Functional Connectivity Associated with Acoustic Stability During Vowel Production: Implications for Vocal-Motor Control

PubMed Central

2015-01-01

Abstract Vowels provide the acoustic foundation of communication through speech and song, but little is known about how the brain orchestrates their production. Positron emission tomography was used to study regional cerebral blood flow (rCBF) during sustained production of the vowel /a/. Acoustic and blood flow data from 13, normal, right-handed, native speakers of American English were analyzed to identify CBF patterns that predicted the stability of the first and second formants of this vowel. Formants are bands of resonance frequencies that provide vowel identity and contribute to voice quality. The results indicated that formant stability was directly associated with blood flow increases and decreases in both left- and right-sided brain regions. Secondary brain regions (those associated with the regions predicting formant stability) were more likely to have an indirect negative relationship with first formant variability, but an indirect positive relationship with second formant variability. These results are not definitive maps of vowel production, but they do suggest that the level of motor control necessary to produce stable vowels is reflected in the complexity of an underlying neural system. These results also extend a systems approach to functional image analysis, previously applied to normal and ataxic speech rate that is solely based on identifying patterns of brain activity associated with specific performance measures. Understanding the complex relationships between multiple brain regions and the acoustic characteristics of vocal stability may provide insight into the pathophysiology of the dysarthrias, vocal disorders, and other speech changes in neurological and psychiatric disorders. PMID:25295385

Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool.

PubMed

Liang, Zifei; He, Xiaohai; Ceritoglu, Can; Tang, Xiaoying; Li, Yue; Kutten, Kwame S; Oishi, Kenichi; Miller, Michael I; Mori, Susumu; Faria, Andreia V

2015-01-01

Brain parcellation tools based on multiple-atlas algorithms have recently emerged as a promising method with which to accurately define brain structures. When dealing with data from various sources, it is crucial that these tools are robust for many different imaging protocols. In this study, we tested the robustness of a multiple-atlas, likelihood fusion algorithm using Alzheimer's Disease Neuroimaging Initiative (ADNI) data with six different protocols, comprising three manufacturers and two magnetic field strengths. The entire brain was parceled into five different levels of granularity. In each level, which defines a set of brain structures, ranging from eight to 286 regions, we evaluated the variability of brain volumes related to the protocol, age, and diagnosis (healthy or Alzheimer's disease). Our results indicated that, with proper pre-processing steps, the impact of different protocols is minor compared to biological effects, such as age and pathology. A precise knowledge of the sources of data variation enables sufficient statistical power and ensures the reliability of an anatomical analysis when using this automated brain parcellation tool on datasets from various imaging protocols, such as clinical databases.

Whole-brain grey matter density predicts balance stability irrespective of age and protects older adults from falling.

PubMed

Boisgontier, Matthieu P; Cheval, Boris; van Ruitenbeek, Peter; Levin, Oron; Renaud, Olivier; Chanal, Julien; Swinnen, Stephan P

2016-03-01

Functional and structural imaging studies have demonstrated the involvement of the brain in balance control. Nevertheless, how decisive grey matter density and white matter microstructural organisation are in predicting balance stability, and especially when linked to the effects of ageing, remains unclear. Standing balance was tested on a platform moving at different frequencies and amplitudes in 30 young and 30 older adults, with eyes open and with eyes closed. Centre of pressure variance was used as an indicator of balance instability. The mean density of grey matter and mean white matter microstructural organisation were measured using voxel-based morphometry and diffusion tensor imaging, respectively. Mixed-effects models were built to analyse the extent to which age, grey matter density, and white matter microstructural organisation predicted balance instability. Results showed that both grey matter density and age independently predicted balance instability. These predictions were reinforced when the level of difficulty of the conditions increased. Furthermore, grey matter predicted balance instability beyond age and at least as consistently as age across conditions. In other words, for balance stability, the level of whole-brain grey matter density is at least as decisive as being young or old. Finally, brain grey matter appeared to be protective against falls in older adults as age increased the probability of losing balance in older adults with low, but not moderate or high grey matter density. No such results were observed for white matter microstructural organisation, thereby reinforcing the specificity of our grey matter findings. Copyright © 2016 Elsevier B.V. All rights reserved.

Inter-subject FDG PET Brain Networks Exhibit Multi-scale Community Structure with Different Normalization Techniques.

PubMed

Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A

2018-07-01

Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p < 0.00001); however, community structure is similar at network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.

Targeted Imaging and Chemo-Phototherapy of Brain Cancer by a Multifunctional Drug Delivery System.

PubMed

Hao, Yongwei; Wang, Lei; Zhao, Yalin; Meng, Dehui; Li, Dong; Li, Haixia; Zhang, Bingxiang; Shi, Jinjin; Zhang, Hongling; Zhang, Zhenzhong; Zhang, Yun

2015-11-01

The aim of this study was to develop multifunctional poly lactide-co-glycolide (PLGA) nanoparticles with the ability to simultaneously deliver indocyanine green (ICG) and docetaxel (DTX) to the brain by surface decoration with the brain-targeting peptide angiopep-2 to achieve combined chemo-phototherapy for glioma under near-infrared (NIR) imaging. ICG was selected as a near-infrared imaging and phototherapy agent and DTX was employed as a chemotherapeutic agent. ICG and DTX were simultaneously incorporated into PLGA nanoparticles with higher stability. These nanoparticles were further decorated with angiopep-2 via the outer maleimide group of 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethyleneglycol)-2000]-maleinimide incorporated in the nanoparticles. The NIR image-guided chemo-phototherapy of the angiopep-2 modified PLGA/DTX/ICG nanoparticles (ANG/PLGA/DTX/ICG NPs) not only highly induced U87MG cell death in vitro, but also efficiently prolonged the life span of the brain orthotopic U87MG glioma xenograft-bearing mice in vivo. Thus, this study suggests that ANG/PLGA/DTX/ICG NPs have the potential for combinatorial chemotherapy and phototherapy for glioma. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design, Synthesis, and Preliminary Evaluation of SPECT Probes for Imaging β-Amyloid in Alzheimer's Disease Affected Brain.

PubMed

Okumura, Yuki; Maya, Yoshifumi; Onishi, Takako; Shoyama, Yoshinari; Izawa, Akihiro; Nakamura, Daisaku; Tanifuji, Shigeyuki; Tanaka, Akihiro; Arano, Yasushi; Matsumoto, Hiroki

2018-04-06

In this study, we synthesized of a series of 2-phenyl- and 2-pyridyl-imidazo[1,2- a]pyridine derivatives and examine their suitability as novel probes for single-photon emission computed tomography (SPECT)-based imaging of β-amyloid (Aβ). Among the 11 evaluated compounds, 10 showed moderate affinity to Aβ(1-42) aggregates, exhibiting half-maximal inhibitory concentrations (IC 50 ) of 14.7 ± 6.07-87.6 ± 39.8 nM. In vitro autoradiography indicated that 123 I-labeled triazole-substituted derivatives displayed highly selective binding to Aβ plaques in the hippocampal region of Alzheimer's disease (AD)-affected brain. Moreover, biodistribution studies performed on normal rats demonstrated that all 123 I-labeled probes featured high initial uptake into the brain followed by a rapid washout and were thus well suited for imaging Aβ plaques, with the highest selectivity observed for a 1 H-1,2,3-triazole-substituted 2-pyridyl-imidazopyridine derivative, [ 123 I]ABC577. This compound showed good kinetics in rat brain as well as moderate in vivo stability in rats and is thus a promising SPECT imaging probe for AD in clinical settings.

Using Copula Distributions to Support More Accurate Imaging-Based Diagnostic Classifiers for Neuropsychiatric Disorders

PubMed Central

Bansal, Ravi; Hao, Xuejun; Liu, Jun; Peterson, Bradley S.

2014-01-01

Many investigators have tried to apply machine learning techniques to magnetic resonance images (MRIs) of the brain in order to diagnose neuropsychiatric disorders. Usually the number of brain imaging measures (such as measures of cortical thickness and measures of local surface morphology) derived from the MRIs (i.e., their dimensionality) has been large (e.g. >10) relative to the number of participants who provide the MRI data (<100). Sparse data in a high dimensional space increases the variability of the classification rules that machine learning algorithms generate, thereby limiting the validity, reproducibility, and generalizability of those classifiers. The accuracy and stability of the classifiers can improve significantly if the multivariate distributions of the imaging measures can be estimated accurately. To accurately estimate the multivariate distributions using sparse data, we propose to estimate first the univariate distributions of imaging data and then combine them using a Copula to generate more accurate estimates of their multivariate distributions. We then sample the estimated Copula distributions to generate dense sets of imaging measures and use those measures to train classifiers. We hypothesize that the dense sets of brain imaging measures will generate classifiers that are stable to variations in brain imaging measures, thereby improving the reproducibility, validity, and generalizability of diagnostic classification algorithms in imaging datasets from clinical populations. In our experiments, we used both computer-generated and real-world brain imaging datasets to assess the accuracy of multivariate Copula distributions in estimating the corresponding multivariate distributions of real-world imaging data. Our experiments showed that diagnostic classifiers generated using imaging measures sampled from the Copula were significantly more accurate and more reproducible than were the classifiers generated using either the real-world imaging measures or their multivariate Gaussian distributions. Thus, our findings demonstrate that estimated multivariate Copula distributions can generate dense sets of brain imaging measures that can in turn be used to train classifiers, and those classifiers are significantly more accurate and more reproducible than are those generated using real-world imaging measures alone. PMID:25093634

Normal gray and white matter volume after weight restoration in adolescents with anorexia nervosa.

PubMed

Lázaro, Luisa; Andrés, Susana; Calvo, Anna; Cullell, Clàudia; Moreno, Elena; Plana, M Teresa; Falcón, Carles; Bargalló, Núria; Castro-Fornieles, Josefina

2013-12-01

The aim of this study was to determine whether treated, weight-stabilized adolescents with anorexia nervosa (AN) present brain volume differences in comparison with healthy controls. Thirty-five adolescents with weight-recovered AN and 17 healthy controls were assessed by means of psychopathology scales and magnetic resonance imaging. Axial three-dimensional T1-weighted images were obtained in a 1.5 Tesla scanner and analyzed using optimized voxel-based morphometry (VBM). There were no significant differences between controls and weight-stabilized AN patients with regard to global volumes of either gray or white brain matter, or in the regional VBM study. Differences were not significant between patients with psychopharmacological treatment and without, between those with amenorrhea and without, as well as between patients with restrictive versus purgative AN. The present findings reveal no global or regional gray or white matter abnormalities in this sample of adolescents following weight restoration. Copyright © 2013 Wiley Periodicals, Inc.

Assessing the feasibility of time-resolved fNIRS to detect brain activity during motor imagery

NASA Astrophysics Data System (ADS)

Abdalmalak, Androu; Milej, Daniel; Diop, Mamadou; Naci, Lorina; Owen, Adrian M.; St. Lawrence, Keith

2016-03-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical technique for detecting brain activity, which has been previously used during motor and motor executive tasks. There is an increasing interest in using fNIRS as a brain computer interface (BCI) for patients who lack the physical, but not the mental, ability to respond to commands. The goal of this study is to assess the feasibility of time-resolved fNIRS to detect brain activity during motor imagery. Stability tests were conducted to ensure the temporal stability of the signal, and motor imagery data were acquired on healthy subjects. The NIRS probes were placed on the scalp over the premotor cortex (PMC) and supplementary motor area (SMA), as these areas are responsible for motion planning. To confirm the fNIRS results, subjects underwent functional magnetic resonance imaging (fMRI) while performing the same task. Seven subjects have participated to date, and significant activation in the SMA and/or the PMC during motor imagery was detected by both fMRI and fNIRS in 4 of the 7 subjects. No activation was detected by either technique in the remaining three participants, which was not unexpected due to the nature of the task. The agreement between the two imaging modalities highlights the potential of fNIRS as a BCI, which could be adapted for bedside studies of patients with disorders of consciousness.

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

Hematopoietic Stem Cell Transplantation in Late-Onset Krabbe Disease: No Evidence of Worsening Demyelination and Axonal Loss 4 Years Post-allograft.

PubMed

Laule, Cornelia; Vavasour, Irene M; Shahinfard, Elham; Mädler, Burkhard; Zhang, Jing; Li, David K B; MacKay, Alex L; Sirrs, Sandra M

2018-05-01

Late-onset adult Krabbe disease is a very rare demyelinating leukodystrophy, affecting less than 1 in a million people. Hematopoietic stem cell transplantation (HSCT) strategies can stop the accumulation of toxic metabolites that damage myelin-producing cells. We used quantitative advanced imaging metrics to longitudinally assess the impact of HSCT on brain abnormalities in adult-onset Krabbe disease. A 42-year-old female with late-onset Krabbe disease and an age/sex-matched healthy control underwent annual 3T MRI (baseline was immediately prior to HSCT for the Krabbe subject). Imaging included conventional scans, myelin water imaging, diffusion tensor imaging, and magnetic resonance spectroscopy. Brain abnormalities far beyond those visible on conventional imaging were detected, suggesting a global pathological process occurs in Krabbe disease with adult-onset etiology, with myelin being more affected than axons, and evidence of wide-spread gliosis. After HSCT, our patient showed clinical stability in all measures, as well as improvement in gait, dysarthria, and pseudobulbar affect at 7.5 years post-transplant. No MRI evidence of worsening demyelination and axonal loss was observed up to 4 years post-allograft. Clinical evidence and stability of advanced MR measures related to myelin and axons supports HSCT as an effective treatment strategy for stopping progression associated with late-onset Krabbe disease. Copyright © 2018 by the American Society of Neuroimaging.

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

Paliwal, B; Asprey, W; Yan, Y

Purpose: In order to take advantage of the high resolution soft tissue imaging available in MR images, we investigated 3D images obtained with the low field 0.35 T MR in ViewRay to serve as an alternative to CT scans for radiotherapy treatment planning. In these images, normal and target structure delineation can be visualized. Assessment is based upon comparison with the CT images and the ability to produce comparable contours. Methods: Routine radiation oncology CT scans were acquired on five patients. Contours of brain, brainstem, esophagus, heart, lungs, spinal cord, and the external body were drawn. The same five patientsmore » were then scanned on the ViewRay TrueFISP-based imaging pulse sequence. The same organs were selected on the MR images and compared to those from the CT scan. Physical volume and the Dice Similarity Coefficient (DSC) were used to assess the contours from the two systems. Image quality stability was quantitatively ensured throughout the study following the recommendations of the ACR MR accreditation procedure. Results: The highest DSC of 0.985, 0.863, and 0.843 were observed for brain, lungs, and heart respectively. On the other hand, the brainstem, spinal cord, and esophagus had the lowest DSC. Volume agreement was most satisfied for the heart (within 5%) and the brain (within 2%). Contour volume for the brainstem and lung (a widely dynamic organ) varied the most (27% and 19%). Conclusion: The DSC and volume measurements suggest that the results obtained from ViewRay images are quantitatively consistent and comparable to those obtained from CT scans for the brain, heart, and lungs. MR images from ViewRay are well-suited for treatment planning and for adaptive MRI-guided radiotherapy. The physical data from 0.35 T MR imaging is consistent with our geometrical understanding of normal structures.« less

Ultrasound-mediated delivery and distribution of polymeric nanoparticles in the normal brain parenchyma of a metastatic brain tumour model

PubMed Central

Baghirov, Habib; Snipstad, Sofie; Sulheim, Einar; Berg, Sigrid; Hansen, Rune; Thorsen, Frits; Mørch, Yrr; Åslund, Andreas K. O.

2018-01-01

The treatment of brain diseases is hindered by the blood-brain barrier (BBB) preventing most drugs from entering the brain. Focused ultrasound (FUS) with microbubbles can open the BBB safely and reversibly. Systemic drug injection might induce toxicity, but encapsulation into nanoparticles reduces accumulation in normal tissue. Here we used a novel platform based on poly(2-ethyl-butyl cyanoacrylate) nanoparticle-stabilized microbubbles to permeabilize the BBB in a melanoma brain metastasis model. With a dual-frequency ultrasound transducer generating FUS at 1.1 MHz and 7.8 MHz, we opened the BBB using nanoparticle-microbubbles and low-frequency FUS, and applied high-frequency FUS to generate acoustic radiation force and push nanoparticles through the extracellular matrix. Using confocal microscopy and image analysis, we quantified nanoparticle extravasation and distribution in the brain parenchyma. We also evaluated haemorrhage, as well as the expression of P-glycoprotein, a key BBB component. FUS and microbubbles distributed nanoparticles in the brain parenchyma, and the distribution depended on the extent of BBB opening. The results from acoustic radiation force were not conclusive, but in a few animals some effect could be detected. P-glycoprotein was not significantly altered immediately after sonication. In summary, FUS with our nanoparticle-stabilized microbubbles can achieve accumulation and displacement of nanoparticles in the brain parenchyma. PMID:29338016

Investigation of lithium distribution in the rat brain ex vivo using lithium-7 magnetic resonance spectroscopy and imaging at 17.2 T.

PubMed

Stout, Jacques; Hanak, Anne-Sophie; Chevillard, Lucie; Djemaï, Boucif; Risède, Patricia; Giacomini, Eric; Poupon, Joël; Barrière, David André; Bellivier, Frank; Mégarbane, Bruno; Boumezbeur, Fawzi

2017-11-01

Lithium is the first-line mood stabilizer for the treatment of patients with bipolar disorder. However, its mechanisms of action and transport across the blood-brain barrier remain poorly understood. The contribution of lithium-7 magnetic resonance imaging ( 7 Li MRI) to investigate brain lithium distribution remains limited because of the modest sensitivity of the lithium nucleus and the expected low brain concentrations in humans and animal models. Therefore, we decided to image lithium distribution in the rat brain ex vivo using a turbo-spin-echo imaging sequence at 17.2 T. The estimation of lithium concentrations was performed using a phantom replacement approach accounting for B 1 inhomogeneities and differential T 1 and T 2 weighting. Our MRI-derived lithium concentrations were validated by comparison with inductively coupled plasma-mass spectrometry (ICP-MS) measurements ([Li] MRI  = 1.18[Li] MS , R = 0.95). Overall, a sensitivity of 0.03 mmol/L was achieved for a spatial resolution of 16 μL. Lithium distribution was uneven throughout the brain (normalized lithium content ranged from 0.4 to 1.4) and was mostly symmetrical, with consistently lower concentrations in the metencephalon (cerebellum and brainstem) and higher concentrations in the cortex. Interestingly, low lithium concentrations were also observed close to the lateral ventricles. The average brain-to-plasma lithium ratio was 0.34 ± 0.04, ranging from 0.29 to 0.39. Brain lithium concentrations were reasonably correlated with plasma lithium concentrations, with Pearson correlation factors ranging from 0.63 to 0.90. Copyright © 2017 John Wiley & Sons, Ltd.

