induced cytological changes and the extent of CARS signal intensity reductions. The results were confirmed on samples of human glioblastoma. Conclusions CARS imaging enables label-free, rapid and objective identification of primary and secondary brain tumors. Therefore, it is a potential tool for diagnostic neuropathology as well as for intraoperative tumor delineation. PMID:25198698

Genomic characterization of brain metastases reveals branched evolution and potential therapeutic targets

PubMed Central

Santagata, Sandro; Cahill, Daniel P.; Taylor-Weiner, Amaro; Jones, Robert T.; Van Allen, Eliezer M.; Lawrence, Michael S.; Horowitz, Peleg M.; Cibulskis, Kristian; Ligon, Keith L.; Tabernero, Josep; Seoane, Joan; Martinez-Saez, Elena; Curry, William T.; Dunn, Ian F.; Paek, Sun Ha; Park, Sung-Hye; McKenna, Aaron; Chevalier, Aaron; Rosenberg, Mara; Barker, Frederick G.; Gill, Corey M.; Van Hummelen, Paul; Thorner, Aaron R.; Johnson, Bruce E.; Hoang, Mai P.; Choueiri, Toni K.; Signoretti, Sabina; Sougnez, Carrie; Rabin, Michael S.; Lin, Nancy U.; Winer, Eric P.; Stemmer-Rachamimov, Anat; Meyerson, Matthew; Garraway, Levi; Gabriel, Stacey; Lander, Eric S.; Beroukhim, Rameen; Batchelor, Tracy T.; Baselga, Jose; Louis, David N.

2016-01-01

Brain metastases are associated with a dismal prognosis. Whether brain metastases harbor distinct genetic alterations beyond those observed in primary tumors is unknown. We performed whole-exome sequencing of 86 matched brain metastases, primary tumors and normal tissue. In all clonally related cancer samples, we observed branched evolution, where all metastatic and primary sites shared a common ancestor yet continued to evolve independently. In 53% of cases, we found potentially clinically informative alterations in the brain metastases not detected in the matched primary-tumor sample. In contrast, spatially and temporally separated brain metastasis sites were genetically homogenous. Distal extracranial and regional lymph node metastases were highly divergent from brain metastases. We detected alterations associated with sensitivity to PI3K/AKT/mTOR, CDK, and HER2/EGFR inhibitors in the brain metastases. Genomic analysis of brain metastases provides an opportunity to identify potentially clinically informative alterations not detected in clinically sampled primary tumors, regional lymph nodes, or extracranial metastases. PMID:26410082

Dietary Selenium Supplementation Modulates Growth of Brain Metastatic Tumors and Changes the Expression of Adhesion Molecules in Brain Microvessels.

PubMed

Wrobel, Jagoda K; Wolff, Gretchen; Xiao, Rijin; Power, Ronan F; Toborek, Michal

2016-08-01

Various dietary agents can modulate tumor invasiveness. The current study explored whether selenoglycoproteins (SeGPs) extracted from selenium-enriched yeast affect tumor cell homing and growth in the brain. Mice were fed diets enriched with specific SeGPs (SeGP40 or SeGP65, 1 mg/kg Se each), glycoproteins (GP40 or GP65, 0.2-0.3 mg/kg Se each) or a control diet (0.2-0.3 mg/kg Se) for 12 weeks. Then, murine Lewis lung carcinoma cells were infused into the brain circulation. Analyses were performed at early (48 h) and late stages (3 weeks) post tumor cell infusion. Imaging of tumor progression in the brain revealed that mice fed SeGP65-enriched diet displayed diminished metastatic tumor growth, fewer extravasating tumor cells and smaller metastatic lesions. While administration of tumor cells resulted in a significant upregulation of adhesion molecules in the early stage of tumor progression, overexpression of VCAM-1 (vascular call adhesion molecule-1) and ALCAM (activated leukocyte cell adhesion molecule) messenger RNA (mRNA) was diminished in SeGP65 supplemented mice. Additionally, mice fed SeGP65 showed decreased expression of acetylated NF-κB p65, 48 h post tumor cell infusion. The results indicate that tumor progression in the brain can be modulated by specific SeGPs. Selenium-containing compounds were more effective than their glycoprotein controls, implicating selenium as a potential negative regulator of metastatic process.

Mobile phones, brain tumors, and the interphone study: where are we now?

PubMed

Swerdlow, Anthony J; Feychting, Maria; Green, Adele C; Leeka Kheifets, Leeka Kheifets; Savitz, David A

2011-11-01

In the past 15 years, mobile telephone use has evolved from an uncommon activity to one with > 4.6 billion subscriptions worldwide. However, there is public concern about the possibility that mobile phones might cause cancer, especially brain tumors. We reviewed the evidence on whether mobile phone use raises the risk of the main types of brain tumor—glioma and meningioma—with a particular focus on the recent publication of the largest epidemiologic study yet: the 13-country Interphone Study. Methodological defcits limit the conclusions that can be drawn from the Interphone study, but its results, along with those from other epidemiologic, biological, and animal studies and brain tumor incidence trends, suggest that within about 10–15 years after first use of mobile phones there is unlikely to be a material increase in the risk of brain tumors in adults. Data for childhood tumors and for periods beyond 15 years are currently lacking. Although there remains some uncertainty, the trend in the accumulating evidence is increasingly against the hypothesis that mobile phone use can cause brain tumors in adults.

Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN).

PubMed

Iqbal, Sajid; Ghani, M Usman; Saba, Tanzila; Rehman, Amjad

2018-04-01

A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treatment of brain tumors. Deep Learning is a set of promising techniques that could provide better results as compared to nondeep learning techniques for segmenting timorous part inside a brain. This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs. The proposed network uses BRATS segmentation challenge dataset which is composed of images obtained through four different modalities. Accordingly, we present an extended version of existing network to solve segmentation problem. The network architecture consists of multiple neural network layers connected in sequential order with the feeding of Convolutional feature maps at the peer level. Experimental results on BRATS 2015 benchmark data thus show the usability of the proposed approach and its superiority over the other approaches in this area of research. © 2018 Wiley Periodicals, Inc.

Mobile Phones, Brain Tumors, and the Interphone Study: Where Are We Now?

PubMed Central

Feychting, Maria; Green, Adele C.; Kheifets, Leeka; Savitz, David A.

2011-01-01

Background: In the past 15 years, mobile telephone use has evolved from an uncommon activity to one with > 4.6 billion subscriptions worldwide. However, there is public concern about the possibility that mobile phones might cause cancer, especially brain tumors. Objectives: We reviewed the evidence on whether mobile phone use raises the risk of the main types of brain tumor—glioma and meningioma—with a particular focus on the recent publication of the largest epidemiologic study yet: the 13-country Interphone Study. Discussion: Methodological deficits limit the conclusions that can be drawn from the Interphone study, but its results, along with those from other epidemiologic, biological, and animal studies and brain tumor incidence trends, suggest that within about 10–15 years after first use of mobile phones there is unlikely to be a material increase in the risk of brain tumors in adults. Data for childhood tumors and for periods beyond 15 years are currently lacking. Conclusions: Although there remains some uncertainty, the trend in the accumulating evidence is increasingly against the hypothesis that mobile phone use can cause brain tumors in adults. PMID:22171384

Non-invasive intraoperative optical coherence tomography of the resection cavity during surgery of intrinsic brain tumors

NASA Astrophysics Data System (ADS)

Giese, A.; Böhringer, H. J.; Leppert, J.; Kantelhardt, S. R.; Lankenau, E.; Koch, P.; Birngruber, R.; Hüttmann, G.

2006-02-01

Optical coherence tomography (OCT) is a non-invasive imaging technique with a micrometer resolution. It allows non-contact / non-invasive analysis of central nervous system tissues with a penetration depth of 1-3,5 mm reaching a spatial resolution of approximately 4-15 μm. We have adapted spectral-domain OCT (SD-OCT) and time-domain OCT (TD-OCT) for intraoperative detection of residual tumor during brain tumor surgery. Human brain tumor tissue and areas of the resection cavity were analyzed during the resection of gliomas using this new technology. The site of analysis was registered using a neuronavigation system and biopsies were taken and submitted to routine histology. We have used post image acquisition processing to compensate for movements of the brain and to realign A-scan images for calculation of a light attenuation factor. OCT imaging of normal cortex and white matter showed a typical light attenuation profile. Tumor tissue depending on the cellularity of the specimen showed a loss of the normal light attenuation profile resulting in altered light attenuation coefficients compared to normal brain. Based on this parameter and the microstructure of the tumor tissue, which was entirely absent in normal tissue, OCT analysis allowed the discrimination of normal brain tissue, invaded brain, solid tumor tissue, and necrosis. Following macroscopically complete resections OCT analysis of the resection cavity displayed the typical microstructure and light attenuation profile of tumor tissue in some specimens, which in routine histology contained microscopic residual tumor tissue. We have demonstrated that this technology may be applied to the intraoperative detection of residual tumor during resection of human gliomas.

Automatic labeling of MR brain images through extensible learning and atlas forests.

PubMed

Xu, Lijun; Liu, Hong; Song, Enmin; Yan, Meng; Jin, Renchao; Hung, Chih-Cheng

2017-12-01

Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations. We propose an extensible learning model which allows the multiatlas-based framework capable of managing the datasets with numerous atlases or dynamic atlas datasets and simultaneously ensure the accuracy of automatic labeling. Two new strategies are used to reduce the time and space complexity and improve the efficiency of the automatic labeling of brain MR images. First, atlases are encoded to atlas forests through random forest technology to reduce the time consumed for cross-registration between atlases and target image, and a scatter spatial vector is designed to eliminate errors caused by inaccurate registration. Second, an atlas selection method based on the extensible learning model is used to select atlases for target image without traversing the entire dataset and then obtain the accurate labeling. The labeling results of the proposed method were evaluated in three public datasets, namely, IBSR, LONI LPBA40, and ADNI. With the proposed method, the dice coefficient metric values on the three datasets were 84.17 ± 4.61%, 83.25 ± 4.29%, and 81.88 ± 4.53% which were 5% higher than those of the conventional method, respectively. The efficiency of the extensible learning model was evaluated by state-of-the-art methods for labeling of MR brain images. Experimental results showed that the proposed method could achieve accurate labeling for MR brain images without traversing the entire datasets. In the proposed multiatlas-based method, extensible learning and atlas forests were applied to control the automatic labeling of brain anatomies on large atlas datasets or dynamic atlas datasets and obtain accurate results. © 2017 American Association of Physicists in Medicine.

Profiles of Brain Metastases: Prioritization of Therapeutic Targets.

PubMed

Ferguson, Sherise D; Zheng, Siyuan; Xiu, Joanne; Zhou, Shouhao; Khasraw, Mustafa; Brastianos, Priscilla K; Kesari, Santosh; Hu, Jethro; Rudnick, Jeremy; Salacz, Michael E; Piccioni, David; Huang, Suyun; Davies, Michael A; Glitza, Isabella C; Heymach, John V; Zhang, Jianjun; Ibrahim, Nuhad K; DeGroot, John F; McCarty, Joseph; O'Brien, Barbara J; Sawaya, Raymond; Verhaak, Roeland G W; Reddy, Sandeep K; Priebe, Waldemar; Gatalica, Zoran; Spetzler, David; Heimberger, Amy B

2018-06-19

We sought to compare the tumor profiles of brain metastases from common cancers with those of primary tumors and extracranial metastases in order to identify potential targets and prioritize rational treatment strategies. Tumor samples were collected from both the primary and metastatic sites of non-small cell lung cancer, breast cancer, and melanoma from patients in locations worldwide, and these were submitted to Caris Life Sciences for tumor multiplatform analysis, including gene sequencing (Sanger and next-generation sequencing with a targeted 47-gene panel), protein expression (assayed by immunohistochemistry), and gene amplification (assayed by in situ hybridization). The data analysis considered differential protein expression, gene amplification, and mutations among brain metastases, extracranial metastases, and primary tumors. The analyzed population included: 16,999 unmatched primary tumor and/or metastasis samples: 8178 non-small cell lung cancers (5098 primaries; 2787 systemic metastases; 293 brain metastases), 7064 breast cancers (3496 primaries; 3469 systemic metastases; 99 brain metastases), and 1757 melanomas (660 primaries; 996 systemic metastases; 101 brain metastases). TOP2A expression was increased in brain metastases from all 3 cancers, and brain metastases overexpressed multiple proteins clustering around functions critical to DNA synthesis and repair and implicated in chemotherapy resistance, including RRM1, TS, ERCC1, and TOPO1. cMET was overexpressed in melanoma brain metastases relative to primary skin specimens. Brain metastasis patients may particularly benefit from therapeutic targeting of enzymes associated with DNA synthesis, replication, and/or repair. This article is protected by copyright. All rights reserved. © 2018 UICC.

Brain Tumor Statistics

MedlinePlus

... Scientific Advisory Council & Reviewers The International Low Grade Glioma Registry Get Involved Advocacy Breakthrough for Brain Tumors ... an estimated 29,320 new cases in 2018. Gliomas , a broad term which includes all tumors arising ...

Industry progress report on neuro-oncology: Biotech update 2013.

PubMed

Ottenhausen, Malte; Bodhinayake, Imithri; Banu, Matei; Kesavabhotla, Kartik; Ray, Ashley; Boockvar, John A

2013-11-01

For the second time, The Brain Tumor Center of the Weill Cornell Brain and Spine Center, in collaboration with Voices Against Brain Cancer, hosted The Brain Tumor Biotech Summit in New York City in June 2013. After a very successful first summit in 2012, this innovative event has established a platform for intensive networking between neuro-oncologists, neurosurgeons, neuroscientists, members of the biotechnology and pharmaceutical communities, members of the financial community and leaders of non-profit organizations. This year's summit highlighted dendritic cell vaccines, novel antibody, heat shock protein and targeted therapies as well as exosome technologies, MRI-guided therapies and other novel drug delivery tools. This report presents a short overview of the current progress in brain tumor research and therapy as presented at the 2013 Brain Tumor Biotech Summit.

Establishment and Characterization of a Tumor Stem Cell-Based Glioblastoma Invasion Model.

PubMed

Jensen, Stine Skov; Meyer, Morten; Petterson, Stine Asferg; Halle, Bo; Rosager, Ann Mari; Aaberg-Jessen, Charlotte; Thomassen, Mads; Burton, Mark; Kruse, Torben A; Kristensen, Bjarne Winther

2016-01-01

Glioblastoma is the most frequent and malignant brain tumor. Recurrence is inevitable and most likely connected to tumor invasion and presence of therapy resistant stem-like tumor cells. The aim was therefore to establish and characterize a three-dimensional in vivo-like in vitro model taking invasion and tumor stemness into account. Glioblastoma stem cell-like containing spheroid (GSS) cultures derived from three different patients were established and characterized. The spheroids were implanted in vitro into rat brain slice cultures grown in stem cell medium and in vivo into brains of immuno-compromised mice. Invasion was followed in the slice cultures by confocal time-lapse microscopy. Using immunohistochemistry, we compared tumor cell invasion as well as expression of proliferation and stem cell markers between the models. We observed a pronounced invasion into brain slice cultures both by confocal time-lapse microscopy and immunohistochemistry. This invasion closely resembled the invasion in vivo. The Ki-67 proliferation indexes in spheroids implanted into brain slices were lower than in free-floating spheroids. The expression of stem cell markers varied between free-floating spheroids, spheroids implanted into brain slices and tumors in vivo. The established invasion model kept in stem cell medium closely mimics tumor cell invasion into the brain in vivo preserving also to some extent the expression of stem cell markers. The model is feasible and robust and we suggest the model as an in vivo-like model with a great potential in glioma studies and drug discovery.

Neuropathological biomarker candidates in brain tumors: key issues for translational efficiency.

PubMed

Hainfellner, J A; Heinzl, H

2010-01-01

Brain tumors comprise a large spectrum of rare malignancies in children and adults that are often associated with severe neurological symptoms and fatal outcome. Neuropathological tumor typing provides both prognostic and predictive tissue information which is the basis for optimal postoperative patient management and therapy. Molecular biomarkers may extend and refine prognostic and predictive information in a brain tumor case, providing more individualized and optimized treatment options. In the recent past a few neuropathological brain tumor biomarkers have translated smoothly into clinical use whereas many candidates show protracted translation. We investigated the causes of protracted translation of candidate brain tumor biomarkers. Considering the research environment from personal, social and systemic perspectives we identified eight determinants of translational success: methodology, funding, statistics, organization, phases of research, cooperation, self-reflection, and scientific progeny. Smoothly translating biomarkers are associated with low degrees of translational complexity whereas biomarkers with protracted translation are associated with high degrees. Key issues for translational efficiency of neuropathological brain tumor biomarker research seem to be related to (i) the strict orientation to the mission of medical research, that is the improval of medical practice as primordial purpose of research, (ii) definition of research priorities according to clinical needs, and (iii) absorption of translational complexities by means of operatively beneficial standards. To this end, concrete actions should comprise adequate scientific education of young investigators, and shaping of integrative diagnostics and therapy research both on the local level and the level of influential international brain tumor research platforms.

Digit ratio (2D:4D) in primary brain tumor patients: A case-control study.

PubMed

Bunevicius, Adomas; Tamasauskas, Sarunas; Deltuva, Vytenis Pranas; Tamasauskas, Arimantas; Sliauzys, Albertas; Bunevicius, Robertas

2016-12-01

The second-to-fourth digit ratio (2D:4D) reflects prenatal estrogen and testosterone exposure, and is established in utero. Sex steroids are implicated in development and progression of primary brain tumors. To investigate whether there is a link between 2D:4D ratio and primary brain tumors, and age at presentation. Digital images of the right and left palms of 85 primary brain tumor patients (age 56.96±13.68years; 71% women) and 106 (age 54.31±13.68years; 68% women) gender and age matched controls were obtained. The most common brain tumor diagnoses were meningioma (41%), glioblastoma (20%) and pituitary adenoma (16%). Right and left 2D:4D ratios, and right minus left 2D:4D (D r-l ) were compared between patients and controls, and were correlated with age. Right and left 2D:4D ratios were significantly lower in primary brain tumor patients relative to controls (t=-4.28, p<0.001 and t=-3.69, p<0.001, respectively). The D r-l was not different between brain tumor patients and controls (p=0.27). In meningioma and glioma patients, age at presentation correlated negatively with left 2D:4D ratio (rho=-0.42, p=0.01 and rho=-0.36, p=0.02, respectively) and positively with D r-l (rho=0.45, p=0.009 and rho=0.65, p=0.04, respectively). Right and left hand 2D:4D ratios are lower in primary brain tumor patients relative to healthy individuals suggesting greater prenatal testosterone and lower prenatal estrogen exposure in brain tumor patients. Greater age at presentation is associated with greater D r-l and with lower left 2D:4D ratio of meningioma and glioma patients. Due to small sample size our results should be considered preliminary and interpreted with caution. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Global and Targeted Pathway Impact of Gliomas on White Matter Integrity Based on Lobar Localization.

PubMed

Ormond, David R; D'Souza, Shawn; Thompson, John A

2017-09-07

Primary brain tumors comprise 28% of all tumors and 80% of malignant tumors. Pathophysiology of high-grade gliomas includes significant distortion of white matter architecture, necrosis, the breakdown of the blood brain barrier, and increased intracranial pressure. Diffusion tensor imaging (DTI), a diffusion weighted imaging technique, can be used to assess white matter architecture. Use of DTI as a non-invasive pathophysiological tool to analyze glioma impact on white matter microstructure has yet to be fully explored. Preliminary assessment of DTI tractography was done as a measure of intracranial tumor impact on white matter architecture. Specifically, we addressed three questions: 1) whether glioma differentially affects local white matter structure compared to metastasis, 2) whether glioma affects tract integrity of major white matter bundles, 3) whether glioma lobe localization affects tract integrity of different white matter bundles. In this study, we retrospectively investigated preoperative DTI scans from 24 patients undergoing tumor resection. Fiber tractography was estimated using a deterministic fiber tracking algorithm in DSI (diffusion spectrum imaging) Studio. The automatic anatomical labeling (AAL) atlas was used to define the left and right (L/R)   hemisphere regions of interest (ROI). In addition, the John Hopkins University (JHU) White Matter Atlas was used to auto-segment major white matter bundle ROIs. For all tracts derived from ROI seed targets, we computed the following parameters: tract number, tract length, fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD). The DTI tractography analysis revealed that white matter integrity in the hemisphere ipsilateral to intracranial tumor was significantly compromised compared to the control contralateral hemisphere. No differences were observed between high vs low-grade gliomas, however, gliomas induced significantly greater white matter degradation than metastases. In addition, targeted analysis of major white matter bundles important for sensory/motor function (i.e., corticospinal tract and superior longitudinal fasciculus) revealed tract-parameter specific susceptibility due to the presence of the tumor. Finally, major tract bundles were differentially affected based on lobar localization of the glioma. These DTI-based tractographic analyses complement findings from gross histopathological examination of glioma impact on neural tissue. Global and focal white matter architecture, ipsilateral to glioma, shows higher rates of degradation or edema - based on DTI tractographic metrics - in comparison to normal brain or metastases. Gliomas, which arise in the parietal lobe, also have a higher negative impact (potentially due to increased edema) on white matter integrity of the superior longitudinal fasciculus(SLF) than those which arise in the frontal lobe. Future studies will focus on using preoperative and postoperative tractography to predict functional deficits following resective surgery.

Nanoparticle-assisted photothermal ablation of brain tumor in an orthotopic canine model

NASA Astrophysics Data System (ADS)

Schwartz, Jon A.; Shetty, Anil M.; Price, Roger E.; Stafford, R. Jason; Wang, James C.; Uthamanthil, Rajesh K.; Pham, Kevin; McNichols, Roger J.; Coleman, Chris L.; Payne, J. Donald

2009-02-01

We report on a pilot study demonstrating a proof of concept for the passive delivery of nanoshells to an orthotopic tumor where they induce a local, confined therapeutic response distinct from that of normal brain resulting in the photo-thermal ablation of canine Transmissible Venereal Tumor (cTVT) in a canine brain model. cTVT fragments grown in SCID mice were successfully inoculated in the parietal lobe of immuno-suppressed, mixed-breed hound dogs. A single dose of near-infrared absorbing, 150 nm nanoshells was infused intravenously and allowed time to passively accumulate in the intracranial tumors which served as a proxy for an orthotopic brain metastasis. The nanoshells accumulated within the intracranial cTVT suggesting that its neo-vasculature represented an interruption of the normal blood-brain barrier. Tumors were thermally ablated by percutaneous, optical fiber-delivered, near-infrared radiation using a 3.5 W average, 3-minute laser dose at 808 nm that selectively elevated the temperature of tumor tissue to 65.8+/-4.1ºC. Identical laser doses applied to normal white and gray matter on the contralateral side of the brain yielded sub-lethal temperatures of 48.6+/-1.1ºC. The laser dose was designed to minimize thermal damage to normal brain tissue in the absence of nanoshells and compensate for variability in the accumulation of nanoshells in tumor. Post-mortem histopathology of treated brain sections demonstrated the effectiveness and selectivity of the nanoshell-assisted thermal ablation.

Stereotactic Radiosurgery - Gamma Knife

MedlinePlus

... nerve that connects the ear to the brain ( acoustic neuroma ) Pituitary tumors Tumors that are not cancer ( ... and the A.D.A.M. Editorial team. Acoustic Neuroma Read more Brain Tumors Read more Radiation ...

Neuronavigation in the surgical management of brain tumors: current and future trends

PubMed Central

Orringer, Daniel A; Golby, Alexandra; Jolesz, Ferenc

2013-01-01

Neuronavigation has become an ubiquitous tool in the surgical management of brain tumors. This review describes the use and limitations of current neuronavigational systems for brain tumor biopsy and resection. Methods for integrating intraoperative imaging into neuronavigational datasets developed to address the diminishing accuracy of positional information that occurs over the course of brain tumor resection are discussed. In addition, the process of integration of functional MRI and tractography into navigational models is reviewed. Finally, emerging concepts and future challenges relating to the development and implementation of experimental imaging technologies in the navigational environment are explored. PMID:23116076

Complete prevalence of malignant primary brain tumors registry data in the United States compared with other common cancers, 2010

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

Zhang, Adah S.; Ostrom, Quinn T.; Kruchko, Carol

Complete prevalence proportions illustrate the burden of disease in a population. Here, this study estimates the 2010 complete prevalence of malignant primary brain tumors overall and by Central Brain Tumor Registry of the United States (CBTRUS) histology groups, and compares the brain tumor prevalence estimates to the complete prevalence of other common cancers as determined by the Surveillance, Epidemiology, and End Results Program (SEER) by age at prevalence (2010): children (0–14 y), adolescent and young adult (AYA) (15–39 y), and adult (40+ y).

Complete prevalence of malignant primary brain tumors registry data in the United States compared with other common cancers, 2010

DOE PAGES

Zhang, Adah S.; Ostrom, Quinn T.; Kruchko, Carol; ...

2016-12-29

Complete prevalence proportions illustrate the burden of disease in a population. Here, this study estimates the 2010 complete prevalence of malignant primary brain tumors overall and by Central Brain Tumor Registry of the United States (CBTRUS) histology groups, and compares the brain tumor prevalence estimates to the complete prevalence of other common cancers as determined by the Surveillance, Epidemiology, and End Results Program (SEER) by age at prevalence (2010): children (0–14 y), adolescent and young adult (AYA) (15–39 y), and adult (40+ y).

Semi-automated brain tumor and edema segmentation using MRI.

PubMed

Xie, Kai; Yang, Jie; Zhang, Z G; Zhu, Y M

2005-10-01

Manual segmentation of brain tumors from magnetic resonance images is a challenging and time-consuming task. A semi-automated method has been developed for brain tumor and edema segmentation that will provide objective, reproducible segmentations that are close to the manual results. Additionally, the method segments non-enhancing brain tumor and edema from healthy tissues in magnetic resonance images. In this study, a semi-automated method was developed for brain tumor and edema segmentation and volume measurement using magnetic resonance imaging (MRI). Some novel algorithms for tumor segmentation from MRI were integrated in this medical diagnosis system. We exploit a hybrid level set (HLS) segmentation method driven by region and boundary information simultaneously, region information serves as a propagation force which is robust and boundary information serves as a stopping functional which is accurate. Ten different patients with brain tumors of different size, shape and location were selected, a total of 246 axial tumor-containing slices obtained from 10 patients were used to evaluate the effectiveness of segmentation methods. This method was applied to 10 non-enhancing brain tumors and satisfactory results were achieved. Two quantitative measures for tumor segmentation quality estimation, namely, correspondence ratio (CR) and percent matching (PM), were performed. For the segmentation of brain tumor, the volume total PM varies from 79.12 to 93.25% with the mean of 85.67+/-4.38% while the volume total CR varies from 0.74 to 0.91 with the mean of 0.84+/-0.07. For the segmentation of edema, the volume total PM varies from 72.86 to 87.29% with the mean of 79.54+/-4.18% while the volume total CR varies from 0.69 to 0.85 with the mean of 0.79+/-0.08. The HLS segmentation method perform better than the classical level sets (LS) segmentation method in PM and CR. The results of this research may have potential applications, both as a staging procedure and a method of evaluating tumor response during treatment, this method can be used as a clinical image analysis tool for doctors or radiologists.

FDTD analysis of a noninvasive hyperthermia system for brain tumors

PubMed Central

2012-01-01

Background Hyperthermia is considered one of the new therapeutic modalities for cancer treatment and is based on the difference in thermal sensitivity between healthy tissues and tumors. During hyperthermia treatment, the temperature of the tumor is raised to 40–45°C for a definite period resulting in the destruction of cancer cells. This paper investigates design, modeling and simulation of a new non-invasive hyperthermia applicator system capable of effectively heating deep seated as well as superficial brain tumors using inexpensive, simple, and easy to fabricate components without harming surrounding healthy brain tissues. Methods The proposed hyperthermia applicator system is composed of an air filled partial half ellipsoidal chamber, a patch antenna, and a head model with an embedded tumor at an arbitrary location. The irradiating antenna is placed at one of the foci of the hyperthermia chamber while the center of the brain tumor is placed at the other focus. The finite difference time domain (FDTD) method is used to compute both the SAR patterns and the temperature distribution in three different head models due to two different patch antennas at a frequency of 915 MHz. Results The obtained results suggest that by using the proposed noninvasive hyperthermia system it is feasible to achieve sufficient and focused energy deposition and temperature rise to therapeutic values in deep seated as well as superficial brain tumors without harming surrounding healthy tissue. Conclusions The proposed noninvasive hyperthermia system proved suitable for raising the temperature in tumors embedded in the brain to therapeutic values by carefully selecting the systems components. The operator of the system only needs to place the center of the brain tumor at a pre-specified location and excite the antenna at a single frequency of 915 MHz. Our study may provide a basis for a clinical applicator prototype capable of heating brain tumors. PMID:22891953

Brain Diseases

MedlinePlus

The brain is the control center of the body. It controls thoughts, memory, speech, and movement. It regulates the function of many organs. When the brain is healthy, it works quickly and automatically. However, ...

TuMore: generation of synthetic brain tumor MRI data for deep learning based segmentation approaches

NASA Astrophysics Data System (ADS)

Lindner, Lydia; Pfarrkirchner, Birgit; Gsaxner, Christina; Schmalstieg, Dieter; Egger, Jan

2018-03-01

Accurate segmentation and measurement of brain tumors plays an important role in clinical practice and research, as it is critical for treatment planning and monitoring of tumor growth. However, brain tumor segmentation is one of the most challenging tasks in medical image analysis. Since manual segmentations are subjective, time consuming and neither accurate nor reliable, there exists a need for objective, robust and fast automated segmentation methods that provide competitive performance. Therefore, deep learning based approaches are gaining interest in the field of medical image segmentation. When the training data set is large enough, deep learning approaches can be extremely effective, but in domains like medicine, only limited data is available in the majority of cases. Due to this reason, we propose a method that allows to create a large dataset of brain MRI (Magnetic Resonance Imaging) images containing synthetic brain tumors - glioblastomas more specifically - and the corresponding ground truth, that can be subsequently used to train deep neural networks.

Ex vivo micro-CT imaging of murine brain models using non-ionic iodinated contrast

NASA Astrophysics Data System (ADS)

Salas Bautista, N.; Martínez-Dávalos, A.; Rodríguez-Villafuerte, M.; Murrieta-Rodríguez, T.; Manjarrez-Marmolejo, J.; Franco-Pérez, J.; Calvillo-Velasco, M. E.

2014-11-01

Preclinical investigation of brain tumors is frequently carried out by means of intracranial implantation of brain tumor xenografts or allografts, with subsequent analysis of tumor growth using conventional histopathology. However, very little has been reported on the use contrast-enhanced techniques in micro-CT imaging for the study of malignant brain tumors in small animal models. The aim of this study has been to test a protocol for ex vivo imaging of murine brain models of glioblastoma multiforme (GBM) after treatment with non-ionic iodinated solution, using an in-house developed laboratory micro-CT. We have found that the best compromise between acquisition time and image quality is obtained using a 50 kVp, 0.5 mAs, 1° angular step on a 360 degree orbit acquisition protocol, with 70 μm reconstructed voxel size using the Feldkamp algorithm. With this parameters up to 4 murine brains can be scanned in tandem in less than 15 minutes. Image segmentation and analysis of three sample brains allowed identifying tumor volumes as small as 0.4 mm3.

A correlative optical microscopy and scanning electron microscopy approach to locating nanoparticles in brain tumors.

PubMed

Kempen, Paul J; Kircher, Moritz F; de la Zerda, Adam; Zavaleta, Cristina L; Jokerst, Jesse V; Mellinghoff, Ingo K; Gambhir, Sanjiv S; Sinclair, Robert

2015-01-01

The growing use of nanoparticles in biomedical applications, including cancer diagnosis and treatment, demands the capability to exactly locate them within complex biological systems. In this work a correlative optical and scanning electron microscopy technique was developed to locate and observe multi-modal gold core nanoparticle accumulation in brain tumor models. Entire brain sections from mice containing orthotopic brain tumors injected intravenously with nanoparticles were imaged using both optical microscopy to identify the brain tumor, and scanning electron microscopy to identify the individual nanoparticles. Gold-based nanoparticles were readily identified in the scanning electron microscope using backscattered electron imaging as bright spots against a darker background. This information was then correlated to determine the exact location of the nanoparticles within the brain tissue. The nanoparticles were located only in areas that contained tumor cells, and not in the surrounding healthy brain tissue. This correlative technique provides a powerful method to relate the macro- and micro-scale features visible in light microscopy with the nanoscale features resolvable in scanning electron microscopy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Improving labeling efficiency in automatic quality control of MRSI data.

