Sex steroid hormones and brain function: PET imaging as a tool for research.

PubMed

Moraga-Amaro, R; van Waarde, A; Doorduin, J; de Vries, E F J

2018-02-01

Sex steroid hormones are major regulators of sexual characteristic among species. These hormones, however, are also produced in the brain. Steroidal hormone-mediated signalling via the corresponding hormone receptors can influence brain function at the cellular level and thus affect behaviour and higher brain functions. Altered steroid hormone signalling has been associated with psychiatric disorders, such as anxiety and depression. Neurosteroids are also considered to have a neuroprotective effect in neurodegenerative diseases. So far, the role of steroid hormone receptors in physiological and pathological conditions has mainly been investigated post mortem on animal or human brain tissues. To study the dynamic interplay between sex steroids, their receptors, brain function and behaviour in psychiatric and neurological disorders in a longitudinal manner, however, non-invasive techniques are needed. Positron emission tomography (PET) is a non-invasive imaging tool that is used to quantitatively investigate a variety of physiological and biochemical parameters in vivo. PET uses radiotracers aimed at a specific target (eg, receptor, enzyme, transporter) to visualise the processes of interest. In this review, we discuss the current status of the use of PET imaging for studying sex steroid hormones in the brain. So far, PET has mainly been investigated as a tool to measure (changes in) sex hormone receptor expression in the brain, to measure a key enzyme in the steroid synthesis pathway (aromatase) and to evaluate the effects of hormonal treatment by imaging specific downstream processes in the brain. Although validated radiotracers for a number of targets are still warranted, PET can already be a useful technique for steroid hormone research and facilitate the translation of interesting findings in animal studies to clinical trials in patients. © 2017 The Authors. Journal of Neuroendocrinology published by John Wiley & Sons Ltd on behalf of British Society for Neuroendocrinology.

Traumatic Brain Injury Diffusion Magnetic Resonance Imaging Research Roadmap Development Project

DTIC Science & Technology

2011-10-01

promising technology on the horizon is the Diffusion Tensor Imaging ( DTI ). Diffusion tensor imaging ( DTI ) is a magnetic resonance imaging (MRI)-based...in the brain. The potential for DTI to improve our understanding of TBI has not been fully explored and challenges associated with non-existent...processing tools, quality control standards, and a shared image repository. The recommendations will be disseminated and pilot tested. A DTI of TBI

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

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

A validation framework for brain tumor segmentation.

PubMed

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

2007-10-01

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

Development and assessment of a new 3D neuroanatomy teaching tool for MRI training.

PubMed

Drapkin, Zachary A; Lindgren, Kristen A; Lopez, Michael J; Stabio, Maureen E

2015-01-01

A computerized three-dimensional (3D) neuroanatomy teaching tool was developed for training medical students to identify subcortical structures on a magnetic resonance imaging (MRI) series of the human brain. This program allows the user to transition rapidly between two-dimensional (2D) MRI slices, 3D object composites, and a combined model in which 3D objects are overlaid onto the 2D MRI slices, all while rotating the brain in any direction and advancing through coronal, sagittal, or axial planes. The efficacy of this tool was assessed by comparing scores from an MRI identification quiz and survey in two groups of first-year medical students. The first group was taught using this new 3D teaching tool, and the second group was taught the same content for the same amount of time but with traditional methods, including 2D images of brain MRI slices and 3D models from widely used textbooks and online sources. Students from the experimental group performed marginally better than the control group on overall test score (P = 0.07) and significantly better on test scores extracted from questions involving C-shaped internal brain structures (P < 0.01). Experimental participants also expressed higher confidence in their abilities to visualize the 3D structure of the brain (P = 0.02) after using this tool. Furthermore, when surveyed, 100% of the students in the experimental group recommended this tool for future students. These results suggest that this neuroanatomy teaching tool is an effective way to train medical students to read an MRI of the brain and is particularly effective for teaching C-shaped internal brain structures. © 2015 American Association of Anatomists.

Nuclear medicine in clinical neurology: an update

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

Oldendorf, W.H.

1981-01-01

Isotope scanning using technetium 99m pertechnetate has fallen into disuse since the advent of x-ray computerized tomography. Regional brain blood flow studies have been pursued on a research basis. Increased regional blood flow during focal seizure activity has been demonstrated and is of use in localizing such foci. Cisternography as a predictive tool in normal pressure hydrocephalus is falling into disuse. Positron tomographic scanning is a potent research tool that can demonstrate both regional glycolysis and blood flow. Unfortunately, it is extremely expensive and complex to apply in a clinical setting. With support from the National Institutes of Health, sevenmore » extramural centers have been funded to develop positron tomographic capabilities, and they will greatly advance our knowledge of stroke pathophysiology, seizure disorders, brain tumors, and various degenerative diseases. Nuclear magnetic resonance imaging is a potentially valuable tool since it creates tomographic images representing the distribution of brain water. No tissue ionization is produced, and images comparable to second-generation computerized tomographic scans are already being produced in humans.« less

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.

Confocal microscopy for astrocyte in vivo imaging: Recycle and reuse in microscopy

PubMed Central

Pérez-Alvarez, Alberto; Araque, Alfonso; Martín, Eduardo D.

2013-01-01

In vivo imaging is one of the ultimate and fundamental approaches for the study of the brain. Two-photon laser scanning microscopy (2PLSM) constitutes the state-of-the-art technique in current neuroscience to address questions regarding brain cell structure, development and function, blood flow regulation and metabolism. This technique evolved from laser scanning confocal microscopy (LSCM), which impacted the field with a major improvement in image resolution of live tissues in the 1980s compared to widefield microscopy. While nowadays some of the unparalleled features of 2PLSM make it the tool of choice for brain studies in vivo, such as the possibility to image deep within a tissue, LSCM can still be useful in this matter. Here we discuss the validity and limitations of LSCM and provide a guide to perform high-resolution in vivo imaging of the brain of live rodents with minimal mechanical disruption employing LSCM. We describe the surgical procedure and experimental setup that allowed us to record intracellular calcium variations in astrocytes evoked by sensory stimulation, and to monitor intact neuronal dendritic spines and astrocytic processes as well as blood vessel dynamics. Therefore, in spite of certain limitations that need to be carefully considered, LSCM constitutes a useful, convenient, and affordable tool for brain studies in vivo. PMID:23658537

Brain's tumor image processing using shearlet transform

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Traumatic Brain Injury Diffusion Magnetic Resonance Imaging Research Roadmap Development Project

DTIC Science & Technology

2012-10-01

Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT . Traumatic Brain Injury ( TBI ) is a public health problem of immense magnitude and...immediate importance that has become endemic among military personnel and veterans. Imaging biomarkers of TBI are needed to support diagnosis and therapy...and to predict TBI consequences while avoiding further injury. Diffusion magnetic resonance imaging has potential to become the non-invasive tool

[Non-medical applications for brain MRI: Ethical considerations].

PubMed

Sarrazin, S; Fagot-Largeault, A; Leboyer, M; Houenou, J

2015-04-01

The recent neuroimaging techniques offer the possibility to better understand complex cognitive processes that are involved in mental disorders and thus have become cornerstone tools for research in psychiatry. The performances of functional magnetic resonance imaging are not limited to medical research and are used in non-medical fields. These recent applications represent new challenges for bioethics. In this article we aim at discussing the new ethical issues raised by the applications of the latest neuroimaging technologies to non-medical fields. We included a selection of peer-reviewed English medical articles after a search on NCBI Pubmed database and Google scholar from 2000 to 2013. We screened bibliographical tables for supplementary references. Websites of governmental French institutions implicated in ethical questions were also screened for governmental reports. Findings of brain areas supporting emotional responses and regulation have been used for marketing research, also called neuromarketing. The discovery of different brain activation patterns in antisocial disorder has led to changes in forensic psychiatry with the use of imaging techniques with unproven validity. Automated classification algorithms and multivariate statistical analyses of brain images have been applied to brain-reading techniques, aiming at predicting unconscious neural processes in humans. We finally report the current position of the French legislation recently revised and discuss the technical limits of such techniques. In the near future, brain imaging could find clinical applications in psychiatry as diagnostic or predictive tools. However, the latest advances in brain imaging are also used in non-scientific fields raising key ethical questions. Involvement of neuroscientists, psychiatrists, physicians but also of citizens in neuroethics discussions is crucial to challenge the risk of unregulated uses of brain imaging. Copyright © 2014 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Optical Imaging and Control of Neurons

NASA Astrophysics Data System (ADS)

Song, Yoon-Kyu

Although remarkable progress has been made in our understanding of the function, organization, and development of the brain by various approaches of modern science and technology, how the brain performs its marvelous function remains unsolved or incompletely understood. This is mainly attributed to the insufficient capability of currently available research tools and conceptual frameworks to deal with enormous complexity of the brain. Hence, in the last couple of decades, a significant effort has been made to crack the complexity of brain by utilizing research tools from diverse scientific areas. The research tools include the optical neurotechnology which incorporates the exquisite characteristics of optics, such as multi-parallel access and non-invasiveness, in sensing and stimulating the excitable membrane of a neuron, the basic functional unit of the brain. This chapter is aimed to serve as a short introduction to the optical neurotechnology for those who wish to use optical techniques as one of their brain research tools.

Optogenetics and the future of neuroscience.

PubMed

Boyden, Edward S

2015-09-01

Over the last 10 years, optogenetics has become widespread in neuroscience for the study of how specific cell types contribute to brain functions and brain disorder states. The full impact of optogenetics will emerge only when other toolsets mature, including neural connectivity and cell phenotyping tools and neural recording and imaging tools. The latter tools are rapidly improving, in part because optogenetics has helped galvanize broad interest in neurotechnology development.

Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue

PubMed Central

Spühler, Isabelle A.; Conley, Gaurasundar M.; Scheffold, Frank; Sprecher, Simon G.

2016-01-01

Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation. PMID:27303270

Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue.

PubMed

Spühler, Isabelle A; Conley, Gaurasundar M; Scheffold, Frank; Sprecher, Simon G

2016-01-01

Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation.

Live imaging of mitosis in the developing mouse embryonic cortex.

PubMed

Pilaz, Louis-Jan; Silver, Debra L

2014-06-04

Although of short duration, mitosis is a complex and dynamic multi-step process fundamental for development of organs including the brain. In the developing cerebral cortex, abnormal mitosis of neural progenitors can cause defects in brain size and function. Hence, there is a critical need for tools to understand the mechanisms of neural progenitor mitosis. Cortical development in rodents is an outstanding model for studying this process. Neural progenitor mitosis is commonly examined in fixed brain sections. This protocol will describe in detail an approach for live imaging of mitosis in ex vivo embryonic brain slices. We will describe the critical steps for this procedure, which include: brain extraction, brain embedding, vibratome sectioning of brain slices, staining and culturing of slices, and time-lapse imaging. We will then demonstrate and describe in detail how to perform post-acquisition analysis of mitosis. We include representative results from this assay using the vital dye Syto11, transgenic mice (histone H2B-EGFP and centrin-EGFP), and in utero electroporation (mCherry-α-tubulin). We will discuss how this procedure can be best optimized and how it can be modified for study of genetic regulation of mitosis. Live imaging of mitosis in brain slices is a flexible approach to assess the impact of age, anatomy, and genetic perturbation in a controlled environment, and to generate a large amount of data with high temporal and spatial resolution. Hence this protocol will complement existing tools for analysis of neural progenitor mitosis.

Implantable self-reset CMOS image sensor and its application to hemodynamic response detection in living mouse brain

NASA Astrophysics Data System (ADS)

Yamaguchi, Takahiro; Takehara, Hiroaki; Sunaga, Yoshinori; Haruta, Makito; Motoyama, Mayumi; Ohta, Yasumi; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Ohta, Jun

2016-04-01

A self-reset pixel of 15 × 15 µm2 with high signal-to-noise ratio (effective peak SNR ≃64 dB) for an implantable image sensor has been developed for intrinsic signal detection arising from hemodynamic responses in a living mouse brain. For detecting local conversion between oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in brain tissues, an implantable imaging device was fabricated with our newly designed self-reset image sensor and orange light-emitting diodes (LEDs; λ = 605 nm). We demonstrated imaging of hemodynamic responses in the sensory cortical area accompanied by forelimb stimulation of a living mouse. The implantable imaging device for intrinsic signal detection is expected to be a powerful tool to measure brain activities in living animals used in behavioral analysis.

Open Science CBS Neuroimaging Repository: Sharing ultra-high-field MR images of the brain.

PubMed

Tardif, Christine Lucas; Schäfer, Andreas; Trampel, Robert; Villringer, Arno; Turner, Robert; Bazin, Pierre-Louis

2016-01-01

Magnetic resonance imaging at ultra high field opens the door to quantitative brain imaging at sub-millimeter isotropic resolutions. However, novel image processing tools to analyze these new rich datasets are lacking. In this article, we introduce the Open Science CBS Neuroimaging Repository: a unique repository of high-resolution and quantitative images acquired at 7 T. The motivation for this project is to increase interest for high-resolution and quantitative imaging and stimulate the development of image processing tools developed specifically for high-field data. Our growing repository currently includes datasets from MP2RAGE and multi-echo FLASH sequences from 28 and 20 healthy subjects respectively. These datasets represent the current state-of-the-art in in-vivo relaxometry at 7 T, and are now fully available to the entire neuroimaging community. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Near-Infrared Neuroimaging with NinPy

PubMed Central

Strangman, Gary E.; Zhang, Quan; Zeffiro, Thomas

2009-01-01

There has been substantial recent growth in the use of non-invasive optical brain imaging in studies of human brain function in health and disease. Near-infrared neuroimaging (NIN) is one of the most promising of these techniques and, although NIN hardware continues to evolve at a rapid pace, software tools supporting optical data acquisition, image processing, statistical modeling, and visualization remain less refined. Python, a modular and computationally efficient development language, can support functional neuroimaging studies of diverse design and implementation. In particular, Python's easily readable syntax and modular architecture allow swift prototyping followed by efficient transition to stable production systems. As an introduction to our ongoing efforts to develop Python software tools for structural and functional neuroimaging, we discuss: (i) the role of non-invasive diffuse optical imaging in measuring brain function, (ii) the key computational requirements to support NIN experiments, (iii) our collection of software tools to support NIN, called NinPy, and (iv) future extensions of these tools that will allow integration of optical with other structural and functional neuroimaging data sources. Source code for the software discussed here will be made available at www.nmr.mgh.harvard.edu/Neural_SystemsGroup/software.html. PMID:19543449

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

Neuroanatomical phenotyping of the mouse brain with three-dimensional autofluorescence imaging

PubMed Central

Wong, Michael D.; Dazai, Jun; Altaf, Maliha; Mark Henkelman, R.; Lerch, Jason P.; Nieman, Brian J.

2012-01-01

The structural organization of the brain is important for normal brain function and is critical to understand in order to evaluate changes that occur during disease processes. Three-dimensional (3D) imaging of the mouse brain is necessary to appreciate the spatial context of structures within the brain. In addition, the small scale of many brain structures necessitates resolution at the ∼10 μm scale. 3D optical imaging techniques, such as optical projection tomography (OPT), have the ability to image intact large specimens (1 cm3) with ∼5 μm resolution. In this work we assessed the potential of autofluorescence optical imaging methods, and specifically OPT, for phenotyping the mouse brain. We found that both specimen size and fixation methods affected the quality of the OPT image. Based on these findings we developed a specimen preparation method to improve the images. Using this method we assessed the potential of optical imaging for phenotyping. Phenotypic differences between wild-type male and female mice were quantified using computer-automated methods. We found that optical imaging of the endogenous autofluorescence in the mouse brain allows for 3D characterization of neuroanatomy and detailed analysis of brain phenotypes. This will be a powerful tool for understanding mouse models of disease and development and is a technology that fits easily within the workflow of biology and neuroscience labs. PMID:22718750

Consumer nueroscience: a new area of study for biomedical engineers.

PubMed

Babiloni, Fabio

2012-01-01

In scientific literature, the most accepted definition of consumer neuroscience or neuromarketing is that it is a field of study concerning the application of neuroscience methods to analyze and understand human behavior related to markets and marketing exchanges. First, it might seem strange that marketers would be interested in using neuroscience to understand consumer's preferences. Yet in practice, the basic goal of marketers is to guide the design and presentation of products in such a way that they are highly compatible with consumer preferences. To understand consumers preferences, several standard research tools are commonly used by marketers, such as personal interviews with the consumers, scoring questionnaries gathered from consumers, and focus groups. The reason marketing researchers are interested in using brain imaging tools instead of simply asking people for their preferences in front of marketing stimuli, arises from the assumption that people cannot (or do not want to) fully explain their preference when explicitly asked. Researchers in the field hypothesize that neuroimaging tools can access information within the consumer's brain during the generation of a preference or the observation of a commercial advertisement. The question of will this information be useful in further promoting the product is still up for debate in marketing literature. From the marketing researchers point of view, there is a hope that this body of brain imaging techniques will provide an efficient tradeoff between costs and benefits of the research. Currently, neuroscience methodology includes powerful brain imaging tools based on the gathering of hemodynamic or electromagnetic signals related to the human brain activity during the performance of a relevant task for marketing objectives. These tools are briefly reviewed in this article.

Three-dimensional functional magnetic resonance imaging of human brain on a clinical 1.5-T scanner.

PubMed Central

van Gelderen, P; Ramsey, N F; Liu, G; Duyn, J H; Frank, J A; Weinberger, D R; Moonen, C T

1995-01-01

Functional magnetic resonance imaging (fMRI) is a tool for mapping brain function that utilizes neuronal activity-induced changes in blood oxygenation. An efficient three-dimensional fMRI method is presented for imaging brain activity on conventional, widely available, 1.5-T scanners, without additional hardware. This approach uses large magnetic susceptibility weighting based on the echo-shifting principle combined with multiple gradient echoes per excitation. Motor stimulation, induced by self-paced finger tapping, reliably produced significant signal increase in the hand region of the contralateral primary motor cortex in every subject tested. Images Fig. 2 Fig. 3 PMID:7624341

A fast atlas-guided high density diffuse optical tomography system for brain imaging

NASA Astrophysics Data System (ADS)

Dai, Xianjin; Zhang, Tao; Yang, Hao; Jiang, Huabei

2017-02-01

Near infrared spectroscopy (NIRS) is an emerging functional brain imaging tool capable of assessing cerebral concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) during brain activation noninvasively. As an extension of NIRS, diffuse optical tomography (DOT) not only shares the merits of providing continuous readings of cerebral oxygenation, but also has the ability to provide spatial resolution in the millimeter scale. Based on the scattering and absorption properties of nonionizing near-infrared light in biological tissue, DOT has been successfully applied in the imaging of breast tumors, osteoarthritis and cortex activations. Here, we present a state-of-art fast high density DOT system suitable for brain imaging. It can achieve up to a 21 Hz sampling rate for a full set of two-wavelength data for 3-D DOT brain image reconstruction. The system was validated using tissue-mimicking brain-model phantom. Then, experiments on healthy subjects were conducted to demonstrate the capability of the system.

Prenatal Brain MR Imaging: Reference Linear Biometric Centiles between 20 and 24 Gestational Weeks.

PubMed

Conte, G; Milani, S; Palumbo, G; Talenti, G; Boito, S; Rustico, M; Triulzi, F; Righini, A; Izzo, G; Doneda, C; Zolin, A; Parazzini, C

2018-05-01

Evaluation of biometry is a fundamental step in prenatal brain MR imaging. While different studies have reported reference centiles for MR imaging biometric data of fetuses in the late second and third trimesters of gestation, no one has reported them in fetuses in the early second trimester. We report centiles of normal MR imaging linear biometric data of a large cohort of fetal brains within 24 weeks of gestation. From the data bases of 2 referral centers of fetal medicine, accounting for 3850 examinations, we retrospectively collected 169 prenatal brain MR imaging examinations of singleton pregnancies, between 20 and 24 weeks of gestational age, with normal brain anatomy at MR imaging and normal postnatal neurologic development. To trace the reference centiles, we used the CG-LMS method. Reference biometric centiles for the developing structures of the cerebrum, cerebellum, brain stem, and theca were obtained. The overall interassessor agreement was adequate for all measurements. Reference biometric centiles of the brain structures in fetuses between 20 and 24 weeks of gestational age may be a reliable tool in assessing fetal brain development. © 2018 by American Journal of Neuroradiology.

Implementation of a computer-aided detection tool for quantification of intracranial radiologic markers on brain CT images

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Ross, Stephen R.; Wang, Yunzhi; Wu, Dee H.; Cornwell, Benjamin O.; Ray, Bappaditya; Zheng, Bin

2017-03-01

Aneurysmal subarachnoid hemorrhage (aSAH) is a form of hemorrhagic stroke that affects middle-aged individuals and associated with significant morbidity and/or mortality especially those presenting with higher clinical and radiologic grades at the time of admission. Previous studies suggested that blood extravasated after aneurysmal rupture was a potentially clinical prognosis factor. But all such studies used qualitative scales to predict prognosis. The purpose of this study is to develop and test a new interactive computer-aided detection (CAD) tool to detect, segment and quantify brain hemorrhage and ventricular cerebrospinal fluid on non-contrasted brain CT images. First, CAD segments brain skull using a multilayer region growing algorithm with adaptively adjusted thresholds. Second, CAD assigns pixels inside the segmented brain region into one of three classes namely, normal brain tissue, blood and fluid. Third, to avoid "black-box" approach and increase accuracy in quantification of these two image markers using CT images with large noise variation in different cases, a graphic User Interface (GUI) was implemented and allows users to visually examine segmentation results. If a user likes to correct any errors (i.e., deleting clinically irrelevant blood or fluid regions, or fill in the holes inside the relevant blood or fluid regions), he/she can manually define the region and select a corresponding correction function. CAD will automatically perform correction and update the computed data. The new CAD tool is now being used in clinical and research settings to estimate various quantitatively radiological parameters/markers to determine radiological severity of aSAH at presentation and correlate the estimations with various homeostatic/metabolic derangements and predict clinical outcome.

Pulsed laser diode photoacoustic tomography (PLD-PAT) system for fast in vivo imaging of small animal brain

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Kalva, Sandeep Kumar; Moothanchery, Mohesh; Pramanik, Manojit

2017-03-01

In recent years, high-repetition rate pulsed laser diode (PLD) was used as an alternative to the Nd:YAG lasers for photoacoustic tomography (PAT). The use of PLD makes the overall PAT system, a low-cost, portable, and high frame rate imaging tool for preclinical applications. In this work, we will present a portable in vivo pulsed laser diode based photoacoustic tomography (PLD-PAT) system. The PLD is integrated inside a circular scanning geometry. The PLD can provide near-infrared ( 803 nm) pulses with pulse duration 136 ns, and pulse energy 1.4 mJ / pulse at 7 kHz repetition rate. The system will be demonstrated for in vivo fast imaging of small animal brain. To enhance the contrast of brain imaging, experiments will be carried out using contrast agents which have strong absorption around laser excitation wavelength. This low-cost, portable small animal brain imaging system could be very useful for brain tumor imaging and therapy.

Optical Coherence Tomography for Brain Imaging and Developmental Biology

PubMed Central

Men, Jing; Huang, Yongyang; Solanki, Jitendra; Zeng, Xianxu; Alex, Aneesh; Jerwick, Jason; Zhang, Zhan; Tanzi, Rudolph E.; Li, Airong; Zhou, Chao

2016-01-01

Optical coherence tomography (OCT) is a promising research tool for brain imaging and developmental biology. Serving as a three-dimensional optical biopsy technique, OCT provides volumetric reconstruction of brain tissues and embryonic structures with micrometer resolution and video rate imaging speed. Functional OCT enables label-free monitoring of hemodynamic and metabolic changes in the brain in vitro and in vivo in animal models. Due to its non-invasiveness nature, OCT enables longitudinal imaging of developing specimens in vivo without potential damage from surgical operation, tissue fixation and processing, and staining with exogenous contrast agents. In this paper, various OCT applications in brain imaging and developmental biology are reviewed, with a particular focus on imaging heart development. In addition, we report findings on the effects of a circadian gene (Clock) and high-fat-diet on heart development in Drosophila melanogaster. These findings contribute to our understanding of the fundamental mechanisms connecting circadian genes and obesity to heart development and cardiac diseases. PMID:27721647

A mass spectrometry imaging approach for investigating how drug-drug interactions influence drug blood-brain barrier permeability.

PubMed

Vallianatou, Theodosia; Strittmatter, Nicole; Nilsson, Anna; Shariatgorji, Mohammadreza; Hamm, Gregory; Pereira, Marcela; Källback, Patrik; Svenningsson, Per; Karlgren, Maria; Goodwin, Richard J A; Andrén, Per E

2018-05-15

There is a high need to develop quantitative imaging methods capable of providing detailed brain localization information of several molecular species simultaneously. In addition, extensive information on the effect of the blood-brain barrier on the penetration, distribution and efficacy of neuroactive compounds is required. Thus, we have developed a mass spectrometry imaging method to visualize and quantify the brain distribution of drugs with varying blood-brain barrier permeability. With this approach, we were able to determine blood-brain barrier transport of different drugs and define the drug distribution in very small brain structures (e.g., choroid plexus) due to the high spatial resolution provided. Simultaneously, we investigated the effect of drug-drug interactions by inhibiting the membrane transporter multidrug resistance 1 protein. We propose that the described approach can serve as a valuable analytical tool during the development of neuroactive drugs, as it can provide physiologically relevant information often neglected by traditional imaging technologies. Copyright © 2018. Published by Elsevier Inc.

Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales

PubMed Central

Hogstrom, L. J.; Guo, S. M.; Murugadoss, K.; Bathe, M.

2016-01-01

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure. PMID:26855758

Use of Electrical Impedance Tomography to Monitor Regional Cerebral Edema during Clinical Dehydration Treatment

PubMed Central

Hu, Shi-Jie; Li, Xia; Xu, Can-Hua; Wang, Bing; Yang, Bin; Tang, Meng-Xing; Dong, Xiu-Zhen; Fei, Zhou; Shi, Xue-Tao

2014-01-01

Objective Variations of conductive fluid content in brain tissue (e.g. cerebral edema) change tissue impedance and can potentially be measured by Electrical Impedance Tomography (EIT), an emerging medical imaging technique. The objective of this work is to establish the feasibility of using EIT as an imaging tool for monitoring brain fluid content. Design a prospective study. Setting In this study EIT was used, for the first time, to monitor variations in cerebral fluid content in a clinical model with patients undergoing clinical dehydration treatment. The EIT system was developed in house and its imaging sensitivity and spatial resolution were evaluated on a saline-filled tank. Patients 23 patients with brain edema. Interventions The patients were continuously imaged by EIT for two hours after initiation of dehydration treatment using 0.5 g/kg intravenous infusion of mannitol for 20 minutes. Measurement and Main Results Overall impedance across the brain increased significantly before and after mannitol dehydration treatment (p = 0.0027). Of the all 23 patients, 14 showed high-level impedance increase and maintained this around 4 hours after the dehydration treatment whereas the other 9 also showed great impedance gain during the treatment but it gradually decreased after the treatment. Further analysis of the regions of interest in the EIT images revealed that diseased regions, identified on corresponding CT images, showed significantly less impedance changes than normal regions during the monitoring period, indicating variations in different patients' responses to such treatment. Conclusions EIT shows potential promise as an imaging tool for real-time and non-invasive monitoring of brain edema patients. PMID:25474474

Atlas-Guided Segmentation of Vervet Monkey Brain MRI

PubMed Central

Fedorov, Andriy; Li, Xiaoxing; Pohl, Kilian M; Bouix, Sylvain; Styner, Martin; Addicott, Merideth; Wyatt, Chris; Daunais, James B; Wells, William M; Kikinis, Ron

2011-01-01

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model. PMID:22253661

MRI-Guided Delivery of Viral Vectors.

PubMed

Salegio, Ernesto A; Bringas, John; Bankiewicz, Krystof S

2016-01-01

Gene therapy has emerged as a potential avenue of treatment for many neurological disorders. Technological advances in imaging techniques allow for the monitoring of real-time infusions into the brain of rodents, nonhuman primates, and humans. Here, we discuss the use of magnetic resonance imaging (MRI) as a tool in the delivery of adeno-associated viral (AAV) particles into brain of nonhuman primates.

Preoperative three-dimensional model creation of magnetic resonance brain images as a tool to assist neurosurgical planning.

PubMed

Spottiswoode, B S; van den Heever, D J; Chang, Y; Engelhardt, S; Du Plessis, S; Nicolls, F; Hartzenberg, H B; Gretschel, A

2013-01-01

Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention. Copyright © 2013 S. Karger AG, Basel.

Iron in Multiple Sclerosis and Its Noninvasive Imaging with Quantitative Susceptibility Mapping

PubMed Central

Stüber, Carsten; Pitt, David; Wang, Yi

2016-01-01

Iron is considered to play a key role in the development and progression of Multiple Sclerosis (MS). In particular, iron that accumulates in myeloid cells after the blood-brain barrier (BBB) seals may contribute to chronic inflammation, oxidative stress and eventually neurodegeneration. Magnetic resonance imaging (MRI) is a well-established tool for the non-invasive study of MS. In recent years, an advanced MRI method, quantitative susceptibility mapping (QSM), has made it possible to study brain iron through in vivo imaging. Moreover, immunohistochemical investigations have helped defining the lesional and cellular distribution of iron in MS brain tissue. Imaging studies in MS patients and of brain tissue combined with histological studies have provided important insights into the role of iron in inflammation and neurodegeneration in MS. PMID:26784172

In Vivo Follow-up of Brain Tumor Growth via Bioluminescence Imaging and Fluorescence Tomography

PubMed Central

Genevois, Coralie; Loiseau, Hugues; Couillaud, Franck

2016-01-01

Reporter gene-based strategies are widely used in experimental oncology. Bioluminescence imaging (BLI) using the firefly luciferase (Fluc) as a reporter gene and d-luciferin as a substrate is currently the most widely employed technique. The present paper compares the performances of BLI imaging with fluorescence imaging using the near infrared fluorescent protein (iRFP) to monitor brain tumor growth in mice. Fluorescence imaging includes fluorescence reflectance imaging (FRI), fluorescence diffuse optical tomography (fDOT), and fluorescence molecular Imaging (FMT®). A U87 cell line was genetically modified for constitutive expression of both the encoding Fluc and iRFP reporter genes and assayed for cell, subcutaneous tumor and brain tumor imaging. On cultured cells, BLI was more sensitive than FRI; in vivo, tumors were first detected by BLI. Fluorescence of iRFP provided convenient tools such as flux cytometry, direct detection of the fluorescent protein on histological slices, and fluorescent tomography that allowed for 3D localization and absolute quantification of the fluorescent signal in brain tumors. PMID:27809256

In Vivo Follow-up of Brain Tumor Growth via Bioluminescence Imaging and Fluorescence Tomography.

PubMed

Genevois, Coralie; Loiseau, Hugues; Couillaud, Franck

2016-10-31

Reporter gene-based strategies are widely used in experimental oncology. Bioluminescence imaging (BLI) using the firefly luciferase (Fluc) as a reporter gene and d-luciferin as a substrate is currently the most widely employed technique. The present paper compares the performances of BLI imaging with fluorescence imaging using the near infrared fluorescent protein (iRFP) to monitor brain tumor growth in mice. Fluorescence imaging includes fluorescence reflectance imaging (FRI), fluorescence diffuse optical tomography (fDOT), and fluorescence molecular Imaging (FMT ® ). A U87 cell line was genetically modified for constitutive expression of both the encoding Fluc and iRFP reporter genes and assayed for cell, subcutaneous tumor and brain tumor imaging. On cultured cells, BLI was more sensitive than FRI; in vivo, tumors were first detected by BLI. Fluorescence of iRFP provided convenient tools such as flux cytometry, direct detection of the fluorescent protein on histological slices, and fluorescent tomography that allowed for 3D localization and absolute quantification of the fluorescent signal in brain tumors.

Whole-Brain Microscopy Meets In Vivo Neuroimaging: Techniques, Benefits, and Limitations.

PubMed

Aswendt, Markus; Schwarz, Martin; Abdelmoula, Walid M; Dijkstra, Jouke; Dedeurwaerdere, Stefanie

2017-02-01

Magnetic resonance imaging, positron emission tomography, and optical imaging have emerged as key tools to understand brain function and neurological disorders in preclinical mouse models. They offer the unique advantage of monitoring individual structural and functional changes over time. What remained unsolved until recently was to generate whole-brain microscopy data which can be correlated to the 3D in vivo neuroimaging data. Conventional histological sections are inappropriate especially for neuronal tracing or the unbiased screening for molecular targets through the whole brain. As part of the European Society for Molecular Imaging (ESMI) meeting 2016 in Utrecht, the Netherlands, we addressed this issue in the Molecular Neuroimaging study group meeting. Presentations covered new brain clearing methods, light sheet microscopes for large samples, and automatic registration of microscopy to in vivo imaging data. In this article, we summarize the discussion; give an overview of the novel techniques; and discuss the practical needs, benefits, and limitations.

Wavelet-domain de-noising of OCT images of human brain malignant glioma

NASA Astrophysics Data System (ADS)

Dolganova, I. N.; Aleksandrova, P. V.; Beshplav, S.-I. T.; Chernomyrdin, N. V.; Dubyanskaya, E. N.; Goryaynov, S. A.; Kurlov, V. N.; Reshetov, I. V.; Potapov, A. A.; Tuchin, V. V.; Zaytsev, K. I.

2018-04-01

We have proposed a wavelet-domain de-noising technique for imaging of human brain malignant glioma by optical coherence tomography (OCT). It implies OCT image decomposition using the direct fast wavelet transform, thresholding of the obtained wavelet spectrum and further inverse fast wavelet transform for image reconstruction. By selecting both wavelet basis and thresholding procedure, we have found an optimal wavelet filter, which application improves differentiation of the considered brain tissue classes - i.e. malignant glioma and normal/intact tissue. Namely, it allows reducing the scattering noise in the OCT images and retaining signal decrement for each tissue class. Therefore, the observed results reveals the wavelet-domain de-noising as a prospective tool for improved characterization of biological tissue using the OCT.

Acute Brain Imaging in Children: Can MRI Replace CT as a Screening Tool?

PubMed

Wagner, Matthias W; Kontzialis, Marinos; Seeburg, Daniel; Stern, Steven E; Oshmyansky, Alexander; Poretti, Andrea; Huisman, Thierry A G M

2016-01-01

To determine if axial T2-weighted imaging can serve as screening tool for pediatric brain imaging. We retrospectively evaluated consecutive brain magnetic resonance imaging (MRI) data of 161 children (74 girls) with a mean age of 7.44 ± 5.71 years. Standard of reference was the final report of neuroradiology attendings. Three readers with different levels of experience were blinded for clinical diagnoses and study indications. First, readers studied only the axial T2-weighted screening sequence. Second, they studied all available anatomical and functional MRI sequences as performed per standard protocol for each clinical indication. The readings were classified as normal or abnormal. Sensitivity and specificity were measured. Axial T2 screening yielded a sensitivity of 77-88% and a specificity of 92%. The full studies/data sets had a sensitivity of 89-95% and a specificity of 86-93%. Nineteen of 167 studies were acquired for acute and 148 of 167 studies for nonacute clinical indication. Twenty-five false-negative diagnoses paneled in three groups were made by all readers together. Readers misread four of 19 studies with acute and 21 of 148 studies with nonacute clinical indication. Four of 21 misread studies with nonacute indications harbored unexpected findings needing management. Axial T2 screening can detect pediatric brain abnormalities with high sensitivity and specificity and can possibly replace CT as screening tool if the reading physician is aware of possible limitations/pitfalls. The level of experience influences sensitivity and specificity. Adding diffusion-weighted imaging and susceptibility-weighted imaging to a 3-dimensional T2-weighted sequence would most likely further increase sensitivity and specificity. Copyright © 2015 by the American Society of Neuroimaging.

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

PubMed Central

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

2013-01-01

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

Reflection imaging of China ink-perfused brain vasculature using confocal laser-scanning microscopy after clarification of brain tissue by the Spalteholz method.

PubMed

Gutierre, R C; Vannucci Campos, D; Mortara, R A; Coppi, A A; Arida, R M

2017-04-01

Confocal laser-scanning microscopy is a useful tool for visualizing neurons and glia in transparent preparations of brain tissue from laboratory animals. Currently, imaging capillaries and venules in transparent brain tissues requires the use of fluorescent proteins. Here, we show that vessels can be imaged by confocal laser-scanning microscopy in transparent cortical, hippocampal and cerebellar preparations after clarification of China ink-injected specimens by the Spalteholz method. This method may be suitable for global, three-dimensional, quantitative analyses of vessels, including stereological estimations of total volume and length and of surface area of vessels, which constitute indirect approaches to investigate angiogenesis. © 2017 Anatomical Society.

Computational and mathematical methods in brain atlasing.

PubMed

Nowinski, Wieslaw L

2017-12-01

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

Tau and Beta-Amyloid Deposition, Microhemorrhage and Brain Function after Traumatic Brain Injury in War Veterans

DTIC Science & Technology

2015-10-01

imaging and 7T- MRI to the Australian Imaging Biomarkers and Lifestyle - Veterans study (AIBL-VETS) of post-traumatic stress disorder and...focal and widespread changes in white matter integrity. 4: 7T- MRI will reveal more extensive microhemorrhage than seen on 3T- MRI and this will relate to...PET imaging, and MRI as well as clinical and neuropsychological tools to identify war veterans at risk of Alzheimer’s disease (AD) and chronic

A simple water-immersion condenser for imaging living brain slices on an inverted microscope.

PubMed

Prusky, G T

1997-09-05

Due to some physical limitations of conventional condensers, inverted compound microscopes are not optimally suited for imaging living brain slices with transmitted light. Herein is described a simple device that converts an inverted microscope into an effective tool for this application by utilizing an objective as a condenser. The device is mounted on a microscope in place of the condenser, is threaded to accept a water immersion objective, and has a slot for a differential interference contrast (DIC) slider. When combined with infrared video techniques, this device allows an inverted microscope to effectively image living cells within thick brain slices in an open perfusion chamber.

Level set method with automatic selective local statistics for brain tumor segmentation in MR images.

PubMed

Thapaliya, Kiran; Pyun, Jae-Young; Park, Chun-Su; Kwon, Goo-Rak

2013-01-01

The level set approach is a powerful tool for segmenting images. This paper proposes a method for segmenting brain tumor images from MR images. A new signed pressure function (SPF) that can efficiently stop the contours at weak or blurred edges is introduced. The local statistics of the different objects present in the MR images were calculated. Using local statistics, the tumor objects were identified among different objects. In this level set method, the calculation of the parameters is a challenging task. The calculations of different parameters for different types of images were automatic. The basic thresholding value was updated and adjusted automatically for different MR images. This thresholding value was used to calculate the different parameters in the proposed algorithm. The proposed algorithm was tested on the magnetic resonance images of the brain for tumor segmentation and its performance was evaluated visually and quantitatively. Numerical experiments on some brain tumor images highlighted the efficiency and robustness of this method. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

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.

Neuroimaging in Pediatric Traumatic Brain Injury: Current and Future Predictors of Functional Outcome

ERIC Educational Resources Information Center

Suskauer, Stacy J.; Huisman, Thierry A. G. M.

2009-01-01

Although neuroimaging has long played a role in the acute management of pediatric traumatic brain injury (TBI), until recently, its use as a tool for understanding and predicting long-term brain-behavior relationships after TBI has been limited by the relatively poor sensitivity of routine clinical imaging for detecting diffuse axonal injury…

High-resolution in vivo Wistar rodent brain atlas based on T1 weighted image

NASA Astrophysics Data System (ADS)

Huang, Su; Lu, Zhongkang; Huang, Weimin; Seramani, Sankar; Ramasamy, Boominathan; Sekar, Sakthivel; Guan, Cuntai; Bhakoo, Kishore

2016-03-01

Image based atlases for rats brain have a significant impact on pre-clinical research. In this project we acquired T1-weighted images from Wistar rodent brains with fine 59μm isotropical resolution for generation of the atlas template image. By applying post-process procedures using a semi-automatic brain extraction method, we delineated the brain tissues from source data. Furthermore, we applied a symmetric group-wise normalization method to generate an optimized template of T1 image of rodent brain, then aligned our template to the Waxholm Space. In addition, we defined several simple and explicit landmarks to corresponding our template with the well known Paxinos stereotaxic reference system. Anchoring at the origin of the Waxholm Space, we applied piece-wise linear transformation method to map the voxels of the template into the coordinates system in Paxinos' stereotoxic coordinates to facilitate the labelling task. We also cross-referenced our data with both published rodent brain atlas and image atlases available online, methodologically labelling the template to produce a Wistar brain atlas identifying more than 130 structures. Particular attention was paid to the cortex and cerebellum, as these areas encompass the most researched aspects of brain functions. Moreover, we adopted the structure hierarchy and naming nomenclature common to various atlases, so that the names and hierarchy structure presented in the atlas are readily recognised for easy use. It is believed the atlas will present a useful tool in rodent brain functional and pharmaceutical studies.

Egas Moniz: 90 Years (1927-2017) from Cerebral Angiography.

PubMed

Artico, Marco; Spoletini, Marialuisa; Fumagalli, Lorenzo; Biagioni, Francesca; Ryskalin, Larisa; Fornai, Francesco; Salvati, Maurizio; Frati, Alessandro; Pastore, Francesco Saverio; Taurone, Samanta

2017-01-01

In June 2017 we celebrate the 90th anniversary of the pioneer discovery of cerebral angiography, the seminal imaging technique used for visualizing cerebral blood vessels and vascular alterations as well as other intracranial disorders. Egas Moniz (1874-1955) was the first to describe the use of this revolutionary technique which, until 1975 (when computed tomography, CT, scan was introduced in the clinical practice), was the sole diagnostic tool to provide an imaging of cerebral vessels and therefore alterations due to intracranial pathology. Moniz introduced in the clinical practice this fundamental and important diagnostic tool. The present contribution wishes to pay a tribute to the Portuguese neurosurgeon, who was also a distinguished neurologist and statesman. Despite his tremendous contribution in modern brain imaging, Egas Moniz was awarded the Nobel Prize in Physiology or Medicine in 1949 for prefrontal leucotomy, the neurosurgical intervention nowadays unacceptable, but should rather be remembered for his key contribution to modern brain imaging.

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

Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging

NASA Astrophysics Data System (ADS)

Reisman, Matthew David

As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images

PubMed Central

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections. PMID:29875639

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images.

PubMed

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections.

Getting a handle on virtual tools: An examination of the neuronal activity associated with virtual tool use.

PubMed

Rallis, Austin; Fercho, Kelene A; Bosch, Taylor J; Baugh, Lee A

2018-01-31

Tool use is associated with three visual streams-dorso-dorsal, ventro-dorsal, and ventral visual streams. These streams are involved in processing online motor planning, action semantics, and tool semantics features, respectively. Little is known about the way in which the brain represents virtual tools. To directly assess this question, a virtual tool paradigm was created that provided the ability to manipulate tool components in isolation of one another. During functional magnetic resonance imaging (fMRI), adult participants performed a series of virtual tool manipulation tasks in which vision and movement kinematics of the tool were manipulated. Reaction time and hand movement direction were monitored while the tasks were performed. Functional imaging revealed that activity within all three visual streams was present, in a similar pattern to what would be expected with physical tool use. However, a previously unreported network of right-hemisphere activity was found including right inferior parietal lobule, middle and superior temporal gyri and supramarginal gyrus - regions well known to be associated with tool processing within the left hemisphere. These results provide evidence that both virtual and physical tools are processed within the same brain regions, though virtual tools recruit bilateral tool processing regions to a greater extent than physical tools. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlation of two-photon in vivo imaging and FIB/SEM microscopy

PubMed Central

Blazquez-Llorca, L; Hummel, E; Zimmerman, H; Zou, C; Burgold, S; Rietdorf, J; Herms, J

2015-01-01

Advances in the understanding of brain functions are closely linked to the technical developments in microscopy. In this study, we describe a correlative microscopy technique that offers a possibility of combining two-photon in vivo imaging with focus ion beam/scanning electron microscope (FIB/SEM) techniques. Long-term two-photon in vivo imaging allows the visualization of functional interactions within the brain of a living organism over the time, and therefore, is emerging as a new tool for studying the dynamics of neurodegenerative diseases, such as Alzheimer’s disease. However, light microscopy has important limitations in revealing alterations occurring at the synaptic level and when this is required, electron microscopy is mandatory. FIB/SEM microscopy is a novel tool for three-dimensional high-resolution reconstructions, since it acquires automated serial images at ultrastructural level. Using FIB/SEM imaging, we observed, at 10 nm isotropic resolution, the same dendrites that were imaged in vivo over 9 days. Thus, we analyzed their ultrastructure and monitored the dynamics of the neuropil around them. We found that stable spines (present during the 9 days of imaging) formed typical asymmetric contacts with axons, whereas transient spines (present only during one day of imaging) did not form a synaptic contact. Our data suggest that the morphological classification that was assigned to a dendritic spine according to the in vivo images did not fit with its ultrastructural morphology. The correlative technique described herein is likely to open opportunities for unravelling the earlier unrecognized complexity of the nervous system. Lay Description Neuroscience and the understanding of brain functions are closely linked to the technical advances in microscopy. In this study we performed a correlative microscopy technique that offers the possibility to combine 2 photon in vivo imaging and FIB/SEM microscopy. Long term 2 photon in vivo imaging allows the visualization of functional interactions within the brain of a living organism over the time, and therefore, is emerging as a new tool to study the dynamics of neurodegenerative diseases, such as Alzheimer’s disease. However, light microscopy has important limitations in revealing synapses that are the connections between neurons, and for this purpose, the electron microscopy is necessary. FIB/SEM microscopy is a novel tool for three-dimensional (3D) high resolution reconstructions since it acquires automated serial images at ultrastructural level. This correlative technique will open up new horizons and opportunities for unravelling the complexity of the nervous system. PMID:25786682

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.

Brain imaging in the context of food perception and eating.

PubMed

Hollmann, Maurice; Pleger, Burkhard; Villringer, Arno; Horstmann, Annette

2013-02-01

Eating behavior depends heavily on brain function. In recent years, brain imaging has proved to be a powerful tool to elucidate brain function and brain structure in the context of eating. In this review, we summarize recent findings in the fast growing body of literature in the field and provide an overview of technical aspects as well as the basic brain mechanisms identified with imaging. Furthermore, we highlight findings linking neural processing of eating-related stimuli with obesity. The consumption of food is based on a complex interplay between homeostatic and hedonic mechanisms. Several hormones influence brain activity to regulate food intake and interact with the brain's reward circuitry, which is partly mediated by dopamine signaling. Additionally, it was shown that food stimuli trigger cognitive control mechanisms that incorporate internal goals into food choice. The brain mechanisms observed in this context are strongly influenced by genetic factors, sex and personality traits. Overall, a complex picture arises from brain-imaging findings, because a multitude of factors influence human food choice. Although several key mechanisms have been identified, there is no comprehensive model that is able to explain the behavioral observations to date. Especially a careful characterization of patients according to genotypes and phenotypes could help to better understand the current and future findings in neuroimaging studies.

Learning implicit brain MRI manifolds with deep learning

NASA Astrophysics Data System (ADS)

Bermudez, Camilo; Plassard, Andrew J.; Davis, Larry T.; Newton, Allen T.; Resnick, Susan M.; Landman, Bennett A.

2018-03-01

An important task in image processing and neuroimaging is to extract quantitative information from the acquired images in order to make observations about the presence of disease or markers of development in populations. Having a low-dimensional manifold of an image allows for easier statistical comparisons between groups and the synthesis of group representatives. Previous studies have sought to identify the best mapping of brain MRI to a low-dimensional manifold, but have been limited by assumptions of explicit similarity measures. In this work, we use deep learning techniques to investigate implicit manifolds of normal brains and generate new, high-quality images. We explore implicit manifolds by addressing the problems of image synthesis and image denoising as important tools in manifold learning. First, we propose the unsupervised synthesis of T1-weighted brain MRI using a Generative Adversarial Network (GAN) by learning from 528 examples of 2D axial slices of brain MRI. Synthesized images were first shown to be unique by performing a cross-correlation with the training set. Real and synthesized images were then assessed in a blinded manner by two imaging experts providing an image quality score of 1-5. The quality score of the synthetic image showed substantial overlap with that of the real images. Moreover, we use an autoencoder with skip connections for image denoising, showing that the proposed method results in higher PSNR than FSL SUSAN after denoising. This work shows the power of artificial networks to synthesize realistic imaging data, which can be used to improve image processing techniques and provide a quantitative framework to structural changes in the brain.

A synthetic luciferin improves in vivo bioluminescence imaging of gene expression in cardiovascular brain regions.

PubMed

Simonyan, Hayk; Hurr, Chansol; Young, Colin N

2016-10-01

Bioluminescence imaging is an effective tool for in vivo investigation of molecular processes. We have demonstrated the applicability of bioluminescence imaging to spatiotemporally monitor gene expression in cardioregulatory brain nuclei during the development of cardiovascular disease, via incorporation of firefly luciferase into living animals, combined with exogenous d-luciferin substrate administration. Nevertheless, d-luciferin uptake into the brain tissue is low, which decreases the sensitivity of bioluminescence detection, particularly when considering small changes in gene expression in tiny central areas. Here, we tested the hypothesis that a synthetic luciferin, cyclic alkylaminoluciferin (CycLuc1), would be superior to d-luciferin for in vivo bioluminescence imaging in cardiovascular brain regions. Male C57B1/6 mice underwent targeted delivery of an adenovirus encoding the luciferase gene downstream of the CMV promoter to the subfornical organ (SFO) or paraventricular nucleus of hypothalamus (PVN), two crucial cardioregulatory neural regions. While bioluminescent signals could be obtained following d-luciferin injection (150 mg/kg), CycLuc1 administration resulted in a three- to fourfold greater bioluminescent emission from the SFO and PVN, at 10- to 20-fold lower substrate concentrations (7.5-15 mg/kg). This CycLuc1-mediated enhancement in bioluminescent emission was evident early following substrate administration (i.e., 6-10 min) and persisted for up to 1 h. When the exposure time was reduced from 60 s to 1,500 ms, minimal signal in the PVN was detectable with d-luciferin, whereas bioluminescent images could be reliably captured with CycLuc1. These findings demonstrate that bioluminescent imaging with the synthetic luciferin CycLuc1 provides an improved physiological genomics tool to investigate molecular events in discrete cardioregulatory brain nuclei. Copyright © 2016 the American Physiological Society.

Roadmap on neurophotonics

NASA Astrophysics Data System (ADS)

Cho, Yong Ku; Zheng, Guoan; Augustine, George J.; Hochbaum, Daniel; Cohen, Adam; Knöpfel, Thomas; Pisanello, Ferruccio; Pavone, Francesco S.; Vellekoop, Ivo M.; Booth, Martin J.; Hu, Song; Zhu, Jiang; Chen, Zhongping; Hoshi, Yoko

2016-09-01

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science’s grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain’s structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and ‘map’ them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken.

Roadmap on neurophotonics

PubMed Central

Cho, Yong Ku; Zheng, Guoan; Augustine, George J; Hochbaum, Daniel; Cohen, Adam; Knöpfel, Thomas; Pisanello, Ferruccio; Pavone, Francesco S; Vellekoop, Ivo M; Booth, Martin J; Hu, Song; Zhu, Jiang; Chen, Zhongping; Hoshi, Yoko

2017-01-01

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science’s grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain’s structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and ‘map’ them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken. PMID:28386392

Advances in magnetic resonance neuroimaging techniques in the evaluation of neonatal encephalopathy.

PubMed

Panigrahy, Ashok; Blüml, Stefan

2007-02-01

Magnetic resonance (MR) imaging has become an essential tool in the evaluation of neonatal encephalopathy. Magnetic resonance-compatible neonatal incubators allow sick neonates to be transported to the MR scanner, and neonatal head coils can improve signal-to-noise ratio, critical for advanced MR imaging techniques. Refinement of conventional imaging techniques include the use of PROPELLER techniques for motion correction. Magnetic resonance spectroscopic imaging and diffusion tensor imaging provide quantitative assessment of both brain development and brain injury in the newborn with respect to metabolite abnormalities and hypoxic-ischemic injury. Knowledge of normal developmental changes in MR spectroscopy metabolite concentration and diffusion tensor metrics is essential to interpret pathological cases. Perfusion MR and functional MR can provide additional physiological information. Both MR spectroscopy and diffusion tensor imaging can provide additional information in the differential of neonatal encephalopathy, including perinatal white matter injury, hypoxic-ischemic brain injury, metabolic disease, infection, and birth injury.

Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers

PubMed Central

Crosson, Bruce; Ford, Anastasia; McGregor, Keith M.; Meinzer, Marcus; Cheshkov, Sergey; Li, Xiufeng; Walker-Batson, Delaina; Briggs, Richard W.

2010-01-01

Functional neuroimaging and related neuroimaging techniques are becoming important tools for rehabilitation research. Functional neuroimaging techniques can be used to determine the effects of brain injury or disease on brain systems related to cognition and behavior and to determine how rehabilitation changes brain systems. These techniques include: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), and transcranial magnetic stimulation (TMS). Related diffusion weighted magnetic resonance imaging techniques (DWI), including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), can quantify white matter integrity. With the proliferation of these imaging techniques in rehabilitation research, it is critical that rehabilitation researchers, as well as consumers of rehabilitation research, become familiar with neuroimaging techniques, what they can offer, and their strengths and weaknesses The purpose to this review is to provide such an introduction to these neuroimaging techniques. PMID:20593321

Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions

NASA Astrophysics Data System (ADS)

Galimzianova, Alfiia; Lesjak, Žiga; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga

2015-03-01

Neuroimaging biomarkers are an important paraclinical tool used to characterize a number of neurological diseases, however, their extraction requires accurate and reliable segmentation of normal and pathological brain structures. For MR images of healthy brains the intensity models of normal-appearing brain tissue (NABT) in combination with Markov random field (MRF) models are known to give reliable and smooth NABT segmentation. However, the presence of pathology, MR intensity bias and natural tissue-dependent intensity variability altogether represent difficult challenges for a reliable estimation of NABT intensity model based on MR images. In this paper, we propose a novel method for segmentation of normal and pathological structures in brain MR images of multiple sclerosis (MS) patients that is based on locally-adaptive NABT model, a robust method for the estimation of model parameters and a MRF-based segmentation framework. Experiments on multi-sequence brain MR images of 27 MS patients show that, compared to whole-brain model and compared to the widely used Expectation-Maximization Segmentation (EMS) method, the locally-adaptive NABT model increases the accuracy of MS lesion segmentation.

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.

MRI Evaluation and Safety in the Developing Brain

PubMed Central

Tocchio, Shannon; Kline-Fath, Beth; Kanal, Emanuel; Schmithorst, Vincent J.; Panigrahy, Ashok

2015-01-01

Magnetic resonance imaging (MRI) evaluation of the developing brain has dramatically increased over the last decade. Faster acquisitions and the development of advanced MRI sequences such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), perfusion imaging, functional MR imaging (fMRI), and susceptibility weighted imaging (SWI), as well as the use of higher magnetic field strengths has made MRI an invaluable tool for detailed evaluation of the developing brain. This article will provide an overview of the use and challenges associated with 1.5T and 3T static magnetic fields for evaluation of the developing brain. This review will also summarize the advantages, clinical challenges and safety concerns specifically related to MRI in the fetus and newborn, including the implications of increased magnetic field strength, logistics related to transporting and monitoring of neonates during scanning, sedation considerations and a discussion of current technologies such as MRI-conditional neonatal incubators and dedicated small-foot print neonatal intensive care unit (NICU) scanners. PMID:25743582

MRI evaluation and safety in the developing brain.

PubMed

Tocchio, Shannon; Kline-Fath, Beth; Kanal, Emanuel; Schmithorst, Vincent J; Panigrahy, Ashok

2015-03-01

Magnetic resonance imaging (MRI) evaluation of the developing brain has dramatically increased over the last decade. Faster acquisitions and the development of advanced MRI sequences, such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), perfusion imaging, functional MR imaging (fMRI), and susceptibility-weighted imaging (SWI), as well as the use of higher magnetic field strengths has made MRI an invaluable tool for detailed evaluation of the developing brain. This article will provide an overview of the use and challenges associated with 1.5-T and 3-T static magnetic fields for evaluation of the developing brain. This review will also summarize the advantages, clinical challenges, and safety concerns specifically related to MRI in the fetus and newborn, including the implications of increased magnetic field strength, logistics related to transporting and monitoring of neonates during scanning, and sedation considerations, and a discussion of current technologies such as MRI conditional neonatal incubators and dedicated small-foot print neonatal intensive care unit (NICU) scanners. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantifying structural alterations in Alzheimer's disease brains using quantitative phase imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Moosung; Lee, Eeksung; Jung, JaeHwang; Yu, Hyeonseung; Kim, Kyoohyun; Yoon, Jonghee; Lee, Shinhwa; Jeong, Yong; Park, YongKeun

2017-02-01

Imaging brain tissues is an essential part of neuroscience because understanding brain structure provides relevant information about brain functions and alterations associated with diseases. Magnetic resonance imaging and positron emission tomography exemplify conventional brain imaging tools, but these techniques suffer from low spatial resolution around 100 μm. As a complementary method, histopathology has been utilized with the development of optical microscopy. The traditional method provides the structural information about biological tissues to cellular scales, but relies on labor-intensive staining procedures. With the advances of illumination sources, label-free imaging techniques based on nonlinear interactions, such as multiphoton excitations and Raman scattering, have been applied to molecule-specific histopathology. Nevertheless, these techniques provide limited qualitative information and require a pulsed laser, which is difficult to use for pathologists with no laser training. Here, we present a label-free optical imaging of mouse brain tissues for addressing structural alteration in Alzheimer's disease. To achieve the mesoscopic, unlabeled tissue images with high contrast and sub-micrometer lateral resolution, we employed holographic microscopy and an automated scanning platform. From the acquired hologram of the brain tissues, we could retrieve scattering coefficients and anisotropies according to the modified scattering-phase theorem. This label-free imaging technique enabled direct access to structural information throughout the tissues with a sub-micrometer lateral resolution and presented a unique means to investigate the structural changes in the optical properties of biological tissues.

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors.

PubMed

Guo, Lu; Wang, Gang; Feng, Yuanming; Yu, Tonggang; Guo, Yu; Bai, Xu; Ye, Zhaoxiang

2016-09-21

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

Extracting morphologies from third harmonic generation images of structurally normal human brain tissue.