Snapshot gradient-recalled echo-planar images of rat brains at long echo time at 9.4 T

PubMed Central

Lei, Hongxia; Mlynárik, Vladimir; Just, Nathalie; Gruetter, Rolf

2009-01-01

With improved B0 homogeneity along with satisfactory gradient performance at high magnetic fields, snapshot gradient-recalled echo-planar imaging (GRE-EPI) would perform at long echo times (TEs) on the order of T2*, which intrinsically allows obtaining strongly T2*-weighted images with embedded substantial anatomical details in ultrashort time. The aim of this study was to investigate the feasibility and quality of long TE snapshot GRE-EPI images of rat brain at 9.4 T. When compensating for B0 inhomogeneities, especially second-order shim terms, a 200×200 μm2 in-plane resolution image was reproducibly obtained at long TE (>25 ms). The resulting coronal images at 30 ms had diminished geometric distortions and, thus, embedded substantial anatomical details. Concurrently with the very consistent stability, such GRE-EPI images should permit to resolve functional data not only with high specificity but also with substantial anatomical details, therefore allowing coregistration of the acquired functional data on the same image data set. PMID:18486393

Beta activity in the premotor cortex is increased during stabilized as compared to normal walking

PubMed Central

Bruijn, Sjoerd M.; Van Dieën, Jaap H.; Daffertshofer, Andreas

2015-01-01

Walking on two legs is inherently unstable. Still, we humans perform remarkable well at it, mostly without falling. To gain more understanding of the role of the brain in controlling gait stability we measured brain activity using electro-encephalography (EEG) during stabilized and normal walking. Subjects walked on a treadmill in two conditions, each lasting 10 min; normal, and while being laterally stabilized by elastic cords. Kinematics of trunk and feet, electro-myography (EMG) of neck muscles, as well as 64-channel EEG were recorded. To assess gait stability the local divergence exponent, step width, and trunk range of motion were calculated from the kinematic data. We used independent component (IC) analysis to remove movement, EMG, and eyeblink artifacts from the EEG, after which dynamic imaging of coherent sources beamformers were determined to identify cortical sources that showed a significant difference between conditions. Stabilized walking led to a significant increase in gait stability, i.e., lower local divergence exponents. Beamforming analysis of the beta band activity revealed significant sources in bilateral pre-motor cortices. Projection of sensor data on these sources showed a significant difference only in the left premotor area, with higher beta power during stabilized walking, specifically around push-off, although only significant around contralateral push-off. It appears that even during steady gait the cortex is involved in the control of stability. PMID:26578937

Atypical inter-hemispheric communication correlates with altered motor inhibition during learning of a new bimanual coordination pattern in developmental coordination disorder.

PubMed

Blais, Mélody; Amarantini, David; Albaret, Jean-Michel; Chaix, Yves; Tallet, Jessica

2018-05-01

Impairment of motor learning skills in developmental coordination disorder (DCD) has been reported in several studies. Some hypotheses on neural mechanisms of motor learning deficits in DCD have emerged but, to date, brain-imaging investigations are scarce. The aim of the present study is to assess possible changes in communication between brain areas during practice of a new bimanual coordination task in teenagers with DCD (n = 10) compared to matched controls (n = 10). Accuracy, stability and number of mirror movements were computed as behavioural variables. Neural variables were assessed by electroencephalographic coherence analyses of intra-hemispheric and inter-hemispheric fronto-central electrodes. In both groups, accuracy of the new coordination increased concomitantly with right intra-hemispheric fronto-central coherence. Compared to typically developing teenagers, DCD teenagers presented learning difficulties expressed by less stability, no stabilization of the new coordination and a greater number of mirror movements despite practice. These measures correlated with reduced inter-hemispheric communication, even after practice of the new coordination. For the first time, these findings provide neuro-imaging evidence of a kind of inter-hemispheric 'disconnection' related to altered inhibition of mirror movements during motor learning in DCD. © 2017 John Wiley & Sons Ltd.

MONSTIR II: A 32-channel, multispectral, time-resolved optical tomography system for neonatal brain imaging

NASA Astrophysics Data System (ADS)

Cooper, Robert J.; Magee, Elliott; Everdell, Nick; Magazov, Salavat; Varela, Marta; Airantzis, Dimitrios; Gibson, Adam P.; Hebden, Jeremy C.

2014-05-01

We detail the design, construction and performance of the second generation UCL time-resolved optical tomography system, known as MONSTIR II. Intended primarily for the study of the newborn brain, the system employs 32 source fibres that sequentially transmit picosecond pulses of light at any four wavelengths between 650 and 900 nm. The 32 detector channels each contain an independent photo-multiplier tube and temporally correlated photon-counting electronics that allow the photon transit time between each source and each detector position to be measured with high temporal resolution. The system's response time, temporal stability, cross-talk, and spectral characteristics are reported. The efficacy of MONSTIR II is demonstrated by performing multi-spectral imaging of a simple phantom.

A simple one-step method to prepare fluorescent carbon dots and their potential application in non-invasive glioma imaging

NASA Astrophysics Data System (ADS)

Ruan, Shaobo; Qian, Jun; Shen, Shun; Zhu, Jianhua; Jiang, Xinguo; He, Qin; Gao, Huile

2014-08-01

Fluorescent carbon dots (CD) possess impressive potential in bioimaging because of their low photobleaching, absence of optical blinking and good biocompatibility. However, their relatively short excitation/emission wavelengths restrict their application in in vivo imaging. In the present study, a kind of CD was prepared by a simple heat treatment method using glycine as the only precursor. The diameter of CD was lower than 5 nm, and the highest emission wavelength was 500 nm. However, at 600 nm, there was still a relatively strong fluorescent emission, suggesting CD could be used for in vivo imaging. Additionally, several experiments demonstrated that CD possessed good serum stability and low cytotoxicity. In vitro, CD could be taken up into C6 glioma cells in a time- and concentration-dependent manner, with both endosomes and mitochondria involved. In vivo, CD could be used for non-invasive glioma imaging because of its high accumulation in the glioma site of the brain, which was demonstrated by both in vivo imaging and ex vivo tissue imaging. Furthermore, the fluorescent distribution in tissue slices also showed CD distributed in glioma with high intensity, while with a low intensity in normal brain tissue. In conclusion, CD were prepared using a simple method with relatively long excitation and emission wavelengths and could be used for non-invasive glioma imaging.Fluorescent carbon dots (CD) possess impressive potential in bioimaging because of their low photobleaching, absence of optical blinking and good biocompatibility. However, their relatively short excitation/emission wavelengths restrict their application in in vivo imaging. In the present study, a kind of CD was prepared by a simple heat treatment method using glycine as the only precursor. The diameter of CD was lower than 5 nm, and the highest emission wavelength was 500 nm. However, at 600 nm, there was still a relatively strong fluorescent emission, suggesting CD could be used for in vivo imaging. Additionally, several experiments demonstrated that CD possessed good serum stability and low cytotoxicity. In vitro, CD could be taken up into C6 glioma cells in a time- and concentration-dependent manner, with both endosomes and mitochondria involved. In vivo, CD could be used for non-invasive glioma imaging because of its high accumulation in the glioma site of the brain, which was demonstrated by both in vivo imaging and ex vivo tissue imaging. Furthermore, the fluorescent distribution in tissue slices also showed CD distributed in glioma with high intensity, while with a low intensity in normal brain tissue. In conclusion, CD were prepared using a simple method with relatively long excitation and emission wavelengths and could be used for non-invasive glioma imaging. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr02657h

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

PubMed Central

Fransson, Peter

2016-01-01

Abstract Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed. PMID:27784176

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

PubMed

Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Filopodial dynamics and growth cone stabilization in Drosophila visual circuit development

PubMed Central

Özel, Mehmet Neset; Langen, Marion; Hassan, Bassem A; Hiesinger, P Robin

2015-01-01

Filopodial dynamics are thought to control growth cone guidance, but the types and roles of growth cone dynamics underlying neural circuit assembly in a living brain are largely unknown. To address this issue, we have developed long-term, continuous, fast and high-resolution imaging of growth cone dynamics from axon growth to synapse formation in cultured Drosophila brains. Using R7 photoreceptor neurons as a model we show that >90% of the growth cone filopodia exhibit fast, stochastic dynamics that persist despite ongoing stepwise layer formation. Correspondingly, R7 growth cones stabilize early and change their final position by passive dislocation. N-Cadherin controls both fast filopodial dynamics and growth cone stabilization. Surprisingly, loss of N-Cadherin causes no primary targeting defects, but destabilizes R7 growth cones to jump between correct and incorrect layers. Hence, growth cone dynamics can influence wiring specificity without a direct role in target recognition and implement simple rules during circuit assembly. DOI: http://dx.doi.org/10.7554/eLife.10721.001 PMID:26512889

Stability of whole brain and regional network topology within and between resting and cognitive states.

PubMed

Rzucidlo, Justyna K; Roseman, Paige L; Laurienti, Paul J; Dagenbach, Dale

2013-01-01

Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI) data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well. fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state. These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

PubMed Central

Savalia, Neil K.; Agres, Phillip F.; Chan, Micaela Y.; Feczko, Eric J.; Kennedy, Kristen M.

2016-01-01

Abstract Motion‐contaminated T1‐weighted (T1w) magnetic resonance imaging (MRI) results in misestimates of brain structure. Because conventional T1w scans are not collected with direct measures of head motion, a practical alternative is needed to identify potential motion‐induced bias in measures of brain anatomy. Head movements during functional MRI (fMRI) scanning of 266 healthy adults (20–89 years) were analyzed to reveal stable features of in‐scanner head motion. The magnitude of head motion increased with age and exhibited within‐participant stability across different fMRI scans. fMRI head motion was then related to measurements of both quality control (QC) and brain anatomy derived from a T1w structural image from the same scan session. A procedure was adopted to “flag” individuals exhibiting excessive head movement during fMRI or poor T1w quality rating. The flagging procedure reliably reduced the influence of head motion on estimates of gray matter thickness across the cortical surface. Moreover, T1w images from flagged participants exhibited reduced estimates of gray matter thickness and volume in comparison to age‐ and gender‐matched samples, resulting in inflated effect sizes in the relationships between regional anatomical measures and age. Gray matter thickness differences were noted in numerous regions previously reported to undergo prominent atrophy with age. Recommendations are provided for mitigating this potential confound, and highlight how the procedure may lead to more accurate measurement and comparison of anatomical features. Hum Brain Mapp 38:472–492, 2017. © 2016 Wiley Periodicals, Inc. PMID:27634551

Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes

PubMed Central

Bansal, Arjun K.; Singer, Jedediah M.; Anderson, William S.; Golby, Alexandra; Madsen, Joseph R.

2012-01-01

The cerebral cortex needs to maintain information for long time periods while at the same time being capable of learning and adapting to changes. The degree of stability of physiological signals in the human brain in response to external stimuli over temporal scales spanning hours to days remains unclear. Here, we quantitatively assessed the stability across sessions of visually selective intracranial field potentials (IFPs) elicited by brief flashes of visual stimuli presented to 27 subjects. The interval between sessions ranged from hours to multiple days. We considered electrodes that showed robust visual selectivity to different shapes; these electrodes were typically located in the inferior occipital gyrus, the inferior temporal cortex, and the fusiform gyrus. We found that IFP responses showed a strong degree of stability across sessions. This stability was evident in averaged responses as well as single-trial decoding analyses, at the image exemplar level as well as at the category level, across different parts of visual cortex, and for three different visual recognition tasks. These results establish a quantitative evaluation of the degree of stationarity of visually selective IFP responses within and across sessions and provide a baseline for studies of cortical plasticity and for the development of brain-machine interfaces. PMID:22956795

Development and characterisation of a brain tumour mimicking protoporphyrin IX fluorescence phantom (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xie, Yijing; Tisca, Cristiana; Peveler, William; Noimark, Sacha; Desjardins, Adrien E.; Parkin, Ivan P.; Ourselin, Sebastien; Vercauteren, Tom

2017-02-01

5-ALA-PpIX fluorescence-guided brain tumour resection can increase the accuracy at which cancerous tissue is removed and thereby improve patient outcomes, as compared with standard white light imaging. Novel optical devices that aim to increase the specificity and sensitivity of PpIX detection are typically assessed by measurements in tissue-mimicking optical phantoms of which all optical properties are defined. Current existing optical phantoms specified for PpIX lack consistency in their optical properties, and stability with respect to photobleaching, thus yielding an unstable correspondence between PpIX concentration and the fluorescence intensity. In this study, we developed a set of aqueous-based phantoms with different compositions, using deionised water or PBS buffer as background medium, intralipid as scattering material, bovine haemoglobin as background absorber, and either PpIX dissolved in DMSO or a novel nanoparticle with similar absorption and emission spectrum to PpIX as the fluorophore. We investigated the phantom stability in terms of aggregation and photobleaching by comparing with different background medium and fluorophores, respectively. We characterised the fluorescence intensity of the fluorescent nanoparticle in different concentration of intralipid and haemoglobin and its time-dependent stability, as compared to the PpIX-induced fluorescence. We corroborated that the background medium was essential to prepare a stable aqueous phantom. The novel fluorescent nanoparticle used as surrogate fluorophore of PpIX presented an improved temporal stability and a reliable correspondence between concentration and emission intensity. We proposed an optimised phantom composition and recipe to produce reliable and repeatable phantom for validation of imaging device.

Comparison of [(18)F]altanserin and [(18)F]deuteroaltanserin for PET imaging of serotonin(2A) receptors in baboon brain: pharmacological studies.

PubMed

Staley, J K; Van Dyck, C H; Tan, P Z; Al Tikriti, M; Ramsby, Q; Klump, H; Ng, C; Garg, P; Soufer, R; Baldwin, R M; Innis, R B

2001-04-01

The regional distribution in brain, distribution volumes, and pharmacological specificity of the PET 5-HT(2A) receptor radiotracer [(18)F]deuteroaltanserin were evaluated and compared to those of its non-deuterated derivative [(18)F]altanserin. Both radiotracers were administered to baboons by bolus plus constant infusion and PET images were acquired up to 8 h. The time-activity curves for both tracers stabilized between 4 and 6 h. The ratio of total and free parent to metabolites was not significantly different between radiotracers; nevertheless, total cortical R(T) (equilibrium ratio of specific to nondisplaceable brain uptake) was significantly higher (34-78%) for [(18)F]deuteroaltanserin than for [(18)F]altanserin. In contrast, the binding potential (Bmax/K(D)) was similar between radiotracers. [(18)F]Deuteroaltanserin cortical activity was displaced by the 5-HT(2A) receptor antagonist SR 46349B but was not altered by changes in endogenous 5-HT induced by fenfluramine. These findings suggest that [(18)F]deuteroaltanserin is essentially equivalent to [(18)F]altanserin for 5-HT(2A) receptor imaging in the baboon.

Time-lapse imaging of disease progression in deep brain areas using fluorescence microendoscopy

PubMed Central

Barretto, Robert P. J.; Ko, Tony H.; Jung, Juergen C.; Wang, Tammy J.; Capps, George; Waters, Allison C.; Ziv, Yaniv; Attardo, Alessio; Recht, Lawrence; Schnitzer, Mark J.

2013-01-01

The combination of intravital microscopy and animal models of disease has propelled studies of disease mechanisms and treatments. However, many disorders afflict tissues inaccessible to light microscopy in live subjects. Here we introduce cellular-level time-lapse imaging deep within the live mammalian brain by one- and two-photon fluorescence microendoscopy over multiple weeks. Bilateral imaging sites allowed longitudinal comparisons within individual subjects, including of normal and diseased tissues. Using this approach we tracked CA1 hippocampal pyramidal neuron dendrites in adult mice, revealing these dendrites' extreme stability (>8,000 day mean lifetime) and rare examples of their structural alterations. To illustrate disease studies, we tracked deep lying gliomas by observing tumor growth, visualizing three-dimensional vasculature structure, and determining microcirculatory speeds. Average erythrocyte speeds in gliomas declined markedly as the disease advanced, notwithstanding significant increases in capillary diameters. Time-lapse microendoscopy will be applicable to studies of numerous disorders, including neurovascular, neurological, cancerous, and trauma-induced conditions. PMID:21240263

Abnormal brain activation during emotion processing of euthymic bipolar patients taking different mood stabilizers.

PubMed

Li, Linling; Ji, Erni; Tang, Fei; Qiu, Yunhai; Han, Xue; Zhang, Shengli; Zhang, Zhiguo; Yang, Haichen

2018-06-16

Numerous functional magnetic resonance imaging studies have been conducted to elucidate emotion processing of patients with bipolar disorder (BD), but due to different inclusion criteria used, especially for the history of medication use, the results for euthymic BD patients are inconsistent. For this reason, brain functional effects of psychopharmacological treatments on BD patients have been investigated by numerous fMRI studies, but there is no existing report for brain functional effects of different mood stabilizers. In this study, we compared the emotion processing in BD patients treated by two popularly used mood stabilizer, lithium (N = 13; 30 ± 9 years) and valproate (N = 16; 33 ± 8 years), as well as healthy controls (HC; N = 16; 29 ± 7 years). Two emotional tasks were applied in this study: one used emotional pictures of everyday objects and scenes, and another used emotional facial expression pictures. The main findings were that BD on lithium showed increased fMRI activation in the right dorsal anterior cingulate cortex and bilateral lingual gyrus in response to the positive pictures relative to neutral pictures compared with BD on valproate and HC. Besides, no abnormal activation was observed in the amygdala. Limitations of this study comprise the small sample size and the cross-sectional design. Therefore, the results were suggestive of a different effect of lithium and valproate on brain activities during emotion processing but no causal role can be proposed. The enduring impairments in euthymic state could provide clues to the brain regions involved in the primary pathology of BD.