PubMed

Pedrosa de Barros, Nuno; McKinley, Richard; Wiest, Roland; Slotboom, Johannes

2017-12-01

To improve the efficiency of the labeling task in automatic quality control of MR spectroscopy imaging data. 28'432 short and long echo time (TE) spectra (1.5 tesla; point resolved spectroscopy (PRESS); repetition time (TR)= 1,500 ms) from 18 different brain tumor patients were labeled by two experts as either accept or reject, depending on their quality. For each spectrum, 47 signal features were extracted. The data was then used to run several simulations and test an active learning approach using uncertainty sampling. The performance of the classifiers was evaluated as a function of the number of patients in the training set, number of spectra in the training set, and a parameter α used to control the level of classification uncertainty required for a new spectrum to be selected for labeling. The results showed that the proposed strategy allows reductions of up to 72.97% for short TE and 62.09% for long TE in the amount of data that needs to be labeled, without significant impact in classification accuracy. Further reductions are possible with significant but minimal impact in performance. Active learning using uncertainty sampling is an effective way to increase the labeling efficiency for training automatic quality control classifiers. Magn Reson Med 78:2399-2405, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Non-invasive monitoring of hemodynamic changes in orthotropic brain tumor

NASA Astrophysics Data System (ADS)

Kashyap, Dheerendra; Sharma, Vikrant; Liu, Hanli

2007-02-01

Radio surgical interventions such as Gamma Knife and Cyberknife have become attractive as therapeutic interventions. However, one of the drawbacks of cyberknife is radionecrosis, which is caused by excessive radiation to surrounding normal tissues. Radionecrosis occurs in about 10-15% of cases and could have adverse effects leading to death. Currently available imaging techniques have failed to reliably distinguish radionecrosis from tumor growth. Development of imaging techniques that could provide distinction between tumor growth and radionecrosis would give us ability to monitor effects of radiation therapy non-invasively. This paper investigates the use of near infrared spectroscopy (NIRS) as a new technique to monitor the growth of brain tumors. Brain tumors (9L glioma cell line) were implanted in right caudate nucleus of rats (250-300 gms, Male Fisher C) through a guide screw. A new algorithm was developed, which used broadband steady-state reflectance measurements made using a single source-detector pair, to quantify absolute concentrations of hemoglobin derivatives and reduced scattering coefficients. Preliminary results from the brain tumors indicated decreases in oxygen saturation, oxygenated hemoglobin concentrations and increases in deoxygenated hemoglobin concentrations with tumor growth. The study demonstrates that NIRS technology could provide an efficient, noninvasive means of monitoring vascular oxygenation dynamics of brain tumors and further facilitate investigations of efficacy of tumor treatments.

Current status of gene therapy for brain tumors

PubMed Central

MURPHY, ANDREA M.; RABKIN, SAMUEL D.

2013-01-01

Glioblastoma (GBM) is the most common and deadliest primary brain tumor in adults, with current treatments having limited impact on disease progression. Therefore the development of alternative treatment options is greatly needed. Gene therapy is a treatment strategy that relies on the delivery of genetic material, usually transgenes or viruses, into cells for therapeutic purposes, and has been applied to GBM with increasing promise. We have included selectively replication-competent oncolytic viruses within this strategy, although the virus acts directly as a complex biologic anti-tumor agent rather than as a classic gene delivery vehicle. GBM is a good candidate for gene therapy because tumors remain locally within the brain and only rarely metastasize to other tissues; the majority of cells in the brain are post-mitotic, which allows for specific targeting of dividing tumor cells; and tumors can often be accessed neurosurgically for administration of therapy. Delivery vehicles used for brain tumors include nonreplicating viral vectors, normal adult stem/progenitor cells, and oncolytic viruses. The therapeutic transgenes or viruses are typically cytotoxic or express prodrug activating suicide genes to kill glioma cells, immunostimulatory to induce or amplify anti-tumor immune responses, and/or modify the tumor microenvironment such as blocking angiogenesis. This review describes current preclinical and clinical gene therapy strategies for the treatment of glioma. PMID:23246627

Growth hormone treatment and risk of recurrence or progression of brain tumors in children: a review.

PubMed

Bogarin, Roberto; Steinbok, Paul

2009-03-01

Brain tumors are one of the most common types of solid neoplasm in children. As life expectancy of these patients has increased with new and improved therapies, the morbidities associated with the treatments and the tumor itself have become more important. One of the most common morbidities is growth hormone deficiency, and since recombinant growth hormone (GH) became available, its use has increased exponentially. There is concern that in the population of children with brain tumors, GH treatment might increase the risk of tumor recurrence or progression or the appearance of a second neoplasm. In the light of this ongoing concern, the current literature has been reviewed to provide an update on the risk of tumor recurrence, tumor progression, or new intracranial tumor formation when GH is used to treat GH deficiency in children, who have had or have intracranial tumors. On the basis of this review, the authors conclude that the use of GH in patients with brain tumor is safe. GH therapy is not associated with an increased risk of central nervous system tumor progression or recurrence, leukemia (de novo or relapse), or extracranial non-leukemic neoplasms.

Confocal laser endomicroscopy for brain tumor surgery: a milestone journey from microscopy to cellular surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Charalampaki, Cleopatra

2017-02-01

The aim in brain tumor surgery is maximal tumor resection with minimal damage of normal neuronal tissue. Today diagnosis of tumor and definition of tumor borders intraoperatively is based on various visualization methods as well as on the histopathologic examination of a limited number of biopsy specimens via frozen sections. Unfortunately, intraoperative histopathology bears several shortcomings, and many biopsies are inconclusive. Therefore, the desirable treatment could be to have the ability to identify intraoperative cellular structures, and differentiate tumor from normal functional brain tissue on a cellular level. To achieve this goal new technological equipment integrated with new surgical concepts is needed.Confocal Laser Endomicroscopy (CLE) is an imaging technique which provides microscopic information of tissue in real-time. We are able to use these technique to perform intraoperative "optical biopsies" in bringing the microscope inside to the patients brain through miniaturized fiber-optic probes, and allow real-time histopathology. In our knowledge we are worldwide the only one neurosurgical group using CLE intraoperative for brain tumor surgery. We can detect and characterize intraoperative tumor cells, providing immediate online diagnosis without the need for frozen sections. It also provides delineation of borders between tumor and normal tissue on a cellular level, making surgical margins more accurate than ever before. The applications of CLE-assisted neurosurgery help to accurate the therapy by extending the resection borders and protecting the functionality of normal brain tissue in critical eloquent areas.

Brain Cancer Stem Cells Display Preferential Sensitivity to Akt Inhibition

PubMed Central

Eyler, Christine E.; Foo, Wen-Chi; LaFiura, Katherine M.; McLendon, Roger E.; Hjelmeland, Anita B.; Rich, Jeremy N.

2009-01-01

Malignant brain tumors are among the most lethal cancers, and conventional therapies are largely limited to palliation. Novel therapies targeted against specific molecular pathways may offer improved efficacy and reduced toxicity compared to conventional therapies, but initial clinical trials of molecular targeted agents in brain cancer therapy have been frequently disappointing. In brain tumors and other cancers, subpopulations of tumor cells have recently been characterized by their ability to self-renew and initiate tumors. Although these cancer stem cells, or tumor initiating cells, are often only present in small numbers in human tumors, mounting evidence suggests that cancer stem cells contribute to tumor maintenance and therapeutic resistance. Thus, the development of therapies that target cancer stem cell signal transduction and biologies may improve brain tumor patient survival. We now demonstrate that populations enriched for cancer stem cells are preferentially sensitive to an inhibitor of Akt, a prominent cell survival and invasion signaling node. Treatment with an Akt inhibitor more potently reduced the numbers of viable brain cancer stem cells relative to matched non-stem cancer cells associated with a preferential induction of apoptosis and a suppression of neurosphere formation. Akt inhibition also reduced the motility and invasiveness of all tumor cells but had a greater impact on cancer stem cell behaviors. Furthermore, inhibition of Akt activity in cancer stem cells increased survival of immunocompromised mice bearing human glioma xenografts in vivo. Together, these results suggest that Akt inhibitors may function as effective anti-cancer stem cell therapies. PMID:18802038

Issues of diagnostic review in brain tumor studies: from the Brain Tumor Epidemiology Consortium.

PubMed

Davis, Faith G; Malmer, Beatrice S; Aldape, Ken; Barnholtz-Sloan, Jill S; Bondy, Melissa L; Brännström, Thomas; Bruner, Janet M; Burger, Peter C; Collins, V Peter; Inskip, Peter D; Kruchko, Carol; McCarthy, Bridget J; McLendon, Roger E; Sadetzki, Siegal; Tihan, Tarik; Wrensch, Margaret R; Buffler, Patricia A

2008-03-01

Epidemiologists routinely conduct centralized single pathology reviews to minimize interobserver diagnostic variability, but this practice does not facilitate the combination of studies across geographic regions and institutions where diagnostic practices differ. A meeting of neuropathologists and epidemiologists focused on brain tumor classification issues in the context of protocol needs for consortial studies (http://epi.grants.cancer.gov/btec/). It resulted in recommendations relevant to brain tumors and possibly other rare disease studies. Two categories of brain tumors have enough general agreement over time, across regions, and between individual pathologists that one can consider using existing diagnostic data without further review: glioblastomas and meningiomas (as long as uniform guidelines such as those provided by the WHO are used). Prospective studies of these tumors benefit from collection of pathology reports, at a minimum recording the pathology department and classification system used in the diagnosis. Other brain tumors, such as oligodendroglioma, are less distinct and require careful histopathologic review for consistent classification across study centers. Epidemiologic study protocols must consider the study specific aims, diagnostic changes that have taken place over time, and other issues unique to the type(s) of tumor being studied. As diagnostic changes are being made rapidly, there are no readily available answers on disease classification issues. It is essential that epidemiologists and neuropathologists collaborate to develop appropriate study designs and protocols for specific hypothesis and populations.

The diagnostic accuracy of multiparametric MRI to determine pediatric brain tumor grades and types.

PubMed

Koob, Mériam; Girard, Nadine; Ghattas, Badih; Fellah, Slim; Confort-Gouny, Sylviane; Figarella-Branger, Dominique; Scavarda, Didier

2016-04-01

Childhood brain tumors show great histological variability. The goal of this retrospective study was to assess the diagnostic accuracy of multimodal MR imaging (diffusion, perfusion, MR spectroscopy) in the distinction of pediatric brain tumor grades and types. Seventy-six patients (range 1 month to 18 years) with brain tumors underwent multimodal MR imaging. Tumors were categorized by grade (I-IV) and by histological type (A-H). Multivariate statistical analysis was performed to evaluate the diagnostic accuracy of single and combined MR modalities, and of single imaging parameters to distinguish the different groups. The highest diagnostic accuracy for tumor grading was obtained with diffusion-perfusion (73.24%) and for tumor typing with diffusion-perfusion-MR spectroscopy (55.76%). The best diagnostic accuracy was obtained for tumor grading in I and IV and for tumor typing in embryonal tumor and pilocytic astrocytoma. Poor accuracy was seen in other grades and types. ADC and rADC were the best parameters for tumor grading and typing followed by choline level with an intermediate echo time, CBV for grading and Tmax for typing. Multiparametric MR imaging can be accurate in determining tumor grades (primarily grades I and IV) and types (mainly pilocytic astrocytomas and embryonal tumors) in children.

[Tumor segmentation of brain MRI with adaptive bandwidth mean shift].

PubMed

Hou, Xiaowen; Liu, Qi

2014-10-01

In order to get the adaptive bandwidth of mean shift to make the tumor segmentation of brain magnetic resonance imaging (MRI) to be more accurate, we in this paper present an advanced mean shift method. Firstly, we made use of the space characteristics of brain image to eliminate the impact on segmentation of skull; and then, based on the characteristics of spatial agglomeration of different tissues of brain (includes tumor), we applied edge points to get the optimal initial mean value and the respectively adaptive bandwidth, in order to improve the accuracy of tumor segmentation. The results of experiment showed that, contrast to the fixed bandwidth mean shift method, the method in this paper could segment the tumor more accurately.

In vivo imaging and characterization of hypoxia-induced neovascularization and tumor invasion.

PubMed

Lungu, Gina F; Li, Meng-Lin; Xie, Xueyi; Wang, Lihong V; Stoica, George

2007-01-01

Hypoxia is a critical event in tumor progression and angiogenesis. Hypoxia can be detected noninvasively by a novel spectroscopic photoacoustic tomography technology (SPAT) and this finding is supported by our molecular biology investigation aimed to elucidate the etiopathogenesis of SPAT detected hypoxia and angiogenesis. The present study provides an integrated approach to define oxygen status (hypoxia) of intracranial tumor xenografts using spectroscopic photoacoustic tomography. Brain tumors can be identified based on their distorted vascular architecture and oxygen saturation (SO2) images. Noninvasive in vivo tumor oxygenation imaging using SPAT is based on the spectroscopic absorption differences between oxyhemoglobin (O2Hb) and deoxyhemoblobin (HHb). Sprague-Dawley rats inoculated intracranially with ENU1564, a carcinogen-induced rat mammary adenocarcinoma cell line, were imaged with SPAT three weeks post inoculation. Proteins important for tumor angiogenesis and invasion were detected in hypoxic brain foci identified by SPAT and were elevated compared with control brain. Immunohistochemistry, Western blotting, and semi-quantitative RT-PCR showed that HIF-1 alpha, VEGF-A, and VEGFR2 (Flk-1) protein and mRNA expression levels were significantly higher (P < 0.05) in brain tumor tissues compared to normal brain. Gelatin zymography and RT-PCR demonstrated the upregulation of MMP-9 in tumor foci compared with brain control. Together these results suggest the critical role of hypoxia in driving tumor angiogenesis and invasion through upregulation of target genes important for these functions. Moreover this report validates our hypothesis that a novel noninvasive technology (SPAT) developed in our laboratory is suitable for detection of tumors, hypoxia, and angiogenesis.

The brain-penetrant clinical ATM inhibitor AZD1390 radiosensitizes and improves survival of preclinical brain tumor models.

PubMed

Durant, Stephen T; Zheng, Li; Wang, Yingchun; Chen, Kan; Zhang, Lingli; Zhang, Tianwei; Yang, Zhenfan; Riches, Lucy; Trinidad, Antonio G; Fok, Jacqueline H L; Hunt, Tom; Pike, Kurt G; Wilson, Joanne; Smith, Aaron; Colclough, Nicola; Reddy, Venkatesh Pilla; Sykes, Andrew; Janefeldt, Annika; Johnström, Peter; Varnäs, Katarina; Takano, Akihiro; Ling, Stephanie; Orme, Jonathan; Stott, Jonathan; Roberts, Caroline; Barrett, Ian; Jones, Gemma; Roudier, Martine; Pierce, Andrew; Allen, Jasmine; Kahn, Jenna; Sule, Amrita; Karlin, Jeremy; Cronin, Anna; Chapman, Melissa; Valerie, Kristoffer; Illingworth, Ruth; Pass, Martin

2018-06-01

Poor survival rates of patients with tumors arising from or disseminating into the brain are attributed to an inability to excise all tumor tissue (if operable), a lack of blood-brain barrier (BBB) penetration of chemotherapies/targeted agents, and an intrinsic tumor radio-/chemo-resistance. Ataxia-telangiectasia mutated (ATM) protein orchestrates the cellular DNA damage response (DDR) to cytotoxic DNA double-strand breaks induced by ionizing radiation (IR). ATM genetic ablation or pharmacological inhibition results in tumor cell hypersensitivity to IR. We report the primary pharmacology of the clinical-grade, exquisitely potent (cell IC 50 , 0.78 nM), highly selective [>10,000-fold over kinases within the same phosphatidylinositol 3-kinase-related kinase (PIKK) family], orally bioavailable ATM inhibitor AZD1390 specifically optimized for BBB penetration confirmed in cynomolgus monkey brain positron emission tomography (PET) imaging of microdosed 11 C-labeled AZD1390 ( K p,uu , 0.33). AZD1390 blocks ATM-dependent DDR pathway activity and combines with radiation to induce G 2 cell cycle phase accumulation, micronuclei, and apoptosis. AZD1390 radiosensitizes glioma and lung cancer cell lines, with p53 mutant glioma cells generally being more radiosensitized than wild type. In in vivo syngeneic and patient-derived glioma as well as orthotopic lung-brain metastatic models, AZD1390 dosed in combination with daily fractions of IR (whole-brain or stereotactic radiotherapy) significantly induced tumor regressions and increased animal survival compared to IR treatment alone. We established a pharmacokinetic-pharmacodynamic-efficacy relationship by correlating free brain concentrations, tumor phospho-ATM/phospho-Rad50 inhibition, apoptotic biomarker (cleaved caspase-3) induction, tumor regression, and survival. On the basis of the data presented here, AZD1390 is now in early clinical development for use as a radiosensitizer in central nervous system malignancies.

The brain-penetrant clinical ATM inhibitor AZD1390 radiosensitizes and improves survival of preclinical brain tumor models

PubMed Central

Wang, Yingchun; Chen, Kan; Zhang, Lingli; Zhang, Tianwei; Yang, Zhenfan; Riches, Lucy; Trinidad, Antonio G.; Pike, Kurt G.; Wilson, Joanne; Smith, Aaron; Colclough, Nicola; Johnström, Peter; Varnäs, Katarina; Takano, Akihiro; Ling, Stephanie; Orme, Jonathan; Stott, Jonathan; Barrett, Ian; Jones, Gemma; Allen, Jasmine; Kahn, Jenna; Sule, Amrita; Cronin, Anna; Chapman, Melissa; Illingworth, Ruth; Pass, Martin

2018-01-01

Poor survival rates of patients with tumors arising from or disseminating into the brain are attributed to an inability to excise all tumor tissue (if operable), a lack of blood-brain barrier (BBB) penetration of chemotherapies/targeted agents, and an intrinsic tumor radio-/chemo-resistance. Ataxia-telangiectasia mutated (ATM) protein orchestrates the cellular DNA damage response (DDR) to cytotoxic DNA double-strand breaks induced by ionizing radiation (IR). ATM genetic ablation or pharmacological inhibition results in tumor cell hypersensitivity to IR. We report the primary pharmacology of the clinical-grade, exquisitely potent (cell IC50, 0.78 nM), highly selective [>10,000-fold over kinases within the same phosphatidylinositol 3-kinase–related kinase (PIKK) family], orally bioavailable ATM inhibitor AZD1390 specifically optimized for BBB penetration confirmed in cynomolgus monkey brain positron emission tomography (PET) imaging of microdosed 11C-labeled AZD1390 (Kp,uu, 0.33). AZD1390 blocks ATM-dependent DDR pathway activity and combines with radiation to induce G2 cell cycle phase accumulation, micronuclei, and apoptosis. AZD1390 radiosensitizes glioma and lung cancer cell lines, with p53 mutant glioma cells generally being more radiosensitized than wild type. In in vivo syngeneic and patient-derived glioma as well as orthotopic lung-brain metastatic models, AZD1390 dosed in combination with daily fractions of IR (whole-brain or stereotactic radiotherapy) significantly induced tumor regressions and increased animal survival compared to IR treatment alone. We established a pharmacokinetic-pharmacodynamic-efficacy relationship by correlating free brain concentrations, tumor phospho-ATM/phospho-Rad50 inhibition, apoptotic biomarker (cleaved caspase-3) induction, tumor regression, and survival. On the basis of the data presented here, AZD1390 is now in early clinical development for use as a radiosensitizer in central nervous system malignancies. PMID:29938225

Trends and Outcomes in the Treatment of Gliomas Based on Data during 2001–2004 from the Brain Tumor Registry of Japan

PubMed Central

NARITA, Yoshitaka; SHIBUI, Soichiro

2015-01-01

The committee of Brain Tumor Registry of Japan (BTRJ) was founded in 1973 and conducts surveys and analyses of incidence, therapeutic methods, and treatment outcomes of primary and metastatic brain tumors with the cooperation of the Japan Neurosurgical Society members. Newly diagnosed 3,000–4,000 primary brain tumors and 600–1,000 brain metastases patients were enrolled in each year. This report describes the trends and treatment outcomes of gliomas from BTRJ volume 13, including 13,431 patients with primary brain tumors who newly started treatment from 2001 to 2004. Data from 382 diffuse astrocytomas (DAs), 121 oligodendrogliomas (OLs), 90 oligoastrocytomas (OAs), 513 anaplastic astrocytomas (AAs), 126 anaplastic oligodendrogliomas (AOs), 106 anaplastic oligoastrocytomas (AOAs), and 1,489 glioblastomas (GBMs) were analyzed for overall survival (OS) and progression free survival (PFS) depending on age, symptoms, Karnofsky performance status, location of the tumor, extent of resection (EOR), initial radiotherapy and chemotherapy. The 5-year PFS rates of the patients with DA, OL + OA, AA, AO + AOA, and GBM were 57.0%, 74.6%, 28.7%, 54.0%, and 9.2%, and the 5-year OS rates were 75.0%, 90.0%, 41.1%, 68.2%, and 10.1%, respectively. Higher EOR ≥ 75% in DA and OL + OA and that ≥ 50% in AA, AO + AOA, and GBM significantly prolonged OS. Complications and cause of death were also reported. BTRJ had been edited for all the patients, researchers, and especially for clinicians at bedside to give useful information about brain tumors and to contribute to the advances in brain tumor treatment. This report revealed various clinical problematic issues pertaining to the diagnosis and treatment of gliomas. PMID:25797780

Increased brain edema following 5-aminolevulinic acid mediated photodynamic in normal and tumor bearing rats

NASA Astrophysics Data System (ADS)

Hirschberg, Henry; Angell-Petersen, Even; Spetalen, Signe; Mathews, Marlon; Madsen, Steen J.

2007-02-01

Introduction: Failure of treatment for high grade gliomas is usually due to local recurrence at the site of surgical resection indicating that a more aggressive form of local therapy, such as PDT, could be of benefit. PDT causes damage to both tumor cells as well as cerebral blood vessels leading to degradation of the blood brain barrier with subsequent increase of brain edema. The increase in brain edema following ALA-PDT was evaluated in terms of animal survival, histopatological changes in normal brain and tumor tissue and MRI scanning. The effect of steroid treatment, to reduce post-treatment PDT induced edema, was also examined. Methods:Tumors were established in the brains of inbred BD-IX and Fisher rats. At various times following tumor induction the animals were injected with ALA ip. and four hours later light treatment at escalating fluences and fluence rates were given. Nontumor bearing control animals were also exposed to ALA-PDT in a similar manner to evaluate damage to normal brain and degree of blood brain barrier (BBB) disruption. Results: Despite a very low level of PpIX production in normal brain, with a 200:1 tumor to normal tissue selectivity ratio measured at a distance of 2 mm from the tumor border, many animals succumbed shortly after treatment. A total radiant energy of 54 J to non-tumor bearing animals resulted in 50% mortality within 5 days of treatment. Treatment of tumor bearing animals with moderate fluence levels produced similar brain edema compared to higher fluence levels. ALA PDT in nontumor bearing animals produced edema that was light dose dependent. PDT appeared to open the BBB for a period of 24-48 hrs after which it was restored. The addition of post operative steroid treatment reduced the incident of post treatment morbidity and mortality. Conclusions: T2 and contrast enhanced T1 MRI scanning proved to be a highly effective and non-evasive modality in following the development of the edema reaction and the degree and time course of BBB dysfunction thus allowing the use of fewer animals.

The Implications of the Cancer Stem Cell Hypothesis for Neuro-Oncology and Neurology.

PubMed

Rich, Jeremy N

2008-05-01

The cancer stem cell hypothesis posits that cancers contain a subset of neoplastic cells that propagate and maintain tumors through sustained self-renewal and potent tumorigenecity. Recent excitement has been generated by a number of reports that have demonstrated the existence of cancer stem cells in several types of brain tumors. Brain cancer stem cells - also called tumor initiating cells or tumor propagating cells - share features with normal neural stem cells but do not necessarily originate from stem cells. Although most cancers have only a small fraction of cancer stem cells, these tumor cells have been shown in laboratory studies to contribute to therapeutic resistance, formation of new blood vessels to supply the tumor, and tumor spread. As malignant brain tumors rank among the deadliest of all neurologic diseases, the identification of new cellular targets may have profound implications in neuro-oncology. Novel drugs that target stem cell pathways active in brain tumors have been efficacious against cancer stem cells suggesting that anti-cancer stem cell therapies may advance brain tumor therapy. The cancer stem cell hypothesis may have several implications for other neurologic diseases as caution must be exercised in activating stem cell maintenance pathways in cellular therapies for neurodegenerative diseases. The ability for a small fraction of cells to determine the overall course of a disease may also inform new paradigms of disease that may translate into improved patient outcomes.

[Brain tumor immunotherapy: Illusion or hope?

PubMed

Migliorini, Denis; Dutoit, Valérie; Walker, Paul R; Dietrich, Pierre-Yves

2017-05-01

Immunotherapy has proven efficient for many tumors and is now part of standard of care in many indications. What is the picture for brain tumors? The recent development of anti-CTLA-4 and PD1 immune checkpoint inhibitors, which have the ability to restore T lymphocytes activity, has gathered enthusiasm and is now paving the way towards more complex models of immune system manipulation. These models include, among others, vaccination and adoptive T cell transfer technologies. Complementary to those strategies, molecules capable of reshaping the immune tumor microenvironment are currently being investigated in early phase trials. Indeed, the tumor bed is hostile to anti-tumor immune responses due to many escape mechanisms, and this is particularly true in the context of brain tumors, a master in eliciting immunosuppressive cells and molecules. The goal of this review is to describe the hopes and challenges of brain tumors immunotherapy and to propose an inventory of the current clinical research with specific focus on the therapies targeting the tumor microenvironment. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Intra-operative visualization of brain tumors with 5-aminolevulinic acid-induced fluorescence.

PubMed

Widhalm, Georg

2014-01-01

Precise histopathological diagnosis of brain tumors is essential for the correct patient management. Furthermore, complete resection of brain tumors is associated with an improved patient prognosis. However, histopathological undergrading and incomplete tumor removal are not uncommon, especially due to insufficient intra-operative visualization of brain tumor tissue. The fluorescent dye 5-aminolevulinic acid (5-ALA) is currently applied for fluorescence-guided resections of high-grade gliomas. The value of 5-ALA-induced protoporphyrin (PpIX) fluorescence for intra-operative visualization of other tumors than high-grade gliomas remains unclear. Within the frame of this thesis, we found a significantly higher rate of complete resections of our high-grade gliomas as compared to control cases by using the newly established 5-ALA fluorescence technology at our department. Additionally, we showed that MRI spectroscopy-based chemical shift imaging (CSI) is capable to identify intratumoral high-grade glioma areas (= anaplastic foci) during navigation guided resections to avoid histopathological undergrading. However, the accuracy of navigation systems with integrated pre-operative imaging data such as CSI declines during resections due to intra-operative brainshift. In two further studies, we found that 5-ALA induced PpIX fluorescence is capable as a novel intra-operative marker to detect anaplastic foci within initially suspected low-grade gliomas independent of brainshift. Finally, we showed that the application of 5-ALA is also of relevance in needle biopsies for intra-operative identification of representative brain tumor tissue. These data indicate that 5-ALA is not only of major importance for resection of high-grade gliomas, but also for intra-operative visualization of anaplastic foci as well as representative brain tumor tissue in needle biopsies unaffected by brainshift. Consequently, this new technique might become a novel standard in brain tumor surgery that optimizes the patient management and improves the patient prognosis by maximizing the extent of tumor resection and enabling a precise histopathological tumor diagnosis.

EGFR-directed Affibody for fluorescence-guided glioma surgery: time-dose analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ribeiro de Souza, Ana Luiza; Marra, Kayla; Gunn, Jason R.; Elliott, Jonathan T.; Samkoe, Kimberley S.; Paulsen, Keith D.; Draney, Daniel R.; Feldwisch, Joachim

2016-03-01

The key to fluorescence guided surgical oncology is the ability to create specific contrast between normal and glioma tissue. The blood brain barrier that limits the delivery of substances to the normal brain is broken in tumors, allowing accumulation of agents in the tumor interior. However, for a clinical success, imaging agents should be in the infiltrative edges to minimize the resection of normal brain while enable the removal of tumor. The aberrant overexpression and/or activation of EGFR is associated with many types of cancers, including glioblastoma and the injection of a fluorescent molecule targeted to these receptors would improve tumor contrast during fluorescence guided surgery. Affibody molecules have intentional medium affinity and high potential specificity, which are the desirable features of a good surgical imaging agent. The aim of this study was evaluate the brain/glioma uptake of ABY029 labeled with near-infrared dye IRDye800CW after intravenous injection. Rats were either inoculated with orthotopic implantations of U251 human glioma cell line or PBS (shams control) in the brain. The tumors were allowed to grow for 2-3 weeks before carrying out fluorescent tracer experiments. Fluorescent imaging of ex vivo brain slices from rats was acquired at different time points after infection of fluorescently labeled EGFR-specific affibody to verify which time provided maximal contrast tumor to normal brain. Although the tumor was most clearly visualized after 1h of IRDye800CW-labeled ABY029 injection, the tumor location could be identified from the background after 48h. These results suggest that the NIR-labeled affibody examined shows excellent potential to increase surgical visualization for confirmed EGFR positive tumors.

Prevalence estimates for primary brain tumors in the United States by age, gender, behavior, and histology.

PubMed

Porter, Kimberly R; McCarthy, Bridget J; Freels, Sally; Kim, Yoonsang; Davis, Faith G

2010-06-01

Prevalence is the best indicator of cancer survivorship in the population, but few studies have focused on brain tumor prevalence because of previous data limitations. Hence, the full impact of primary brain tumors on the healthcare system in the United States is not completely described. The present study provides an estimate of the prevalence of disease in the United States, updating an earlier prevalence study. Incidence data for 2004 and survival data for 1985-2005 were obtained by the Central Brain Tumor Registry of the United States from selected regions, modeled under 2 different survival assumptions, to estimate prevalence rates for the year 2004 and projected estimates for 2010. The overall incidence rate for primary brain tumors was 18.1 per 100 000 person-years with 2-, 5-, 10-, and 20-year observed survival rates of 62%, 54%, 45%, and 30%, respectively. On the basis of the sum of nonmalignant and averaged malignant estimates, the overall prevalence rate of individuals with a brain tumor was estimated to be 209.0 per 100 000 in 2004 and 221.8 per 100 000 in 2010. The female prevalence rate (264.8 per 100 000) was higher than that in males (158.7 per 100 000). The averaged prevalence rate for malignant tumors (42.5 per 100 000) was lower than the prevalence for nonmalignant tumors (166.5 per 100 000). This study provides estimates of the 2004 (n = 612 770) and 2010 (n = 688 096) expected number of individuals living with primary brain tumor diagnoses in the United States, providing more current and robust estimates for aiding healthcare planning and patient advocacy for an aging US population.

Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study

PubMed Central

Deeley, M A; Chen, A; Datteri, R; Noble, J; Cmelak, A; Donnelly, E; Malcolm, A; Moretti, L; Jaboin, J; Niermann, K; Yang, Eddy S; Yu, David S; Yei, F; Koyama, T; Ding, G X; Dawant, B M

2011-01-01

The purpose of this work was to characterize expert variation in segmentation of intracranial structures pertinent to radiation therapy, and to assess a registration-driven atlas-based segmentation algorithm in that context. Eight experts were recruited to segment the brainstem, optic chiasm, optic nerves, and eyes, of 20 patients who underwent therapy for large space-occupying tumors. Performance variability was assessed through three geometric measures: volume, Dice similarity coefficient, and Euclidean distance. In addition, two simulated ground truth segmentations were calculated via the simultaneous truth and performance level estimation (STAPLE) algorithm and a novel application of probability maps. The experts and automatic system were found to generate structures of similar volume, though the experts exhibited higher variation with respect to tubular structures. No difference was found between the mean Dice coefficient (DSC) of the automatic and expert delineations as a group at a 5% significance level over all cases and organs. The larger structures of the brainstem and eyes exhibited mean DSC of approximately 0.8–0.9, whereas the tubular chiasm and nerves were lower, approximately 0.4–0.5. Similarly low DSC have been reported previously without the context of several experts and patient volumes. This study, however, provides evidence that experts are similarly challenged. The average maximum distances (maximum inside, maximum outside) from a simulated ground truth ranged from (−4.3, +5.4) mm for the automatic system to (−3.9, +7.5) mm for the experts considered as a group. Over all the structures in a rank of true positive rates at a 2 mm threshold from the simulated ground truth, the automatic system ranked second of the nine raters. This work underscores the need for large scale studies utilizing statistically robust numbers of patients and experts in evaluating quality of automatic algorithms. PMID:21725140

Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study

NASA Astrophysics Data System (ADS)

Deeley, M. A.; Chen, A.; Datteri, R.; Noble, J. H.; Cmelak, A. J.; Donnelly, E. F.; Malcolm, A. W.; Moretti, L.; Jaboin, J.; Niermann, K.; Yang, Eddy S.; Yu, David S.; Yei, F.; Koyama, T.; Ding, G. X.; Dawant, B. M.

2011-07-01

The purpose of this work was to characterize expert variation in segmentation of intracranial structures pertinent to radiation therapy, and to assess a registration-driven atlas-based segmentation algorithm in that context. Eight experts were recruited to segment the brainstem, optic chiasm, optic nerves, and eyes, of 20 patients who underwent therapy for large space-occupying tumors. Performance variability was assessed through three geometric measures: volume, Dice similarity coefficient, and Euclidean distance. In addition, two simulated ground truth segmentations were calculated via the simultaneous truth and performance level estimation algorithm and a novel application of probability maps. The experts and automatic system were found to generate structures of similar volume, though the experts exhibited higher variation with respect to tubular structures. No difference was found between the mean Dice similarity coefficient (DSC) of the automatic and expert delineations as a group at a 5% significance level over all cases and organs. The larger structures of the brainstem and eyes exhibited mean DSC of approximately 0.8-0.9, whereas the tubular chiasm and nerves were lower, approximately 0.4-0.5. Similarly low DSCs have been reported previously without the context of several experts and patient volumes. This study, however, provides evidence that experts are similarly challenged. The average maximum distances (maximum inside, maximum outside) from a simulated ground truth ranged from (-4.3, +5.4) mm for the automatic system to (-3.9, +7.5) mm for the experts considered as a group. Over all the structures in a rank of true positive rates at a 2 mm threshold from the simulated ground truth, the automatic system ranked second of the nine raters. This work underscores the need for large scale studies utilizing statistically robust numbers of patients and experts in evaluating quality of automatic algorithms.

Ultrastructural findings in transplanted experimental brain tumors and their significance for the cytogenesis of such tumors.

PubMed

Mennel, H D

1988-01-01

Tumors induced by transplacental action in the spinal cord of rats were transplanted into the brains of the same rat strain. They were followed up by electron microscopy during the first ten passages. Three architectural features were detected: First pure tumor parts, second myelin breakdown and phagocytosis, and third the resulting accumulation of resting macrophages. Architecture two and three were interpreted as result of considerable phagocytotic activity of tumor cells localized within the white substance of the brain and spinal cord. Only architecture one was considered to represent proper tumor. Since this was low differentiated and partial astrocytic differentiation only occurred around vessels to remarkable extent, the thesis is put forward that these transplacentally induced tumors correspond to human primitive neuroectodermal tumors.

Dimethyl sulfoxide (DMSO) as a potential contrast agent for brain tumors.

PubMed

Delgado-Goñi, T; Martín-Sitjar, J; Simões, R V; Acosta, M; Lope-Piedrafita, S; Arús, C

2013-02-01

Dimethyl sulfoxide (DMSO) is commonly used in preclinical studies of animal models of high-grade glioma as a solvent for chemotherapeutic agents. A strong DMSO signal was detected by single-voxel MRS in the brain of three C57BL/6 control mice during a pilot study of DMSO tolerance after intragastric administration. This led us to investigate the accumulation and wash-out kinetics of DMSO in both normal brain parenchyma (n=3 control mice) by single-voxel MRS, and in 12 GL261 glioblastomas (GBMs) by single-voxel MRS (n=3) and MRSI (n=9). DMSO accumulated differently in each tissue type, reaching its highest concentration in tumors: 6.18 ± 0.85 µmol/g water, 1.5-fold higher than in control mouse brain (p<0.05). A faster wash-out was detected in normal brain parenchyma with respect to GBM tissue: half-lives of 2.06 ± 0.58 and 4.57 ± 1.15 h, respectively. MRSI maps of time-course DMSO changes revealed clear hotspots of differential spatial accumulation in GL261 tumors. Additional MRSI studies with four mice bearing oligodendrogliomas (ODs) revealed similar results as in GBM tumors. The lack of T(1) contrast enhancement post-gadolinium (gadopentetate dimeglumine, Gd-DTPA) in control mouse brain and mice with ODs suggested that DMSO was fully able to cross the intact blood-brain barrier in both normal brain parenchyma and in low-grade tumors. Our results indicate a potential role for DMSO as a contrast agent for brain tumor detection, even in those tumors 'invisible' to standard gadolinium-enhanced MRI, and possibly for monitoring heterogeneities associated with progression or with therapeutic response. Copyright © 2012 John Wiley & Sons, Ltd.

Automatic, accurate, and reproducible segmentation of the brain and cerebro-spinal fluid in T1-weighted volume MRI scans and its application to serial cerebral and intracranial volumetry

NASA Astrophysics Data System (ADS)

Lemieux, Louis

2001-07-01

A new fully automatic algorithm for the segmentation of the brain and cerebro-spinal fluid (CSF) from T1-weighted volume MRI scans of the head was specifically developed in the context of serial intra-cranial volumetry. The method is an extension of a previously published brain extraction algorithm. The brain mask is used as a basis for CSF segmentation based on morphological operations, automatic histogram analysis and thresholding. Brain segmentation is then obtained by iterative tracking of the brain-CSF interface. Grey matter (GM), white matter (WM) and CSF volumes are calculated based on a model of intensity probability distribution that includes partial volume effects. Accuracy was assessed using a digital phantom scan. Reproducibility was assessed by segmenting pairs of scans from 20 normal subjects scanned 8 months apart and 11 patients with epilepsy scanned 3.5 years apart. Segmentation accuracy as measured by overlap was 98% for the brain and 96% for the intra-cranial tissues. The volume errors were: total brain (TBV): -1.0%, intra-cranial (ICV):0.1%, CSF: +4.8%. For repeated scans, matching resulted in improved reproducibility. In the controls, the coefficient of reliability (CR) was 1.5% for the TVB and 1.0% for the ICV. In the patients, the Cr for the ICV was 1.2%.

Epidemiology of primary brain tumors: current concepts and review of the literature.

PubMed Central

Wrensch, Margaret; Minn, Yuriko; Chew, Terri; Bondy, Melissa; Berger, Mitchel S.

2002-01-01

The purpose of this review is to provide a sufficiently detailed perspective on epidemiologic studies of primary brain tumors to encourage multidisciplinary etiologic and prognostic studies among surgeons, neuro-oncologists, epidemiologists, and molecular scientists. Molecular tumor markers that predict survival and treatment response are being identified with hope of even greater gains in this area from emerging array technologies. Regarding risk factors, studies of inherited susceptibility and constitutive polymorphisms in genes pertinent to carcinogenesis (for example, DNA repair and detoxification genes and mutagen sensitivity) have revealed provocative findings. Inverse associations of the history of allergies with glioma risk observed in 3 large studies and reports of inverse associations of glioma with common infections suggest a possible role of immune factors in glioma genesis or progression. Studies continue to suggest that brain tumors might result from workplace, dietary, and other personal and residential exposures, but studies of cell phone use and power frequency electromagnetic fields have found little to support a causal connection with brain tumors; caveats remain. The only proven causes of brain tumors (that is, rare hereditary syndromes, therapeutic radiation, and immune suppression giving rise to brain lymphomas) account for a small proportion of cases. Progress in understanding primary brain tumors might result from studies of well-defined histologic and molecular tumor types incorporating assessment of potentially relevant information on subject susceptibility and environmental and noninherited endogenous factors (viruses, radiation, and carcinogenic or protective chemical exposures through diet, workplace, oxidative metabolism, or other sources). Such studies will require the cooperation of researchers from many disciplines. PMID:12356358

Microglia function in brain tumors.

PubMed

Watters, Jyoti J; Schartner, Jill M; Badie, Behnam

2005-08-01

Microglia play an important role in inflammatory diseases of the central nervous system (CNS). These cells have also been identified in brain neoplasms; however, as of yet their function largely remains unclear. More recent studies designed to characterize further tumor-associated microglia suggest that the immune effector function of these cells may be suppressed in CNS tumors. Furthermore, microglia and macrophages can secrete various cytokines and growth factors that may contribute to the successful immune evasion, growth, and invasion of brain neoplasms. A better understanding of microglia and macrophage function is essential for the development of immune-based treatment strategies against malignant brain tumors. (c) 2005 Wiley-Liss, Inc.

Development of an in-home standardized end-of-life treatment program for pediatric patients dying of brain tumors.

PubMed

Arland, Lesley C; Hendricks-Ferguson, Verna L; Pearson, Joanne; Foreman, Nicholas K; Madden, Jennifer R

2013-04-01

To evaluate an end-of-life (EOL) program related to specific outcomes (i.e., number of hospitalizations and place of death) for children with brain tumors. From 1990 to 2005, a retrospective chart review was performed related to specified outcomes for 166 children with admission for pediatric brain tumors. Patients who received the EOL program were hospitalized less often (n = 114; chi-square = 5.001 with df = 1, p <.05) than patients who did not receive the program. An EOL program may improve symptom management and decrease required hospital admissions for children with brain tumors. © 2013, Wiley Periodicals, Inc.

Glioblastoma and chemoresistance to alkylating agents: Involvement of apoptosis, autophagy, and unfolded protein response.

PubMed

Hombach-Klonisch, Sabine; Mehrpour, Maryam; Shojaei, Shahla; Harlos, Craig; Pitz, Marshall; Hamai, Ahmed; Siemianowicz, Krzysztof; Likus, Wirginia; Wiechec, Emilia; Toyota, Brian D; Hoshyar, Reyhane; Seyfoori, Amir; Sepehri, Zahra; Ande, Sudharsana R; Khadem, Forough; Akbari, Mohsen; Gorman, Adrienne M; Samali, Afshin; Klonisch, Thomas; Ghavami, Saeid

2018-04-01

Despite advances in neurosurgical techniques and radio-/chemotherapy, the treatment of brain tumors remains a challenge. This is particularly true for the most frequent and fatal adult brain tumor, glioblastoma (GB). Upon diagnosis, the average survival time of GB patients remains only approximately 15months. The alkylating drug temozolomide (TMZ) is routinely used in brain tumor patients and induces apoptosis, autophagy and unfolded protein response (UPR). Here, we review these cellular mechanisms and their contributions to TMZ chemoresistance in brain tumors, with a particular emphasis on TMZ chemoresistance in glioma stem cells and GB. Copyright © 2017 Elsevier Inc. All rights reserved.

Effect of intravenous gadolinium-DTPA on diffusion-weighted imaging of brain tumors: a short temporal interval assessment.

PubMed

Li, Xiang; Qu, Jin-Rong; Luo, Jun-Peng; Li, Jing; Zhang, Hong-Kai; Shao, Nan-Nan; Kwok, Keith; Zhang, Shou-Ning; Li, Yan-le; Liu, Cui-Cui; Zee, Chi-Shing; Li, Hai-Liang

2014-09-01

To determine the effect of intravenous administration of gadolinium (Gd) contrast medium (Gd-DTPA) on diffusion-weighted imaging (DWI) for the evaluation of normal brain parenchyma vs. brain tumor following a short temporal interval. Forty-four DWI studies using b values of 0 and 1000 s/mm(2) were performed before, immediately after, 1 min after, 3 min after, and 5 min after the administration of Gd-DTPA on 62 separate lesions including 15 meningioma, 17 glioma and 30 metastatic lesions. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and apparent diffusion coefficient (ADC) values of the brain tumor lesions and normal brain tissues were measured on pre- and postcontrast images. Statistical analysis using paired t-test between precontrast and postcontrast data were obtained on three brain tumors and normal brain tissue. The SNR and CNR of brain tumors and the SNR of normal brain tissue showed no statistical differences between pre- and postcontrast (P > 0.05). The ADC values on the three cases of brain tumors demonstrated significant initial increase on the immediate time point (P < 0.01) and decrease on following the 1 min time point (P < 0.01) after contrast. Significant decrease of ADC value was still found at 3min and 5min time point in the meningioma group (P < 0.01) with gradual normalization over time. The ADC values of normal brain tissues demonstrated significant initial elevation on the immediately postcontrast DWI sequence (P < 0.01). Contrast medium can cause a slight but statistically significant change on the ADC value within a short temporal interval after the contrast administration. The effect is both time and lesion-type dependent. © 2013 Wiley Periodicals, Inc.

Convection-enhanced delivery for the treatment of brain tumors

PubMed Central

Debinski, Waldemar; Tatter, Stephen B

2013-01-01

The brain is highly accessible for nutrients and oxygen, however delivery of drugs to malignant brain tumors is a very challenging task. Convection-enhanced delivery (CED) has been designed to overcome some of the difficulties so that pharmacological agents that would not normally cross the BBB can be used for treatment. Drugs are delivered through one to several catheters placed stereotactically directly within the tumor mass or around the tumor or the resection cavity. Several classes of drugs are amenable to this technology including standard chemotherapeutics or novel experimental targeted drugs. The first Phase III trial for CED-delivered, molecularly targeted cytotoxin in the treatment of recurrent glioblastoma multiforme has been accomplished and demonstrated objective clinical efficacy. The lessons learned from more than a decade of attempts at exploiting CED for brain cancer treatment weigh critically for its future clinical applications. The main issues center around the type of catheters used, number of catheters and their exact placement; pharmacological formulation of drugs, prescreening patients undergoing treatment and monitoring the distribution of drugs in tumors and the tumor-infiltrated brain. It is expected that optimizing CED will make this technology a permanent addition to clinical management of brain malignancies. PMID:19831841

Bafetinib in Treating Patients With Recurrent High-Grade Glioma or Brain Metastases

ClinicalTrials.gov

2018-04-12

Adult Anaplastic Astrocytoma; Adult Anaplastic Ependymoma; Adult Anaplastic Oligodendroglioma; Adult Giant Cell Glioblastoma; Adult Glioblastoma; Adult Gliosarcoma; Adult Mixed Glioma; Recurrent Adult Brain Tumor; Tumors Metastatic to Brain; Adult Anaplastic Oligoastrocytoma

Tomographic brain imaging with nucleolar detail and automatic cell counting

NASA Astrophysics Data System (ADS)

Hieber, Simone E.; Bikis, Christos; Khimchenko, Anna; Schweighauser, Gabriel; Hench, Jürgen; Chicherova, Natalia; Schulz, Georg; Müller, Bert

2016-09-01

Brain tissue evaluation is essential for gaining in-depth insight into its diseases and disorders. Imaging the human brain in three dimensions has always been a challenge on the cell level. In vivo methods lack spatial resolution, and optical microscopy has a limited penetration depth. Herein, we show that hard X-ray phase tomography can visualise a volume of up to 43 mm3 of human post mortem or biopsy brain samples, by demonstrating the method on the cerebellum. We automatically identified 5,000 Purkinje cells with an error of less than 5% at their layer and determined the local surface density to 165 cells per mm2 on average. Moreover, we highlight that three-dimensional data allows for the segmentation of sub-cellular structures, including dendritic tree and Purkinje cell nucleoli, without dedicated staining. The method suggests that automatic cell feature quantification of human tissues is feasible in phase tomograms obtained with isotropic resolution in a label-free manner.

White matter lesion extension to automatic brain tissue segmentation on MRI.

PubMed

de Boer, Renske; Vrooman, Henri A; van der Lijn, Fedde; Vernooij, Meike W; Ikram, M Arfan; van der Lugt, Aad; Breteler, Monique M B; Niessen, Wiro J

2009-05-01

A fully automated brain tissue segmentation method is optimized and extended with white matter lesion segmentation. Cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM) are segmented by an atlas-based k-nearest neighbor classifier on multi-modal magnetic resonance imaging data. This classifier is trained by registering brain atlases to the subject. The resulting GM segmentation is used to automatically find a white matter lesion (WML) threshold in a fluid-attenuated inversion recovery scan. False positive lesions are removed by ensuring that the lesions are within the white matter. The method was visually validated on a set of 209 subjects. No segmentation errors were found in 98% of the brain tissue segmentations and 97% of the WML segmentations. A quantitative evaluation using manual segmentations was performed on a subset of 6 subjects for CSF, GM and WM segmentation and an additional 14 for the WML segmentations. The results indicated that the automatic segmentation accuracy is close to the interobserver variability of manual segmentations.

Semiquantitative Analysis Using Thallium-201 SPECT for Differential Diagnosis Between Tumor Recurrence and Radiation Necrosis After Gamma Knife Surgery for Malignant Brain Tumors

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

Matsunaga, Shigeo, E-mail: shigeo-m@mui.biglobe.ne.jp; Shuto, Takashi; Takase, Hajime

Purpose: Semiquantitative analysis of thallium-201 chloride single photon emission computed tomography ({sup 201}Tl SPECT) was evaluated for the discrimination between recurrent brain tumor and delayed radiation necrosis after gamma knife surgery (GKS) for metastatic brain tumors and high-grade gliomas. Methods and Materials: The medical records were reviewed of 75 patients, including 48 patients with metastatic brain tumor and 27 patients with high-grade glioma who underwent GKS in our institution, and had suspected tumor recurrence or radiation necrosis on follow-up neuroimaging and deteriorating clinical status after GKS. Analysis of {sup 201}Tl SPECT data used the early ratio (ER) and the delayedmore » ratio (DR) calculated as tumor/normal average counts on the early and delayed images, and the retention index (RI) as the ratio of DR to ER. Results: A total of 107 tumors were analyzed with {sup 201}Tl SPECT. Nineteen lesions were removed surgically and histological diagnoses established, and the other lesions were evaluated with follow-up clinical and neuroimaging examinations after GKS. The final diagnosis was considered to be recurrent tumor in 65 lesions and radiation necrosis in 42 lesions. Semiquantitative analysis demonstrated significant differences in DR (P=.002) and RI (P<.0001), but not in ER (P=.372), between the tumor recurrence and radiation necrosis groups, and no significant differences between metastatic brain tumors and high-grade gliomas in all indices (P=.926 for ER, P=.263 for DR, and P=.826 for RI). Receiver operating characteristics analysis indicated that RI was the most informative index with the optimum threshold of 0.775, which provided 82.8% sensitivity, 83.7% specificity, and 82.8% accuracy. Conclusions: Semiquantitative analysis of {sup 201}Tl SPECT provides useful information for the differentiation between tumor recurrence and radiation necrosis in metastatic brain tumors and high-grade gliomas after GKS, and the RI may be the most valuable index for this purpose.« less

Distinct Neural Stem Cell Populations Give Rise to Disparate Brain Tumors in Response to N-MYC

PubMed Central

Swartling, Fredrik J.; Savov, Vasil; Persson, Anders I.; Chen, Justin; Hackett, Christopher S.; Northcott, Paul A.; Grimmer, Matthew R.; Lau, Jasmine; Chesler, Louis; Perry, Arie; Phillips, Joanna J.; Taylor, Michael D.; Weiss, William A.

2012-01-01

SUMMARY The proto-oncogene MYCN is mis-expressed in various types of human brain tumors. To clarify how developmental and regional differences influence transformation, we transduced wild-type or mutationally-stabilized murine N-mycT58A into neural stem cells (NSCs) from perinatal murine cerebellum, brain stem and forebrain. Transplantation of N-mycWT NSCs was insufficient for tumor formation. N-mycT58A cerebellar and brain stem NSCs generated medulloblastoma/primitive neuroectodermal tumors, whereas forebrain NSCs developed diffuse glioma. Expression analyses distinguished tumors generated from these different regions, with tumors from embryonic versus postnatal cerebellar NSCs demonstrating SHH-dependence and SHH-independence, respectively. These differences were regulated in-part by the transcription factor SOX9, activated in the SHH subclass of human medulloblastoma. Our results demonstrate context-dependent transformation of NSCs in response to a common oncogenic signal. PMID:22624711

"She Was a Little Social Butterfly": A Qualitative Analysis of Parent Perception of Social Functioning in Adolescent and Young Adult Brain Tumor Survivors.

PubMed

Wilford, Justin; Buchbinder, David; Fortier, Michelle A; Osann, Kathryn; Shen, Violet; Torno, Lilibeth; Sender, Leonard S; Parsons, Susan K; Wenzel, Lari

Psychosocial sequelae of diagnosis and treatment for childhood brain tumor survivors are significant, yet little is known about their impact on adolescent and young adult (AYA) brain tumor survivors. Interviews were conducted with parents of AYA brain tumor survivors with a focus on social functioning. Semistructured interviews were conducted with English- and Spanish-speaking parents of AYA brain tumor survivors ≥10 years of age who were >2 years postdiagnosis, and analyzed using emergent themes theoretically integrated with a social neuroscience model of social competence. Twenty parents representing 19 survivors with a survivor mean age 15.7 ± 3.3 years and 10.1 ± 4.8 years postdiagnosis were interviewed. Several themes relevant to the social neuroscience social competence model emerged. First, parents' perceptions of their children's impaired social functioning corroborated the model, particularly with regard to poor social adjustment, social withdrawal, impaired social information processing, and developmentally inappropriate peer communication. Second, ongoing physical and emotional sequelae of central nervous system insults were seen by parents as adversely affecting social functioning among survivors. Third, a disrupted family environment and ongoing parent psychosocial distress were experienced as salient features of daily life. We document that the aforementioned framework is useful for understanding the social impact of diagnosis and treatment on AYA brain tumor survivorship. Moreover, the framework highlights areas of intervention that may enhance social functioning for AYA brain tumor survivors.

Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.

PubMed

Somasundaram, Karuppanagounder; Ezhilarasan, Kamalanathan

2015-01-01

To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. The proposed method is based on gray scale transformation and morphological operations. The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.

The Influence of Frontal Lobe Tumors and Surgical Treatment on Advanced Cognitive Functions.

PubMed

Fang, Shengyu; Wang, Yinyan; Jiang, Tao

2016-07-01

Brain cognitive functions affect patient quality of life. The frontal lobe plays a crucial role in advanced cognitive functions, including executive function, meta-cognition, decision-making, memory, emotion, and language. Therefore, frontal tumors can lead to serious cognitive impairments. Currently, neurosurgical treatment is the primary method to treat brain tumors; however, the effects of the surgical treatments are difficult to predict or control. The treatment may both resolve the effects of the tumor to improve cognitive function or cause permanent disabilities resulting from damage to healthy functional brain tissue. Previous studies have focused on the influence of frontal lesions and surgical treatments on patient cognitive function. Here, we review cognitive impairment caused by frontal lobe brain tumors. Copyright © 2016 Elsevier Inc. All rights reserved.

Medulloblastoma Genotype Dictates Blood Brain Barrier Phenotype.

PubMed

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

2016-04-11

The childhood brain tumor, medulloblastoma, includes four subtypes with very different prognoses. Here, we show that paracrine signals driven by mutant β-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-tumoral chemotherapy and a robust therapeutic response. In contrast, SHH-medulloblastoma, a less curable disease subtype, contains an intact blood brain barrier, rendering this tumor 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 tumor vessel phenotype, explaining in part the disparate prognoses among medulloblastoma subtypes and suggesting an approach to enhance the chemoresponsiveness of other brain tumors. Copyright © 2016 Elsevier Inc. All rights reserved.

Stem cell-based therapies for tumors in the brain: are we there yet?

PubMed Central

Shah, Khalid

2016-01-01

Advances in understanding adult stem cell biology have facilitated the development of novel cell-based therapies for cancer. Recent developments in conventional therapies (eg, tumor resection techniques, chemotherapy strategies, and radiation therapy) for treating both metastatic and primary tumors in the brain, particularly glioblastoma have not resulted in a marked increase in patient survival. Preclinical studies have shown that multiple stem cell types exhibit inherent tropism and migrate to the sites of malignancy. Recent studies have validated the feasibility potential of using engineered stem cells as therapeutic agents to target and eliminate malignant tumor cells in the brain. This review will discuss the recent progress in the therapeutic potential of stem cells for tumors in the brain and also provide perspectives for future preclinical studies and clinical translation. PMID:27282399

Brain invasion and the risk of seizures in patients with meningioma.

PubMed

Hess, Katharina; Spille, Dorothee Cäcilia; Adeli, Alborz; Sporns, Peter B; Brokinkel, Caroline; Grauer, Oliver; Mawrin, Christian; Stummer, Walter; Paulus, Werner; Brokinkel, Benjamin

2018-04-27

OBJECTIVE Identification of risk factors for perioperative epilepsy remains crucial in the care of patients with meningioma. Moreover, associations of brain invasion with clinical and radiological variables have been largely unexplored. The authors hypothesized that invasion of the cortex and subsequent increased edema facilitate seizures, and they compared radiological data and perioperative seizures in patients with brain-invasive or noninvasive meningioma. METHODS Correlations of brain invasion with tumor and edema volumes and preoperative and postoperative seizures were analyzed in univariate and multivariate analyses. RESULTS Totals of 108 (61%) females and 68 (39%) males with a median age of 60 years and harboring totals of 92 (52%) grade I, 79 (45%) grade II, and 5 (3%) grade III tumors were included. Brain invasion was found in 38 (22%) patients and was absent in 138 (78%) patients. The tumors were located at the convexity in 72 (41%) patients, at the falx cerebri in 26 (15%), at the skull base in 69 (39%), in the posterior fossa in 7 (4%), and in the ventricle in 2 (1%); the median tumor and edema volumes were 13.73 cm 3 (range 0.81-162.22 cm 3 ) and 1.38 cm 3 (range 0.00-355.80 cm 3 ), respectively. As expected, edema volume increased with rising tumor volume (p < 0.001). Brain invasion was independent of tumor volume (p = 0.176) but strongly correlated with edema volume (p < 0.001). The mean edema volume in noninvasive tumors was 33.0 cm 3 , but in invasive tumors, it was 130.7 cm 3 (p = 0.008). The frequency of preoperative seizures was independent of the patients' age, sex, and tumor location; however, the frequency was 32% (n = 12) in patients with invasive meningioma and 15% (n = 21) in those with noninvasive meningioma (p = 0.033). In contrast, the probability of detecting brain invasion microscopically was increased more than 2-fold in patients with a history of preoperative seizures (OR 2.57, 95% CI 1.13-5.88; p = 0.025). In univariate analyses, the rate of preoperative seizures correlated slightly with tumor volume (p = 0.049) but strongly with edema volume (p = 0.014), whereas seizure semiology was found to be independent of brain invasion (p = 0.211). In multivariate analyses adjusted for age, sex, tumor location, tumor and edema volumes, and WHO grade, rising tumor volume (OR 1.02, 95% CI 1.00-1.03; p = 0.042) and especially brain invasion (OR 5.26, 95% CI 1.52-18.15; p = 0.009) were identified as independent predictors of preoperative seizures. Nine (5%) patients developed new seizures within a median follow-up time of 15 months after surgery. Development of postoperative epilepsy was independent of all clinical variables, including Simpson grade (p = 0.133), tumor location (p = 0.936), brain invasion (p = 0.408), and preoperative edema volume (p = 0.081), but was correlated with increasing preoperative tumor volume (p = 0.004). Postoperative seizure-free rates were similar among patients with invasive and those with noninvasive meningioma (p = 0.372). CONCLUSIONS Brain invasion was identified as a new and strong predictor for preoperative, but not postoperative, seizures. Although also associated with increased peritumoral edema, seizures in patients with invasive meningioma might be facilitated substantially by cortical invasion itself. Consideration of seizures in consultations between the neurosurgeon and neuropathologist can improve the microscopic detection of brain invasion.

A novel pre-clinical in vivo mouse model for malignant brain tumor growth and invasion.

PubMed

Shelton, Laura M; Mukherjee, Purna; Huysentruyt, Leanne C; Urits, Ivan; Rosenberg, Joshua A; Seyfried, Thomas N

2010-09-01

Glioblastoma multiforme (GBM) is a rapidly progressive disease of morbidity and mortality and is the most common form of primary brain cancer in adults. Lack of appropriate in vivo models has been a major roadblock to developing effective therapies for GBM. A new highly invasive in vivo GBM model is described that was derived from a spontaneous brain tumor (VM-M3) in the VM mouse strain. Highly invasive tumor cells could be identified histologically on the hemisphere contralateral to the hemisphere implanted with tumor cells or tissue. Tumor cells were highly expressive for the chemokine receptor CXCR4 and the proliferation marker Ki-67 and could be identified invading through the pia mater, the vascular system, the ventricular system, around neurons, and over white matter tracts including the corpus callosum. In addition, the brain tumor cells were labeled with the firefly luciferase gene, allowing for non-invasive detection and quantitation through bioluminescent imaging. The VM-M3 tumor has a short incubation time with mortality occurring in 100% of the animals within approximately 15 days. The VM-M3 brain tumor model therefore can be used in a pre-clinical setting for the rapid evaluation of novel anti-invasive therapies.

Donepezil in Treating Young Patients With Primary Brain Tumors Previously Treated With Radiation Therapy to the Brain

ClinicalTrials.gov

2017-07-31

Brain and Central Nervous System Tumors; Cognitive/Functional Effects; Long-term Effects Secondary to Cancer Therapy in Children; Neurotoxicity; Psychosocial Effects of Cancer and Its Treatment; Radiation Toxicity

Near infrared Raman spectra of human brain lipids

NASA Astrophysics Data System (ADS)

Krafft, Christoph; Neudert, Lars; Simat, Thomas; Salzer, Reiner

2005-05-01

Human brain tissue, in particular white matter, contains high lipid content. These brain lipids can be divided into three principal classes: neutral lipids including the steroid cholesterol, phospholipids and sphingolipids. Major lipids in normal human brain tissue are phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, phosphatidic acid, sphingomyelin, galactocerebrosides, gangliosides, sulfatides and cholesterol. Minor lipids are cholesterolester and triacylglycerides. During transformation from normal brain tissue to tumors, composition and concentration of lipids change in a specific way. Therefore, analysis of lipids might be used as a diagnostic parameter to distinguish normal tissue from tumors and to determine the tumor type and tumor grade. Raman spectroscopy has been suggested as an analytical tool to detect these changes even under intra-operative conditions. We recorded Raman spectra of the 12 major and minor brain lipids with 785 nm excitation in order to identify their spectral fingerprints for qualitative and quantitative analyses.

Precision about the automatic emotional brain.

PubMed

Vuilleumier, Patrik

2015-01-01

The question of automaticity in emotion processing has been debated under different perspectives in recent years. Satisfying answers to this issue will require a better definition of automaticity in terms of relevant behavioral phenomena, ecological conditions of occurrence, and a more precise mechanistic account of the underlying neural circuits.

Salmonella as a biological "Trojan horse" for neoplasia: future possibilities including brain cancer.

PubMed

Mlynarczyk, Gregory S A; Berg, Carrie A; Withrock, Isabelle C; Fick, Meghan E; Anderson, Stephen J; Laboissonniere, Lauren A; Jefferson, Matthew A; Brewer, Matthew T; Stock, Matthew L; Lange, Jennifer K; Luna, K C; Acharya, Sreemoyee; Kanuri, Sriharsha; Sharma, Shaunik; Kondru, Naveen C; McCormack, Garrett R; Carlson, Steve A

2014-09-01

This manuscript considers available evidence that a specific Salmonella strain could be used as an effective orally-administered option for cancer therapy involving the brain. It has been established that Salmonella preferentially colonizes neoplastic tissue and thrives as a facultative anaerobe in the intra-tumor environment. Although Salmonella accumulates in tumors by passive processes, it is still possible for lipopolysaccharide to cause sepsis and endotoxic shock during the migration of bacteria to the tumor site. An LPS-free version of a recently identified Salmonella isolate may have the capability to circumvent the blood brain barrier and provide a safer method of reaching brain tumors. This isolate merits further research as a "Trojan horse" for future oral biotherapy of brain cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Immunohistochemical hormonal mismatch and human epidermal growth factor type 2 [HER2] phenotype of brain metastases in breast cancer carcinoma compared to primary tumors].

PubMed

Joubert, C; Boissonneau, S; Fina, F; Figarella-Branger, D; Ouafik, L; Fuentes, S; Dufour, H; Gonçalves, A; Charaffe-Jauffret, E; Metellus, P

2016-06-01

Phenotype changes between primary tumor and the corresponding brain metastases are recent reported data. Breast cancer, with biological markers predicting prognosis and guiding therapeutic strategy remains an interesting model to observe and evaluate theses changes. The objective of our study was to compare molecular features (estrogen receptor [ER], progesterone receptor [PR], and human epidermal growth factor receptor type 2, [HER2]) between brain metastases and its primary tumor in patients presenting with pathologically confirmed breast cancer. This retrospective study was based on the immunohistochemical analysis of the brain metastases paraffin embedded samples stored in our institutional tumor bank, after surgical resection. The level of expression of hormonal receptors and HER2 on brain metastases were centrally reviewed and compared to the expression status in primary breast cancer from medical records. Forty-four samples of brain metastases were available for analysis. Hormonal receptor modification status was observed in 11/44 brain metastases (25%) for ER and 6/44 (13.6%) for PR. A modification of HER2 overexpression was observed in brain metastases in 6/44 (13.6%). Molecular subtype modification was shown in 17 cases (38.6%). A significant difference was demonstrated between time to develop brain metastases in cases without status modification (HER2, ER and PR) (med=49.5months [7.8-236.4]) and in cases in which brain metastases status differs from primary tumor (med=27.5months [0-197.3]), (P=0.0244, IC95=3.09-51.62, Mann and Whitney test). the main interest of this study was to focus on the molecular feature changes between primary tumor and their brain metastases. Time to develop brain metastases was correlated to phenotypic changes in brain metastases. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

IDH1 Mutation in Brain Stem Glioma: Case Report and Review of Literature.

PubMed

Javadi, Seyed Amirhossein; Hartmann, Christian; Walter, Gerhard Franz; Banan, Roozbeh; Samii, Amir

2018-01-01

The role of isocitrate dehydrogenase 1 (IDH1) mutation in brain stem glioma is not clear. To the best of our knowledge, six cases of brain stem gliomas carrying IDH1/2 mutations are currently reported in the literature. One case of diffuse brain stem glioma with IDH1 mutation, which was followed for 2 years, is presented and compared with IDH1 negative tumors. A 22-year-old lady was referred with diplopia and left arm palsy. Neuroimaging detected a nonenhancing, nonhomogeneous diffuse infiltrating brain stem tumor extending from pons to medulla. Microsurgical debulking was performed. Microscopic evaluation of the tissue specimen and immunohistochemistry revealed an astrocytoma WHO Grade II with proliferation rate of 3% and glial fibrillary acidic protein (GFAP)-positive tumor cells. Interestingly, the tumor cells expressed mutated IDH1 R132H protein. The patient underwent adjuvant radiation and chemotherapy. The primary and 2 years' clinical/radiological characteristics did not indicate any significant difference from other cases without IDH1 mutation. the prognostic value of IDH1/2 mutation in brain stem glioma is unclear. Brain stem biopsies may allow determination of a tissue-based tumor diagnosis for further investigations.

Training stem cells for treatment of malignant brain tumors

PubMed Central

Li, Shengwen Calvin; Kabeer, Mustafa H; Vu, Long T; Keschrumrus, Vic; Yin, Hong Zhen; Dethlefs, Brent A; Zhong, Jiang F; Weiss, John H; Loudon, William G

2014-01-01

The treatment of malignant brain tumors remains a challenge. Stem cell technology has been applied in the treatment of brain tumors largely because of the ability of some stem cells to infiltrate into regions within the brain where tumor cells migrate as shown in preclinical studies. However, not all of these efforts can translate in the effective treatment that improves the quality of life for patients. Here, we perform a literature review to identify the problems in the field. Given the lack of efficacy of most stem cell-based agents used in the treatment of malignant brain tumors, we found that stem cell distribution (i.e., only a fraction of stem cells applied capable of targeting tumors) are among the limiting factors. We provide guidelines for potential improvements in stem cell distribution. Specifically, we use an engineered tissue graft platform that replicates the in vivo microenvironment, and provide our data to validate that this culture platform is viable for producing stem cells that have better stem cell distribution than with the Petri dish culture system. PMID:25258664

3D brain tumor localization and parameter estimation using thermographic approach on GPU.

PubMed

Bousselham, Abdelmajid; Bouattane, Omar; Youssfi, Mohamed; Raihani, Abdelhadi

2018-01-01

The aim of this paper is to present a GPU parallel algorithm for brain tumor detection to estimate its size and location from surface temperature distribution obtained by thermography. The normal brain tissue is modeled as a rectangular cube including spherical tumor. The temperature distribution is calculated using forward three dimensional Pennes bioheat transfer equation, it's solved using massively parallel Finite Difference Method (FDM) and implemented on Graphics Processing Unit (GPU). Genetic Algorithm (GA) was used to solve the inverse problem and estimate the tumor size and location by minimizing an objective function involving measured temperature on the surface to those obtained by numerical simulation. The parallel implementation of Finite Difference Method reduces significantly the time of bioheat transfer and greatly accelerates the inverse identification of brain tumor thermophysical and geometrical properties. Experimental results show significant gains in the computational speed on GPU and achieve a speedup of around 41 compared to the CPU. The analysis performance of the estimation based on tumor size inside brain tissue also presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of tumor- and stroma-supplied proteolytic networks reveals a brain metastasis-promoting role for cathepsin S

PubMed Central

Sevenich, Lisa; Bowman, Robert L.; Mason, Steven D.; Quail, Daniela F.; Rapaport, Franck; Elie, Benelita T.; Brogi, Edi; Brastianos, Priscilla K.; Hahn, William C.; Holsinger, Leslie J.; Massagué, Joan; Leslie, Christina S.; Joyce, Johanna A.

2014-01-01

Metastasis remains the most common cause of death in most cancers, with limited therapies for combating disseminated disease. While the primary tumor microenvironment is an important regulator of cancer progression, it is less well understood how different tissue environments influence metastasis. We analyzed tumor-stroma interactions that modulate organ tropism of brain, bone and lung metastasis in xenograft models. We identified a number of potential modulators of site-specific metastasis, including cathepsin S as a regulator of breast-to-brain metastasis. High cathepsin S expression at the primary site correlated with decreased brain metastasis-free survival in breast cancer patients. Both macrophages and tumor cells produce cathepsin S, and only the combined depletion significantly reduced brain metastasis in vivo. Cathepsin S specifically mediates blood-brain barrier transmigration via proteolytic processing of the junctional adhesion molecule (JAM)-B. Pharmacological inhibition of cathepsin S significantly reduced experimental brain metastasis, supporting its consideration as a therapeutic target for this disease. PMID:25086747

Nanoparticle Formulation Derived from Carboxymethyl Cellulose, Polyethylene Glycol, and Cabazitaxel for Chemotherapy Delivery to the Brain.

PubMed

Bteich, Joseph; Ernsting, Mark J; Mohammed, Mohammed; Kiyota, Taira; McKee, Trevor D; Trikha, Mohit; Lowman, Henry B; Sokoll, Kenneth K

2018-05-23

Nanoparticles provide a unique opportunity to explore the benefits of selective distribution and release of cancer therapeutics at sites of disease through varying particle sizes and compositions that exploit the enhanced permeability of tumor-associated blood vessels. Though delivery of larger as opposed to smaller and/or actively transported molecules to the brain is prima facie a challenging endeavor, we wondered whether nanoparticles could improve the therapeutic index of existing drugs for use in treating brain tumors via these vascular effects. We therefore selected a family of nanoparticles composed of cabazitaxel-carboxymethyl cellulose amphiphilic polymers to investigate the potential for delivering a brain-penetrant taxane to intracranial brain tumors in mice. Among a small set of nanoparticle formulations, we found evidence for nanoparticle accumulation in the brain, and one such formulation demonstrated activity in an orthotopic model of glioma, suggesting that such nanoparticles could be useful for the treatment of glioma and brain metastases of other tumor types.

Surgical benefits of combined awake craniotomy and intraoperative magnetic resonance imaging for gliomas associated with eloquent areas.

PubMed

Motomura, Kazuya; Natsume, Atsushi; Iijima, Kentaro; Kuramitsu, Shunichiro; Fujii, Masazumi; Yamamoto, Takashi; Maesawa, Satoshi; Sugiura, Junko; Wakabayashi, Toshihiko

2017-10-01

OBJECTIVE Maximum extent of resection (EOR) for lower-grade and high-grade gliomas can increase survival rates of patients. However, these infiltrative gliomas are often observed near or within eloquent regions of the brain. Awake surgery is of known benefit for the treatment of gliomas associated with eloquent regions in that brain function can be preserved. On the other hand, intraoperative MRI (iMRI) has been successfully used to maximize the resection of tumors, which can detect small amounts of residual tumors. Therefore, the authors assessed the value of combining awake craniotomy and iMRI for the resection of brain tumors in eloquent areas of the brain. METHODS The authors retrospectively reviewed the records of 33 consecutive patients with glial tumors in the eloquent brain areas who underwent awake surgery using iMRI. Volumetric analysis of MRI studies was performed. The pre-, intra-, and postoperative tumor volumes were measured in all cases using MRI studies obtained before, during, and after tumor resection. RESULTS Intraoperative MRI was performed to check for the presence of residual tumor during awake surgery in a total of 25 patients. Initial iMRI confirmed no further tumor resection in 9 patients (36%) because all observable tumors had already been removed. In contrast, intraoperative confirmation of residual tumor during awake surgery led to further tumor resection in 16 cases (64%) and eventually an EOR of more than 90% in 8 of 16 cases (50%). Furthermore, EOR benefiting from iMRI by more than 15% was found in 7 of 16 cases (43.8%). Interestingly, the increase in EOR as a result of iMRI for tumors associated mainly with the insular lobe was significantly greater, at 15.1%, than it was for the other tumors, which was 8.0% (p = 0.001). CONCLUSIONS This study revealed that combining awake surgery with iMRI was associated with a favorable surgical outcome for intrinsic brain tumors associated with eloquent areas. In particular, these benefits were noted for patients with tumors with complex anatomy, such as those associated with the insular lobe.

Efficacy, safety and outcome of frameless image-guided robotic radiosurgery for brain metastases after whole brain radiotherapy.

PubMed

Lohkamp, Laura-Nanna; Vajkoczy, Peter; Budach, Volker; Kufeld, Markus

2018-05-01

Estimating efficacy, safety and outcome of frameless image-guided robotic radiosurgery for the treatment of recurrent brain metastases after whole brain radiotherapy (WBRT). We performed a retrospective single-center analysis including patients with recurrent brain metastases after WBRT, who have been treated with single session radiosurgery, using the CyberKnife® Radiosurgery System (CKRS) (Accuray Inc., CA) between 2011 and 2016. The primary end point was local tumor control, whereas secondary end points were distant tumor control, treatment-related toxicity and overall survival. 36 patients with 140 recurrent brain metastases underwent 46 single session CKRS treatments. Twenty one patients had multiple brain metastases (58%). The mean interval between WBRT and CKRS accounted for 2 years (range 0.2-7 years). The median number of treated metastases per treatment session was five (range 1-12) with a tumor volume of 1.26 ccm (mean) and a median tumor dose of 18 Gy prescribed to the 70% isodose line. Two patients experienced local tumor recurrence within the 1st year after treatment and 13 patients (36%) developed novel brain metastases. Nine of these patients underwent additional one to three CKRS treatments. Eight patients (22.2%) showed treatment-related radiation reactions on MRI, three with clinical symptoms. Median overall survival was 19 months after CKRS. The actuarial 1-year local control rate was 94.2%. CKRS has proven to be locally effective and safe due to high local tumor control rates and low toxicity. Thus CKRS offers a reliable salvage treatment option for recurrent brain metastases after WBRT.

Childhood brain cancer and its psychosocial impact on survivors and their parents: A qualitative thematic synthesis.

PubMed

Woodgate, Roberta L; Tailor, Ketan; Yanofsky, Rochelle; Vanan, Magimairajan Issai

2016-02-01

The multiple late-effects experienced by survivors of childhood brain tumors, are not only a source of great distress for survivors, but also for their parents and siblings. The aim of this review is to systematically identify and synthesize qualitative evidence on how survivors of childhood brain tumors and their parents experience life after surviving childhood brain tumors. Based on literature search in seven databases, 10 qualitative studies, published between 2004 and 2014 were included. Surviving a childhood brain tumor was experienced as paradox for survivors and their parents. While parents and survivors celebrated making it through the cancer experience, they nonetheless encountered a world with loss and new challenges. In short, the experience of survival was a bittersweet experience for survivors and their parents. Survivors and their parents experienced change that included living with uncertainty, intensification of the parenting role, a changing social world, a different way of being, and the need for additional help. Results from this synthesis reinforce that surviving a childhood brain tumor should be viewed as a point on a continuum of living with a brain tumor. Psychosocial effects of surviving brain cancer affect the entire family unit. A need for psychosocial support is evident, although development of such supports necessitates a more full understanding of challenges face by the child affected, their parents, and siblings. The limitations noted in this synthesis reinforce that more qualitative research is needed in this subject area. Copyright © 2015 Elsevier Ltd. All rights reserved.

¹H MRS characterization of neurochemical profiles in orthotopic mouse models of human brain tumors.

PubMed

Hulsey, Keith M; Mashimo, Tomoyuki; Banerjee, Abhishek; Soesbe, Todd C; Spence, Jeffrey S; Vemireddy, Vamsidhara; Maher, Elizabeth A; Bachoo, Robert M; Choi, Changho

2015-01-01

Glioblastoma (GBM), the most common primary brain tumor, is resistant to currently available treatments. The development of mouse models of human GBM has provided a tool for studying mechanisms involved in tumor initiation and growth as well as a platform for preclinical investigation of new drugs. In this study we used (1) H MR spectroscopy to study the neurochemical profile of a human orthotopic tumor (HOT) mouse model of human GBM. The goal of this study was to evaluate differences in metabolite concentrations in the GBM HOT mice when compared with normal mouse brain in order to determine if MRS could reliably differentiate tumor from normal brain. A TE =19 ms PRESS sequence at 9.4 T was used for measuring metabolite levels in 12 GBM mice and 8 healthy mice. Levels for 12 metabolites and for lipids/macromolecules at 0.9 ppm and at 1.3 ppm were reliably detected in all mouse spectra. The tumors had significantly lower concentrations of total creatine, GABA, glutamate, total N-acetylaspartate, aspartate, lipids/macromolecules at 0.9 ppm, and lipids/macromolecules at 1.3 ppm than did the brains of normal mice. The concentrations of glycine and lactate, however, were significantly higher in tumors than in normal brain. Copyright © 2014 John Wiley & Sons, Ltd.

Association of The IDH1 C.395G>A (R132H) Mutation with Histological Type in Malay Brain Tumors

PubMed

Mohamed Yusoff, Abdul Aziz; Zulfakhar, Fatin Najwa; Sul’ain, Mohd Dasuki; Idris, Zamzuri; Abdullah, Jafri Malin

2016-12-01

Background: Brain tumors, constituting one of the most deadly forms of cancer worldwide, result from the accumulation of multiple genetic and epigenetic alterations in genes and signaling pathways. Isocitrate dehydrogenase enzyme isoform 1 (IDH1) mutations are frequently identified in primary brain tumors and acute myeloid leukemia. Studies on IDH1 gene mutations have been extensively performed in various populations worldwide but not in Malaysia. This work was conducted to study the prevalence of IDH1 c.395G>A (R132H) hotspot mutations in a group of Malaysian patients with brain tumors in order to gain local data for the IDH1 mutation profile in our population. Methods: Mutation analysis of c.395G>A (R132H) of IDH1 was performed in 40 brain tumor specimens by the polymerase chain reaction-restriction fragment length polymorphism method (PCR-RFLP) and then verified by direct sequencing. Associations between the IDH1 c.395G>A (R132H) mutation and clinicopathologic characteristics were also analyzed. Results: The IDH1 c.395G>A (R132H) mutation was detected in 14/40 patients (35%). A significant association was found with histological tumor types, but not with age, gender and race. Conclusions: IDH1 is frequently mutated and associated with histological subtypes in Malay brain tumors. Creative Commons Attribution License

Association of The IDH1 C.395G>A (R132H) Mutation with Histological Type in Malay Brain Tumors

PubMed Central

Yusoff, Abdul Aziz Mohamed; Zulfakhar, Fatin Najwa; Sul’ain, Mohd Dasuki; Idris, Zamzuri; Abdullah, Jafri Malin

2016-01-01

Background: Brain tumors, constituting one of the most deadly forms of cancer worldwide, result from the accumulation of multiple genetic and epigenetic alterations in genes and signaling pathways. Isocitrate dehydrogenase enzyme isoform 1 (IDH1) mutations are frequently identified in primary brain tumors and acute myeloid leukemia. Studies on IDH1 gene mutations have been extensively performed in various populations worldwide but not in Malaysia. This work was conducted to study the prevalence of IDH1 c.395G>A (R132H) hotspot mutations in a group of Malaysian patients with brain tumors in order to gain local data for the IDH1 mutation profile in our population. Methods: Mutation analysis of c.395G>A (R132H) of IDH1 was performed in 40 brain tumor specimens by the polymerase chain reaction-restriction fragment length polymorphism method (PCR-RFLP) and then verified by direct sequencing. Associations between the IDH1 c.395G>A (R132H) mutation and clinicopathologic characteristics were also analyzed. Results: The IDH1 c.395G>A (R132H) mutation was detected in 14/40 patients (35%). A significant association was found with histological tumor types, but not with age, gender and race. Conclusions: IDH1 is frequently mutated and associated with histological subtypes in Malay brain tumors. PMID:28125199

Coloring brain tumor with multi-potent micellar nanoscale drug delivery system

NASA Astrophysics Data System (ADS)

Chong, Kyuha; Choi, Kyungsun; Kim, EunSoo; Han, Eun Chun; Lee, Jungsul; Cha, Junghwa; Ku, Taeyun; Yoon, Jonghee; Park, Ji Ho; Choi, Chulhee

2012-10-01

Brain tumor, especially glioblastoma multiforme (GBM), is one of the most malignant tumors, which not only demands perplexing treatment approaches but also requires potent and effective treatment modality to deal with recurrence of the tumor. Photodynamic therapy (PDT) is a treatment which has been recommended as a third-level treatment. We are trying to investigate possibility of the PDT as an efficient adjuvant therapeutic modality for the treatment of brain tumor. Inhibition of tumor progression with photosensitizer was verified, in vitro. With micellar nanoscale drug delivery system, localization of the tumor was identified, in vivo, which is able to be referred as photodynamic diagnosis. With consequent results, we are suggesting photodynamic diagnosis and therapy is able to be performed simultaneously with our nanoscale drug delivery system.

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors.

PubMed

Guo, Lu; Wang, Gang; Feng, Yuanming; Yu, Tonggang; Guo, Yu; Bai, Xu; Ye, Zhaoxiang

2016-09-21

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

The mental cost of cognitive enhancement.

PubMed

Iuculano, Teresa; Cohen Kadosh, Roi

2013-03-06

Noninvasive brain stimulation provides a potential tool for affecting brain functions in the typical and atypical brain and offers in several cases an alternative to pharmaceutical intervention. Some studies have suggested that transcranial electrical stimulation (TES), a form of noninvasive brain stimulation, can also be used to enhance cognitive performance. Critically, research so far has primarily focused on optimizing protocols for effective stimulation, or assessing potential physical side effects of TES while neglecting the possibility of cognitive side effects. We assessed this possibility by targeting the high-level cognitive abilities of learning and automaticity in the mathematical domain. Notably, learning and automaticity represent critical abilities for potential cognitive enhancement in typical and atypical populations. Over 6 d, healthy human adults underwent cognitive training on a new numerical notation while receiving TES to the posterior parietal cortex or the dorsolateral prefrontal cortex. Stimulation to the the posterior parietal cortex facilitated numerical learning, whereas automaticity for the learned material was impaired. In contrast, stimulation to the dorsolateral prefrontal cortex impaired the learning process, whereas automaticity for the learned material was enhanced. The observed double dissociation indicates that cognitive enhancement through TES can occur at the expense of other cognitive functions. These findings have important implications for the future use of enhancement technologies for neurointervention and performance improvement in healthy populations.

Occurrence of Pineal Gland Tumors in Combined Chronic Toxicity/Carcinogenicity Studies in Wistar Rats.

PubMed

Treumann, Silke; Buesen, Roland; Gröters, Sibylle; Eichler, Jens-Olaf; van Ravenzwaay, Bennard

2015-08-01

Pineal gland tumors are very rare brain lesions in rats as well as in other species including humans. A total of 8 (out of 1,360 examined) Wistar rats from 3 different combined chronic toxicity/carcinogenicity or mere carcinogenicity studies revealed pineal gland tumors. The tumors were regarded to be spontaneous and unrelated to treatment. The morphology and immunohistochemical evaluation led to the diagnosis malignant pinealoma. The main characteristics that were variably developed within the tumors were the following: cellular atypia, high mitotic index, giant cells, necrosis, Homer Wright rosettes, Flexner-Wintersteiner rosettes and pseudorosettes, positive immunohistochemical reaction for synaptophysin, and neuron-specific enolase. The pineal gland is not a protocol organ for histopathological examination in carcinogenicity studies. Nevertheless, the pineal gland can occasionally be encountered on the routine brain section or if it is the origin of a tumor protruding into the brain, the finding will be recorded. Therefore, although known to be a rare tumor in rats, pineal neoplasms should be included in the list of possible differential diagnoses for brain tumors, especially when the tumor is located in the region of the pineal body. © 2015 by The Author(s).

2-[1-hexyloxyethyl]-2-devinyl pyropheophorbide-a (HPPH) in a nude rat glioma model: implications for photodynamic therapy.

PubMed

Lobel, J; MacDonald, I J; Ciesielski, M J; Barone, T; Potter, W R; Pollina, J; Plunkett, R J; Fenstermaker, R A; Dougherty, T J

2001-01-01

In this study, we evaluated 2-[1-hexyloxyethyl]-2-devinyl pyropheophorbide-alpha (HPPH or Photochlor) as a photosensitizer for the treatment of malignant gliomas by photodynamic therapy (PDT). We performed in vivo reflection spectroscopy in athymic rats to measure the attenuation of light in normal brain tissue. We also studied HPPH pharmacokinetics and PDT effects in nude rats with brain tumors derived from stereotactically implanted U87 human glioma cells. Rats implanted with tumors were sacrificed at designated time points to determine the pharmacokinetics of HPPH in serum, tumor, normal brain, and brain adjacent to tumor (BAT). HPPH concentrations in normal brain, BAT and tumor were determined using fluorescence spectroscopy. Twenty-four hours after intravenous injection of HPPH, we administered interstitial PDT treatment at a wavelength of 665 nm. Light was given in doses of 3.5, 7.5 or 15 J/cm at the tumor site and at a rate of 50 mW/cm. In vivo spectroscopy of normal brain tissue showed that the attenuation depth of 665 nm light is approximately 30% greater than that of 630 nm light used to activate Photofrin, which is currently being evaluated for PDT as an adjuvant to surgery for malignant gliomas. The t1/2 of disappearance of drug from serum and tumor was 25 and 30 hours, respectively. Twenty-four hours after injection of 0.5 mg/kg HPPH, tumor-to-brain drug ratios ranged from 5:1 to 15:1. Enhanced survival was observed in each of the HPPH/PDT-treated animal groups. These data suggest that HPPH may be a useful adjuvant for the treatment of malignant gliomas.

Potential application of a handheld confocal endomicroscope imaging system using a variety of fluorophores in experimental gliomas and normal brain.

PubMed

Martirosyan, Nikolay L; Georges, Joseph; Eschbacher, Jennifer M; Cavalcanti, Daniel D; Elhadi, Ali M; Abdelwahab, Mohammed G; Scheck, Adrienne C; Nakaji, Peter; Spetzler, Robert F; Preul, Mark C

2014-02-01

The authors sought to assess the feasibility of a handheld visible-wavelength confocal endomicroscope imaging system (Optiscan 5.1, Optiscan Pty., Ltd.) using a variety of rapid-acting fluorophores to provide histological information on gliomas, tumor margins, and normal brain in animal models. Mice (n = 25) implanted with GL261 cells were used to image fluorescein sodium (FNa), 5-aminolevulinic acid (5-ALA), acridine orange (AO), acriflavine (AF), and cresyl violet (CV). A U251 glioma xenograft model in rats (n = 5) was used to image sulforhodamine 101 (SR101). A swine (n = 3) model with AO was used to identify confocal features of normal brain. Images of normal brain, obvious tumor, and peritumoral zones were collected using the handheld confocal endomicroscope. Histological samples were acquired through biopsies from matched imaging areas. Samples were visualized with a benchtop confocal microscope. Histopathological features in corresponding confocal images and photomicrographs of H & E-stained tissues were reviewed. Fluorescence induced by FNa, 5-ALA, AO, AF, CV, and SR101 and detected with the confocal endomicroscope allowed interpretation of histological features. Confocal endomicroscopy revealed satellite tumor cells within peritumoral tissue, a definitive tumor border, and striking fluorescent cellular and subcellular structures. Fluorescence in various tumor regions correlated with standard histology and known tissue architecture. Characteristic features of different areas of normal brain were identified as well. Confocal endomicroscopy provided rapid histological information precisely related to the site of microscopic imaging with imaging characteristics of cells related to the unique labeling features of the fluorophores. Although experimental with further clinical trial validation required, these data suggest that intraoperative confocal imaging can help to distinguish normal brain from tumor and tumor margin and may have application in improving intraoperative decisions during resection of brain tumors.

Risk Factors for Preoperative Seizures and Loss of Seizure Control in Patients Undergoing Surgery for Metastatic Brain Tumors.

PubMed

Wu, Adela; Weingart, Jon D; Gallia, Gary L; Lim, Michael; Brem, Henry; Bettegowda, Chetan; Chaichana, Kaisorn L

2017-08-01

Metastatic brain tumors are the most common brain tumors in adults. Patients with metastatic brain tumors have poor prognoses with median survival of 6-12 months. Seizures are a major presenting symptom and cause of morbidity and mortality. In this article, risk factors for the onset of preoperative seizures and postoperative seizure control are examined. Adult patients who underwent resection of one or more brain metastases at a single institution between 1998 and 2011 were reviewed retrospectively. Of 565 patients, 114 (20.2%) patients presented with seizures. Factors independently associated with preoperative seizures were preoperative headaches (P = 0.044), cognitive deficits (P = 0.031), more than 2 intracranial metastatic tumors (P = 0.013), temporal lobe location (P = 0.031), occipital lobe location (P = 0.010), and bone involvement by tumor (P = 0.029). Factors independently associated with loss of seizure control after surgical resection were preoperative seizures (P = 0.001), temporal lobe location (P = 0.037), lack of postoperative chemotherapy (P = 0.010), subtotal resection of tumor (P = 0.022), and local recurrence (P = 0.027). At last follow-up, the majority of patients (93.8%) were seizure-free. Thirty patients (5.30%) in total had loss of seizure control, and only 8 patients (1.41%) who did not have preoperative seizures presented with new-onset seizures after surgical resection of their metastases. The brain is a common site for metastases from numerous primary cancers, such as breast and lung. The identification of factors associated with onset of preoperative seizures as well as seizure control postoperatively could aid management strategies for patients with metastatic brain tumors. Patients with preoperative seizures who underwent resection tended to have good seizure control after surgery. Copyright © 2017 Elsevier Inc. All rights reserved.

The biology of brain metastases—translation to new therapies

PubMed Central

Eichler, April F.; Chung, Euiheon; Kodack, David P.; Loeffler, Jay S.; Fukumura, Dai; Jain, Rakesh K.

2012-01-01

Brain metastases are a serious obstacle in the treatment of patients with solid tumors and contribute to the morbidity and mortality of these cancers. It is speculated that the frequency of brain metastasis is increasing for several reasons, including improved systemic therapy and survival, and detection of metastases in asymptomatic patients. The lack of preclinical models that recapitulate the clinical setting and the exclusion of patients with brain metastases from most clinical trials have slowed progress. Molecular factors contributing to brain metastases are being elucidated, such as genes involved in cell adhesion, extravasation, metabolism, and cellular signaling. Furthermore, the role of the unique brain microenvironment is beginning to be explored. Although the presence and function of the blood–brain barrier in metastatic tumors is still poorly understood, it is likely that some tumor cells are protected from therapeutics by the blood–tumor barrier, creating a sanctuary site. This Review discusses what is known about the biology of brain metastases, what preclinical models are available to study the disease, and which novel therapeutic strategies are being studied in patients. PMID:21487419

Cilengitide in Treating Children With Refractory Primary Brain Tumors

ClinicalTrials.gov

2013-09-27

Childhood Central Nervous System Germ Cell Tumor; Childhood Choroid Plexus Tumor; Childhood Craniopharyngioma; Childhood Ependymoblastoma; Childhood Grade I Meningioma; Childhood Grade II Meningioma; Childhood Grade III Meningioma; Childhood High-grade Cerebellar Astrocytoma; Childhood High-grade Cerebral Astrocytoma; Childhood Infratentorial Ependymoma; Childhood Low-grade Cerebellar Astrocytoma; Childhood Low-grade Cerebral Astrocytoma; Childhood Medulloepithelioma; Childhood Mixed Glioma; Childhood Oligodendroglioma; Childhood Supratentorial Ependymoma; Recurrent Childhood Brain Stem Glioma; Recurrent Childhood Brain Tumor; Recurrent Childhood Cerebellar Astrocytoma; Recurrent Childhood Cerebral Astrocytoma; Recurrent Childhood Ependymoma; Recurrent Childhood Medulloblastoma; Recurrent Childhood Pineoblastoma; Recurrent Childhood Subependymal Giant Cell Astrocytoma; Recurrent Childhood Supratentorial Primitive Neuroectodermal Tumor; Recurrent Childhood Visual Pathway and Hypothalamic Glioma

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.

PubMed

Rundo, Leonardo; Stefano, Alessandro; Militello, Carmelo; Russo, Giorgio; Sabini, Maria Gabriella; D'Arrigo, Corrado; Marletta, Francesco; Ippolito, Massimo; Mauri, Giancarlo; Vitabile, Salvatore; Gilardi, Maria Carla

2017-06-01

Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [ 11 C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation. A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife ® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV MRI . A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment, the feasibility and the clinical value of BTV integration in Gamma Knife treatment planning were considered. Therefore, a qualitative evaluation was carried out by three experienced clinicians. The achieved experimental results showed that GTV and BTV segmentations are statistically correlated (Spearman's rank correlation coefficient: 0.898) but they have low similarity degree (average Dice Similarity Coefficient: 61.87 ± 14.64). Therefore, volume measurements as well as evaluation metrics values demonstrated that MRI and PET convey different but complementary imaging information. GTV and BTV could be combined to enhance treatment planning. In more than 50% of cases the CTV was strongly or moderately conditioned by metabolic imaging. Especially, BTV MRI enhanced the CTV more accurately than BTV in 25% of cases. The proposed fully automatic multimodal PET/MRI segmentation method is a valid operator-independent methodology helping the clinicians to define a CTV that includes both metabolic and morphologic information. BTV MRI and GTV should be considered for a comprehensive treatment planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of scan initiation timing after 11C-methionine administration for the diagnosis of suspected recurrent brain tumors.

PubMed

Nakajima, Reiko; Abe, Koichiro; Momose, Mitsuru; Fukushima, Kenji; Matsuo, Yuka; Kimura, Ken; Kondo, Chisato; Sakai, Shuji

2017-02-01

11 C-Methionine (MET) positron emission tomography (PET) imaging is a valuable technique for the evaluation of primary and recurrent brain tumors. Many studies have used MET-PET for data acquisition starting at 20 min after the tracer injection, while others have used scan initiation times at 5-15 min postinjection. No previous studies have identified the best acquisition timing during MET-PET imaging for suspected recurrent brain tumors. Here we sought to determine the optimal scan initiating timing after MET administration for the detection of recurrent brain tumors. Twenty-three consecutive patients with suspected recurrent brain tumors underwent MET-PET examinations. Brain PET images were reconstructed from the four serial data sets (10-15, 15-20, 20-25, and 25-30 min postinjection) that were obtained using the list-mode acquisition technique. We determined the maximal standardized uptake values (SUVmax) of the target lesions and the target-to-normal-tissue ratios (TNRs), calculated as the SUVmax to the SUVmean of a region of interest placed on the normal contralateral frontal cortex. Target lesions without significant MET uptake were excluded. Thirty-one lesions from 23 patients were enrolled. There were no significant differences in MET SUVmax or TNR values among the PET images that were reconstructed with the data extracted from the four phases postinjection. The MET uptake in the suspected recurrent brain tumors was comparable among all data extraction time phases from 10 to 30 min postinjection. The scan initiation time of MET-PET at 10 min after the injection is allowable for the detection of recurrent brain tumors. The registration identification number of the original study is 1002.

Volumetric glioma quantification: comparison of manual and semi-automatic tumor segmentation for the quantification of tumor growth.

PubMed

Odland, Audun; Server, Andres; Saxhaug, Cathrine; Breivik, Birger; Groote, Rasmus; Vardal, Jonas; Larsson, Christopher; Bjørnerud, Atle

2015-11-01

Volumetric magnetic resonance imaging (MRI) is now widely available and routinely used in the evaluation of high-grade gliomas (HGGs). Ideally, volumetric measurements should be included in this evaluation. However, manual tumor segmentation is time-consuming and suffers from inter-observer variability. Thus, tools for semi-automatic tumor segmentation are needed. To present a semi-automatic method (SAM) for segmentation of HGGs and to compare this method with manual segmentation performed by experts. The inter-observer variability among experts manually segmenting HGGs using volumetric MRIs was also examined. Twenty patients with HGGs were included. All patients underwent surgical resection prior to inclusion. Each patient underwent several MRI examinations during and after adjuvant chemoradiation therapy. Three experts performed manual segmentation. The results of tumor segmentation by the experts and by the SAM were compared using Dice coefficients and kappa statistics. A relatively close agreement was seen among two of the experts and the SAM, while the third expert disagreed considerably with the other experts and the SAM. An important reason for this disagreement was a different interpretation of contrast enhancement as either surgically-induced or glioma-induced. The time required for manual tumor segmentation was an average of 16 min per scan. Editing of the tumor masks produced by the SAM required an average of less than 2 min per sample. Manual segmentation of HGG is very time-consuming and using the SAM could increase the efficiency of this process. However, the accuracy of the SAM ultimately depends on the expert doing the editing. Our study confirmed a considerable inter-observer variability among experts defining tumor volume from volumetric MRIs. © The Foundation Acta Radiologica 2014.

Web-based tool for visualization of electric field distribution in deep-seated body structures and planning of electroporation-based treatments.

PubMed

Marčan, Marija; Pavliha, Denis; Kos, Bor; Forjanič, Tadeja; Miklavčič, Damijan

2015-01-01

Treatments based on electroporation are a new and promising approach to treating tumors, especially non-resectable ones. The success of the treatment is, however, heavily dependent on coverage of the entire tumor volume with a sufficiently high electric field. Ensuring complete coverage in the case of deep-seated tumors is not trivial and can in best way be ensured by patient-specific treatment planning. The basis of the treatment planning process consists of two complex tasks: medical image segmentation, and numerical modeling and optimization. In addition to previously developed segmentation algorithms for several tissues (human liver, hepatic vessels, bone tissue and canine brain) and the algorithms for numerical modeling and optimization of treatment parameters, we developed a web-based tool to facilitate the translation of the algorithms and their application in the clinic. The developed web-based tool automatically builds a 3D model of the target tissue from the medical images uploaded by the user and then uses this 3D model to optimize treatment parameters. The tool enables the user to validate the results of the automatic segmentation and make corrections if necessary before delivering the final treatment plan. Evaluation of the tool was performed by five independent experts from four different institutions. During the evaluation, we gathered data concerning user experience and measured performance times for different components of the tool. Both user reports and performance times show significant reduction in treatment-planning complexity and time-consumption from 1-2 days to a few hours. The presented web-based tool is intended to facilitate the treatment planning process and reduce the time needed for it. It is crucial for facilitating expansion of electroporation-based treatments in the clinic and ensuring reliable treatment for the patients. The additional value of the tool is the possibility of easy upgrade and integration of modules with new functionalities as they are developed.

Web-based tool for visualization of electric field distribution in deep-seated body structures and planning of electroporation-based treatments

PubMed Central

2015-01-01

Background Treatments based on electroporation are a new and promising approach to treating tumors, especially non-resectable ones. The success of the treatment is, however, heavily dependent on coverage of the entire tumor volume with a sufficiently high electric field. Ensuring complete coverage in the case of deep-seated tumors is not trivial and can in best way be ensured by patient-specific treatment planning. The basis of the treatment planning process consists of two complex tasks: medical image segmentation, and numerical modeling and optimization. Methods In addition to previously developed segmentation algorithms for several tissues (human liver, hepatic vessels, bone tissue and canine brain) and the algorithms for numerical modeling and optimization of treatment parameters, we developed a web-based tool to facilitate the translation of the algorithms and their application in the clinic. The developed web-based tool automatically builds a 3D model of the target tissue from the medical images uploaded by the user and then uses this 3D model to optimize treatment parameters. The tool enables the user to validate the results of the automatic segmentation and make corrections if necessary before delivering the final treatment plan. Results Evaluation of the tool was performed by five independent experts from four different institutions. During the evaluation, we gathered data concerning user experience and measured performance times for different components of the tool. Both user reports and performance times show significant reduction in treatment-planning complexity and time-consumption from 1-2 days to a few hours. Conclusions The presented web-based tool is intended to facilitate the treatment planning process and reduce the time needed for it. It is crucial for facilitating expansion of electroporation-based treatments in the clinic and ensuring reliable treatment for the patients. The additional value of the tool is the possibility of easy upgrade and integration of modules with new functionalities as they are developed. PMID:26356007

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%.

Endoscopic and minimally invasive microsurgical approaches for treating brain tumor patients.

PubMed

Badie, Behnam; Brooks, Nathaniel; Souweidane, Mark M

2004-01-01

Recent developments in neuroendoscopy and minimally invasive procedures have greatly impacted the diagnosis and treatment of brain tumors. In this paper, we will review these innovations and discuss how they have influenced our approach to the treatment of intraventricular and pituitary tumors. Finally, the concept of keyhole neurosurgery is illustrated by discussing 'eyebrow orbitotomy' approach as an example. As noninvasive therapeutic alternative become available, future neurosurgeons will be challenged to develop effective and less invasive surgical approaches for the diagnosis and treatment of patients will brain tumors.

Medical management of brain tumors and the sequelae of treatment

PubMed Central

Schiff, David; Lee, Eudocia Q.; Nayak, Lakshmi; Norden, Andrew D.; Reardon, David A.; Wen, Patrick Y.

2015-01-01

Patients with malignant brain tumors are prone to complications that negatively impact their quality of life and sometimes their overall survival as well. Tumors may directly provoke seizures, hypercoagulable states with resultant venous thromboembolism, and mood and cognitive disorders. Antitumor treatments and supportive therapies also produce side effects. In this review, we discuss major aspects of supportive care for patients with malignant brain tumors, with particular attention to management of seizures, venous thromboembolism, corticosteroids and their complications, chemotherapy including bevacizumab, and fatigue, mood, and cognitive dysfunction. PMID:25358508

ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation

PubMed Central

Li, Hai; Fan, Lingzhong; Zhuo, Junjie; Wang, Jiaojian; Zhang, Yu; Yang, Zhengyi; Jiang, Tianzi

2017-01-01

There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation. PMID:28611620

A superpixel-based framework for automatic tumor segmentation on breast DCE-MRI

NASA Astrophysics Data System (ADS)

Yu, Ning; Wu, Jia; Weinstein, Susan P.; Gaonkar, Bilwaj; Keller, Brad M.; Ashraf, Ahmed B.; Jiang, YunQing; Davatzikos, Christos; Conant, Emily F.; Kontos, Despina

2015-03-01

Accurate and efficient automated tumor segmentation in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is highly desirable for computer-aided tumor diagnosis. We propose a novel automatic segmentation framework which incorporates mean-shift smoothing, superpixel-wise classification, pixel-wise graph-cuts partitioning, and morphological refinement. A set of 15 breast DCE-MR images, obtained from the American College of Radiology Imaging Network (ACRIN) 6657 I-SPY trial, were manually segmented to generate tumor masks (as ground truth) and breast masks (as regions of interest). Four state-of-the-art segmentation approaches based on diverse models were also utilized for comparison. Based on five standard evaluation metrics for segmentation, the proposed framework consistently outperformed all other approaches. The performance of the proposed framework was: 1) 0.83 for Dice similarity coefficient, 2) 0.96 for pixel-wise accuracy, 3) 0.72 for VOC score, 4) 0.79 mm for mean absolute difference, and 5) 11.71 mm for maximum Hausdorff distance, which surpassed the second best method (i.e., adaptive geodesic transformation), a semi-automatic algorithm depending on precise initialization. Our results suggest promising potential applications of our segmentation framework in assisting analysis of breast carcinomas.

Interactive-cut: Real-time feedback segmentation for translational research.

PubMed

Egger, Jan; Lüddemann, Tobias; Schwarzenberg, Robert; Freisleben, Bernd; Nimsky, Christopher

2014-06-01

In this contribution, a scale-invariant image segmentation algorithm is introduced that "wraps" the algorithm's parameters for the user by its interactive behavior, avoiding the definition of "arbitrary" numbers that the user cannot really understand. Therefore, we designed a specific graph-based segmentation method that only requires a single seed-point inside the target-structure from the user and is thus particularly suitable for immediate processing and interactive, real-time adjustments by the user. In addition, color or gray value information that is needed for the approach can be automatically extracted around the user-defined seed point. Furthermore, the graph is constructed in such a way, so that a polynomial-time mincut computation can provide the segmentation result within a second on an up-to-date computer. The algorithm presented here has been evaluated with fixed seed points on 2D and 3D medical image data, such as brain tumors, cerebral aneurysms and vertebral bodies. Direct comparison of the obtained automatic segmentation results with costlier, manual slice-by-slice segmentations performed by trained physicians, suggest a strong medical relevance of this interactive approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Paraneoplastic brain stem encephalitis.

PubMed

Blaes, Franz

2013-04-01

Paraneoplastic brain stem encephalitis can occur as an isolated clinical syndrome or, more often, may be part of a more widespread encephalitis. Different antineuronal autoantibodies, such as anti-Hu, anti-Ri, and anti-Ma2 can be associated with the syndrome, and the most frequent tumors are lung and testicular cancer. Anti-Hu-associated brain stem encephalitis does not normally respond to immunotherapy; the syndrome may stabilize under tumor treatment. Brain stem encephalitis with anti-Ma2 often improves after immunotherapy and/or tumor therapy, whereas only a minority of anti-Ri positive patients respond to immunosuppressants or tumor treatment. The Opsoclonus-myoclonus syndrome (OMS) in children, almost exclusively associated with neuroblastoma, shows a good response to steroids, ACTH, and rituximab, some patients do respond to intravenous immunoglobulins or cyclophosphamide. In adults, OMS is mainly associated with small cell lung cancer or gynecological tumors and only a small part of the patients show improvement after immunotherapy. Earlier diagnosis and treatment seem to be one major problem to improve the prognosis of both, paraneoplastic brain stem encephalitis, and OMS.

Emerging Applications of Therapeutic Ultrasound in Neuro-Oncology: Moving Beyond Tumor Ablation

PubMed Central

Hersh, David S.; Kim, Anthony J.; Winkles, Jeffrey A.; Eisenberg, Howard M.; Woodworth, Graeme F.; Frenkel, Victor

2016-01-01

Transcranial focused ultrasound (FUS) can noninvasively transmit acoustic energy with a high degree of accuracy and safety to targets and regions within the brain. Technological advances, including phased array transducers and real-time temperature monitoring with magnetic resonance (MR) thermometry, have created new opportunities for FUS research and clinical translation. Neuro-oncology, in particular, has become a major area of interest, as FUS offers a multifaceted approach to the treatment of brain tumors. FUS has the potential to (1) generate cytotoxicity within tumor tissue, both directly via thermal ablation and indirectly through radiosensitization and sonodynamic therapy; (2) enhance the delivery of therapeutic agents to brain tumors by transiently opening the blood-brain barrier and/or improving distribution through the brain extracellular space; and (3) modulate the tumor microenvironment in order to generate an immune response. In this review, we describe each of these applications for FUS, the proposed mechanisms of action, and the preclinical and clinical studies that have set the foundation for utilizing FUS in neuro-oncology. PMID:27552589

[Therapeutic strategies targeting brain tumor stem cells].

PubMed

Toda, Masahiro

2009-07-01

Progress in stem cell research reveals cancer stem cells to be present in a variety of malignant tumors. Since they exhibit resistance to anticancer drugs and radiotherapy, analysis of their properties has been rapidly carried forward as an important target for the treatment of intractable malignancies, including brain tumors. In fact, brain cancer stem cells (BCSCs) have been isolated from brain tumor tissue and brain tumor cell lines by using neural stem cell culture methods and isolation methods for side population (SP) cells, which have high drug-efflux capacity. Although the analysis of the properties of BCSCs is the most important to developing methods in treating BCSCs, the absence of BCSC purification methods should be remedied by taking it up as an important research task in the immediate future. Thus far, there are no effective treatment methods for BCSCs, and several treatment methods have been proposed based on the cell biology characteristics of BCSCs. In this article, I outline potential treatment methods damaging treatment-resistant BCSCs, including immunotherapy which is currently a topic of our research.

Targeting Phosphatidylserine for Radioimmunotherapy of Breast Cancer Brain Metastasis

DTIC Science & Technology

2015-12-01

response. e. Correlate imaging findings with histological studies of vascular damage, tumor cell and endothelial cell apoptosis or necrosis and vascular ...phosphatidylserine (PS) is exposed exclusively on tumor vascular endothelium of brain metastases in mouse models. A novel PS-targeting antibody, PGN635... vascular endothelial cells in multi-focal brain metastases throughout the whole mouse brain. Vascular endothelium in normal brain tissues is negative

Proton Beam Radiation Therapy in Treating Patients With Low Grade Gliomas

ClinicalTrials.gov

2015-12-14

Adult Brain Tumor; Adult Brain Stem Glioma; Adult Diffuse Astrocytoma; Adult Ependymoma; Adult Grade II Meningioma; Adult Melanocytic Lesion; Adult Meningeal Hemangiopericytoma; Adult Mixed Glioma; Adult Oligodendroglioma; Adult Pineal Gland Astrocytoma; Adult Pineocytoma; Recurrent Adult Brain Tumor

Novel Polyomavirus associated with Brain Tumors in Free-Ranging Raccoons, Western United States

PubMed Central

Dela Cruz, Florante N.; Giannitti, Federico; Li, Linlin; Woods, Leslie W.; Del Valle, Luis; Delwart, Eric

2013-01-01

Tumors of any type are exceedingly rare in raccoons. High-grade brain tumors, consistently located in the frontal lobes and olfactory tracts, were detected in 10 raccoons during March 2010–May 2012 in California and Oregon, suggesting an emerging, infectious origin. We have identified a candidate etiologic agent, dubbed raccoon polyomavirus, that was present in the tumor tissue of all affected animals but not in tissues from 20 unaffected animals. Southern blot hybridization and rolling circle amplification showed the episomal viral genome in the tumors. The multifunctional nuclear protein large T-antigen was detectable by immunohistochemical analyses in a subset of neoplastic cells. Raccoon polyomavirus may contribute to the development of malignant brain tumors of raccoons. PMID:23260029

Novel polyomavirus associated with brain tumors in free-ranging raccoons, western United States.

PubMed

Dela Cruz, Florante N; Giannitti, Federico; Li, Linlin; Woods, Leslie W; Del Valle, Luis; Delwart, Eric; Pesavento, Patricia A

2013-01-01

Tumors of any type are exceedingly rare in raccoons. High-grade brain tumors, consistently located in the frontal lobes and olfactory tracts, were detected in 10 raccoons during March 2010-May 2012 in California and Oregon, suggesting an emerging, infectious origin. We have identified a candidate etiologic agent, dubbed raccoon polyomavirus, that was present in the tumor tissue of all affected animals but not in tissues from 20 unaffected animals. Southern blot hybridization and rolling circle amplification showed the episomal viral genome in the tumors. The multifunctional nuclear protein large T-antigen was detectable by immunohistochemical analyses in a subset of neoplastic cells. Raccoon polyomavirus may contribute to the development of malignant brain tumors of raccoons.

Nanobiotechnology-based delivery strategies: New frontiers in brain tumor targeted therapies.

PubMed

Mangraviti, Antonella; Gullotti, David; Tyler, Betty; Brem, Henry

2016-10-28

Despite recent technological advancements and promising preclinical experiments, brain tumor patients are still met with limited treatment options. Some of the barriers to clinical improvements include the systemic toxicity of cytotoxic compounds, the impedance of the blood brain barrier (BBB), and the lack of therapeutic agents that can selectively target the intracranial tumor environment. To overcome such barriers, a number of chemotherapeutic agents and nucleic acid-based therapies are rapidly being synthesized and tested as new brain tumor-targeted delivery strategies. Novel carriers include liposomal and polymeric nanoparticles, wafers, microchips, microparticle-based nanoplatforms and cells-based vectors. Strong preclinical results suggest that these nanotechnologies are set to transform the therapeutic paradigm for brain tumor treatment. In addition to new tumoricidal agents, parallel work is also being conducted on the BBB front. Preclinical testing of chemical and physical modulation strategies is yielding improved intracranial concentrations. New diagnostic and therapeutic imaging techniques, such as high-intensity focused ultrasound and MRI-guided focused ultrasound, are being used to modulate the BBB in a more precise and non-invasive manner. This review details some of the tremendous advances that are being explored in current brain tumor targeted therapies, including local implant development, nanobiotechnology-based delivery strategies, and techniques of BBB manipulation. Copyright © 2016 Elsevier B.V. All rights reserved.

EGFRvIII-specific chimeric antigen receptor T cells migrate to and kill tumor deposits infiltrating the brain parenchyma in an invasive xenograft model of glioblastoma.

PubMed

Miao, Hongsheng; Choi, Bryan D; Suryadevara, Carter M; Sanchez-Perez, Luis; Yang, Shicheng; De Leon, Gabriel; Sayour, Elias J; McLendon, Roger; Herndon, James E; Healy, Patrick; Archer, Gary E; Bigner, Darell D; Johnson, Laura A; Sampson, John H

2014-01-01

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults and is uniformly lethal. T-cell-based immunotherapy offers a promising platform for treatment given its potential to specifically target tumor tissue while sparing the normal brain. However, the diffuse and infiltrative nature of these tumors in the brain parenchyma may pose an exceptional hurdle to successful immunotherapy in patients. Areas of invasive tumor are thought to reside behind an intact blood brain barrier, isolating them from effective immunosurveillance and thereby predisposing the development of "immunologically silent" tumor peninsulas. Therefore, it remains unclear if adoptively transferred T cells can migrate to and mediate regression in areas of invasive GBM. One barrier has been the lack of a preclinical mouse model that accurately recapitulates the growth patterns of human GBM in vivo. Here, we demonstrate that D-270 MG xenografts exhibit the classical features of GBM and produce the diffuse and invasive tumors seen in patients. Using this model, we designed experiments to assess whether T cells expressing third-generation chimeric antigen receptors (CARs) targeting the tumor-specific mutation of the epidermal growth factor receptor, EGFRvIII, would localize to and treat invasive intracerebral GBM. EGFRvIII-targeted CAR (EGFRvIII+ CAR) T cells demonstrated in vitro EGFRvIII antigen-specific recognition and reactivity to the D-270 MG cell line, which naturally expresses EGFRvIII. Moreover, when administered systemically, EGFRvIII+ CAR T cells localized to areas of invasive tumor, suppressed tumor growth, and enhanced survival of mice with established intracranial D-270 MG tumors. Together, these data demonstrate that systemically administered T cells are capable of migrating to the invasive edges of GBM to mediate antitumor efficacy and tumor regression.

Not so Fast: Co-Requirements for Sonic Hedgehog Induced Brain Tumorigenesis.

PubMed

Ward, Stacey A; Rubin, Joshua B

2015-08-06

The Sonic hedgehog (Shh) pathway plays an integral role in cellular proliferation during normal brain development and also drives growth in a variety of cancers including brain cancer. Clinical trials of Shh pathway inhibitors for brain tumors have yielded disappointing results, indicating a more nuanced role for Shh signaling. We postulate that Shh signaling does not work alone but requires co-activation of other signaling pathways for tumorigenesis and stem cell maintenance. This review will focus on the interplay between the Shh pathway and these pathways to promote tumor growth in brain tumors, presenting opportunities for the study of combinatorial therapies.

Novel Nanotechnologies for Brain Cancer Therapeutics and Imaging.

PubMed

Ferroni, Letizia; Gardin, Chiara; Della Puppa, Alessandro; Sivolella, Stefano; Brunello, Giulia; Scienza, Renato; Bressan, Eriberto; D'Avella, Domenico; Zavan, Barbara

2015-11-01

Despite progress in surgery, radiotherapy, and in chemotherapy, an effective curative treatment of brain cancer, specifically malignant gliomas, does not yet exist. The efficacy of current anti-cancer strategies in brain tumors is limited by the lack of specific therapies against malignant cells. Besides, the delivery of the drugs to brain tumors is limited by the presence of the blood-brain barrier. Nanotechnology today offers a unique opportunity to develop more effective brain cancer imaging and therapeutics. In particular, the development of nanocarriers that can be conjugated with several functional molecules including tumor-specific ligands, anticancer drugs, and imaging probes, can provide new devices which are able to overcome the difficulties of the classical strategies. Nanotechnology-based approaches hold great promise for revolutionizing brain cancer medical treatments, imaging, and diagnosis.

Growth of melanoma brain tumors monitored by photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Staley, Jacob; Grogan, Patrick; Samadi, Abbas K.; Cui, Huizhong; Cohen, Mark S.; Yang, Xinmai

2010-07-01

Melanoma is a primary malignancy that is known to metastasize to the brain and often causes death. The ability to image the growth of brain melanoma in vivo can provide new insights into its evolution and response to therapies. In our study, we use a reflection mode photoacoustic microscopy (PAM) system to detect the growth of melanoma brain tumor in a small animal model. The melanoma tumor cells are implanted in the brain of a mouse at the beginning of the test. Then, PAM is used to scan the region of implantation in the mouse brain, and the growth of the melanoma is monitored until the death of the animal. It is demonstrated that PAM is capable of detecting and monitoring the brain melanoma growth noninvasively in vivo.

[Development of a Computer-aided Diagnosis System to Distinguish between Benign and Malignant Mammary Tumors in Dynamic Magnetic Resonance Images: Automatic Detection of the Position with the Strongest Washout Effect in the Tumor].

PubMed

Miyazaki, Yoshiaki; Tabata, Nobuyuki; Taroura, Tomomi; Shinozaki, Kenji; Kubo, Yuichiro; Tokunaga, Eriko; Taguchi, Kenichi

We propose a computer-aided diagnostic (CAD) system that uses time-intensity curves to distinguish between benign and malignant mammary tumors. Many malignant tumors show a washout pattern in time-intensity curves. Therefore, we designed a program that automatically detects the position with the strongest washout effect using the technique, such as the subtraction technique, which extracts only the washout area in the tumor, and by scanning data in 2×2 pixel region of interest (ROI). Operation of this independently developed program was verified using a phantom system that simulated tumors. In three cases of malignant tumors, the washout pattern detection rate in images with manually set ROI was ≤6%, whereas the detection rate with our novel method was 100%. In one case of a benign tumor, when the same method was used, we checked that there was no washout effect and detected the persistent pattern. Thus, the distinction between benign and malignant tumors using our method was completely consistent with the pathological diagnoses made. Our novel method is therefore effective for differentiating between benign and malignant mammary tumors in dynamic magnetic resonance images.

Study Protocol for a Randomized Controlled Trial Evaluating the Efficacy of an Evidence-Based iPad-App for Cognitive Rehabilitation in Patients with Primary Brain Tumors.

PubMed

van der Linden, Sophie Dorothee; Sitskoorn, Margriet Maria; Rutten, Geert-Jan Maria; Gehring, Karin

2018-06-16

Many patients with primary brain tumors suffer from cognitive deficits, which negatively impact their quality of life. However, cognitive rehabilitation programs for these patients are scarce. We developed an iPad-based cognitive rehabilitation program for brain tumor patients, which was based on our effective face-to-face cognitive rehabilitation program. After successful completion of a feasibility study, a randomized controlled trial has been started. To evaluate the immediate and long-term effects of the iPad-based program on cognitive performance and patient-reported outcome measures (PROMs) in patients with primary brain tumors in an early stage of the disease. Prior to surgery, patients with presumed low-grade glioma and meningioma are included. Before surgery and 3 mo after surgery, neuropsychological assessments are conducted. After the second neuropsychological assessment, patients are assigned to the intervention group or waiting-list control group. The intervention consists of psychoeducation, compensation training, and retraining. Patients are advised to spend 3 h per week on the program for 10 wk. Immediately after completion of the program and a half-year thereafter, postintervention assessments take place. Patients in the control group are offered the opportunity to follow the program after all study assessments. We expect that early cognitive rehabilitation has beneficial effects on cognitive performance and PROMs in brain tumor patients. The iPad-based program allows brain tumor patients to follow a cognitive rehabilitation program from their homes. Forthcoming results may contribute to further improvement of supportive care for brain tumor patients.

Automatic Segmentation of Drosophila Neural Compartments Using GAL4 Expression Data Reveals Novel Visual Pathways.

PubMed

Panser, Karin; Tirian, Laszlo; Schulze, Florian; Villalba, Santiago; Jefferis, Gregory S X E; Bühler, Katja; Straw, Andrew D

2016-08-08

Identifying distinct anatomical structures within the brain and developing genetic tools to target them are fundamental steps for understanding brain function. We hypothesize that enhancer expression patterns can be used to automatically identify functional units such as neuropils and fiber tracts. We used two recent, genome-scale Drosophila GAL4 libraries and associated confocal image datasets to segment large brain regions into smaller subvolumes. Our results (available at https://strawlab.org/braincode) support this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. The basis for the structural assignment is clustering of voxels based on patterns of enhancer expression. These initial clusters are agglomerated to make hierarchical predictions of structure. We applied the algorithm to central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 11 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Epilepsy and brain tumors

PubMed Central

ENGLOT, DARIO J.; CHANG, EDWARD F.; VECHT, CHARLES J.

2016-01-01

Seizures are common in patients with brain tumors, and epilepsy can significantly impact patient quality of life. Therefore, a thorough understanding of rates and predictors of seizures, and the likelihood of seizure freedom after resection, is critical in the treatment of brain tumors. Among all tumor types, seizures are most common with glioneuronal tumors (70–80%), particularly in patients with frontotemporal or insular lesions. Seizures are also common in individuals with glioma, with the highest rates of epilepsy (60–75%) observed in patients with low-grade gliomas located in superficial cortical or insular regions. Approximately 20–50% of patients with meningioma and 20–35% of those with brain metastases also suffer from seizures. After tumor resection, approximately 60–90% are rendered seizure-free, with most favorable seizure outcomes seen in individuals with glioneuronal tumors. Gross total resection, earlier surgical therapy, and a lack of generalized seizures are common predictors of a favorable seizure outcome. With regard to anticonvulsant medication selection, evidence-based guidelines for the treatment of focal epilepsy should be followed, and individual patient factors should also be considered, including patient age, sex, organ dysfunction, comorbidity, or cotherapy. As concomitant chemotherapy commonly forms an essential part of glioma treatment, enzyme-inducing anticonvulsants should be avoided when possible. Seizure freedom is the ultimate goal in the treatment of brain tumor patients with epilepsy, given the adverse effects of seizures on quality of life. PMID:26948360

Impaired capacity for upregulation of MHC class II in tumor-associated microglia.

PubMed

Schartner, Jill M; Hagar, Aaron R; Van Handel, Michelle; Zhang, Leying; Nadkarni, Nivedita; Badie, Behnam

2005-09-01

Immunotherapy for malignant gliomas is being studied as a possible adjunctive therapy for this highly fatal disease. Thus far, inadequate understanding of brain tumor immunology has hindered the design of such therapies. For instance, the role of microglia and macrophages, which comprise a significant proportion of tumor-infiltrating inflammatory cells, in the regulation of the local anti-tumor immune response is poorly understood. To study the response of microglia and macrophages to known activators in brain tumors, we injected CpG oligodeoxynucleotide (ODN), interferon-gamma (IFN-gamma), and IFN-gamma/LPS into normal and intracranial RG2 glioma-bearing rodents. Microglia/macrophage infiltration and their surface expression of MHC class II B7.1 and B7.2 was examined by flow cytometry. Each agent evaluated yielded a distinct microglia/macrophage response: CpG ODN was the most potent inducer of microglia/macrophage infiltration and B7.1 expression, while IFN-gamma resulted in the highest MHC-II expression in both normal and tumors. Regardless of the agent injected, however, MHC-II induction was significantly muted in tumor microglia/macrophage as compared with normal brain. These data suggest that microglia/macrophage responsiveness to activators can vary in brain tumors when compared with normal brain. Understanding the mechanism of these differences may be critical in the development of novel immunotherapies for malignant glioma. (c) 2005 Wiley-Liss, Inc.

The utilization of fluorescein in brain tumor surgery: a systematic review.

PubMed

Cavallo, Claudio; De Laurentis, Camilla; Vetrano, Ignazio G; Falco, Jacopo; Broggi, Morgan; Schiariti, Marco; Ferroli, Paolo; Acerbi, Francesco

2018-05-22

Sodium Fluorescein (SF) is a green, water-soluble dye with the capacity to accumulate in cerebral areas as a result of damaged blood-brain barrier (BBB); this property allows SF to concentrate specifically at the tumor site of various types of brain neoplasms, making the tumor tissue more clearly visible. A literature search (1947-2018) was conducted with the keywords "fluorescein neurosurgery", "YELLOW neurosurgery", "fluorescein brain tumor", "YELLOW brain tumor". We included clinical studies, clinical trials, observational studies, only conducted on humans and concerning surgery; in addition, we have included 3 articles derived from the analysis of the references of other papers. Ultimately, 57 articles were included for further analysis. Fluorescein as a fluorescent tracer in neuro-oncology is gaining a wider acceptance in the neurosurgical literature: until February 1st, 2018, at least 1099 neuro-oncological patients have been operated through fluorescein-assistance, mostly only after 2012. The most important application remains the aim to improve tumor visualization and extent of resection for high-grade gliomas (HGG), but the nonspecific mechanism of action is the theoretical base for its use also for tumors different from HGG. Nevertheless, no homogenous protocol of fluorescein utilization in neurosurgical oncology can be found in literature. Fluorescein-guided surgery is a safe and effective technique to improve visualization and resection of different CNS tumors and conditions, based on BBB alteration, with a growing evidence-based background.

ALA-induced PpIX spectroscopy for brain tumor image-guided surgery

NASA Astrophysics Data System (ADS)

Valdes, Pablo A.; Leblond, Frederic; Kim, Anthony; Harris, Brent T.; Wilson, Brian C.; Paulsen, Keith D.; Roberts, David W.

2011-03-01

Maximizing the extent of brain tumor resection correlates with improved survival and quality of life outcomes in patients. Optimal surgical resection requires accurate discrimination between normal and abnormal, cancerous tissue. We present our recent experience using quantitative optical spectroscopy in 5-aminolevulinic acid (ALA)-induced protoporphyrin IX (PpIX) fluorescence-guided resection. Exogenous administration of ALA leads to preferential accumulation in tumor tissue of the fluorescent compound, PpIX, which can be used for in vivo surgical guidance. Using the state of the art approach with a fluorescence surgical microscope, we have been able to visualize a subset of brain tumors, but the sensitivity and accuracy of fluorescence detection for tumor tissue with this system are low. To take full advantage of the biological selectivity of PpIX accumulation in brain tumors, we used a quantitative optical spectroscopy system for in vivo measurements of PpIX tissue concentrations. We have shown that, using our quantitative approach for determination of biomarker concentrations, ALA-induced PpIX fluorescence-guidance can achieve accuracies of greater than 90% for most tumor histologies. Here we show multivariate analysis of fluorescence and diffuse reflectance signals in brain tumors with comparable diagnostic performance to our previously reported quantitative approach. These results are promising, since they show that technological improvements in current fluorescence-guided surgical technologies and more biologically relevant approaches are required to take full advantage of fluorescent biomarkers, achieve better tumor identification, increase extent of resection, and subsequently, lead to improve survival and quality of life in patients.

Gallium Maltolate Disrupts Tumor Iron Metabolism and Retards the Growth of Glioblastoma by Inhibiting Mitochondrial Function and Ribonucleotide Reductase.

PubMed

Chitambar, Christopher R; Al-Gizawiy, Mona M; Alhajala, Hisham S; Pechman, Kimberly R; Wereley, Janine P; Wujek, Robert; Clark, Paul A; Kuo, John S; Antholine, William E; Schmainda, Kathleen M

2018-06-01

Gallium, a metal with antineoplastic activity, binds transferrin (Tf) and enters tumor cells via Tf receptor1 (TfR1); it disrupts iron homeostasis leading to cell death. We hypothesized that TfR1 on brain microvascular endothelial cells (BMEC) would facilitate Tf-Ga transport into the brain enabling it to target TfR-bearing glioblastoma. We show that U-87 MG and D54 glioblastoma cell lines and multiple glioblastoma stem cell (GSC) lines express TfRs, and that their growth is inhibited by gallium maltolate (GaM) in vitro After 24 hours of incubation with GaM, cells displayed a loss of mitochondrial reserve capacity followed by a dose-dependent decrease in oxygen consumption and a decrease in the activity of the iron-dependent M2 subunit of ribonucleotide reductase (RRM2). IHC staining of rat and human tumor-bearing brains showed that glioblastoma, but not normal glial cells, expressed TfR1 and RRM2, and that glioblastoma expressed greater levels of H- and L-ferritin than normal brain. In an orthotopic U-87 MG glioblastoma xenograft rat model, GaM retarded the growth of brain tumors relative to untreated control ( P = 0.0159) and reduced tumor mitotic figures ( P = 0.045). Tumors in GaM-treated animals displayed an upregulation of TfR1 expression relative to control animals, thus indicating that gallium produced tumor iron deprivation. GaM also inhibited iron uptake and upregulated TfR1 expression in U-87 MG and D54 cells in vitro We conclude that GaM enters the brain via TfR1 on BMECs and targets iron metabolism in glioblastoma in vivo, thus inhibiting tumor growth. Further development of novel gallium compounds for brain tumor treatment is warranted. Mol Cancer Ther; 17(6); 1240-50. ©2018 AACR . ©2018 American Association for Cancer Research.

Polyethyleneimine-modified iron oxide nanoparticles for brain tumor drug delivery using magnetic targeting and intra-carotid administration

PubMed Central

Chertok, Beata; David, Allan E.; Yang, Victor C.

2010-01-01

This study aimed to examine the applicability of polyethyleneimine (PEI)-modified magnetic nanoparticles (GPEI) as a potential vascular drug/gene carrier to brain tumors. In vitro, GPEI exhibited high cell association and low cell toxicity – properties which are highly desirable for intracellular drug/gene delivery. In addition, a high saturation magnetization of 93 emu/g Fe was expected to facilitate magnetic targeting of GPEI to brain tumor lesions. However, following intravenous administration, GPEI could not be magnetically accumulated in tumors of rats harboring orthotopic 9L-gliosarcomas due to its poor pharmacokinetic properties, reflected by a negligibly low plasma AUC of 12 ± 3 μg Fe/ml*min. To improve “passive” GPEI presentation to brain tumor vasculature for subsequent “active” magnetic capture, we examined the intra-carotid route as an alternative for nanoparticle administration. Intra-carotid administration in conjunction with magnetic targeting resulted in 30-fold (p = 0.002) increase in tumor entrapment of GPEI compared to that seen with intravenous administration. In addition, magnetic accumulation of cationic GPEI (ζ-potential = + 37.2 mV) in tumor lesions was 5.2-fold higher (p = 0.004) than that achieved with slightly anionic G100 (ζ-potential = −12 mV) following intra-carotid administration, while no significant accumulation difference was detected between the two types of nanoparticles in the contra-lateral brain (p = 0.187). These promising results warrant further investigation of GPEI as a potential cell-permeable, magnetically-responsive platform for brain tumor delivery of drugs and genes. PMID:20494439

Polyethyleneimine-modified iron oxide nanoparticles for brain tumor drug delivery using magnetic targeting and intra-carotid administration.

PubMed

Chertok, Beata; David, Allan E; Yang, Victor C

2010-08-01

This study aimed to examine the applicability of polyethyleneimine (PEI)-modified magnetic nanoparticles (GPEI) as a potential vascular drug/gene carrier to brain tumors. In vitro, GPEI exhibited high cell association and low cell toxicity--properties which are highly desirable for intracellular drug/gene delivery. In addition, a high saturation magnetization of 93 emu/g Fe was expected to facilitate magnetic targeting of GPEI to brain tumor lesions. However, following intravenous administration, GPEI could not be magnetically accumulated in tumors of rats harboring orthotopic 9L-gliosarcomas due to its poor pharmacokinetic properties, reflected by a negligibly low plasma AUC of 12 +/- 3 microg Fe/ml min. To improve "passive" GPEI presentation to brain tumor vasculature for subsequent "active" magnetic capture, we examined the intra-carotid route as an alternative for nanoparticle administration. Intra-carotid administration in conjunction with magnetic targeting resulted in 30-fold (p=0.002) increase in tumor entrapment of GPEI compared to that seen with intravenous administration. In addition, magnetic accumulation of cationic GPEI (zeta-potential = + 37.2 mV) in tumor lesions was 5.2-fold higher (p=0.004) than that achieved with slightly anionic G100 (zeta-potential= -12 mV) following intra-carotid administration, while no significant accumulation difference was detected between the two types of nanoparticles in the contra-lateral brain (p=0.187). These promising results warrant further investigation of GPEI as a potential cell-permeable, magnetically-responsive platform for brain tumor delivery of drugs and genes. 2010 Elsevier Ltd. All rights reserved.

Interobserver variability in identification of breast tumors in MRI and its implications for prognostic biomarkers and radiogenomics

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

Saha, Ashirbani, E-mail: as698@duke.edu; Grimm, La

Purpose: To assess the interobserver variability of readers when outlining breast tumors in MRI, study the reasons behind the variability, and quantify the effect of the variability on algorithmic imaging features extracted from breast MRI. Methods: Four readers annotated breast tumors from the MRI examinations of 50 patients from one institution using a bounding box to indicate a tumor. All of the annotated tumors were biopsy proven cancers. The similarity of bounding boxes was analyzed using Dice coefficients. An automatic tumor segmentation algorithm was used to segment tumors from the readers’ annotations. The segmented tumors were then compared between readersmore » using Dice coefficients as the similarity metric. Cases showing high interobserver variability (average Dice coefficient <0.8) after segmentation were analyzed by a panel of radiologists to identify the reasons causing the low level of agreement. Furthermore, an imaging feature, quantifying tumor and breast tissue enhancement dynamics, was extracted from each segmented tumor for a patient. Pearson’s correlation coefficients were computed between the features for each pair of readers to assess the effect of the annotation on the feature values. Finally, the authors quantified the extent of variation in feature values caused by each of the individual reasons for low agreement. Results: The average agreement between readers in terms of the overlap (Dice coefficient) of the bounding box was 0.60. Automatic segmentation of tumor improved the average Dice coefficient for 92% of the cases to the average value of 0.77. The mean agreement between readers expressed by the correlation coefficient for the imaging feature was 0.96. Conclusions: There is a moderate variability between readers when identifying the rectangular outline of breast tumors on MRI. This variability is alleviated by the automatic segmentation of the tumors. Furthermore, the moderate interobserver variability in terms of the bounding box does not translate into a considerable variability in terms of assessment of enhancement dynamics. The authors propose some additional ways to further reduce the interobserver variability.« less

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

2008-04-01

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Automatic Multiple-Needle Surgical Planning of Robotic-Assisted Microwave Coagulation in Large Liver Tumor Therapy

PubMed Central

Liu, Shaoli; Xia, Zeyang; Liu, Jianhua; Xu, Jing; Ren, He; Lu, Tong; Yang, Xiangdong

2016-01-01

The “robotic-assisted liver tumor coagulation therapy” (RALTCT) system is a promising candidate for large liver tumor treatment in terms of accuracy and speed. A prerequisite for effective therapy is accurate surgical planning. However, it is difficult for the surgeon to perform surgical planning manually due to the difficulties associated with robot-assisted large liver tumor therapy. These main difficulties include the following aspects: (1) multiple needles are needed to destroy the entire tumor, (2) the insertion trajectories of the needles should avoid the ribs, blood vessels, and other tissues and organs in the abdominal cavity, (3) the placement of multiple needles should avoid interference with each other, (4) an inserted needle will cause some deformation of liver, which will result in changes in subsequently inserted needles’ operating environment, and (5) the multiple needle-insertion trajectories should be consistent with the needle-driven robot’s movement characteristics. Thus, an effective multiple-needle surgical planning procedure is needed. To overcome these problems, we present an automatic multiple-needle surgical planning of optimal insertion trajectories to the targets, based on a mathematical description of all relevant structure surfaces. The method determines the analytical expression of boundaries of every needle “collision-free reachable workspace” (CFRW), which are the feasible insertion zones based on several constraints. Then, the optimal needle insertion trajectory within the optimization criteria will be chosen in the needle CFRW automatically. Also, the results can be visualized with our navigation system. In the simulation experiment, three needle-insertion trajectories were obtained successfully. In the in vitro experiment, the robot successfully achieved insertion of multiple needles. The proposed automatic multiple-needle surgical planning can improve the efficiency and safety of robot-assisted large liver tumor therapy, significantly reduce the surgeon’s workload, and is especially helpful for an inexperienced surgeon. The methodology should be easy to adapt in other body parts. PMID:26982341

Brain Cancer Stem Cells in Adults and Children: Cell Biology and Therapeutic Implications.

PubMed

Abou-Antoun, Tamara J; Hale, James S; Lathia, Justin D; Dombrowski, Stephen M

2017-04-01

Brain tumors represent some of the most malignant cancers in both children and adults. Current treatment options target the majority of tumor cells but do not adequately target self-renewing cancer stem cells (CSCs). CSCs have been reported to resist the most aggressive radiation and chemotherapies, and give rise to recurrent, treatment-resistant secondary malignancies. With advancing technologies, we now have a better understanding of the genetic, epigenetic and molecular signatures and microenvironmental influences which are useful in distinguishing between distinctly different tumor subtypes. As a result, efforts are now underway to identify and target CSCs within various tumor subtypes based on this foundation. This review discusses progress in CSC biology as it relates to targeted therapies which may be uniquely different between pediatric and adult brain tumors. Studies to date suggest that pediatric brain tumors may benefit more from genetic and epigenetic targeted therapies, while combination treatments aimed specifically at multiple molecular pathways may be more effective in treating adult brain tumors which seem to have a greater propensity towards microenvironmental interactions. Ultimately, CSC targeting approaches in combination with current clinical therapies have the potential to be more effective owing to their ability to compromise CSCs maintenance and the mechanisms which underlie their highly aggressive and deadly nature.

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

Breast cancer brain metastases show increased levels of genomic aberration based homologous recombination deficiency scores relative to their corresponding primary tumors.

PubMed

Diossy, M; Reiniger, L; Sztupinszki, Z; Krzystanek, M; Timms, K M; Neff, C; Solimeno, C; Pruss, D; Eklund, A C; Tóth, E; Kiss, O; Rusz, O; Cserni, G; Zombori, T; Székely, B; Tímár, J; Csabai, I; Szallasi, Z

2018-06-18

Based on its mechanism of action, PARP inhibitor therapy is expected to benefit mainly tumor cases with homologous recombination deficiency (HRD). Therefore, identification of tumor types with increased HRD is important for the optimal use of this class of therapeutic agents. HRD levels can be estimated using various mutational signatures from next generation sequencing data and we used this approach to determine whether breast cancer brain metastases show altered levels of HRD scores relative to their corresponding primary tumor. We used a previously published next generation sequencing dataset of twenty-one matched primary breast cancer/brain metastasis pairs to derive the various mutational signatures/HRD scores strongly associated with HRD. We also performed the myChoice HRD analysis on an independent cohort of seventeen breast cancer patients with matched primary/brain metastasis pairs. All of the mutational signatures indicative of HRD showed a significant increase in the brain metastases relative to their matched primary tumor in the previously published whole exome sequencing dataset. In the independent validation cohort the myChoice HRD assay showed an increased level in 87.5% of the brain metastases relative to the primary tumor, with 56% of brain metastases being HRD positive according to the myChoice criteria. The consistent observation that brain metastases of breast cancer tend to have higher HRD measures may raise the possibility that brain metastases may be more sensitive to PARP inhibitor treatment. This observation warrants further investigation to assess whether this increase is common to other metastatic sites as well, and whether clinical trials should adjust their strategy in the application of HRD measures for the prioritization of patients for PARP inhibitor therapy.

Stereotactic radiosurgery for small brain metastases and implications regarding management with systemic therapy alone.

PubMed

Trifiletti, Daniel M; Hill, Colin; Cohen-Inbar, Or; Xu, Zhiyuan; Sheehan, Jason P

2017-09-01

While stereotactic radiosurgery (SRS) has been shown effective in the management of brain metastases, small brain metastases (≤10 mm) can pose unique challenges. Our aim was to investigate the efficacy of SRS in the treatment of small brain metastases, as well as elucidate clinically relevant factors impacting local failure (LF). We utilized a large, single-institution cohort to perform a retrospective analysis of patients with brain metastases up to 1 cm in maximal dimension. Clinical and radiosurgical parameters were investigated for an association with LF and compared using a competing risk model to calculate cumulative incidence functions, with death and whole brain radiotherapy serving as competing risks. 1596 small brain metastases treated with SRS among 424 patients were included. Among these tumors, 33 developed LF during the follow-up period (2.4% at 12 months following SRS). Competing risk analysis demonstrated that LF was dependent on tumor size (0.7% if ≤2 mm and 3.0% if 2-10 mm at 12 months, p = 0.016). Other factors associated with increasing risk of LF were the decreasing margin dose, increasing maximal tumor diameter, volume, and radioresistant tumors (each p < 0.01). 22 tumors (0.78%) developed radiographic radiation necrosis following SRS, and this incidence did not differ by tumor size (≤2 mm and 2-10 mm, p = 0.200). This large analysis confirms that SRS remains an effective modality in treatment of small brain metastases. In light of the excellent local control and relatively low risk of toxicity, patients with small brain metastases who otherwise have a reasonable expected survival should be considered for radiosurgical management.

NKTR-102 Efficacy versus irinotecan in a mouse model of brain metastases of breast cancer.

PubMed

Adkins, Chris E; Nounou, Mohamed I; Hye, Tanvirul; Mohammad, Afroz S; Terrell-Hall, Tori; Mohan, Neel K; Eldon, Michael A; Hoch, Ute; Lockman, Paul R

2015-10-13

Brain metastases are an increasing problem in women with invasive breast cancer. Strategies designed to treat brain metastases of breast cancer, particularly chemotherapeutics such as irinotecan, demonstrate limited efficacy. Conventional irinotecan distributes poorly to brain metastases; therefore, NKTR-102, a PEGylated irinotecan conjugate should enhance irinotecan and its active metabolite SN38 exposure in brain metastases leading to brain tumor cytotoxicity. Female nude mice were intracranially or intracardially implanted with human brain seeking breast cancer cells (MDA-MB-231Br) and dosed with irinotecan or NKTR-102 to determine plasma and tumor pharmacokinetics of irinotecan and SN38. Tumor burden and survival were evaluated in mice treated with vehicle, irinotecan (50 mg/kg), or NKTR-102 low and high doses (10 mg/kg, 50 mg/kg respectively). NKTR-102 penetrates the blood-tumor barrier and distributes to brain metastases. NKTR-102 increased and prolonged SN38 exposure (>20 ng/g for 168 h) versus conventional irinotecan (>1 ng/g for 4 h). Treatment with NKTR-102 extended survival time (from 35 days to 74 days) and increased overall survival for NKTR-102 low dose (30 % mice) and NKTR-102 high dose (50 % mice). Tumor burden decreased (37 % with 10 mg/kg NKTR-102 and 96 % with 50 mg/kg) and lesion sizes decreased (33 % with 10 mg/kg NKTR-102 and 83 % with 50 mg/kg NKTR-102) compared to conventional irinotecan treated animals. Elevated and prolonged tumor SN38 exposure after NKTR-102 administration appears responsible for increased survival in this model of breast cancer brain metastasis. Further, SN38 concentrations observed in this study are clinically achieved with 145 mg/m(2) NKTR-102, such as those used in the BEACON trial, underlining translational relevance of these results.

The orthotopic xenotransplant of human glioblastoma successfully recapitulates glioblastoma-microenvironment interactions in a non-immunosuppressed mouse model.

PubMed

Garcia, Celina; Dubois, Luiz Gustavo; Xavier, Anna Lenice; Geraldo, Luiz Henrique; da Fonseca, Anna Carolina Carvalho; Correia, Ana Helena; Meirelles, Fernanda; Ventura, Grasiella; Romão, Luciana; Canedo, Nathalie Henriques Silva; de Souza, Jorge Marcondes; de Menezes, João Ricardo Lacerda; Moura-Neto, Vivaldo; Tovar-Moll, Fernanda; Lima, Flavia Regina Souza

2014-12-08

Glioblastoma (GBM) is the most common primary brain tumor and the most aggressive glial tumor. This tumor is highly heterogeneous, angiogenic, and insensitive to radio- and chemotherapy. Here we have investigated the progression of GBM produced by the injection of human GBM cells into the brain parenchyma of immunocompetent mice. Xenotransplanted animals were submitted to magnetic resonance imaging (MRI) and histopathological analyses. Our data show that two weeks after injection, the produced tumor presents histopathological characteristics recommended by World Health Organization for the diagnosis of GBM in humans. The tumor was able to produce reactive gliosis in the adjacent parenchyma, angiogenesis, an intense recruitment of macrophage and microglial cells, and presence of necrosis regions. Besides, MRI showed that tumor mass had enhanced contrast, suggesting a blood-brain barrier disruption. This study demonstrated that the xenografted tumor in mouse brain parenchyma develops in a very similar manner to those found in patients affected by GBM and can be used to better understand the biology of GBM as well as testing potential therapies.

Self-Assembly of Gold Nanoparticles Shows Microenvironment-Mediated Dynamic Switching and Enhanced Brain Tumor Targeting

PubMed Central

Feng, Qishuai; Shen, Yajing; Fu, Yingjie; Muroski, Megan E.; Zhang, Peng; Wang, Qiaoyue; Xu, Chang; Lesniak, Maciej S.; Li, Gang; Cheng, Yu

2017-01-01

Inorganic nanoparticles with unique physical properties have been explored as nanomedicines for brain tumor treatment. However, the clinical applications of the inorganic formulations are often hindered by the biological barriers and failure to be bioeliminated. The size of the nanoparticle is an essential design parameter which plays a significant role to affect the tumor targeting and biodistribution. Here, we report a feasible approach for the assembly of gold nanoparticles into ~80 nm nanospheres as a drug delivery platform for enhanced retention in brain tumors with the ability to be dynamically switched into the single formulation for excretion. These nanoassemblies can target epidermal growth factor receptors on cancer cells and are responsive to tumor microenvironmental characteristics, including high vascular permeability and acidic and redox conditions. Anticancer drug release was controlled by a pH-responsive mechanism. Intracellular L-glutathione (GSH) triggered the complete breakdown of nanoassemblies to single gold nanoparticles. Furthermore, in vivo studies have shown that nanospheres display enhanced tumor-targeting efficiency and therapeutic effects relative to single-nanoparticle formulations. Hence, gold nanoassemblies present an effective targeting strategy for brain tumor treatment. PMID:28638474

Self-Assembly of Gold Nanoparticles Shows Microenvironment-Mediated Dynamic Switching and Enhanced Brain Tumor Targeting.

PubMed

Feng, Qishuai; Shen, Yajing; Fu, Yingjie; Muroski, Megan E; Zhang, Peng; Wang, Qiaoyue; Xu, Chang; Lesniak, Maciej S; Li, Gang; Cheng, Yu

2017-01-01

Inorganic nanoparticles with unique physical properties have been explored as nanomedicines for brain tumor treatment. However, the clinical applications of the inorganic formulations are often hindered by the biological barriers and failure to be bioeliminated. The size of the nanoparticle is an essential design parameter which plays a significant role to affect the tumor targeting and biodistribution. Here, we report a feasible approach for the assembly of gold nanoparticles into ~80 nm nanospheres as a drug delivery platform for enhanced retention in brain tumors with the ability to be dynamically switched into the single formulation for excretion. These nanoassemblies can target epidermal growth factor receptors on cancer cells and are responsive to tumor microenvironmental characteristics, including high vascular permeability and acidic and redox conditions. Anticancer drug release was controlled by a pH-responsive mechanism. Intracellular L-glutathione (GSH) triggered the complete breakdown of nanoassemblies to single gold nanoparticles. Furthermore, in vivo studies have shown that nanospheres display enhanced tumor-targeting efficiency and therapeutic effects relative to single-nanoparticle formulations. Hence, gold nanoassemblies present an effective targeting strategy for brain tumor treatment.

Presumed choroidal metastasis of Merkel cell carcinoma

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

Small, K.W.; Rosenwasser, G.O.; Alexander, E. III

1990-05-01

Merkel cell carcinoma is a rare skin tumor of neural crest origin and is part of the amine precursor uptake and decarboxylase system. It typically occurs on the face of elderly people. Distant metastasis is almost uniformly fatal. Choroidal metastasis, to our knowledge, has not been described. We report a patient with Merkel cell carcinoma who had a synchronous solid choroidal tumor and a biopsy-proven brain metastasis. Our 56-year-old patient presented with a rapidly growing, violaceous preauricular skin tumor. Computed tomography of the head disclosed incidental brain and choroidal tumors. Light and electron microscopy of biopsy specimens of both themore » skin and the brain lesions showed Merkel cell carcinoma. Ophthalmoscopy, fluorescein angiography, and A and B echography revealed a solid choroidal mass. The brain and skin tumors responded well to irradiation. A radioactive episcleral plaque was applied subsequently to the choroidal tumor. All tumors regressed, and the patient was doing well 28 months later. To our knowledge this is the first case of presumed choroidal metastasis of Merkel cell carcinoma.« less

In Vivo Follow-up of Brain Tumor Growth via Bioluminescence Imaging and Fluorescence Tomography

PubMed Central

Genevois, Coralie; Loiseau, Hugues; Couillaud, Franck

2016-01-01

Reporter gene-based strategies are widely used in experimental oncology. Bioluminescence imaging (BLI) using the firefly luciferase (Fluc) as a reporter gene and d-luciferin as a substrate is currently the most widely employed technique. The present paper compares the performances of BLI imaging with fluorescence imaging using the near infrared fluorescent protein (iRFP) to monitor brain tumor growth in mice. Fluorescence imaging includes fluorescence reflectance imaging (FRI), fluorescence diffuse optical tomography (fDOT), and fluorescence molecular Imaging (FMT®). A U87 cell line was genetically modified for constitutive expression of both the encoding Fluc and iRFP reporter genes and assayed for cell, subcutaneous tumor and brain tumor imaging. On cultured cells, BLI was more sensitive than FRI; in vivo, tumors were first detected by BLI. Fluorescence of iRFP provided convenient tools such as flux cytometry, direct detection of the fluorescent protein on histological slices, and fluorescent tomography that allowed for 3D localization and absolute quantification of the fluorescent signal in brain tumors. PMID:27809256

In Vivo Follow-up of Brain Tumor Growth via Bioluminescence Imaging and Fluorescence Tomography.

PubMed

Genevois, Coralie; Loiseau, Hugues; Couillaud, Franck

2016-10-31

Reporter gene-based strategies are widely used in experimental oncology. Bioluminescence imaging (BLI) using the firefly luciferase (Fluc) as a reporter gene and d-luciferin as a substrate is currently the most widely employed technique. The present paper compares the performances of BLI imaging with fluorescence imaging using the near infrared fluorescent protein (iRFP) to monitor brain tumor growth in mice. Fluorescence imaging includes fluorescence reflectance imaging (FRI), fluorescence diffuse optical tomography (fDOT), and fluorescence molecular Imaging (FMT ® ). A U87 cell line was genetically modified for constitutive expression of both the encoding Fluc and iRFP reporter genes and assayed for cell, subcutaneous tumor and brain tumor imaging. On cultured cells, BLI was more sensitive than FRI; in vivo, tumors were first detected by BLI. Fluorescence of iRFP provided convenient tools such as flux cytometry, direct detection of the fluorescent protein on histological slices, and fluorescent tomography that allowed for 3D localization and absolute quantification of the fluorescent signal in brain tumors.

Outcomes of Adoptive Cell Transfer With Tumor-infiltrating Lymphocytes for Metastatic Melanoma Patients With and Without Brain Metastases.

PubMed

Mehta, Gautam U; Malekzadeh, Parisa; Shelton, Thomas; White, Donald E; Butman, John A; Yang, James C; Kammula, Udai S; Goff, Stephanie L; Rosenberg, Steven A; Sherry, Richard M

2018-06-01

Brain metastases cause significant morbidity and mortality in patients with metastatic melanoma. Although adoptive cell therapy (ACT) with tumor-infiltrating lymphocytes (TIL) can achieve complete and durable remission of advanced cutaneous melanoma, the efficacy of this therapy for brain metastases is unclear. Records of patients with M1c melanoma treated with ACT using TIL, including patients with treated and untreated brain metastases, were analyzed. Treatment consisted of preparative chemotherapy, autologous TIL infusion, and high-dose interleukin-2. Treatment outcomes, sites of initial tumor progression, and overall survival were analyzed. Among 144 total patients, 15 patients with treated and 18 patients with untreated brain metastases were identified. Intracranial objective responses (OR) occurred in 28% patients with untreated brain metastases. The systemic OR rates for patients with M1c disease without identified brain disease, treated brain disease, and untreated brain disease, and were 49%, 33% and 33%, respectively, of which 59%, 20% and 16% were durable at last follow-up. The site of untreated brain disease was the most likely site of initial tumor progression (61%) in patients with untreated brain metastases. Overall, we found that ACT with TIL can eliminate small melanoma brain metastases. However, following TIL therapy these patients frequently progress in the brain at a site of untreated brain disease. Patients with treated or untreated brain disease are less likely to achieve durable systemic ORs following TIL therapy compared with M1c disease and no history of brain disease. Melanoma brain metastases likely require local therapy despite the systemic effect of ACT.

Analysis of Dose at the Site of Second Tumor Formation After Radiotherapy to the Central Nervous System

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

Galloway, Thomas J.; University of Florida Proton Therapy Institute, Jacksonville, FL; Indelicato, Daniel J., E-mail: dindelicato@floridaproton.org

Purpose: Second tumors are an uncommon complication of multimodality treatment of childhood cancer. The present analysis attempted to correlate the dose received as a component of primary treatment and the site of the eventual development of a second tumor. Methods and Materials: We retrospectively identified 16 patients who had received radiotherapy to sites in the craniospinal axis and subsequently developed a second tumor. We compared the historical fields and port films of the primary treatment with the modern imaging of the second tumor locations. We classified the location of the second tumors as follows: in the boost field; marginal tomore » the boost field, but in a whole-brain field; in a whole-brain field; marginal to the whole brain/primary treatment field; and distant to the field. We divided the dose received into 3 broad categories: high dose (>45 Gy), moderate dose (20-36 Gy), and low dose (<20 Gy). Results: The most common location of the second tumor was in the whole brain field (57%) and in the moderate-dose range (81%). Conclusions: Our data contradict previous publications that suggested that most second tumors develop in tissues that receive a low radiation dose. Almost all the second tumors in our series occurred in tissue within a target volume in the cranium that had received a moderate dose (20-36 Gy). These findings suggest that a major decrease in the brain volume that receives a moderate radiation dose is the only way to substantially decrease the second tumor rate after central nervous system radiotherapy.« less

Stereotactic delivery of a recombinant adenovirus into a C6 glioma cell line in a rat brain tumor model.

PubMed

Badie, B; Hunt, K; Economou, J S; Black, K L

1994-11-01

The dismal results of conventional therapy for primary malignant brain tumors has justified exploring gene therapy approaches for this disease. Transduction of animal brain tumor models in vivo has been reported previously with retroviruses and herpes viruses. Because adenoviruses have the advantage of transducing quiescent and actively dividing tumor cells, they may prove to be more effective in such therapy. We used a replication-deficient recombinant adenovirus bearing the Escherichia coli beta-galactosidase gene in a rat C6 glioma tumor model. Transduced cells were detected by X-5-bromo-4-chloro-3-indolyl beta-D-galactoside staining to reveal beta-galactosidase activity. Initial experiments in vitro showed 50% and 90% transduction at vector titers of approximately 10(7) and 10(8) plaque-forming units/ml, respectively. Although no cytopathic effects were seen at 10(7) plaque-forming units/ml, more than 50% reduction in tumor cell growth was noted at 10(8) plaque-forming units/ml both in vitro and in vivo. Stereotactic delivery of the recombinant adenovirus into the frontal lobe of normal rat brains resulted in intense staining of all cell types, that is, neurons, astrocytes, and ependymal cells. Stereotactic injection into C6 glioma brain tumors in rats stained 25 to 30% of the tumor cells. We conclude that adenovirus vectors can be used to transfer genes to central nervous system tumors in vivo. Using stereotactic delivery, adenovirus vectors can transfer genes into the central nervous system intended for tumor therapy.

Co-evolution of breast-to-brain metastasis and neural progenitor cells.

PubMed

Neman, Josh; Choy, Cecilia; Kowolik, Claudia M; Anderson, Athena; Duenas, Vincent J; Waliany, Sarah; Chen, Bihong T; Chen, Mike Y; Jandial, Rahul

2013-08-01

Brain colonization by metastatic tumor cells offers a unique opportunity to investigate microenvironmental influences on the neoplastic process. The bi-directional interplay of breast cancer cells (mesodermal origin) and brain cells (neuroectodermal origin) is poorly understood and rarely investigated. In our patients undergoing neurosurgical resection of breast-to-brain metastases, specimens from the tumor/brain interface exhibited increased active gliosis as previously described. In addition, our histological characterization revealed infiltration of neural progenitor cells (NPCs) both outside and inside the tumor margin, leading us to investigate the cellular and molecular interactions between NPCs and metastases. Since signaling by the TGF-β superfamily is involved in both developmental neurobiology and breast cancer pathogenesis, we examined the role of these proteins in the context of brain metastases. The brain-metastatic breast cancer cell line MDA-MB-231Br (231Br) expressed BMP-2 at significantly higher levels compared to its matched primary breast cancer cell line MDA-MB-231 (231). Co-culturing was used to examine bi-directional cellular effects and the relevance of BMP-2 overexpression. When co-cultured with NPCs, 231 (primary) tumor cells failed to proliferate over 15 days. However, 231Br (brain metastatic) tumor cells co-cultured with NPCs escaped growth inhibition after day 5 and proliferated, occurring in parallel with NPC differentiation into astrocytes. Using shRNA and gene knock-in, we then demonstrated BMP-2 secreted by 231Br cells mediated NPC differentiation into astrocytes and concomitant tumor cell proliferation in vitro. In xenografts, overexpression of BMP-2 in primary breast cancer cells significantly enhanced their ability to engraft and colonize the brain, thereby creating a metastatic phenotype. Conversely, BMP-2 knockdown in metastatic breast cancer cells significantly diminished engraftment and colonization. The results suggest metastatic tumor cells create a permissive neural niche by steering NPC differentiation toward astrocytes through paracrine BMP-2 signaling.

Co-evolution of breast-to-brain metastasis and neural progenitor cells

PubMed Central

Neman, Josh; Choy, Cecilia; Kowolik, Claudia M.; Anderson, Athena; Duenas, Vincent J.; Waliany, Sarah; Chen, Bihong T.; Chen, Mike Y.

2013-01-01

Brain colonization by metastatic tumor cells offers a unique opportunity to investigate microenvironmental influences on the neoplastic process. The bi-directional interplay of breast cancer cells (mesodermal origin) and brain cells (neuroectodermal origin) is poorly understood and rarely investigated. In our patients undergoing neurosurgical resection of breast-to-brain metastases, specimens from the tumor/brain interface exhibited increased active gliosis as previously described. In addition, our histological characterization revealed infiltration of neural progenitor cells (NPCs) both outside and inside the tumor margin, leading us to investigate the cellular and molecular interactions between NPCs and metastases. Since signaling by the TGF-β superfamily is involved in both developmental neurobiology and breast cancer pathogenesis, we examined the role of these proteins in the context of brain metastases. The brain-metastatic breast cancer cell line MDA-MB-231Br (231Br) expressed BMP-2 at significantly higher levels compared to its matched primary breast cancer cell line MDA-MB-231 (231). Co-culturing was used to examine bi-directional cellular effects and the relevance of BMP-2 overexpression. When co-cultured with NPCs, 231 (primary) tumor cells failed to proliferate over 15 days. However, 231Br (brain meta-static) tumor cells co-cultured with NPCs escaped growth inhibition after day 5 and proliferated, occurring in parallel with NPC differentiation into astrocytes. Using shRNA and gene knock-in, we then demonstrated BMP-2 secreted by 231Br cells mediated NPC differentiation into astrocytes and concomitant tumor cell proliferation in vitro. In xenografts, overexpression of BMP-2 in primary breast cancer cells significantly enhanced their ability to engraft and colonize the brain, thereby creating a metastatic phenotype. Conversely, BMP-2 knockdown in metastatic breast cancer cells significantly diminished engraftment and colonization. The results suggest metastatic tumor cells create a permissive neural niche by steering NPC differentiation toward astrocytes through paracrine BMP-2 signaling. PMID:23456474

SU-E-J-212: MR Diffusion Tensor Imaging for Assessment of Tumor and Normal Brain Tissue Responses of Juvenile Pilocytic Astrocytoma Treated by Proton Therapy

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

Hou, P; Park, P; Li, H

Purpose: Diffusion tensor imaging (DTI) can measure molecular mobility at the cellular level, quantified by the apparent diffusion coefficient (ADC). DTI may also reveal axonal fiber directional information in the white matter, quantified by the fractional anisotropy (FA). Juvenile pilocytic astrocytoma (JPA) is a rare brain tumor that occurs in children and young adults. Proton therapy (PT) is increasingly used in the treatment of pediatric brain tumors including JPA. However, the response of both tumors and normal tissues to PT is currently under investigation. We report tumor and normal brain tissue responses for a pediatric case of JPA treated withmore » PT assessed using DTI. Methods: A ten year old male with JPA of the left thalamus received passive scattered PT to a dose of 50.4 Gy (RBE) in 28 fractions. Post PT, the patient has been followed up in seven years. At each follow up, MRI imaging including DTI was performed to assess response. MR images were registered to the treatment planning CT and the GTV mapped onto each MRI. The GTV contour was then mirrored to the right side of brain through the patient’s middle line to represent normal brain tissue. ADC and FA were measured within the ROIs. Results: Proton therapy can completely spare contra lateral brain while the target volume received full prescribed dose. From a series of MRI ADC images before and after PT at different follow ups, the enhancement corresponding to GTV had nearly disappeared more than 2 years after PT. Both ADC and FA demonstrate that contralateral normal brain tissue were not affect by PT and the tumor volume reverted to normal ADC and FA values. Conclusion: DTI allowed quantitative evaluation of tumor and normal brain tissue responses to PT. Further study in a larger cohort is warranted.« less

Straight trajectory planning for keyhole neurosurgery in sheep with automatic brain structures segmentation

NASA Astrophysics Data System (ADS)

Favaro, Alberto; Lad, Akash; Formenti, Davide; Zani, Davide Danilo; De Momi, Elena

2017-03-01

In a translational neuroscience/neurosurgery perspective, sheep are considered good candidates to study because of the similarity between their brain and the human one. Automatic planning systems for safe keyhole neurosurgery maximize the probe/catheter distance from vessels and risky structures. This work consists in the development of a trajectories planner for straight catheters placement intended to be used for investigating the drug diffusivity mechanisms in sheep brain. Automatic brain segmentation of gray matter, white matter and cerebrospinal fluid is achieved using an online available sheep atlas. Ventricles, midbrain and cerebellum segmentation have been also carried out. The veterinary surgeon is asked to select a target point within the white matter to be reached by the probe and to define an entry area on the brain cortex. To mitigate the risk of hemorrhage during the insertion process, which can prevent the success of the insertion procedure, the trajectory planner performs a curvature analysis of the brain cortex and wipes out from the poll of possible entry points the sulci, as part of brain cortex where superficial blood vessels are naturally located. A limited set of trajectories is then computed and presented to the surgeon, satisfying an optimality criteria based on a cost function which considers the distance from critical brain areas and the whole trajectory length. The planner proved to be effective in defining rectilinear trajectories accounting for the safety constraints determined by the brain morphology. It also demonstrated a short computational time and good capability in segmenting gyri and sulci surfaces.

Lapatinib distribution in HER2 overexpressing experimental brain metastases of breast cancer.

PubMed

Taskar, Kunal S; Rudraraju, Vinay; Mittapalli, Rajendar K; Samala, Ramakrishna; Thorsheim, Helen R; Lockman, Julie; Gril, Brunilde; Hua, Emily; Palmieri, Diane; Polli, Joseph W; Castellino, Stephen; Rubin, Stephen D; Lockman, Paul R; Steeg, Patricia S; Smith, Quentin R

2012-03-01

Lapatinib, a small molecule EGFR/HER2 inhibitor, partially inhibits the outgrowth of HER2+ brain metastases in preclinical models and in a subset of CNS lesions in clinical trials of HER2+ breast cancer. We investigated the ability of lapatinib to reach therapeutic concentrations in the CNS following (14)C-lapatinib administration (100 mg/kg p.o. or 10 mg/kg, i.v.) to mice with MDA-MD-231-BR-HER2 brain metastases of breast cancer. Drug concentrations were determined at differing times after administration by quantitative autoradiography and chromatography. (14)C-Lapatinib concentration varied among brain metastases and correlated with altered blood-tumor barrier permeability. On average, brain metastasis concentration was 7-9-fold greater than surrounding brain tissue at 2 and 12 h after oral administration. However, average lapatinib concentration in brain metastases was still only 10-20% of those in peripheral metastases. Only in a subset of brain lesions (17%) did lapatinib concentration approach that of systemic metastases. No evidence was found of lapatinib resistance in tumor cells cultured ex vivo from treated brains. Results show that lapatinib distribution to brain metastases of breast cancer is partially restricted and blood-tumor barrier permeability is a key component of lapatinib therapeutic efficacy which varies between tumors.

Lapatinib Distribution in HER2 Overexpressing Experimental Brain Metastases of Breast Cancer

PubMed Central

Taskar, Kunal S.; Rudraraju, Vinay; Mittapalli, Rajendar K.; Samala, Ramakrishna; R. Thorsheim, Helen; Lockman, Julie; Gril, Brunilde; Hua, Emily; Palmieri, Diane; Polli, Joseph W.; Castellino, Stephen; Rubin, Stephen D.; Lockman, Paul R.; Steeg, Patricia S.; Smith, Quentin R.

2012-01-01

Purpose Lapatinib, a small molecule EGFR/HER2 inhibitor, has limited effect on outgrowth of HER2+ brain metastases in preclinical and clinical trials. We investigated the ability of lapatinib to reach therapeutic concentrations in the CNS following 14C-lapatinib administration (100 mg/kg p.o. or 10 mg/kg, i.v.) to mice with MDA-MD-231-BR-HER2 brain metastases of breast cancer. Methods Drug concentrations were determined at differing times after administration by quantitative autoradiography and chromatography. Results 14C-Lapatinib concentration varied among brain metastases and correlated with altered blood-tumor barrier permeability. On average, brain metastasis concentration was 7–9-fold greater than surrounding brain tissue at 2 and 12 hours after oral administration. However, average lapatinib concentration in brain metastases was still only 10–20% of those in peripheral metastases. Only in a subset of brain lesions (17%) did lapatinib concentration approach that of systemic metastases. No evidence was found of lapatinib resistance in tumor cells remaining in brain after lapatinib treatment. Conclusions Results show that lapatinib distribution to brain metastases of breast cancer is restricted and blood-tumor barrier permeability is a key component of lapatinib therapeutic efficacy which varies within and between tumors. PMID:22011930

Brain Tumor Surgery

MedlinePlus

... Proton Therapy Alternative & Integrative Medicine Clinical Trials GBM AGILE TTFields – Optune™ Brain Tumor Treatment Locations Treatment Side Effects & their Management Support and Resources Caregiver Resource Center Pediatric Caregiver ...

Focused Ultrasound-Induced Blood–Brain Barrier Opening to Enhance Temozolomide Delivery for Glioblastoma Treatment: A Preclinical Study

PubMed Central

Wei, Kuo-Chen; Chu, Po-Chun; Wang, Hay-Yan Jack; Huang, Chiung-Yin; Chen, Pin-Yuan; Tsai, Hong-Chieh; Lu, Yu-Jen; Lee, Pei-Yun; Tseng, I-Chou; Feng, Li-Ying; Hsu, Peng-Wei; Yen, Tzu-Chen; Liu, Hao-Li

2013-01-01

The purpose of this study is to assess the preclinical therapeutic efficacy of magnetic resonance imaging (MRI)-monitored focused ultrasound (FUS)-induced blood-brain barrier (BBB) disruption to enhance Temozolomide (TMZ) delivery for improving Glioblastoma Multiforme (GBM) treatment. MRI-monitored FUS with microbubbles was used to transcranially disrupt the BBB in brains of Fisher rats implanted with 9L glioma cells. FUS-BBB opening was spectrophotometrically determined by leakage of dyes into the brain, and TMZ was quantitated in cerebrospinal fluid (CSF) and plasma by LC-MS\\MS. The effects of treatment on tumor progression (by MRI), animal survival and brain tissue histology were investigated. Results demonstrated that FUS-BBB opening increased the local accumulation of dyes in brain parenchyma by 3.8-/2.1-fold in normal/tumor tissues. Compared to TMZ alone, combined FUS treatment increased the TMZ CSF/plasma ratio from 22.7% to 38.6%, reduced the 7-day tumor progression ratio from 24.03 to 5.06, and extended the median survival from 20 to 23 days. In conclusion, this study provided preclinical evidence that FUS BBB-opening increased the local concentration of TMZ to improve the control of tumor progression and animal survival, suggesting its clinical potential for improving current brain tumor treatment. PMID:23527068

Accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue.

PubMed

Zhang, Jing; Fan, Yimeng; He, Min; Ma, Xuelei; Song, Yanlin; Liu, Ming; Xu, Jianguo

2017-05-30

Raman spectroscopy could be applied to distinguish tumor from normal tissues. This meta-analysis was conducted to assess the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. PubMed and Embase were searched to identify suitable studies prior to Jan 1st, 2016. We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (LR), diagnostic odds ratio (DOR), and constructed summary receiver operating characteristics (SROC) curves to identity the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. A total of six studies with 1951 spectra were included. For glioma, the pooled sensitivity and specificity of Raman spectroscopy were 0.96 (95% CI 0.94-0.97) and 0.99 (95% CI 0.98-0.99), respectively. The area under the curve (AUC) was 0.9831. For meningioma, the pooled sensitivity and specificity were 0.98 (95% CI 0.94-1.00) and 1.00 (95% CI 0.98-1.00), respectively. The AUC was 0.9955. This meta-analysis suggested that Raman spectroscopy could be an effective and accurate tool for differentiating glioma and meningioma from normal brain tissue, which would help us both avoid removal of normal tissue and minimize the volume of residual tumor.

Determination of fluence rate and temperature distributions in the rat brain; implications for photodynamic therapy.

PubMed

Angell-Petersen, Even; Hirschberg, Henry; Madsen, Steen J

2007-01-01

Light and heat distributions are measured in a rat glioma model used in photodynamic therapy. A fiber delivering 632-nm light is fixed in the brain of anesthetized BDIX rats. Fluence rates are measured using calibrated isotropic probes that are positioned stereotactically. Mathematical models are then used to derive tissue optical properties, enabling calculation of fluence rate distributions for general tumor and light application geometries. The fluence rates in tumor-free brains agree well with the models based on diffusion theory and Monte Carlo simulation. In both cases, the best fit is found for absorption and reduced scattering coefficients of 0.57 and 28 cm(-1), respectively. In brains with implanted BT(4)C tumors, a discrepancy between diffusion and Monte Carlo-derived two-layer models is noted. Both models suggest that tumor tissue has higher absorption and less scattering than normal brain. Temperatures are measured by inserting thermocouples directly into tumor-free brains. A model based on diffusion theory and the bioheat equation is found to be in good agreement with the experimental data and predict a thermal penetration depth of 0.60 cm in normal rat brain. The predicted parameters can be used to estimate the fluences, fluence rates, and temperatures achieved during photodynamic therapy.

The biochemical, nanomechanical and chemometric signatures of brain cancer

NASA Astrophysics Data System (ADS)

Abramczyk, Halina; Imiela, Anna

2018-01-01

Raman spectroscopy and imaging combined with AFM topography and mechanical indentation by AFM have been shown to be an effective tool for analysis and discrimination of human brain tumors from normal structures. Raman methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n = 5) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma (IV grade), and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational spectra and Raman images we provide a real-time feedback that is label-free method to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, and proteins. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have shown that the ratio of Raman intensities I2930/I2845 at 2930 and 2845 cm- 1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the lipid and protein contents of tumorous brain tissue compared to the non-tumor tissue. Almost all brain tumors have the Raman intensity ratios significantly higher (1.99 ± 0.026) than that found in non-tumor brain tissue, which is 1.456 ± 0.02, and indicates that the relative amount of lipids compared to proteins is significantly higher in the normal brain tissue. Mechanical indentation using AFM on sliced human brain tissues (medulloblastoma, grade IV) revealed that the mechanical properties of this tissue are strongly heterogeneous, between 1.8 and 75.7 kPa, and the mean of 27.16 kPa. The sensitivity and specificity obtained directly from PLSDA and cross validation gives a sensitivity and specificity of 98.5% and 96% and 96.3% and 92% for cross-validation, respectively. The high sensitivity and specificity demonstrates usefulness for a proper decision for a Raman diagnostic test on biochemical alterations monitored by Raman spectroscopy related to brain cancer development.

Coagulation Alteration and Deep Vein Thrombosis in Brain Tumor Patients During the Perioperative Period.

PubMed

Guo, Xiaopeng; Zhang, Fa; Wu, Yue; Gao, Lu; Wang, Qiang; Wang, Zihao; Feng, Chenzhe; Yang, Yi; Xing, Bing; Xu, Zhiqin

2018-06-01

To explore coagulation function in patients with brain tumors before and after craniotomy and tumor resection and to analyze its correlation with deep vein thrombosis (DVT). This study enrolled 133 consecutive patients with brain tumors. Coagulation evaluation and limb venous ultrasonography were performed before and after surgery. Clinical characteristics and dynamic changes in coagulation parameters were recorded, and their correlations with DVT were analyzed. The incidence of postoperative DVT in patients with brain tumors was 10.5%. The average age of patients with DVT was older compared with patients without DVT (63.21 ± 11.21 years vs. 50.24 ± 11.95 years, P < 0.001), and the incidence of hepatitis B (21% vs. 4%, P = 0.035) was higher in patients with DVT compared with patients without DVT. D-dimer and fibrinogen were the most variable parameters during the perioperative period. In patients with DVT, D-dimer levels displayed a "zigzagging-rise" trend and were significantly higher than levels in patients without DVT. Platelet levels displayed a "first-descend-then-rise" trend and were significantly lower in patients with DVT on the second and third postoperative days. In patients with brain tumors, D-dimer and fibrinogen were elevated postoperatively, manifesting as hypercoagulability. Postoperative DVT was correlated with aging and hepatitis B. A "zigzagging-rise" trend of D-dimer and a "sharp-descent" trend of platelets in the early postoperative period might predict DVT in patients with brain tumors. Copyright © 2018 Elsevier Inc. All rights reserved.

The Role of Surgery, Radiosurgery and Whole Brain Radiation Therapy in the Management of Patients with Metastatic Brain Tumors

PubMed Central

Ellis, Thomas L.; Neal, Matthew T.; Chan, Michael D.

2012-01-01

Brain tumors constitute the most common intracranial tumor. Management of brain metastases has become increasingly complex as patients with brain metastases are living longer and more treatment options develop. The goal of this paper is to review the role of stereotactic radiosurgery (SRS), whole brain radiation therapy (WBRT), and surgery, in isolation and in combination, in the contemporary treatment of brain metastases. Surgery and SRS both offer management options that may help to optimize therapy in selected patients. WBRT is another option but can lead to late toxicity and suboptimal local control in longer term survivors. Improved prognostic indices will be critical for selecting the best therapies. Further prospective trials are necessary to continue to elucidate factors that will help triage patients to the proper brain-directed therapy for their cancer. PMID:22312545

"Facilitated" amino acid transport is upregulated in brain tumors.

PubMed

Miyagawa, T; Oku, T; Uehara, H; Desai, R; Beattie, B; Tjuvajev, J; Blasberg, R

1998-05-01

The goal of this study was to determine the magnitude of "facilitated" amino acid transport across tumor and brain capillaries and to evaluate whether amino acid transporter expression is "upregulated" in tumor vessels compared to capillaries in contralateral brain tissue. Aminocyclopentane carboxylic acid (ACPC), a non-metabolized [14C]-labeled amino acid, and a reference molecule for passive vascular permeability, [67Ga]-gallium-diethylenetriaminepentaacetic acid (Ga-DTPA), were used in these studies. Two experimental rat gliomas were studied (C6 and RG2). Brain tissue was rapidly processed for double label quantitative autoradiography 10 minutes after intravenous injection of ACPC and Ga-DTPA. Parametric images of blood-to-brain transport (K1ACPC and K1Ga-DTPA, microL/min/g) produced from the autoradiograms and the histology were obtained from the same tissue section. These three images were registered in an image array processor; regions of interest in tumor and contralateral brain were defined on morphologic criteria (histology) and were transferred to the autoradiographic images to obtain mean values. The facilitated component of ACPC transport (deltaK1ACPC) was calculated from the K1ACPC and K1Ga-DTPA data, and paired comparisons between tumor and contralateral brain were performed. ACPC flux, K1ACPC, across normal brain capillaries (22.6 +/- 8.1 microL/g/min) was >200-fold greater than that of Ga-DTPA (0.09 +/- 0.04 microL/g/min), and this difference was largely (approximately 90%) due to facilitated ACPC transport. Substantially higher K1ACPC values compared to corresponding K1DTPA values were also measured in C6 and RG2 gliomas. The deltaK1ACPC values for C6 glioma were more than twice that of contralateral brain cortex. K1ACPC and deltaK1ACPC values for RG2 gliomas was not significantly higher than that of contralateral cortex, although a approximately 2-fold difference in facilitated transport is obtained after normalization for differences in capillary surface area between RG2 tumors and contralateral cortex. K1ACPC, deltaK1ACPC, and K DTPA were directly related to tumor cell density, were higher in regions of "impending" necrosis, and the tumor/contralateral brain ACPC radio-activity ratios (0 to 10 minutes) were very similar to that obtained with 0 to 60 minutes experiments. These results indicate that facilitated transport of ACPC is upregulated across C6 and RG2 glioma capillaries, and that tumors can induce upregulation of amino acid transporter expression in their supporting vasculature. They also suggest that early imaging (e.g., 0 to 20 minutes) with radiolabeled amino acids in a clinical setting may be optimal for defining brain tumors.

Huntingtin interacting protein 1 is a novel brain tumor marker that associates with epidermal growth factor receptor.

PubMed

Bradley, Sarah V; Holland, Eric C; Liu, Grace Y; Thomas, Dafydd; Hyun, Teresa S; Ross, Theodora S

2007-04-15

Huntingtin interacting protein 1 (HIP1) is a multidomain oncoprotein whose expression correlates with increased epidermal growth factor receptor (EGFR) levels in certain tumors. For example, HIP1-transformed fibroblasts and HIP1-positive breast cancers have elevated EGFR protein levels. The combined association of HIP1 with huntingtin, the protein that is mutated in Huntington's disease, and the known overexpression of EGFR in glial brain tumors prompted us to explore HIP1 expression in a group of patients with different types of brain cancer. We report here that HIP1 is overexpressed with high frequency in brain cancers and that this overexpression correlates with EGFR and platelet-derived growth factor beta receptor expression. Furthermore, serum samples from patients with brain cancer contained anti-HIP1 antibodies more frequently than age-matched brain cancer-free controls. Finally, we report that HIP1 physically associates with EGFR and that this association is independent of the lipid, clathrin, and actin interacting domains of HIP1. These findings suggest that HIP1 may up-regulate or maintain EGFR overexpression in primary brain tumors by directly interacting with the receptor. This novel HIP1-EGFR interaction may work with or independent of HIP1 modulation of EGFR degradation via clathrin-mediated membrane trafficking pathways. Further investigation of HIP1 function in brain cancer biology and validation of its use as a prognostic or predictive brain tumor marker are now warranted.

Advanced age negatively impacts survival in an experimental brain tumor model.

PubMed

Ladomersky, Erik; Zhai, Lijie; Gritsina, Galina; Genet, Matthew; Lauing, Kristen L; Wu, Meijing; James, C David; Wainwright, Derek A

2016-09-06

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with an average age of 64 years at the time of diagnosis. To study GBM, a number of mouse brain tumor models have been utilized. In these animal models, subjects tend to range from 6 to 12 weeks of age, which is analogous to that of a human teenager. Here, we examined the impact of age on host immunity and the gene expression associated with immune evasion in immunocompetent mice engrafted with syngeneic intracranial GL261. The data indicate that, in mice with brain tumors, youth conveys an advantage to survival. While age did not affect the tumor-infiltrating T cell phenotype or quantity, we discovered that old mice express higher levels of the immunoevasion enzyme, IDO1, which was decreased by the presence of brain tumor. Interestingly, other genes associated with promoting immunosuppression including CTLA-4, PD-L1 and FoxP3, were unaffected by age. These data highlight the possibility that IDO1 contributes to faster GBM outgrowth with advanced age, providing rationale for future investigation into immunotherapeutic targeting in the future. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Episodic Memory Impairments in Primary Brain Tumor Patients.

PubMed

Durand, Thomas; Berzero, Giulia; Bompaire, Flavie; Hoffmann, Sabine; Léger, Isabelle; Jego, Virginie; Baruteau, Marie; Delgadillo, Daniel; Taillia, Hervé; Psimaras, Dimitri; Ricard, Damien

2018-01-04

Cognitive investigations in brain tumor patients have mostly explored episodic memory without differentiating between encoding, storage, and retrieval deficits. The aim of this study is to offer insight into the memory sub-processes affected in primary brain tumor patients and propose an appropriate assessment method. We retrospectively reviewed the clinical and memory assessments of 158 patients with primary brain tumors who had presented to our departments with cognitive complaints and were investigated using the Free and Cued Selective Reminding Test. Retrieval was the process of episodic memory most frequently affected, with deficits in this domain detected in 92% of patients with episodic memory impairments. Storage and encoding deficits were less prevalent, with impairments, respectively, detected in 41% and 23% of memory-impaired patients. The pattern of episodic memory impairment was similar across different tumor histologies and treatment modalities. Although all processes of episodic memory were found to be impaired, retrieval was by far the most widely affected function. A thorough assessment of all three components of episodic memory should be part of the regular neuropsychological evaluation in patients with primary brain tumors. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Raman spectroscopic imaging as complementary tool for histopathologic assessment of brain tumors

NASA Astrophysics Data System (ADS)

Krafft, Christoph; Bergner, Norbert; Romeike, Bernd; Reichart, Rupert; Kalff, Rolf; Geiger, Kathrin; Kirsch, Matthias; Schackert, Gabriele; Popp, Jürgen

2012-02-01

Raman spectroscopy enables label-free assessment of brain tissues and tumors based on their biochemical composition. Combination of the Raman spectra with the lateral information allows grading of tumors, determining the primary tumor of brain metastases and delineating tumor margins - even during surgery after coupling with fiber optic probes. This contribution presents exemplary Raman spectra and images collected from low grade and high grade regions of astrocytic gliomas and brain metastases. A region of interest in dried tissue sections encompassed slightly increased cell density. Spectral unmixing by vertex component analysis (VCA) and N-FINDR resolved cell nuclei in score plots and revealed the spectral contributions of nucleic acids, cholesterol, cholesterol ester and proteins in endmember signatures. The results correlated with the histopathological analysis after staining the specimens by hematoxylin and eosin. For a region of interest in non-dried, buffer immersed tissue sections image processing was not affected by drying artifacts such as denaturation of biomolecules and crystallization of cholesterol. Consequently, the results correspond better to in vivo situations. Raman spectroscopic imaging of a brain metastases from renal cell carcinoma showed an endmember with spectral contributions of glycogen which can be considered as a marker for this primary tumor.

Local control of brain metastases by stereotactic radiosurgery in relation to dose to the tumor margin.

PubMed

Vogelbaum, Michael A; Angelov, Lilyana; Lee, Shih-Yuan; Li, Liang; Barnett, Gene H; Suh, John H

2006-06-01

The maximal tolerated dose (MTD) for stereotactic radiosurgery (SRS) for brain tumors was established by the Radiation Therapy Oncology Group (RTOG) in protocol 90-05, which defined three dose groups based on the maximal tumor diameter. The goal in this retrospective study was to determine whether differences in doses to the margins of brain metastases affect the ability of SRS to achieve local control. Between 1997 and 2003, 202 patients harboring 375 tumors that met study entry criteria underwent SRS for treatment of one or multiple brain metastases. The median overall follow-up duration was 10.7 months (range 3-83 months). A dose of 24 Gy to the tumor margin had a significantly lower risk of local failure than 15 or 18 Gy (p = 0.0005; hazard ratio 0.277, confidence interval [CI] 0.134-0.573), whereas the 15- and 18-Gy groups were not significantly different from each other (p = 0.82) in this regard. The 1-year local control rate was 85% (95% CI 78-92%) in tumors treated with 24 Gy, compared with 49% (CI 30-68%) in tumors treated with 18 Gy and 45% (CI 23-67%) in tumors treated with 15 Gy. Overall patient survival was independent of dose to the tumor margin. Use of the RTOG 90-05 dosing scheme for brain metastases is associated with a variable local control rate. Tumors larger than 2 cm are less effectively controlled than smaller lesions, which can be safely treated with 24 Gy. Prospective evaluations of the relationship between dose to the tumor margin and local control should be performed to confirm these observations.

Wiring Pathways to Replace Aggression

ERIC Educational Resources Information Center

Bath, Howard

2006-01-01

The previous article in this series introduced the triune brain, the three components of which handle specialized life tasks. The survival brain, or brain stem, directs automatic physiological functions, such as heartbeat and breathing, and mobilizes fight/flight behaviour in times of threat. The emotional (or limbic) brain activates positive or…

Brain tumor modeling: glioma growth and interaction with chemotherapy

NASA Astrophysics Data System (ADS)

Banaem, Hossein Y.; Ahmadian, Alireza; Saberi, Hooshangh; Daneshmehr, Alireza; Khodadad, Davood

2011-10-01

In last decade increasingly mathematical models of tumor growths have been studied, particularly on solid tumors which growth mainly caused by cellular proliferation. In this paper we propose a modified model to simulate the growth of gliomas in different stages. Glioma growth is modeled by a reaction-advection-diffusion. We begin with a model of untreated gliomas and continue with models of polyclonal glioma following chemotherapy. From relatively simple assumptions involving homogeneous brain tissue bounded by a few gross anatomical landmarks (ventricles and skull) the models have been expanded to include heterogeneous brain tissue with different motilities of glioma cells in grey and white matter. Tumor growth is characterized by a dangerous change in the control mechanisms, which normally maintain a balance between the rate of proliferation and the rate of apoptosis (controlled cell death). Result shows that this model closes to clinical finding and can simulate brain tumor behavior properly.

Immunotherapy targeting immune check-point(s) in brain metastases.

PubMed

Di Giacomo, Anna Maria; Valente, Monica; Covre, Alessia; Danielli, Riccardo; Maio, Michele

2017-08-01

Immunotherapy with monoclonal antibodies (mAb) directed to different immune check-point(s) is showing a significant clinical impact in a growing number of human tumors of different histotype, both in terms of disease response and long-term survival patients. In this rapidly changing scenario, treatment of brain metastases remains an high unmeet medical need, and the efficacy of immunotherapy in these highly dismal clinical setting remains to be largely demonstrated. Nevertheless, up-coming observations are beginning to suggest a clinical potential of cancer immunotherapy also in brain metastases, regardless the underlying tumor histotype. These observations remain to be validated in larger clinical trials eventually designed also to address the efficacy of therapeutic mAb to immune check-point(s) within multimodality therapies for brain metastases. Noteworthy, the initial proofs of efficacy on immunotherapy in central nervous system metastases are already fostering clinical trials investigating its therapeutic potential also in primary brain tumors. We here review ongoing immunotherapeutic approaches to brain metastases and primary brain tumors, and the foreseeable strategies to overcome their main biologic hurdles and clinical challenges. Copyright © 2017 Elsevier Ltd. All rights reserved.

Delineating Normal from Diseased Brain by Aminolevulinic Acid-Induced Fluorescence

NASA Astrophysics Data System (ADS)

Stepp, Herbert; Stummer, Walter

5-Aminolevulinic acid (5-ALA) as a precursor of protoporphyrin IX (PpIX) has been established as an orally applied drug to guide surgical resection of malignant brain tumors by exciting the red fluorescence of PpIX. The accumulation of PpIX in glioblastoma multiforme (GBM) is highly selective and provides excellent contrast to normal brain when using surgical microscopes with appropriately filtered light sources and cameras. The positive predictive value of fluorescent tissue is very high, enabling safe gross total resection of GBM and other brain tumors and improving prognosis of patients. Compared to other intraoperative techniques that have been developed with the aim of increasing the rate of safe gross total resections of malignant gliomas, PpIX fluorescence is considerably simpler, more cost effective, and comparably reliable. We present the basics of 5-ALA-based fluorescence-guided resection, and discuss the clinical results obtained for GBM and the experience with the fluorescence staining of other primary brain tumors and metastases as well as the results for spinal cord tumors. The phototoxicity of PpIX, increasingly used for photodynamic therapy of brain tumors, is mentioned briefly in this chapter.

Emerging Applications of Therapeutic Ultrasound in Neuro-oncology: Moving Beyond Tumor Ablation.

PubMed

Hersh, David S; Kim, Anthony J; Winkles, Jeffrey A; Eisenberg, Howard M; Woodworth, Graeme F; Frenkel, Victor

2016-11-01

: Transcranial focused ultrasound (FUS) can noninvasively transmit acoustic energy with a high degree of accuracy and safety to targets and regions within the brain. Technological advances, including phased-array transducers and real-time temperature monitoring with magnetic resonance thermometry, have created new opportunities for FUS research and clinical translation. Neuro-oncology, in particular, has become a major area of interest because FUS offers a multifaceted approach to the treatment of brain tumors. FUS has the potential to generate cytotoxicity within tumor tissue, both directly via thermal ablation and indirectly through radiosensitization and sonodynamic therapy; to enhance the delivery of therapeutic agents to brain tumors by transiently opening the blood-brain barrier or improving distribution through the brain extracellular space; and to modulate the tumor microenvironment to generate an immune response. In this review, we describe each of these applications for FUS, the proposed mechanisms of action, and the preclinical and clinical studies that have set the foundation for using FUS in neuro-oncology. BBB, blood-brain barrierCED, convection-enhanced delivery5-Ala, 5-aminolevulinic acidFUS, focused ultrasoundGBM, glioblastoma multiformeHSP, heat shock proteinMRgFUS, magnetic resonance-guided focused ultrasoundpFUS, pulsed focused ultrasound.

History and current state of immunotherapy in glioma and brain metastasis.

PubMed

McGranahan, Tresa; Li, Gordon; Nagpal, Seema

2017-05-01

Malignant brain tumors such as glioblastoma (GBM) and brain metastasis have poor prognosis despite conventional therapies. Successful use of vaccines and checkpoint inhibitors in systemic malignancy has increased the hope that immune therapies could improve survival in patients with brain tumors. Manipulating the immune system to fight malignancy has a long history of both modest breakthroughs and pitfalls that should be considered when applying the current immunotherapy approaches to patients with brain tumors. Therapeutic vaccine trials for GBM date back to the mid 1900s and have taken many forms; from irradiated tumor lysate to cell transfer therapies and peptide vaccines. These therapies were generally well tolerated without significant autoimmune toxicity, however also did not demonstrate significant clinical benefit. In contrast, the newer checkpoint inhibitors have demonstrated durable benefit in some metastatic malignancies, accompanied by significant autoimmune toxicity. While this toxicity was not unexpected, it exceeded what was predicted from pre-clinical studies and in many ways was similar to the prior trials of immunostimulants. This review will discuss the history of these studies and demonstrate that the future use of immune therapy for brain tumors will likely need a personalized approach that balances autoimmune toxicity with the opportunity for significant survival benefit.

Role of Caspase-9 Gene Ex5+32 G>A (rs1052576) Variant in Susceptibility to Primary Brain Tumors.

PubMed

Ozdogan, Selcuk; Kafadar, Ali; Yilmaz, Seda Gulec; Timirci-Kahraman, Ozlem; Gormus, Uzay; Isbir, Turgay

2017-09-01

This study is the first to evaluate the relationship of caspase-9 (CASP-9) gene polymorphism with the risk for primary brain tumor development. The study group included 43 glioma and 27 meningioma patients and 76 healthy individuals. CASP-9 gene Ex5+32 G>A (rs1052576) polymorphism was analyzed by real-time polymerase chain reaction (RT-PCR). Individuals with the CASP-9 GG genotype had significantly decreased risk of developing a glioma brain tumor (p=0.024). Additionally, the GA genotype was significantly lower in patients with glioma than the control group (p=0.019). A significantly decreased risk of developing glioma was found in the A allele carrier group (p=0.024). However, there was no statistically significant relationship between CASP-9 polymorphism and brain meningioma (p=0.493). CASP-9 (rs1052576) mutant A allele seems to be a protective factor for glioma brain tumor. Future studies with a larger sample size will clarify the possible roles of CASP-9 gene in the etiology and progression of primary brain tumors. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Plexiform neurofibroma tissue classification

NASA Astrophysics Data System (ADS)

Weizman, L.; Hoch, L.; Ben Sira, L.; Joskowicz, L.; Pratt, L.; Constantini, S.; Ben Bashat, D.

2011-03-01

Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NF1), a common genetic disease that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the nerve in various parts of the body. Treatment decision is based on tumor volume assessment using MRI, which is currently time consuming and error prone, with limited semi-automatic segmentation support. We present in this paper a new method for the segmentation and tumor mass quantification of PN from STIR MRI scans. The method starts with a user-based delineation of the tumor area in a single slice and automatically detects the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets yield a mean volume overlap difference of 25% as compared to manual segmentation by expert radiologist with a mean computation and interaction time of 12 minutes vs. over an hour for manual annotation. Since the user interaction in the segmentation process is minimal, our method has the potential to successfully become part of the clinical workflow.

Development of an autofluorescent probe designed to help brain tumor removal: study on an animal model

NASA Astrophysics Data System (ADS)

Siebert, R.; Leh, B.; Charon, Y.; Collado-Hilly, M.; Duval, M.-A.; Menard, L.; Monnet, F. P.; Varlet, P.

2010-02-01

The complete resection of the brain tumour is crucial to the patient life quality and prognosis. An autofluorescence probe aiming at helping the surgeon to improve the completeness of the removal is being developed. Autofluorescence spectroscopy is a promising approach to define whether the tissue is cancerous or not. First ex vivo measurements have been realised on an animal model. After tumorous cell injection in rat brain, autofluorescence intensity is revealed from the extracted brain. These autofluorescence data are compared to results from a histological analysis of same brains. First indicators are identified that may have the ability to differentiate tumorous and healthy tissues.

Robust augmented reality registration method for localization of solid organs' tumors using CT-derived virtual biomechanical model and fluorescent fiducials.

PubMed

Kong, Seong-Ho; Haouchine, Nazim; Soares, Renato; Klymchenko, Andrey; Andreiuk, Bohdan; Marques, Bruno; Shabat, Galyna; Piechaud, Thierry; Diana, Michele; Cotin, Stéphane; Marescaux, Jacques

2017-07-01

Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials. Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials. Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images. Our preliminary experiments showed the potential of a biomechanical model with fluorescent fiducials to propagate the deformation of solid organs' surface to their inner structures including tumors with good accuracy and automatized robust tracking.

[A Case of Subcortical Intracerebral Hemorrhage Caused by Underlying Oligodendroglioma Diagnosed through Long-Term Follow-Up].

PubMed

Kidoguchi, Masamune; Isozaki, Makoto; Hirose, Satoshi; Kitai, Ryuhei; Kikuta, Ken-Ichiro

2017-03-01

We report on a case of an oligodendroglioma that caused intracerebral hemorrhage, which was diagnosed by long-term follow-up. An 82-year-old man with underlying hypertrophic cardiomyopathy presented with weakness in the right upper extremity. Computed tomography and magnetic resonance imaging(MRI)showed intracerebral hemorrhage and focal brain edema. Since there was a discrepancy between hematoma and focal brain edema, we first diagnosed cardiogenic cerebral embolism. Six months later, MRI results showed an improvement of the brain edema; however, the lesion developed after a year. We suspected that this lesion included a brain tumor and performed an open surgical biopsy. Pathological examination revealed that the tumor was an oligodendroglioma(World Health Organization grade 2). Because brain tumors that are complicated with intratumoral bleeding are often highly malignant and the lesions gradually increase in size, it is relatively easy to make a precise diagnosis. However, in low-grade gliomas, the intracerebral hemorrhage and brain edema may occasionally improve in the short term. We show that a case with a discrepancy between hematoma and brain edema should be followed up for at least more than a year, even when initial MRI does not reveal a brain tumor .

Brain Tumors - Multiple Languages

MedlinePlus

... FAQs Customer Support Health Topics Drugs & Supplements Videos & Tools You Are Here: Home → Multiple Languages → All Health Topics → Brain Tumors URL of this page: https://medlineplus.gov/ ...

Systemic treatments for brain metastases from breast cancer, non-small cell lung cancer, melanoma and renal cell carcinoma: an overview of the literature.

PubMed

Lombardi, Giuseppe; Di Stefano, Anna Luisa; Farina, Patrizia; Zagonel, Vittorina; Tabouret, Emeline

2014-09-01

The frequency of metastatic brain tumors has increased over recent years; the primary tumors most involved are breast cancer, lung cancer, melanoma and renal cell carcinoma. While radiation therapy and surgery remain the mainstay treatment in selected patients, new molecular drugs have been developed for brain metastases. Studies so far report interesting results. This review focuses on systemic cytotoxic drugs and, in particular, on new targeted therapies and their clinically relevant activities in brain metastases from solid tumors in adults. Copyright © 2014 Elsevier Ltd. All rights reserved.

Complete prevalence of malignant primary brain tumors registry data in the United States compared with other common cancers, 2010

PubMed Central

Zhang, Adah S.; Ostrom, Quinn T.; Kruchko, Carol; Rogers, Lisa; Peereboom, David M.

2017-01-01

Abstract Background. Complete prevalence proportions illustrate the burden of disease in a population. This study estimates the 2010 complete prevalence of malignant primary brain tumors overall and by Central Brain Tumor Registry of the United States (CBTRUS) histology groups, and compares the brain tumor prevalence estimates to the complete prevalence of other common cancers as determined by the Surveillance, Epidemiology, and End Results Program (SEER) by age at prevalence (2010): children (0–14 y), adolescent and young adult (AYA) (15–39 y), and adult (40+ y). Methods. Complete prevalence proportions were estimated using a novel regression method extended from the Completeness Index Method, which combines survival and incidence data from multiple sources. In this study, two datasets, CBTRUS and SEER, were used to calculate complete prevalence estimates of interest. Results. Complete prevalence for malignant primary brain tumors was 47.59/100000 population (22.31, 48.49, and 57.75/100000 for child, AYA, and adult populations). The most prevalent cancers by age were childhood leukemia (36.65/100000), AYA melanoma of the skin (66.21/100000), and adult female breast (1949.00/100000). The most prevalent CBTRUS histologies in children and AYA were pilocytic astrocytoma (6.82/100000, 5.92/100000), and glioblastoma (12.76/100000) in adults. Conclusions. The relative impact of malignant primary brain tumors is higher among children than any other age group; it emerges as the second most prevalent cancer among children. Complete prevalence estimates for primary malignant brain tumors fills a gap in overall cancer knowledge, which provides critical information toward public health and health care planning, including treatment, decision making, funding, and advocacy programs. PMID:28039365

Mobile phones, cordless phones and rates of brain tumors in different age groups in the Swedish National Inpatient Register and the Swedish Cancer Register during 1998-2015.

PubMed

Hardell, Lennart; Carlberg, Michael

2017-01-01

We used the Swedish Inpatient Register (IPR) to analyze rates of brain tumors of unknown type (D43) during 1998-2015. Average Annual Percentage Change (AAPC) per 100,000 increased with +2.06%, 95% confidence interval (CI) +1.27, +2.86% in both genders combined. A joinpoint was found in 2007 with Annual Percentage Change (APC) 1998-2007 of +0.16%, 95% CI -0.94, +1.28%, and 2007-2015 of +4.24%, 95% CI +2.87, +5.63%. Highest AAPC was found in the age group 20-39 years. In the Swedish Cancer Register the age-standardized incidence rate per 100,000 increased for brain tumors, ICD-code 193.0, during 1998-2015 with AAPC in men +0.49%, 95% CI +0.05, +0.94%, and in women +0.33%, 95% CI -0.29, +0.45%. The cases with brain tumor of unknown type lack morphological examination. Brain tumor diagnosis was based on cytology/histopathology in 83% for men and in 87% for women in 1980. This frequency increased to 90% in men and 88% in women in 2015. During the same time period CT and MRI imaging techniques were introduced and morphology is not always necessary for diagnosis. If all brain tumors based on clinical diagnosis with CT or MRI had been reported to the Cancer Register the frequency of diagnoses based on cytology/histology would have decreased in the register. The results indicate underreporting of brain tumor cases to the Cancer Register. The real incidence would be higher. Thus, incidence trends based on the Cancer Register should be used with caution. Use of wireless phones should be considered in relation to the change of incidence rates.

Confronting pediatric brain tumors: parent stories.

PubMed

McMillan, Gigi

2014-01-01

This narrative symposium brings to light the extreme difficulties faced by parents of children diagnosed with brain tumors. NIB editorial staff and narrative symposium editors, Gigi McMillan and Christy A. Rentmeester, developed a call for stories that was distributed on several list serves and posted on Narrative Inquiry in Bioethics' website. The call asks parents to share their personal experience of diagnosis, treatment, long-term effects of treatment, social issues and the doctor-patient-parent dynamic that develops during this process. Thirteen stories are found in the print version of the journal and an additional six supplemental stories are published online only through Project MUSE. One change readers may notice is that the story authors are not listed in alphabetical order. The symposium editors had a vision for this issue that included leading readers through the timeline of this topic: diagnosis-treatment-acute recovery-recurrence-treatment (again)-acute recovery (again)-long-term quality of life-(possibly) end of life. Stories are arranged to help lead the reader through this timeline.Gigi McMillan is a patient and research subject advocate, co-founder of We Can, Pediatric Brain Tumor Network, as well as, the mother of a child who suffered from a pediatric brain tumor. She also authored the introduction for this symposium. Christy Rentmeester is an Associate Professor of Health Policy and Ethics in the Creighton University School of Medicine. She served as a commentator for this issue. Other commentators for this issue are Michael Barraza, a clinical psychologist and board member of We Can, Pediatric Brain Tumor Network; Lisa Stern, a pediatrician who has diagnosed six children with brain tumors in her 20 years of practice; and Katie Rose, a pediatric brain tumor patient who shares her special insights about this world.

Cancer-specific health-related quality of life in children with brain tumors.

PubMed

Sato, Iori; Higuchi, Akiko; Yanagisawa, Takaaki; Mukasa, Akitake; Ida, Kohmei; Sawamura, Yutaka; Sugiyama, Kazuhiko; Saito, Nobuhito; Kumabe, Toshihiro; Terasaki, Mizuhiko; Nishikawa, Ryo; Ishida, Yasushi; Kamibeppu, Kiyoko

2014-05-01

To understand the influence of disease and treatment on the health-related quality of life (HRQOL) of children with brain tumors, compared to the HRQOL of children with other cancers, from the viewpoints of children and parents. A total of 133 children aged 5-18 years and 165 parents of children aged 2-18 completed questionnaires of the Pediatric Quality of Life Inventory Cancer Module (Pain and Hurt, Nausea, Procedural Anxiety, Treatment Anxiety, Worry, Cognitive Problems, Perceived Physical Appearance, and Communication scales); higher scores indicate a better HRQOL. The Cancer Module scores, weighted by age and treatment status, were compared to those obtained in a previous study of children with other cancers (mostly leukemia). The weighted mean scores for Pain and Hurt (effect size d = 0.26) and Nausea (d = 0.23) from child reports and the scores for Nausea (d = 0.28) from parent reports were higher for children with brain tumors than scores for children with other cancers. The scores for Procedural Anxiety (d = -0.22) and Treatment Anxiety (d = -0.32) from parent reports were lower for parents of children with brain tumors than the scores for parents of children with other cancers. The child-reported Pain and Hurt score of the Cancer Module was higher (d = 0.29) and in less agreement (intraclass correlation coefficient = 0.43) with scores from the Brain Tumor Module, indicating that assessments completed with the Cancer Module misesteem pain and hurt problems in children with brain tumors. The profiles of cancer-specific HRQOL in children with brain tumors differ from those of children with other cancers; we therefore suggest that these children receive specific psychological support.

Imaging the delivery of brain-penetrating PLGA nanoparticles in the brain using magnetic resonance.

PubMed

Strohbehn, Garth; Coman, Daniel; Han, Liang; Ragheb, Ragy R T; Fahmy, Tarek M; Huttner, Anita J; Hyder, Fahmeed; Piepmeier, Joseph M; Saltzman, W Mark; Zhou, Jiangbing

2015-02-01

Current therapy for glioblastoma multiforme (GBM) is largely ineffective, with nearly universal tumor recurrence. The failure of current therapy is primarily due to the lack of approaches for the efficient delivery of therapeutics to diffuse tumors in the brain. In our prior study, we developed brain-penetrating nanoparticles that are capable of penetrating brain tissue and distribute over clinically relevant volumes when administered via convection-enhanced delivery (CED). We demonstrated that these particles are capable of efficient delivery of chemotherapeutics to diffuse tumors in the brain, indicating that they may serve as a groundbreaking approach for the treatment of GBM. In the original study, nanoparticles in the brain were imaged using positron emission tomography (PET). However, clinical translation of this delivery platform can be enabled by engineering a non-invasive detection modality using magnetic resonance imaging (MRI). For this purpose, we developed chemistry to incorporate superparamagnetic iron oxide (SPIO) into the brain-penetrating nanoparticles. We demonstrated that SPIO-loaded nanoparticles, which retain the same morphology as nanoparticles without SPIO, have an excellent transverse (T(2)) relaxivity. After CED, the distribution of nanoparticles in the brain (i.e., in the vicinity of injection site) can be detected using MRI and the long-lasting signal attenuation of SPIO-loaded brain-penetrating nanoparticles lasted over a one-month timecourse. Development of these nanoparticles is significant as, in future clinical applications, co-administration of SPIO-loaded nanoparticles will allow for intraoperative monitoring of particle distribution in the brain to ensure drug-loaded nanoparticles reach tumors as well as for monitoring the therapeutic benefit with time and to evaluate tumor relapse patterns.

Annual report to the nation on the status of cancer, 1975-2007, featuring tumors of the brain and other nervous system.

PubMed

Kohler, Betsy A; Ward, Elizabeth; McCarthy, Bridget J; Schymura, Maria J; Ries, Lynn A G; Eheman, Christie; Jemal, Ahmedin; Anderson, Robert N; Ajani, Umed A; Edwards, Brenda K

2011-05-04

The American Cancer Society, the Centers for Disease Control and Prevention (CDC), the National Cancer Institute, and the North American Association of Central Cancer Registries (NAACCR) collaborate annually to provide updated information on cancer occurrence and trends in the United States. This year's report highlights brain and other nervous system (ONS) tumors, including nonmalignant brain tumors, which became reportable on a national level in 2004. Cancer incidence data were obtained from the National Cancer Institute, CDC, and NAACCR, and information on deaths was obtained from the CDC's National Center for Health Statistics. The annual percentage changes in age-standardized incidence and death rates (2000 US population standard) for all cancers combined and for the top 15 cancers for men and for women were estimated by joinpoint analysis of long-term (1992-2007 for incidence; 1975-2007 for mortality) trends and short-term fixed interval (1998-2007) trends. Analyses of malignant neuroepithelial brain and ONS tumors were based on data from 1980-2007; data on nonmalignant tumors were available for 2004-2007. All statistical tests were two-sided. Overall cancer incidence rates decreased by approximately 1% per year; the decrease was statistically significant (P < .05) in women, but not in men, because of a recent increase in prostate cancer incidence. The death rates continued to decrease for both sexes. Childhood cancer incidence rates continued to increase, whereas death rates continued to decrease. Lung cancer death rates decreased in women for the first time during 2003-2007, more than a decade after decreasing in men. During 2004-2007, more than 213 500 primary brain and ONS tumors were diagnosed, and 35.8% were malignant. From 1987-2007, the incidence of neuroepithelial malignant brain and ONS tumors decreased by 0.4% per year in men and women combined. The decrease in cancer incidence and mortality reflects progress in cancer prevention, early detection, and treatment. However, major challenges remain, including increasing incidence rates and continued low survival for some cancers. Malignant and nonmalignant brain tumors demonstrate differing patterns of occurrence by sex, age, and race, and exhibit considerable biologic diversity. Inclusion of nonmalignant brain tumors in cancer registries provides a fuller assessment of disease burden and medical resource needs associated with these unique tumors.

Multiclass feature selection for improved pediatric brain tumor segmentation

NASA Astrophysics Data System (ADS)

Ahmed, Shaheen; Iftekharuddin, Khan M.

2012-03-01

In our previous work, we showed that fractal-based texture features are effective in detection, segmentation and classification of posterior-fossa (PF) pediatric brain tumor in multimodality MRI. We exploited an information theoretic approach such as Kullback-Leibler Divergence (KLD) for feature selection and ranking different texture features. We further incorporated the feature selection technique with segmentation method such as Expectation Maximization (EM) for segmentation of tumor T and non tumor (NT) tissues. In this work, we extend the two class KLD technique to multiclass for effectively selecting the best features for brain tumor (T), cyst (C) and non tumor (NT). We further obtain segmentation robustness for each tissue types by computing Bay's posterior probabilities and corresponding number of pixels for each tissue segments in MRI patient images. We evaluate improved tumor segmentation robustness using different similarity metric for 5 patients in T1, T2 and FLAIR modalities.

Metabolic brain imaging correlated with clinical features of brain tumors

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

Alavi, J.; Alavi, A.; Dann, R.

1985-05-01

Nineteen adults with brain tumors have been studied with positron emission tomography utilizing FDG. Fourteen had biopsy proven cerebral malignant glioma, one each had meningioma, hemangiopericytoma, primitive neuroectodermal tumor (PNET), two had unbiopsied lesions, and one patient had an area of biopsy proven radiation necrosis. Three different patterns of glucose metabolism are observed: marked increase in metabolism at the site of the known tumor in (10 high grade gliomas and the PNET), lower than normal metabolism at the tumor (in 1 grade II glioma, 3 grade III gliomas, 2 unbiopsied low density nonenhancing lesions, and the meningioma), no abnormality (1more » enhancing glioma, the hemangiopericytoma and the radiation necrosis.) The metabolic rate of the tumor or the surrounding brain did not appear to be correlated with the history of previous irradiation or chemotherapy. Decreased metabolism was frequently observed in the rest of the affected hemisphere and in the contralateral cerebellum. Tumors of high grade or with enhancing CT characteristics were more likely to show increased metabolism. Among the patients with proven gliomas, survival after PETT scan tended to be longer for those with low metabolic activity tumors than for those with highly active tumors. The authors conclude that PETT may help to predict the malignant potential of tumors, and may add useful clinical information to the CT scan.« less

Neurocognitive status in patients with newly-diagnosed brain tumors in good neurological condition: The impact of tumor type, volume, and location.

PubMed

Hendrix, Philipp; Hans, Elisa; Griessenauer, Christoph J; Simgen, Andreas; Oertel, Joachim; Karbach, Julia

2017-05-01

Neurocognitive function is of great importance in patients with brain tumors. Even patients in good neurological condition may suffer from neurocognitive dysfunction that affects their daily living. The purpose of the present study was to identify risk factors for neurocognitive dysfunction in patients suffering from common supratentorial brain tumors with minor neurological deficits. A prospective study evaluating neurocognitive dysfunction in patients with a newly-diagnosed brain tumor in good neurological condition was performed at a major German academic institution. Patients underwent extensive neurocognitive testing assessing perceptual speed, executive function, visual-spatial and verbal working memory, short- and long-term memory, verbal fluency, fluid intelligence, anxiety, and depression. For each patient, a healthy control was pair-matched based on age, sex, handedness, and profession. A total of 46 patients and 46 healthy controls underwent neurocognitive testing. Patients suffered from glioblastoma multiforme (10), cerebral metastasis (10), pituitary adenoma (13), or meningioma (13). There was neither any difference in age, educational level, fluid intelligence, neurological deficits, and anxiety nor in any depression scores between tumor subgroups. Overall, neurocognitive performance was significantly worse in patients compared to healthy controls. Larger tumor volume, frontal location, and left/dominant hemisphere were associated with worse executive functioning and verbal fluency. Additionally, larger tumors and left/dominant location correlated with impairments on perceptual speed tasks. Frontal tumor location was related to worse performance in visual-spatial and short- and long-term memory. Tumor type, clinical presentation, and patient self-awareness were not associated with specific neurocognitive impairments. Patients suffering from newly-diagnosed brain tumors presenting in good neurological condition display neurocognitive impairments in various domains. Larger tumor volumes, frontal location, and left/dominant hemisphere are important predictors for potential neurocognitive deficits. Tumor type, clinical presentation, or self-awareness are less significant at the time of diagnosis. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic T1 bladder tumor detection by using wavelet analysis in cystoscopy images

NASA Astrophysics Data System (ADS)

Freitas, Nuno R.; Vieira, Pedro M.; Lima, Estevão; Lima, Carlos S.

2018-02-01

Correct classification of cystoscopy images depends on the interpreter’s experience. Bladder cancer is a common lesion that can only be confirmed by biopsying the tissue, therefore, the automatic identification of tumors plays a significant role in early stage diagnosis and its accuracy. To our best knowledge, the use of white light cystoscopy images for bladder tumor diagnosis has not been reported so far. In this paper, a texture analysis based approach is proposed for bladder tumor diagnosis presuming that tumors change in tissue texture. As is well accepted by the scientific community, texture information is more present in the medium to high frequency range which can be selected by using a discrete wavelet transform (DWT). Tumor enhancement can be improved by using automatic segmentation, since a mixing with normal tissue is avoided under ideal conditions. The segmentation module proposed in this paper takes advantage of the wavelet decomposition tree to discard poor texture information in such a way that both steps of the proposed algorithm segmentation and classification share the same focus on texture. Multilayer perceptron and a support vector machine with a stratified ten-fold cross-validation procedure were used for classification purposes by using the hue-saturation-value (HSV), red-green-blue, and CIELab color spaces. Performances of 91% in sensitivity and 92.9% in specificity were obtained regarding HSV color by using both preprocessing and classification steps based on the DWT. The proposed method can achieve good performance on identifying bladder tumor frames. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis.

(18)F-fluoromisonidazole positron emission tomography can predict pathological necrosis of brain tumors.

PubMed

Toyonaga, Takuya; Hirata, Kenji; Yamaguchi, Shigeru; Hatanaka, Kanako C; Yuzawa, Sayaka; Manabe, Osamu; Kobayashi, Kentaro; Watanabe, Shiro; Shiga, Tohru; Terasaka, Shunsuke; Kobayashi, Hiroyuki; Kuge, Yuji; Tamaki, Nagara

2016-07-01

Tumor necrosis is one of the indicators of tumor aggressiveness. (18)F-fluoromisonidazole (FMISO) is the most widely used positron emission tomography (PET) tracer to evaluate severe hypoxia in vivo. Because severe hypoxia causes necrosis, we hypothesized that intratumoral necrosis can be detected by FMISO PET in brain tumors regardless of their histopathology. We applied FMISO PET to various types of brain tumors before tumor resection and evaluated the correlation between histopathological necrosis and FMISO uptake. This study included 59 brain tumor patients who underwent FMISO PET/computed tomography before any treatments. According to the pathological diagnosis, the brain tumors were divided into three groups: astrocytomas (group 1), neuroepithelial tumors except for astrocytomas (group 2), and others (group 3). Two experienced neuropathologists evaluated the presence of necrosis in consensus. FMISO uptake in the tumor was evaluated visually and semi-quantitatively using the tumor-to-normal cerebellum ratio (TNR). In visual analyses, 26/27 cases in the FMISO-positive group presented with necrosis, whereas 28/32 cases in the FMISO-negative group did not show necrosis. Mean TNRs with and without necrosis were 3.49 ± 0.97 and 1.43 ± 0.42 (p < 0.00001) in group 1, 2.91 ± 0.83 and 1.44 ± 0.20 (p < 0.005) in group 2, and 2.63 ± 1.16 and 1.35 ± 0.23 (p < 0.05) in group 3, respectively. Using a cut-off value of TNR = 1.67, which was calculated by normal reference regions of interest, we could predict necrosis with sensitivity, specificity, and accuracy of 96.7, 93.1, and 94.9 %, respectively. FMISO uptake within the lesion indicated the presence of histological micro-necrosis. When we used a TNR of 1.67 as the cut-off value, intratumoral micro-necrosis was sufficiently predictable. Because the presence of necrosis implies a poor prognosis, our results suggest that FMISO PET could provide important information for treatment decisions or surgical strategies of any type of brain tumor.

Neuroprotective effects of vagus nerve stimulation on traumatic brain injury

PubMed Central

Zhou, Long; Lin, Jinhuang; Lin, Junming; Kui, Guoju; Zhang, Jianhua; Yu, Yigang

2014-01-01

Previous studies have shown that vagus nerve stimulation can improve the prognosis of traumatic brain injury. The aim of this study was to elucidate the mechanism of the neuroprotective effects of vagus nerve stimulation in rabbits with brain explosive injury. Rabbits with brain explosive injury received continuous stimulation (10 V, 5 Hz, 5 ms, 20 minutes) of the right cervical vagus nerve. Tumor necrosis factor-α, interleukin-1β and interleukin-10 concentrations were detected in serum and brain tissues, and water content in brain tissues was measured. Results showed that vagus nerve stimulation could reduce the degree of brain edema, decrease tumor necrosis factor-α and interleukin-1β concentrations, and increase interleukin-10 concentration after brain explosive injury in rabbits. These data suggest that vagus nerve stimulation may exert neuroprotective effects against explosive injury via regulating the expression of tumor necrosis factor-α, interleukin-1β and interleukin-10 in the serum and brain tissue. PMID:25368644

Automatic delineation of tumor volumes by co-segmentation of combined PET/MR data

NASA Astrophysics Data System (ADS)

Leibfarth, S.; Eckert, F.; Welz, S.; Siegel, C.; Schmidt, H.; Schwenzer, N.; Zips, D.; Thorwarth, D.

2015-07-01

Combined PET/MRI may be highly beneficial for radiotherapy treatment planning in terms of tumor delineation and characterization. To standardize tumor volume delineation, an automatic algorithm for the co-segmentation of head and neck (HN) tumors based on PET/MR data was developed. Ten HN patient datasets acquired in a combined PET/MR system were available for this study. The proposed algorithm uses both the anatomical T2-weighted MR and FDG-PET data. For both imaging modalities tumor probability maps were derived, assigning each voxel a probability of being cancerous based on its signal intensity. A combination of these maps was subsequently segmented using a threshold level set algorithm. To validate the method, tumor delineations from three radiation oncologists were available. Inter-observer variabilities and variabilities between the algorithm and each observer were quantified by means of the Dice similarity index and a distance measure. Inter-observer variabilities and variabilities between observers and algorithm were found to be comparable, suggesting that the proposed algorithm is adequate for PET/MR co-segmentation. Moreover, taking into account combined PET/MR data resulted in more consistent tumor delineations compared to MR information only.

Reduced tumorigenicity of rat glioma cells in the brain when mediated by hygromycin phosphotransferase.

PubMed

Hormigo, A; Friedlander, D R; Brittis, P A; Zagzag, D; Grumet, M

2001-04-01

A variant of C6 glioma cells, C6R-G/H cells express hygromycin phosphotransferase (HPT) and appear to have reduced tumorigenicity in the embryonic brain. The goal of this study was to investigate their reduced capacity to generate tumors in the adult rat brain. Cell lines were implanted into rat brains and tumorigenesis was evaluated. After 3 weeks, all rats with C6 cells showed signs of neurological disease, whereas rats with C6R-G/H cells did not and were either killed then or allowed to survive until later. Histological studies were performed to analyze tumor size, malignancy, angiogenesis, and cell proliferation. Cells isolated from rat brain tumors were analyzed for mutation to HPT by testing their sensitivity to hygromycin. The results indicate that HPT suppresses tumor formation. Three weeks after implantation, only 44% of animals implanted with C6R-G/H cells developed tumors, whereas all animals that received C6 glioma cells developed high-grade gliomas. The C6R-G/H cells filled a 20-fold smaller maximal cross-sectional area than the C6 cells, and exhibited less malignant characteristics, including reduced angiogenesis, mitosis, and cell proliferation. Similar results were obtained in the brain of nude rats, indicating that the immune system did not play a significant role in suppressing tumor growth. The combination of green fluorescent protein (GFP) and HPT was more effective in suppressing tumorigenesis than either plasmid by itself, indicating that the GFP may protect against inactivation of the HPT. Interestingly. hygromycin resistance was lost in tumor cells that were recovered from a group of animals in which C6R-G/H cells formed tumors, confirming the correlation of HPT with reduced tumorigenicity.