PubMed

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

2017-06-01

The morphologies contained in 3D third harmonic generation (THG) images of human brain tissue can report on the pathological state of the tissue. However, the complexity of THG brain images makes the usage of modern image processing tools, especially those of image filtering, segmentation and validation, to extract this information challenging. We developed a salient edge-enhancing model of anisotropic diffusion for image filtering, based on higher order statistics. We split the intrinsic 3-phase segmentation problem into two 2-phase segmentation problems, each of which we solved with a dedicated model, active contour weighted by prior extreme. We applied the novel proposed algorithms to THG images of structurally normal ex-vivo human brain tissue, revealing key tissue components-brain cells, microvessels and neuropil, enabling statistical characterization of these components. Comprehensive comparison to manually delineated ground truth validated the proposed algorithms. Quantitative comparison to second harmonic generation/auto-fluorescence images, acquired simultaneously from the same tissue area, confirmed the correctness of the main THG features detected. The software and test datasets are available from the authors. z.zhang@vu.nl. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A novel combinational approach of microstimulation and bioluminescence imaging to study the mechanisms of action of cerebral electrical stimulation in mice

PubMed Central

Arsenault, Dany; Drouin-Ouellet, Janelle; Saint-Pierre, Martine; Petrou, Petros; Dubois, Marilyn; Kriz, Jasna; Barker, Roger A; Cicchetti, Antonio; Cicchetti, Francesca

2015-01-01

Key points We have developed a unique prototype to perform brain stimulation in mice. This system presents a number of advantages and new developments: 1) all stimulation parameters can be adjusted, 2) both positive and negative current pulses can be generated, guaranteeing electrically balanced stimulation regimen, 3) which can be produced with both low and high impedance electrodes, 4) the developed electrodes ensure localized stimulation and 5) can be used to stimulate and/or record brain potential and 6) in vivo recording of electric pulses allows the detection of defective electrodes (wire breakage or short circuits). This new micro-stimulator device further allows simultaneous live bioluminescence imaging of the mouse brain, enabling real time assessment of the impact of stimulation on cerebral tissue. The use of this novel tool in various transgenic mouse models of disease opens up a whole new range of possibilities in better understanding brain stimulation. Abstract Deep brain stimulation (DBS) is used to treat a number of neurological conditions and is currently being tested to intervene in neuropsychiatric conditions. However, a better understanding of how it works would ensure that side effects could be minimized and benefits optimized. We have thus developed a unique device to perform brain stimulation (BS) in mice and to address fundamental issues related to this methodology in the pre-clinical setting. This new microstimulator prototype was specifically designed to allow simultaneous live bioluminescence imaging of the mouse brain, allowing real time assessment of the impact of stimulation on cerebral tissue. We validated the authenticity of this tool in vivo by analysing the expression of toll-like receptor 2 (TLR2), corresponding to the microglial response, in the stimulated brain regions of TLR2-fluc-GFP transgenic mice, which we further corroborated with post-mortem analyses in these animals as well as in human brains of patients who underwent DBS to treat their Parkinson's disease. In the present study, we report on the development of the first BS device that allows for simultaneous live in vivo imaging in mice. This tool opens up a whole new range of possibilities that allow a better understanding of BS and how to optimize its effects through its use in murine models of disease. PMID:25653107

A multimedia comprehensive informatics system with decision support tools for a multi-site collaboration research of stroke rehabilitation

NASA Astrophysics Data System (ADS)

Wang, Ximing; Documet, Jorge; Garrison, Kathleen A.; Winstein, Carolee J.; Liu, Brent

2012-02-01

Stroke is a major cause of adult disability. The Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (I-CARE) clinical trial aims to evaluate a therapy for arm rehabilitation after stroke. A primary outcome measure is correlative analysis between stroke lesion characteristics and standard measures of rehabilitation progress, from data collected at seven research facilities across the country. Sharing and communication of brain imaging and behavioral data is thus a challenge for collaboration. A solution is proposed as a web-based system with tools supporting imaging and informatics related data. In this system, users may upload anonymized brain images through a secure internet connection and the system will sort the imaging data for storage in a centralized database. Users may utilize an annotation tool to mark up images. In addition to imaging informatics, electronic data forms, for example, clinical data forms, are also integrated. Clinical information is processed and stored in the database to enable future data mining related development. Tele-consultation is facilitated through the development of a thin-client image viewing application. For convenience, the system supports access through desktop PC, laptops, and iPAD. Thus, clinicians may enter data directly into the system via iPAD while working with participants in the study. Overall, this comprehensive imaging informatics system enables users to collect, organize and analyze stroke cases efficiently.

Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

PubMed

Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

2017-08-01

The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

Brain connectivity study of joint attention using frequency-domain optical imaging technique

NASA Astrophysics Data System (ADS)

Chaudhary, Ujwal; Zhu, Banghe; Godavarty, Anuradha

2010-02-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic populations. In this study, diffuse optical imaging is being used to study brain connectivity for the first time in response to joint attention experience in normal adults. The prefrontal region of the brain was non-invasively imaged using a frequency-domain based optical imager. The imaging studies were performed on 11 normal right-handed adults and optical measurements were acquired in response to joint-attention based video clips. While the intensity-based optical data provides information about the hemodynamic response of the underlying neural process, the time-dependent phase-based optical data has the potential to explicate the directional information on the activation of the brain. Thus brain connectivity studies are performed by computing covariance/correlations between spatial units using this frequency-domain based optical measurements. The preliminary results indicate that the extent of synchrony and directional variation in the pattern of activation varies in the left and right frontal cortex. The results have significant implication for research in neural pathways associated with autism that can be mapped using diffuse optical imaging tools in the future.

Automatic MRI 2D brain segmentation using graph searching technique.

PubMed

Pedoia, Valentina; Binaghi, Elisabetta

2013-09-01

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

Towards Ultra-High Resolution Fibre Tract Mapping of the Human Brain – Registration of Polarised Light Images and Reorientation of Fibre Vectors

PubMed Central

Palm, Christoph; Axer, Markus; Gräßel, David; Dammers, Jürgen; Lindemeyer, Johannes; Zilles, Karl; Pietrzyk, Uwe; Amunts, Katrin

2009-01-01

Polarised light imaging (PLI) utilises the birefringence of the myelin sheaths in order to visualise the orientation of nerve fibres in microtome sections of adult human post-mortem brains at ultra-high spatial resolution. The preparation of post-mortem brains for PLI involves fixation, freezing and cutting into 100-μm-thick sections. Hence, geometrical distortions of histological sections are inevitable and have to be removed for 3D reconstruction and subsequent fibre tracking. We here present a processing pipeline for 3D reconstruction of these sections using PLI derived multimodal images of post-mortem brains. Blockface images of the brains were obtained during cutting; they serve as reference data for alignment and elimination of distortion artefacts. In addition to the spatial image transformation, fibre orientation vectors were reoriented using the transformation fields, which consider both affine and subsequent non-linear registration. The application of this registration and reorientation approach results in a smooth fibre vector field, which reflects brain morphology. PLI combined with 3D reconstruction and fibre tracking is a powerful tool for human brain mapping. It can also serve as an independent method for evaluating in vivo fibre tractography. PMID:20461231

An algorithm for automatic parameter adjustment for brain extraction in BrainSuite

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

Identification of the boundary between normal brain tissue and ischemia region using two-photon excitation fluorescence microscopy

NASA Astrophysics Data System (ADS)

Du, Huiping; Wang, Shu; Wang, Xingfu; Zhu, Xiaoqin; Zhuo, Shuangmu; Chen, Jianxin

2016-10-01

Ischemic stroke is one of the common neurological diseases, and it is becoming the leading causes of death and permanent disability around the world. Early and accurate identification of the potentially salvageable boundary region of ischemia brain tissues may enable selection of the most appropriate candidates for early stroke therapies. In this work, TPEF microscopy was used to image the microstructures of normal brain tissues, ischemia regions and the boundary region between normal and ischemia brain tissues. The ischemia brain tissues from Sprague-Dawley (SD) rats were subjected to 6 hours of middle cerebral artery occlusion (MCAO). Our study demonstrates that TPEF microscopy has the ability to not only reveal the morphological changes of the neurons but also identify the boundary between normal brain tissue and ischemia region, which correspond well to the hematoxylin and eosin (H and E) stained images. With the development of miniaturized TPEF microscope imaging devices, TPEF microscopy can be developed into an effectively diagnostic and monitoring tool for cerebral ischemia.

Optimizing parameter choice for FSL-Brain Extraction Tool (BET) on 3D T1 images in multiple sclerosis.

PubMed

Popescu, V; Battaglini, M; Hoogstrate, W S; Verfaillie, S C J; Sluimer, I C; van Schijndel, R A; van Dijk, B W; Cover, K S; Knol, D L; Jenkinson, M; Barkhof, F; de Stefano, N; Vrenken, H

2012-07-16

Brain atrophy studies often use FSL-BET (Brain Extraction Tool) as the first step of image processing. Default BET does not always give satisfactory results on 3DT1 MR images, which negatively impacts atrophy measurements. Finding the right alternative BET settings can be a difficult and time-consuming task, which can introduce unwanted variability. To systematically analyze the performance of BET in images of MS patients by varying its parameters and options combinations, and quantitatively comparing its results to a manual gold standard. Images from 159 MS patients were selected from different MAGNIMS consortium centers, and 16 different 3DT1 acquisition protocols at 1.5 T or 3T. Before running BET, one of three pre-processing pipelines was applied: (1) no pre-processing, (2) removal of neck slices, or (3) additional N3 inhomogeneity correction. Then BET was applied, systematically varying the fractional intensity threshold (the "f" parameter) and with either one of the main BET options ("B" - bias field correction and neck cleanup, "R" - robust brain center estimation, or "S" - eye and optic nerve cleanup) or none. For comparison, intracranial cavity masks were manually created for all image volumes. FSL-FAST (FMRIB's Automated Segmentation Tool) tissue-type segmentation was run on all BET output images and on the image volumes masked with the manual intracranial cavity masks (thus creating the gold-standard tissue masks). The resulting brain tissue masks were quantitatively compared to the gold standard using Dice overlap coefficient (DOC). Normalized brain volumes (NBV) were calculated with SIENAX. NBV values obtained using for SIENAX other BET settings than default were compared to gold standard NBV with the paired t-test. The parameter/preprocessing/options combinations resulted in 20,988 BET runs. The median DOC for default BET (f=0.5, g=0) was 0.913 (range 0.321-0.977) across all 159 native scans. For all acquisition protocols, brain extraction was substantially improved for lower values of "f" than the default value. Using native images, optimum BET performance was observed for f=0.2 with option "B", giving median DOC=0.979 (range 0.867-0.994). Using neck removal before BET, optimum BET performance was observed for f=0.1 with option "B", giving median DOC 0.983 (range 0.844-0.996). Using the above BET-options for SIENAX instead of default, the NBV values obtained from images after neck removal with f=0.1 and option "B" did not differ statistically from NBV values obtained with gold-standard. Although default BET performs reasonably well on most 3DT1 images of MS patients, the performance can be improved substantially. The removal of the neck slices, either externally or within BET, has a marked positive effect on the brain extraction quality. BET option "B" with f=0.1 after removal of the neck slices seems to work best for all acquisition protocols. Copyright © 2012 Elsevier Inc. All rights reserved.

A three-dimensional stereotaxic MRI brain atlas of the cichlid fish Oreochromis mossambicus.

PubMed

Simões, José M; Teles, Magda C; Oliveira, Rui F; Van der Linden, Annemie; Verhoye, Marleen

2012-01-01

The African cichlid Oreochromis mossambicus (Mozambique tilapia) has been used as a model system in a wide range of behavioural and neurobiological studies. The increasing number of genetic tools available for this species, together with the emerging interest in its use for neurobiological studies, increased the need for an accurate hodological mapping of the tilapia brain to supplement the available histological data. The goal of our study was to elaborate a three-dimensional, high-resolution digital atlas using magnetic resonance imaging, supported by Nissl staining. Resulting images were viewed and analysed in all orientations (transverse, sagittal, and horizontal) and manually labelled to reveal structures in the olfactory bulb, telencephalon, diencephalon, optic tectum, and cerebellum. This high resolution tilapia brain atlas is expected to become a very useful tool for neuroscientists using this fish model and will certainly expand their use in future studies regarding the central nervous system.

Multi circular-cavity surface coil for magnetic resonance imaging of monkey's brain at 4 Tesla

NASA Astrophysics Data System (ADS)

Osorio, A. I.; Solis-Najera, S. E.; Vázquez, F.; Wang, R. L.; Tomasi, D.; Rodriguez, A. O.

2014-11-01

Animal models in medical research has been used to study humans diseases for several decades. The use of different imaging techniques together with different animal models offers a great advantage due to the possibility to study some human pathologies without the necessity of chirurgical intervention. The employ of magnetic resonance imaging for the acquisition of anatomical and functional images is an excellent tool because its noninvasive nature. Dedicated coils to perform magnetic resonance imaging experiments are obligatory due to the improvement on the signal-to-noise ratio and reduced specific absorption ratio. A specifically designed surface coil for magnetic resonance imaging of monkey's brain is proposed based on the multi circular-slot coil. Numerical simulations of the magnetic and electric fields were also performed using the Finite Integration Method to solve Maxwell's equations for this particular coil design and, to study the behavior of various vector magnetic field configurations and specific absorption ratio. Monkey's brain images were then acquired with a research-dedicated magnetic resonance imaging system at 4T, to evaluate the anatomical images with conventional imaging sequences. This coil showed good quality images of a monkey's brain and full compatibility with standard pulse sequences implemented in research-dedicated imager.

Functional Magnetic Resonance Imaging Methods

PubMed Central

Chen, Jingyuan E.; Glover, Gary H.

2015-01-01

Since its inception in 1992, Functional Magnetic Resonance Imaging (fMRI) has become an indispensible tool for studying cognition in both the healthy and dysfunctional brain. FMRI monitors changes in the oxygenation of brain tissue resulting from altered metabolism consequent to a task-based evoked neural response or from spontaneous fluctuations in neural activity in the absence of conscious mentation (the “resting state”). Task-based studies have revealed neural correlates of a large number of important cognitive processes, while fMRI studies performed in the resting state have demonstrated brain-wide networks that result from brain regions with synchronized, apparently spontaneous activity. In this article, we review the methods used to acquire and analyze fMRI signals. PMID:26248581

Balanced steady state free precession for arterial spin labeling MRI: Initial experience for blood flow mapping in human brain, retina, and kidney.

PubMed

Park, Sung-Hong; Wang, Danny J J; Duong, Timothy Q

2013-09-01

We implemented pseudo-continuous ASL (pCASL) with 2D and 3D balanced steady state free precession (bSSFP) readout for mapping blood flow in the human brain, retina, and kidney, free of distortion and signal dropout, which are typically observed in the most commonly used echo-planar imaging acquisition. High resolution functional brain imaging in the human visual cortex was feasible with 3D bSSFP pCASL. Blood flow of the human retina could be imaged with pCASL and bSSFP in conjunction with a phase cycling approach to suppress the banding artifacts associated with bSSFP. Furthermore, bSSFP based pCASL enabled us to map renal blood flow within a single breath hold. Control and test-retest experiments suggested that the measured blood flow values in retina and kidney were reliable. Because there is no specific imaging tool for mapping human retina blood flow and the standard contrast agent technique for mapping renal blood flow can cause problems for patients with kidney dysfunction, bSSFP based pCASL may provide a useful tool for the diagnosis of retinal and renal diseases and can complement existing imaging techniques. Copyright © 2013 Elsevier Inc. All rights reserved.

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

Adjustable-Viewing-Angle Endoscopic Tool for Skull Base and Brain Surgery

NASA Technical Reports Server (NTRS)

Bae, Youngsam; Liao, Anna; Manohara, Harish; Shahinian, Hrayr

2008-01-01

The term Multi-Angle and Rear Viewing Endoscopic tooL (MARVEL) denotes an auxiliary endoscope, now undergoing development, that a surgeon would use in conjunction with a conventional endoscope to obtain additional perspective. The role of the MARVEL in endoscopic brain surgery would be similar to the role of a mouth mirror in dentistry. Such a tool is potentially useful for in-situ planetary geology applications for the close-up imaging of unexposed rock surfaces in cracks or those not in the direct line of sight. A conventional endoscope provides mostly a frontal view that is, a view along its longitudinal axis and, hence, along a straight line extending from an opening through which it is inserted. The MARVEL could be inserted through the same opening as that of the conventional endoscope, but could be adjusted to provide a view from almost any desired angle. The MARVEL camera image would be displayed, on the same monitor as that of the conventional endoscopic image, as an inset within the conventional endoscopic image. For example, while viewing a tumor from the front in the conventional endoscopic image, the surgeon could simultaneously view the tumor from the side or the rear in the MARVEL image, and could thereby gain additional visual cues that would aid in precise three-dimensional positioning of surgical tools to excise the tumor. Indeed, a side or rear view through the MARVEL could be essential in a case in which the object of surgical interest was not visible from the front. The conceptual design of the MARVEL exploits the surgeon s familiarity with endoscopic surgical tools. The MARVEL would include a miniature electronic camera and miniature radio transmitter mounted on the tip of a surgical tool derived from an endo-scissor (see figure). The inclusion of the radio transmitter would eliminate the need for wires, which could interfere with manipulation of this and other surgical tools. The handgrip of the tool would be connected to a linkage similar to that of an endo-scissor, but the linkage would be configured to enable adjustment of the camera angle instead of actuation of a scissor blade. It is envisioned that thicknesses of the tool shaft and the camera would be less than 4 mm, so that the camera-tipped tool could be swiftly inserted and withdrawn through a dime-size opening. Electronic cameras having dimensions of the order of millimeters are already commercially available, but their designs are not optimized for use in endoscopic brain surgery. The variety of potential endoscopic, thoracoscopic, and laparoscopic applications can be expected to increase as further development of electronic cameras yields further miniaturization and improvements in imaging performance.

The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization

PubMed Central

Rohlfing, Torsten; Kroenke, Christopher D.; Sullivan, Edith V.; Dubach, Mark F.; Bowden, Douglas M.; Grant, Kathleen A.; Pfefferbaum, Adolf

2012-01-01

The INIA19 is a new, high-quality template for imaging-based studies of non-human primate brains, created from high-resolution, T1-weighted magnetic resonance (MR) images of 19 rhesus macaque (Macaca mulatta) animals. Combined with the comprehensive cortical and sub-cortical label map of the NeuroMaps atlas, the INIA19 is equally suitable for studies requiring both spatial normalization and atlas label propagation. Population-averaged template images are provided for both the brain and the whole head, to allow alignment of the atlas with both skull-stripped and unstripped data, and thus to facilitate its use for skull stripping of new images. This article describes the construction of the template using freely available software tools, as well as the template itself, which is being made available to the scientific community (http://nitrc.org/projects/inia19/). PMID:23230398

The heritability of the functional connectome is robust to common nonlinear registration methods

NASA Astrophysics Data System (ADS)

Hafzalla, George W.; Prasad, Gautam; Baboyan, Vatche G.; Faskowitz, Joshua; Jahanshad, Neda; McMahon, Katie L.; de Zubicaray, Greig I.; Wright, Margaret J.; Braskie, Meredith N.; Thompson, Paul M.

2016-03-01

Nonlinear registration algorithms are routinely used in brain imaging, to align data for inter-subject and group comparisons, and for voxelwise statistical analyses. To understand how the choice of registration method affects maps of functional brain connectivity in a sample of 611 twins, we evaluated three popular nonlinear registration methods: Advanced Normalization Tools (ANTs), Automatic Registration Toolbox (ART), and FMRIB's Nonlinear Image Registration Tool (FNIRT). Using both structural and functional MRI, we used each of the three methods to align the MNI152 brain template, and 80 regions of interest (ROIs), to each subject's T1-weighted (T1w) anatomical image. We then transformed each subject's ROIs onto the associated resting state functional MRI (rs-fMRI) scans and computed a connectivity network or functional connectome for each subject. Given the different degrees of genetic similarity between pairs of monozygotic (MZ) and same-sex dizygotic (DZ) twins, we used structural equation modeling to estimate the additive genetic influences on the elements of the function networks, or their heritability. The functional connectome and derived statistics were relatively robust to nonlinear registration effects.

Two-photon imaging in living brain slices.

PubMed

Mainen, Z F; Maletic-Savatic, M; Shi, S H; Hayashi, Y; Malinow, R; Svoboda, K

1999-06-01

Two-photon excitation laser scanning microscopy (TPLSM) has become the tool of choice for high-resolution fluorescence imaging in intact neural tissues. Compared with other optical techniques, TPLSM allows high-resolution imaging and efficient detection of fluorescence signal with minimal photobleaching and phototoxicity. The advantages of TPLSM are especially pronounced in highly scattering environments such as the brain slice. Here we describe our approaches to imaging various aspects of synaptic function in living brain slices. To combine several imaging modes together with patch-clamp electrophysiological recordings we found it advantageous to custom-build an upright microscope. Our design goals were primarily experimental convenience and efficient collection of fluorescence. We describe our TPLSM imaging system and its performance in detail. We present dynamic measurements of neuronal morphology of neurons expressing green fluorescent protein (GFP) and GFP fusion proteins as well as functional imaging of calcium dynamics in individual dendritic spines. Although our microscope is a custom instrument, its key advantages can be easily implemented as a modification of commercial laser scanning microscopes. Copyright 1999 Academic Press.

Validation tools for image segmentation

NASA Astrophysics Data System (ADS)

Padfield, Dirk; Ross, James

2009-02-01

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

The diffusion tensor imaging (DTI) component of the NIH MRI study of normal brain development (PedsDTI).

PubMed

Walker, Lindsay; Chang, Lin-Ching; Nayak, Amritha; Irfanoglu, M Okan; Botteron, Kelly N; McCracken, James; McKinstry, Robert C; Rivkin, Michael J; Wang, Dah-Jyuu; Rumsey, Judith; Pierpaoli, Carlo

2016-01-01

The NIH MRI Study of normal brain development sought to characterize typical brain development in a population of infants, toddlers, children and adolescents/young adults, covering the socio-economic and ethnic diversity of the population of the United States. The study began in 1999 with data collection commencing in 2001 and concluding in 2007. The study was designed with the final goal of providing a controlled-access database; open to qualified researchers and clinicians, which could serve as a powerful tool for elucidating typical brain development and identifying deviations associated with brain-based disorders and diseases, and as a resource for developing computational methods and image processing tools. This paper focuses on the DTI component of the NIH MRI study of normal brain development. In this work, we describe the DTI data acquisition protocols, data processing steps, quality assessment procedures, and data included in the database, along with database access requirements. For more details, visit http://www.pediatricmri.nih.gov. This longitudinal DTI dataset includes raw and processed diffusion data from 498 low resolution (3 mm) DTI datasets from 274 unique subjects, and 193 high resolution (2.5 mm) DTI datasets from 152 unique subjects. Subjects range in age from 10 days (from date of birth) through 22 years. Additionally, a set of age-specific DTI templates are included. This forms one component of the larger NIH MRI study of normal brain development which also includes T1-, T2-, proton density-weighted, and proton magnetic resonance spectroscopy (MRS) imaging data, and demographic, clinical and behavioral data. Published by Elsevier Inc.

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology.

PubMed

Morawski, Markus; Kirilina, Evgeniya; Scherf, Nico; Jäger, Carsten; Reimann, Katja; Trampel, Robert; Gavriilidis, Filippos; Geyer, Stefan; Biedermann, Bernd; Arendt, Thomas; Weiskopf, Nikolaus

2017-11-28

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

An improved FSL-FIRST pipeline for subcortical gray matter segmentation to study abnormal brain anatomy using quantitative susceptibility mapping (QSM).

PubMed

Feng, Xiang; Deistung, Andreas; Dwyer, Michael G; Hagemeier, Jesper; Polak, Paul; Lebenberg, Jessica; Frouin, Frédérique; Zivadinov, Robert; Reichenbach, Jürgen R; Schweser, Ferdinand

2017-06-01

Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool (FIRST) is one of the most popular software tools for automated subcortical segmentation based on T 1 -weighted (T1w) images. In this work, we demonstrate that FIRST tends to produce inaccurate SGM segmentation results in the case of abnormal brain anatomy, such as present in atrophied brains, due to a poor spatial match of the subcortical structures with the training data in the MNI space as well as due to insufficient contrast of SGM structures on T1w images. Consequently, such deviations from the average brain anatomy may introduce analysis bias in clinical studies, which may not always be obvious and potentially remain unidentified. To improve the segmentation of subcortical nuclei, we propose to use FIRST in combination with a special Hybrid image Contrast (HC) and Non-Linear (nl) registration module (HC-nlFIRST), where the hybrid image contrast is derived from T1w images and magnetic susceptibility maps to create subcortical contrast that is similar to that in the Montreal Neurological Institute (MNI) template. In our approach, a nonlinear registration replaces FIRST's default linear registration, yielding a more accurate alignment of the input data to the MNI template. We evaluated our method on 82 subjects with particularly abnormal brain anatomy, selected from a database of >2000 clinical cases. Qualitative and quantitative analyses revealed that HC-nlFIRST provides improved segmentation compared to the default FIRST method. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.; ...

2016-05-09

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

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

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

High-throughput isotropic mapping of whole mouse brain using multi-view light-sheet microscopy

NASA Astrophysics Data System (ADS)

Nie, Jun; Li, Yusha; Zhao, Fang; Ping, Junyu; Liu, Sa; Yu, Tingting; Zhu, Dan; Fei, Peng

2018-02-01

Light-sheet fluorescence microscopy (LSFM) uses an additional laser-sheet to illuminate selective planes of the sample, thereby enabling three-dimensional imaging at high spatial-temporal resolution. These advantages make LSFM a promising tool for high-quality brain visualization. However, even by the use of LSFM, the spatial resolution remains insufficient to resolve the neural structures across a mesoscale whole mouse brain in three dimensions. At the same time, the thick-tissue scattering prevents a clear observation from the deep of brain. Here we use multi-view LSFM strategy to solve this challenge, surpassing the resolution limit of standard light-sheet microscope under a large field-of-view (FOV). As demonstrated by the imaging of optically-cleared mouse brain labelled with thy1-GFP, we achieve a brain-wide, isotropic cellular resolution of 3μm. Besides the resolution enhancement, multi-view braining imaging can also recover complete signals from deep tissue scattering and attenuation. The identification of long distance neural projections across encephalic regions can be identified and annotated as a result.

Non-imaged based method for matching brains in a common anatomical space for cellular imagery.

PubMed

Midroit, Maëllie; Thevenet, Marc; Fournel, Arnaud; Sacquet, Joelle; Bensafi, Moustafa; Breton, Marine; Chalençon, Laura; Cavelius, Matthias; Didier, Anne; Mandairon, Nathalie

2018-04-22

Cellular imagery using histology sections is one of the most common techniques used in Neuroscience. However, this inescapable technique has severe limitations due to the need to delineate regions of interest on each brain, which is time consuming and variable across experimenters. We developed algorithms based on a vectors field elastic registration allowing fast, automatic realignment of experimental brain sections and associated labeling in a brain atlas with high accuracy and in a streamlined way. Thereby, brain areas of interest can be finely identified without outlining them and different experimental groups can be easily analyzed using conventional tools. This method directly readjusts labeling in the brain atlas without any intermediate manipulation of images. We mapped the expression of cFos, in the mouse brain (C57Bl/6J) after olfactory stimulation or a non-stimulated control condition and found an increased density of cFos-positive cells in the primary olfactory cortex but not in non-olfactory areas of the odor-stimulated animals compared to the controls. Existing methods of matching are based on image registration which often requires expensive material (two-photon tomography mapping or imaging with iDISCO) or are less accurate since they are based on mutual information contained in the images. Our new method is non-imaged based and relies only on the positions of detected labeling and the external contours of sections. We thus provide a new method that permits automated matching of histology sections of experimental brains with a brain reference atlas. Copyright © 2018 Elsevier B.V. All rights reserved.

Diagnostic Value of 68Ga PSMA-11 PET/CT Imaging of Brain Tumors-Preliminary Analysis.

PubMed

Sasikumar, Arun; Joy, Ajith; Pillai, M R A; Nanabala, Raviteja; Anees K, Muhammed; Jayaprakash, P G; Madhavan, Jayaprakash; Nair, Suresh

2017-01-01

To evaluate the feasibility of using Ga PSMA-11 PET/CT for imaging brain lesions and its comparison with F-FDG. Ten patients with brain lesions were included in the study. Five patients were treated cases of glioblastoma with suspected recurrence. F-FDG and Ga PSMA-11 brain scans were done for these patients. Five patients were sent for assessing the nature (primary lesion/metastasis) of space occupying lesion in brain. They underwent whole body F-FDG PET/CT scan and a primary site elsewhere in the body was ruled out. Subsequently they underwent Ga PSMA-11 brain PET/CT imaging. Target to background ratios (TBR) for the brain lesions were calculated using contralateral cerebellar uptake as background. In five treated cases of glioblastoma with suspected recurrence the findings of Ga PSMA-11 PET/CT showed good correlation with that of F-FDG PET/CT scan. Compared to the F-FDG, Ga PSMA-11 PET/CT showed better visualization of the recurrent lesion (presence/absence) owing to its significantly high TBR. Among the five cases evaluated for lesion characterization glioma and atypical meningioma patients showed higher SUVmax in the lesion with Ga PSMA-11 than with F-FDG and converse in cases of lymphoma. TBR was better with Ga PSMA PET/CT in all cases. Ga PSMA-11 PET/CT brain imaging is a potentially useful imaging tool in the evaluation of brain lesions. Absence of physiological uptake of Ga PSMA-11 in the normal brain parenchyma results in high TBR values and consequently better visualization of metabolically active disease in brain.

Study of the development of fetal baboon brain using magnetic resonance imaging at 3 Tesla

PubMed Central

Liu, Feng; Garland, Marianne; Duan, Yunsuo; Stark, Raymond I.; Xu, Dongrong; Dong, Zhengchao; Bansal, Ravi; Peterson, Bradley S.; Kangarlu, Alayar

2008-01-01

Direct observational data on the development of the brains of human and nonhuman primates is on remarkably scant, and most of our understanding of primate brain development is extrapolated from findings in rodent models. Magnetic resonance imaging (MRI) is a promising tool for the noninvasive, longitudinal study of the developing primate brain. We devised a protocol to scan pregnant baboons serially at 3 T for up to 3 h per session. Seven baboons were scanned 1–6 times, beginning as early as 56 days post-conceptional age, and as late as 185 days (term ~185 days). Successful scanning of the fetal baboon required careful animal preparation and anesthesia, in addition to optimization of the scanning protocol. We successfully acquired maps of relaxation times (T1 and T2) and high-resolution anatomical images of the brains of fetal baboons at multiple time points during the course of gestation. These images demonstrated the convergence of gray and white matter contrast near term, and furthermore demonstrated that the loss of contrast at that age is a consequence of the continuous change in relaxation times during fetal brain development. These data furthermore demonstrate that maps of relaxation times have clear advantages over the relaxation time weighted images for the tracking of the changes in brain structure during fetal development. This protocol for in utero MRI of fetal baboon brains will help to advance the use of nonhuman primate models to study fetal brain development longitudinally. PMID:18155925

A Review on the Bioinformatics Tools for Neuroimaging

PubMed Central

MAN, Mei Yen; ONG, Mei Sin; Mohamad, Mohd Saberi; DERIS, Safaai; SULONG, Ghazali; YUNUS, Jasmy; CHE HARUN, Fauzan Khairi

2015-01-01

Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system. PMID:27006633

Brain imaging in methamphetamine-treated mice using a nitroxide contrast agent for EPR imaging of the redox status and a gadolinium contrast agent for MRI observation of blood-brain barrier function.

PubMed

Emoto, M C; Yamato, M; Sato-Akaba, H; Yamada, K; Matsuoka, Y; Fujii, H G

2015-01-01

Methamphetamine (METH)-induced neurotoxicity is associated with mitochondrial dysfunction and enhanced oxidative stress. The aims of the present study conducted in the mouse brain repetitively treated with METH were to (1) examine the redox status using the redox-sensitive imaging probe 3-methoxycarbonyl-2,2,5,5-tetramethylpiperidine-1-oxyl (MCP) and (2) non-invasively visualize the brain redox status with electron paramagnetic resonance (EPR) imaging. The rate of reduction of MCP was measured from a series of temporal EPR images of mouse heads, and this rate was used to construct a two-dimensional map of rate constants called a "redox map." The obtained redox map clearly illustrated the change in redox balance in the METH-treated mouse brain that is a known result of oxidative damage. Biochemical assays also showed that the level of thiobarbituric acid-reactive substance, an index of lipid peroxidation, was increased in mouse brains by METH. The enhanced reduction in MCP observed in mouse brains was remarkably suppressed by treatment with the dopamine synthase inhibitor, α-methyl-p-tyrosine, suggesting that enhancement of the reduction reaction of MCP resulted from enzymatic reduction in the mitochondrial respiratory chain. Furthermore, magnetic resonance imaging (MRI) of METH-treated mice using a blood-brain barrier (BBB)-impermeable paramagnetic contrast agent revealed BBB dysfunction after treatment with METH for 7 days. MRI also indicated that the impaired BBB recovered after withdrawal of METH. EPR imaging and MRI are useful tools not only for following changes in the redox status and BBB dysfunction in mouse brains repeatedly administered METH, but also for tracing the drug effect after withdrawal of METH.

Low cost light-sheet microscopy for whole brain imaging

NASA Astrophysics Data System (ADS)

Kumar, Manish; Nasenbeny, Jordan; Kozorovitskiy, Yevgenia

2018-02-01

Light-sheet microscopy has evolved as an indispensable tool in imaging biological samples. It can image 3D samples at fast speed, with high-resolution optical sectioning, and with reduced photobleaching effects. These properties make light-sheet microscopy ideal for imaging fluorophores in a variety of biological samples and organisms, e.g. zebrafish, drosophila, cleared mouse brains, etc. While most commercial turnkey light-sheet systems are expensive, the existing lower cost implementations, e.g. OpenSPIM, are focused on achieving high-resolution imaging of small samples or organisms like zebrafish. In this work, we substantially reduce the cost of light-sheet microscope system while targeting to image much larger samples, i.e. cleared mouse brains, at single-cell resolution. The expensive components of a lightsheet system - excitation laser, water-immersion objectives, and translation stage - are replaced with an incoherent laser diode, dry objectives, and a custom-built Arduino-controlled translation stage. A low-cost CUBIC protocol is used to clear fixed mouse brain samples. The open-source platforms of μManager and Fiji support image acquisition, processing, and visualization. Our system can easily be extended to multi-color light-sheet microscopy.

Egas Moniz: 90 Years (1927–2017) from Cerebral Angiography

PubMed Central

Artico, Marco; Spoletini, Marialuisa; Fumagalli, Lorenzo; Biagioni, Francesca; Ryskalin, Larisa; Fornai, Francesco; Salvati, Maurizio; Frati, Alessandro; Pastore, Francesco Saverio; Taurone, Samanta

2017-01-01

In June 2017 we celebrate the 90th anniversary of the pioneer discovery of cerebral angiography, the seminal imaging technique used for visualizing cerebral blood vessels and vascular alterations as well as other intracranial disorders. Egas Moniz (1874–1955) was the first to describe the use of this revolutionary technique which, until 1975 (when computed tomography, CT, scan was introduced in the clinical practice), was the sole diagnostic tool to provide an imaging of cerebral vessels and therefore alterations due to intracranial pathology. Moniz introduced in the clinical practice this fundamental and important diagnostic tool. The present contribution wishes to pay a tribute to the Portuguese neurosurgeon, who was also a distinguished neurologist and statesman. Despite his tremendous contribution in modern brain imaging, Egas Moniz was awarded the Nobel Prize in Physiology or Medicine in 1949 for prefrontal leucotomy, the neurosurgical intervention nowadays unacceptable, but should rather be remembered for his key contribution to modern brain imaging. PMID:28974927

Brain SPECT Imaging in Complex Psychiatric Cases: An Evidence-Based, Underutilized Tool

PubMed Central

Amen, Daniel G; Trujillo, Manuel; Newberg, Andrew; Willeumier, Kristen; Tarzwell, Robert; Wu, Joseph C; Chaitin, Barry

2011-01-01

Over the past 20 years brain Single Photon Emission Computed Tomography (SPECT) imaging has developed a substantial, evidence-based foundation and is now recommended by professional societies for numerous indications relevant to psychiatric practice. Unfortunately, SPECT in clinical practice is utilized by only a handful of clinicians. This article presents a rationale for a more widespread use of SPECT in clinical practice for complex cases, and includes seven clinical applications where it may help optimize patient care. PMID:21863144

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.

Label-free NIR reflectance imaging as a complimentary tool for two-photon fluorescence microscopy: multimodal investigation of stroke (Conference Presentation)

NASA Astrophysics Data System (ADS)

Allegra Mascaro, Anna Letizia; Costantini, Irene; Margoni, Emilia; Iannello, Giulio; Bria, Alessandro; Sacconi, Leonardo; Pavone, Francesco S.

2016-03-01

Two-photon imaging combined with targeted fluorescent indicators is extensively used for visualizing critical features of brain functionality and structural plasticity. Back-scattered photons from the NIR laser provide complimentary information without introducing any exogenous labelling. Here, we describe a versatile approach that, by collecting the reflected NIR light, provides structural details on the myelinated axons and blood vessels in the brain, both in fixed samples and in live animals. Indeed, by combining NIR reflectance and two-photon imaging of a slice of hippocampus from Thy1-GFPm mice, we show the presence of randomly oriented axons intermingled with sparsely fluorescent neuronal processes. The back-scattered photons guide the contextualization of the fluorescence structure within brain atlas thanks to the recognition of characteristic hippocampal structures. Label-free detection of axonal elongations over the layer 2/3 of mouse cortex under a cranial window was also possible in live brain. Finally, blood flow could be measured in vivo, thus validating label free NIR reflectance as a tool for monitoring hemodynamic fluctuations. The prospective versatility of this label-free technique complimentary to two-photon fluorescence microscopy is demonstrated in a mouse model of photothrombotic stroke in which the axonal degeneration and blood flow remodeling can be investigated simultaneously.

A Review of Magnetic Resonance Imaging and Diffusion Tensor Imaging Findings in Mild Traumatic Brain Injury

PubMed Central

Shenton, ME; Hamoda, HM; Schneiderman, JS; Bouix, S; Pasternak, O; Rathi, Y; M-A, Vu; Purohit, MP; Helmer, K; Koerte, I; Lin, AP; C-F, Westin; Kikinis, R; Kubicki, M; Stern, RA; Zafonte, R

2013-01-01

Mild traumatic brain injury (mTBI), also referred to as concussion, remains a controversial diagnosis because the brain often appears quite normal on conventional computed tomography (CT) and magnetic resonance imaging (MRI) scans. Such conventional tools, however, do not adequately depict brain injury in mTBI because they are not sensitive to detecting diffuse axonal injuries (DAI), also described as traumatic axonal injuries (TAI), the major brain injuries in mTBI. Furthermore, for the 15 to 30% of those diagnosed with mTBI on the basis of cognitive and clinical symptoms, i.e., the “miserable minority,” the cognitive and physical symptoms do not resolve following the first three months post-injury. Instead, they persist, and in some cases lead to long-term disability. The explanation given for these chronic symptoms, i.e., postconcussive syndrome, particularly in cases where there is no discernible radiological evidence for brain injury, has led some to posit a psychogenic origin. Such attributions are made all the easier since both post-traumatic stress disorder (PTSD) and depression are frequently co-morbid with mTBI. The challenge is thus to use neuroimaging tools that are sensitive to DAI/TAI, such as diffusion tensor imaging (DTI), in order to detect brain injuries in mTBI. Of note here, recent advances in neuroimaging techniques, such as DTI, make it possible to characterize better extant brain abnormalities in mTBI. These advances may lead to the development of biomarkers of injury, as well as to staging of reorganization and reversal of white matter changes following injury, and to the ability to track and to characterize changes in brain injury over time. Such tools will likely be used in future research to evaluate treatment efficacy, given their enhanced sensitivity to alterations in the brain. In this article we review the incidence of mTBI and the importance of characterizing this patient population using objective radiological measures. Evidence is presented for detecting brain abnormalities in mTBI based on studies that use advanced neuroimaging techniques. Taken together, these findings suggest that more sensitive neuroimaging tools improve the detection of brain abnormalities (i.e., diagnosis) in mTBI. These tools will likely also provide important information relevant to outcome (prognosis), as well as play an important role in longitudinal studies that are needed to understand the dynamic nature of brain injury in mTBI. Additionally, summary tables of MRI and DTI findings are included. We believe that the enhanced sensitivity of newer and more advanced neuroimaging techniques for identifying areas of brain damage in mTBI will be important for documenting the biological basis of postconcussive symptoms, which are likely associated with subtle brain alterations, alterations that have heretofore gone undetected due to the lack of sensitivity of earlier neuroimaging techniques. Nonetheless, it is noteworthy to point out that detecting brain abnormalities in mTBI does not mean that other disorders of a more psychogenic origin are not co-morbid with mTBI and equally important to treat. They arguably are. The controversy of psychogenic versus physiogenic, however, is not productive because the psychogenic view does not carefully consider the limitations of conventional neuroimaging techniques in detecting subtle brain injuries in mTBI, and the physiogenic view does not carefully consider the fact that PTSD and depression, and other co-morbid conditions, may be present in those suffering from mTBI. Finally, we end with a discussion of future directions in research that will lead to the improved care of patients diagnosed with mTBI. PMID:22438191

Development of Realistic Striatal Digital Brain (SDB) Phantom for 123I-FP-CIT SPECT and Effect on Ventricle in the Brain for Semi-quantitative Index of Specific Binding Ratio.

PubMed

Furuta, Akihiro; Onishi, Hideo; Nakamoto, Kenta

This study aimed at developing the realistic striatal digital brain (SDB) phantom and to assess specific binding ratio (SBR) for ventricular effect in the 123 I-FP-CIT SPECT imaging. SDB phantom was constructed in to four segments (striatum, ventricle, brain parenchyma, and skull bone) using Percentile method and other image processing in the T2-weighted MR images. The reference image was converted into 128×128 matrixes to align MR images with SPECT images. The process image was reconstructed with projection data sets generated from reference images additive blurring, attenuation, scatter, and statically noise. The SDB phantom was evaluated to find the accuracy of calculated SBR and to find the effect of SBR with/without ventricular counts with the reference and process images. We developed and investigated the utility of the SDB phantom in the 123 I-FP-CIT SPECT clinical study. The true value of SBR was just marched to calculate SBR from reference and process images. The SBR was underestimated 58.0% with ventricular counts in reference image, however, was underestimated 162% with ventricular counts in process images. The SDB phantom provides an extremely convenient tool for discovering basic properties of 123 I-FP-CIT SPECT clinical study image. It was suggested that the SBR was susceptible to ventricle.

The Correlation Between a Short-term Conventional Electroencephalography in the First Day of Life and Brain Magnetic Resonance Imaging in Newborns Undergoing Hypothermia for Hypoxic-Ischemic Encephalopathy.

PubMed

Obeid, Rawad; Sogawa, Yoshimi; Gedela, Satyanarayana; Naik, Monica; Lee, Vince; Telesco, Richard; Wisnowski, Jessica; Magill, Christine; Painter, Michael J; Panigrahy, Ashok

2017-02-01

Electroencephalograph recorded in the first day of life in newborns treated with hypothermia for hypoxic-ischemic encephalopathy could be utilized as a predictive tool for the severity of brain injury on magnetic resonance imaging and mortality. We analyzed newborns who were admitted for therapeutic hypothermia due to hypoxic-ischemic encephalopathy. All enrolled infants underwent encephalography within the first 24 hours of life and underwent brain magnetic resonance imaging after rewarming. All encephalographs were independently reviewed for background amplitude, continuity, and variability. Brain injury determined by magnetic resonance imaging was scored using methods described by Bonifacio et al. Forty-one newborns were included in the study. Each encephalograph variable correlated significantly with the severity of injury on brain magnetic resonance imaging (P < 0.001 for each). The overall encephalograph severity estimated as mild, moderate, and severe also correlated with injury (P < 0.001). Each encephalograph variable correlated with mortality (P < 0.001 for each) and also the overall encephalograph severity (P < 0.001). Severity of electrographic findings on encephalograph in the first day of life during therapeutic hypothermia for hypoxic-ischemic encephalopathy correlated with the extent of injury on brain magnetic resonance imaging. This information may be useful for families and aid guide clinical decision making. Copyright © 2017 Elsevier Inc. All rights reserved.

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).

Whole brain myelin mapping using T1- and T2-weighted MR imaging data

PubMed Central

Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante

2014-01-01

Despite recent advancements in MR imaging, non-invasive mapping of myelin in the brain still remains an open issue. Here we attempted to provide a potential solution. Specifically, we developed a processing workflow based on T1-w and T2-w MR data to generate an optimized myelin enhanced contrast image. The workflow allows whole brain mapping using the T1-w/T2-w technique, which was originally introduced as a non-invasive method for assessing cortical myelin content. The hallmark of our approach is a retrospective calibration algorithm, applied to bias-corrected T1-w and T2-w images, that relies on image intensities outside the brain. This permits standardizing the intensity histogram of the ratio image, thereby allowing for across-subject statistical analyses. Quantitative comparisons of image histograms within and across different datasets confirmed the effectiveness of our normalization procedure. Not only did the calibrated T1-w/T2-w images exhibit a comparable intensity range, but also the shape of the intensity histograms was largely corresponding. We also assessed the reliability and specificity of the ratio image compared to other MR-based techniques, such as magnetization transfer ratio (MTR), fractional anisotropy (FA), and fluid-attenuated inversion recovery (FLAIR). With respect to these other techniques, T1-w/T2-w had consistently high values, as well as low inter-subject variability, in brain structures where myelin is most abundant. Overall, our results suggested that the T1-w/T2-w technique may be a valid tool supporting the non-invasive mapping of myelin in the brain. Therefore, it might find important applications in the study of brain development, aging and disease. PMID:25228871

4D microvascular imaging based on ultrafast Doppler tomography.

PubMed

Demené, Charlie; Tiran, Elodie; Sieu, Lim-Anna; Bergel, Antoine; Gennisson, Jean Luc; Pernot, Mathieu; Deffieux, Thomas; Cohen, Ivan; Tanter, Mickael

2016-02-15

4D ultrasound microvascular imaging was demonstrated by applying ultrafast Doppler tomography (UFD-T) to the imaging of brain hemodynamics in rodents. In vivo real-time imaging of the rat brain was performed using ultrasonic plane wave transmissions at very high frame rates (18,000 frames per second). Such ultrafast frame rates allow for highly sensitive and wide-field-of-view 2D Doppler imaging of blood vessels far beyond conventional ultrasonography. Voxel anisotropy (100 μm × 100 μm × 500 μm) was corrected for by using a tomographic approach, which consisted of ultrafast acquisitions repeated for different imaging plane orientations over multiple cardiac cycles. UFT-D allows for 4D dynamic microvascular imaging of deep-seated vasculature (up to 20 mm) with a very high 4D resolution (respectively 100 μm × 100 μm × 100 μm and 10 ms) and high sensitivity to flow in small vessels (>1 mm/s) for a whole-brain imaging technique without requiring any contrast agent. 4D ultrasound microvascular imaging in vivo could become a valuable tool for the study of brain hemodynamics, such as cerebral flow autoregulation or vascular remodeling after ischemic stroke recovery, and, more generally, tumor vasculature response to therapeutic treatment. Copyright © 2015 Elsevier Inc. All rights reserved.

A Whole Brain Staining, Embedding, and Clearing Pipeline for Adult Zebrafish to Visualize Cell Proliferation and Morphology in 3-Dimensions.

PubMed

Lindsey, Benjamin W; Douek, Alon M; Loosli, Felix; Kaslin, Jan

2017-01-01

The field of macro-imaging has grown considerably with the appearance of innovative clearing methods and confocal microscopes with lasers capable of penetrating increasing tissue depths. The ability to visualize and model the growth of whole organs as they develop from birth, or with manipulation, disease or injury, provides new ways of thinking about development, tissue-wide signaling, and cell-to-cell interactions. The zebrafish ( Danio rerio ) has ascended from a predominantly developmental model to a leading adult model of tissue regeneration. The unmatched neurogenic and regenerative capacity of the mature central nervous system, in particular, has received much attention, however tools to interrogate the adult brain are sparse. At present there exists no straightforward methods of visualizing changes in the whole adult brain in 3-dimensions (3-D) to examine systemic patterns of cell proliferation or cell populations of interest under physiological, injury, or diseased conditions. The method presented here is the first of its kind to offer an efficient step-by-step pipeline from intraperitoneal injections of the proliferative marker, 5-ethynyl-2'-deoxyuridine (EdU), to whole brain labeling, to a final embedded and cleared brain sample suitable for 3-D imaging using optical projection tomography (OPT). Moreover, this method allows potential for imaging GFP-reporter lines and cell-specific antibodies in the presence or absence of EdU. The small size of the adult zebrafish brain, the highly consistent degree of EdU labeling, and the use of basic clearing agents, benzyl benzoate, and benzyl alcohol, makes this method highly tractable for most laboratories interested in understanding the vertebrate central nervous system in health and disease. Post-processing of OPT-imaged adult zebrafish brains injected with EdU illustrate that proliferative patterns in EdU can readily be observed and analyzed using IMARIS and/or FIJI/IMAGEJ software. This protocol will be a valuable tool to unlock new ways of understanding systemic patterns in cell proliferation in the healthy and injured brain, brain-wide cellular interactions, stem cell niche development, and changes in brain morphology.

A Whole Brain Staining, Embedding, and Clearing Pipeline for Adult Zebrafish to Visualize Cell Proliferation and Morphology in 3-Dimensions

PubMed Central

Lindsey, Benjamin W.; Douek, Alon M.; Loosli, Felix; Kaslin, Jan

2018-01-01

The field of macro-imaging has grown considerably with the appearance of innovative clearing methods and confocal microscopes with lasers capable of penetrating increasing tissue depths. The ability to visualize and model the growth of whole organs as they develop from birth, or with manipulation, disease or injury, provides new ways of thinking about development, tissue-wide signaling, and cell-to-cell interactions. The zebrafish (Danio rerio) has ascended from a predominantly developmental model to a leading adult model of tissue regeneration. The unmatched neurogenic and regenerative capacity of the mature central nervous system, in particular, has received much attention, however tools to interrogate the adult brain are sparse. At present there exists no straightforward methods of visualizing changes in the whole adult brain in 3-dimensions (3-D) to examine systemic patterns of cell proliferation or cell populations of interest under physiological, injury, or diseased conditions. The method presented here is the first of its kind to offer an efficient step-by-step pipeline from intraperitoneal injections of the proliferative marker, 5-ethynyl-2′-deoxyuridine (EdU), to whole brain labeling, to a final embedded and cleared brain sample suitable for 3-D imaging using optical projection tomography (OPT). Moreover, this method allows potential for imaging GFP-reporter lines and cell-specific antibodies in the presence or absence of EdU. The small size of the adult zebrafish brain, the highly consistent degree of EdU labeling, and the use of basic clearing agents, benzyl benzoate, and benzyl alcohol, makes this method highly tractable for most laboratories interested in understanding the vertebrate central nervous system in health and disease. Post-processing of OPT-imaged adult zebrafish brains injected with EdU illustrate that proliferative patterns in EdU can readily be observed and analyzed using IMARIS and/or FIJI/IMAGEJ software. This protocol will be a valuable tool to unlock new ways of understanding systemic patterns in cell proliferation in the healthy and injured brain, brain-wide cellular interactions, stem cell niche development, and changes in brain morphology. PMID:29386991

Automatic detection of the hippocampal region associated with Alzheimer's disease from microscopic images of mice brain

NASA Astrophysics Data System (ADS)

Albaidhani, Tahseen; Hawkes, Cheryl; Jassim, Sabah; Al-Assam, Hisham

2016-05-01

The hippocampus is the region of the brain that is primarily associated with memory and spatial navigation. It is one of the first brain regions to be damaged when a person suffers from Alzheimer's disease. Recent research in this field has focussed on the assessment of damage to different blood vessels within the hippocampal region from a high throughput brain microscopic images. The ultimate aim of our research is the creation of an automatic system to count and classify different blood vessels such as capillaries, veins, and arteries in the hippocampus region. This work should provide biologists with efficient and accurate tools in their investigation of the causes of Alzheimer's disease. Locating the boundary of the Region of Interest in the hippocampus from microscopic images of mice brain is the first essential stage towards developing such a system. This task benefits from the variation in colour channels and texture between the two sides of the hippocampus and the boundary region. Accordingly, the developed initial step of our research to locating the hippocampus edge uses a colour-based segmentation of the brain image followed by Hough transforms on the colour channel that isolate the hippocampus region. The output is then used to split the brain image into two sides of the detected section of the boundary: the inside region and the outside region. Experimental results on a sufficiently number of microscopic images demonstrate the effectiveness of the developed solution.

Neuroimaging of Narcolepsy and Kleine-Levin Syndrome.

PubMed

Hong, Seung Bong

2017-09-01

Narcolepsy is a chronic neurologic disorder with the abnormal regulation of the sleep-wake cycle, resulting in excessive daytime sleepiness, disturbed nocturnal sleep, and manifestations related to rapid eye movement sleep, such as cataplexy, sleep paralysis, and hypnagogic hallucination. Over the past decade, numerous neuroimaging studies have been performed to characterize the pathophysiology and various clinical features of narcolepsy. This article reviews structural and functional brain imaging findings in narcolepsy and Kleine-Levin syndrome. Based on the current state of research, brain imaging is a useful tool to investigate and understand the neuroanatomic correlates and brain abnormalities of narcolepsy and other hypersomnia. Copyright © 2017 Elsevier Inc. All rights reserved.

Chemical imaging analysis of the brain with X-ray methods

NASA Astrophysics Data System (ADS)

Collingwood, Joanna F.; Adams, Freddy

2017-04-01

Cells employ various metal and metalloid ions to augment the structure and the function of proteins and to assist with vital biological processes. In the brain they mediate biochemical processes, and disrupted metabolism of metals may be a contributing factor in neurodegenerative disorders. In this tutorial review we will discuss the particular role of X-ray methods for elemental imaging analysis of accumulated metal species and metal-containing compounds in biological materials, in the context of post-mortem brain tissue. X-rays have the advantage that they have a short wavelength and can penetrate through a thick biological sample. Many of the X-ray microscopy techniques that provide the greatest sensitivity and specificity for trace metal concentrations in biological materials are emerging at synchrotron X-ray facilities. Here, the extremely high flux available across a wide range of soft and hard X-rays, combined with state-of-the-art focusing techniques and ultra-sensitive detectors, makes it viable to undertake direct imaging of a number of elements in brain tissue. The different methods for synchrotron imaging of metals in brain tissues at regional, cellular, and sub-cellular spatial resolution are discussed. Methods covered include X-ray fluorescence for elemental imaging, X-ray absorption spectrometry for speciation imaging, X-ray diffraction for structural imaging, phase contrast for enhanced contrast imaging and scanning transmission X-ray microscopy for spectromicroscopy. Two- and three-dimensional (confocal and tomographic) imaging methods are considered as well as the correlation of X-ray microscopy with other imaging tools.

Registration of in vivo MR to histology of rodent brains using blockface imaging

NASA Astrophysics Data System (ADS)

Uberti, Mariano; Liu, Yutong; Dou, Huanyu; Mosley, R. Lee; Gendelman, Howard E.; Boska, Michael

2009-02-01

Registration of MRI to histopathological sections can enhance bioimaging validation for use in pathobiologic, diagnostic, and therapeutic evaluations. However, commonly used registration methods fall short of this goal due to tissue shrinkage and tearing after brain extraction and preparation. In attempts to overcome these limitations we developed a software toolbox using 3D blockface imaging as the common space of reference. This toolbox includes a semi-automatic brain extraction technique using constraint level sets (CLS), 3D reconstruction methods for the blockface and MR volume, and a 2D warping technique using thin-plate splines with landmark optimization. Using this toolbox, the rodent brain volume is first extracted from the whole head MRI using CLS. The blockface volume is reconstructed followed by 3D brain MRI registration to the blockface volume to correct the global deformations due to brain extraction and fixation. Finally, registered MRI and histological slices are warped to corresponding blockface images to correct slice specific deformations. The CLS brain extraction technique was validated by comparing manual results showing 94% overlap. The image warping technique was validated by calculating target registration error (TRE). Results showed a registration accuracy of a TRE < 1 pixel. Lastly, the registration method and the software tools developed were used to validate cell migration in murine human immunodeficiency virus type one encephalitis.

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

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.

Simultaneous and Noninvasive Imaging of Cerebral Oxygen Metabolic Rate, Blood Flow and Oxygen Extraction Fraction in Stroke Mice

PubMed Central

Zhu, Xiao-Hong; Chen, James; Tu, Tsang-Wei; Chen, Wei; Song, Sheng-Kwei

2012-01-01

Many brain diseases have been linked to abnormal oxygen metabolism and blood perfusion; nevertheless, there is still a lack of robust diagnostic tools for directly imaging cerebral metabolic rate of oxygen (CMRO2) and cerebral blood flow (CBF), as well as the oxygen extraction fraction (OEF) that reflects the balance between CMRO2 and CBF. This study employed the recently developed in vivo 17O MR spectroscopic imaging to simultaneously assess CMRO2, CBF and OEF in the brain using a preclinical middle cerebral arterial occlusion mouse model with a brief inhalation of 17O-labeled oxygen gas. The results demonstrated high sensitivity and reliability of the noninvasive 17O-MR approach for rapidly imaging CMRO2, CBF and OEF abnormalities in the ischemic cortex of the MCAO mouse brain. It was found that in the ischemic brain regions both CMRO2 and CBF were substantially lower than that of intact brain regions, even for the mildly damaged brain regions that were unable to be clearly identified by the conventional MRI. In contrast, OEF was higher in the MCAO affected brain regions. This study demonstrates a promising 17O MRI technique for imaging abnormal oxygen metabolism and perfusion in the diseased brain regions. This 17O MRI technique is advantageous because of its robustness, simplicity, noninvasiveness and reliability: features that are essential to potentially translate it to human patients for early diagnosis and monitoring of treatment efficacy. PMID:23000789

Simultaneous and noninvasive imaging of cerebral oxygen metabolic rate, blood flow and oxygen extraction fraction in stroke mice.

PubMed

Zhu, Xiao-Hong; Chen, James M; Tu, Tsang-Wei; Chen, Wei; Song, Sheng-Kwei

2013-01-01

Many brain diseases have been linked to abnormal oxygen metabolism and blood perfusion; nevertheless, there is still a lack of robust diagnostic tools for directly imaging cerebral metabolic rate of oxygen (CMRO(2)) and cerebral blood flow (CBF), as well as the oxygen extraction fraction (OEF) that reflects the balance between CMRO(2) and CBF. This study employed the recently developed in vivo (17)O MR spectroscopic imaging to simultaneously assess CMRO(2), CBF and OEF in the brain using a preclinical middle cerebral arterial occlusion mouse model with a brief inhalation of (17)O-labeled oxygen gas. The results demonstrated high sensitivity and reliability of the noninvasive (17)O-MR approach for rapidly imaging CMRO(2), CBF and OEF abnormalities in the ischemic cortex of the MCAO mouse brain. It was found that in the ischemic brain regions both CMRO(2) and CBF were substantially lower than that of intact brain regions, even for the mildly damaged brain regions that were unable to be clearly identified by the conventional MRI. In contrast, OEF was higher in the MCAO affected brain regions. This study demonstrates a promising (17)O MRI technique for imaging abnormal oxygen metabolism and perfusion in the diseased brain regions. This (17)O MRI technique is advantageous because of its robustness, simplicity, noninvasiveness and reliability: features that are essential to potentially translate it to human patients for early diagnosis and monitoring of treatment efficacy. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantile rank maps: a new tool for understanding individual brain development.

PubMed

Chen, Huaihou; Kelly, Clare; Castellanos, F Xavier; He, Ye; Zuo, Xi-Nian; Reiss, Philip T

2015-05-01

We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample. Copyright © 2015 Elsevier Inc. All rights reserved.

New MR imaging assessment tool to define brain abnormalities in very preterm infants at term.