Propagation stability of self-reconstructing Bessel beams enables contrast-enhanced imaging in thick media.

PubMed

Fahrbach, Florian O; Rohrbach, Alexander

2012-01-17

Laser beams that can self-reconstruct their initial beam profile even in the presence of massive phase perturbations are able to propagate deeper into inhomogeneous media. This ability has crucial advantages for light sheet-based microscopy in thick media, such as cell clusters, embryos, skin or brain tissue or plants, as well as scattering synthetic materials. A ring system around the central intensity maximum of a Bessel beam enables its self-reconstruction, but at the same time illuminates out-of-focus regions and deteriorates image contrast. Here we present a detection method that minimizes the negative effect of the ring system. The beam's propagation stability along one straight line enables the use of a confocal line principle, resulting in a significant increase in image contrast. The axial resolution could be improved by nearly 100% relative to the standard light-sheet techniques using scanned Gaussian beams, while demonstrating self-reconstruction also for high propagation depths.

Three-Photon Luminescence of Gold Nanorods and Its Applications for High Contrast Tissue and Deep In Vivo Brain Imaging

PubMed Central

Wang, Shaowei; Xi, Wang; Cai, Fuhong; Zhao, Xinyuan; Xu, Zhengping; Qian, Jun; He, Sailing

2015-01-01

Gold nanoparticles can be used as contrast agents for bio-imaging applications. Here we studied multi-photon luminescence (MPL) of gold nanorods (GNRs), under the excitation of femtosecond (fs) lasers. GNRs functionalized with polyethylene glycol (PEG) molecules have high chemical and optical stability, and can be used as multi-photon luminescent nanoprobes for deep in vivo imaging of live animals. We have found that the depth of in vivo imaging is dependent upon the transmission and focal capability of the excitation light interacting with the GNRs. Our study focused on the comparison of MPL from GNRs with two different aspect ratios, as well as their ex vivo and in vivo imaging effects under 760 nm and 1000 nm excitation, respectively. Both of these wavelengths were located at an optically transparent window of biological tissue (700-1000 nm). PEGylated GNRs, which were intravenously injected into mice via the tail vein and accumulated in major organs and tumor tissue, showed high image contrast due to distinct three-photon luminescence (3PL) signals upon irradiation of a 1000 nm fs laser. Concerning in vivo mouse brain imaging, the 3PL imaging depth of GNRs under 1000 nm fs excitation could reach 600 μm, which was approximately 170 μm deeper than the two-photon luminescence (2PL) imaging depth of GNRs with a fs excitation of 760 nm. PMID:25553113

A three-wavelength multi-channel brain functional imager based on digital lock-in photon-counting technique

NASA Astrophysics Data System (ADS)

Ding, Xuemei; Wang, Bingyuan; Liu, Dongyuan; Zhang, Yao; He, Jie; Zhao, Huijuan; Gao, Feng

2018-02-01

During the past two decades there has been a dramatic rise in the use of functional near-infrared spectroscopy (fNIRS) as a neuroimaging technique in cognitive neuroscience research. Diffuse optical tomography (DOT) and optical topography (OT) can be employed as the optical imaging techniques for brain activity investigation. However, most current imagers with analogue detection are limited by sensitivity and dynamic range. Although photon-counting detection can significantly improve detection sensitivity, the intrinsic nature of sequential excitations reduces temporal resolution. To improve temporal resolution, sensitivity and dynamic range, we develop a multi-channel continuous-wave (CW) system for brain functional imaging based on a novel lock-in photon-counting technique. The system consists of 60 Light-emitting device (LED) sources at three wavelengths of 660nm, 780nm and 830nm, which are modulated by current-stabilized square-wave signals at different frequencies, and 12 photomultiplier tubes (PMT) based on lock-in photon-counting technique. This design combines the ultra-high sensitivity of the photon-counting technique with the parallelism of the digital lock-in technique. We can therefore acquire the diffused light intensity for all the source-detector pairs (SD-pairs) in parallel. The performance assessments of the system are conducted using phantom experiments, and demonstrate its excellent measurement linearity, negligible inter-channel crosstalk, strong noise robustness and high temporal resolution.

Syringe-injectable mesh electronics integrate seamlessly with minimal chronic immune response in the brain

PubMed Central

Zhou, Tao; Hong, Guosong; Fu, Tian-Ming; Yang, Xiao; Schuhmann, Thomas G.; Viveros, Robert D.; Lieber, Charles M.

2017-01-01

Implantation of electrical probes into the brain has been central to both neuroscience research and biomedical applications, although conventional probes induce gliosis in surrounding tissue. We recently reported ultraflexible open mesh electronics implanted into rodent brains by syringe injection that exhibit promising chronic tissue response and recording stability. Here we report time-dependent histology studies of the mesh electronics/brain-tissue interface obtained from sections perpendicular and parallel to probe long axis, as well as studies of conventional flexible thin-film probes. Confocal fluorescence microscopy images of the perpendicular and parallel brain slices containing mesh electronics showed that the distribution of astrocytes, microglia, and neurons became uniform from 2–12 wk, whereas flexible thin-film probes yield a marked accumulation of astrocytes and microglia and decrease of neurons for the same period. Quantitative analyses of 4- and 12-wk data showed that the signals for neurons, axons, astrocytes, and microglia are nearly the same from the mesh electronics surface to the baseline far from the probes, in contrast to flexible polymer probes, which show decreases in neuron and increases in astrocyte and microglia signals. Notably, images of sagittal brain slices containing nearly the entire mesh electronics probe showed that the tissue interface was uniform and neurons and neurofilaments penetrated through the mesh by 3 mo postimplantation. The minimal immune response and seamless interface with brain tissue postimplantation achieved by ultraflexible open mesh electronics probes provide substantial advantages and could enable a wide range of opportunities for in vivo chronic recording and modulation of brain activity in the future. PMID:28533392

Syringe-injectable mesh electronics integrate seamlessly with minimal chronic immune response in the brain.

PubMed

Zhou, Tao; Hong, Guosong; Fu, Tian-Ming; Yang, Xiao; Schuhmann, Thomas G; Viveros, Robert D; Lieber, Charles M

2017-06-06

Implantation of electrical probes into the brain has been central to both neuroscience research and biomedical applications, although conventional probes induce gliosis in surrounding tissue. We recently reported ultraflexible open mesh electronics implanted into rodent brains by syringe injection that exhibit promising chronic tissue response and recording stability. Here we report time-dependent histology studies of the mesh electronics/brain-tissue interface obtained from sections perpendicular and parallel to probe long axis, as well as studies of conventional flexible thin-film probes. Confocal fluorescence microscopy images of the perpendicular and parallel brain slices containing mesh electronics showed that the distribution of astrocytes, microglia, and neurons became uniform from 2-12 wk, whereas flexible thin-film probes yield a marked accumulation of astrocytes and microglia and decrease of neurons for the same period. Quantitative analyses of 4- and 12-wk data showed that the signals for neurons, axons, astrocytes, and microglia are nearly the same from the mesh electronics surface to the baseline far from the probes, in contrast to flexible polymer probes, which show decreases in neuron and increases in astrocyte and microglia signals. Notably, images of sagittal brain slices containing nearly the entire mesh electronics probe showed that the tissue interface was uniform and neurons and neurofilaments penetrated through the mesh by 3 mo postimplantation. The minimal immune response and seamless interface with brain tissue postimplantation achieved by ultraflexible open mesh electronics probes provide substantial advantages and could enable a wide range of opportunities for in vivo chronic recording and modulation of brain activity in the future.

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.

Chalcone Based Homodimeric PET Agent, 11C-(Chal)2DEA-Me, for Beta Amyloid Imaging: Synthesis and Bioevaluation.

PubMed

Chauhan, Kanchan; Tiwari, Anjani K; Chadha, Nidhi; Kaul, Ankur; Singh, Ajai Kumar; Datta, Anupama

2018-04-02

Homodimeric chalcone based 11 C-PET radiotracer, 11 C-(Chal) 2 DEA-Me, was synthesized, and binding affinity toward beta amyloid (Aβ) was evaluated. The computational studies revealed multiple binding of the tracer at the recognition sites of Aβ fibrils. The bivalent ligand 11 C-(Chal) 2 DEA-Me displayed higher binding affinity compared to the corresponding monomer, 11 C-Chal-Me, and classical Aβ agents. The radiolabeling yield with carbon-11 was 40-55% (decay corrected) with specific activity of 65-90 GBq/μmol. A significant ( p < 0.0001) improvement in the binding affinity of 11 C-(Chal) 2 DEA-Me with synthetic Aβ42 aggregates over the monomer, 11 C-Chal-Me, demonstrates the utility of the bivalent approach. The PET imaging and biodistribution data displayed suitable brain pharmacokinetics of both ligands with higher brain uptake in the case of the bivalent ligand. Metabolite analysis of healthy ddY mouse brain homogenates exhibited high stability of the radiotracers in the brain with >93% intact tracer at 30 min post injection. Both chalcone derivatives were fluorescent in nature and demonstrated significant changes in the emission properties after binding with Aβ42. The preliminary analysis indicates high potential of 11 C-(Chal) 2 DEA-Me as in vivo Aβ42 imaging tracer and highlights the significance of the bivalent approach to achieve a higher biological response for detection of early stages of amyloidosis.

A philosophy for CNS radiotracer design.

PubMed

Van de Bittner, Genevieve C; Ricq, Emily L; Hooker, Jacob M

2014-10-21

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test-retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood-brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.

Enhanced FIB-SEM systems for large-volume 3D imaging.

PubMed

Xu, C Shan; Hayworth, Kenneth J; Lu, Zhiyuan; Grob, Patricia; Hassan, Ahmed M; García-Cerdán, José G; Niyogi, Krishna K; Nogales, Eva; Weinberg, Richard J; Hess, Harald F

2017-05-13

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here, we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 10 6 µm 3 . These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processes and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, Drosophila brain, and Chlamydomonas reinhardtii to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology.

Brain injury tolerance limit based on computation of axonal strain.

PubMed

Sahoo, Debasis; Deck, Caroline; Willinger, Rémy

2016-07-01

Traumatic brain injury (TBI) is the leading cause of death and permanent impairment over the last decades. In both the severe and mild TBIs, diffuse axonal injury (DAI) is the most common pathology and leads to axonal degeneration. Computation of axonal strain by using finite element head model in numerical simulation can enlighten the DAI mechanism and help to establish advanced head injury criteria. The main objective of this study is to develop a brain injury criterion based on computation of axonal strain. To achieve the objective a state-of-the-art finite element head model with enhanced brain and skull material laws, was used for numerical computation of real world head trauma. The implementation of new medical imaging data such as, fractional anisotropy and axonal fiber orientation from Diffusion Tensor Imaging (DTI) of 12 healthy patients into the finite element brain model was performed to improve the brain constitutive material law with more efficient heterogeneous anisotropic visco hyper-elastic material law. The brain behavior has been validated in terms of brain deformation against Hardy et al. (2001), Hardy et al. (2007), and in terms of brain pressure against Nahum et al. (1977) and Trosseille et al. (1992) experiments. Verification of model stability has been conducted as well. Further, 109 well-documented TBI cases were simulated and axonal strain computed to derive brain injury tolerance curve. Based on an in-depth statistical analysis of different intra-cerebral parameters (brain axonal strain rate, axonal strain, first principal strain, Von Mises strain, first principal stress, Von Mises stress, CSDM (0.10), CSDM (0.15) and CSDM (0.25)), it was shown that axonal strain was the most appropriate candidate parameter to predict DAI. The proposed brain injury tolerance limit for a 50% risk of DAI has been established at 14.65% of axonal strain. This study provides a key step for a realistic novel injury metric for DAI. Copyright © 2016 Elsevier Ltd. All rights reserved.

Regional ADC values of the normal brain: differences due to age, gender, and laterality.

PubMed

Naganawa, Shinji; Sato, Kimihide; Katagiri, Toshio; Mimura, Takeo; Ishigaki, Takeo

2003-01-01

The purpose of this study was to evaluate the stability of measurement for apparent diffusion coefficient (ADC) values in normal brain, to clarify the effect of aging on ADC values, to compare ADC values between men and women, and to compare ADC values between right and left sides of the brain. To evaluate the stability of measurements, five normal volunteers (four men and one woman) were examined five times on different days. Then, 294 subjects with normal MR imaging (147 men and 147 women; age range 20-89 years) were measured. The ADC measurement in normal volunteers was stable. The ADC values stayed within the 5% deviation of average values in all volunteers (mean+/-standard deviation 2.3+/-1.2%). The ADC values gradually increased by aging in all regions. In thalamus, no significant difference was seen between right and left in the subjects under 60 years; however, right side showed higher values in the subjects over 60 years (p<0.01). In the subjects under 60 years, women showed higher values in right frontal, bilateral thalamus, and temporal (p<0.01); however, in the subjects over 60 years, no region showed difference between men and women. The knowledge obtained in this study may be helpful to understand the developmental and aging mechanisms of normal brain and may be useful for the future quantitative study as a reference.

Chemical nature and structure of organic coating of quantum dots is crucial for their application in imaging diagnostics

PubMed Central

Bakalova, Rumiana; Zhelev, Zhivko; Kokuryo, Daisuke; Spasov, Lubomir; Aoki, Ichio; Saga, Tsuneo

2011-01-01

Background: One of the most attractive properties of quantum dots is their potential to extend the opportunities for fluorescent and multimodal imaging in vivo. The aim of the present study was to clarify whether the composition and structure of organic coating of nanoparticles are crucial for their application in vivo. Methods: We compared quantum dots coated with non-crosslinked amino-functionalized polyamidoamine (PAMAM) dendrimers, quantum dots encapsulated in crosslinked carboxyl-functionalized PAMAM dendrimers, and silica-shelled amino-functionalized quantum dots. A multimodal fluorescent and paramagnetic quantum dot probe was also developed and analyzed. The probes were applied intravenously in anesthetized animals for visualization of brain vasculature using two-photon excited fluorescent microscopy and visualization of tumors using fluorescent IVIS® imaging (Caliper Life Sciences, Hopkinton, MA) and magnetic resonance imaging. Results: Quantum dots coated with non-crosslinked dendrimers were cytotoxic. They induced side effects in vivo, including vasodilatation with a decrease in mean arterial blood pressure and heart rate. The quantum dots penetrated the vessels, which caused the quality of fluorescent imaging to deteriorate. Quantum dots encapsulated in crosslinked dendrimers had low cytotoxicity and were biocompatible. In concentrations <0.3 nmol quantum dots/kg bodyweight, these nanoparticles did not affect blood pressure and heart rate, and did not induce vasodilatation or vasoconstriction. PEGylation (PEG [polyethylene glycol]) was an indispensable step in development of a quantum dot probe for in vivo imaging, based on silica-shelled quantum dots. The non-PEGylated silica-shelled quantum dots possessed low colloidal stability in high-salt physiological fluids, accompanied by rapid aggregation in vivo. The conjugation of silica-shelled quantum dots with PEG1100 increased their stability and half-life in the circulation without significant enhancement of their size. In concentrations <2.5 nmol/kg bodyweight, these quantum dots did not affect the main physiological variables. It was possible to visualize capillaries, which makes this quantum dot probe appropriate for investigation of mediators of vasoconstriction, vasodilatation, and brain circulation in intact animals in vivo. The multimodal silica-shelled quantum dots allowed visualization of tumor tissue in an early stage of its development, using magnetic resonance imaging. Conclusion: The present study shows that the type and structure of organic/bioorganic shells of quantum dots determine their biocompatibility and are crucial for their application in imaging in vivo, due to the effects of the shell on the following properties: colloidal stability, solubility in physiological fluids, influence of the basic physiological parameters, and cytotoxicity. PMID:21980235

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

NASA Astrophysics Data System (ADS)

Stanley, Dennis Nichols

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

In vitro stabilization of a low-tin bone-imaging agent (99mTc-Sn-HEDP) by ascorbic acid.

PubMed

Tofe, A J; Francis, M D

1976-09-01

The presence of oxidants in the 99mTc-pertechnetate and of oxygen in diagnostic kits containing low concentrations of Sn(II) has a detrimental effect upon in vitro and in vivo stability. Maintaining a nitrogen atmosphere or increasing the Sn(II) concentration inhibits the formation of 99mTcO4-. However, the latter remedy is likely to cause uptake in the reticuloendothelial system and has been associated with false positive or negative brain scans. We used ascorbic acid (an antioxidant) to ensure the in vitro stability with the low-Sn(II) bone agent disodium etidronate. In vitro stability studies by instant thin-layer chromatography, using high-acitivity generators and "instant pertechnetate," yielded less than 2% free pertechnetate at 24 hr after preparation. Distribution studies in guinea pigs show neither altered distribution of the bone agent nor abnormal distribution of ascorbic acid, suggesting its sole function as a noncomplexing stabilizer.

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

PubMed Central

Moore-Stovall, J.; Venkatesh, R.

1993-01-01

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

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.

Sparse network-based models for patient classification using fMRI

PubMed Central

Rosa, Maria J.; Portugal, Liana; Hahn, Tim; Fallgatter, Andreas J.; Garrido, Marta I.; Shawe-Taylor, John; Mourao-Miranda, Janaina

2015-01-01

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. PMID:25463459

Desirability function combining metabolic stability and functionality of peptides.

PubMed

Van Dorpe, Sylvia; Adriaens, Antita; Vermeire, Simon; Polis, Ingeborgh; Peremans, Kathelijne; Spiegeleer, Bart De

2011-05-01

The evaluation of peptides as potential therapeutic or diagnostic agents requires the consideration of several criteria that are targeted around two axes: functionality and metabolic stability. Most often, a compromise has to be made between these mutually opposing characteristics. In this study, Derringer's desirability function, a multi-criteria decision-making method, was applied to determine the best peptide for opioid studies in a single figure-of-merit. The penetration of the blood-brain barrier (BBB) determines the biological functionality of neuropeptides in the brain target tissue, and consists of an influx and an efflux component. The metabolic stability in the two concerned tissues, i.e. plasma and brain, are taken into consideration as well. The overall selection of the peptide drug candidate having the highest BBB-drugability is difficult due to these conflicting responses as well as the different scalings of the four biological parameters under consideration. The highest desirability, representing the best BBB-drugability, was observed for dermorphin. This peptide is thus the most promising drug candidate from the set of eight opioid peptides that were investigated. The least desirable candidate, with the worst BBB influx and/or metabolic stability, was found to be CTAP. Validation of the desirability function by in vivo medical imaging showed that dermorphin and DAMGO penetrate the BBB, whereas EM-1 and TAPP did not. These results are thus consistent with those obtained with the desirability evaluation. To conclude, the multi-criteria decision method was proven to be useful in biomedical research, where a selection of the best candidate based on opposing characteristics is often required. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.

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.

Sensorimotor Functional and Structural Networks after Intracerebral Stem Cell Grafts in the Ischemic Mouse Brain.

PubMed

Green, Claudia; Minassian, Anuka; Vogel, Stefanie; Diedenhofen, Michael; Beyrau, Andreas; Wiedermann, Dirk; Hoehn, Mathias

2018-02-14

Past investigations on stem cell-mediated recovery after stroke have limited their focus on the extent and morphological development of the ischemic lesion itself over time or on the integration capacity of the stem cell graft ex vivo However, an assessment of the long-term functional and structural improvement in vivo is essential to reliably quantify the regenerative capacity of cell implantation after stroke. We induced ischemic stroke in nude mice and implanted human neural stem cells (H9 derived) into the ipsilateral cortex in the acute phase. Functional and structural connectivity changes of the sensorimotor network were noninvasively monitored using magnetic resonance imaging for 3 months after stem cell implantation. A sharp decrease of the functional sensorimotor network extended even to the contralateral hemisphere, persisting for the whole 12 weeks of observation. In mice with stem cell implantation, functional networks were stabilized early on, pointing to a paracrine effect as an early supportive mechanism of the graft. This stabilization required the persistent vitality of the stem cells, monitored by bioluminescence imaging. Thus, we also observed deterioration of the early network stabilization upon vitality loss of the graft after a few weeks. Structural connectivity analysis showed fiber-density increases between the cortex and white matter regions occurring predominantly on the ischemic hemisphere. These fiber-density changes were nearly the same for both study groups. This motivated us to hypothesize that the stem cells can influence, via early paracrine effect, the functional networks, while observed structural changes are mainly stimulated by the ischemic event. SIGNIFICANCE STATEMENT In recent years, research on strokes has made a shift away from a focus on immediate ischemic effects and towards an emphasis on the long-range effects of the lesion on the whole brain. Outcome improvements in stem cell therapies also require the understanding of their influence on the whole-brain networks. Here, we have longitudinally and noninvasively monitored the structural and functional network alterations in the mouse model of focal cerebral ischemia. Structural changes of fiber-density increases are stimulated in the endogenous tissue without further modulation by the stem cells, while functional networks are stabilized by the stem cells via a paracrine effect. These results will help decipher the underlying networks of brain plasticity in response to cerebral lesions and offer clues to unravelling the mystery of how stem cells mediate regeneration. Copyright © 2018 the authors 0270-6474/18/381648-14$15.00/0.

Dissociation of Self-Motion and Object Motion by Linear Population Decoding That Approximates Marginalization

PubMed Central

Sasaki, Ryo; Angelaki, Dora E.

2017-01-01

We use visual image motion to judge the movement of objects, as well as our own movements through the environment. Generally, image motion components caused by object motion and self-motion are confounded in the retinal image. Thus, to estimate heading, the brain would ideally marginalize out the effects of object motion (or vice versa), but little is known about how this is accomplished neurally. Behavioral studies suggest that vestibular signals play a role in dissociating object motion and self-motion, and recent computational work suggests that a linear decoder can approximate marginalization by taking advantage of diverse multisensory representations. By measuring responses of MSTd neurons in two male rhesus monkeys and by applying a recently-developed method to approximate marginalization by linear population decoding, we tested the hypothesis that vestibular signals help to dissociate self-motion and object motion. We show that vestibular signals stabilize tuning for heading in neurons with congruent visual and vestibular heading preferences, whereas they stabilize tuning for object motion in neurons with discrepant preferences. Thus, vestibular signals enhance the separability of joint tuning for object motion and self-motion. We further show that a linear decoder, designed to approximate marginalization, allows the population to represent either self-motion or object motion with good accuracy. Decoder weights are broadly consistent with a readout strategy, suggested by recent computational work, in which responses are decoded according to the vestibular preferences of multisensory neurons. These results demonstrate, at both single neuron and population levels, that vestibular signals help to dissociate self-motion and object motion. SIGNIFICANCE STATEMENT The brain often needs to estimate one property of a changing environment while ignoring others. This can be difficult because multiple properties of the environment may be confounded in sensory signals. The brain can solve this problem by marginalizing over irrelevant properties to estimate the property-of-interest. We explore this problem in the context of self-motion and object motion, which are inherently confounded in the retinal image. We examine how diversity in a population of multisensory neurons may be exploited to decode self-motion and object motion from the population activity of neurons in macaque area MSTd. PMID:29030435

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.

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

Xu, C. Shan; Hayworth, Kenneth J.; Lu, Zhiyuan

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here, we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 10 6 ?m 3 . These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processesmore » and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, Drosophila brain, and Chlamydomonas reinhardtii to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology.« less

Biocompatible KMnF3 nanoparticular contrast agent with proper plasma retention time for in vivo magnetic resonance imaging.

PubMed

Liu, Zhi-jun; Song, Xiao-xia; Xu, Xian-zhu; Tang, Qun

2014-04-18

Nanoparticular MRI contrast agents are rapidly becoming suitable for use in clinical diagnosis. An ideal nanoparticular contrast agent should be endowed with high relaxivity, biocompatibility, proper plasma retention time, and tissue-specific or tumor-targeting imaging. Herein we introduce PEGylated KMnF3 nanoparticles as a new type of T1 contrast agent. Studies showed that the nanoparticular contrast agent revealed high bio-stability with bovine serum albumin in PBS buffer solution, and presented excellent biocompatibility (low cytotoxicity, undetectable hemolysis and hemagglutination). Meanwhile the new contrast agent possessed proper plasma retention time (circulation half-life t1/2 is approximately 2 h) in the body of the administrated mice. It can be delivered into brain vessels and maintained there for hours, and is mostly cleared from the body within 48 h, as demonstrated by time-resolved MRI and Mn-biodistribution analysis. Those distinguishing features make it suitable to obtain contrast-enhanced brain magnetic resonance angiography. Moreover, through the process of passive targeting delivery, the T1 contrast agent clearly illuminates a brain tumor (glioma) with high contrast image and defined shape. This study demonstrates that PEGylated KMnF3 nanoparticles represent a promising biocompatible vascular contrast agent for magnetic resonance angiography and can potentially be further developed into an active targeted tumor MRI contrast agent.

The proton permeability of self-assembled polymersomes and their neuroprotection by enhancing a neuroprotective peptide across the blood-brain barrier after modification with lactoferrin.

PubMed

Yu, Yuan; Jiang, Xinguo; Gong, Shuyu; Feng, Liang; Zhong, Yanqiang; Pang, Zhiqing

2014-03-21

Biotherapeutics such as peptides possess strong potential for the treatment of intractable neurological disorders. However, because of their low stability and the impermeability of the blood-brain barrier (BBB), biotherapeutics are difficult to transport into brain parenchyma via intravenous injection. Herein, we present a novel poly(ethylene glycol)-poly(d,l-lactic-co-glycolic acid) polymersome-based nanomedicine with self-assembled bilayers, which was functionalized with lactoferrin (Lf-POS) to facilitate the transport of a neuroprotective peptide into the brain. The apparent diffusion coefficient (D*) of H(+) through the polymersome membrane was 5.659 × 10(-26) cm(2) s(-1), while that of liposomes was 1.017 × 10(-24) cm(2) s(-1). The stability of the polymersome membrane was much higher than that of liposomes. The uptake of polymersomes by mouse brain capillary endothelial cells proved that the optimal density of lactoferrin was 101 molecules per polymersome. Fluorescence imaging indicated that Lf101-POS was effectively transferred into the brain. In pharmacokinetics, compared with transferrin-modified polymersomes and cationic bovine serum albumin-modified polymersomes, Lf-POS obtained the greatest BBB permeability surface area and percentage of injected dose per gram (%ID per g). Furthermore, Lf-POS holding S14G-humanin protected against learning and memory impairment induced by amyloid-β25-35 in rats. Western blotting revealed that the nanomedicine provided neuroprotection against over-expression of apoptotic proteins exhibiting neurofibrillary tangle pathology in neurons. The results indicated that polymersomes can be exploited as a promising non-invasive nanomedicine capable of mediating peptide therapeutic delivery and controlling the release of drugs to the central nervous system.

The proton permeability of self-assembled polymersomes and their neuroprotection by enhancing a neuroprotective peptide across the blood-brain barrier after modification with lactoferrin

NASA Astrophysics Data System (ADS)

Yu, Yuan; Jiang, Xinguo; Gong, Shuyu; Feng, Liang; Zhong, Yanqiang; Pang, Zhiqing

2014-02-01

Biotherapeutics such as peptides possess strong potential for the treatment of intractable neurological disorders. However, because of their low stability and the impermeability of the blood-brain barrier (BBB), biotherapeutics are difficult to transport into brain parenchyma via intravenous injection. Herein, we present a novel poly(ethylene glycol)-poly(d,l-lactic-co-glycolic acid) polymersome-based nanomedicine with self-assembled bilayers, which was functionalized with lactoferrin (Lf-POS) to facilitate the transport of a neuroprotective peptide into the brain. The apparent diffusion coefficient (D*) of H+ through the polymersome membrane was 5.659 × 10-26 cm2 s-1, while that of liposomes was 1.017 × 10-24 cm2 s-1. The stability of the polymersome membrane was much higher than that of liposomes. The uptake of polymersomes by mouse brain capillary endothelial cells proved that the optimal density of lactoferrin was 101 molecules per polymersome. Fluorescence imaging indicated that Lf101-POS was effectively transferred into the brain. In pharmacokinetics, compared with transferrin-modified polymersomes and cationic bovine serum albumin-modified polymersomes, Lf-POS obtained the greatest BBB permeability surface area and percentage of injected dose per gram (%ID per g). Furthermore, Lf-POS holding S14G-humanin protected against learning and memory impairment induced by amyloid-β25-35 in rats. Western blotting revealed that the nanomedicine provided neuroprotection against over-expression of apoptotic proteins exhibiting neurofibrillary tangle pathology in neurons. The results indicated that polymersomes can be exploited as a promising non-invasive nanomedicine capable of mediating peptide therapeutic delivery and controlling the release of drugs to the central nervous system.

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

Plasmonic fluorescent CdSe/Cu2S hybrid nanocrystals for multichannel imaging and cancer directed photo-thermal therapy

NASA Astrophysics Data System (ADS)

Sheikh Mohamed, M.; Poulose, Aby Cheruvathoor; Veeranarayanan, Srivani; Romero Aburto, Rebecca; Mitcham, Trevor; Suzuki, Yuko; Sakamoto, Yasushi; Ajayan, Pulickel M.; Bouchard, Richard R.; Yoshida, Yasuhiko; Maekawa, Toru; Sakthi Kumar, D.

2016-04-01

A simple, crude Jatropha curcas (JC) oil-based synthesis approach, devoid of any toxic phosphine and pyrophoric ligands, to produce size and shape tuned CdSe QDs and a further copper sulfide (Cu2S) encasing is presented. The QDs exhibited excellent photoluminescent properties with narrow band gap emission. Furthermore, the Cu2S shell rendered additional cytocompatibility and stability to the hybrid nanomaterial, which are major factors for translational and clinical applications of QDs. The nanocomposites were PEGylated and folate conjugated to augment their cytoamiability and enhance their specificity towards cancer cells. The nanohybrids possess potentials for visible, near infrared (NIR), photoacoustic (PA) and computed tomography (μCT) imaging. The diverse functionality of the composite was derived from the multi-channel imaging abilities and thermal competence on NIR laser irradiation to specifically actuate the photo-thermal ablation of brain cancer cells.A simple, crude Jatropha curcas (JC) oil-based synthesis approach, devoid of any toxic phosphine and pyrophoric ligands, to produce size and shape tuned CdSe QDs and a further copper sulfide (Cu2S) encasing is presented. The QDs exhibited excellent photoluminescent properties with narrow band gap emission. Furthermore, the Cu2S shell rendered additional cytocompatibility and stability to the hybrid nanomaterial, which are major factors for translational and clinical applications of QDs. The nanocomposites were PEGylated and folate conjugated to augment their cytoamiability and enhance their specificity towards cancer cells. The nanohybrids possess potentials for visible, near infrared (NIR), photoacoustic (PA) and computed tomography (μCT) imaging. The diverse functionality of the composite was derived from the multi-channel imaging abilities and thermal competence on NIR laser irradiation to specifically actuate the photo-thermal ablation of brain cancer cells. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr05225d

Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

NASA Astrophysics Data System (ADS)

Chouzouris, Teresa; Omelchenko, Iryna; Zakharova, Anna; Hlinka, Jaroslav; Jiruska, Premysl; Schöll, Eckehard

2018-04-01

Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

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…

A philosophy for CNS radiotracer design

DOE PAGES

Van de Bittner, Genevieve C.; Ricq, Emily L.; Hooker, Jacob M.

2014-10-01

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfallsmore » of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test–retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood–brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Lastly, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.« less

A Philosophy for CNS Radiotracer Design

PubMed Central

2015-01-01

Conspectus Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test–retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood–brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible. PMID:25272291

Influence of magnetic field strength and image registration strategy on voxel-based morphometry in a study of Alzheimer's disease.

PubMed

Marchewka, Artur; Kherif, Ferath; Krueger, Gunnar; Grabowska, Anna; Frackowiak, Richard; Draganski, Bogdan

2014-05-01

Multi-centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non-quantitative character of the widely used structural T1-weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi-site MR images, there are only sparse empirically-based recommendations for processing and analysis of pooled multi-centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel-based morphometry in AD. We perform a whole-brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi-centre VBM studies irrespective of disease status or MFS. Copyright © 2013 Wiley Periodicals, Inc.

Molecular imaging of σ receptors: synthesis and evaluation of the potent σ1 selective radioligand [18F]fluspidine.

PubMed

Fischer, Steffen; Wiese, Christian; Maestrup, Eva Grosse; Hiller, Achim; Deuther-Conrad, Winnie; Scheunemann, Matthias; Schepmann, Dirk; Steinbach, Jörg; Wünsch, Bernhard; Brust, Peter

2011-03-01

Neuroimaging of σ(1) receptors in the human brain has been proposed for the investigation of the pathophysiology of neurodegenerative and psychiatric diseases. However, there is a lack of suitable (18)F-labelled PET radioligands for that purpose. The selective σ(1) receptor ligand [(18)F]fluspidine (1'-benzyl-3-(2-[(18)F]fluoroethyl)-3H-spiro[[2]benzofuran-1,4'-piperidine]) was synthesized by nucleophilic (18)F(-) substitution of the tosyl precursor. In vitro receptor binding affinity and selectivity were assessed by radioligand competition in tissue homogenate and autoradiographic approaches. In female CD-1 mice, in vivo properties of [(18)F]fluspidine were evaluated by ex vivo brain section imaging and organ distribution of intravenously administered radiotracer. Target specificity was validated by organ distribution of [(18)F]fluspidine after treatment with 1 mg/kg i.p. of the σ receptor antagonist haloperidol or the emopamil binding protein (EBP) inhibitor tamoxifen. In vitro metabolic stability and in vivo metabolism were investigated by LC-MS(n) and radio-HPLC analysis. [(18)F]Fluspidine was obtained with a radiochemical yield of 35-45%, a radiochemical purity of ≥ 99.6% and a specific activity of 150-350 GBq/μmol (n = 6) within a total synthesis time of 90-120 min. In vitro, fluspidine bound specifically and with high affinity to σ(1) receptors (K (i) = 0.59 nM). In mice, [(18)F]fluspidine rapidly accumulated in brain with uptake values of 3.9 and 4.7%ID/g and brain to blood ratios of 7 and 13 at 5 and 30 min after intravenous application of the radiotracer, respectively. By ex vivo autoradiography of brain slices, resemblance between binding site occupancy of [(18)F]fluspidine and the expression of σ(1) receptors was shown. The radiotracer uptake in the brain as well as in peripheral σ(1) receptor expressing organs was significantly inhibited by haloperidol but not by tamoxifen. Incubation with rat liver microsomes led to a fast biotransformation of fluspidine. After an incubation period of 30 min only 13% of the parent compound was left. Seven metabolites were identified by HPLC-UV and LC-MS(n) techniques. However, [(18)F]fluspidine showed a higher metabolic stability in vivo. In plasma samples ∼ 94% of parent compound remained at 30 min and ∼ 67% at 60 min post-injection. Only one major radiometabolite was detected. None of the radiometabolites crossed the blood-brain barrier. [(18)F]Fluspidine demonstrated favourable target affinity and specificity as well as metabolic stability both in vitro and in animal experiments. The in vivo properties of [(18)F]fluspidine offer a high potential of this radiotracer for neuroimaging and quantitation of σ(1) receptors in vivo.

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post-Bed Rest and Space Flight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Peters, B.; De Dios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Oddsson, L.; Kreutzberg, G.; Zanello, S.;

Quantitative assessments of traumatic axonal injury in human brain: concordance of microdialysis and advanced MRI.

PubMed

Magnoni, Sandra; Mac Donald, Christine L; Esparza, Thomas J; Conte, Valeria; Sorrell, James; Macrì, Mario; Bertani, Giulio; Biffi, Riccardo; Costa, Antonella; Sammons, Brian; Snyder, Abraham Z; Shimony, Joshua S; Triulzi, Fabio; Stocchetti, Nino; Brody, David L

2015-08-01

Axonal injury is a major contributor to adverse outcomes following brain trauma. However, the extent of axonal injury cannot currently be assessed reliably in living humans. Here, we used two experimental methods with distinct noise sources and limitations in the same cohort of 15 patients with severe traumatic brain injury to assess axonal injury. One hundred kilodalton cut-off microdialysis catheters were implanted at a median time of 17 h (13-29 h) after injury in normal appearing (on computed tomography scan) frontal white matter in all patients, and samples were collected for at least 72 h. Multiple analytes, such as the metabolic markers glucose, lactate, pyruvate, glutamate and tau and amyloid-β proteins, were measured every 1-2 h in the microdialysis samples. Diffusion tensor magnetic resonance imaging scans at 3 T were performed 2-9 weeks after injury in 11 patients. Stability of diffusion tensor imaging findings was verified by repeat scans 1-3 years later in seven patients. An additional four patients were scanned only at 1-3 years after injury. Imaging abnormalities were assessed based on comparisons with five healthy control subjects for each patient, matched by age and sex (32 controls in total). No safety concerns arose during either microdialysis or scanning. We found that acute microdialysis measurements of the axonal cytoskeletal protein tau in the brain extracellular space correlated well with diffusion tensor magnetic resonance imaging-based measurements of reduced brain white matter integrity in the 1-cm radius white matter-masked region near the microdialysis catheter insertion sites. Specifically, we found a significant inverse correlation between microdialysis measured levels of tau 13-36 h after injury and anisotropy reductions in comparison with healthy controls (Spearman's r = -0.64, P = 0.006). Anisotropy reductions near microdialysis catheter insertion sites were highly correlated with reductions in multiple additional white matter regions. We interpret this result to mean that both microdialysis and diffusion tensor magnetic resonance imaging accurately reflect the same pathophysiological process: traumatic axonal injury. This cross-validation increases confidence in both methods for the clinical assessment of axonal injury. However, neither microdialysis nor diffusion tensor magnetic resonance imaging have been validated versus post-mortem histology in humans. Furthermore, future work will be required to determine the prognostic significance of these assessments of traumatic axonal injury when combined with other clinical and radiological measures. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Formulation, Optimization, Characterization, and Pharmacokinetics of Progesterone Intravenous Lipid Emulsion for Traumatic Brain Injury Therapy.

PubMed

Zhao, Jin; Yuan, Quan; Cai, WeiHui; Sun, Pan; Ding, LiYan; Jin, Fang

2017-07-01

Traumatic brain injury (TBI) is a major cause of mortality and disability throughout the world. Progesterone (PROG) plays an important role in neurologic treatment. The aim of this study was to develop a progesterone formulation with good physical and chemical stability. Progesterone intravenous lipid emulsion (PILE) was prepared based on one-factor-at-a-time experiments and orthogonal design. The optimal PILE was evaluated for mean particle size, particle size distribution, zeta potential, morphology, pH, osmolarity, entrapment efficiency, storage stability, and pharmacokinetics in ICR mice compared with the commercial progesterone products. The droplets of PILE had the smallest possible diameters of 218.0 ± 1.8 nm and adequate zeta potential of -41.1 ± 0.9 mV. The volume percentage of droplets exceeding 5 μm (PFAT 5 ) of PILE was 0.003 ± 0.0015% and much less than the specified standard. The TEM imaging proved that emulsion droplets had a smooth spherical appearance. Chemically and physically stable PILE was obtained with excellent entrapment efficiency that was up to 95.23%, with suitable pH at 7.15 ± 0.01 and osmolarity at 301.3 ± 1.2 mOsmol/l. Storage stability tests indicated that the emulsion was stable long term under ambient temperature conditions. Animal studies demonstrated that the emulsion was more effective with the higher progesterone concentration in the brain compared with commercial products. Therefore, the optimized PILE would offer great promise as a means of progesterone delivery for TBI therapy.

A self-organized learning strategy for object recognition by an embedded line of attraction

NASA Astrophysics Data System (ADS)

Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

2012-04-01

For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

PubMed

Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

2018-02-01

The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

Enhanced FIB-SEM systems for large-volume 3D imaging

PubMed Central

Xu, C Shan; Hayworth, Kenneth J; Lu, Zhiyuan; Grob, Patricia; Hassan, Ahmed M; García-Cerdán, José G; Niyogi, Krishna K; Nogales, Eva; Weinberg, Richard J; Hess, Harald F

2017-01-01

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here, we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 106 µm3. These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processes and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, Drosophila brain, and Chlamydomonas reinhardtii to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology. DOI: http://dx.doi.org/10.7554/eLife.25916.001 PMID:28500755

Enhanced FIB-SEM systems for large-volume 3D imaging

DOE PAGES

Xu, C. Shan; Hayworth, Kenneth J.; Lu, Zhiyuan; ...

2017-05-13

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here, we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 10 6 ?m 3 . These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processesmore » and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, Drosophila brain, and Chlamydomonas reinhardtii to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology.« less

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

PubMed

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

2013-08-15

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

Betacam: a commercial approach to β-autoradiography

NASA Astrophysics Data System (ADS)

Cabello, J.; Holland, A.; Holland, K.; Bailey, A.; Kitchen, I.; Wells, K.

2009-02-01

Autoradiography is a well established imaging modality in Biology and Medicine. This aims to measure the location and concentration of labelled molecules within thin tissue sections. The brain is the most anatomically complex organ and identification of neuroanatomical structures is still a challenge particularly when small animals are used for pre-clinical trials. High spatial resolution and high sensitivity are therefore necessary. This work shows the performance and ability of a prototype commercial system, based on a Charged-Couple Device (CCD), to accurately obtain detailed functional information in brain Autoradiography. The sample is placed in contact with the detector enabling direct detection of β- particles in silicon, and the system is run in a range of quasi-room temperatures (17-22 °C) under stable conditions by using a precision temperature controller. Direct detection of β- particles with low energy down to ~5 keV from 3[H] is possible using this room temperature approach. The CCD used in this work is an E2V CCD47-20 frame-transfer device which removes the image smear arising in conventional full-frame imaging devices. The temporal stability of the system has been analyzed by exposing a set of 14[C] calibrated microscales for different periods of time, and measuring the stability of the resultant sensitivity and background noise. The thermal performance of the system has also been analyzed in order to demonstrate its capability of working in other life science applications, where higher working temperatures are required. Once the performance of the system was studied, a set of experiments with biological samples, labelled with typical β- radioisotopes, such as 3[H], has been carried out to demonstrate its application in life sciences.

Long-Term Monitoring of Brain Dopamine Metabolism In Vivo with Carbon Paste Electrodes

PubMed Central

O'Neill, Robert D.

2005-01-01

This review focuses on the stability of voltammetric signals recorded over periods of months with carbon paste electrodes (CPEs) implanted in the brain. The key interaction underlying this stability is between the pasting oil and brain lipids that are capable of inhibiting the fouling caused by proteins. In brain regions receiving a significant dopaminergic input, a peak due to the methylated metabolites of dopamine, principally homovanillic acid (HVA), is clearly resolved using slow sweep voltammetry. Although a number of factors limit the time resolution for monitoring brain HVA concentration dynamics, the stability of CPEs allows investigations of long-term effects of drugs, as well as behavioral studies, not possible using other in-vivo monitoring techniques.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Early Detection of Ventilation-Induced Brain Injury Using Magnetic Resonance Spectroscopy and Diffusion Tensor Imaging: An In Vivo Study in Preterm Lambs

PubMed Central

Skiöld, Béatrice; Wu, Qizhu; Hooper, Stuart B.; Davis, Peter G.; McIntyre, Richard; Tolcos, Mary; Pearson, James; Vreys, Ruth; Egan, Gary F.; Barton, Samantha K.; Cheong, Jeanie L. Y.; Polglase, Graeme R.

2014-01-01

Background and Aim High tidal volume (VT) ventilation during resuscitation of preterm lambs results in brain injury evident histologically within hours after birth. We aimed to investigate whether magnetic resonance spectroscopy (MRS) and/or diffusion tensor imaging (DTI) can be used for early in vivo detection of ventilation-induced brain injury in preterm lambs. Methods Newborn lambs (0.85 gestation) were stabilized with a “protective ventilation” strategy (PROT, n = 7: prophylactic Curosurf, sustained inflation, VT 7 mL/kg, positive end expiratory pressure (PEEP) 5 cmH2O) or an initial 15 minutes of “injurious ventilation” (INJ, n = 10: VT 12 mL/kg, no PEEP, late Curosurf) followed by PROT ventilation for the remainder of the experiment. At 1 hour, lambs underwent structural magnetic resonance imaging (Siemens, 3 Tesla). For measures of mean/axial/radial diffusivity (MD, AD, RD) and fractional anisotropy (FA), 30 direction DTI was performed. Regions of interests encompassed the thalamus, internal capsule, periventricular white matter and the cerebellar vermis. MRS was performed using a localized single-voxel (15×15×20 mm3, echo time 270 ms) encompassing suptratentorial deep nuclear grey matter and central white matter. Peak-area ratios for lactate (Lac) relative to N-acetylaspartate (NAA), choline (Cho) and creatine (Cr) were calculated. Groups were compared using 2-way RM-ANOVA, Mann-Whitney U-test and Spearman's correlations. Results No cerebral injury was seen on structural MR images. Lambs in the INJ group had higher mean FA and lower mean RD in the thalamus compared to PROT lambs, but not in the other regions of interest. Peak-area lactate ratios >1.0 was only seen in INJ lambs. A trend of higher mean peak-area ratios for Lac/Cr and Lac/Cho was seen, which correlated with lower pH in both groups. Conclusion Acute changes in brain diffusion measures and metabolite peak-area ratios were observed after injurious ventilation. Early MRS/DTI is able to detect the initiation of ventilation-induced brain injury. PMID:24759765

Human brain MRI at 500 MHz, scientific perspectives and technological challenges

NASA Astrophysics Data System (ADS)

Le Bihan, Denis; Schild, Thierry

2017-03-01

The understanding of the human brain is one of the main scientific challenges of the 21st century. In the early 2000s the French Alternative Energies and Atomic Energy Commission launched a program to conceive and build a ‘human brain explorer’, the first human MRI scanner operating at 11.7 T. This scanner was envisioned to be part of the ambitious French-German project Iseult, bridging together industrial and academic partners to push the limits of molecular neuroimaging, from mouse to man, using ultra-high field MRI. In this article we provide a summary of the main neuroscience and medical targets of the Iseult project, mainly to acquire within timescales compatible with human tolerances images at a scale of 100 μm at which everything remains to discover, and to create new approaches to develop new imaging biomarkers for specific neurological and psychiatric disorders. The system specifications, the technological challenges, in terms of magnet design, winding technology, cryogenics, quench protection, stability control, and the solutions which have been chosen to overcome them and build this outstanding instrument are provided. Lines of the research and development which will be necessary to fully exploit the potential of this and other UHF MRI scanners are also outlined.

Brain Injury in Neonates with Complex Congenital Heart Disease: What Is the Predictive Value of MRI in the Fetal Period?

PubMed

Brossard-Racine, M; du Plessis, A; Vezina, G; Robertson, R; Donofrio, M; Tworetzky, W; Limperopoulos, C

2016-07-01

Brain injury in neonates with congenital heart disease is an important predictor of adverse neurodevelopmental outcome. Impaired brain development in congenital heart disease may have a prenatal origin, but the sensitivity and specificity of fetal brain MR imaging for predicting neonatal brain lesions are currently unknown. We sought to determine the value of conventional fetal MR imaging for predicting abnormal findings on neonatal preoperative MR imaging in neonates with complex congenital heart disease. MR imaging studies were performed in 103 fetuses with confirmed congenital heart disease (mean gestational age, 31.57 ± 3.86 weeks) and were repeated postnatally before cardiac surgery (mean age, 6.8 ± 12.2 days). Each MR imaging study was read by a pediatric neuroradiologist. Brain abnormalities were detected in 17/103 (16%) fetuses by fetal MR imaging and in 33/103 (32%) neonates by neonatal MR imaging. Only 9/33 studies with abnormal neonatal findings were preceded by abnormal findings on fetal MR imaging. The sensitivity and specificity of conventional fetal brain MR imaging for predicting neonatal brain abnormalities were 27% and 89%, respectively. Brain abnormalities detected by in utero MR imaging in fetuses with congenital heart disease are associated with higher risk of postnatal preoperative brain injury. However, a substantial proportion of anomalies on postnatal MR imaging were not present on fetal MR imaging; this result is likely due to the limitations of conventional fetal MR imaging and the emergence of new lesions that occurred after the fetal studies. Postnatal brain MR imaging studies are needed to confirm the presence of injury before open heart surgery. © 2016 by American Journal of Neuroradiology.

Compact and mobile high resolution PET brain imager

DOEpatents

Majewski, Stanislaw [Yorktown, VA; Proffitt, James [Newport News, VA

2011-02-08

A brain imager includes a compact ring-like static PET imager mounted in a helmet-like structure. When attached to a patient's head, the helmet-like brain imager maintains the relative head-to-imager geometry fixed through the whole imaging procedure. The brain imaging helmet contains radiation sensors and minimal front-end electronics. A flexible mechanical suspension/harness system supports the weight of the helmet thereby allowing for patient to have limited movements of the head during imaging scans. The compact ring-like PET imager enables very high resolution imaging of neurological brain functions, cancer, and effects of trauma using a rather simple mobile scanner with limited space needs for use and storage.

Case 254: Posttraumatic Migrating Fat Embolus Causing Fat Emboli Syndrome.

PubMed

Molière, Sébastien; Kremer, Stéphane; Bierry, Guillaume

2018-06-01

History An otherwise healthy 18-year-old man was admitted to the emergency department with a closed displaced fracture of the left femoral shaft ( Fig 1 ) after a high-velocity motorbike accident. At admission, other physical examination findings were unremarkable. Initial unenhanced and contrast material-enhanced (120 mL of Iomeron 400; Bracco Imaging, Milan, Italy) computed tomography (CT) was performed in the arterial and venous phases from the head to the knees. No abnormalities were noted in the brain or chest at initial CT. [Figure: see text] Within a few hours, the patient developed sudden mental confusion and severe hypoxemia, with rapidly worsening tachypnea and perturbed arterial blood gas with low partial pressure of oxygen (61 mmHg [8.1 kPa]; normal range, 75-100 mmHg [10.0-13.3 kPa]) and low partial pressure of carbon dioxide (32 mmHg [4.3 kPa]; normal range, 38-42 mmHg [5.1-5.6 kPa]). A second contrast-enhanced chest CT examination and initial brain magnetic resonance (MR) imaging were performed. Femoral fracture was stabilized with external fixation, and the patient was admitted to the intensive care unit, with progressive neurologic recovery at day 3 and respiratory improvement at day 4. Treatment included intubation with mechanical ventilation and intravenous administration of steroids and noradrenaline. Afterward, the femoral fracture was stabilized with an intramedullary nail. The patient made a full neurologic recovery 1 month after the accident.

Dissociation of Self-Motion and Object Motion by Linear Population Decoding That Approximates Marginalization.

PubMed

Sasaki, Ryo; Angelaki, Dora E; DeAngelis, Gregory C

2017-11-15

We use visual image motion to judge the movement of objects, as well as our own movements through the environment. Generally, image motion components caused by object motion and self-motion are confounded in the retinal image. Thus, to estimate heading, the brain would ideally marginalize out the effects of object motion (or vice versa), but little is known about how this is accomplished neurally. Behavioral studies suggest that vestibular signals play a role in dissociating object motion and self-motion, and recent computational work suggests that a linear decoder can approximate marginalization by taking advantage of diverse multisensory representations. By measuring responses of MSTd neurons in two male rhesus monkeys and by applying a recently-developed method to approximate marginalization by linear population decoding, we tested the hypothesis that vestibular signals help to dissociate self-motion and object motion. We show that vestibular signals stabilize tuning for heading in neurons with congruent visual and vestibular heading preferences, whereas they stabilize tuning for object motion in neurons with discrepant preferences. Thus, vestibular signals enhance the separability of joint tuning for object motion and self-motion. We further show that a linear decoder, designed to approximate marginalization, allows the population to represent either self-motion or object motion with good accuracy. Decoder weights are broadly consistent with a readout strategy, suggested by recent computational work, in which responses are decoded according to the vestibular preferences of multisensory neurons. These results demonstrate, at both single neuron and population levels, that vestibular signals help to dissociate self-motion and object motion. SIGNIFICANCE STATEMENT The brain often needs to estimate one property of a changing environment while ignoring others. This can be difficult because multiple properties of the environment may be confounded in sensory signals. The brain can solve this problem by marginalizing over irrelevant properties to estimate the property-of-interest. We explore this problem in the context of self-motion and object motion, which are inherently confounded in the retinal image. We examine how diversity in a population of multisensory neurons may be exploited to decode self-motion and object motion from the population activity of neurons in macaque area MSTd. Copyright © 2017 the authors 0270-6474/17/3711204-16$15.00/0.

Pulse Coupled Neural Networks for the Segmentation of Magnetic Resonance Brain Images.

DTIC Science & Technology

1996-12-01

PULSE COUPLED NEURAL NETWORKS FOR THE SEGMENTATION OF MAGNETIC RESONANCE BRAIN IMAGES THESIS Shane Lee Abrahamson First Lieutenant, USAF AFIT/GCS/ENG...COUPLED NEURAL NETWORKS FOR THE SEGMENTATION OF MAGNETIC RESONANCE BRAIN IMAGES THESIS Shane Lee Abrahamson First Lieutenant, USAF AFIT/GCS/ENG/96D-01...research develops an automated method for segmenting Magnetic Resonance (MR) brain images based on Pulse Coupled Neural Networks (PCNN). MR brain image

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

N-[18F]-FluoropropylJDTic for κ-opioid receptor PET imaging: Radiosynthesis, pre-clinical evaluation, and metabolic investigation in comparison with parent JDTic.

PubMed

Schmitt, Sébastien; Delamare, Jérôme; Tirel, Olivier; Fillesoye, Fabien; Dhilly, Martine; Perrio, Cécile

2017-01-01

To image kappa opioid receptor (KOR) for preclinical studies, N-fluoropropylJDTic 9 derived from the best-established KOR antagonist JDTic, was labeled with fluorine-18. Radiosynthesis of [ 18 F]9 was achieved according to an automated two-step procedure from [ 18 F]-fluoride. Peripheral and cerebral distributions were determined by ex vivo experiments and by PET imaging in mouse. Radiometabolism studies were performed both in vivo in mice and in vitro in mouse and human liver microsomes. Identification of the major metabolic fragmentations was carried out by UPLC-MS analysis of enzymatic cleavage of non-radioactive ligand 9. Microsomal metabolic degradation of parent JDTic was also achieved for comparison. The radiotracer [ 18 F]9 was produced after 140±5min total synthesis time (2.2±0.4% not decay corrected radiochemical yield) with a specific activity of 41-89GBq/μmol (1.1-2.4Ci/μmol). Peripheral and regional brain distributions of [ 18 F]9 were consistent with known KOR locations but no significant specific binding in brain was shown. [ 18 F]9 presented a typical hepatobiliary and renal elimination, and was rapidly metabolized. The in vivo and in vitro radiometabolic profiles of [ 18 F]9 were similar. Piperidine 12 was identified as the major metabolic fragment of the non-radioactive ligand 9. JDTic 7 was found to be much more stable than 9. Although the newly proposed radioligand [ 18 F]9 was concluded to be not suitable for KOR PET imaging due to the formation of brain penetrating radiometabolites, our findings highlight the metabolic stability of JDTic and may help in the design of novel JDTic derivatives for in vivo applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Blurring the boundaries between frame-based and frameless stereotaxy: feasibility study for brain biopsies performed with the use of a head-mounted robot.

PubMed

Grimm, Florian; Naros, Georgios; Gutenberg, Angelika; Keric, Naureen; Giese, Alf; Gharabaghi, Alireza

2015-09-01

Frame-based stereotactic interventions are considered the gold standard for brain biopsies, but they have limitations with regard to flexibility and patient comfort because of the bulky head ring attached to the patient. Frameless image guidance systems that use scalp fiducial markers offer more flexibility and patient comfort but provide less stability and accuracy during drilling and biopsy needle positioning. Head-mounted robot-guided biopsies could provide the advantages of these 2 techniques without the downsides. The goal of this study was to evaluate the feasibility and safety of a robotic guidance device, affixed to the patient's skull through a small mounting platform, for use in brain biopsy procedures. This was a retrospective study of 37 consecutive patients who presented with supratentorial lesions and underwent brain biopsy procedures in which a surgical guidance robot was used to determine clinical outcomes and technical procedural operability. The portable head-mounted device was well tolerated by the patients and enabled stable drilling and needle positioning during surgery. Flexible adjustments of predefined paths and selection of new trajectories were successfully performed intraoperatively without the need for manual settings and fixations. The patients experienced no permanent deficits or infections after surgery. The head-mounted robot-guided approach presented here combines the stability of a bone-mounted set-up with the flexibility and tolerability of frameless systems. By reducing human interference (i.e., manual parameter settings, calibrations, and adjustments), this technology might be particularly useful in neurosurgical interventions that necessitate multiple trajectories.

Dynamic studies of small animals with a four-color diffuse optical tomography imager

NASA Astrophysics Data System (ADS)

Schmitz, Christoph H.; Graber, Harry L.; Pei, Yaling; Farber, Mark; Stewart, Mark; Levina, Rita D.; Levin, Mikhail B.; Xu, Yong; Barbour, Randall L.

2005-09-01

We present newly developed instrumentation for full-tomographic four-wavelength, continuous wave, diffuse optical tomography (DOT) imaging on small animals. A small-animal imaging stage was constructed, from materials compatible with in-magnet studies, which offers stereotaxic fixation of the animal and precise, stable probe positioning. Instrument performance, based on calibration and phantom studies, demonstrates excellent long-term signal stability. DOT measurements of the functional rat brain response to electric paw stimulation are presented, and these demonstrate high data quality and excellent sensitivity to hemodynamic changes. A general linear model analysis on individual trials is used to localize and quantify the occurrence of functional behavior associated with the different hemoglobin state responses. Statistical evaluation of outcomes of individual trials is employed to identify significant regional response variations for different stimulation sites. Image results reveal a diffuse cortical response and a strong reaction of the thalamus, both indicative of activation of pain pathways by the stimulation. In addition, a weaker lateralized functional component is observed in the brain response, suggesting presence of motor activation. An important outcome of the experiment is that it shows that reactions to individual provocations can be monitored, without having to resort to signal averaging. Thus the described technology may be useful for studies of long-term trends in hemodynamic response, as would occur, for example, in behavioral studies involving freely moving animals.

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

NASA Astrophysics Data System (ADS)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

Alzheimer's disease imaging biomarkers using small-angle x-ray scattering

NASA Astrophysics Data System (ADS)

Choi, Mina; Alam, Nadia; Dahal, Eshan; Ghammraoui, Bahaa; Badano, Aldo

2016-03-01

There is a need for novel imaging techniques for the earlier detection of Alzheimer's disease (AD). Two hallmarks of AD are amyloid beta (Aβ) plaques and tau tangles that are formed in the brain. Well-characterized x-ray cross sections of Aβ and tau proteins in a variety of structural states could potentially be used as AD biomarkers for small-angle x-ray scattering (SAXS) imaging without the need for injectable probes or contrast agents. First, however, the protein structures must be controlled and measured to determine accurate biomarkers for SAXS imaging. Here we report SAXS measurements of Aβ42 and tau352 in a 50% dimethyl sulfoxide (DMSO) solution in which these proteins are believed to remain monomeric because of the stabilizing interaction of DMSO solution. Our SAXS analysis showed the aggregation of both proteins. In particular, we found that the aggregation of Aβ42 slowly progresses with time in comparison to tau352 that aggregates at a faster rate and reaches a steady-state. Furthermore, the measured signals were compared to the theoretical SAXS profiles of Aβ42 monomer, Aβ42 fibril, and tau352 that were computed from their respective protein data bank structures. We have begun the work to systematically control the structural states of these proteins in vitro using various solvent conditions. Our future work is to utilize the distinct SAXS profiles of various structural states of Aβ and tau to build a library of signals of interest for SAXS imaging in brain tissue.

One-pot synthesis of water-soluble superparamagnetic iron oxide nanoparticles and their MRI contrast effects in the mouse brains.

PubMed

Wang, Jun; Zhang, Baolin; Wang, Lei; Wang, Ming; Gao, Fabao

2015-03-01

Water-soluble superparamagnetic iron oxide nanoparticles (SPIONs) were synthesized by the thermal decomposition of iron (III) acetylacetonate (Fe(acac)3) in the mixture of poly(ethylene glycol) (PEG) and poly(ethylene imine) (PEI). The average sizes of the SPIONs are in the range of 6-12nm, which could be tuned by adjusting the synthesis temperature and molecular weight of PEI. Benefiting from the coating of hydrophilic PEG and PEI, the resulted SPIONs showed excellent colloidal stability in deionized water and other physiological buffers. The XRD patterns indicate that the obtained SPIONs are magnetite. The PEG/PEI-SPIONs exhibited high r2/r1 ratio. In vivo magnetic resonance imaging (MRI) of the mouse brains after intravenous injection of the SPIONs showed their good contrast effect. Considering the facile fabrication process and excellent imaging performance of the water soluble PEG-SPIONs and PEG/PEI-SPIONs, it is believed that the SPIONs will find great potential in advanced MRI. Copyright © 2014 Elsevier B.V. All rights reserved.

Disposition of 3H-selamectin and 3H-ivermectin in the brain of the cat flea Ctenocephalides felis felis using micro-image analysis.

PubMed

Phipps, A N; Martin-Short, M R; Littlewood, L; Blanchflower, S E; Gration, K A F

2005-07-15

In addition to intrinsic potency and metabolic stability, the disposition of an antiparasitic drug within the target parasite plays a major role in determining drug activity. A novel technique that allows the disposition of radiolabelled drugs to be visualised within the body of the cat flea (Ctenocephalides felis felis) is described. The concentrations of two macrocyclic lactones, (3)H-selamectin and (3)H-ivermectin, within the supra- and sub-oesophageal ganglia of the flea brain following in vitro feeding of fleas on different doses of drug solubilised in calf blood have been measured. Drug disposition was visualised in cryostat sections of fleas using a micro-image analysis (MIA). A relationship between the concentration of radioactivity in the ganglia and the dose of drug in the blood meal was obtained. The concentration of selamectin in the ganglia was significantly higher than ivermectin at all doses investigated. The enhanced concentration of selamectin, at a site rich in glutamate-gated chloride channels may, in part, explain the higher potency of selamectin against fleas compared to ivermectin.

Longitudinal assessment of childhood optic gliomas: relationship between flicker visual evoked potentials and magnetic resonance imaging findings.

PubMed

Falsini, Benedetto; Ziccardi, Lucia; Lazzareschi, Ilaria; Ruggiero, Antonio; Placentino, Luca; Dickmann, Anna; Liotti, Lucia; Piccardi, Marco; Balestrazzi, Emilio; Colosimo, Cesare; Di Rocco, Concezio; Riccardi, Riccardo

2008-05-01

The aim of this study was to evaluate longitudinally functional and neuro-radiologic findings in childhood optic gliomas (OG), by comparing flicker visual evoked potentials (F-VEPs) with brain magnetic resonance imaging (MRI) changes. Fourteen children (age range: 1-13 years) with OGs underwent serial F-VEP, MRI and neuro-ophthalmic examinations over a 38 month (median, range: 6-76) follow-up. F-VEPs were elicited by 8 Hz sine-wave flicker stimuli presented in a mini-Ganzfeld. Contrast-enhanced MRI examinations were performed. Results of both tests were blindly assessed by independent evaluators. F-VEPs were judged to be improved, stable or worsened if changes in the amplitude and/or phase angle of the response exceeded the limits of test-retest variability (+/-90th percentile) established for the same patients. MRI results were judged to show regression, stabilization or progression of OG based on its changes in size (+/-20%) or extension. Two to seven pairs of F-VEP/MRI examinations per patient (median: 4) were collected. Based on a total of 38 pairs of F-VEP/MRI examinations, both tests agreed in showing worsening (progression), stabilization and improvement (regression) in 5, 15 and 10 cases, respectively. In 3 cases, F-VEPs showed a worsening and MRI a stabilization, while in 5 cases F-VEPs showed an improvement and MRI a stabilization. Agreement between F-VEP and MRI changes was 78.9% (95% CI: +/- 37%, K statistics = 0.67, P < 0.001). The results indicate that longitudinal F-VEP changes can predict changes in MRI-assessed OG size and extension, providing a non-invasive functional assay, complementary to neuro-imaging, for OG follow-up.

Automated segmentation of three-dimensional MR brain images

NASA Astrophysics Data System (ADS)

Park, Jonggeun; Baek, Byungjun; Ahn, Choong-Il; Ku, Kyo Bum; Jeong, Dong Kyun; Lee, Chulhee

2006-03-01

Brain segmentation is a challenging problem due to the complexity of the brain. In this paper, we propose an automated brain segmentation method for 3D magnetic resonance (MR) brain images which are represented as a sequence of 2D brain images. The proposed method consists of three steps: pre-processing, removal of non-brain regions (e.g., the skull, meninges, other organs, etc), and spinal cord restoration. In pre-processing, we perform adaptive thresholding which takes into account variable intensities of MR brain images corresponding to various image acquisition conditions. In segmentation process, we iteratively apply 2D morphological operations and masking for the sequences of 2D sagittal, coronal, and axial planes in order to remove non-brain tissues. Next, final 3D brain regions are obtained by applying OR operation for segmentation results of three planes. Finally we reconstruct the spinal cord truncated during the previous processes. Experiments are performed with fifteen 3D MR brain image sets with 8-bit gray-scale. Experiment results show the proposed algorithm is fast, and provides robust and satisfactory results.

Improving the convergence rate in affine registration of PET and SPECT brain images using histogram equalization.

PubMed

Salas-Gonzalez, D; Górriz, J M; Ramírez, J; Padilla, P; Illán, I A

2013-01-01

A procedure to improve the convergence rate for affine registration methods of medical brain images when the images differ greatly from the template is presented. The methodology is based on a histogram matching of the source images with respect to the reference brain template before proceeding with the affine registration. The preprocessed source brain images are spatially normalized to a template using a general affine model with 12 parameters. A sum of squared differences between the source images and the template is considered as objective function, and a Gauss-Newton optimization algorithm is used to find the minimum of the cost function. Using histogram equalization as a preprocessing step improves the convergence rate in the affine registration algorithm of brain images as we show in this work using SPECT and PET brain images.

A Primer on Brain Imaging in Developmental Psychopathology: What Is It Good For?

ERIC Educational Resources Information Center

Pine, Daniel S.

2006-01-01

This primer introduces a Special Section on brain imaging, which includes a commentary and 10 data papers presenting applications of brain imaging to questions on developmental psychopathology. This primer serves two purposes. First, the article summarizes the strength and weaknesses of various brain-imaging techniques typically employed in…

Brain MR image segmentation using NAMS in pseudo-color.

PubMed

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

High-Speed and Scalable Whole-Brain Imaging in Rodents and Primates.

PubMed

Seiriki, Kaoru; Kasai, Atsushi; Hashimoto, Takeshi; Schulze, Wiebke; Niu, Misaki; Yamaguchi, Shun; Nakazawa, Takanobu; Inoue, Ken-Ichi; Uezono, Shiori; Takada, Masahiko; Naka, Yuichiro; Igarashi, Hisato; Tanuma, Masato; Waschek, James A; Ago, Yukio; Tanaka, Kenji F; Hayata-Takano, Atsuko; Nagayasu, Kazuki; Shintani, Norihito; Hashimoto, Ryota; Kunii, Yasuto; Hino, Mizuki; Matsumoto, Junya; Yabe, Hirooki; Nagai, Takeharu; Fujita, Katsumasa; Matsuda, Toshio; Takuma, Kazuhiro; Baba, Akemichi; Hashimoto, Hitoshi

2017-06-21

Subcellular resolution imaging of the whole brain and subsequent image analysis are prerequisites for understanding anatomical and functional brain networks. Here, we have developed a very high-speed serial-sectioning imaging system named FAST (block-face serial microscopy tomography), which acquires high-resolution images of a whole mouse brain in a speed range comparable to that of light-sheet fluorescence microscopy. FAST enables complete visualization of the brain at a resolution sufficient to resolve all cells and their subcellular structures. FAST renders unbiased quantitative group comparisons of normal and disease model brain cells for the whole brain at a high spatial resolution. Furthermore, FAST is highly scalable to non-human primate brains and human postmortem brain tissues, and can visualize neuronal projections in a whole adult marmoset brain. Thus, FAST provides new opportunities for global approaches that will allow for a better understanding of brain systems in multiple animal models and in human diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Rehabilitation-triggered cortical plasticity after stroke: in vivo imaging at multiple scales (Conference Presentation)

NASA Astrophysics Data System (ADS)

Allegra Mascaro, Anna Letizia; Conti, Emilia; Lai, Stefano; Spalletti, Cristina; Di Giovanna, Antonino Paolo; Alia, Claudia; Panarese, Alessandro; Sacconi, Leonardo; Micera, Silvestro; Caleo, Matteo; Pavone, Francesco S.

2017-02-01

Neurorehabilitation protocols based on the use of robotic devices provide a highly repeatable therapy and have recently shown promising clinical results. Little is known about how rehabilitation molds the brain to promote motor recovery of the affected limb. We used a custom-made robotic platform that provides quantitative assessment of forelimb function in a retraction test. Complementary imaging techniques allowed us to access to the multiple facets of robotic rehabilitation-induced cortical plasticity after unilateral photothrombotic stroke in mice Primary Motor Cortex (Caudal Forelimb Area - CFA). First, we analyzed structural features of vasculature and dendritic reshaping in the peri-infarct area with two-photon fluorescence microscopy. Longitudinal analysis of dendritic branches and spines of pyramidal neurons suggests that robotic rehabilitation promotes the stabilization of peri-infarct cortical excitatory circuits, which is not accompanied by consistent vascular reorganization towards pre-stroke conditions. To investigate if this structural stabilization was linked to functional remapping, we performed mesoscale wide-field imaging on GCaMP6 mice while performing the motor task on the robotic platform. We revealed temporal and spatial features of the motor-triggered cortical activation, shining new light on rehabilitation-induced functional remapping of the ipsilesional cortex. Finally, by using an all-optical approach that combines optogenetic activation of the contralesional hemisphere and wide-field functional imaging of peri-infarct area, we dissected the effect of robotic rehabilitation on inter-hemispheric cortico-cortical connectivity.

Stability of Gradient Field Corrections for Quantitative Diffusion MRI.

PubMed

Rogers, Baxter P; Blaber, Justin; Welch, E Brian; Ding, Zhaohua; Anderson, Adam W; Landman, Bennett A

2017-02-11

In magnetic resonance diffusion imaging, gradient nonlinearity causes significant bias in the estimation of quantitative diffusion parameters such as diffusivity, anisotropy, and diffusion direction in areas away from the magnet isocenter. This bias can be substantially reduced if the scanner- and coil-specific gradient field nonlinearities are known. Using a set of field map calibration scans on a large (29 cm diameter) phantom combined with a solid harmonic approximation of the gradient fields, we predicted the obtained b-values and applied gradient directions throughout a typical field of view for brain imaging for a typical 32-direction diffusion imaging sequence. We measured the stability of these predictions over time. At 80 mm from scanner isocenter, predicted b-value was 1-6% different than intended due to gradient nonlinearity, and predicted gradient directions were in error by up to 1 degree. Over the course of one month the change in these quantities due to calibration-related factors such as scanner drift and variation in phantom placement was <0.5% for b-values, and <0.5 degrees for angular deviation. The proposed calibration procedure allows the estimation of gradient nonlinearity to correct b-values and gradient directions ahead of advanced diffusion image processing for high angular resolution data, and requires only a five-minute phantom scan that can be included in a weekly or monthly quality assurance protocol.

Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM

NASA Astrophysics Data System (ADS)

Kutten, Kwame S.; Vogelstein, Joshua T.; Charon, Nicolas; Ye, Li; Deisseroth, Karl; Miller, Michael I.

2016-04-01

The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for discovering which regions contain signals of interest. Manually annotating whole-brain, terabyte CLARITY images is difficult, time-consuming, subjective, and error-prone. Automatically registering CLARITY images to a pre-annotated brain atlas offers a solution, but is difficult for several reasons. Removal of the brain from the skull and subsequent storage and processing cause variable non-rigid deformations, thus compounding inter-subject anatomical variability. Additionally, the signal in CLARITY images arises from various biochemical contrast agents which only sparsely label brain structures. This sparse labeling challenges the most commonly used registration algorithms that need to match image histogram statistics to the more densely labeled histological brain atlases. The standard method is a multiscale Mutual Information B-spline algorithm that dynamically generates an average template as an intermediate registration target. We determined that this method performs poorly when registering CLARITY brains to the Allen Institute's Mouse Reference Atlas (ARA), because the image histogram statistics are poorly matched. Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically finds the brain boundary and learns the optimal deformation between the brain and atlas masks. Using Mask-LDDMM without an average template provided better results than the standard approach when registering CLARITY brains to the ARA. The LDDMM pipelines developed here provide a fast automated way to anatomically annotate CLARITY images; our code is available as open source software at http://NeuroData.io.

Surfactants, not size or zeta-potential influence blood-brain barrier passage of polymeric nanoparticles.

PubMed

Voigt, Nadine; Henrich-Noack, Petra; Kockentiedt, Sarah; Hintz, Werner; Tomas, Jürgen; Sabel, Bernhard A

2014-05-01

Nanoparticles (NP) can deliver drugs across the blood-brain barrier (BBB), but little is known which of the factors surfactant, size and zeta-potential are essential for allowing BBB passage. To this end we designed purpose-built fluorescent polybutylcyanoacrylate (PBCA) NP and imaged the NP's passage over the blood-retina barrier - which is a model of the BBB - in live animals. Rats received intravenous injections of fluorescent PBCA-NP fabricated by mini-emulsion polymerisation to obtain various NP's compositions that varied in surfactants (non-ionic, anionic, cationic), size (67-464nm) and zeta-potential. Real-time imaging of retinal blood vessels and retinal tissue was carried out with in vivo confocal neuroimaging (ICON) before, during and after NP's injection. Successful BBB passage with subsequent cellular labelling was achieved if NP were fabricated with non-ionic surfactants or cationic stabilizers but not when anionic compounds were added. NP's size and charge had no influence on BBB passage and cell labelling. This transport was not caused by an unspecific opening of the BBB because control experiments with injections of unlabelled NP and fluorescent dye (to test a "door-opener" effect) did not lead to parenchymal labelling. Thus, neither NP's size nor chemo-electric charge, but particle surface is the key factor determining BBB passage. This result has important implications for NP engineering in medicine: depending on the surfactant, NP can serve one of two opposite functions: while non-ionic tensides enhance brain up-take, addition of anionic tensides prevents it. NP can now be designed to specifically enhance drug delivery to the brain or, alternatively, to prevent brain penetration so to reduce unwanted psychoactive effects of drugs or prevent environmental nanoparticles from entering tissue of the central nervous system. Copyright © 2014 Elsevier B.V. All rights reserved.

Multicolor Fluorescence Imaging of Traumatic Brain Injury in a Cryolesion Mouse Model

PubMed Central

2012-01-01

Traumatic brain injury is characterized by initial tissue damage, which then can lead to secondary processes such as cell death and blood-brain-barrier disruption. Clinical and preclinical studies of traumatic brain injury typically employ anatomical imaging techniques and there is a need for new molecular imaging methods that provide complementary biochemical information. Here, we assess the ability of a targeted, near-infrared fluorescent probe, named PSS-794, to detect cell death in a brain cryolesion mouse model that replicates certain features of traumatic brain injury. In short, the model involves brief contact of a cold rod to the head of a living, anesthetized mouse. Using noninvasive whole-body fluorescence imaging, PSS-794 permitted visualization of the cryolesion in the living animal. Ex vivo imaging and histological analysis confirmed PSS-794 localization to site of brain cell death. The nontargeted, deep-red Tracer-653 was validated as a tracer dye for monitoring blood-brain-barrier disruption, and a binary mixture of PSS-794 and Tracer-653 was employed for multicolor imaging of cell death and blood-brain-barrier permeability in a single animal. The imaging data indicates that at 3 days after brain cryoinjury the amount of cell death had decreased significantly, but the integrity of the blood-brain-barrier was still impaired; at 7 days, the blood-brain-barrier was still three times more permeable than before cryoinjury. PMID:22860222

Bilateral vertebral artery lesion after dislocating cervical spine trauma. A case report.

PubMed

Wirbel, R; Pistorius, G; Braun, C; Eichler, A; Mutschler, W

1996-06-01

This case report illustrates the problems associated with diagnosis and management of vertebral artery injuries resulting from dislocating cervical spine trauma. Treatment involved the principles of anterior stabilization of dislocating cervical spine fracture as well as the diagnostic procedures and therapeutic modalities appropriate for vertebral artery lesions. Because vertebral artery injuries with cervical spine trauma are rarely symptomatic, they can easily be overlooked. Bilateral or dominant vertebral artery occlusion, however, may cause fatal ischemic damage to the brain stem and cerebellum. Cervical spine dislocation was stabilized immediately after admission using internal fixation by ventral plate and corticocancellous bone graft. Immediate angiography was performed when brain stem neurologic dysfunction manifested 36 hours after surgery. The patient was treated with anticoagulation, osmotherapy, and controlled hypertension. A fatal outcome resulted in this case of dominant left vertebral artery occlusion. Necropsy even revealed bilateral vertebral artery damage at the level of the osseous lesion. The possibility of the complication of a vertebral artery lesion should be kept in mind when examining patients with cervical spine trauma, especially in patients with fracture-dislocation. Immediate identification by vertebral angiography, magnetic resonance imaging, or thin-slice computed tomography scan is necessary for optimal management of this injury.

Quantitative Susceptibility Mapping after Sports-Related Concussion.

PubMed

Koch, K M; Meier, T B; Karr, R; Nencka, A S; Muftuler, L T; McCrea, M

2018-06-07

Quantitative susceptibility mapping using MR imaging can assess changes in brain tissue structure and composition. This report presents preliminary results demonstrating changes in tissue magnetic susceptibility after sports-related concussion. Longitudinal quantitative susceptibility mapping metrics were produced from imaging data acquired from cohorts of concussed and control football athletes. One hundred thirty-six quantitative susceptibility mapping datasets were analyzed across 3 separate visits (24 hours after injury, 8 days postinjury, and 6 months postinjury). Longitudinal quantitative susceptibility mapping group analyses were performed on stability-thresholded brain tissue compartments and selected subregions. Clinical concussion metrics were also measured longitudinally in both cohorts and compared with the measured quantitative susceptibility mapping. Statistically significant increases in white matter susceptibility were identified in the concussed athlete group during the acute (24 hour) and subacute (day 8) period. These effects were most prominent at the 8-day visit but recovered and showed no significant difference from controls at the 6-month visit. The subcortical gray matter showed no statistically significant group differences. Observed susceptibility changes after concussion appeared to outlast self-reported clinical recovery metrics at a group level. At an individual subject level, susceptibility increases within the white matter showed statistically significant correlations with return-to-play durations. The results of this preliminary investigation suggest that sports-related concussion can induce physiologic changes to brain tissue that can be detected using MR imaging-based magnetic susceptibility estimates. In group analyses, the observed tissue changes appear to persist beyond those detected on clinical outcome assessments and were associated with return-to-play duration after sports-related concussion. © 2018 by American Journal of Neuroradiology.

Fluorine magnetic resonance spectroscopy measurement of brain fluvoxamine and fluoxetine in pediatric patients treated for pervasive developmental disorders.

PubMed

Strauss, Wayne L; Unis, Alan S; Cowan, Charles; Dawson, Geraldine; Dager, Stephen R

2002-05-01

Pediatric populations, including those with autistic disorder or other pervasive developmental disorders, increasingly are being prescribed selective serotonin reuptake inhibitors (SSRIs). Little is known about the age-related brain pharmacokinetics of SSRIs; there is a lack of data regarding optimal dosing of medications for children. The authors used fluorine magnetic resonance spectroscopy ((19)F MRS) to evaluate age effects on whole-brain concentrations of fluvoxamine and fluoxetine in children taking SSRIs. Twenty-one pediatric subjects with diagnoses of autistic disorder or other pervasive developmental disorders, 6-15 years old and stabilized with a consistent dose of fluvoxamine or fluoxetine, were recruited for the study; 16 successfully completed the imaging protocol. Whole-brain drug levels in this group were compared to similarly acquired data from 28 adults. A significant relationship between dose and brain drug concentration was observed for both drugs across the age range studied. Brain fluvoxamine concentration in the children was lower, consistent with a lower dose/body mass drug prescription; when brain concentration was adjusted for dose/mass, age effects were no longer significant. Brain fluoxetine concentration was similar between age groups; no significant age effects on brain fluoxetine drug levels remained after adjustment for dose/mass. Observations of brain fluoxetine bioavailability and elimination half-life also were similar between age groups. These findings suggest that fluvoxamine or fluoxetine prescriptions adjusted for dose/mass are an acceptable treatment approach for medicating children with autistic disorder or other pervasive developmental disorders. It must be determined whether these findings can be generalized to other pediatric populations.

Development of PET/MRI with insertable PET for simultaneous PET and MR imaging of human brain.

PubMed

Jung, Jin Ho; Choi, Yong; Jung, Jiwoong; Kim, Sangsu; Lim, Hyun Keong; Im, Ki Chun; Oh, Chang Hyun; Park, Hyun-wook; Kim, Kyung Min; Kim, Jong Guk

2015-05-01

The purpose of this study was to develop a dual-modality positron emission tomography (PET)/magnetic resonance imaging (MRI) with insertable PET for simultaneous PET and MR imaging of the human brain. The PET detector block was composed of a 4 × 4 matrix of detector modules, each consisting of a 4 × 4 array LYSO coupled to a 4 × 4 Geiger-mode avalanche photodiode (GAPD) array. The PET insert consisted of 18 detector blocks, circularly mounted on a custom-made plastic base to form a ring with an inner diameter of 390 mm and axial length of 60 mm. The PET gantry was shielded with gold-plated conductive fabric tapes with a thickness of 0.1 mm. The charge signals of PET detector transferred via 4 m long flat cables were fed into the position decoder circuit. The flat cables were shielded with a mesh-type aluminum sheet with a thickness of 0.24 mm. The position decoder circuit and field programmable gate array-embedded DAQ modules were enclosed in an aluminum box with a thickness of 10 mm and located at the rear of the MR bore inside the MRI room. A 3-T human MRI system with a Larmor frequency of 123.7 MHz and inner bore diameter of 60 cm was used as the PET/MRI hybrid system. A custom-made radio frequency (RF) coil with an inner diameter of 25 cm was fabricated. The PET was positioned between gradient and the RF coils. PET performance was measured outside and inside the MRI scanner using echo planar imaging, spin echo, turbo spin echo, and gradient echo sequences. MRI performance was also evaluated with and without the PET insert. The stability of the newly developed PET insert was evaluated and simultaneous PET and MR images of a brain phantom were acquired. No significant degradation of the PET performance caused by MR was observed when the PET was operated using various MR imaging sequences. The signal-to-noise ratio of MR images was slightly degraded due to the PET insert installed inside the MR bore while the homogeneity was maintained. The change of gain of the 256 GAPD/scintillator elements of a detector block was <3% for 60 min, and simultaneous PET and MR images of a brain phantom were successfully acquired. Experimental results indicate that a compact and lightweight PET insert for hybrid PET/MRI can be developed using GAPD arrays and charge signal transmission method proposed in this study without significant interference.

A study of the standard brain in Japanese children: morphological comparison with the MNI template.

PubMed

Uchiyama, Hitoshi T; Seki, Ayumi; Tanaka, Daisuke; Koeda, Tatsuya; Jcs Group

2013-03-01

Functional magnetic resonance imaging (MRI) studies involve normalization so that the brains of different subjects can be described using the same coordinate system. However, standard brain templates, including the Montreal Neurological Institute (MNI) template that is most frequently used at present, were created based on the brains of Western adults. Because morphological characteristics of the brain differ by race and ethnicity and between adults and children, errors are likely to occur when data from the brains of non-Western individuals are processed using these templates. Therefore, this study was conducted to collect basic data for the creation of a Japanese pediatric standard brain. Participants in this study were 45 healthy children (contributing 65 brain images) between the ages of 6 and 9 years, who had nothing notable in their perinatal and other histories and neurological findings, had normal physical findings and cognitive function, exhibited no behavioral abnormalities, and provided analyzable MR images. 3D-T1-weighted images were obtained using a 1.5-T MRI device, and images from each child were adjusted to the reference image by affine transformation using SPM8. The lengths were measured and compared with those of the MNI template. The Western adult standard brain and the Japanese pediatric standard brain obtained in this study differed greatly in size, particularly along the anteroposterior diameter and in height, suggesting that the correction rates are high, and that errors are likely to occur in the normalization of pediatric brain images. We propose that the use of the Japanese pediatric standard brain created in this study will improve the accuracy of identification of brain regions in functional brain imaging studies involving children. Copyright © 2012 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

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

Gain in Body Fat Is Associated with Increased Striatal Response to Palatable Food Cues, whereas Body Fat Stability Is Associated with Decreased Striatal Response

PubMed Central

Yokum, Sonja

2016-01-01

Cross-sectional brain-imaging studies reveal that obese versus lean humans show greater responsivity of reward and attention regions to palatable food cues, but lower responsivity of reward regions to palatable food receipt. However, these individual differences in responsivity may result from a period of overeating. We conducted a repeated-measures fMRI study to test whether healthy weight adolescent humans who gained body fat over a 2 or 3 year follow-up period show an increase in responsivity of reward and attention regions to a cue signaling impending milkshake receipt and a simultaneous decrease in responsivity of reward regions to milkshake receipt versus adolescents who showed stability of or loss of body fat. Adolescents who gained body fat, who largely remained in a healthy weight range, showed increases in activation in the putamen, mid-insula, Rolandic operculum, and precuneus to a cue signaling impending milkshake receipt versus those who showed stability of or loss of body fat, though these effects were partially driven by reductions in responsivity among the latter groups. Adolescents who gained body fat reported significantly greater milkshake wanting and milkshake pleasantness ratings at follow-up compared to those who lost body fat. Adolescents who gained body fat did not show a reduction in responsivity of reward regions to milkshake receipt or changes in responsivity to receipt and anticipated receipt of monetary reward. Data suggest that initiating a prolonged period of overeating may increase striatal responsivity to food cues, and that maintaining a balance between caloric intake and expenditure may reduce striatal, insular, and Rolandic operculum responsivity. SIGNIFICANCE STATEMENT This novel, repeated-measures brain-imaging study suggests that adolescents who gained body fat over our follow-up period experienced an increase in striatal responsivity to cues for palatable foods compared to those who showed stability of or loss of body fat. Results also imply that maintaining a balance between caloric intake and expenditure over time may reduce striatal, insular, and Rolandic operculum responsivity to food cues, which might decrease risk for future overeating. PMID:27358453

Enhanced visualization of MR angiogram with modified MIP and 3D image fusion

NASA Astrophysics Data System (ADS)

Kim, JongHyo; Yeon, Kyoung M.; Han, Man Chung; Lee, Dong Hyuk; Cho, Han I.

1997-05-01

We have developed a 3D image processing and display technique that include image resampling, modification of MIP, volume rendering, and fusion of MIP image with volumetric rendered image. This technique facilitates the visualization of the 3D spatial relationship between vasculature and surrounding organs by overlapping the MIP image on the volumetric rendered image of the organ. We applied this technique to a MR brain image data to produce an MRI angiogram that is overlapped with 3D volume rendered image of brain. MIP technique was used to visualize the vasculature of brain, and volume rendering was used to visualize the other structures of brain. The two images are fused after adjustment of contrast and brightness levels of each image in such a way that both the vasculature and brain structure are well visualized either by selecting the maximum value of each image or by assigning different color table to each image. The resultant image with this technique visualizes both the brain structure and vasculature simultaneously, allowing the physicians to inspect their relationship more easily. The presented technique will be useful for surgical planning for neurosurgery.

Semiautomated volumetry of the cerebrum, cerebellum-brain stem, and temporal lobe on brain magnetic resonance images.

PubMed

Hayashi, Norio; Sanada, Shigeru; Suzuki, Masayuki; Matsuura, Yukihiro; Kawahara, Kazuhiro; Tsujii, Hideo; Yamamoto, Tomoyuki; Matsui, Osamu

2008-02-01

The aim of this study was to develop an automated method of segmenting the cerebrum, cerebellum-brain stem, and temporal lobe simultaneously on magnetic resonance (MR) images. We obtained T1-weighted MR images from 10 normal subjects and 19 patients with brain atrophy. To perform automated volumetry from MR images, we performed the following three steps: (1) segmentation of the brain region; (2) separation between the cerebrum and the cerebellum-brain stem; and (3) segmentation of the temporal lobe. Evaluation was based on the correctly recognized region (CRR) (i.e., the region recognized by both the automated and manual methods). The mean CRRs of the normal and atrophic brains were 98.2% and 97.9% for the cerebrum, 87.9% and 88.5% for the cerebellum-brain stem, and 76.9% and 85.8% for the temporal lobe, respectively. We introduce an automated volumetric method for the cerebrum, cerebellum-brain stem, and temporal lobe on brain MR images. Our method can be applied to not only the normal brain but also the atrophic brain.

Developing a clinical translational neuroscience taxonomy for anxiety and mood disorder: protocol for the baseline-follow up Research domain criteria Anxiety and Depression ("RAD") project.

PubMed

Williams, Leanne M; Goldstein-Piekarski, Andrea N; Chowdhry, Nowreen; Grisanzio, Katherine A; Haug, Nancy A; Samara, Zoe; Etkin, Amit; O'Hara, Ruth; Schatzberg, Alan F; Suppes, Trisha; Yesavage, Jerome

2016-03-15

Understanding how brain circuit dysfunctions relate to specific symptoms offers promise for developing a brain-based taxonomy for classifying psychopathology, identifying targets for mechanistic studies and ultimately for guiding treatment choice. The goal of the Research Domain Criteria (RDoC) initiative of the National Institute of Mental Health is to accelerate the development of such neurobiological models of mental disorder independent of traditional diagnostic criteria. In our RDoC Anxiety and Depression ("RAD") project we focus trans-diagnostically on the spectrum of depression and anxiety psychopathology. Our aims are a) to use brain imaging to define cohesive dimensions defined by dysfunction of circuits involved in reactivity to and regulation of negatively valenced emotional stimulation and in cognitive control, b) to assess the relationships between these dimension and specific symptoms, behavioral performance and the real world capacity to function socially and at work and c) to assess the stability of brain-symptom-behavior-function relationships over time. Here we present the protocol for the "RAD" project, one of the first RDoC studies to use brain circuit functioning to define new dimensions of psychopathology. The RAD project follows baseline-follow up design. In line with RDoC principles we use a strategy for recruiting all clients who "walk through the door" of a large community mental health clinic as well as the surrounding community. The clinic attends to a broad spectrum of anxiety and mood-related symptoms. Participants are unmedicated and studied at baseline using a standardized battery of functional brain imaging, structural brain imaging and behavioral probes that assay constructs of threat reactivity, threat regulation and cognitive control. The battery also includes self-report measures of anxiety and mood symptoms, and social and occupational functioning. After baseline assessments, therapists in the clinic apply treatment planning as usual. Follow-up assessments are undertaken at 3 months, to establish the reliability of brain-based subgroups over time and to assess whether these subgroups predict real-world functional capacity over time. First enrollment was August 2013, and is ongoing. This project is designed to advance knowledge toward a neural circuit taxonomy for mental disorder. Data will be shared via the RDoC database for dissemination to the scientific community. The clinical translational neuroscience goals of the project are to develop brain-behavior profile reports for each individual participant and to refine these reports with therapist feedback. Reporting of results is expected from December 2016 onward. ClinicalTrials.gov Identifier: NCT02220309 . Registered: August 13, 2014.

ViRPET--combination of virtual reality and PET brain imaging

DOEpatents

Majewski, Stanislaw; Brefczynski-Lewis, Julie

2017-05-23

Various methods, systems and apparatus are provided for brain imaging during virtual reality stimulation. In one example, among others, a system for virtual ambulatory environment brain imaging includes a mobile brain imager configured to obtain positron emission tomography (PET) scans of a subject in motion, and a virtual reality (VR) system configured to provide one or more stimuli to the subject during the PET scans. In another example, a method for virtual ambulatory environment brain imaging includes providing stimulation to a subject through a virtual reality (VR) system; and obtaining a positron emission tomography (PET) scan of the subject while moving in response to the stimulation from the VR system. The mobile brain imager can be positioned on the subject with an array of imaging photodetector modules distributed about the head of the subject.

Pain measurement and brain activity: will neuroimages replace pain ratings?

PubMed

Robinson, Michael E; Staud, Roland; Price, Donald D

2013-04-01

Arguments made for the advantages of replacing pain ratings with brain-imaging data include assumptions that pain ratings are less reliable and objective and that brain image data would greatly benefit the measurement of treatment efficacy. None of these assumptions are supported by available evidence. Self-report of pain is predictable and does not necessarily reflect unreliability or error. Because pain is defined as an experience, magnitudes of its dimensions can be estimated by well-established methods, including those used to validate brain imaging of pain. Brain imaging helps to study pain mechanisms and might be used as proxy measures of pain in persons unable to provide verbal reports. Yet eliminating pain ratings or replacing them with neuroimaging data is misguided because brain images only help explain pain if they are used in conjunction with self-report. There is no objective readout mechanism of pain (pain thermometer) that is unaffected by psychological factors. Benefits from including neuroimaging data might include increased understanding of underlying neural mechanisms of treatment efficacy, discovery of new treatment vectors, and support of conclusions derived from self-report. However, neither brain imaging nor self-report data are privileged over the other. The assumption that treatment efficacy is hampered by self-report has not been shown; there is a plethora of treatment studies showing that self-report is sensitive to treatment. Dismissal of patients' self-reports (pain ratings) by brain-imaging data is potentially harmful. The aim of replacing self-report with brain-imaging data is misguided and has no scientific or philosophical foundation. Although brain imaging may offer considerable insight into the neural mechanisms of pain, including relevant causes and correlations, brain images cannot and should not replace self-report. Only the latter assesses the experience of pain, which is not identical to neural activity. Brain imaging may help to explain pain, but replacing self-report with brain-imaging data would be philosophically and scientifically misguided and potentially harmful to pain patients. Copyright © 2013 American Pain Society. Published by Elsevier Inc. All rights reserved.

The role of image registration in brain mapping

PubMed Central

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

2008-01-01

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

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

PubMed

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

2013-01-01

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

Activity patterns in networks stabilized by background oscillations.

PubMed

Hoppensteadt, Frank

2009-07-01

The brain operates in a highly oscillatory environment. We investigate here how such an oscillating background can create stable organized behavior in an array of neuro-oscillators that is not observable in the absence of oscillation, much like oscillating the support point of an inverted pendulum can stabilize its up position, which is unstable without the oscillation. We test this idea in an array of electronic circuits coming from neuroengineering: we show how the frequencies of the background oscillation create a partition of the state space into distinct basins of attraction. Thus, background signals can stabilize persistent activity that is otherwise not observable. This suggests that an image, represented as a stable firing pattern which is triggered by a voltage pulse and is sustained in synchrony or resonance with the background oscillation, can persist as a stable behavior long after the initial stimulus is removed. The background oscillations provide energy for organized behavior in the array, and these behaviors are categorized by the basins of attraction determined by the oscillation frequencies.

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

Advanced Pediatric Brain Imaging Research and Training Program

DTIC Science & Technology

2013-10-01

diffusion tensor imaging and perfusion ( arterial spin labeling) MRI data and to relate measures of global and regional brain microstructural organization...AD_________________ Award Number: W81XWH-11-2-0198 TITLE: Advanced Pediatric Brain Imaging...September 2013 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Advanced Pediatric Brain Imaging Research and Training Program 5b. GRANT NUMBER W81XWH

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

RNA interference therapy: a new solution for intracranial atherosclerosis?

PubMed Central

Tang, Tao; Wong, Ka-Sing

2014-01-01

Intracranial atherosclerotic stenosis (ICAS) of a major intracranial artery, especially middle cerebral artery (MCA), is reported to be one leading cause of ischemic stroke throughout the world. Compared with other stroke subtypes, ICAS is associated with a higher risk of recurrent stroke despite aggressive medical therapy. Increased understanding of the pathophysiology of ICAS has highlighted several possible targets for therapeutic interventions. Both luminal stenosis and plaque components of ICAS have been found to be associated with ischemic stroke based a post-mortem study. Recent application of high-resolution magnetic resonance imaging (HRMRI) in evaluating ICAS provides new insight into the vascular biology of plaque morphology and component. High signal on T1-weighted fat-suppressed images (HST1) within MCA plaque of HRMRI, highly suggested of fresh or recent intraplaque hemorrhage, has been found to be associated with ipsilateral brain infarction. Thus, the higher prevalence of intraplaque hemorrhage and neovasculature in symptomatic patients with MCA stenosis may provide a potential target for plaque stabilization. We hypothesize that RNA interference (RNAi) therapy delivered by modified nanoparticles may achieve in vivo biomedical imaging and targeted therapy. With the rapid developments in studies about therapeutic and diagnostic nanomaterials, future studies further exploring the molecular biology of atherosclerosis may provide more drug targets for plaque stabilization. PMID:25333054

Multiplex Mass Spectrometric Imaging with Polarity Switching for Concurrent Acquisition of Positive and Negative Ion Images

NASA Astrophysics Data System (ADS)

Korte, Andrew R.; Lee, Young Jin

2013-06-01

We have recently developed a multiplex mass spectrometry imaging (MSI) method which incorporates high mass resolution imaging and MS/MS and MS3 imaging of several compounds in a single data acquisition utilizing a hybrid linear ion trap-Orbitrap mass spectrometer (Perdian and Lee, Anal. Chem. 82, 9393-9400, 2010). Here we extend this capability to obtain positive and negative ion MS and MS/MS spectra in a single MS imaging experiment through polarity switching within spiral steps of each raster step. This methodology was demonstrated for the analysis of various lipid class compounds in a section of mouse brain. This allows for simultaneous imaging of compounds that are readily ionized in positive mode (e.g., phosphatidylcholines and sphingomyelins) and those that are readily ionized in negative mode (e.g., sulfatides, phosphatidylinositols and phosphatidylserines). MS/MS imaging was also performed for a few compounds in both positive and negative ion mode within the same experimental set-up. Insufficient stabilization time for the Orbitrap high voltage leads to slight deviations in observed masses, but these deviations are systematic and were easily corrected with a two-point calibration to background ions.

Improving data availability for brain image biobanking in healthy subjects: Practice-based suggestions from an international multidisciplinary working group

PubMed Central

Shenkin, Susan D.; Pernet, Cyril; Nichols, Thomas E.; Poline, Jean-Baptiste; Matthews, Paul M.; van der Lugt, Aad; Mackay, Clare; Lanyon, Linda; Mazoyer, Bernard; Boardman, James P.; Thompson, Paul M.; Fox, Nick; Marcus, Daniel S.; Sheikh, Aziz; Cox, Simon R.; Anblagan, Devasuda; Job, Dominic E.; Dickie, David Alexander; Rodriguez, David; Wardlaw, Joanna M.

2017-01-01

Brain imaging is now ubiquitous in clinical practice and research. The case for bringing together large amounts of image data from well-characterised healthy subjects and those with a range of common brain diseases across the life course is now compelling. This report follows a meeting of international experts from multiple disciplines, all interested in brain image biobanking. The meeting included neuroimaging experts (clinical and non-clinical), computer scientists, epidemiologists, clinicians, ethicists, and lawyers involved in creating brain image banks. The meeting followed a structured format to discuss current and emerging brain image banks; applications such as atlases; conceptual and statistical problems (e.g. defining ‘normality’); legal, ethical and technological issues (e.g. consents, potential for data linkage, data security, harmonisation, data storage and enabling of research data sharing). We summarise the lessons learned from the experiences of a wide range of individual image banks, and provide practical recommendations to enhance creation, use and reuse of neuroimaging data. Our aim is to maximise the benefit of the image data, provided voluntarily by research participants and funded by many organisations, for human health. Our ultimate vision is of a federated network of brain image biobanks accessible for large studies of brain structure and function. PMID:28232121

Improving data availability for brain image biobanking in healthy subjects: Practice-based suggestions from an international multidisciplinary working group.

PubMed

Shenkin, Susan D; Pernet, Cyril; Nichols, Thomas E; Poline, Jean-Baptiste; Matthews, Paul M; van der Lugt, Aad; Mackay, Clare; Lanyon, Linda; Mazoyer, Bernard; Boardman, James P; Thompson, Paul M; Fox, Nick; Marcus, Daniel S; Sheikh, Aziz; Cox, Simon R; Anblagan, Devasuda; Job, Dominic E; Dickie, David Alexander; Rodriguez, David; Wardlaw, Joanna M

2017-06-01

Brain imaging is now ubiquitous in clinical practice and research. The case for bringing together large amounts of image data from well-characterised healthy subjects and those with a range of common brain diseases across the life course is now compelling. This report follows a meeting of international experts from multiple disciplines, all interested in brain image biobanking. The meeting included neuroimaging experts (clinical and non-clinical), computer scientists, epidemiologists, clinicians, ethicists, and lawyers involved in creating brain image banks. The meeting followed a structured format to discuss current and emerging brain image banks; applications such as atlases; conceptual and statistical problems (e.g. defining 'normality'); legal, ethical and technological issues (e.g. consents, potential for data linkage, data security, harmonisation, data storage and enabling of research data sharing). We summarise the lessons learned from the experiences of a wide range of individual image banks, and provide practical recommendations to enhance creation, use and reuse of neuroimaging data. Our aim is to maximise the benefit of the image data, provided voluntarily by research participants and funded by many organisations, for human health. Our ultimate vision is of a federated network of brain image biobanks accessible for large studies of brain structure and function. Copyright © 2017 Elsevier Inc. All rights reserved.

Dedicated mobile volumetric cone-beam computed tomography for human brain imaging: A phantom study.

PubMed

Ryu, Jong-Hyun; Kim, Tae-Hoon; Jeong, Chang-Won; Jun, Hong-Young; Heo, Dong-Woon; Lee, Jinseok; Kim, Kyong-Woo; Yoon, Kwon-Ha

2015-01-01

Mobile computed tomography (CT) with a cone-beam source is increasingly used in the clinical field. Mobile cone-beam CT (CBCT) has great merits; however, its clinical utility for brain imaging has been limited due to problems including scan time and image quality. The aim of this study was to develop a dedicated mobile volumetric CBCT for obtaining brain images, and to optimize the imaging protocol using a brain phantom. The mobile volumetric CBCT system was evaluated with regards to scan time and image quality, measured as signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), spatial resolution (10% MTF), and effective dose. Brain images were obtained using a CT phantom. The CT scan took 5.14 s at 360 projection views. SNR and CNR were 5.67 and 14.5 at 120 kV/10 mA. SNR and CNR values showed slight improvement as the x-ray voltage and current increased (p < 0.001). Effective dose and 10% MTF were 0.92 mSv and 360 μ m at 120 kV/10 mA. Various intracranial structures were clearly visible in the brain phantom images. Using this CBCT under optimal imaging acquisition conditions, it is possible to obtain human brain images with low radiation dose, reproducible image quality, and fast scan time.

Left insular cortex and left SFG underlie prismatic adaptation effects on time perception: evidence from fMRI.

PubMed

Magnani, Barbara; Frassinetti, Francesca; Ditye, Thomas; Oliveri, Massimiliano; Costantini, Marcello; Walsh, Vincent

2014-05-15

Prismatic adaptation (PA) has been shown to affect left-to-right spatial representations of temporal durations. A leftward aftereffect usually distorts time representation toward an underestimation, while rightward aftereffect usually results in an overestimation of temporal durations. Here, we used functional magnetic resonance imaging (fMRI) to study the neural mechanisms that underlie PA effects on time perception. Additionally, we investigated whether the effect of PA on time is transient or stable and, in the case of stability, which cortical areas are responsible of its maintenance. Functional brain images were acquired while participants (n=17) performed a time reproduction task and a control-task before, immediately after and 30 min after PA inducing a leftward aftereffect, administered outside the scanner. The leftward aftereffect induced an underestimation of time intervals that lasted for at least 30 min. The left anterior insula and the left superior frontal gyrus showed increased functional activation immediately after versus before PA in the time versus the control-task, suggesting these brain areas to be involved in the executive spatial manipulation of the representation of time. The left middle frontal gyrus showed an increase of activation after 30 min with respect to before PA. This suggests that this brain region may play a key role in the maintenance of the PA effect over time. Copyright © 2014. Published by Elsevier Inc.

Altered local spontaneous activity in frontal lobe epilepsy: a resting-state functional magnetic resonance imaging study.

PubMed

Dong, Li; Li, Hechun; He, Zhongqiong; Jiang, Sisi; Klugah-Brown, Benjamin; Chen, Lin; Wang, Pu; Tan, Song; Luo, Cheng; Yao, Dezhong

2016-11-01

The purpose of this study was to investigate the local spatiotemporal consistency of spontaneous brain activity in patients with frontal lobe epilepsy (FLE). Eyes closed resting-state functional magnetic resonance imaging (fMRI) data were collected from 19 FLE patients and 19 age- and gender-matched healthy controls. A novel measure, named FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) was used to assess the spatiotemporal consistency of local spontaneous activity (emphasizing both local temporal homogeneity and regional stability of brain activity states). Then, two-sample t test was performed to detect the FOCA differences between two groups. Partial correlations between the FOCA values and durations of epilepsy were further analyzed. Compared with controls, FLE patients demonstrated increased FOCA in distant brain regions including the frontal and parietal cortices, as well as the basal ganglia. The decreased FOCA was located in the temporal cortex, posterior default model regions, and cerebellum. In addition, the FOCA measure was linked to the duration of epilepsy in basal ganglia. Our study suggested that alterations of local spontaneous activity in frontoparietal cortex and basal ganglia was associated with the pathophysiology of FLE; and the abnormality in frontal and default model regions might account for the potential cognitive impairment in FLE. We also presumed that the FOCA measure had potential to provide important insights into understanding epilepsy such as FLE.

The iconographic brain. A critical philosophical inquiry into (the resistance of) the image

PubMed Central

De Vos, Jan

2014-01-01

The brain image plays a central role in contemporary image culture and, in turn, (co)constructs contemporary forms of subjectivity. The central aim of this paper is to probe the unmistakably potent interpellative power of brain images by delving into the power of imaging and the power of the image itself. This is not without relevance for the neurosciences, inasmuch as these do not take place in a vacuum; hence the importance of inquiring into the status of the image within scientific culture and science itself. I will mount a critical philosophical investigation of the brain qua image, focusing on the issue of mapping the mental onto the brain and how, in turn, the brain image plays a pivotal role in processes of subjectivation. Hereto, I draw upon Science & Technology Studies, juxtaposed with culture and ideology critique and theories of image culture. The first section sets out from Althusser's concept of interpellation, linking ideology to subjectivity. Doing so allows to spell out the central question of the paper: what could serve as the basis for a critical approach, or, where can a locus of resistance be found? In the second section, drawing predominantly on Baudrillard, I delve into the dimension of virtuality as this is opened up by brain image culture. This leads to the question of whether the digital brain must be opposed to old analog psychology: is it the psyche which resists? This issue is taken up in the third section which, ultimately, concludes that the psychological is not the requisite locus of resistance. The fourth section proceeds to delineate how the brain image is constructed from what I call the data-gaze (the claim that brain data are always already visual). In the final section, I discuss how an engagement with theories of iconology affords a critical understanding of the interpellative force of the brain image, which culminates in the somewhat unexpected claim that the sought after resistance lies in the very status of the image itself. PMID:24860480

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

New image-stabilizing system

NASA Astrophysics Data System (ADS)

Zhao, Yuejin

1996-06-01

In this paper, a new method for image stabilization with a three-axis image- stabilizing reflecting prism assembly is presented, and the principle of image stabilization in this prism assembly, formulae for image stabilization and working formulae with an approximation up to the third power are given in detail. In this image-stabilizing system, a single chip microcomputer is used to calculate value of compensating angles and thus to control the prism assembly. Two gyroscopes act as sensors from which information of angular perturbation is obtained, three stepping motors drive the prism assembly to compensate for the movement of image produced by angular perturbation. The image-stabilizing device so established is a multifold system which involves optics, mechanics, electronics and computer.

High-sensitivity terahertz imaging of traumatic brain injury in a rat model

NASA Astrophysics Data System (ADS)

Zhao, Hengli; Wang, Yuye; Chen, Linyu; Shi, Jia; Ma, Kang; Tang, Longhuang; Xu, Degang; Yao, Jianquan; Feng, Hua; Chen, