Brain Imaging in Alzheimer Disease

PubMed Central

Johnson, Keith A.; Fox, Nick C.; Sperling, Reisa A.; Klunk, William E.

2012-01-01

Imaging has played a variety of roles in the study of Alzheimer disease (AD) over the past four decades. Initially, computed tomography (CT) and then magnetic resonance imaging (MRI) were used diagnostically to rule out other causes of dementia. More recently, a variety of imaging modalities including structural and functional MRI and positron emission tomography (PET) studies of cerebral metabolism with fluoro-deoxy-d-glucose (FDG) and amyloid tracers such as Pittsburgh Compound-B (PiB) have shown characteristic changes in the brains of patients with AD, and in prodromal and even presymptomatic states that can help rule-in the AD pathophysiological process. No one imaging modality can serve all purposes as each have unique strengths and weaknesses. These modalities and their particular utilities are discussed in this article. The challenge for the future will be to combine imaging biomarkers to most efficiently facilitate diagnosis, disease staging, and, most importantly, development of effective disease-modifying therapies. PMID:22474610

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

A Review of Multivariate Methods for Multimodal Fusion of Brain Imaging Data

PubMed Central

Adali, Tülay; Yu, Qingbao; Calhoun, Vince D.

2011-01-01

The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure. However, despite improvements in individual modalities, it is becoming increasingly clear that the most effective research approaches will utilize multi-modal fusion, which takes advantage of the fact that each modality provides a limited view of the brain. The goal of multimodal fusion is to capitalize on the strength of each modality in a joint analysis, rather than a separate analysis of each. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. Numerous research efforts have been reported in the field based on various statistical approaches, e.g. independent component analysis (ICA), canonical correlation analysis (CCA) and partial least squares (PLS). In this review paper, we survey a number of multivariate methods appearing in previous reports, which are performed with or without prior information and may have utility for identifying potential brain illness biomarkers. We also discuss the possible strengths and limitations of each method, and review their applications to brain imaging data. PMID:22108139

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

PubMed Central

Goscinski, Wojtek J.; McIntosh, Paul; Felzmann, Ulrich; Maksimenko, Anton; Hall, Christopher J.; Gureyev, Timur; Thompson, Darren; Janke, Andrew; Galloway, Graham; Killeen, Neil E. B.; Raniga, Parnesh; Kaluza, Owen; Ng, Amanda; Poudel, Govinda; Barnes, David G.; Nguyen, Toan; Bonnington, Paul; Egan, Gary F.

2014-01-01

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. PMID:24734019

Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

PubMed

Prastawa, Marcel; Bullitt, Elizabeth; Gerig, Guido

2009-04-01

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

PubMed

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Q.; Culver, Joseph P.; Wang, Lihong V.

2014-03-01

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer's, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging.

Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation.

PubMed

Eytan, Danny; Pang, Elizabeth W; Doesburg, Sam M; Nenadovic, Vera; Gavrilovic, Bojan; Laussen, Peter; Guerguerian, Anne-Marie

2016-01-01

Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.

Brain activation during neurocognitive testing using functional near-infrared spectroscopy in patients following concussion compared to healthy controls.

PubMed

Kontos, A P; Huppert, T J; Beluk, N H; Elbin, R J; Henry, L C; French, J; Dakan, S M; Collins, M W

2014-12-01

There is no accepted clinical imaging modality for concussion, and current imaging modalities including fMRI, DTI, and PET are expensive and inaccessible to most clinics/patients. Functional near-infrared spectroscopy (fNIRS) is a non-invasive, portable, and low-cost imaging modality that can measure brain activity. The purpose of this study was to compare brain activity as measured by fNIRS in concussed and age-matched controls during the performance of cognitive tasks from a computerized neurocognitive test battery. Participants included nine currently symptomatic patients aged 18-45 years with a recent (15-45 days) sport-related concussion and five age-matched healthy controls. The participants completed a computerized neurocognitive test battery while wearing the fNIRS unit. Our results demonstrated reduced brain activation in the concussed subject group during word memory, (spatial) design memory, digit-symbol substitution (symbol match), and working memory (X's and O's) tasks. Behavioral performance (percent-correct and reaction time respectively) was lower for concussed participants on the word memory, design memory, and symbol match tasks than controls. The results of this preliminary study suggest that fNIRS could be a useful, portable assessment tool to assess reduced brain activation and augment current approaches to assessment and management of patients following concussion.

Slice-to-Volume Nonrigid Registration of Histological Sections to MR Images of the Human Brain

PubMed Central

Osechinskiy, Sergey; Kruggel, Frithjof

2011-01-01

Registration of histological images to three-dimensional imaging modalities is an important step in quantitative analysis of brain structure, in architectonic mapping of the brain, and in investigation of the pathology of a brain disease. Reconstruction of histology volume from serial sections is a well-established procedure, but it does not address registration of individual slices from sparse sections, which is the aim of the slice-to-volume approach. This study presents a flexible framework for intensity-based slice-to-volume nonrigid registration algorithms with a geometric transformation deformation field parametrized by various classes of spline functions: thin-plate splines (TPS), Gaussian elastic body splines (GEBS), or cubic B-splines. Algorithms are applied to cross-modality registration of histological and magnetic resonance images of the human brain. Registration performance is evaluated across a range of optimization algorithms and intensity-based cost functions. For a particular case of histological data, best results are obtained with a TPS three-dimensional (3D) warp, a new unconstrained optimization algorithm (NEWUOA), and a correlation-coefficient-based cost function. PMID:22567290

Feature-based fusion of medical imaging data.

PubMed

Calhoun, Vince D; Adali, Tülay

2009-09-01

The acquisition of multiple brain imaging types for a given study is a very common practice. There have been a number of approaches proposed for combining or fusing multitask or multimodal information. These can be roughly divided into those that attempt to study convergence of multimodal imaging, for example, how function and structure are related in the same region of the brain, and those that attempt to study the complementary nature of modalities, for example, utilizing temporal EEG information and spatial functional magnetic resonance imaging information. Within each of these categories, one can attempt data integration (the use of one imaging modality to improve the results of another) or true data fusion (in which multiple modalities are utilized to inform one another). We review both approaches and present a recent computational approach that first preprocesses the data to compute features of interest. The features are then analyzed in a multivariate manner using independent component analysis. We describe the approach in detail and provide examples of how it has been used for different fusion tasks. We also propose a method for selecting which combination of modalities provides the greatest value in discriminating groups. Finally, we summarize and describe future research topics.

Patient-tailored multimodal neuroimaging, visualization and quantification of human intra-cerebral hemorrhage

NASA Astrophysics Data System (ADS)

Goh, Sheng-Yang M.; Irimia, Andrei; Vespa, Paul M.; Van Horn, John D.

2016-03-01

In traumatic brain injury (TBI) and intracerebral hemorrhage (ICH), the heterogeneity of lesion sizes and types necessitates a variety of imaging modalities to acquire a comprehensive perspective on injury extent. Although it is advantageous to combine imaging modalities and to leverage their complementary benefits, there are difficulties in integrating information across imaging types. Thus, it is important that efforts be dedicated to the creation and sustained refinement of resources for multimodal data integration. Here, we propose a novel approach to the integration of neuroimaging data acquired from human patients with TBI/ICH using various modalities; we also demonstrate the integrated use of multimodal magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data for TBI analysis based on both visual observations and quantitative metrics. 3D models of healthy-appearing tissues and TBIrelated pathology are generated, both of which are derived from multimodal imaging data. MRI volumes acquired using FLAIR, SWI, and T2 GRE are used to segment pathology. Healthy tissues are segmented using user-supervised tools, and results are visualized using a novel graphical approach called a `connectogram', where brain connectivity information is depicted within a circle of radially aligned elements. Inter-region connectivity and its strength are represented by links of variable opacities drawn between regions, where opacity reflects the percentage longitudinal change in brain connectivity density. Our method for integrating, analyzing and visualizing structural brain changes due to TBI and ICH can promote knowledge extraction and enhance the understanding of mechanisms underlying recovery.

Diagnostic imaging of traumatic brain injury.

PubMed

Furlow, Bryant

2006-01-01

In this Directed Reading, the history and epidemiology of traumatic brain injury (TBI) will be briefly introduced, the physical and physiological nature of TBI reviewed and the role of imaging in the assessment of TBI patients described. New imaging techniques and recent findings about the neurological correlates of TBI symptoms and outcomes from studies using different imaging modalities and techniques will also be discussed. This directed reading will focus on closed-head TBI; penetrating missile brain injuries, such as those caused by bullet wounds, will not be reviewed.

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

PubMed Central

Calhoun, Vince D; Sui, Jing

2016-01-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. PMID:27347565

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

PubMed

Calhoun, Vince D; Sui, Jing

2016-05-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

Diffuse Optical Tomography for Brain Imaging: Theory

NASA Astrophysics Data System (ADS)

Yuan, Zhen; Jiang, Huabei

Diffuse optical tomography (DOT) is a noninvasive, nonionizing, and inexpensive imaging technique that uses near-infrared light to probe tissue optical properties. Regional variations in oxy- and deoxy-hemoglobin concentrations as well as blood flow and oxygen consumption can be imaged by monitoring spatiotemporal variations in the absorption spectra. For brain imaging, this provides DOT unique abilities to directly measure the hemodynamic, metabolic, and neuronal responses to cells (neurons), and tissue and organ activations with high temporal resolution and good tissue penetration. DOT can be used as a stand-alone modality or can be integrated with other imaging modalities such as fMRI/MRI, PET/CT, and EEG/MEG in studying neurophysiology and pathology. This book chapter serves as an introduction to the basic theory and principles of DOT for neuroimaging. It covers the major aspects of advances in neural optical imaging including mathematics, physics, chemistry, reconstruction algorithm, instrumentation, image-guided spectroscopy, neurovascular and neurometabolic coupling, and clinical applications.

T1-T2 dual-modal MRI of brain gliomas using PEGylated Gd-doped iron oxide nanoparticles.

PubMed

Xiao, Ning; Gu, Wei; Wang, Hao; Deng, Yunlong; Shi, Xin; Ye, Ling

2014-03-01

To overcome the negative contrast limitations of iron oxide-based contrast agents and to improve the biocompatibility of Gd-chelate contrast agents, PEGylated Gd-doped iron oxide (PEG-GdIO) NPs as a T1-T2 dual-modal contrast agent were synthesized by the polyol method. The transverse relaxivity (r2) and longitudinal relaxivity (r1) of PEG-GdIO were determined to be 66.9 and 65.9 mM(-1) s(-1), respectively. The high r1 value and low r2/r1 ratio make PEG-GdIO NPs suitable as a T1-T2 dual-modal contrast agent. The in vivo MRI demonstrated a brighter contrast enhancement in T1-weighted image and a simultaneous darken effect in T2-weighted MR image compared to the pre-contrast image in the region of glioma. Furthermore, the biocompatibility of PEG-GdIO NPs was confirmed by the in vitro MTT cytotoxicity and in vivo histological analyses (H&E). Therefore, PEG-GdIO NPs hold great potential in T1-T2 dual-modal imaging for the diagnosis of brain glioma. Copyright © 2013 Elsevier Inc. All rights reserved.

Brain activation during neurocognitive testing using functional near-infrared spectroscopy in patients following concussion compared to healthy controls

PubMed Central

Huppert, T. J.; Beluk, N. H.; Elbin, R. J.; Henry, L. C.; French, J.; Dakan, S. M.; Collins, M. W.

2016-01-01

There is no accepted clinical imaging modality for concussion, and current imaging modalities including fMRI, DTI, and PET are expensive and inaccessible to most clinics/ patients. Functional near-infrared spectroscopy (fNIRS) is a non-invasive, portable, and low-cost imaging modality that can measure brain activity. The purpose of this study was to compare brain activity as measured by fNIRS in concussed and age-matched controls during the performance of cognitive tasks from a computerized neurocognitive test battery. Participants included nine currently symptomatic patients aged 18–45 years with a recent (15–45 days) sport-related concussion and five age-matched healthy controls. The participants completed a computerized neurocognitive test battery while wearing the fNIRS unit. Our results demonstrated reduced brain activation in the concussed subject group during word memory, (spatial) design memory, digit-symbol substitution (symbol match), and working memory (X’s and O’s) tasks. Behavioral performance (percent-correct and reaction time respectively) was lower for concussed participants on the word memory, design memory, and symbol match tasks than controls. The results of this preliminary study suggest that fNIRS could be a useful, portable assessment tool to assess reduced brain activation and augment current approaches to assessment and management of patients following concussion. PMID:24477579

Multimodal Diffuse Optical Imaging

NASA Astrophysics Data System (ADS)

Intes, Xavier; Venugopal, Vivek; Chen, Jin; Azar, Fred S.

Diffuse optical imaging, particularly diffuse optical tomography (DOT), is an emerging clinical modality capable of providing unique functional information, at a relatively low cost, and with nonionizing radiation. Multimodal diffuse optical imaging has enabled a synergistic combination of functional and anatomical information: the quality of DOT reconstructions has been significantly improved by incorporating the structural information derived by the combined anatomical modality. In this chapter, we will review the basic principles of diffuse optical imaging, including instrumentation and reconstruction algorithm design. We will also discuss the approaches for multimodal imaging strategies that integrate DOI with clinically established modalities. The merit of the multimodal imaging approaches is demonstrated in the context of optical mammography, but the techniques described herein can be translated to other clinical scenarios such as brain functional imaging or muscle functional imaging.

Hollow Polypropylene Yarns as a Biomimetic Brain Phantom for the Validation of High-Definition Fiber Tractography Imaging.

PubMed

Guise, Catarina; Fernandes, Margarida M; Nóbrega, João M; Pathak, Sudhir; Schneider, Walter; Fangueiro, Raul

2016-11-09

Current brain imaging methods largely fail to provide detailed information about the location and severity of axonal injuries and do not anticipate recovery of the patients with traumatic brain injury. High-definition fiber tractography appears as a novel imaging modality based on water motion in the brain that allows for direct visualization and quantification of the degree of axons damage, thus predicting the functional deficits due to traumatic axonal injury and loss of cortical projections. This neuroimaging modality still faces major challenges because it lacks a "gold standard" for the technique validation and respective quality control. The present work aims to study the potential of hollow polypropylene yarns to mimic human white matter axons and construct a brain phantom for the calibration and validation of brain diffusion techniques based on magnetic resonance imaging, including high-definition fiber tractography imaging. Hollow multifilament polypropylene yarns were produced by melt-spinning process and characterized in terms of their physicochemical properties. Scanning electronic microscopy images of the filaments cross section has shown an inner diameter of approximately 12 μm, confirming their appropriateness to mimic the brain axons. The chemical purity of polypropylene yarns as well as the interaction between the water and the filament surface, important properties for predicting water behavior and diffusion inside the yarns, were also evaluated. Restricted and hindered water diffusion was confirmed by fluorescence microscopy. Finally, the yarns were magnetic resonance imaging scanned and analyzed using high-definition fiber tractography, revealing an excellent choice of these hollow polypropylene structures for simulation of the white matter brain axons and their suitability for constructing an accurate brain phantom.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Fetal cerebral imaging - ultrasound vs. MRI: an update.

PubMed

Blondiaux, Eléonore; Garel, Catherine

2013-11-01

The purpose of this article is to analyze the advantages and limitations of prenatal ultrasonography (US) and magnetic resonance imaging (MRI) in the evaluation of the fetal brain. These imaging modalities should not be seen as competitive but rather as complementary. There are wide variations in the world regarding screening policies, technology, skills, and legislation about termination of pregnancy, and these variations markedly impact on the way of using prenatal imaging. According to the contribution expected from each technique and to local working conditions, one should choose the most appropriate imaging modality on a case-by-case basis. The advantages and limitations of US and MRI in the setting of fetal brain imaging are displayed. Different anatomical regions (midline, ventricles, subependymal area, cerebral parenchyma, pericerebral space, posterior fossa) and pathological conditions are analyzed and illustrated in order to compare the respective contribution of each technique. An accurate prenatal diagnosis of cerebral abnormalities is of utmost importance for prenatal counseling.

Neural substrate of initiation of cross-modal working memory retrieval.

PubMed

Zhang, Yangyang; Hu, Yang; Guan, Shuchen; Hong, Xiaolong; Wang, Zhaoxin; Li, Xianchun

2014-01-01

Cross-modal working memory requires integrating stimuli from different modalities and it is associated with co-activation of distributed networks in the brain. However, how brain initiates cross-modal working memory retrieval remains not clear yet. In the present study, we developed a cued matching task, in which the necessity for cross-modal/unimodal memory retrieval and its initiation time were controlled by a task cue appeared in the delay period. Using functional magnetic resonance imaging (fMRI), significantly larger brain activations were observed in the left lateral prefrontal cortex (l-LPFC), left superior parietal lobe (l-SPL), and thalamus in the cued cross-modal matching trials (CCMT) compared to those in the cued unimodal matching trials (CUMT). However, no significant differences in the brain activations prior to task cue were observed for sensory stimulation in the l-LPFC and l-SPL areas. Although thalamus displayed differential responses to the sensory stimulation between two conditions, the differential responses were not the same with responses to the task cues. These results revealed that the frontoparietal-thalamus network participated in the initiation of cross-modal working memory retrieval. Secondly, the l-SPL and thalamus showed differential activations between maintenance and working memory retrieval, which might be associated with the enhanced demand for cognitive resources.

Visualizing the anatomical-functional correlation of the human brain

NASA Astrophysics Data System (ADS)

Chang, YuKuang; Rockwood, Alyn P.; Reiman, Eric M.

1995-04-01

Three-dimensional tomographic images obtained from different modalities or from the same modality at different times provide complementary information. For example, while PET shows brain function, images from MRI identify anatomical structures. In this paper, we investigate the problem of displaying available information about structures and function together. Several steps are described to achieve our goal. These include segmentation of the data, registration, resampling, and display. Segmentation is used to identify brain tissue from surrounding tissues, especially in the MRI data. Registration aligns the different modalities as closely as possible. Resampling arises from the registration since two data sets do not usually correspond and the rendering method is most easily achieved if the data correspond to the same grid used in display. We combine several techniques to display the data. MRI data is reconstructed from 2D slices into 3D structures from which isosurfaces are extracted and represented by approximating polygonalizations. These are then displayed using standard graphics pipelines including shaded and transparent images. PET data measures the qualitative rates of cerebral glucose utilization or oxygen consumption. PET image is best displayed as a volume of luminous particles. The combination of both display methods allows the viewer to compare the functional information contained in the PET data with the anatomically more precise MRI data.

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury.

PubMed

Amyot, Franck; Arciniegas, David B; Brazaitis, Michael P; Curley, Kenneth C; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R; Manley, Geoffrey T; Pacifico, Anthony; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G; Stocker, Derek

2015-11-15

The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI.

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury

PubMed Central

Amyot, Franck; Arciniegas, David B.; Brazaitis, Michael P.; Curley, Kenneth C.; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R.; Manley, Geoffrey T.; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G.; Stocker, Derek

2015-01-01

Abstract The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI. PMID:26176603

Biological fiducial point based registration for multiple brain tissues reconstructed from different imaging modalities

NASA Astrophysics Data System (ADS)

Wu, Huiqun; Zhou, Gangping; Geng, Xingyun; Zhang, Xiaofeng; Jiang, Kui; Tang, Lemin; Zhou, Guomin; Dong, Jiancheng

2013-10-01

With the development of computer aided navigation system, more and more tissues shall be reconstructed to provide more useful information for surgical pathway planning. In this study, we aimed to propose a registration framework for different reconstructed tissues from multi-modalities based on some fiducial points on lateral ventricles. A male patient with brain lesion was admitted and his brain scans were performed by different modalities. Then, the different brain tissues were segmented in different modality with relevant suitable algorithms. Marching cubes were calculated for three dimensional reconstructions, and then the rendered tissues were imported to a common coordinate system for registration. Four pairs of fiducial markers were selected to calculate the rotation and translation matrix using least-square measure method. The registration results were satisfied in a glioblastoma surgery planning as it provides the spatial relationship between tumors and surrounding fibers as well as vessels. Hence, our framework is of potential value for clinicians to plan surgery.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Neural Bases Of Food Perception: Coordinate-Based Meta-Analyses Of Neuroimaging Studies In Multiple Modalities

PubMed Central

Huerta, Claudia I; Sarkar, Pooja R; Duong, Timothy Q.; Laird, Angela R; Fox, Peter T

2013-01-01

Objective The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm; and, ii) the relative robustness and reliability of responses to each paradigm. Design and Methods functional magnetic resonance imaging (fMRI) studies using standardized stereotactic coordinates to report brain responses to food cues were identified using on-line databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation (ALE) was used to identify statistically reliable regional responses within each stimulation paradigm. Results Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. Conclusions These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions. PMID:24174404

Large scale digital atlases in neuroscience

NASA Astrophysics Data System (ADS)

Hawrylycz, M.; Feng, D.; Lau, C.; Kuan, C.; Miller, J.; Dang, C.; Ng, L.

2014-03-01

Imaging in neuroscience has revolutionized our current understanding of brain structure, architecture and increasingly its function. Many characteristics of morphology, cell type, and neuronal circuitry have been elucidated through methods of neuroimaging. Combining this data in a meaningful, standardized, and accessible manner is the scope and goal of the digital brain atlas. Digital brain atlases are used today in neuroscience to characterize the spatial organization of neuronal structures, for planning and guidance during neurosurgery, and as a reference for interpreting other data modalities such as gene expression and connectivity data. The field of digital atlases is extensive and in addition to atlases of the human includes high quality brain atlases of the mouse, rat, rhesus macaque, and other model organisms. Using techniques based on histology, structural and functional magnetic resonance imaging as well as gene expression data, modern digital atlases use probabilistic and multimodal techniques, as well as sophisticated visualization software to form an integrated product. Toward this goal, brain atlases form a common coordinate framework for summarizing, accessing, and organizing this knowledge and will undoubtedly remain a key technology in neuroscience in the future. Since the development of its flagship project of a genome wide image-based atlas of the mouse brain, the Allen Institute for Brain Science has used imaging as a primary data modality for many of its large scale atlas projects. We present an overview of Allen Institute digital atlases in neuroscience, with a focus on the challenges and opportunities for image processing and computation.

Synchrotron radiation imaging is a powerful tool to image brain microvasculature

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

Zhang, Mengqi; Sun, Danni; Xie, Yuanyuan

2014-03-15

Synchrotron radiation (SR) imaging is a powerful experimental tool for micrometer-scale imaging of microcirculation in vivo. This review discusses recent methodological advances and findings from morphological investigations of cerebral vascular networks during several neurovascular pathologies. In particular, it describes recent developments in SR microangiography for real-time assessment of the brain microvasculature under various pathological conditions in small animal models. It also covers studies that employed SR-based phase-contrast imaging to acquire 3D brain images and provide detailed maps of brain vasculature. In addition, a brief introduction of SR technology and current limitations of SR sources are described in this review. Inmore » the near future, SR imaging could transform into a common and informative imaging modality to resolve subtle details of cerebrovascular function.« less

Synchrotron radiation imaging is a powerful tool to image brain microvasculature.

PubMed

Zhang, Mengqi; Peng, Guanyun; Sun, Danni; Xie, Yuanyuan; Xia, Jian; Long, Hongyu; Hu, Kai; Xiao, Bo

2014-03-01

Synchrotron radiation (SR) imaging is a powerful experimental tool for micrometer-scale imaging of microcirculation in vivo. This review discusses recent methodological advances and findings from morphological investigations of cerebral vascular networks during several neurovascular pathologies. In particular, it describes recent developments in SR microangiography for real-time assessment of the brain microvasculature under various pathological conditions in small animal models. It also covers studies that employed SR-based phase-contrast imaging to acquire 3D brain images and provide detailed maps of brain vasculature. In addition, a brief introduction of SR technology and current limitations of SR sources are described in this review. In the near future, SR imaging could transform into a common and informative imaging modality to resolve subtle details of cerebrovascular function.

Progress on the diagnosis and evaluation of brain tumors

PubMed Central

Gao, Huile

2013-01-01

Abstract Brain tumors are one of the most challenging disorders encountered, and early and accurate diagnosis is essential for the management and treatment of these tumors. In this article, diagnostic modalities including single-photon emission computed tomography, positron emission tomography, magnetic resonance imaging, and optical imaging are reviewed. We mainly focus on the newly emerging, specific imaging probes, and their potential use in animal models and clinical settings. PMID:24334439

Comparing three-dimensional serial optical coherence tomography histology to MRI imaging in the entire mouse brain

NASA Astrophysics Data System (ADS)

Castonguay, Alexandre; Lefebvre, Joël; Pouliot, Philippe; Lesage, Frédéric

2018-01-01

An automated serial histology setup combining optical coherence tomography (OCT) imaging with vibratome sectioning was used to image eight wild type mouse brains. The datasets resulted in thousands of volumetric tiles resolved at a voxel size of (4.9×4.9×6.5) μm3 stitched back together to give a three-dimensional map of the brain from which a template OCT brain was obtained. To assess deformation caused by tissue sectioning, reconstruction algorithms, and fixation, OCT datasets were compared to both in vivo and ex vivo magnetic resonance imaging (MRI) imaging. The OCT brain template yielded a highly detailed map of the brain structure, with a high contrast in white matter fiber bundles and was highly resemblant to the in vivo MRI template. Brain labeling using the Allen brain framework showed little variation in regional brain volume among imaging modalities with no statistical differences. The high correspondence between the OCT template brain and its in vivo counterpart demonstrates the potential of whole brain histology to validate in vivo imaging.

Penetrating the Blood-Brain Barrier: Promise of Novel Nanoplatforms and Delivery Vehicles.

PubMed

Ali, Iqbal Unnisa; Chen, Xiaoyuan

2015-10-27

Multifunctional nanoplatforms combining versatile therapeutic modalities with a variety of imaging options have the potential to diagnose, monitor, and treat brain diseases. The promise of nanotechnology can only be realized by the simultaneous development of innovative brain-targeting delivery vehicles capable of penetrating the blood-brain barrier without compromising its structural integrity.

Linking brain, mind and behavior.

PubMed

Makeig, Scott; Gramann, Klaus; Jung, Tzyy-Ping; Sejnowski, Terrence J; Poizner, Howard

2009-08-01

Cortical brain areas and dynamics evolved to organize motor behavior in our three-dimensional environment also support more general human cognitive processes. Yet traditional brain imaging paradigms typically allow and record only minimal participant behavior, then reduce the recorded data to single map features of averaged responses. To more fully investigate the complex links between distributed brain dynamics and motivated natural behavior, we propose the development of wearable mobile brain/body imaging (MoBI) systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships. The new imaging modality should allow new insights into how spatially distributed brain dynamics support natural human cognition and agency.

Transferring cognitive tasks between brain imaging modalities: implications for task design and results interpretation in FMRI studies.

PubMed

Warbrick, Tracy; Reske, Martina; Shah, N Jon

2014-09-22

As cognitive neuroscience methods develop, established experimental tasks are used with emerging brain imaging modalities. Here transferring a paradigm (the visual oddball task) with a long history of behavioral and electroencephalography (EEG) experiments to a functional magnetic resonance imaging (fMRI) experiment is considered. The aims of this paper are to briefly describe fMRI and when its use is appropriate in cognitive neuroscience; illustrate how task design can influence the results of an fMRI experiment, particularly when that task is borrowed from another imaging modality; explain the practical aspects of performing an fMRI experiment. It is demonstrated that manipulating the task demands in the visual oddball task results in different patterns of blood oxygen level dependent (BOLD) activation. The nature of the fMRI BOLD measure means that many brain regions are found to be active in a particular task. Determining the functions of these areas of activation is very much dependent on task design and analysis. The complex nature of many fMRI tasks means that the details of the task and its requirements need careful consideration when interpreting data. The data show that this is particularly important in those tasks relying on a motor response as well as cognitive elements and that covert and overt responses should be considered where possible. Furthermore, the data show that transferring an EEG paradigm to an fMRI experiment needs careful consideration and it cannot be assumed that the same paradigm will work equally well across imaging modalities. It is therefore recommended that the design of an fMRI study is pilot tested behaviorally to establish the effects of interest and then pilot tested in the fMRI environment to ensure appropriate design, implementation and analysis for the effects of interest.

Imaging Evaluation of Acute Traumatic Brain Injury

PubMed Central

Mutch, Christopher A.; Talbott, Jason F.; Gean, Alisa

2016-01-01

SYNOPSIS Traumatic brain injury (TBI) is a major cause of morbidity and mortality worldwide. Imaging plays an important role in the evaluation, diagnosis, and triage of patients with TBI. Recent studies suggest that it will also help predict patient outcomes. TBI consists of multiple pathoanatomical entities. Here we review the current state of TBI imaging including its indications, benefits and limitations of the modalities, imaging protocols, and imaging findings for each these pathoanatomic entities. We also briefly survey advanced imaging techniques, which include a number of promising areas of TBI research. PMID:27637393

Detection of relationships among multi-modal brain imaging meta-features via information flow.

PubMed

Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

2018-01-15

Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is powerful, intuitive and very efficiently provides a high-level overview of a massive data space. In our application it exposes both expected relationships and relationships very rarely considered worth investigating by clinical researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

Unveiling molecular events in the brain by noninvasive imaging.

PubMed

Klohs, Jan; Rudin, Markus

2011-10-01

Neuroimaging allows researchers and clinicians to noninvasively assess structure and function of the brain. With the advances of imaging modalities such as magnetic resonance, nuclear, and optical imaging; the design of target-specific probes; and/or the introduction of reporter gene assays, these technologies are now capable of visualizing cellular and molecular processes in vivo. Undoubtedly, the system biological character of molecular neuroimaging, which allows for the study of molecular events in the intact organism, will enhance our understanding of physiology and pathophysiology of the brain and improve our ability to diagnose and treat diseases more specifically. Technical/scientific challenges to be faced are the development of highly sensitive imaging modalities, the design of specific imaging probe molecules capable of penetrating the CNS and reporting on endogenous cellular and molecular processes, and the development of tools for extracting quantitative, biologically relevant information from imaging data. Today, molecular neuroimaging is still an experimental approach with limited clinical impact; this is expected to change within the next decade. This article provides an overview of molecular neuroimaging approaches with a focus on rodent studies documenting the exploratory state of the field. Concepts are illustrated by discussing applications related to the pathophysiology of Alzheimer's disease.

The Brain Dynamics of Intellectual Development: Waxing and Waning White and Gray Matter

ERIC Educational Resources Information Center

Tamnes, Christian K.; Fjell, Anders M.; Ostby, Ylva; Westlye, Lars T.; Due-Tonnessen, Paulina; Bjornerud, Atle; Walhovd, Kristine B.

2011-01-01

Distributed brain areas support intellectual abilities in adults. How structural maturation of these areas in childhood enables development of intelligence is not established. Neuroimaging can be used to monitor brain development, but studies to date have typically considered single imaging modalities. To explore the impact of structural brain…

Surgical treatment of solitary brain metastases.

PubMed

Gates, Marilyn; Alsaidi, Mohammed; Kalkanis, Steven

2012-01-01

Brain metastases are the most common form of brain tumors and are diagnosed in about 40% of all patients with systemic malignancies. Although the percentage of solitary brain metastases has dropped in recent estimates from about 50-30% of all patients with brain metastases, this percentage still represents a significant number of patients, and the overall incidence of brain metastases is still on the rise. Historically, brain metastases carried a grim prognosis with a median survival of only a few weeks. The utilization of whole-brain radiation therapy (WBRT) and steroids improved the prognosis to few months. However, it was not until the advent of advanced surgical techniques in conjunction with other treatment modalities such as WBRT and stereotactic radiosurgery that patients became less likely to succumb to neurological complications. In the last few decades, surgical resection has evolved from a mere emergent palliative treatment to a standard treatment modality that has led to improved clinical outcomes in carefully selected patients with brain metastases. This positive contribution has been made possible by randomized clinical trials, advancement of surgical techniques and tools, imaging modalities, and better understanding of the pathophysiology and perioperative care. Copyright © 2012 S. Karger AG, Basel.

Engineered core-shell magnetic nanoparticle for MR dual-modal tracking and safe magnetic manipulation of ependymal cells in live rodents

NASA Astrophysics Data System (ADS)

Peng, Yung-Kang; Lui, Cathy N. P.; Chen, Yu-Wei; Chou, Shang-Wei; Chou, Pi-Tai; Yung, Ken K. L.; Edman Tsang, S. C.

2018-01-01

Tagging recognition group(s) on superparamagnetic iron oxide is known to aid localisation (imaging), stimulation and separation of biological entities using magnetic resonance imaging (MRI) and magnetic agitation/separation (MAS) techniques. Despite the wide applicability of iron oxide nanoparticles in T 2-weighted MRI and MAS, the quality of the images and safe manipulation of the exceptionally delicate neural cells in a live brain are currently the key challenges. Here, we demonstrate the engineered manganese oxide clusters-iron oxide core-shell nanoparticle as an MR dual-modal contrast agent for neural stem cells (NSCs) imaging and magnetic manipulation in live rodents. As a result, using this engineered nanoparticle and associated technologies, identification, stimulation and transportation of labelled potentially multipotent NSCs from a specific location of a live brain to another by magnetic means for self-healing therapy can therefore be made possible.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging.

PubMed

Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2014-03-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Advantages in functional imaging of the brain.

PubMed

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this-visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

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.

Magnetic resonance spectroscopy of fiber tracts in children with traumatic brain injury: A combined MRS - Diffusion MRI study.

PubMed

Dennis, Emily L; Babikian, Talin; Alger, Jeffry; Rashid, Faisal; Villalon-Reina, Julio E; Jin, Yan; Olsen, Alexander; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-05-10

Traumatic brain injury can cause extensive damage to the white matter (WM) of the brain. These disruptions can be especially damaging in children, whose brains are still maturing. Diffusion magnetic resonance imaging (dMRI) is the most commonly used method to assess WM organization, but it has limited resolution to differentiate causes of WM disruption. Magnetic resonance spectroscopy (MRS) yields spectra showing the levels of neurometabolites that can indicate neuronal/axonal health, inflammation, membrane proliferation/turnover, and other cellular processes that are on-going post-injury. Previous analyses on this dataset revealed a significant division within the msTBI patient group, based on interhemispheric transfer time (IHTT); one subgroup of patients (TBI-normal) showed evidence of recovery over time, while the other showed continuing degeneration (TBI-slow). We combined dMRI with MRS to better understand WM disruptions in children with moderate-severe traumatic brain injury (msTBI). Tracts with poorer WM organization, as shown by lower FA and higher MD and RD, also showed lower N-acetylaspartate (NAA), a marker of neuronal and axonal health and myelination. We did not find lower NAA in tracts with normal WM organization. Choline, a marker of inflammation, membrane turnover, or gliosis, did not show such associations. We further show that multi-modal imaging can improve outcome prediction over a single modality, as well as over earlier cognitive function measures. Our results suggest that demyelination plays an important role in WM disruption post-injury in a subgroup of msTBI children and indicate the utility of multi-modal imaging. © 2018 Wiley Periodicals, Inc.

Structural Brain Atlases: Design, Rationale, and Applications in Normal and Pathological Cohorts

PubMed Central

Mandal, Pravat K.; Mahajan, Rashima; Dinov, Ivo D.

2015-01-01

Structural magnetic resonance imaging (MRI) provides anatomical information about the brain in healthy as well as in diseased conditions. On the other hand, functional MRI (fMRI) provides information on the brain activity during performance of a specific task. Analysis of fMRI data requires the registration of the data to a reference brain template in order to identify the activated brain regions. Brain templates also find application in other neuroimaging modalities, such as diffusion tensor imaging and multi-voxel spectroscopy. Further, there are certain differences (e.g., brain shape and size) in the brains of populations of different origin and during diseased conditions like in Alzheimer’s disease (AD), population and disease-specific brain templates may be considered crucial for accurate registration and subsequent analysis of fMRI as well as other neuroimaging data. This manuscript provides a comprehensive review of the history, construction and application of brain atlases. A chronological outline of the development of brain template design, starting from the Talairach and Tournoux atlas to the Chinese brain template (to date), along with their respective detailed construction protocols provides the backdrop to this manuscript. The manuscript also provides the automated workflow-based protocol for designing a population-specific brain atlas from structural MRI data using LONI Pipeline graphical workflow environment. We conclude by discussing the scope of brain templates as a research tool and their application in various neuroimaging modalities. PMID:22647262

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.

PubMed

Langen, Carolyn D; White, Tonya; Ikram, M Arfan; Vernooij, Meike W; Niessen, Wiro J

2015-01-01

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Integration of Sparse Multi-modality Representation and Geometrical Constraint for Isointense Infant Brain Segmentation

PubMed Central

Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H.; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6–8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods. PMID:24505729

Integration of sparse multi-modality representation and geometrical constraint for isointense infant brain segmentation.

PubMed

Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

2013-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6-8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods.

Integration of fMRI, NIROT and ERP for studies of human brain function.

PubMed

Gore, John C; Horovitz, Silvina G; Cannistraci, Christopher J; Skudlarski, Pavel

2006-05-01

Different methods of assessing human brain function possess specific advantages and disadvantages compared to others, but it is believed that combining different approaches will provide greater information than can be obtained from each alone. For example, functional magnetic resonance imaging (fMRI) has good spatial resolution but poor temporal resolution, whereas the converse is true for electrophysiological recordings (event-related potentials or ERPs). In this review of recent work, we highlight a novel approach to combining these modalities in a manner designed to increase information on the origins and locations of the generators of specific ERPs and the relationship between fMRI and ERP signals. Near infrared imaging techniques have also been studied as alternatives to fMRI and can be readily integrated with simultaneous electrophysiological recordings. Each of these modalities may in principle be also used in so-called steady-state acquisitions in which the correlational structure of signals from the brain may be analyzed to provide new insights into brain function.

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

PubMed

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

2016-01-01

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

Shared Syntax in Language Production and Language Comprehension—An fMRI Study

PubMed Central

Menenti, Laura; Weber, Kirsten; Petersson, Karl Magnus; Hagoort, Peter

2012-01-01

During speaking and listening syntactic processing is a crucial step. It involves specifying syntactic relations between words in a sentence. If the production and comprehension modality share the neuronal substrate for syntactic processing then processing syntax in one modality should lead to adaptation effects in the other modality. In the present functional magnetic resonance imaging experiment, participants either overtly produced or heard descriptions of pictures. We looked for brain regions showing adaptation effects to the repetition of syntactic structures. In order to ensure that not just the same brain regions but also the same neuronal populations within these regions are involved in syntactic processing in speaking and listening, we compared syntactic adaptation effects within processing modalities (syntactic production-to-production and comprehension-to-comprehension priming) with syntactic adaptation effects between processing modalities (syntactic comprehension-to-production and production-to-comprehension priming). We found syntactic adaptation effects in left inferior frontal gyrus (Brodmann's area [BA] 45), left middle temporal gyrus (BA 21), and bilateral supplementary motor area (BA 6) which were equally strong within and between processing modalities. Thus, syntactic repetition facilitates syntactic processing in the brain within and across processing modalities to the same extent. We conclude that that the same neurobiological system seems to subserve syntactic processing in speaking and listening. PMID:21934094

Recent technological advances in pediatric brain tumor surgery.

PubMed

Zebian, Bassel; Vergani, Francesco; Lavrador, José Pedro; Mukherjee, Soumya; Kitchen, William John; Stagno, Vita; Chamilos, Christos; Pettorini, Benedetta; Mallucci, Conor

2017-01-01

X-rays and ventriculograms were the first imaging modalities used to localize intracranial lesions including brain tumors as far back as the 1880s. Subsequent advances in preoperative radiological localization included computed tomography (CT; 1971) and MRI (1977). Since then, other imaging modalities have been developed for clinical application although none as pivotal as CT and MRI. Intraoperative technological advances include the microscope, which has allowed precise surgery under magnification and improved lighting, and the endoscope, which has improved the treatment of hydrocephalus and allowed biopsy and complete resection of intraventricular, pituitary and pineal region tumors through a minimally invasive approach. Neuronavigation, intraoperative MRI, CT and ultrasound have increased the ability of the neurosurgeon to perform safe and maximal tumor resection. This may be facilitated by the use of fluorescing agents, which help define the tumor margin, and intraoperative neurophysiological monitoring, which helps identify and protect eloquent brain.

Diffuse optical systems and methods to image physiological changes of the brain in response to focal TBI (Conference Presentation)

NASA Astrophysics Data System (ADS)

Abookasis, David; Volkov, Boris; Kofman, Itamar

2017-02-01

During the last four decades, various optical techniques have been proposed and intensively used for biomedical diagnosis and therapy both in animal model and in human. These techniques have several advantages over the traditional existing methods: simplicity in structure, low-cost, easy to handle, portable, can be used repeatedly over time near the patient bedside for continues monitoring, and offer high spatiotemporal resolution. In this work, we demonstrate the use of two optical imaging modalities namely, spatially modulated illumination and dual-wavelength laser speckle to image the changes in brain tissue chromophores, morphology, and metabolic before, during, and after the onset of focal traumatic brain injury in intact mouse head (n=15). Injury was applied in anesthetized mice by weight-drop apparatus using 50gram metal rod striking the mouse's head. Following data analysis, we show a series of hemodynamic and structural changes over time including higher deoxyhemoglobin, reduction in oxygen saturation and blood flow, cell swelling, etc., in comparison with baseline measurements. In addition, to validate the monitoring of cerebral blood flow by the imaging system, measurements with laser Doppler flowmetry were also performed (n=5), which confirmed reduction in blood flow following injury. Overall, our result demonstrates the capability of diffuse optical modalities to monitor and map brain tissue optical and physiological properties following brain trauma.

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.

The role of image registration in brain mapping

PubMed Central

Toga, A.W.; Thompson, P.M.

2008-01-01

Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483

Imaging of brain metastases.

PubMed

Fink, Kathleen R; Fink, James R

2013-01-01

Imaging plays a key role in the diagnosis of central nervous system (CNS) metastasis. Imaging is used to detect metastases in patients with known malignancies and new neurological signs or symptoms, as well as to screen for CNS involvement in patients with known cancer. Computed tomography (CT) and magnetic resonance imaging (MRI) are the key imaging modalities used in the diagnosis of brain metastases. In difficult cases, such as newly diagnosed solitary enhancing brain lesions in patients without known malignancy, advanced imaging techniques including proton magnetic resonance spectroscopy (MRS), contrast enhanced magnetic resonance perfusion (MRP), diffusion weighted imaging (DWI), and diffusion tensor imaging (DTI) may aid in arriving at the correct diagnosis. This image-rich review discusses the imaging evaluation of patients with suspected intracranial involvement and malignancy, describes typical imaging findings of parenchymal brain metastasis on CT and MRI, and provides clues to specific histological diagnoses such as the presence of hemorrhage. Additionally, the role of advanced imaging techniques is reviewed, specifically in the context of differentiating metastasis from high-grade glioma and other solitary enhancing brain lesions. Extra-axial CNS involvement by metastases, including pachymeningeal and leptomeningeal metastases is also briefly reviewed.

Conventional digital subtractional vs non-invasive MR angiography in the assessment of brain arteriovenous malformation.

PubMed

Cuong, Nguyen Ngoc; Luu, Vu Dang; Tuan, Tran Anh; Linh, Le Tuan; Hung, Kieu Dinh; Ngoc, Vo Truong Nhu; Sharma, Kulbhushan; Pham, Van Huy; Chu, Dinh-Toi

2018-06-01

Digital subtractional angiography (DSA) is the standard method for diagnosis, assessment and management of arteriovenous malformation in the brain. Conventional DSA (cDSA) is an invasive imaging modality that is often indicated before interventional treatments (embolization, open surgery, gamma knife). Here, we aimed to compare this technique with a non-invasive MR angiography (MRI DSA) for brain arteriovenous malformation (bAVM). Fourteen patients with ruptured brain AVM underwent embolization treatment pre-operation. Imaging was performed for all patients using MRI (1.5 T). After injecting contrast Gadolinium, dynamic MRI was performed with 40 phases, each phase of a duration of 1.2 s and having 70 images. The MRI results were independently assessed by experienced radiologist blinded to the cDSA. The AVM nidus was depicted in all patients using cDSA and MRI DSA; there was an excellent correlation between these techniques in terms of the maximum diameter and Spetzler Martin grading. Of the fourteen patients, the drainage vein was depicted in 13 by both cDSA and MRI DSA showing excellent correlation between the techniques used. MRI DSA is a non-invasive imaging modality that can give the images in dynamic view. It can be considered as an adjunctive method with cDSA to plan the strategy treatment for bAVM. Copyright © 2018 Elsevier B.V. All rights reserved.

The taste-visual cross-modal Stroop effect: An event-related brain potential study.

PubMed

Xiao, X; Dupuis-Roy, N; Yang, X L; Qiu, J F; Zhang, Q L

2014-03-28

Event-related potentials (ERPs) were recorded to explore, for the first time, the electrophysiological correlates of the taste-visual cross-modal Stroop effect. Eighteen healthy participants were presented with a taste stimulus and a food image, and asked to categorize the image as "sweet" or "sour" by pressing the relevant button as quickly as possible. Accurate categorization of the image was faster when it was presented with a congruent taste stimulus (e.g., sour taste/image of lemon) than with an incongruent one (e.g., sour taste/image of ice cream). ERP analyses revealed a negative difference component (ND430-620) between 430 and 620ms in the taste-visual cross-modal Stroop interference. Dipole source analysis of the difference wave (incongruent minus congruent) indicated that two generators localized in the prefrontal cortex and the parahippocampal gyrus contributed to this taste-visual cross-modal Stroop effect. This result suggests that the prefrontal cortex is associated with the process of conflict control in the taste-visual cross-modal Stroop effect. Also, we speculate that the parahippocampal gyrus is associated with the process of discordant information in the taste-visual cross-modal Stroop effect. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Multimedia human brain database system for surgical candidacy determination in temporal lobe epilepsy with content-based image retrieval

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-01-01

This paper presents the development of a human brain multimedia database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted MRI and FLAIR MRI and ictal and interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication pretty much fits with the surgeons" expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

PubMed

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8 months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. PMID:25541188

Brain activity during auditory and visual phonological, spatial and simple discrimination tasks.

PubMed

Salo, Emma; Rinne, Teemu; Salonen, Oili; Alho, Kimmo

2013-02-16

We used functional magnetic resonance imaging to measure human brain activity during tasks demanding selective attention to auditory or visual stimuli delivered in concurrent streams. Auditory stimuli were syllables spoken by different voices and occurring in central or peripheral space. Visual stimuli were centrally or more peripherally presented letters in darker or lighter fonts. The participants performed a phonological, spatial or "simple" (speaker-gender or font-shade) discrimination task in either modality. Within each modality, we expected a clear distinction between brain activations related to nonspatial and spatial processing, as reported in previous studies. However, within each modality, different tasks activated largely overlapping areas in modality-specific (auditory and visual) cortices, as well as in the parietal and frontal brain regions. These overlaps may be due to effects of attention common for all three tasks within each modality or interaction of processing task-relevant features and varying task-irrelevant features in the attended-modality stimuli. Nevertheless, brain activations caused by auditory and visual phonological tasks overlapped in the left mid-lateral prefrontal cortex, while those caused by the auditory and visual spatial tasks overlapped in the inferior parietal cortex. These overlapping activations reveal areas of multimodal phonological and spatial processing. There was also some evidence for intermodal attention-related interaction. Most importantly, activity in the superior temporal sulcus elicited by unattended speech sounds was attenuated during the visual phonological task in comparison with the other visual tasks. This effect might be related to suppression of processing irrelevant speech presumably distracting the phonological task involving the letters. Copyright © 2012 Elsevier B.V. All rights reserved.

Magnetic resonance imaging spectrum of perinatal hypoxic-ischemic brain injury

PubMed Central

Varghese, Binoj; Xavier, Rose; Manoj, V C; Aneesh, M K; Priya, P S; Kumar, Ashok; Sreenivasan, V K

2016-01-01

Perinatal hypoxic–ischemic brain injury results in neonatal hypoxic–ischemic encephalopathy and serious long-term neurodevelopmental sequelae. Magnetic resonance imaging (MRI) of the brain is an ideal and safe imaging modality for suspected hypoxic–ischemic injury. The pattern of injury depends on brain maturity at the time of insult, severity of hypotension, and duration of insult. Time of imaging after the insult influences the imaging findings. Mild to moderate hypoperfusion results in germinal matrix hemorrhages and periventricular leukomalacia in preterm neonates and parasagittal watershed territory infarcts in full-term neonates. Severe insult preferentially damages the deep gray matter in both term and preterm infants. However, associated frequent perirolandic injury is seen in term neonates. MRI is useful in establishing the clinical diagnosis, assessing the severity of injury, and thereby prognosticating the outcome. Familiarity with imaging spectrum and insight into factors affecting the injury will enlighten the radiologist to provide an appropriate diagnosis. PMID:27857456

Encoding of physics concepts: concreteness and presentation modality reflected by human brain dynamics.

PubMed

Lai, Kevin; She, Hsiao-Ching; Chen, Sheng-Chang; Chou, Wen-Chi; Huang, Li-Yu; Jung, Tzyy-Ping; Gramann, Klaus

2012-01-01

Previous research into working memory has focused on activations in different brain areas accompanying either different presentation modalities (verbal vs. non-verbal) or concreteness (abstract vs. concrete) of non-science concepts. Less research has been conducted investigating how scientific concepts are learned and further processed in working memory. To bridge this gap, the present study investigated human brain dynamics associated with encoding of physics concepts, taking both presentation modality and concreteness into account. Results of this study revealed greater theta and low-beta synchronization in the anterior cingulate cortex (ACC) during encoding of concrete pictures as compared to the encoding of both high and low imageable words. In visual brain areas, greater theta activity accompanying stimulus onsets was observed for words as compared to pictures while stronger alpha suppression was observed in responses to pictures as compared to words. In general, the EEG oscillation patterns for encoding words of different levels of abstractness were comparable but differed significantly from encoding of pictures. These results provide insights into the effects of modality of presentation on human encoding of scientific concepts and thus might help in developing new ways to better teach scientific concepts in class.

Combinations of Multiple Neuroimaging Markers using Logistic Regression for Auxiliary Diagnosis of Alzheimer Disease and Mild Cognitive Impairment.

PubMed

Mao, Nini; Liu, Yunting; Chen, Kewei; Yao, Li; Wu, Xia

2018-06-05

Multiple neuroimaging modalities have been developed providing various aspects of information on the human brain. Used together and properly, these complementary multimodal neuroimaging data integrate multisource information which can facilitate a diagnosis and improve the diagnostic accuracy. In this study, 3 types of brain imaging data (sMRI, FDG-PET, and florbetapir-PET) were fused in the hope to improve diagnostic accuracy, and multivariate methods (logistic regression) were applied to these trimodal neuroimaging indices. Then, the receiver-operating characteristic (ROC) method was used to analyze the outcomes of the logistic classifier, with either each index, multiples from each modality, or all indices from all 3 modalities, to investigate their differential abilities to identify the disease. With increasing numbers of indices within each modality and across modalities, the accuracy of identifying Alzheimer disease (AD) increases to varying degrees. For example, the area under the ROC curve is above 0.98 when all the indices from the 3 imaging data types are combined. Using a combination of different indices, the results confirmed the initial hypothesis that different biomarkers were potentially complementary, and thus the conjoint analysis of multiple information from multiple sources would improve the capability to identify diseases such as AD and mild cognitive impairment. © 2018 S. Karger AG, Basel.

Integrating research and clinical neuroimaging for the evaluation of traumatic brain injury recovery

NASA Astrophysics Data System (ADS)

Senseney, Justin; Ollinger, John; Graner, John; Lui, Wei; Oakes, Terry; Riedy, Gerard

2015-03-01

Advanced MRI research and other imaging modalities may serve as biomarkers for the evaluation of traumatic brain injury (TBI) recovery. However, these advanced modalities typically require off-line processing which creates images that are incompatible with radiologist viewing software sold commercially. AGFA Impax is an example of such a picture archiving and communication system(PACS) that is used by many radiology departments in the United States Military Health System. By taking advantage of Impax's use of the Digital Imaging and Communications in Medicine (DICOM) standard, we developed a system that allows for advanced medical imaging to be incorporated into clinical PACS. Radiology research can now be conducted using existing clinical imaging display platforms resources in combination with image processingtechniques that are only available outside of the clinical scanning environment. We extracted the spatial and identification elements of theDICOM standard that are necessary to allow research images to be incorporatedinto a clinical radiology system, and developed a tool that annotates research images with the proper tags. This allows for the evaluation of imaging representations of biological markers that may be useful in theevaluation of TBI and TBI recovery.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

Multimodality medical image database for temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-05-01

This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Brain-based decoding of mentally imagined film clips and sounds reveals experience-based information patterns in film professionals.

PubMed

de Borst, Aline W; Valente, Giancarlo; Jääskeläinen, Iiro P; Tikka, Pia

2016-04-01

In the perceptual domain, it has been shown that the human brain is strongly shaped through experience, leading to expertise in highly-skilled professionals. What has remained unclear is whether specialization also shapes brain networks underlying mental imagery. In our fMRI study, we aimed to uncover modality-specific mental imagery specialization of film experts. Using multi-voxel pattern analysis we decoded from brain activity of professional cinematographers and sound designers whether they were imagining sounds or images of particular film clips. In each expert group distinct multi-voxel patterns, specific for the modality of their expertise, were found during classification of imagery modality. These patterns were mainly localized in the occipito-temporal and parietal cortex for cinematographers and in the auditory cortex for sound designers. We also found generalized patterns across perception and imagery that were distinct for the two expert groups: they involved frontal cortex for the cinematographers and temporal cortex for the sound designers. Notably, the mental representations of film clips and sounds of cinematographers contained information that went beyond modality-specificity. We were able to successfully decode the implicit presence of film genre from brain activity during mental imagery in cinematographers. The results extend existing neuroimaging literature on expertise into the domain of mental imagery and show that experience in visual versus auditory imagery can alter the representation of information in modality-specific association cortices. Copyright © 2016 Elsevier Inc. All rights reserved.

Identification of Amnestic Mild Cognitive Impairment Using Multi-Modal Brain Features: A Combined Structural MRI and Diffusion Tensor Imaging Study.

PubMed

Xie, Yunyan; Cui, Zaixu; Zhang, Zhongmin; Sun, Yu; Sheng, Can; Li, Kuncheng; Gong, Gaolang; Han, Ying; Jia, Jianping

2015-01-01

Identifying amnestic mild cognitive impairment (aMCI) is of great clinical importance because aMCI is a putative prodromal stage of Alzheimer's disease. The present study aimed to explore the feasibility of accurately identifying aMCI with a magnetic resonance imaging (MRI) biomarker. We integrated measures of both gray matter (GM) abnormalities derived from structural MRI and white matter (WM) alterations acquired from diffusion tensor imaging at the voxel level across the entire brain. In particular, multi-modal brain features, including GM volume, WM fractional anisotropy, and mean diffusivity, were extracted from a relatively large sample of 64 Han Chinese aMCI patients and 64 matched controls. Then, support vector machine classifiers for GM volume, FA, and MD were fused to distinguish the aMCI patients from the controls. The fused classifier was evaluated with the leave-one-out and the 10-fold cross-validations, and the classifier had an accuracy of 83.59% and an area under the curve of 0.862. The most discriminative regions of GM were mainly located in the medial temporal lobe, temporal lobe, precuneus, cingulate gyrus, parietal lobe, and frontal lobe, whereas the most discriminative regions of WM were mainly located in the corpus callosum, cingulum, corona radiata, frontal lobe, and parietal lobe. Our findings suggest that aMCI is characterized by a distributed pattern of GM abnormalities and WM alterations that represent discriminative power and reflect relevant pathological changes in the brain, and these changes further highlight the advantage of multi-modal feature integration for identifying aMCI.

Image Guided Biodistribution and Pharmacokinetic Studies of Theranostics

PubMed Central

Ding, Hong; Wu, Fang

2012-01-01

Image guided technique is playing an increasingly important role in the investigation of the biodistribution and pharmacokinetics of drugs or drug delivery systems in various diseases, especially cancers. Besides anatomical imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), molecular imaging strategy including optical imaging, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) will facilitate the localization and quantization of radioisotope or optical probe labeled nanoparticle delivery systems in the category of theranostics. The quantitative measurement of the bio-distribution and pharmacokinetics of theranostics in the fields of new drug/probe development, diagnosis and treatment process monitoring as well as tracking the brain-blood-barrier (BBB) breaking through by high sensitive imaging method, and the applications of the representative imaging modalities are summarized in this review. PMID:23227121

In vivo monitoring of glial scar proliferation on chronically implanted neural electrodes by fiber optical coherence tomography

PubMed Central

Xie, Yijing; Martini, Nadja; Hassler, Christina; Kirch, Robert D.; Stieglitz, Thomas; Seifert, Andreas; Hofmann, Ulrich G.

2014-01-01

In neural prosthetics and stereotactic neurosurgery, intracortical electrodes are often utilized for delivering therapeutic electrical pulses, and recording neural electrophysiological signals. Unfortunately, neuroinflammation impairs the neuron-electrode-interface by developing a compact glial encapsulation around the implants in long term. At present, analyzing this immune reaction is only feasible with post-mortem histology; currently no means for specific in vivo monitoring exist and most applicable imaging modalities can not provide information in deep brain regions. Optical coherence tomography (OCT) is a well established imaging modality for in vivo studies, providing cellular resolution and up to 1.2 mm imaging depth in brain tissue. A fiber based spectral domain OCT was shown to be capable of minimally invasive brain imaging. In the present study, we propose to use a fiber based spectral domain OCT to monitor the progression of the tissue's immune response through scar encapsulation progress in a rat animal model. A fine fiber catheter was implanted in rat brain together with a flexible polyimide microelectrode in sight both of which acts as a foreign body and induces the brain tissue immune reaction. OCT signals were collected from animals up to 12 weeks after implantation and thus gliotic scarring in vivo monitored for that time. Preliminary data showed a significant enhancement of the OCT backscattering signal during the first 3 weeks after implantation, and increased attenuation factor of the sampled tissue due to the glial scar formation. PMID:25191264

The Neural Basis of Taste-visual Modal Conflict Control in Appetitive and Aversive Gustatory Context.

PubMed

Xiao, Xiao; Dupuis-Roy, Nicolas; Jiang, Jun; Du, Xue; Zhang, Mingmin; Zhang, Qinglin

2018-02-21

The functional magnetic resonance imaging (fMRI) technique was used to investigate brain activations related to conflict control in a taste-visual cross-modal pairing task. On each trial, participants had to decide whether the taste of a gustatory stimulus matched or did not match the expected taste of the food item depicted in an image. There were four conditions: Negative match (NM; sour gustatory stimulus and image of sour food), negative mismatch (NMM; sour gustatory stimulus and image of sweet food), positive match (PM; sweet gustatory stimulus and image of sweet food), positive mismatch (PMM; sweet gustatory stimulus and image of sour food). Blood oxygenation level-dependent (BOLD) contrasts between the NMM and the NM conditions revealed an increased activity in the middle frontal gyrus (MFG) (BA 6), the lingual gyrus (LG) (BA 18), and the postcentral gyrus. Furthermore, the NMM minus NM BOLD differences observed in the MFG were correlated with the NMM minus NM differences in response time. These activations were specifically associated with conflict control during the aversive gustatory stimulation. BOLD contrasts between the PMM and the PM condition revealed no significant positive activation, which supported the hypothesis that the human brain is especially sensitive to aversive stimuli. Altogether, these results suggest that the MFG is associated with the taste-visual cross-modal conflict control. A possible role of the LG as an information conflict detector at an early perceptual stage is further discussed, along with a possible involvement of the postcentral gyrus in the processing of the taste-visual cross-modal sensory contrast. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

PubMed

Chen, Hao; Dou, Qi; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

2018-04-15

Segmentation of key brain tissues from 3D medical images is of great significance for brain disease diagnosis, progression assessment and monitoring of neurologic conditions. While manual segmentation is time-consuming, laborious, and subjective, automated segmentation is quite challenging due to the complicated anatomical environment of brain and the large variations of brain tissues. We propose a novel voxelwise residual network (VoxResNet) with a set of effective training schemes to cope with this challenging problem. The main merit of residual learning is that it can alleviate the degradation problem when training a deep network so that the performance gains achieved by increasing the network depth can be fully leveraged. With this technique, our VoxResNet is built with 25 layers, and hence can generate more representative features to deal with the large variations of brain tissues than its rivals using hand-crafted features or shallower networks. In order to effectively train such a deep network with limited training data for brain segmentation, we seamlessly integrate multi-modality and multi-level contextual information into our network, so that the complementary information of different modalities can be harnessed and features of different scales can be exploited. Furthermore, an auto-context version of the VoxResNet is proposed by combining the low-level image appearance features, implicit shape information, and high-level context together for further improving the segmentation performance. Extensive experiments on the well-known benchmark (i.e., MRBrainS) of brain segmentation from 3D magnetic resonance (MR) images corroborated the efficacy of the proposed VoxResNet. Our method achieved the first place in the challenge out of 37 competitors including several state-of-the-art brain segmentation methods. Our method is inherently general and can be readily applied as a powerful tool to many brain-related studies, where accurate segmentation of brain structures is critical. Copyright © 2017 Elsevier Inc. All rights reserved.

Multimodal optical coherence tomography for in vivo imaging of brain tissue structure and microvascular network at glioblastoma

NASA Astrophysics Data System (ADS)

Yashin, Konstantin S.; Kiseleva, Elena B.; Gubarkova, Ekaterina V.; Matveev, Lev A.; Karabut, Maria M.; Elagin, Vadim V.; Sirotkina, Marina A.; Medyanik, Igor A.; Kravets, L. Y.; Gladkova, Natalia D.

2017-02-01

In the case of infiltrative brain tumors the surgeon faces difficulties in determining their boundaries to achieve total resection. The aim of the investigation was to evaluate the performance of multimodal OCT (MM OCT) for differential diagnostics of normal brain tissue and glioma using an experimental model of glioblastoma. The spectral domain OCT device that was used for the study provides simultaneously two modes: cross-polarization and microangiographic OCT. The comparative analysis of the both OCT modalities images from tumorous and normal brain tissue areas concurrently with histologic correlation shows certain difference between when accordingly to morphological and microvascular tissue features.

Quantitative comparison of 3D third harmonic generation and fluorescence microscopy images.

PubMed

Zhang, Zhiqing; Kuzmin, Nikolay V; Groot, Marie Louise; de Munck, Jan C

2018-01-01

Third harmonic generation (THG) microscopy is a label-free imaging technique that shows great potential for rapid pathology of brain tissue during brain tumor surgery. However, the interpretation of THG brain images should be quantitatively linked to images of more standard imaging techniques, which so far has been done qualitatively only. We establish here such a quantitative link between THG images of mouse brain tissue and all-nuclei-highlighted fluorescence images, acquired simultaneously from the same tissue area. For quantitative comparison of a substantial pair of images, we present here a segmentation workflow that is applicable for both THG and fluorescence images, with a precision of 91.3 % and 95.8 % achieved respectively. We find that the correspondence between the main features of the two imaging modalities amounts to 88.9 %, providing quantitative evidence of the interpretation of dark holes as brain cells. Moreover, 80 % bright objects in THG images overlap with nuclei highlighted in the fluorescence images, and they are 2 times smaller than the dark holes, showing that cells of different morphologies can be recognized in THG images. We expect that the described quantitative comparison is applicable to other types of brain tissue and with more specific staining experiments for cell type identification. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

A brain MRI atlas of the common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.

2014-03-01

The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.

Dementia resulting from traumatic brain injury

PubMed Central

Ramalho, Joana; Castillo, Mauricio

2015-01-01

Traumatic brain injury (TBI) represents a significant public health problem in modern societies. It is primarily a consequence of traffic-related accidents and falls. Other recently recognized causes include sports injuries and indirect forces such as shock waves from battlefield explosions. TBI is an important cause of death and lifelong disability and represents the most well-established environmental risk factor for dementia. With the growing recognition that even mild head injury can lead to neurocognitive deficits, imaging of brain injury has assumed greater importance. However, there is no single imaging modality capable of characterizing TBI. Current advances, particularly in MR imaging, enable visualization and quantification of structural and functional brain changes not hitherto possible. In this review, we summarize data linking TBI with dementia, emphasizing the imaging techniques currently available in clinical practice along with some advances in medical knowledge. PMID:29213985

Towards the development of a spring-based continuum robot for neurosurgery

NASA Astrophysics Data System (ADS)

Kim, Yeongjin; Cheng, Shing Shin; Desai, Jaydev P.

2015-03-01

Brain tumor is usually life threatening due to the uncontrolled growth of abnormal cells native to the brain or the spread of tumor cells from outside the central nervous system to the brain. The risks involved in carrying out surgery within such a complex organ can cause severe anxiety in cancer patients. However, neurosurgery, which remains one of the more effective ways of treating brain tumors focused in a confined volume, can have a tremendously increased success rate if the appropriate imaging modality is used for complete tumor removal. Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast and is the imaging modality of choice for brain tumor imaging. MRI combined with continuum soft robotics has immense potential to be the revolutionary treatment technique in the field of brain cancer. It eliminates the concern of hand tremor and guarantees a more precise procedure. One of the prototypes of Minimally Invasive Neurosurgical Intracranial Robot (MINIR-II), which can be classified as a continuum soft robot, consists of a snake-like body made of three segments of rapid prototyped plastic springs. It provides improved dexterity with higher degrees of freedom and independent joint control. It is MRI-compatible, allowing surgeons to track and determine the real-time location of the robot relative to the brain tumor target. The robot was manufactured in a single piece using rapid prototyping technology at a low cost, allowing it to disposable after each use. MINIR-II has two DOFs at each segment with both joints controlled by two pairs of MRI-compatible SMA spring actuators. Preliminary motion tests have been carried out using vision-tracking method and the robot was able to move to different positions based on user commands.

Quantitative Imaging of Energy Expenditure in Human Brain

PubMed Central

Zhu, Xiao-Hong; Qiao, Hongyan; Du, Fei; Xiong, Qiang; Liu, Xiao; Zhang, Xiaoliang; Ugurbil, Kamil; Chen, Wei

2012-01-01

Despite the essential role of the brain energy generated from ATP hydrolysis in supporting cortical neuronal activity and brain function, it is challenging to noninvasively image and directly quantify the energy expenditure in the human brain. In this study, we applied an advanced in vivo 31P MRS imaging approach to obtain regional cerebral metabolic rates of high-energy phosphate reactions catalyzed by ATPase (CMRATPase) and creatine kinase (CMRCK), and to determine CMRATPase and CMRCK in pure grey mater (GM) and white mater (WM), respectively. It was found that both ATPase and CK rates are three times higher in GM than WM; and CMRCK is seven times higher than CMRATPase in GM and WM. Among the total brain ATP consumption in the human cortical GM and WM, 77% of them are used by GM in which approximately 96% is by neurons. A single cortical neuron utilizes approximately 4.7 billion ATPs per second in a resting human brain. This study demonstrates the unique utility of in vivo 31P MRS imaging modality for direct imaging of brain energy generated from ATP hydrolysis, and provides new insights into the human brain energetics and its role in supporting neuronal activity and brain function. PMID:22487547

Neuronal chronometry of target detection: fusion of hemodynamic and event-related potential data.

PubMed

Calhoun, V D; Adali, T; Pearlson, G D; Kiehl, K A

2006-04-01

Event-related potential (ERP) studies of the brain's response to infrequent, target (oddball) stimuli elicit a sequence of physiological events, the most prominent and well studied being a complex, the P300 (or P3) peaking approximately 300 ms post-stimulus for simple stimuli and slightly later for more complex stimuli. Localization of the neural generators of the human oddball response remains challenging due to the lack of a single imaging technique with good spatial and temporal resolution. Here, we use independent component analyses to fuse ERP and fMRI modalities in order to examine the dynamics of the auditory oddball response with high spatiotemporal resolution across the entire brain. Initial activations in auditory and motor planning regions are followed by auditory association cortex and motor execution regions. The P3 response is associated with brainstem, temporal lobe, and medial frontal activity and finally a late temporal lobe "evaluative" response. We show that fusing imaging modalities with different advantages can provide new information about the brain.

Evaluation of laser speckle contrast imaging as an intrinsic method to monitor blood brain barrier integrity

PubMed Central

Dufour, Suzie; Atchia, Yaaseen; Gad, Raanan; Ringuette, Dene; Sigal, Iliya; Levi, Ofer

2013-01-01

The integrity of the blood brain barrier (BBB) can contribute to the development of many brain disorders. We evaluate laser speckle contrast imaging (LSCI) as an intrinsic modality for monitoring BBB disruptions through simultaneous fluorescence and LSCI with vertical cavity surface emitting lasers (VCSELs). We demonstrated that drug-induced BBB opening was associated with a relative change of the arterial and venous blood velocities. Cross-sectional flow velocity ratio (veins/arteries) decreased significantly in rats treated with BBB-opening drugs, ≤0.81 of initial values. PMID:24156049

Semi-Supervised Tripled Dictionary Learning for Standard-dose PET Image Prediction using Low-dose PET and Multimodal MRI

PubMed Central

Wang, Yan; Ma, Guangkai; An, Le; Shi, Feng; Zhang, Pei; Lalush, David S.; Wu, Xi; Pu, Yifei; Zhou, Jiliu; Shen, Dinggang

2017-01-01

Objective To obtain high-quality positron emission tomography (PET) image with low-dose tracer injection, this study attempts to predict the standard-dose PET (S-PET) image from both its low-dose PET (L-PET) counterpart and corresponding magnetic resonance imaging (MRI). Methods It was achieved by patch-based sparse representation (SR), using the training samples with a complete set of MRI, L-PET and S-PET modalities for dictionary construction. However, the number of training samples with complete modalities is often limited. In practice, many samples generally have incomplete modalities (i.e., with one or two missing modalities) that thus cannot be used in the prediction process. In light of this, we develop a semi-supervised tripled dictionary learning (SSTDL) method for S-PET image prediction, which can utilize not only the samples with complete modalities (called complete samples) but also the samples with incomplete modalities (called incomplete samples), to take advantage of the large number of available training samples and thus further improve the prediction performance. Results Validation was done on a real human brain dataset consisting of 18 subjects, and the results show that our method is superior to the SR and other baseline methods. Conclusion This work proposed a new S-PET prediction method, which can significantly improve the PET image quality with low-dose injection. Significance The proposed method is favorable in clinical application since it can decrease the potential radiation risk for patients. PMID:27187939

An automatic brain tumor segmentation tool.

PubMed

Diaz, Idanis; Boulanger, Pierre; Greiner, Russell; Hoehn, Bret; Rowe, Lindsay; Murtha, Albert

2013-01-01

This paper introduces an automatic brain tumor segmentation method (ABTS) for segmenting multiple components of brain tumor using four magnetic resonance image modalities. ABTS's four stages involve automatic histogram multi-thresholding and morphological operations including geodesic dilation. Our empirical results, on 16 real tumors, show that ABTS works very effectively, achieving a Dice accuracy compared to expert segmentation of 81% in segmenting edema and 85% in segmenting gross tumor volume (GTV).

Spatial Mapping of Structural and Connectional Imaging Data for the Developing Human Brain with Diffusion Tensor Imaging

PubMed Central

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao

2014-01-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302

In vivo microscopy of the mouse brain using multiphoton laser scanning techniques

NASA Astrophysics Data System (ADS)

Yoder, Elizabeth J.

2002-06-01

The use of multiphoton microscopy for imaging mouse brain in vivo offers several advantages and poses several challenges. This tutorial begins by briefly comparing multiphoton microscopy with other imaging modalities used to visualize the brain and its activity. Next, an overview of the techniques for introducing fluorescence into whole animals to generate contrast for in vivo microscopy using two-photon excitation is presented. Two different schemes of surgically preparing mice for brain imaging with multiphoton microscopy are reviewed. Then, several issues and problems with in vivo microscopy - including motion artifact, respiratory and cardiac rhythms, maintenance of animal health, anesthesia, and the use of fiducial markers - are discussed. Finally, examples of how these techniques have been applied to visualize the cerebral vasculature and its response to hypercapnic stimulation are provided.

Sight and sound converge to form modality-invariant representations in temporo-parietal cortex

PubMed Central

Man, Kingson; Kaplan, Jonas T.; Damasio, Antonio; Meyer, Kaspar

2013-01-01

People can identify objects in the environment with remarkable accuracy, irrespective of the sensory modality they use to perceive them. This suggests that information from different sensory channels converges somewhere in the brain to form modality-invariant representations, i.e., representations that reflect an object independently of the modality through which it has been apprehended. In this functional magnetic resonance imaging study of human subjects, we first identified brain areas that responded to both visual and auditory stimuli and then used crossmodal multivariate pattern analysis to evaluate the neural representations in these regions for content-specificity (i.e., do different objects evoke different representations?) and modality-invariance (i.e., do the sight and the sound of the same object evoke a similar representation?). While several areas became activated in response to both auditory and visual stimulation, only the neural patterns recorded in a region around the posterior part of the superior temporal sulcus displayed both content-specificity and modality-invariance. This region thus appears to play an important role in our ability to recognize objects in our surroundings through multiple sensory channels and to process them at a supra-modal (i.e., conceptual) level. PMID:23175818

Diverse Application of Magnetic Resonance Imaging for Mouse Phenotyping

PubMed Central

Wu, Yijen L.; Lo, Cecilia W.

2017-01-01

Small animal models, particularly mouse models, of human diseases are becoming an indispensable tool for biomedical research. Studies in animal models have provided important insights into the etiology of diseases and accelerated the development of therapeutic strategies. Detailed phenotypic characterization is essential, both for the development of such animal models and mechanistic studies into disease pathogenesis and testing the efficacy of experimental therapeutics. Magnetic Resonance Imaging (MRI) is a versatile and non-invasive imaging modality with excellent penetration depth, tissue coverage, and soft tissue contrast. MRI, being a multi-modal imaging modality, together with proven imaging protocols and availability of good contrast agents, is ideally suited for phenotyping mutant mouse models. Here we describe the applications of MRI for phenotyping structural birth defects involving the brain, heart, and kidney in mice. The versatility of MRI and its ease of use are well suited to meet the rapidly increasing demands for mouse phenotyping in the coming age of functional genomics. PMID:28544650

Designing Image Operators for MRI-PET Image Fusion of the Brain

NASA Astrophysics Data System (ADS)

Márquez, Jorge; Gastélum, Alfonso; Padilla, Miguel A.

2006-09-01

Our goal is to obtain images combining in a useful and precise way the information from 3D volumes of medical imaging sets. We address two modalities combining anatomy (Magnetic Resonance Imaging or MRI) and functional information (Positron Emission Tomography or PET). Commercial imaging software offers image fusion tools based on fixed blending or color-channel combination of two modalities, and color Look-Up Tables (LUTs), without considering the anatomical and functional character of the image features. We used a sensible approach for image fusion taking advantage mainly from the HSL (Hue, Saturation and Luminosity) color space, in order to enhance the fusion results. We further tested operators for gradient and contour extraction to enhance anatomical details, plus other spatial-domain filters for functional features corresponding to wide point-spread-function responses in PET images. A set of image-fusion operators was formulated and tested on PET and MRI acquisitions.

Explicit Encoding of Multimodal Percepts by Single Neurons in the Human Brain

PubMed Central

Quiroga, Rodrigo Quian; Kraskov, Alexander; Koch, Christof; Fried, Itzhak

2010-01-01

Summary Different pictures of Marilyn Monroe can evoke the same percept, even if greatly modified as in Andy Warhol’s famous portraits. But how does the brain recognize highly variable pictures as the same percept? Various studies have provided insights into how visual information is processed along the “ventral pathway,” via both single-cell recordings in monkeys [1, 2] and functional imaging in humans [3, 4]. Interestingly, in humans, the same “concept” of Marilyn Monroe can be evoked with other stimulus modalities, for instance by hearing or reading her name. Brain imaging studies have identified cortical areas selective to voices [5, 6] and visual word forms [7, 8]. However, how visual, text, and sound information can elicit a unique percept is still largely unknown. By using presentations of pictures and of spoken and written names, we show that (1) single neurons in the human medial temporal lobe (MTL) respond selectively to representations of the same individual across different sensory modalities; (2) the degree of multimodal invariance increases along the hierarchical structure within the MTL; and (3) such neuronal representations can be generated within less than a day or two. These results demonstrate that single neurons can encode percepts in an explicit, selective, and invariant manner, even if evoked by different sensory modalities. PMID:19631538

Measuring speaker–listener neural coupling with functional near infrared spectroscopy

PubMed Central

Liu, Yichuan; Piazza, Elise A.; Simony, Erez; Shewokis, Patricia A.; Onaral, Banu; Hasson, Uri; Ayaz, Hasan

2017-01-01

The present study investigates brain-to-brain coupling, defined as inter-subject correlations in the hemodynamic response, during natural verbal communication. We used functional near-infrared spectroscopy (fNIRS) to record brain activity of 3 speakers telling stories and 15 listeners comprehending audio recordings of these stories. Listeners’ brain activity was significantly correlated with speakers’ with a delay. This between-brain correlation disappeared when verbal communication failed. We further compared the fNIRS and functional Magnetic Resonance Imaging (fMRI) recordings of listeners comprehending the same story and found a significant relationship between the fNIRS oxygenated-hemoglobin concentration changes and the fMRI BOLD in brain areas associated with speech comprehension. This correlation between fNIRS and fMRI was only present when data from the same story were compared between the two modalities and vanished when data from different stories were compared; this cross-modality consistency further highlights the reliability of the spatiotemporal brain activation pattern as a measure of story comprehension. Our findings suggest that fNIRS can be used for investigating brain-to-brain coupling during verbal communication in natural settings. PMID:28240295

A cross-modal investigation of the neural substrates for ongoing cognition

PubMed Central

Wang, Megan; He, Biyu J.

2014-01-01

What neural mechanisms underlie the seamless flow of our waking consciousness? A necessary albeit insufficient condition for such neural mechanisms is that they should be consistently modulated across time were a segment of the conscious stream to be repeated twice. In this study, we experimentally manipulated the content of a story followed by subjects during functional magnetic resonance imaging (fMRI) independently from the modality of sensory input (as visual text or auditory speech) as well as attentional focus. We then extracted brain activity patterns consistently modulated across subjects by the evolving content of the story regardless of whether it was presented visually or auditorily. Specifically, in one experiment we presented the same story to different subjects via either auditory or visual modality. In a second experiment, we presented two different stories simultaneously, one auditorily, one visually, and manipulated the subjects' attentional focus. This experimental design allowed us to dissociate brain activities underlying modality-specific sensory processing from modality-independent story processing. We uncovered a network of brain regions consistently modulated by the evolving content of a story regardless of the sensory modality used for stimulus input, including the superior temporal sulcus/gyrus (STS/STG), the inferior frontal gyrus (IFG), the posterior cingulate cortex (PCC), the medial frontal cortex (MFC), the temporal pole (TP), and the temporoparietal junction (TPJ). Many of these regions have previously been implicated in semantic processing. Interestingly, different stories elicited similar brain activity patterns, but with subtle differences potentially attributable to varying degrees of emotional valence and self-relevance. PMID:25206347

Brain activity during divided and selective attention to auditory and visual sentence comprehension tasks

PubMed Central

Moisala, Mona; Salmela, Viljami; Salo, Emma; Carlson, Synnöve; Vuontela, Virve; Salonen, Oili; Alho, Kimmo

2015-01-01

Using functional magnetic resonance imaging (fMRI), we measured brain activity of human participants while they performed a sentence congruence judgment task in either the visual or auditory modality separately, or in both modalities simultaneously. Significant performance decrements were observed when attention was divided between the two modalities compared with when one modality was selectively attended. Compared with selective attention (i.e., single tasking), divided attention (i.e., dual-tasking) did not recruit additional cortical regions, but resulted in increased activity in medial and lateral frontal regions which were also activated by the component tasks when performed separately. Areas involved in semantic language processing were revealed predominantly in the left lateral prefrontal cortex by contrasting incongruent with congruent sentences. These areas also showed significant activity increases during divided attention in relation to selective attention. In the sensory cortices, no crossmodal inhibition was observed during divided attention when compared with selective attention to one modality. Our results suggest that the observed performance decrements during dual-tasking are due to interference of the two tasks because they utilize the same part of the cortex. Moreover, semantic dual-tasking did not appear to recruit additional brain areas in comparison with single tasking, and no crossmodal inhibition was observed during intermodal divided attention. PMID:25745395

Brain activity during divided and selective attention to auditory and visual sentence comprehension tasks.

PubMed

Moisala, Mona; Salmela, Viljami; Salo, Emma; Carlson, Synnöve; Vuontela, Virve; Salonen, Oili; Alho, Kimmo

2015-01-01

Using functional magnetic resonance imaging (fMRI), we measured brain activity of human participants while they performed a sentence congruence judgment task in either the visual or auditory modality separately, or in both modalities simultaneously. Significant performance decrements were observed when attention was divided between the two modalities compared with when one modality was selectively attended. Compared with selective attention (i.e., single tasking), divided attention (i.e., dual-tasking) did not recruit additional cortical regions, but resulted in increased activity in medial and lateral frontal regions which were also activated by the component tasks when performed separately. Areas involved in semantic language processing were revealed predominantly in the left lateral prefrontal cortex by contrasting incongruent with congruent sentences. These areas also showed significant activity increases during divided attention in relation to selective attention. In the sensory cortices, no crossmodal inhibition was observed during divided attention when compared with selective attention to one modality. Our results suggest that the observed performance decrements during dual-tasking are due to interference of the two tasks because they utilize the same part of the cortex. Moreover, semantic dual-tasking did not appear to recruit additional brain areas in comparison with single tasking, and no crossmodal inhibition was observed during intermodal divided attention.

Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

PubMed Central

Attique, Muhammad; Gilanie, Ghulam; Hafeez-Ullah; Mehmood, Malik S.; Naweed, Muhammad S.; Ikram, Masroor; Kamran, Javed A.; Vitkin, Alex

2012-01-01

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described. PMID:22479421

Resting functional imaging tools (MRS, SPECT, PET and PCT).

PubMed

Van Der Naalt, J

2015-01-01

Functional imaging includes imaging techniques that provide information about the metabolic and hemodynamic status of the brain. Most commonly applied functional imaging techniques in patients with traumatic brain injury (TBI) include magnetic resonance spectroscopy (MRS), single photon emission computed tomography (SPECT), positron emission tomography (PET) and perfusion CT (PCT). These imaging modalities are used to determine the extent of injury, to provide information for the prediction of outcome, and to assess evidence of cerebral ischemia. In TBI, secondary brain damage mainly comprises ischemia and is present in more than 80% of fatal cases with traumatic brain injury (Graham et al., 1989; Bouma et al., 1991; Coles et al., 2004). In particular, while SPECT measures cerebral perfusion and MRS determines metabolism, PET is able to assess both perfusion and cerebral metabolism. This chapter will describe the application of these techniques in traumatic brain injury separately for the major groups of severity comprising the mild and moderate to severe group. The application in TBI and potential difficulties of each technique is described. The use of imaging techniques in children will be separately outlined. © 2015 Elsevier B.V. All rights reserved.

Comparison of simultaneously recorded [H2(15)O]-PET and LORETA during cognitive and pharmacological activation.

PubMed

Gamma, Alex; Lehmann, Dietrich; Frei, Edi; Iwata, Kazuki; Pascual-Marqui, Roberto D; Vollenweider, Franz X

2004-06-01

The complementary strengths and weaknesses of established functional brain imaging methods (high spatial, low temporal resolution) and EEG-based techniques (low spatial, high temporal resolution) make their combined use a promising avenue for studying brain processes at a more fine-grained level. However, this strategy requires a better understanding of the relationship between hemodynamic/metabolic and neuroelectric measures of brain activity. We investigated possible correspondences between cerebral blood flow (CBF) as measured by [H2O]-PET and intracerebral electric activity computed by Low Resolution Brain Electromagnetic Tomography (LORETA) from scalp-recorded multichannel EEG in healthy human subjects during cognitive and pharmacological stimulation. The two imaging modalities were compared by descriptive, correlational, and variance analyses, the latter carried out using statistical parametric mapping (SPM99). Descriptive visual comparison showed a partial overlap between the sets of active brain regions detected by the two modalities. A number of exclusively positive correlations of neuroelectric activity with regional CBF were found across the whole EEG frequency range, including slow wave activity, the latter finding being in contrast to most previous studies conducted in patients. Analysis of variance revealed an extensive lack of statistically significant correspondences between brain activity changes as measured by PET vs. EEG-LORETA. In general, correspondences, to the extent they were found, were dependent on experimental condition, brain region, and EEG frequency. Copyright 2004 Wiley-Liss, Inc.

Localisation of epileptic foci using novel imaging modalities

PubMed Central

De Ciantis, Alessio; Lemieux, Louis

2013-01-01

Purpose of review This review examines recent reports on the use of advanced techniques to map the regions and networks involved during focal epileptic seizure generation in humans. Recent findings A number of imaging techniques are capable of providing new localizing information on the ictal processes and epileptogenic zone. Evaluating the clinical utility of these findings has been mainly performed through post-hoc comparison with the findings of invasive EEG and ictal single-photon emission computed tomography, using postsurgical seizure reduction as the main outcome measure. Added value has been demonstrated in MRI-negative cases. Improved understanding of the human ictiogenic processes and the focus vs. network hypothesis is likely to result from the application of multimodal techniques that combine electrophysiological, semiological, and whole-brain coverage of brain activity changes. Summary On the basis of recent research in the field of neuroimaging, several novel imaging modalities have been improved and developed to provide information about the localization of epileptic foci. PMID:23823464

Alzheimer disease: focus on computed tomography.

PubMed

Reynolds, April

2013-01-01

Alzheimer disease is the most common type of dementia, affecting approximately 5.3 million Americans. This debilitating disease is marked by memory loss, confusion, and loss of cognitive ability. The exact cause of Alzheimer disease is unknown although research suggests that it might result from a combination of factors. The hallmarks of Alzheimer disease are the presence of beta-amyloid plaques and neurofibrillary tangles in the brain. Radiologic imaging can help physicians detect these structural characteristics and monitor disease progression and brain function. Computed tomography and magnetic resonance imaging are considered first-line imaging modalities for the routine evaluation of Alzheimer disease.

In vivo imaging of endogenous neural stem cells in the adult brain

PubMed Central

Rueger, Maria Adele; Schroeter, Michael

2015-01-01

The discovery of endogenous neural stem cells (eNSCs) in the adult mammalian brain with their ability to self-renew and differentiate into functional neurons, astrocytes and oligodendrocytes has raised the hope for novel therapies of neurological diseases. Experimentally, those eNSCs can be mobilized in vivo, enhancing regeneration and accelerating functional recovery after, e.g., focal cerebral ischemia, thus constituting a most promising approach in stem cell research. In order to translate those current experimental approaches into a clinical setting in the future, non-invasive imaging methods are required to monitor eNSC activation in a longitudinal and intra-individual manner. As yet, imaging protocols to assess eNSC mobilization non-invasively in the live brain remain scarce, but considerable progress has been made in this field in recent years. This review summarizes and discusses the current imaging modalities suitable to monitor eNSCs in individual experimental animals over time, including optical imaging, magnetic resonance tomography and-spectroscopy, as well as positron emission tomography (PET). Special emphasis is put on the potential of each imaging method for a possible clinical translation, and on the specificity of the signal obtained. PET-imaging with the radiotracer 3’-deoxy-3’-[18F]fluoro-L-thymidine in particular constitutes a modality with excellent potential for clinical translation but low specificity; however, concomitant imaging of neuroinflammation is feasible and increases its specificity. The non-invasive imaging strategies presented here allow for the exploitation of novel treatment strategies based upon the regenerative potential of eNSCs, and will help to facilitate a translation into the clinical setting. PMID:25621107

Changing Utilization of Noninvasive Diagnostic Imaging Over 2 Decades: An Examination Family-Focused Analysis of Medicare Claims Using the Neiman Imaging Types of Service Categorization System.

PubMed

Rosman, David A; Duszak, Richard; Wang, Wenyi; Hughes, Danny R; Rosenkrantz, Andrew B

2018-02-01

The objective of our study was to use a new modality and body region categorization system to assess changing utilization of noninvasive diagnostic imaging in the Medicare fee-for-service population over a recent 20-year period (1994-2013). All Medicare Part B Physician Fee Schedule services billed between 1994 and 2013 were identified using Physician/Supplier Procedure Summary master files. Billed codes for diagnostic imaging were classified using the Neiman Imaging Types of Service (NITOS) coding system by both modality and body region. Utilization rates per 1000 beneficiaries were calculated for families of services. Among all diagnostic imaging modalities, growth was greatest for MRI (+312%) and CT (+151%) and was lower for ultrasound, nuclear medicine, and radiography and fluoroscopy (range, +1% to +31%). Among body regions, service growth was greatest for brain (+126%) and spine (+74%) imaging; showed milder growth (range, +18% to +67%) for imaging of the head and neck, breast, abdomen and pelvis, and extremity; and showed slight declines (range, -2% to -7%) for cardiac and chest imaging overall. The following specific imaging service families showed massive (> +100%) growth: cardiac CT, cardiac MRI, and breast MRI. NITOS categorization permits identification of temporal shifts in noninvasive diagnostic imaging by specific modality- and region-focused families, providing a granular understanding and reproducible analysis of global changes in imaging overall. Service family-level perspectives may help inform ongoing policy efforts to optimize imaging utilization and appropriateness.

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration.

PubMed

Young Kim, Eun; Johnson, Hans J

2013-01-01

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain

PubMed Central

Huppert, Theodore J.; Diamond, Solomon G.; Franceschini, Maria A.; Boas, David A.

2009-01-01

Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging tool for studying evoked hemodynamic changes within the brain. By this technique, changes in the optical absorption of light are recorded over time and are used to estimate the functionally evoked changes in cerebral oxyhemoglobin and deoxyhemoglobin concentrations that result from local cerebral vascular and oxygen metabolic effects during brain activity. Over the past three decades this technology has continued to grow, and today NIRS studies have found many niche applications in the fields of psychology, physiology, and cerebral pathology. The growing popularity of this technique is in part associated with a lower cost and increased portability of NIRS equipment when compared with other imaging modalities, such as functional magnetic resonance imaging and positron emission tomography. With this increasing number of applications, new techniques for the processing, analysis, and interpretation of NIRS data are continually being developed. We review some of the time-series and functional analysis techniques that are currently used in NIRS studies, we describe the practical implementation of various signal processing techniques for removing physiological, instrumental, and motion-artifact noise from optical data, and we discuss the unique aspects of NIRS analysis in comparison with other brain imaging modalities. These methods are described within the context of the MATLAB-based graphical user interface program, HomER, which we have developed and distributed to facilitate the processing of optical functional brain data. PMID:19340120

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas

PubMed Central

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G.; Leergaard, Trygve B.; Kirlangic, Mehmet E.; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time. PMID:27199682

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas.

PubMed

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G; Leergaard, Trygve B; Kirlangic, Mehmet E; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time.

Ultrasonic evaluation of the neonatal brain.

PubMed

Johnson, M L; Rumack, C M

1980-04-01

Ultrasound examination of the infant brain has been performed in selected medical centers for many years. However, the equipment necessary for obtaining satisfactory visualization of the brain has only recently become commercially available. Currently, ultrasonography is an excellent, noninvasive, inexpensive, rapid, and safe imaging modality for the evaluation of hydrocephalus and other pathologic conditions of the neonatal brain. Ventricular size can often be evaluated in infants up to two or three years of age, but a detailed image of the brain parenchyma becomes more difficult to obtain in a term infant after the first two to three months of life. With the use of the water path and high resolution, real-time systems and with the delineation of structures by multiple projections, (axial, coronal, sagittal and occipital), complex abnormalities may be delineated.

SEGMA: An Automatic SEGMentation Approach for Human Brain MRI Using Sliding Window and Random Forests

PubMed Central

Serag, Ahmed; Wilkinson, Alastair G.; Telford, Emma J.; Pataky, Rozalia; Sparrow, Sarah A.; Anblagan, Devasuda; Macnaught, Gillian; Semple, Scott I.; Boardman, James P.

2017-01-01

Quantitative volumes from brain magnetic resonance imaging (MRI) acquired across the life course may be useful for investigating long term effects of risk and resilience factors for brain development and healthy aging, and for understanding early life determinants of adult brain structure. Therefore, there is an increasing need for automated segmentation tools that can be applied to images acquired at different life stages. We developed an automatic segmentation method for human brain MRI, where a sliding window approach and a multi-class random forest classifier were applied to high-dimensional feature vectors for accurate segmentation. The method performed well on brain MRI data acquired from 179 individuals, analyzed in three age groups: newborns (38–42 weeks gestational age), children and adolescents (4–17 years) and adults (35–71 years). As the method can learn from partially labeled datasets, it can be used to segment large-scale datasets efficiently. It could also be applied to different populations and imaging modalities across the life course. PMID:28163680

Sexual dimorphism of volume reduction but not cognitive deficit in fetal alcohol spectrum disorders: A combined diffusion tensor imaging, cortical thickness and brain volume study.

PubMed

Treit, Sarah; Chen, Zhang; Zhou, Dongming; Baugh, Lauren; Rasmussen, Carmen; Andrew, Gail; Pei, Jacqueline; Beaulieu, Christian

2017-01-01

Quantitative magnetic resonance imaging (MRI) has revealed abnormalities in brain volumes, cortical thickness and white matter microstructure in fetal alcohol spectrum disorders (FASD); however, no study has reported all three measures within the same cohort to assess the relative magnitude of deficits, and few studies have examined sex differences. Participants with FASD (n = 70; 30 females; 5-32 years) and healthy controls (n = 74; 35 females; 5-32 years) underwent cognitive testing and MRI to assess cortical thickness, regional brain volumes and fractional anisotropy (FA)/mean diffusivity (MD) of white matter tracts. A significant effect of group, age-by-group, or sex-by-group was found for 9/9 volumes, 7/39 cortical thickness regions, 3/9 white matter tracts, and 9/10 cognitive tests, indicating group differences that in some cases differ by age or sex. Volume reductions for several structures were larger in males than females, despite similar deficits of cognition in both sexes. Correlations between brain structure and cognitive scores were found in females of both groups, but were notably absent in males. Correlations within a given MRI modality (e.g. total brain volume and caudate volume) were prevalent in both the control and FASD groups, and were more numerous than correlations between measurement types (e.g. volumes and diffusion tensor imaging) in either cohort. This multi-modal MRI study finds widespread differences of brain structure in participants with prenatal alcohol exposure, and to a greater extent in males than females which may suggest attenuation of the expected process of sexual dimorphism of brain structure during typical development.

Brain tumor image segmentation using kernel dictionary learning.

PubMed

Jeon Lee; Seung-Jun Kim; Rong Chen; Herskovits, Edward H

2015-08-01

Automated brain tumor image segmentation with high accuracy and reproducibility holds a big potential to enhance the current clinical practice. Dictionary learning (DL) techniques have been applied successfully to various image processing tasks recently. In this work, kernel extensions of the DL approach are adopted. Both reconstructive and discriminative versions of the kernel DL technique are considered, which can efficiently incorporate multi-modal nonlinear feature mappings based on the kernel trick. Our novel discriminative kernel DL formulation allows joint learning of a task-driven kernel-based dictionary and a linear classifier using a K-SVD-type algorithm. The proposed approaches were tested using real brain magnetic resonance (MR) images of patients with high-grade glioma. The obtained preliminary performances are competitive with the state of the art. The discriminative kernel DL approach is seen to reduce computational burden without much sacrifice in performance.

Potential of optical microangiography to monitor cerebral blood perfusion and vascular plasticity following traumatic brain injury in mice in vivo

NASA Astrophysics Data System (ADS)

Jia, Yali; Alkayed, Nabil; Wang, Ruikang K.

2009-07-01

Optical microanglography (OMAG) is a recently developed imaging modality capable of volumetric imaging of dynamic blood perfusion, down to capillary level resolution, with an imaging depth up to 2.00 mm beneath the tissue surface. We report the use of OMAG to monitor the cerebral blood flow (CBF) over the cortex of mouse brain upon traumatic brain injury (TBI), with the cranium left intact, for a period of two weeks on the same animal. We show the ability of OMAG to repeatedly image 3-D cerebral vasculatures during pre- and post-traumatic phases, and to visualize the changes of regulated CBF and the vascular plasticity after TBI. The results indicate the potential of OMAG to explore the mechanism involved in the rehabilitation of TBI.

Parallel workflow tools to facilitate human brain MRI post-processing

PubMed Central

Cui, Zaixu; Zhao, Chenxi; Gong, Gaolang

2015-01-01

Multi-modal magnetic resonance imaging (MRI) techniques are widely applied in human brain studies. To obtain specific brain measures of interest from MRI datasets, a number of complex image post-processing steps are typically required. Parallel workflow tools have recently been developed, concatenating individual processing steps and enabling fully automated processing of raw MRI data to obtain the final results. These workflow tools are also designed to make optimal use of available computational resources and to support the parallel processing of different subjects or of independent processing steps for a single subject. Automated, parallel MRI post-processing tools can greatly facilitate relevant brain investigations and are being increasingly applied. In this review, we briefly summarize these parallel workflow tools and discuss relevant issues. PMID:26029043

Impact of Single-Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) and Positron Emission Tomography/Computed Tomography (PET/CT) in the Diagnosis of Traumatic Brain Injury (TBI): Case Report.

PubMed

Molina-Vicenty, Irma L; Santiago-Sánchez, Michelaldemar; Vélez-Miró, Iván; Motta-Valencia, Keryl

2016-09-01

Traumatic brain injury (TBI) is defined as damage to the brain resulting from an external force. TBI, a global leading cause of death and disability, is associated with serious social, economic, and health problems. In cases of mild-to-moderate brain damage, conventional anatomical imaging modalities may or may not detect the cascade of metabolic changes that have occurred or are occurring at the intracellular level. Functional nuclear medicine imaging and neurophysiological parameters can be used to characterize brain damage, as the former provides direct visualization of brain function, even in the absence of overt behavioral manifestations or anatomical findings. We report the case of a 30-year-old Hispanic male veteran who, after 2 traumatic brain injury events, developed cognitive and neuropsychological problems with no clear etiology in the presence of negative computed tomography (CT) findings.

Music-of-Light Stethoscope: A Demonstration of the Photoacoustic Effect

ERIC Educational Resources Information Center

Nikitichev, D. I.; Xia, W.; Hill, E.; Mosse, C. A.; Perkins, T.; Konyn, K.; Ourselin, S.; Desjardins, A. E.; Vercauteren, T.

2016-01-01

In this paper we present a system aimed at demonstrating the photoacoustic (PA) effect for educational purposes. PA imaging is a hybrid imaging modality that requires no contrast agent and has a great potential for spine and brain lesion characterisation, breast cancer and blood flow monitoring notably in the context of fetal surgery. It relies on…

The production of digital and printed resources from multiple modalities using visualization and three-dimensional printing techniques.

PubMed

Shui, Wuyang; Zhou, Mingquan; Chen, Shi; Pan, Zhouxian; Deng, Qingqiong; Yao, Yong; Pan, Hui; He, Taiping; Wang, Xingce

2017-01-01

Virtual digital resources and printed models have become indispensable tools for medical training and surgical planning. Nevertheless, printed models of soft tissue organs are still challenging to reproduce. This study adopts open source packages and a low-cost desktop 3D printer to convert multiple modalities of medical images to digital resources (volume rendering images and digital models) and lifelike printed models, which are useful to enhance our understanding of the geometric structure and complex spatial nature of anatomical organs. Neuroimaging technologies such as CT, CTA, MRI, and TOF-MRA collect serial medical images. The procedures for producing digital resources can be divided into volume rendering and medical image reconstruction. To verify the accuracy of reconstruction, this study presents qualitative and quantitative assessments. Subsequently, digital models are archived as stereolithography format files and imported to the bundled software of the 3D printer. The printed models are produced using polylactide filament materials. We have successfully converted multiple modalities of medical images to digital resources and printed models for both hard organs (cranial base and tooth) and soft tissue organs (brain, blood vessels of the brain, the heart chambers and vessel lumen, and pituitary tumor). Multiple digital resources and printed models were provided to illustrate the anatomical relationship between organs and complicated surrounding structures. Three-dimensional printing (3DP) is a powerful tool to produce lifelike and tangible models. We present an available and cost-effective method for producing both digital resources and printed models. The choice of modality in medical images and the processing approach is important when reproducing soft tissue organs models. The accuracy of the printed model is determined by the quality of organ models and 3DP. With the ongoing improvement of printing techniques and the variety of materials available, 3DP will become an indispensable tool in medical training and surgical planning.

Gold Nanoparticles for Brain Tumor Imaging: A Systematic Review.

PubMed

Meola, Antonio; Rao, Jianghong; Chaudhary, Navjot; Sharma, Mayur; Chang, Steven D

2018-01-01

Demarcation of malignant brain tumor boundaries is critical to achieve complete resection and to improve patient survival. Contrast-enhanced brain magnetic resonance imaging (MRI) is the gold standard for diagnosis and pre-surgical planning, despite limitations of gadolinium (Gd)-based contrast agents to depict tumor margins. Recently, solid metal-based nanoparticles (NPs) have shown potential as diagnostic probes for brain tumors. Gold nanoparticles (GNPs) emerged among those, because of their unique physical and chemical properties and biocompatibility. The aim of the present study is to review the application of GNPs for in vitro and in vivo brain tumor diagnosis. We performed a PubMed search of reports exploring the application of GNPs in the diagnosis of brain tumors in biological models including cells, animals, primates, and humans. The search words were "gold" AND "NP" AND "brain tumor." Two reviewers performed eligibility assessment independently in an unblinded standardized manner. The following data were extracted from each paper: first author, year of publication, animal/cellular model, GNP geometry, GNP size, GNP coating [i.e., polyethylene glycol (PEG) and Gd], blood-brain barrier (BBB) crossing aids, imaging modalities, and therapeutic agents conjugated to the GNPs. The PubMed search provided 100 items. A total of 16 studies, published between the 2011 and 2017, were included in our review. No studies on humans were found. Thirteen studies were conducted in vivo on rodent models. The most common shape was a nanosphere (12 studies). The size of GNPs ranged between 20 and 120 nm. In eight studies, the GNPs were covered in PEG. The BBB penetration was increased by surface molecules (nine studies) or by means of external energy sources (in two studies). The most commonly used imaging modalities were MRI (four studies), surface-enhanced Raman scattering (three studies), and fluorescent microscopy (three studies). In two studies, the GNPs were conjugated with therapeutic agents. Experimental studies demonstrated that GNPs might be versatile, persistent, and safe contrast agents for multimodality imaging, thus enhancing the tumor edges pre-, intra-, and post-operatively improving microscopic precision. The diagnostic GNPs might also be used for multiple therapeutic approaches, namely as "theranostic" NPs.

Multimodal neural correlates of cognitive control in the Human Connectome Project.

PubMed

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function. Copyright © 2017 Elsevier Inc. All rights reserved.

Important considerations in lesion-symptom mapping: Illustrations from studies of word comprehension.

PubMed

Shahid, Hinna; Sebastian, Rajani; Schnur, Tatiana T; Hanayik, Taylor; Wright, Amy; Tippett, Donna C; Fridriksson, Julius; Rorden, Chris; Hillis, Argye E

2017-06-01

Lesion-symptom mapping is an important method of identifying networks of brain regions critical for functions. However, results might be influenced substantially by the imaging modality and timing of assessment. We tested the hypothesis that brain regions found to be associated with acute language deficits depend on (1) timing of behavioral measurement, (2) imaging sequences utilized to define the "lesion" (structural abnormality only or structural plus perfusion abnormality), and (3) power of the study. We studied 191 individuals with acute left hemisphere stroke with MRI and language testing to identify areas critical for spoken word comprehension. We use the data from this study to examine the potential impact of these three variables on lesion-symptom mapping. We found that only the combination of structural and perfusion imaging within 48 h of onset identified areas where more abnormal voxels was associated with more severe acute deficits, after controlling for lesion volume and multiple comparisons. The critical area identified with this methodology was the left posterior superior temporal gyrus, consistent with other methods that have identified an important role of this area in spoken word comprehension. Results have implications for interpretation of other lesion-symptom mapping studies, as well as for understanding areas critical for auditory word comprehension in the healthy brain. We propose that lesion-symptom mapping at the acute stage of stroke addresses a different sort of question about brain-behavior relationships than lesion-symptom mapping at the chronic stage, but that timing of behavioral measurement and imaging modalities should be considered in either case. Hum Brain Mapp 38:2990-3000, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A super-resolution ultrasound method for brain vascular mapping

PubMed Central

O'Reilly, Meaghan A.; Hynynen, Kullervo

2013-01-01

Purpose: High-resolution vascular imaging has not been achieved in the brain due to limitations of current clinical imaging modalities. The authors present a method for transcranial ultrasound imaging of single micrometer-size bubbles within a tube phantom. Methods: Emissions from single bubbles within a tube phantom were mapped through an ex vivo human skull using a sparse hemispherical receiver array and a passive beamforming algorithm. Noninvasive phase and amplitude correction techniques were applied to compensate for the aberrating effects of the skull bone. The positions of the individual bubbles were estimated beyond the diffraction limit of ultrasound to produce a super-resolution image of the tube phantom, which was compared with microcomputed tomography (micro-CT). Results: The resulting super-resolution ultrasound image is comparable to results obtained via the micro-CT for small tissue specimen imaging. Conclusions: This method provides superior resolution to deep-tissue contrast ultrasound and has the potential to be extended to provide complete vascular network imaging in the brain. PMID:24320408

Development of large field-of-view two photon microscopy for imaging mouse cortex (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bumstead, Jonathan; Côté, Daniel C.; Culver, Joseph P.

2017-02-01

Spontaneous neuronal activity has been measured at cellular resolution in mice, zebrafish, and C. elegans using optical sectioning microscopy techniques, such as light sheet microscopy (LSM) and two photon microscopy (TPM). Recent improvements in these modalities and genetically encoded calcium indicators (GECI's) have enabled whole brain imaging of calcium dynamics in zebrafish and C. elegans. However, these whole brain microscopy studies have not been extended to mice due to the limited field of view (FOV) of TPM and the cumbersome geometry of LSM. Conventional TPM is restricted to diffraction limited imaging over this small FOV (around 500 x 500 microns) due to the use of high magnification objectives (e.g. 1.0 NA; 20X) and the aberrations introduced by relay optics used in scanning the beam across the sample. To overcome these limitations, we have redesigned the entire optical path of the two photon microscope (scanning optics and objective lens) to support a field of view of Ø7 mm with relatively high spatial resolution (<10 microns). Using optical engineering software Zemax, we designed our system with commercially available optics that minimize astigmatism, field curvature, chromatic focal shift, and vignetting. Performance of the system was also tested experimentally with fluorescent beads in agarose, fixed samples, and in vivo structural imaging. Our large-FOV TPM provides a modality capable of studying distributed brain networks in mice at cellular resolution.

Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank.

PubMed

Alfaro-Almagro, Fidel; Jenkinson, Mark; Bangerter, Neal K; Andersson, Jesper L R; Griffanti, Ludovica; Douaud, Gwenaëlle; Sotiropoulos, Stamatios N; Jbabdi, Saad; Hernandez-Fernandez, Moises; Vallee, Emmanuel; Vidaurre, Diego; Webster, Matthew; McCarthy, Paul; Rorden, Christopher; Daducci, Alessandro; Alexander, Daniel C; Zhang, Hui; Dragonu, Iulius; Matthews, Paul M; Miller, Karla L; Smith, Stephen M

2018-02-01

UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Fully integrated reflection-mode photoacoustic, two-photon, and second harmonic generation microscopy in vivo

NASA Astrophysics Data System (ADS)

Song, Wei; Xu, Qiang; Zhang, Yang; Zhan, Yang; Zheng, Wei; Song, Liang

2016-08-01

The ability to obtain comprehensive structural and functional information from intact biological tissue in vivo is highly desirable for many important biomedical applications, including cancer and brain studies. Here, we developed a fully integrated multimodal microscopy that can provide photoacoustic (optical absorption), two-photon (fluorescence), and second harmonic generation (SHG) information from tissue in vivo, with intrinsically co-registered images. Moreover, using a delicately designed optical-acoustic coupling configuration, a high-frequency miniature ultrasonic transducer was integrated into a water-immersion optical objective, thus allowing all three imaging modalities to provide a high lateral resolution of ~290 nm with reflection-mode imaging capability, which is essential for studying intricate anatomy, such as that of the brain. Taking advantage of the complementary and comprehensive contrasts of the system, we demonstrated high-resolution imaging of various tissues in living mice, including microvasculature (by photoacoustics), epidermis cells, cortical neurons (by two-photon fluorescence), and extracellular collagen fibers (by SHG). The intrinsic image co-registration of the three modalities conveniently provided improved visualization and understanding of the tissue microarchitecture. The reported results suggest that, by revealing complementary tissue microstructures in vivo, this multimodal microscopy can potentially facilitate a broad range of biomedical studies, such as imaging of the tumor microenvironment and neurovascular coupling.

Near-Infrared Confocal Laser Reflectance Cytoarchitectural Imaging of the Substantia Nigra and Cerebellum in the Fresh Human Cadaver.

PubMed

Cheyuo, Cletus; Grand, Walter; Balos, Lucia L

2017-01-01

Cytoarchitectural neuroimaging remains critical for diagnosis of many brain diseases. Fluorescent dye-enhanced, near-infrared confocal in situ cellular imaging of the brain has been reported. However, impermeability of the blood-brain barrier to most fluorescent dyes limits clinical utility of this modality. The differential degree of reflectance from brain tissue with unenhanced near-infrared imaging may represent an alternative technique for in situ cytoarchitectural neuroimaging. We assessed the utility of unenhanced near-infrared confocal laser reflectance imaging of the cytoarchitecture of the cerebellum and substantia nigra in 2 fresh human cadaver brains using a confocal near-infrared laser probe. Cellular images based on near-infrared differential reflectance were captured at depths of 20-180 μm from the brain surface. Parts of the cerebellum and substantia nigra imaged using the probe were subsequently excised and stained with hematoxylin and eosin for histologic correlation. Near-infrared reflectance imaging revealed the 3-layered cytoarchitecture of the cerebellum, with Purkinje cells appearing hyperreflectant. In the substantia nigra, neurons appeared hyporeflectant with hyperreflectant neuromelanin cytoplasmic inclusions. Cytoarchitecture of the cerebellum and substantia nigra revealed on near-infrared imaging closely correlated with the histology on hematoxylin-eosin staining. We showed that unenhanced near-infrared reflectance imaging of fresh human cadaver brain can reliably identify and distinguish neurons and detailed cytoarchitecture of the cerebellum and substantia nigra. Copyright © 2016 Elsevier Inc. All rights reserved.

MRIVIEW: An interactive computational tool for investigation of brain structure and function

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

Ranken, D.; George, J.

MRIVIEW is a software system which uses image processing and visualization to provide neuroscience researchers with an integrated environment for combining functional and anatomical information. Key features of the software include semi-automated segmentation of volumetric head data and an interactive coordinate reconciliation method which utilizes surface visualization. The current system is a precursor to a computational brain atlas. We describe features this atlas will incorporate, including methods under development for visualizing brain functional data obtained from several different research modalities.

Molecular brain imaging in the multimodality era

PubMed Central

Price, Julie C

2012-01-01

Multimodality molecular brain imaging encompasses in vivo visualization, evaluation, and measurement of cellular/molecular processes. Instrumentation and software developments over the past 30 years have fueled advancements in multimodality imaging platforms that enable acquisition of multiple complementary imaging outcomes by either combined sequential or simultaneous acquisition. This article provides a general overview of multimodality neuroimaging in the context of positron emission tomography as a molecular imaging tool and magnetic resonance imaging as a structural and functional imaging tool. Several image examples are provided and general challenges are discussed to exemplify complementary features of the modalities, as well as important strengths and weaknesses of combined assessments. Alzheimer's disease is highlighted, as this clinical area has been strongly impacted by multimodality neuroimaging findings that have improved understanding of the natural history of disease progression, early disease detection, and informed therapy evaluation. PMID:22434068

Optical imaging of cell death in traumatic brain injury using a heat shock protein-90 alkylator

PubMed Central

Xie, B-W; Park, D; Van Beek, E R; Blankevoort, V; Orabi, Y; Que, I; Kaijzel, E L; Chan, A; Hogg, P J; Löwik, C W G M

2013-01-01

Traumatic brain injury is a major public health concern and is characterised by both apoptotic and necrotic cell death in the lesion. Anatomical imaging is usually used to assess traumatic brain injuries and there is a need for imaging modalities that provide complementary cellular information. We sought to non-invasively image cell death in a mouse model of traumatic brain injury using a near-infrared fluorescent conjugate of a synthetic heat shock protein-90 alkylator, 4-(N-(S-glutathionylacetyl) amino) phenylarsonous acid (GSAO). GSAO labels both apoptotic and necrotic cells coincident with loss of plasma membrane integrity. The optical GSAO specifically labelled apoptotic and necrotic cells in culture and did not accumulate in healthy organs or tissues in the living mouse body. The conjugate is a very effective imager of cell death in brain lesions. The optical GSAO was detected by fluorescence intensity and GSAO bound to dying/dead cells was detected from prolongation of the fluorescence lifetime. An optimal signal-to-background ratio was achieved as early as 3 h after injection of the probe and the signal intensity positively correlated with both lesion size and probe concentration. This optical GSAO offers a convenient and robust means to non-invasively image apoptotic and necrotic cell death in brain and other lesions. PMID:23348587

Multi-modal spectroscopic imaging with synchrotron light to study mechanisms of brain disease

NASA Astrophysics Data System (ADS)

Summers, Kelly L.; Fimognari, Nicholas; Hollings, Ashley; Kiernan, Mitchell; Lam, Virginie; Tidy, Rebecca J.; Takechi, Ryu; George, Graham N.; Pickering, Ingrid J.; Mamo, John C.; Harris, Hugh H.; Hackett, Mark J.

2017-04-01

The international health care costs associated with Alzheimer's disease (AD) and dementia have been predicted to reach $2 trillion USD by 2030. As such, there is urgent need to develop new treatments and diagnostic methods to stem an international health crisis. A major limitation to therapy and diagnostic development is the lack of complete understanding about the disease mechanisms. Spectroscopic methods at synchrotron light sources, such as FTIR, XRF, and XAS, offer a "multi-modal imaging platform" to reveal a wealth of important biochemical information in situ within ex vivo tissue sections, to increase our understanding of disease mechanisms.

Characterization and evaluation of ionizing and non-ionizing imaging systems used in state of the art image-guided radiation therapy techniques

NASA Astrophysics Data System (ADS)

Stanley, Dennis Nichols

With the growing incidence of cancer worldwide, the need for effective cancer treatment is paramount. Currently, radiation therapy exists as one of the few effective, non-invasive methods of reducing tumor size and has the capability for the elimination of localized tumors. Radiation therapy utilizes non-invasive external radiation to treat localized cancers but to be effective, physicians must be able to visualize and monitor the internal anatomy and target displacements. Image-Guided Radiation Therapy frequently utilizes planar and volumetric imaging during a course of radiation therapy to improve the precision and accuracy of the delivered treatment to the internal anatomy. Clinically, visualization of the internal anatomy allows physicians to refine the treatment to include as little healthy tissue as possible. This not only increases the effectiveness of treatment by damaging only the tumor but also increases the quality of life for the patient by decreasing the amount of healthy tissue damaged. Image-Guided Radiation Therapy is commonly used to treat tumors in areas of the body that are prone to movement, such as the lungs, liver, and prostate, as well as tumors located close to critical organs and tissues such as the tumors in the brain and spinal cord. Image-Guided Radiation Therapy can utilize both ionizing modalities, like x-ray based planar radiography and cone-beam CT, and nonionizing modalities like MRI, ultrasound and video-based optical scanning systems. Currently ionizing modalities are most commonly utilized for their ability to visualize and monitor internal anatomy but cause an increase to the total dose to the patient. Nonionizing imaging modalities allow frequent/continuous imaging without the increase in dose; however, they are just beginning to be clinically implemented in radiation oncology. With the growing prevalence and variety of Image-Guided Radiation Therapy imaging modalities the ability to evaluate the overall image quality, monitor the stability of the imaging systems and characterize each system are important to ensuring the consistency and effectiveness of the overall treatment. Image-Guided Radiation Therapy quality assurance allows a method of quantifying the accuracy and stability of the imaging systems. Understanding how the ionizing imaging systems operate and change over time allows for a more effective overall treatment and will be the focus of the first step of this project. In each of the first three aims, different ionizing imaging modalities will be evaluated for their temporal stability and a record of the determined tolerance level will be reported. The Second step of this project will be a characterization of the accuracy and performance of the new C-Rad CatalystHD a video-based, surface-imaging guided patient localization system. The catalyst will be analyzed for it accuracy of setup and patient positing, intra- and inter- fraction motion detection as well as its respiratory gating capabilities. The final step of this project will be to use the well-established accuracy of the XVI volumetric imaging system as a benchmark to assess the accuracy of the C-Rad CatalystHD system for use in pretreatment patient position verification for cranial stereotactic procedures. The treatment of brain lesions generally requires a very high degree of precision due to relatively small target sizes, close proximity to eloquent areas of the brain, and large, ablative doses being delivered. Stringent accuracy in imaging is needed to verify and monitor the correct spatial delivery of radiation throughout treatment. In order to investigate if the CatalystHD system is a capable imaging system for such deliveries, the system will need to be assessed and benchmarked against the XVI in a phantom geometry. By doing so, the currently unproven utility of the CatalystHD system for cranial stereotactic delivery may be established. (Abstract shortened by ProQuest.).

Endoscopic Full-Field Swept-Source Optical Coherence Tomography Neuroimaging System

NASA Astrophysics Data System (ADS)

Felts Almog, Ilan

Optical Coherence Tomography (OCT) has the capability to differentiate brain elements with intrinsic contrast and at a resolution an order-of-magnitude higher than other imaging modalities. This thesis investigates the feasibility of OCT for neuroimaging applied to neurosurgical guidance. We present, to our knowledge, the first Full-Field Swept-Source OCT system operating near a wavelength of 1310 nm, achieving a transverse imaging resolution of 6.5 mum, an axial resolution of 14 mum in tissue and a field of view of 270 mum x 180 mum x 400 mum. Imaging experiments were performed on rat brain tissues ex vivo, human cortical tissue ex vivo, and rats in vivo. A multi-level threshold metric applied on the intensity of the images led to a plausible correlation between the observed density and location in the brain. The proof-of-concept OCT system can be improved and miniaturized for clinical use.

Multi-modal imaging of long-term recovery post-stroke by positron emission tomography and matrix-assisted laser desorption/ionisation mass spectrometry.

PubMed

Henderson, Fiona; Hart, Philippa J; Pradillo, Jesus M; Kassiou, Michael; Christie, Lidan; Williams, Kaye J; Boutin, Herve; McMahon, Adam

2018-05-15

Stroke is a leading cause of disability worldwide. Understanding the recovery process post-stroke is essential; however, longer-term recovery studies are lacking. In vivo positron emission tomography (PET) can image biological recovery processes, but is limited by spatial resolution and its targeted nature. Untargeted mass spectrometry imaging offers high spatial resolution, providing an ideal ex vivo tool for brain recovery imaging. Magnetic resonance imaging (MRI) was used to image a rat brain 48 h after ischaemic stroke to locate the infarcted regions of the brain. PET was carried out 3 months post-stroke using the tracers [ 18 F]DPA-714 for TSPO and [ 18 F]IAM6067 for sigma-1 receptors to image neuroinflammation and neurodegeneration, respectively. The rat brain was flash-frozen immediately after PET scanning, and sectioned for matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) imaging. Three months post-stroke, PET imaging shows minimal detection of neurodegeneration and neuroinflammation, indicating that the brain has stabilised. However, MALDI-MS images reveal distinct differences in lipid distributions (e.g. phosphatidylcholine and sphingomyelin) between the scar and the healthy brain, suggesting that recovery processes are still in play. It is currently not known if the altered lipids in the scar will change on a longer time scale, or if they are stabilised products of the brain post-stroke. The data demonstrates the ability to combine MALD-MS with in vivo PET to image different aspects of stroke recovery. Copyright © 2018 John Wiley & Sons, Ltd.

Noninvasive photoacoustic computed tomography of mouse brain metabolism in vivo

NASA Astrophysics Data System (ADS)

Yao, Junjie; Xia, Jun; Maslov, Konstantin; Avanaki, Mohammadreza R. N.; Tsytsarev, Vassiliy; Demchenko, Alexei V.; Wang, Lihong V.

2013-03-01

To control the overall action of the body, brain consumes a large amount of energy in proportion to its volume. In humans and many other species, the brain gets most of its energy from oxygen-dependent metabolism of glucose. An abnormal metabolic rate of glucose and/or oxygen usually reflects a diseased status of brain, such as cancer or Alzheimer's disease. We have demonstrated the feasibility of imaging mouse brain metabolism using photoacoustic computed tomography (PACT), a fast, noninvasive and functional imaging modality with optical contrast and acoustic resolution. Brain responses to forepaw stimulations were imaged transdermally and transcranially. 2-NBDG, which diffuses well across the blood-brain-barrier, provided exogenous contrast for photoacoustic imaging of glucose response. Concurrently, hemoglobin provided endogenous contrast for photoacoustic imaging of hemodynamic response. Glucose and hemodynamic responses were quantitatively unmixed by using two-wavelength measurements. We found that glucose uptake and blood perfusion around the somatosensory region of the contralateral hemisphere were both increased by stimulations, indicating elevated neuron activity. The glucose response amplitude was about half that of the hemodynamic response. While the glucose response area was more homogenous and confined within the somatosensory region, the hemodynamic response area showed a clear vascular pattern and spread about twice as wide as that of the glucose response. The PACT of mouse brain metabolism was validated by high-resolution open-scalp OR-PAM and fluorescence imaging. Our results demonstrate that 2-NBDG-enhanced PACT is a promising tool for noninvasive studies of brain metabolism.

Pet Imaging Of The Chemistry Of The Brain

NASA Astrophysics Data System (ADS)

Wagner, Henry N., Jr.

1986-06-01

Advances in neurobiology today are as important as the advances in atomic physics at the turn of the century and molecular genetics in the 1950's. Positron-emission tomography is participating in these advances by making it possible for the first time to measure the chemistry of the living human brain in health and disease and to relate the changes at the molecular level to the functioning of the human mind. The amount of data generated requires modern data processing, display, and archiving capabilities. To achieve maximum benefit from the PET imaging and the derived quantitative measurements, the data must be combined with information, usually of a structural nature, from other imaging modalities, chiefly computed tomography and magnetic resonance imaging.

Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

NASA Astrophysics Data System (ADS)

Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

2015-03-01

Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

PubMed Central

Rockne, Russell C.; Trister, Andrew D.; Jacobs, Joshua; Hawkins-Daarud, Andrea J.; Neal, Maxwell L.; Hendrickson, Kristi; Mrugala, Maciej M.; Rockhill, Jason K.; Kinahan, Paul; Krohn, Kenneth A.; Swanson, Kristin R.

2015-01-01

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient's disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [18F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model–data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning. PMID:25540239

Siloxane nanoprobes for labeling and dual modality imaging of neural stem cells

PubMed Central

Addington, Caroline P.; Cusick, Alex; Shankar, Rohini Vidya; Agarwal, Shubhangi; Stabenfeldt, Sarah E.; Kodibagkar, Vikram D.

2015-01-01

Cell therapy represents a promising therapeutic for a myriad of medical conditions, including cancer, traumatic brain injury, and cardiovascular disease among others. A thorough understanding of the efficacy and cellular dynamics of these therapies necessitates the ability to non-invasively track cells in vivo. Magnetic resonance imaging (MRI) provides a platform to track cells as a non-invasive modality with superior resolution and soft tissue contrast. We recently reported a new nanoprobe platform for cell labeling and imaging using fluorophore doped siloxane core nanoemulsions as dual modality (1H MRI/Fluorescence), dual-functional (oximetry/detection) nanoprobes. Here, we successfully demonstrate the labeling, dual-modality imaging, and oximetry of neural progenitor/stem cells (NPSCs) in vitro using this platform. Labeling at a concentration of 10 μl/104 cells with a 40%v/v polydimethylsiloxane core nanoemulsion, doped with rhodamine, had minimal effect on viability, no effect on migration, proliferation and differentiation of NPSCs and allowed for unambiguous visualization of labeled NPSCs by 1H MR and fluorescence and local pO2 reporting by labeled NPSCs. This new approach for cell labeling with a positive contrast 1H MR probe has the potential to improve mechanistic knowledge of current therapies, and guide the design of future cell therapies due to its clinical translatability. PMID:26597417

A convergent functional architecture of the insula emerges across imaging modalities.

PubMed

Kelly, Clare; Toro, Roberto; Di Martino, Adriana; Cox, Christine L; Bellec, Pierre; Castellanos, F Xavier; Milham, Michael P

2012-07-16

Empirical evidence increasingly supports the hypothesis that patterns of intrinsic functional connectivity (iFC) are sculpted by a history of evoked coactivation within distinct neuronal networks. This, together with evidence of strong correspondence among the networks defined by iFC and those delineated using a variety of other neuroimaging techniques, suggests a fundamental brain architecture detectable across multiple functional and structural imaging modalities. Here, we leverage this insight to examine the functional organization of the human insula. We parcellated the insula on the basis of three distinct neuroimaging modalities - task-evoked coactivation, intrinsic (i.e., task-independent) functional connectivity, and gray matter structural covariance. Clustering of these three different covariance-based measures revealed a convergent elemental organization of the insula that likely reflects a fundamental brain architecture governing both brain structure and function at multiple spatial scales. While not constrained to be hierarchical, our parcellation revealed a pseudo-hierarchical, multiscale organization that was consistent with previous clustering and meta-analytic studies of the insula. Finally, meta-analytic examination of the cognitive and behavioral domains associated with each of the insular clusters obtained elucidated the broad functional dissociations likely underlying the topography observed. To facilitate future investigations of insula function across healthy and pathological states, the insular parcels have been made freely available for download via http://fcon_1000.projects.nitrc.org, along with the analytic scripts used to perform the parcellations. Copyright © 2012 Elsevier Inc. All rights reserved.

Composite PET and MRI for accurate localization and metabolic modeling: a very useful tool for research and clinic

NASA Astrophysics Data System (ADS)

Bidaut, Luc M.

1991-06-01

In order to help in analyzing PET data and really take advantage of their metabolic content, a system was designed and implemented to align and process data from various medical imaging modalities, particularly (but not only) for brain studies. Although this system is for now mostly used for anatomical localization, multi-modality ROIs and pharmaco-kinetic modeling, more multi-modality protocols will be implemented in the future, not only to help in PET reconstruction data correction and semi-automated ROI definition, but also for helping in improving diagnostic accuracy along with surgery and therapy planning.

The teen brain: insights from neuroimaging.

PubMed

Giedd, Jay N

2008-04-01

Few parents of a teenager are surprised to hear that the brain of a 16-year-old is different from the brain of an 8-year-old. Yet to pin down these differences in a rigorous scientific way has been elusive. Magnetic resonance imaging, with the capacity to provide exquisitely accurate quantifications of brain anatomy and physiology without the use of ionizing radiation, has launched a new era of adolescent neuroscience. Longitudinal studies of subjects from ages 3-30 years demonstrate a general pattern of childhood peaks of gray matter followed by adolescent declines, functional and structural increases in connectivity and integrative processing, and a changing balance between limbic/subcortical and frontal lobe functions, extending well into young adulthood. Although overinterpretation and premature application of neuroimaging findings for diagnostic purposes remains a risk, converging data from multiple imaging modalities is beginning to elucidate the implications of these brain changes on cognition, emotion, and behavior.

Functional magnetic resonance imaging in clinical practice: State of the art and science.

PubMed

Barras, Christen D; Asadi, Hamed; Baldeweg, Torsten; Mancini, Laura; Yousry, Tarek A; Bisdas, Sotirios

2016-11-01

Functional magnetic resonance imaging (fMRI) has become a mainstream neuroimaging modality in the assessment of patients being evaluated for brain tumour and epilepsy surgeries. Thus, it is important for doctors in primary care settings to be well acquainted with the present and potential future applications, as well as limitations, of this modality. The objective of this article is to introduce the theoretical principles and state-of-the-art clinical applications of fMRI in brain tumour and epilepsy surgery, with a focus on the implications for clinical primary care. fMRI enables non-invasive functional mapping of specific cortical tasks (eg motor, language, memory-based, visual), revealing information about functional localisation, anatomical variation in cortical function, and disease effects and adaptations, including the fascinating phenomenon of brain plasticity. fMRI is currently ordered by specialist neurologists and neurosurgeons for the purposes of pre-surgical assessment, and within the context of an experienced multidisciplinary team to prepare, conduct and interpret the scan. With an increasing number of patients undergoing fMRI, general practitioners can expect questions about the current and emerging role of fMRI in clinical care from these patients and their families.

Neurosurgical confocal endomicroscopy: A review of contrast agents, confocal systems, and future imaging modalities

PubMed Central

Zehri, Aqib H.; Ramey, Wyatt; Georges, Joseph F.; Mooney, Michael A.; Martirosyan, Nikolay L.; Preul, Mark C.; Nakaji, Peter

2014-01-01

Background: The clinical application of fluorescent contrast agents (fluorescein, indocyanine green, and aminolevulinic acid) with intraoperative microscopy has led to advances in intraoperative brain tumor imaging. Their properties, mechanism of action, history of use, and safety are analyzed in this report along with a review of current laser scanning confocal endomicroscopy systems. Additional imaging modalities with potential neurosurgical utility are also analyzed. Methods: A comprehensive literature search was performed utilizing PubMed and key words: In vivo confocal microscopy, confocal endomicroscopy, fluorescence imaging, in vivo diagnostics/neoplasm, in vivo molecular imaging, and optical imaging. Articles were reviewed that discussed clinically available fluorophores in neurosurgery, confocal endomicroscopy instrumentation, confocal microscopy systems, and intraoperative cancer diagnostics. Results: Current clinically available fluorescent contrast agents have specific properties that provide microscopic delineation of tumors when imaged with laser scanning confocal endomicroscopes. Other imaging modalities such as coherent anti-Stokes Raman scattering (CARS) microscopy, confocal reflectance microscopy, fluorescent lifetime imaging (FLIM), two-photon microscopy, and second harmonic generation may also have potential in neurosurgical applications. Conclusion: In addition to guiding tumor resection, intraoperative fluorescence and microscopy have the potential to facilitate tumor identification and complement frozen section analysis during surgery by providing real-time histological assessment. Further research, including clinical trials, is necessary to test the efficacy of fluorescent contrast agents and optical imaging instrumentation in order to establish their role in neurosurgery. PMID:24872922

Ex vivo brain tumor analysis using spectroscopic optical coherence tomography

NASA Astrophysics Data System (ADS)

Lenz, Marcel; Krug, Robin; Welp, Hubert; Schmieder, Kirsten; Hofmann, Martin R.

2016-03-01

A big challenge during neurosurgeries is to distinguish between healthy tissue and cancerous tissue, but currently a suitable non-invasive real time imaging modality is not available. Optical Coherence Tomography (OCT) is a potential technique for such a modality. OCT has a penetration depth of 1-2 mm and a resolution of 1-15 μm which is sufficient to illustrate structural differences between healthy tissue and brain tumor. Therefore, we investigated gray and white matter of healthy central nervous system and meningioma samples with a Spectral Domain OCT System (Thorlabs Callisto). Additional OCT images were generated after paraffin embedding and after the samples were cut into 10 μm thin slices for histological investigation with a bright field microscope. All samples were stained with Hematoxylin and Eosin. In all cases B-scans and 3D images were made. Furthermore, a camera image of the investigated area was made by the built-in video camera of our OCT system. For orientation, the backsides of all samples were marked with blue ink. The structural differences between healthy tissue and meningioma samples were most pronounced directly after removal. After paraffin embedding these differences diminished. A correlation between OCT en face images and microscopy images can be seen. In order to increase contrast, post processing algorithms were applied. Hence we employed Spectroscopic OCT, pattern recognition algorithms and machine learning algorithms such as k-means Clustering and Principal Component Analysis.

Multi Modality Brain Mapping System (MBMS) Using Artificial Intelligence and Pattern Recognition

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Kateb, Babak (Inventor)

2017-01-01

A Multimodality Brain Mapping System (MBMS), comprising one or more scopes (e.g., microscopes or endoscopes) coupled to one or more processors, wherein the one or more processors obtain training data from one or more first images and/or first data, wherein one or more abnormal regions and one or more normal regions are identified; receive a second image captured by one or more of the scopes at a later time than the one or more first images and/or first data and/or captured using a different imaging technique; and generate, using machine learning trained using the training data, one or more viewable indicators identifying one or abnormalities in the second image, wherein the one or more viewable indicators are generated in real time as the second image is formed. One or more of the scopes display the one or more viewable indicators on the second image.

Recent Developments in Molecular Brain Imaging of Neuropsychiatric Disorders.

PubMed

Slifstein, Mark; Abi-Dargham, Anissa

2017-01-01

Molecular imaging with PET or SPECT has been an important research tool in psychiatry for as long as these modalities have been available. Here, we discuss two areas of neuroimaging relevant to current psychiatry research. The first is the use of imaging to study neurotransmission. We discuss the use of pharmacologic probes to induce changes in levels of neurotransmitters that can be inferred through their effects on outcome measures of imaging experiments, from their historical origins focusing on dopamine transmission through recent developments involving serotonin, GABA, and glutamate. Next, we examine imaging of neuroinflammation in the context of psychiatry. Imaging markers of neuroinflammation have been studied extensively in other areas of brain research, but they have more recently attracted interest in psychiatry research, based on accumulating evidence that there may be an inflammatory component to some psychiatric conditions. Furthermore, new probes are under development that would allow unprecedented insights into cellular processes. In summary, molecular imaging would continue to offer great potential as a unique tool to further our understanding of brain function in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Multimodal Fusion with Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

PubMed Central

Qi, Shile; Calhoun, Vince D.; van Erp, Theo G. M.; Bustillo, Juan; Damaraju, Eswar; Turner, Jessica A.; Du, Yuhui; Chen, Jiayu; Yu, Qingbao; Mathalon, Daniel H.; Ford, Judith M.; Voyvodic, James; Mueller, Bryon A.; Belger, Aysenil; Ewen, Sarah Mc; Potkin, Steven G.; Preda, Adrian; Jiang, Tianzi

2017-01-01

Multimodal fusion is an effective approach to take advantage of cross-information among multiple imaging data to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. To date, there is increasing interest to uncover the neurocognitive mapping of specific behavioral measurement on enriched brain imaging data; hence, a supervised, goal-directed model that enables a priori information as a reference to guide multimodal data fusion is in need and a natural option. Here we proposed a fusion with reference model, called “multi-site canonical correlation analysis with reference plus joint independent component analysis” (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to reference information, such as cognitive scores. In a 3-way fusion simulation, the proposed method was compared with its alternatives on estimation accuracy of both target component decomposition and modality linkage detection. MCCAR+jICA outperforms others with higher precision. In human imaging data, working memory performance was utilized as a reference to investigate the covarying functional and structural brain patterns among 3 modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Interestingly, similar brain maps were identified between the two cohorts, with substantial overlap in the executive control networks in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports, while MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the potential of such results to identify potential neuromarkers for mental disorders. PMID:28708547

Simultaneous photoacoustic and optically mediated ultrasound microscopy: an in vivo study

PubMed Central

Orlova, Anna; Shirmanova, Marina; Postnikova, Anna; Turchin, Ilya

2015-01-01

We propose the use of thermoelastic (TE) excitation of an ultrasonic (US) detector by backscattered laser radiation as a means of upgrading a single-modality photoacoustic (PA) microscope to dual-modality PA/US imaging at minimal cost. The upgraded scanning head of our dual-modality microscope consists of a fiber bundle with 14 output arms and a 32MHz polyvinylidene difluoride (PVDF) detector with a 34 MHz bandwidth (−6 dB level), 12.7 mm focal length, and a 0.25 numerical aperture. A single optical pulse delivered through the fiber bundle to the biotissue being investigated, in combination with a metalized surface on the PVDF detector allows us to obtain both PA and US A-scans. To demonstrate the in vivo capabilities of the proposed method we present the results of bimodal imaging of the brain of a newborn rat, a mouse tail and a mouse tumor. PMID:25780752

Serial nonenhancing magnetic resonance imaging scans of high grade glioblastoma multiforme.

PubMed Central

Moore-Stovall, J.; Venkatesh, R.

1993-01-01

Magnetic resonance imaging (MRI) from clinical experience has proven to be superior to all other diagnostic imaging modalities, including computed tomography (CT) in the detection of intracranial neoplasms. Although glioblastoma multiforme presents a challenge for all diagnostic imaging modalities including MRI, MRI is paramount to CT in detecting subtle abnormal water accumulation in brain tissue caused by tumor even before there is disruption of the blood brain barrier. Currently, clinical research and investigational trials on nonionic gadolinium contrast agents have proven that nonionic gadolinium HP-DO3A (ProHance) contrast agents have lower osmolality and greater stability, which make them superior compounds to gadolinium diethylenetriamine-pentacetic acid (Gd-DTPA). Therefore, the nonionic gadolinium contrasts have been safely administered more rapidly, in higher or multiple doses for contrast enhanced MRI without adverse side effects or changes in serum iron or total bilirubin, and the intensity of the area of enhancement and number of lesions detected were superior to that of Gd-DTPA (Magnevist) at the standard dose (0.1 mmol/Kg). Perhaps if the nonionic gadolinium contrast agent, ProHance, had been approved by the Food and Drug Administration (FDA) when this MRI was performed in 1990 it would have aided in providing contrast enhancement and visualization of the tumor lesion to assist in patient diagnosis and management. Magnetic resonance imaging also provides unique multiplanar capabilities that allow for optimal visualization of the temporal and occipital lobes of the brain without bone interference.(ABSTRACT TRUNCATED AT 250 WORDS) Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9A Figure 9B Figure 10 Figure 11 Figure 12 Figure 13 PMID:8382751

Multiscale Imaging of the Mouse Cortex Using Two-Photon Microscopy and Wide-Field Illumination

NASA Astrophysics Data System (ADS)

Bumstead, Jonathan R.

The mouse brain can be studied over vast spatial scales ranging from microscopic imaging of single neurons to macroscopic measurements of hemodynamics acquired over the majority of the mouse cortex. However, most neuroimaging modalities are limited by a fundamental trade-off between the spatial resolution and the field-of-view (FOV) over which the brain can be imaged, making it difficult to fully understand the functional and structural architecture of the healthy mouse brain and its disruption in disease. My dissertation has focused on developing multiscale optical systems capable of imaging the mouse brain at both microscopic and mesoscopic spatial scales, specifically addressing the difference in spatial scales imaged with two-photon microscopy (TPM) and optical intrinsic signal imaging (OISI). Central to this work has been the formulation of a principled design strategy for extending the FOV of the two-photon microscope. Using this design approach, we constructed a TPM system with subcellular resolution and a FOV area 100 times greater than a conventional two-photon microscope. To image the ellipsoidal shape of the mouse cortex, we also developed the microscope to image arbitrary surfaces within a single frame using an electrically tunable lens. Finally, to address the speed limitations of the TPM systems developed during my dissertation, I also conducted research in large-scale neural phenomena occurring in the mouse brain imaged with high-speed OISI. The work conducted during my dissertation addresses some of the fundamental principles in designing and applying optical systems for multiscale imaging of the mouse brain.

Dissecting the pathobiology of altered MRI signal in amyotrophic lateral sclerosis: A post mortem whole brain sampling strategy for the integration of ultra-high-field MRI and quantitative neuropathology.

PubMed

Pallebage-Gamarallage, Menuka; Foxley, Sean; Menke, Ricarda A L; Huszar, Istvan N; Jenkinson, Mark; Tendler, Benjamin C; Wang, Chaoyue; Jbabdi, Saad; Turner, Martin R; Miller, Karla L; Ansorge, Olaf

2018-03-13

Amyotrophic lateral sclerosis (ALS) is a clinically and histopathologically heterogeneous neurodegenerative disorder, in which therapy is hindered by the rapid progression of disease and lack of biomarkers. Magnetic resonance imaging (MRI) has demonstrated its potential for detecting the pathological signature and tracking disease progression in ALS. However, the microstructural and molecular pathological substrate is poorly understood and generally defined histologically. One route to understanding and validating the pathophysiological correlates of MRI signal changes in ALS is to directly compare MRI to histology in post mortem human brains. The article delineates a universal whole brain sampling strategy of pathologically relevant grey matter (cortical and subcortical) and white matter tracts of interest suitable for histological evaluation and direct correlation with MRI. A standardised systematic sampling strategy that was compatible with co-registration of images across modalities was established for regions representing phosphorylated 43-kDa TAR DNA-binding protein (pTDP-43) patterns that were topographically recognisable with defined neuroanatomical landmarks. Moreover, tractography-guided sampling facilitated accurate delineation of white matter tracts of interest. A digital photography pipeline at various stages of sampling and histological processing was established to account for structural deformations that might impact alignment and registration of histological images to MRI volumes. Combined with quantitative digital histology image analysis, the proposed sampling strategy is suitable for routine implementation in a high-throughput manner for acquisition of large-scale histology datasets. Proof of concept was determined in the spinal cord of an ALS patient where multiple MRI modalities (T1, T2, FA and MD) demonstrated sensitivity to axonal degeneration and associated heightened inflammatory changes in the lateral corticospinal tract. Furthermore, qualitative comparison of R2* and susceptibility maps in the motor cortex of 2 ALS patients demonstrated varying degrees of hyperintense signal changes compared to a control. Upon histological evaluation of the same region, intensity of signal changes in both modalities appeared to correspond primarily to the degree of microglial activation. The proposed post mortem whole brain sampling methodology enables the accurate intraindividual study of pathological propagation and comparison with quantitative MRI data, to more fully understand the relationship of imaging signal changes with underlying pathophysiology in ALS.

Electroencephalographic imaging of higher brain function

NASA Technical Reports Server (NTRS)

Gevins, A.; Smith, M. E.; McEvoy, L. K.; Leong, H.; Le, J.

1999-01-01

High temporal resolution is necessary to resolve the rapidly changing patterns of brain activity that underlie mental function. Electroencephalography (EEG) provides temporal resolution in the millisecond range. However, traditional EEG technology and practice provide insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. Recent advances help to overcome this problem by recording EEGs from more electrodes, by registering EEG data with anatomical images, and by correcting the distortion caused by volume conduction of EEG signals through the skull and scalp. In addition, statistical measurements of sub-second interdependences between EEG time-series recorded from different locations can help to generate hypotheses about the instantaneous functional networks that form between different cortical regions during perception, thought and action. Example applications are presented from studies of language, attention and working memory. Along with its unique ability to monitor brain function as people perform everyday activities in the real world, these advances make modern EEG an invaluable complement to other functional neuroimaging modalities.

Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

PubMed Central

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C.

2015-01-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data,, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked auto-encoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework image registration experiments were conducted on 7.0-tesla brain MR images. In all experiments, the results showed the new image registration framework consistently demonstrated more accurate registration results when compared to state-of-the-art. PMID:26552069

Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

PubMed

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C; Shen, Dinggang

2016-07-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art.

Laser Polarized 129Xe Magnetic Resonance Imaging and Spectroscopy Studies: Development of a New Modality of Functional Imaging

NASA Astrophysics Data System (ADS)

Rosen, M.; Coulter, K. P.; Chupp, T. E.; Swanson, S. D.; Agranoff, B. W.

1996-05-01

One of the most exciting prospects for the application of laser polarized noble gas magnetic resonance imaging and spectroscopy of ^129Xe is the quantitative measurement of cerebral blood flow changes in response to various stimuli. Development of this new modality of functional imaging requires tracking the transport of inspirated laser polarized ^129Xe from the lungs to the blood and to the brain. We describe a series of experiments with rats that include producing noble gas magnetic resonance images and study of the uptake and transport of polarized ^129Xe in the blood and to the head. We have observed spectral components of the ^129Xe at about -200 ppm relative to the free gas and confirmed their transport to the head. The time dependence of this component in the head has been studied. Current efforts are to spatially localize the polarized ^129Xe and image the magnetization in the steady state.

Multimodal Imaging of Alzheimer Pathophysiology in the Brain's Default Mode Network

DOE PAGES

Shin, Jonghan; Kepe, Vladimir; Small, Gary W.; ...

2011-01-01

The spatial correlations between the brain's default mode network (DMN) and the brain regions known to develop pathophysiology in Alzheimer's disease (AD) have recently attracted much attention. In this paper, we compare results of different functional and structural imaging modalities, including MRI and PET, and highlight different patterns of anomalies observed within the DMN. Multitracer PET imaging in subjects with and without dementia has demonstrated that [C-11]PIB- and [F-18]FDDNP-binding patterns in patients with AD overlap within nodes of the brain's default network including the prefrontal, lateral parietal, lateral temporal, and posterior cingulate cortices, with the exception of the medial temporalmore » cortex (especially, the hippocampus) where significant discrepancy between increased [F-18]FDDNP binding and negligible [C-11]PIB-binding was observed. [F-18]FDDNP binding in the medial temporal cortex—a key constituent of the DMN—coincides with both the presence of amyloid and tau pathology, and also with cortical areas with maximal atrophy as demonstrated by T1-weighted MR imaging of AD patients.« less

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

PubMed

Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

2015-08-01

Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

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.

Multichannel optical brain imaging to separate cerebral vascular, tissue metabolic, and neuronal effects of cocaine

NASA Astrophysics Data System (ADS)

Ren, Hugang; Luo, Zhongchi; Yuan, Zhijia; Pan, Yingtian; Du, Congwu

2012-02-01

Characterization of cerebral hemodynamic and oxygenation metabolic changes, as well neuronal function is of great importance to study of brain functions and the relevant brain disorders such as drug addiction. Compared with other neuroimaging modalities, optical imaging techniques have the potential for high spatiotemporal resolution and dissection of the changes in cerebral blood flow (CBF), blood volume (CBV), and hemoglobing oxygenation and intracellular Ca ([Ca2+]i), which serves as markers of vascular function, tissue metabolism and neuronal activity, respectively. Recently, we developed a multiwavelength imaging system and integrated it into a surgical microscope. Three LEDs of λ1=530nm, λ2=570nm and λ3=630nm were used for exciting [Ca2+]i fluorescence labeled by Rhod2 (AM) and sensitizing total hemoglobin (i.e., CBV), and deoxygenated-hemoglobin, whereas one LD of λ1=830nm was used for laser speckle imaging to form a CBF mapping of the brain. These light sources were time-sharing for illumination on the brain and synchronized with the exposure of CCD camera for multichannel images of the brain. Our animal studies indicated that this optical approach enabled simultaneous mapping of cocaine-induced changes in CBF, CBV and oxygenated- and deoxygenated hemoglobin as well as [Ca2+]i in the cortical brain. Its high spatiotemporal resolution (30μm, 10Hz) and large field of view (4x5 mm2) are advanced as a neuroimaging tool for brain functional study.

Tracking short-term biodistribution and long-term clearance of SPIO tracers in magnetic particle imaging

NASA Astrophysics Data System (ADS)

Keselman, Paul; Yu, Elaine Y.; Zhou, Xinyi Y.; Goodwill, Patrick W.; Chandrasekharan, Prashant; Ferguson, R. Matthew; Khandhar, Amit P.; Kemp, Scott J.; Krishnan, Kannan M.; Zheng, Bo; Conolly, Steven M.

2017-05-01

Magnetic particle imaging (MPI) is an emerging tracer-based medical imaging modality that images non-radioactive, kidney-safe superparamagnetic iron oxide (SPIO) tracers. MPI offers quantitative, high-contrast and high-SNR images, so MPI has exceptional promise for applications such as cell tracking, angiography, brain perfusion, cancer detection, traumatic brain injury and pulmonary imaging. In assessing MPI’s utility for applications mentioned above, it is important to be able to assess tracer short-term biodistribution as well as long-term clearance from the body. Here, we describe the biodistribution and clearance for two commonly used tracers in MPI: Ferucarbotran (Meito Sangyo Co., Japan) and LS-oo8 (LodeSpin Labs, Seattle, WA). We successfully demonstrate that 3D MPI is able to quantitatively assess short-term biodistribution, as well as long-term tracking and clearance of these tracers in vivo.

Magnetic Resonance Imaging to Detect Early Molecular and Cellular Changes in Alzheimer's Disease.

PubMed

Knight, Michael J; McCann, Bryony; Kauppinen, Risto A; Coulthard, Elizabeth J

2016-01-01

Recent pharmaceutical trials have demonstrated that slowing or reversing pathology in Alzheimer's disease is likely to be possible only in the earliest stages of disease, perhaps even before significant symptoms develop. Pathology in Alzheimer's disease accumulates for well over a decade before symptoms are detected giving a large potential window of opportunity for intervention. It is therefore important that imaging techniques detect subtle changes in brain tissue before significant macroscopic brain atrophy. Current diagnostic techniques often do not permit early diagnosis or are too expensive for routine clinical use. Magnetic Resonance Imaging (MRI) is the most versatile, affordable, and powerful imaging modality currently available, being able to deliver detailed analyses of anatomy, tissue volumes, and tissue state. In this mini-review, we consider how MRI might detect patients at risk of future dementia in the early stages of pathological change when symptoms are mild. We consider the contributions made by the various modalities of MRI (structural, diffusion, perfusion, relaxometry) in identifying not just atrophy (a late-stage AD symptom) but more subtle changes reflective of early dementia pathology. The sensitivity of MRI not just to gross anatomy but to the underlying "health" at the cellular (and even molecular) scales, makes it very well suited to this task.

Optical imaging of the rat brain suggests a previously missing link between top-down and bottom-up nervous system function

PubMed Central

Greenfield, Susan A.; Badin, Antoine-Scott; Ferrati, Giovanni; Devonshire, Ian M.

2017-01-01

Abstract. Optical imaging with voltage-sensitive dyes enables the visualization of extensive yet highly transient coalitions of neurons (assemblies) operating throughout the brain on a subsecond time scale. We suggest that operating at the mesoscale level of brain organization, neuronal assemblies may provide a functional link between “bottom-up” cellular mechanisms and “top-down” cognitive ones within anatomically defined regions. We demonstrate in ex vivo rat brain slices how varying spatiotemporal dynamics of assemblies reveal differences not previously appreciated between: different stages of development in cortical versus subcortical brain areas, different sensory modalities (hearing versus vision), different classes of psychoactive drugs (anesthetics versus analgesics), different effects of anesthesia linked to hyperbaric conditions and, in vivo, depths of anesthesia. The strategy of voltage-sensitive dye imaging is therefore as powerful as it is versatile and as such can now be applied to the evaluation of neurochemical signaling systems and the screening of related new drugs, as well as to mathematical modeling and, eventually, even theories of consciousness. PMID:28573153

Optical imaging of the rat brain suggests a previously missing link between top-down and bottom-up nervous system function.

PubMed

Greenfield, Susan A; Badin, Antoine-Scott; Ferrati, Giovanni; Devonshire, Ian M

2017-07-01

Optical imaging with voltage-sensitive dyes enables the visualization of extensive yet highly transient coalitions of neurons (assemblies) operating throughout the brain on a subsecond time scale. We suggest that operating at the mesoscale level of brain organization, neuronal assemblies may provide a functional link between "bottom-up" cellular mechanisms and "top-down" cognitive ones within anatomically defined regions. We demonstrate in ex vivo rat brain slices how varying spatiotemporal dynamics of assemblies reveal differences not previously appreciated between: different stages of development in cortical versus subcortical brain areas, different sensory modalities (hearing versus vision), different classes of psychoactive drugs (anesthetics versus analgesics), different effects of anesthesia linked to hyperbaric conditions and, in vivo , depths of anesthesia. The strategy of voltage-sensitive dye imaging is therefore as powerful as it is versatile and as such can now be applied to the evaluation of neurochemical signaling systems and the screening of related new drugs, as well as to mathematical modeling and, eventually, even theories of consciousness.

Neuroimaging effects of prenatal alcohol exposure on the developing human brain: a magnetic resonance imaging review.

PubMed

Donald, Kirsten Ann; Eastman, Emma; Howells, Fleur Margaret; Adnams, Colleen; Riley, Edward Patrick; Woods, Roger Paul; Narr, Katherine Louise; Stein, Dan Joseph

2015-10-01

This paper reviews the magnetic resonance imaging (MRI) literature on the effects of prenatal alcohol exposure on the developing human brain. A literature search was conducted through the following databases: PubMed, PsycINFO and Google Scholar. Combinations of the following search terms and keywords were used to identify relevant studies: 'alcohol', 'fetal alcohol spectrum disorders', 'fetal alcohol syndrome', 'FAS', 'FASD', 'MRI', 'DTI', 'MRS', 'neuroimaging', 'children' and 'infants'. A total of 64 relevant articles were identified across all modalities. Overall, studies reported smaller total brain volume as well as smaller volume of both the white and grey matter in specific cortical regions. The most consistently reported structural MRI findings were alterations in the shape and volume of the corpus callosum, as well as smaller volume in the basal ganglia and hippocampi. The most consistent finding from diffusion tensor imaging studies was lower fractional anisotropy in the corpus callosum. Proton magnetic resonance spectroscopy studies are few to date, but showed altered neurometabolic profiles in the frontal and parietal cortex, thalamus and dentate nuclei. Resting-state functional MRI studies reported reduced functional connectivity between cortical and deep grey matter structures. Discussion There is a critical gap in the literature of MRI studies in alcohol-exposed children under 5 years of age across all MRI modalities. The dynamic nature of brain maturation and appreciation of the effects of alcohol exposure on the developing trajectory of the structural and functional network argue for the prioritisation of studies that include a longitudinal approach to understanding this spectrum of effects and potential therapeutic time points.

Bioimpedance imaging: an overview of potential clinical applications.

PubMed

Bayford, Richard; Tizzard, Andrew

2012-10-21

Electrical Impedance Tomography (EIT) is an imaging technique based on multiple bio impedance measurements to produce a map (image) of impedance or changes in impedance across a region. Its origins lay in geophysics where it is still used to today. This review highlights potential clinical applications of EIT. Beginning with a brief overview of the underlying principles behind the modality, it describes the background research leading towards the development of the application of EIT for monitoring pulmonary function, detecting and localising tumours and monitoring brain function.

Optical coherence tomography of the preterm eye: from retinopathy of prematurity to brain development

PubMed Central

Rothman, Adam L; Mangalesh, Shwetha; Chen, Xi; Toth, Cynthia A

2016-01-01

Preterm infants with retinopathy of prematurity are at increased risk of poor neurodevelopmental outcomes. Because the neurosensory retina is an extension of the central nervous system, anatomic abnormalities in the anterior visual pathway often relate to system and central nervous system health. We describe optical coherence tomography as a powerful imaging modality that has recently been adapted to the infant population and provides noninvasive, high-resolution, cross-sectional imaging of the infant eye at the bedside. Optical coherence tomography has increased understanding of normal eye development and has identified several potential biomarkers of brain abnormalities and poorer neurodevelopment. PMID:28539807

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function

PubMed Central

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D.

2009-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings. PMID:19834575

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function.

PubMed

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D

2008-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings.

Intraoperative Functional Ultrasound Imaging of Human Brain Activity.

PubMed

Imbault, Marion; Chauvet, Dorian; Gennisson, Jean-Luc; Capelle, Laurent; Tanter, Mickael

2017-08-04

The functional mapping of brain activity is essential to perform optimal glioma surgery and to minimize the risk of postoperative deficits. We introduce a new, portable neuroimaging modality of the human brain based on functional ultrasound (fUS) for deep functional cortical mapping. Using plane-wave transmissions at an ultrafast frame rate (1 kHz), fUS is performed during surgery to measure transient changes in cerebral blood volume with a high spatiotemporal resolution (250 µm, 1 ms). fUS identifies, maps and differentiates regions of brain activation during task-evoked cortical responses within the depth of a sulcus in both awake and anaesthetized patients.

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography

PubMed Central

Niso, Guiomar; Gorgolewski, Krzysztof J.; Bock, Elizabeth; Brooks, Teon L.; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N.; Jas, Mainak; Litvak, Vladimir; T. Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-01-01

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone. PMID:29917016

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography.

PubMed

Niso, Guiomar; Gorgolewski, Krzysztof J; Bock, Elizabeth; Brooks, Teon L; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N; Jas, Mainak; Litvak, Vladimir; T Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-06-19

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone.

Development of magneto-plasmonic nanoparticles for multimodal image-guided therapy to the brain.

PubMed

Tomitaka, Asahi; Arami, Hamed; Raymond, Andrea; Yndart, Adriana; Kaushik, Ajeet; Jayant, Rahul Dev; Takemura, Yasushi; Cai, Yong; Toborek, Michal; Nair, Madhavan

2017-01-05

Magneto-plasmonic nanoparticles are one of the emerging multi-functional materials in the field of nanomedicine. Their potential for targeting and multi-modal imaging is highly attractive. In this study, magnetic core/gold shell (MNP@Au) magneto-plasmonic nanoparticles were synthesized by citrate reduction of Au ions on magnetic nanoparticle seeds. Hydrodynamic size and optical properties of magneto-plasmonic nanoparticles synthesized with the variation of Au ions and reducing agent concentrations were evaluated. The synthesized magneto-plasmonic nanoparticles exhibited superparamagnetic properties, and their magnetic properties contributed to the concentration-dependent contrast in magnetic resonance imaging (MRI). The imaging contrast from the gold shell part of the magneto-plasmonic nanoparticles was also confirmed by X-ray computed tomography (CT). The transmigration study of the magneto-plasmonic nanoparticles using an in vitro blood-brain barrier (BBB) model proved enhanced transmigration efficiency without disrupting the integrity of the BBB, and showed potential to be used for brain diseases and neurological disorders.

Robust Transient Dynamics and Brain Functions

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo

2011-01-01

In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques) has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc., have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework – heteroclinic sequential dynamics – to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i) within the same modality, (ii) among different modalities from the same family (like perception), and (iii) among modalities from different families (like emotion and cognition). The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential) dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory – a vital cognitive function –, and to find specific dynamical signatures – different kinds of instabilities – of several brain functions and mental diseases. PMID:21716642

Resting state brain networks and their implications in neurodegenerative disease

NASA Astrophysics Data System (ADS)

Sohn, William S.; Yoo, Kwangsun; Kim, Jinho; Jeong, Yong

2012-10-01

Neurons are the basic units of the brain, and form network by connecting via synapses. So far, there have been limited ways to measure the brain networks. Recently, various imaging modalities are widely used for this purpose. In this paper, brain network mapping using resting state fMRI will be introduced with several applications including neurodegenerative disease such as Alzheimer's disease, frontotemporal lobar degeneration and Parkinson's disease. The resting functional connectivity using intrinsic functional connectivity in mouse is useful since we can take advantage of perturbation or stimulation of certain nodes of the network. The study of brain connectivity will open a new era in understanding of brain and diseases thus will be an essential foundation for future research.

Gold nanoparticles for photoacoustic imaging

PubMed Central

Li, Wanwan; Chen, Xiaoyuan

2015-01-01

Photoacoustic (PA) imaging is a biomedical imaging modality that provides functional information regarding the cellular and molecular signatures of tissue by using endogenous and exogenous contrast agents. There has been tremendous effort devoted to the development of PA imaging agents, and gold nanoparticles as exogenous contrast agents have great potential for PA imaging due to their inherent and geometrically induced optical properties. The gold-based nanoparticles that are most commonly employed for PA imaging include spheres, rods, shells, prisms, cages, stars and vesicles. This article provides an overview of the current state of research in utilizing these gold nanomaterials for PA imaging of cancer, atherosclerotic plaques, brain function and image-guided therapy. PMID:25600972

Paramagnetic perfluorocarbon-filled albumin-(Gd-DTPA) microbubbles for the induction of focused-ultrasound-induced blood-brain barrier opening and concurrent MR and ultrasound imaging

NASA Astrophysics Data System (ADS)

Liao, Ai-Ho; Liu, Hao-Li; Su, Chia-Hao; Hua, Mu-Yi; Yang, Hung-Wei; Weng, Yu-Ting; Hsu, Po-Hung; Huang, Sheng-Min; Wu, Shih-Yen; Wang, Hsin-Ell; Yen, Tzu-Chen; Li, Pai-Chi

2012-05-01

This paper presents new albumin-shelled Gd-DTPA microbubbles (MBs) that can concurrently serve as a dual-modality contrast agent for ultrasound (US) imaging and magnetic resonance (MR) imaging to assist blood-brain barrier (BBB) opening and detect intracerebral hemorrhage (ICH) during focused ultrasound brain drug delivery. Perfluorocarbon-filled albumin-(Gd-DTPA) MBs were prepared with a mean diameter of 2320 nm and concentration of 2.903×109 MBs ml-1 using albumin-(Gd-DTPA) and by sonication with perfluorocarbon (C3F8) gas. The albumin-(Gd-DTPA) MBs were then centrifuged and the procedure was repeated until the free Gd3+ ions were eliminated (which were detected by the xylenol orange sodium salt solution). The albumin-(Gd-DTPA) MBs were also characterized and evaluated both in vitro and in vivo by US and MR imaging. Focused US was used with the albumin-(Gd-DTPA) MBs to induce disruption of the BBB in 18 rats. BBB disruption was confirmed with contrast-enhanced T1-weighted turbo-spin-echo sequence MR imaging. Heavy T2*-weighted 3D fast low-angle shot sequence MR imaging was used to detect ICH. In vitro US imaging experiments showed that albumin-(Gd-DTPA) MBs can significantly enhance the US contrast in T1-, T2- and T2*-weighted MR images. The r1 and r2 relaxivities for Gd-DTPA were 7.69 and 21.35 s-1mM-1, respectively, indicating that the MBs represent a positive contrast agent in T1-weighted images. In vivo MR imaging experiments on 18 rats showed that focused US combined with albumin-(Gd-DTPA) MBs can be used to both induce disruption of the BBB and detect ICH. To compare the signal intensity change between pure BBB opening and BBB opening accompanying ICH, albumin-(Gd-DTPA) MB imaging can provide a ratio of 5.14 with significant difference (p = 0.026), whereas Gd-DTPA imaging only provides a ratio of 2.13 and without significant difference (p = 0.108). The results indicate that albumin-(Gd-DTPA) MBs have potential as a US/MR dual-modality contrast agent for BBB opening and differentiating focused-US-induced BBB opening from ICH, and can monitor the focused ultrasound brain drug delivery process.

Paramagnetic perfluorocarbon-filled albumin-(Gd-DTPA) microbubbles for the induction of focused-ultrasound-induced blood-brain barrier opening and concurrent MR and ultrasound imaging.

PubMed

Liao, Ai-Ho; Liu, Hao-Li; Su, Chia-Hao; Hua, Mu-Yi; Yang, Hung-Wei; Weng, Yu-Ting; Hsu, Po-Hung; Huang, Sheng-Min; Wu, Shih-Yen; Wang, Hsin-Ell; Yen, Tzu-Chen; Li, Pai-Chi

2012-05-07

This paper presents new albumin-shelled Gd-DTPA microbubbles (MBs) that can concurrently serve as a dual-modality contrast agent for ultrasound (US) imaging and magnetic resonance (MR) imaging to assist blood-brain barrier (BBB) opening and detect intracerebral hemorrhage (ICH) during focused ultrasound brain drug delivery. Perfluorocarbon-filled albumin-(Gd-DTPA) MBs were prepared with a mean diameter of 2320 nm and concentration of 2.903×10(9) MBs ml(-1) using albumin-(Gd-DTPA) and by sonication with perfluorocarbon (C(3)F(8)) gas. The albumin-(Gd-DTPA) MBs were then centrifuged and the procedure was repeated until the free Gd(3+) ions were eliminated (which were detected by the xylenol orange sodium salt solution). The albumin-(Gd-DTPA) MBs were also characterized and evaluated both in vitro and in vivo by US and MR imaging. Focused US was used with the albumin-(Gd-DTPA) MBs to induce disruption of the BBB in 18 rats. BBB disruption was confirmed with contrast-enhanced T(1)-weighted turbo-spin-echo sequence MR imaging. Heavy T(2)*-weighted 3D fast low-angle shot sequence MR imaging was used to detect ICH. In vitro US imaging experiments showed that albumin-(Gd-DTPA) MBs can significantly enhance the US contrast in T(1)-, T(2)- and T(2)*-weighted MR images. The r(1) and r(2) relaxivities for Gd-DTPA were 7.69 and 21.35 s(-1)mM(-1), respectively, indicating that the MBs represent a positive contrast agent in T(1)-weighted images. In vivo MR imaging experiments on 18 rats showed that focused US combined with albumin-(Gd-DTPA) MBs can be used to both induce disruption of the BBB and detect ICH. To compare the signal intensity change between pure BBB opening and BBB opening accompanying ICH, albumin-(Gd-DTPA) MB imaging can provide a ratio of 5.14 with significant difference (p = 0.026), whereas Gd-DTPA imaging only provides a ratio of 2.13 and without significant difference (p = 0.108). The results indicate that albumin-(Gd-DTPA) MBs have potential as a US/MR dual-modality contrast agent for BBB opening and differentiating focused-US-induced BBB opening from ICH, and can monitor the focused ultrasound brain drug delivery process.

Alteration of diffusion-tensor MRI measures in brain regions involved in early stages of Parkinson's disease.

PubMed

Chen, Nan-Kuei; Chou, Ying-Hui; Sundman, Mark; Hickey, Patrick; Kasoff, Willard S; Bernstein, Adam; Trouard, Theodore P; Lin, Tanya; Rapcsak, Steven Z; Sherman, Scott J; Weingarten, Carol

2018-06-07

Many non-motor symptoms (e.g., hyposmia) appear years before the cardinal motor features of Parkinson's disease (PD). It is thus desirable to be able to use noninvasive brain imaging methods, such as magnetic resonance imaging (MRI), to detect brain abnormalities in early PD stages. Among the MRI modalities, diffusion tensor imaging (DTI) is suitable for detecting changes of brain tissue structure due to neurological diseases. The main purpose of this study was to investigate whether DTI signals measured from brain regions involved in early stages of PD differ from those of healthy controls. To answer this question, we analyzed whole-brain DTI data of 30 early-stage PD patients and 30 controls using improved ROI based analysis methods. Results showed that 1) the fractional anisotropy (FA) values in the olfactory tract (connected with the olfactory bulb: one of the first structures affected by PD) are lower in PD patients than healthy controls; 2) FA values are higher in PD patients than healthy controls in the following brain regions: corticospinal tract, cingulum (near hippocampus), and superior longitudinal fasciculus (temporal part). Experimental results suggest that the tissue property, measured by FA, in olfactory regions is structurally modulated by PD with a mechanism that is different from other brain regions.

A novel non-contrast-enhanced MRA using silent scan for evaluation of brain arteriovenous malformation: A case report and review of literature.

PubMed

Moon, Jin Il; Baek, Hye Jin; Ryu, Kyeong Hwa; Park, Hyun

2017-11-01

Brain arteriovenous malformations (AVMs) are congenital vascular abnormalities involving abnormal connections between arteries and veins. In clinical practice, imaging studies help evaluate feeding arteries, niduses, draining venous systems, and coexisting complications in patients with brain AVM. They also have an impact on decision-making regarding clinical management. We applied a novel non-contrast-enhanced MR angiography (MRA) technique, termed "silent MRA," for evaluating an incidental brain AVM. Here, we describe the clinical case with radiological review and highlight the technical background and clinical usefulness of silent MRA. A 60-year-old woman underwent neuroimaging study including MRA to evaluate intracranial cause of headache. The brain AVM, including its nidus and draining veins, was conspicuously delineated on silent MRA images; these findings correlated well with conventional angiographic findings. The patient did not receive interventional or surgical treatment. The patient is being followed up regularly at the outpatient department. The silent MRA can be a suitable imaging modality for repeated follow-up evaluation for not only brain AVMs but also various intracranial vascular diseases without the use of contrast materials.

Mapping the Critical Gestational Age at Birth that Alters Brain Development in Preterm-born Infants using Multi-Modal MRI

PubMed Central

Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi

2017-01-01

Preterm birth adversely affects postnatal brain development. In order to investigate the critical gestational age at birth (GAB) that alters the developmental trajectory of gray and white matter structures in the brain, we investigated diffusion tensor and quantitative T2 mapping data in 43 term-born and 43 preterm-born infants. A novel multivariate linear model—the change point model, was applied to detect change points in fractional anisotropy, mean diffusivity, and T2 relaxation time. Change points captured the “critical” GAB value associated with a change in the linear relation between GAB and MRI measures. The analysis was performed in 126 regions across the whole brain using an atlas-based image quantification approach to investigate the spatial pattern of the critical GAB. Our results demonstrate that the critical GABs are region- and modality-specific, generally following a central-to-peripheral and bottom-to-top order of structural development. This study may offer unique insights into the postnatal neurological development associated with differential degrees of preterm birth. PMID:28111189

Mapping the critical gestational age at birth that alters brain development in preterm-born infants using multi-modal MRI.

PubMed

Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi

2017-04-01

Preterm birth adversely affects postnatal brain development. In order to investigate the critical gestational age at birth (GAB) that alters the developmental trajectory of gray and white matter structures in the brain, we investigated diffusion tensor and quantitative T2 mapping data in 43 term-born and 43 preterm-born infants. A novel multivariate linear model-the change point model, was applied to detect change points in fractional anisotropy, mean diffusivity, and T2 relaxation time. Change points captured the "critical" GAB value associated with a change in the linear relation between GAB and MRI measures. The analysis was performed in 126 regions across the whole brain using an atlas-based image quantification approach to investigate the spatial pattern of the critical GAB. Our results demonstrate that the critical GABs are region- and modality-specific, generally following a central-to-peripheral and bottom-to-top order of structural development. This study may offer unique insights into the postnatal neurological development associated with differential degrees of preterm birth. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Functional photoacoustic tomography for neonatal brain imaging: developments and challenges

NASA Astrophysics Data System (ADS)

Hariri, Ali; Tavakoli, Emytis; Adabi, Saba; Gelovani, Juri; Avanaki, Mohammad R. N.

2017-03-01

Transfontanelle ultrasound imaging (TFUSI) is a routine diagnostic brain imaging method in infants who are born prematurely, whose skull bones have not completely fused together and have openings between them, so-called fontanelles. Open fontanelles in neonates provide acoustic windows, allowing the ultrasound beam to freely pass through. TFUSI is used to rule out neurological complications of premature birth including subarachnoid hemorrhage (SAH), intraventricular (IVH), subependimal (SEPH), subdural (SDH) or intracerebral (ICH) hemorrhages, as well as hypoxic brain injuries. TFUSI is widely used in the clinic owing to its low cost, safety, accessibility, and noninvasive nature. Nevertheless, the accuracy of TFUSI is limited. To address several limitations of current clinical imaging modalities, we develop a novel transfontanelle photoacoustic imaging (TFPAI) probe, which, for the first time, should allow for non-invasive structural and functional imaging of the infant brain. In this study, we test the feasibility of TFPAI for detection of experimentally-induced intra ventricular and Intraparenchymal hemorrhage phantoms in a sheep model with a surgically-induced cranial window which will serve as a model of neonatal fontanelle. This study is towards using the probe we develop for bedside monitoring of neonates with various disease conditions and complications affecting brain perfusion and oxygenation, including apnea, asphyxia, as well as for detection of various types of intracranial hemorrhages (SAH, IVH, SEPH, SDH, ICH).

Alzheimer disease detection from structural MR images using FCM based weighted probabilistic neural network.

PubMed

Duraisamy, Baskar; Shanmugam, Jayanthi Venkatraman; Annamalai, Jayanthi

2018-02-19

An early intervention of Alzheimer's disease (AD) is highly essential due to the fact that this neuro degenerative disease generates major life-threatening issues, especially memory loss among patients in society. Moreover, categorizing NC (Normal Control), MCI (Mild Cognitive Impairment) and AD early in course allows the patients to experience benefits from new treatments. Therefore, it is important to construct a reliable classification technique to discriminate the patients with or without AD from the bio medical imaging modality. Hence, we developed a novel FCM based Weighted Probabilistic Neural Network (FWPNN) classification algorithm and analyzed the brain images related to structural MRI modality for better discrimination of class labels. Initially our proposed framework begins with brain image normalization stage. In this stage, ROI regions related to Hippo-Campus (HC) and Posterior Cingulate Cortex (PCC) from the brain images are extracted using Automated Anatomical Labeling (AAL) method. Subsequently, nineteen highly relevant AD related features are selected through Multiple-criterion feature selection method. At last, our novel FWPNN classification algorithm is imposed to remove suspicious samples from the training data with an end goal to enhance the classification performance. This newly developed classification algorithm combines both the goodness of supervised and unsupervised learning techniques. The experimental validation is carried out with the ADNI subset and then to the Bordex-3 city dataset. Our proposed classification approach achieves an accuracy of about 98.63%, 95.4%, 96.4% in terms of classification with AD vs NC, MCI vs NC and AD vs MCI. The experimental results suggest that the removal of noisy samples from the training data can enhance the decision generation process of the expert systems.

A generative probabilistic model and discriminative extensions for brain lesion segmentation – with application to tumor and stroke

PubMed Central

Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-André; Székely, Gabor; Ayache, Nicholas; Golland, Polina

2016-01-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM) to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as “tumor core” or “fluid-filled structure”, but without a one-to-one correspondence to the hypo-or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the generative-discriminative model to be one of the top ranking methods in the BRATS evaluation. PMID:26599702

A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation--With Application to Tumor and Stroke.

PubMed

Menze, Bjoern H; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-Andre; Szekely, Gabor; Ayache, Nicholas; Golland, Polina

2016-04-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM), to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as "tumor core" or "fluid-filled structure", but without a one-to-one correspondence to the hypo- or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the extended discriminative -discriminative model to be one of the top ranking methods in the BRATS evaluation.

Dual-modality micro-positron emission tomography/computed tomography and near-infrared fluorescence imaging of EphB4 in orthotopic glioblastoma xenograft models.

PubMed

Huang, Miao; Xiong, Chiyi; Lu, Wei; Zhang, Rui; Zhou, Min; Huang, Qian; Weinberg, Jeffrey; Li, Chun

2014-02-01

In glioblastoma, EphB4 receptors, a member of the largest family of receptor tyrosine kinases, are overexpressed in both tumor cells and angiogenic blood vessels. The purpose of this study was to examine whether the EphB4-binding peptide TNYL-RAW labeled with both (64)Cu and near-infrared fluorescence dye Cy5.5 could be used as a molecular imaging agent for dual-modality positron emission tomography/computed tomography [PET/CT] and optical imaging of human glioblastoma in orthotopic brain tumor models. TNYL-RAW was conjugated to Cy5.5 and the radiometal chelator 1,4,7,10-tetraazadodecane-N,N',N″,N‴-tetraacetic acid. The conjugate was then labeled with (64)Cu for in vitro binding and in vivo dual μPET/CT and optical imaging studies in nude mice implanted with EphB4-expressing U251 and EphB4-negative U87 human glioblastoma cells. Tumors and brains were removed at the end of the imaging sessions for immunohistochemical staining and fluorescence microscopic examinations. μPET/CT and near-infrared optical imaging clearly showed specific uptake of the dual-labeled TNYL-RAW peptide in both U251 and U87 tumors in the brains of the nude mice after intravenous injection of the peptide. In U251 tumors, the Cy5.5-labeled peptide colocalized with both tumor blood vessels and tumor cells; in U87 tumors, the tracer colocalized only with tumor blood vessels, not with tumor cells. Dual-labeled EphB4-specific peptide could be used as a noninvasive molecular imaging agent for PET/CT and optical imaging of glioblastoma owing to its ability to bind to both EphB4-expressing angiogenic blood vessels and EphB4-expressing tumor cells.

Dual-Modality Micro-Positron Emission Tomography/Computed Tomography and Near-Infrared Fluorescence Imaging of EphB4 in Orthotopic Glioblastoma Xenograft Models

PubMed Central

Huang, Miao; Xiong, Chiyi; Lu, Wei; Zhang, Rui; Zhou, Min; Huang, Qian; Weinberg, Jeffrey; Li, Chun

2013-01-01

Purpose In glioblastoma, EphB4 receptors, a member of the largest family of receptor tyrosine kinases, are overexpressed in both tumor cells and angiogenic blood vessels. The purpose of this study was to examine whether the EphB4-binding peptide TNYL-RAW labeled with both 64Cu and near-infrared fluorescence dye Cy5.5 could be used as a molecular imaging agent for dual-modality positron emission tomography/computed tomography [PET/CT] and optical imaging of human glioblastoma in orthotopic brain tumor models. Materials and Methods TNYL-RAW was conjugated to Cy5.5 and the radiometal chelator 1,4,7,10-tetraazadodecane-N,N′,N″,N‴ -tetraacetic acid. The conjugate was then labeled with 64Cu for in vitro binding and in vivo dual μPET/CT and optical imaging studies in nude mice implanted with EphB4-expressing U251 and EphB4-negative U87 human glioblastoma cells. Tumors and brains were removed at the end of the imaging sessions for immunohistochemical staining and fluorescence microscopic examinations. Results μPET/CT and near-infrared optical imaging clearly showed specific uptake of the dual-labeled TNYL-RAW peptide in both U251 and U87 tumors in the brains of the nude mice after intravenous injection of the peptide. In U251 tumors, the Cy5.5-labeled peptide colocalized with both tumor blood vessels and tumor cells; in U87 tumors, the tracer colocalized only with tumor blood vessels, not with tumor cells. Conclusions Dual-labeled EphB4-specific peptide could be used as a noninvasive molecular imaging agent for PET/CT and optical imaging of glioblastoma owing to its ability to bind to both EphB4-expressing angiogenic blood vessels and EphB4-expressing tumor cells. PMID:23918654

Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model

PubMed Central

Hurley, Samuel A.; Vernon, Anthony C.; Torres, Joel; Dell’Acqua, Flavio; Williams, Steve C.R.; Cash, Diana

2016-01-01

Myelin is a critical component of the nervous system and a major contributor to contrast in Magnetic Resonance (MR) images. However, the precise contribution of myelination to multiple MR modalities is still under debate. The cuprizone mouse is a well-established model of demyelination that has been used in several MR studies, but these have often imaged only a single slice and analysed a small region of interest in the corpus callosum. We imaged and analyzed the whole brain of the cuprizone mouse ex-vivo using high-resolution quantitative MR methods (multi-component relaxometry, Diffusion Tensor Imaging (DTI) and morphometry) and found changes in multiple regions, including the corpus callosum, cerebellum, thalamus and hippocampus. The presence of inflammation, confirmed with histology, presents difficulties in isolating the sensitivity and specificity of these MR methods to demyelination using this model. PMID:27833805

Seeing touch is correlated with content-specific activity in primary somatosensory cortex.

PubMed

Meyer, Kaspar; Kaplan, Jonas T; Essex, Ryan; Damasio, Hanna; Damasio, Antonio

2011-09-01

There is increasing evidence to suggest that primary sensory cortices can become active in the absence of external stimulation in their respective modalities. This occurs, for example, when stimuli processed via one sensory modality imply features characteristic of a different modality; for instance, visual stimuli that imply touch have been observed to activate the primary somatosensory cortex (SI). In the present study, we addressed the question of whether such cross-modal activations are content specific. To this end, we investigated neural activity in the primary somatosensory cortex of subjects who observed human hands engaged in the haptic exploration of different everyday objects. Using multivariate pattern analysis of functional magnetic resonance imaging data, we were able to predict, based exclusively on the activity pattern in SI, which of several objects a subject saw being explored. Along with previous studies that found similar evidence for other modalities, our results suggest that primary sensory cortices represent information relevant for their modality even when this information enters the brain via a different sensory system.

Multimodal Image Registration through Simultaneous Segmentation.

PubMed

Aganj, Iman; Fischl, Bruce

2017-11-01

Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. In this work, we introduce a new non-information-theoretical method for pairwise multimodal image registration, in which the error of segmentation - using both images - is considered as the registration cost function. We empirically evaluate our method via rigid registration of multi-contrast brain magnetic resonance images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods.

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

NASA Astrophysics Data System (ADS)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.

PubMed

Ambastha, Abhinit Kumar; Leong, Tze-Yun

2017-01-01

Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain. The proposed technique has a classification accuracy of 81.79% for AD against healthy subjects using a single modality imaging dataset.

Detection of early seizures by diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zhang, Tao; Hajihashemi, M. Reza; Zhou, Junli; Carney, Paul R.; Jiang, Huabei

2015-03-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Besides, preclinical seizure experiments need to be conducted in awake animals with images reconstructed and displayed in real-time. We demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking brain activities with high spatiotemporal resolution. We developed methods to conduct seizure experiments in fully awake rats using a subject-specific helmet and a restraining mechanism. For the first time, we detected early hemodynamic responses with heterogeneous patterns several minutes preceding the electroencephalographic seizure onset, supporting the presence of a "pre-seizure" state both in anesthetized and awake rats. Using a novel time-series analysis of scattering images, we show that the analysis of scattered diffuse light is a sensitive and reliable modality for detecting changes in neural activity associated with generalized seizure. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways.

The possibility of application of spiral brain computed tomography to traumatic brain injury.

PubMed

Lim, Daesung; Lee, Soo Hoon; Kim, Dong Hoon; Choi, Dae Seub; Hong, Hoon Pyo; Kang, Changwoo; Jeong, Jin Hee; Kim, Seong Chun; Kang, Tae-Sin

2014-09-01

The spiral computed tomography (CT) with the advantage of low radiation dose, shorter test time required, and its multidimensional reconstruction is accepted as an essential diagnostic method for evaluating the degree of injury in severe trauma patients and establishment of therapeutic plans. However, conventional sequential CT is preferred for the evaluation of traumatic brain injury (TBI) over spiral CT due to image noise and artifact. We aimed to compare the diagnostic power of spiral facial CT for TBI to that of conventional sequential brain CT. We evaluated retrospectively the images of 315 traumatized patients who underwent both brain CT and facial CT simultaneously. The hemorrhagic traumatic brain injuries such as epidural hemorrhage, subdural hemorrhage, subarachnoid hemorrhage, and contusional hemorrhage were evaluated in both images. Statistics were performed using Cohen's κ to compare the agreement between 2 imaging modalities and sensitivity, specificity, positive predictive value, and negative predictive value of spiral facial CT to conventional sequential brain CT. Almost perfect agreement was noted regarding hemorrhagic traumatic brain injuries between spiral facial CT and conventional sequential brain CT (Cohen's κ coefficient, 0.912). To conventional sequential brain CT, sensitivity, specificity, positive predictive value, and negative predictive value of spiral facial CT were 92.2%, 98.1%, 95.9%, and 96.3%, respectively. In TBI, the diagnostic power of spiral facial CT was equal to that of conventional sequential brain CT. Therefore, expanded spiral facial CT covering whole frontal lobe can be applied to evaluate TBI in the future. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Listening to light scattering in turbid media: quantitative optical scattering imaging using photoacoustic measurements with one-wavelength illumination

NASA Astrophysics Data System (ADS)

Yuan, Zhen; Li, Xiaoqi; Xi, Lei

2014-06-01

Biomedical photoacoustic tomography (PAT), as a potential imaging modality, can visualize tissue structure and function with high spatial resolution and excellent optical contrast. It is widely recognized that the ability of quantitatively imaging optical absorption and scattering coefficients from photoacoustic measurements is essential before PAT can become a powerful imaging modality. Existing quantitative PAT (qPAT), while successful, has been focused on recovering absorption coefficient only by assuming scattering coefficient a constant. An effective method for photoacoustically recovering optical scattering coefficient is presently not available. Here we propose and experimentally validate such a method for quantitative scattering coefficient imaging using photoacoustic data from one-wavelength illumination. The reconstruction method developed combines conventional PAT with the photon diffusion equation in a novel way to realize the recovery of scattering coefficient. We demonstrate the method using various objects having scattering contrast only or both absorption and scattering contrasts embedded in turbid media. The listening-to-light-scattering method described will be able to provide high resolution scattering imaging for various biomedical applications ranging from breast to brain imaging.

Kinesthetic Imagery Provides Additive Benefits to Internal Visual Imagery on Slalom Task Performance.

PubMed

Callow, Nichola; Jiang, Dan; Roberts, Ross; Edwards, Martin G

2017-02-01

Recent brain imaging research demonstrates that the use of internal visual imagery (IVI) or kinesthetic imagery (KIN) activates common and distinct brain areas. In this paper, we argue that combining the imagery modalities (IVI and KIN) will lead to a greater cognitive representation (with more brain areas activated), and this will cause a greater slalom-based motor performance compared with using IVI alone. To examine this assertion, we randomly allocated 56 participants to one of the three groups: IVI, IVI and KIN, or a math control group. Participants performed a slalom-based driving task in a driving simulator, with average lap time used as a measure of performance. Results revealed that the IVI and KIN group achieved significantly quicker lap times than the IVI and the control groups. The discussion includes a theoretical advancement on why the combination of imagery modalities might facilitate performance, with links made to the cognitive neuroscience literature and applied practice.

First noninvasive thermal ablation of a brain tumor with MR-guided focused ultrasound

PubMed Central

2014-01-01

Magnetic resonance-guided focused ultrasound surgery (MRgFUS) allows for precise thermal ablation of target tissues. While this emerging modality is increasingly used for the treatment of various types of extracranial soft tissue tumors, it has only recently been acknowledged as a modality for noninvasive neurosurgery. MRgFUS has been particularly successful for functional neurosurgery, whereas its clinical application for tumor neurosurgery has been delayed for various technical and procedural reasons. Here, we report the case of a 63-year-old patient presenting with a centrally located recurrent glioblastoma who was included in our ongoing clinical phase I study aimed at evaluating the feasibility and safety of transcranial MRgFUS for brain tumor ablation. Applying 25 high-power sonications under MR imaging guidance, partial tumor ablation could be achieved without provoking neurological deficits or other adverse effects in the patient. This proves, for the first time, the feasibility of using transcranial MR-guided focused ultrasound to safely ablate substantial volumes of brain tumor tissue. PMID:25671132

Modality-specific spectral dynamics in response to visual and tactile sequential shape information processing tasks: An MEG study using multivariate pattern classification analysis.

PubMed

Gohel, Bakul; Lee, Peter; Jeong, Yong

2016-08-01

Brain regions that respond to more than one sensory modality are characterized as multisensory regions. Studies on the processing of shape or object information have revealed recruitment of the lateral occipital cortex, posterior parietal cortex, and other regions regardless of input sensory modalities. However, it remains unknown whether such regions show similar (modality-invariant) or different (modality-specific) neural oscillatory dynamics, as recorded using magnetoencephalography (MEG), in response to identical shape information processing tasks delivered to different sensory modalities. Modality-invariant or modality-specific neural oscillatory dynamics indirectly suggest modality-independent or modality-dependent participation of particular brain regions, respectively. Therefore, this study investigated the modality-specificity of neural oscillatory dynamics in the form of spectral power modulation patterns in response to visual and tactile sequential shape-processing tasks that are well-matched in terms of speed and content between the sensory modalities. Task-related changes in spectral power modulation and differences in spectral power modulation between sensory modalities were investigated at source-space (voxel) level, using a multivariate pattern classification (MVPC) approach. Additionally, whole analyses were extended from the voxel level to the independent-component level to take account of signal leakage effects caused by inverse solution. The modality-specific spectral dynamics in multisensory and higher-order brain regions, such as the lateral occipital cortex, posterior parietal cortex, inferior temporal cortex, and other brain regions, showed task-related modulation in response to both sensory modalities. This suggests modality-dependency of such brain regions on the input sensory modality for sequential shape-information processing. Copyright © 2016 Elsevier B.V. All rights reserved.

Early brain magnetic resonance imaging can predict short and long-term outcomes after organophosphate poisoning in a rat model.

PubMed

Shrot, Shai; Tauber, Maya; Shiyovich, Arthur; Milk, Nadav; Rosman, Yossi; Eisenkraft, Arik; Kadar, Tamar; Kassirer, Michael; Cohen, Yoram

2015-05-01

Magnetic resonance (MR) imaging is a sensitive modality for demonstrating in vivo alterations in brain structure and function after acute organophosphate (OP) poisoning. The goals of this study were to explore early imaging findings in organophosphate-poisoned animals, to assess the efficacy of centrally acting antidotes and to find whether early MR findings can predict post-poisoning cognitive dysfunction. Sprague-Dawley rats were poisoned with the agricultural OP paraoxon and were treated with immediate atropine and obidoxime (ATOX) to reduce acute mortality caused by peripheral inhibition of acetylcholinesterase. Animals were randomly divided into three groups based on the protocol of centrally acting antidotal treatment: group 1 - no central antidotal treatment (n=10); group 2 - treated with midazolam (MID) at 30 min after poisoning (n=9), group 3 - treated with a combination of MID and scopolamine (SCOP) at 30 min after poisoning (n=9) and controls (n=6). Each animal had a brain MR examination 3 and 24 h after poisoning. Each MR examination included the acquisition of a T2 map and a single-voxel (1)H MR spectroscopy (localized on the thalami, to measure total creatine [Cr], N-acetyl-aspartate [NAA] and cholines [Cho] levels). Eleven days after poisoning each animal underwent a Morris water maze to assess hippocampal learning. Eighteen days after poisoning, animals were euthanized, and their brains were dissected, fixed and processed for histology. All paraoxon poisoned animals developed generalized convulsions, starting within a few minutes following paraoxon injection. Brain edema was maximal on MR imaging 3 h after poisoning. Both MID and MID+SCOP prevented most of the cortical edema, with equivalent efficacy. Brain metabolic dysfunction, manifested as decreased NAA/Cr, appeared in all poisoned animals as early as 3h after exposure (1.1 ± 0.07 and 1.42 ± 0.05 in ATOX and control groups, respectively) and remained lower compared to non-poisoned animals even 24h after poisoning. MID and MID+SCOP prevented much of the 3h NAA/Cr decrease (1.22 ± 0.05 and 1.32 ± 0.1, respectively). Significant correlations were found between imaging findings (brain edema and spectroscopic changes) and clinical outcomes (poor learning, weight loss and pathological score) with correlation coefficients of 0.4-0.75 (p<0.05). MR imaging is a sensitive modality to explore organophosphate-induced brain damage. Delayed treatment with midazolam with or without scopolamine provides only transient neuroprotection with some advantage in adding scopolamine. Early imaging findings were found to correlate with clinical consequences of organophosphate poisoning and could be potentially used in the future to predict long-term prognosis of poisoned casualties. Copyright © 2015 Elsevier Inc. All rights reserved.

In Vivo Mammalian Brain Imaging Using One- and Two-Photon Fluorescence Microendoscopy

PubMed Central

Jung, Juergen C.; Mehta, Amit D.; Aksay, Emre; Stepnoski, Raymond; Schnitzer, Mark J.

2010-01-01

One of the major limitations in the current set of techniques available to neuroscientists is a dearth of methods for imaging individual cells deep within the brains of live animals. To overcome this limitation, we developed two forms of minimally invasive fluorescence microendoscopy and tested their abilities to image cells in vivo. Both one- and two-photon fluorescence microendoscopy are based on compound gradient refractive index (GRIN) lenses that are 350–1,000 μm in diameter and provide micron-scale resolution. One-photon microendoscopy allows full-frame images to be viewed by eye or with a camera, and is well suited to fast frame-rate imaging. Two-photon microendoscopy is a laser-scanning modality that provides optical sectioning deep within tissue. Using in vivo microendoscopy we acquired video-rate movies of thalamic and CA1 hippocampal red blood cell dynamics and still-frame images of CA1 neurons and dendrites in anesthetized rats and mice. Microendoscopy will help meet the growing demand for in vivo cellular imaging created by the rapid emergence of new synthetic and genetically encoded fluorophores that can be used to label specific brain areas or cell classes. PMID:15128753

Stroke-Related Translational Research

PubMed Central

Caplan, Louis R.; Arenillas, Juan; Cramer, Steven C.; Joutel, Anne; Lo, Eng H.; Meschia, James; Savitz, Sean; Tournier-Lasserve, Elizabeth

2013-01-01

Stroke-related translational research is multifaceted. Herein, we highlight genome-wide association studies and genetic studies of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, COL4A1 mutations, and cerebral cavernous malformations; advances in molecular biology and biomarkers; newer brain imaging research; and recovery from stroke emphasizing cell-based and other rehabilitative modalities. PMID:21555605

High-resolution imaging-guided electroencephalography source localization: temporal effect regularization incorporation in LORETA inverse solution

NASA Astrophysics Data System (ADS)

Boughariou, Jihene; Zouch, Wassim; Slima, Mohamed Ben; Kammoun, Ines; Hamida, Ahmed Ben

2015-11-01

Electroencephalography (EEG) and magnetic resonance imaging (MRI) are noninvasive neuroimaging modalities. They are widely used and could be complementary. The fusion of these modalities may enhance some emerging research fields targeting the exploration better brain activities. Such research attracted various scientific investigators especially to provide a convivial and helpful advanced clinical-aid tool enabling better neurological explorations. Our present research was, in fact, in the context of EEG inverse problem resolution and investigated an advanced estimation methodology for the localization of the cerebral activity. Our focus was, therefore, on the integration of temporal priors to low-resolution brain electromagnetic tomography (LORETA) formalism and to solve the inverse problem in the EEG. The main idea behind our proposed method was in the integration of a temporal projection matrix within the LORETA weighting matrix. A hyperparameter is the principal fact for such a temporal integration, and its importance would be obvious when obtaining a regularized smoothness solution. Our experimental results clearly confirmed the impact of such an optimization procedure adopted for the temporal regularization parameter comparatively to the LORETA method.

A new vibrator to stimulate muscle proprioceptors in fMRI.

PubMed

Montant, Marie; Romaiguère, Patricia; Roll, Jean-Pierre

2009-03-01

Studying cognitive brain functions by functional magnetic resonance imaging (fMRI) requires appropriate stimulation devices that do not interfere with the magnetic fields. Since the emergence of fMRI in the 90s, a number of stimulation devices have been developed for the visual and auditory modalities. Only few devices, however, have been developed for the somesthesic modality. Here, we present a vibration device for studying somesthesia that is compatible with high magnetic field environments and that can be used in fMRI machines. This device consists of a poly vinyl chloride (PVC) vibrator containing a wind turbine and of a pneumatic apparatus that controls 1-6 vibrators simultaneously. Just like classical electromagnetic vibrators, our device stimulates muscle mechanoreceptors (muscle spindles) and generates reliable illusions of movement. We provide the fMRI compatibility data (phantom test), the calibration curve (vibration frequency as a function of air flow), as well as the results of a kinesthetic test (perceived speed of the illusory movement as a function of vibration frequency). This device was used successfully in several brain imaging studies using both fMRI and magnetoencephalography.

Sensory modality of smoking cues modulates neural cue reactivity.

PubMed

Yalachkov, Yavor; Kaiser, Jochen; Görres, Andreas; Seehaus, Arne; Naumer, Marcus J

2013-01-01

Behavioral experiments have demonstrated that the sensory modality of presentation modulates drug cue reactivity. The present study on nicotine addiction tested whether neural responses to smoking cues are modulated by the sensory modality of stimulus presentation. We measured brain activation using functional magnetic resonance imaging (fMRI) in 15 smokers and 15 nonsmokers while they viewed images of smoking paraphernalia and control objects and while they touched the same objects without seeing them. Haptically presented, smoking-related stimuli induced more pronounced neural cue reactivity than visual cues in the left dorsal striatum in smokers compared to nonsmokers. The severity of nicotine dependence correlated positively with the preference for haptically explored smoking cues in the left inferior parietal lobule/somatosensory cortex, right fusiform gyrus/inferior temporal cortex/cerebellum, hippocampus/parahippocampal gyrus, posterior cingulate cortex, and supplementary motor area. These observations are in line with the hypothesized role of the dorsal striatum for the expression of drug habits and the well-established concept of drug-related automatized schemata, since haptic perception is more closely linked to the corresponding object-specific action pattern than visual perception. Moreover, our findings demonstrate that with the growing severity of nicotine dependence, brain regions involved in object perception, memory, self-processing, and motor control exhibit an increasing preference for haptic over visual smoking cues. This difference was not found for control stimuli. Considering the sensory modality of the presented cues could serve to develop more reliable fMRI-specific biomarkers, more ecologically valid experimental designs, and more effective cue-exposure therapies of addiction.

Measuring Brain Connectivity: Diffusion Tensor Imaging Validates Resting State Temporal Correlations

PubMed Central

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D.; Hampson, Michelle; Skudlarska, Beata A.; Pearlson, Godfrey

2015-01-01

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions. PMID:18771736

Measuring brain connectivity: diffusion tensor imaging validates resting state temporal correlations.

PubMed

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D; Hampson, Michelle; Skudlarska, Beata A; Pearlson, Godfrey

2008-11-15

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions.

Functional Brain Imaging

PubMed Central

2006-01-01

Executive Summary Objective The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer’s disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson’s disease (PD). Clinical Need: Target Population and Condition Alzheimer’s disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be due to a combination of etiologies, including genetic and environmental components. The prevalence of MS in Canada is 240 cases per 100,000 people. Parkinson’s disease is the most prevalent movement disorder; it affects an estimated 100,000 Canadians. Currently, the standard for measuring disease progression is through the use of scales, which are subjective measures of disease progression. Functional brain imaging may provide an objective measure of disease progression, differentiation between parkinsonian syndromes, and response to therapy. The Technology Being Reviewed Functional Brain Imaging Functional brain imaging technologies measure blood flow and metabolism. The results of these tests are often used in conjunction with structural imaging (e.g., MRI or CT). Positron emission tomography and MRS identify abnormalities in brain tissues. The former measures abnormalities through uptake of radiotracers in the brain, while the latter measures chemical shifts in metabolite ratios to identify abnormalities. The potential role of functional MRI (fMRI) is to identify the areas of the brain responsible for language, sensory and motor function (sensorimotor cortex), rather than identifying abnormalities in tissues. Magnetoencephalography measures magnetic fields of the electric currents in the brain, identifying aberrant activity. Magnetoencephalography may have the potential to localize seizure foci and to identify the sensorimotor cortex, visual cortex and auditory cortex. In terms of regulatory status, MEG and PET are licensed by Health Canada. Both MRS and fMRI use a MRI platform; thus, they do not have a separate licence from Health Canada. The radiotracers used in PET scanning are not licensed by Health Canada for general use but can be used through a Clinical Trials Application. Review Strategy The literature published up to September 2006 was searched in the following databases: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Database of Systematic Reviews, CENTRAL, and International Network of Agencies for Health Technology Assessment (INAHTA). The database search was supplemented with a search of relevant Web sites and a review of the bibliographies of selected papers. General inclusion criteria were applied to all conditions. Those criteria included the following: Full reports of systematic reviews, randomized controlled trials (RCTs), cohort-control studies, prospective cohort studies (PCS’), and retrospective studies. Sample sizes of at least 20 patients (≥ 10 with condition being reviewed). English-language studies. Human studies. Any age. Studying at least one of the following: fMRI, PET, MRS, or MEG. Functional brain imaging modality must be compared with a clearly defined reference standard. Must report at least one of the following outcomes: sensitivity, specificity, accuracy, positive predictive value (PPV), receiver operating characteristic curve, outcome measuring impact on diagnostic testing, treatment, patient health, or cost. Summary of Findings There is evidence to indicate that PET can accurately diagnose AD; however, at this time, there is no evidence to suggest that a diagnosis of AD with PET alters the clinical outcomes of patients. The addition of MRS or O-(2-18F-Fluoroethyl)-L-Tyrosine (FET)-PET to gadolinium (Gd)-enhanced MRI for distinguishing malignant from benign tumours during primary diagnosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients to distinguish malignant from benign tumours is unclear, because patients with a suspected brain tumour will likely undergo a biopsy despite additional imaging results. The addition of MRS, FET-PET, or MRI T2 to Gd-enhanced MRI for the differentiation of recurrence from radiation necrosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients with a suspected recurrence is in the monitoring of patients. Based on the evidence available, it is unclear if one of the imaging modalities (MRS, FET-PET, or MRI T2) offers significantly improved specificity over another. There may be a role for fMRI in the identification of surgical candidates for tumour resection; however, this requires further research. Based on the studies available, it is unclear if MEG has similar accuracy in localizing seizure foci to intracranial electroencephalogram (ICEEG). More high-quality research is needed to establish whether there is a difference in accuracy between MEG and ICEEG. The results of the studies comparing PET to noninvasive electroencephalogram (EEG) did not demonstrate that PET was more accurate at localizing seizure foci; however, there may be some specific conditions, such as tuberous sclerosis, where PET may be more accurate than noninvasive EEG. There may be some clinical utility for MEG or fMRI in presurgical functional mapping; however, this needs further investigation involving comparisons with other modalities. The clinical utility of MRS has yet to be established for patients with epilepsy. Positron emission tomography has high sensitivity and specificity in the diagnosis of PD and the differential diagnosis of parkinsonian syndromes; however, it is unclear at this time if the addition of PET in the diagnosis of these conditions contributes to the treatment and clinical outcomes of patients. There is limited clinical utility of functional brain imaging in the management of patients with MS at this time. Diagnosis of MS is established through clinical history, evoked potentials, and MRI. Magnetic resonance imaging can identify the multifocal white lesions and other structural characteristics of MS. PMID:23074493

Functional brain imaging: an evidence-based analysis.

PubMed

2006-01-01

The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer's disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson's disease (PD). TARGET POPULATION AND CONDITION Alzheimer's disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be due to a combination of etiologies, including genetic and environmental components. The prevalence of MS in Canada is 240 cases per 100,000 people. Parkinson's disease is the most prevalent movement disorder; it affects an estimated 100,000 Canadians. Currently, the standard for measuring disease progression is through the use of scales, which are subjective measures of disease progression. Functional brain imaging may provide an objective measure of disease progression, differentiation between parkinsonian syndromes, and response to therapy. FUNCTIONAL BRAIN IMAGING: Functional brain imaging technologies measure blood flow and metabolism. The results of these tests are often used in conjunction with structural imaging (e.g., MRI or CT). Positron emission tomography and MRS identify abnormalities in brain tissues. The former measures abnormalities through uptake of radiotracers in the brain, while the latter measures chemical shifts in metabolite ratios to identify abnormalities. The potential role of functional MRI (fMRI) is to identify the areas of the brain responsible for language, sensory and motor function (sensorimotor cortex), rather than identifying abnormalities in tissues. Magnetoencephalography measures magnetic fields of the electric currents in the brain, identifying aberrant activity. Magnetoencephalography may have the potential to localize seizure foci and to identify the sensorimotor cortex, visual cortex and auditory cortex. In terms of regulatory status, MEG and PET are licensed by Health Canada. Both MRS and fMRI use a MRI platform; thus, they do not have a separate licence from Health Canada. The radiotracers used in PET scanning are not licensed by Health Canada for general use but can be used through a Clinical Trials Application. The literature published up to September 2006 was searched in the following databases: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Database of Systematic Reviews, CENTRAL, and International Network of Agencies for Health Technology Assessment (INAHTA). The database search was supplemented with a search of relevant Web sites and a review of the bibliographies of selected papers. General inclusion criteria were applied to all conditions. Those criteria included the following: Full reports of systematic reviews, randomized controlled trials (RCTs), cohort-control studies, prospective cohort studies (PCS'), and retrospective studies.Sample sizes of at least 20 patients (≥ 10 with condition being reviewed).English-language studies.Human studies.Any age.STUDYING AT LEAST ONE OF THE FOLLOWING: fMRI, PET, MRS, or MEG.Functional brain imaging modality must be compared with a clearly defined reference standard.MUST REPORT AT LEAST ONE OF THE FOLLOWING OUTCOMES: sensitivity, specificity, accuracy, positive predictive value (PPV), receiver operating characteristic curve, outcome measuring impact on diagnostic testing, treatment, patient health, or cost. There is evidence to indicate that PET can accurately diagnose AD; however, at this time, there is no evidence to suggest that a diagnosis of AD with PET alters the clinical outcomes of patients. The addition of MRS or O-(2-(18)F-Fluoroethyl)-L-Tyrosine (FET)-PET to gadolinium (Gd)-enhanced MRI for distinguishing malignant from benign tumours during primary diagnosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients to distinguish malignant from benign tumours is unclear, because patients with a suspected brain tumour will likely undergo a biopsy despite additional imaging results. The addition of MRS, FET-PET, or MRI T2 to Gd-enhanced MRI for the differentiation of recurrence from radiation necrosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients with a suspected recurrence is in the monitoring of patients. Based on the evidence available, it is unclear if one of the imaging modalities (MRS, FET-PET, or MRI T2) offers significantly improved specificity over another. There may be a role for fMRI in the identification of surgical candidates for tumour resection; however, this requires further research. Based on the studies available, it is unclear if MEG has similar accuracy in localizing seizure foci to intracranial electroencephalogram (ICEEG). More high-quality research is needed to establish whether there is a difference in accuracy between MEG and ICEEG. The results of the studies comparing PET to noninvasive electroencephalogram (EEG) did not demonstrate that PET was more accurate at localizing seizure foci; however, there may be some specific conditions, such as tuberous sclerosis, where PET may be more accurate than noninvasive EEG. There may be some clinical utility for MEG or fMRI in presurgical functional mapping; however, this needs further investigation involving comparisons with other modalities. The clinical utility of MRS has yet to be established for patients with epilepsy. Positron emission tomography has high sensitivity and specificity in the diagnosis of PD and the differential diagnosis of parkinsonian syndromes; however, it is unclear at this time if the addition of PET in the diagnosis of these conditions contributes to the treatment and clinical outcomes of patients. There is limited clinical utility of functional brain imaging in the management of patients with MS at this time. Diagnosis of MS is established through clinical history, evoked potentials, and MRI. Magnetic resonance imaging can identify the multifocal white lesions and other structural characteristics of MS.

FMRI investigation of cross-modal interactions in beat perception: Audition primes vision, but not vice versa

PubMed Central

Grahn, Jessica A.; Henry, Molly J.; McAuley, J. Devin

2011-01-01

How we measure time and integrate temporal cues from different sensory modalities are fundamental questions in neuroscience. Sensitivity to a “beat” (such as that routinely perceived in music) differs substantially between auditory and visual modalities. Here we examined beat sensitivity in each modality, and examined cross-modal influences, using functional magnetic resonance imaging (fMRI) to characterize brain activity during perception of auditory and visual rhythms. In separate fMRI sessions, participants listened to auditory sequences or watched visual sequences. The order of auditory and visual sequence presentation was counterbalanced so that cross-modal order effects could be investigated. Participants judged whether sequences were speeding up or slowing down, and the pattern of tempo judgments was used to derive a measure of sensitivity to an implied beat. As expected, participants were less sensitive to an implied beat in visual sequences than in auditory sequences. However, visual sequences produced a stronger sense of beat when preceded by auditory sequences with identical temporal structure. Moreover, increases in brain activity were observed in the bilateral putamen for visual sequences preceded by auditory sequences when compared to visual sequences without prior auditory exposure. No such order-dependent differences (behavioral or neural) were found for the auditory sequences. The results provide further evidence for the role of the basal ganglia in internal generation of the beat and suggest that an internal auditory rhythm representation may be activated during visual rhythm perception. PMID:20858544

The Human Connectome Project: A data acquisition perspective

PubMed Central

Van Essen, D.C.; Ugurbil, K.; Auerbach, E.; Barch, D.; Behrens, T.E.J.; Bucholz, R.; Chang, A.; Chen, L.; Corbetta, M.; Curtiss, S.W.; Della Penna, S.; Feinberg, D.; Glasser, M.F.; Harel, N.; Heath, A.C.; Larson-Prior, L.; Marcus, D.; Michalareas, G.; Moeller, S.; Oostenveld, R.; Petersen, S.E.; Prior, F.; Schlaggar, B.L.; Smith, S.M.; Snyder, A.Z.; Xu, J.; Yacoub, E.

2012-01-01

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences. PMID:22366334

Creation and Validation of a Simulator for Neonatal Brain Ultrasonography: A Pilot Study.

PubMed

Tsai, Andy; Barnewolt, Carol E; Prahbu, Sanjay P; Yonekura, Reimi; Hosmer, Andrew; Schulz, Noah E; Weinstock, Peter H

2017-01-01

Historically, skills training in performing brain ultrasonography has been limited to hours of scanning infants for lack of adequate synthetic models or alternatives. The aim of this study was to create a simulator and determine its utility as an educational tool in teaching the skills that can be used in performing brain ultrasonography on infants. A brain ultrasonography simulator was created using a combination of multi-modality imaging, three-dimensional printing, material and acoustic engineering, and sculpting and molding. Radiology residents participated prior to their pediatric rotation. The study included (1) an initial questionnaire and resident creation of three coronal images using the simulator; (2) brain ultrasonography lecture; (3) hands-on simulator practice; and (4) a follow-up questionnaire and re-creation of the same three coronal images on the simulator. A blinded radiologist scored the quality of the pre- and post-training images using metrics including symmetry of the images and inclusion of predetermined landmarks. Wilcoxon rank-sum test was used to compare pre- and post-training questionnaire rankings and image quality scores. Ten residents participated in the study. Analysis of pre- and post-training rankings showed improvements in technical knowledge and confidence, and reduction in anxiety in performing brain ultrasonography. Objective measures of image quality likewise improved. Mean reported value score for simulator training was high across participants who reported perceived improvements in scanning skills and enjoyment from simulator use, with interest in additional practice on the simulator and recommendations for its use. This pilot study supports the use of a simulator in teaching radiology residents the skills that can be used to perform brain ultrasonography. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

PubMed Central

Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r = 0.7033, MCCB social cognition r = 0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r = 0.7785, PANSS negative r = 0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. PMID:27177764

A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients

NASA Astrophysics Data System (ADS)

Agn, Mikael; Law, Ian; Munck af Rosenschöld, Per; Van Leemput, Koen

2016-03-01

We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstem and hippocampus. The preliminary results demonstrate the feasibility of the method.

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

Coronal in vivo forward-imaging of rat brain morphology with an ultra-small optical coherence tomography fiber probe

NASA Astrophysics Data System (ADS)

Xie, Yijing; Bonin, Tim; Löffler, Susanne; Hüttmann, Gereon; Tronnier, Volker; Hofmann, Ulrich G.

2013-02-01

A well-established navigation method is one of the key conditions for successful brain surgery: it should be accurate, safe and online operable. Recent research shows that optical coherence tomography (OCT) is a potential solution for this application by providing a high resolution and small probe dimension. In this study a fiber-based spectral-domain OCT system utilizing a super-luminescent-diode with the center wavelength of 840 nm providing 14.5 μm axial resolution was used. A composite 125 μm diameter detecting probe with a gradient index (GRIN) fiber fused to a single mode fiber was employed. Signals were reconstructed into grayscale images by horizontally aligning A-scans from the same trajectory with different depths. The reconstructed images can display brain morphology along the entire trajectory. For scans of typical white matter, the signals showed a higher reflection of light intensity with lower penetration depth as well as a steeper attenuation rate compared to the scans typical for gray matter. Micro-structures such as axon bundles (70 μm) in the caudate nucleus are visible in the reconstructed images. This study explores the potential of OCT to be a navigation modality in brain surgery.

High-density diffuse optical tomography of term infant visual cortex in the nursery

NASA Astrophysics Data System (ADS)

Liao, Steve M.; Ferradal, Silvina L.; White, Brian R.; Gregg, Nicholas; Inder, Terrie E.; Culver, Joseph P.

2012-08-01

Advancements in antenatal and neonatal medicine over the last few decades have led to significant improvement in the survival rates of sick newborn infants. However, this improvement in survival has not been matched by a reduction in neurodevelopmental morbidities with increasing recognition of the diverse cognitive and behavioral challenges that preterm infants face in childhood. Conventional neuroimaging modalities, such as cranial ultrasound and magnetic resonance imaging, provide an important definition of neuroanatomy with recognition of brain injury. However, they fail to define the functional integrity of the immature brain, particularly during this critical developmental period. Diffuse optical tomography methods have established success in imaging adult brain function; however, few studies exist to demonstrate their feasibility in the neonatal population. We demonstrate the feasibility of using recently developed high-density diffuse optical tomography (HD-DOT) to map functional activation of the visual cortex in healthy term-born infants. The functional images show high contrast-to-noise ratio obtained in seven neonates. These results illustrate the potential for HD-DOT and provide a foundation for investigations of brain function in more vulnerable newborns, such as preterm infants.

Malformations of cortical development: 3T magnetic resonance imaging features

PubMed Central

Battal, Bilal; Ince, Selami; Akgun, Veysel; Kocaoglu, Murat; Ozcan, Emrah; Tasar, Mustafa

2015-01-01

Malformation of cortical development (MCD) is a term representing an inhomogeneous group of central nervous system abnormalities, referring particularly to embriyological aspect as a consequence of any of the three developmental stages, i.e., cell proliferation, cell migration and cortical organization. These include cotical dysgenesis, microcephaly, polymicrogyria, schizencephaly, lissencephaly, hemimegalencephaly, heterotopia and focal cortical dysplasia. Since magnetic resonance imaging is the modality of choice that best identifies the structural anomalies of the brain cortex, we aimed to provide a mini review of MCD by using 3T magnetic resonance scanner images. PMID:26516429

Devastating metabolic brain disorders of newborns and young infants.

PubMed

Yoon, Hyun Jung; Kim, Ji Hye; Jeon, Tae Yeon; Yoo, So-Young; Eo, Hong

2014-01-01

Metabolic disorders of the brain that manifest in the neonatal or early infantile period are usually associated with acute and severe illness and are thus referred to as devastating metabolic disorders. Most of these disorders may be classified as organic acid disorders, amino acid metabolism disorders, primary lactic acidosis, or fatty acid oxidation disorders. Each disorder has distinctive clinical, biochemical, and radiologic features. Early diagnosis is important both for prompt treatment to prevent death or serious sequelae and for genetic counseling. However, diagnosis is often challenging because many findings overlap and may mimic those of more common neonatal conditions, such as hypoxic-ischemic encephalopathy and infection. Ultrasonography (US) may be an initial screening method for the neonatal brain, and magnetic resonance (MR) imaging is the modality of choice for evaluating metabolic brain disorders. Although nonspecific imaging findings are common in early-onset metabolic disorders, characteristic patterns of brain involvement have been described for several disorders. In addition, diffusion-weighted images may be used to characterize edema during an acute episode of encephalopathy, and MR spectroscopy depicts changes in metabolites that may help diagnose metabolic disorders and assess response to treatment. Imaging findings, including those of advanced MR imaging techniques, must be closely reviewed. If one of these rare disorders is suspected, the appropriate biochemical test or analysis of the specific gene should be performed to confirm the diagnosis. ©RSNA, 2014.

Applications of Ultrasound in the Resection of Brain Tumors

PubMed Central

Sastry, Rahul; Bi, Wenya Linda; Pieper, Steve; Frisken, Sarah; Kapur, Tina; Wells, William; Golby, Alexandra J.

2016-01-01

Neurosurgery makes use of pre-operative imaging to visualize pathology, inform surgical planning, and evaluate the safety of selected approaches. The utility of pre-operative imaging for neuronavigation, however, is diminished by the well characterized phenomenon of brain shift, in which the brain deforms intraoperatively as a result of craniotomy, swelling, gravity, tumor resection, cerebrospinal fluid (CSF) drainage, and many other factors. As such, there is a need for updated intraoperative information that accurately reflects intraoperative conditions. Since 1982, intraoperative ultrasound has allowed neurosurgeons to craft and update operative plans without ionizing radiation exposure or major workflow interruption. Continued evolution of ultrasound technology since its introduction has resulted in superior imaging quality, smaller probes, and more seamless integration with neuronavigation systems. Furthermore, the introduction of related imaging modalities, such as 3-dimensional ultrasound, contrast-enhanced ultrasound, high-frequency ultrasound, and ultrasound elastography have dramatically expanded the options available to the neurosurgeon intraoperatively. In the context of these advances, we review the current state, potential, and challenges of intraoperative ultrasound for brain tumor resection. We begin by evaluating these ultrasound technologies and their relative advantages and disadvantages. We then review three specific applications of these ultrasound technologies to brain tumor resection: (1) intraoperative navigation, (2) assessment of extent of resection, and (3) brain shift monitoring and compensation. We conclude by identifying opportunities for future directions in the development of ultrasound technologies. PMID:27541694

Optical imaging characterizing brain response to thermal insult in injured rodent

NASA Astrophysics Data System (ADS)

Abookasis, David; Shaul, Oren; Meitav, Omri; Pinhasi, Gadi A.

2018-02-01

We used spatially modulated optical imaging system to assess the effect of temperature elevation on intact brain tissue in a mouse heatstress model. Heatstress or heatstroke is a medical emergency defined by abnormally elevated body temperature that causes biochemical, physiological and hematological changes. During experiments, brain temperature was measured concurrently with a thermal camera while core body temperature was monitored with rectal thermocouple probe. Changes in a battery of macroscopic brain physiological parameters, such as hemoglobin oxygen saturation level, cerebral water content, as well as intrinsic tissue optical properties were monitored during temperature elevation. These concurrent changes reflect the pathophysiology of the brain during heatstress and demonstrate successful monitoring of thermoregulation mechanisms. In addition, the variation of tissue refractive index was calculated showing a monotonous decrease with increasing wavelength. We found increased temperature to greatly affect both the scattering properties and refractive index which represent cellular and subcellular swelling indicative of neuronal damage. The overall trends detected in brain tissue parameters were consistent with previous observations using conventional medical devices and optical modalities.

Methods to Differentiate Radiation Necrosis and Recurrent Disease in Gliomas

NASA Astrophysics Data System (ADS)

Ewell, Lars

2007-03-01

Given the difficulty in differentiating Radiation Induced Necrosis (RIN) and recurrent disease in glioma patients using conventional techniques (CT scans, MRI scans), researchers have looked for different imaging modalities. Among these different modalities are Diffusion Weighted Magnetic Resonance Imaging (DWMRI) and Magnetic Resonance Spectroscopy (MRS). In DWMRI, an Apparent Diffusion Coefficient (ADC) is calculated for a Region Of Interest (ROI), and then monitored over time (longitudinally). In the brain, different anatomical features can complicate the interpretation of ADCs. In particular, the density and spatial variation of the cerebral spinal fluid filled fissures known as sulci can influence how a change in an ADC is explained. We have used the covariance of pixel intensity in T1 weighted MRI scans to study how intra-patient and inter-patient sulci density varies, and will present these results. MRS uses the shift in the MR signal due to the local chemical environment to determine the concentration of brain metabolites like choline and creatin. The ratio of metabolites such as these has been shown to have the power to discriminate between RIN and recurrent disease in glioma patients. At our institution, we have initiated a protocol whereby we will use DWMRI and MRS to study how best to utilize these complimentary forms of imaging.

A patient-specific segmentation framework for longitudinal MR images of traumatic brain injury

NASA Astrophysics Data System (ADS)

Wang, Bo; Prastawa, Marcel; Irimia, Andrei; Chambers, Micah C.; Vespa, Paul M.; Van Horn, John D.; Gerig, Guido

2012-02-01

Traumatic brain injury (TBI) is a major cause of death and disability worldwide. Robust, reproducible segmentations of MR images with TBI are crucial for quantitative analysis of recovery and treatment efficacy. However, this is a significant challenge due to severe anatomy changes caused by edema (swelling), bleeding, tissue deformation, skull fracture, and other effects related to head injury. In this paper, we introduce a multi-modal image segmentation framework for longitudinal TBI images. The framework is initialized through manual input of primary lesion sites at each time point, which are then refined by a joint approach composed of Bayesian segmentation and construction of a personalized atlas. The personalized atlas construction estimates the average of the posteriors of the Bayesian segmentation at each time point and warps the average back to each time point to provide the updated priors for Bayesian segmentation. The difference between our approach and segmenting longitudinal images independently is that we use the information from all time points to improve the segmentations. Given a manual initialization, our framework automatically segments healthy structures (white matter, grey matter, cerebrospinal fluid) as well as different lesions such as hemorrhagic lesions and edema. Our framework can handle different sets of modalities at each time point, which provides flexibility in analyzing clinical scans. We show results on three subjects with acute baseline scans and chronic follow-up scans. The results demonstrate that joint analysis of all the points yields improved segmentation compared to independent analysis of the two time points.

Modeling skull's acoustic attenuation and dispersion on photoacoustic signal

NASA Astrophysics Data System (ADS)

Mohammadi, L.; Behnam, H.; Nasiriavanaki, M. R.

2017-03-01

Despite the great promising results of a recent new transcranial photoacoustic brain imaging technology, it has been shown that the presence of the skull severely affects the performance of this imaging modality. In this paper, we investigate the effect of skull on generated photoacoustic signals with a mathematical model. The developed model takes into account the frequency dependence attenuation and acoustic dispersion effects occur with the wave reflection and refraction at the skull surface. Numerical simulations based on the developed model are performed for calculating the propagation of photoacoustic waves through the skull. From the simulation results, it was found that the skull-induced distortion becomes very important and the reconstructed image would be strongly distorted without correcting these effects. In this regard, it is anticipated that an accurate quantification and modeling of the skull transmission effects would ultimately allow for skull aberration correction in transcranial photoacoustic brain imaging.

Functional connectivity of the rodent brain using optical imaging

NASA Astrophysics Data System (ADS)

Guevara Codina, Edgar

The aim of this thesis is to apply functional connectivity in a variety of animal models, using several optical imaging modalities. Even at rest, the brain shows high metabolic activity: the correlation in slow spontaneous fluctuations identifies remotely connected areas of the brain; hence the term "functional connectivity". Ongoing changes in spontaneous activity may provide insight into the neural processing that takes most of the brain metabolic activity, and so may provide a vast source of disease related changes. Brain hemodynamics may be modified during disease and affect resting-state activity. The thesis aims to better understand these changes in functional connectivity due to disease, using functional optical imaging. The optical imaging techniques explored in the first two contributions of this thesis are Optical Imaging of Intrinsic Signals and Laser Speckle Contrast Imaging, together they can estimate the metabolic rate of oxygen consumption, that closely parallels neural activity. They both have adequate spatial and temporal resolution and are well adapted to image the convexity of the mouse cortex. In the last article, a depth-sensitive modality called photoacoustic tomography was used in the newborn rat. Optical coherence tomography and laminar optical tomography were also part of the array of imaging techniques developed and applied in other collaborations. The first article of this work shows the changes in functional connectivity in an acute murine model of epileptiform activity. Homologous correlations are both increased and decreased with a small dependence on seizure duration. These changes suggest a potential decoupling between the hemodynamic parameters in resting-state networks, underlining the importance to investigate epileptic networks with several independent hemodynamic measures. The second study examines a novel murine model of arterial stiffness: the unilateral calcification of the right carotid. Seed-based connectivity analysis showed a decreasing trend of homologous correlation in the motor and cingulate cortices. Graph analyses showed a randomization of the cortex functional networks, suggesting a loss of connectivity, more specifically in the motor cortex ipsilateral to the treated carotid; however these changes are not reflected in differentiated metabolic estimates. Confounds remain due to the fact that carotid rigidification gives rise to neural decline in the hippocampus as well as unilateral alteration of vascular pulsatility; however the results support the need to look at several hemodynamic parameters when imaging the brain after arterial remodeling. The third article of this thesis studies a model of inflammatory injury on the newborn rat. Oxygen saturation and functional connectivity were assessed with photoacoustic tomography. Oxygen saturation was decreased in the site of the lesion and on the cortex ipsilateral to the injury; however this decrease is not fully explained by hypovascularization revealed by histology. Seed-based functional connectivity analysis showed that inter-hemispheric connectivity is not affected by inflammatory injury.

Optical pathology of human brain metastasis of lung cancer using combined resonance Raman and spatial frequency spectroscopies

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; Pu, Yang; Cheng, Gangge; Zhou, Lixin; Chen, Jun; Zhu, Ke; Alfano, Robert R.

2016-03-01

Raman spectroscopy has become widely used for diagnostic purpose of breast, lung and brain cancers. This report introduced a new approach based on spatial frequency spectra analysis of the underlying tissue structure at different stages of brain tumor. Combined spatial frequency spectroscopy (SFS), Resonance Raman (RR) spectroscopic method is used to discriminate human brain metastasis of lung cancer from normal tissues for the first time. A total number of thirty-one label-free micrographic images of normal and metastatic brain cancer tissues obtained from a confocal micro- Raman spectroscopic system synchronously with examined RR spectra of the corresponding samples were collected from the identical site of tissue. The difference of the randomness of tissue structures between the micrograph images of metastatic brain tumor tissues and normal tissues can be recognized by analyzing spatial frequency. By fitting the distribution of the spatial frequency spectra of human brain tissues as a Gaussian function, the standard deviation, σ, can be obtained, which was used to generate a criterion to differentiate human brain cancerous tissues from the normal ones using Support Vector Machine (SVM) classifier. This SFS-SVM analysis on micrograph images presents good results with sensitivity (85%), specificity (75%) in comparison with gold standard reports of pathology and immunology. The dual-modal advantages of SFS combined with RR spectroscopy method may open a new way in the neuropathology applications.

Discriminative Power of Arterial Spin Labeling Magnetic Resonance Imaging and 18F-Fluorodeoxyglucose Positron Emission Tomography Changes for Amyloid-β-Positive Subjects in the Alzheimer's Disease Continuum.

PubMed

Tosun, Duygu; Schuff, Norbert; Jagust, William; Weiner, Michael W

2016-01-01

Recent studies have demonstrated that arterial spin labeling magnetic resonance imaging (ASL-MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) identify similar regional abnormalities and have comparable diagnostic accuracy in Alzheimer's disease (AD). The agreement between these modalities in the AD continuum, which is an important concept for early detection and disease monitoring, is yet unclear. We aimed to assess the ability of the cerebral blood flow (CBF) measures from ASL-MRI and cerebral metabolic rate for glucose (CMRgl) measures from FDG-PET to distinguish amyloid-β-positive (Aβ+) subjects in the AD continuum from healthy controls. The study included asymptomatic, cognitively normal (CN) controls and patients with early mild cognitive impairment (MCI), late MCI, and AD, all with significant levels of cortical Aβ based on their florbetapir PET scans to restrict the study to patients truly in the AD continuum. The discrimination power of each modality was based on the whole-brain patterns of CBF and CMRgl changes identified by partial least squares logistic regression, a multivariate analysis technique. While CBF changes in the posterior inferior aspects of the brain and a pattern of CMRgl changes in the superior aspects of the brain including frontal and parietal regions best discriminated the Aβ+ subjects in the early disease stages from the Aβ- CN subjects, there was a greater agreement in the whole-brain patterns of CBF and CMRgl changes that best discriminated the Aβ+ subjects from the Aβ- CN subjects in the later disease stages. Despite the differences in the whole-brain patterns of CBF and CMRgl changes, the discriminative powers of both modalities were similar with statistically nonsignificant performance differences in sensitivity and specificity. The results comparing measurements of CBF to CMRgl add to previous reports that MRI-measured CBF has a similar diagnostic ability to detect AD as has FDG-PET. Our findings that CBF and CMRgl changes occur in different brain regions in Aβ+ subjects across the AD continuum compared with Aβ- CN subjects may be the result of methodological differences. Alternatively, these findings may signal alterations in neurovascular coupling which alter relationships between brain perfusion and glucose metabolism in the AD continuum. © 2015 S. Karger AG, Basel.

Brain development during the preschool years

PubMed Central

Brown, Timothy T.; Jernigan, Terry L.

2012-01-01

The preschool years represent a time of expansive psychological growth, with the initial expression of many psychological abilities that will continue to be refined into young adulthood. Likewise, brain development during this age is characterized by its “blossoming” nature, showing some of its most dynamic and elaborative anatomical and physiological changes. In this article, we review human brain development during the preschool years, sampling scientific evidence from a variety of sources. First, we cover neurobiological foundations of early postnatal development, explaining some of the primary mechanisms seen at a larger scale within neuroimaging studies. Next, we review evidence from both structural and functional imaging studies, which now accounts for a large portion of our current understanding of typical brain development. Within anatomical imaging, we focus on studies of developing brain morphology and tissue properties, including diffusivity of white matter fiber tracts. We also present new data on changes during the preschool years in cortical area, thickness, and volume. Physiological brain development is then reviewed, touching on influential results from several different functional imaging and recording modalities in the preschool and early school-age years, including positron emission tomography (PET), electroencephalography (EEG) and event-related potentials (ERP), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS). Here, more space is devoted to explaining some of the key methodological factors that are required for interpretation. We end with a section on multimodal and multidimensional imaging approaches, which we believe will be critical for increasing our understanding of brain development and its relationship to cognitive and behavioral growth in the preschool years and beyond. PMID:23007644

A two-view ultrasound CAD system for spina bifida detection using Zernike features

NASA Astrophysics Data System (ADS)

Konur, Umut; Gürgen, Fikret; Varol, Füsun

2011-03-01

In this work, we address a very specific CAD (Computer Aided Detection/Diagnosis) problem and try to detect one of the relatively common birth defects - spina bifida, in the prenatal period. To do this, fetal ultrasound images are used as the input imaging modality, which is the most convenient so far. Our approach is to decide using two particular types of views of the fetal neural tube. Transcerebellar head (i.e. brain) and transverse (axial) spine images are processed to extract features which are then used to classify healthy (normal), suspicious (probably defective) and non-decidable cases. Decisions raised by two independent classifiers may be individually treated, or if desired and data related to both modalities are available, those decisions can be combined to keep matters more secure. Even more security can be attained by using more than two modalities and base the final decision on all those potential classifiers. Our current system relies on feature extraction from images for cases (for particular patients). The first step is image preprocessing and segmentation to get rid of useless image pixels and represent the input in a more compact domain, which is hopefully more representative for good classification performance. Next, a particular type of feature extraction, which uses Zernike moments computed on either B/W or gray-scale image segments, is performed. The aim here is to obtain values for indicative markers that signal the presence of spina bifida. Markers differ depending on the image modality being used. Either shape or texture information captured by moments may propose useful features. Finally, SVM is used to train classifiers to be used as decision makers. Our experimental results show that a promising CAD system can be actualized for the specific purpose. On the other hand, the performance of such a system would highly depend on the qualities of image preprocessing, segmentation, feature extraction and comprehensiveness of image data.

Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging☆

PubMed Central

Oishi, Kenichi; Faria, Andreia V.; Yoshida, Shoko; Chang, Linda; Mori, Susumu

2013-01-01

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a “growth percentile chart,” which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application. PMID:23796902

Three-dimensional magnetic resonance imaging based on time-of-flight magnetic resonance angiography for superficial cerebral arteriovenous malformation--technical note.

PubMed

Murata, Takahiro; Horiuchi, Tetsuyoshi; Rahmah, Nunung Nur; Sakai, Keiichi; Hongo, Kazuhiro

2011-01-01

Direct surgery remains important for the treatment of superficial cerebral arteriovenous malformation (AVM). Surgical planning on the basis of careful analysis from various neuroimaging modalities can aid in resection of superficial AVM with favorable outcome. Three-dimensional (3D) magnetic resonance (MR) imaging reconstructed from time-of-flight (TOF) MR angiography was developed as an adjunctive tool for surgical planning of superficial AVM. 3-T TOF MR imaging without contrast medium was performed preoperatively in patients with superficial AVM. The images were imported into OsiriX imaging software and the 3D reconstructed MR image was produced using the volume rendering method. This 3D MR image could clearly visualize the surface angioarchitecture of the AVM with the surrounding brain on a single image, and clarified feeding arteries including draining veins and the relationship with sulci or fissures surrounding the nidus. 3D MR image of the whole AVM angioarchitecture was also displayed by skeletonization of the surrounding brain. Preoperative 3D MR image corresponded to the intraoperative view. Feeders on the brain surface were easily confirmed and obliterated during surgery, with the aid of the 3D MR images. 3D MR imaging for surgical planning of superficial AVM is simple and noninvasive to perform, enhances intraoperative orientation, and is helpful for successful resection.

Simultaneous MRI and PET imaging of a rat brain

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Lemieux, Susan K.; Sendhil Velan, S.; Kross, Brian; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.; Zorn, Carl; Marano, Gary D.

2006-12-01

Multi-modality imaging is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET fused with anatomical structure images created by MRI will allow the correlation of form with function. Our group is developing a system to acquire MRI and PET images contemporaneously. The prototype device consists of two opposed detector heads, operating in coincidence mode. Each MRI-PET detector module consists of an array of LSO detector elements coupled through a long fibre optic light guide to a single Hamamatsu flat panel position-sensitive photomultiplier tube (PSPMT). The use of light guides allows the PSPMTs to be positioned outside the bore of a 3T MRI scanner where the magnetic field is relatively small. To test the device, simultaneous MRI and PET images of the brain of a male Sprague Dawley rat injected with FDG were successfully obtained. The images revealed no noticeable artefacts in either image set. Future work includes the construction of a full ring PET scanner, improved light guides and construction of a specialized MRI coil to permit higher quality MRI imaging.

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

Buis, Dennis R.; Lagerwaard, Frank J.; Dirven, Clemens M.F.

Purpose: To assess the dosimetric consequences of brain arteriovenous malformation (bAVM) delineation on magnetic resonance angiography (MRA) for the purpose of stereotactic radiosurgery. Methods and Materials: Three observers contoured a bAVM in 20 patients, using digital subtraction angiography (V{sub DSA}) and three-dimensional time-of-flight MRA (V{sub MRA}). Displacement between contours was calculated. Agreement and differences between observers and imaging modalities were assessed. A standardized treatment plan with dynamic conformal arcs was generated and dosimetric coverage of all contours and the volume of normal brain tissue within the high dose region was determined. Results: The generalized reliability coefficient was 'fair' for targetmore » volume (0.79), but 'poor' for displacement (0.35). V{sub MRA} was larger than V{sub DSA} (5.0 vs. 4.0 mL, p = 0.001). No difference in displacement was found (2.8 vs. 2.5 mm, p = 0.156). Dosimetric coverage of V{sub MRA} was 62.9% (95% CI, 56.9-68.8) when V{sub DSA} was used as planning target volume, and coverage of V{sub DSA} was 83.5% (95% CI, 78.1-88.8) when V{sub MRA} was used for planning (p < 0.001). The mean volume of normal brain within the 80% isodose was larger when the bAVM was delineated on MRA (0.7 vs. 1.0 mL (p = 0.02) for targets {<=}3 mL and 3.7 vs. 7.0 mL (p = 0.01) for targets >3 mL). Conclusions: Brain arteriovenous malformations delineated on MRA are larger and more randomly displaced. However, for bAVMs {<=}3 mL, the difference in volume of normal brain tissue within the high-dose region does not seem to be clinically relevant. Therefore, MRA-images might be used as the sole imaging modality for the radiosurgical treatment of bAVMs {<=}3 mL when the bAVM is located in a noneloquent position.« less

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Functional magnetic resonance imaging can be used to explore tactile and nociceptive processing in the infant brain

PubMed Central

Williams, Gemma; Fabrizi, Lorenzo; Meek, Judith; Jackson, Deborah; Tracey, Irene; Robertson, Nicola; Slater, Rebeccah; Fitzgerald, Maria

2015-01-01

Aim Despite the importance of neonatal skin stimulation, little is known about activation of the newborn human infant brain by sensory stimulation of the skin. We carried out functional magnetic resonance imaging (fMRI) to assess the feasibility of measuring brain activation to a range of mechanical stimuli applied to the skin of neonatal infants. Methods We studied 19 term infants with a mean age of 13 days. Brain activation was measured in response to brushing, von Frey hair (vFh) punctate stimulation and, in one case, nontissue damaging pinprick stimulation of the plantar surface of the foot. Initial whole brain analysis was followed by region of interest analysis of specific brain areas. Results Distinct patterns of functional brain activation were evoked by brush and vFh punctate stimulation, which were reduced, but still present, under chloral hydrate sedation. Brain activation increased with increasing stimulus intensity. The feasibility of using pinprick stimulation in fMRI studies was established in one unsedated healthy full-term infant. Conclusion Distinct brain activity patterns can be measured in response to different modalities and intensities of skin sensory stimulation in term infants. This indicates the potential for fMRI studies in exploring tactile and nociceptive processing in the infant brain. PMID:25358870

Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia

PubMed Central

Selb, Juliette; Boas, David A.; Chan, Suk-Tak; Evans, Karleyton C.; Buckley, Erin M.; Carp, Stefan A.

2014-01-01

Abstract. Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) are two diffuse optical technologies for brain imaging that are sensitive to changes in hemoglobin concentrations and blood flow, respectively. Measurements for both modalities are acquired on the scalp, and therefore hemodynamic processes in the extracerebral vasculature confound the interpretation of cortical hemodynamic signals. The sensitivity of NIRS to the brain versus the extracerebral tissue and the contrast-to-noise ratio (CNR) of NIRS to cerebral hemodynamic responses have been well characterized, but the same has not been evaluated for DCS. This is important to assess in order to understand their relative capabilities in measuring cerebral physiological changes. We present Monte Carlo simulations on a head model that demonstrate that the relative brain-to-scalp sensitivity is about three times higher for DCS (0.3 at 3 cm) than for NIRS (0.1 at 3 cm). However, because DCS has higher levels of noise due to photon-counting detection, the CNR is similar for both modalities in response to a physiologically realistic simulation of brain activation. Even so, we also observed higher CNR of the hemodynamic response during graded hypercapnia in adult subjects with DCS than with NIRS. PMID:25453036

Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future.

PubMed

Iima, Mami; Le Bihan, Denis

2016-01-01

The concept of diffusion magnetic resonance (MR) imaging emerged in the mid-1980s, together with the first images of water diffusion in the human brain, as a way to probe tissue structure at a microscopic scale, although the images were acquired at a millimetric scale. Since then, diffusion MR imaging has become a pillar of modern clinical imaging. Diffusion MR imaging has mainly been used to investigate neurologic disorders. A dramatic application of diffusion MR imaging has been acute brain ischemia, providing patients with the opportunity to receive suitable treatment at a stage when brain tissue might still be salvageable, thus avoiding terrible handicaps. On the other hand, it was found that water diffusion is anisotropic in white matter, because axon membranes limit molecular movement perpendicularly to the nerve fibers. This feature can be exploited to produce stunning maps of the orientation in space of the white matter tracts and brain connections in just a few minutes. Diffusion MR imaging is now also rapidly expanding in oncology, for the detection of malignant lesions and metastases, as well as monitoring. Water diffusion is usually largely decreased in malignant tissues, and body diffusion MR imaging, which does not require any tracer injection, is rapidly becoming a modality of choice to detect, characterize, or even stage malignant lesions, especially for breast or prostate cancer. After a brief summary of the key methodological concepts beyond diffusion MR imaging, this article will give a review of the clinical literature, mainly focusing on current outstanding issues, followed by some innovative proposals for future improvements. © RSNA, 2016

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.

Importance of Multimodal MRI in Characterizing Brain Tissue and Its Potential Application for Individual Age Prediction.

PubMed

Cherubini, Andrea; Caligiuri, Maria Eugenia; Peran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2016-09-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2(*) relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. The results of the linear model were used to predict apparent age in different regions of individual brain. This approach pointed to a number of novel applications that could potentially help highlighting areas particularly vulnerable to disease.

High-speed pre-clinical brain imaging using pulsed laser diode based photoacoustic tomography (PLD-PAT) system

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Pramanik, Manojit

2016-03-01

Photoacoustic tomography (PAT) is a promising biomedical imaging modality for small animal imaging, breast cancer imaging, monitoring of vascularisation, tumor angiogenesis, blood oxygenation, total haemoglobin concentration etc. The existing PAT systems that uses Q-switched Nd:YAG and OPO nanosecond lasers have limitations in clinical applications because they are expensive, non-potable and not suitable for real-time imaging due to their low pulse repetition rate. Low-energy pulsed near-infrared diode laser which are low-cost, compact, and light-weight (<200 grams), can be used as an alternate. In this work, we present a photoacoustic tomography system with a pulsed laser diode (PLD) that can nanosecond pulses with pulse energy 1.3 mJ/pulse at ~803 nm wavelength and 7000 Hz repetition rate. The PLD is integrated inside a single-detector circular scanning geometric system. To verify the high speed imaging capabilities of the PLD-PAT system, we performed in vivo experimental results on small animal brain imaging using this system. The proposed system is portable, low-cost and can provide real-time imaging.

The dual loop model: its relation to language and other modalities

PubMed Central

Rijntjes, Michel; Weiller, Cornelius; Bormann, Tobias; Musso, Mariacristina

2012-01-01

The current neurobiological consensus of a general dual loop system scaffolding human and primate brains gives evidence that the dorsal and ventral connections subserve similar functions, independent of the modality and species. However, most current commentators agree that although bees dance and chimpanzees grunt, these systems of communication differ qualitatively from human language. So why is language unique to humans? We discuss anatomical differences between humans and other animals, the meaning of lesion studies in patients, the role of inner speech, and compare functional imaging studies in language with other modalities in respect to the dual loop model. These aspects might be helpful for understanding what kind of biological system the language faculty is, and how it relates to other systems in our own species and others. PMID:22783188

Neonatal neuroimaging: going beyond the pictures.

PubMed

Ramenghi, Luca A; Rutherford, Mary; Fumagalli, Monica; Bassi, Laura; Messner, Hubert; Counsell, Serena; Mosca, Fabio

2009-10-01

The cerebral ultrasound has been used many years for the diagnosis of brain lesions in term and preterm newborns. Major improvements were obtained by the combination of different imaging modalities such as Magnetic Resonance Imaging with the Diffusion Weighted Imaging (DWI) and the new quantitative Diffusion Tensor Imaging (DTI). The clinical use of MRI has been validated over some years especially to depict the perinatal asphyxia lesions in term newborns, but its use in order to diagnose the typical diseases of preterm babies is very recent and useful in identifying a marker able to predict neurological outcome. The imaging correlates for motor impairment are well recognized (periventricular white matter cavitations), but no any imaging correlate for cognitive impairment and neurobehavioral disorders. While DWI has been used in term newborns to identify the ischemic areas with restricted diffusion, it may be also used to characterize brain development in preterm infants with the Apparent Diffusion Coefficient (ADC) and may allow us to detect abnormalities responsible for the non-motor impairments. Recent datas showed that in infants without focal lesions higher ADC values in WM were associated with poorer neurodevelopmental assessment at 2 years. The DTI also allows to detect the Fractional Anisotropy (FA) that measures the microstructure. DTI can also be used to map the WM tracts in the immature brain and may be applied to understand the normal development or the response of the brain to injury. Some WM regions in the preterm brain have a lower FA suggesting that widespread WM abnormalities are present in preterms even in the absence of focal lesions. The complexity of the developing brain can be explained by the new tractography that can assess the connectivity of different WM regions and the association between structure and function, such as optic radiations microstructure and visual assessment score. Technological advances in neonatal brain imaging have made a major contribution to understand the neurobehavioral disorders of the developing brain that have the origin in the early structural cerebral organization and maturation.

Simultaneous acquisition of magnetic resonance spectroscopy (MRS) data and positron emission tomography (PET) images with a prototype MR-compatible, small animal PET imager

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Velan, S. Sendhil; Lemieux, Susan; Kross, Brian; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.

2007-06-01

Multi-modality imaging (such as PET-CT) is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET, fused with anatomical images created by MRI, allow the correlation of form with function. Perhaps more exciting than the combination of anatomical MRI with PET, is the melding of PET with MR spectroscopy (MRS). Thus, two aspects of physiology could be combined in novel ways to produce new insights into the physiology of normal and pathological processes. Our team is developing a system to acquire MRI images and MRS spectra, and PET images contemporaneously. The prototype MR-compatible PET system consists of two opposed detector heads (appropriate in size for small animal imaging), operating in coincidence mode with an active field-of-view of ˜14 cm in diameter. Each detector consists of an array of LSO detector elements coupled through a 2-m long fiber optic light guide to a single position-sensitive photomultiplier tube. The use of light guides allows these magnetic field-sensitive elements of the PET imager to be positioned outside the strong magnetic field of our 3T MRI scanner. The PET scanner imager was integrated with a 12-cm diameter, 12-leg custom, birdcage coil. Simultaneous MRS spectra and PET images were successfully acquired from a multi-modality phantom consisting of a sphere filled with 17 brain relevant substances and a positron-emitting radionuclide. There were no significant changes in MRI or PET scanner performance when both were present in the MRI magnet bore. This successful initial test demonstrates the potential for using such a multi-modality to obtain complementary MRS and PET data.

Imaging separation of neuronal from vascular effects of cocaine on rat cortical brain in vivo

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

Yuan, Z.; Du, C.; Yuan, Z.

MRI techniques to study brain function assume coupling between neuronal activity, metabolism and flow. However, recent evidence of physiological uncoupling between neuronal and cerebrovascular events highlights the need for methods to simultaneously measure these three properties. We report a multimodality optical approach that integrates dual-wavelength laser speckle imaging (measures changes in blood flow, blood volume and hemoglobin oxygenation), digital-frequency-ramping optical coherence tomography (images quantitative 3D vascular network) and Rhod2 fluorescence (images intracellular calcium for measure of neuronal activity) at high spatiotemporal resolutions (30 {micro}m, 10 Hz) and over a large field of view (3 x 5 mm{sup 2}). We applymore » it to assess cocaine's effects in rat cortical brain and show an immediate decrease 3.5 {+-} 0.9 min, phase (1) in the oxygen content of hemoglobin and the cerebral blood flow followed by an overshoot 7.1 {+-} 0.2 min, phase (2) lasting over 20 min whereas Ca{sup 2+} increased immediately (peaked at t = 4.1 {+-} 0.4 min) and remained elevated. This enabled us to identify a delay (2.9 {+-} 0.5 min) between peak neuronal and vascular responses in phase 2. The ability of this multimodality optical approach for simultaneous imaging at high spatiotemporal resolutions permits us to distinguish the vascular versus cellular changes of the brain, thus complimenting other neuroimaging modalities for brain functional studies (e. g., PET, fMRI).« less

Advanced imaging in acute stroke management-Part I: Computed tomographic.

PubMed

Saini, Monica; Butcher, Ken

2009-01-01

Neuroimaging is fundamental to stroke diagnosis and management. Non-contrast computed tomography (NCCT) has been the primary imaging modality utilized for this purpose for almost four decades. Although NCCT does permit identification of intracranial hemorrhage and parenchymal ischemic changes, insights into blood vessel patency and cerebral perfusion are limited. Advances in reperfusion strategies have made identification of potentially salvageable brain tissue a more practical concern. Advances in CT technology now permit identification of acute and chronic arterial lesions, as well as cerebral blood flow deficits. This review outlines principles of advanced CT image acquisition and its utility in acute stroke management.

Phase congruency map driven brain tumour segmentation

NASA Astrophysics Data System (ADS)

Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

2015-03-01

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

Use of Visual Cues by Adults With Traumatic Brain Injuries to Interpret Explicit and Inferential Information.

PubMed

Brown, Jessica A; Hux, Karen; Knollman-Porter, Kelly; Wallace, Sarah E

2016-01-01

Concomitant visual and cognitive impairments following traumatic brain injuries (TBIs) may be problematic when the visual modality serves as a primary source for receiving information. Further difficulties comprehending visual information may occur when interpretation requires processing inferential rather than explicit content. The purpose of this study was to compare the accuracy with which people with and without severe TBI interpreted information in contextually rich drawings. Fifteen adults with and 15 adults without severe TBI. Repeated-measures between-groups design. Participants were asked to match images to sentences that either conveyed explicit (ie, main action or background) or inferential (ie, physical or mental inference) information. The researchers compared accuracy between participant groups and among stimulus conditions. Participants with TBI demonstrated significantly poorer accuracy than participants without TBI extracting information from images. In addition, participants with TBI demonstrated significantly higher response accuracy when interpreting explicit rather than inferential information; however, no significant difference emerged between sentences referencing main action versus background information or sentences providing physical versus mental inference information for this participant group. Difficulties gaining information from visual environmental cues may arise for people with TBI given their difficulties interpreting inferential content presented through the visual modality.

Hearing, feeling or seeing a beat recruits a supramodal network in the auditory dorsal stream.

PubMed

Araneda, Rodrigo; Renier, Laurent; Ebner-Karestinos, Daniela; Dricot, Laurence; De Volder, Anne G

2017-06-01

Hearing a beat recruits a wide neural network that involves the auditory cortex and motor planning regions. Perceiving a beat can potentially be achieved via vision or even touch, but it is currently not clear whether a common neural network underlies beat processing. Here, we used functional magnetic resonance imaging (fMRI) to test to what extent the neural network involved in beat processing is supramodal, that is, is the same in the different sensory modalities. Brain activity changes in 27 healthy volunteers were monitored while they were attending to the same rhythmic sequences (with and without a beat) in audition, vision and the vibrotactile modality. We found a common neural network for beat detection in the three modalities that involved parts of the auditory dorsal pathway. Within this network, only the putamen and the supplementary motor area (SMA) showed specificity to the beat, while the brain activity in the putamen covariated with the beat detection speed. These results highlighted the implication of the auditory dorsal stream in beat detection, confirmed the important role played by the putamen in beat detection and indicated that the neural network for beat detection is mostly supramodal. This constitutes a new example of convergence of the same functional attributes into one centralized representation in the brain. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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.

Cerebral Amyloid Angiopathy: An Important Differential Diagnosis of Stroke in the Elderly

PubMed Central

AZMIN, Shahrul; OSMAN, Syazarina Sharis; MUKARI, Shahizon; SAHATHEVAN, Ramesh

2015-01-01

Cerebral amyloid angiopathy (CAA) accounts for approximately 10–20% of spontaneous intracerebral haemorrhage (ICH). This figure is thought to be higher in the elderly population. With the increasing life expectancy of our population, we anticipate that the prevalence of CAA- related ICH will increase in tandem. Although CAA-related ICH and hypertension-related ICH are distinct entities based on histopathology and imaging, the clinical presentation of the two conditions is similar. The use of brain computed tomography (CT) scans remain the ICH imaging modality of choice in Malaysia due to its availability, cost, and sensitivity in detecting acute bleeds. On the other hand, the use of brain magnetic resonance imaging (MRI) with susceptibility-weighted imaging (SWI) sequencing enables the clinician to determine the presence of chronic blood products in the brain, especially clinically silent microbleeds associated with CAA. However, the use of brain MRI scans in our country is limited and leads to a blurring of lines when differentiating between hypertension-related ICH and CAA-related ICH. How this misrepresentation affects the management of these conditions is unclear. In this study, we present two cases of ICH to illustrate this point and to serve as a springboard to question current practice and promote discussion. PMID:25892953

General Anesthesia Inhibits the Activity of the “Glymphatic System”

PubMed Central

Gakuba, Clement; Gaberel, Thomas; Goursaud, Suzanne; Bourges, Jennifer; Di Palma, Camille; Quenault, Aurélien; Martinez de Lizarrondo, Sara; Vivien, Denis; Gauberti, Maxime

2018-01-01

INTRODUCTION: According to the “glymphatic system” hypothesis, brain waste clearance is mediated by a continuous replacement of the interstitial milieu by a bulk flow of cerebrospinal fluid (CSF). Previous reports suggested that this cerebral CSF circulation is only active during general anesthesia or sleep, an effect mediated by the dilatation of the extracellular space. Given the controversies regarding the plausibility of this phenomenon and the limitations of currently available methods to image the glymphatic system, we developed original whole-brain in vivo imaging methods to investigate the effects of general anesthesia on the brain CSF circulation. METHODS: We used magnetic resonance imaging (MRI) and near-infrared fluorescence imaging (NIRF) after injection of a paramagnetic contrast agent or a fluorescent dye in the cisterna magna, in order to investigate the impact of general anesthesia (isoflurane, ketamine or ketamine/xylazine) on the intracranial CSF circulation in mice. RESULTS: In vivo imaging allowed us to image CSF flow in awake and anesthetized mice and confirmed the existence of a brain-wide CSF circulation. Contrary to what was initially thought, we demonstrated that the parenchymal CSF circulation is mainly active during wakefulness and significantly impaired during general anesthesia. This effect was especially significant when high doses of anesthetic agent were used (3% isoflurane). These results were consistent across the different anesthesia regimens and imaging modalities. Moreover, we failed to detect a significant change in the brain extracellular water volume using diffusion weighted imaging in awake and anesthetized mice. CONCLUSION: The parenchymal diffusion of small molecular weight compounds from the CSF is active during wakefulness. General anesthesia has a negative impact on the intracranial CSF circulation, especially when using a high dose of anesthetic agent. PMID:29344300

General Anesthesia Inhibits the Activity of the "Glymphatic System".

PubMed

Gakuba, Clement; Gaberel, Thomas; Goursaud, Suzanne; Bourges, Jennifer; Di Palma, Camille; Quenault, Aurélien; de Lizarrondo, Sara Martinez; Vivien, Denis; Gauberti, Maxime

2018-01-01

INTRODUCTION: According to the "glymphatic system" hypothesis, brain waste clearance is mediated by a continuous replacement of the interstitial milieu by a bulk flow of cerebrospinal fluid (CSF). Previous reports suggested that this cerebral CSF circulation is only active during general anesthesia or sleep, an effect mediated by the dilatation of the extracellular space. Given the controversies regarding the plausibility of this phenomenon and the limitations of currently available methods to image the glymphatic system, we developed original whole-brain in vivo imaging methods to investigate the effects of general anesthesia on the brain CSF circulation. METHODS: We used magnetic resonance imaging (MRI) and near-infrared fluorescence imaging (NIRF) after injection of a paramagnetic contrast agent or a fluorescent dye in the cisterna magna, in order to investigate the impact of general anesthesia (isoflurane, ketamine or ketamine/xylazine) on the intracranial CSF circulation in mice. RESULTS: In vivo imaging allowed us to image CSF flow in awake and anesthetized mice and confirmed the existence of a brain-wide CSF circulation. Contrary to what was initially thought, we demonstrated that the parenchymal CSF circulation is mainly active during wakefulness and significantly impaired during general anesthesia. This effect was especially significant when high doses of anesthetic agent were used (3% isoflurane). These results were consistent across the different anesthesia regimens and imaging modalities. Moreover, we failed to detect a significant change in the brain extracellular water volume using diffusion weighted imaging in awake and anesthetized mice. CONCLUSION: The parenchymal diffusion of small molecular weight compounds from the CSF is active during wakefulness. General anesthesia has a negative impact on the intracranial CSF circulation, especially when using a high dose of anesthetic agent.

Artifact removal algorithms for stroke detection using a multistatic MIST beamforming algorithm.

PubMed

Ricci, E; Di Domenico, S; Cianca, E; Rossi, T

2015-01-01

Microwave imaging (MWI) has been recently proved as a promising imaging modality for low-complexity, low-cost and fast brain imaging tools, which could play a fundamental role to efficiently manage emergencies related to stroke and hemorrhages. This paper focuses on the UWB radar imaging approach and in particular on the processing algorithms of the backscattered signals. Assuming the use of the multistatic version of the MIST (Microwave Imaging Space-Time) beamforming algorithm, developed by Hagness et al. for the early detection of breast cancer, the paper proposes and compares two artifact removal algorithms. Artifacts removal is an essential step of any UWB radar imaging system and currently considered artifact removal algorithms have been shown not to be effective in the specific scenario of brain imaging. First of all, the paper proposes modifications of a known artifact removal algorithm. These modifications are shown to be effective to achieve good localization accuracy and lower false positives. However, the main contribution is the proposal of an artifact removal algorithm based on statistical methods, which allows to achieve even better performance but with much lower computational complexity.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8.

PubMed

Ferreira, Fábio S; Pereira, João M S; Duarte, João V; Castelo-Branco, Miguel

2017-01-01

Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

PubMed Central

Ferreira, Fábio S.; Pereira, João M.S.; Duarte, João V.; Castelo-Branco, Miguel

2017-01-01

Background: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Objective: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). Method: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately – using standard univariate VBM - and simultaneously, with multivariate analyses. Results: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. Conclusion: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities. PMID:28761571

Non-destructive optical clearing technique enhances optical coherence tomography (OCT) for real-time, 3D histomorphometry of brain tissue (Conference Presentation)

NASA Astrophysics Data System (ADS)

Paul, Akshay; Chang, Theodore H.; Chou, Li-Dek; Ramalingam, Tirunelveli S.

2016-03-01

Evaluation of neurodegenerative disease often requires examination of brain morphology. Volumetric analysis of brain regions and structures can be used to track developmental changes, progression of disease, and the presence of transgenic phenotypes. Current standards for microscopic investigation of brain morphology are limited to detection of superficial structures at a maximum depth of 300μm. While histological techniques can provide detailed cross-sections of brain structures, they require complicated tissue preparation and the ultimate destruction of the sample. A non-invasive, label-free imaging modality known as Optical Coherence Tomography (OCT) can produce 3-dimensional reconstructions through high-speed, cross-sectional scans of biological tissue. Although OCT allows for the preservation of intact samples, the highly scattering and absorbing properties of biological tissue limit imaging depth to 1-2mm. Optical clearing agents have been utilized to increase imaging depth by index matching and lipid digestion, however, these contemporary techniques are expensive and harsh on tissues, often irreversibly denaturing proteins. Here we present an ideal optical clearing agent that offers ease-of-use and reversibility. Similar to how SeeDB has been effective for microscopy, our fructose-based, reversible optical clearing technique provides improved OCT imaging and functional immunohistochemical mapping of disease. Fructose is a natural, non-toxic sugar with excellent water solubility, capable of increasing tissue transparency and reducing light scattering. We will demonstrate the improved depth-resolving performance of OCT for enhanced whole-brain imaging of normal and diseased murine brains following a fructose clearing treatment. This technique potentially enables rapid, 3-dimensional evaluation of biological tissues at axial and lateral resolutions comparable to histopathology.

Utilization of a multimedia PACS workstation for surgical planning of epilepsy

NASA Astrophysics Data System (ADS)

Soo Hoo, Kent; Wong, Stephen T.; Hawkins, Randall A.; Knowlton, Robert C.; Laxer, Kenneth D.; Rowley, Howard A.

1997-05-01

Surgical treatment of temporal lobe epilepsy requires the localization of the epileptogenic zone for surgical resection. Currently, clinicians utilize electroencephalography, various neuroimaging modalities, and psychological tests together to determine the location of this zone. We investigate how a multimedia neuroimaging workstation built on top of the UCSF Picture Archiving and Communication System can be used to aid surgical planning of epilepsy and related brain diseases. This usage demonstrates the ability of the workstation to retrieve image and textural data from PACS and other image sources, register multimodality images, visualize and render 3D data sets, analyze images, generate new image and text data from the analysis, and organize all data in a relational database management system.

Neuroimaging is a novel tool to understand the impact of environmental chemicals on neurodevelopment

PubMed Central

Horton, Megan K.; Margolis, Amy E.; Tang, Cheuk; Wright, Robert

2014-01-01

Purpose of review The prevalence of childhood neurodevelopmental disorders (ND) has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of NDs. Very little is known about the mechanistic processes by which environmental chemicals alter brain development. We review recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Recent findings Neuroimaging techniques (volumetric and functional magnetic resonance imaging (MRI), diffusor tensor imaging (DTI), magnetic resonance spectroscopy (MRS)) have opened unprecedented access to study the developing human brain. These techniques are non-invasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. Summary MRI is a powerful tool that allows in vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure. PMID:24535497

WE-B-210-01: Introduction

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

Holland, M.

In the last fifteen years, the introduction of plane or diverging wave transmissions rather than line by line scanning focused beams has broken the conventional barriers of ultrasound imaging. By using such large field of view transmissions, the frame rate reaches the theoretical limit of physics dictated by the ultrasound speed and an ultrasonic map can be provided typically in tens of micro-seconds (several thousands of frames per second). Interestingly, this leap in frame rate is not only a technological breakthrough but it permits the advent of completely new ultrasound imaging modes, including shear wave elastography, electromechanical wave imaging, ultrafastmore » doppler, ultrafast contrast imaging, and even functional ultrasound imaging of brain activity (fUltrasound) introducing Ultrasound as an emerging full-fledged neuroimaging modality. At ultrafast frame rates, it becomes possible to track in real time the transient vibrations – known as shear waves – propagating through organs. Such “human body seismology” provides quantitative maps of local tissue stiffness whose added value for diagnosis has been recently demonstrated in many fields of radiology (breast, prostate and liver cancer, cardiovascular imaging, …). Today, Supersonic Imagine company is commercializing the first clinical ultrafast ultrasound scanner, Aixplorer with real time Shear Wave Elastography. This is the first example of an ultrafast Ultrasound approach surpassing the research phase and now widely spread in the clinical medical ultrasound community with an installed base of more than 1000 Aixplorer systems in 54 countries worldwide. For blood flow imaging, ultrafast Doppler permits high-precision characterization of complex vascular and cardiac flows. It also gives ultrasound the ability to detect very subtle blood flow in very small vessels. In the brain, such ultrasensitive Doppler paves the way for fUltrasound (functional ultrasound imaging) of brain activity with unprecedented spatial and temporal resolution compared to fMRI. Combined with contrast agents, our group demonstrated that Ultrafast Ultrasound Localization could provide a first in vivo and non invasive imaging modality at microscopic scales deep into organs. Many of these ultrafast modes should lead to major improvements in ultrasound screening, diagnosis, and therapeutic monitoring. Learning Objectives: Achieve familiarity with recent advances in ultrafast ultrasound imaging technology. Develop an understanding of potential applications of ultrafast ultrasound imaging for diagnosis and therapeutic monitoring. Dr. Tanter is a co-founder of Supersonic Imagine,a French company positioned in the field of medical ultrasound imaging and therapy.« less

WE-B-210-00: Carson/Zagzebski Distinguished Lectureship

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

NONE

In the last fifteen years, the introduction of plane or diverging wave transmissions rather than line by line scanning focused beams has broken the conventional barriers of ultrasound imaging. By using such large field of view transmissions, the frame rate reaches the theoretical limit of physics dictated by the ultrasound speed and an ultrasonic map can be provided typically in tens of micro-seconds (several thousands of frames per second). Interestingly, this leap in frame rate is not only a technological breakthrough but it permits the advent of completely new ultrasound imaging modes, including shear wave elastography, electromechanical wave imaging, ultrafastmore » doppler, ultrafast contrast imaging, and even functional ultrasound imaging of brain activity (fUltrasound) introducing Ultrasound as an emerging full-fledged neuroimaging modality. At ultrafast frame rates, it becomes possible to track in real time the transient vibrations – known as shear waves – propagating through organs. Such “human body seismology” provides quantitative maps of local tissue stiffness whose added value for diagnosis has been recently demonstrated in many fields of radiology (breast, prostate and liver cancer, cardiovascular imaging, …). Today, Supersonic Imagine company is commercializing the first clinical ultrafast ultrasound scanner, Aixplorer with real time Shear Wave Elastography. This is the first example of an ultrafast Ultrasound approach surpassing the research phase and now widely spread in the clinical medical ultrasound community with an installed base of more than 1000 Aixplorer systems in 54 countries worldwide. For blood flow imaging, ultrafast Doppler permits high-precision characterization of complex vascular and cardiac flows. It also gives ultrasound the ability to detect very subtle blood flow in very small vessels. In the brain, such ultrasensitive Doppler paves the way for fUltrasound (functional ultrasound imaging) of brain activity with unprecedented spatial and temporal resolution compared to fMRI. Combined with contrast agents, our group demonstrated that Ultrafast Ultrasound Localization could provide a first in vivo and non invasive imaging modality at microscopic scales deep into organs. Many of these ultrafast modes should lead to major improvements in ultrasound screening, diagnosis, and therapeutic monitoring. Learning Objectives: Achieve familiarity with recent advances in ultrafast ultrasound imaging technology. Develop an understanding of potential applications of ultrafast ultrasound imaging for diagnosis and therapeutic monitoring. Dr. Tanter is a co-founder of Supersonic Imagine,a French company positioned in the field of medical ultrasound imaging and therapy.« less

WE-B-210-03: Closing

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

Holland, M.

In the last fifteen years, the introduction of plane or diverging wave transmissions rather than line by line scanning focused beams has broken the conventional barriers of ultrasound imaging. By using such large field of view transmissions, the frame rate reaches the theoretical limit of physics dictated by the ultrasound speed and an ultrasonic map can be provided typically in tens of micro-seconds (several thousands of frames per second). Interestingly, this leap in frame rate is not only a technological breakthrough but it permits the advent of completely new ultrasound imaging modes, including shear wave elastography, electromechanical wave imaging, ultrafastmore » doppler, ultrafast contrast imaging, and even functional ultrasound imaging of brain activity (fUltrasound) introducing Ultrasound as an emerging full-fledged neuroimaging modality. At ultrafast frame rates, it becomes possible to track in real time the transient vibrations – known as shear waves – propagating through organs. Such “human body seismology” provides quantitative maps of local tissue stiffness whose added value for diagnosis has been recently demonstrated in many fields of radiology (breast, prostate and liver cancer, cardiovascular imaging, …). Today, Supersonic Imagine company is commercializing the first clinical ultrafast ultrasound scanner, Aixplorer with real time Shear Wave Elastography. This is the first example of an ultrafast Ultrasound approach surpassing the research phase and now widely spread in the clinical medical ultrasound community with an installed base of more than 1000 Aixplorer systems in 54 countries worldwide. For blood flow imaging, ultrafast Doppler permits high-precision characterization of complex vascular and cardiac flows. It also gives ultrasound the ability to detect very subtle blood flow in very small vessels. In the brain, such ultrasensitive Doppler paves the way for fUltrasound (functional ultrasound imaging) of brain activity with unprecedented spatial and temporal resolution compared to fMRI. Combined with contrast agents, our group demonstrated that Ultrafast Ultrasound Localization could provide a first in vivo and non invasive imaging modality at microscopic scales deep into organs. Many of these ultrafast modes should lead to major improvements in ultrasound screening, diagnosis, and therapeutic monitoring. Learning Objectives: Achieve familiarity with recent advances in ultrafast ultrasound imaging technology. Develop an understanding of potential applications of ultrafast ultrasound imaging for diagnosis and therapeutic monitoring. Dr. Tanter is a co-founder of Supersonic Imagine,a French company positioned in the field of medical ultrasound imaging and therapy.« less

Multi-modal neuroimaging in premanifest and early Huntington's disease: 18 month longitudinal data from the IMAGE-HD study.

PubMed

Domínguez D, Juan F; Egan, Gary F; Gray, Marcus A; Poudel, Govinda R; Churchyard, Andrew; Chua, Phyllis; Stout, Julie C; Georgiou-Karistianis, Nellie

2013-01-01

IMAGE-HD is an Australian based multi-modal longitudinal magnetic resonance imaging (MRI) study in premanifest and early symptomatic Huntington's disease (pre-HD and symp-HD, respectively). In this investigation we sought to determine the sensitivity of imaging methods to detect macrostructural (volume) and microstructural (diffusivity) longitudinal change in HD. We used a 3T MRI scanner to acquire T1 and diffusion weighted images at baseline and 18 months in 31 pre-HD, 31 symp-HD and 29 controls. Volume was measured across the whole brain, and volume and diffusion measures were ascertained for caudate and putamen. We observed a range of significant volumetric and, for the first time, diffusion changes over 18 months in both pre-HD and symp-HD, relative to controls, detectable at the brain-wide level (volume change in grey and white matter) and in caudate and putamen (volume and diffusivity change). Importantly, longitudinal volume change in the caudate was the only measure that discriminated between groups across all stages of disease: far from diagnosis (>15 years), close to diagnosis (<15 years) and after diagnosis. Of the two diffusion metrics (mean diffusivity, MD; fractional anisotropy, FA), only longitudinal FA change was sensitive to group differences, but only after diagnosis. These findings further confirm caudate atrophy as one of the most sensitive and early biomarkers of neurodegeneration in HD. They also highlight that different tissue properties have varying schedules in their ability to discriminate between groups along disease progression and may therefore inform biomarker selection for future therapeutic interventions.

Distinct cortical areas for names of numbers and body parts independent of language and input modality.

PubMed

Le Clec'H, G; Dehaene, S; Cohen, L; Mehler, J; Dupoux, E; Poline, J B; Lehéricy, S; van de Moortele, P F; Le Bihan, D

2000-10-01

Some models of word comprehension postulate that the processing of words presented in different modalities and languages ultimately converges toward common cerebral systems associated with semantic-level processing and that the localization of these systems may vary with the category of semantic knowledge being accessed. We used functional magnetic resonance imaging to investigate this hypothesis with two categories of words, numerals, and body parts, for which the existence of distinct category-specific areas is debated in neuropsychology. Across two experiments, one with a blocked design and the other with an event-related design, a reproducible set of left-hemispheric parietal and prefrontal areas showed greater activation during the manipulation of topographical knowledge about body parts and a right-hemispheric parietal network during the manipulation of numerical quantities. These results complement the existing neuropsychological and brain-imaging literature by suggesting that within the extensive network of bilateral parietal regions active during both number and body-part processing, a subset shows category-specific responses independent of the language and modality of presentation. Copyright 2000 Academic Press.

A combined MR and CT study for precise quantitative analysis of the avian brain

NASA Astrophysics Data System (ADS)

Jirak, Daniel; Janacek, Jiri; Kear, Benjamin P.

2015-10-01

Brain size is widely used as a measure of behavioural complexity and sensory-locomotive capacity in avians but has largely relied upon laborious dissections, endoneurocranial tissue displacement, and physical measurement to derive comparative volumes. As an alternative, we present a new precise calculation method based upon coupled magnetic resonance (MR) imaging and computed tomography (CT). Our approach utilizes a novel interactive Fakir probe cross-referenced with an automated CT protocol to efficiently generate total volumes and surface areas of the brain tissue and endoneurocranial space, as well as the discrete cephalic compartments. We also complemented our procedures by using sodium polytungstate (SPT) as a contrast agent. This greatly enhanced CT applications but did not degrade MR quality and is therefore practical for virtual brain tissue reconstructions employing multiple imaging modalities. To demonstrate our technique, we visualized sex-based brain size differentiation in a sample set of Ring-necked pheasants (Phasianus colchicus). This revealed no significant variance in relative volume or surface areas of the primary brain regions. Rather, a trend towards isometric enlargement of the total brain and endoneurocranial space was evidenced in males versus females, thus advocating a non-differential sexually dimorphic pattern of brain size increase amongst these facultatively flying birds.

[The autopsy of the brain and spinal cord in the diagnosis of neurodegenerative diseases - a practical approach to optimize the examination].

PubMed

Rohan, Zdeněk; Matěj, Radoslav

2015-01-01

Brain and spinal cord autopsies aimed at neuropathological diagnosis of the causes of dementia and motor abnormalities are of increasing importance. Neuropathological brain examination is often the only diagnostic modality capable of definitive diagnosis of a neurodegenerative disease and thus serves as invaluable feedback for clinicians and biochemical and imaging diagnostics. The brain and spinal cord autopsy is performed following a standardized protocol and its goal is to sample all diagnostically relevant structures. Subsequent diagnostics are then done using standard and special histologic stainings, however state-of-the-art diagnostics can be achieved only using immunohistochemical methods. The purpose of the article is to provide the pathologists with a brief and practical guideline for brain and spinal cord autopsy when diagnosis of a neurodegenerative disease is suspected.

PET Imaging - from Physics to Clinical Molecular Imaging

NASA Astrophysics Data System (ADS)

Majewski, Stan

2008-03-01

From the beginnings many years ago in a few physics laboratories and first applications as a research brain function imager, PET became lately a leading molecular imaging modality used in diagnosis, staging and therapy monitoring of cancer, as well as has increased use in assessment of brain function (early diagnosis of Alzheimer's, etc) and in cardiac function. To assist with anatomic structure map and with absorption correction CT is often used with PET in a duo system. Growing interest in the last 5-10 years in dedicated organ specific PET imagers (breast, prostate, brain, etc) presents again an opportunity to the particle physics instrumentation community to contribute to the important field of medical imaging. In addition to the bulky standard ring structures, compact, economical and high performance mobile imagers are being proposed and build. The latest development in standard PET imaging is introduction of the well known TOF concept enabling clearer tomographic pictures of the patient organs. Development and availability of novel photodetectors such as Silicon PMT immune to magnetic fields offers an exciting opportunity to use PET in conjunction with MRI and fMRI. As before with avalanche photodiodes, particle physics community plays a leading role in developing these devices. The presentation will mostly focus on present and future opportunities for better PET designs based on new technologies and methods: new scintillators, photodetectors, readout, software.

Reorganization of neural systems mediating peripheral visual selective attention in the deaf: An optical imaging study.

PubMed

Seymour, Jenessa L; Low, Kathy A; Maclin, Edward L; Chiarelli, Antonio M; Mathewson, Kyle E; Fabiani, Monica; Gratton, Gabriele; Dye, Matthew W G

2017-01-01

Theories of brain plasticity propose that, in the absence of input from the preferred sensory modality, some specialized brain areas may be recruited when processing information from other modalities, which may result in improved performance. The Useful Field of View task has previously been used to demonstrate that early deafness positively impacts peripheral visual attention. The current study sought to determine the neural changes associated with those deafness-related enhancements in visual performance. Based on previous findings, we hypothesized that recruitment of posterior portions of Brodmann area 22, a brain region most commonly associated with auditory processing, would be correlated with peripheral selective attention as measured using the Useful Field of View task. We report data from severe to profoundly deaf adults and normal-hearing controls who performed the Useful Field of View task while cortical activity was recorded using the event-related optical signal. Behavioral performance, obtained in a separate session, showed that deaf subjects had lower thresholds (i.e., better performance) on the Useful Field of View task. The event-related optical data indicated greater activity for the deaf adults than for the normal-hearing controls during the task in the posterior portion of Brodmann area 22 in the right hemisphere. Furthermore, the behavioral thresholds correlated significantly with this neural activity. This work provides further support for the hypothesis that cross-modal plasticity in deaf individuals appears in higher-order auditory cortices, whereas no similar evidence was obtained for primary auditory areas. It is also the only neuroimaging study to date that has linked deaf-related changes in the right temporal lobe to visual task performance outside of the imaging environment. The event-related optical signal is a valuable technique for studying cross-modal plasticity in deaf humans. The non-invasive and relatively quiet characteristics of this technique have great potential utility in research with clinical populations such as deaf children and adults who have received cochlear or auditory brainstem implants. Copyright © 2016 Elsevier B.V. All rights reserved.

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images.

PubMed

Gong, Kuang; Yang, Jaewon; Kim, Kyungsang; El Fakhri, Georges; Seo, Youngho; Li, Quanzheng

2018-05-23

Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as Magnetic Resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we present deep neural network methods to derive the continuous attenuation coefficients for brain PET imaging from MR images. With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods. When both Dixon and zero echo time (ZTE) images are available, we have proposed a modified U-net structure, named GroupU-net, to efficiently make use of both Dixon and ZTE information through group convolution modules when the network goes deeper. Quantitative analysis based on fourteen real patient data sets demonstrates that both network approaches can perform better than the standard methods, and the proposed network structure can further reduce the PET quantification error compared to the U-net structure. © 2018 Institute of Physics and Engineering in Medicine.

Graph theory findings in the pathophysiology of temporal lobe epilepsy

PubMed Central

Chiang, Sharon; Haneef, Zulfi

2014-01-01

Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE. PMID:24831083

Quantitative mouse brain phenotyping based on single and multispectral MR protocols

PubMed Central

Badea, Alexandra; Gewalt, Sally; Avants, Brian B.; Cook, James J.; Johnson, G. Allan

2013-01-01

Sophisticated image analysis methods have been developed for the human brain, but such tools still need to be adapted and optimized for quantitative small animal imaging. We propose a framework for quantitative anatomical phenotyping in mouse models of neurological and psychiatric conditions. The framework encompasses an atlas space, image acquisition protocols, and software tools to register images into this space. We show that a suite of segmentation tools (Avants, Epstein et al., 2008) designed for human neuroimaging can be incorporated into a pipeline for segmenting mouse brain images acquired with multispectral magnetic resonance imaging (MR) protocols. We present a flexible approach for segmenting such hyperimages, optimizing registration, and identifying optimal combinations of image channels for particular structures. Brain imaging with T1, T2* and T2 contrasts yielded accuracy in the range of 83% for hippocampus and caudate putamen (Hc and CPu), but only 54% in white matter tracts, and 44% for the ventricles. The addition of diffusion tensor parameter images improved accuracy for large gray matter structures (by >5%), white matter (10%), and ventricles (15%). The use of Markov random field segmentation further improved overall accuracy in the C57BL/6 strain by 6%; so Dice coefficients for Hc and CPu reached 93%, for white matter 79%, for ventricles 68%, and for substantia nigra 80%. We demonstrate the segmentation pipeline for the widely used C57BL/6 strain, and two test strains (BXD29, APP/TTA). This approach appears promising for characterizing temporal changes in mouse models of human neurological and psychiatric conditions, and may provide anatomical constraints for other preclinical imaging, e.g. fMRI and molecular imaging. This is the first demonstration that multiple MR imaging modalities combined with multivariate segmentation methods lead to significant improvements in anatomical segmentation in the mouse brain. PMID:22836174

Your brain on drugs: imaging of drug-related changes in the central nervous system.

PubMed

Tamrazi, Benita; Almast, Jeevak

2012-01-01

Drug abuse is a substantial problem in society today and is associated with significant morbidity and mortality. Various drugs are associated with serious complications affecting the brain, and it is critical to recognize the imaging findings of these complications to provide prompt medical management. The central nervous system (CNS) is a target organ for drugs of abuse as well as specific prescribed medications. Drugs of abuse affecting the CNS include cocaine, heroin, alcohol, amphetamines, toluene, and cannabis. Prescribed medications or medical therapies that can affect the CNS include immunosuppressants, antiepileptics, nitrous oxide, and total parenteral nutrition. The CNS complications of these drugs include neurovascular complications, encephalopathy, atrophy, infection, changes in the corpus callosum, and other miscellaneous changes. Imaging abnormalities indicative of these complications can be appreciated at both magnetic resonance (MR) imaging and computed tomography (CT). It is critical for radiologists to recognize complications related to drugs of abuse as well as iatrogenic effects of various medications. Therefore, diagnostic imaging modalities such as MR imaging and CT can play a pivotal role in the recognition and timely management of drug-related complications in the CNS.

The Washington University Central Neuroimaging Data Archive

PubMed Central

Gurney, Jenny; Olsen, Timothy; Flavin, John; Ramaratnam, Mohana; Archie, Kevin; Ransford, James; Herrick, Rick; Wallace, Lauren; Cline, Jeanette; Horton, Will; Marcus, Daniel S

2016-01-01

Since the early 2000’s, much of the neuroimaging work at Washington University (WU) has been facilitated by the Central Neuroimaging Data Archive (CNDA), an XNAT-based imaging informatics system. The CNDA is uniquely related to XNAT, as it served as the original codebase for the XNAT open source platform. The CNDA hosts data acquired in over 1000 research studies, encompassing 36,000 subjects and more than 60,000 imaging sessions. Most imaging modalities used in modern human research are represented in the CNDA, including magnetic resonance (MR), positron emission tomography (PET), computed tomography (CT), nuclear medicine (NM), computed radiography (CR), digital radiography (DX), and ultrasound (US). However, the majority of the imaging data in the CNDA are MR and PET of the human brain. Currently, about 20% of the total imaging data in the CNDA is available by request to external researchers. CNDA’s available data includes large sets of imaging sessions and in some cases clinical, psychometric, tissue, or genetic data acquired in the study of Alzheimer’s disease, brain metabolism, cancer, HIV, sickle cell anemia, and Tourette syndrome. PMID:26439514

Folic acid-functionalized up-conversion nanoparticles: toxicity studies in vivo and in vitro and targeted imaging applications

NASA Astrophysics Data System (ADS)

Sun, Lining; Wei, Zuwu; Chen, Haige; Liu, Jinliang; Guo, Jianjian; Cao, Ming; Wen, Tieqiao; Shi, Liyi

2014-07-01

Folate receptors (FRs) are overexpressed on a variety of human cancer cells and tissues, including cancers of the breast, ovaries, endometrium, and brain. This over-expression of FRs can be used to target folate-linked imaging specifically to FR-expressing tumors. Fluorescence is emerging as a powerful new modality for molecular imaging in both the diagnosis and treatment of disease. Combining innovative molecular biology and chemistry, we prepared three kinds of folate-targeted up-conversion nanoparticles as imaging agents (UCNC-FA: UCNC-Er-FA, UCNC-Tm-FA, and UCNC-Er,Tm-FA). In vivo and in vitro toxicity studies showed that these nanoparticles have both good biocompatibility and low toxicity. Moreover, the up-conversion luminescence imaging indicated that they have good targeting to HeLa cells and can therefore serve as potential fluorescent contrast agents.Folate receptors (FRs) are overexpressed on a variety of human cancer cells and tissues, including cancers of the breast, ovaries, endometrium, and brain. This over-expression of FRs can be used to target folate-linked imaging specifically to FR-expressing tumors. Fluorescence is emerging as a powerful new modality for molecular imaging in both the diagnosis and treatment of disease. Combining innovative molecular biology and chemistry, we prepared three kinds of folate-targeted up-conversion nanoparticles as imaging agents (UCNC-FA: UCNC-Er-FA, UCNC-Tm-FA, and UCNC-Er,Tm-FA). In vivo and in vitro toxicity studies showed that these nanoparticles have both good biocompatibility and low toxicity. Moreover, the up-conversion luminescence imaging indicated that they have good targeting to HeLa cells and can therefore serve as potential fluorescent contrast agents. Electronic supplementary information (ESI) available: Up-conversion luminescence spectra of UCNC-Er and UCNC-Er-FA, UCNC-Tm and UCNC-Tm-FA. Confocal luminescence imaging data collected as a series along the Z optical axis. See DOI: 10.1039/c4nr02312a

Detection of human brain tumor infiltration with multimodal multiscale optical analysis

NASA Astrophysics Data System (ADS)

Poulon, Fanny; Metais, Camille; Jamme, Frederic; Zanello, Marc; Varlet, Pascale; Devaux, Bertrand; Refregiers, Matthieu; Abi Haidar, Darine

2017-02-01

Brain tumor surgeries are facing major challenges to improve patients' quality of life. The extent of resection while preserving surrounding eloquent brain areas is necessary to equilibrate the onco-functional. A tool able to increase the accuracy of tissue analysis and to deliver an immediate diagnostic on tumor, could drastically improve actual surgeries and patient survival rates. To achieve such performances a complete optical study, ranging from ultraviolet to infrared, of biopsies has been started by our group. Four different contrasts were used: 1) spectral analysis covering the DUV to IR range, 2) two photon fluorescence lifetime imaging and one photon time domain measurement, 3) second harmonic generation imaging and 4) fluorescence imaging using DUV to IR, one and two photon excitation. All these measurements were done on the endogenous fluorescence of tissues to avoid any bias and further clinical complication due to the introduction of external markers. The different modalities are then crossed to build a matrix of criteria to discriminate tumorous tissues. The results of multimodal optical analysis on human biopsies were compared to the gold standard histopathology.

Stereotactic intracranial implantation and in vivo bioluminescent imaging of tumor xenografts in a mouse model system of glioblastoma multiforme.

PubMed

Baumann, Brian C; Dorsey, Jay F; Benci, Joseph L; Joh, Daniel Y; Kao, Gary D

2012-09-25

Glioblastoma multiforme (GBM) is a high-grade primary brain cancer with a median survival of only 14.6 months in humans despite standard tri-modality treatment consisting of surgical resection, post-operative radiation therapy and temozolomide chemotherapy. New therapeutic approaches are clearly needed to improve patient survival and quality of life. The development of more effective treatment strategies would be aided by animal models of GBM that recapitulate human disease yet allow serial imaging to monitor tumor growth and treatment response. In this paper, we describe our technique for the precise stereotactic implantation of bio-imageable GBM cancer cells into the brains of nude mice resulting in tumor xenografts that recapitulate key clinical features of GBM. This method yields tumors that are reproducible and are located in precise anatomic locations while allowing in vivo bioluminescent imaging to serially monitor intracranial xenograft growth and response to treatments. This method is also well-tolerated by the animals with low perioperative morbidity and mortality.

Harvard Aging Brain Study: Dataset and accessibility.

PubMed

Dagley, Alexander; LaPoint, Molly; Huijbers, Willem; Hedden, Trey; McLaren, Donald G; Chatwal, Jasmeer P; Papp, Kathryn V; Amariglio, Rebecca E; Blacker, Deborah; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Schultz, Aaron P

2017-01-01

The Harvard Aging Brain Study is sharing its data with the global research community. The longitudinal dataset consists of a 284-subject cohort with the following modalities acquired: demographics, clinical assessment, comprehensive neuropsychological testing, clinical biomarkers, and neuroimaging. To promote more extensive analyses, imaging data was designed to be compatible with other publicly available datasets. A cloud-based system enables access to interested researchers with blinded data available contingent upon completion of a data usage agreement and administrative approval. Data collection is ongoing and currently in its fifth year. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

A novel approach to analyzing fMRI and SNP data via parallel independent component analysis

NASA Astrophysics Data System (ADS)

Liu, Jingyu; Pearlson, Godfrey; Calhoun, Vince; Windemuth, Andreas

2007-03-01

There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.

Spatial patterns of atrophy, hypometabolism, and amyloid deposition in Alzheimer's disease correspond to dissociable functional brain networks.

PubMed

Grothe, Michel J; Teipel, Stefan J

2016-01-01

Recent neuroimaging studies of Alzheimer's disease (AD) have emphasized topographical similarities between AD-related brain changes and a prominent cortical association network called the default-mode network (DMN). However, the specificity of distinct imaging abnormalities for the DMN compared to other intrinsic connectivity networks (ICNs) of the limbic and heteromodal association cortex has not yet been examined systematically. We assessed regional amyloid load using AV45-PET, neuronal metabolism using FDG-PET, and gray matter volume using structural MRI in 473 participants from the Alzheimer's Disease Neuroimaging Initiative, including preclinical, predementia, and clinically manifest AD stages. Complementary region-of-interest and voxel-based analyses were used to assess disease stage- and modality-specific changes within seven principle ICNs of the human brain as defined by a standardized functional connectivity atlas. Amyloid deposition in AD dementia showed a preference for the DMN, but high effect sizes were also observed for other neocortical ICNs, most notably the frontoparietal-control network. Atrophic changes were most specific for an anterior limbic network, followed by the DMN, whereas other neocortical networks were relatively spared. Hypometabolism appeared to be a mixture of both amyloid- and atrophy-related profiles. Similar patterns of modality-dependent network specificity were also observed in the predementia and, for amyloid deposition, in the preclinical stage. These quantitative data confirm a high vulnerability of the DMN for multimodal imaging abnormalities in AD. However, rather than being selective for the DMN, imaging abnormalities more generally affect higher order cognitive networks and, importantly, the vulnerability profiles of these networks markedly differ for distinct aspects of AD pathology. © 2015 Wiley Periodicals, Inc.

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.

Preclinical Efficacy of the Anti-Hepatocyte Growth Factor Antibody Ficlatuzumab in a Mouse Brain Orthotopic Glioma Model Evaluated by Bioluminescence, PET, and MRI

PubMed Central

Mittra, Erik S.; Fan-Minogue, Hua; Lin, Frank I.; Karamchandani, Jason; Sriram, Venkataraman; Han, May; Gambhir, Sanjiv S.

2016-01-01

Purpose Ficlatuzumab is a novel therapeutic agent targeting the hepatocyte growth factor (HGF)/c-MET pathway. We summarize extensive preclinical work using this agent in a mouse brain orthotopic model of glioblastoma. Experimental Design Sequential experiments were done using eight- to nine-week-old nude mice injected with 3 × 105 U87 MG (glioblastoma) cells into the brain. Evaluation of ficlatuzumab dose response for this brain tumor model and comparison of its response to ficlatuzumab and to temozolamide were conducted first. Subsequently, various small-animal imaging modalities, including bioluminescence imaging (BLI), positron emission tomography (PET), and MRI, were used with a U87 MG-Luc 2 stable cell line, with and without the use of ficlatuzumab, to evaluate the ability to non-invasively assess tumor growth and response to therapy. ANOVA was conducted to evaluate for significant differences in the response. Results There was a survival benefit with ficlatuzumab alone or in combination with temozolamide. BLI was more sensitive than PET in detecting tumor cells. Fluoro-D-thymidine (FLT) PET provided a better signal-to-background ratio than 2[18F]fluoro-2-deoxy-D-glucose (FDG) PET. In addition, both BLI and FLT PET showed significant changes over time in the control group as well as with response to therapy. MRI does not disclose any time-dependent change. Also, the MRI results showed a temporal delay in comparison to the BLI and FLT PET findings, showing similar results one drug cycle later. Conclusions Targeting the HGF/c-MET pathway with the novel agent ficlatuzumab appears promising for the treatment of glioblastoma. Various clinically applicable imaging modalities including FLT, PET, and MRI provide reliable ways of assessing tumor growth and response to therapy. Given the clinical applicability of these findings, future studies on patients with glioblastoma may be appropriate. PMID:23983258

Classifying magnetic resonance image modalities with convolutional neural networks

NASA Astrophysics Data System (ADS)

Remedios, Samuel; Pham, Dzung L.; Butman, John A.; Roy, Snehashis

2018-02-01

Magnetic Resonance (MR) imaging allows the acquisition of images with different contrast properties depending on the acquisition protocol and the magnetic properties of tissues. Many MR brain image processing techniques, such as tissue segmentation, require multiple MR contrasts as inputs, and each contrast is treated differently. Thus it is advantageous to automate the identification of image contrasts for various purposes, such as facilitating image processing pipelines, and managing and maintaining large databases via content-based image retrieval (CBIR). Most automated CBIR techniques focus on a two-step process: extracting features from data and classifying the image based on these features. We present a novel 3D deep convolutional neural network (CNN)- based method for MR image contrast classification. The proposed CNN automatically identifies the MR contrast of an input brain image volume. Specifically, we explored three classification problems: (1) identify T1-weighted (T1-w), T2-weighted (T2-w), and fluid-attenuated inversion recovery (FLAIR) contrasts, (2) identify pre vs postcontrast T1, (3) identify pre vs post-contrast FLAIR. A total of 3418 image volumes acquired from multiple sites and multiple scanners were used. To evaluate each task, the proposed model was trained on 2137 images and tested on the remaining 1281 images. Results showed that image volumes were correctly classified with 97.57% accuracy.

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.

Patch Based Synthesis of Whole Head MR Images: Application to EPI Distortion Correction.

PubMed

Roy, Snehashis; Chou, Yi-Yu; Jog, Amod; Butman, John A; Pham, Dzung L

2016-10-01

Different magnetic resonance imaging pulse sequences are used to generate image contrasts based on physical properties of tissues, which provide different and often complementary information about them. Therefore multiple image contrasts are useful for multimodal analysis of medical images. Often, medical image processing algorithms are optimized for particular image contrasts. If a desirable contrast is unavailable, contrast synthesis (or modality synthesis) methods try to "synthesize" the unavailable constrasts from the available ones. Most of the recent image synthesis methods generate synthetic brain images, while whole head magnetic resonance (MR) images can also be useful for many applications. We propose an atlas based patch matching algorithm to synthesize T 2 -w whole head (including brain, skull, eyes etc) images from T 1 -w images for the purpose of distortion correction of diffusion weighted MR images. The geometric distortion in diffusion MR images due to in-homogeneous B 0 magnetic field are often corrected by non-linearly registering the corresponding b = 0 image with zero diffusion gradient to an undistorted T 2 -w image. We show that our synthetic T 2 -w images can be used as a template in absence of a real T 2 -w image. Our patch based method requires multiple atlases with T 1 and T 2 to be registeLowRes to a given target T 1 . Then for every patch on the target, multiple similar looking matching patches are found on the atlas T 1 images and corresponding patches on the atlas T 2 images are combined to generate a synthetic T 2 of the target. We experimented on image data obtained from 44 patients with traumatic brain injury (TBI), and showed that our synthesized T 2 images produce more accurate distortion correction than a state-of-the-art registration based image synthesis method.

Semiautomatic tumor segmentation with multimodal images in a conditional random field framework.

PubMed

Hu, Yu-Chi; Grossberg, Michael; Mageras, Gikas

2016-04-01

Volumetric medical images of a single subject can be acquired using different imaging modalities, such as computed tomography, magnetic resonance imaging (MRI), and positron emission tomography. In this work, we present a semiautomatic segmentation algorithm that can leverage the synergies between different image modalities while integrating interactive human guidance. The algorithm provides a statistical segmentation framework partly automating the segmentation task while still maintaining critical human oversight. The statistical models presented are trained interactively using simple brush strokes to indicate tumor and nontumor tissues and using intermediate results within a patient's image study. To accomplish the segmentation, we construct the energy function in the conditional random field (CRF) framework. For each slice, the energy function is set using the estimated probabilities from both user brush stroke data and prior approved segmented slices within a patient study. The progressive segmentation is obtained using a graph-cut-based minimization. Although no similar semiautomated algorithm is currently available, we evaluated our method with an MRI data set from Medical Image Computing and Computer Assisted Intervention Society multimodal brain segmentation challenge (BRATS 2012 and 2013) against a similar fully automatic method based on CRF and a semiautomatic method based on grow-cut, and our method shows superior performance.

TheHiveDB image data management and analysis framework.

PubMed

Muehlboeck, J-Sebastian; Westman, Eric; Simmons, Andrew

2014-01-06

The hive database system (theHiveDB) is a web-based brain imaging database, collaboration, and activity system which has been designed as an imaging workflow management system capable of handling cross-sectional and longitudinal multi-center studies. It can be used to organize and integrate existing data from heterogeneous projects as well as data from ongoing studies. It has been conceived to guide and assist the researcher throughout the entire research process, integrating all relevant types of data across modalities (e.g., brain imaging, clinical, and genetic data). TheHiveDB is a modern activity and resource management system capable of scheduling image processing on both private compute resources and the cloud. The activity component supports common image archival and management tasks as well as established pipeline processing (e.g., Freesurfer for extraction of scalar measures from magnetic resonance images). Furthermore, via theHiveDB activity system algorithm developers may grant access to virtual machines hosting versioned releases of their tools to collaborators and the imaging community. The application of theHiveDB is illustrated with a brief use case based on organizing, processing, and analyzing data from the publically available Alzheimer Disease Neuroimaging Initiative.

TheHiveDB image data management and analysis framework

PubMed Central

Muehlboeck, J-Sebastian; Westman, Eric; Simmons, Andrew

2014-01-01

The hive database system (theHiveDB) is a web-based brain imaging database, collaboration, and activity system which has been designed as an imaging workflow management system capable of handling cross-sectional and longitudinal multi-center studies. It can be used to organize and integrate existing data from heterogeneous projects as well as data from ongoing studies. It has been conceived to guide and assist the researcher throughout the entire research process, integrating all relevant types of data across modalities (e.g., brain imaging, clinical, and genetic data). TheHiveDB is a modern activity and resource management system capable of scheduling image processing on both private compute resources and the cloud. The activity component supports common image archival and management tasks as well as established pipeline processing (e.g., Freesurfer for extraction of scalar measures from magnetic resonance images). Furthermore, via theHiveDB activity system algorithm developers may grant access to virtual machines hosting versioned releases of their tools to collaborators and the imaging community. The application of theHiveDB is illustrated with a brief use case based on organizing, processing, and analyzing data from the publically available Alzheimer Disease Neuroimaging Initiative. PMID:24432000

Speech processing asymmetry revealed by dichotic listening and functional brain imaging.

PubMed

Hugdahl, Kenneth; Westerhausen, René

2016-12-01

In this article, we review research in our laboratory from the last 25 to 30 years on the neuronal basis for laterality of speech perception focusing on the upper, posterior parts of the temporal lobes, and its functional and structural connections to other brain regions. We review both behavioral and brain imaging data, with a focus on dichotic listening experiments, and using a variety of imaging modalities. The data have come in most parts from healthy individuals and from studies on normally functioning brain, although we also review a few selected clinical examples. We first review and discuss the structural model for the explanation of the right-ear advantage (REA) and left hemisphere asymmetry for auditory language processing. A common theme across many studies have been our interest in the interaction between bottom-up, stimulus-driven, and top-down, instruction-driven, aspects of hemispheric asymmetry, and how perceptual factors interact with cognitive factors to shape asymmetry of auditory language information processing. In summary, our research have shown laterality for the initial processing of consonant-vowel syllables, first observed as a behavioral REA when subjects are required to report which syllable of a dichotic syllable-pair they perceive. In subsequent work we have corroborated the REA with brain imaging, and have shown that the REA is modulated through both bottom-up manipulations of stimulus properties, like sound intensity, and top-down manipulations of cognitive properties, like attention focus. Copyright © 2015 Elsevier Ltd. All rights reserved.

In Vivo Imaging of Trypanosome-Brain Interactions and Development of a Rapid Screening Test for Drugs against CNS Stage Trypanosomiasis

PubMed Central

Myburgh, Elmarie; Coles, Jonathan A.; Ritchie, Ryan; Kennedy, Peter G. E.; McLatchie, Alex P.; Rodgers, Jean; Taylor, Martin C.; Barrett, Michael P.; Brewer, James M.; Mottram, Jeremy C.

2013-01-01

Human African trypanosomiasis (HAT) manifests in two stages of disease: firstly, haemolymphatic, and secondly, an encephalitic phase involving the central nervous system (CNS). New drugs to treat the second-stage disease are urgently needed, yet testing of novel drug candidates is a slow process because the established animal model relies on detecting parasitemia in the blood as late as 180 days after treatment. To expedite compound screening, we have modified the GVR35 strain of Trypanosoma brucei brucei to express luciferase, and have monitored parasite distribution in infected mice following treatment with trypanocidal compounds using serial, non-invasive, bioluminescence imaging. Parasites were detected in the brains of infected mice following treatment with diminazene, a drug which cures stage 1 but not stage 2 disease. Intravital multi-photon microscopy revealed that trypanosomes enter the brain meninges as early as day 5 post-infection but can be killed by diminazene, whereas those that cross the blood-brain barrier and enter the parenchyma by day 21 survived treatment and later caused bloodstream recrudescence. In contrast, all bioluminescent parasites were permanently eliminated by treatment with melarsoprol and DB829, compounds known to cure stage 2 disease. We show that this use of imaging reduces by two thirds the time taken to assess drug efficacy and provides a dual-modal imaging platform for monitoring trypanosome infection in different areas of the brain. PMID:23991236

Auditory and visual connectivity gradients in frontoparietal cortex

PubMed Central

Hellyer, Peter J.; Wise, Richard J. S.; Leech, Robert

2016-01-01

Abstract A frontoparietal network of brain regions is often implicated in both auditory and visual information processing. Although it is possible that the same set of multimodal regions subserves both modalities, there is increasing evidence that there is a differentiation of sensory function within frontoparietal cortex. Magnetic resonance imaging (MRI) in humans was used to investigate whether different frontoparietal regions showed intrinsic biases in connectivity with visual or auditory modalities. Structural connectivity was assessed with diffusion tractography and functional connectivity was tested using functional MRI. A dorsal–ventral gradient of function was observed, where connectivity with visual cortex dominates dorsal frontal and parietal connections, while connectivity with auditory cortex dominates ventral frontal and parietal regions. A gradient was also observed along the posterior–anterior axis, although in opposite directions in prefrontal and parietal cortices. The results suggest that the location of neural activity within frontoparietal cortex may be influenced by these intrinsic biases toward visual and auditory processing. Thus, the location of activity in frontoparietal cortex may be influenced as much by stimulus modality as the cognitive demands of a task. It was concluded that stimulus modality was spatially encoded throughout frontal and parietal cortices, and was speculated that such an arrangement allows for top–down modulation of modality‐specific information to occur within higher‐order cortex. This could provide a potentially faster and more efficient pathway by which top–down selection between sensory modalities could occur, by constraining modulations to within frontal and parietal regions, rather than long‐range connections to sensory cortices. Hum Brain Mapp 38:255–270, 2017. © 2016 Wiley Periodicals, Inc. PMID:27571304

Hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic imaging

NASA Astrophysics Data System (ADS)

Chen, Zhenyue; Deán-Ben, Xosé Luís.; Gottschalk, Sven; Razansky, Daniel

2018-02-01

Fluorescence imaging is widely employed in all fields of cell and molecular biology due to its high sensitivity, high contrast and ease of implementation. However, the low spatial resolution and lack of depth information, especially in strongly-scattering samples, restrict its applicability for deep-tissue imaging applications. On the other hand, optoacoustic imaging is known to deliver a unique set of capabilities such as high spatial and temporal resolution in three dimensions, deep penetration and spectrally-enriched imaging contrast. Since fluorescent substances can generate contrast in both modalities, simultaneous fluorescence and optoacoustic readings can provide new capabilities for functional and molecular imaging of living organisms. Optoacoustic images can further serve as valuable anatomical references based on endogenous hemoglobin contrast. Herein, we propose a hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic tomography, both operating in reflection mode, which synergistically combines the advantages of stand-alone systems. Validation of the spatial resolution and sensitivity of the system were first carried out in tissue mimicking phantoms while in vivo imaging was further demonstrated by tracking perfusion of an optical contrast agent in a mouse brain in the hybrid imaging mode. Experimental results show that the proposed system effectively exploits the contrast mechanisms of both imaging modalities, making it especially useful for accurate monitoring of fluorescence-based signal dynamics in highly scattering samples.

Fusing DTI and FMRI Data: A Survey of Methods and Applications

PubMed Central

Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

2014-01-01

The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849

Pre-Adult MRI of Brain Cancer and Neurological Injury: Multivariate Analyses

PubMed Central

Levman, Jacob; Takahashi, Emi

2016-01-01

Brain cancer and neurological injuries, such as stroke, are life-threatening conditions for which further research is needed to overcome the many challenges associated with providing optimal patient care. Multivariate analysis (MVA) is a class of pattern recognition technique involving the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of neuroimaging challenges, including identifying variables associated with patient outcomes; understanding an injury’s etiology, development, and progression; creating diagnostic tests; assisting in treatment monitoring; and more. Compared to adults, imaging of the developing brain has attracted less attention from MVA researchers, however, remarkable MVA growth has occurred in recent years. This paper presents the results of a systematic review of the literature focusing on MVA technologies applied to brain injury and cancer in neurological fetal, neonatal, and pediatric magnetic resonance imaging (MRI). With a wide variety of MRI modalities providing physiologically meaningful biomarkers and new biomarker measurements constantly under development, MVA techniques hold enormous potential toward combining available measurements toward improving basic research and the creation of technologies that contribute to improving patient care. PMID:27446888

Brain segmentation and the generation of cortical surfaces

NASA Technical Reports Server (NTRS)

Joshi, M.; Cui, J.; Doolittle, K.; Joshi, S.; Van Essen, D.; Wang, L.; Miller, M. I.

1999-01-01

This paper describes methods for white matter segmentation in brain images and the generation of cortical surfaces from the segmentations. We have developed a system that allows a user to start with a brain volume, obtained by modalities such as MRI or cryosection, and constructs a complete digital representation of the cortical surface. The methodology consists of three basic components: local parametric modeling and Bayesian segmentation; surface generation and local quadratic coordinate fitting; and surface editing. Segmentations are computed by parametrically fitting known density functions to the histogram of the image using the expectation maximization algorithm [DLR77]. The parametric fits are obtained locally rather than globally over the whole volume to overcome local variations in gray levels. To represent the boundary of the gray and white matter we use triangulated meshes generated using isosurface generation algorithms [GH95]. A complete system of local parametric quadratic charts [JWM+95] is superimposed on the triangulated graph to facilitate smoothing and geodesic curve tracking. Algorithms for surface editing include extraction of the largest closed surface. Results for several macaque brains are presented comparing automated and hand surface generation. Copyright 1999 Academic Press.

Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study.

PubMed

Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Heute, U; Deuschl, G; Raethjen, J; Muthuraman, Muthuraman

2016-09-01

Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a significantly greater forward than backward information flow between the ROIs. This simultaneous fMRI, fNIRS and EEG study has shown through independent GC analysis of the respective time series that a bi-directional effective connectivity occurs within a cortico-cortical sensorimotor network (SMC, PMC and DLPFC) during finger movement tasks.

Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing.

PubMed

Hsieh, Thomas M; Liu, Yi-Min; Liao, Chun-Chih; Xiao, Furen; Chiang, I-Jen; Wong, Jau-Min

2011-08-26

In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain. The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT) on a pixel level. Overall data were then evaluated using a quantified system. The quantified parameters, including the "percent match" (PM) and "correlation ratio" (CR), suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain.Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related. Results indicated that, even when using only two sets of non-contrasted MR images, the system is a reliable and efficient method of brain-tumor detection. With further development the system demonstrates high potential for practical clinical use.

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.

The Etiology of Cirrhosis is a Strong Determinant of Brain Reserve: A Multi-modal MR Imaging Study

PubMed Central

Ahluwalia, Vishwadeep; Wade, James B; Moeller, F Gerard; White, Melanie B; Unser, Ariel B; Gavis, Edith A; Sterling, Richard K; Stravitz, R Todd; Sanyal, Arun J; Siddiqui, Mohammad S; Puri, Puneet; Luketic, Velimir; Heuman, Douglas M; Fuchs, Michael; Matherly, Scott; Bajaj, Jasmohan S

2015-01-01

Background Poor brain reserve in alcoholic cirrhosis could worsen insight regarding disease severity and increase the patients’ vulnerability towards further deterioration. Aim To analyze brain reserve in abstinent alcoholic (Alc) compared to non-alcoholic (Nalc) cirrhosis patients in the context of hepatic encephalopathy (HE) and evaluate relative change in brain reserve between groups over time and before/after elective TIPS placement. Methods Cross-sectional study 46 Alc and 102 Nalc outpatients with or without HE. Cognitive tests followed by magnetic resonance (MR) imaging including 1-H MR Spectroscopy (MRS), Diffusion tensor (DTI) and T1-weighted imaging. Prospective study MRS on subset of 10 patients before/after TIPS placement. Another subset of 26 patients underwent MRS at least one year apart. Results Cross-sectional study Alc patients were worse on cognitive tests than Nalc. MR results suggest a greater effect of hyperammonemia, brain edema and significantly higher cortical damage in Alc as compared to Nalc patients. Effect of HE status on cognitive tests and brain reserve was more marked in Nalc than in Alc group. TIPS study Nalc patients showed a greater adverse relative change after TIPS compared to Alc group. 1-year follow-up Both groups remained stable between the two visits. However, Alc patients continued to show poor brain reserve than Nalc over time. Conclusions Patients with alcoholic cirrhosis, despite abstinence, have a poor brain reserve while, non-alcoholic cirrhosis patients have a greater potential for brain reserve deterioration after HE and TIPS. Information regarding the brain reserve in cirrhosis could assist medical teams to refine their communication and monitoring strategies for different etiologies. PMID:25939692

Neuroimaging with functional near infrared spectroscopy: From formation to interpretation

NASA Astrophysics Data System (ADS)

Herrera-Vega, Javier; Treviño-Palacios, Carlos G.; Orihuela-Espina, Felipe

2017-09-01

Functional Near Infrared Spectroscopy (fNIRS) is gaining momentum as a functional neuroimaging modality to investigate the cerebral hemodynamics subsequent to neural metabolism. As other neuroimaging modalities, it is neuroscience's tool to understand brain systems functions at behaviour and cognitive levels. To extract useful knowledge from functional neuroimages it is critical to understand the series of transformations applied during the process of the information retrieval and how they bound the interpretation. This process starts with the irradiation of the head tissues with infrared light to obtain the raw neuroimage and proceeds with computational and statistical analysis revealing hidden associations between pixels intensities and neural activity encoded to end up with the explanation of some particular aspect regarding brain function.To comprehend the overall process involved in fNIRS there is extensive literature addressing each individual step separately. This paper overviews the complete transformation sequence through image formation, reconstruction and analysis to provide an insight of the final functional interpretation.

Grapheme-color synesthetes show peculiarities in their emotional brain: cortical and subcortical evidence from VBM analysis of 3D-T1 and DTI data.

PubMed

Melero, Helena; Peña-Melián, Ángel; Ríos-Lago, Marcos; Pajares, Gonzalo; Hernández-Tamames, Juan Antonio; Álvarez-Linera, Juan

2013-06-01

Grapheme-color synesthesia is a neurological phenomenon in which viewing achromatic letters/numbers leads to automatic and involuntary color experiences. In this study, voxel-based morphometry analyses were performed on T1 images and fractional anisotropy measures to examine the whole brain in associator grapheme-color synesthetes. These analyses provide new evidence of variations in emotional areas (both at the cortical and subcortical levels), findings that help understand the emotional component as a relevant aspect of the synesthetic experience. Additionally, this study replicates previous findings in the left intraparietal sulcus and, for the first time, reports the existence of anatomical differences in subcortical gray nuclei of developmental grapheme-color synesthetes, providing a link between acquired and developmental synesthesia. This empirical evidence, which goes beyond modality-specific areas, could lead to a better understanding of grapheme-color synesthesia as well as of other modalities of the phenomenon.

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.

PubMed

Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P; Frank, Lawrence R

2018-04-13

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Synaesthetic colour in the brain: beyond colour areas. A functional magnetic resonance imaging study of synaesthetes and matched controls.

PubMed

van Leeuwen, Tessa M; Petersson, Karl Magnus; Hagoort, Peter

2010-08-10

In synaesthesia, sensations in a particular modality cause additional experiences in a second, unstimulated modality (e.g., letters elicit colour). Understanding how synaesthesia is mediated in the brain can help to understand normal processes of perceptual awareness and multisensory integration. In several neuroimaging studies, enhanced brain activity for grapheme-colour synaesthesia has been found in ventral-occipital areas that are also involved in real colour processing. Our question was whether the neural correlates of synaesthetically induced colour and real colour experience are truly shared. First, in a free viewing functional magnetic resonance imaging (fMRI) experiment, we located main effects of synaesthesia in left superior parietal lobule and in colour related areas. In the left superior parietal lobe, individual differences between synaesthetes (projector-associator distinction) also influenced brain activity, confirming the importance of the left superior parietal lobe for synaesthesia. Next, we applied a repetition suppression paradigm in fMRI, in which a decrease in the BOLD (blood-oxygenated-level-dependent) response is generally observed for repeated stimuli. We hypothesized that synaesthetically induced colours would lead to a reduction in BOLD response for subsequently presented real colours, if the neural correlates were overlapping. We did find BOLD suppression effects induced by synaesthesia, but not within the colour areas. Because synaesthetically induced colours were not able to suppress BOLD effects for real colour, we conclude that the neural correlates of synaesthetic colour experience and real colour experience are not fully shared. We propose that synaesthetic colour experiences are mediated by higher-order visual pathways that lie beyond the scope of classical, ventral-occipital visual areas. Feedback from these areas, in which the left parietal cortex is likely to play an important role, may induce V4 activation and the percept of synaesthetic colour.

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

PubMed

Hong, Keum-Shik; Khan, Muhammad Jawad

2017-01-01

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

Multimodal image analysis of clinical influences on preterm brain development

PubMed Central

Ball, Gareth; Aljabar, Paul; Nongena, Phumza; Kennea, Nigel; Gonzalez‐Cinca, Nuria; Falconer, Shona; Chew, Andrew T.M.; Harper, Nicholas; Wurie, Julia; Rutherford, Mary A.; Edwards, A. David

2017-01-01

Objective Premature birth is associated with numerous complex abnormalities of white and gray matter and a high incidence of long‐term neurocognitive impairment. An integrated understanding of these abnormalities and their association with clinical events is lacking. The aim of this study was to identify specific patterns of abnormal cerebral development and their antenatal and postnatal antecedents. Methods In a prospective cohort of 449 infants (226 male), we performed a multivariate and data‐driven analysis combining multiple imaging modalities. Using canonical correlation analysis, we sought separable multimodal imaging markers associated with specific clinical and environmental factors and correlated to neurodevelopmental outcome at 2 years. Results We found five independent patterns of neuroanatomical variation that related to clinical factors including age, prematurity, sex, intrauterine complications, and postnatal adversity. We also confirmed the association between imaging markers of neuroanatomical abnormality and poor cognitive and motor outcomes at 2 years. Interpretation This data‐driven approach defined novel and clinically relevant imaging markers of cerebral maldevelopment, which offer new insights into the nature of preterm brain injury. Ann Neurol 2017;82:233–246 PMID:28719076

Neuroimaging is a novel tool to understand the impact of environmental chemicals on neurodevelopment.

PubMed

Horton, Megan K; Margolis, Amy E; Tang, Cheuk; Wright, Robert

2014-04-01

The prevalence of childhood neurodevelopmental disorders has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of neurodevelopmental disorders. Very little information is known about the mechanistic processes by which environmental chemicals alter brain development. We review the recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Neuroimaging techniques (volumetric and functional MRI, diffusor tensor imaging, and magnetic resonance spectroscopy) have opened unprecedented access to study the developing human brain. These techniques are noninvasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. MRI is a powerful tool that allows in-vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure.

Brain metastases in women with epithelial ovarian cancer: multimodal treatment including surgery or gamma-knife radiation is associated with prolonged survival.

PubMed

Niu, Xiaoyu; Rajanbabu, Anupama; Delisle, Megan; Peng, Feng; Vijaykumar, Dehannathuparambil K; Pavithran, Keechilattu; Feng, Yukuan; Lau, Susie; Gotlieb, Walter H; Press, Joshua Z

2013-09-01

To explore the impact of treatment modality on survival in patients with brain metastases from epithelial ovarian cancer. We conducted a retrospective review of cases of ovarian cancer with brain metastases treated at institutions in three countries (Canada, China, and India) and conducted a search for studies regarding brain metastases in ovarian cancer reporting survival related to treatment modality. Survival was analyzed according to treatment regimens involving (1) some form of surgical excision or gamma-knife radiation with or without other modalities, (2) other modalities without surgery or gamma-knife radiation, or (3) palliation only. Twelve patients (mean age 56 years) with detailed treatment/outcome data were included; five were from China, four from Canada, and three from India. Median time from diagnosis of ovarian cancer to brain metastasis was 19 months (range 10 to 37 months), and overall median survival time from diagnosis of ovarian cancer was 38 months (13 to 82 months). Median survival time from diagnosis of brain metastasis was 17 months (1 to 45 months). Among patients who had multimodal treatment including gamma-knife radiotherapy or surgical excision, the median survival time after the identification of brain metastasis was 25.6 months, compared with 6.0 months in patients whose treatment did not include this type of focused localized modality (P = 0.006). Analysis of 20 studies also indicated that use of gamma-knife radiotherapy and excisional surgery in multi-modal treatment resulted in improved median survival interval (25 months vs. 6.0 months, P < 0.001). In the subset of patients with brain metastases from ovarian cancer, prolonged survival may result from use of multidisciplinary therapy, particularly if metastases are amenable to localized treatments such as gamma-knife radiotherapy and surgical excision.

Detection of white matter lesion regions in MRI using SLIC0 and convolutional neural network.

PubMed

Diniz, Pedro Henrique Bandeira; Valente, Thales Levi Azevedo; Diniz, João Otávio Bandeira; Silva, Aristófanes Corrêa; Gattass, Marcelo; Ventura, Nina; Muniz, Bernardo Carvalho; Gasparetto, Emerson Leandro

2018-04-19

White matter lesions are non-static brain lesions that have a prevalence rate up to 98% in the elderly population. Because they may be associated with several brain diseases, it is important that they are detected as soon as possible. Magnetic Resonance Imaging (MRI) provides three-dimensional data with the possibility to detect and emphasize contrast differences in soft tissues, providing rich information about the human soft tissue anatomy. However, the amount of data provided for these images is far too much for manual analysis/interpretation, representing a difficult and time-consuming task for specialists. This work presents a computational methodology capable of detecting regions of white matter lesions of the brain in MRI of FLAIR modality. The techniques highlighted in this methodology are SLIC0 clustering for candidate segmentation and convolutional neural networks for candidate classification. The methodology proposed here consists of four steps: (1) images acquisition, (2) images preprocessing, (3) candidates segmentation and (4) candidates classification. The methodology was applied on 91 magnetic resonance images provided by DASA, and achieved an accuracy of 98.73%, specificity of 98.77% and sensitivity of 78.79% with 0.005 of false positives, without any false positives reduction technique, in detection of white matter lesion regions. It is demonstrated the feasibility of the analysis of brain MRI using SLIC0 and convolutional neural network techniques to achieve success in detection of white matter lesions regions. Copyright © 2018. Published by Elsevier B.V.

Pediatric Traumatic Brain Injury and Autism: Elucidating Shared Mechanisms

PubMed Central

Singh, Rahul; Nguyen, Linda; Motwani, Kartik; Swatek, Michelle

2016-01-01

Pediatric traumatic brain injury (TBI) and autism spectrum disorder (ASD) are two serious conditions that affect youth. Recent data, both preclinical and clinical, show that pediatric TBI and ASD share not only similar symptoms but also some of the same biologic mechanisms that cause these symptoms. Prominent symptoms for both disorders include gastrointestinal problems, learning difficulties, seizures, and sensory processing disruption. In this review, we highlight some of these shared mechanisms in order to discuss potential treatment options that might be applied for each condition. We discuss potential therapeutic and pharmacologic options as well as potential novel drug targets. Furthermore, we highlight advances in understanding of brain circuitry that is being propelled by improved imaging modalities. Going forward, advanced imaging will help in diagnosis and treatment planning strategies for pediatric patients. Lessons from each field can be applied to design better and more rigorous trials that can be used to improve guidelines for pediatric patients suffering from TBI or ASD. PMID:28074078

Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study.

PubMed

Cherubini, Andrea; Caligiuri, Maria Eugenia; Péran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2015-01-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.

The role of 99Tcm-HMPAO brain SPET in paediatric traumatic brain injury.

PubMed

Goshen, E; Zwas, S T; Shahar, E; Tadmor, R

1996-05-01

Twenty-eight paediatric patients suffering from chronic sequelae of traumatic brain injury (TBI) were examined by EEG, radionuclide imaging with 99Tcm-hexamethylpropyleneamine oxime (99Tcm-HMPAO), computed tomography (CT) and, when available, magnetic resonance imaging (MRI), the results of which were evaluated retrospectively. Our findings indicate that neuro-SPET (single photon emission tomography) with 99Tcm-HMPAO is more sensitive than morphological or electrophysiological tests in detecting functional lesions. In our group, 15 of 32 CT scans were normal, compared with 3 of 35 SPET studies. SPET identified approximately 2.5 times more lesions than CT (86 vs 34). SPET was found to be particularly sensitive in detecting organic abnormalities in the basal ganglia and cerebellar regions, with a 3.6:1 detection rate in the basal ganglia and a 5:1 detection rate in the cerebellum compared with CT. In conclusion, neuro-SPET appears to be very useful when evaluating paediatric post-TBI patients in whom other modalities are not successful.

Accuracy of Intraoperative Computed Tomography during Deep Brain Stimulation Procedures: Comparison with Postoperative Magnetic Resonance Imaging

PubMed Central

Bot, Maarten; van den Munckhof, Pepijn; Bakay, Roy; Stebbins, Glenn; Verhagen Metman, Leo

2017-01-01

Objective To determine the accuracy of intraoperative computed tomography (iCT) in localizing deep brain stimulation (DBS) electrodes by comparing this modality with postoperative magnetic resonance imaging (MRI). Background Optimal lead placement is a critical factor for the outcome of DBS procedures and preferably confirmed during surgery. iCT offers 3-dimensional verification of both microelectrode and lead location during DBS surgery. However, accurate electrode representation on iCT has not been extensively studied. Methods DBS surgery was performed using the Leksell stereotactic G frame. Stereotactic coordinates of 52 DBS leads were determined on both iCT and postoperative MRI and compared with intended final target coordinates. The resulting absolute differences in X (medial-lateral), Y (anterior-posterior), and Z (dorsal-ventral) coordinates (ΔX, ΔY, and ΔZ) for both modalities were then used to calculate the euclidean distance. Results Euclidean distances were 2.7 ± 1.1 and 2.5 ± 1.2 mm for MRI and iCT, respectively (p = 0.2). Conclusion Postoperative MRI and iCT show equivalent DBS lead representation. Intraoperative localization of both microelectrode and DBS lead in stereotactic space enables direct adjustments. Verification of lead placement with postoperative MRI, considered to be the gold standard, is unnecessary. PMID:28601874

Accuracy of Intraoperative Computed Tomography during Deep Brain Stimulation Procedures: Comparison with Postoperative Magnetic Resonance Imaging.

PubMed

Bot, Maarten; van den Munckhof, Pepijn; Bakay, Roy; Stebbins, Glenn; Verhagen Metman, Leo

2017-01-01

To determine the accuracy of intraoperative computed tomography (iCT) in localizing deep brain stimulation (DBS) electrodes by comparing this modality with postoperative magnetic resonance imaging (MRI). Optimal lead placement is a critical factor for the outcome of DBS procedures and preferably confirmed during surgery. iCT offers 3-dimensional verification of both microelectrode and lead location during DBS surgery. However, accurate electrode representation on iCT has not been extensively studied. DBS surgery was performed using the Leksell stereotactic G frame. Stereotactic coordinates of 52 DBS leads were determined on both iCT and postoperative MRI and compared with intended final target coordinates. The resulting absolute differences in X (medial-lateral), Y (anterior-posterior), and Z (dorsal-ventral) coordinates (ΔX, ΔY, and ΔZ) for both modalities were then used to calculate the euclidean distance. Euclidean distances were 2.7 ± 1.1 and 2.5 ± 1.2 mm for MRI and iCT, respectively (p = 0.2). Postoperative MRI and iCT show equivalent DBS lead representation. Intraoperative localization of both microelectrode and DBS lead in stereotactic space enables direct adjustments. Verification of lead placement with postoperative MRI, considered to be the gold standard, is unnecessary. © 2017 The Author(s) Published by S. Karger AG, Basel.

Photoacoustic imaging of living mouse brain vasculature using hollow gold nanospheres.

PubMed

Lu, Wei; Huang, Qian; Ku, Geng; Wen, Xiaoxia; Zhou, Min; Guzatov, Dmitry; Brecht, Peter; Su, Richard; Oraevsky, Alexander; Wang, Lihong V; Li, Chun

2010-03-01

Photoacoustic tomography (PAT) also referred to as optoacoustic tomography (OAT) is a hybrid imaging modality that employs nonionizing optical radiation and ultrasonic detection. Here, we describe the application of a new class of optical contrast agents based on mesoscopic hollow gold nanospheres (HAuNS) to PAT. HAuNS are approximately 40 nm in diameter with a hollow interior and consist of a thin gold wall. They display strong resonance absorption tuned to the near-infrared (NIR) range, with an absorption peak at 800 nm, whose photoacoustic efficiency is significantly greater than that of blood. Following surface conjugation with thiolated poly(ethylene glycol), the pegylated HAuNS (PEG-HAuNS) had distribution and elimination half-lives of 1.38 +/- 0.38 and 71.82 +/- 30.46 h, respectively. Compared with PAT images based on the intrinsic optical contrast in nude mice, the PAT images acquired within 2 h after intravenous administration of PEG-HAuNS showed the brain vasculature with greater clarity and detail. The image depicted brain blood vessels as small as approximately 100 mum in diameter using PEG-HAuNS as contrast agents. Preliminary results showed no acute toxicity to the liver, spleen, or kidneys in mice following a single imaging dose of PEG-HAuNS. Our results indicate that PEG-HAuNS are promising contrast agents for PAT, with high spatial resolution and enhanced sensitivity. Copyright 2009 Elsevier Ltd. All rights reserved.

Sensory perception: lessons from synesthesia: using synesthesia to inform the understanding of sensory perception.

PubMed

Harvey, Joshua Paul

2013-06-01

Synesthesia, the conscious, idiosyncratic, repeatable, and involuntary sensation of one sensory modality in response to another, is a condition that has puzzled both researchers and philosophers for centuries. Much time has been spent proving the condition's existence as well as investigating its etiology, but what can be learned from synesthesia remains a poorly discussed topic. Here, synaesthesia is presented as a possible answer rather than a question to the current gaps in our understanding of sensory perception. By first appreciating the similarities between normal sensory perception and synesthesia, one can use what is known about synaesthesia, from behavioral and imaging studies, to inform our understanding of "normal" sensory perception. In particular, in considering synesthesia, one can better understand how and where the different sensory modalities interact in the brain, how different sensory modalities can interact without confusion - the binding problem - as well as how sensory perception develops.

Brain serotonergic circuitries

PubMed Central

Charnay, Yves; Leger, Lucienne

2010-01-01

Brain serotonergic circuitries interact with other neurotransmitter systems on a multitude of different molecular levels. In humans, as in other mammalian species, serotonin (5-HT) plays a modulatory role in almost every physiological function. Furthermore, serotonergic dysfunction is thought to be implicated in several psychiatric and neurodegenerative disorders. We describe the neuroanatomy and neurochemistry of brain serotonergic circuitries. The contribution of emergent in vivo imaging methods to the regional localization of binding site receptors and certain aspects of their functional connectivity in correlation to behavior is also discussed. 5-HT cell bodies, mainly localized in the raphe nuclei, send axons to almost every brain region. It is argued that the specificity of the local chemocommunication between 5-HT and other neuronal elements mainly depends on mechanisms regulating the extracellular concentration of 5-HT, the diversity of high-affinity membrane receptors, and their specific transduction modalities. PMID:21319493

Imaging Characteristics of Children with Auditory Neuropathy Spectrum Disorder

PubMed Central

Roche, Joseph P.; Huang, Benjamin Y.; Castillo, Mauricio; Bassim, Marc K.; Adunka, Oliver F.; Buchman, Craig A.

2013-01-01

Objective To identify and define the imaging characteristics of children with auditory neuropathy spectrum disorder (ANSD). Design Retrospective medical records review and analysis of both temporal bone computed tomography (CT) and magnetic resonance images (MRI) in from children with the diagnosis of ANSD. Setting Tertiary referral center. Patients 118 children with the electrophysiological characteristics of ANSD with available imaging studies for review. Interventions Two neuroradiologists and a neurotologist reviewed each study and consensus descriptions were established. Main outcome measures The type and number of imaging findings were tabulated. Results Sixty-eight (64%) MRIs revealed at least one imaging abnormality while selective use of CT identified 23 (55%) with anomalies. The most prevalent MRI findings included cochlear nerve deficiency (n=51; 28% of 183 nerves), brain abnormalities (n=42; 40% of 106 brains) and prominent temporal horns (n=33, 16% of 212 temporal lobes). The most prevalent CT finding from selective use of CT was cochlear dysplasia (n=13; 31%). Conclusions MRI will identify many abnormalities in children with ANSD that are not readily discernable on CT. Specifically, both developmental and acquired abnormalities of the brain, posterior cranial fossa, and cochlear nerves are not uncommonly seen in this patient population. Inner ear anomalies are well delineated using either imaging modality. Since many of the central nervous system findings identified in this study using MRI can alter the treatment and prognosis for these children, we believe that MRI should be the initial imaging study of choice for children with ANSD. PMID:20593543

Fast and robust brain tumor segmentation using level set method with multiple image information.

PubMed

Lok, Ka Hei; Shi, Lin; Zhu, Xianlun; Wang, Defeng

2017-01-01

Brain tumor segmentation is a challenging task for its variation in intensity. The phenomenon is caused by the inhomogeneous content of tumor tissue and the choice of imaging modality. In 2010 Zhang developed the Selective Binary Gaussian Filtering Regularizing Level Set (SBGFRLS) model that combined the merits of edge-based and region-based segmentation. To improve the SBGFRLS method by modifying the singed pressure force (SPF) term with multiple image information and demonstrate effectiveness of proposed method on clinical images. In original SBGFRLS model, the contour evolution direction mainly depends on the SPF. By introducing a directional term in SPF, the metric could control the evolution direction. The SPF is altered by statistic values enclosed by the contour. This concept can be extended to jointly incorporate multiple image information. The new SPF term is expected to bring a solution for blur edge problem in brain tumor segmentation. The proposed method is validated with clinical images including pre- and post-contrast magnetic resonance images. The accuracy and robustness is compared with sensitivity, specificity, DICE similarity coefficient and Jaccard similarity index. Experimental results show improvement, in particular the increase of sensitivity at the same specificity, in segmenting all types of tumors except for the diffused tumor. The novel brain tumor segmentation method is clinical-oriented with fast, robust and accurate implementation and a minimal user interaction. The method effectively segmented homogeneously enhanced, non-enhanced, heterogeneously-enhanced, and ring-enhanced tumor under MR imaging. Though the method is limited by identifying edema and diffuse tumor, several possible solutions are suggested to turn the curve evolution into a fully functional clinical diagnosis tool.

WE-B-210-02: The Advent of Ultrafast Imaging in Biomedical Ultrasound

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

Tanter, M.

In the last fifteen years, the introduction of plane or diverging wave transmissions rather than line by line scanning focused beams has broken the conventional barriers of ultrasound imaging. By using such large field of view transmissions, the frame rate reaches the theoretical limit of physics dictated by the ultrasound speed and an ultrasonic map can be provided typically in tens of micro-seconds (several thousands of frames per second). Interestingly, this leap in frame rate is not only a technological breakthrough but it permits the advent of completely new ultrasound imaging modes, including shear wave elastography, electromechanical wave imaging, ultrafastmore » doppler, ultrafast contrast imaging, and even functional ultrasound imaging of brain activity (fUltrasound) introducing Ultrasound as an emerging full-fledged neuroimaging modality. At ultrafast frame rates, it becomes possible to track in real time the transient vibrations – known as shear waves – propagating through organs. Such “human body seismology” provides quantitative maps of local tissue stiffness whose added value for diagnosis has been recently demonstrated in many fields of radiology (breast, prostate and liver cancer, cardiovascular imaging, …). Today, Supersonic Imagine company is commercializing the first clinical ultrafast ultrasound scanner, Aixplorer with real time Shear Wave Elastography. This is the first example of an ultrafast Ultrasound approach surpassing the research phase and now widely spread in the clinical medical ultrasound community with an installed base of more than 1000 Aixplorer systems in 54 countries worldwide. For blood flow imaging, ultrafast Doppler permits high-precision characterization of complex vascular and cardiac flows. It also gives ultrasound the ability to detect very subtle blood flow in very small vessels. In the brain, such ultrasensitive Doppler paves the way for fUltrasound (functional ultrasound imaging) of brain activity with unprecedented spatial and temporal resolution compared to fMRI. Combined with contrast agents, our group demonstrated that Ultrafast Ultrasound Localization could provide a first in vivo and non invasive imaging modality at microscopic scales deep into organs. Many of these ultrafast modes should lead to major improvements in ultrasound screening, diagnosis, and therapeutic monitoring. Learning Objectives: Achieve familiarity with recent advances in ultrafast ultrasound imaging technology. Develop an understanding of potential applications of ultrafast ultrasound imaging for diagnosis and therapeutic monitoring. Dr. Tanter is a co-founder of Supersonic Imagine,a French company positioned in the field of medical ultrasound imaging and therapy.« less

Magnetic Resonance Imaging in Aneurysmal Subarachnoid Hemorrhage: Current Evidence and Future Directions.

PubMed

Nelson, Sarah E; Sair, Haris I; Stevens, Robert D

2018-04-09

Aneurysmal subarachnoid hemorrhage (aSAH) is associated with an unacceptably high mortality and chronic disability in survivors, underscoring a need to validate new approaches for treatment and prognosis. The use of advanced imaging, magnetic resonance imaging (MRI) in particular, could help address this gap given its versatile capacity to quantitatively evaluate and map changes in brain anatomy, physiology and functional activation. Yet there is uncertainty about the real value of brain MRI in the clinical setting of aSAH. In this review, we discuss current and emerging MRI research in aSAH. PubMed was searched from inception to June 2017, and additional studies were then chosen on the basis of relevance to the topics covered in this review. Available studies suggest that brain MRI is a feasible, safe, and valuable testing modality. MRI detects brain abnormalities associated with neurologic examination, outcomes, and aneurysm treatment and thus has the potential to increase knowledge of aSAH pathophysiology as well as to guide management and outcome prediction. Newer pulse sequences have the potential to reveal structural and physiological changes that could also improve management of aSAH. Research is needed to confirm the value of MRI-based biomarkers in clinical practice and as endpoints in clinical trials, with the goal of improving outcome for patients with aSAH.

Risk factor analysis of new brain lesions associated with carotid endarterectmy.

PubMed

Lee, Jae Hoon; Suh, Bo Yang

2014-01-01

Carotid endarterectomy (CEA) is the standard treatment for carotid artery stenosis. New brain ischemia is a major concern associated with CEA and diffusion weighted imaging (DWI) is a good imaging modality for detecting early ischemic brain lesions. We aimed to investigate the surgical complications and identify the potential risk factors for the incidence of new brain lesions (NBL) on DWI after CEA. From January 2006 to November 2011, 94 patients who had been studied by magnetic resonance imaging including DWI within 1 week after CEA were included in this study. Data were retrospectively investigated by review of vascular registry protocol. Seven clinical variables and three procedural variables were analyzed as risk factors for NBL after CEA. The incidence of periprocedural NBL on DWI was 27.7%. There were no fatal complications, such as ipsilateral disabling stroke, myocardial infarction or mortality. A significantly higher incidence of NBL was found in ulcer positive patients as opposed to ulcer negative patients (P = 0.029). The incidence of NBL after operation was significantly higher in patients treated with conventional technique than with eversion technique (P = 0.042). Our data shows CEA has acceptable periprocedural complication rates and the existence of ulcerative plaque and conventional technique of endarterectomy are high risk factors for NBL development after CEA.

Validating new diagnostic imaging criteria for primary progressive aphasia via anatomical likelihood estimation meta-analyses.

PubMed

Bisenius, S; Neumann, J; Schroeter, M L

2016-04-01

Recently, diagnostic clinical and imaging criteria for primary progressive aphasia (PPA) have been revised by an international consortium (Gorno-Tempini et al. Neurology 2011;76:1006-14). The aim of this study was to validate the specificity of the new imaging criteria and investigate whether different imaging modalities [magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET)] require different diagnostic subtype-specific imaging criteria. Anatomical likelihood estimation meta-analyses were conducted for PPA subtypes across a large cohort of 396 patients: firstly, across MRI studies for each of the three PPA subtypes followed by conjunction and subtraction analyses to investigate the specificity, and, secondly, by comparing results across MRI vs. FDG-PET studies in semantic dementia and progressive nonfluent aphasia. Semantic dementia showed atrophy in temporal, fusiform, parahippocampal gyri, hippocampus, and amygdala, progressive nonfluent aphasia in left putamen, insula, middle/superior temporal, precentral, and frontal gyri, logopenic progressive aphasia in middle/superior temporal, supramarginal, and dorsal posterior cingulate gyri. Results of the disease-specific meta-analyses across MRI studies were disjunct. Similarly, atrophic and hypometabolic brain networks were regionally dissociated in both semantic dementia and progressive nonfluent aphasia. In conclusion, meta-analyses support the specificity of new diagnostic imaging criteria for PPA and suggest that they should be specified for each imaging modality separately. © 2016 EAN.

Simultaneous trimodal PET-MR-EEG imaging: Do EEG caps generate artefacts in PET images?

PubMed

Rajkumar, Ravichandran; Rota Kops, Elena; Mauler, Jörg; Tellmann, Lutz; Lerche, Christoph; Herzog, Hans; Shah, N Jon; Neuner, Irene

2017-01-01

Trimodal simultaneous acquisition of positron emission tomography (PET), magnetic resonance imaging (MRI), and electroencephalography (EEG) has become feasible due to the development of hybrid PET-MR scanners. To capture the temporal dynamics of neuronal activation on a millisecond-by-millisecond basis, an EEG system is appended to the quantitative high resolution PET-MR imaging modality already established in our institute. One of the major difficulties associated with the development of simultaneous trimodal acquisition is that the components traditionally used in each modality can cause interferences in its counterpart. The mutual interferences of MRI components and PET components on PET and MR images, and the influence of EEG electrodes on functional MRI images have been studied and reported on. Building on this, this study aims to investigate the influence of the EEG cap on the quality and quantification of PET images acquired during simultaneous PET-MR measurements. A preliminary transmission scan study on the ECAT HR+ scanner, using an Iida phantom, showed visible attenuation effect due to the EEG cap. The BrainPET-MR emission images of the Iida phantom with [18F]Fluordeoxyglucose, as well as of human subjects with the EEG cap, did not show significant effects of the EEG cap, even though the applied attenuation correction did not take into account the attenuation of the EEG cap itself.

Impalement brain injury from steel rod causing injury to jugular bulb: case report and review of the literature.

PubMed

Grossbach, Andrew J; Abel, Taylor J; Smietana, Janel; Dahdaleh, Nader; Severson, Meryl A; Hasan, David

2014-01-01

The management of impalement penetrating brain injuries (IPBI) from non-missile objects is extremely challenging, especially when vascular structures are involved. Cerebral angiography is a crucial tool in initial evaluation to assess for vascular injury as standard non-invasive imaging modalities are limited by foreign body artifact, especially for metallic objects. This study reports a case of an IPBI caused by a segment of steel rebar resulting in injury to the left jugular bulb and posterior temporal lobe. It describes the initial presentation, radiology, management and outcome in this patient and reviews the literature of similar injuries.

Review of MR Elastography Applications and Recent Developments

PubMed Central

Glaser, Kevin J.; Manduca, Armando; Ehman, Richard L.

2012-01-01

The technique of MR elastography (MRE) has emerged as a useful modality for quantitatively imaging the mechanical properties of soft tissues in vivo. Recently, MRE has been introduced as a clinical tool for evaluating chronic liver disease, but many other potential applications are being explored. These applications include measuring tissue changes associated with diseases of the liver, breast, brain, heart, and skeletal muscle including both focal lesions (e.g., hepatic, breast, and brain tumors) and diffuse diseases (e.g., fibrosis and multiple sclerosis). The purpose of this review article is to summarize some of the recent developments of MRE and to highlight some emerging applications. PMID:22987755

Graph theory findings in the pathophysiology of temporal lobe epilepsy.

PubMed

Chiang, Sharon; Haneef, Zulfi

2014-07-01

Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Preoperative magnetic resonance and intraoperative ultrasound fusion imaging for real-time neuronavigation in brain tumor surgery.

PubMed

Prada, F; Del Bene, M; Mattei, L; Lodigiani, L; DeBeni, S; Kolev, V; Vetrano, I; Solbiati, L; Sakas, G; DiMeco, F

2015-04-01

Brain shift and tissue deformation during surgery for intracranial lesions are the main actual limitations of neuro-navigation (NN), which currently relies mainly on preoperative imaging. Ultrasound (US), being a real-time imaging modality, is becoming progressively more widespread during neurosurgical procedures, but most neurosurgeons, trained on axial computed tomography (CT) and magnetic resonance imaging (MRI) slices, lack specific US training and have difficulties recognizing anatomic structures with the same confidence as in preoperative imaging. Therefore real-time intraoperative fusion imaging (FI) between preoperative imaging and intraoperative ultrasound (ioUS) for virtual navigation (VN) is highly desirable. We describe our procedure for real-time navigation during surgery for different cerebral lesions. We performed fusion imaging with virtual navigation for patients undergoing surgery for brain lesion removal using an ultrasound-based real-time neuro-navigation system that fuses intraoperative cerebral ultrasound with preoperative MRI and simultaneously displays an MRI slice coplanar to an ioUS image. 58 patients underwent surgery at our institution for intracranial lesion removal with image guidance using a US system equipped with fusion imaging for neuro-navigation. In all cases the initial (external) registration error obtained by the corresponding anatomical landmark procedure was below 2 mm and the craniotomy was correctly placed. The transdural window gave satisfactory US image quality and the lesion was always detectable and measurable on both axes. Brain shift/deformation correction has been successfully employed in 42 cases to restore the co-registration during surgery. The accuracy of ioUS/MRI fusion/overlapping was confirmed intraoperatively under direct visualization of anatomic landmarks and the error was < 3 mm in all cases (100 %). Neuro-navigation using intraoperative US integrated with preoperative MRI is reliable, accurate and user-friendly. Moreover, the adjustments are very helpful in correcting brain shift and tissue distortion. This integrated system allows true real-time feedback during surgery and is less expensive and time-consuming than other intraoperative imaging techniques, offering high precision and orientation. © Georg Thieme Verlag KG Stuttgart · New York.

Listening to membrane potential: photoacoustic voltage-sensitive dye recording.

PubMed

Zhang, Haichong K; Yan, Ping; Kang, Jeeun; Abou, Diane S; Le, Hanh N D; Jha, Abhinav K; Thorek, Daniel L J; Kang, Jin U; Rahmim, Arman; Wong, Dean F; Boctor, Emad M; Loew, Leslie M

2017-04-01

Voltage-sensitive dyes (VSDs) are designed to monitor membrane potential by detecting fluorescence changes in response to neuronal or muscle electrical activity. However, fluorescence imaging is limited by depth of penetration and high scattering losses, which leads to low sensitivity in vivo systems for external detection. By contrast, photoacoustic (PA) imaging, an emerging modality, is capable of deep tissue, noninvasive imaging by combining near-infrared light excitation and ultrasound detection. Here, we show that voltage-dependent quenching of dye fluorescence leads to a reciprocal enhancement of PA intensity. We synthesized a near-infrared photoacoustic VSD (PA-VSD), whose PA intensity change is sensitive to membrane potential. In the polarized state, this cyanine-based probe enhances PA intensity while decreasing fluorescence output in a lipid vesicle membrane model. A theoretical model accounts for how the experimental PA intensity change depends on fluorescence and absorbance properties of the dye. These results not only demonstrate PA voltage sensing but also emphasize the interplay of both fluorescence and absorbance properties in the design of optimized PA probes. Together, our results demonstrate PA sensing as a potential new modality for recording and external imaging of electrophysiological and neurochemical events in the brain.

Listening to membrane potential: photoacoustic voltage-sensitive dye recording

NASA Astrophysics Data System (ADS)

Zhang, Haichong K.; Yan, Ping; Kang, Jeeun; Abou, Diane S.; Le, Hanh N. D.; Jha, Abhinav K.; Thorek, Daniel L. J.; Kang, Jin U.; Rahmim, Arman; Wong, Dean F.; Boctor, Emad M.; Loew, Leslie M.

2017-04-01

Voltage-sensitive dyes (VSDs) are designed to monitor membrane potential by detecting fluorescence changes in response to neuronal or muscle electrical activity. However, fluorescence imaging is limited by depth of penetration and high scattering losses, which leads to low sensitivity in vivo systems for external detection. By contrast, photoacoustic (PA) imaging, an emerging modality, is capable of deep tissue, noninvasive imaging by combining near-infrared light excitation and ultrasound detection. Here, we show that voltage-dependent quenching of dye fluorescence leads to a reciprocal enhancement of PA intensity. We synthesized a near-infrared photoacoustic VSD (PA-VSD), whose PA intensity change is sensitive to membrane potential. In the polarized state, this cyanine-based probe enhances PA intensity while decreasing fluorescence output in a lipid vesicle membrane model. A theoretical model accounts for how the experimental PA intensity change depends on fluorescence and absorbance properties of the dye. These results not only demonstrate PA voltage sensing but also emphasize the interplay of both fluorescence and absorbance properties in the design of optimized PA probes. Together, our results demonstrate PA sensing as a potential new modality for recording and external imaging of electrophysiological and neurochemical events in the brain.

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities

PubMed Central

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior. PMID:29535614

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities.

PubMed

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior.

Amodal processing in human prefrontal cortex.

PubMed

Tamber-Rosenau, Benjamin J; Dux, Paul E; Tombu, Michael N; Asplund, Christopher L; Marois, René

2013-07-10

Information enters the cortex via modality-specific sensory regions, whereas actions are produced by modality-specific motor regions. Intervening central stages of information processing map sensation to behavior. Humans perform this central processing in a flexible, abstract manner such that sensory information in any modality can lead to response via any motor system. Cognitive theories account for such flexible behavior by positing amodal central information processing (e.g., "central executive," Baddeley and Hitch, 1974; "supervisory attentional system," Norman and Shallice, 1986; "response selection bottleneck," Pashler, 1994). However, the extent to which brain regions embodying central mechanisms of information processing are amodal remains unclear. Here we apply multivariate pattern analysis to functional magnetic resonance imaging (fMRI) data to compare response selection, a cognitive process widely believed to recruit an amodal central resource across sensory and motor modalities. We show that most frontal and parietal cortical areas known to activate across a wide variety of tasks code modality, casting doubt on the notion that these regions embody a central processor devoid of modality representation. Importantly, regions of anterior insula and dorsolateral prefrontal cortex consistently failed to code modality across four experiments. However, these areas code at least one other task dimension, process (instantiated as response selection vs response execution), ensuring that failure to find coding of modality is not driven by insensitivity of multivariate pattern analysis in these regions. We conclude that abstract encoding of information modality is primarily a property of subregions of the prefrontal cortex.

Lactoferrin conjugated iron oxide nanoparticles for targeting brain glioma cells in magnetic particle imaging

NASA Astrophysics Data System (ADS)

Tomitaka, Asahi; Arami, Hamed; Gandhi, Sonu; Krishnan, Kannan M.

2015-10-01

Magnetic Particle Imaging (MPI) is a new real-time imaging modality, which promises high tracer mass sensitivity and spatial resolution directly generated from iron oxide nanoparticles. In this study, monodisperse iron oxide nanoparticles with median core diameters ranging from 14 to 26 nm were synthesized and their surface was conjugated with lactoferrin to convert them into brain glioma targeting agents. The conjugation was confirmed with the increase of the hydrodynamic diameters, change of zeta potential, and Bradford assay. Magnetic particle spectrometry (MPS), performed to evaluate the MPI performance of these nanoparticles, showed no change in signal after lactoferrin conjugation to nanoparticles for all core diameters, suggesting that the MPI signal is dominated by Néel relaxation and thus independent of hydrodynamic size difference or presence of coating molecules before and after conjugations. For this range of core sizes (14-26 nm), both MPS signal intensity and spatial resolution improved with increasing core diameter of nanoparticles. The lactoferrin conjugated iron oxide nanoparticles (Lf-IONPs) showed specific cellular internalization into C6 cells with a 5-fold increase in MPS signal compared to IONPs without lactoferrin, both after 24 h incubation. These results suggest that Lf-IONPs can be used as tracers for targeted brain glioma imaging using MPI.

MR to CT registration of brains using image synthesis

NASA Astrophysics Data System (ADS)

Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon

2014-03-01

Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

Hyperbaric oxygen modalities are differentially effective in distinct brain ischemia models

PubMed Central

Ostrowski, Robert P.; Stępień, Katarzyna; Pucko, Emanuela; Matyja, Ewa

2016-01-01

The effectiveness and efficacy of hyperbaric oxygen (HBO) preconditioning and post-treatment modalities have been demonstrated in experimental models of ischemic cerebrovascular diseases, including global brain ischemia, transient focal and permanent focal cerebral ischemia, and experimental neonatal hypoxia-ischemia encephalopathy. In general, early and repetitive post-treatment of HBO appears to create enhanced protection against brain ischemia whereas delayed HBO treatment after transient focal ischemia may even aggravate brain injury. This review advocates the level of injury reduction upon HBO as an important component for translational evaluation of HBO based treatment modalities. The combined preconditioning and HBO post-treatment that would provide synergistic effects is also worth considering. PMID:27826422

Subacute sclerosing panencephalitis resembling Rasmussen's encephalitis on magnetic resonance imaging.

PubMed

Jakkani, Ravi Kanth; Sureka, Jyoti; Panwar, Sanuj

2015-09-01

Subacute sclerosing panencephalitis (SSPE) is a rare, slowly progressing but invariably fatal disease that is related to a prior measles virus infection and most commonly affects paediatric patients. Magnetic resonance (MR) imaging is the modality of choice for determining such changes in white matter. SSPE typically demonstrates bilateral but asymmetric periventricular and subcortical white matter involvement. We herein report a rare case of unilateral white matter involvement in a 13-year-old boy with SSPE that closely simulated Rasmussen's encephalitis. To the best of our knowledge, this is the first report of an atypical presentation on MR imaging in which SSPE was a rare cause of unilateral brain parenchymal involvement in a patient with intractable seizures.

Changes of the directional brain networks related with brain plasticity in patients with long-term unilateral sensorineural hearing loss.

PubMed

Zhang, G-Y; Yang, M; Liu, B; Huang, Z-C; Li, J; Chen, J-Y; Chen, H; Zhang, P-P; Liu, L-J; Wang, J; Teng, G-J

2016-01-28

Previous studies often report that early auditory deprivation or congenital deafness contributes to cross-modal reorganization in the auditory-deprived cortex, and this cross-modal reorganization limits clinical benefit from cochlear prosthetics. However, there are inconsistencies among study results on cortical reorganization in those subjects with long-term unilateral sensorineural hearing loss (USNHL). It is also unclear whether there exists a similar cross-modal plasticity of the auditory cortex for acquired monaural deafness and early or congenital deafness. To address this issue, we constructed the directional brain functional networks based on entropy connectivity of resting-state functional MRI and researched changes of the networks. Thirty-four long-term USNHL individuals and seventeen normally hearing individuals participated in the test, and all USNHL patients had acquired deafness. We found that certain brain regions of the sensorimotor and visual networks presented enhanced synchronous output entropy connectivity with the left primary auditory cortex in the left long-term USNHL individuals as compared with normally hearing individuals. Especially, the left USNHL showed more significant changes of entropy connectivity than the right USNHL. No significant plastic changes were observed in the right USNHL. Our results indicate that the left primary auditory cortex (non-auditory-deprived cortex) in patients with left USNHL has been reorganized by visual and sensorimotor modalities through cross-modal plasticity. Furthermore, the cross-modal reorganization also alters the directional brain functional networks. The auditory deprivation from the left or right side generates different influences on the human brain. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Multi-site exploration of sex differences in brain reactivity to smoking cues: Consensus across sites and methodologies.

PubMed

Dumais, Kelly M; Franklin, Teresa R; Jagannathan, Kanchana; Hager, Nathan; Gawrysiak, Michael; Betts, Jennifer; Farmer, Stacey; Guthier, Emily; Pater, Heather; Janes, Amy C; Wetherill, Reagan R

2017-09-01

Biological sex influences cigarette smoking behavior. More men than women smoke, but women have a harder time quitting. Sex differences in smoking cue (SC) reactivity may underlie such behavioral differences. However, the influence of sex on brain reactivity to SCs has yielded inconsistent findings suggesting the need for continued study. Here, we investigated the effect of sex on SC reactivity across two sites using different imaging modalities and SC stimulus types. Pseudo-continuous arterial spin-labeled (pCASL) perfusion functional magnetic resonance imaging (fMRI) was used to assess brain responses to SC versus non-SC videos in 40 smokers (23 females) at the University of Pennsylvania. BOLD fMRI was used to assess brain responses to SC versus non-SC still images in 32 smokers (18 females) at McLean Hospital. Brain reactivity to SCs was compared between men and women and was correlated with SC-induced craving. In both cohorts, males showed higher SC versus non-SC reactivity compared to females in reward-related brain regions (i.e., ventral striatum/ventral pallidum, ventral medial prefrontal cortex). Brain activation during SC versus non-SC exposure correlated positively with SC-induced subjective craving in males, but not females. The current work provides much needed replication and validation of sex differences in SC-reactivity. These findings also add to a body of literature showing that men have greater reward-related brain activation to drug cues across drug classes. Such sex differences confirm the need to consider sex not only when evaluating SC-reactivity but when examining nicotine dependence etiology and treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Management of brain metastasis in a patient with advanced epithelial ovarian carcinoma by gamma-knife radiosurgery.

PubMed

Nikolaoul, Marinos; Stamenković, Srdjan; Stergiou, Christos; Skarleas, Christos; Torrens, Michael

2015-01-01

Brain metastases from epithelial ovarian cancer (EOC) are rare events. We present a rare case of single ovarian cancer metastasis to the brain treated with gamma-knife radiosurgery (GKRS). A 65-year-old woman with advanced EOC presented with severe neurologic symptoms. A single brain metastasis of 3.2 cm with surrounding edema in the left parietal lobe was detected by brain magnetic resonance imaging (MRI) scan during the work-up. The decision to perform GKRS was due to a surgical inaccessibility of intracranial lesion. Twelve weeks after the procedure, the MRI scan showed reduction in the diameter of brain metastasis and surrounding edema and the patient returned to good mental and motor performance.The patient survived for 22 months following treatment and died from a progressive intra-abdominal disease. Prognosis of ovarian cancer patients with brain metastases is generally poor regardless of treatment. Our case shows that GKRS as primary treatment modality for the control of ovarian cancer metastases to the brain was effective and can be considered as a treatment of choice if international selection criteria are followed.

Evaluation of the co-registration capabilities of a MRI/PET compatible bed in an Experimental autoimmune encephalomyelitis (EAE) model

NASA Astrophysics Data System (ADS)

Esposito, Giovanna; D'angeli, Luca; Bartoli, Antonietta; Chaabane, Linda; Terreno, Enzo

2013-02-01

Positron Emission Tomography (PET) with 18F-FDG is a promising tool for the detection and evaluation of active inflammation in animal models of neuroinflammation. MRI is a complementary imaging technique with high resolution and contrast suitable to obtain the anatomical data required to analyze PET data. To combine PET and MRI modalities, we developed a support bed system compatible for both scanners that allowed to perform imaging exams without animal repositioning. With this approach, MRI and PET data were acquired in mice with Experimental autoimmune encephalomyelitis (EAE). In this model, it was possible to measure a variation of 18F-FDG uptake proportional to the degree of disease severity which is mainly related to Central Nervous System (CNS) inflammation. Against the low resolved PET images, the co-registered MRI/PET images allowed to distinguish the different brain structures and to obtain a more accurate tracer evaluation. This is essential in particular for brain regions whose size is of the order of the spatial resolution of PET.

Imaging cerebral haemorrhage with magnetic induction tomography: numerical modelling.

PubMed

Zolgharni, M; Ledger, P D; Armitage, D W; Holder, D S; Griffiths, H

2009-06-01

Magnetic induction tomography (MIT) is a new electromagnetic imaging modality which has the potential to image changes in the electrical conductivity of the brain due to different pathologies. In this study the feasibility of detecting haemorrhagic cerebral stroke with a 16-channel MIT system operating at 10 MHz was investigated. The finite-element method combined with a realistic, multi-layer, head model comprising 12 different tissues, was used for the simulations in the commercial FE package, Comsol Multiphysics. The eddy-current problem was solved and the MIT signals computed for strokes of different volumes occurring at different locations in the brain. The results revealed that a large, peripheral stroke (volume 49 cm(3)) produced phase changes that would be detectable with our currently achievable instrumentation phase noise level (17 m degrees ) in 70 (27%) of the 256 exciter/sensor channel combinations. However, reconstructed images showed that a lower noise level than this, of 1 m degrees , was necessary to obtain good visualization of the strokes. The simulated MIT measurements were compared with those from an independent transmission-line-matrix model in order to give confidence in the results.

Angiogram, fundus, and oxygen saturation optic nerve head image fusion

NASA Astrophysics Data System (ADS)

Cao, Hua; Khoobehi, Bahram

2009-02-01

A novel multi-modality optic nerve head image fusion approach has been successfully designed. The new approach has been applied on three ophthalmologic modalities: angiogram, fundus, and oxygen saturation retinal optic nerve head images. It has achieved an excellent result by giving the visualization of fundus or oxygen saturation images with a complete angiogram overlay. During this study, two contributions have been made in terms of novelty, efficiency, and accuracy. The first contribution is the automated control point detection algorithm for multi-sensor images. The new method employs retina vasculature and bifurcation features by identifying the initial good-guess of control points using the Adaptive Exploratory Algorithm. The second contribution is the heuristic optimization fusion algorithm. In order to maximize the objective function (Mutual-Pixel-Count), the iteration algorithm adjusts the initial guess of the control points at the sub-pixel level. A refinement of the parameter set is obtained at the end of each loop, and finally an optimal fused image is generated at the end of the iteration. It is the first time that Mutual-Pixel-Count concept has been introduced into biomedical image fusion area. By locking the images in one place, the fused image allows ophthalmologists to match the same eye over time and get a sense of disease progress and pinpoint surgical tools. The new algorithm can be easily expanded to human or animals' 3D eye, brain, or body image registration and fusion.

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

PubMed

Xiang, Lei; Wang, Qian; Nie, Dong; Zhang, Lichi; Jin, Xiyao; Qiao, Yu; Shen, Dinggang

2018-07-01

Recently, more and more attention is drawn to the field of medical image synthesis across modalities. Among them, the synthesis of computed tomography (CT) image from T1-weighted magnetic resonance (MR) image is of great importance, although the mapping between them is highly complex due to large gaps of appearances of the two modalities. In this work, we aim to tackle this MR-to-CT synthesis task by a novel deep embedding convolutional neural network (DECNN). Specifically, we generate the feature maps from MR images, and then transform these feature maps forward through convolutional layers in the network. We can further compute a tentative CT synthesis from the midway of the flow of feature maps, and then embed this tentative CT synthesis result back to the feature maps. This embedding operation results in better feature maps, which are further transformed forward in DECNN. After repeating this embedding procedure for several times in the network, we can eventually synthesize a final CT image in the end of the DECNN. We have validated our proposed method on both brain and prostate imaging datasets, by also comparing with the state-of-the-art methods. Experimental results suggest that our DECNN (with repeated embedding operations) demonstrates its superior performances, in terms of both the perceptive quality of the synthesized CT image and the run-time cost for synthesizing a CT image. Copyright © 2018. Published by Elsevier B.V.

Magnetic resonance imaging. Application to family practice.

PubMed

Goh, R H; Somers, S; Jurriaans, E; Yu, J

1999-09-01

To review indications, contraindications, and risks of using magnetic resonance imaging (MRI) in order to help primary care physicians refer patients appropriately for MRI, screen for contraindications to using MRI, and educate patients about MRI. Recommendations are based on classic textbooks, the policies of our MRI group, and a literature search using MEDLINE with the MeSH headings magnetic resonance imaging, brain, musculoskeletal, and spine. The search was limited to human, English-language, and review articles. Evidence in favour of using MRI for imaging the head, spine, and joints is well established. For cardiac, abdominal, and pelvic conditions, MRI has been shown useful for certain indications, usually to complement other modalities. For demonstrating soft tissue conditions, MRI is better than computed tomography (CT), but CT shows bone and acute bleeding better. Therefore, patients with trauma or suspected intracranial bleeding should have CT. Tumours, congenital abnormalities, vascular structures, and the cervical or thoracic spine show better on MRI. Either modality can be used for lower back pain. Cardiac, abdominal, and pelvic abnormalities should be imaged with ultrasound or CT before MRI. Contraindications for MRI are mainly metallic implants or shrapnel, severe claustrophobia, or obesity. With the increasing availability of MRI scanners in Canada, better understanding of the indications, contraindications, and risks will be helpful for family physicians and their patients.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey

PubMed Central

Ismail, Marwa M. T.; Keynton, Robert S.; Mostapha, Mahmoud M. M. O.; ElTanboly, Ahmed H.; Casanova, Manuel F.; Gimel'farb, Georgy L.; El-Baz, Ayman

2016-01-01

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics. PMID:27242476

Do early sensory cortices integrate cross-modal information?

PubMed

Kayser, Christoph; Logothetis, Nikos K

2007-09-01

Our different senses provide complementary evidence about the environment and their interaction often aids behavioral performance or alters the quality of the sensory percept. A traditional view defers the merging of sensory information to higher association cortices, and posits that a large part of the brain can be reduced into a collection of unisensory systems that can be studied in isolation. Recent studies, however, challenge this view and suggest that cross-modal interactions can already occur in areas hitherto regarded as unisensory. We review results from functional imaging and electrophysiology exemplifying cross-modal interactions that occur early during the evoked response, and at the earliest stages of sensory cortical processing. Although anatomical studies revealed several potential origins of these cross-modal influences, there is yet no clear relation between particular functional observations and specific anatomical connections. In addition, our view on sensory integration at the neuronal level is coined by many studies on subcortical model systems of sensory integration; yet, the patterns of cross-modal interaction in cortex deviate from these model systems in several ways. Consequently, future studies on cortical sensory integration need to leave the descriptive level and need to incorporate cross-modal influences into models of the organization of sensory processing. Only then will we be able to determine whether early cross-modal interactions truly merit the label sensory integration, and how they increase a sensory system's ability to scrutinize its environment and finally aid behavior.

Simultaneous measurement of cerebral blood flow and mRNA signals: pixel-based inter-modality correlational analysis.

PubMed

Zhao, W; Busto, R; Truettner, J; Ginsberg, M D

2001-07-30

The analysis of pixel-based relationships between local cerebral blood flow (LCBF) and mRNA expression can reveal important insights into brain function. Traditionally, LCBF and in situ hybridization studies for genes of interest have been analyzed in separate series. To overcome this limitation and to increase the power of statistical analysis, this study focused on developing a double-label method to measure local cerebral blood flow (LCBF) and gene expressions simultaneously by means of a dual-autoradiography procedure. A 14C-iodoantipyrine autoradiographic LCBF study was first performed. Serial brain sections (12 in this study) were obtained at multiple coronal levels and were processed in the conventional manner to yield quantitative LCBF images. Two replicate sections at each bregma level were then used for in situ hybridization. To eliminate the 14C-iodoantipyrine from these sections, a chloroform-washout procedure was first performed. The sections were then processed for in situ hybridization autoradiography for the probes of interest. This method was tested in Wistar rats subjected to 12 min of global forebrain ischemia by two-vessel occlusion plus hypotension, followed by 2 or 6 h of reperfusion (n=4-6 per group). LCBF and in situ hybridization images for heat shock protein 70 (HSP70) were generated for each rat, aligned by disparity analysis, and analyzed on a pixel-by-pixel basis. This method yielded detailed inter-modality correlation between LCBF and HSP70 mRNA expressions. The advantages of this method include reducing the number of experimental animals by one-half; and providing accurate pixel-based correlations between different modalities in the same animals, thus enabling paired statistical analyses. This method can be extended to permit correlation of LCBF with the expression of multiple genes of interest.

SPECT brain perfusion abnormalities in mild or moderate traumatic brain injury.

PubMed

Abdel-Dayem, H M; Abu-Judeh, H; Kumar, M; Atay, S; Naddaf, S; El-Zeftawy, H; Luo, J Q

1998-05-01

The purpose of this atlas is to present a review of the literature showing the advantages of SPECT brain perfusion imaging (BPI) in mild or moderate traumatic brain injury (TBI) over other morphologic imaging modalities such as x-ray CT or MRI. The authors also present the technical recommendations for SPECT brain perfusion currently practiced at their center. For the radiopharmaceutical of choice, a comparison between early and delayed images using Tc-99m HMPAO and Tc-99m ECD showed that Tc-99m HMPAO is more stable in the brain with no washout over time. Therefore, the authors feel that Tc-99m HMPAO is preferable to Tc-99m ECD. Recommendations regarding standardizing intravenous injection, the acquisition, processing parameters, and interpretation of scans using a ten grade color scale, and use of the cerebellum as the reference organ are presented. SPECT images of 228 patients (age range, 11 to 88; mean, 40.8 years) with mild or moderate TBI and no significant medical history that interfered with the results of the SPECT BP were reviewed. The etiology of the trauma was in the following order of frequency: motor vehicle accidents (45%) followed by blow to the head (36%) and a fall (19%). Frequency of the symptoms was headache (60.9%), memory problems (27.6%), dizziness (26.7%), and sleep disorders (8.7%). Comparison between patients imaged early (<3 months) versus those imaged delayed (>3 months) from the time of the accident, showed that early imaging detected more lesions (4.2 abnormal lesions per study compared to 2.7 in those imaged more than 3 months after the accident). Of 41 patients who had mild traumatic injury without loss of consciousness and had normal CT, 28 studies were abnormal. Focal areas of hypoperfusion were seen in 77% (176 patients, 612 lesions) of the group of 228 patients. The sites of abnormalities were in the following order: basal ganglia and thalami, 55.2%, frontal lobes, 23.8%, temporal lobes, 13%, parietal, 3.7%, insular and occipital lobes together, 4.6%.

A prototype hand-held tri-modal instrument for in vivo ultrasound, photoacoustic, and fluorescence imaging

NASA Astrophysics Data System (ADS)

Kang, Jeeun; Chang, Jin Ho; Wilson, Brian C.; Veilleux, Israel; Bai, Yanhui; DaCosta, Ralph; Kim, Kang; Ha, Seunghan; Lee, Jong Gun; Kim, Jeong Seok; Lee, Sang-Goo; Kim, Sun Mi; Lee, Hak Jong; Ahn, Young Bok; Han, Seunghee; Yoo, Yangmo; Song, Tai-Kyong

2015-03-01

Multi-modality imaging is beneficial for both preclinical and clinical applications as it enables complementary information from each modality to be obtained in a single procedure. In this paper, we report the design, fabrication, and testing of a novel tri-modal in vivo imaging system to exploit molecular/functional information from fluorescence (FL) and photoacoustic (PA) imaging as well as anatomical information from ultrasound (US) imaging. The same ultrasound transducer was used for both US and PA imaging, bringing the pulsed laser light into a compact probe by fiberoptic bundles. The FL subsystem is independent of the acoustic components but the front end that delivers and collects the light is physically integrated into the same probe. The tri-modal imaging system was implemented to provide each modality image in real time as well as co-registration of the images. The performance of the system was evaluated through phantom and in vivo animal experiments. The results demonstrate that combining the modalities does not significantly compromise the performance of each of the separate US, PA, and FL imaging techniques, while enabling multi-modality registration. The potential applications of this novel approach to multi-modality imaging range from preclinical research to clinical diagnosis, especially in detection/localization and surgical guidance of accessible solid tumors.

Support Vector Machine Classification of Major Depressive Disorder Using Diffusion-Weighted Neuroimaging and Graph Theory

PubMed Central

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

2015-01-01

Recently, there has been considerable interest in understanding brain networks in major depressive disorder (MDD). Neural pathways can be tracked in the living brain using diffusion-weighted imaging (DWI); graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on “support vector machines” to differentiate depressed from healthy individuals based on multiple brain network properties. We also assessed how important specific graph metrics were for this differentiation. Finally, we conducted a local graph analysis to identify abnormal connectivity at specific nodes of the network. We were able to classify depression using whole-brain graph metrics. Small-worldness was the most useful graph metric for classification. The right pars orbitalis, right inferior parietal cortex, and left rostral anterior cingulate all showed abnormal network connectivity in MDD. This is the first use of structural global graph metrics to classify depressed individuals. These findings highlight the importance of future research to understand network properties in depression across imaging modalities, improve classification results, and relate network alterations to psychiatric symptoms, medication, and comorbidities. PMID:25762941

Support vector machine classification of major depressive disorder using diffusion-weighted neuroimaging and graph theory.

PubMed

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

2015-01-01

Recently, there has been considerable interest in understanding brain networks in major depressive disorder (MDD). Neural pathways can be tracked in the living brain using diffusion-weighted imaging (DWI); graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on "support vector machines" to differentiate depressed from healthy individuals based on multiple brain network properties. We also assessed how important specific graph metrics were for this differentiation. Finally, we conducted a local graph analysis to identify abnormal connectivity at specific nodes of the network. We were able to classify depression using whole-brain graph metrics. Small-worldness was the most useful graph metric for classification. The right pars orbitalis, right inferior parietal cortex, and left rostral anterior cingulate all showed abnormal network connectivity in MDD. This is the first use of structural global graph metrics to classify depressed individuals. These findings highlight the importance of future research to understand network properties in depression across imaging modalities, improve classification results, and relate network alterations to psychiatric symptoms, medication, and comorbidities.

A variational Bayes spatiotemporal model for electromagnetic brain mapping.

PubMed

Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

2014-03-01

In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.

Optoacoustic imaging in five dimensions

NASA Astrophysics Data System (ADS)

Deán-Ben, X. L.; Gottschalk, Sven; Fehm, Thomas F.; Razansky, Daniel

2015-03-01

We report on an optoacoustic imaging system capable of acquiring volumetric multispectral optoacoustic data in real time. The system is based on simultaneous acquisition of optoacoustic signals from 256 different tomographic projections by means of a spherical matrix array. Thereby, volumetric reconstructions can be done at high frame rate, only limited by the pulse repetition rate of the laser. The developed tomographic approach presents important advantages over previously reported systems that use scanning for attaining volumetric optoacoustic data. First, dynamic processes, such as the biodistribution of optical biomarkers, can be monitored in the entire volume of interest. Second, out-of-plane and motion artifacts that could degrade the image quality when imaging living specimens can be avoided. Finally, real-time 3D performance can obviously save time required for experimental and clinical observations. The feasibility of optoacoustic imaging in five dimensions, i.e. real time acquisition of volumetric datasets at multiple wavelengths, is reported. In this way, volumetric images of spectrally resolved chromophores are rendered in real time, thus offering an unparallel imaging performance among the current bio-imaging modalities. This performance is subsequently showcased by video-rate visualization of in vivo hemodynamic changes in mouse brain and handheld visualization of blood oxygenation in deep human vessels. The newly discovered capacities open new prospects for translating the optoacoustic technology into highly performing imaging modality for biomedical research and clinical practice with multiple applications envisioned, from cardiovascular and cancer diagnostics to neuroimaging and ophthalmology.

Diagnostic Imaging of Pregnant Women – The Role of Magnetic Resonance Imaging

PubMed Central

Bekiesińska-Figatowska, Monika; Romaniuk-Doroszewska, Anna; Szkudlińska-Pawlak, Sylwia; Duczkowska, Agnieszka; Mądzik, Jarosław; Szopa-Krupińska, Martyna; Maciejewski, Tomasz M.

2017-01-01

Summary Background Presentation of magnetic resonance imaging (MRI) findings in pregnant women in the Department of Diagnostic Imaging, Institute of Mother and Child, Warsaw, Poland. Material/Methods Forty-three symptomatic pregnant women underwent MRI between 9 and 33 weeks of gestation (mean of 23 weeks). Moreover, we included 2 pregnant women who underwent fetal MRI and had incidental abnormalities. Results In 9 cases, we excluded the suspected brain abnormalities. In 4 cases, we found unremarkable changes in the brain without clinical significance. One patient was diagnosed with multiple sclerosis, one with cortical dysplasia, one with pineal hemorrhage and one with a brain tumor. On abdominal MRI, 2 patients had normal findings, one patient had colon cancer with a hepatic metastasis, one patient had a hepatic angioma, one patient had an extraadrenal pheochromocytoma, one patient had an abscess in the iliopsoas muscle, 9 patients had myomas, two patients had ovarian simple cysts, two endometrial cysts, three dermoid cysts, one patient had sacrococcygeal teratoma, one patient had a cystadenofibroma (partial borderline tumor), one patient had an androgenic ovarian tumor and two patients had hyperreactio luteinalis. One patient was diagnosed with transient osteoporosis of the hip and one with a stress fracture of the sacral bone. Conclusions Magnetic resonance imaging is the best imaging modality for pregnant women. Although ultrasonography is the method of choice, doubtful cases as well as structures that cannot be examined with ultrasonography can be non-invasively evaluated with MRI. PMID:28507642

Accurate determination of imaging modality using an ensemble of text- and image-based classifiers.

PubMed

Kahn, Charles E; Kalpathy-Cramer, Jayashree; Lam, Cesar A; Eldredge, Christina E

2012-02-01

Imaging modality can aid retrieval of medical images for clinical practice, research, and education. We evaluated whether an ensemble classifier could outperform its constituent individual classifiers in determining the modality of figures from radiology journals. Seventeen automated classifiers analyzed 77,495 images from two radiology journals. Each classifier assigned one of eight imaging modalities--computed tomography, graphic, magnetic resonance imaging, nuclear medicine, positron emission tomography, photograph, ultrasound, or radiograph-to each image based on visual and/or textual information. Three physicians determined the modality of 5,000 randomly selected images as a reference standard. A "Simple Vote" ensemble classifier assigned each image to the modality that received the greatest number of individual classifiers' votes. A "Weighted Vote" classifier weighted each individual classifier's vote based on performance over a training set. For each image, this classifier's output was the imaging modality that received the greatest weighted vote score. We measured precision, recall, and F score (the harmonic mean of precision and recall) for each classifier. Individual classifiers' F scores ranged from 0.184 to 0.892. The simple vote and weighted vote classifiers correctly assigned 4,565 images (F score, 0.913; 95% confidence interval, 0.905-0.921) and 4,672 images (F score, 0.934; 95% confidence interval, 0.927-0.941), respectively. The weighted vote classifier performed significantly better than all individual classifiers. An ensemble classifier correctly determined the imaging modality of 93% of figures in our sample. The imaging modality of figures published in radiology journals can be determined with high accuracy, which will improve systems for image retrieval.

Three modality image registration of brain SPECT/CT and MR images for quantitative analysis of dopamine transporter imaging

NASA Astrophysics Data System (ADS)

Yamaguchi, Yuzuho; Takeda, Yuta; Hara, Takeshi; Zhou, Xiangrong; Matsusako, Masaki; Tanaka, Yuki; Hosoya, Kazuhiko; Nihei, Tsutomu; Katafuchi, Tetsuro; Fujita, Hiroshi

2016-03-01

Important features in Parkinson's disease (PD) are degenerations and losses of dopamine neurons in corpus striatum. 123I-FP-CIT can visualize activities of the dopamine neurons. The activity radio of background to corpus striatum is used for diagnosis of PD and Dementia with Lewy Bodies (DLB). The specific activity can be observed in the corpus striatum on SPECT images, but the location and the shape of the corpus striatum on SPECT images only are often lost because of the low uptake. In contrast, MR images can visualize the locations of the corpus striatum. The purpose of this study was to realize a quantitative image analysis for the SPECT images by using image registration technique with brain MR images that can determine the region of corpus striatum. In this study, the image fusion technique was used to fuse SPECT and MR images by intervening CT image taken by SPECT/CT. The mutual information (MI) for image registration between CT and MR images was used for the registration. Six SPECT/CT and four MR scans of phantom materials are taken by changing the direction. As the results of the image registrations, 16 of 24 combinations were registered within 1.3mm. By applying the approach to 32 clinical SPECT/CT and MR cases, all of the cases were registered within 0.86mm. In conclusions, our registration method has a potential in superimposing MR images on SPECT images.

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

NASA Astrophysics Data System (ADS)

Raghunath, N.; Faber, T. L.; Suryanarayanan, S.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

Application of Thinned-Skull Cranial Window to Mouse Cerebral Blood Flow Imaging Using Optical Microangiography

PubMed Central

Wang, Ruikang K.

2014-01-01

In vivo imaging of mouse brain vasculature typically requires applying skull window opening techniques: open-skull cranial window or thinned-skull cranial window. We report non-invasive 3D in vivo cerebral blood flow imaging of C57/BL mouse by the use of ultra-high sensitive optical microangiography (UHS-OMAG) and Doppler optical microangiography (DOMAG) techniques to evaluate two cranial window types based on their procedures and ability to visualize surface pial vessel dynamics. Application of the thinned-skull technique is found to be effective in achieving high quality images for pial vessels for short-term imaging, and has advantages over the open-skull technique in available imaging area, surgical efficiency, and cerebral environment preservation. In summary, thinned-skull cranial window serves as a promising tool in studying hemodynamics in pial microvasculature using OMAG or other OCT blood flow imaging modalities. PMID:25426632

Fast and robust multimodal image registration using a local derivative pattern.

PubMed

Jiang, Dongsheng; Shi, Yonghong; Chen, Xinrong; Wang, Manning; Song, Zhijian

2017-02-01

Deformable multimodal image registration, which can benefit radiotherapy and image guided surgery by providing complementary information, remains a challenging task in the medical image analysis field due to the difficulty of defining a proper similarity measure. This article presents a novel, robust and fast binary descriptor, the discriminative local derivative pattern (dLDP), which is able to encode images of different modalities into similar image representations. dLDP calculates a binary string for each voxel according to the pattern of intensity derivatives in its neighborhood. The descriptor similarity is evaluated using the Hamming distance, which can be efficiently computed, instead of conventional L1 or L2 norms. For the first time, we validated the effectiveness and feasibility of the local derivative pattern for multimodal deformable image registration with several multi-modal registration applications. dLDP was compared with three state-of-the-art methods in artificial image and clinical settings. In the experiments of deformable registration between different magnetic resonance imaging (MRI) modalities from BrainWeb, between computed tomography and MRI images from patient data, and between MRI and ultrasound images from BITE database, we show our method outperforms localized mutual information and entropy images in terms of both accuracy and time efficiency. We have further validated dLDP for the deformable registration of preoperative MRI and three-dimensional intraoperative ultrasound images. Our results indicate that dLDP reduces the average mean target registration error from 4.12 mm to 2.30 mm. This accuracy is statistically equivalent to the accuracy of the state-of-the-art methods in the study; however, in terms of computational complexity, our method significantly outperforms other methods and is even comparable to the sum of the absolute difference. The results reveal that dLDP can achieve superior performance regarding both accuracy and time efficiency in general multimodal image registration. In addition, dLDP also indicates the potential for clinical ultrasound guided intervention. © 2016 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Multisensory Integration of Sounds and Vibrotactile Stimuli in Processing Streams for “What” and “Where”

PubMed Central

Renier, Laurent A.; Anurova, Irina; De Volder, Anne G.; Carlson, Synnöve; VanMeter, John; Rauschecker, Josef P.

2012-01-01

The segregation between cortical pathways for the identification and localization of objects is thought of as a general organizational principle in the brain. Yet, little is known about the unimodal versus multimodal nature of these processing streams. The main purpose of the present study was to test whether the auditory and tactile dual pathways converged into specialized multisensory brain areas. We used functional magnetic resonance imaging (fMRI) to compare directly in the same subjects the brain activation related to localization and identification of comparable auditory and vibrotactile stimuli. Results indicate that the right inferior frontal gyrus (IFG) and both left and right insula were more activated during identification conditions than during localization in both touch and audition. The reverse dissociation was found for the left and right inferior parietal lobules (IPL), the left superior parietal lobule (SPL) and the right precuneus-SPL, which were all more activated during localization conditions in the two modalities. We propose that specialized areas in the right IFG and the left and right insula are multisensory operators for the processing of stimulus identity whereas parts of the left and right IPL and SPL are specialized for the processing of spatial attributes independently of sensory modality. PMID:19726653

Informatic parcellation of the network involved in the computation of subjective value

PubMed Central

Rangel, Antonio

2014-01-01

Understanding how the brain computes value is a basic question in neuroscience. Although individual studies have driven this progress, meta-analyses provide an opportunity to test hypotheses that require large collections of data. We carry out a meta-analysis of a large set of functional magnetic resonance imaging studies of value computation to address several key questions. First, what is the full set of brain areas that reliably correlate with stimulus values when they need to be computed? Second, is this set of areas organized into dissociable functional networks? Third, is a distinct network of regions involved in the computation of stimulus values at decision and outcome? Finally, are different brain areas involved in the computation of stimulus values for different reward modalities? Our results demonstrate the centrality of ventromedial prefrontal cortex (VMPFC), ventral striatum and posterior cingulate cortex (PCC) in the computation of value across tasks, reward modalities and stages of the decision-making process. We also find evidence of distinct subnetworks of co-activation within VMPFC, one involving central VMPFC and dorsal PCC and another involving more anterior VMPFC, left angular gyrus and ventral PCC. Finally, we identify a posterior-to-anterior gradient of value representations corresponding to concrete-to-abstract rewards. PMID:23887811

A supramodal brain substrate of word form processing--an fMRI study on homonym finding with auditory and visual input.

PubMed

Balthasar, Andrea J R; Huber, Walter; Weis, Susanne

2011-09-02

Homonym processing in German is of theoretical interest as homonyms specifically involve word form information. In a previous study (Weis et al., 2001), we found inferior parietal activation as a correlate of successfully finding a homonym from written stimuli. The present study tries to clarify the underlying mechanism and to examine to what extend the previous homonym effect is dependent on visual in contrast to auditory input modality. 18 healthy subjects were examined using an event-related functional magnetic resonance imaging paradigm. Participants had to find and articulate a homonym in relation to two spoken or written words. A semantic-lexical task - oral naming from two-word definitions - was used as a control condition. When comparing brain activation for solved homonym trials to both brain activation for unsolved homonyms and solved definition trials we obtained two activations patterns, which characterised both auditory and visual processing. Semantic-lexical processing was related to bilateral inferior frontal activation, whereas left inferior parietal activation was associated with finding the correct homonym. As the inferior parietal activation during successful access to the word form of a homonym was independent of input modality, it might be the substrate of access to word form knowledge. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Multimodality stereotactic brain tissue identification: the NASA smart probe project

NASA Technical Reports Server (NTRS)

Andrews, R.; Mah, R.; Aghevli, A.; Freitas, K.; Galvagni, A.; Guerrero, M.; Papsin, R.; Reed, C.; Stassinopoulos, D.

1999-01-01

Real-time tissue identification can benefit procedures such as stereotactic brain biopsy, functional neurosurgery and brain tumor excision. Optical scattering spectroscopy has been shown to be effective at discriminating cancer from noncancerous conditions in the colon, bladder and breast. The NASA Smart Probe extends the concept of 'optical biopsy' by using neural network techniques to combine the output from 3 microsensors contained within a cannula 2. 7 mm in diameter (i.e. the diameter of a stereotactic brain biopsy needle). Experimental data from 5 rats show the clear differentiation between tissues such as brain, nerve, fat, artery and muscle that can be achieved with optical scattering spectroscopy alone. These data and previous findings with other modalities such as (1) analysis of the image from a fiberoptic neuroendoscope and (2) the output from a microstrain gauge suggest the Smart Probe multiple microsensor technique shows promise for real-time tissue identification in neurosurgical procedures. Copyright 2000 S. Karger AG, Basel.

Evaluating the effects of maternal alcohol consumption on murine fetal brain vasculature using optical coherence tomography.

PubMed

Raghunathan, Raksha; Wu, Chen; Singh, Manmohan; Liu, Chih-Hao; Miranda, Rajesh C; Larin, Kirill V

2018-05-01

Prenatal alcohol exposure (PAE) can result in a range of anomalies including brain and behavioral dysfunctions, collectively termed fetal alcohol spectrum disorder. PAE during the 1st and 2nd trimester is common, and research in animal models has documented significant neural developmental deficits associated with PAE during this period. However, little is known about the immediate effects of PAE on fetal brain vasculature. In this study, we used in utero speckle variance optical coherence tomography, a high spatial- and temporal-resolution imaging modality, to evaluate dynamic changes in microvasculature of the 2nd trimester equivalent murine fetal brain, minutes after binge-like maternal alcohol exposure. Acute binge-like PAE resulted in a rapid (<1 hour) and significant decrease (P < .001) in vessel diameter as compared to the sham group. The data show that a single binge-like maternal alcohol exposure resulted in swift vasoconstriction in fetal brain vessels during the critical period of neurogenesis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Brain/MINDS 3D digital marmoset brain atlas

PubMed Central

Woodward, Alexander; Hashikawa, Tsutomu; Maeda, Masahide; Kaneko, Takaaki; Hikishima, Keigo; Iriki, Atsushi; Okano, Hideyuki; Yamaguchi, Yoko

2018-01-01

We present a new 3D digital brain atlas of the non-human primate, common marmoset monkey (Callithrix jacchus), with MRI and coregistered Nissl histology data. To the best of our knowledge this is the first comprehensive digital 3D brain atlas of the common marmoset having normalized multi-modal data, cortical and sub-cortical segmentation, and in a common file format (NIfTI). The atlas can be registered to new data, is useful for connectomics, functional studies, simulation and as a reference. The atlas was based on previously published work but we provide several critical improvements to make this release valuable for researchers. Nissl histology images were processed to remove illumination and shape artifacts and then normalized to the MRI data. Brain region segmentation is provided for both hemispheres. The data is in the NIfTI format making it easy to integrate into neuroscience pipelines, whereas the previous atlas was in an inaccessible file format. We also provide cortical, mid-cortical and white matter boundary segmentations useful for visualization and analysis. PMID:29437168

A scalable method to improve gray matter segmentation at ultra high field MRI.

PubMed

Gulban, Omer Faruk; Schneider, Marian; Marquardt, Ingo; Haast, Roy A M; De Martino, Federico

2018-01-01

High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data.

A scalable method to improve gray matter segmentation at ultra high field MRI

PubMed Central

De Martino, Federico

2018-01-01

High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data. PMID:29874295

Functional dissociations in top-down control dependent neural repetition priming.

PubMed

Klaver, Peter; Schnaidt, Malte; Fell, Jürgen; Ruhlmann, Jürgen; Elger, Christian E; Fernández, Guillén

2007-02-15

Little is known about the neural mechanisms underlying top-down control of repetition priming. Here, we use functional brain imaging to investigate these mechanisms. Study and repetition tasks used a natural/man-made forced choice task. In the study phase subjects were required to respond to either pictures or words that were presented superimposed on each other. In the repetition phase only words were presented that were new, previously attended or ignored, or picture names that were derived from previously attended or ignored pictures. Relative to new words we found repetition priming for previously attended words. Previously ignored words showed a reduced priming effect, and there was no significant priming for pictures repeated as picture names. Brain imaging data showed that neural priming of words in the left prefrontal cortex (LIPFC) and left fusiform gyrus (LOTC) was affected by attention, semantic compatibility of superimposed stimuli during study and cross-modal priming. Neural priming reduced for words in the LIPFC and for words and pictures in the LOTC if stimuli were previously ignored. Previously ignored words that were semantically incompatible with a superimposed picture during study induce increased neural priming compared to semantically compatible ignored words (LIPFC) and decreased neural priming of previously attended pictures (LOTC). In summary, top-down control induces dissociable effects on neural priming by attention, cross-modal priming and semantic compatibility in a way that was not evident from behavioral results.

Magnetic resonance imaging for diagnosis of early Alzheimer's disease.

PubMed

Colliot, O; Hamelin, L; Sarazin, M

2013-10-01

A major challenge for neuroimaging is to contribute to the early diagnosis of Alzheimer's disease (AD). In particular, magnetic resonance imaging (MRI) allows detecting different types of structural and functional abnormalities at an early stage of the disease. Anatomical MRI is the most widely used technique and provides local and global measures of atrophy. The recent diagnostic criteria of "mild cognitive impairment due to AD" include hippocampal atrophy, which is considered a marker of neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in the hippocampus and throughout the whole brain. Recent modalities such as diffusion-tensor imaging and resting-state functional MRI provide additional measures that could contribute to the early diagnosis but require further validation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Co-registration of multi-modality imaging allows for comprehensive analysis of tumor-induced bone disease

PubMed Central

Seeley, Erin H.; Wilson, Kevin J.; Yankeelov, Thomas E.; Johnson, Rachelle W.; Gore, John C.; Caprioli, Richard M.; Matrisian, Lynn M.; Sterling, Julie A.

2014-01-01

Bone metastases are a clinically significant problem that arises in approximately 70% of metastatic breast cancer patients. Once established in bone, tumor cells induce changes in the bone microenvironment that lead to bone destruction, pain, and significant morbidity. While much is known about the later stages of bone disease, less is known about the earlier stages or the changes in protein expression in the tumor micro-environment. Due to promising results of combining magnetic resonance imaging (MRI) and Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry (MALDI IMS) ion images in the brain, we developed methods for applying these modalities to models of tumor-induced bone disease in order to better understand the changes in protein expression that occur within the tumor-bone microenvironment. Specifically, we integrated three dimensional-volume reconstructions of spatially resolved MALDI IMS with high-resolution anatomical and diffusion weighted MRI data and histology in an intratibial model of breast tumor-induced bone disease. This approach enables us to analyze proteomic profiles from MALDI IMS data with corresponding in vivo imaging and ex vivo histology data. To the best of our knowledge, this is the first time these three modalities have been rigorously registered in the bone. The MALDI mass-to-charge ratio peaks indicate differential expression of calcyclin, ubiquitin, and other proteins within the tumor cells, while peaks corresponding to hemoglobin A and calgranulin A provided molecular information that aided in the identification of areas rich in red and white blood cells, respectively. This multimodality approach will allow us to comprehensively understand the bone-tumor microenvironment and thus may allow us to better develop and test approaches for inhibiting bone metastases. PMID:24487126

First-in-human study of PET and optical dual-modality image-guided surgery in glioblastoma using 68Ga-IRDye800CW-BBN.

PubMed

Li, Deling; Zhang, Jingjing; Chi, Chongwei; Xiao, Xiong; Wang, Junmei; Lang, Lixin; Ali, Iqbal; Niu, Gang; Zhang, Liwei; Tian, Jie; Ji, Nan; Zhu, Zhaohui; Chen, Xiaoyuan

2018-01-01

Purpose : Despite the use of fluorescence-guided surgery (FGS), maximum safe resection of glioblastoma multiforme (GBM) remains a major challenge. It has restricted surgeons between preoperative diagnosis and intraoperative treatment. Currently, an integrated approach combining preoperative assessment with intraoperative guidance would be a significant step in this direction. Experimental design : We developed a novel 68 Ga-IRDye800CW-BBN PET/near-infrared fluorescence (NIRF) dual-modality imaging probe targeting gastrin-releasing peptide receptor (GRPR) in GBM. The preclinical in vivo tumor imaging and FGS were first evaluated using an orthotopic U87MG glioma xenograft model. Subsequently, the first-in-human prospective cohort study (NCT 02910804) of GBM patients were conducted with preoperative PET assessment and intraoperative FGS. Results : The orthotopic tumors in mice could be precisely resected using the near-infrared intraoperative system. Translational cohort research in 14 GBM patients demonstrated an excellent correlation between preoperative positive PET uptake and intraoperative NIRF signal. The tumor fluorescence signals were significantly higher than those from adjacent brain tissue in vivo and ex vivo (p < 0.0001). Compared with pathology, the sensitivity and specificity of fluorescence using 42 loci of fluorescence-guided sampling were 93.9% (95% CI 79.8%-99.3%) and 100% (95% CI 66.4%-100%), respectively. The tracer was safe and the extent of resection was satisfactory without newly developed neurologic deficits. Progression-free survival (PFS) at 6 months was 80% and two newly diagnosed patients achieved long PFS. Conclusions: This initial study has demonstrated that the novel dual-modality imaging technique is feasible for integrated pre- and intraoperative targeted imaging via the same molecular receptor and improved intraoperative GBM visualization and maximum safe resection.

Words in the bilingual brain: an fNIRS brain imaging investigation of lexical processing in sign-speech bimodal bilinguals

PubMed Central

Kovelman, Ioulia; Shalinsky, Mark H.; Berens, Melody S.; Petitto, Laura-Ann

2014-01-01

Early bilingual exposure, especially exposure to two languages in different modalities such as speech and sign, can profoundly affect an individual's language, culture, and cognition. Here we explore the hypothesis that bimodal dual language exposure can also affect the brain's organization for language. These changes occur across brain regions universally important for language and parietal regions especially critical for sign language (Newman et al., 2002). We investigated three groups of participants (N = 29) that completed a word repetition task in American Sign Language (ASL) during fNIRS brain imaging. Those groups were (1) hearing ASL-English bimodal bilinguals (n = 5), (2) deaf ASL signers (n = 7), and (3) English monolinguals naïve to sign language (n = 17). The key finding of the present study is that bimodal bilinguals showed reduced activation in left parietal regions relative to deaf ASL signers when asked to use only ASL. In contrast, this group of bimodal signers showed greater activation in left temporo-parietal regions relative to English monolinguals when asked to switch between their two languages (Kovelman et al., 2009). Converging evidence now suggest that bimodal bilingual experience changes the brain bases of language, including the left temporo-parietal regions known to be critical for sign language processing (Emmorey et al., 2007). The results provide insight into the resilience and constraints of neural plasticity for language and bilingualism. PMID:25191247

Vessel segmentation in 4D arterial spin labeling magnetic resonance angiography images of the brain

NASA Astrophysics Data System (ADS)

Phellan, Renzo; Lindner, Thomas; Falcão, Alexandre X.; Forkert, Nils D.

2017-03-01

4D arterial spin labeling magnetic resonance angiography (4D ASL MRA) is a non-invasive and safe modality for cerebrovascular imaging procedures. It uses the patient's magnetically labeled blood as intrinsic contrast agent, so that no external contrast media is required. It provides important 3D structure and blood flow information but a sufficient cerebrovascular segmentation is important since it can help clinicians to analyze and diagnose vascular diseases faster, and with higher confidence as compared to simple visual rating of raw ASL MRA images. This work presents a new method for automatic cerebrovascular segmentation in 4D ASL MRA images of the brain. In this process images are denoised, corresponding image label/control image pairs of the 4D ASL MRA sequences are subtracted, and temporal intensity averaging is used to generate a static representation of the vascular system. After that, sets of vessel and background seeds are extracted and provided as input for the image foresting transform algorithm to segment the vascular system. Four 4D ASL MRA datasets of the brain arteries of healthy subjects and corresponding time-of-flight (TOF) MRA images were available for this preliminary study. For evaluation of the segmentation results of the proposed method, the cerebrovascular system was automatically segmented in the high-resolution TOF MRA images using a validated algorithm and the segmentation results were registered to the 4D ASL datasets. Corresponding segmentation pairs were compared using the Dice similarity coefficient (DSC). On average, a DSC of 0.9025 was achieved, indicating that vessels can be extracted successfully from 4D ASL MRA datasets by the proposed segmentation method.

Hybrid-modality high-resolution imaging: for diagnostic biomedical imaging and sensing for disease diagnosis

NASA Astrophysics Data System (ADS)

Murukeshan, Vadakke M.; Hoong Ta, Lim

2014-11-01

Medical diagnostics in the recent past has seen the challenging trend to come up with dual and multi-modality imaging for implementing better diagnostic procedures. The changes in tissues in the early disease stages are often subtle and can occur beneath the tissue surface. In most of these cases, conventional types of medical imaging using optics may not be able to detect these changes easily due to its penetration depth of the orders of 1 mm. Each imaging modality has its own advantages and limitations, and the use of a single modality is not suitable for every diagnostic applications. Therefore the need for multi or hybrid-modality imaging arises. Combining more than one imaging modalities overcomes the limitation of individual imaging method and integrates the respective advantages into a single setting. In this context, this paper will be focusing on the research and development of two multi-modality imaging platforms. The first platform combines ultrasound and photoacoustic imaging for diagnostic applications in the eye. The second platform consists of optical hyperspectral and photoacoustic imaging for diagnostic applications in the colon. Photoacoustic imaging is used as one of the modalities in both platforms as it can offer deeper penetration depth compared to optical imaging. The optical engineering and research challenges in developing the dual/multi-modality platforms will be discussed, followed by initial results validating the proposed scheme. The proposed schemes offer high spatial and spectral resolution imaging and sensing, and is expected to offer potential biomedical imaging solutions in the near future.

Precise diagnosis in different scenarios using photoacoustic and fluorescence imaging with dual-modality nanoparticles

NASA Astrophysics Data System (ADS)

Peng, Dong; Du, Yang; Shi, Yiwen; Mao, Duo; Jia, Xiaohua; Li, Hui; Zhu, Yukun; Wang, Kun; Tian, Jie

2016-07-01

Photoacoustic imaging and fluorescence molecular imaging are emerging as important research tools for biomedical studies. Photoacoustic imaging offers both strong optical absorption contrast and high ultrasonic resolution, and fluorescence molecular imaging provides excellent superficial resolution, high sensitivity, high throughput, and the ability for real-time imaging. Therefore, combining the imaging information of both modalities can provide comprehensive in vivo physiological and pathological information. However, currently there are limited probes available that can realize both fluorescence and photoacoustic imaging, and advanced biomedical applications for applying this dual-modality imaging approach remain underexplored. In this study, we developed a dual-modality photoacoustic-fluorescence imaging nanoprobe, ICG-loaded Au@SiO2, which was uniquely designed, consisting of gold nanorod cores and indocyanine green with silica shell spacer layers to overcome fluorophore quenching. This nanoprobe was examined by both PAI and FMI for in vivo imaging on tumor and ischemia mouse models. Our results demonstrated that the nanoparticles can specifically accumulate at the tumor and ischemic areas and be detected by both imaging modalities. Moreover, this dual-modality imaging strategy exhibited superior advantages for a precise diagnosis in different scenarios. The new nanoprobe with the dual-modality imaging approach holds great potential for diagnosis and stage classification of tumor and ischemia related diseases.Photoacoustic imaging and fluorescence molecular imaging are emerging as important research tools for biomedical studies. Photoacoustic imaging offers both strong optical absorption contrast and high ultrasonic resolution, and fluorescence molecular imaging provides excellent superficial resolution, high sensitivity, high throughput, and the ability for real-time imaging. Therefore, combining the imaging information of both modalities can provide comprehensive in vivo physiological and pathological information. However, currently there are limited probes available that can realize both fluorescence and photoacoustic imaging, and advanced biomedical applications for applying this dual-modality imaging approach remain underexplored. In this study, we developed a dual-modality photoacoustic-fluorescence imaging nanoprobe, ICG-loaded Au@SiO2, which was uniquely designed, consisting of gold nanorod cores and indocyanine green with silica shell spacer layers to overcome fluorophore quenching. This nanoprobe was examined by both PAI and FMI for in vivo imaging on tumor and ischemia mouse models. Our results demonstrated that the nanoparticles can specifically accumulate at the tumor and ischemic areas and be detected by both imaging modalities. Moreover, this dual-modality imaging strategy exhibited superior advantages for a precise diagnosis in different scenarios. The new nanoprobe with the dual-modality imaging approach holds great potential for diagnosis and stage classification of tumor and ischemia related diseases. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03809c

WE-H-206-02: Recent Advances in Multi-Modality Molecular Imaging of Small Animals

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

Tsui, B.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

Non-parametric combination and related permutation tests for neuroimaging.

PubMed

Winkler, Anderson M; Webster, Matthew A; Brooks, Jonathan C; Tracey, Irene; Smith, Stephen M; Nichols, Thomas E

2016-04-01

In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume-based representations of the brain, including non-imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non-parametric combination (NPC) methodology, such that instead of a two-phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one-way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Tractography-Based Score for Learning Effective Connectivity From Multimodal Imaging Data Using Dynamic Bayesian Networks.

PubMed

Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun K

2018-05-01

Effective connectivity (EC) is the methodology for determining functional-integration among the functionally active segregated regions of the brain. By definition EC is "the causal influence exerted by one neuronal group on another" which is constrained by anatomical connectivity (AC) (axonal connections). AC is necessary for EC but does not fully determine it, because synaptic communication occurs dynamically in a context-dependent fashion. Although there is a vast emerging evidence of structure-function relationship using multimodal imaging studies, till date only a few studies have done joint modeling of the two modalities: functional MRI (fMRI) and diffusion tensor imaging (DTI). We aim to propose a unified probabilistic framework that combines information from both sources to learn EC using dynamic Bayesian networks (DBNs). DBNs are probabilistic graphical temporal models that learn EC in an exploratory fashion. Specifically, we propose a novel anatomically informed (AI) score that evaluates fitness of a given connectivity structure to both DTI and fMRI data simultaneously. The AI score is employed in structure learning of DBN given the data. Experiments with synthetic-data demonstrate the face validity of structure learning with our AI score over anatomically uninformed counterpart. Moreover, real-data results are cross-validated by performing classification-experiments. EC inferred on real fMRI-DTI datasets is found to be consistent with previous literature and show promising results in light of the AC present as compared to other classically used techniques such as Granger-causality. Multimodal analyses provide a more reliable basis for differentiating brain under abnormal/diseased conditions than the single modality analysis.

Hyperpolarized xenon magnetic resonance of the lung and the brain

NASA Astrophysics Data System (ADS)

Venkatesh, Arvind Krishnamachari

2001-04-01

Hyperpolarized noble gas Magnetic Resonance Imaging (MRI) is a new diagnostic modality that has been used successfully for lung imaging. Xenon is soluble in blood and inhaled xenon is transported to the brain via circulating blood. Xenon also accumulates in the lipid rich white matter of the brain. Hyperpolarized xenon can hence be used as a tissue- sensitive probe of brain function. The goals of this study were to identify the NMR resonances of xenon in the rat brain and evaluate the role of hyperpolarized xenon for brain MRI. We have developed systems to produce sufficient volumes of hyperpolarized xenon for in vivo brain experiments. The specialized instrumentation developed include an apparatus for optical pump-cell manufacture and high purity gas manifolds for filling cells. A hyperpolarized gas delivery system was designed to ventilate small animals with hyperpolarized xenon for transport to the brain. The T1 of xenon dissolved in blood indicates that the lifetime of xenon in the blood is sufficient for significant magnetization to be transferred to distal tissues. A variety of carrier agents for intravenous delivery of hyperpolarized xenon were tested for transport to distal tissues. Using our new gas delivery system, high SNR 129Xe images of rat lungs were obtained. Spectroscopy with hyperpolarized xenon indicated that xenon was transported from the lungs to the blood and tissues with intact magnetization. After preliminary studies that indicated the feasibility for in vivo rat brain studies, experiments were performed with adult rats and young rats with different stages of white matter development. Both in vivo and in vitro experiments showed the prominence of one peak from xenon in the rat brain, which was assigned to brain lipids. Cerebral brain perfusion was calculated from the wash-out of the hyperpolarized xenon signal in the brain. An increase in brain perfusion during maturation was observed. These experiments showed that hyperpolarized xenon MRI can be used to develop unique approaches to studying white matter and gray matter in the brain. Some of the possible applications of hyperpolarized xenon MRI in the brain are clinical diagnosis of white matter diseases, functional MRI (fMRI) and measurement of cerebral blood perfusion.

Using CT Data to Improve the Quantitative Analysis of 18F-FBB PET Neuroimages

PubMed Central

Segovia, Fermín; Sánchez-Vañó, Raquel; Górriz, Juan M.; Ramírez, Javier; Sopena-Novales, Pablo; Testart Dardel, Nathalie; Rodríguez-Fernández, Antonio; Gómez-Río, Manuel

2018-01-01

18F-FBB PET is a neuroimaging modality that is been increasingly used to assess brain amyloid deposits in potential patients with Alzheimer's disease (AD). In this work, we analyze the usefulness of these data to distinguish between AD and non-AD patients. A dataset with 18F-FBB PET brain images from 94 subjects diagnosed with AD and other disorders was evaluated by means of multiple analyses based on t-test, ANOVA, Fisher Discriminant Analysis and Support Vector Machine (SVM) classification. In addition, we propose to calculate amyloid standardized uptake values (SUVs) using only gray-matter voxels, which can be estimated using Computed Tomography (CT) images. This approach allows assessing potential brain amyloid deposits along with the gray matter loss and takes advantage of the structural information provided by most of the scanners used for PET examination, which allow simultaneous PET and CT data acquisition. The results obtained in this work suggest that SUVs calculated according to the proposed method allow AD and non-AD subjects to be more accurately differentiated than using SUVs calculated with standard approaches. PMID:29930505

Hypnosis and imaging of the living human brain.

PubMed

Landry, Mathieu; Raz, Amir

2015-01-01

Over more than two decades, studies using imaging techniques of the living human brain have begun to explore the neural correlates of hypnosis. The collective findings provide a gripping, albeit preliminary, account of the underlying neurobiological mechanisms involved in hypnotic phenomena. While substantial advances lend support to different hypotheses pertaining to hypnotic modulation of attention, control, and monitoring processes, the complex interactions among the many mediating variables largely hinder our ability to isolate robust commonalities across studies. The present account presents a critical integrative synthesis of neuroimaging studies targeting hypnosis as a function of suggestion. Specifically, hypnotic induction without task-specific suggestion is examined, as well as suggestions concerning sensation and perception, memory, and ideomotor response. The importance of carefully designed experiments is highlighted to better tease apart the neural correlates that subserve hypnotic phenomena. Moreover, converging findings intimate that hypnotic suggestions seem to induce specific neural patterns. These observations propose that suggestions may have the ability to target focal brain networks. Drawing on evidence spanning several technological modalities, neuroimaging studies of hypnosis pave the road to a more scientific understanding of a dramatic, yet largely evasive, domain of human behavior.

Retinal microvascular network alterations: potential biomarkers of cerebrovascular and neural diseases.

PubMed

Cabrera DeBuc, Delia; Somfai, Gabor Mark; Koller, Akos

2017-02-01

Increasing evidence suggests that the conditions of retinal microvessels are indicators to a variety of cerebrovascular, neurodegenerative, psychiatric, and developmental diseases. Thus noninvasive visualization of the human retinal microcirculation offers an exceptional opportunity for the investigation of not only the retinal but also cerebral microvasculature. In this review, we show how the conditions of the retinal microvessels could be used to assess the conditions of brain microvessels because the microvascular network of the retina and brain share, in many aspects, standard features in development, morphology, function, and pathophysiology. Recent techniques and imaging modalities, such as optical coherence tomography (OCT), allow more precise visualization of various layers of the retina and its microcirculation, providing a "microscope" to brain microvessels. We also review the potential role of retinal microvessels in the risk identification of cerebrovascular and neurodegenerative diseases. The association between vision problems and cerebrovascular and neurodegenerative diseases, as well as the possible role of retinal microvascular imaging biomarkers in cerebrovascular and neurodegenerative screening, their potentials, and limitations, are also discussed. Copyright © 2017 the American Physiological Society.

Brain abscesses as a metastatic manifestation of strangles: symptomatology and the use of magnetic resonance imaging as a diagnostic aid.

PubMed

Spoormakers, T J P; Ensink, J M; Goehring, L S; Koeman, J P; Ter Braake, F; van der Vlugt-Meijer, R H; van den Belt, A J M

2003-03-01

The occurrence of unexpectedly high numbers of horses with neurological signs during two outbreaks of strangles required prompt in-depth researching of these cases, including the exploration of magnetic resonance imaging (MRI) as a possible diagnostic technique. To describe the case series and assess the usefulness of MRI as an imaging modality for cases suspected of space-occupying lesions in the cerebral cavity. Four cases suspected of suffering from cerebral damage due to Streptococcus equi subsp. equi infection were examined clinically, pathologically, bacteriologically, by clinical chemistry (3 cases) and MRI (2 cases). In one case, MRI findings were compared to images acquired using computer tomography (CT). In all cases, cerebral abscesses positive for Streptococcus equi subsp. equi were found, which explained the clinical signs. Although the lesions could be visualised with CT, MRI images were superior in representing the exact anatomic reality of the soft tissue lesions. The diagnosis of bastard strangles characterised by metastatic brain abscesses was confirmed. MRI appeared to be an excellent tool for the imaging of cerebral lesions in the horse. The high incidence of neurological complications could not be explained but possibly indicated a change in virulence of certain strains of Streptococcus equi subsp. equi. MRI images were very detailed, permitting visualisation of much smaller lesions than demonstrated in this study and this could allow prompt clinical intervention in less advanced cases with a better prognosis. Further, MRI could assist in the surgical treatment of brain abscesses, as has been described earlier for CT.

Warnings and caveats in brain controllability.

PubMed

Tu, Chengyi; Rocha, Rodrigo P; Corbetta, Maurizio; Zampieri, Sandro; Zorzi, Marco; Suweis, S

2018-08-01

A recent article by Gu et al. (Nat. Commun. 6, 2015) proposed to characterize brain networks, quantified using anatomical diffusion imaging, in terms of their "controllability", drawing on concepts and methods of control theory. They reported that brain activity is controllable from a single node, and that the topology of brain networks provides an explanation for the types of control roles that different regions play in the brain. In this work, we first briefly review the framework of control theory applied to complex networks. We then show contrasting results on brain controllability through the analysis of five different datasets and numerical simulations. We find that brain networks are not controllable (in a statistical significant way) by one single region. Additionally, we show that random null models, with no biological resemblance to brain network architecture, produce the same type of relationship observed by Gu et al. between the average/modal controllability and weighted degree. Finally, we find that resting state networks defined with fMRI cannot be attributed specific control roles. In summary, our study highlights some warning and caveats in the brain controllability framework. Copyright © 2018 Elsevier Inc. All rights reserved.

Brain Structure and Function Associated with a History of Sport Concussion: A Multi-Modal Magnetic Resonance Imaging Study.

PubMed

Churchill, Nathan; Hutchison, Michael; Richards, Doug; Leung, General; Graham, Simon; Schweizer, Tom A

2017-02-15

There is growing concern about the potential long-term consequences of sport concussion for young, currently active athletes. However, there remains limited information about brain abnormalities associated with a history of concussion and how they relate to clinical factors. In this study, advanced MRI was used to comprehensively describe abnormalities in brain structure and function associated with a history of sport concussion. Forty-three athletes (21 male, 22 female) were recruited from interuniversity teams at the beginning of the season, including 21 with a history of concussion and 22 without prior concussion; both groups also contained a balanced sample of contact and noncontact sports. Multi-modal MRI was used to evaluate abnormalities in brain structure and function. Athletes with a history of concussion showed frontal decreases in brain volume and blood flow. However, they also demonstrated increased posterior cortical volume and elevated markers of white matter microstructure. A greater number of prior concussions was associated with more extensive decreases in cerebral blood flow and insular volume, whereas recovery time from most recent concussion was correlated with reduced frontotemporal volume. White matter showed limited correlations with clinical factors, predominantly in the anterior corona radiata. This study provides the first evidence of the long-term effects of concussion on gray matter volume, blood flow, and white matter microstructure within a single athlete cohort. This was examined for a mixture of male and female athletes in both contact and noncontact sports, demonstrating the relevance of these findings for the overall sporting community.

Subacute sclerosing panencephalitis resembling Rasmussen’s encephalitis on magnetic resonance imaging

PubMed Central

Jakkani, Ravi Kanth; Sureka, Jyoti; Panwar, Sanuj

2015-01-01

Subacute sclerosing panencephalitis (SSPE) is a rare, slowly progressing but invariably fatal disease that is related to a prior measles virus infection and most commonly affects paediatric patients. Magnetic resonance (MR) imaging is the modality of choice for determining such changes in white matter. SSPE typically demonstrates bilateral but asymmetric periventricular and subcortical white matter involvement. We herein report a rare case of unilateral white matter involvement in a 13-year-old boy with SSPE that closely simulated Rasmussen’s encephalitis. To the best of our knowledge, this is the first report of an atypical presentation on MR imaging in which SSPE was a rare cause of unilateral brain parenchymal involvement in a patient with intractable seizures. PMID:26451061

A hybrid approach of using symmetry technique for brain tumor segmentation.

PubMed

Saddique, Mubbashar; Kazmi, Jawad Haider; Qureshi, Kalim

2014-01-01

Tumor and related abnormalities are a major cause of disability and death worldwide. Magnetic resonance imaging (MRI) is a superior modality due to its noninvasiveness and high quality images of both the soft tissues and bones. In this paper we present two hybrid segmentation techniques and their results are compared with well-recognized techniques in this area. The first technique is based on symmetry and we call it a hybrid algorithm using symmetry and active contour (HASA). In HASA, we take refection image, calculate the difference image, and then apply the active contour on the difference image to segment the tumor. To avoid unimportant segmented regions, we improve the results by proposing an enhancement in the form of the second technique, EHASA. In EHASA, we also take reflection of the original image, calculate the difference image, and then change this image into a binary image. This binary image is mapped onto the original image followed by the application of active contouring to segment the tumor region.

Intrinsic Brain Activity of Cognitively Normal Older Persons Resembles More That of Patients Both with and at Risk for Alzheimer's Disease Than That of Healthy Younger Persons

PubMed Central

Pasquini, Lorenzo; Tonch, Annika; Plant, Claudia; Zherdin, Andrew; Ortner, Marion; Kurz, Alexander; Förstl, Hans; Zimmer, Claus; Grimmer, Timo; Wohlschäger, Afra; Riedl, Valentin

2014-01-01

Abstract In Alzheimer's disease (AD), recent findings suggest that amyloid-β (Aβ)-pathology might start 20–30 years before first cognitive symptoms arise. To account for age as most relevant risk factor for sporadic AD, it has been hypothesized that lifespan intrinsic (i.e., ongoing) activity of hetero-modal brain areas with highest levels of functional connectivity triggers Aβ-pathology. This model induces the simple question whether in older persons without any cognitive symptoms intrinsic activity of hetero-modal areas is more similar to that of symptomatic patients with AD or to that of younger healthy persons. We hypothesize that due to advanced age and therefore potential impact of pre-clinical AD, intrinsic activity of older persons resembles more that of patients than that of younger controls. We tested this hypothesis in younger (ca. 25 years) and older healthy persons (ca. 70 years) and patients with mild cognitive impairment and AD-dementia (ca. 70 years) by the use of resting-state functional magnetic resonance imaging, distinct measures of intrinsic brain activity, and different hierarchical clustering approaches. Independently of applied methods and involved areas, healthy older persons' intrinsic brain activity was consistently more alike that of patients than that of younger controls. Our result provides evidence for larger similarity in intrinsic brain activity between healthy older persons and patients with or at-risk for AD than between older and younger ones, suggesting a significant proportion of pre-clinical AD cases in the group of cognitively normal older people. The observed link of aging and AD with intrinsic brain activity supports the view that lifespan intrinsic activity may contribute critically to the pathogenesis of AD. PMID:24689864

Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure☆

PubMed Central

Frick, Andreas; Gingnell, Malin; Marquand, Andre F.; Howner, Katarina; Fischer, Håkan; Kristiansson, Marianne; Williams, Steven C.R.; Fredrikson, Mats; Furmark, Tomas

2014-01-01

Functional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n = 14) from healthy controls (n = 12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD. PMID:24239689

Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

PubMed

Milz, Patricia; Pascual-Marqui, Roberto D; Lehmann, Dietrich; Faber, Pascal L

2016-05-01

Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the distinct electrophysiological cortical frequency-dependent networks within which they operate.

The risk assessment of Gd2O3:Yb3+/Er3+ nanocomposites as dual-modal nanoprobes for magnetic and fluorescence imaging

NASA Astrophysics Data System (ADS)

Huang, Long; Tian, Xiumei; Liu, Jun; Zheng, Cunjing; Xie, Fukang; Li, Li

2017-02-01

Our group has synthesized Gd2O3:Yb3+/Er3+ nanocomposites as magnetic/fluorescence imaging successfully in the previous study, which exhibit good uniformity and monodispersibility with a mean size of 7.4 nm. However, their systematic risk assessment remains unknown. In this article, the in vitro biocompatibility of the Gd2O3:Yb3+/Er3+ was assessed on the basis of cell viability and apoptosis. In vivo immunotoxicity was evaluated by monitoring the product of reactive oxygen species (ROS), clusters of differentiation (CD) markers, and superoxide dismutase (SOD) in Balb/c mice. No significant differences were found in cell viability, apoptosis, and immunotoxicity between our Gd2O3:Yb3+/Er3+ and gadodiamide which are used commonly in clinical. Few nanoprobes were localized in the phagosomes of the liver, heart, lung, spleen, kidney, brain, and tumor under the transmission electron microscopy (TEM) images. In addition, our products reveal good T1-weighted contrast enhancement of xenografted murine tumor. Therefore, the above results may contribute to the effective application of Gd2O3:Yb3+/Er3+ as molecular imaging contrast agents and dual-modal nanoprobes for cancer detection.

Common Sense in Choice: The Effect of Sensory Modality on Neural Value Representations.

PubMed

Shuster, Anastasia; Levy, Dino J

2018-01-01

Although it is well established that the ventromedial prefrontal cortex (vmPFC) represents value using a common currency across categories of rewards, it is unknown whether the vmPFC represents value irrespective of the sensory modality in which alternatives are presented. In the current study, male and female human subjects completed a decision-making task while their neural activity was recorded using functional magnetic resonance imaging. On each trial, subjects chose between a safe alternative and a lottery, which was presented visually or aurally. A univariate conjunction analysis revealed that the anterior portion of the vmPFC tracks subjective value (SV) irrespective of the sensory modality. Using a novel cross-modality multivariate classifier, we were able to decode auditory value based on visual trials and vice versa. In addition, we found that the visual and auditory sensory cortices, which were identified using functional localizers, are also sensitive to the value of stimuli, albeit in a modality-specific manner. Whereas both primary and higher-order auditory cortices represented auditory SV (aSV), only a higher-order visual area represented visual SV (vSV). These findings expand our understanding of the common currency network of the brain and shed a new light on the interplay between sensory and value information processing.

Common Sense in Choice: The Effect of Sensory Modality on Neural Value Representations

PubMed Central

2018-01-01

Abstract Although it is well established that the ventromedial prefrontal cortex (vmPFC) represents value using a common currency across categories of rewards, it is unknown whether the vmPFC represents value irrespective of the sensory modality in which alternatives are presented. In the current study, male and female human subjects completed a decision-making task while their neural activity was recorded using functional magnetic resonance imaging. On each trial, subjects chose between a safe alternative and a lottery, which was presented visually or aurally. A univariate conjunction analysis revealed that the anterior portion of the vmPFC tracks subjective value (SV) irrespective of the sensory modality. Using a novel cross-modality multivariate classifier, we were able to decode auditory value based on visual trials and vice versa. In addition, we found that the visual and auditory sensory cortices, which were identified using functional localizers, are also sensitive to the value of stimuli, albeit in a modality-specific manner. Whereas both primary and higher-order auditory cortices represented auditory SV (aSV), only a higher-order visual area represented visual SV (vSV). These findings expand our understanding of the common currency network of the brain and shed a new light on the interplay between sensory and value information processing. PMID:29619408

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.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

High-fidelity artifact correction for cone-beam CT imaging of the brain

NASA Astrophysics Data System (ADS)

Sisniega, A.; Zbijewski, W.; Xu, J.; Dang, H.; Stayman, J. W.; Yorkston, J.; Aygun, N.; Koliatsos, V.; Siewerdsen, J. H.

2015-02-01

CT is the frontline imaging modality for diagnosis of acute traumatic brain injury (TBI), involving the detection of fresh blood in the brain (contrast of 30-50 HU, detail size down to 1 mm) in a non-contrast-enhanced exam. A dedicated point-of-care imaging system based on cone-beam CT (CBCT) could benefit early detection of TBI and improve direction to appropriate therapy. However, flat-panel detector (FPD) CBCT is challenged by artifacts that degrade contrast resolution and limit application in soft-tissue imaging. We present and evaluate a fairly comprehensive framework for artifact correction to enable soft-tissue brain imaging with FPD CBCT. The framework includes a fast Monte Carlo (MC)-based scatter estimation method complemented by corrections for detector lag, veiling glare, and beam hardening. The fast MC scatter estimation combines GPU acceleration, variance reduction, and simulation with a low number of photon histories and reduced number of projection angles (sparse MC) augmented by kernel de-noising to yield a runtime of ~4 min per scan. Scatter correction is combined with two-pass beam hardening correction. Detector lag correction is based on temporal deconvolution of the measured lag response function. The effects of detector veiling glare are reduced by deconvolution of the glare response function representing the long range tails of the detector point-spread function. The performance of the correction framework is quantified in experiments using a realistic head phantom on a testbench for FPD CBCT. Uncorrected reconstructions were non-diagnostic for soft-tissue imaging tasks in the brain. After processing with the artifact correction framework, image uniformity was substantially improved, and artifacts were reduced to a level that enabled visualization of ~3 mm simulated bleeds throughout the brain. Non-uniformity (cupping) was reduced by a factor of 5, and contrast of simulated bleeds was improved from ~7 to 49.7 HU, in good agreement with the nominal blood contrast of 50 HU. Although noise was amplified by the corrections, the contrast-to-noise ratio (CNR) of simulated bleeds was improved by nearly a factor of 3.5 (CNR = 0.54 without corrections and 1.91 after correction). The resulting image quality motivates further development and translation of the FPD-CBCT system for imaging of acute TBI.

Advances in PET Imaging of P-Glycoprotein Function at the Blood-Brain Barrier

PubMed Central

2012-01-01

Efflux transporter P-glycoprotein (P-gp) at the blood-brain barrier (BBB) restricts substrate compounds from entering the brain and may thus contribute to pharmacoresistance observed in patient groups with refractory epilepsy and HIV. Altered P-gp function has also been implicated in neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. Positron emission tomography (PET), a molecular imaging modality, has become a promising method to study the role of P-gp at the BBB. The first PET study of P-gp function was conducted in 1998, and during the past 15 years two main categories of P-gp PET tracers have been investigated: tracers that are substrates of P-gp efflux and tracers that are inhibitors of P-gp function. PET, as a noninvasive imaging technique, allows translational research. Examples of this are preclinical investigations of P-gp function before and after administering P-gp modulating drugs, investigations in various animal and disease models, and clinical investigations regarding disease and aging. The objective of the present review is to give an overview of available PET radiotracers for studies of P-gp and to discuss how such studies can be designed. Further, the review summarizes results from PET studies of P-gp function in different central nervous system disorders. PMID:23421673

Statistical validation of brain tumor shape approximation via spherical harmonics for image-guided neurosurgery.

PubMed

Goldberg-Zimring, Daniel; Talos, Ion-Florin; Bhagwat, Jui G; Haker, Steven J; Black, Peter M; Zou, Kelly H

2005-04-01

Surgical planning now routinely uses both two-dimensional (2D) and three-dimensional (3D) models that integrate data from multiple imaging modalities, each highlighting one or more aspects of morphology or function. We performed a preliminary evaluation of the use of spherical harmonics (SH) in approximating the 3D shape and estimating the volume of brain tumors of varying characteristics. Magnetic resonance (MR) images from five patients with brain tumors were selected randomly from our MR-guided neurosurgical practice. Standardized mean square reconstruction errors (SMSRE) by tumor volume were measured. Validation metrics for comparing performances of the SH method against segmented contours (SC) were the dice similarity coefficient (DSC) and standardized Euclidean distance (SED) measure. Tumor volume range was 22,413-85,189 mm3, and range of number of vertices in triangulated models was 3674-6544. At SH approximations with degree of at least 30, SMSRE were within 1.66 x 10(-5) mm(-1). Summary measures yielded a DSC range of 0.89-0.99 (pooled median, 0.97 and significantly >0.7; P < .001) and an SED range of 0.0002-0.0028 (pooled median, 0.0005). 3D shapes of tumors may be approximated by using SH for neurosurgical applications.

Multi-modal Registration for Correlative Microscopy using Image Analogies

PubMed Central

Cao, Tian; Zach, Christopher; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

2014-01-01

Correlative microscopy is a methodology combining the functionality of light microscopy with the high resolution of electron microscopy and other microscopy technologies for the same biological specimen. In this paper, we propose an image registration method for correlative microscopy, which is challenging due to the distinct appearance of biological structures when imaged with different modalities. Our method is based on image analogies and allows to transform images of a given modality into the appearance-space of another modality. Hence, the registration between two different types of microscopy images can be transformed to a mono-modality image registration. We use a sparse representation model to obtain image analogies. The method makes use of corresponding image training patches of two different imaging modalities to learn a dictionary capturing appearance relations. We test our approach on backscattered electron (BSE) scanning electron microscopy (SEM)/confocal and transmission electron microscopy (TEM)/confocal images. We perform rigid, affine, and deformable registration via B-splines and show improvements over direct registration using both mutual information and sum of squared differences similarity measures to account for differences in image appearance. PMID:24387943

Comprehensive approach to image-guided surgery

NASA Astrophysics Data System (ADS)

Peters, Terence M.; Comeau, Roch M.; Kasrai, Reza; St. Jean, Philippe; Clonda, Diego; Sinasac, M.; Audette, Michel A.; Fenster, Aaron

1998-06-01

Image-guided surgery has evolved over the past 15 years from stereotactic planning, where the surgeon planned approaches to intracranial targets on the basis of 2D images presented on a simple workstation, to the use of sophisticated multi- modality 3D image integration in the operating room, with guidance being provided by mechanically, optically or electro-magnetically tracked probes or microscopes. In addition, sophisticated procedures such as thalamotomies and pallidotomies to relieve the symptoms of Parkinson's disease, are performed with the aid of volumetric atlases integrated with the 3D image data. Operations that are performed stereotactically, that is to say via a small burr- hole in the skull, are able to assume that the information contained in the pre-operative imaging study, accurately represents the brain morphology during the surgical procedure. On the other hand, preforming a procedure via an open craniotomy presents a problem. Not only does tissue shift when the operation begins, even the act of opening the skull can cause significant shift of the brain tissue due to the relief of intra-cranial pressure, or the effect of drugs. Means of tracking and correcting such shifts from an important part of the work in the field of image-guided surgery today. One approach has ben through the development of intra-operative MRI imaging systems. We describe an alternative approach which integrates intra-operative ultrasound with pre-operative MRI to track such changes in tissue morphology.

A standardized method for the construction of tracer specific PET and SPECT rat brain templates: validation and implementation of a toolbox.

PubMed

Vállez Garcia, David; Casteels, Cindy; Schwarz, Adam J; Dierckx, Rudi A J O; Koole, Michel; Doorduin, Janine

2015-01-01

High-resolution anatomical image data in preclinical brain PET and SPECT studies is often not available, and inter-modality spatial normalization to an MRI brain template is frequently performed. However, this procedure can be challenging for tracers where substantial anatomical structures present limited tracer uptake. Therefore, we constructed and validated strain- and tracer-specific rat brain templates in Paxinos space to allow intra-modal registration. PET [18F]FDG, [11C]flumazenil, [11C]MeDAS, [11C]PK11195 and [11C]raclopride, and SPECT [99mTc]HMPAO brain scans were acquired from healthy male rats. Tracer-specific templates were constructed by averaging the scans, and by spatial normalization to a widely used MRI-based template. The added value of tracer-specific templates was evaluated by quantification of the residual error between original and realigned voxels after random misalignments of the data set. Additionally, the impact of strain differences, disease uptake patterns (focal and diffuse lesion), and the effect of image and template size on the registration errors were explored. Mean registration errors were 0.70 ± 0.32 mm for [18F]FDG (n = 25), 0.23 ± 0.10mm for [11C]flumazenil (n = 13), 0.88 ± 0.20 mm for [11C]MeDAS (n = 15), 0.64 ± 0.28 mm for [11C]PK11195 (n = 19), 0.34 ± 0.15 mm for [11C]raclopride (n = 6), and 0.40 ± 0.13 mm for [99mTc]HMPAO (n = 15). These values were smallest with tracer-specific templates, when compared to the use of [18F]FDG as reference template (p<0.001). Additionally, registration errors were smallest with strain-specific templates (p<0.05), and when images and templates had the same size (p ≤ 0.001). Moreover, highest registration errors were found for the focal lesion group (p<0.005) and the diffuse lesion group (p = n.s.). In the voxel-based analysis, the reported coordinates of the focal lesion model are consistent with the stereotaxic injection procedure. The use of PET/SPECT strain- and tracer-specific templates allows accurate registration of functional rat brain data, independent of disease specific uptake patterns and with registration error below spatial resolution of the cameras. The templates and the SAMIT package will be freely available for the research community [corrected].

A Standardized Method for the Construction of Tracer Specific PET and SPECT Rat Brain Templates: Validation and Implementation of a Toolbox

PubMed Central

Vállez Garcia, David; Casteels, Cindy; Schwarz, Adam J.; Dierckx, Rudi A. J. O.; Koole, Michel; Doorduin, Janine

2015-01-01

High-resolution anatomical image data in preclinical brain PET and SPECT studies is often not available, and inter-modality spatial normalization to an MRI brain template is frequently performed. However, this procedure can be challenging for tracers where substantial anatomical structures present limited tracer uptake. Therefore, we constructed and validated strain- and tracer-specific rat brain templates in Paxinos space to allow intra-modal registration. PET [18F]FDG, [11C]flumazenil, [11C]MeDAS, [11C]PK11195 and [11C]raclopride, and SPECT [99mTc]HMPAO brain scans were acquired from healthy male rats. Tracer-specific templates were constructed by averaging the scans, and by spatial normalization to a widely used MRI-based template. The added value of tracer-specific templates was evaluated by quantification of the residual error between original and realigned voxels after random misalignments of the data set. Additionally, the impact of strain differences, disease uptake patterns (focal and diffuse lesion), and the effect of image and template size on the registration errors were explored. Mean registration errors were 0.70±0.32mm for [18F]FDG (n = 25), 0.23±0.10mm for [11C]flumazenil (n = 13), 0.88±0.20 mm for [11C]MeDAS (n = 15), 0.64±0.28mm for [11C]PK11195 (n = 19), 0.34±0.15mm for [11C]raclopride (n = 6), and 0.40±0.13mm for [99mTc]HMPAO (n = 15). These values were smallest with tracer-specific templates, when compared to the use of [18F]FDG as reference template (p&0.001). Additionally, registration errors were smallest with strain-specific templates (p&0.05), and when images and templates had the same size (p≤0.001). Moreover, highest registration errors were found for the focal lesion group (p&0.005) and the diffuse lesion group (p = n.s.). In the voxel-based analysis, the reported coordinates of the focal lesion model are consistent with the stereotaxic injection procedure. The use of PET/SPECT strain- and tracer-specific templates allows accurate registration of functional rat brain data, independent of disease specific uptake patterns and with registration error below spatial resolution of the cameras. The templates and the SAMIT package will be freely available for the research community. PMID:25823005

Multimodal Image Alignment via Linear Mapping between Feature Modalities.

PubMed

Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

2017-01-01

We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies.

PubMed

Heggdal, Peder O Laugen; Brännström, Jonas; Aarstad, Hans Jørgen; Vassbotn, Flemming S; Specht, Karsten

2016-02-01

This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss. A literature search was performed in PubMed. Search criterions were peer reviewed original research papers in English completed by the 11th of March 2015. Twelve studies were found to use neuroimaging in subjects with unilateral hearing loss. An additional five papers not identified by the literature search were provided by a reviewer. Thus, a total of 17 studies were included in the review. Four different neuroimaging methods were used in these studies: Functional magnetic resonance imaging (fMRI) (n = 11), diffusion tensor imaging (DTI) (n = 4), T1/T2 volumetric images (n = 2), magnetic resonance spectroscopy (MRS) (n = 1). One study utilized two imaging methods (fMRI and T1 volumetric images). Neuroimaging techniques could provide valuable information regarding the effects of unilateral hearing loss on both auditory and non-auditory performance. fMRI-studies showing a bilateral BOLD-response in patients with unilateral hearing loss have not yet been followed by DTI studies confirming their microstructural correlates. In addition, the review shows that an auditory modality-specific deficit could affect multi-modal brain regions and their connections. Copyright © 2015 Elsevier B.V. All rights reserved.

Resolution improvement in positron emission tomography using anatomical Magnetic Resonance Imaging.

PubMed

Chu, Yong; Su, Min-Ying; Mandelkern, Mark; Nalcioglu, Orhan

2006-08-01

An ideal imaging system should provide information with high-sensitivity, high spatial, and temporal resolution. Unfortunately, it is not possible to satisfy all of these desired features in a single modality. In this paper, we discuss methods to improve the spatial resolution in positron emission imaging (PET) using a priori information from Magnetic Resonance Imaging (MRI). Our approach uses an image restoration algorithm based on the maximization of mutual information (MMI), which has found significant success for optimizing multimodal image registration. The MMI criterion is used to estimate the parameters in the Sharpness-Constrained Wiener filter. The generated filter is then applied to restore PET images of a realistic digital brain phantom. The resulting restored images show improved resolution and better signal-to-noise ratio compared to the interpolated PET images. We conclude that a Sharpness-Constrained Wiener filter having parameters optimized from a MMI criterion may be useful for restoring spatial resolution in PET based on a priori information from correlated MRI.

Automatic delineation of brain regions on MRI and PET images from the pig.

PubMed

Villadsen, Jonas; Hansen, Hanne D; Jørgensen, Louise M; Keller, Sune H; Andersen, Flemming L; Petersen, Ida N; Knudsen, Gitte M; Svarer, Claus

2018-01-15

The increasing use of the pig as a research model in neuroimaging requires standardized processing tools. For example, extraction of regional dynamic time series from brain PET images requires parcellation procedures that benefit from being automated. Manual inter-modality spatial normalization to a MRI atlas is operator-dependent, time-consuming, and can be inaccurate with lack of cortical radiotracer binding or skull uptake. A parcellated PET template that allows for automatic spatial normalization to PET images of any radiotracer. MRI and [ 11 C]Cimbi-36 PET scans obtained in sixteen pigs made the basis for the atlas. The high resolution MRI scans allowed for creation of an accurately averaged MRI template. By aligning the within-subject PET scans to their MRI counterparts, an averaged PET template was created in the same space. We developed an automatic procedure for spatial normalization of the averaged PET template to new PET images and hereby facilitated transfer of the atlas regional parcellation. Evaluation of the automatic spatial normalization procedure found the median voxel displacement to be 0.22±0.08mm using the MRI template with individual MRI images and 0.92±0.26mm using the PET template with individual [ 11 C]Cimbi-36 PET images. We tested the automatic procedure by assessing eleven PET radiotracers with different kinetics and spatial distributions by using perfusion-weighted images of early PET time frames. We here present an automatic procedure for accurate and reproducible spatial normalization and parcellation of pig PET images of any radiotracer with reasonable blood-brain barrier penetration. Copyright © 2017 Elsevier B.V. All rights reserved.

Magnetic resonance imaging of the brain in epileptic adult patients: experience in Ramathibodi Hospital.

PubMed

Solosrungruang, Anusorn; Laothamatas, Jiraporn; Chinwarun, Yotin

2007-04-01

The purpose of the present study was to classify the imaging structural abnormalities of epileptic adult patients referred for magnetic resonance imaging (MR imaging) of the brain at Ramathibodi Hospital and to correlate with the clinical data and EEG. MR imaging of 91 adult epileptic patients (age ranging from 15-85 years old with an average of 36.90 years old) were retrospectively reviewed and classified into eight groups according to etiologies. Then clinical data and EEG correlations were analyzed using the Kappa analysis. All of the MR imaging of the brain were performed at Ramathibodi Hospital from January 2001 to December 2002. Secondary generalized tonic clonic seizure was the most common clinical presenting seizure type. Extra temporal lobe epilepsy was the most common clinical diagnosis. Of the thirty-three patients who underwent EEG before performing MR imaging, 17 had normal EEG From MR imaging, temporal lobe lesion was the main affected location and mesial temporal sclerosis (MTS) was the most common cause of the epilepsy in patients. For age group classification, young adult (15-34 years old) and adult (35-64 years old) age groups, MTS was the most common etiology of epilepsy with cortical dysplasia being the second most common cause for the first group and vascular disease for the latter group. For the older age group (> 64 years old), vascular disease and idiopathic cause were equally common etiologies. MRI, EEG findings, and clinical data were all concordant with statistical significance. MRI is the non-invasive modality of choice for evaluation of the epileptic patients. The result is concordant with the clinical and EEG findings. It can detect and localize the structural abnormality accurately and is useful in the treatment planning.

Cone-beam CT of traumatic brain injury using statistical reconstruction with a post-artifact-correction noise model

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Sisniega, A.; Xu, J.; Zbijewski, W.; Yorkston, J.; Aygun, N.; Koliatsos, V.; Siewerdsen, J. H.

2015-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered back-projection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

Introduction and overview of the special issue "Brain imaging and aging": The new era of neuroimaging in aging research.

PubMed

Furukawa, Katsutoshi; Ishiki, Aiko; Tomita, Naoki; Onaka, Yuta; Saito, Haruka; Nakamichi, Tomoko; Hara, Kazunari; Kusano, Yusuke; Ebara, Masamune; Arata, Yuki; Sakota, Miku; Miyazawa, Isabelle; Totsune, Tomoko; Okinaga, Shoji; Okamura, Nobuyuki; Kudo, Yukitsuka; Arai, Hiroyuki

2016-09-01

It is well known that the brain is one of the organs particularly affected by aging in terms of function, relative to the gastrointestinal tract and liver, which exhibit less functional decline. There is also a wide range of age-related neurological disorders such as stroke, Alzheimer's disease, and Parkinson's disease. Therefore, it is very important to understand the relationship between functional age-related change and neurological dysfunction. Neuroimaging techniques including magnetic resonance imaging and positron emission tomography have been significantly improved over recent years. Many physicians and researchers have investigated various mechanisms of age-related cerebral change and associated neurological disorders using neuroimaging techniques. In this special issue of Ageing Research Reviews, we focus on cerebral- and neuro-imaging, which are a range of tools used to visualize structure, functions, and pathogenic molecules in the nervous system. In addition, we summarize several review articles about the history, present values, and future perspectives of neuroimaging modalities. Copyright © 2016 Elsevier B.V. All rights reserved.

Three dimensional image correlation of CT, MR, and PET studies in radiotherapy treatment planning of brain tumors.

PubMed

Schad, L R; Boesecke, R; Schlegel, W; Hartmann, G H; Sturm, V; Strauss, L G; Lorenz, W J

1987-01-01

A treatment planning system for stereotactic convergent beam irradiation of deeply localized brain tumors is reported. The treatment technique consists of several moving field irradiations in noncoplanar planes at a linear accelerator facility. Using collimated narrow beams, a high concentration of dose within small volumes with a dose gradient of 10-15%/mm was obtained. The dose calculation was based on geometrical information of multiplanar CT or magnetic resonance (MR) imaging data. The patient's head was fixed in a stereotactic localization system, which is usable at CT, MR, and positron emission tomography (PET) installations. Special computer programs for correction of the geometrical MR distortions allowed a precise correlation of the different imaging modalities. The therapist can use combinations of CT, MR, and PET data for defining target volume. For instance, the superior soft tissue contrast of MR coupled with the metabolic features of PET may be a useful addition in the radiation treatment planning process. Furthermore, other features such as calculated dose distribution to critical structures can also be transferred from one set of imaging data to another and can be displayed as three-dimensional shaded structures.

MRI measurements of Blood-Brain Barrier function in dementia: A review of recent studies.

PubMed

Raja, Rajikha; Rosenberg, Gary A; Caprihan, Arvind

2018-05-15

Blood-brain barrier (BBB) separates the systemic circulation and the brain, regulating transport of most molecules to protect the brain microenvironment. Multiple structural and functional components preserve the integrity of the BBB. Several imaging modalities are available to study disruption of the BBB. However, the subtle changes in BBB leakage that occurs in vascular cognitive impairment and Alzheimer's disease have been less well studied. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is the most widely adopted non-invasive imaging technique for evaluating BBB breakdown. It is used as a significant marker for a wide variety of diseases with large permeability leaks, such as brain tumors and multiple sclerosis, to more subtle disruption in chronic vascular disease and dementia. DCE-MRI analysis of BBB includes both model-free parameters and quantitative parameters using pharmacokinetic modelling. We review MRI studies of BBB breakdown in dementia. The challenges in measuring subtle BBB changes and the state of the art techniques are initially examined. Subsequently, a systematic review comparing methodologies from recent in-vivo MRI studies is presented. Various factors related to subtle BBB permeability measurement such as DCE-MRI acquisition parameters, arterial input assessment, T 1 mapping and data analysis methods are reviewed with the focus on finding the optimal technique. Finally, the reported BBB permeability values in dementia are compared across different studies and across various brain regions. We conclude that reliable measurement of low-level BBB permeability across sites remains a difficult problem and a standardization of the methodology for both data acquisition and quantitative analysis is required. This article is part of the Special Issue entitled 'Cerebral Ischemia'. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of FUS-Tissue Interactions In Vivo

NASA Astrophysics Data System (ADS)

Haritonova, Alyona V.

Focused ultrasound (FUS) has been proposed for a variety of minimally invasive therapeutic applications, including tumor ablation, neuromodulation, targeted drug delivery and blood brain barrier opening. To date, FUS beams have been primarily monitored through MR and ultrasound diagnostic imaging modalities. The recent introduction of real-time dual-mode ultrasound array (DMUA) systems offers a new paradigm for the guidance of therapeutic focused ultrasound. The DMUA approach allows for inherent registration between the therapeutic and imaging coordinate systems. In this thesis we investigated the use of ultrasound-based thermography to assess FUS-tissue interactions. Specifically, we focused on two aspects of image-guided therapy: 1) monitoring and localization of FUS-tissue interactions, and 2) tissue damage assessment. Towards this end, we presented first experimental results of ultrasound-guided transcranial FUS in a rat brain, both ex vivo and in vivo. DMUA imaging was used to monitor and localize FUS-tissue thermal interactions in real-time. The transcranial echo data allowed for a reliable estimation of temperature change in brain tissue, which had never been done before using ultrasound image guidance. Despite some measurable distortion and loss in focusing gain, transcranial FUS beams at 3.2 MHz were localized axially and laterally. This confirms the results obtained using DMUA-based transcranial ultrasound thermography. A high degree of focusing with the DMUA was then successfully leveraged to perform localized tissue damage assessment in both ex vivo and in vivo. The experimental results presented in this thesis demonstrate some of the unique aspects of image guidance using DMUAs, especially when FUS is subject to significant distortions as in transcranial applications.

Evidence of Neurobiological Changes in the Presymptomatic PINK1 Knockout Rat.

PubMed

Ferris, Craig F; Morrison, Thomas R; Iriah, Sade; Malmberg, Samantha; Kulkarni, Praveen; Hartner, Jochen C; Trivedi, Malav

2018-01-01

Genetic models of Parkinson's disease (PD) coupled with advanced imaging techniques can elucidate neurobiological disease progression, and can help identify early biomarkers before clinical signs emerge. PTEN-induced putative kinase 1 (PINK1) helps protect neurons from mitochondrial dysfunction, and a mutation in the associated gene is a risk factor for recessive familial PD. The PINK1 knockout (KO) rat is a novel model for familial PD that has not been neuroradiologically characterized for alterations in brain structure/function, alongside behavior, prior to 4 months of age. To identify biomarkers of presymptomatic PD in the PINK1 -/- rat at 3 months using magnetic resonance imaging techniques. At postnatal weeks 12-13; one month earlier than previously reported signs of motor and cognitive dysfunction, this study combined imaging modalities, including assessment of quantitative anisotropy across 171 individual brain areas using an annotated MRI rat brain atlas to identify sites of gray matter alteration between wild-type and PINK1 -/- rats. The olfactory system, hypothalamus, thalamus, nucleus accumbens, and cerebellum showed differences in anisotropy between experimental groups. Molecular analyses revealed reduced levels of glutathione, ATP, and elevated oxidative stress in the substantia nigra, striatum and deep cerebellar nuclei. Mitochondrial genes encoding proteins in Complex IV, along with mRNA levels associated with mitochondrial function and genes involved in glutathione synthesis were reduced. Differences in brain structure did not align with any cognitive or motor impairment. These data reveal early markers, and highlight novel brain regions involved in the pathology of PD in the PINK1 -/- rat before behavioral dysfunction occurs.

Efficacy of texture, shape, and intensity features for robust posterior-fossa tumor segmentation in MRI

NASA Astrophysics Data System (ADS)

Ahmed, S.; Iftekharuddin, K. M.; Ogg, R. J.; Laningham, F. H.

2009-02-01

Our previous works suggest that fractal-based texture features are very useful for detection, segmentation and classification of posterior-fossa (PF) pediatric brain tumor in multimodality MRI. In this work, we investigate and compare efficacy of our texture features such as fractal and multifractional Brownian motion (mBm), and intensity along with another useful level-set based shape feature in PF tumor segmentation. We study feature selection and ranking using Kullback -Leibler Divergence (KLD) and subsequent tumor segmentation; all in an integrated Expectation Maximization (EM) framework. We study the efficacy of all four features in both multimodality as well as disparate MRI modalities such as T1, T2 and FLAIR. Both KLD feature plots and information theoretic entropy measure suggest that mBm feature offers the maximum separation between tumor and non-tumor tissues in T1 and FLAIR MRI modalities. The same metrics show that intensity feature offers the maximum separation between tumor and non-tumor tissue in T2 MRI modality. The efficacies of these features are further validated in segmenting PF tumor using both single modality and multimodality MRI for six pediatric patients with over 520 real MR images.

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

PubMed

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

Incidental Findings in Imaging Research: Evaluating Incidence, Benefit and Burden

PubMed Central

Orme, Nicholas M.; Fletcher, Joel G.; Siddiki, Hassan A.; Harmsen, W. Scott; O’Byrne, Megan M.; Port, John D.; Tremaine, William J.; Pitot, Henry C.; McFarland, Beth; Robinson, Marguerite E.; Koenig, Barabara A.; King, Bernard F.; Wolf, Susan M.

2013-01-01

Context Little information exists concerning the frequency of clinically significant incidental findings (IFs) identified in the course of imaging research across a broad spectrum of imaging modalities and body regions. Objective To estimate the frequency with which research imaging IFs generate further clinical action, and the medical benefit/burden of identifying these IFs. Design, Setting, and Participants Retrospective review of subjects undergoing a research imaging exam that was interpreted by a radiologist for IFs in the first quarter of 2004, with 3-year clinical follow-up. An expert panel reviewed IFs generating clinical action to determine medical benefit/burden based on predefined criteria. Main Outcome Measures Frequency of (1) IFs that generated further clinical action by modality, body part, age, gender, and (2) IFs resulting in clear medical benefit or burden. Results 1376 patients underwent 1426 research imaging studies. 40% (567/1426) of exams had at least one IF (1055 total). Risk of an IF increased significantly by age (OR=1.5; [1.4–1.7=95% C.I.] per decade increase). Abdominopelvic CT generated more IFs than other exams (OR=18.9 compared with ultrasound; 9.2% with subsequent clinical action), with CT Thorax and MR brain next (OR=11.9 and 5.9; 2.8% and 2.2% with action, respectively). Overall 6.2% of exams (35/567) with an IF generated clinical action, resulting in clear medical benefit in 1.1% (6/567) and clear medical burden in 0.5% (3/567). In most instances, medical benefit/burden was unclear (4.6%; 26/567). Conclusions The frequency of IFs in imaging research exams varies significantly by imaging modality, body region and age. Research imaging studies at high risk for generating IFs can be identified. Routine evaluation of research images by radiologists may result in identification of IFs in a substantial number of cases and subsequent clinical action to address them in much smaller number. Such clinical action can result in medical benefit to a small number of patients. PMID:20876402

Guidelines for imaging retinoblastoma: imaging principles and MRI standardization.

PubMed

de Graaf, Pim; Göricke, Sophia; Rodjan, Firazia; Galluzzi, Paolo; Maeder, Philippe; Castelijns, Jonas A; Brisse, Hervé J

2012-01-01

Retinoblastoma is the most common intraocular tumor in children. The diagnosis is usually established by the ophthalmologist on the basis of fundoscopy and US. Together with US, high-resolution MRI has emerged as an important imaging modality for pretreatment assessment, i.e. for diagnostic confirmation, detection of local tumor extent, detection of associated developmental malformation of the brain and detection of associated intracranial primitive neuroectodermal tumor (trilateral retinoblastoma). Minimum requirements for pretreatment diagnostic evaluation of retinoblastoma or mimicking lesions are presented, based on consensus among members of the European Retinoblastoma Imaging Collaboration (ERIC). The most appropriate techniques for imaging in a child with leukocoria are reviewed. CT is no longer recommended. Implementation of a standardized MRI protocol for retinoblastoma in clinical practice may benefit children worldwide, especially those with hereditary retinoblastoma, since a decreased use of CT reduces the exposure to ionizing radiation.

Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients

PubMed Central

Onofrey, John A.; Staib, Lawrence H.; Papademetris, Xenophon

2015-01-01

This paper describes a framework for learning a statistical model of non-rigid deformations induced by interventional procedures. We make use of this learned model to perform constrained non-rigid registration of pre-procedural and post-procedural imaging. We demonstrate results applying this framework to non-rigidly register post-surgical computed tomography (CT) brain images to pre-surgical magnetic resonance images (MRIs) of epilepsy patients who had intra-cranial electroencephalography electrodes surgically implanted. Deformations caused by this surgical procedure, imaging artifacts caused by the electrodes, and the use of multi-modal imaging data make non-rigid registration challenging. Our results show that the use of our proposed framework to constrain the non-rigid registration process results in significantly improved and more robust registration performance compared to using standard rigid and non-rigid registration methods. PMID:26900569

Design analysis of an MPI human functional brain scanner

PubMed Central

Mason, Erica E.; Cooley, Clarissa Z.; Cauley, Stephen F.; Griswold, Mark A.; Conolly, Steven M.; Wald, Lawrence L.

2017-01-01

MPI’s high sensitivity makes it a promising modality for imaging brain function. Functional contrast is proposed based on blood SPION concentration changes due to Cerebral Blood Volume (CBV) increases during activation, a mechanism utilized in fMRI studies. MPI offers the potential for a direct and more sensitive measure of SPION concentration, and thus CBV, than fMRI. As such, fMPI could surpass fMRI in sensitivity, enhancing the scientific and clinical value of functional imaging. As human-sized MPI systems have not been attempted, we assess the technical challenges of scaling MPI from rodent to human brain. We use a full-system MPI simulator to test arbitrary hardware designs and encoding practices, and we examine tradeoffs imposed by constraints that arise when scaling to human size as well as safety constraints (PNS and central nervous system stimulation) not considered in animal scanners, thereby estimating spatial resolutions and sensitivities achievable with current technology. Using a projection FFL MPI system, we examine coil hardware options and their implications for sensitivity and spatial resolution. We estimate that an fMPI brain scanner is feasible, although with reduced sensitivity (20×) and spatial resolution (5×) compared to existing rodent systems. Nonetheless, it retains sufficient sensitivity and spatial resolution to make it an attractive future instrument for studying the human brain; additional technical innovations can result in further improvements. PMID:28752130

Patterns of Individual Variation in Visual Pathway Structure and Function in the Sighted and Blind

PubMed Central

Datta, Ritobrato; Benson, Noah C.; Prasad, Sashank; Jacobson, Samuel G.; Cideciyan, Artur V.; Bridge, Holly; Watkins, Kate E.; Butt, Omar H.; Dain, Aleksandra S.; Brandes, Lauren; Gennatas, Efstathios D.

2016-01-01

Many structural and functional brain alterations accompany blindness, with substantial individual variation in these effects. In normally sighted people, there is correlated individual variation in some visual pathway structures. Here we examined if the changes in brain anatomy produced by blindness alter the patterns of anatomical variation found in the sighted. We derived eight measures of central visual pathway anatomy from a structural image of the brain from 59 sighted and 53 blind people. These measures showed highly significant differences in mean size between the sighted and blind cohorts. When we examined the measurements across individuals within each group we found three clusters of correlated variation, with V1 surface area and pericalcarine volume linked, and independent of the thickness of V1 cortex. These two clusters were in turn relatively independent of the volumes of the optic chiasm and lateral geniculate nucleus. This same pattern of variation in visual pathway anatomy was found in the sighted and the blind. Anatomical changes within these clusters were graded by the timing of onset of blindness, with those subjects with a post-natal onset of blindness having alterations in brain anatomy that were intermediate to those seen in the sighted and congenitally blind. Many of the blind and sighted subjects also contributed functional MRI measures of cross-modal responses within visual cortex, and a diffusion tensor imaging measure of fractional anisotropy within the optic radiations and the splenium of the corpus callosum. We again found group differences between the blind and sighted in these measures. The previously identified clusters of anatomical variation were also found to be differentially related to these additional measures: across subjects, V1 cortical thickness was related to cross-modal activation, and the volume of the optic chiasm and lateral geniculate was related to fractional anisotropy in the visual pathway. Our findings show that several of the structural and functional effects of blindness may be reduced to a smaller set of dimensions. It also seems that the changes in the brain that accompany blindness are on a continuum with normal variation found in the sighted. PMID:27812129

WE-H-206-03: Promises and Challenges of Benchtop X-Ray Fluorescence CT (XFCT) for Quantitative in Vivo Imaging

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

Cho, S.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

WE-H-206-01: Photoacoustic Tomography: Multiscale Imaging From Organelles to Patients by Ultrasonically Beating the Optical Diffusion Limit

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

Wang, L.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

WE-H-206-00: Advances in Preclinical Imaging

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

NONE

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

Multi-Modality Phantom Development

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

Huber, Jennifer S.; Peng, Qiyu; Moses, William W.

2009-03-20

Multi-modality imaging has an increasing role in the diagnosis and treatment of a large number of diseases, particularly if both functional and anatomical information are acquired and accurately co-registered. Hence, there is a resulting need for multi modality phantoms in order to validate image co-registration and calibrate the imaging systems. We present our PET-ultrasound phantom development, including PET and ultrasound images of a simple prostate phantom. We use agar and gelatin mixed with a radioactive solution. We also present our development of custom multi-modality phantoms that are compatible with PET, transrectal ultrasound (TRUS), MRI and CT imaging. We describe bothmore » our selection of tissue mimicking materials and phantom construction procedures. These custom PET-TRUS-CT-MRI prostate phantoms use agargelatin radioactive mixtures with additional contrast agents and preservatives. We show multi-modality images of these custom prostate phantoms, as well as discuss phantom construction alternatives. Although we are currently focused on prostate imaging, this phantom development is applicable to many multi-modality imaging applications.« less

Multimodal Imaging of the Normal Eye.

PubMed

Kawali, Ankush; Pichi, Francesco; Avadhani, Kavitha; Invernizzi, Alessandro; Hashimoto, Yuki; Mahendradas, Padmamalini

2017-10-01

Multimodal imaging is the concept of "bundling" images obtained from various imaging modalities, viz., fundus photograph, fundus autofluorescence imaging, infrared (IR) imaging, simultaneous fluorescein and indocyanine angiography, optical coherence tomography (OCT), and, more recently, OCT angiography. Each modality has its pros and cons as well as its limitations. Combination of multiple imaging techniques will overcome their individual weaknesses and give a comprehensive picture. Such approach helps in accurate localization of a lesion and understanding the pathology in posterior segment. It is important to know imaging of normal eye before one starts evaluating pathology. This article describes multimodal imaging modalities in detail and discusses healthy eye features as seen on various imaging modalities mentioned above.

Contemporary imaging of mild TBI: the journey toward diffusion tensor imaging to assess neuronal damage.

PubMed

Fox, W Christopher; Park, Min S; Belverud, Shawn; Klugh, Arnett; Rivet, Dennis; Tomlin, Jeffrey M

2013-04-01

To follow the progression of neuroimaging as a means of non-invasive evaluation of mild traumatic brain injury (mTBI) in order to provide recommendations based on reproducible, defined imaging findings. A comprehensive literature review and analysis of contemporary published articles was performed to study the progression of neuroimaging findings as a non-invasive 'biomarker' for mTBI. Multiple imaging modalities exist to support the evaluation of patients with mTBI, including ultrasound (US), computed tomography (CT), single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI). These techniques continue to evolve with the development of fractional anisotropy (FA), fiber tractography (FT), and diffusion tensor imaging (DTI). Modern imaging techniques, when applied in the appropriate clinical setting, may serve as a valuable tool for diagnosis and management of patients with mTBI. An understanding of modern neuroanatomical imaging will enhance our ability to analyse injury and recognize the manifestations of mTBI.

MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

PubMed Central

Fei, Baowei; Yang, Xiaofeng; Nye, Jonathon A.; Aarsvold, John N.; Raghunath, Nivedita; Cervo, Morgan; Stark, Rebecca; Meltzer, Carolyn C.; Votaw, John R.

2012-01-01

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [11C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR/PET. PMID:23039679

Silent music reading: auditory imagery and visuotonal modality transfer in singers and non-singers.

PubMed

Hoppe, Christian; Splittstößer, Christoph; Fliessbach, Klaus; Trautner, Peter; Elger, Christian E; Weber, Bernd

2014-11-01

In daily life, responses are often facilitated by anticipatory imagery of expected targets which are announced by associated stimuli from different sensory modalities. Silent music reading represents an intriguing case of visuotonal modality transfer in working memory as it induces highly defined auditory imagery on the basis of presented visuospatial information (i.e. musical notes). Using functional MRI and a delayed sequence matching-to-sample paradigm, we compared brain activations during retention intervals (10s) of visual (VV) or tonal (TT) unimodal maintenance versus visuospatial-to-tonal modality transfer (VT) tasks. Visual or tonal sequences were comprised of six elements, white squares or tones, which were low, middle, or high regarding vertical screen position or pitch, respectively (presentation duration: 1.5s). For the cross-modal condition (VT, session 3), the visuospatial elements from condition VV (session 1) were re-defined as low, middle or high "notes" indicating low, middle or high tones from condition TT (session 2), respectively, and subjects had to match tonal sequences (probe) to previously presented note sequences. Tasks alternately had low or high cognitive load. To evaluate possible effects of music reading expertise, 15 singers and 15 non-musicians were included. Scanner task performance was excellent in both groups. Despite identity of applied visuospatial stimuli, visuotonal modality transfer versus visual maintenance (VT>VV) induced "inhibition" of visual brain areas and activation of primary and higher auditory brain areas which exceeded auditory activation elicited by tonal stimulation (VT>TT). This transfer-related visual-to-auditory activation shift occurred in both groups but was more pronounced in experts. Frontoparietal areas were activated by higher cognitive load but not by modality transfer. The auditory brain showed a potential to anticipate expected auditory target stimuli on the basis of non-auditory information and sensory brain activation rather mirrored expectation than stimulation. Silent music reading probably relies on these basic neurocognitive mechanisms. Copyright © 2014 Elsevier Inc. All rights reserved.

Dual modal ultra-bright nanodots with aggregation-induced emission and gadolinium-chelation for vascular integrity and leakage detection.

PubMed

Feng, Guangxue; Li, Jackson Liang Yao; Claser, Carla; Balachander, Akhila; Tan, Yingrou; Goh, Chi Ching; Kwok, Immanuel Weng Han; Rénia, Laurent; Tang, Ben Zhong; Ng, Lai Guan; Liu, Bin

2018-01-01

The study of blood brain barrier (BBB) functions is important for neurological disorder research. However, the lack of suitable tools and methods has hampered the progress of this field. Herein, we present a hybrid nanodot strategy, termed AIE-Gd dots, comprising of a fluorogen with aggregation-induced emission (AIE) characteristics as the core to provide bright and stable fluorescence for optical imaging, and gadolinium (Gd) for accurate quantification of vascular leakage via inductively-coupled plasma mass spectrometry (ICP-MS). In this report, we demonstrate that AIE-Gd dots enable direct visualization of brain vascular networks under resting condition, and that they form localized punctate aggregates and accumulate in the brain tissue during experimental cerebral malaria, indicative of hemorrhage and BBB malfunction. With its superior detection sensitivity and multimodality, we hereby propose that AIE-Gd dots can serve as a better alternative to Evans blue for visualization and quantification of changes in brain barrier functions. Copyright © 2017. Published by Elsevier Ltd.

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.

Fiducial marker for correlating images

DOEpatents

Miller, Lisa Marie [Rocky Point, NY; Smith, Randy J [Wading River, NY; Warren, John B [Port Jefferson, NY; Elliott, Donald [Hampton Bays, NY

2011-06-21

The invention relates to a fiducial marker having a marking grid that is used to correlate and view images produced by different imaging modalities or different imaging and viewing modalities. More specifically, the invention relates to the fiducial marking grid that has a grid pattern for producing either a viewing image and/or a first analytical image that can be overlaid with at least one other second analytical image in order to view a light path or to image different imaging modalities. Depending on the analysis, the grid pattern has a single layer of a certain thickness or at least two layers of certain thicknesses. In either case, the grid pattern is imageable by each imaging or viewing modality used in the analysis. Further, when viewing a light path, the light path of the analytical modality cannot be visualized by viewing modality (e.g., a light microscope objective). By correlating these images, the ability to analyze a thin sample that is, for example, biological in nature but yet contains trace metal ions is enhanced. Specifically, it is desired to analyze both the organic matter of the biological sample and the trace metal ions contained within the biological sample without adding or using extrinsic labels or stains.

Cross-Modal Multivariate Pattern Analysis

PubMed Central

Meyer, Kaspar; Kaplan, Jonas T.

2011-01-01

Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6. Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog? In two previous studies7,8, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices. PMID:22105246

Concomitant fractional anisotropy and volumetric abnormalities in temporal lobe epilepsy: cross-sectional evidence for progressive neurologic injury.

PubMed

Keller, Simon S; Schoene-Bake, Jan-Christoph; Gerdes, Jan S; Weber, Bernd; Deppe, Michael

2012-01-01

In patients with temporal lobe epilepsy and associated hippocampal sclerosis (TLEhs) there are brain abnormalities extending beyond the presumed epileptogenic zone as revealed separately in conventional magnetic resonance imaging (MRI) and MR diffusion tensor imaging (DTI) studies. However, little is known about the relation between macroscopic atrophy (revealed by volumetric MRI) and microstructural degeneration (inferred by DTI). For 62 patients with unilateral TLEhs and 68 healthy controls, we determined volumes and mean fractional anisotropy (FA) of ipsilateral and contralateral brain structures from T1-weighted and DTI data, respectively. We report significant volume atrophy and FA alterations of temporal lobe, subcortical and callosal regions, which were more diffuse and bilateral in patients with left TLEhs relative to right TLEhs. We observed significant relationships between volume loss and mean FA, particularly of the thalamus and putamen bilaterally. When corrected for age, duration of epilepsy was significantly correlated with FA loss of an anatomically plausible route - including ipsilateral parahippocampal gyrus and temporal lobe white matter, the thalamus bilaterally, and posterior regions of the corpus callosum that contain temporal lobe fibres - that may be suggestive of progressive brain degeneration in response to recurrent seizures. Chronic TLEhs is associated with interrelated DTI-derived and volume-derived brain degenerative abnormalities that are influenced by the duration of the disorder and the side of seizure onset. This work confirms previously contradictory findings by employing multi-modal imaging techniques in parallel in a large sample of patients.

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.

Image acquisition unit for the Mayo/IBM PACS project

NASA Astrophysics Data System (ADS)

Reardon, Frank J.; Salutz, James R.

1991-07-01

The Mayo Clinic and IBM Rochester, Minnesota, have jointly developed a picture archiving, distribution and viewing system for use with Mayo's CT and MRI imaging modalities. Images are retrieved from the modalities and sent over the Mayo city-wide token ring network to optical storage subsystems for archiving, and to server subsystems for viewing on image review stations. Images may also be retrieved from archive and transmitted back to the modalities. The subsystems that interface to the modalities and communicate to the other components of the system are termed Image Acquisition Units (LAUs). The IAUs are IBM Personal System/2 (PS/2) computers with specially developed software. They operate independently in a network of cooperative subsystems and communicate with the modalities, archive subsystems, image review server subsystems, and a central subsystem that maintains information about the content and location of images. This paper provides a detailed description of the function and design of the Image Acquisition Units.

Multimodal description of whole brain connectivity: A comparison of resting state MEG, fMRI, and DWI.

PubMed

Garcés, Pilar; Pereda, Ernesto; Hernández-Tamames, Juan A; Del-Pozo, Francisco; Maestú, Fernando; Pineda-Pardo, José Ángel

2016-01-01

Structural and functional connectivity (SC and FC) have received much attention over the last decade, as they offer unique insight into the coordination of brain functioning. They are often assessed independently with three imaging modalities: SC using diffusion-weighted imaging (DWI), FC using functional magnetic resonance imaging (fMRI), and magnetoencephalography/electroencephalography (MEG/EEG). DWI provides information about white matter organization, allowing the reconstruction of fiber bundles. fMRI uses blood-oxygenation level-dependent (BOLD) contrast to indirectly map neuronal activation. MEG and EEG are direct measures of neuronal activity, as they are sensitive to the synchronous inputs in pyramidal neurons. Seminal studies have targeted either the electrophysiological substrate of BOLD or the anatomical basis of FC. However, multimodal comparisons have been scarcely performed, and the relation between SC, fMRI-FC, and MEG-FC is still unclear. Here we present a systematic comparison of SC, resting state fMRI-FC, and MEG-FC between cortical regions, by evaluating their similarities at three different scales: global network, node, and hub distribution. We obtained strong similarities between the three modalities, especially for the following pairwise combinations: SC and fMRI-FC; SC and MEG-FC at theta, alpha, beta and gamma bands; and fMRI-FC and MEG-FC in alpha and beta. Furthermore, highest node similarity was found for regions of the default mode network and primary motor cortex, which also presented the highest hubness score. Distance was partially responsible for these similarities since it biased all three connectivity estimates, but not the unique contributor, since similarities remained after controlling for distance. © 2015 Wiley Periodicals, Inc.

Non‐parametric combination and related permutation tests for neuroimaging

PubMed Central

Webster, Matthew A.; Brooks, Jonathan C.; Tracey, Irene; Smith, Stephen M.; Nichols, Thomas E.

2016-01-01

Abstract In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well‐known definition of union‐intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume‐based representations of the brain, including non‐imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non‐parametric combination (NPC) methodology, such that instead of a two‐phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one‐way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486‐1511, 2016. © 2016 Wiley Periodicals, Inc. PMID:26848101

Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.

PubMed

Franco, Alexandre R; Ling, Josef; Caprihan, Arvind; Calhoun, Vince D; Jung, Rex E; Heileman, Gregory L; Mayer, Andrew R

2008-12-01

The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the methods.

Challenges With the Diagnosis and Treatment of Cerebral Radiation Necrosis

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

Chao, Samuel T., E-mail: chaos@ccf.org; Rose Ella Burkhardt Brain Tumor and Neuro-oncology Center, Cleveland Clinic, Cleveland, Ohio; Ahluwalia, Manmeet S.

The incidence of radiation necrosis has increased secondary to greater use of combined modality therapy for brain tumors and stereotactic radiosurgery. Given that its characteristics on standard imaging are no different that tumor recurrence, it is difficult to diagnose without use of more sophisticated imaging and nuclear medicine scans, although the accuracy of such scans is controversial. Historically, treatment had been limited to steroids, hyperbaric oxygen, anticoagulants, and surgical resection. A recent prospective randomized study has confirmed the efficacy of bevacizumab in treating radiation necrosis. Novel therapies include using focused interstitial laser thermal therapy. This article will review the diagnosismore » and treatment of radiation necrosis.« less

Few-mode fiber detection for tissue characterization in optical coherence tomography

NASA Astrophysics Data System (ADS)

Eugui, Pablo; Lichtenegger, Antonia; Augustin, Marco; Harper, Danielle J.; Fialová, Stanislava; Wartak, Andreas; Hitzenberger, Christoph K.; Baumann, Bernhard

2017-07-01

A few-mode fiber based detection for OCT systems is presented. The capability of few-mode fibers for delivering light through different fiber paths enables the application of these fibers for angular scattering tissue character- ization. Since the optical path lengths traveled in the fiber change between the fiber modes, the OCT image information will be reconstructed at different depth positions, separating the directly backscattered light from the light scattered at other angles. Using the proposed method, the relation between the angle of reflection from the sample and the respective modal intensity distribution was investigated. The system was demonstrated for imaging ex-vivo brain tissue samples of patients with Alzheimer's disease.

The Age-ility Project (Phase 1): Structural and functional imaging and electrophysiological data repository.

PubMed

Karayanidis, Frini; Keuken, Max C; Wong, Aaron; Rennie, Jaime L; de Hollander, Gilles; Cooper, Patrick S; Ross Fulham, W; Lenroot, Rhoshel; Parsons, Mark; Phillips, Natalie; Michie, Patricia T; Forstmann, Birte U

2016-01-01

Our understanding of the complex interplay between structural and functional organisation of brain networks is being advanced by the development of novel multi-modal analyses approaches. The Age-ility Project (Phase 1) data repository offers open access to structural MRI, diffusion MRI, and resting-state fMRI scans, as well as resting-state EEG recorded from the same community participants (n=131, 15-35 y, 66 male). Raw imaging and electrophysiological data as well as essential demographics are made available via the NITRC website. All data have been reviewed for artifacts using a rigorous quality control protocol and detailed case notes are provided. Copyright © 2015. Published by Elsevier Inc.

Rehabilitation modality and onset differentially influence whisker sensory hypersensitivity after diffuse traumatic brain injury in the rat.

PubMed

Thomas, Theresa Currier; Stockhausen, Ellen Magee; Law, L Matthew; Khodadad, Aida; Lifshitz, Jonathan

2017-01-01

As rehabilitation strategies advance as therapeutic interventions, the modality and onset of rehabilitation after traumatic brain injury (TBI) are critical to optimize treatment. Our laboratory has detected and characterized a late-onset, long-lasting sensory hypersensitivity to whisker stimulation in diffuse brain-injured rats; a deficit that is comparable to visual or auditory sensory hypersensitivity in humans with an acquired brain injury. We hypothesize that the modality and onset of rehabilitation therapies will differentially influence sensory hypersensitivity in response to the Whisker Nuisance Task (WNT) as well as WNT-induced corticosterone (CORT) stress response in diffuse brain-injured rats and shams. After midline fluid percussion brain injury (FPI) or sham surgery, rats were assigned to one of four rehabilitative interventions: (1) whisker sensory deprivation during week one or (2) week two or (3) whisker stimulation during week one or (4) week two. At 28 days following FPI and sham procedures, sensory hypersensitivity was assessed using the WNT. Plasma CORT was evaluated immediately following the WNT (aggravated levels) and prior to the pre-determined endpoint 24 hours later (non-aggravated levels). Deprivation therapy during week two elicited significantly greater sensory hypersensitivity to the WNT compared to week one (p < 0.05), and aggravated CORT levels in FPI rats were significantly lower than sham levels. Stimulation therapy during week one resulted in low levels of sensory hypersensitivity to the WNT, similar to deprivation therapy and naïve controls, however, non-aggravated CORT levels in FPI rats were significantly higher than sham. These data indicate that modality and onset of sensory rehabilitation can differentially influence FPI and sham rats, having a lasting impact on behavioral and stress responses to the WNT, emphasizing the necessity for continued evaluation of modality and onset of rehabilitation after TBI.

3D perfused brain phantom for interstitial ultrasound thermal therapy and imaging: design, construction and characterization

NASA Astrophysics Data System (ADS)

Martínez, José M.; Jarosz, Boguslaw J.

2015-03-01

Thermal therapy has emerged as an independent modality of treating some tumors. In many clinics the hyperthermia, one of the thermal therapy modalities, has been used adjuvant to radio- or chemotherapy to substantially improve the clinical treatment outcomes. In this work, a methodology for building a realistic brain phantom for interstitial ultrasound low dose-rate thermal therapy of the brain is proposed. A 3D brain phantom made of the tissue mimicking material (TMM) had the acoustic and thermal properties in the 20-32 °C range, which is similar to that of a brain at 37 °C. The phantom had 10-11% by mass of bovine gelatin powder dissolved in ethylene glycol. The TMM sonicated at 1 MHz, 1.6 MHz and 2.5 MHz yielded the amplitude attenuation coefficients of 62  ±  1 dB m-1, 115  ±  4 dB m-1 and 175  ±  9 dB m-1, respectively. The density and acoustic speed determination at room temperature (~24 °C) gave 1040  ±  40 kg m-3 and 1545  ±  44 m s-1, respectively. The average thermal conductivity was 0.532 W m-1 K-1. The T1 and T2 values of the TMM were 207  ±  4 and 36.2  ±  0.4 ms, respectively. We envisage the use of our phantom for treatment planning and for quality assurance in MRI based temperature determination. Our phantom preparation methodology may be readily extended to other thermal therapy technologies.

Specifying the brain anatomy underlying temporo-parietal junction activations for theory of mind: A review using probabilistic atlases from different imaging modalities.

PubMed

Schurz, Matthias; Tholen, Matthias G; Perner, Josef; Mars, Rogier B; Sallet, Jerome

2017-09-01

In this quantitative review, we specified the anatomical basis of brain activity reported in the Temporo-Parietal Junction (TPJ) in Theory of Mind (ToM) research. Using probabilistic brain atlases, we labeled TPJ peak coordinates reported in the literature. This was carried out for four different atlas modalities: (i) gyral-parcellation, (ii) sulco-gyral parcellation, (iii) cytoarchitectonic parcellation and (iv) connectivity-based parcellation. In addition, our review distinguished between two ToM task types (false belief and social animations) and a nonsocial task (attention reorienting). We estimated the mean probabilities of activation for each atlas label, and found that for all three task types part of TPJ activations fell into the same areas: (i) Angular Gyrus (AG) and Lateral Occpital Cortex (LOC) in terms of a gyral atlas, (ii) AG and Superior Temporal Sulcus (STS) in terms of a sulco-gyral atlas, (iii) areas PGa and PGp in terms of cytoarchitecture and (iv) area TPJp in terms of a connectivity-based parcellation atlas. Beside these commonalities, we also found that individual task types showed preferential activation for particular labels. Main findings for the right hemisphere were preferential activation for false belief tasks in AG/PGa, and in Supramarginal Gyrus (SMG)/PFm for attention reorienting. Social animations showed strongest selective activation in the left hemisphere, specifically in left Middle Temporal Gyrus (MTG). We discuss how our results (i.e., identified atlas structures) can provide a new reference for describing future findings, with the aim to integrate different labels and terminologies used for studying brain activity around the TPJ. Hum Brain Mapp 38:4788-4805, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Functional Imaging of Audio-Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed

Rinne, Teemu; Muers, Ross S; Salo, Emma; Slater, Heather; Petkov, Christopher I

2017-06-01

The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio-visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio-visual selective attention modulates the primate brain, identify sources for "lost" attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. © The Author 2017. Published by Oxford University Press.

Functional Imaging of Audio–Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed Central

Muers, Ross S.; Salo, Emma; Slater, Heather; Petkov, Christopher I.

2017-01-01

Abstract The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio–visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio–visual selective attention modulates the primate brain, identify sources for “lost” attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. PMID:28419201

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

PubMed

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

2015-08-01

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

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

MIND: modality independent neighbourhood descriptor for multi-modal deformable registration.

PubMed

Heinrich, Mattias P; Jenkinson, Mark; Bhushan, Manav; Matin, Tahreema; Gleeson, Fergus V; Brady, Sir Michael; Schnabel, Julia A

2012-10-01

Deformable registration of images obtained from different modalities remains a challenging task in medical image analysis. This paper addresses this important problem and proposes a modality independent neighbourhood descriptor (MIND) for both linear and deformable multi-modal registration. Based on the similarity of small image patches within one image, it aims to extract the distinctive structure in a local neighbourhood, which is preserved across modalities. The descriptor is based on the concept of image self-similarity, which has been introduced for non-local means filtering for image denoising. It is able to distinguish between different types of features such as corners, edges and homogeneously textured regions. MIND is robust to the most considerable differences between modalities: non-functional intensity relations, image noise and non-uniform bias fields. The multi-dimensional descriptor can be efficiently computed in a dense fashion across the whole image and provides point-wise local similarity across modalities based on the absolute or squared difference between descriptors, making it applicable for a wide range of transformation models and optimisation algorithms. We use the sum of squared differences of the MIND representations of the images as a similarity metric within a symmetric non-parametric Gauss-Newton registration framework. In principle, MIND would be applicable to the registration of arbitrary modalities. In this work, we apply and validate it for the registration of clinical 3D thoracic CT scans between inhale and exhale as well as the alignment of 3D CT and MRI scans. Experimental results show the advantages of MIND over state-of-the-art techniques such as conditional mutual information and entropy images, with respect to clinically annotated landmark locations. Copyright © 2012 Elsevier B.V. All rights reserved.

Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis

NASA Astrophysics Data System (ADS)

Laksari, Kaveh; Kurt, Mehmet; Babaee, Hessam; Kleiven, Svein; Camarillo, David

2018-03-01

Although concussion is one of the greatest health challenges today, our physical understanding of the cause of injury is limited. In this Letter, we simulated football head impacts in a finite element model and extracted the most dominant modal behavior of the brain's deformation. We showed that the brain's deformation is most sensitive in low frequency regimes close to 30 Hz, and discovered that for most subconcussive head impacts, the dynamics of brain deformation is dominated by a single global mode. In this Letter, we show the existence of localized modes and multimodal behavior in the brain as a hyperviscoelastic medium. This dynamical phenomenon leads to strain concentration patterns, particularly in deep brain regions, which is consistent with reported concussion pathology.

Manifold Regularized Multitask Feature Learning for Multimodality Disease Classification

PubMed Central

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2015-01-01

Multimodality based methods have shown great advantages in classification of Alzheimer’s disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. PMID:25277605

Technetium-99m-HMPAO SPECT in the evaluation of patients with a remote history of traumatic brain injury: a comparison with x-ray computed tomography.

PubMed

Gray, B G; Ichise, M; Chung, D G; Kirsh, J C; Franks, W

1992-01-01

The functional imaging modality has potential for demonstrating parenchymal abnormalities not detectable by traditional morphological imaging. Fifty-three patients with a remote history of traumatic brain injury (TBI) were studied with SPECT using 99mTc-hexamethylpropyleneamineoxime (HMPAO) and x-ray computed tomography (CT). Overall, 42 patients (80%) showed regional cerebral blood flow (rCBF) deficits by HMPAO SPECT, whereas 29 patients (55%) showed morphological abnormalities by CT. Out of 20 patients with minor head injury, 12 patients (60%) showed rCBF deficits and 5 patients (25%) showed CT abnormalities. Of 33 patients with major head injury, 30 patients (90%) showed rCBF deficits and 24 patients (72%) showed CT abnormalities. Thus, HMPAO SPECT was more sensitive than CT in detecting abnormalities in patients with a history of TBI, particularly in the minor head injury group. In the major head injury group, three patients showed localized cortical atrophy by CT and normal rCBF by HMPAO SPECT. In the evaluation of TBI patients, HMPAO SPECT is a useful technique to demonstrate regional brain dysfunction in the presence of morphological integrity as assessed by CT.

Multi-Modal Nano-Probes for Radionuclide and 5-color Near Infrared Optical Lymphatic Imaging

PubMed Central

Kobayashi, Hisataka; Koyama, Yoshinori; Barrett, Tristan; Hama, Yukihiro; Regino, Celeste A. S.; Shin, In Soo; Jang, Beom-Su; Le, Nhat; Paik, Chang H.; Choyke, Peter L.; Urano, Yasuteru

2008-01-01

Current contrast agents generally have one function and can only be imaged in monochrome, therefore, the majority of imaging methods can only impart uniparametric information. A single nano-particle has the potential to be loaded with multiple payloads. Such multi-modality probes have the ability to be imaged by more than one imaging technique, which could compensate for the weakness or even combine the advantages of each individual modality. Furthermore, optical imaging using different optical probes enables us to achieve multi-color in vivo imaging, wherein multiple parameters can be read from a single image. To allow differentiation of multiple optical signals in vivo, each probe should have a close but different near infrared emission. To this end, we synthesized nano-probes with multi-modal and multi-color potential, which employed a polyamidoamine dendrimer platform linked to both radionuclides and optical probes, permitting dual-modality scintigraphic and 5-color near infrared optical lymphatic imaging using a multiple excitation spectrally-resolved fluorescence imaging technique. PMID:19079788

Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

PubMed

Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

2008-12-01

Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

Targeting of deep-brain structures in nonhuman primates using MR and CT Images

NASA Astrophysics Data System (ADS)

Chen, Antong; Hines, Catherine; Dogdas, Belma; Bone, Ashleigh; Lodge, Kenneth; O'Malley, Stacey; Connolly, Brett; Winkelmann, Christopher T.; Bagchi, Ansuman; Lubbers, Laura S.; Uslaner, Jason M.; Johnson, Colena; Renger, John; Zariwala, Hatim A.

2015-03-01

In vivo gene delivery in central nervous systems of nonhuman primates (NHP) is an important approach for gene therapy and animal model development of human disease. To achieve a more accurate delivery of genetic probes, precise stereotactic targeting of brain structures is required. However, even with assistance from multi-modality 3D imaging techniques (e.g. MR and CT), the precision of targeting is often challenging due to difficulties in identification of deep brain structures, e.g. the striatum which consists of multiple substructures, and the nucleus basalis of meynert (NBM), which often lack clear boundaries to supporting anatomical landmarks. Here we demonstrate a 3D-image-based intracranial stereotactic approach applied toward reproducible intracranial targeting of bilateral NBM and striatum of rhesus. For the targeting we discuss the feasibility of an atlas-based automatic approach. Delineated originally on a high resolution 3D histology-MR atlas set, the NBM and the striatum could be located on the MR image of a rhesus subject through affine and nonrigid registrations. The atlas-based targeting of NBM was compared with the targeting conducted manually by an experienced neuroscientist. Based on the targeting, the trajectories and entry points for delivering the genetic probes to the targets could be established on the CT images of the subject after rigid registration. The accuracy of the targeting was assessed quantitatively by comparison between NBM locations obtained automatically and manually, and finally demonstrated qualitatively via post mortem analysis of slices that had been labelled via Evan Blue infusion and immunohistochemistry.

Out of focus - brain attention control deficits in adult ADHD.

PubMed

Salmi, Juha; Salmela, Viljami; Salo, Emma; Mikkola, Katri; Leppämäki, Sami; Tani, Pekka; Hokkanen, Laura; Laasonen, Marja; Numminen, Jussi; Alho, Kimmo

2018-04-24

Modern environments are full of information, and place high demands on the attention control mechanisms that allow the selection of information from one (focused attention) or multiple (divided attention) sources, react to changes in a given situation (stimulus-driven attention), and allocate effort according to demands (task-positive and task-negative activity). We aimed to reveal how attention deficit hyperactivity disorder (ADHD) affects the brain functions associated with these attention control processes in constantly demanding tasks. Sixteen adults with ADHD and 17 controls performed adaptive visual and auditory discrimination tasks during functional magnetic resonance imaging (fMRI). Overlapping brain activity in frontoparietal saliency and default-mode networks, as well as in the somato-motor, cerebellar, and striatal areas were observed in all participants. In the ADHD participants, we observed exclusive activity enhancement in the brain areas typically considered to be primarily involved in other attention control functions: During auditory-focused attention, we observed higher activation in the sensory cortical areas of irrelevant modality and the default-mode network (DMN). DMN activity also increased during divided attention in the ADHD group, in turn decreasing during a simple button-press task. Adding irrelevant stimulation resulted in enhanced activity in the salience network. Finally, the irrelevant distractors that capture attention in a stimulus-driven manner activated dorsal attention networks and the cerebellum. Our findings suggest that attention control deficits involve the activation of irrelevant sensory modality, problems in regulating the level of attention on demand, and may encumber top-down processing in cases of irrelevant information. Copyright © 2018. Published by Elsevier B.V.

Globally altered structural brain network topology in grapheme-color synesthesia.

PubMed

Hänggi, Jürgen; Wotruba, Diana; Jäncke, Lutz

2011-04-13

Synesthesia is a perceptual phenomenon in which stimuli in one particular modality elicit a sensation within the same or another sensory modality (e.g., specific graphemes evoke the perception of particular colors). Grapheme-color synesthesia (GCS) has been proposed to arise from abnormal local cross-activation between grapheme and color areas because of their hyperconnectivity. Recently published studies did not confirm such a hyperconnectivity, although morphometric alterations were found in occipitotemporal, parietal, and frontal regions of synesthetes. We used magnetic resonance imaging surface-based morphometry and graph-theoretical network analyses to investigate the topology of structural brain networks in 24 synesthetes and 24 nonsynesthetes. Connectivity matrices were derived from region-wise cortical thickness correlations of 2366 different cortical parcellations across the whole cortex and from 154 more common brain divisions as well. Compared with nonsynesthetes, synesthetes revealed a globally altered structural network topology as reflected by reduced small-worldness, increased clustering, increased degree, and decreased betweenness centrality. Connectivity of the fusiform gyrus (FuG) and intraparietal sulcus (IPS) was changed as well. Hierarchical modularity analysis revealed increased intramodular and intermodular connectivity of the IPS in GCS. However, connectivity differences in the FuG and IPS showed a low specificity because of global changes. We provide first evidence that GCS is rooted in a reduced small-world network organization that is driven by increased clustering suggesting global hyperconnectivity within the synesthetes' brain. Connectivity alterations were widespread and not restricted to the FuG and IPS. Therefore, synesthetic experience might be only one phenotypic manifestation of the globally altered network architecture in GCS.

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

PubMed Central

Hong, Keum-Shik; Khan, Muhammad Jawad

2017-01-01

In this article, non-invasive hybrid brain–computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain–computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided. PMID:28790910

Convergent and invariant object representations for sight, sound, and touch.

PubMed

Man, Kingson; Damasio, Antonio; Meyer, Kaspar; Kaplan, Jonas T

2015-09-01

We continuously perceive objects in the world through multiple sensory channels. In this study, we investigated the convergence of information from different sensory streams within the cerebral cortex. We presented volunteers with three common objects via three different modalities-sight, sound, and touch-and used multivariate pattern analysis of functional magnetic resonance imaging data to map the cortical regions containing information about the identity of the objects. We could reliably predict which of the three stimuli a subject had seen, heard, or touched from the pattern of neural activity in the corresponding early sensory cortices. Intramodal classification was also successful in large portions of the cerebral cortex beyond the primary areas, with multiple regions showing convergence of information from two or all three modalities. Using crossmodal classification, we also searched for brain regions that would represent objects in a similar fashion across different modalities of presentation. We trained a classifier to distinguish objects presented in one modality and then tested it on the same objects presented in a different modality. We detected audiovisual invariance in the right temporo-occipital junction, audiotactile invariance in the left postcentral gyrus and parietal operculum, and visuotactile invariance in the right postcentral and supramarginal gyri. Our maps of multisensory convergence and crossmodal generalization reveal the underlying organization of the association cortices, and may be related to the neural basis for mental concepts. © 2015 Wiley Periodicals, Inc.

Imaging investigations in Spine Trauma: The value of commonly used imaging modalities and emerging imaging modalities.

PubMed

Tins, Bernhard J

2017-01-01

Traumatic spine injuries can be devastating for patients affected and for health care professionals if preventable neurological deterioration occurs. This review discusses the imaging options for the diagnosis of spinal trauma. It lays out when imaging is appropriate and when it is not. It discusses strength and weakness of available imaging modalities. Advanced techniques for spinal injury imaging will be explored. The review concludes with a review of imaging protocols adjusted to clinical circumstances.

Role of functional imaging in the development and refinement of invasive neuromodulation for psychiatric disorders

PubMed Central

Williams, Nolan R; Taylor, Joseph J; Lamb, Kayla; Hanlon, Colleen A; Short, E Baron; George, Mark S

2014-01-01

Deep brain stimulation (DBS) is emerging as a powerful tool for the alleviation of targeted symptoms in treatment-resistant neuropsychiatric disorders. Despite the expanding use of neuropsychiatric DBS, the mechanisms responsible for its effects are only starting to be elucidated. Several modalities such as quantitative electroencephalography as well a intraoperative recordings have been utilized to attempt to understand the underpinnings of this new treatment modality, but functional imaging appears to offer several unique advantages. Functional imaging techniques like positron emission tomography, single photon emission computed tomography and functional magnetic resonance imaging have been used to examine the effects of focal DBS on activity in a distributed neural network. These investigations are critical for advancing the field of invasive neuromodulation in a safe and effective manner, particularly in terms of defining the neuroanatomical targets and refining the stimulation protocols. The purpose of this review is to summarize the current functional neuroimaging findings from neuropsychiatric DBS implantation for three disorders: treatment-resistant depression, obsessive-compulsive disorder, and Tourette syndrome. All of the major targets will be discussed (Nucleus accumbens, anterior limb of internal capsule, subcallosal cingulate, Subthalamic nucleus, Centromedial nucleus of the thalamus-Parafasicular complex, frontal pole, and dorsolateral prefrontal cortex). We will also address some apparent inconsistencies within this literature, and suggest potential future directions for this promising area. PMID:25349661

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases.

PubMed

Rondina, Jane Maryam; Ferreira, Luiz Kobuti; de Souza Duran, Fabio Luis; Kubo, Rodrigo; Ono, Carla Rachel; Leite, Claudia Costa; Smid, Jerusa; Nitrini, Ricardo; Buchpiguel, Carlos Alberto; Busatto, Geraldo F

2018-01-01

Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL). We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18 F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18 F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients. Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18 F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei. The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18 F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls.

Interactive natural language acquisition in a multi-modal recurrent neural architecture

NASA Astrophysics Data System (ADS)

Heinrich, Stefan; Wermter, Stefan

2018-01-01

For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

Positron emission tomography (PET) advances in neurological applications

NASA Astrophysics Data System (ADS)

Sossi, V.

2003-09-01

Positron Emission Tomography (PET) is a functional imaging modality used in brain research to map in vivo neurotransmitter and receptor activity and to investigate glucose utilization or blood flow patterns both in healthy and disease states. Such research is made possible by the wealth of radiotracers available for PET, by the fact that metabolic and kinetic parameters of particular processes can be extracted from PET data and by the continuous development of imaging techniques. In recent years great advancements have been made in the areas of PET instrumentation, data quantification and image reconstruction that allow for more detailed and accurate biological information to be extracted from PET data. It is now possible to quantitatively compare data obtained either with different tracers or with the same tracer under different scanning conditions. These sophisticated imaging approaches enable detailed investigation of disease mechanisms and system response to disease and/or therapy.

Quantitative comparison of high-resolution MRI and myelin-stained histology of the human cerebral cortex.

PubMed

Osechinskiy, Sergey; Kruggel, Frithjof

2009-01-01

The architectonic analysis of the human cerebral cortex is presently based on the examination of stained tissue sections. Recent progress in high-resolution magnetic resonance imaging (MRI) promotes the feasibility of an in vivo architectonic analysis. Since the exact relationship between the laminar fine-structure of a cortical MRI signal and histological cyto-and myeloarchitectonic staining patterns is not known, a quantitative study comparing high-resolution MRI to histological ground truth images is necessary for validating a future MRI based architectonic analysis. This communication describes an ongoing study comparing post mortem MR images to a myelin-stained histology of the brain cortex. After establishing a close spatial correspondence between histological sections and MRI using a slice-to-volume nonrigid registration algorithm, transcortical intensity profiles, extracted from both imaging modalities along curved trajectories of a Laplacian vector field, are compared via a cross-correlational analysis.

Cross-modal pattern of brain activations associated with the processing of self- and significant other's name.

PubMed

Tacikowski, Pawel; Brechmann, André; Nowicka, Anna

2013-09-01

Previous neuroimaging studies have shown that the patterns of brain activity during the processing of personally relevant names (e.g., own name, friend's name, partner's name, etc.) and the names of famous people (e.g., celebrities) are different. However, it is not known how the activity in this network is influenced by the modality of the presented stimuli. In this fMRI study, we investigated the pattern of brain activations during the recognition of aurally and visually presented full names of the subject, a significant other, a famous person and unknown individuals. In both modalities, we found that the processing of self-name and the significant other's name was associated with increased activation in the medial prefrontal cortex (MPFC). Acoustic presentations of these names also activated bilateral inferior frontal gyri (IFG). This pattern of results supports the role of MPFC in the processing of personally relevant information, irrespective of their modality. Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.

Dual-modality imaging of function and physiology

NASA Astrophysics Data System (ADS)

Hasegawa, Bruce H.; Iwata, Koji; Wong, Kenneth H.; Wu, Max C.; Da Silva, Angela; Tang, Hamilton R.; Barber, William C.; Hwang, Andrew B.; Sakdinawat, Anne E.

2002-04-01

Dual-modality imaging is a technique where computed tomography or magnetic resonance imaging is combined with positron emission tomography or single-photon computed tomography to acquire structural and functional images with an integrated system. The data are acquired during a single procedure with the patient on a table viewed by both detectors to facilitate correlation between the structural and function images. The resulting data can be useful for localization for more specific diagnosis of disease. In addition, the anatomical information can be used to compensate the correlated radionuclide data for physical perturbations such as photon attenuation, scatter radiation, and partial volume errors. Thus, dual-modality imaging provides a priori information that can be used to improve both the visual quality and the quantitative accuracy of the radionuclide images. Dual-modality imaging systems also are being developed for biological research that involves small animals. The small-animal dual-modality systems offer advantages for measurements that currently are performed invasively using autoradiography and tissue sampling. By acquiring the required data noninvasively, dual-modality imaging has the potential to allow serial studies in a single animal, to perform measurements with fewer animals, and to improve the statistical quality of the data.

Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

PubMed

Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

2013-01-01

Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

Assessing the Dosimetric Accuracy of Magnetic Resonance-Generated Synthetic CT Images for Focal Brain VMAT Radiation Therapy.

PubMed

Paradis, Eric; Cao, Yue; Lawrence, Theodore S; Tsien, Christina; Feng, Mary; Vineberg, Karen; Balter, James M

2015-12-01

The purpose of this study was to assess the dosimetric accuracy of synthetic CT (MRCT) volumes generated from magnetic resonance imaging (MRI) data for focal brain radiation therapy. A study was conducted in 12 patients with gliomas who underwent both MR and CT imaging as part of their simulation for external beam treatment planning. MRCT volumes were generated from MR images. Patients' clinical treatment planning directives were used to create 12 individual volumetric modulated arc therapy (VMAT) plans, which were then optimized 10 times on each of their respective CT and MRCT-derived electron density maps. Dose metrics derived from optimization criteria, as well as monitor units and gamma analyses, were evaluated to quantify differences between the imaging modalities. Mean differences between planning target volume (PTV) doses on MRCT and CT plans across all patients were 0.0% (range: -0.1 to 0.2%) for D(95%); 0.0% (-0.7 to 0.6%) for D(5%); and -0.2% (-1.0 to 0.2%) for D(max). MRCT plans showed no significant changes in monitor units (-0.4%) compared to CT plans. Organs at risk (OARs) had average D(max) differences of 0.0 Gy (-2.2 to 1.9 Gy) over 85 structures across all 12 patients, with no significant differences when calculated doses approached planning constraints. Focal brain VMAT plans optimized on MRCT images show excellent dosimetric agreement with standard CT-optimized plans. PTVs show equivalent coverage, and OARs do not show any overdose. These results indicate that MRI-derived synthetic CT volumes can be used to support treatment planning of most patients treated for intracranial lesions. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrating histology and MRI in the first digital brain of common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Sun, Peizhen; Parvathaneni, Prasanna; Schilling, Kurt G.; Gao, Yurui; Janve, Vaibhav; Anderson, Adam; Landman, Bennett A.

2015-03-01

This effort is a continuation of development of a digital brain atlas of the common squirrel monkey, Saimiri sciureus, a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. Here, we present the integration of histology with multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. The central concept of this work is to use block face photography to establish an intermediate common space in coordinate system which preserves the high resolution in-plane resolution of histology while enabling 3-D correspondence with MRI. In vivo MRI acquisitions include high resolution T2 structural imaging (300 μm isotropic) and low resolution diffusion tensor imaging (600 um isotropic). Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging (both 300 μm isotropic). Cortical regions were manually annotated on the co-registered volumes based on published histological sections in-plane. We describe mapping of histology and MRI based data of the common squirrel monkey and construction of a viewing tool that enable online viewing of these datasets. The previously descried atlas MRI is used for its deformation to provide accurate conformation to the MRI, thus adding information at the histological level to the MRI volume. This paper presents the mapping of single 2D image slice in block face as a proof of concept and this can be extended to map the atlas space in 3D coordinate system as part of the future work and can be loaded to an XNAT system for further use.