PubMed

Kidokoro, H; Neil, J J; Inder, T E

2013-01-01

WM injury is the dominant form of injury in preterm infants. However, other cerebral structures, including the deep gray matter and the cerebellum, can also be affected by injury and/or impaired growth. Current MR imaging injury assessment scales are subjective and are challenging to apply. Thus, we developed a new assessment tool and applied it to MR imaging studies obtained from very preterm infants at term age. MR imaging scans from 97 very preterm infants (< 30 weeks' gestation) and 22 healthy term-born infants were evaluated retrospectively. The severity of brain injury (defined by signal abnormalities) and impaired brain growth (defined with biometrics) was scored in the WM, cortical gray matter, deep gray matter, and cerebellum. Perinatal variables for clinical risks were collected. In very preterm infants, brain injury was observed in the WM (n=23), deep GM (n=5), and cerebellum (n=23). Combining measures of injury and impaired growth showed moderate to severe abnormalities most commonly in the WM (n=38) and cerebellum (n=32) but still notable in the cortical gray matter (n=16) and deep gray matter (n=11). WM signal abnormalities were associated with a reduced deep gray matter area but not with cerebellar abnormality. Intraventricular and/or parenchymal hemorrhage was associated with cerebellar signal abnormality and volume reduction. Multiple clinical risk factors, including prolonged intubation, prolonged parenteral nutrition, postnatal corticosteroid use, and postnatal sepsis, were associated with increased global abnormality on MR imaging. Very preterm infants demonstrate a high prevalence of injury and growth impairment in both the WM and gray matter. This MR imaging scoring system provides a more comprehensive and objective classification of the nature and extent of abnormalities than existing measures.

Toward a preoperative planning tool for brain tumor resection therapies.

PubMed

Coffey, Aaron M; Miga, Michael I; Chen, Ishita; Thompson, Reid C

2013-01-01

Neurosurgical procedures involving tumor resection require surgical planning such that the surgical path to the tumor is determined to minimize the impact on healthy tissue and brain function. This work demonstrates a predictive tool to aid neurosurgeons in planning tumor resection therapies by finding an optimal model-selected patient orientation that minimizes lateral brain shift in the field of view. Such orientations may facilitate tumor access and removal, possibly reduce the need for retraction, and could minimize the impact of brain shift on image-guided procedures. In this study, preoperative magnetic resonance images were utilized in conjunction with pre- and post-resection laser range scans of the craniotomy and cortical surface to produce patient-specific finite element models of intraoperative shift for 6 cases. These cases were used to calibrate a model (i.e., provide general rules for the application of patient positioning parameters) as well as determine the current model-based framework predictive capabilities. Finally, an objective function is proposed that minimizes shift subject to patient position parameters. Patient positioning parameters were then optimized and compared to our neurosurgeon as a preliminary study. The proposed model-driven brain shift minimization objective function suggests an overall reduction of brain shift by 23 % over experiential methods. This work recasts surgical simulation from a trial-and-error process to one where options are presented to the surgeon arising from an optimization of surgical goals. To our knowledge, this is the first realization of an evaluative tool for surgical planning that attempts to optimize surgical approach by means of shift minimization in this manner.

Resting-state functional brain connectivity: lessons from functional near-infrared spectroscopy.

PubMed

Niu, Haijing; He, Yong

2014-04-01

Resting-state functional near-infrared spectroscopy (R-fNIRS) is an active area of interest and is currently attracting considerable attention as a new imaging tool for the study of resting-state brain function. Using variations in hemodynamic concentration signals, R-fNIRS measures the brain's low-frequency spontaneous neural activity, combining the advantages of portability, low-cost, high temporal sampling rate and less physical burden to participants. The temporal synchronization of spontaneous neuronal activity in anatomically separated regions is referred to as resting-state functional connectivity (RSFC). In the past several years, an increasing body of R-fNIRS RSFC studies has led to many important findings about functional integration among local or whole-brain regions by measuring inter-regional temporal synchronization. Here, we summarize recent advances made in the R-fNIRS RSFC methodologies, from the detection of RSFC (e.g., seed-based correlation analysis, independent component analysis, whole-brain correlation analysis, and graph-theoretical topological analysis), to the assessment of RSFC performance (e.g., reliability, repeatability, and validity), to the application of RSFC in studying normal development and brain disorders. The literature reviewed here suggests that RSFC analyses based on R-fNIRS data are valid and reliable for the study of brain function in healthy and diseased populations, thus providing a promising imaging tool for cognitive science and clinics.

Statistical parametric mapping of stimuli-evoked changes in quantitative blood flow using extended-focus optical coherence microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Marchand, Paul J.; Bouwens, Arno; Shamaei, Vincent; Nguyen, David; Extermann, Jerome; Bolmont, Tristan; Lasser, Theo

2016-03-01

Magnetic Resonance Imaging has revolutionised our understanding of brain function through its ability to image human cerebral structures non-invasively over the entire brain. By exploiting the different magnetic properties of oxygenated and deoxygenated blood, functional MRI can indirectly map areas undergoing neural activation. Alongside the development of fMRI, powerful statistical tools have been developed in an effort to shed light on the neural pathways involved in processing of sensory and cognitive information. In spite of the major improvements made in fMRI technology, the obtained spatial resolution of hundreds of microns prevents MRI in resolving and monitoring processes occurring at the cellular level. In this regard, Optical Coherence Microscopy is an ideal instrumentation as it can image at high spatio-temporal resolution. Moreover, by measuring the mean and the width of the Doppler spectra of light scattered by moving particles, OCM allows extracting the axial and lateral velocity components of red blood cells. The ability to assess quantitatively total blood velocity, as opposed to classical axial velocity Doppler OCM, is of paramount importance in brain imaging as a large proportion of cortical vascular is oriented perpendicularly to the optical axis. We combine here quantitative blood flow imaging with extended-focus Optical Coherence Microscopy and Statistical Parametric Mapping tools to generate maps of stimuli-evoked cortical hemodynamics at the capillary level.

Advances in Light Microscopy for Neuroscience

PubMed Central

Wilt, Brian A.; Burns, Laurie D.; Ho, Eric Tatt Wei; Ghosh, Kunal K.; Mukamel, Eran A.

2010-01-01

Since the work of Golgi and Cajal, light microscopy has remained a key tool for neuroscientists to observe cellular properties. Ongoing advances have enabled new experimental capabilities using light to inspect the nervous system across multiple spatial scales, including ultrastructural scales finer than the optical diffraction limit. Other progress permits functional imaging at faster speeds, at greater depths in brain tissue, and over larger tissue volumes than previously possible. Portable, miniaturized fluorescence microscopes now allow brain imaging in freely behaving mice. Complementary progress on animal preparations has enabled imaging in head-restrained behaving animals, as well as time-lapse microscopy studies in the brains of live subjects. Mouse genetic approaches permit mosaic and inducible fluorescence-labeling strategies, whereas intrinsic contrast mechanisms allow in vivo imaging of animals and humans without use of exogenous markers. This review surveys such advances and highlights emerging capabilities of particular interest to neuroscientists. PMID:19555292

Automated metastatic brain lesion detection: a computer aided diagnostic and clinical research tool

NASA Astrophysics Data System (ADS)

Devine, Jeremy; Sahgal, Arjun; Karam, Irene; Martel, Anne L.

2016-03-01

The accurate localization of brain metastases in magnetic resonance (MR) images is crucial for patients undergoing stereotactic radiosurgery (SRS) to ensure that all neoplastic foci are targeted. Computer automated tumor localization and analysis can improve both of these tasks by eliminating inter and intra-observer variations during the MR image reading process. Lesion localization is accomplished using adaptive thresholding to extract enhancing objects. Each enhancing object is represented as a vector of features which includes information on object size, symmetry, position, shape, and context. These vectors are then used to train a random forest classifier. We trained and tested the image analysis pipeline on 3D axial contrast-enhanced MR images with the intention of localizing the brain metastases. In our cross validation study and at the most effective algorithm operating point, we were able to identify 90% of the lesions at a precision rate of 60%.

Automated three-dimensional quantification of myocardial perfusion and brain SPECT.

PubMed

Slomka, P J; Radau, P; Hurwitz, G A; Dey, D

2001-01-01

To allow automated and objective reading of nuclear medicine tomography, we have developed a set of tools for clinical analysis of myocardial perfusion tomography (PERFIT) and Brain SPECT/PET (BRASS). We exploit algorithms for image registration and use three-dimensional (3D) "normal models" for individual patient comparisons to composite datasets on a "voxel-by-voxel basis" in order to automatically determine the statistically significant abnormalities. A multistage, 3D iterative inter-subject registration of patient images to normal templates is applied, including automated masking of the external activity before final fit. In separate projects, the software has been applied to the analysis of myocardial perfusion SPECT, as well as brain SPECT and PET data. Automatic reading was consistent with visual analysis; it can be applied to the whole spectrum of clinical images, and aid physicians in the daily interpretation of tomographic nuclear medicine images.

Correlation of neurocognitive function and brain lesion load on magnetic resonance imaging in systemic lupus erythematosus.

PubMed

Roldan, Paola C; Jung, Rex E; Sibbitt, Wilmer L; Qualls, Clifford R; Flores, Ranee A; Roldan, Carlos A

2018-06-13

Neurocognitive dysfunction and brain injury on magnetic resonance imaging (MRI) are common in patients with systemic lupus erythematosus (SLE) and are associated with increased morbidity and mortality. However, brain MRI is expensive, is restricted by payers, and requires high expertise. Neurocognitive assessment is an easily available, safe, and inexpensive clinical tool that may select patients needing brain MRI. In this cross-sectional and controlled study, 76 SLE patients (69 women, age 37 ± 12 years) and 26 age and gender-matched healthy subjects (22 women, age 34 ± 11 years) underwent assessment of attention, memory, processing speed, executive function, motor function, and global neurocognitive function. All subjects underwent brain MRI with T1-weighted, fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging. Hemispheric and whole brain lesion load in cm 3 were determined using semi-automated methods. Neurocognitive z-scores in all clinical domains were significantly lower and whole brain and right and left hemispheres brain lesion load were significantly greater in patients than in controls (all p ≤ 0.02). There was significant correlation between neurocognitive z-scores in all domains and whole brain lesion load: processing speed (r = - 0.46; p < 0.0001), attention (r = - 0.42; p < 0.001), memory (r = - 0.40; p = 0.0004), executive function (r = - 0.25; p = 0.03), motor function (r = - 0.25; p = 0.05), and global neurocognitive function (r = - 0.38; p = 0.006). Similar correlations were found for brain hemisphere lesion loads (all p ≤ 0.05). These correlations were strengthened when adjusted for glucocorticoid therapy and SLE disease activity index. Finally, global neurocognitive z-score and erythrosedimentation rate were the only independent predictors of whole brain lesion load (both p ≤ 0.007). Neurocognitive measures and brain lesion load are worse in SLE patients than in controls. In SLE patients, neurocognitive z-scores correlate negatively with and independently predict brain lesion load. Therefore, neurocognitive testing may be an effective clinical tool to select patients needing brain MRI.

MO-C-17A-13: Uncertainty Evaluation of CT Image Deformable Registration for H and N Cancer Adaptive Radiotherapy

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

Qin, A; Yan, D

2014-06-15

Purpose: To evaluate uncertainties of organ specific Deformable Image Registration (DIR) for H and N cancer Adaptive Radiation Therapy (ART). Methods: A commercial DIR evaluation tool, which includes a digital phantom library of 8 patients, and the corresponding “Ground truth Deformable Vector Field” (GT-DVF), was used in the study. Each patient in the phantom library includes the GT-DVF created from a pair of CT images acquired prior to and at the end of the treatment course. Five DIR tools, including 2 commercial tools (CMT1, CMT2), 2 in-house (IH-FFD1, IH-FFD2), and a classic DEMON algorithms, were applied on the patient images.more » The resulting DVF was compared to the GT-DVF voxel by voxel. Organ specific DVF uncertainty was calculated for 10 ROIs: Whole Body, Brain, Brain Stem, Cord, Lips, Mandible, Parotid, Esophagus and Submandibular Gland. Registration error-volume histogram was constructed for comparison. Results: The uncertainty is relatively small for brain stem, cord and lips, while large in parotid and submandibular gland. CMT1 achieved best overall accuracy (on whole body, mean vector error of 8 patients: 0.98±0.29 mm). For brain, mandible, parotid right, parotid left and submandibular glad, the classic Demon algorithm got the lowest uncertainty (0.49±0.09, 0.51±0.16, 0.46±0.11, 0.50±0.11 and 0.69±0.47 mm respectively). For brain stem, cord and lips, the DVF from CMT1 has the best accuracy (0.28±0.07, 0.22±0.08 and 0.27±0.12 mm respectively). All algorithms have largest right parotid uncertainty on patient #7, which has image artifact caused by tooth implantation. Conclusion: Uncertainty of deformable CT image registration highly depends on the registration algorithm, and organ specific. Large uncertainty most likely appears at the location of soft-tissue organs far from the bony structures. Among all 5 DIR methods, the classic DEMON and CMT1 seem to be the best to limit the uncertainty within 2mm for all OARs. Partially supported by research grant from Elekta.« less

Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging.

PubMed

Mohseni Salehi, Seyed Sadegh; Erdogmus, Deniz; Gholipour, Ali

2017-11-01

Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines. The accuracy and the robustness of brain extraction, therefore, are crucial for the accuracy of the entire brain analysis process. The state-of-the-art brain extraction techniques rely heavily on the accuracy of alignment or registration between brain atlases and query brain anatomy, and/or make assumptions about the image geometry, and therefore have limited success when these assumptions do not hold or image registration fails. With the aim of designing an accurate, learning-based, geometry-independent, and registration-free brain extraction tool, in this paper, we present a technique based on an auto-context convolutional neural network (CNN), in which intrinsic local and global image features are learned through 2-D patches of different window sizes. We consider two different architectures: 1) a voxelwise approach based on three parallel 2-D convolutional pathways for three different directions (axial, coronal, and sagittal) that implicitly learn 3-D image information without the need for computationally expensive 3-D convolutions and 2) a fully convolutional network based on the U-net architecture. Posterior probability maps generated by the networks are used iteratively as context information along with the original image patches to learn the local shape and connectedness of the brain to extract it from non-brain tissue. The brain extraction results we have obtained from our CNNs are superior to the recently reported results in the literature on two publicly available benchmark data sets, namely, LPBA40 and OASIS, in which we obtained the Dice overlap coefficients of 97.73% and 97.62%, respectively. Significant improvement was achieved via our auto-context algorithm. Furthermore, we evaluated the performance of our algorithm in the challenging problem of extracting arbitrarily oriented fetal brains in reconstructed fetal brain magnetic resonance imaging (MRI) data sets. In this application, our voxelwise auto-context CNN performed much better than the other methods (Dice coefficient: 95.97%), where the other methods performed poorly due to the non-standard orientation and geometry of the fetal brain in MRI. Through training, our method can provide accurate brain extraction in challenging applications. This, in turn, may reduce the problems associated with image registration in segmentation tasks.

3D Slicer as a tool for interactive brain tumor segmentation.

PubMed

Kikinis, Ron; Pieper, Steve

2011-01-01

User interaction is required for reliable segmentation of brain tumors in clinical practice and in clinical research. By incorporating current research tools, 3D Slicer provides a set of interactive, easy to use tools that can be efficiently used for this purpose. One of the modules of 3D Slicer is an interactive editor tool, which contains a variety of interactive segmentation effects. Use of these effects for fast and reproducible segmentation of a single glioblastoma from magnetic resonance imaging data is demonstrated. The innovation in this work lies not in the algorithm, but in the accessibility of the algorithm because of its integration into a software platform that is practical for research in a clinical setting.

A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain.

PubMed

Arganda-Carreras, Ignacio; Manoliu, Tudor; Mazuras, Nicolas; Schulze, Florian; Iglesias, Juan E; Bühler, Katja; Jenett, Arnim; Rouyer, François; Andrey, Philippe

2018-01-01

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila , one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species.

Classification of stroke disease using convolutional neural network

NASA Astrophysics Data System (ADS)

Marbun, J. T.; Seniman; Andayani, U.

2018-03-01

Stroke is a condition that occurs when the blood supply stop flowing to the brain because of a blockage or a broken blood vessel. A symptoms that happen when experiencing stroke, some of them is a dropped consciousness, disrupted vision and paralyzed body. The general examination is being done to get a picture of the brain part that have stroke using Computerized Tomography (CT) Scan. The image produced from CT will be manually checked and need a proper lighting by doctor to get a type of stroke. That is why it needs a method to classify stroke from CT image automatically. A method proposed in this research is Convolutional Neural Network. CT image of the brain is used as the input for image processing. The stage before classification are image processing (Grayscaling, Scaling, Contrast Limited Adaptive Histogram Equalization, then the image being classified with Convolutional Neural Network. The result then showed that the method significantly conducted was able to be used as a tool to classify stroke disease in order to distinguish the type of stroke from CT image.

Wavelet-enhanced convolutional neural network: a new idea in a deep learning paradigm.

PubMed

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

2018-05-29

Manual brain tumor segmentation is a challenging task that requires the use of machine learning techniques. One of the machine learning techniques that has been given much attention is the convolutional neural network (CNN). The performance of the CNN can be enhanced by combining other data analysis tools such as wavelet transform. In this study, one of the famous implementations of CNN, a fully convolutional network (FCN), was used in brain tumor segmentation and its architecture was enhanced by wavelet transform. In this combination, a wavelet transform was used as a complementary and enhancing tool for CNN in brain tumor segmentation. Comparing the performance of basic FCN architecture against the wavelet-enhanced form revealed a remarkable superiority of enhanced architecture in brain tumor segmentation tasks. Using mathematical functions and enhancing tools such as wavelet transform and other mathematical functions can improve the performance of CNN in any image processing task such as segmentation and classification.

Raman spectroscopic imaging as complementary tool for histopathologic assessment of brain tumors

NASA Astrophysics Data System (ADS)

Krafft, Christoph; Bergner, Norbert; Romeike, Bernd; Reichart, Rupert; Kalff, Rolf; Geiger, Kathrin; Kirsch, Matthias; Schackert, Gabriele; Popp, Jürgen

2012-02-01

Raman spectroscopy enables label-free assessment of brain tissues and tumors based on their biochemical composition. Combination of the Raman spectra with the lateral information allows grading of tumors, determining the primary tumor of brain metastases and delineating tumor margins - even during surgery after coupling with fiber optic probes. This contribution presents exemplary Raman spectra and images collected from low grade and high grade regions of astrocytic gliomas and brain metastases. A region of interest in dried tissue sections encompassed slightly increased cell density. Spectral unmixing by vertex component analysis (VCA) and N-FINDR resolved cell nuclei in score plots and revealed the spectral contributions of nucleic acids, cholesterol, cholesterol ester and proteins in endmember signatures. The results correlated with the histopathological analysis after staining the specimens by hematoxylin and eosin. For a region of interest in non-dried, buffer immersed tissue sections image processing was not affected by drying artifacts such as denaturation of biomolecules and crystallization of cholesterol. Consequently, the results correspond better to in vivo situations. Raman spectroscopic imaging of a brain metastases from renal cell carcinoma showed an endmember with spectral contributions of glycogen which can be considered as a marker for this primary tumor.

Geometry Processing of Conventionally Produced Mouse Brain Slice Images.

PubMed

Agarwal, Nitin; Xu, Xiangmin; Gopi, M

2018-04-21

Brain mapping research in most neuroanatomical laboratories relies on conventional processing techniques, which often introduce histological artifacts such as tissue tears and tissue loss. In this paper we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space. This is achieved first by constructing a virtual 3D mouse brain model from annotated slices of Allen Reference Atlas (ARA). Virtual re-slicing of the reconstructed model generates ARA-based slice images corresponding to the microscopic images of histological brain sections. These image pairs are aligned using a geometric approach through contour images. Histological artifacts in the microscopic images are detected and removed using Constrained Delaunay Triangulation before performing global alignment. Finally, non-linear registration is performed by solving Laplace's equation with Dirichlet boundary conditions. Our methods provide significant improvements over previously reported registration techniques for the tested slices in 3D space, especially on slices with significant histological artifacts. Further, as one of the application we count the number of neurons in various anatomical regions using a dataset of 51 microscopic slices from a single mouse brain. To the best of our knowledge the presented work is the first that automatically registers both clean as well as highly damaged high-resolutions histological slices of mouse brain to a 3D annotated reference atlas space. This work represents a significant contribution to this subfield of neuroscience as it provides tools to neuroanatomist for analyzing and processing histological data. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessment of the usefulness of magnetic resonance brain imaging in patients presenting with acute seizures.

PubMed

Olszewska, D A; Costello, D J

2014-12-01

Magnetic Resonance Imaging (MRI) is increasingly available as a tool for assessment of patients presenting to acute services with seizures. We set out to prospectively determine the usefulness of early MRI brain in a cohort of patients presenting with acute seizures. We examined the MR imaging studies performed in patients admitted solely because of acute seizures to Cork University Hospital over a 12-month period. The main aim of the study was to determine if the MRI established the proximate cause for the patient's recent seizure. We identified 91 patients who underwent MRI brain within 48 h of admission for seizures. Of the 91 studies, 51 were normal (56 %). The remaining 40 studies were abnormal as follows: microvascular disease (usually moderate/severe) (n = 19), post-traumatic gliosis (n = 7), remote symptomatic lesion (n = 6), primary brain tumour (n = 5), venous sinus thrombosis (n = 3), developmental lesion (n = 3), post-surgical gliosis (n = 3) and single cases of demyelination, unilateral hippocampal sclerosis, lobar haemorrhage and metastatic malignant melanoma. Abnormalities in diffusion-weighted sequences that were attributable to prolonged ictal activity were seen in nine patients, all of who had significant ongoing clinical deficits, most commonly delirium. Of the 40 patients with abnormal MRI studies, seven patients had unremarkable CT brain. MR brain imaging revealed the underlying cause for acute seizures in 44 % of patients. CT brain imaging failed to detect the cause of the acute seizures in 19 % of patients in whom subsequent MRI established the cause. This study emphasises the importance of obtaining optimal imaging in people admitted with acute seizures.

Real-time functional magnetic imaging-brain-computer interface and virtual reality promising tools for the treatment of pedophilia.

PubMed

Renaud, Patrice; Joyal, Christian; Stoleru, Serge; Goyette, Mathieu; Weiskopf, Nikolaus; Birbaumer, Niels

2011-01-01

This chapter proposes a prospective view on using a real-time functional magnetic imaging (rt-fMRI) brain-computer interface (BCI) application as a new treatment for pedophilia. Neurofeedback mediated by interactive virtual stimuli is presented as the key process in this new BCI application. Results on the diagnostic discriminant power of virtual characters depicting sexual stimuli relevant to pedophilia are given. Finally, practical and ethical implications are briefly addressed. Copyright © 2011 Elsevier B.V. All rights reserved.

Efficacy of Distortion Correction on Diffusion Imaging: Comparison of FSL Eddy and Eddy_Correct Using 30 and 60 Directions Diffusion Encoding

PubMed Central

Yamada, Haruyasu; Abe, Osamu; Shizukuishi, Takashi; Kikuta, Junko; Shinozaki, Takahiro; Dezawa, Ko; Nagano, Akira; Matsuda, Masayuki; Haradome, Hiroki; Imamura, Yoshiki

2014-01-01

Diffusion imaging is a unique noninvasive tool to detect brain white matter trajectory and integrity in vivo. However, this technique suffers from spatial distortion and signal pileup or dropout originating from local susceptibility gradients and eddy currents. Although there are several methods to mitigate these problems, most techniques can be applicable either to susceptibility or eddy-current induced distortion alone with a few exceptions. The present study compared the correction efficiency of FSL tools, “eddy_correct” and the combination of “eddy” and “topup” in terms of diffusion-derived fractional anisotropy (FA). The brain diffusion images were acquired from 10 healthy subjects using 30 and 60 directions encoding schemes based on the electrostatic repulsive forces. For the 30 directions encoding, 2 sets of diffusion images were acquired with the same parameters, except for the phase-encode blips which had opposing polarities along the anteroposterior direction. For the 60 directions encoding, non–diffusion-weighted and diffusion-weighted images were obtained with forward phase-encoding blips and non–diffusion-weighted images with the same parameter, except for the phase-encode blips, which had opposing polarities. FA images without and with distortion correction were compared in a voxel-wise manner with tract-based spatial statistics. We showed that images corrected with eddy and topup possessed higher FA values than images uncorrected and corrected with eddy_correct with trilinear (FSL default setting) or spline interpolation in most white matter skeletons, using both encoding schemes. Furthermore, the 60 directions encoding scheme was superior as measured by increased FA values to the 30 directions encoding scheme, despite comparable acquisition time. This study supports the combination of eddy and topup as a superior correction tool in diffusion imaging rather than the eddy_correct tool, especially with trilinear interpolation, using 60 directions encoding scheme. PMID:25405472

Efficacy of distortion correction on diffusion imaging: comparison of FSL eddy and eddy_correct using 30 and 60 directions diffusion encoding.

PubMed

Yamada, Haruyasu; Abe, Osamu; Shizukuishi, Takashi; Kikuta, Junko; Shinozaki, Takahiro; Dezawa, Ko; Nagano, Akira; Matsuda, Masayuki; Haradome, Hiroki; Imamura, Yoshiki

2014-01-01

Diffusion imaging is a unique noninvasive tool to detect brain white matter trajectory and integrity in vivo. However, this technique suffers from spatial distortion and signal pileup or dropout originating from local susceptibility gradients and eddy currents. Although there are several methods to mitigate these problems, most techniques can be applicable either to susceptibility or eddy-current induced distortion alone with a few exceptions. The present study compared the correction efficiency of FSL tools, "eddy_correct" and the combination of "eddy" and "topup" in terms of diffusion-derived fractional anisotropy (FA). The brain diffusion images were acquired from 10 healthy subjects using 30 and 60 directions encoding schemes based on the electrostatic repulsive forces. For the 30 directions encoding, 2 sets of diffusion images were acquired with the same parameters, except for the phase-encode blips which had opposing polarities along the anteroposterior direction. For the 60 directions encoding, non-diffusion-weighted and diffusion-weighted images were obtained with forward phase-encoding blips and non-diffusion-weighted images with the same parameter, except for the phase-encode blips, which had opposing polarities. FA images without and with distortion correction were compared in a voxel-wise manner with tract-based spatial statistics. We showed that images corrected with eddy and topup possessed higher FA values than images uncorrected and corrected with eddy_correct with trilinear (FSL default setting) or spline interpolation in most white matter skeletons, using both encoding schemes. Furthermore, the 60 directions encoding scheme was superior as measured by increased FA values to the 30 directions encoding scheme, despite comparable acquisition time. This study supports the combination of eddy and topup as a superior correction tool in diffusion imaging rather than the eddy_correct tool, especially with trilinear interpolation, using 60 directions encoding scheme.

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.

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

PubMed

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

2018-06-01

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

Simultaneous imaging of cerebral partial pressure of oxygen and blood flow during functional activation and cortical spreading depression

PubMed Central

Sakadžić, Sava; Yuan, Shuai; Dilekoz, Ergin; Ruvinskaya, Svetlana; Vinogradov, Sergei A.; Ayata, Cenk; Boas, David A.

2009-01-01

We developed a novel imaging technique that provides real-time two-dimensional maps of the absolute partial pressure of oxygen and relative cerebral blood flow in rats by combining phosphorescence lifetime imaging with laser speckle contrast imaging. Direct measurement of blood oxygenation based on phosphorescence lifetime is not significantly affected by changes in the optical parameters of the tissue during the experiment. The potential of the system as a novel tool for quantitative analysis of the dynamic delivery of oxygen to support brain metabolism was demonstrated in rats by imaging cortical responses to forepaw stimulation and the propagation of cortical spreading depression waves. This new instrument will enable further study of neurovascular coupling in normal and diseased brain. PMID:19340106

Multifunctional Nanoparticles for Brain Tumor Diagnosis and Therapy

PubMed Central

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

2013-01-01

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

Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

PubMed Central

Sunkin, Susan M.; Ng, Lydia; Lau, Chris; Dolbeare, Tim; Gilbert, Terri L.; Thompson, Carol L.; Hawrylycz, Michael; Dang, Chinh

2013-01-01

The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal. PMID:23193282

Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition

PubMed Central

Li, Wei; Wu, Bing; Liu, Chunlei

2011-01-01

Image phase from gradient echo MRI provides a unique contrast that reflects brain tissue composition variations, such as iron and myelin distribution. Phase imaging is emerging as a powerful tool for the investigation of functional brain anatomy and disease diagnosis. However, the quantitative value of phase is compromised by its nonlocal and orientation dependent properties. There is an increasing need for reliable quantification of magnetic susceptibility, the intrinsic property of tissue. In this study, we developed a novel and accurate susceptibility mapping method that is also phase-wrap insensitive. The proposed susceptibility mapping method utilized two complementary equations: (1) the Fourier relationship of phase and magnetic susceptibility; and (2) the first-order partial derivative of the first equation in the spatial frequency domain. In numerical simulation, this method reconstructed the susceptibility map almost free of streaking artifact. Further, the iterative implementation of this method allowed for high quality reconstruction of susceptibility maps of human brain in vivo. The reconstructed susceptibility map provided excellent contrast of iron-rich deep nuclei and white matter bundles from surrounding tissues. Further, it also revealed anisotropic magnetic susceptibility in brain white matter. Hence, the proposed susceptibility mapping method may provide a powerful tool for the study of brain physiology and pathophysiology. Further elucidation of anisotropic magnetic susceptibility in vivo may allow us to gain more insight into the white matter microarchitectures. PMID:21224002

Utility of 68Ga-PSMA-11 PET/CT in Imaging of Glioma-A Pilot Study.

PubMed

Sasikumar, Arun; Kashyap, Raghava; Joy, Ajith; Charan Patro, Kanhu; Bhattacharya, Parthasarathy; Reddy Pilaka, Venkata Krishna; Oommen, Karuna Elza; Pillai, Maroor Raghavan Ambikalmajan

2018-06-22

Imaging of gliomas remains challenging. The aim of the study was to assess the feasibility of using Ga-PSMA-11 PET/CT for imaging gliomas. Fifteen patients with glioma from 2 centers were included in the study. Ten patients were treated cases of glioblastoma with suspected recurrence. Two patients were sent for assessing the nature (primary lesion/metastasis) of space-occupying lesion in the brain; 3 patients were imaged immediately after surgery and before radiotherapy. Target-to-background ratios (TBR) for the brain lesions were calculated using contralateral cerebellar uptake as background. Among the 10 cases with suspected recurrence, scan was positive in 9, subsequent surgery was done, and histopathology proved it to be true recurrence. In the scan-negative case on follow-up, no evidence of disease could be made clinically or radiologically. Among the other cases the presence or absence of disease could be unequivocally identified on the Ga-PSMA-11 brain scan and correlated with the histopathology or other imaging. Apart from the visual assessment quantitative assessment of the lesions with TBR also showed a significantly high TBR value for those with true disease compared with those with no disease. In the evaluation of gliomas, Ga-PSMA-11 PET/CT brain imaging is a potentially useful imaging tool. The use of Ga-PSMA-11 brain PET/CT in evaluation of recurrent glioma seems promising. Absence of physiological uptake of Ga-PSMA-11 in the normal brain parenchyma results in high TBR values and consequently better visualization of glioma lesions.

Predicting consumer behavior: using novel mind-reading approaches.

PubMed

Calvert, Gemma A; Brammer, Michael J

2012-01-01

Advances in machine learning as applied to functional magnetic resonance imaging (fMRI) data offer the possibility of pretesting and classifying marketing communications using unbiased pattern recognition algorithms. By using these algorithms to analyze brain responses to brands, products, or existing marketing communications that either failed or succeeded in the marketplace and identifying the patterns of brain activity that characterize success or failure, future planned campaigns or new products can now be pretested to determine how well the resulting brain responses match the desired (successful) pattern of brain activity without the need for verbal feedback. This major advance in signal processing is poised to revolutionize the application of these brain-imaging techniques in the marketing sector by offering greater accuracy of prediction in terms of consumer acceptance of new brands, products, and campaigns at a speed that makes them accessible as routine pretesting tools that will clearly demonstrate return on investment.

aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data

PubMed Central

Niedworok, Christian J.; Brown, Alexander P. Y.; Jorge Cardoso, M.; Osten, Pavel; Ourselin, Sebastien; Modat, Marc; Margrie, Troy W.

2016-01-01

The validation of automated image registration and segmentation is crucial for accurate and reliable mapping of brain connectivity and function in three-dimensional (3D) data sets. While validation standards are necessarily high and routinely met in the clinical arena, they have to date been lacking for high-resolution microscopy data sets obtained from the rodent brain. Here we present a tool for optimized automated mouse atlas propagation (aMAP) based on clinical registration software (NiftyReg) for anatomical segmentation of high-resolution 3D fluorescence images of the adult mouse brain. We empirically evaluate aMAP as a method for registration and subsequent segmentation by validating it against the performance of expert human raters. This study therefore establishes a benchmark standard for mapping the molecular function and cellular connectivity of the rodent brain. PMID:27384127

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

PubMed

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

2017-11-01

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

Towards hyperpolarized 13C-succinate imaging of brain cancer

PubMed Central

Bhattacharya, Pratip; Chekmenev, Eduard Y.; Perman, William H.; Harris, Kent C.; Lin, Alexander P.; Norton, Valerie A.; Tan, Chou T.; Ross, Brian D.; Weitekamp, Daniel P.

2009-01-01

We describe a novel 13C enriched precursor molecule, sodium 1-13C acetylenedicarboxylate, which after hydrogenation by PASADE-NA (Parahydrogen and Synthesis Allows Dramatically Enhanced Nuclear Alignment) under controlled experimental conditions, becomes hyperpolarized 13C sodium succinate. Fast in vivo 3D FIESTA MR imaging demonstrated that, following carotid arterial injection, the hyperpolarized 13C-succinate appeared in the head and cerebral circulation of normal and tumor-bearing rats. At this time, no in vivo hyperpolarized signal has been localized to normal brain or brain tumor. On the other hand, ex vivo samples of brain harvested from rats bearing a 9L brain tumor, 1 h or more following in vivo carotid injection of hyperpolarized 13C sodium succinate, contained significant concentrations of the injected substrate, 13C sodium succinate, together with 13C maleate and succinate metabolites 1-13C-glutamate, 5-13C-glutamate, 1-13C-glutamine and 5-13C-glutamine. The 13C substrates and products were below the limits of NMR detection in ex vivo samples of normal brain consistent with an intact blood–brain barrier. These ex vivo results indicate that hyperpolarized 13C sodium succinate may become a useful tool for rapid in vivo identification of brain tumors, providing novel biomarkers in 13C MR spectral-spatial images. PMID:17303454

Towards hyperpolarized 13C-succinate imaging of brain cancer

NASA Astrophysics Data System (ADS)

Bhattacharya, Pratip; Chekmenev, Eduard Y.; Perman, William H.; Harris, Kent C.; Lin, Alexander P.; Norton, Valerie A.; Tan, Chou T.; Ross, Brian D.; Weitekamp, Daniel P.

2007-05-01

We describe a novel 13C enriched precursor molecule, sodium 1- 13C acetylenedicarboxylate, which after hydrogenation by PASADENA (Parahydrogen and Synthesis Allows Dramatically Enhanced Nuclear Alignment) under controlled experimental conditions, becomes hyperpolarized 13C sodium succinate. Fast in vivo 3D FIESTA MR imaging demonstrated that, following carotid arterial injection, the hyperpolarized 13C-succinate appeared in the head and cerebral circulation of normal and tumor-bearing rats. At this time, no in vivo hyperpolarized signal has been localized to normal brain or brain tumor. On the other hand, ex vivo samples of brain harvested from rats bearing a 9L brain tumor, 1 h or more following in vivo carotid injection of hyperpolarized 13C sodium succinate, contained significant concentrations of the injected substrate, 13C sodium succinate, together with 13C maleate and succinate metabolites 1- 13C-glutamate, 5- 13C-glutamate, 1- 13C-glutamine and 5- 13C-glutamine. The 13C substrates and products were below the limits of NMR detection in ex vivo samples of normal brain consistent with an intact blood-brain barrier. These ex vivo results indicate that hyperpolarized 13C sodium succinate may become a useful tool for rapid in vivo identification of brain tumors, providing novel biomarkers in 13C MR spectral-spatial images.

Advanced neuroimaging techniques for the term newborn with encephalopathy.

PubMed

Chau, Vann; Poskitt, Kenneth John; Miller, Steven Paul

2009-03-01

Neonatal encephalopathy is associated with a high risk of morbidity and mortality in the neonatal period and of long-term neurodevelopmental disability in survivors. Advanced magnetic resonance techniques now play a major role in the clinical care of newborns with encephalopathy and in research addressing this important condition. From conventional magnetic resonance imaging, typical patterns of injury have been defined in neonatal encephalopathy. When applied in contemporary cohorts of newborns with encephalopathy, the patterns of brain injury on magnetic resonance imaging distinguish risk factors, clinical presentation, and risk of abnormal outcome. Advanced magnetic resonance techniques such as magnetic resonance spectroscopy, diffusion-weighted imaging, and diffusion tensor imaging provide novel perspectives on neonatal brain metabolism, microstructure, and connectivity. With the application of these imaging tools, it is increasingly apparent that brain injury commonly occurs at or near the time of birth and evolves over the first weeks of life. These observations have complemented findings from trials of emerging strategies of brain protection, such as hypothermia. Application of these advanced magnetic resonance techniques may enable the earliest possible identification of newborns at risk of neurodevelopmental impairment, thereby ensuring appropriate follow-up with rehabilitation and psychoeducational resources.

Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis.

PubMed

Goch, Caspar J; Stieltjes, Bram; Henze, Romy; Hering, Jan; Poustka, Luise; Meinzer, Hans-Peter; Maier-Hein, Klaus H

2014-05-01

Diagnosis of autism spectrum disorders (ASD) is difficult, as symptoms vary greatly and are difficult to quantify objectively. Recent work has focused on the assessment of non-invasive diffusion tensor imaging-based biomarkers that reflect the microstructural characteristics of neuronal pathways in the brain. While tractography-based approaches typically analyze specific structures of interest, a graph-based large-scale network analysis of the connectome can yield comprehensive measures of larger-scale architectural patterns in the brain. Commonly applied global network indices, however, do not provide any specificity with respect to functional areas or anatomical structures. Aim of this work was to assess the concept of network centrality as a tool to perform locally specific analysis without disregarding the global network architecture and compare it to other popular network indices. We create connectome networks from fiber tractographies and parcellations of the human brain and compute global network indices as well as local indices for Wernicke's Area, Broca's Area and the Motor Cortex. Our approach was evaluated on 18 children suffering from ASD and 18 typically developed controls using magnetic resonance imaging-based cortical parcellations in combination with diffusion tensor imaging tractography. We show that the network centrality of Wernicke's area is significantly (p<0.001) reduced in ASD, while the motor cortex, which was used as a control region, did not show significant alterations. This could reflect the reduced capacity for comprehension of language in ASD. The betweenness centrality could potentially be an important metric in the development of future diagnostic tools in the clinical context of ASD diagnosis. Our results further demonstrate the applicability of large-scale network analysis tools in the domain of region-specific analysis with a potential application in many different psychological disorders.

Automated Morphological Analysis of Microglia After Stroke.

PubMed

Heindl, Steffanie; Gesierich, Benno; Benakis, Corinne; Llovera, Gemma; Duering, Marco; Liesz, Arthur

2018-01-01

Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.

NeuroImaging Radiological Interpretation System (NIRIS) for Acute Traumatic Brain Injury (TBI).

PubMed

Wintermark, Max; Li, Ying; Ding, Victoria Y; Xu, Yingding; Jiang, Bin; Ball, Robyn L; Zeineh, Michael; Gean, Alisa; Sanelli, Pina

2018-04-18

To develop an outcome-based NeuroImaging Radiological Interpretation System (NIRIS) for acute traumatic brain injury (TBI) patients that would standardize the interpretation of non-contrast head CTs and consolidate imaging findings into ordinal severity categories that would inform specific patient management actions and that could be used as a clinical decision support tool. We retrospectively identified all patients transported to our emergency department by ambulance or helicopter, for whom a trauma alert was triggered per established criteria and who underwent a non-contrast head CT due to suspicion of TBI, between November 2015 and April 2016. Two neuroradiologists reviewed the non-contrast head CTs and assessed the TBI imaging common data elements (CDEs), as defined by the National Institutes of Health (NIH). Using descriptive statistics and receiver operating characteristic curve analyses to identify imaging characteristics and associated thresholds that best distinguished among outcomes, we classified patients into five mutually exclusive categories: 0-discharge from the emergency department; 1-follow-up brain imaging and/or admission; 2-admission to an advanced care unit; 3-neurosurgical procedure; 4-death up to 6 months after TBI. Sensitivity of NIRIS with respect to each patient's true outcome was then evaluated and compared to that of the Marshall and Rotterdam scoring systems for TBI. In our cohort of 542 TBI patients, NIRIS was developed to predict discharge (182 patients), follow-up brain imaging/admission (187 patients), need for advanced care unit (151 patients). neurosurgical procedures (10 patients) and death (12 patients). NIRIS performed similarly to the Marshall and Rotterdam scoring systems in terms of predicting mortality. We developed an interpretation system for neuroimaging using the CDEs that informs specific patient management actions and could be used as a clinical decision support tool for patients with TBI. Our NIRIS classification, with evidence-based grouping of the CDEs into actionable categories, will need to be validated in different TBI populations.

Neuroimaging in adult penetrating brain injury: a guide for radiographers

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

Temple, Nikki; Donald, Cortny; Skora, Amanda

Penetrating brain injuries (PBI) are a medical emergency, often resulting in complex damage and high mortality rates. Neuroimaging is essential to evaluate the location and extent of injuries, and to manage them accordingly. Currently, a myriad of imaging modalities are included in the diagnostic workup for adult PBI, including skull radiography, computed tomography (CT), magnetic resonance imaging (MRI) and angiography, with each modality providing their own particular benefits. This literature review explores the current modalities available for investigating PBI and aims to assist in decision making for the appropriate use of diagnostic imaging when presented with an adult PBI. Basedmore » on the current literature, the authors have developed an imaging pathway for adult penetrating brain injury that functions as both a learning tool and reference guide for radiographers and other health professionals. Currently, CT is recommended as the imaging modality of choice for the initial assessment of PBI patients, while MRI is important in the sub-acute setting where it aids prognosis prediction and rehabilitation planning, Additional follow-up imaging, such as angiography, should be dependent upon clinical findings.« less

A Learning-Based Wrapper Method to Correct Systematic Errors in Automatic Image Segmentation: Consistently Improved Performance in Hippocampus, Cortex and Brain Segmentation

PubMed Central

Wang, Hongzhi; Das, Sandhitsu R.; Suh, Jung Wook; Altinay, Murat; Pluta, John; Craige, Caryne; Avants, Brian; Yushkevich, Paul A.

2011-01-01

We propose a simple but generally applicable approach to improving the accuracy of automatic image segmentation algorithms relative to manual segmentations. The approach is based on the hypothesis that a large fraction of the errors produced by automatic segmentation are systematic, i.e., occur consistently from subject to subject, and serves as a wrapper method around a given host segmentation method. The wrapper method attempts to learn the intensity, spatial and contextual patterns associated with systematic segmentation errors produced by the host method on training data for which manual segmentations are available. The method then attempts to correct such errors in segmentations produced by the host method on new images. One practical use of the proposed wrapper method is to adapt existing segmentation tools, without explicit modification, to imaging data and segmentation protocols that are different from those on which the tools were trained and tuned. An open-source implementation of the proposed wrapper method is provided, and can be applied to a wide range of image segmentation problems. The wrapper method is evaluated with four host brain MRI segmentation methods: hippocampus segmentation using FreeSurfer (Fischl et al., 2002); hippocampus segmentation using multi-atlas label fusion (Artaechevarria et al., 2009); brain extraction using BET (Smith, 2002); and brain tissue segmentation using FAST (Zhang et al., 2001). The wrapper method generates 72%, 14%, 29% and 21% fewer erroneously segmented voxels than the respective host segmentation methods. In the hippocampus segmentation experiment with multi-atlas label fusion as the host method, the average Dice overlap between reference segmentations and segmentations produced by the wrapper method is 0.908 for normal controls and 0.893 for patients with mild cognitive impairment. Average Dice overlaps of 0.964, 0.905 and 0.951 are obtained for brain extraction, white matter segmentation and gray matter segmentation, respectively. PMID:21237273

Seeing the forest and trees: whole-body and whole-brain imaging for circadian biology.

PubMed

Ode, K L; Ueda, H R

2015-09-01

Recent advances in methods for making mammalian organs translucent have made possible whole-body fluorescent imaging with single-cell resolution. Because organ-clearing methods can be used to image the heterogeneous nature of cell populations, they are powerful tools to investigate the hierarchical organization of the cellular circadian clock, and how the clock synchronizes a variety of physiological activities. In particular, methods compatible with genetically encoded fluorescent reporters have the potential to detect circadian activity in different brain regions and the circadian-phase distribution across the whole body. In this review, we summarize the current methods and strategy for making organs translucent (removal of lipids, decolourization of haemoglobin and adjusting the refractive index of the specimen). We then discuss possible applications to circadian biology. For example, the coupling of circadian rhythms among different brain regions, brain activity in sleep-wake cycles and the role of migrating cells such as immune cells and cancer cells in chronopharmacology. © 2015 John Wiley & Sons Ltd.

How does the brain process music?

PubMed

Warren, Jason

2008-02-01

The organisation of the musical brain is a major focus of interest in contemporary neuroscience. This reflects the increasing sophistication of tools (especially imaging techniques) to examine brain anatomy and function in health and disease, and the recognition that music provides unique insights into a number of aspects of nonverbal brain function. The emerging picture is complex but coherent, and moves beyond older ideas of music as the province of a single brain area or hemisphere to the concept of music as a 'whole-brain' phenomenon. Music engages a distributed set of cortical modules that process different perceptual, cognitive and emotional components with varying selectivity. 'Why' rather than 'how' the brain processes music is a key challenge for the future.

A method to classify schizophrenia using inter-task spatial correlations of functional brain images.

PubMed

Michael, Andrew M; Calhoun, Vince D; Andreasen, Nancy C; Baum, Stefi A

2008-01-01

The clinical heterogeneity of schizophrenia (scz) and the overlap of self reported and observed symptoms with other mental disorders makes its diagnosis a difficult task. At present no laboratory-based or image-based diagnostic tool for scz exists and such tools are desired to support existing methods for more precise diagnosis. Functional magnetic resonance imaging (fMRI) is currently employed to identify and correlate cognitive processes related to scz and its symptoms. Fusion of multiple fMRI tasks that probe different cognitive processes may help to better understand hidden networks of this complex disorder. In this paper we utilize three different fMRI tasks and introduce an approach to classify subjects based on inter-task spatial correlations of brain activation. The technique was applied to groups of patients and controls and its validity was checked with the leave-one-out method. We show that the classification rate increases when information from multiple tasks are combined.

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

PubMed

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

2016-08-01

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

Comparison of quality control software tools for diffusion tensor imaging.

PubMed

Liu, Bilan; Zhu, Tong; Zhong, Jianhui

2015-04-01

Image quality of diffusion tensor imaging (DTI) is critical for image interpretation, diagnostic accuracy and efficiency. However, DTI is susceptible to numerous detrimental artifacts that may impair the reliability and validity of the obtained data. Although many quality control (QC) software tools are being developed and are widely used and each has its different tradeoffs, there is still no general agreement on an image quality control routine for DTIs, and the practical impact of these tradeoffs is not well studied. An objective comparison that identifies the pros and cons of each of the QC tools will be helpful for the users to make the best choice among tools for specific DTI applications. This study aims to quantitatively compare the effectiveness of three popular QC tools including DTI studio (Johns Hopkins University), DTIprep (University of North Carolina at Chapel Hill, University of Iowa and University of Utah) and TORTOISE (National Institute of Health). Both synthetic and in vivo human brain data were used to quantify adverse effects of major DTI artifacts to tensor calculation as well as the effectiveness of different QC tools in identifying and correcting these artifacts. The technical basis of each tool was discussed, and the ways in which particular techniques affect the output of each of the tools were analyzed. The different functions and I/O formats that three QC tools provide for building a general DTI processing pipeline and integration with other popular image processing tools were also discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Molecular neuroanatomy: a generation of progress.

PubMed

Pollock, Jonathan D; Wu, Da-Yu; Satterlee, John S

2014-02-01

The neuroscience research landscape has changed dramatically over the past decade. Specifically, an impressive array of new tools and technologies have been generated, including but not limited to: brain gene expression atlases, genetically encoded proteins to monitor and manipulate neuronal activity, and new methods for imaging and mapping circuits. However, despite these technological advances, several significant challenges must be overcome to enable a better understanding of brain function and to develop cell type-targeted therapeutics to treat brain disorders. This review provides an overview of some of the tools and technologies currently being used to advance the field of molecular neuroanatomy, and also discusses emerging technologies that may enable neuroscientists to address these crucial scientific challenges over the coming decade. Published by Elsevier Ltd.

Real-time optoacoustic monitoring of stroke

NASA Astrophysics Data System (ADS)

Kneipp, Moritz; Turner, Jake; Hambauer, Sebastian; Krieg, Sandro M.; Lehmberg, Jens; Lindauer, Ute; Razansky, Daniel

2014-03-01

Characterizing disease progression and identifying possible therapeutic interventions in stroke is greatly aided by the use of longitudinal function imaging studies. In this study, we investigate the applicability of real-time multispectral optoacoustic tomography (MSOT) as a tool for non-invasive monitoring of the progression of stroke in the whole brain. The middle cerebral artery occlusion (MCAO) method was used to induce stroke. Mice were imaged under isoflurane anesthesia preoperatively and at several time points during and after the 60-minute occlusion. The animals were sacrificed after 24 hours and their excised brains frozen at -80°C for sectioning. The cryosection were stained using H&E staining to identify the ischemic lesion. Major vessels are readily identifiable in the whole mouse head in the in vivo optoacoustic scans. During ischemia, a reduction in cerebral blood volume is detectable in the cortex. Post ischemia, spectral unmixing of the optoacoustic signals shows an asymmetry of the deoxygenated hemoglobin in the hemisphere affected by MCAO. This hypoxic area was mainly located around the boundary of the ischemic lesion and was therefore identified as the ischemic penumbra. Non-invasive functional MSOT imaging is able to visualize the hypoxic penumbra in brains affected by stroke. Stopping the spread of the infarct area and revitalizing the penumbra is central in stroke research, this new imaging technique may therefore prove to be a valuable tool in the monitoring and developing new treatments.

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

PubMed

Liu, Yan; Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lau, Steven; Lu, Weiguo; Yan, Yulong; Jiang, Steve B; Zhen, Xin; Timmerman, Robert; Nedzi, Lucien; Gu, Xuejun

2017-01-01

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

Tool-use: An open window into body representation and its plasticity

PubMed Central

Martel, Marie; Cardinali, Lucilla; Roy, Alice C.; Farnè, Alessandro

2016-01-01

ABSTRACT Over the last decades, scientists have questioned the origin of the exquisite human mastery of tools. Seminal studies in monkeys, healthy participants and brain-damaged patients have primarily focused on the plastic changes that tool-use induces on spatial representations. More recently, we focused on the modifications tool-use must exert on the sensorimotor system and highlighted plastic changes at the level of the body representation used by the brain to control our movements, i.e., the Body Schema. Evidence is emerging for tool-use to affect also more visually and conceptually based representations of the body, such as the Body Image. Here we offer a critical review of the way different tool-use paradigms have been, and should be, used to try disentangling the critical features that are responsible for tool incorporation into different body representations. We will conclude that tool-use may offer a very valuable means to investigate high-order body representations and their plasticity. PMID:27315277

Tool-use: An open window into body representation and its plasticity.

PubMed

Martel, Marie; Cardinali, Lucilla; Roy, Alice C; Farnè, Alessandro

2016-01-01

Over the last decades, scientists have questioned the origin of the exquisite human mastery of tools. Seminal studies in monkeys, healthy participants and brain-damaged patients have primarily focused on the plastic changes that tool-use induces on spatial representations. More recently, we focused on the modifications tool-use must exert on the sensorimotor system and highlighted plastic changes at the level of the body representation used by the brain to control our movements, i.e., the Body Schema. Evidence is emerging for tool-use to affect also more visually and conceptually based representations of the body, such as the Body Image. Here we offer a critical review of the way different tool-use paradigms have been, and should be, used to try disentangling the critical features that are responsible for tool incorporation into different body representations. We will conclude that tool-use may offer a very valuable means to investigate high-order body representations and their plasticity.

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.

A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain

PubMed Central

Arganda-Carreras, Ignacio; Manoliu, Tudor; Mazuras, Nicolas; Schulze, Florian; Iglesias, Juan E.; Bühler, Katja; Jenett, Arnim; Rouyer, François; Andrey, Philippe

2018-01-01

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila, one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species. PMID:29628885

4D MEMRI atlas of neonatal FVB/N mouse brain development.

PubMed

Szulc, Kamila U; Lerch, Jason P; Nieman, Brian J; Bartelle, Benjamin B; Friedel, Miriam; Suero-Abreu, Giselle A; Watson, Charles; Joyner, Alexandra L; Turnbull, Daniel H

2015-09-01

The widespread use of the mouse as a model system to study brain development has created the need for noninvasive neuroimaging methods that can be applied to early postnatal mice. The goal of this study was to optimize in vivo three- (3D) and four-dimensional (4D) manganese (Mn)-enhanced MRI (MEMRI) approaches for acquiring and analyzing data from the developing mouse brain. The combination of custom, stage-dependent holders and self-gated (motion-correcting) 3D MRI sequences enabled the acquisition of high-resolution (100-μm isotropic), motion artifact-free brain images with a high level of contrast due to Mn-enhancement of numerous brain regions and nuclei. We acquired high-quality longitudinal brain images from two groups of FVB/N strain mice, six mice per group, each mouse imaged on alternate odd or even days (6 3D MEMRI images at each day) covering the developmental stages between postnatal days 1 to 11. The effects of Mn-exposure, anesthesia and MRI were assessed, showing small but significant transient effects on body weight and brain volume, which recovered with time and did not result in significant morphological differences when compared to controls. Metrics derived from deformation-based morphometry (DBM) were used for quantitative analysis of changes in volume and position of a number of brain regions. The cerebellum, a brain region undergoing significant changes in size and patterning at early postnatal stages, was analyzed in detail to demonstrate the spatiotemporal characterization made possible by this new atlas of mouse brain development. These results show that MEMRI is a powerful tool for quantitative analysis of mouse brain development, with great potential for in vivo phenotype analysis in mouse models of neurodevelopmental diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Combined Diffusion Tensor and Magnetic Resonance Spectroscopic Imaging Methodology for Automated Regional Brain Analysis: Application in a Normal Pediatric Population.

PubMed

Ghosh, Nirmalya; Holshouser, Barbara; Oyoyo, Udo; Barnes, Stanley; Tong, Karen; Ashwal, Stephen

2017-01-01

During human brain development, anatomic regions mature at different rates. Quantitative anatomy-specific analysis of longitudinal diffusion tensor imaging (DTI) and magnetic resonance spectroscopic imaging (MRSI) data may improve our ability to quantify and categorize these maturational changes. Computational tools designed to quickly fuse and analyze imaging information from multiple, technically different datasets would facilitate research on changes during normal brain maturation and for comparison to disease states. In the current study, we developed a complete battery of computational tools to execute such data analyses that include data preprocessing, tract-based statistical analysis from DTI data, automated brain anatomy parsing from T1-weighted MR images, assignment of metabolite information from MRSI data, and co-alignment of these multimodality data streams for reporting of region-specific indices. We present statistical analyses of regional DTI and MRSI data in a cohort of normal pediatric subjects (n = 72; age range: 5-18 years; mean 12.7 ± 3.3 years) to establish normative data and evaluate maturational trends. Several regions showed significant maturational changes for several DTI parameters and MRSI ratios, but the percent change over the age range tended to be small. In the subcortical region (combined basal ganglia [BG], thalami [TH], and corpus callosum [CC]), the largest combined percent change was a 10% increase in fractional anisotropy (FA) primarily due to increases in the BG (12.7%) and TH (9%). The largest significant percent increase in N-acetylaspartate (NAA)/creatine (Cr) ratio was seen in the brain stem (BS) (18.8%) followed by the subcortical regions in the BG (11.9%), CC (8.9%), and TH (6.0%). We found consistent, significant (p < 0.01), but weakly positive correlations (r = 0.228-0.329) between NAA/Cr ratios and mean FA in the BS, BG, and CC regions. Age- and region-specific normative MR diffusion and spectroscopic metabolite ranges show brain maturation changes and are requisite for detecting abnormalities in an injured or diseased population. © 2017 S. Karger AG, Basel.

Characterizing stroke lesions using digital templates and lesion quantification tools in a web-based imaging informatics system for a large-scale stroke rehabilitation clinical trial

NASA Astrophysics Data System (ADS)

Wang, Ximing; Edwardson, Matthew; Dromerick, Alexander; Winstein, Carolee; Wang, Jing; Liu, Brent

2015-03-01

Previously, we presented an Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (ICARE) imaging informatics system that supports a large-scale phase III stroke rehabilitation trial. The ePR system is capable of displaying anonymized patient imaging studies and reports, and the system is accessible to multiple clinical trial sites and users across the United States via the web. However, the prior multicenter stroke rehabilitation trials lack any significant neuroimaging analysis infrastructure. In stroke related clinical trials, identification of the stroke lesion characteristics can be meaningful as recent research shows that lesion characteristics are related to stroke scale and functional recovery after stroke. To facilitate the stroke clinical trials, we hope to gain insight into specific lesion characteristics, such as vascular territory, for patients enrolled into large stroke rehabilitation trials. To enhance the system's capability for data analysis and data reporting, we have integrated new features with the system: a digital brain template display, a lesion quantification tool and a digital case report form. The digital brain templates are compiled from published vascular territory templates at each of 5 angles of incidence. These templates were updated to include territories in the brainstem using a vascular territory atlas and the Medical Image Processing, Analysis and Visualization (MIPAV) tool. The digital templates are displayed for side-by-side comparisons and transparent template overlay onto patients' images in the image viewer. The lesion quantification tool quantifies planimetric lesion area from user-defined contour. The digital case report form stores user input into a database, then displays contents in the interface to allow for reviewing, editing, and new inputs. In sum, the newly integrated system features provide the user with readily-accessible web-based tools to identify the vascular territory involved, estimate lesion area, and store these results in a web-based digital format.

Imaging brain tumour microstructure.

PubMed

Nilsson, Markus; Englund, Elisabet; Szczepankiewicz, Filip; van Westen, Danielle; Sundgren, Pia C

2018-05-08

Imaging is an indispensable tool for brain tumour diagnosis, surgical planning, and follow-up. Definite diagnosis, however, often demands histopathological analysis of microscopic features of tissue samples, which have to be obtained by invasive means. A non-invasive alternative may be to probe corresponding microscopic tissue characteristics by MRI, or so called 'microstructure imaging'. The promise of microstructure imaging is one of 'virtual biopsy' with the goal to offset the need for invasive procedures in favour of imaging that can guide pre-surgical planning and can be repeated longitudinally to monitor and predict treatment response. The exploration of such methods is motivated by the striking link between parameters from MRI and tumour histology, for example the correlation between the apparent diffusion coefficient and cellularity. Recent microstructure imaging techniques probe even more subtle and specific features, providing parameters associated to cell shape, size, permeability, and volume distributions. However, the range of scenarios in which these techniques provide reliable imaging biomarkers that can be used to test medical hypotheses or support clinical decisions is yet unknown. Accurate microstructure imaging may moreover require acquisitions that go beyond conventional data acquisition strategies. This review covers a wide range of candidate microstructure imaging methods based on diffusion MRI and relaxometry, and explores advantages, challenges, and potential pitfalls in brain tumour microstructure imaging. Copyright © 2018. Published by Elsevier Inc.

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain.

PubMed

Eide, Per Kristian; Ringstad, Geir

2015-11-01

Recently, the "glymphatic system" of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain.

MR images of mouse brain using clinical 3T MR scanner and 4CH-Mouse coil

NASA Astrophysics Data System (ADS)

Lim, Soo Mee; Park, Eun Mi; Lyoo, In Kyoon; Lee, Junghyun; Han, Bo Mi; Lee, Jeong Kyong; Lee, Su Bin

2015-07-01

Objectives: Although small-bore high-field magnets are useful for research in small rodent models,this technology, however, has not been easily accessible to most researchers. This current study, thus,tried to evaluate the usability of 4CH-Mouse coil (Philips Healthcare, Best, the Netherlands) forpreclinical investigations in clinical 3T MR scan environment. We evaluated the effects of ischemicpreconditioning (IP) in the mouse stroke model with clinical 3T MR scanner and 4CH-Mouse coil. Materials and Methods: Experiments were performed on male C57BL/6 mice that either received the IP or sham operation (control). Three different MR sequences including diffusion weighted images (DWI), T2-weighted images (T2WI), and fluid attenuated inversion recovery (FLAIR) were performed on the mouse brains following 24, 72 hours of middle cerebral artery occlusion (MCAO) and analyzed for infarct lesions. Results: The images showed that the IP-treated mouse brains had significantly smaller infarct volumes compared to the control group. Of the MR sequences employed, the T2WI showed the highest level of correlations with postmortem infarct volume measurements. Conclusions: The clinical 3T MR scanner turned out to have a solid potential as a practical tool for imaging small animal brains. MR sequences including DWI, T2WI, FLAIR were obtained with acceptable resolution and in a reasonable time constraint in evaluating a mouse stroke model brain.

Echo simulator with novel training and competency testing tools.

PubMed

Sheehan, Florence H; Otto, Catherine M; Freeman, Rosario V

2013-01-01

We developed and validated an echo simulator with three novel tools that facilitate training and enable quantitative and objective measurement of psychomotor as well as cognitive skill. First, the trainee can see original patient images - not synthetic or simulated images - that morph in real time as the mock transducer is manipulated on the mannequin. Second, augmented reality is used for Visual Guidance, a tool that assists the trainee in scanning by displaying the target organ in 3-dimensions (3D) together with the location of the current view plane and the plane of the anatomically correct view. Third, we introduce Image Matching, a tool that leverages the aptitude of the human brain for recognizing similarities and differences to help trainees learn to perform visual assessment of ultrasound images. Psychomotor competence is measured in terms of the view plane angle error. The construct validity of the simulator for competency testing was established by demonstrating its ability to discriminate novices vs. experts.

Neurovascular abnormalities in brain disorders: highlights with angiogenesis and magnetic resonance imaging studies.

PubMed

Chen, Chiao-Chi V; Chen, Yu-Chen; Hsiao, Han-Yun; Chang, Chen; Chern, Yijuang

2013-07-05

The coupling between neuronal activity and vascular responses is controlled by the neurovascular unit (NVU), which comprises multiple cell types. Many different types of dysfunction in these cells may impair the proper control of vascular responses by the NVU. Magnetic resonance imaging, which is the most powerful tool available to investigate neurovascular structures or functions, will be discussed in the present article in relation to its applications and discoveries. Because aberrant angiogenesis and vascular remodeling have been increasingly reported as being implicated in brain pathogenesis, this review article will refer to this hallmark event when suitable.

A Device for Long-Term Perfusion, Imaging, and Electrical Interfacing of Brain Tissue In vitro

PubMed Central

Killian, Nathaniel J.; Vernekar, Varadraj N.; Potter, Steve M.; Vukasinovic, Jelena

2016-01-01

Distributed microelectrode array (MEA) recordings from consistent, viable, ≥500 μm thick tissue preparations over time periods from days to weeks may aid in studying a wide range of problems in neurobiology that require in vivo-like organotypic morphology. Existing tools for electrically interfacing with organotypic slices do not address necrosis that inevitably occurs within thick slices with limited diffusion of nutrients and gas, and limited removal of waste. We developed an integrated device that enables long-term maintenance of thick, functionally active, brain tissue models using interstitial perfusion and distributed recordings from thick sections of explanted tissue on a perforated multi-electrode array. This novel device allows for automated culturing, in situ imaging, and extracellular multi-electrode interfacing with brain slices, 3-D cell cultures, and potentially other tissue culture models. The device is economical, easy to assemble, and integrable with standard electrophysiology tools. We found that convective perfusion through the culture thickness provided a functional benefit to the preparations as firing rates were generally higher in perfused cultures compared to their respective unperfused controls. This work is a step toward the development of integrated tools for days-long experiments with more consistent, healthier, thicker, and functionally more active tissue cultures with built-in distributed electrophysiological recording and stimulation functionality. The results may be useful for the study of normal processes, pathological conditions, and drug screening strategies currently hindered by the limitations of acute (a few hours long) brain slice preparations. PMID:27065793

Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Identify ADHD and Autism

PubMed Central

Ghiassian, Sina; Greiner, Russell; Jin, Ping; Brown, Matthew R. G.

2016-01-01

A clinical tool that can diagnose psychiatric illness using functional or structural magnetic resonance (MR) brain images has the potential to greatly assist physicians and improve treatment efficacy. Working toward the goal of automated diagnosis, we propose an approach for automated classification of ADHD and autism based on histogram of oriented gradients (HOG) features extracted from MR brain images, as well as personal characteristic data features. We describe a learning algorithm that can produce effective classifiers for ADHD and autism when run on two large public datasets. The algorithm is able to distinguish ADHD from control with hold-out accuracy of 69.6% (over baseline 55.0%) using personal characteristics and structural brain scan features when trained on the ADHD-200 dataset (769 participants in training set, 171 in test set). It is able to distinguish autism from control with hold-out accuracy of 65.0% (over baseline 51.6%) using functional images with personal characteristic data when trained on the Autism Brain Imaging Data Exchange (ABIDE) dataset (889 participants in training set, 222 in test set). These results outperform all previously presented methods on both datasets. To our knowledge, this is the first demonstration of a single automated learning process that can produce classifiers for distinguishing patients vs. controls from brain imaging data with above-chance accuracy on large datasets for two different psychiatric illnesses (ADHD and autism). Working toward clinical applications requires robustness against real-world conditions, including the substantial variability that often exists among data collected at different institutions. It is therefore important that our algorithm was successful with the large ADHD-200 and ABIDE datasets, which include data from hundreds of participants collected at multiple institutions. While the resulting classifiers are not yet clinically relevant, this work shows that there is a signal in the (f)MRI data that a learning algorithm is able to find. We anticipate this will lead to yet more accurate classifiers, over these and other psychiatric disorders, working toward the goal of a clinical tool for high accuracy differential diagnosis. PMID:28030565

LittleQuickWarp: an ultrafast image warping tool.

PubMed

Qu, Lei; Peng, Hanchuan

2015-02-01

Warping images into a standard coordinate space is critical for many image computing related tasks. However, for multi-dimensional and high-resolution images, an accurate warping operation itself is often very expensive in terms of computer memory and computational time. For high-throughput image analysis studies such as brain mapping projects, it is desirable to have high performance image warping tools that are compatible with common image analysis pipelines. In this article, we present LittleQuickWarp, a swift and memory efficient tool that boosts 3D image warping performance dramatically and at the same time has high warping quality similar to the widely used thin plate spline (TPS) warping. Compared to the TPS, LittleQuickWarp can improve the warping speed 2-5 times and reduce the memory consumption 6-20 times. We have implemented LittleQuickWarp as an Open Source plug-in program on top of the Vaa3D system (http://vaa3d.org). The source code and a brief tutorial can be found in the Vaa3D plugin source code repository. Copyright © 2014 Elsevier Inc. All rights reserved.

The Effects of Video Games on Cognition and Brain Structure: Potential Implications for Neuropsychiatric Disorders.

PubMed

Shams, Tahireh A; Foussias, George; Zawadzki, John A; Marshe, Victoria S; Siddiqui, Ishraq; Müller, Daniel J; Wong, Albert H C

2015-09-01

Video games are now a ubiquitous form of entertainment that has occasionally attracted negative attention. Video games have also been used to test cognitive function, as therapeutic interventions for neuropsychiatric disorders, and to explore mechanisms of experience-dependent structural brain changes. Here, we review current research on video games published from January 2011 to April 2014 with a focus on studies relating to mental health, cognition, and brain imaging. Overall, there is evidence that specific types of video games can alter brain structure or improve certain aspects of cognitive functioning. Video games can also be useful as neuropsychological assessment tools. While research in this area is still at a very early stage, there are interesting results that encourage further work in this field, and hold promise for utilizing this technology as a powerful therapeutic and experimental tool.

Brain imaging in mitochondrial respiratory chain deficiency: combination of brain MRI features as a useful tool for genotype/phenotype correlations.

PubMed

Bricout, M; Grévent, D; Lebre, A S; Rio, M; Desguerre, I; De Lonlay, P; Valayannopoulos, V; Brunelle, F; Rötig, A; Munnich, A; Boddaert, N

2014-07-01

Mitochondrial diseases are characterised by a broad clinical and genetic heterogeneity that makes diagnosis difficult. Owing to the wide pattern of symptoms in mitochondrial disorders and the constantly growing number of disease genes, their genetic diagnosis is difficult and genotype/phenotype correlations remain elusive. Brain MRI appears as a useful tool for genotype/phenotype correlations. Here, we summarise the various combinations of MRI lesions observed in the most frequent mitochondrial respiratory chain deficiencies so as to direct molecular genetic test in patients at risk of such diseases. We believe that the combination of brain MRI features is of value to support respiratory chain deficiency and direct molecular genetic tests. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Deep-tissue two-photon imaging in brain and peripheral nerve with a compact high-pulse energy ytterbium fiber laser

NASA Astrophysics Data System (ADS)

Fontaine, Arjun K.; Kirchner, Matthew S.; Caldwell, John H.; Weir, Richard F.; Gibson, Emily A.

2018-02-01

Two-photon microscopy is a powerful tool of current scientific research, allowing optical visualization of structures below the surface of tissues. This is of particular value in neuroscience, where optically accessing regions within the brain is critical for the continued advancement in understanding of neural circuits. However, two-photon imaging at significant depths have typically used Ti:Sapphire based amplifiers that are prohibitively expensive and bulky. In this study, we demonstrate deep tissue two-photon imaging using a compact, inexpensive, turnkey operated Ytterbium fiber laser (Y-Fi, KM Labs). The laser is based on all-normal dispersion (ANDi) that provides short pulse durations and high pulse energies. Depth measurements obtained in ex vivo mouse cortex exceed those obtainable with standard two-photon microscopes using Ti:Sapphire lasers. In addition to demonstrating the capability of deep-tissue imaging in the brain, we investigated imaging depth in highly-scattering white matter with measurements in sciatic nerve showing limited optical penetration of heavily myelinated nerve tissue relative to grey matter.

Studying Axon-Astrocyte Functional Interactions by 3D Two-Photon Ca2+ Imaging: A Practical Guide to Experiments and "Big Data" Analysis.

PubMed

Savtchouk, Iaroslav; Carriero, Giovanni; Volterra, Andrea

2018-01-01

Recent advances in fast volumetric imaging have enabled rapid generation of large amounts of multi-dimensional functional data. While many computer frameworks exist for data storage and analysis of the multi-gigabyte Ca 2+ imaging experiments in neurons, they are less useful for analyzing Ca 2+ dynamics in astrocytes, where transients do not follow a predictable spatio-temporal distribution pattern. In this manuscript, we provide a detailed protocol and commentary for recording and analyzing three-dimensional (3D) Ca 2+ transients through time in GCaMP6f-expressing astrocytes of adult brain slices in response to axonal stimulation, using our recently developed tools to perform interactive exploration, filtering, and time-correlation analysis of the transients. In addition to the protocol, we release our in-house software tools and discuss parameters pertinent to conducting axonal stimulation/response experiments across various brain regions and conditions. Our software tools are available from the Volterra Lab webpage at https://wwwfbm.unil.ch/dnf/group/glia-an-active-synaptic-partner/member/volterra-andrea-volterra in the form of software plugins for Image J (NIH)-a de facto standard in scientific image analysis. Three programs are available: MultiROI_TZ_profiler for interactive graphing of several movable ROIs simultaneously, Gaussian_Filter5D for Gaussian filtering in several dimensions, and Correlation_Calculator for computing various cross-correlation parameters on voxel collections through time.

Molecular Neuroanatomy: A Generation of Progress

PubMed Central

Pollock, Jonathan D.; Wu, Da-Yu; Satterlee, John

2014-01-01

The neuroscience research landscape has changed dramatically over the past decade. An impressive array of neuroscience tools and technologies have been generated, including brain gene expression atlases, genetically encoded proteins to monitor and manipulate neuronal activity and function, cost effective genome sequencing, new technologies enabling genome manipulation, new imaging methods and new tools for mapping neuronal circuits. However, despite these technological advances, several significant scientific challenges must be overcome in the coming decade to enable a better understanding of brain function and to develop next generation cell type-targeted therapeutics to treat brain disorders. For example, we do not have an inventory of the different types of cells that exist in the brain, nor do we know how to molecularly phenotype them. We also lack robust technologies to map connections between cells. This review will provide an overview of some of the tools and technologies neuroscientists are currently using to move the field of molecular neuroanatomy forward and also discuss emerging technologies that may enable neuroscientists to address these critical scientific challenges over the coming decade. PMID:24388609

Development and Assessment of a New 3D Neuroanatomy Teaching Tool for MRI Training

ERIC Educational Resources Information Center

Drapkin, Zachary A.; Lindgren, Kristen A.; Lopez, Michael J.; Stabio, Maureen E.

2015-01-01

A computerized three-dimensional (3D) neuroanatomy teaching tool was developed for training medical students to identify subcortical structures on a magnetic resonance imaging (MRI) series of the human brain. This program allows the user to transition rapidly between two-dimensional (2D) MRI slices, 3D object composites, and a combined model in…

Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change.

PubMed

Williams, Owen A; Zeestraten, Eva A; Benjamin, Philip; Lambert, Christian; Lawrence, Andrew J; Mackinnon, Andrew D; Morris, Robin G; Markus, Hugh S; Charlton, Rebecca A; Barrick, Thomas R

2017-01-01

Cerebral small vessel disease (SVD) is the primary cause of vascular cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related changes in a single unitary score across the whole cerebrum, to investigate its relationship with cognitive change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to change in EF and IPS ( p  < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of change in EF and IPS in the multivariate models ( p  = 0.002). Change in DSEG θ was also related to change in all other MRI markers ( p  < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain change in SVD that has a negative impact on cognition and remains a significant predictor of cognitive change when other MRI markers of brain change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural changes and successfully predicts cognitive change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).

The cerebellar development in chinese children-a study by voxel-based volume measurement of reconstructed 3D MRI scan.

PubMed

Wu, Kuan-Hsun; Chen, Chia-Yuan; Shen, Ein-Yiao

2011-01-01

Cerebellar disorder was frequently reported to have relation with structural brain volume alteration and/or morphology change. In dealing with such clinical situations, we need a convenient and noninvasive imaging tool to provide clinicians with a means of tracing developmental changes in the cerebellum. Herein, we present a new daily practice method for cerebellum imaging that uses a work station and a software program to process reconstructed 3D neuroimages after MRI scanning. In a 3-y period, 3D neuroimages reconstructed from MRI scans of 50 children aged 0.2-12.7 y were taken. The resulting images were then statistically analyzed against a growth curve. We observed a remarkable increase in the size of the cerebellum in the first 2 y of life. Furthermore, the unmyelinated cerebellum grew mainly between birth and 2 y of age in the postnatal stage. In contrast, the postnatal development of the brain mainly depended on the growth of myelinated cerebellum from birth through adolescence. This study presents basic data from a study of ethnic Chinese children's cerebellums using reconstructed 3D brain images. Based on the technique we introduce here, clinicians can evaluate the growth of the brain.

Development and validation of an open source quantification tool for DSC-MRI studies.

PubMed

Gordaliza, P M; Mateos-Pérez, J M; Montesinos, P; Guzmán-de-Villoria, J A; Desco, M; Vaquero, J J

2015-03-01

This work presents the development of an open source tool for the quantification of dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies. The development of this tool is motivated by the lack of open source tools implemented on open platforms to allow external developers to implement their own quantification methods easily and without the need of paying for a development license. This quantification tool was developed as a plugin for the ImageJ image analysis platform using the Java programming language. A modular approach was used in the implementation of the components, in such a way that the addition of new methods can be done without breaking any of the existing functionalities. For the validation process, images from seven patients with brain tumors were acquired and quantified with the presented tool and with a widely used clinical software package. The resulting perfusion parameters were then compared. Perfusion parameters and the corresponding parametric images were obtained. When no gamma-fitting is used, an excellent agreement with the tool used as a gold-standard was obtained (R(2)>0.8 and values are within 95% CI limits in Bland-Altman plots). An open source tool that performs quantification of perfusion studies using magnetic resonance imaging has been developed and validated using a clinical software package. It works as an ImageJ plugin and the source code has been published with an open source license. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Single unit approaches to human vision and memory.

PubMed

Kreiman, Gabriel

2007-08-01

Research on the visual system focuses on using electrophysiology, pharmacology and other invasive tools in animal models. Non-invasive tools such as scalp electroencephalography and imaging allow examining humans but show a much lower spatial and/or temporal resolution. Under special clinical conditions, it is possible to monitor single-unit activity in humans when invasive procedures are required due to particular pathological conditions including epilepsy and Parkinson's disease. We review our knowledge about the visual system and visual memories in the human brain at the single neuron level. The properties of the human brain seem to be broadly compatible with the knowledge derived from animal models. The possibility of examining high-resolution brain activity in conscious human subjects allows investigators to ask novel questions that are challenging to address in animal models.

Brain activity underlying tool-related and imitative skills after major left hemisphere stroke.

PubMed

Martin, Markus; Nitschke, Kai; Beume, Lena; Dressing, Andrea; Bühler, Laura E; Ludwig, Vera M; Mader, Irina; Rijntjes, Michel; Kaller, Christoph P; Weiller, Cornelius

2016-05-01

Apraxia is a debilitating cognitive motor disorder that frequently occurs after left hemisphere stroke and affects tool-associated and imitative skills. However, the severity of the apraxic deficits varies even across patients with similar lesions. This variability raises the question whether regions outside the left hemisphere network typically associated with cognitive motor tasks in healthy subjects are of additional functional relevance. To investigate this hypothesis, we explored regions where functional magnetic resonance imaging activity is associated with better cognitive motor performance in patients with left hemisphere ischaemic stroke. Thirty-six patients with chronic (>6 months) large left hemisphere infarcts (age ± standard deviation, 60 ± 12 years, 29 male) and 29 control subjects (age ± standard deviation, 72 ± 7, 15 male) were first assessed behaviourally outside the scanner with tests for actual tool use, pantomime and imitation of tool-use gestures, as well as for meaningless gesture imitation. Second, functional magnetic resonance imaging activity was registered during the passive observation of videos showing tool-associated actions. Voxel-wise linear regression analyses were used to identify areas where behavioural performance was correlated with functional magnetic resonance imaging activity. Furthermore, lesions were delineated on the magnetic resonance imaging scans for voxel-based lesion-symptom mapping. The analyses revealed two sets of regions where functional magnetic resonance imaging activity was associated with better performance in the clinical tasks. First, activity in left hemisphere areas thought to mediate cognitive motor functions in healthy individuals (i.e. activity within the putative 'healthy' network) was correlated with better scores. Within this network, tool-associated tasks were mainly related to activity in supramarginal gyrus and ventral premotor cortex, while meaningless gesture imitation depended more on the anterior intraparietal sulcus and superior parietal lobule. Second, repeating the regression analyses with total left hemisphere lesion volume as additional covariate demonstrated that tool-related skills were further supported by right premotor, right inferior frontal and left anterior temporal areas, while meaningless gesture imitation was also driven by the left dorso-lateral prefrontal cortex. In summary, tool-related and imitative skills in left hemisphere stroke patients depend on the activation of spared left hemisphere regions that support these abilities in healthy individuals. In addition, cognitive motor functions rely on the activation of ipsi- and contralesional areas that are situated outside this 'healthy' network. This activity may explain why some patients perform surprisingly well despite large left brain lesions, while others are severely impaired. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The white matter structural network underlying human tool use and tool understanding.

PubMed

Bi, Yanchao; Han, Zaizhu; Zhong, Suyu; Ma, Yujun; Gong, Gaolang; Huang, Ruiwang; Song, Luping; Fang, Yuxing; He, Yong; Caramazza, Alfonso

2015-04-29

The ability to recognize, create, and use complex tools is a milestone in human evolution. Widely distributed brain regions in parietal, frontal, and temporal cortices have been implicated in using and understanding tools, but the roles of their anatomical connections in supporting tool use and tool conceptual behaviors are unclear. Using deterministic fiber tracking in healthy participants, we first examined how 14 cortical regions that are consistently activated by tool processing are connected by white matter (WM) tracts. The relationship between the integrity of each of the 33 obtained tracts and tool processing deficits across 86 brain-damaged patients was investigated. WM tract integrity was measured with both lesion percentage (structural imaging) and mean fractional anisotropy (FA) values (diffusion imaging). Behavioral abilities were assessed by a tool use task, a range of conceptual tasks, and control tasks. We found that three left hemisphere tracts connecting frontoparietal and intrafrontal areas overlapping with left superior longitudinal fasciculus are crucial for tool use such that larger lesion and lower mean FA values on these tracts were associated with more severe tool use deficits. These tracts and five additional left hemisphere tracts connecting frontal and temporal/parietal regions, mainly overlapping with left superior longitudinal fasciculus, inferior frontooccipital fasciculus, uncinate fasciculus, and anterior thalamic radiation, are crucial for tool concept processing. Largely consistent results were also obtained using voxel-based symptom mapping analyses. Our results revealed the WM structural networks that support the use and conceptual understanding of tools, providing evidence for the anatomical skeleton of the tool knowledge network. Copyright © 2015 the authors 0270-6474/15/356822-14$15.00/0.

Imaging MALDI MS of Dosed Brain Tissues Utilizing an Alternative Analyte Pre-extraction Approach

NASA Astrophysics Data System (ADS)

Quiason, Cristine M.; Shahidi-Latham, Sheerin K.

2015-06-01

Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry has been adopted in the pharmaceutical industry as a useful tool to detect xenobiotic distribution within tissues. A unique sample preparation approach for MALDI imaging has been described here for the extraction and detection of cobimetinib and clozapine, which were previously undetectable in mouse and rat brain using a single matrix application step. Employing a combination of a buffer wash and a cyclohexane pre-extraction step prior to standard matrix application, the xenobiotics were successfully extracted and detected with an 8 to 20-fold gain in sensitivity. This alternative approach for sample preparation could serve as an advantageous option when encountering difficult to detect analytes.

Development of functional in vivo imaging of cerebral lenticulostriate artery using novel synchrotron radiation angiography

NASA Astrophysics Data System (ADS)

Lin, Xiaojie; Miao, Peng; Mu, Zhihao; Jiang, Zhen; Lu, Yifan; Guan, Yongjing; Chen, Xiaoyan; Xiao, Tiqiao; Wang, Yongting; Yang, Guo-Yuan

2015-02-01

The lenticulostriate artery plays a vital role in the onset and development of cerebral ischemia. However, current imaging techniques cannot assess the in vivo functioning of small arteries such as the lenticulostriate artery in the brain of rats. Here, we report a novel method to achieve a high resolution multi-functional imaging of the cerebrovascular system using synchrotron radiation angiography, which is based on spatio-temporal analysis of contrast density in the arterial cross section. This method provides a unique tool for studying the sub-cortical vascular elasticity after cerebral ischemia in rats. Using this technique, we demonstrated that the vascular elasticity of the lenticulostriate artery decreased from day 1 to day 7 after transient middle cerebral artery occlusion in rats and recovered from day 7 to day 28 compared to the controls (p < 0.001), which paralleled with brain edema formation and inversely correlated with blood flow velocity (p < 0.05). Our results demonstrated that the change of vascular elasticity was related to the levels of brain edema and the velocity of focal blood flow, suggesting that reducing brain edema is important for the improvement of the function of the lenticulostriate artery in the ischemic brain.

High-resolution digital brain atlases: a Hubble telescope for the brain.

PubMed

Jones, Edward G; Stone, James M; Karten, Harvey J

2011-05-01

We describe implementation of a method for digitizing at microscopic resolution brain tissue sections containing normal and experimental data and for making the content readily accessible online. Web-accessible brain atlases and virtual microscopes for online examination can be developed using existing computer and internet technologies. Resulting databases, made up of hierarchically organized, multiresolution images, enable rapid, seamless navigation through the vast image datasets generated by high-resolution scanning. Tools for visualization and annotation of virtual microscope slides enable remote and universal data sharing. Interactive visualization of a complete series of brain sections digitized at subneuronal levels of resolution offers fine grain and large-scale localization and quantification of many aspects of neural organization and structure. The method is straightforward and replicable; it can increase accessibility and facilitate sharing of neuroanatomical data. It provides an opportunity for capturing and preserving irreplaceable, archival neurohistological collections and making them available to all scientists in perpetuity, if resources could be obtained from hitherto uninterested agencies of scientific support. © 2011 New York Academy of Sciences.

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 Function Biomedical Informatics Research Network Data Repository

PubMed Central

Keator, David B.; van Erp, Theo G.M.; Turner, Jessica A.; Glover, Gary H.; Mueller, Bryon A.; Liu, Thomas T.; Voyvodic, James T.; Rasmussen, Jerod; Calhoun, Vince D.; Lee, Hyo Jong; Toga, Arthur W.; McEwen, Sarah; Ford, Judith M.; Mathalon, Daniel H.; Diaz, Michele; O’Leary, Daniel S.; Bockholt, H. Jeremy; Gadde, Syam; Preda, Adrian; Wible, Cynthia G.; Stern, Hal S.; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G.

2015-01-01

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical datasets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 dataset consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 Tesla scanners. The FBIRN Phase 2 and Phase 3 datasets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN’s multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data. PMID:26364863

Touch, tools, and telepresence: embodiment in mediated environments

NASA Astrophysics Data System (ADS)

IJsselsteijn, Wijnand A.; Haans, Antal

2008-02-01

We tend to think of our body image as fixed. However, human brains appear to support highly negotiable body images. As a result, our brains show a remarkable flexibility in incorporating non-biological elements (tools and technologies) into the body image, provided reliable, real-time intersensory correlations can be established, and artifacts can be plausibly mapped onto an already existing body image representation. A particularly interesting and relevant phenomenon in this respect is a recently reported crossmodal perceptual illusion known as the rubber-hand illusion (RHI). When a person is watching a fake hand being stroked and tapped in precise synchrony with his or her own unseen hand, the person will, within a few minutes of stimulation, start experiencing the fake hand as an actual part of his or her own body. In this paper, we will review recent work on the RHI and argue that such experimental transformation of the intimate ties between body morphology, proprioception and self-perception enhances our fundamental understanding of the phenomenal experience of self. Moreover, it will enable us to significantly improve the design of interactive media, including the design of avatars in virtual environments and digital games, as well as a range of human-like telerobotic devices.

Optimizing real time fMRI neurofeedback for therapeutic discovery and development

PubMed Central

Stoeckel, L.E.; Garrison, K.A.; Ghosh, S.; Wighton, P.; Hanlon, C.A.; Gilman, J.M.; Greer, S.; Turk-Browne, N.B.; deBettencourt, M.T.; Scheinost, D.; Craddock, C.; Thompson, T.; Calderon, V.; Bauer, C.C.; George, M.; Breiter, H.C.; Whitfield-Gabrieli, S.; Gabrieli, J.D.; LaConte, S.M.; Hirshberg, L.; Brewer, J.A.; Hampson, M.; Van Der Kouwe, A.; Mackey, S.; Evins, A.E.

2014-01-01

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health, the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain–behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders. PMID:25161891

GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging.

PubMed

Gabr, Refaat E; Tefera, Getaneh B; Allen, William J; Pednekar, Amol S; Narayana, Ponnada A

2017-03-01

We present a platform, GRAphical Pipeline Environment (GRAPE), to facilitate the development of patient-adaptive magnetic resonance imaging (MRI) protocols. GRAPE is an open-source project implemented in the Qt C++ framework to enable graphical creation, execution, and debugging of real-time image analysis algorithms integrated with the MRI scanner. The platform provides the tools and infrastructure to design new algorithms, and build and execute an array of image analysis routines, and provides a mechanism to include existing analysis libraries, all within a graphical environment. The application of GRAPE is demonstrated in multiple MRI applications, and the software is described in detail for both the user and the developer. GRAPE was successfully used to implement and execute three applications in MRI of the brain, performed on a 3.0-T MRI scanner: (i) a multi-parametric pipeline for segmenting the brain tissue and detecting lesions in multiple sclerosis (MS), (ii) patient-specific optimization of the 3D fluid-attenuated inversion recovery MRI scan parameters to enhance the contrast of brain lesions in MS, and (iii) an algebraic image method for combining two MR images for improved lesion contrast. GRAPE allows graphical development and execution of image analysis algorithms for inline, real-time, and adaptive MRI applications.

Synthesis of nanostructured barium phosphate and its application in micro-computed tomography of mouse brain vessels in ex vivo

NASA Astrophysics Data System (ADS)

Zhu, Bangshang; Yuan, Falei; Yuan, Xiaoya; Bo, Yang; Wang, Yongting; Yang, Guo-Yuan; Drummen, Gregor P. C.; Zhu, Xinyuan

2014-02-01

Micro-computed tomography (micro-CT) is a powerful tool for visualizing the vascular systems of tissues, organs, or entire small animals. Vascular contrast agents play a vital role in micro-CT imaging in order to obtain clear and high-quality images. In this study, a new kind of nanostructured barium phosphate was fabricated and used as a contrast agent for ex vivo micro-CT imaging of blood vessels in the mouse brain. Nanostructured barium phosphate was synthesized through a simple wet precipitation method using Ba(NO3)2, and (NH4)2HPO4 as starting materials. The physiochemical properties of barium phosphate were characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and thermal analysis. Furthermore, the impact of the produced nanostructures on cell viability was evaluated via the MTT assay, which generally showed low to moderate cytotoxicity. Finally, the animal test images demonstrated that the use of nanostructured barium phosphate as a contrast agent in Micro-CT imaging produced sharp images with excellent contrast. Both major vessels and the microvasculature were clearly observable in the imaged mouse brain. Overall, the results indicate that nanostructured barium phosphate is a potential and useful vascular contrast agent for micro-CT imaging.

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

PubMed

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

2014-05-15

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

Lesion registration for longitudinal disease tracking in an imaging informatics-based multiple sclerosis eFolder

NASA Astrophysics Data System (ADS)

Ma, Kevin; Liu, Joseph; Zhang, Xuejun; Lerner, Alex; Shiroishi, Mark; Amezcua, Lilyana; Liu, Brent

2016-03-01

We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results stored in DICOM-SR format. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system needs to quantify lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. In order to perform lesion registration, we have developed a brain warping and normalizing methodology using Statistical Parametric Mapping (SPM) MATLAB toolkit for brain MRI. Patients' brain MR images are processed via SPM's normalization processes, and the brain images are analyzed and warped according to the tissue probability map. Lesion identification and contouring are completed by neuroradiologists, and lesion volume quantification is completed by the eFolder's CAD program. Lesion comparison results in longitudinal studies show key growth and active regions. The results display successful lesion registration and tracking over a longitudinal study. Lesion change results are graphically represented in the web-based user interface, and users are able to correlate patient progress and changes in the MRI images. The completed lesion and disease tracking tool would enable the eFolder to provide complete patient profiles, improve the efficiency of patient care, and perform comprehensive data analysis through an integrated imaging informatics system.

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

PubMed

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

2015-12-15

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

Brain Volume Estimation Enhancement by Morphological Image Processing Tools.

PubMed

Zeinali, R; Keshtkar, A; Zamani, A; Gharehaghaji, N

2017-12-01

Volume estimation of brain is important for many neurological applications. It is necessary in measuring brain growth and changes in brain in normal/abnormal patients. Thus, accurate brain volume measurement is very important. Magnetic resonance imaging (MRI) is the method of choice for volume quantification due to excellent levels of image resolution and between-tissue contrast. Stereology method is a good method for estimating volume but it requires to segment enough MRI slices and have a good resolution. In this study, it is desired to enhance stereology method for volume estimation of brain using less MRI slices with less resolution. In this study, a program for calculating volume using stereology method has been introduced. After morphologic method, dilation was applied and the stereology method enhanced. For the evaluation of this method, we used T1-wighted MR images from digital phantom in BrainWeb which had ground truth. The volume of 20 normal brain extracted from BrainWeb, was calculated. The volumes of white matter, gray matter and cerebrospinal fluid with given dimension were estimated correctly. Volume calculation from Stereology method in different cases was made. In three cases, Root Mean Square Error (RMSE) was measured. Case I with T=5, d=5, Case II with T=10, D=10 and Case III with T=20, d=20 (T=slice thickness, d=resolution as stereology parameters). By comparing these results of two methods, it is obvious that RMSE values for our proposed method are smaller than Stereology method. Using morphological operation, dilation allows to enhance the estimation volume method, Stereology. In the case with less MRI slices and less test points, this method works much better compared to Stereology method.

Mapping cell-specific functional connections in the mouse brain using ChR2-evoked hemodynamics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael; Lee, Jin-Moo; Culver, Joseph P.

2017-02-01

Functional magnetic resonance imaging (fMRI) has transformed our understanding of the brain's functional organization. However, mapping subunits of a functional network using hemoglobin alone presents several disadvantages. Evoked and spontaneous hemodynamic fluctuations reflect ensemble activity from several populations of neurons making it difficult to discern excitatory vs inhibitory network activity. Still, blood-based methods of brain mapping remain powerful because hemoglobin provides endogenous contrast in all mammalian brains. To add greater specificity to hemoglobin assays, we integrated optical intrinsic signal(OIS) imaging with optogenetic stimulation to create an Opto-OIS mapping tool that combines the cell-specificity of optogenetics with label-free, hemoglobin imaging. Before mapping, titrated photostimuli determined which stimulus parameters elicited linear hemodynamic responses in the cortex. Optimized stimuli were then scanned over the left hemisphere to create a set of optogenetically-defined effective connectivity (Opto-EC) maps. For many sites investigated, Opto-EC maps exhibited higher spatial specificity than those determined using spontaneous hemodynamic fluctuations. For example, resting-state functional connectivity (RS-FC) patterns exhibited widespread ipsilateral connectivity while Opto-EC maps contained distinct short- and long-range constellations of ipsilateral connectivity. Further, RS-FC maps were usually symmetric about midline while Opto-EC maps displayed more heterogeneous contralateral homotopic connectivity. Both Opto-EC and RS-FC patterns were compared to mouse connectivity data from the Allen Institute. Unlike RS-FC maps, Thy1-based maps collected in awake, behaving mice closely recapitulated the connectivity structure derived using ex vivo anatomical tracer methods. Opto-OIS mapping could be a powerful tool for understanding cellular and molecular contributions to network dynamics and processing in the mouse brain.

NIRS in clinical neurology - a 'promising' tool?

PubMed

Obrig, Hellmuth

2014-01-15

Near-infrared spectroscopy (NIRS) has become a relevant research tool in neuroscience. In special populations such as infants and for special tasks such as walking, NIRS has asserted itself as a low resolution functional imaging technique which profits from its ease of application, portability and the option to co-register other neurophysiological and behavioral data in a 'near natural' environment. For clinical use in neurology this translates into the option to provide a bed-side oximeter for the brain, broadly available at comparatively low costs. However, while some potential for routine brain monitoring during cardiac and vascular surgery and in neonatology has been established, NIRS is largely unknown to clinical neurologists. The article discusses some of the reasons for this lack of use in clinical neurology. Research using NIRS in three major neurologic diseases (cerebrovascular disease, epilepsy and headache) is reviewed. Additionally the potential to exploit the established position of NIRS as a functional imaging tool with regard to clinical questions such as preoperative functional assessment and neurorehabilitation is discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Computation of a high-resolution MRI 3D stereotaxic atlas of the sheep brain.

PubMed

Ella, Arsène; Delgadillo, José A; Chemineau, Philippe; Keller, Matthieu

2017-02-15

The sheep model was first used in the fields of animal reproduction and veterinary sciences and then was utilized in fundamental and preclinical studies. For more than a decade, magnetic resonance (MR) studies performed on this model have been increasingly reported, especially in the field of neuroscience. To contribute to MR translational neuroscience research, a brain template and an atlas are necessary. We have recently generated the first complete T1-weighted (T1W) and T2W MR population average images (or templates) of in vivo sheep brains. In this study, we 1) defined a 3D stereotaxic coordinate system for previously established in vivo population average templates; 2) used deformation fields obtained during optimized nonlinear registrations to compute nonlinear tissues or prior probability maps (nlTPMs) of cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) tissues; 3) delineated 25 external and 28 internal sheep brain structures by segmenting both templates and nlTPMs; and 4) annotated and labeled these structures using an existing histological atlas. We built a quality high-resolution 3D atlas of average in vivo sheep brains linked to a reference stereotaxic space. The atlas and nlTPMs, associated with previously computed T1W and T2W in vivo sheep brain templates and nlTPMs, provide a complete set of imaging space that are able to be imported into other imaging software programs and could be used as standardized tools for neuroimaging studies or other neuroscience methods, such as image registration, image segmentation, identification of brain structures, implementation of recording devices, or neuronavigation. J. Comp. Neurol. 525:676-692, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Radiomicrobiomics: Advancing Along the Gut-brain Axis Through Big Data Analysis.

PubMed

De Santis, Silvia; Moratal, David; Canals, Santiago

2017-12-10

The gut-brain axis communicates the brain with the gut microbiota, a bidirectional conduit that has received increasing attention in recent years thanks to its emerging role in brain development and function. Alterations in microbiota composition have been associated to neurological and psychiatric disorders, and several studies suggest that the immune system plays a fundamental role in the gut-brain interaction. Recent advances in brain imaging and in microbiome sequencing have generated a large amount of information, yet the data from both these sources need to be combined efficiently to extract biological meaning, and any diagnostic and/or prognostic benefit from these tools. In addition, the causal nature of the gut-brain interaction remains to be fully established, and preclinical findings translated to humans. In this "Perspective" article, we discuss recent efforts to combine data on the gut microbiota with the features that can be obtained from the conversion of brain images into mineable data. The subsequent analysis of these data for diagnostic and prognostic purposes is an approach we call radiomicrobiomics and it holds tremendous potential to enhance our understanding of this fascinating connection. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

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

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

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain

PubMed Central

Ringstad, Geir

2015-01-01

Recently, the “glymphatic system” of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain. PMID:26634147

Functional magnetic resonance imaging: basic principles and application in the neurosciences.

PubMed

Labbé Atenas, T; Ciampi Díaz, E; Cruz Quiroga, J P; Uribe Arancibia, S; Cárcamo Rodríguez, C

2018-03-12

Functional magnetic resonance imaging (fMRI) is an advanced tool for the study of brain functions in healthy subjects and in neuropsychiatric patients. This tool makes it possible to identify and locate specific phenomena related to neuronal metabolism and activity. Starting with the detection of changes in the blood supply to a region that participates in a function, more complex approaches have been developed to study the dynamics of neuronal networks. Studies examining the brain at rest or involved in different tasks have provided evidence related to the onset, development, and/or response to treatment in various diseases. The diversity of the possible artifacts associated with image registration as well as the complexity of the analytical experimental designs has generated abundant debate about the technique behind fMRI. This article aims to introduce readers to the fundamentals underlying fMRI, to explain how fMRI studies are interpreted, and to discuss fMRI's contributions to the study of the mechanisms underlying diverse diseases of the nervous system. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Towards the utilization of EEG as a brain imaging tool.

PubMed

Michel, Christoph M; Murray, Micah M

2012-06-01

Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications. Copyright © 2011 Elsevier Inc. All rights reserved.

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery

PubMed Central

Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lau, Steven; Lu, Weiguo; Yan, Yulong; Jiang, Steve B.; Zhen, Xin; Timmerman, Robert; Nedzi, Lucien

2017-01-01

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases. PMID:28985229

An investigation into the induced electric fields from transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Hadimani, Ravi; Lee, Erik; Duffy, Walter; Waris, Mohammed; Siddiqui, Waquar; Islam, Faisal; Rajamani, Mahesh; Nathan, Ryan; Jiles, David; David C Jiles Team; Walter Duffy Collaboration

Transcranial magnetic stimulation (TMS) is a promising tool for noninvasive brain stimulation that has been approved by the FDA for the treatment of major depressive disorder. To stimulate the brain, TMS uses large, transient pulses of magnetic field to induce an electric field in the head. This transient magnetic field is large enough to cause the depolarization of cortical neurons and initiate a synaptic signal transmission. For this study, 50 unique head models were created from MRI images. Previous simulation studies have primarily used a single head model, and thus give a limited image of the induced electric field from TMS. This study uses finite element analysis simulations on 50 unique, heterogeneous head models to better investigate the relationship between TMS and the electric field induced in brain tissues. Results showed a significant variation in the strength of the induced electric field in the brain, which can be reasonably predicted by the distance from the TMS coil to the stimulated brain. Further, it was seen that some models had high electric field intensities in over five times as much brain volume as other models.

Threshold selection for classification of MR brain images by clustering method

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Obreja, Cristian; Moraru, Luminita

2015-12-01

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

Neuroimaging biomarkers of preterm brain injury: toward developing the preterm connectome

PubMed Central

Panigrahy, Ashok; Wisnowski, Jessica L.; Furtado, Andre; Lepore, Natasha; Paquette, Lisa; Bluml, Stefan

2013-01-01

For typically developing infants, the last trimester of fetal development extending into the first post-natal months is a period of rapid brain development. Infants who are born premature face significant risk of brain injury (e.g., intraventricular or germinal matrix hemorrhage and periventricular leukomalacia) from complications in the perinatal period and also potential long-term neurodevelopmental disabilities because these early injuries can interrupt normal brain maturation. Neuroimaging has played an important role in the diagnosis and management of the preterm infant. Both cranial US and conventional MRI techniques are useful in diagnostic and prognostic evaluation of preterm brain development and injury. Cranial US is highly sensitive for intraventricular hemorrhage IVH and provides prognostic information regarding cerebral palsy. Data are limited regarding the utility of MRI as a routine screening instrument for brain injury for all preterm infants. However, MRI might provide diagnostic or prognostic information regarding PVL and other types of preterm brain injury in the setting of specific clinical indications and risk factors. Further development of advanced MR techniques like volumetric MR imaging, diffusion tensor imaging, metabolic imaging (MR spectroscopy) and functional connectivity are necessary to provide additional insight into the molecular, cellular and systems processes that underlie brain development and outcome in the preterm infant. The adult concept of the “connectome” is also relevant in understanding brain networks that underlie the preterm brain. Knowledge of the preterm connectome will provide a framework for understanding preterm brain function and dysfunction, and potentially even a roadmap for brain plasticity. By combining conventional imaging techniques with more advanced techniques, neuroimaging findings will likely be used not only as diagnostic and prognostic tools, but also as biomarkers for long-term neurodevelopmental outcomes, instruments to assess the efficacy of neuroprotective agents and maneuvers in the NICU, and as screening instruments to appropriately select infants for longitudinal developmental interventions. PMID:22395719

Intraoperative brain hemodynamic response assessment with real-time hyperspectral optical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Laurence, Audrey; Pichette, Julien; Angulo-Rodríguez, Leticia M.; Saint Pierre, Catherine; Lesage, Frédéric; Bouthillier, Alain; Nguyen, Dang Khoa; Leblond, Frédéric

2016-03-01

Following normal neuronal activity, there is an increase in cerebral blood flow and cerebral blood volume to provide oxygenated hemoglobin to active neurons. For abnormal activity such as epileptiform discharges, this hemodynamic response may be inadequate to meet the high metabolic demands. To verify this hypothesis, we developed a novel hyperspectral imaging system able to monitor real-time cortical hemodynamic changes during brain surgery. The imaging system is directly integrated into a surgical microscope, using the white-light source for illumination. A snapshot hyperspectral camera is used for detection (4x4 mosaic filter array detecting 16 wavelengths simultaneously). We present calibration experiments where phantoms made of intralipid and food dyes were imaged. Relative concentrations of three dyes were recovered at a video rate of 30 frames per second. We also present hyperspectral recordings during brain surgery of epileptic patients with concurrent electrocorticography recordings. Relative concentration maps of oxygenated and deoxygenated hemoglobin were extracted from the data, allowing real-time studies of hemodynamic changes with a good spatial resolution. Finally, we present preliminary results on phantoms obtained with an integrated spatial frequency domain imaging system to recover tissue optical properties. This additional module, used together with the hyperspectral imaging system, will allow quantification of hemoglobin concentrations maps. Our hyperspectral imaging system offers a new tool to analyze hemodynamic changes, especially in the case of epileptiform discharges. It also offers an opportunity to study brain connectivity by analyzing correlations between hemodynamic responses of different tissue regions.

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases

PubMed Central

Forbes, Jessica L.; Kim, Regina E. Y.; Paulsen, Jane S.; Johnson, Hans J.

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%. PMID:27536233

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases.

PubMed

Forbes, Jessica L; Kim, Regina E Y; Paulsen, Jane S; Johnson, Hans J

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%.

Planar implantable sensor for in vivo measurement of cellular oxygen metabolism in brain tissue.

PubMed

Tsytsarev, Vassiliy; Akkentli, Fatih; Pumbo, Elena; Tang, Qinggong; Chen, Yu; Erzurumlu, Reha S; Papkovsky, Dmitri B

2017-04-01

Brain imaging methods are continually improving. Imaging of the cerebral cortex is widely used in both animal experiments and charting human brain function in health and disease. Among the animal models, the rodent cerebral cortex has been widely used because of patterned neural representation of the whiskers on the snout and relative ease of activating cortical tissue with whisker stimulation. We tested a new planar solid-state oxygen sensor comprising a polymeric film with a phosphorescent oxygen-sensitive coating on the working side, to monitor dynamics of oxygen metabolism in the cerebral cortex following sensory stimulation. Sensory stimulation led to changes in oxygenation and deoxygenation processes of activated areas in the barrel cortex. We demonstrate the possibility of dynamic mapping of relative changes in oxygenation in live mouse brain tissue with such a sensor. Oxygenation-based functional magnetic resonance imaging (fMRI) is very effective method for functional brain mapping but have high costs and limited spatial resolution. Optical imaging of intrinsic signal (IOS) does not provide the required sensitivity, and voltage-sensitive dye optical imaging (VSDi) has limited applicability due to significant toxicity of the voltage-sensitive dye. Our planar solid-state oxygen sensor imaging approach circumvents these limitations, providing a simple optical contrast agent with low toxicity and rapid application. The planar solid-state oxygen sensor described here can be used as a tool in visualization and real-time analysis of sensory-evoked neural activity in vivo. Further, this approach allows visualization of local neural activity with high temporal and spatial resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

MRI as a tool to study brain structure from mouse models for mental retardation

NASA Astrophysics Data System (ADS)

Verhoye, Marleen; Sijbers, Jan; Kooy, R. F.; Reyniers, E.; Fransen, E.; Oostra, B. A.; Willems, Peter; Van der Linden, Anne-Marie

1998-07-01

Nowadays, transgenic mice are a common tool to study brain abnormalities in neurological disorders. These studies usually rely on neuropathological examinations, which have a number of drawbacks, including the risk of artefacts introduced by fixation and dehydration procedures. Here we present 3D Fast Spin Echo Magnetic Resonance Imaging (MRI) in combination with 2D and 3D segmentation techniques as a powerful tool to study brain anatomy. We set up MRI of the brain in mouse models for the fragile X syndrome (FMR1 knockout) and Corpus callosum hypoplasia, mental Retardation, Adducted thumbs, Spastic paraplegia and Hydrocephalus (CRASH) syndrome (L1CAM knockout). Our major goal was to determine qualitative and quantitative differences in specific brain structures. MRI of the brain of fragile X and CRASH patients has revealed alterations in the size of specific brain structures, including the cerebellar vermis and the ventricular system. In the present MRI study of the brain from fragile X knockout mice, we have measured the size of the brain, cerebellum and 4th ventricle, which were reported as abnormal in human fragile X patients, but found no evidence for altered brain regions in the mouse model. In CRASH syndrome, the most specific brain abnormalities are vermis hypoplasia and abnormalities of the ventricular system with some degree of hydrocephalus. With the MRI study of L1CAM knockout mice we found vermis hypoplasia, abnormalities of the ventricular system including dilatation of the lateral and the 4th ventricles. These subtle abnormalities were not detected upon standard neuropathological examination. Here we proved that this sensitive MRI technique allows to measure small differences which can not always be detected by means of pathology.

A mathematical theory of shape and neuro-fuzzy methodology-based diagnostic analysis: a comparative study on early detection and treatment planning of brain cancer.

PubMed

Kar, Subrata; Majumder, D Dutta

2017-08-01

Investigation of brain cancer can detect the abnormal growth of tissue in the brain using computed tomography (CT) scans and magnetic resonance (MR) images of patients. The proposed method classifies brain cancer on shape-based feature extraction as either benign or malignant. The authors used input variables such as shape distance (SD) and shape similarity measure (SSM) in fuzzy tools, and used fuzzy rules to evaluate the risk status as an output variable. We presented a classifier neural network system (NNS), namely Levenberg-Marquardt (LM), which is a feed-forward back-propagation learning algorithm used to train the NN for the status of brain cancer, if any, and which achieved satisfactory performance with 100% accuracy. The proposed methodology is divided into three phases. First, we find the region of interest (ROI) in the brain to detect the tumors using CT and MR images. Second, we extract the shape-based features, like SD and SSM, and grade the brain tumors as benign or malignant with the concept of SD function and SSM as shape-based parameters. Third, we classify the brain cancers using neuro-fuzzy tools. In this experiment, we used a 16-sample database with SSM (μ) values and classified the benignancy or malignancy of the brain tumor lesions using the neuro-fuzzy system (NFS). We have developed a fuzzy expert system (FES) and NFS for early detection of brain cancer from CT and MR images. In this experiment, shape-based features, such as SD and SSM, were extracted from the ROI of brain tumor lesions. These shape-based features were considered as input variables and, using fuzzy rules, we were able to evaluate brain cancer risk values for each case. We used an NNS with LM, a feed-forward back-propagation learning algorithm, as a classifier for the diagnosis of brain cancer and achieved satisfactory performance with 100% accuracy. The proposed network was trained with MR image datasets of 16 cases. The 16 cases were fed to the ANN with 2 input neurons, one hidden layer of 10 neurons and 2 output neurons. Of the 16-sample database, 10 datasets for training, 3 datasets for validation, and 3 datasets for testing were used in the ANN classification system. From the SSM (µ) confusion matrix, the number of output datasets of true positive, false positive, true negative and false negative was 6, 0, 10, and 0, respectively. The sensitivity, specificity and accuracy were each equal to 100%. The method of diagnosing brain cancer presented in this study is a successful model to assist doctors in the screening and treatment of brain cancer patients. The presented FES successfully identified the presence of brain cancer in CT and MR images using the extracted shape-based features and the use of NFS for the identification of brain cancer in the early stages. From the analysis and diagnosis of the disease, the doctors can decide the stage of cancer and take the necessary steps for more accurate treatment. Here, we have presented an investigation and comparison study of the shape-based feature extraction method with the use of NFS for classifying brain tumors as showing normal or abnormal patterns. The results have proved that the shape-based features with the use of NFS can achieve a satisfactory performance with 100% accuracy. We intend to extend this methodology for the early detection of cancer in other regions such as the prostate region and human cervix.

Feasibility of in Vivo SAXS Imaging for Detection of Alzheiemer's Disease

NASA Astrophysics Data System (ADS)

Choi, Mina

Small-angle x-ray scattering (SAXS) imaging has been proposed as a technique to characterize and selectively image structures based on electron density structure which allows for discriminating materials based on their scatter cross sections. This dissertation explores the feasibility of SAXS imaging for the detection of Alzheimer's disease (AD) amyloid plaques. The inherent scatter cross sections of amyloid plaque serve as biomarkers in vivo without the need of injected molecular tags. SAXS imaging can also assist in a better understanding of how these biomarkers play a role in Alzheimer's disease which in turn can lead to the development of more effective disease-modifying therapies. I implement simulations of x-ray transport using Monte Carlo methods for SAXS imaging enabling accurate calculation of radiation dose and image quality in SAXS-computed tomography (CT). I describe SAXS imaging phantoms with tissue-mimicking material and embedded scatter targets as a way of demonstrating the characteristics of SAXS imaging. I also performed a comprehensive study of scattering cross sections of brain tissue from measurements of ex-vivo sections of a wild-type mouse brain and reported generalized cross sections of gray matter, white matter, and corpus callosum obtained and registered by planar SAXS imaging. Finally, I demonstrate the ability of SAXS imaging to locate an amyloid fibril pellet within a brain section. This work contributes to novel application of SAXS imaging for Alzheimer's disease detection and studies its feasibility as an imaging tool for AD biomarkers.

Alpha-band rhythm modulation under the condition of subliminal face presentation: MEG study.

PubMed

Sakuraba, Satoshi; Kobayashi, Hana; Sakai, Shinya; Yokosawa, Koichi

2013-01-01

The human brain has two streams to process visual information: a dorsal stream and a ventral stream. Negative potential N170 or its magnetic counterpart M170 is known as the face-specific signal originating from the ventral stream. It is possible to present a visual image unconsciously by using continuous flash suppression (CFS), which is a visual masking technique adopting binocular rivalry. In this work, magnetoencephalograms were recorded during presentation of the three invisible images: face images, which are processed by the ventral stream; tool images, which could be processed by the dorsal stream, and a blank image. Alpha-band activities detected by sensors that are sensitive to M170 were compared. The alpha-band rhythm was suppressed more during presentation of face images than during presentation of the blank image (p=.028). The suppression remained for about 1 s after ending presentations. However, no significant difference was observed between tool and other images. These results suggest that alpha-band rhythm can be modulated also by unconscious visual images.

Selective plane illumination microscopy (SPIM) with time-domain fluorescence lifetime imaging microscopy (FLIM) for volumetric measurement of cleared mouse brain samples

NASA Astrophysics Data System (ADS)

Funane, Tsukasa; Hou, Steven S.; Zoltowska, Katarzyna Marta; van Veluw, Susanne J.; Berezovska, Oksana; Kumar, Anand T. N.; Bacskai, Brian J.

2018-05-01

We have developed an imaging technique which combines selective plane illumination microscopy with time-domain fluorescence lifetime imaging microscopy (SPIM-FLIM) for three-dimensional volumetric imaging of cleared mouse brains with micro- to mesoscopic resolution. The main features of the microscope include a wavelength-adjustable pulsed laser source (Ti:sapphire) (near-infrared) laser, a BiBO frequency-doubling photonic crystal, a liquid chamber, an electrically focus-tunable lens, a cuvette based sample holder, and an air (dry) objective lens. The performance of the system was evaluated with a lifetime reference dye and micro-bead phantom measurements. Intensity and lifetime maps of three-dimensional human embryonic kidney (HEK) cell culture samples and cleared mouse brain samples expressing green fluorescent protein (GFP) (donor only) and green and red fluorescent protein [positive Förster (fluorescence) resonance energy transfer] were acquired. The results show that the SPIM-FLIM system can be used for sample sizes ranging from single cells to whole mouse organs and can serve as a powerful tool for medical and biological research.

Evaluation of 64Cu-Based Radiopharmaceuticals that Target Aβ Peptide Aggregates as Diagnostic Tools for Alzheimer's Disease.

PubMed

Bandara, Nilantha; Sharma, Anuj K; Krieger, Stephanie; Schultz, Jason W; Han, Byung Hee; Rogers, Buck E; Mirica, Liviu M

2017-09-13

Positron emission tomography (PET) imaging agents that detect amyloid plaques containing amyloid beta (Aβ) peptide aggregates in the brain of Alzheimer's disease (AD) patients have been successfully developed and recently approved by the FDA for clinical use. However, the short half-lives of the currently used radionuclides 11 C (20.4 min) and 18 F (109.8 min) may limit the widespread use of these imaging agents. Therefore, we have begun to evaluate novel AD diagnostic agents that can be radiolabeled with 64 Cu, a radionuclide with a half-life of 12.7 h, ideal for PET imaging. Described herein are a series of bifunctional chelators (BFCs), L 1 -L 5 , that were designed to tightly bind 64 Cu and shown to interact with Aβ aggregates both in vitro and in transgenic AD mouse brain sections. Importantly, biodistribution studies show that these compounds exhibit promising brain uptake and rapid clearance in wild-type mice, and initial microPET imaging studies of transgenic AD mice suggest that these compounds could serve as lead compounds for the development of improved diagnostic agents for AD.

Enabling Real-Time Volume Rendering of Functional Magnetic Resonance Imaging on an iOS Device.

PubMed

Holub, Joseph; Winer, Eliot

2017-12-01

Powerful non-invasive imaging technologies like computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI) are used daily by medical professionals to diagnose and treat patients. While 2D slice viewers have long been the standard, many tools allowing 3D representations of digital medical data are now available. The newest imaging advancement, functional MRI (fMRI) technology, has changed medical imaging from viewing static to dynamic physiology (4D) over time, particularly to study brain activity. Add this to the rapid adoption of mobile devices for everyday work and the need to visualize fMRI data on tablets or smartphones arises. However, there are few mobile tools available to visualize 3D MRI data, let alone 4D fMRI data. Building volume rendering tools on mobile devices to visualize 3D and 4D medical data is challenging given the limited computational power of the devices. This paper describes research that explored the feasibility of performing real-time 3D and 4D volume raycasting on a tablet device. The prototype application was tested on a 9.7" iPad Pro using two different fMRI datasets of brain activity. The results show that mobile raycasting is able to achieve between 20 and 40 frames per second for traditional 3D datasets, depending on the sampling interval, and up to 9 frames per second for 4D data. While the prototype application did not always achieve true real-time interaction, these results clearly demonstrated that visualizing 3D and 4D digital medical data is feasible with a properly constructed software framework.

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

PubMed Central

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo

2016-01-01

Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

PubMed

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

2016-12-01

Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.

Ex-vivo quantitative susceptibility mapping of human brain hemispheres

PubMed Central

Kotrotsou, Aikaterini; Tamhane, Ashish A.; Dawe, Robert J.; Kapasi, Alifiya; Leurgans, Sue E.; Schneider, Julie A.; Bennett, David A.; Arfanakis, Konstantinos

2017-01-01

Ex-vivo brain quantitative susceptibility mapping (QSM) allows investigation of brain characteristics at essentially the same point in time as histopathologic examination, and therefore has the potential to become an important tool for determining the role of QSM as a diagnostic and monitoring tool of age-related neuropathologies. In order to be able to translate the ex-vivo QSM findings to in-vivo, it is crucial to understand the effects of death and chemical fixation on brain magnetic susceptibility measurements collected ex-vivo. Thus, the objective of this work was twofold: a) to assess the behavior of magnetic susceptibility in both gray and white matter of human brain hemispheres as a function of time postmortem, and b) to establish the relationship between in-vivo and ex-vivo gray matter susceptibility measurements on the same hemispheres. Five brain hemispheres from community-dwelling older adults were imaged ex-vivo with QSM on a weekly basis for six weeks postmortem, and the longitudinal behavior of ex-vivo magnetic susceptibility in both gray and white matter was assessed. The relationship between in-vivo and ex-vivo gray matter susceptibility measurements was investigated using QSM data from eleven older adults imaged both antemortem and postmortem. No systematic change in ex-vivo magnetic susceptibility of gray or white matter was observed over time postmortem. Additionally, it was demonstrated that, gray matter magnetic susceptibility measured ex-vivo may be well modeled as a linear function of susceptibility measured in-vivo. In conclusion, magnetic susceptibility in gray and white matter measured ex-vivo with QSM does not systematically change in the first six weeks after death. This information is important for future cross-sectional ex-vivo QSM studies of hemispheres imaged at different postmortem intervals. Furthermore, the linear relationship between in-vivo and ex-vivo gray matter magnetic susceptibility suggests that ex-vivo QSM captures information linked to antemortem gray matter magnetic susceptibility, which is important for translation of ex-vivo QSM findings to in-vivo. PMID:29261693

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.

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.

AP-MALDI Mass Spectrometry Imaging of Gangliosides Using 2,6-Dihydroxyacetophenone

NASA Astrophysics Data System (ADS)

Jackson, Shelley N.; Muller, Ludovic; Roux, Aurelie; Oktem, Berk; Moskovets, Eugene; Doroshenko, Vladimir M.; Woods, Amina S.

2018-03-01

Matrix-assisted laser/desorption ionization (MALDI) mass spectrometry imaging (MSI) is widely used as a unique tool to record the distribution of a large range of biomolecules in tissues. 2,6-Dihydroxyacetophenone (DHA) matrix has been shown to provide efficient ionization of lipids, especially gangliosides. The major drawback for DHA as it applies to MS imaging is that it sublimes under vacuum (low pressure) at the extended time necessary to complete both high spatial and mass resolution MSI studies of whole organs. To overcome the problem of sublimation, we used an atmospheric pressure (AP)-MALDI source to obtain high spatial resolution images of lipids in the brain using a high mass resolution mass spectrometer. Additionally, the advantages of atmospheric pressure and DHA for imaging gangliosides are highlighted. The imaging of [M-H]- and [M-H2O-H]- mass peaks for GD1 gangliosides showed different distribution, most likely reflecting the different spatial distribution of GD1a and GD1b species in the brain. [Figure not available: see fulltext.

Complex network inference from P300 signals: Decoding brain state under visual stimulus for able-bodied and disabled subjects

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Cai, Qing; Dong, Na; Zhang, Shan-Shan; Bo, Yun; Zhang, Jie

2016-10-01

Distinguishing brain cognitive behavior underlying disabled and able-bodied subjects constitutes a challenging problem of significant importance. Complex network has established itself as a powerful tool for exploring functional brain networks, which sheds light on the inner workings of the human brain. Most existing works in constructing brain network focus on phase-synchronization measures between regional neural activities. In contrast, we propose a novel approach for inferring functional networks from P300 event-related potentials by integrating time and frequency domain information extracted from each channel signal, which we show to be efficient in subsequent pattern recognition. In particular, we construct brain network by regarding each channel signal as a node and determining the edges in terms of correlation of the extracted feature vectors. A six-choice P300 paradigm with six different images is used in testing our new approach, involving one able-bodied subject and three disabled subjects suffering from multiple sclerosis, cerebral palsy, traumatic brain and spinal-cord injury, respectively. We then exploit global efficiency, local efficiency and small-world indices from the derived brain networks to assess the network topological structure associated with different target images. The findings suggest that our method allows identifying brain cognitive behaviors related to visual stimulus between able-bodied and disabled subjects.

The potential role of sensory testing, skin biopsy, and functional brain imaging as biomarkers in chronic pain clinical trials: IMMPACT considerations

PubMed Central

Smith, Shannon M.; Dworkin, Robert H.; Turk, Dennis C.; Baron, Ralf; Polydefkis, Michael; Tracey, Irene; Borsook, David; Edwards, Robert R.; Harris, Richard E.; Wager, Tor D.; Arendt-Nielsen, Lars; Burke, Laurie B.; Carr, Daniel B.; Chappell, Amy; Farrar, John T.; Freeman, Roy; Gilron, Ian; Goli, Veeraindar; Haeussler, Juergen; Jensen, Troels; Katz, Nathaniel P.; Kent, Jeffrey; Kopecky, Ernest A.; Lee, David A.; Maixner, William; Markman, John D.; McArthur, Justin C.; McDermott, Michael P.; Parvathenani, Lav; Raja, Srinivasa N.; Rappaport, Bob A.; Rice, Andrew S. C.; Rowbotham, Michael C.; Tobias, Jeffrey K.; Wasan, Ajay D.; Witter, James

2017-01-01

Valid and reliable biomarkers can play an important role in clinical trials as indicators of biological or pathogenic processes or as a signal of treatment response. Currently, there are no biomarkers for pain qualified by the US Food and Drug Administration or the European Medicines Agency for use in clinical trials. This article summarizes an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) meeting in which 3 potential biomarkers were discussed for use in the development of analgesic treatments: (1) sensory testing, (2), skin punch biopsy, and (3) brain imaging. The empirical evidence supporting the use of these tests is described within the context of the 4 categories of biomarkers: (1) diagnostic, (2) prognostic, (3) predictive, and (4) pharmacodynamic. Although sensory testing, skin punch biopsy, and brain imaging are promising tools for pain in clinical trials, additional evidence is needed to further support and standardize these tests for use as biomarkers in pain clinical trials. PMID:28254585

Nanosensors for the Chemical Imaging of Acetylcholine Using Magnetic Resonance Imaging.

PubMed

Luo, Yi; Kim, Eric H; Flask, Chris A; Clark, Heather A

2018-06-06

A suite of imaging tools for detecting specific chemicals in the central nervous system could accelerate the understanding of neural signaling events critical to brain function and disease. Here, we introduce a class of nanoparticle sensors for the highly specific detection of acetylcholine in the living brain using magnetic resonance imaging. The nanosensor is composed of acetylcholine-catalyzing enzymes and pH-sensitive gadolinium contrast agents co-localized onto the surface of polymer nanoparticles, which leads to changes in T 1 relaxation rate (1/ T 1 ). The mechanism of the sensor involves the enzymatic hydrolysis of acetylcholine leading to a localized decrease in pH which is detected by the pH-sensitive gadolinium chelate. The concomitant change in 1/ T 1 in vitro measured a 20% increase from 0 to 10 μM acetylcholine concentration. The applicability of the nanosensors in vivo was demonstrated in the rat medial prefrontal cortex showing distinct changes in 1/ T 1 induced by pharmacological stimuli. The highly specific acetylcholine nanosensor we present here offers a promising strategy for detection of cholinergic neurotransmission and will facilitate our understanding of brain function through chemical imaging.

Machine learning for neuroimaging with scikit-learn.

PubMed

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

Machine learning for neuroimaging with scikit-learn

PubMed Central

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388

Three-dimensional imaging of the brain cavities in human embryos.

PubMed

Blaas, H G; Eik-Nes, S H; Kiserud, T; Berg, S; Angelsen, B; Olstad, B

1995-04-01

A system for high-resolution three-dimensional imaging of small structures has been developed, based on the Vingmed CFM-800 annular array sector scanner with a 7.5-MHz transducer attached to a PC-based TomTec Echo-Scan unit. A stepper motor rotates the transducer 180 degrees and the complete three-dimensional scan consists of 132 two-dimensional images, video-grabbed and scan-converted into a regular volumetric data set by the TomTec unit. Three normal pregnancies with embryos of gestational age 7, 9 and 10 weeks received a transvaginal examination with special attention to the embryonic/fetal brain. In all three cases, it was possible to obtain high-resolution images of the brain cavities. At 7 weeks, both hemispheres and their connection to the third ventricle were delineated. The isthmus rhombencephali could be visualized. At 9 weeks, the continuous development of the brain cavities could be followed and at 11 weeks the dominating size of the hemispheres could be depicted. It is concluded that present ultrasound technology has reached a stage where structures of only a few millimeters can be imaged in vivo in three-dimensions with a quality that resembles the plaster figures used in embryonic laboratories. The method can become an important tool in future embryological research and also in the detection of early developmental disorders of the embryo.

Intravital imaging of dendritic spine plasticity

PubMed Central

Sau Wan Lai, Cora

2014-01-01

Abstract Dendritic spines are the postsynaptic part of most excitatory synapses in the mammalian brain. Recent works have suggested that the structural and functional plasticity of dendritic spines have been associated with information coding and memories. Advances in imaging and labeling techniques enable the study of dendritic spine dynamics in vivo. This perspective focuses on intravital imaging studies of dendritic spine plasticity in the neocortex. I will introduce imaging tools for studying spine dynamics and will further review current findings on spine structure and function under various physiological and pathological conditions. PMID:28243511

Educational Neuroscience: Neuroethical Considerations

ERIC Educational Resources Information Center

Lalancette, Helene; Campbell, Stephen R.

2012-01-01

Research design and methods in educational neuroscience involve using neuroscientific tools such as brain image technologies to investigate cognitive functions and inform educational practices. The ethical challenges raised by research in social neuroscience have become the focus of neuroethics, a sub-discipline of bioethics. More specifically…

Camelid single-domain antibodies: A versatile tool for in vivo imaging of extracellular and intracellular brain targets.

PubMed

Li, Tengfei; Vandesquille, Matthias; Koukouli, Fani; Dudeffant, Clémence; Youssef, Ihsen; Lenormand, Pascal; Ganneau, Christelle; Maskos, Uwe; Czech, Christian; Grueninger, Fiona; Duyckaerts, Charles; Dhenain, Marc; Bay, Sylvie; Delatour, Benoît; Lafaye, Pierre

2016-12-10

Detection of intracerebral targets with imaging probes is challenging due to the non-permissive nature of blood-brain barrier (BBB). The present work describes two novel single-domain antibodies (VHHs or nanobodies) that specifically recognize extracellular amyloid deposits and intracellular tau neurofibrillary tangles, the two core lesions of Alzheimer's disease (AD). Following intravenous administration in transgenic mouse models of AD, in vivo real-time two-photon microscopy showed gradual extravasation of the VHHs across the BBB, diffusion in the parenchyma and labeling of amyloid deposits and neurofibrillary tangles. Our results demonstrate that VHHs can be used as specific BBB-permeable probes for both extracellular and intracellular brain targets and suggest new avenues for therapeutic and diagnostic applications in neurology. Copyright © 2016 Elsevier B.V. All rights reserved.

Validation of DWI pre-processing procedures for reliable differentiation between human brain gliomas.

PubMed

Vellmer, Sebastian; Tonoyan, Aram S; Suter, Dieter; Pronin, Igor N; Maximov, Ivan I

2018-02-01

Diffusion magnetic resonance imaging (dMRI) is a powerful tool in clinical applications, in particular, in oncology screening. dMRI demonstrated its benefit and efficiency in the localisation and detection of different types of human brain tumours. Clinical dMRI data suffer from multiple artefacts such as motion and eddy-current distortions, contamination by noise, outliers etc. In order to increase the image quality of the derived diffusion scalar metrics and the accuracy of the subsequent data analysis, various pre-processing approaches are actively developed and used. In the present work we assess the effect of different pre-processing procedures such as a noise correction, different smoothing algorithms and spatial interpolation of raw diffusion data, with respect to the accuracy of brain glioma differentiation. As a set of sensitive biomarkers of the glioma malignancy grades we chose the derived scalar metrics from diffusion and kurtosis tensor imaging as well as the neurite orientation dispersion and density imaging (NODDI) biophysical model. Our results show that the application of noise correction, anisotropic diffusion filtering, and cubic-order spline interpolation resulted in the highest sensitivity and specificity for glioma malignancy grading. Thus, these pre-processing steps are recommended for the statistical analysis in brain tumour studies. Copyright © 2017. Published by Elsevier GmbH.

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

PubMed

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

2018-06-12

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

The insect central complex as model for heterochronic brain development-background, concepts, and tools.

PubMed

Koniszewski, Nikolaus Dieter Bernhard; Kollmann, Martin; Bigham, Mahdiyeh; Farnworth, Max; He, Bicheng; Büscher, Marita; Hütteroth, Wolf; Binzer, Marlene; Schachtner, Joachim; Bucher, Gregor

2016-06-01

The adult insect brain is composed of neuropils present in most taxa. However, the relative size, shape, and developmental timing differ between species. This diversity of adult insect brain morphology has been extensively described while the genetic mechanisms of brain development are studied predominantly in Drosophila melanogaster. However, it has remained enigmatic what cellular and genetic mechanisms underlie the evolution of neuropil diversity or heterochronic development. In this perspective paper, we propose a novel approach to study these questions. We suggest using genome editing to mark homologous neural cells in the fly D. melanogaster, the beetle Tribolium castaneum, and the Mediterranean field cricket Gryllus bimaculatus to investigate developmental differences leading to brain diversification. One interesting aspect is the heterochrony observed in central complex development. Ancestrally, the central complex is formed during embryogenesis (as in Gryllus) but in Drosophila, it arises during late larval and metamorphic stages. In Tribolium, it forms partially during embryogenesis. Finally, we present tools for brain research in Tribolium including 3D reconstruction and immunohistochemistry data of first instar brains and the generation of transgenic brain imaging lines. Further, we characterize reporter lines labeling the mushroom bodies and reflecting the expression of the neuroblast marker gene Tc-asense, respectively.

Neurocognitive inefficacy of the strategy process.

PubMed

Klein, Harold E; D'Esposito, Mark

2007-11-01

The most widely used (and taught) protocols for strategic analysis-Strengths, Weaknesses, Opportunities, and Threats (SWOT) and Porter's (1980) Five Force Framework for industry analysis-have been found to be insufficient as stimuli for strategy creation or even as a basis for further strategy development. We approach this problem from a neurocognitive perspective. We see profound incompatibilities between the cognitive process-deductive reasoning-channeled into the collective mind of strategists within the formal planning process through its tools of strategic analysis (i.e., rational technologies) and the essentially inductive reasoning process actually needed to address ill-defined, complex strategic situations. Thus, strategic analysis protocols that may appear to be and, indeed, are entirely rational and logical are not interpretable as such at the neuronal substrate level where thinking takes place. The analytical structure (or propositional representation) of these tools results in a mental dead end, the phenomenon known in cognitive psychology as functional fixedness. The difficulty lies with the inability of the brain to make out meaningful (i.e., strategy-provoking) stimuli from the mental images (or depictive representations) generated by strategic analysis tools. We propose decreasing dependence on these tools and conducting further research employing brain imaging technology to explore complex data handling protocols with richer mental representation and greater potential for strategy creation.

Using brain stimulation to disentangle neural correlates of conscious vision

PubMed Central

de Graaf, Tom A.; Sack, Alexander T.

2014-01-01

Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs. PMID:25295015

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.

Single-subject-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mild traumatic brain injury

PubMed Central

Huang, Ming-Xiong; Nichols, Sharon; Baker, Dewleen G.; Robb, Ashley; Angeles, Annemarie; Yurgil, Kate A.; Drake, Angela; Levy, Michael; Song, Tao; McLay, Robert; Theilmann, Rebecca J.; Diwakar, Mithun; Risbrough, Victoria B.; Ji, Zhengwei; Huang, Charles W.; Chang, Douglas G.; Harrington, Deborah L.; Muzzatti, Laura; Canive, Jose M.; Christopher Edgar, J.; Chen, Yu-Han; Lee, Roland R.

2014-01-01

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI) can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1–4 Hz) that can be measured and localized by resting-state magnetoencephalography (MEG). In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1–4 Hz) from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes), our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes), blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI. PMID:25009772

Simulation of High-Resolution Magnetic Resonance Images on the IBM Blue Gene/L Supercomputer Using SIMRI

DOE PAGES

Baum, K. G.; Menezes, G.; Helguera, M.

2011-01-01

Medical imaging system simulators are tools that provide a means to evaluate system architecture and create artificial image sets that are appropriate for specific applications. We have modified SIMRI, a Bloch equation-based magnetic resonance image simulator, in order to successfully generate high-resolution 3D MR images of the Montreal brain phantom using Blue Gene/L systems. Results show that redistribution of the workload allows an anatomically accurate 256 3 voxel spin-echo simulation in less than 5 hours when executed on an 8192-node partition of a Blue Gene/L system.

Simulation of High-Resolution Magnetic Resonance Images on the IBM Blue Gene/L Supercomputer Using SIMRI.

PubMed

Baum, K G; Menezes, G; Helguera, M

2011-01-01

Medical imaging system simulators are tools that provide a means to evaluate system architecture and create artificial image sets that are appropriate for specific applications. We have modified SIMRI, a Bloch equation-based magnetic resonance image simulator, in order to successfully generate high-resolution 3D MR images of the Montreal brain phantom using Blue Gene/L systems. Results show that redistribution of the workload allows an anatomically accurate 256(3) voxel spin-echo simulation in less than 5 hours when executed on an 8192-node partition of a Blue Gene/L system.

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.

[Recent advances in newborn MRI].

PubMed

Morel, B; Hornoy, P; Husson, B; Bloch, I; Adamsbaum, C

2014-07-01

The accurate morphological exploration of the brain is a major challenge in neonatology that advances in magnetic resonance imaging (MRI) can now provide. MRI is the gold standard if an hypoxic ischemic pathology is suspected in a full term neonate. In prematures, the specific role of MRI remains to be defined, secondary to US in any case. We present a state of the art of hardware and software technical developments in MRI. The increase in magnetic field strength (3 tesla) and the emergence of new MRI sequences provide access to new information. They both have positive and negative consequences on the daily clinical data acquisition use. The semiology of brain imaging in full term newborns and prematures is more extensive and complex and thereby more difficult to interpret. The segmentation of different brain structures in the newborn, even very premature, is now available. It is now possible to dissociate the cortex and basal ganglia from the cerebral white matter, to calculate the volume of anatomical structures, which improves the morphometric quantification and the understanding of the normal and abnormal brain development. MRI is a powerful tool to analyze the neonatal brain. The relevance of the diagnostic contribution requires an adaptation of the parameters of the sequences to acquire and of the image processing methods. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

A challenging issue: Detection of white matter hyperintensities in neonatal brain MRI.

PubMed

Morel, Baptiste; Yongchao Xu; Virzi, Alessio; Geraud, Thierry; Adamsbaum, Catherine; Bloch, Isabelle

2016-08-01

The progress of magnetic resonance imaging (MRI) allows for a precise exploration of the brain of premature infants at term equivalent age. The so-called DEHSI (diffuse excessive high signal intensity) of the white matter of premature brains remains a challenging issue in terms of definition, and thus of interpretation. We propose a semi-automatic detection and quantification method of white matter hyperintensities in MRI relying on morphological operators and max-tree representations, which constitutes a powerful tool to help radiologists to improve their interpretation. Results show better reproducibility and robustness than interactive segmentation.

Seeing Circuits Assemble

PubMed Central

Lichtman, Jeff W.; Smith, Stephen J.

2009-01-01

Developmental neurobiology has been greatly invigorated by a recent string of breakthroughs in molecular biology and optical physics that permit direct in vivo observation of neural circuit assembly. The imaging done thus far suggests that as brains are built, a significant amount of unbuilding is also occurring. We offer the view that this tumult is the result of the intersecting behaviors of the many single-celled creatures (i.e., neurons, glia, and progenitors) that inhabit brains. New tools will certainly be needed if we wish to monitor the myriad cooperative and competitive interactions at play in the cellular society that builds brains. PMID:18995818

The Brain Database: A Multimedia Neuroscience Database for Research and Teaching

PubMed Central

Wertheim, Steven L.

1989-01-01

The Brain Database is an information tool designed to aid in the integration of clinical and research results in neuroanatomy and regional biochemistry. It can handle a wide range of data types including natural images, 2 and 3-dimensional graphics, video, numeric data and text. It is organized around three main entities: structures, substances and processes. The database will support a wide variety of graphical interfaces. Two sample interfaces have been made. This tool is intended to serve as one component of a system that would allow neuroscientists and clinicians 1) to represent clinical and experimental data within a common framework 2) to compare results precisely between experiments and among laboratories, 3) to use computing tools as an aid in collaborative work and 4) to contribute to a shared and accessible body of knowledge about the nervous system.

The Function Biomedical Informatics Research Network Data Repository.

PubMed

Keator, David B; van Erp, Theo G M; Turner, Jessica A; Glover, Gary H; Mueller, Bryon A; Liu, Thomas T; Voyvodic, James T; Rasmussen, Jerod; Calhoun, Vince D; Lee, Hyo Jong; Toga, Arthur W; McEwen, Sarah; Ford, Judith M; Mathalon, Daniel H; Diaz, Michele; O'Leary, Daniel S; Jeremy Bockholt, H; Gadde, Syam; Preda, Adrian; Wible, Cynthia G; Stern, Hal S; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G

2016-01-01

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data. Copyright © 2015 Elsevier Inc. All rights reserved.

When structure affects function--the need for partial volume effect correction in functional and resting state magnetic resonance imaging studies.

PubMed

Dukart, Juergen; Bertolino, Alessandro

2014-01-01

Both functional and also more recently resting state magnetic resonance imaging have become established tools to investigate functional brain networks. Most studies use these tools to compare different populations without controlling for potential differences in underlying brain structure which might affect the functional measurements of interest. Here, we adapt a simulation approach combined with evaluation of real resting state magnetic resonance imaging data to investigate the potential impact of partial volume effects on established functional and resting state magnetic resonance imaging analyses. We demonstrate that differences in the underlying structure lead to a significant increase in detected functional differences in both types of analyses. Largest increases in functional differences are observed for highest signal-to-noise ratios and when signal with the lowest amount of partial volume effects is compared to any other partial volume effect constellation. In real data, structural information explains about 25% of within-subject variance observed in degree centrality--an established resting state connectivity measurement. Controlling this measurement for structural information can substantially alter correlational maps obtained in group analyses. Our results question current approaches of evaluating these measurements in diseased population with known structural changes without controlling for potential differences in these measurements.

sfDM: Open-Source Software for Temporal Analysis and Visualization of Brain Tumor Diffusion MR Using Serial Functional Diffusion Mapping.

PubMed

Ceschin, Rafael; Panigrahy, Ashok; Gopalakrishnan, Vanathi

2015-01-01

A major challenge in the diagnosis and treatment of brain tumors is tissue heterogeneity leading to mixed treatment response. Additionally, they are often difficult or at very high risk for biopsy, further hindering the clinical management process. To overcome this, novel advanced imaging methods are increasingly being adapted clinically to identify useful noninvasive biomarkers capable of disease stage characterization and treatment response prediction. One promising technique is called functional diffusion mapping (fDM), which uses diffusion-weighted imaging (DWI) to generate parametric maps between two imaging time points in order to identify significant voxel-wise changes in water diffusion within the tumor tissue. Here we introduce serial functional diffusion mapping (sfDM), an extension of existing fDM methods, to analyze the entire tumor diffusion profile along the temporal course of the disease. sfDM provides the tools necessary to analyze a tumor data set in the context of spatiotemporal parametric mapping: the image registration pipeline, biomarker extraction, and visualization tools. We present the general workflow of the pipeline, along with a typical use case for the software. sfDM is written in Python and is freely available as an open-source package under the Berkley Software Distribution (BSD) license to promote transparency and reproducibility.

Non-invasive fluorescent imaging of gliosis in transgenic mice for profiling developmental neurotoxicity

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

Ho, Gideon; Zhang Chunyan; Zhuo Lang

2007-05-15

Gliosis is a universal response of Brain to almost all types of neural insults, including neurotoxicity, neurodegeneration, viral infection, and stroke. A hallmark of gliotic reaction is the up-regulation of the astrocytic biomarker GFAP (glial fibrillary acidic protein), which often precedes the anatomically apparent damages in Brain. In this study, neonatal transgenic mice at postnatal day (PD) 4 expressing GFP (green fluorescent protein) under the control of a widely used 2.2-kb human GFAP promoter in Brain are treated with two model neurotoxicants, 1-methyl-4(2'-methylphenyl)-1,2,3,6-tetrahydropyridine (2'-CH{sub 3}-MPTP), and kainic acid (KA), respectively, to induce gliosis. Here we show that the neurotoxicant-induced acutemore » gliosis can be non-invasively imaged and quantified in Brain of conscious (un-anesthetized) mice in real-time, at 0, 2, 4, 6, and 8 h post-toxicant dosing. Therefore the current methodology could be a useful tool for studying the developmental aspects of neuropathies and neurotoxicity.« less

Granular computing with multiple granular layers for brain big data processing.

PubMed

Wang, Guoyin; Xu, Ji

2014-12-01

Big data is the term for a collection of datasets so huge and complex that it becomes difficult to be processed using on-hand theoretical models and technique tools. Brain big data is one of the most typical, important big data collected using powerful equipments of functional magnetic resonance imaging, multichannel electroencephalography, magnetoencephalography, Positron emission tomography, near infrared spectroscopic imaging, as well as other various devices. Granular computing with multiple granular layers, referred to as multi-granular computing (MGrC) for short hereafter, is an emerging computing paradigm of information processing, which simulates the multi-granular intelligent thinking model of human brain. It concerns the processing of complex information entities called information granules, which arise in the process of data abstraction and derivation of information and even knowledge from data. This paper analyzes three basic mechanisms of MGrC, namely granularity optimization, granularity conversion, and multi-granularity joint computation, and discusses the potential of introducing MGrC into intelligent processing of brain big data.

Mapping Epileptic Activity: Sources or Networks for the Clinicians?

PubMed Central

Pittau, Francesca; Mégevand, Pierre; Sheybani, Laurent; Abela, Eugenio; Grouiller, Frédéric; Spinelli, Laurent; Michel, Christoph M.; Seeck, Margitta; Vulliemoz, Serge

2014-01-01

Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity. PMID:25414692

Optical manipulation for optogenetics: otoliths manipulation in zebrafish (Conference Presentation)

NASA Astrophysics Data System (ADS)

Favre-Bulle, Itia A.; Scott, Ethan; Rubinsztein-Dunlop, Halina

2016-03-01

Otoliths play an important role in Zebrafish in terms of hearing and sense of balance. Many studies have been conducted to understand its structure and function, however the encoding of its movement in the brain remains unknown. Here we developed a noninvasive system capable of manipulating the otolith using optical trapping while we image its behavioral response and brain activity. We'll also present our tools for behavioral response detection and brain activity mapping. Acceleration is sensed through movements of the otoliths in the inner ear. Because experimental manipulations involve movements, electrophysiology and fluorescence microscopy are difficult. As a result, the neural codes underlying acceleration sensation are poorly understood. We have developed a technique for optically trapping otoliths, allowing us to simulate acceleration in stationary larval zebrafish. By applying forces to the otoliths, we can elicit behavioral responses consistent with compensation for perceived acceleration. Since the animal is stationary, we can use calcium imaging in these animals' brains to identify the functional circuits responsible for mediating responses to acceleration in natural settings.

Neuroimaging of Cerebrovascular Disease in the Aging Brain

PubMed Central

Gupta, Ajay; Nair, Sreejit; Schweitzer, Andrew D.; Kishore, Sirish; Johnson, Carl E.; Comunale, Joseph P.; Tsiouris, Apostolos J.; Sanelli, Pina C.

2012-01-01

Cerebrovascular disease remains a significant public health burden with its greatest impact on the elderly population. Advances in neuroimaging techniques allow detailed and sophisticated evaluation of many manifestations of cerebrovascular disease in the brain parenchyma as well as in the intracranial and extracranial vasculature. These tools continue to contribute to our understanding of the multifactorial processes that occur in the age-dependent development of cerebrovascular disease. Structural abnormalities related to vascular disease in the brain and vessels have been well characterized with CT and MRI based techniques. We review some of the pathophysiologic mechanisms in the aging brain and cerebral vasculature and the related structural abnormalities detectable on neuroimaging, including evaluation of age-related white matter changes, atherosclerosis of the cerebral vasculature, and cerebral infarction. In addition, newer neuroimaging techniques, such as diffusion tensor imaging, perfusion techniques, and assessment of cerebrovascular reserve, are also reviewed, as these techniques can detect physiologic alterations which complement the morphologic changes that cause cerebrovascular disease in the aging brain.Further investigation of these advanced imaging techniques has potential application to the understanding and diagnosis of cerebrovascular disease in the elderly. PMID:23185721

Threshold selection for classification of MR brain images by clustering method

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

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

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

Neuroimaging in pedophilia.

PubMed

Wiebking, Christine; Northoff, Georg

2013-04-01

Paraphilia is a set of disorders characterized by abnormal sexual desires. Perhaps most discussed amongst them, pedophilia is a complex interaction of disturbances of the emotional, cognitive and sexual experience. Using new imaging techniques such as functional magnetic resonance imaging, neural correlates of emotional, sexual and cognitive abnormalities and interactions have been investigated. As described on the basis of current research, altered patterns of brain activity, especially in the frontal areas of the brain, are seen in pedophilia. Building on these results, the analysis of neural correlates of impaired psychological functions opens the opportunity to further explore sexual deviances, which may contribute ultimately to the development of tools for risk assessment, classification methods and new therapeutic approaches.

Toward a workbench for rodent brain image data: systems architecture and design.

PubMed

Moene, Ivar A; Subramaniam, Shankar; Darin, Dmitri; Leergaard, Trygve B; Bjaalie, Jan G

2007-01-01

We present a novel system for storing and manipulating microscopic images from sections through the brain and higher-level data extracted from such images. The system is designed and built on a three-tier paradigm and provides the research community with a web-based interface for facile use in neuroscience research. The Oracle relational database management system provides the ability to store a variety of objects relevant to the images and provides the framework for complex querying of data stored in the system. Further, the suite of applications intimately tied into the infrastructure in the application layer provide the user the ability not only to query and visualize the data, but also to perform analysis operations based on the tools embedded into the system. The presentation layer uses extant protocols of the modern web browser and this provides ease of use of the system. The present release, named Functional Anatomy of the Cerebro-Cerebellar System (FACCS), available through The Rodent Brain Workbench (http:// rbwb.org/), is targeted at the functional anatomy of the cerebro-cerebellar system in rats, and holds axonal tracing data from these projections. The system is extensible to other circuits and projections and to other categories of image data and provides a unique environment for analysis of rodent brain maps in the context of anatomical data. The FACCS application assumes standard animal brain atlas models and can be extended to future models. The system is available both for interactive use from a remote web-browser client as well as for download to a local server machine.

High-contrast differentiation resolution 3D imaging of rodent brain by X-ray computed microtomography

NASA Astrophysics Data System (ADS)

Zikmund, T.; Novotná, M.; Kavková, M.; Tesařová, M.; Kaucká, M.; Szarowská, B.; Adameyko, I.; Hrubá, E.; Buchtová, M.; Dražanová, E.; Starčuk, Z.; Kaiser, J.

2018-02-01

The biomedically focused brain research is largely performed on laboratory mice considering a high homology between the human and mouse genomes. A brain has an intricate and highly complex geometrical structure that is hard to display and analyse using only 2D methods. Applying some fast and efficient methods of brain visualization in 3D will be crucial for the neurobiology in the future. A post-mortem analysis of experimental animals' brains usually involves techniques such as magnetic resonance and computed tomography. These techniques are employed to visualize abnormalities in the brains' morphology or reparation processes. The X-ray computed microtomography (micro CT) plays an important role in the 3D imaging of internal structures of a large variety of soft and hard tissues. This non-destructive technique is applied in biological studies because the lab-based CT devices enable to obtain a several-micrometer resolution. However, this technique is always used along with some visualization methods, which are based on the tissue staining and thus differentiate soft tissues in biological samples. Here, a modified chemical contrasting protocol of tissues for a micro CT usage is introduced as the best tool for ex vivo 3D imaging of a post-mortem mouse brain. This way, the micro CT provides a high spatial resolution of the brain microscopic anatomy together with a high tissue differentiation contrast enabling to identify more anatomical details in the brain. As the micro CT allows a consequent reconstruction of the brain structures into a coherent 3D model, some small morphological changes can be given into context of their mutual spatial relationships.

Techniques on semiautomatic segmentation using the Adobe Photoshop

NASA Astrophysics Data System (ADS)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

2005-04-01

The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.

NIR time domain diffuse optical tomography experiments on human forearm

NASA Astrophysics Data System (ADS)

Zhao, Huijuan; Gao, Feng; Tanikawa, Yukari; Homma, Kazuhiro; Yamada, Yukio

2003-07-01

To date, the applications of near infrared (NIR) diffusion optical tomography (DOT) are mostly focused on the potential of imaging woman breast, human head hemodynamics and neonatal head. For the neonates, who are suffered from ischaemia or hemorrhages in brain, bedside monitoring of the cerebral perfusion situation, e.g., the blood oxygen saturation and blood volume, is necessary for avoiding permanent injure. NIR DOT is on the promising tools because it is noninvasive, smaller in size, and moveable. Prior to achieving the ultimate goal of imaging infant brain and woman breast using DOT, in this paper, the developed methodologies are justified by imaging in vivo human forearms. The absolute absorption- and scattering-coefficient images revealed the inner structure of the forearm and the bones were clearly distinguished from the muscle. The differential images showed the changes in oxy-hemoglobin, deoxy-hemoglobin and blood volume during the hand-gripping exercises, which are consistent with the physiological process reported on literatures.

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.

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

PubMed

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

2014-10-01

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

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

PubMed Central

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

2014-01-01

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

Single slice US-MRI registration for neurosurgical MRI-guided US

NASA Astrophysics Data System (ADS)

Pardasani, Utsav; Baxter, John S. H.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Image-based ultrasound to magnetic resonance image (US-MRI) registration can be an invaluable tool in image-guided neuronavigation systems. State-of-the-art commercial and research systems utilize image-based registration to assist in functions such as brain-shift correction, image fusion, and probe calibration. Since traditional US-MRI registration techniques use reconstructed US volumes or a series of tracked US slices, the functionality of this approach can be compromised by the limitations of optical or magnetic tracking systems in the neurosurgical operating room. These drawbacks include ergonomic issues, line-of-sight/magnetic interference, and maintenance of the sterile field. For those seeking a US vendor-agnostic system, these issues are compounded with the challenge of instrumenting the probe without permanent modification and calibrating the probe face to the tracking tool. To address these challenges, this paper explores the feasibility of a real-time US-MRI volume registration in a small virtual craniotomy site using a single slice. We employ the Linear Correlation of Linear Combination (LC2) similarity metric in its patch-based form on data from MNI's Brain Images for Tumour Evaluation (BITE) dataset as a PyCUDA enabled Python module in Slicer. By retaining the original orientation information, we are able to improve on the poses using this approach. To further assist the challenge of US-MRI registration, we also present the BOXLC2 metric which demonstrates a speed improvement to LC2, while retaining a similar accuracy in this context.

The informatics of a C57BL/6J mouse brain atlas.

PubMed

MacKenzie-Graham, Allan; Jones, Eagle S; Shattuck, David W; Dinov, Ivo D; Bota, Mihail; Toga, Arthur W

2003-01-01

The Mouse Atlas Project (MAP) aims to produce a framework for organizing and analyzing the large volumes of neuroscientific data produced by the proliferation of genetically modified animals. Atlases provide an invaluable aid in understanding the impact of genetic manipulations by providing a standard for comparison. We use a digital atlas as the hub of an informatics network, correlating imaging data, such as structural imaging and histology, with text-based data, such as nomenclature, connections, and references. We generated brain volumes using magnetic resonance microscopy (MRM), classical histology, and immunohistochemistry, and registered them into a common and defined coordinate system. Specially designed viewers were developed in order to visualize multiple datasets simultaneously and to coordinate between textual and image data. Researchers can navigate through the brain interchangeably, in either a text-based or image-based representation that automatically updates information as they move. The atlas also allows the independent entry of other types of data, the facile retrieval of information, and the straight-forward display of images. In conjunction with centralized servers, image and text data can be kept current and can decrease the burden on individual researchers' computers. A comprehensive framework that encompasses many forms of information in the context of anatomic imaging holds tremendous promise for producing new insights. The atlas and associated tools can be found at http://www.loni.ucla.edu/MAP.

The Cerefy Neuroradiology Atlas: a Talairach-Tournoux atlas-based tool for analysis of neuroimages available over the internet.

PubMed

Nowinski, Wieslaw L; Belov, Dmitry

2003-09-01

The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.

The neural basis of functional neuroimaging signal with positron and single-photon emission tomography.

PubMed

Sestini, S

2007-07-01

Functional imaging techniques such as positron and single-photon emission tomography exploit the relationship between neural activity, energy demand and cerebral blood flow to functionally map the brain. Despite the fact that neurobiological processes are not completely understood, several results have revealed the signals that trigger the metabolic and vascular changes accompanying variations in neural activity. Advances in this field have demonstrated that release of the major excitatory neurotransmitter glutamate initiates diverse signaling processes between neurons, astrocytes and blood perfusion, and that this signaling is crucial for the occurrence of brain imaging signals. Better understanding of the neural sites of energy consumption and the temporal correlation between energy demand, energy consumption and associated cerebrovascular hemodynamics gives novel insight into the potential of these imaging tools in the study of metabolic neurodegenerative disorders.

iELVis: An open source MATLAB toolbox for localizing and visualizing human intracranial electrode data.

PubMed

Groppe, David M; Bickel, Stephan; Dykstra, Andrew R; Wang, Xiuyuan; Mégevand, Pierre; Mercier, Manuel R; Lado, Fred A; Mehta, Ashesh D; Honey, Christopher J

2017-04-01

Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive. iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Quantitative Susceptibility Mapping as a Possible Tool to Radiographically Diagnose Sentinel Headache Associated with Intracranial Aneurysm: Case Report.

PubMed

Nakagawa, Daichi; Cushing, Cameron; Nagahama, Yasunori; Allan, Lauren; Hasan, David

2017-07-01

Sentinel headache (SH) occurs before aneurysm rupture in an estimated 15%-60% of cases of aneurysmal subarachnoid hemorrhage (aSAH). By definition, noncontrast computed tomography (CT) scan of the brain and lumbar puncture are both negative in patients presenting with SH. One of the theories explaining this phenomenon is that microhemorrhage (MH) from the aneurysm wall contribute to iron deposition in the interface between the aneurysm wall and brain parenchyma. Quantitative susceptibility mapping (QSM) is a recently introduced magnetic resonance imaging (MRI) technique that has proven capable of localizing the deposition of paramagnetic metals, particularly ferric iron. Thus, the QSM sequence may be able to detect iron deposition secondary to MH. A 76-year-old male presented with the "worst headache of my life." Noncontrast head CT scan and lumbar puncture were negative. Magnetic resonance angiography (MRA) of the brain revealed an anterior communicating artery (A-com) aneurysm measuring 7 mm with a large bleb. T1-weighted imaging (WI), T2-WI, MRA, T2 star-weighted angiography (SWAN), and QSM sequences were obtained. T2-WI, SWAN, and QSM revealed isointense, hypointense, and hyperintense signals, respectively, at the interface of the aneurysm wall and brain tissue. These findings were consistent with deposition of ferric iron at this interface. The A-com aneurysm was treated with coil embolization, and the patient exhibited no postoperative deficits. The MRI QSM sequence can localize iron deposition resulting from MH within an aneurysmal wall. This sequence may be a promising imaging tool for screening patients presenting with SH. Copyright © 2017 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Wegmayr, Viktor; Aitharaju, Sai; Buhmann, Joachim

2018-02-01

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

Improved field localization in transcranial magnetic stimulation of the brain with the utilization of a conductive shield plate in the stimulator.

PubMed

Kim, Dong-Hun; Georghiou, George E; Won, Chulho

2006-04-01

In this paper, a carefully designed conductive shield plate is presented, which helps to improve localization of the electric field distribution induced by transcranial magnetic stimulation for neuron stimulation. The shield plate is introduced between a figure-of-eight coil and the head. In order to accurately predict the field distribution inside the brain and to examine the effects of the shield plate, a realistic head model is constructed from magnetic resonance image data with the help of image processing tools and the finite-element method in three dimensions is employed. Finally, to show the improvements obtained, the results are compared with two conventional coil designs. It is found that an incorporation of the shield plate into the coil, effectively improves the induced field localization by more than 50%, and prevents other parts of the brain from exposure to high pulsed magnetic fields.

Three-Dimensional Visualization with Large Data Sets: A Simulation of Spreading Cortical Depression in Human Brain

PubMed Central

Ertürk, Korhan Levent; Şengül, Gökhan

2012-01-01

We developed 3D simulation software of human organs/tissues; we developed a database to store the related data, a data management system to manage the created data, and a metadata system for the management of data. This approach provides two benefits: first of all the developed system does not require to keep the patient's/subject's medical images on the system, providing less memory usage. Besides the system also provides 3D simulation and modification options, which will help clinicians to use necessary tools for visualization and modification operations. The developed system is tested in a case study, in which a 3D human brain model is created and simulated from 2D MRI images of a human brain, and we extended the 3D model to include the spreading cortical depression (SCD) wave front, which is an electrical phoneme that is believed to cause the migraine. PMID:23258956

Mapping pharmaceuticals in rat brain sections using MALDI imaging mass spectrometry.

PubMed

Hsieh, Yunsheng; Li, Fangbiao; Korfmacher, Walter A

2010-01-01

Matrix-assisted laser desorption/ionization-tandem mass spectrometric method (MALDI-MS/MS) has proven to be a reliable tool for direct measurement of the disposition of small molecules in animal tissue sections. As example, MALDI-MS/MS imaging system was employed for visualizing the spatial distribution of astemizole and its primary metabolite in rat brain tissues. Astemizole is a second-generation antihistamine, a block peripheral H1 receptor, which was introduced to provide comparable therapeutic benefit but was withdrawn in most countries due to toxicity risks. Astemizole was observed to be heterogeneously distributed to most parts of brain tissue slices including cortex, hippocampus, hypothalamic, thalamus, and ventricle regions while its major metabolite, desmethylastemizole, was only found around ventricle sites. We have shown that astemizole alone is likely to be responsible for the central nervous system (CNS) side effects when its exposures became elevated.

Single-cell imaging tools for brain energy metabolism: a review

PubMed Central

San Martín, Alejandro; Sotelo-Hitschfeld, Tamara; Lerchundi, Rodrigo; Fernández-Moncada, Ignacio; Ceballo, Sebastian; Valdebenito, Rocío; Baeza-Lehnert, Felipe; Alegría, Karin; Contreras-Baeza, Yasna; Garrido-Gerter, Pamela; Romero-Gómez, Ignacio; Barros, L. Felipe

2014-01-01

Abstract. Neurophotonics comes to light at a time in which advances in microscopy and improved calcium reporters are paving the way toward high-resolution functional mapping of the brain. This review relates to a parallel revolution in metabolism. We argue that metabolism needs to be approached both in vitro and in vivo, and that it does not just exist as a low-level platform but is also a relevant player in information processing. In recent years, genetically encoded fluorescent nanosensors have been introduced to measure glucose, glutamate, ATP, NADH, lactate, and pyruvate in mammalian cells. Reporting relative metabolite levels, absolute concentrations, and metabolic fluxes, these sensors are instrumental for the discovery of new molecular mechanisms. Sensors continue to be developed, which together with a continued improvement in protein expression strategies and new imaging technologies, herald an exciting era of high-resolution characterization of metabolism in the brain and other organs. PMID:26157964

Chemical reactivation of resin-embedded pHuji adds red for simultaneous two-color imaging with EGFP

PubMed Central

Guo, Wenyan; Liu, Xiuli; Liu, Yurong; Gang, Yadong; He, Xiaobin; Jia, Yao; Yin, Fangfang; Li, Pei; Huang, Fei; Zhou, Hongfu; Wang, Xiaojun; Gong, Hui; Luo, Qingming; Xu, Fuqiang; Zeng, Shaoqun

2017-01-01

The pH-sensitive fluorescent proteins enabling chemical reactivation in resin are useful tools for fluorescence microimaging. EGFP or EYFP is good for such applications. For simultaneous two-color imaging, a suitable red fluorescent protein is an urgent need. Here a pH-sensitive red fluorescent protein, pHuji, is selected and verified to remain pH-sensitive in HM20 resin. We observe 183% fluorescence intensity of pHuji in resin-embeded mouse brain and 29.08-fold fluorescence intensity of reactivated pHuji compared to the quenched state. pHuji and EGFP can be quenched and chemically reactivated simultaneously in resin, thus enabling simultaneous two-color micro-optical sectioning tomography of resin-embedded mouse brain. This method may greatly facilitate the visualization of neuronal morphology and neural circuits to promote understanding of the structure and function of the brain. PMID:28717566

Chemical reactivation of resin-embedded pHuji adds red for simultaneous two-color imaging with EGFP.

PubMed

Guo, Wenyan; Liu, Xiuli; Liu, Yurong; Gang, Yadong; He, Xiaobin; Jia, Yao; Yin, Fangfang; Li, Pei; Huang, Fei; Zhou, Hongfu; Wang, Xiaojun; Gong, Hui; Luo, Qingming; Xu, Fuqiang; Zeng, Shaoqun

2017-07-01

The pH-sensitive fluorescent proteins enabling chemical reactivation in resin are useful tools for fluorescence microimaging. EGFP or EYFP is good for such applications. For simultaneous two-color imaging, a suitable red fluorescent protein is an urgent need. Here a pH-sensitive red fluorescent protein, pHuji, is selected and verified to remain pH-sensitive in HM20 resin. We observe 183% fluorescence intensity of pHuji in resin-embeded mouse brain and 29.08-fold fluorescence intensity of reactivated pHuji compared to the quenched state. pHuji and EGFP can be quenched and chemically reactivated simultaneously in resin, thus enabling simultaneous two-color micro-optical sectioning tomography of resin-embedded mouse brain. This method may greatly facilitate the visualization of neuronal morphology and neural circuits to promote understanding of the structure and function of the brain.

Magnetic resonance spectroscopy of the human brain

NASA Astrophysics Data System (ADS)

Strózik-Kotlorz, D.

2014-01-01

I give a brief description of the magnetic resonance spectroscopy (MRS) in the human brain examinations. MRS allows a noninvasive chemical analysis of the brain using a standard high field MR system. Nowadays, the dominant form of MR brain spectroscopy is proton spectroscopy. Two main techniques of MRS, which utilize the chemical shift of metabolites in the external magnetic field, are SVS (single voxel) and CSI (single slice). The major peaks in the spectrum of a normal brain include NAA, Cr, Cho and m-Ins, which are neuronal, energetic, membrane turnover and glial markers, respectively. In disease, two pathological metabolites can be found in the brain spectra: Lac, which is end product of anaerobic glycolysis and Lip, which is a marker of membrane breakdown, occurring in necrosis. The common way to analyze clinical spectra is to determine metabolite ratios, e.g. NAA/Cr, Cho/Cr, Cho/NAA. This analysis permits a safe and noninvasive examination of the brain tissue as each disease state has its own characteristic spectroscopic image. MRS is a valuable diagnostic tool in such clinical applications as detecting brain tumors and differentiating tumors from inflammatory and infectious processes. Proton MRS is also very helpful in diagnostic of ischemic lesions, Alzheimer's disease and hepatic encephalopathy. The MRS brain spectra should always be correlated with the Magnetic Resonance Imaging (MRI) results and alone cannot make neurological diagnosis.

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods.

PubMed

Georgiadis, Pantelis; Cavouras, Dionisis; Kalatzis, Ioannis; Glotsos, Dimitris; Athanasiadis, Emmanouil; Kostopoulos, Spiros; Sifaki, Koralia; Malamas, Menelaos; Nikiforidis, George; Solomou, Ekaterini

2009-01-01

Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.

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.

Multi-object model-based multi-atlas segmentation for rodent brains using dense discrete correspondences

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Kim, Sun Hyung; Styner, Martin

2016-03-01

The delineation of rodent brain structures is challenging due to low-contrast multiple cortical and subcortical organs that are closely interfacing to each other. Atlas-based segmentation has been widely employed due to its ability to delineate multiple organs at the same time via image registration. The use of multiple atlases and subsequent label fusion techniques has further improved the robustness and accuracy of atlas-based segmentation. However, the accuracy of atlas-based segmentation is still prone to registration errors; for example, the segmentation of in vivo MR images can be less accurate and robust against image artifacts than the segmentation of post mortem images. In order to improve the accuracy and robustness of atlas-based segmentation, we propose a multi-object, model-based, multi-atlas segmentation method. We first establish spatial correspondences across atlases using a set of dense pseudo-landmark particles. We build a multi-object point distribution model using those particles in order to capture inter- and intra- subject variation among brain structures. The segmentation is obtained by fitting the model into a subject image, followed by label fusion process. Our result shows that the proposed method resulted in greater accuracy than comparable segmentation methods, including a widely used ANTs registration tool.

The Hidden Lives of Nurses' Cognitive Artifacts.

PubMed

Blaz, Jacquelyn W; Doig, Alexa K; Cloyes, Kristin G; Staggers, Nancy

2016-09-07

Standardizing nursing handoffs at shift change is recommended to improve communication, with electronic tools as the primary approach. However, nurses continue to rely on personally created paper-based cognitive artifacts - their "paper brains" - to support handoffs, indicating a deficiency in available electronic versions. The purpose of this qualitative study was to develop a deep understanding of nurses' paper-based cognitive artifacts in the context of a cancer specialty hospital. After completing 73 hours of hospital unit field observations, 13 medical oncology nurses were purposively sampled, shadowed for a single shift and interviewed using a semi-structured technique. An interpretive descriptive study design guided analysis of the data corpus of field notes, transcribed interviews, images of nurses' paper-based cognitive artifacts, and analytic memos. Findings suggest nurses' paper brains are personal, dynamic, living objects that undergo a life cycle during each shift and evolve over the course of a nurse's career. The life cycle has four phases: Creation, Application, Reproduction, and Destruction. Evolution in a nurse's individually styled, paper brain is triggered by a change in the nurse's environment that reshapes cognitive needs. If a paper brain no longer provides cognitive support in the new environment, it is modified into (adapted) or abandoned (made extinct) for a different format that will provide the necessary support. The "hidden lives" - the life cycle and evolution - of paper brains have implications for the design of successful electronic tools to support nursing practice, including handoff. Nurses' paper brains provide cognitive support beyond the context of handoff. Information retrieval during handoff is undoubtedly an important function of nurses' paper brains, but tools designed to standardize handoff communication without accounting for cognitive needs during all phases of the paper brain life cycle or the ability to evolve with changes to those cognitive needs will be underutilized.

Multimodal optical imaging system for in vivo investigation of cerebral oxygen delivery and energy metabolism

PubMed Central

Yaseen, Mohammad A.; Srinivasan, Vivek J.; Gorczynska, Iwona; Fujimoto, James G.; Boas, David A.; Sakadžić, Sava

2015-01-01

Improving our understanding of brain function requires novel tools to observe multiple physiological parameters with high resolution in vivo. We have developed a multimodal imaging system for investigating multiple facets of cerebral blood flow and metabolism in small animals. The system was custom designed and features multiple optical imaging capabilities, including 2-photon and confocal lifetime microscopy, optical coherence tomography, laser speckle imaging, and optical intrinsic signal imaging. Here, we provide details of the system’s design and present in vivo observations of multiple metrics of cerebral oxygen delivery and energy metabolism, including oxygen partial pressure, microvascular blood flow, and NADH autofluorescence. PMID:26713212

The Potential Role of Sensory Testing, Skin Biopsy, and Functional Brain Imaging as Biomarkers in Chronic Pain Clinical Trials: IMMPACT Considerations.

PubMed

Smith, Shannon M; Dworkin, Robert H; Turk, Dennis C; Baron, Ralf; Polydefkis, Michael; Tracey, Irene; Borsook, David; Edwards, Robert R; Harris, Richard E; Wager, Tor D; Arendt-Nielsen, Lars; Burke, Laurie B; Carr, Daniel B; Chappell, Amy; Farrar, John T; Freeman, Roy; Gilron, Ian; Goli, Veeraindar; Haeussler, Juergen; Jensen, Troels; Katz, Nathaniel P; Kent, Jeffrey; Kopecky, Ernest A; Lee, David A; Maixner, William; Markman, John D; McArthur, Justin C; McDermott, Michael P; Parvathenani, Lav; Raja, Srinivasa N; Rappaport, Bob A; Rice, Andrew S C; Rowbotham, Michael C; Tobias, Jeffrey K; Wasan, Ajay D; Witter, James

2017-07-01

Valid and reliable biomarkers can play an important role in clinical trials as indicators of biological or pathogenic processes or as a signal of treatment response. Currently, there are no biomarkers for pain qualified by the U.S. Food and Drug Administration or the European Medicines Agency for use in clinical trials. This article summarizes an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials meeting in which 3 potential biomarkers were discussed for use in the development of analgesic treatments: 1) sensory testing, 2) skin punch biopsy, and 3) brain imaging. The empirical evidence supporting the use of these tests is described within the context of the 4 categories of biomarkers: 1) diagnostic, 2) prognostic, 3) predictive, and 4) pharmacodynamic. Although sensory testing, skin punch biopsy, and brain imaging are promising tools for pain in clinical trials, additional evidence is needed to further support and standardize these tests for use as biomarkers in pain clinical trials. The applicability of sensory testing, skin biopsy, and brain imaging as diagnostic, prognostic, predictive, and pharmacodynamic biomarkers for use in analgesic treatment trials is considered. Evidence in support of their use and outlining problems is presented, as well as a call for further standardization and demonstrations of validity and reliability. Copyright © 2017 American Pain Society. All rights reserved.

PET IMAGING STUDIES IN DRUG ABUSE RESEARCH.

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

Fowler, J.S.; Volkow, N.D.; Ding, Y.S.

There is overwhelming evidence that addiction is a disease of the brain (Leshner, 1997). Yet public perception that addiction is a reflection of moral weakness or a lack of willpower persists. The insidious consequence of this perception is that we lose sight of the fact that there are enormous medical consequences of addiction including the fact that a large fraction of the total deaths from cancer and heart disease are caused by smoking addiction. Ironically the medical school that educates physicians in addiction medicine and the cancer hospital that has a smoking cessation clinic are vanishingly rare and efforts atmore » harm reduction are frequently met with a public indignation. Meanwhile the number of people addicted to substances is enormous and increasing particularly the addictions to cigarettes and alcohol. It is particularly tragic that addiction usually begins in adolescence and becomes a chronic relapsing problem and there are basically no completely effective treatments. Clearly we need to understand how drugs of abuse affect the brain and we need to be creative in using this information to develop effective treatments. Imaging technologies have played a major role in the conceptualization of addiction as a disease of the brain (Fowler et al., 1998a; Fowler et al., 1999a). New knowledge has been driven by advances in radiotracer design and chemistry and positron emission tomography (PET) instrumentation and the integration of these scientific tools with the tools of biochemistry, pharmacology and medicine. This topic cuts across the medical specialties of neurology, psychiatry, cancer and heart disease because of the high medical, social and economic toll that drugs of abuse, including and especially the legal drugs, cigarettes and alcohol, take on society. In this chapter we will begin by highlighting the important role that chemistry has played in making it possible to quantitatively image the movement of drugs as well as their effects on the human brain. This will be followed by highlights of PET studies of the acute effects of the psychostimulant drugs cocaine and methylphenidate (ritalin) and studies of the chronic effects of cocaine and of tobacco smoke on the human brain. This chapter concludes with the description of a study which uses brain imaging coupled with a specific pharmacological challenge to address the age-old question of why some people who experiment with drugs become addicted while others do not.« less

Graph theory for feature extraction and classification: a migraine pathology case study.

PubMed

Jorge-Hernandez, Fernando; Garcia Chimeno, Yolanda; Garcia-Zapirain, Begonya; Cabrera Zubizarreta, Alberto; Gomez Beldarrain, Maria Angeles; Fernandez-Ruanova, Begonya

2014-01-01

Graph theory is also widely used as a representational form and characterization of brain connectivity network, as is machine learning for classifying groups depending on the features extracted from images. Many of these studies use different techniques, such as preprocessing, correlations, features or algorithms. This paper proposes an automatic tool to perform a standard process using images of the Magnetic Resonance Imaging (MRI) machine. The process includes pre-processing, building the graph per subject with different correlations, atlas, relevant feature extraction according to the literature, and finally providing a set of machine learning algorithms which can produce analyzable results for physicians or specialists. In order to verify the process, a set of images from prescription drug abusers and patients with migraine have been used. In this way, the proper functioning of the tool has been proved, providing results of 87% and 92% of success depending on the classifier used.

Imaging screening of catastrophic neurological events using a software tool: preliminary results.

PubMed

Fernandes, A P; Gomes, A; Veiga, J; Ermida, D; Vardasca, T

2015-05-01

In Portugal, as in most countries, the most frequent organ donors are brain-dead donors. To answer the increasing need for transplants, donation programs have been implemented. The goal is to recognize virtually all the possible and potential brain-dead donors admitted to hospitals. The aim of this work was to describe preliminary results of a software application designed to identify devastating neurological injury victims who may progress to brain death and can be possible organ donors. This was an observational, longitudinal study with retrospective data collection. The software application is an automatic algorithm based on natural language processing for selected keywords/expressions present in the cranio-encephalic computerized tomography (CE CT) scan reports to identify catastrophic neurological situations, with e-mail notification to the Transplant Coordinator (TC). The first 7 months of this application were analyzed and compared with the standard clinical evaluation methodology. The imaging identification tool showed a sensitivity of 77% and a specificity of 66%; predictive positive value (PPV) was 0.8 and predictive negative value (PNV) was 0.7 for the identification of catastrophic neurological events. The methodology proposed in this work seems promising in improving the screening efficiency of critical neurological events. Copyright © 2015 Elsevier Inc. All rights reserved.

Safety and feasibility of countering neurological impairment by intravenous administration of autologous cord blood in cerebral palsy

PubMed Central

2012-01-01

Backgrounds We conducted a pilot study of the infusion of intravenous autologous cord blood (CB) in children with cerebral palsy (CP) to assess the safety and feasibility of the procedure as well as its potential efficacy in countering neurological impairment. Methods Patients diagnosed with CP were enrolled in this study if their parents had elected to bank their CB at birth. Cryopreserved CB units were thawed and infused intravenously over 10~20 minutes. We assessed potential efficacy over 6 months by brain magnetic resonance imaging (MRI)-diffusion tensor imaging (DTI), brain perfusion single-photon emission computed tomography (SPECT), and various evaluation tools for motor and cognitive functions. Results Twenty patients received autologous CB infusion and were evaluated. The types of CP were as follows: 11 quadriplegics, 6 hemiplegics, and 3 diplegics. Infusion was generally well-tolerated, although 5 patients experienced temporary nausea, hemoglobinuria, or urticaria during intravenous infusion. Diverse neurological domains improved in 5 patients (25%) as assessed with developmental evaluation tools as well as by fractional anisotropy values in brain MRI-DTI. The neurologic improvement occurred significantly in patients with diplegia or hemiplegia rather than quadriplegia. Conclusions Autologous CB infusion is safe and feasible, and has yielded potential benefits in children with CP. PMID:22443810

A Manual Segmentation Tool for Three-Dimensional Neuron Datasets.

PubMed

Magliaro, Chiara; Callara, Alejandro L; Vanello, Nicola; Ahluwalia, Arti

2017-01-01

To date, automated or semi-automated software and algorithms for segmentation of neurons from three-dimensional imaging datasets have had limited success. The gold standard for neural segmentation is considered to be the manual isolation performed by an expert. To facilitate the manual isolation of complex objects from image stacks, such as neurons in their native arrangement within the brain, a new Manual Segmentation Tool (ManSegTool) has been developed. ManSegTool allows user to load an image stack, scroll down the images and to manually draw the structures of interest stack-by-stack. Users can eliminate unwanted regions or split structures (i.e., branches from different neurons that are too close each other, but, to the experienced eye, clearly belong to a unique cell), to view the object in 3D and save the results obtained. The tool can be used for testing the performance of a single-neuron segmentation algorithm or to extract complex objects, where the available automated methods still fail. Here we describe the software's main features and then show an example of how ManSegTool can be used to segment neuron images acquired using a confocal microscope. In particular, expert neuroscientists were asked to segment different neurons from which morphometric variables were subsequently extracted as a benchmark for precision. In addition, a literature-defined index for evaluating the goodness of segmentation was used as a benchmark for accuracy. Neocortical layer axons from a DIADEM challenge dataset were also segmented with ManSegTool and compared with the manual "gold-standard" generated for the competition.

Brain tissue analysis using texture features based on optical coherence tomography images

NASA Astrophysics Data System (ADS)

Lenz, Marcel; Krug, Robin; Dillmann, Christopher; Gerhardt, Nils C.; Welp, Hubert; Schmieder, Kirsten; Hofmann, Martin R.

2018-02-01

Brain tissue differentiation is highly demanded in neurosurgeries, i.e. tumor resection. Exact navigation during the surgery is essential in order to guarantee best life quality afterwards. So far, no suitable method has been found that perfectly covers this demands. With optical coherence tomography (OCT), fast three dimensional images can be obtained in vivo and contactless with a resolution of 1-15 μm. With these specifications OCT is a promising tool to support neurosurgeries. Here, we investigate ex vivo samples of meningioma, healthy white and healthy gray matter in a preliminary study towards in vivo brain tumor removal assistance. Raw OCT images already display structural variations for different tissue types, especially meningioma. But, in order to achieve neurosurgical guidance directly during resection, an automated differentiation approach is desired. For this reason, we employ different texture feature based algorithms, perform a Principal Component Analysis afterwards and then train a Support Vector Machine classifier. In the future we will try different combinations of texture features and perform in vivo measurements in order to validate our findings.

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.

Evolution of structural abnormalities in the rat brain following in utero exposure to maternal immune activation: A longitudinal in vivo MRI study.

PubMed

Crum, William R; Sawiak, Stephen J; Chege, Winfred; Cooper, Jonathan D; Williams, Steven C R; Vernon, Anthony C

2017-07-01

Genetic and environmental risk factors for psychiatric disorders are suggested to disrupt the trajectory of brain maturation during adolescence, leading to the development of psychopathology in adulthood. Rodent models are powerful tools to dissect the specific effects of such risk factors on brain maturational profiles, particularly when combined with Magnetic Resonance Imaging (MRI; clinically comparable technology). We therefore investigated the effect of maternal immune activation (MIA), an epidemiological risk factor for adult-onset psychiatric disorders, on rat brain maturation using atlas and tensor-based morphometry analysis of longitudinal in vivo MR images. Exposure to MIA resulted in decreases in the volume of several cortical regions, the hippocampus, amygdala, striatum, nucleus accumbens and unexpectedly, the lateral ventricles, relative to controls. In contrast, the volumes of the thalamus, ventral mesencephalon, brain stem and major white matter tracts were larger, relative to controls. These volumetric changes were maximal between post-natal day 50 and 100 with no differences between the groups thereafter. These data are consistent with and extend prior studies of brain structure in MIA-exposed rodents. Apart from the ventricular findings, these data have robust face validity to clinical imaging findings reported in studies of individuals at high clinical risk for a psychiatric disorder. Further work is now required to address the relationship of these MRI changes to behavioral dysfunction and to establish thier cellular correlates. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Custom fit 3D-printed brain holders for comparison of histology with MRI in marmosets.

PubMed

Guy, Joseph R; Sati, Pascal; Leibovitch, Emily; Jacobson, Steven; Silva, Afonso C; Reich, Daniel S

2016-01-15

MRI has the advantage of sampling large areas of tissue and locating areas of interest in 3D space in both living and ex vivo systems, whereas histology has the ability to examine thin slices of ex vivo tissue with high detail and specificity. Although both are valuable tools, it is currently difficult to make high-precision comparisons between MRI and histology due to large differences inherent to the techniques. A method combining the advantages would be an asset to understanding the pathological correlates of MRI. 3D-printed brain holders were used to maintain marmoset brains in the same orientation during acquisition of ex vivo MRI and pathologic cutting of the tissue. The results of maintaining this same orientation show that sub-millimeter, discrete neuropathological features in marmoset brain consistently share size, shape, and location between histology and ex vivo MRI, which facilitates comparison with serial imaging acquired in vivo. Existing methods use computational approaches sensitive to data input in order to warp histologic images to match large-scale features on MRI, but the new method requires no warping of images, due to a preregistration accomplished in the technique, and is insensitive to data formatting and artifacts in both MRI and histology. The simple method of using 3D-printed brain holders to match brain orientation during pathologic sectioning and MRI acquisition enables rapid and precise comparison of small features seen on MRI to their underlying histology. Published by Elsevier B.V.

Three-dimensional high-resolution diffusion tensor imaging and tractography of the developing rabbit brain.

PubMed

D'Arceuil, Helen; Liu, Christina; Levitt, Pat; Thompson, Barbara; Kosofsky, Barry; de Crespigny, Alex

2008-01-01

Diffusion tensor imaging (DTI) is sensitive to structural ordering in brain tissue particularly in the white matter tracts. Diffusion anisotropy changes with disease and also with neural development. We used high-resolution DTI of fixed rabbit brains to study developmental changes in regional diffusion anisotropy and white matter fiber tract development. Imaging was performed on a 4.7-tesla Bruker Biospec Avance scanner using custom-built solenoid coils and DTI was performed at various postnatal ages. Trace apparent diffusion coefficient, fractional diffusion anisotropy maps and fiber tracts were generated and compared across the ages. The brain was highly anisotropic at birth and white matter anisotropy increased with age. Regional DTI tractography of the internal capsule showed refinement in regional tract architecture with maturation. Interestingly, brains with congenital deficiencies of the callosal commissure showed selectively strikingly different fiber architecture compared to age-matched brains. There was also some evidence of subcortical to cortical fiber connectivity. DTI tractography of the anterior and posterior limbs of the internal capsule showed reproducibly coherent fiber tracts corresponding to known corticospinal and corticobulbar tract anatomy. There was some minor interanimal tract variability, but there was remarkable similarity between the tracts in all animals. Therefore, ex vivo DTI tractography is a potentially powerful tool for neuroscience investigations and may also reveal effects (such as fiber tract pruning during development) which may be important targets for in vivo human studies. Copyright 2007 S. Karger AG, Basel.

A high resolution spatiotemporal atlas of gene expression of the developing mouse brain

PubMed Central

Thompson, Carol L.; Ng, Lydia; Menon, Vilas; Martinez, Salvador; Lee, Chang-Kyu; Glattfelder, Katie; Sunkin, Susan M.; Henry, Alex; Lau, Christopher; Dang, Chinh; Garcia-Lopez, Raquel; Martinez-Ferre, Almudena; Pombero, Ana; Rubenstein, John L.R.; Wakeman, Wayne B.; Hohmann, John; Dee, Nick; Sodt, Andrew J.; Young, Rob; Smith, Kimberly; Nguyen, Thuc-Nghi; Kidney, Jolene; Kuan, Leonard; Jeromin, Andreas; Kaykas, Ajamete; Miller, Jeremy; Page, Damon; Orta, Geri; Bernard, Amy; Riley, Zackery; Smith, Simon; Wohnoutka, Paul; Hawrylycz, Mike; Puelles, Luis; Jones, Allan R.

2015-01-01

SUMMARY To provide a temporal framework for the genoarchitecture of brain development, in situ hybridization data were generated for embryonic and postnatal mouse brain at 7 developmental stages for ~2100 genes, processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, 7 reference atlases, an ontogenetic ontology, and tools to explore co-expression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (developingmouse.brain-map.org). PMID:24952961

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

Magnetic resonance-compatible robotic and mechatronics systems for image-guided interventions and rehabilitation: a review study.

PubMed

Tsekos, Nikolaos V; Khanicheh, Azadeh; Christoforou, Eftychios; Mavroidis, Constantinos

2007-01-01

The continuous technological progress of magnetic resonance imaging (MRI), as well as its widespread clinical use as a highly sensitive tool in diagnostics and advanced brain research, has brought a high demand for the development of magnetic resonance (MR)-compatible robotic/mechatronic systems. Revolutionary robots guided by real-time three-dimensional (3-D)-MRI allow reliable and precise minimally invasive interventions with relatively short recovery times. Dedicated robotic interfaces used in conjunction with fMRI allow neuroscientists to investigate the brain mechanisms of manipulation and motor learning, as well as to improve rehabilitation therapies. This paper gives an overview of the motivation, advantages, technical challenges, and existing prototypes for MR-compatible robotic/mechatronic devices.

Quantitative Evaluation of Automated Skull-Stripping Methods Applied to Contemporary and Legacy Images: Effects of Diagnosis, Bias Correction, and Slice Location

PubMed Central

Fennema-Notestine, Christine; Ozyurt, I. Burak; Clark, Camellia P.; Morris, Shaunna; Bischoff-Grethe, Amanda; Bondi, Mark W.; Jernigan, Terry L.; Fischl, Bruce; Segonne, Florent; Shattuck, David W.; Leahy, Richard M.; Rex, David E.; Toga, Arthur W.; Zou, Kelly H.; BIRN, Morphometry; Brown, Gregory G.

2008-01-01

Performance of automated methods to isolate brain from nonbrain tissues in magnetic resonance (MR) structural images may be influenced by MR signal inhomogeneities, type of MR image set, regional anatomy, and age and diagnosis of subjects studied. The present study compared the performance of four methods: Brain Extraction Tool (BET; Smith [2002]: Hum Brain Mapp 17:143–155); 3dIntracranial (Ward [1999] Milwaukee: Biophysics Research Institute, Medical College of Wisconsin; in AFNI); a Hybrid Watershed algorithm (HWA, Segonne et al. [2004] Neuroimage 22:1060–1075; in FreeSurfer); and Brain Surface Extractor (BSE, Sandor and Leahy [1997] IEEE Trans Med Imag 16:41–54; Shattuck et al. [2001] Neuroimage 13:856 – 876) to manually stripped images. The methods were applied to uncorrected and bias-corrected datasets; Legacy and Contemporary T1-weighted image sets; and four diagnostic groups (depressed, Alzheimer’s, young and elderly control). To provide a criterion for outcome assessment, two experts manually stripped six sagittal sections for each dataset in locations where brain and nonbrain tissue are difficult to distinguish. Methods were compared on Jaccard similarity coefficients, Hausdorff distances, and an Expectation-Maximization algorithm. Methods tended to perform better on contemporary datasets; bias correction did not significantly improve method performance. Mesial sections were most difficult for all methods. Although AD image sets were most difficult to strip, HWA and BSE were more robust across diagnostic groups compared with 3dIntracranial and BET. With respect to specificity, BSE tended to perform best across all groups, whereas HWA was more sensitive than other methods. The results of this study may direct users towards a method appropriate to their T1-weighted datasets and improve the efficiency of processing for large, multisite neuroimaging studies. PMID:15986433

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

Spatiotemporal characterization of brain infarction by sequential multimodal MR imaging following transient focal ischemia in a Rat model of intra-arterial middle cerebral artery occlusion.

PubMed

Gory, Benjamin; Chauveau, Fabien; Bolbos, Radu; Langlois, Jean-Baptiste; Labeyrie, Paul-Emile; Signorelli, Francesco; Turjman, Alexis; Turjman, Francis

2016-12-01

To assess spatiotemporal brain infarction evolution by sequential multimodal magnetic resonance (MR) imaging in an endovascular model of acute stroke in rats. A microwire was selectively placed in the middle cerebral artery (MCA) in 16 consecutives rats during 90 minutes occlusion. Longitudinal 7-T MR imaging, including angiography, diffusion, and perfusion was performed during ischemia, immediately after reperfusion, 3 h and 24 h after subsequent reperfusion. MCA occlusion was complete in 75 % and partial in 18.7 %. Hypoperfusion (mean ± SD) was observed in all animals during ischemia (-59 ± 18 % of contralateral hemisphere, area 31 ± 5 mm 2 ). Infarction volume (mean ± SD) was 90 ± 64 mm 3 during ischemia and 57 ± 67 mm 3 at 24 h. Brain infarction was fronto-parietal cortical in five animals (31 %), striatal in four animals (25 %), and cortico-striatal in seven animals (44 %) at 24 h. All rats survived at 24 h. This model is suitable to neuroprotection studies because of possible acute and close characterization of spatiotemporal evolution of brain infarction by MR imaging techniques, and evidence of ischemic penumbra, the target of neuroprotection agents. However, optimization of the brain infarct reproducibility needs further technical and neurointerventional tools improvements. • Nitinol microwire is MRI compatible allowing spatiotemporal characterization of brain infarction in rats. • Microwire selective placement in middle cerebral artery allows complete artery occlusion in 75 %. • A diffusion/perfusion mismatch during arterial occlusion is observed in 77 % of rats.

MR imaging of adult acute infectious encephalitis.

PubMed

Bertrand, A; Leclercq, D; Martinez-Almoyna, L; Girard, N; Stahl, J-P; De-Broucker, T

2017-05-01

Imaging is a key tool for the diagnosis of acute encephalitis. Brain CT scan must be urgently performed to rule out a brain lesion with mass effect that would contraindicate lumbar puncture. Brain MRI is less accessible than CT scan, but can provide crucial information with patients presenting with acute encephalitis. We performed a literature review on PubMed on April 1, 2015 with the search terms "MRI" and "encephalitis". We first described the various brain MRI abnormalities associated with each pathogen of acute encephalitis (HSV, VZV, other viral agents targeting immunocompromised patients or travelers; tuberculosis, listeriosis, other less frequent bacterial agents). Then, we identified specific patterns of brain MRI abnomalies that may suggest a particular pathogen. Limbic encephalitis is highly suggestive of HSV; it also occurs less frequently in encephalitis due to HHV6, syphillis, Whipple's disease and HIV primary infection. Rhombencephalitis is suggestive of tuberculosis and listeriosis. Acute ischemic lesions can occur in patients presenting with severe bacterial encephalitis, tuberculosis, VZV encephalitis, syphilis, and fungal infections. Brain MRI plays a crucial role in the diagnosis of acute encephalitis. It detects brain signal changes that reinforce the clinical suspicion of encephalitis, especially when the causative agent is not identified by lumbar puncture; it can suggest a particular pathogen based on the pattern of brain abnormalities and it rules out important differential diagnosis (vascular, tumoral or inflammatory causes). Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Application for the Drosophila ventral nerve cord standard in neuronal circuit reconstruction and in-depth analysis of mutant morphology.

PubMed

Boerner, Jana; Godenschwege, Tanja Angela

2010-09-01

The Drosophila standard brain has been a useful tool that provides information about position and size of different brain structures within a wild-type brain and allows the comparison of imaging data that were collected from individual preparations. Therefore the standard can be used to reveal and visualize differences of brain regions between wild-type and mutant brains and can provide spatial description of single neurons within the nervous system. Recently the standard brain was complemented by the generation of a ventral nerve cord (VNC) standard. Here the authors have registered the major components of a simple neuronal circuit, the Giant Fiber System (GFS), into this standard. The authors show that they can also virtually reconstruct the well-characterized synaptic contact of the Giant Fiber with its motorneuronal target when they register the individual neurons from different preparations into the VNC standard. In addition to the potential application for the standard thorax in neuronal circuit reconstruction, the authors show that it is a useful tool for in-depth analysis of mutant morphology of single neurons. The authors find quantitative and qualitative differences when they compared the Giant Fibers of two different neuroglian alleles, nrg(849) and nrg(G00305), using the averaged wild-type GFS in the standard VNC as a reference.

Development and application of an optogenetic platform for controlling and imaging a large number of individual neurons

NASA Astrophysics Data System (ADS)

Mohammed, Ali Ibrahim Ali

The understanding and treatment of brain disorders as well as the development of intelligent machines is hampered by the lack of knowledge of how the brain fundamentally functions. Over the past century, we have learned much about how individual neurons and neural networks behave, however new tools are critically needed to interrogate how neural networks give rise to complex brain processes and disease conditions. Recent innovations in molecular techniques, such as optogenetics, have enabled neuroscientists unprecedented precision to excite, inhibit and record defined neurons. The impressive sensitivity of currently available optogenetic sensors and actuators has now enabled the possibility of analyzing a large number of individual neurons in the brains of behaving animals. To promote the use of these optogenetic tools, this thesis integrates cutting edge optogenetic molecular sensors which is ultrasensitive for imaging neuronal activity with custom wide field optical microscope to analyze a large number of individual neurons in living brains. Wide-field microscopy provides a large field of view and better spatial resolution approaching the Abbe diffraction limit of fluorescent microscope. To demonstrate the advantages of this optical platform, we imaged a deep brain structure, the Hippocampus, and tracked hundreds of neurons over time while mouse was performing a memory task to investigate how those individual neurons related to behavior. In addition, we tested our optical platform in investigating transient neural network changes upon mechanical perturbation related to blast injuries. In this experiment, all blasted mice show a consistent change in neural network. A small portion of neurons showed a sustained calcium increase for an extended period of time, whereas the majority lost their activities. Finally, using optogenetic silencer to control selective motor cortex neurons, we examined their contributions to the network pathology of basal ganglia related to Parkinson's disease. We found that inhibition of motor cortex does not alter exaggerated beta oscillations in the striatum that are associated with parkinsonianism. Together, these results demonstrate the potential of developing integrated optogenetic system to advance our understanding of the principles underlying neural network computation, which would have broad applications from advancing artificial intelligence to disease diagnosis and treatment.

Label-free distinguishing between neurons and glial cells based on two-photon excited fluorescence signal of neuron perinuclear granules

NASA Astrophysics Data System (ADS)

Du, Huiping; Jiang, Liwei; Wang, Xingfu; Liu, Gaoqiang; Wang, Shu; Zheng, Liqin; Li, Lianhuang; Zhuo, Shuangmu; Zhu, Xiaoqin; Chen, Jianxin

2016-08-01

Neurons and glial cells are two critical cell types of brain tissue. Their accurate identification is important for the diagnosis of psychiatric disorders such as depression and schizophrenia. In this paper, distinguishing between neurons and glial cells by using the two-photon excited fluorescence (TPEF) signals of intracellular intrinsic sources was performed. TPEF microscopy combined with TUJ-1 and GFAP immunostaining and quantitative image analysis demonstrated that the perinuclear granules of neurons in the TPEF images of brain tissue and the primary cultured cortical cells were a unique characteristic of neurons compared to glial cells which can become a quantitative feature to distinguish neurons from glial cells. With the development of miniaturized TPEF microscope (‘two-photon fiberscopes’) imaging devices, TPEF microscopy can be developed into an effective diagnostic and monitoring tool for psychiatric disorders such as depression and schizophrenia.

Approximating high angular resolution apparent diffusion coefficient profiles using spherical harmonics under BiGaussian assumption

NASA Astrophysics Data System (ADS)

Cao, Ning; Liang, Xuwei; Zhuang, Qi; Zhang, Jun

2009-02-01

Magnetic Resonance Imaging (MRI) techniques have achieved much importance in providing visual and quantitative information of human body. Diffusion MRI is the only non-invasive tool to obtain information of the neural fiber networks of the human brain. The traditional Diffusion Tensor Imaging (DTI) is only capable of characterizing Gaussian diffusion. High Angular Resolution Diffusion Imaging (HARDI) extends its ability to model more complex diffusion processes. Spherical harmonic series truncated to a certain degree is used in recent studies to describe the measured non-Gaussian Apparent Diffusion Coefficient (ADC) profile. In this study, we use the sampling theorem on band-limited spherical harmonics to choose a suitable degree to truncate the spherical harmonic series in the sense of Signal-to-Noise Ratio (SNR), and use Monte Carlo integration to compute the spherical harmonic transform of human brain data obtained from icosahedral schema.

Multi-layer Cortical Ca2+ Imaging in Freely Moving Mice with Prism Probes and Miniaturized Fluorescence Microscopy

PubMed Central

Gulati, Srishti; Cao, Vania Y.; Otte, Stephani

2017-01-01

In vivo circuit and cellular level functional imaging is a critical tool for understanding the brain in action. High resolution imaging of mouse cortical neurons with two-photon microscopy has provided unique insights into cortical structure, function and plasticity. However, these studies are limited to head fixed animals, greatly reducing the behavioral complexity available for study. In this paper, we describe a procedure for performing chronic fluorescence microscopy with cellular-resolution across multiple cortical layers in freely behaving mice. We used an integrated miniaturized fluorescence microscope paired with an implanted prism probe to simultaneously visualize and record the calcium dynamics of hundreds of neurons across multiple layers of the somatosensory cortex as the mouse engaged in a novel object exploration task, over several days. This technique can be adapted to other brain regions in different animal species for other behavioral paradigms. PMID:28654056

Cerebral edema induced in mice by a convulsive dose of soman. Evaluation through diffusion-weighted magnetic resonance imaging and histology

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

Testylier, Guy; Lahrech, Hana; Universite Joseph Fourier, Grenoble, F-38043

2007-04-15

Purpose: In the present study, diffusion-weighted magnetic resonance imaging (DW-MRI) and histology were used to assess cerebral edema and lesions in mice intoxicated by a convulsive dose of soman, an organophosphate compound acting as an irreversible cholinesterase inhibitor. Methods: Three hours and 24 h after the intoxication with soman (172 {mu}g/kg), the mice were anesthetized with an isoflurane/N{sub 2}O mixture and their brain examined with DW-MRI. After the imaging sessions, the mice were sacrificed for histological analysis of their brain. Results: A decrease in the apparent diffusion coefficient (ADC) was detected as soon as 3 h after the intoxication andmore » was found strongly enhanced at 24 h. A correlation was obtained between the ADC change and the severity of the overall brain damage (edema and cellular degeneration): the more severe the damage, the stronger the ADC drop. Anesthesia was shown to interrupt soman-induced seizures and to attenuate edema and cell change in certain sensitive brain areas. Finally, brain water content was assessed using the traditional dry/wet weight method. A significant increase of brain water was observed following the intoxication. Conclusions: The ADC decrease observed in the present study suggests that brain edema in soman poisoning is mainly intracellular and cytotoxic. Since entry of water into Brain was also evidenced, this type of edema is certainly mixed with others (vasogenic, hydrostatic, osmotic). The present study confirms the potential of DW-MRI as a non-invasive tool for monitoring the acute neuropathological consequences (edema and neurodegeneration) of soman-induced seizures.« less

Beef assessments using functional magnetic resonance imaging and sensory evaluation.

PubMed

Tapp, W N; Davis, T H; Paniukov, D; Brooks, J C; Brashears, M M; Miller, M F

2017-04-01

Functional magnetic resonance imaging (fMRI) has been used to unveil how some foods and basic rewards are processed in the human brain. This study evaluated how resting state functional connectivity in regions of the human brain changed after differing qualities of beef steaks were consumed. Functional images of participants (n=8) were collected after eating high or low quality beef steaks on separate days, after consumption a sensory ballot was administered to evaluate consumers' perceptions of tenderness, juiciness, flavor, and overall liking. Imaging data showed that high quality steak samples resulted in greater functional connectivity to the striatum, medial orbitofrontal cortex, and insular cortex at various stages after consumption (P≤0.05). Furthermore, high quality steaks elicited higher sensory ballot scores for each palatability trait (P≤0.01). Together, these results suggest that resting state fMRI may be a useful tool for evaluating the neural process that follows positive sensory experiences such as the enjoyment of high quality beef steaks. Published by Elsevier Ltd.

Brainstem abnormalities and vestibular nerve enhancement in acute neuroborreliosis.

PubMed

Farshad-Amacker, Nadja A; Scheffel, Hans; Frauenfelder, Thomas; Alkadhi, Hatem

2013-12-21

Borreliosis is a widely distributed disease. Neuroborreliosis may present with unspecific symptoms and signs and often remains difficult to diagnose in patients with central nervous system symptoms, particularly if the pathognomonic erythema chronica migrans does not develop or is missed. Thus, vigilance is mandatory in cases with atypical presentation of the disease and with potentially severe consequences if not recognized early. We present a patient with neuroborreliosis demonstrating brain stem and vestibular nerve abnormalities on magnetic resonance imaging. A 28-year-old Caucasian female presented with headaches, neck stiffness, weight loss, nausea, tremor, and gait disturbance. Magnetic resonance imaging showed T2-weighted hyperintense signal alterations in the pons and in the vestibular nerves as well as bilateral post-contrast enhancement of the vestibular nerves. Serologic testing of the cerebrospinal fluid revealed the diagnosis of neuroborreliosis. Patients infected with neuroborreliosis may present with unspecific neurologic symptoms and magnetic resonance imaging as a noninvasive imaging tool showing signal abnormalities in the brain stem and nerve root enhancement may help in establishing the diagnosis.

Generative diffeomorphic modelling of large MRI data sets for probabilistic template construction.

PubMed

Blaiotta, Claudia; Freund, Patrick; Cardoso, M Jorge; Ashburner, John

2018-02-01

In this paper we present a hierarchical generative model of medical image data, which can capture simultaneously the variability of both signal intensity and anatomical shapes across large populations. Such a model has a direct application for learning average-shaped probabilistic tissue templates in a fully automated manner. While in principle the generality of the proposed Bayesian approach makes it suitable to address a wide range of medical image computing problems, our work focuses primarily on neuroimaging applications. In particular we validate the proposed method on both real and synthetic brain MR scans including the cervical cord and demonstrate that it yields accurate alignment of brain and spinal cord structures, as compared to state-of-the-art tools for medical image registration. At the same time we illustrate how the resulting tissue probability maps can readily be used to segment, bias correct and spatially normalise unseen data, which are all crucial pre-processing steps for MR imaging studies. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Evaluation of software tools for automated identification of neuroanatomical structures in quantitative β-amyloid PET imaging to diagnose Alzheimer's disease.

PubMed

Tuszynski, Tobias; Rullmann, Michael; Luthardt, Julia; Butzke, Daniel; Tiepolt, Solveig; Gertz, Hermann-Josef; Hesse, Swen; Seese, Anita; Lobsien, Donald; Sabri, Osama; Barthel, Henryk

2016-06-01

For regional quantification of nuclear brain imaging data, defining volumes of interest (VOIs) by hand is still the gold standard. As this procedure is time-consuming and operator-dependent, a variety of software tools for automated identification of neuroanatomical structures were developed. As the quality and performance of those tools are poorly investigated so far in analyzing amyloid PET data, we compared in this project four algorithms for automated VOI definition (HERMES Brass, two PMOD approaches, and FreeSurfer) against the conventional method. We systematically analyzed florbetaben brain PET and MRI data of ten patients with probable Alzheimer's dementia (AD) and ten age-matched healthy controls (HCs) collected in a previous clinical study. VOIs were manually defined on the data as well as through the four automated workflows. Standardized uptake value ratios (SUVRs) with the cerebellar cortex as a reference region were obtained for each VOI. SUVR comparisons between ADs and HCs were carried out using Mann-Whitney-U tests, and effect sizes (Cohen's d) were calculated. SUVRs of automatically generated VOIs were correlated with SUVRs of conventionally derived VOIs (Pearson's tests). The composite neocortex SUVRs obtained by manually defined VOIs were significantly higher for ADs vs. HCs (p=0.010, d=1.53). This was also the case for the four tested automated approaches which achieved effect sizes of d=1.38 to d=1.62. SUVRs of automatically generated VOIs correlated significantly with those of the hand-drawn VOIs in a number of brain regions, with regional differences in the degree of these correlations. Best overall correlation was observed in the lateral temporal VOI for all tested software tools (r=0.82 to r=0.95, p<0.001). Automated VOI definition by the software tools tested has a great potential to substitute for the current standard procedure to manually define VOIs in β-amyloid PET data analysis.

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

PubMed

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

2017-04-15

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

Thermal camera used for the assessment of metabolism and functions of the rat brain

NASA Astrophysics Data System (ADS)

Kastek, Mariusz; Piatkowski, Tadeusz; Polakowski, Henryk; Kaczmarska, Katarzyna; Czernicki, Zbigniew; Koźniewska, Ewa; Przykaza, Lukasz

2014-05-01

Motivation to undertake research on brain surface temperature in clinical practice is based on a strong conviction that the enormous progress in thermal imaging techniques and camera design has a great application potential. Intraoperative imaging of pathological changes and functionally important areas of the brain is not yet fully resolved in neurosurgery and remains a challenge. Extensive knowledge of the complex mechanisms controlling homeostasis (thermodynamic status of an organism being a part of it ) and laws of physics (which are the foundations of thermography), make this method very good and a simple imaging tool in comparison with other modern techniques, such as computed tomography, magnetic resonance imaging and angiography. Measurements of temperature distribution across the brain surface were performed on four rats (Wistar strain) weighing approximately 300 g each. Animals have remained under general anesthesia typically conducted using isoflurane. The brain was unveiled (the dura mater remained untouched) through the skin incision and removal of the bone cranial vault. Cerebrocortical microflow was measured using laser-Doppler flow meter. Arterial blood pressure was also measured in rat femoral artery. From the above data the cerebrovascular resistance index was calculated. Cerebral flow was modified by increasing the CO2 concentration in the inspired air to 5% for the duration of 6 minutes. Another change in cerebral flow was induced by periodic closing of right middle cerebral artery. Artery occlusion was performed by introducing a filament for a period of 15 minutes, then an artery was opened again. Measurements were carried out before, during and after the artery occlusion. Paper presents results and methodology of measurements.

Using human brain imaging studies as a guide towards animal models of schizophrenia

PubMed Central

BOLKAN, Scott S.; DE CARVALHO, Fernanda D.; KELLENDONK, Christoph

2015-01-01

Schizophrenia is a heterogeneous and poorly understood mental disorder that is presently defined solely by its behavioral symptoms. Advances in genetic, epidemiological and brain imaging techniques in the past half century, however, have significantly advanced our understanding of the underlying biology of the disorder. In spite of these advances clinical research remains limited in its power to establish the causal relationships that link etiology with pathophysiology and symptoms. In this context, animal models provide an important tool for causally testing hypotheses about biological processes postulated to be disrupted in the disorder. While animal models can exploit a variety of entry points towards the study of schizophrenia, here we describe an approach that seeks to closely approximate functional alterations observed with brain imaging techniques in patients. By modeling these intermediate pathophysiological alterations in animals, this approach offers an opportunity to (1) tightly link a single functional brain abnormality with its behavioral consequences, and (2) to determine whether a single pathophysiology can causally produce alterations in other brain areas that have been described in patients. In this review we first summarize a selection of well-replicated biological abnormalities described in the schizophrenia literature. We then provide examples of animal models that were studied in the context of patient imaging findings describing enhanced striatal dopamine D2 receptor function, alterations in thalamo-prefrontal circuit function, and metabolic hyperfunction of the hippocampus. Lastly, we discuss the implications of findings from these animal models for our present understanding of schizophrenia, and consider key unanswered questions for future research in animal models and human patients. PMID:26037801

Labeling and tracking exosomes within the brain using gold nanoparticles

NASA Astrophysics Data System (ADS)

Betzer, Oshra; Perets, Nisim; Barnoy, Eran; Offen, Daniel; Popovtzer, Rachela

2018-02-01

Cell-to-cell communication system involves Exosomes, small, membrane-enveloped nanovesicles. Exosomes are evolving as effective therapeutic tools for different pathologies. These extracellular vesicles can bypass biological barriers such as the blood-brain barrier, and can function as powerful nanocarriers for drugs, proteins and gene therapeutics. However, to promote exosomes' therapy development, especially for brain pathologies, a better understanding of their mechanism of action, trafficking, pharmacokinetics and bio-distribution is needed. In this research, we established a new method for non-invasive in-vivo neuroimaging of mesenchymal stem cell (MSC)-derived exosomes, based on computed tomography (CT) imaging with glucose-coated gold nanoparticle (GNP) labeling. We demonstrated that the exosomes were efficiently and directly labeled with GNPs, via an energy-dependent mechanism. Additionally, we found the optimal parameters for exosome labeling and neuroimaging, wherein 5 nm GNPs enhanced labeling, and intranasal administration produced superior brain accumulation. We applied our technique in a mouse model of focal ischemia. Imaging and tracking of intranasally-administered GNP-labeled exosomes revealed specific accumulation and prolonged presence at the lesion area, up to 24 hrs. We propose that this novel exosome labeling and in-vivo neuroimaging technique can serve as a general platform for brain theranostics.

Validation of voxel-based morphometry (VBM) based on MRI

NASA Astrophysics Data System (ADS)

Yang, Xueyu; Chen, Kewei; Guo, Xiaojuan; Yao, Li

2007-03-01

Voxel-based morphometry (VBM) is an automated and objective image analysis technique for detecting differences in regional concentration or volume of brain tissue composition based on structural magnetic resonance (MR) images. VBM has been used widely to evaluate brain morphometric differences between different populations, but there isn't an evaluation system for its validation until now. In this study, a quantitative and objective evaluation system was established in order to assess VBM performance. We recruited twenty normal volunteers (10 males and 10 females, age range 20-26 years, mean age 22.6 years). Firstly, several focal lesions (hippocampus, frontal lobe, anterior cingulate, back of hippocampus, back of anterior cingulate) were simulated in selected brain regions using real MRI data. Secondly, optimized VBM was performed to detect structural differences between groups. Thirdly, one-way ANOVA and post-hoc test were used to assess the accuracy and sensitivity of VBM analysis. The results revealed that VBM was a good detective tool in majority of brain regions, even in controversial brain region such as hippocampus in VBM study. Generally speaking, much more severity of focal lesion was, better VBM performance was. However size of focal lesion had little effects on VBM analysis.

Optogenetic Functional MRI

PubMed Central

Lin, Peter; Fang, Zhongnan; Liu, Jia; Lee, Jin Hyung

2016-01-01

The investigation of the functional connectivity of precise neural circuits across the entire intact brain can be achieved through optogenetic functional magnetic resonance imaging (ofMRI), which is a novel technique that combines the relatively high spatial resolution of high-field fMRI with the precision of optogenetic stimulation. Fiber optics that enable delivery of specific wavelengths of light deep into the brain in vivo are implanted into regions of interest in order to specifically stimulate targeted cell types that have been genetically induced to express light-sensitive trans-membrane conductance channels, called opsins. fMRI is used to provide a non-invasive method of determining the brain's global dynamic response to optogenetic stimulation of specific neural circuits through measurement of the blood-oxygen-level-dependent (BOLD) signal, which provides an indirect measurement of neuronal activity. This protocol describes the construction of fiber optic implants, the implantation surgeries, the imaging with photostimulation and the data analysis required to successfully perform ofMRI. In summary, the precise stimulation and whole-brain monitoring ability of ofMRI are crucial factors in making ofMRI a powerful tool for the study of the connectomics of the brain in both healthy and diseased states. PMID:27167840

Diffusion Tensor Imaging Reveals White Matter Injury in a Rat Model of Repetitive Blast-Induced Traumatic Brain Injury

PubMed Central

Calabrese, Evan; Du, Fu; Garman, Robert H.; Johnson, G. Allan; Riccio, Cory; Tong, Lawrence C.

2014-01-01

Abstract Blast-induced traumatic brain injury (bTBI) is one of the most common combat-related injuries seen in U.S. military personnel, yet relatively little is known about the underlying mechanisms of injury. In particular, the effects of the primary blast pressure wave are poorly understood. Animal models have proven invaluable for the study of primary bTBI, because it rarely occurs in isolation in human subjects. Even less is known about the effects of repeated primary blast wave exposure, but existing data suggest cumulative increases in brain damage with a second blast. MRI and, in particular, diffusion tensor imaging (DTI), have become important tools for assessing bTBI in both clinical and preclinical settings. Computational statistical methods such as voxelwise analysis have shown promise in localizing and quantifying bTBI throughout the brain. In this study, we use voxelwise analysis of DTI to quantify white matter injury in a rat model of repetitive primary blast exposure. Our results show a significant increase in microstructural damage with a second blast exposure, suggesting that primary bTBI may sensitize the brain to subsequent injury. PMID:24392843

The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

PubMed Central

Hebart, Martin N.; Görgen, Kai; Haynes, John-Dylan

2015-01-01

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns. PMID:25610393

Estradiol modulates neural response to conspecific and heterospecific song in female house sparrows: An in vivo positron emission tomography study

PubMed Central

Stabile, Frank A.; Carson, Richard E.

2017-01-01

Although there is growing evidence that estradiol modulates female perception of male sexual signals, relatively little research has focused on female auditory processing. We used in vivo 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) imaging to examine the neuronal effects of estradiol and conspecific song in female house sparrows (Passer domesticus). We assessed brain glucose metabolism, a measure of neuronal activity, in females with empty implants, estradiol implants, and empty implants ~1 month after estradiol implant removal. Females were exposed to conspecific or heterospecific songs immediately prior to imaging. The activity of brain regions involved in auditory perception did not differ between females with empty implants exposed to conspecific vs. heterospecific song, but neuronal activity was significantly reduced in females with estradiol implants exposed to heterospecific song. Furthermore, our within-individual design revealed that changes in brain activity due to high estradiol were actually greater several weeks after peak hormone exposure. Overall, this study demonstrates that PET imaging is a powerful tool for assessing large-scale changes in brain activity in living songbirds, and suggests that after breeding is done, specific environmental and physiological cues are necessary for estradiol-stimulated females to lose the selectivity they display in neural response to conspecific song. PMID:28832614

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.

Advanced MR Imaging of the Placenta: Exploring the in utero placenta-brain connection

PubMed Central

Andescavage, Nickie Niforatos; DuPlessis, Adre; Limperopoulos, Catherine

2015-01-01

The placenta is a vital organ necessary for the healthy neurodevelopment of the fetus. Despite the known associations between placental dysfunction and neurologic impairment, there is a paucity of tools available to reliably assess in vivo placental health and function. Existing clinical tools for placental assessment remain insensitive in predicting and assessing placental well-being. Advanced MRI techniques hold significant promise for the dynamic, non-invasive, real-time assessment of placental health and identification of early placental-based disorders. In this review, we summarize the available clinical tools for placental assessment including ultrasound, Doppler, and conventional MRI. We then explore the emerging role of advanced placental MR imaging techniques for supporting the developing fetus, appraise the strengths and limitations of quantitative MRI in identifying early markers of placental dysfunction for improved pregnancy monitoring and fetal outcomes. PMID:25765905

Animating Brains

PubMed Central

Borck, Cornelius

2016-01-01

A recent paper famously accused the rising field of social neuroscience of using faulty statistics under the catchy title ‘Voodoo Correlations in Social Neuroscience’. This Special Issue invites us to take this claim as the starting point for a cross-cultural analysis: in which meaningful ways can recent research in the burgeoning field of functional imaging be described as, contrasted with, or simply compared to animistic practices? And what light does such a reading shed on the dynamics and effectiveness of a century of brain research into higher mental functions? Reviewing the heated debate from 2009 around recent trends in neuroimaging as a possible candidate for current instances of ‘soul catching’, the paper will then compare these forms of primarily image-based brain research with older regimes, revolving around the deciphering of the brain’s electrical activity. How has the move from a decoding paradigm to a representational regime affected the conceptualisation of self, psyche, mind and soul (if there still is such an entity)? And in what ways does modern technoscience provide new tools for animating brains? PMID:27292322

Accelerated Changes in Cortical Thickness Measurements with Age in Military Service Members with Traumatic Brain Injury.

PubMed

Savjani, Ricky R; Taylor, Brian A; Acion, Laura; Wilde, Elisabeth A; Jorge, Ricardo E

2017-11-15

Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

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

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

DOE PAGES

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning; ...

2017-09-06

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

TeraStitcher - A tool for fast automatic 3D-stitching of teravoxel-sized microscopy images

PubMed Central

2012-01-01

Background Further advances in modern microscopy are leading to teravoxel-sized tiled 3D images at high resolution, thus increasing the dimension of the stitching problem of at least two orders of magnitude. The existing software solutions do not seem adequate to address the additional requirements arising from these datasets, such as the minimization of memory usage and the need to process just a small portion of data. Results We propose a free and fully automated 3D Stitching tool designed to match the special requirements coming out of teravoxel-sized tiled microscopy images that is able to stitch them in a reasonable time even on workstations with limited resources. The tool was tested on teravoxel-sized whole mouse brain images with micrometer resolution and it was also compared with the state-of-the-art stitching tools on megavoxel-sized publicy available datasets. This comparison confirmed that the solutions we adopted are suited for stitching very large images and also perform well on datasets with different characteristics. Indeed, some of the algorithms embedded in other stitching tools could be easily integrated in our framework if they turned out to be more effective on other classes of images. To this purpose, we designed a software architecture which separates the strategies that use efficiently memory resources from the algorithms which may depend on the characteristics of the acquired images. Conclusions TeraStitcher is a free tool that enables the stitching of Teravoxel-sized tiled microscopy images even on workstations with relatively limited resources of memory (<8 GB) and processing power. It exploits the knowledge of approximate tile positions and uses ad-hoc strategies and algorithms designed for such very large datasets. The produced images can be saved into a multiresolution representation to be efficiently retrieved and processed. We provide TeraStitcher both as standalone application and as plugin of the free software Vaa3D. PMID:23181553

SPECT-imaging of activity-dependent changes in regional cerebral blood flow induced by electrical and optogenetic self-stimulation in mice.

PubMed

Kolodziej, Angela; Lippert, Michael; Angenstein, Frank; Neubert, Jenni; Pethe, Annette; Grosser, Oliver S; Amthauer, Holger; Schroeder, Ulrich H; Reymann, Klaus G; Scheich, Henning; Ohl, Frank W; Goldschmidt, Jürgen

2014-12-01

Electrical and optogenetic methods for brain stimulation are widely used in rodents for manipulating behavior and analyzing functional connectivities in neuronal circuits. High-resolution in vivo imaging of the global, brain-wide, activation patterns induced by these stimulations has remained challenging, in particular in awake behaving mice. We here mapped brain activation patterns in awake, intracranially self-stimulating mice using a novel protocol for single-photon emission computed tomography (SPECT) imaging of regional cerebral blood flow (rCBF). Mice were implanted with either electrodes for electrical stimulation of the medial forebrain bundle (mfb-microstim) or with optical fibers for blue-light stimulation of channelrhodopsin-2 expressing neurons in the ventral tegmental area (vta-optostim). After training for self-stimulation by current or light application, respectively, mice were implanted with jugular vein catheters and intravenously injected with the flow tracer 99m-technetium hexamethylpropyleneamine oxime (99mTc-HMPAO) during seven to ten minutes of intracranial self-stimulation or ongoing behavior without stimulation. The 99mTc-brain distributions were mapped in anesthetized animals after stimulation using multipinhole SPECT. Upon self-stimulation rCBF strongly increased at the electrode tip in mfb-microstim mice. In vta-optostim mice peak activations were found outside the stimulation site. Partly overlapping brain-wide networks of activations and deactivations were found in both groups. When testing all self-stimulating mice against all controls highly significant activations were found in the rostromedial nucleus accumbens shell. SPECT-imaging of rCBF using intravenous tracer-injection during ongoing behavior is a new tool for imaging regional brain activation patterns in awake behaving rodents providing higher spatial and temporal resolutions than 18F-2-fluoro-2-dexoyglucose positron emission tomography. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

MRI mediated, non-invasive tracking of intratumoral distribution of nanocarriers in rat glioma

NASA Astrophysics Data System (ADS)

Karathanasis, Efstathios; Park, Jaekeun; Agarwal, Abhiruchi; Patel, Vijal; Zhao, Fuqiang; Annapragada, Ananth V.; Hu, Xiaoping; Bellamkonda, Ravi V.

2008-08-01

Nanocarrier mediated therapy of gliomas has shown promise. The success of systemic nanocarrier-based chemotherapy is critically dependent on the so-called leaky vasculature to permit drug extravasation across the blood-brain barrier. Yet, the extent of vascular permeability in individual tumors varies widely, resulting in a correspondingly wide range of responses to the therapy. However, there exist no tools currently for rationally determining whether tumor blood vessels are amenable to nanocarrier mediated therapy in an individualized, patient specific manner today. To address this need for brain tumor therapy, we have developed a multifunctional 100 nm scale liposomal agent encapsulating a gadolinium-based contrast agent for contrast-enhanced magnetic resonance imaging with prolonged blood circulation. Using a 9.4 T MRI system, we were able to track the intratumoral distribution of the gadolinium-loaded nanocarrier in a rat glioma model for a period of three days due to improved magnetic properties of the contrast agent being packaged in a nanocarrier. Such a nanocarrier provides a tool for non-invasively assessing the suitability of tumors for nanocarrier mediated therapy and then optimizing the treatment protocol for each individual tumor. Additionally, the ability to image the tumor in high resolution can potentially constitute a surgical planning tool for tumor resection.

MRI mediated, non-invasive tracking of intratumoral distribution of nanocarriers in rat glioma.

PubMed

Karathanasis, Efstathios; Park, Jaekeun; Agarwal, Abhiruchi; Patel, Vijal; Zhao, Fuqiang; Annapragada, Ananth V; Hu, Xiaoping; Bellamkonda, Ravi V

2008-08-06

Nanocarrier mediated therapy of gliomas has shown promise. The success of systemic nanocarrier-based chemotherapy is critically dependent on the so-called leaky vasculature to permit drug extravasation across the blood-brain barrier. Yet, the extent of vascular permeability in individual tumors varies widely, resulting in a correspondingly wide range of responses to the therapy. However, there exist no tools currently for rationally determining whether tumor blood vessels are amenable to nanocarrier mediated therapy in an individualized, patient specific manner today. To address this need for brain tumor therapy, we have developed a multifunctional 100 nm scale liposomal agent encapsulating a gadolinium-based contrast agent for contrast-enhanced magnetic resonance imaging with prolonged blood circulation. Using a 9.4 T MRI system, we were able to track the intratumoral distribution of the gadolinium-loaded nanocarrier in a rat glioma model for a period of three days due to improved magnetic properties of the contrast agent being packaged in a nanocarrier. Such a nanocarrier provides a tool for non-invasively assessing the suitability of tumors for nanocarrier mediated therapy and then optimizing the treatment protocol for each individual tumor. Additionally, the ability to image the tumor in high resolution can potentially constitute a surgical planning tool for tumor resection.

Using Digital Images of the Zebra Finch Song System as a Tool to Teach Organizational Effects of Steroid Hormones: A Free Downloadable Module

PubMed Central

Grisham, William; Schottler, Natalie A.; McCauley, Lisa M. Beck; Pham, Anh P.; Ruiz, Maureen L.; Fong, Michelle C.; Cui, Xinran

2011-01-01

Zebra finch song behavior is sexually dimorphic: males sing and females do not. The neural system underlying this behavior is sexually dimorphic, and this sex difference is easy to quantify. During development, the zebra finch song system can be altered by steroid hormones, specifically estradiol, which actually masculinizes it. Because of the ease of quantification and experimental manipulation, the zebra finch song system has great potential for use in undergraduate labs. Unfortunately, the underlying costs prohibit use of this system in undergraduate labs. Further, the time required to perform a developmental study renders such undertakings unrealistic within a single academic term. We have overcome these barriers by creating digital tools, including an image library of song nuclei from zebra finch brains. Students using this library replicate and extend a published experiment examining the dose of estradiol required to masculinize the female zebra finch brain. We have used this library for several terms, and students not only obtain significant experimental results but also make gains in understanding content, experimental controls, and inferential statistics (analysis of variance and post hoc tests). We have provided free access to these digital tools at the following website: http://mdcune.psych.ucla.edu/modules/birdsong. PMID:21633071

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.

PyDBS: an automated image processing workflow for deep brain stimulation surgery.

PubMed

D'Albis, Tiziano; Haegelen, Claire; Essert, Caroline; Fernández-Vidal, Sara; Lalys, Florent; Jannin, Pierre

2015-02-01

Deep brain stimulation (DBS) is a surgical procedure for treating motor-related neurological disorders. DBS clinical efficacy hinges on precise surgical planning and accurate electrode placement, which in turn call upon several image processing and visualization tasks, such as image registration, image segmentation, image fusion, and 3D visualization. These tasks are often performed by a heterogeneous set of software tools, which adopt differing formats and geometrical conventions and require patient-specific parameterization or interactive tuning. To overcome these issues, we introduce in this article PyDBS, a fully integrated and automated image processing workflow for DBS surgery. PyDBS consists of three image processing pipelines and three visualization modules assisting clinicians through the entire DBS surgical workflow, from the preoperative planning of electrode trajectories to the postoperative assessment of electrode placement. The system's robustness, speed, and accuracy were assessed by means of a retrospective validation, based on 92 clinical cases. The complete PyDBS workflow achieved satisfactory results in 92 % of tested cases, with a median processing time of 28 min per patient. The results obtained are compatible with the adoption of PyDBS in clinical practice.

Functional Imaging and Optogenetics in Drosophila

PubMed Central

Simpson, Julie H.; Looger, Loren L.

2018-01-01

Understanding how activity patterns in specific neural circuits coordinate an animal’s behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make Drosophila a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light. PMID:29618589

Validation of Clay Modeling as a Learning Tool for the Periventricular Structures of the Human Brain

ERIC Educational Resources Information Center

Akle, Veronica; Peña-Silva, Ricardo A.; Valencia, Diego M.; Rincón-Perez, Carlos W.

2018-01-01

Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a…

Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial

PubMed Central

Aasted, Christopher M.; Yücel, Meryem A.; Cooper, Robert J.; Dubb, Jay; Tsuzuki, Daisuke; Becerra, Lino; Petkov, Mike P.; Borsook, David; Dan, Ippeita; Boas, David A.

2015-01-01

Abstract. Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that is used to noninvasively measure cerebral hemoglobin concentration changes induced by brain activation. Using structural guidance in fNIRS research enhances interpretation of results and facilitates making comparisons between studies. AtlasViewer is an open-source software package we have developed that incorporates multiple spatial registration tools to enable structural guidance in the interpretation of fNIRS studies. We introduce the reader to the layout of the AtlasViewer graphical user interface, the folder structure, and user files required in the creation of fNIRS probes containing sources and detectors registered to desired locations on the head, evaluating probe fabrication error and intersubject probe placement variability, and different procedures for estimating measurement sensitivity to different brain regions as well as image reconstruction performance. Further, we detail how AtlasViewer provides a generic head atlas for guiding interpretation of fNIRS results, but also permits users to provide subject-specific head anatomies to interpret their results. We anticipate that AtlasViewer will be a valuable tool in improving the anatomical interpretation of fNIRS studies. PMID:26157991

Brain magnetic resonance imaging: perception and expectations of neurologists, neurosurgeons and psychiatrists.

PubMed

Branco, Paulo; Ayres-Basto, Margarida; Portugal, Pedro; Ramos, Isabel; Seixas, Daniela

2014-06-01

Magnetic resonance imaging (MRI) has rapidly become an essential diagnostic tool in modern medicine. Understanding the objectives, perception and expectations of the different medical specialties towards MRI is therefore important to improve the quality of the examinations. Our aim was to better comprehend the reasons and expectations of neurologists, neurosurgeons and psychiatrists when requesting brain MRI scans for their patients, and also to perceive the degree of confidence of these specialists in the images and respective reports. Sixty-three specialists were recruited from two tertiary hospitals and answered a tailored questionnaire. Neurosurgeons were more concerned with the images themselves; neurologists lacked confidence in both MRI images and reports, and one third of the psychiatrists only read the report and were the most confident of the specialties in MRI findings. These results possibly reflect the idiosyncrasies of each of these medical specialties. This knowledge, driven by efficient communication between neuroradiologists and neurosurgeons, neurologists and psychiatrists, may contribute to improve the quality of MRI examinations and consequently patient care and management of health resources.

Brain Magnetic Resonance Imaging: Perception and Expectations of Neurologists, Neurosurgeons and Psychiatrists

PubMed Central

Branco, Paulo; Ayres-Basto, Margarida; Portugal, Pedro; Ramos, Isabel; Seixas, Daniela

2014-01-01

Summary Magnetic resonance imaging (MRI) has rapidly become an essential diagnostic tool in modern medicine. Understanding the objectives, perception and expectations of the different medical specialties towards MRI is therefore important to improve the quality of the examinations. Our aim was to better comprehend the reasons and expectations of neurologists, neurosurgeons and psychiatrists when requesting brain MRI scans for their patients, and also to perceive the degree of confidence of these specialists in the images and respective reports. Sixty-three specialists were recruited from two tertiary hospitals and answered a tailored questionnaire. Neurosurgeons were more concerned with the images themselves; neurologists lacked confidence in both MRI images and reports, and one third of the psychiatrists only read the report and were the most confident of the specialties in MRI findings. These results possibly reflect the idiosyncrasies of each of these medical specialties. This knowledge, driven by efficient communication between neuroradiologists and neurosurgeons, neurologists and psychiatrists, may contribute to improve the quality of MRI examinations and consequently patient care and management of health resources. PMID:24976192

X-Ray Fluorescence Imaging: A New Tool for Studying Manganese Neurotoxicity

PubMed Central

Robison, Gregory; Zakharova, Taisiya; Fu, Sherleen; Jiang, Wendy; Fulper, Rachael; Barrea, Raul; Marcus, Matthew A.; Zheng, Wei; Pushkar, Yulia

2012-01-01

The neurotoxic effect of manganese (Mn) establishes itself in a condition known as manganism or Mn induced parkinsonism. While this condition was first diagnosed about 170 years ago, the mechanism of the neurotoxic action of Mn remains unknown. Moreover, the possibility that Mn exposure combined with other genetic and environmental factors can contribute to the development of Parkinson's disease has been discussed in the literature and several epidemiological studies have demonstrated a correlation between Mn exposure and an elevated risk of Parkinson's disease. Here, we introduce X-ray fluorescence imaging as a new quantitative tool for analysis of the Mn distribution in the brain with high spatial resolution. The animal model employed mimics deficits observed in affected human subjects. The obtained maps of Mn distribution in the brain demonstrate the highest Mn content in the globus pallidus, the thalamus, and the substantia nigra pars compacta. To test the hypothesis that Mn transport into/distribution within brain cells mimics that of other biologically relevant metal ions, such as iron, copper, or zinc, their distributions were compared. It was demonstrated that the Mn distribution does not follow the distributions of any of these metals in the brain. The majority of Mn in the brain was shown to occur in the mobile state, confirming the relevance of the chelation therapy currently used to treat Mn intoxication. In cells with accumulated Mn, it can cause neurotoxic action by affecting the mitochondrial respiratory chain. This can result in increased susceptibility of the neurons of the globus pallidus, thalamus, and substantia nigra pars compacta to various environmental or genetic insults. The obtained data is the first demonstration of Mn accumulation in the substantia nigra pars compacta, and thus, can represent a link between Mn exposure and its potential effects for development of Parkinson's disease. PMID:23185282

Stereo imaging with spaceborne radars

NASA Technical Reports Server (NTRS)

Leberl, F.; Kobrick, M.

1983-01-01

Stereo viewing is a valuable tool in photointerpretation and is used for the quantitative reconstruction of the three dimensional shape of a topographical surface. Stereo viewing refers to a visual perception of space by presenting an overlapping image pair to an observer so that a three dimensional model is formed in the brain. Some of the observer's function is performed by machine correlation of the overlapping images - so called automated stereo correlation. The direct perception of space with two eyes is often called natural binocular vision; techniques of generating three dimensional models of the surface from two sets of monocular image measurements is the topic of stereology.

Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data

PubMed Central

Wang, Yinxue; Shi, Guilai; Miller, David J.; Wang, Yizhi; Wang, Congchao; Broussard, Gerard; Wang, Yue; Tian, Lin; Yu, Guoqiang

2017-01-01

Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca2+ indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca2+ signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP. PMID:28769780

Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data.

PubMed

Wang, Yinxue; Shi, Guilai; Miller, David J; Wang, Yizhi; Wang, Congchao; Broussard, Gerard; Wang, Yue; Tian, Lin; Yu, Guoqiang

2017-01-01

Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca 2+ indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca 2+ signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP.

JAtlasView: a Java atlas-viewer for browsing biomedical 3D images and atlases.

PubMed

Feng, Guangjie; Burton, Nick; Hill, Bill; Davidson, Duncan; Kerwin, Janet; Scott, Mark; Lindsay, Susan; Baldock, Richard

2005-03-09

Many three-dimensional (3D) images are routinely collected in biomedical research and a number of digital atlases with associated anatomical and other information have been published. A number of tools are available for viewing this data ranging from commercial visualization packages to freely available, typically system architecture dependent, solutions. Here we discuss an atlas viewer implemented to run on any workstation using the architecture neutral Java programming language. We report the development of a freely available Java based viewer for 3D image data, descibe the structure and functionality of the viewer and how automated tools can be developed to manage the Java Native Interface code. The viewer allows arbitrary re-sectioning of the data and interactive browsing through the volume. With appropriately formatted data, for example as provided for the Electronic Atlas of the Developing Human Brain, a 3D surface view and anatomical browsing is available. The interface is developed in Java with Java3D providing the 3D rendering. For efficiency the image data is manipulated using the Woolz image-processing library provided as a dynamically linked module for each machine architecture. We conclude that Java provides an appropriate environment for efficient development of these tools and techniques exist to allow computationally efficient image-processing libraries to be integrated relatively easily.

A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.

PubMed

Sui, Jing; Adali, Tülay; Pearlson, Godfrey; Yang, Honghui; Sponheim, Scott R; White, Tonya; Calhoun, Vince D

2010-05-15

Collection of multiple-task brain imaging data from the same subject has now become common practice in medical imaging studies. In this paper, we propose a simple yet effective model, "CCA+ICA", as a powerful tool for multi-task data fusion. This joint blind source separation (BSS) model takes advantage of two multivariate methods: canonical correlation analysis and independent component analysis, to achieve both high estimation accuracy and to provide the correct connection between two datasets in which sources can have either common or distinct between-dataset correlation. In both simulated and real fMRI applications, we compare the proposed scheme with other joint BSS models and examine the different modeling assumptions. The contrast images of two tasks: sensorimotor (SM) and Sternberg working memory (SB), derived from a general linear model (GLM), were chosen to contribute real multi-task fMRI data, both of which were collected from 50 schizophrenia patients and 50 healthy controls. When examining the relationship with duration of illness, CCA+ICA revealed a significant negative correlation with temporal lobe activation. Furthermore, CCA+ICA located sensorimotor cortex as the group-discriminative regions for both tasks and identified the superior temporal gyrus in SM and prefrontal cortex in SB as task-specific group-discriminative brain networks. In summary, we compared the new approach to some competitive methods with different assumptions, and found consistent results regarding each of their hypotheses on connecting the two tasks. Such an approach fills a gap in existing multivariate methods for identifying biomarkers from brain imaging data.

Apparent Diffusion Coefficient Value Changes and Clinical Correlation in 90 Cases of Cytomegalovirus-Infected Fetuses with Unremarkable Fetal MRI Results.

PubMed

Kotovich, D; Guedalia, J S B; Hoffmann, C; Sze, G; Eisenkraft, A; Yaniv, G

2017-07-01

Cytomegalovirus is the leading intrauterine infection. Fetal MR imaging is an accepted tool for fetal brain evaluation, yet it still lacks the ability to accurately predict the extent of the neurodevelopmental impairment, especially in fetal MR imaging scans with unremarkable findings. Our hypothesis was that intrauterine cytomegalovirus infection causes diffusional changes in fetal brains and that those changes may correlate with the severity of neurodevelopmental deficiencies. A retrospective analysis was performed on 90 fetal MR imaging scans of cytomegalovirus-infected fetuses with unremarkable results and compared with a matched gestational age control group of 68 fetal head MR imaging scans. ADC values were measured and averaged in the frontal, parietal, occipital, and temporal lobes; basal ganglia; thalamus; and pons. For neurocognitive assessment, the Vineland Adaptive Behavior Scales, Second Edition (VABS-II) was used on 58 children in the cytomegalovirus-infected group. ADC values were reduced for the cytomegalovirus-infected fetuses in most brain areas studied. The VABS-II showed no trend for the major domains or the composite score of the VABS-II for the cytomegalovirus-infected children compared with the healthy population distribution. Some subdomains showed an association between ADC values and VABS-II scores. Cytomegalovirus infection causes diffuse reduction in ADC values in the fetal brain even in unremarkable fetal MR imaging scans. Cytomegalovirus-infected children with unremarkable fetal MR imaging scans do not deviate from the healthy population in the VABS-II neurocognitive assessment. ADC values were not correlated with VABS-II scores. However, the lack of clinical findings, as seen in most cytomegalovirus-infected fetuses, does not eliminate the possibility of future neurodevelopmental pathology. © 2017 by American Journal of Neuroradiology.

Magnetic resonance techniques for investigation of multiple sclerosis

NASA Astrophysics Data System (ADS)

MacKay, Alex; Laule, Cornelia; Li, David K. B.; Meyers, Sandra M.; Russell-Schulz, Bretta; Vavasour, Irene M.

2014-11-01

Multiple sclerosis (MS) is a common neurological disease which can cause loss of vision and balance, muscle weakness, impaired speech, fatigue, cognitive dysfunction and even paralysis. The key pathological processes in MS are inflammation, edema, myelin loss, axonal loss and gliosis. Unfortunately, the cause of MS is still not understood and there is currently no cure. Magnetic resonance imaging (MRI) is an important clinical and research tool for MS. 'Conventional' MRI images of MS brain reveal bright lesions, or plaques, which demark regions of severe tissue damage. Conventional MRI has been extremely valuable for the diagnosis and management of people who have MS and also for the assessment of therapies designed to reduce inflammation and promote repair. While conventional MRI is clearly valuable, it lack pathological specificity and, in some cases, sensitivity to non-lesional pathology. Advanced MR techniques have been developed to provide information that is more sensitive and specific than what is available with clinical scanning. Diffusion tensor imaging and magnetization transfer provide a general but non-specific measure of the pathological state of brain tissue. MR spectroscopy provides concentrations of brain metabolites which can be related to specific pathologies. Myelin water imaging was designed to assess brain myelination and has proved useful for measuring myelin loss in MS. To combat MS, it is crucial that the pharmaceutical industry finds therapies which can reverse the neurodegenerative processes which occur in the disease. The challenge for magnetic resonance researchers is to design imaging techniques which can provide detailed pathological information relating to the mechanisms of MS therapies. This paper briefly describes the pathologies of MS and demonstrates how MS-associated pathologies can be followed using both conventional and advanced MR imaging protocols.

Fractal analysis of the susceptibility weighted imaging patterns in malignant brain tumors during antiangiogenic treatment: technical report on four cases serially imaged by 7 T magnetic resonance during a period of four weeks.

PubMed

Di Ieva, Antonio; Matula, Christian; Grizzi, Fabio; Grabner, Günther; Trattnig, Siegfried; Tschabitscher, Manfred

2012-01-01

The need for new and objective indexes for the neuroradiologic follow-up of brain tumors and for monitoring the effects of antiangiogenic strategies in vivo led us to perform a technical study on four patients who received computerized analysis of tumor-associated vasculature with ultra-high-field (7 T) magnetic resonance imaging (MRI). The image analysis involved the application of susceptibility weighted imaging (SWI) to evaluate vascular structures. Four patients affected by recurrent malignant brain tumors were enrolled in the present study. After the first 7-T SWI MRI procedure, the patients underwent antiangiogenic treatment with bevacizumab. The imaging was repeated every 2 weeks for a period of 4 weeks. The SWI patterns visualized in the three MRI temporal sequences were analyzed by means of a computer-aided fractal-based method to objectively quantify their geometric complexity. In two clinically deteriorating patients we found an increase of the geometric complexity of the space-filling properties of the SWI patterns over time despite the antiangiogenic treatment. In one patient, who showed improvement with the therapy, the fractal dimension of the intratumoral structure decreased, whereas in the fourth patient, no differences were found. The qualitative changes of the intratumoral SWI patterns during a period of 4 weeks were quantified with the fractal dimension. Because SWI patterns are also related to the presence of vascular structures, the quantification of their space-filling properties with fractal dimension seemed to be a valid tool for the in vivo neuroradiologic follow-up of brain tumors. Copyright © 2012 Elsevier Inc. All rights reserved.

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

PubMed

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

2010-07-23

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

Simulated driving and brain imaging: combining behavior, brain activity, and virtual reality.

PubMed

Carvalho, Kara N; Pearlson, Godfrey D; Astur, Robert S; Calhoun, Vince D

2006-01-01

Virtual reality in the form of simulated driving is a useful tool for studying the brain. Various clinical questions can be addressed, including both the role of alcohol as a modulator of brain function and regional brain activation related to elements of driving. We reviewed a study of the neural correlates of alcohol intoxication through the use of a simulated-driving paradigm and wished to demonstrate the utility of recording continuous-driving behavior through a new study using a programmable driving simulator developed at our center. Functional magnetic resonance imaging data was collected from subjects while operating a driving simulator. Independent component analysis (ICA) was used to analyze the data. Specific brain regions modulated by alcohol, and relationships between behavior, brain function, and alcohol blood levels were examined with aggregate behavioral measures. Fifteen driving epochs taken from two subjects while also recording continuously recorded driving variables were analyzed with ICA. Preliminary findings reveal that four independent components correlate with various aspects of behavior. An increase in braking while driving was found to increase activation in motor areas, while cerebellar areas showed signal increases during steering maintenance, yet signal decreases during steering changes. Additional components and significant findings are further outlined. In summary, continuous behavioral variables conjoined with ICA may offer new insight into the neural correlates of complex human behavior.

Advanced and Conventional Magnetic Resonance Imaging in Neuropsychiatric Lupus

PubMed Central

Sarbu, Nicolae; Bargalló, Núria; Cervera, Ricard

2015-01-01

Neuropsychiatric lupus is a major diagnostic challenge, and a main cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). Magnetic resonance imaging (MRI) is, by far, the main tool for assessing the brain in this disease. Conventional and advanced MRI techniques are used to help establishing the diagnosis, to rule out alternative diagnoses, and recently, to monitor the evolution of the disease. This review explores the neuroimaging findings in SLE, including the recent advances in new MRI methods. PMID:26236469

Deep brain stimulation as a functional scalpel.

PubMed

Broggi, G; Franzini, A; Tringali, G; Ferroli, P; Marras, C; Romito, L; Maccagnano, E

2006-01-01

Since 1995, at the Istituto Nazionale Neurologico "Carlo Besta" in Milan (INNCB,) 401 deep brain electrodes were implanted to treat several drug-resistant neurological syndromes (Fig. 1). More than 200 patients are still available for follow-up and therapeutical considerations. In this paper our experience is reviewed and pioneered fields are highlighted. The reported series of patients extends the use of deep brain stimulation beyond the field of Parkinson's disease to new fields such as cluster headache, disruptive behaviour, SUNCt, epilepsy and tardive dystonia. The low complication rate, the reversibility of the procedure and the available image guided surgery tools will further increase the therapeutic applications of DBS. New therapeutical applications are expected for this functional scalpel.

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.

Visual Systems for Interactive Exploration and Mining of Large-Scale Neuroimaging Data Archives

PubMed Central

Bowman, Ian; Joshi, Shantanu H.; Van Horn, John D.

2012-01-01

While technological advancements in neuroimaging scanner engineering have improved the efficiency of data acquisition, electronic data capture methods will likewise significantly expedite the populating of large-scale neuroimaging databases. As they do and these archives grow in size, a particular challenge lies in examining and interacting with the information that these resources contain through the development of compelling, user-driven approaches for data exploration and mining. In this article, we introduce the informatics visualization for neuroimaging (INVIZIAN) framework for the graphical rendering of, and dynamic interaction with the contents of large-scale neuroimaging data sets. We describe the rationale behind INVIZIAN, detail its development, and demonstrate its usage in examining a collection of over 900 T1-anatomical magnetic resonance imaging (MRI) image volumes from across a diverse set of clinical neuroimaging studies drawn from a leading neuroimaging database. Using a collection of cortical surface metrics and means for examining brain similarity, INVIZIAN graphically displays brain surfaces as points in a coordinate space and enables classification of clusters of neuroanatomically similar MRI images and data mining. As an initial step toward addressing the need for such user-friendly tools, INVIZIAN provides a highly unique means to interact with large quantities of electronic brain imaging archives in ways suitable for hypothesis generation and data mining. PMID:22536181

A case study of magnetic resonance imaging of cerebrovascular reactivity: a powerful imaging marker for mild traumatic brain injury.

PubMed

Chan, Suk-tak; Evans, Karleyton C; Rosen, Bruce R; Song, Tian-yue; Kwong, Kenneth K

2015-01-01

To use breath-hold functional magnetic resonance imaging (fMRI) to localize the brain regions with impaired cerebrovascular reactivity (CVR) in a female patient diagnosed with mild traumatic brain injury (mTBI). The extent of impaired CVR was evaluated 2 months after concussion. Follow-up scan was performed 1 year post-mTBI using the same breath-hold fMRI technique. Case report. fMRI blood oxygenation dependent level (BOLD) signals were measured under breath-hold challenge in a female mTBI patient 2 months after concussion followed by a second fMRI with breath-hold challenge 1 year later. CVR was expressed as the percentage change of BOLD signals per unit time of breath-hold. In comparison with CVR measurement of normal control subjects, statistical maps of CVR revealed substantial neurovascular deficits and hemispheric asymmetry within grey and white matter in the initial breath-hold fMRI scan. Follow-up breath-hold fMRI performed 1 year post-mTBI demonstrated normalization of CVR accompanied with symptomatic recovery. CVR may serve as an imaging biomarker to detect subtle deficits in both grey and white matter for individual diagnosis of mTBI. The findings encourage further investigation of hypercapnic fMRI as a diagnostic tool for mTBI.

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

PubMed Central

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

2013-01-01

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

Categorization for Faces and Tools-Two Classes of Objects Shaped by Different Experience-Differs in Processing Timing, Brain Areas Involved, and Repetition Effects.

PubMed

Kozunov, Vladimir; Nikolaeva, Anastasia; Stroganova, Tatiana A

2017-01-01

The brain mechanisms that integrate the separate features of sensory input into a meaningful percept depend upon the prior experience of interaction with the object and differ between categories of objects. Recent studies using representational similarity analysis (RSA) have characterized either the spatial patterns of brain activity for different categories of objects or described how category structure in neuronal representations emerges in time, but never simultaneously. Here we applied a novel, region-based, multivariate pattern classification approach in combination with RSA to magnetoencephalography data to extract activity associated with qualitatively distinct processing stages of visual perception. We asked participants to name what they see whilst viewing bitonal visual stimuli of two categories predominantly shaped by either value-dependent or sensorimotor experience, namely faces and tools, and meaningless images. We aimed to disambiguate the spatiotemporal patterns of brain activity between the meaningful categories and determine which differences in their processing were attributable to either perceptual categorization per se , or later-stage mentalizing-related processes. We have extracted three stages of cortical activity corresponding to low-level processing, category-specific feature binding, and supra-categorical processing. All face-specific spatiotemporal patterns were associated with bilateral activation of ventral occipito-temporal areas during the feature binding stage at 140-170 ms. The tool-specific activity was found both within the categorization stage and in a later period not thought to be associated with binding processes. The tool-specific binding-related activity was detected within a 210-220 ms window and was located to the intraparietal sulcus of the left hemisphere. Brain activity common for both meaningful categories started at 250 ms and included widely distributed assemblies within parietal, temporal, and prefrontal regions. Furthermore, we hypothesized and tested whether activity within face and tool-specific binding-related patterns would demonstrate oppositely acting effects following procedural perceptual learning. We found that activity in the ventral, face-specific network increased following the stimuli repetition. In contrast, tool processing in the dorsal network adapted by reducing its activity over the repetition period. Altogether, we have demonstrated that activity associated with visual processing of faces and tools during the categorization stage differ in processing timing, brain areas involved, and in their dynamics underlying stimuli learning.

Robotically-adjustable microstereotactic frames for image-guided neurosurgery

NASA Astrophysics Data System (ADS)

Kratchman, Louis B.; Fitzpatrick, J. Michael

2013-03-01

Stereotactic frames are a standard tool for neurosurgical targeting, but are uncomfortable for patients and obstruct the surgical field. Microstereotactic frames are more comfortable for patients, provide better access to the surgical site, and have grown in popularity as an alternative to traditional stereotactic devices. However, clinically available microstereotactic frames require either lengthy manufacturing delays or expensive image guidance systems. We introduce a robotically-adjusted, disposable microstereotactic frame for deep brain stimulation surgery that eliminates the drawbacks of existing microstereotactic frames. Our frame can be automatically adjusted in the operating room using a preoperative plan in less than five minutes. A validation study on phantoms shows that our approach provides a target positioning error of 0.14 mm, which exceeds the required accuracy for deep brain stimulation surgery.

Micromirror structured illumination microscope for high-speed in vivo drosophila brain imaging.

PubMed

Masson, A; Pedrazzani, M; Benrezzak, S; Tchenio, P; Preat, T; Nutarelli, D

2014-01-27

Genetic tools and especially genetically encoded fluorescent reporters have given a special place to optical microscopy in drosophila neurobiology research. In order to monitor neural networks activity, high speed and sensitive techniques, with high spatial resolution are required. Structured illumination microscopies are wide-field approaches with optical sectioning ability. Despite the large progress made with the introduction of the HiLo principle, they did not meet the criteria of speed and/or spatial resolution for drosophila brain imaging. We report on a new implementation that took advantage of micromirror matrix technology to structure the illumination. Thus, we showed that the developed instrument exhibits a spatial resolution close to that of confocal microscopy but it can record physiological responses with a speed improved by more than an order a magnitude.

Simultaneous recording of fluorescence and electrical signals by photometric patch electrode in deep brain regions in vivo

PubMed Central

Hirai, Yasuharu; Nishino, Eri

2015-01-01

Despite its widespread use, high-resolution imaging with multiphoton microscopy to record neuronal signals in vivo is limited to the surface of brain tissue because of limited light penetration. Moreover, most imaging studies do not simultaneously record electrical neural activity, which is, however, crucial to understanding brain function. Accordingly, we developed a photometric patch electrode (PME) to overcome the depth limitation of optical measurements and also enable the simultaneous recording of neural electrical responses in deep brain regions. The PME recoding system uses a patch electrode to excite a fluorescent dye and to measure the fluorescence signal as a light guide, to record electrical signal, and to apply chemicals to the recorded cells locally. The optical signal was analyzed by either a spectrometer of high light sensitivity or a photomultiplier tube depending on the kinetics of the responses. We used the PME in Oregon Green BAPTA-1 AM-loaded avian auditory nuclei in vivo to monitor calcium signals and electrical responses. We demonstrated distinct response patterns in three different nuclei of the ascending auditory pathway. On acoustic stimulation, a robust calcium fluorescence response occurred in auditory cortex (field L) neurons that outlasted the electrical response. In the auditory midbrain (inferior colliculus), both responses were transient. In the brain-stem cochlear nucleus magnocellularis, calcium response seemed to be effectively suppressed by the activity of metabotropic glutamate receptors. In conclusion, the PME provides a powerful tool to study brain function in vivo at a tissue depth inaccessible to conventional imaging devices. PMID:25761950

Simultaneous recording of fluorescence and electrical signals by photometric patch electrode in deep brain regions in vivo.

PubMed

Hirai, Yasuharu; Nishino, Eri; Ohmori, Harunori

2015-06-01

Despite its widespread use, high-resolution imaging with multiphoton microscopy to record neuronal signals in vivo is limited to the surface of brain tissue because of limited light penetration. Moreover, most imaging studies do not simultaneously record electrical neural activity, which is, however, crucial to understanding brain function. Accordingly, we developed a photometric patch electrode (PME) to overcome the depth limitation of optical measurements and also enable the simultaneous recording of neural electrical responses in deep brain regions. The PME recoding system uses a patch electrode to excite a fluorescent dye and to measure the fluorescence signal as a light guide, to record electrical signal, and to apply chemicals to the recorded cells locally. The optical signal was analyzed by either a spectrometer of high light sensitivity or a photomultiplier tube depending on the kinetics of the responses. We used the PME in Oregon Green BAPTA-1 AM-loaded avian auditory nuclei in vivo to monitor calcium signals and electrical responses. We demonstrated distinct response patterns in three different nuclei of the ascending auditory pathway. On acoustic stimulation, a robust calcium fluorescence response occurred in auditory cortex (field L) neurons that outlasted the electrical response. In the auditory midbrain (inferior colliculus), both responses were transient. In the brain-stem cochlear nucleus magnocellularis, calcium response seemed to be effectively suppressed by the activity of metabotropic glutamate receptors. In conclusion, the PME provides a powerful tool to study brain function in vivo at a tissue depth inaccessible to conventional imaging devices. Copyright © 2015 the American Physiological Society.

A New MRI Masking Technique Based on Multi-Atlas Brain Segmentation in Controls and Schizophrenia: A Rapid and Viable Alternative to Manual Masking.

PubMed

Del Re, Elisabetta C; Gao, Yi; Eckbo, Ryan; Petryshen, Tracey L; Blokland, Gabriëlla A M; Seidman, Larry J; Konishi, Jun; Goldstein, Jill M; McCarley, Robert W; Shenton, Martha E; Bouix, Sylvain

2016-01-01

Brain masking of MRI images separates brain from surrounding tissue and its accuracy is important for further imaging analyses. We implemented a new brain masking technique based on multi-atlas brain segmentation (MABS) and compared MABS to masks generated using FreeSurfer (FS; version 5.3), Brain Extraction Tool (BET), and Brainwash, using manually defined masks (MM) as the gold standard. We further determined the effect of different masking techniques on cortical and subcortical volumes generated by FreeSurfer. Images were acquired on a 3-Tesla MR Echospeed system General Electric scanner on five control and five schizophrenia subjects matched on age, sex, and IQ. Automated masks were generated from MABS, FS, BET, and Brainwash, and compared to MM using these metrics: a) volume difference from MM; b) Dice coefficients; and c) intraclass correlation coefficients. Mean volume difference between MM and MABS masks was significantly less than the difference between MM and FS or BET masks. Dice coefficient between MM and MABS was significantly higher than Dice coefficients between MM and FS, BET, or Brainwash. For subcortical and left cortical regions, MABS volumes were closer to MM volumes than were BET or FS volumes. For right cortical regions, MABS volumes were closer to MM volumes than were BET volumes. Brain masks generated using FreeSurfer, BET, and Brainwash are rapidly obtained, but are less accurate than manually defined masks. Masks generated using MABS, in contrast, resemble more closely the gold standard of manual masking, thereby offering a rapid and viable alternative. Copyright © 2015 by the American Society of Neuroimaging.

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

Naumann, Eva A; Fitzgerald, James E; Dunn, Timothy W; Rihel, Jason; Sompolinsky, Haim; Engert, Florian

2016-11-03

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data. Copyright © 2016 Elsevier Inc. All rights reserved.

Biocytin-Derived MRI Contrast Agent for Longitudinal Brain Connectivity Studies

PubMed Central

2011-01-01

To investigate the connectivity of brain networks noninvasively and dynamically, we have developed a new strategy to functionalize neuronal tracers and designed a biocompatible probe that can be visualized in vivo using magnetic resonance imaging (MRI). Furthermore, the multimodal design used allows combined ex vivo studies with microscopic spatial resolution by conventional histochemical techniques. We present data on the functionalization of biocytin, a well-known neuronal tract tracer, and demonstrate the validity of the approach by showing brain networks of cortical connectivity in live rats under MRI, together with the corresponding microscopic details, such as fibers and neuronal morphology under light microscopy. We further demonstrate that the developed molecule is the first MRI-visible probe to preferentially trace retrograde connections. Our study offers a new platform for the development of multimodal molecular imaging tools of broad interest in neuroscience, that capture in vivo the dynamics of large scale neural networks together with their microscopic characteristics, thereby spanning several organizational levels. PMID:22860157

Optimization of Brain T2 Mapping Using Standard CPMG Sequence In A Clinical Scanner

NASA Astrophysics Data System (ADS)

Hnilicová, P.; Bittšanský, M.; Dobrota, D.

2014-04-01

In magnetic resonance imaging, transverse relaxation time (T2) mapping is a useful quantitative tool enabling enhanced diagnostics of many brain pathologies. The aim of our study was to test the influence of different sequence parameters on calculated T2 values, including multi-slice measurements, slice position, interslice gap, echo spacing, and pulse duration. Measurements were performed using standard multi-slice multi-echo CPMG imaging sequence on a 1.5 Tesla routine whole body MR scanner. We used multiple phantoms with different agarose concentrations (0 % to 4 %) and verified the results on a healthy volunteer. It appeared that neither the pulse duration, the size of interslice gap nor the slice shift had any impact on the T2. The measurement accuracy was increased with shorter echo spacing. Standard multi-slice multi-echo CPMG protocol with the shortest echo spacing, also the smallest available interslice gap (100 % of slice thickness) and shorter pulse duration was found to be optimal and reliable for calculating T2 maps in the human brain.

A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei

PubMed Central

Pauli, Wolfgang M.; Nili, Amanda N.; Tyszka, J. Michael

2018-01-01

Recent advances in magnetic resonance imaging methods, including data acquisition, pre-processing and analysis, have benefited research on the contributions of subcortical brain nuclei to human cognition and behavior. At the same time, these developments have led to an increasing need for a high-resolution probabilistic in vivo anatomical atlas of subcortical nuclei. In order to address this need, we constructed high spatial resolution, three-dimensional templates, using high-accuracy diffeomorphic registration of T1- and T2- weighted structural images from 168 typical adults between 22 and 35 years old. In these templates, many tissue boundaries are clearly visible, which would otherwise be impossible to delineate in data from individual studies. The resulting delineations of subcortical nuclei complement current histology-based atlases. We further created a companion library of software tools for atlas development, to offer an open and evolving resource for the creation of a crowd-sourced in vivo probabilistic anatomical atlas of the human brain. PMID:29664465

Clinical field-strength MRI of amyloid plaques induced by low-level cholesterol feeding in rabbits

PubMed Central

Chen, Yuanxin; Bernas, Lisa; Kitzler, Hagen H.; Rogers, Kem A.; Hegele, Robert A.; Rutt, Brian K.

2009-01-01

Two significant barriers have limited the development of effective treatment of Alzheimer's disease. First, for many cases the aetiology is unknown and likely multi-factorial. Among these factors, hypercholesterolemia is a known risk predictor and has been linked to the formation of β-amyloid plaques, a pathological hallmark this disease. Second, standardized diagnostic tools are unable to definitively diagnose this disease prior to death; hence new diagnostic tools are urgently needed. Magnetic resonance imaging (MRI) using high field-strength scanners has shown promise for direct visualization of β-amyloid plaques, allowing in vivo longitudinal tracking of disease progression in mouse models. Here, we present a new rabbit model for studying the relationship between cholesterol and Alzheimer's disease development and new tools for direct visualization of β-amyloid plaques using clinical field-strength MRI. New Zealand white rabbits were fed either a low-level (0.125–0.25% w/w) cholesterol diet (n = 5) or normal chow (n = 4) for 27 months. High-resolution (66 × 66 × 100 µm3; scan time = 96 min) ex vivo MRI of brains was performed using a 3-Tesla (T) MR scanner interfaced with customized gradient and radiofrequency coils. β-Amyloid-42 immunostaining and Prussian blue iron staining were performed on brain sections and MR and histological images were manually registered. MRI revealed distinct signal voids throughout the brains of cholesterol-fed rabbits, whereas minimal voids were seen in control rabbit brains. These voids corresponded directly to small clusters of extracellular β-amyloid-positive plaques, which were consistently identified as iron-loaded (the presumed source of MR contrast). Plaques were typically located in the hippocampus, parahippocampal gyrus, striatum, hypothalamus and thalamus. Quantitative analysis of the number of histologically positive β-amyloid plaques (P < 0.0001) and MR-positive signal voids (P < 0.05) found in cholesterol-fed and control rabbit brains corroborated our qualitative observations. In conclusion, long-term, low-level cholesterol feeding was sufficient to promote the formation of extracellular β-amyloid plaque formation in rabbits, supporting the integral role of cholesterol in the aetiology of Alzheimer's disease. We also present the first evidence that MRI is capable of detecting iron-associated β-amyloid plaques in a rabbit model of Alzheimer's disease and have advanced the sensitivity of MRI for plaque detection to a new level, allowing clinical field-strength scanners to be employed. We believe extension of these technologies to an in vivo setting in rabbits is feasible and that our results support future work exploring the role of MRI as a leading imaging tool for this debilitating and life-threatening disease. PMID:19293239

Creating an anthropomorphic digital MR phantom—an extensible tool for comparing and evaluating quantitative imaging algorithms

NASA Astrophysics Data System (ADS)

Bosca, Ryan J.; Jackson, Edward F.

2016-01-01

Assessing and mitigating the various sources of bias and variance associated with image quantification algorithms is essential to the use of such algorithms in clinical research and practice. Assessment is usually accomplished with grid-based digital reference objects (DRO) or, more recently, digital anthropomorphic phantoms based on normal human anatomy. Publicly available digital anthropomorphic phantoms can provide a basis for generating realistic model-based DROs that incorporate the heterogeneity commonly found in pathology. Using a publicly available vascular input function (VIF) and digital anthropomorphic phantom of a normal human brain, a methodology was developed to generate a DRO based on the general kinetic model (GKM) that represented realistic and heterogeneously enhancing pathology. GKM parameters were estimated from a deidentified clinical dynamic contrast-enhanced (DCE) MRI exam. This clinical imaging volume was co-registered with a discrete tissue model, and model parameters estimated from clinical images were used to synthesize a DCE-MRI exam that consisted of normal brain tissues and a heterogeneously enhancing brain tumor. An example application of spatial smoothing was used to illustrate potential applications in assessing quantitative imaging algorithms. A voxel-wise Bland-Altman analysis demonstrated negligible differences between the parameters estimated with and without spatial smoothing (using a small radius Gaussian kernel). In this work, we reported an extensible methodology for generating model-based anthropomorphic DROs containing normal and pathological tissue that can be used to assess quantitative imaging algorithms.

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

Early craniometric tools as a predecessor to neurosurgical stereotaxis.

PubMed

Serletis, Demitre; Pait, T Glenn

2016-06-01

In this paper the authors trace the history of early craniometry, referring to the technique of obtaining cranial measurements for the accurate correlation of external skull landmarks to specific brain regions. Largely drawing on methods from the newly emerging fields of physical anthropology and phrenology in the late 19th and early 20th centuries, basic mathematical concepts were combined with simplistic (yet at the time, innovative) mechanical tools, leading to the first known attempts at craniocerebral topography. It is important to acknowledge the pioneers of this pre-imaging epoch, who applied creativity and ingenuity to tackle the challenge of reproducibly and reliably accessing a specific target in the brain. In particular, with the emergence of Broca's theory of cortical localization, in vivo craniometric tools, and the introduction of 3D coordinate systems, several innovative devices were conceived that subsequently paved the way for modern-day stereotactic techniques. In this context, the authors present a comprehensive and systematic review of the most popular craniometric tools developed during this time period (prior to the stereotactic era) for the purposes of craniocerebral measurement and target localization.

A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets.

PubMed

Panta, Sandeep R; Wang, Runtang; Fries, Jill; Kalyanam, Ravi; Speer, Nicole; Banich, Marie; Kiehl, Kent; King, Margaret; Milham, Michael; Wager, Tor D; Turner, Jessica A; Plis, Sergey M; Calhoun, Vince D

2016-01-01

In this paper we propose a web-based approach for quick visualization of big data from brain magnetic resonance imaging (MRI) scans using a combination of an automated image capture and processing system, nonlinear embedding, and interactive data visualization tools. We draw upon thousands of MRI scans captured via the COllaborative Imaging and Neuroinformatics Suite (COINS). We then interface the output of several analysis pipelines based on structural and functional data to a t-distributed stochastic neighbor embedding (t-SNE) algorithm which reduces the number of dimensions for each scan in the input data set to two dimensions while preserving the local structure of data sets. Finally, we interactively display the output of this approach via a web-page, based on data driven documents (D3) JavaScript library. Two distinct approaches were used to visualize the data. In the first approach, we computed multiple quality control (QC) values from pre-processed data, which were used as inputs to the t-SNE algorithm. This approach helps in assessing the quality of each data set relative to others. In the second case, computed variables of interest (e.g., brain volume or voxel values from segmented gray matter images) were used as inputs to the t-SNE algorithm. This approach helps in identifying interesting patterns in the data sets. We demonstrate these approaches using multiple examples from over 10,000 data sets including (1) quality control measures calculated from phantom data over time, (2) quality control data from human functional MRI data across various studies, scanners, sites, (3) volumetric and density measures from human structural MRI data across various studies, scanners and sites. Results from (1) and (2) show the potential of our approach to combine t-SNE data reduction with interactive color coding of variables of interest to quickly identify visually unique clusters of data (i.e., data sets with poor QC, clustering of data by site) quickly. Results from (3) demonstrate interesting patterns of gray matter and volume, and evaluate how they map onto variables including scanners, age, and gender. In sum, the proposed approach allows researchers to rapidly identify and extract meaningful information from big data sets. Such tools are becoming increasingly important as datasets grow larger.

Schaltenbrand-Wahren-Talairach-Tournoux brain atlas registration

NASA Astrophysics Data System (ADS)

Nowinski, Wieslaw L.; Fang, Anthony; Nguyen, Bonnie T.

1995-04-01

The CIeMed electronic brain atlas system contains electronic versions of multiple paper brain atlases with 3D extensions; some other 3D brain atlases are under development. Its primary goal is to provide automatic labeling and quantification of brains. The atlas data are digitized, enhanced, color coded, labeled, and organized into volumes. The atlas system provides several tools for registration, 3D display and real-time manipulation, object extraction/editing, quantification, image processing and analysis, reformatting, anatomical index operations, and file handling. The two main stereotactic atlases provided by the system are electronic and enhanced versions of Atlas of Stereotaxy of the Human Brain by Schaltenbrand and Wahren and Co-Planar Stereotactic Atlas of the Human Brain by Talairach and Tournoux. Each of these atlases has its own strengths and their combination has several advantages. First, a complementary information is merged and provided to the user. Second, the user can register data with a single atlas only, as the Schaltenbrand-Wahren-Talairach-Tournoux registration is data-independent. And last but not least, a direct registration of the Schaltenbrand-Wahren microseries with MRI data may not be feasible, since cerebral deep structures are usually not clearly discernible on MRI images. This paper addresses registration of the Schaltenbrand- Wahren and Talairach-Tournoux brain atlases. A modified proportional grid system transformation is introduced and suitable sets of landmarks identifiable in both atlases are defined. The accuracy of registration is discussed. A continuous navigation in the multi- atlas/patient data space is presented.

fMRat: an extension of SPM for a fully automatic analysis of rodent brain functional magnetic resonance series.

PubMed

Chavarrías, Cristina; García-Vázquez, Verónica; Alemán-Gómez, Yasser; Montesinos, Paula; Pascau, Javier; Desco, Manuel

2016-05-01

The purpose of this study was to develop a multi-platform automatic software tool for full processing of fMRI rodent studies. Existing tools require the usage of several different plug-ins, a significant user interaction and/or programming skills. Based on a user-friendly interface, the tool provides statistical parametric brain maps (t and Z) and percentage of signal change for user-provided regions of interest. The tool is coded in MATLAB (MathWorks(®)) and implemented as a plug-in for SPM (Statistical Parametric Mapping, the Wellcome Trust Centre for Neuroimaging). The automatic pipeline loads default parameters that are appropriate for preclinical studies and processes multiple subjects in batch mode (from images in either Nifti or raw Bruker format). In advanced mode, all processing steps can be selected or deselected and executed independently. Processing parameters and workflow were optimized for rat studies and assessed using 460 male-rat fMRI series on which we tested five smoothing kernel sizes and three different hemodynamic models. A smoothing kernel of FWHM = 1.2 mm (four times the voxel size) yielded the highest t values at the somatosensorial primary cortex, and a boxcar response function provided the lowest residual variance after fitting. fMRat offers the features of a thorough SPM-based analysis combined with the functionality of several SPM extensions in a single automatic pipeline with a user-friendly interface. The code and sample images can be downloaded from https://github.com/HGGM-LIM/fmrat .

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.

volBrain: An Online MRI Brain Volumetry System

PubMed Central

Manjón, José V.; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results. PMID:27512372

Stereotaxic gamma knife surgery in treatment of critically located pilocytic astrocytoma: preliminary result

PubMed Central

Hafez, Raef FA

2007-01-01

Background Low-grade gliomas are uncommon primary brain tumors, located more often in the posterior fossa, optic pathway, and brain stem and less commonly in the cerebral hemispheres. Case presentations Two patients with diagnosed recurrent cystic pilocytic astrocytoma critically located within the brain (thalamic and brain stem) were treated with gamma knife surgery. Gamma knife surgery (GKS) did improve the patient's clinical condition very much which remained stable later on. Progressive reduction on the magnetic resonance imaging (MRI) studies of the solid part of the tumor and almost disappearance of the cystic component was achieved within the follow-up period of 36 months in the first case with the (thalamic located lesion) and 22 months in the second case with the (brain stem located lesion). Conclusion Gamma knife surgery represents an alternate tool in the treatment of recurrent and/or small postoperative residual pilocytic astrocytoma especially if they are critically located PMID:17394660

volBrain: An Online MRI Brain Volumetry System.

PubMed

Manjón, José V; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results.

Advanced MR Imaging of the Human Nucleus Accumbens--Additional Guiding Tool for Deep Brain Stimulation.

PubMed

Lucas-Neto, Lia; Reimão, Sofia; Oliveira, Edson; Rainha-Campos, Alexandre; Sousa, João; Nunes, Rita G; Gonçalves-Ferreira, António; Campos, Jorge G

2015-07-01

The human nucleus accumbens (Acc) has become a target for deep brain stimulation (DBS) in some neuropsychiatric disorders. Nonetheless, even with the most recent advances in neuroimaging it remains difficult to accurately delineate the Acc and closely related subcortical structures, by conventional MRI sequences. It is our purpose to perform a MRI study of the human Acc and to determine whether there are reliable anatomical landmarks that enable the precise location and identification of the nucleus and its core/shell division. For the Acc identification and delineation, based on anatomical landmarks, T1WI, T1IR and STIR 3T-MR images were acquired in 10 healthy volunteers. Additionally, 32-direction DTI was obtained for Acc segmentation. Seed masks for the Acc were generated with FreeSurfer and probabilistic tractography was performed using FSL. The probability of connectivity between the seed voxels and distinct brain areas was determined and subjected to k-means clustering analysis, defining 2 different regions. With conventional T1WI, the Acc borders are better defined through its surrounding anatomical structures. The DTI color-coded vector maps and IR sequences add further detail in the Acc identification and delineation. Additionally, using probabilistic tractography it is possible to segment the Acc into a core and shell division and establish its structural connectivity with different brain areas. Advanced MRI techniques allow in vivo delineation and segmentation of the human Acc and represent an additional guiding tool in the precise and safe target definition for DBS. © 2015 International Neuromodulation Society.

Reliability measures of functional magnetic resonance imaging in a longitudinal evaluation of mild cognitive impairment.

PubMed

Zanto, Theodore P; Pa, Judy; Gazzaley, Adam

2014-01-01

As the aging population grows, it has become increasingly important to carefully characterize amnestic mild cognitive impairment (aMCI), a preclinical stage of Alzheimer's disease (AD). Functional magnetic resonance imaging (fMRI) is a valuable tool for monitoring disease progression in selectively vulnerable brain regions associated with AD neuropathology. However, the reliability of fMRI data in longitudinal studies of older adults with aMCI is largely unexplored. To address this, aMCI participants completed two visual working tasks, a Delayed-Recognition task and a One-Back task, on three separate scanning sessions over a three-month period. Test-retest reliability of the fMRI blood oxygen level dependent (BOLD) activity was assessed using an intraclass correlation (ICC) analysis approach. Results indicated that brain regions engaged during the task displayed greater reliability across sessions compared to regions that were not utilized by the task. During task-engagement, differential reliability scores were observed across the brain such that the frontal lobe, medial temporal lobe, and subcortical structures exhibited fair to moderate reliability (ICC=0.3-0.6), while temporal, parietal, and occipital regions exhibited moderate to good reliability (ICC=0.4-0.7). Additionally, reliability across brain regions was more stable when three fMRI sessions were used in the ICC calculation relative to two fMRI sessions. In conclusion, the fMRI BOLD signal is reliable across scanning sessions in this population and thus a useful tool for tracking longitudinal change in observational and interventional studies in aMCI. © 2013.

A minimalist approach to MALDI imaging of glycerophospholipids and sphingolipids in rat brain sections

NASA Astrophysics Data System (ADS)

Wang, Hay-Yan J.; Post, Shelley N. Jackson Jeremy; Woods, Amina S.

2008-12-01

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a powerful tool that has allowed researchers to directly probe tissue molecular structure and drug content with minimal manipulations, while maintaining anatomical integrity. In the present work glycerophospholipids and sphingolipids images were acquired from 16-[mu]m thick coronal rat brain sections using MALDI-MS. Images of phosphatidylinositol 38:4 (PI 38:4), sulfatide 24:1 (ST 24:1), and hydroxyl sulfatide 24:1 (ST 24:1 (OH)) were acquired in negative ion mode, while the images of phosphatidylcholine 34:1 (PC 34:1), potassiated phosphatidylcholines 32:0 (PC 32:0 + K+) and 36:1 (PC 36:1 + K+) were acquired in positive ion mode. The images of PI 38:4 and PC 36:1 + K+ show the preferential distribution of these two lipids in gray matter; and the images of two sulfatides and PC 32:0 + K+ show their preferential distribution in white matter. In addition, the gray cortical band and its adjacent anatomical structures were also identified by contrasting their lipid makeup. The resulting images were compared to lipid images acquired by secondary ion mass spectrometry (SIMS). The suitability of TLC sprayers, Collison Nebulizer, and artistic airbrush were also evaluated as means for matrix deposition.

Neuroimaging Insights into the Pathophysiology of Sleep Disorders

PubMed Central

Desseilles, Martin; Dang-Vu, Thanh; Schabus, Manuel; Sterpenich, Virginie; Maquet, Pierre; Schwartz, Sophie

2008-01-01

Neuroimaging methods can be used to investigate whether sleep disorders are associated with specific changes in brain structure or regional activity. However, it is still unclear how these new data might improve our understanding of the pathophysiology underlying adult sleep disorders. Here we review functional brain imaging findings in major intrinsic sleep disorders (i.e., idiopathic insomnia, narcolepsy, and obstructive sleep apnea) and in abnormal motor behavior during sleep (i.e., periodic limb movement disorder and REM sleep behavior disorder). The studies reviewed include neuroanatomical assessments (voxel-based morphometry, magnetic resonance spectroscopy), metabolic/functional investigations (positron emission tomography, single photon emission computed tomography, functional magnetic resonance imaging), and ligand marker measurements. Based on the current state of the research, we suggest that brain imaging is a useful approach to assess the structural and functional correlates of sleep impairments as well as better understand the cerebral consequences of various therapeutic approaches. Modern neuroimaging techniques therefore provide a valuable tool to gain insight into possible pathophysiological mechanisms of sleep disorders in adult humans. Citation: Desseilles M; Dang-Vu TD; Schabus M; Sterpenich V; Maquet P; Schwartz S. Neuroimaging insights into the pathophysiology of sleep disorders. SLEEP 2008;31(6):777–794. PMID:18548822

Brain tumor response to nimotuzumab treatment evaluated on magnetic resonance imaging.

PubMed

Dalmau, Evelio Rafael González; Cabal Mirabal, Carlos; Martínez, Giselle Saurez; Dávila, Agustín Lage; Suárez, José Carlos Ugarte; Cabanas Armada, Ricardo; Rodriguez Cruz, Gretel; Darias Zayas, Daniel; Castillo, Martha Ríos; Valle Garrido, Luis; Sotolongo, Luis Quevedo; Fernández, Mercedes Monzón

2014-02-01

Nimotuzumab, a humanized monoclonal antibody anti-epidermal growth factor receptor, has been shown to improve survival and quality of life in patients with pediatric malignant brain tumor. It is necessary, however, to increase the objective response criteria to define the optimal therapeutic schedule. The aim of this study was to obtain magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) quantitative information related to dimensions and morphology, molecular mobility and metabolic activity of the lesion and surroundings in order to evaluate any changes through time. Fourteen pediatric patients treated with nimotuzumab were evaluated on MRI and MRS for >2 years. Each patient was their own control. The MRI/MRS pulse sequence parameters were standardized to ensure experimental reproducibility. A total of 71.4% of patients had stable disease; 21.4% had objective response and 7.1% had progression of disease during the >2 year evaluation period. MRI/MRS data with clinical information provide a clearer picture of treatment response and confirm once again that nimotuzumab is effective in the treatment of pediatric brain tumor. These imaging procedures can be a useful tool for the clinical evaluation of study protocol in clinical practice. © 2013 The Authors. Pediatrics International © 2013 Japan Pediatric Society.

Track-weighted functional connectivity (TW-FC): a tool for characterizing the structural-functional connections in the brain.

PubMed

Calamante, Fernando; Masterton, Richard A J; Tournier, Jacques-Donald; Smith, Robert E; Willats, Lisa; Raffelt, David; Connelly, Alan

2013-04-15

MRI provides a powerful tool for studying the functional and structural connections in the brain non-invasively. The technique of functional connectivity (FC) exploits the intrinsic temporal correlations of slow spontaneous signal fluctuations to characterise brain functional networks. In addition, diffusion MRI fibre-tracking can be used to study the white matter structural connections. In recent years, there has been considerable interest in combining these two techniques to provide an overall structural-functional description of the brain. In this work we applied the recently proposed super-resolution track-weighted imaging (TWI) methodology to demonstrate how whole-brain fibre-tracking data can be combined with FC data to generate a track-weighted (TW) FC map of FC networks. The method was applied to data from 8 healthy volunteers, and illustrated with (i) FC networks obtained using a seeded connectivity-based analysis (seeding in the precuneus/posterior cingulate cortex, PCC, known to be part of the default mode network), and (ii) with FC networks generated using independent component analysis (in particular, the default mode, attention, visual, and sensory-motor networks). TW-FC maps showed high intensity in white matter structures connecting the nodes of the FC networks. For example, the cingulum bundles show the strongest TW-FC values in the PCC seeded-based analysis, due to their major role in the connection between medial frontal cortex and precuneus/posterior cingulate cortex; similarly the superior longitudinal fasciculus was well represented in the attention network, the optic radiations in the visual network, and the corticospinal tract and corpus callosum in the sensory-motor network. The TW-FC maps highlight the white matter connections associated with a given FC network, and their intensity in a given voxel reflects the functional connectivity of the part of the nodes of the network linked by the structural connections traversing that voxel. They therefore contain a different (and novel) image contrast from that of the images used to generate them. The results shown in this study illustrate the potential of the TW-FC approach for the fusion of structural and functional data into a single quantitative image. This technique could therefore have important applications in neuroscience and neurology, such as for voxel-based comparison studies. Copyright © 2012 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2017-01-01

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

Machine learning algorithm for automatic detection of CT-identifiable hyperdense lesions associated with traumatic brain injury

NASA Astrophysics Data System (ADS)

Keshavamurthy, Krishna N.; Leary, Owen P.; Merck, Lisa H.; Kimia, Benjamin; Collins, Scott; Wright, David W.; Allen, Jason W.; Brock, Jeffrey F.; Merck, Derek

2017-03-01

Traumatic brain injury (TBI) is a major cause of death and disability in the United States. Time to treatment is often related to patient outcome. Access to cerebral imaging data in a timely manner is a vital component of patient care. Current methods of detecting and quantifying intracranial pathology can be time-consuming and require careful review of 2D/3D patient images by a radiologist. Additional time is needed for image protocoling, acquisition, and processing. These steps often occur in series, adding more time to the process and potentially delaying time-dependent management decisions for patients with traumatic brain injury. Our team adapted machine learning and computer vision methods to develop a technique that rapidly and automatically detects CT-identifiable lesions. Specifically, we use scale invariant feature transform (SIFT)1 and deep convolutional neural networks (CNN)2 to identify important image features that can distinguish TBI lesions from background data. Our learning algorithm is a linear support vector machine (SVM)3. Further, we also employ tools from topological data analysis (TDA) for gleaning insights into the correlation patterns between healthy and pathological data. The technique was validated using 409 CT scans of the brain, acquired via the Progesterone for the Treatment of Traumatic Brain Injury phase III clinical trial (ProTECT_III) which studied patients with moderate to severe TBI4. CT data were annotated by a central radiologist and included patients with positive and negative scans. Additionally, the largest lesion on each positive scan was manually segmented. We reserved 80% of the data for training the SVM and used the remaining 20% for testing. Preliminary results are promising with 92.55% prediction accuracy (sensitivity = 91.15%, specificity = 93.45%), indicating the potential usefulness of this technique in clinical scenarios.

Mapping brain activity in gradient-echo functional MRI using principal component analysis

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Singh, Manbir; Don, Manuel

1997-05-01

The detection of sites of brain activation in functional MRI has been a topic of immense research interest and many technique shave been proposed to this end. Recently, principal component analysis (PCA) has been applied to extract the activated regions and their time course of activation. This method is based on the assumption that the activation is orthogonal to other signal variations such as brain motion, physiological oscillations and other uncorrelated noises. A distinct advantage of this method is that it does not require any knowledge of the time course of the true stimulus paradigm. This technique is well suited to EPI image sequences where the sampling rate is high enough to capture the effects of physiological oscillations. In this work, we propose and apply tow methods that are based on PCA to conventional gradient-echo images and investigate their usefulness as tools to extract reliable information on brain activation. The first method is a conventional technique where a single image sequence with alternating on and off stages is subject to a principal component analysis. The second method is a PCA-based approach called the common spatial factor analysis technique (CSF). As the name suggests, this method relies on common spatial factors between the above fMRI image sequence and a background fMRI. We have applied these methods to identify active brain ares during visual stimulation and motor tasks. The results from these methods are compared to those obtained by using the standard cross-correlation technique. We found good agreement in the areas identified as active across all three techniques. The results suggest that PCA and CSF methods have good potential in detecting the true stimulus correlated changes in the presence of other interfering signals.

Virtual Reality on a Desktop Hailed as New Tool in Distance Education.

ERIC Educational Resources Information Center

Young, Jeffrey R.

2000-01-01

Describes college and university educational applications of desktop virtual reality to provide a more human touch to interactive distance education programs and impress the brain with more vivid images. Critics suggest the technology is too costly and time consuming and may even distract students from the content of an online course. (DB)

Magnetic Resonance Imaging and Volumetric Analysis: Novel Tools to Study Thyroid Hormone Disruption and Its Effect on White Matter Development

EPA Science Inventory

Humans and wildlife are exposed to environmental pollutants that have been shown to interfere with the thyroid hormone system and thus may affect brain development. Our goal was to expose pregnant rats to propylthiouracil (PTU) to measure the effects of a goitrogen on white matte...

Test-retest assessment of cortical activation induced by repetitive transcranial magnetic stimulation with brain atlas-guided optical topography

NASA Astrophysics Data System (ADS)

Tian, Fenghua; Kozel, F. Andrew; Yennu, Amarnath; Croarkin, Paul E.; McClintock, Shawn M.; Mapes, Kimberly S.; Husain, Mustafa M.; Liu, Hanli

2012-11-01

Repetitive transcranial magnetic stimulation (rTMS) is a technology that stimulates neurons with rapidly changing magnetic pulses with demonstrated therapeutic applications for various neuropsychiatric disorders. Functional near-infrared spectroscopy (fNIRS) is a suitable tool to assess rTMS-evoked brain responses without interference from the magnetic or electric fields generated by the TMS coil. We have previously reported a channel-wise study of combined rTMS/fNIRS on the motor and prefrontal cortices, showing a robust decrease of oxygenated hemoglobin concentration (Δ[HbO2]) at the sites of 1-Hz rTMS and the contralateral brain regions. However, the reliability of this putative clinical tool is unknown. In this study, we develop a rapid optical topography approach to spatially characterize the rTMS-evoked hemodynamic responses on a standard brain atlas. A hemispherical approximation of the brain is employed to convert the three-dimensional topography on the complex brain surface to a two-dimensional topography in the spherical coordinate system. The test-retest reliability of the combined rTMS/fNIRS is assessed using repeated measurements performed two to three days apart. The results demonstrate that the Δ[HbO2] amplitudes have moderate-to-high reliability at the group level; and the spatial patterns of the topographic images have high reproducibility in size and a moderate degree of overlap at the individual level.

Application for the Drosophila ventral nerve cord standard in neuronal circuit reconstruction and in-depth analysis of mutant morphology

PubMed Central

Boerner, Jana; Godenschwege, Tanja Angela

2010-01-01

The Drosophila standard brain has been a useful tool that provides information about position and size of different brain structures within a wild-type brain and allows the comparison of imaging data that were collected from individual preparations. Therefore the standard can be used to reveal and visualize differences of brain regions between wild-type and mutant brains and can provide spatial description of single neurons within the nervous system. Recently the standard brain was complemented by the generation of a ventral nerve cord (VNC) standard. Here the authors have registered the major components of a simple neuronal circuit, the Giant Fiber System (GFS), into this standard. The authors show that they can also virtually reconstruct the well-characterized synaptic contact of the Giant Fiber with its motorneuronal target when they register the individual neurons from different preparations into the VNC standard. In addition to the potential application for the standard thorax in neuronal circuit reconstruction, the authors show that it is a useful tool for in-depth analysis of mutant morphology of single neurons. The authors find quantitative and qualitative differences when they compared the Giant Fibers of two different neuroglian alleles, nrg849 and nrgG00305, using the averaged wild-type GFS in the standard VNC as a reference. PMID:20615087

IMART software for correction of motion artifacts in images collected in intravital microscopy

PubMed Central

Dunn, Kenneth W; Lorenz, Kevin S; Salama, Paul; Delp, Edward J

2014-01-01

Intravital microscopy is a uniquely powerful tool, providing the ability to characterize cell and organ physiology in the natural context of the intact, living animal. With the recent development of high-resolution microscopy techniques such as confocal and multiphoton microscopy, intravital microscopy can now characterize structures at subcellular resolution and capture events at sub-second temporal resolution. However, realizing the potential for high resolution requires remarkable stability in the tissue. Whereas the rigid structure of the skull facilitates high-resolution imaging of the brain, organs of the viscera are free to move with respiration and heartbeat, requiring additional apparatus for immobilization. In our experience, these methods are variably effective, so that many studies are compromised by residual motion artifacts. Here we demonstrate the use of IMART, a software tool for removing motion artifacts from intravital microscopy images collected in time series or in three dimensions. PMID:26090271

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.

[The Role of Imaging in Central Nervous System Infections].

PubMed

Yokota, Hajime; Tazoe, Jun; Yamada, Kei

2015-07-01

Many infections invade the central nervous system. Magnetic resonance imaging (MRI) is the main tool that is used to evaluate infectious lesions of the central nervous system. The useful sequences on MRI are dependent on the locations, such as intra-axial, extra-axial, and spinal cord. For intra-axial lesions, besides the fundamental sequences, including T1-weighted images, T2-weighted images, and fluid-attenuated inversion recovery (FLAIR) images, advanced sequences, such as diffusion-weighted imaging, diffusion tensor imaging, susceptibility-weighted imaging, and MR spectroscopy, can be applied. They are occasionally used as determinants for quick and correct diagnosis. For extra-axial lesions, understanding the differences among 2D-conventional T1-weighted images, 2D-fat-saturated T1-weighted images, 3D-Spin echo sequences, and 3D-Gradient echo sequence after the administration of gadolinium is required to avoid wrong interpretations. FLAIR plus gadolinium is a useful tool for revealing abnormal enhancement on the brain surface. For the spinal cord, the sequences are limited. Evaluating the distribution and time course of the spinal cord are essential for correct diagnoses. We summarize the role of imaging in central nervous system infections and show the pitfalls, key points, and latest information in them on clinical practices.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging.

PubMed

Schultz, Simon R; Copeland, Caroline S; Foust, Amanda J; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

PubMed Central

Schultz, Simon R.; Copeland, Caroline S.; Foust, Amanda J.; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size. PMID:28757657

Brain CT image similarity retrieval method based on uncertain location graph.

PubMed

Pan, Haiwei; Li, Pengyuan; Li, Qing; Han, Qilong; Feng, Xiaoning; Gao, Linlin

2014-03-01

A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases. However, the similarity retrieval for brain CT images requires much higher accuracy than the general images. In this paper, a new model of uncertain location graph (ULG) is presented for brain CT image modeling and similarity retrieval. According to the characteristics of brain CT image, we propose a novel method to model brain CT image to ULG based on brain CT image texture. Then, a scheme for ULG similarity retrieval is introduced. Furthermore, an effective index structure is applied to reduce the searching time. Experimental results reveal that our method functions well on brain CT images similarity retrieval with higher accuracy and efficiency.

Soft Tissue Phantoms for Realistic Needle Insertion: A Comparative Study.

PubMed

Leibinger, Alexander; Forte, Antonio E; Tan, Zhengchu; Oldfield, Matthew J; Beyrau, Frank; Dini, Daniele; Rodriguez Y Baena, Ferdinando

2016-08-01

Phantoms are common substitutes for soft tissues in biomechanical research and are usually tuned to match tissue properties using standard testing protocols at small strains. However, the response due to complex tool-tissue interactions can differ depending on the phantom and no comprehensive comparative study has been published to date, which could aid researchers to select suitable materials. In this work, gelatin, a common phantom in literature, and a composite hydrogel developed at Imperial College, were matched for mechanical stiffness to porcine brain, and the interactions during needle insertions within them were analyzed. Specifically, we examined insertion forces for brain and the phantoms; we also measured displacements and strains within the phantoms via a laser-based image correlation technique in combination with fluorescent beads. It is shown that the insertion forces for gelatin and brain agree closely, but that the composite hydrogel better mimics the viscous nature of soft tissue. Both materials match different characteristics of brain, but neither of them is a perfect substitute. Thus, when selecting a phantom material, both the soft tissue properties and the complex tool-tissue interactions arising during tissue manipulation should be taken into consideration. These conclusions are presented in tabular form to aid future selection.

Assessing denoising strategies to increase signal to noise ratio in spinal cord and in brain cortical and subcortical regions

NASA Astrophysics Data System (ADS)

Maugeri, L.; Moraschi, M.; Summers, P.; Favilla, S.; Mascali, D.; Cedola, A.; Porro, C. A.; Giove, F.; Fratini, M.

2018-02-01

Functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygenation Level Dependent (BOLD) contrast has become one of the most powerful tools in neuroscience research. On the other hand, fMRI approaches have seen limited use in the study of spinal cord and subcortical brain regions (such as the brainstem and portions of the diencephalon). Indeed obtaining good BOLD signal in these areas still represents a technical and scientific challenge, due to poor control of physiological noise and to a limited overall quality of the functional series. A solution can be found in the combination of optimized experimental procedures at acquisition stage, and well-adapted artifact mitigation procedures in the data processing. In this framework, we studied two different data processing strategies to reduce physiological noise in cortical and subcortical brain regions and in the spinal cord, based on the aCompCor and RETROICOR denoising tools respectively. The study, performed in healthy subjects, was carried out using an ad hoc isometric motor task. We observed an increased signal to noise ratio in the denoised functional time series in the spinal cord and in the subcortical brain region.

Survey of Non-Rigid Registration Tools in Medicine.

PubMed

Keszei, András P; Berkels, Benjamin; Deserno, Thomas M

2017-02-01

We catalogue available software solutions for non-rigid image registration to support scientists in selecting suitable tools for specific medical registration purposes. Registration tools were identified using non-systematic search in Pubmed, Web of Science, IEEE Xplore® Digital Library, Google Scholar, and through references in identified sources (n = 22). Exclusions are due to unavailability or inappropriateness. The remaining (n = 18) tools were classified by (i) access and technology, (ii) interfaces and application, (iii) living community, (iv) supported file formats, and (v) types of registration methodologies emphasizing the similarity measures implemented. Out of the 18 tools, (i) 12 are open source, 8 are released under a permissive free license, which imposes the least restrictions on the use and further development of the tool, 8 provide graphical processing unit (GPU) support; (ii) 7 are built on software platforms, 5 were developed for brain image registration; (iii) 6 are under active development but only 3 have had their last update in 2015 or 2016; (iv) 16 support the Analyze format, while 7 file formats can be read with only one of the tools; and (v) 6 provide multiple registration methods and 6 provide landmark-based registration methods. Based on open source, licensing, GPU support, active community, several file formats, algorithms, and similarity measures, the tools Elastics and Plastimatch are chosen for the platform ITK and without platform requirements, respectively. Researchers in medical image analysis already have a large choice of registration tools freely available. However, the most recently published algorithms may not be included in the tools, yet.

Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging.

PubMed

Hamaide, Julie; De Groof, Geert; Van Steenkiste, Gwendolyn; Jeurissen, Ben; Van Audekerke, Johan; Naeyaert, Maarten; Van Ruijssevelt, Lisbeth; Cornil, Charlotte; Sijbers, Jan; Verhoye, Marleen; Van der Linden, Annemie

2017-02-01

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural investigation of the zebra finch brain has been performed ex vivo using invasive methods such as histology. These methods are highly specific, however, they strongly interfere with performing whole-brain analyses and exclude longitudinal studies aimed at establishing causal correlations between neuroplastic events and specific behavioral performances. Therefore, the aim of the current study was to implement an in vivo Diffusion Tensor Imaging (DTI) protocol sensitive enough to detect structural sex differences in the adult zebra finch brain. Voxel-wise comparison of male and female DTI parameter maps shows clear differences in several components of the song control system (i.e. Area X surroundings, the high vocal center (HVC) and the lateral magnocellular nucleus of the anterior nidopallium (LMAN)), which corroborate previous findings and are in line with the clear behavioral difference as only males sing. Furthermore, to obtain additional insights into the 3-dimensional organization of the zebra finch brain and clarify findings obtained by the in vivo study, ex vivo DTI data of the male and female brain were acquired as well, using a recently established super-resolution reconstruction (SRR) imaging strategy. Interestingly, the SRR-DTI approach led to a marked reduction in acquisition time without interfering with the (spatial and angular) resolution and SNR which enabled to acquire a data set characterized by a 78μm isotropic resolution including 90 diffusion gradient directions within 44h of scanning time. Based on the reconstructed SRR-DTI maps, whole brain probabilistic Track Density Imaging (TDI) was performed for the purpose of super resolved track density imaging, further pushing the resolution up to 40μm isotropic. The DTI and TDI maps realized atlas-quality anatomical maps that enable a clear delineation of most components of the song control and auditory systems. In conclusion, this study paves the way for longitudinal in vivo and high-resolution ex vivo experiments aimed at disentangling neuroplastic events that characterize the critical period for vocal learning in zebra finch ontogeny. Copyright © 2016 Elsevier Inc. All rights reserved.

Relation between brain architecture and mathematical ability in children: a DBM study.

PubMed

Han, Zhaoying; Davis, Nicole; Fuchs, Lynn; Anderson, Adam W; Gore, John C; Dawant, Benoit M

2013-12-01

Population-based studies indicate that between 5 and 9 percent of US children exhibit significant deficits in mathematical reasoning, yet little is understood about the brain morphological features related to mathematical performances. In this work, deformation-based morphometry (DBM) analyses have been performed on magnetic resonance images of the brains of 79 third graders to investigate whether there is a correlation between brain morphological features and mathematical proficiency. Group comparison was also performed between Math Difficulties (MD-worst math performers) and Normal Controls (NC), where each subgroup consists of 20 age and gender matched subjects. DBM analysis is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to a common space. To evaluate the effect of registration algorithms on DBM results, five nonrigid registration algorithms have been used: (1) the Adaptive Bases Algorithm (ABA); (2) the Image Registration Toolkit (IRTK); (3) the FSL Nonlinear Image Registration Tool; (4) the Automatic Registration Tool (ART); and (5) the normalization algorithm available in SPM8. The deformation field magnitude (DFM) was used to measure the displacement at each voxel, and the Jacobian determinant (JAC) was used to quantify local volumetric changes. Results show there are no statistically significant volumetric differences between the NC and the MD groups using JAC. However, DBM analysis using DFM found statistically significant anatomical variations between the two groups around the left occipital-temporal cortex, left orbital-frontal cortex, and right insular cortex. Regions of agreement between at least two algorithms based on voxel-wise analysis were used to define Regions of Interest (ROIs) to perform an ROI-based correlation analysis on all 79 volumes. Correlations between average DFM values and standard mathematical scores over these regions were found to be significant. We also found that the choice of registration algorithm has an impact on DBM-based results, so we recommend using more than one algorithm when conducting DBM studies. To the best of our knowledge, this is the first study that uses DBM to investigate brain anatomical features related to mathematical performance in a relatively large population of children. © 2013.

Non-uniform dose distributions in cranial radiation therapy

NASA Astrophysics Data System (ADS)

Bender, Edward T.

Radiation treatments are often delivered to patients with brain metastases. For those patients who receive radiation to the entire brain, there is a risk of long-term neuro-cognitive side effects, which may be due to damage to the hippocampus. In clinical MRI and CT scans it can be difficult to identify the hippocampus, but once identified it can be partially spared from radiation dose. Using deformable image registration we demonstrate a semi-automatic technique for obtaining an estimated location of this structure in a clinical MRI or CT scan. Deformable image registration is a useful tool in other areas such as adaptive radiotherapy, where the radiation oncology team monitors patients during the course of treatment and adjusts the radiation treatments if necessary when the patient anatomy changes. Deformable image registration is used in this setting, but there is a considerable level of uncertainty. This work represents one of many possible approaches at investigating the nature of these uncertainties utilizing consistency metrics. We will show that metrics such as the inverse consistency error correlate with actual registration uncertainties. Specifically relating to brain metastases, this work investigates where in the brain metastases are likely to form, and how the primary cancer site is related. We will show that the cerebellum is at high risk for metastases and that non-uniform dose distributions may be advantageous when delivering prophylactic cranial irradiation for patients with small cell lung cancer in complete remission.

Joint eigenvector estimation from mutually anisotropic tensors improves susceptibility tensor imaging of the brain, kidney, and heart.

PubMed

Dibb, Russell; Liu, Chunlei

2017-06-01

To develop a susceptibility-based MRI technique for probing microstructure and fiber architecture of magnetically anisotropic tissues-such as central nervous system white matter, renal tubules, and myocardial fibers-in three dimensions using susceptibility tensor imaging (STI) tools. STI can probe tissue microstructure, but is limited by reconstruction artifacts because of absent phase information outside the tissue and noise. STI accuracy may be improved by estimating a joint eigenvector from mutually anisotropic susceptibility and relaxation tensors. Gradient-recalled echo image data were simulated using a numerical phantom and acquired from the ex vivo mouse brain, kidney, and heart. Susceptibility tensor data were reconstructed using STI, regularized STI, and the proposed algorithm of mutually anisotropic and joint eigenvector STI (MAJESTI). Fiber map and tractography results from each technique were compared with diffusion tensor data. MAJESTI reduced the estimated susceptibility tensor orientation error by 30% in the phantom, 36% in brain white matter, 40% in the inner medulla of the kidney, and 45% in myocardium. This improved the continuity and consistency of susceptibility-based fiber tractography in each tissue. MAJESTI estimation of the susceptibility tensors yields lower orientation errors for susceptibility-based fiber mapping and tractography in the intact brain, kidney, and heart. Magn Reson Med 77:2331-2346, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Brain imaging and behavioral outcome in traumatic brain injury.

PubMed

Bigler, E D

1996-09-01

Brain imaging studies have become an essential diagnostic assessment procedure in evaluating the effects of traumatic brain injury (TBI). Such imaging studies provide a wealth of information about structural and functional deficits following TBI. But how pathologic changes identified by brain imaging methods relate to neurobehavioral outcome is not as well known. Thus, the focus of this article is on brain imaging findings and outcome following TBI. The article starts with an overview of current research dealing with the cellular pathology associated with TBI. Understanding the cellular elements of pathology permits extrapolation to what is observed with brain imaging. Next, this article reviews the relationship of brain imaging findings to underlying pathology and how that pathology relates to neurobehavioral outcome. The brain imaging techniques of magnetic resonance imaging, computerized tomography, and single photon emission computed tomography are reviewed. Various image analysis procedures, and how such findings relate to neuropsychological testing, are discussed. The importance of brain imaging in evaluating neurobehavioral deficits following brain injury is stressed.

Comprehensive Review on Magnetic Resonance Imaging in Alzheimer's Disease.

PubMed

Dona, Olga; Thompson, Jeff; Druchok, Cheryl

2016-01-01

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. However, definitive diagnosis of AD is only achievable postmortem and currently relies on clinical neurological evaluation. Magnetic resonance imaging (MRI) can evaluate brain changes typical of AD, including brain atrophy, presence of amyloid β (Aβ) plaques, and functional and biochemical abnormalities. Structural MRI (sMRI) has historically been used to assess the inherent brain atrophy present in AD. However, new techniques have recently emerged that have refined sMRI into a more precise tool to quantify the thickness and volume of AD-sensitive cerebral structures. Aβ plaques, a defining pathology of AD, are widely believed to contribute to the progressive cognitive decline in AD, but accurate assessment is only possible on autopsy. In vivo MRI of plaques, although currently limited to mouse models of AD, is a very promising technique. Measuring changes in activation and connectivity in AD-specific regions of the brain can be performed with functional MRI (fMRI). To help distinguish AD from diseases with similar symptoms, magnetic resonance spectroscopy (MRS) can be used to look for differing metabolite concentrations in vivo. Together, these MR techniques, evaluating various brain changes typical of AD, may help to provide a more definitive diagnosis and ease the assessment of the disease over time, noninvasively.

Visualizing spatial distribution of alectinib in murine brain using quantitative mass spectrometry imaging.

PubMed

Aikawa, Hiroaki; Hayashi, Mitsuhiro; Ryu, Shoraku; Yamashita, Makiko; Ohtsuka, Naoto; Nishidate, Masanobu; Fujiwara, Yasuhiro; Hamada, Akinobu

2016-03-30

In the development of anticancer drugs, drug concentration measurements in the target tissue have been thought to be crucial for predicting drug efficacy and safety. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is commonly used for determination of average drug concentrations; however, complete loss of spatial information in the target tissue occurs. Mass spectrometry imaging (MSI) has been recently applied as an innovative tool for detection of molecular distribution of pharmacological agents in heterogeneous targets. This study examined the intra-brain transitivity of alectinib, a novel anaplastic lymphoma kinase inhibitor, using a combination of matrix-assisted laser desorption ionization-MSI and LC-MS/MS techniques. We first analyzed the pharmacokinetic profiles in FVB mice and then examined the effect of the multidrug resistance protein-1 (MDR1) using Mdr1a/b knockout mice including quantitative distribution of alectinib in the brain. While no differences were observed between the mice for the plasma alectinib concentrations, diffuse alectinib distributions were found in the brain of the Mdr1a/b knockout versus FVB mice. These results indicate the potential for using quantitative MSI for clarifying drug distribution in the brain on a microscopic level, in addition to suggesting a possible use in designing studies for anticancer drug development and translational research.

Visualizing spatial distribution of alectinib in murine brain using quantitative mass spectrometry imaging

PubMed Central

Aikawa, Hiroaki; Hayashi, Mitsuhiro; Ryu, Shoraku; Yamashita, Makiko; Ohtsuka, Naoto; Nishidate, Masanobu; Fujiwara, Yasuhiro; Hamada, Akinobu

2016-01-01

In the development of anticancer drugs, drug concentration measurements in the target tissue have been thought to be crucial for predicting drug efficacy and safety. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is commonly used for determination of average drug concentrations; however, complete loss of spatial information in the target tissue occurs. Mass spectrometry imaging (MSI) has been recently applied as an innovative tool for detection of molecular distribution of pharmacological agents in heterogeneous targets. This study examined the intra-brain transitivity of alectinib, a novel anaplastic lymphoma kinase inhibitor, using a combination of matrix-assisted laser desorption ionization–MSI and LC-MS/MS techniques. We first analyzed the pharmacokinetic profiles in FVB mice and then examined the effect of the multidrug resistance protein-1 (MDR1) using Mdr1a/b knockout mice including quantitative distribution of alectinib in the brain. While no differences were observed between the mice for the plasma alectinib concentrations, diffuse alectinib distributions were found in the brain of the Mdr1a/b knockout versus FVB mice. These results indicate the potential for using quantitative MSI for clarifying drug distribution in the brain on a microscopic level, in addition to suggesting a possible use in designing studies for anticancer drug development and translational research. PMID:27026287

Brain refractive index measured in vivo with high-NA defocus-corrected full-field OCT and consequences for two-photon microscopy.

PubMed

Binding, Jonas; Ben Arous, Juliette; Léger, Jean-François; Gigan, Sylvain; Boccara, Claude; Bourdieu, Laurent

2011-03-14

Two-photon laser scanning microscopy (2PLSM) is an important tool for in vivo tissue imaging with sub-cellular resolution, but the penetration depth of current systems is potentially limited by sample-induced optical aberrations. To quantify these, we measured the refractive index n' in the somatosensory cortex of 7 rats in vivo using defocus optimization in full-field optical coherence tomography (ff-OCT). We found n' to be independent of imaging depth or rat age. From these measurements, we calculated that two-photon imaging beyond 200 µm into the cortex is limited by spherical aberration, indicating that adaptive optics will improve imaging depth.

Comparison of technetium-99m-HMPAO and technetium-99m-ECD cerebral SPECT images in Alzheimer`s disease

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

Dyck, C.H. van; Lin, C.H.; Smith, E.O.

1996-11-01

SPECT has shown increasing promise as a diagnostic tool in Alzheimer`s disease (AD). Recently, a new SPECT brain perfusion agent, {sup 99m}Tc-ethyl cysteinate dimer ({sup 99m}Tc-ECD) has emerged with purported advantages in image quality over the established tracer, {sup 99m}Tc-hexamethylpropyleneamine oxime ({sup 99m}Tc-HMPAO). This research aimed to compare cerebral images for ({sup 99m}Tc-HMPAO). This research aimed to compare cerebral images for {sup 99}mTc-HMPAO and {sup 99m}Tc-ECD in discriminating patients with AD form control subjects. 51 refs., 5 figs., 3 tabs.

Spectroscopic magnetic resonance imaging of the brain: voxel localisation and tissue segmentation in the follow up of brain tumour.

PubMed

Poloni, Guy; Bastianello, S; Vultaggio, Angela; Pozzi, S; Maccabelli, Gloria; Germani, Giancarlo; Chiarati, Patrizia; Pichiecchio, Anna

2008-01-01

The field of application of magnetic resonance spectroscopy (MRS) in biomedical research is expanding all the time and providing opportunities to investigate tissue metabolism and function. The data derived can be integrated with the information on tissue structure gained from conventional and non-conventional magnetic resonance imaging (MRI) techniques. Clinical MRS is also strongly expected to play an important role as a diagnostic tool. Essential for the future success of MRS as a clinical and research tool in biomedical sciences, both in vivo and in vitro, is the development of an accurate, biochemically relevant and physically consistent and reliable data analysis standard. Stable and well established analysis algorithms, in both the time and the frequency domain, are already available, as is free commercial software for implementing them. In this study, we propose an automatic algorithm that takes into account anatomical localisation, relative concentrations of white matter, grey matter, cerebrospinal fluid and signal abnormalities and inter-scan patient movement. The endpoint is the collection of a series of covariates that could be implemented in a multivariate analysis of covariance (MANCOVA) of the MRS data, as a tool for dealing with differences that may be ascribed to the anatomical variability of the subjects, to inaccuracies in the localisation of the voxel or slab, or to movement, rather than to the pathology under investigation. The aim was to develop an analysis procedure that can be consistently and reliably applied in the follow up of brain tumour. In this study, we demonstrate that the inclusion of such variables in the data analysis of quantitative MRS is fundamentally important (especially in view of the reduced accuracy typical of MRS measures compared to other MRI techniques), reducing the occurrence of false positives.

The effects of alcohol on the nonhuman primate brain: a network science approach to neuroimaging.

PubMed

Telesford, Qawi K; Laurienti, Paul J; Friedman, David P; Kraft, Robert A; Daunais, James B

2013-11-01

Animal studies have long been an important tool for basic research as they offer a degree of control often lacking in clinical studies. Of particular value is the use of nonhuman primates (NHPs) for neuroimaging studies. Currently, studies have been published using functional magnetic resonance imaging (fMRI) to understand the default-mode network in the NHP brain. Network science provides an alternative approach to neuroimaging allowing for evaluation of whole-brain connectivity. In this study, we used network science to build NHP brain networks from fMRI data to understand the basic functional organization of the NHP brain. We also explored how the brain network is affected following an acute ethanol (EtOH) pharmacological challenge. Baseline resting-state fMRI was acquired in an adult male rhesus macaque (n = 1) and a cohort of vervet monkeys (n = 10). A follow-up scan was conducted in the rhesus macaque to assess network variability and to assess the effects of an acute EtOH challenge on the brain network. The most connected regions in the resting-state networks were similar across species and matched regions identified as the default-mode network in previous NHP fMRI studies. Under an acute EtOH challenge, the functional organization of the brain was significantly impacted. Network science offers a great opportunity to understand the brain as a complex system and how pharmacological conditions can affect the system globally. These models are sensitive to changes in the brain and may prove to be a valuable tool in long-term studies on alcohol exposure. Copyright © 2013 by the Research Society on Alcoholism.

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.

Semi-automated brain tumor and edema segmentation using MRI.

PubMed

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

2005-10-01

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

Stereological evaluation of the volume and volume fraction of newborns' brain compartment and brain in magnetic resonance images.

PubMed

Nisari, Mehtap; Ertekin, Tolga; Ozçelik, Ozlem; Cınar, Serife; Doğanay, Selim; Acer, Niyazi

2012-11-01

Brain development in early life is thought to be critical period in neurodevelopmental disorder. Knowledge relating to this period is currently quite limited. This study aimed to evaluate the volume relation of total brain (TB), cerebrum, cerebellum and bulbus+pons by the use of Archimedes' principle and stereological (point-counting) method and after that to compare these approaches with each other in newborns. This study was carried out on five newborn cadavers mean weighing 2.220 ± 1.056 g with no signs of neuropathology. The mean (±SD) age of the subjects was 39.7 (±1.5) weeks. The volume and volume fraction of the total brain, cerebrum, cerebellum and bulbus+pons were determined on magnetic resonance (MR) images using the point-counting approach of stereological methods and by the use of fluid displacement technique. The mean (±SD) TB, cerebrum, cerebellum and bulbus+pons volumes by fluid displacement were 271.48 ± 78.3, 256.6 ± 71.8, 12.16 ± 6.1 and 2.72 ± 1.6 cm3, respectively. By the Cavalieri principle (point-counting) using sagittal MRIs, they were 262.01 ± 74.9, 248.11 ± 68.03, 11.68 ± 6.1 and 2.21 ± 1.13 cm3, respectively. The mean (± SD) volumes by point-counting technique using axial MR images were 288.06 ± 88.5, 275.2 ± 83.1, 19.75 ± 5.3 and 2.11 ± 0.7 cm3, respectively. There were no differences between the fluid displacement and point-counting (using axial and sagittal images) for all structures (p > 0.05). This study presents the basic data for studies relative to newborn's brain volume fractions according to two methods. Stereological (point-counting) estimation may be accepted a beneficial and new tool for neurological evaluation in vivo research of the brain. Based on these techniques we introduce here, the clinician may evaluate the growth of the brain in a more efficient and precise manner.

Brain medical image diagnosis based on corners with importance-values.

PubMed

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection method utilizing the diagnostic information from neurologists and a corner matching method based on the uncertainty and structure of brain medical images. Additionally, we present a similarity calculation method for brain image classification. Experimental results on two brain image sets show the proposed corner-based brain medical image classifier outperforms the state-of-the-art studies.

[Three-dimensional reconstruction of functional brain images].

PubMed

Inoue, M; Shoji, K; Kojima, H; Hirano, S; Naito, Y; Honjo, I

1999-08-01

We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: 1) routine images by SPM, 2) three-dimensional static images, and 3) three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface model is the most common method of three-dimensional display. However, the volume rendering method may be more effective for imaging regions such as the brain.

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.

A Compressive Sensing Approach for Glioma Margin Delineation Using Mass Spectrometry

PubMed Central

Gholami, Behnood; Agar, Nathalie Y. R.; Jolesz, Ferenc A.; Haddad, Wassim M.; Tannenbaum, Allen R.

2013-01-01

Surgery, and specifically, tumor resection, is the primary treatment for most patients suffering from brain tumors. Medical imaging techniques, and in particular, magnetic resonance imaging are currently used in diagnosis as well as image-guided surgery procedures. However, studies show that computed tomography and magnetic resonance imaging fail to accurately identify the full extent of malignant brain tumors and their microscopic infiltration. Mass spectrometry is a well-known analytical technique used to identify molecules in a given sample based on their mass. In a recent study, it is proposed to use mass spectrometry as an intraoperative tool for discriminating tumor and non-tumor tissue. Integration of mass spectrometry with the resection module allows for tumor resection and immediate molecular analysis. In this paper, we propose a framework for tumor margin delineation using compressive sensing. Specifically, we show that the spatial distribution of tumor cell concentration can be efficiently reconstructed and updated using mass spectrometry information from the resected tissue. In addition, our proposed framework is model-free, and hence, requires no prior information of spatial distribution of the tumor cell concentration. PMID:22255629

Selectivity for the human body in the fusiform gyrus.

PubMed

Peelen, Marius V; Downing, Paul E

2005-01-01

Functional neuroimaging studies have revealed human brain regions, notably in the fusiform gyrus, that respond selectively to images of faces as opposed to other kinds of objects. Here we use fMRI to show that the mid-fusiform gyrus responds with nearly the same level of selectivity to images of human bodies without faces, relative to tools and scenes. In a group-average analysis (n = 22), the fusiform activations identified by contrasting faces versus tools and bodies versus tools are very similar. Analyses of within-subjects regions of interest, however, show that the peaks of the two activations occupy close but distinct locations. In a second experiment, we find that the body-selective fusiform region, but not the face-selective region, responds more to stick figure depictions of bodies than to scrambled controls. This result further distinguishes the two foci and confirms that the body-selective response generalizes to abstract image formats. These results challenge accounts of the mid-fusiform gyrus that focus solely on faces and suggest that this region contains multiple distinct category-selective neural representations.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

PubMed

Rueckl, Martin; Lenzi, Stephen C; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca 2+ -imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca 2+ imaging datasets, particularly when these have been acquired at different spatial scales.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

PubMed Central

Rueckl, Martin; Lenzi, Stephen C.; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W.

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales. PMID:28706482

Artificial neural network detects human uncertainty

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Makarov, Vladimir V.; Koronovskii, Alexey A.; Garcia-Prieto, Juan; Antón-Toro, Luis Fernando; Maestú, Fernando; Pisarchik, Alexander N.

2018-03-01

Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.

Concurrent multiscale imaging with magnetic resonance imaging and optical coherence tomography

NASA Astrophysics Data System (ADS)

Liang, Chia-Pin; Yang, Bo; Kim, Il Kyoon; Makris, George; Desai, Jaydev P.; Gullapalli, Rao P.; Chen, Yu

2013-04-01

We develop a novel platform based on a tele-operated robot to perform high-resolution optical coherence tomography (OCT) imaging under continuous large field-of-view magnetic resonance imaging (MRI) guidance. Intra-operative MRI (iMRI) is a promising guidance tool for high-precision surgery, but it may not have sufficient resolution or contrast to visualize certain small targets. To address these limitations, we develop an MRI-compatible OCT needle probe, which is capable of providing microscale tissue architecture in conjunction with macroscale MRI tissue morphology in real time. Coregistered MRI/OCT images on ex vivo chicken breast and human brain tissues demonstrate that the complementary imaging scales and contrast mechanisms have great potential to improve the efficiency and the accuracy of iMRI procedure.

Categorization for Faces and Tools—Two Classes of Objects Shaped by Different Experience—Differs in Processing Timing, Brain Areas Involved, and Repetition Effects

PubMed Central

Kozunov, Vladimir; Nikolaeva, Anastasia; Stroganova, Tatiana A.

2018-01-01

The brain mechanisms that integrate the separate features of sensory input into a meaningful percept depend upon the prior experience of interaction with the object and differ between categories of objects. Recent studies using representational similarity analysis (RSA) have characterized either the spatial patterns of brain activity for different categories of objects or described how category structure in neuronal representations emerges in time, but never simultaneously. Here we applied a novel, region-based, multivariate pattern classification approach in combination with RSA to magnetoencephalography data to extract activity associated with qualitatively distinct processing stages of visual perception. We asked participants to name what they see whilst viewing bitonal visual stimuli of two categories predominantly shaped by either value-dependent or sensorimotor experience, namely faces and tools, and meaningless images. We aimed to disambiguate the spatiotemporal patterns of brain activity between the meaningful categories and determine which differences in their processing were attributable to either perceptual categorization per se, or later-stage mentalizing-related processes. We have extracted three stages of cortical activity corresponding to low-level processing, category-specific feature binding, and supra-categorical processing. All face-specific spatiotemporal patterns were associated with bilateral activation of ventral occipito-temporal areas during the feature binding stage at 140–170 ms. The tool-specific activity was found both within the categorization stage and in a later period not thought to be associated with binding processes. The tool-specific binding-related activity was detected within a 210–220 ms window and was located to the intraparietal sulcus of the left hemisphere. Brain activity common for both meaningful categories started at 250 ms and included widely distributed assemblies within parietal, temporal, and prefrontal regions. Furthermore, we hypothesized and tested whether activity within face and tool-specific binding-related patterns would demonstrate oppositely acting effects following procedural perceptual learning. We found that activity in the ventral, face-specific network increased following the stimuli repetition. In contrast, tool processing in the dorsal network adapted by reducing its activity over the repetition period. Altogether, we have demonstrated that activity associated with visual processing of faces and tools during the categorization stage differ in processing timing, brain areas involved, and in their dynamics underlying stimuli learning. PMID:29379426

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.

Trends in brain oxygenation during mental and physical exercise measured using near-infrared spectroscopy (NIRS): potential for early detection of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Allen, Monica S.; Allen, Jeffery W.; Mikkilineni, Shweta; Liu, Hanli

2005-04-01

Motivation: Early diagnosis of Alzheimer's disease (AD) is crucial because symptoms respond best to available treatments in the initial stages of the disease. Recent studies have shown that marked changes in brain oxygenation during mental and physical tasks can be used for noninvasive functional brain imaging to detect Alzheimer"s disease. The goal of our study is to explore the possibility of using near infrared spectroscopy (NIRS) and mapping (NIRM) as a diagnostic tool for AD before the onset of significant morphological changes in the brain. Methods: A 16-channel NIRS brain imager was used to noninvasively measure spatial and temporal changes in cerebral hemodynamics induced during verbal fluency task and physical activity. The experiments involved healthy subjects (n = 10) in the age range of 25+/-5 years. The NIRS signals were taken from the subjects' prefrontal cortex during the activities. Results and Conclusion: Trends of oxygenated and deoxygenated hemoglobin in the prefrontal cortex of the brain were observed. During the mental stimulation, the subjects showed significant increase in oxygenated hemoglobin [HbO2] with a simultaneous decrease in deoxygenated hemoglobin [Hb]. However, physical exercise caused a rise in levels of HbO2 with small variations in Hb. This study basically demonstrates that NIRM taken from the prefrontal cortex of the human brain is sensitive to both mental and physical tasks and holds potential to serve as a diagnostic means for early detection of Alzheimer's disease.

Transport of nanoparticles through the blood-brain barrier for imaging and therapeutic applications.

PubMed

Shilo, Malka; Motiei, Menachem; Hana, Panet; Popovtzer, Rachela

2014-02-21

A critical problem in the treatment of neurodegenerative disorders and diseases, such as Alzheimer's and Parkinson's, is the incapability to overcome the restrictive mechanism of the blood-brain barrier (BBB) and to deliver important therapeutic agents to the brain. During the last decade, nanoparticles have gained attention as promising drug delivery agents that can transport across the BBB and increase the uptake of appropriate drugs in the brain. In this study we have developed insulin-targeted gold nanoparticles (INS-GNPs) and investigated quantitatively the amount of INS-GNPs that cross the BBB by the receptor-mediated endocytosis process. For this purpose, INS-GNPs and control GNPs were injected into the tail vein of male BALB/c mice. Major organs were then extracted and a blood sample was taken from the mice, and thereafter analyzed for gold content by flame atomic absorption spectroscopy. Results show that two hours post-intravenous injection, the amount of INS-GNPs found in mouse brains is over 5 times greater than that of the control, untargeted GNPs. Results of further experimentation on a rat model show that INS-GNPs can also serve as CT contrast agents to highlight specific brain regions in which they accumulate. Due to the fact that they can overcome the restrictive mechanism of the BBB, this approach could be a potentially valuable tool, helping to confront the great challenge of delivering important imaging and therapeutic agents to the brain for detection and treatment of neurodegenerative disorders and diseases.

Transport of nanoparticles through the blood-brain barrier for imaging and therapeutic applications

NASA Astrophysics Data System (ADS)

Shilo, Malka; Motiei, Menachem; Hana, Panet; Popovtzer, Rachela

2014-01-01

A critical problem in the treatment of neurodegenerative disorders and diseases, such as Alzheimer's and Parkinson's, is the incapability to overcome the restrictive mechanism of the blood-brain barrier (BBB) and to deliver important therapeutic agents to the brain. During the last decade, nanoparticles have gained attention as promising drug delivery agents that can transport across the BBB and increase the uptake of appropriate drugs in the brain. In this study we have developed insulin-targeted gold nanoparticles (INS-GNPs) and investigated quantitatively the amount of INS-GNPs that cross the BBB by the receptor-mediated endocytosis process. For this purpose, INS-GNPs and control GNPs were injected into the tail vein of male BALB/c mice. Major organs were then extracted and a blood sample was taken from the mice, and thereafter analyzed for gold content by flame atomic absorption spectroscopy. Results show that two hours post-intravenous injection, the amount of INS-GNPs found in mouse brains is over 5 times greater than that of the control, untargeted GNPs. Results of further experimentation on a rat model show that INS-GNPs can also serve as CT contrast agents to highlight specific brain regions in which they accumulate. Due to the fact that they can overcome the restrictive mechanism of the BBB, this approach could be a potentially valuable tool, helping to confront the great challenge of delivering important imaging and therapeutic agents to the brain for detection and treatment of neurodegenerative disorders and diseases.

Revealing pathologies in the liquid crystalline structures of the brain by polarimetric studies (Presentation Recording)

NASA Astrophysics Data System (ADS)

Bakhshetyan, Karen; Melkonyan, Gurgen G.; Galstian, Tigran V.; Saghatelyan, Armen

2015-10-01

Natural or "self" alignment of molecular complexes in living tissue represents many similarities with liquid crystals (LC), which are anisotropic liquids. The orientational characteristics of those complexes may be related to many important functional parameters and their study may reveal important pathologies. The know-how, accumulated thanks to the study of LC materials, may thus be used to this end. One of the traditionally used methods, to characterize those materials, is the polarized light imaging (PLI) that allows for label-free analysis of anisotropic structures in the brain tissue and can be used, for example, for the analysis of myelinated fiber bundles. In the current work, we first attempted to apply the PLI on the mouse histological brain sections to create a map of anisotropic structures using cross-polarizer transmission light. Then we implemented the PLI for comparative study of histological sections of human postmortem brain samples under normal and pathological conditions, such as Parkinson's disease (PD). Imaging the coronal, sagittal and horizontal sections of mouse brain allowed us to create a false color-coded fiber orientation map under polarized light. In human brain datasets for both control and PD groups we measured the pixel intensities in myelin-rich subregions of internal capsule and normalized these to non-myelinated background signal from putamen and caudate nucleus. Quantification of intensities revealed a statistically significant reduction of fiber intensity of PD compared to control subjects (2.801 +/- 0.303 and 3.724 +/- 0.07 respectively; *p < 0.05). Our study confirms the validity of PLI method for visualizing myelinated axonal fibers. This relatively simple technique can become a promising tool for study of neurodegenerative diseases where labeling-free imaging is an important benefit.

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

Numerical analysis of the diffusive mass transport in brain tissues with applications to optical sensors

NASA Astrophysics Data System (ADS)

Neculae, Adrian P.; Otte, Andreas; Curticapean, Dan

2013-03-01

In the brain-cell microenvironment, diffusion plays an important role: apart from delivering glucose and oxygen from the vascular system to brain cells, it also moves informational substances between cells. The brain is an extremely complex structure of interwoven, intercommunicating cells, but recent theoretical and experimental works showed that the classical laws of diffusion, cast in the framework of porous media theory, can deliver an accurate quantitative description of the way molecules are transported through this tissue. The mathematical modeling and the numerical simulations are successfully applied in the investigation of diffusion processes in tissues, replacing the costly laboratory investigations. Nevertheless, modeling must rely on highly accurate information regarding the main parameters (tortuosity, volume fraction) which characterize the tissue, obtained by structural and functional imaging. The usual techniques to measure the diffusion mechanism in brain tissue are the radiotracer method, the real time iontophoretic method and integrative optical imaging using fluorescence microscopy. A promising technique for obtaining the values for characteristic parameters of the transport equation is the direct optical investigation using optical fibers. The analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. This paper presents a set of computations concerning the mass transport inside the brain tissue, for different types of cells. By measuring the time evolution of the concentration profile of an injected substance and using suitable fitting procedures, the main parameters characterizing the tissue can be determined. This type of analysis could be an important tool in understanding the functional mechanisms of effective drug delivery in complex structures such as the brain tissue. It also offers possibilities to realize optical imaging methods for in vitro and in vivo measurements using optical fibers. The model also may help in radiotracer biomarker models for the understanding of the mechanism of action of new chemical entities.

3D spatially encoded and accelerated TE-averaged echo planar spectroscopic imaging in healthy human brain.

PubMed

Iqbal, Zohaib; Wilson, Neil E; Thomas, M Albert

2016-03-01

Several different pathologies, including many neurodegenerative disorders, affect the energy metabolism of the brain. Glutamate, a neurotransmitter in the brain, can be used as a biomarker to monitor these metabolic processes. One method that is capable of quantifying glutamate concentration reliably in several regions of the brain is TE-averaged (1) H spectroscopic imaging. However, this type of method requires the acquisition of multiple TE lines, resulting in long scan durations. The goal of this experiment was to use non-uniform sampling, compressed sensing reconstruction and an echo planar readout gradient to reduce the scan time by a factor of eight to acquire TE-averaged spectra in three spatial dimensions. Simulation of glutamate and glutamine showed that the 2.2-2.4 ppm spectral region contained 95% glutamate signal using the TE-averaged method. Peak integration of this spectral range and home-developed, prior-knowledge-based fitting were used for quantitation. Gray matter brain phantom measurements were acquired on a Siemens 3 T Trio scanner. Non-uniform sampling was applied retrospectively to these phantom measurements and quantitative results of glutamate with respect to creatine 3.0 (Glu/Cr) ratios showed a coefficient of variance of 16% for peak integration and 9% for peak fitting using eight-fold acceleration. In vivo scans of the human brain were acquired as well and five different brain regions were quantified using the prior-knowledge-based algorithm. Glu/Cr ratios from these regions agreed with previously reported results in the literature. The method described here, called accelerated TE-averaged echo planar spectroscopic imaging (TEA-EPSI), is a significant methodological advancement and may be a useful tool for categorizing glutamate changes in pathologies where affected brain regions are not known a priori. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Detecting large-scale networks in the human brain using high-density electroencephalography.

PubMed

Liu, Quanying; Farahibozorg, Seyedehrezvan; Porcaro, Camillo; Wenderoth, Nicole; Mantini, Dante

2017-09-01

High-density electroencephalography (hdEEG) is an emerging brain imaging technique that can be used to investigate fast dynamics of electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from reporting brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI). Here, we report for the first time a robust detection of brain networks from resting state (256-channel) hdEEG recordings. Specifically, we obtained 14 networks previously described in fMRI studies by means of realistic 12-layer head models and exact low-resolution brain electromagnetic tomography (eLORETA) source localization, together with independent component analysis (ICA) for functional connectivity analysis. Our analyses revealed three important methodological aspects. First, brain network reconstruction can be improved by performing source localization using the gray matter as source space, instead of the whole brain. Second, conducting EEG connectivity analyses in individual space rather than on concatenated datasets may be preferable, as it permits to incorporate realistic information on head modeling and electrode positioning. Third, the use of a wide frequency band leads to an unbiased and generally accurate reconstruction of several network maps, whereas filtering data in a narrow frequency band may enhance the detection of specific networks and penalize that of others. We hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research. Hum Brain Mapp 38:4631-4643, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

On the use of EEG or MEG brain imaging tools in neuromarketing research.

PubMed

Vecchiato, Giovanni; Astolfi, Laura; De Vico Fallani, Fabrizio; Toppi, Jlenia; Aloise, Fabio; Bez, Francesco; Wei, Daming; Kong, Wanzeng; Dai, Jounging; Cincotti, Febo; Mattia, Donatella; Babiloni, Fabio

2011-01-01

Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI) methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies. By presenting data gathered through MEG and high resolution EEG we will show which kind of information it is possible to gather with these methodologies while the persons are watching marketing relevant stimuli. Such information will be related to the memorization and pleasantness related to such stimuli. We noted that temporal and frequency patterns of brain signals are able to provide possible descriptors conveying information about the cognitive and emotional processes in subjects observing commercial advertisements. These information could be unobtainable through common tools used in standard marketing research. We also show an example of how an EEG methodology could be used to analyze cultural differences between fruition of video commercials of carbonated beverages in Western and Eastern countries.

On the Use of EEG or MEG Brain Imaging Tools in Neuromarketing Research

PubMed Central

Vecchiato, Giovanni; Astolfi, Laura; De Vico Fallani, Fabrizio; Toppi, Jlenia; Aloise, Fabio; Bez, Francesco; Wei, Daming; Kong, Wanzeng; Dai, Jounging; Cincotti, Febo; Mattia, Donatella; Babiloni, Fabio

2011-01-01

Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI) methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies. By presenting data gathered through MEG and high resolution EEG we will show which kind of information it is possible to gather with these methodologies while the persons are watching marketing relevant stimuli. Such information will be related to the memorization and pleasantness related to such stimuli. We noted that temporal and frequency patterns of brain signals are able to provide possible descriptors conveying information about the cognitive and emotional processes in subjects observing commercial advertisements. These information could be unobtainable through common tools used in standard marketing research. We also show an example of how an EEG methodology could be used to analyze cultural differences between fruition of video commercials of carbonated beverages in Western and Eastern countries. PMID:21960996

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images.

PubMed

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S; Lin, Weili; Shen, Dinggang

2015-09-01

Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient's exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [(18)F]FDG PET image by using a low-dose brain [(18)F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. The authors employ a regression forest for predicting the standard-dose brain [(18)F]FDG PET image by low-dose brain [(18)F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [(18)F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [(18)F]FDG PET image and substantially enhanced image quality of low-dose brain [(18)F]FDG PET image. In this paper, the authors propose a framework to generate standard-dose brain [(18)F]FDG PET image using low-dose brain [(18)F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [(18)F]FDG PET can be well-predicted using MRI and low-dose brain [(18)F]FDG PET.

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images

PubMed Central

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S.; Lin, Weili; Shen, Dinggang

2015-01-01

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [18F]FDG PET image by using a low-dose brain [18F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [18F]FDG PET image by low-dose brain [18F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [18F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [18F]FDG PET image and substantially enhanced image quality of low-dose brain [18F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [18F]FDG PET image using low-dose brain [18F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [18F]FDG PET can be well-predicted using MRI and low-dose brain [18F]FDG PET. PMID:26328979

Prediction of standard-dose brain PET image by using MRI and low-dose brain [{sup 18}F]FDG PET images

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

Kang, Jiayin; Gao, Yaozong; Shi, Feng

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. Asmore » yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [{sup 18}F]FDG PET image by using a low-dose brain [{sup 18}F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [{sup 18}F]FDG PET image by low-dose brain [{sup 18}F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [{sup 18}F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [{sup 18}F]FDG PET image and substantially enhanced image quality of low-dose brain [{sup 18}F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [{sup 18}F]FDG PET image using low-dose brain [{sup 18}F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [{sup 18}F]FDG PET can be well-predicted using MRI and low-dose brain [{sup 18}F]FDG PET.« less

Ensemble Semi-supervised Frame-work for Brain Magnetic Resonance Imaging Tissue Segmentation.

PubMed

Azmi, Reza; Pishgoo, Boshra; Norozi, Narges; Yeganeh, Samira

2013-04-01

Brain magnetic resonance images (MRIs) tissue segmentation is one of the most important parts of the clinical diagnostic tools. Pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. Supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to obtain. Moreover, they cannot use unlabeled data to train classifiers. On the other hand, unsupervised segmentation methods have no prior knowledge and lead to low level of performance. However, semi-supervised learning which uses a few labeled data together with a large amount of unlabeled data causes higher accuracy with less trouble. In this paper, we propose an ensemble semi-supervised frame-work for segmenting of brain magnetic resonance imaging (MRI) tissues that it has been used results of several semi-supervised classifiers simultaneously. Selecting appropriate classifiers has a significant role in the performance of this frame-work. Hence, in this paper, we present two semi-supervised algorithms expectation filtering maximization and MCo_Training that are improved versions of semi-supervised methods expectation maximization and Co_Training and increase segmentation accuracy. Afterward, we use these improved classifiers together with graph-based semi-supervised classifier as components of the ensemble frame-work. Experimental results show that performance of segmentation in this approach is higher than both supervised methods and the individual semi-supervised classifiers.

The roadmap for estimation of cell-type-specific neuronal activity from non-invasive measurements

PubMed Central

Uhlirova, Hana; Kılıç, Kıvılcım; Tian, Peifang; Sakadžić, Sava; Thunemann, Martin; Desjardins, Michèle; Saisan, Payam A.; Nizar, Krystal; Yaseen, Mohammad A.; Hagler, Donald J.; Vandenberghe, Matthieu; Djurovic, Srdjan; Andreassen, Ole A.; Silva, Gabriel A.; Masliah, Eliezer; Vinogradov, Sergei; Buxton, Richard B.; Einevoll, Gaute T.; Boas, David A.; Dale, Anders M.; Devor, Anna

2016-01-01

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use non-invasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from non-invasive signals in humans. On the essential path towards this goal is the development of a detailed ‘bottom-up’ forward model bridging neuronal activity at the level of cell-type-specific populations to non-invasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O2 (measurable with quantitative functional Magnetic Resonance Imaging), and electrical currents/potentials (measurable with magneto/electroencephalography). This forward model would then provide the ‘ground truth’ for the development of new tools for tackling the inverse problem—estimation of neuronal activity from multimodal non-invasive imaging data. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574309

Real-time interactive tractography analysis for multimodal brain visualization tool: MultiXplore

NASA Astrophysics Data System (ADS)

Bakhshmand, Saeed M.; de Ribaupierre, Sandrine; Eagleson, Roy

2017-03-01

Most debilitating neurological disorders can have anatomical origins. Yet unlike other body organs, the anatomy alone cannot easily provide an understanding of brain functionality. In fact, addressing the challenge of linking structural and functional connectivity remains in the frontiers of neuroscience. Aggregating multimodal neuroimaging datasets may be critical for developing theories that span brain functionality, global neuroanatomy and internal microstructures. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are main such techniques that are employed to investigate the brain under normal and pathological conditions. FMRI records blood oxygenation level of the grey matter (GM), whereas DTI is able to reveal the underlying structure of the white matter (WM). Brain global activity is assumed to be an integration of GM functional hubs and WM neural pathways that serve to connect them. In this study we developed and evaluated a two-phase algorithm. This algorithm is employed in a 3D interactive connectivity visualization framework and helps to accelerate clustering of virtual neural pathways. In this paper, we will detail an algorithm that makes use of an index-based membership array formed for a whole brain tractography file and corresponding parcellated brain atlas. Next, we demonstrate efficiency of the algorithm by measuring required times for extracting a variety of fiber clusters, which are chosen in such a way to resemble all sizes probable output data files that algorithm will generate. The proposed algorithm facilitates real-time visual inspection of neuroimaging data to further the discovery in structure-function relationship of the brain networks.

Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging.

PubMed

Hintz, S R; Cheong, W F; van Houten, J P; Stevenson, D K; Benaron, D A

1999-01-01

Medical optical imaging (MOI) uses light emitted into opaque tissues to determine the interior structure. Previous reports detailed a portable time-of-flight and absorbance system emitting pulses of near infrared light into tissues and measuring the emerging light. Using this system, optical images of phantoms, whole rats, and pathologic neonatal brain specimens have been tomographically reconstructed. We have now modified the existing instrumentation into a clinically relevant headband-based system to be used for optical imaging of structure in the neonatal brain at the bedside. Eight medical optical imaging studies in the neonatal intensive care unit were performed in a blinded clinical comparison of optical images with ultrasound, computed tomography, and magnetic resonance imaging. Optical images were interpreted as correct in six of eight cases, with one error attributed to the age of the clot, and one small clot not seen. In addition, one disagreement with ultrasound, not reported as an error, was found to be the result of a mislabeled ultrasound report rather than because of an inaccurate optical scan. Optical scan correlated well with computed tomography and magnetic resonance imaging findings in one patient. We conclude that light-based imaging using a portable time-of-flight system is feasible and represents an important new noninvasive diagnostic technique, with potential for continuous monitoring of critically ill neonates at risk for intraventricular hemorrhage or stroke. Further studies are now underway to further investigate the functional imaging capabilities of this new diagnostic tool.

Analysis of electrodes' placement and deformation in deep brain stimulation from medical images

NASA Astrophysics Data System (ADS)

Mehri, Maroua; Lalys, Florent; Maumet, Camille; Haegelen, Claire; Jannin, Pierre

2012-02-01

Deep brain stimulation (DBS) is used to reduce the motor symptoms such as rigidity or bradykinesia, in patients with Parkinson's disease (PD). The Subthalamic Nucleus (STN) has emerged as prime target of DBS in idiopathic PD. However, DBS surgery is a difficult procedure requiring the exact positioning of electrodes in the pre-operative selected targets. This positioning is usually planned using patients' pre-operative images, along with digital atlases, assuming that electrode's trajectory is linear. However, it has been demonstrated that anatomical brain deformations induce electrode's deformations resulting in errors in the intra-operative targeting stage. In order to meet the need of a higher degree of placement accuracy and to help constructing a computer-aided-placement tool, we studied the electrodes' deformation in regards to patients' clinical data (i.e., sex, mean PD duration and brain atrophy index). Firstly, we presented an automatic algorithm for the segmentation of electrode's axis from post-operative CT images, which aims to localize the electrodes' stimulated contacts. To assess our method, we applied our algorithm on 25 patients who had undergone bilateral STNDBS. We found a placement error of 0.91+/-0.38 mm. Then, from the segmented axis, we quantitatively analyzed the electrodes' curvature and correlated it with patients' clinical data. We found a positive significant correlation between mean curvature index of the electrode and brain atrophy index for male patients and between mean curvature index of the electrode and mean PD duration for female patients. These results help understanding DBS electrode' deformations and would help ensuring better anticipation of electrodes' placement.

Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity

PubMed Central

Bassett, Danielle S.; Khambhati, Ankit N.; Grafton, Scott T.

2018-01-01

Neuroengineering is faced with unique challenges in repairing or replacing complex neural systems that are composed of many interacting parts. These interactions form intricate patterns over large spatiotemporal scales and produce emergent behaviors that are difficult to predict from individual elements. Network science provides a particularly appropriate framework in which to study and intervene in such systems by treating neural elements (cells, volumes) as nodes in a graph and neural interactions (synapses, white matter tracts) as edges in that graph. Here, we review the emerging discipline of network neuroscience, which uses and develops tools from graph theory to better understand and manipulate neural systems from micro- to macroscales. We present examples of how human brain imaging data are being modeled with network analysis and underscore potential pitfalls. We then highlight current computational and theoretical frontiers and emphasize their utility in informing diagnosis and monitoring, brain–machine interfaces, and brain stimulation. A flexible and rapidly evolving enterprise, network neuroscience provides a set of powerful approaches and fundamental insights that are critical for the neuroengineer’s tool kit. PMID:28375650

On consciousness, resting state fMRI, and neurodynamics

PubMed Central

2010-01-01

Background During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively. Results The present work deals with a pluralistic approach to "consciousness'', where we connect theory and tools from three quite different disciplines: (1) philosophy of mind (emergentism and global workspace theory), (2) functional neuroimaging acquisitions, and (3) theory of deterministic and statistical neurodynamics – in particular the Wilson-Cowan model and stochastic resonance. Conclusions Based on recent experimental and theoretical work, we believe that the study of large-scale neuronal processes (activity fluctuations, state transitions) that goes on in the living human brain while examined with functional MRI during "resting state", can deepen our understanding of graded consciousness in a clinical setting, and clarify the concept of "consiousness" in neurocognitive and neurophilosophy research. PMID:20522270

Human brain regions involved in recognizing environmental sounds.

PubMed

Lewis, James W; Wightman, Frederic L; Brefczynski, Julie A; Phinney, Raymond E; Binder, Jeffrey R; DeYoe, Edgar A

2004-09-01

To identify the brain regions preferentially involved in environmental sound recognition (comprising portions of a putative auditory 'what' pathway), we collected functional imaging data while listeners attended to a wide range of sounds, including those produced by tools, animals, liquids and dropped objects. These recognizable sounds, in contrast to unrecognizable, temporally reversed control sounds, evoked activity in a distributed network of brain regions previously associated with semantic processing, located predominantly in the left hemisphere, but also included strong bilateral activity in posterior portions of the middle temporal gyri (pMTG). Comparisons with earlier studies suggest that these bilateral pMTG foci partially overlap cortex implicated in high-level visual processing of complex biological motion and recognition of tools and other artifacts. We propose that the pMTG foci process multimodal (or supramodal) information about objects and object-associated motion, and that this may represent 'action' knowledge that can be recruited for purposes of recognition of familiar environmental sound-sources. These data also provide a functional and anatomical explanation for the symptoms of pure auditory agnosia for environmental sounds reported in human lesion studies.

The Hidden Lives of Nurses’ Cognitive Artifacts

PubMed Central

Doig, Alexa K.; Cloyes, Kristin G.; Staggers, Nancy

2016-01-01

Summary Background Standardizing nursing handoffs at shift change is recommended to improve communication, with electronic tools as the primary approach. However, nurses continue to rely on personally created paper-based cognitive artifacts – their “paper brains” – to support handoffs, indicating a deficiency in available electronic versions. Objective The purpose of this qualitative study was to develop a deep understanding of nurses’ paper-based cognitive artifacts in the context of a cancer specialty hospital. Methods After completing 73 hours of hospital unit field observations, 13 medical oncology nurses were purposively sampled, shadowed for a single shift and interviewed using a semi-structured technique. An interpretive descriptive study design guided analysis of the data corpus of field notes, transcribed interviews, images of nurses’ paper-based cognitive artifacts, and analytic memos. Results Findings suggest nurses’ paper brains are personal, dynamic, living objects that undergo a life cycle during each shift and evolve over the course of a nurse’s career. The life cycle has four phases: Creation, Application, Reproduction, and Destruction. Evolution in a nurse’s individually styled, paper brain is triggered by a change in the nurse’s environment that reshapes cognitive needs. If a paper brain no longer provides cognitive support in the new environment, it is modified into (adapted) or abandoned (made extinct) for a different format that will provide the necessary support. Conclusions The “hidden lives“ – the life cycle and evolution – of paper brains have implications for the design of successful electronic tools to support nursing practice, including handoff. Nurses’ paper brains provide cognitive support beyond the context of handoff. Information retrieval during handoff is undoubtedly an important function of nurses’ paper brains, but tools designed to standardize handoff communication without accounting for cognitive needs during all phases of the paper brain life cycle or the ability to evolve with changes to those cognitive needs will be underutilized. PMID:27602412

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

Brain Imaging and Behavioral Outcome in Traumatic Brain Injury.

ERIC Educational Resources Information Center

Bigler, Erin D.

1996-01-01

This review explores the cellular pathology associated with traumatic brain injury (TBI) and its relation to neurobehavioral outcomes, the relationship of brain imaging findings to underlying pathology, brain imaging techniques, various image analysis procedures and how they relate to neuropsychological testing, and the importance of brain imaging…

Highly sensitive time-resolved thermography and multivariate image analysis of the cerebral cortex for intrasurgical diagnostics

NASA Astrophysics Data System (ADS)

Hollmach, Julia; Hoffmann, Nico; Schnabel, Christian; Küchler, Saskia; Sobottka, Stephan; Kirsch, Matthias; Schackert, Gabriele; Koch, Edmund; Steiner, Gerald

2013-03-01

Time-resolved thermography is a novel method to assess thermal variations and heterogeneities in tissue and blood. The recent generation of thermal cameras provides a sensitivity of less than mK. This high sensitivity in conjunction with non-invasive, label-free and radiation-free monitoring makes thermography a promising tool for intrasurgical diagnostics. In brain surgery, time-resolved thermography can be employed to distinguish between normal and anomalous tissue. In this study, we investigated and discussed the potential of time-resolved thermography in neurosurgery for the intraoperative detection and demarcation of tumor borders. Algorithms for segmentation, reduction of movement artifacts and image fusion were developed. The preprocessed image stacks were subjected to discrete wavelet transform to examine individual frequency components. K-means clustering was used for image evaluation to reveal similarities within the image sequence. The image evaluation shows significant differences for both types of tissue. Tumor and normal tissues have different time characteristics in heat production and transfer. Furthermore, tumor could be highlighted. These results demonstrate that time-resolved thermography is able to support the detection of tumors in a contactless manner without any side effects for the tissue. The intraoperative usage of time-resolved thermography improves the accuracy of tumor resections to prevent irreversible brain damage during surgery.

Geometry-aware multiscale image registration via OBBTree-based polyaffine log-demons.

PubMed

Seiler, Christof; Pennec, Xavier; Reyes, Mauricio

2011-01-01

Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

Coordination Chemistry of Bifunctional Chemical Agents Designed for Applications in 64Cu PET Imaging for Alzheimer's Disease.

PubMed

Sharma, Anuj K; Schultz, Jason W; Prior, John T; Rath, Nigam P; Mirica, Liviu M

2017-11-20

Positron emission tomography (PET) is emerging as one of the most important diagnostic tools for brain imaging, yet the most commonly used radioisotopes in PET imaging, 11 C and 18 F, have short half-lives, and their usage is thus somewhat limited. By comparison, the 64 Cu radionuclide has a half-life of 12.7 h, which is ideal for administering and imaging purposes. In spite of appreciable research efforts, high-affinity copper chelators suitable for brain imaging applications are still lacking. Herein, we present the synthesis and characterization of a series of bifunctional compounds (BFCs) based on macrocyclic 1,4,7-triazacyclononane and 2,11-diaza[3.3](2,6)pyridinophane ligand frameworks that exhibit a high affinity for Cu 2+ ions. In addition, these BFCs contain a 2-phenylbenzothiazole fragment that is known to interact tightly with amyloid β fibrillar aggregates. Determination of the protonation constants (pK a values) and stability constants (log β values) of these BFCs, as well as characterization of the isolated copper complexes using X-ray crystallography, electron paramagnetic resonance spectroscopy, and electrochemical studies, suggests that these BFCs exhibit desirable properties for the development of novel 64 Cu PET imaging agents for Alzheimer's disease.

Introducing the depth transfer curve for 3D capture system characterization

NASA Astrophysics Data System (ADS)

Goma, Sergio R.; Atanassov, Kalin; Ramachandra, Vikas

2011-03-01

3D technology has recently made a transition from movie theaters to consumer electronic devices such as 3D cameras and camcorders. In addition to what 2D imaging conveys, 3D content also contains information regarding the scene depth. Scene depth is simulated through the strongest brain depth cue, namely retinal disparity. This can be achieved by capturing an image by horizontally separated cameras. Objects at different depths will be projected with different horizontal displacement on the left and right camera images. These images, when fed separately to either eye, leads to retinal disparity. Since the perception of depth is the single most important 3D imaging capability, an evaluation procedure is needed to quantify the depth capture characteristics. Evaluating depth capture characteristics subjectively is a very difficult task since the intended and/or unintended side effects from 3D image fusion (depth interpretation) by the brain are not immediately perceived by the observer, nor do such effects lend themselves easily to objective quantification. Objective evaluation of 3D camera depth characteristics is an important tool that can be used for "black box" characterization of 3D cameras. In this paper we propose a methodology to evaluate the 3D cameras' depth capture capabilities.

High-resolution, high-throughput imaging with a multibeam scanning electron microscope

PubMed Central

EBERLE, AL; MIKULA, S; SCHALEK, R; LICHTMAN, J; TATE, ML KNOTHE; ZEIDLER, D

2015-01-01

Electron–electron interactions and detector bandwidth limit the maximal imaging speed of single-beam scanning electron microscopes. We use multiple electron beams in a single column and detect secondary electrons in parallel to increase the imaging speed by close to two orders of magnitude and demonstrate imaging for a variety of samples ranging from biological brain tissue to semiconductor wafers. Lay Description The composition of our world and our bodies on the very small scale has always fascinated people, making them search for ways to make this visible to the human eye. Where light microscopes reach their resolution limit at a certain magnification, electron microscopes can go beyond. But their capability of visualizing extremely small features comes at the cost of a very small field of view. Some of the questions researchers seek to answer today deal with the ultrafine structure of brains, bones or computer chips. Capturing these objects with electron microscopes takes a lot of time – maybe even exceeding the time span of a human being – or new tools that do the job much faster. A new type of scanning electron microscope scans with 61 electron beams in parallel, acquiring 61 adjacent images of the sample at the same time a conventional scanning electron microscope captures one of these images. In principle, the multibeam scanning electron microscope’s field of view is 61 times larger and therefore coverage of the sample surface can be accomplished in less time. This enables researchers to think about large-scale projects, for example in the rather new field of connectomics. A very good introduction to imaging a brain at nanometre resolution can be found within course material from Harvard University on http://www.mcb80x.org/# as featured media entitled ‘connectomics’. PMID:25627873

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.

A novel framework for the local extraction of extra-axial cerebrospinal fluid from MR brain images

NASA Astrophysics Data System (ADS)

Mostapha, Mahmoud; Shen, Mark D.; Kim, SunHyung; Swanson, Meghan; Collins, D. Louis; Fonov, Vladimir; Gerig, Guido; Piven, Joseph; Styner, Martin A.

2018-03-01

The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain developmental. Extr a-axial fluid (EA-CSF), which is characterized by the CSF in the subarachnoid space, is promising in the early detection of children at risk for neurodevelopmental disorders. Currently, though, there is no tool to extract local EA-CSF measurements in a way that is suitable for localized analysis. In this paper, we propose a novel framework for the localized, cortical surface based analysis of EA-CSF. In our proposed processing, we combine probabilistic brain tissue segmentation, cortical surface reconstruction as well as streamline based local EA-CSF quantification. For streamline computation, we employ the vector field generated by solving a Laplacian partial differential equation (PDE) between the cortical surface and the outer CSF hull. To achieve sub-voxel accuracy while minimizing numerical errors, fourth-order Runge-Kutta (RK4) integration was used to generate the streamlines. Finally, the local EA-CSF is computed by integrating the CSF probability along the generated streamlines. The proposed local EA-CSF extraction tool was used to study the early postnatal brain development in typically developing infants. The results show that the proposed localized EA-CSF extraction pipeline can produce statistically significant regions that are not observed in previous global approach.

Development of three-dimensional brain arteriovenous malformation model for patient communication and young neurosurgeon education.

PubMed

Dong, Mengqi; Chen, Guangzhong; Qin, Kun; Ding, Xiaowen; Zhou, Dong; Peng, Chao; Zeng, Shaojian; Deng, Xianming

2018-01-15

Rapid prototyping technology is used to fabricate three-dimensional (3D) brain arteriovenous malformation (AVM) models and facilitate presurgical patient communication and medical education for young surgeons. Two intracranial AVM cases were selected for this study. Using 3D CT angiography or 3D rotational angiography images, the brain AVM models were reconstructed on personal computer and the rapid prototyping process was completed using a 3D printer. The size and morphology of the models were compared to brain digital subtraction arteriography of the same patients. 3D brain AVM models were used for preoperative patient communication and young neurosurgeon education. Two brain AVM models were successfully produced. By neurosurgeons' evaluation, the printed models have high fidelity with the actual brain AVM structures of the patients. The patient responded positively toward the brain AVM model specific to himself. Twenty surgical residents from residency programs tested the brain AVM models and provided positive feedback on their usefulness as educational tool and resemblance to real brain AVM structures. Patient-specific 3D printed models of brain AVM can be constructed with high fidelity. 3D printed brain AVM models are proved to be helpful in preoperative patient consultation, surgical planning and resident training.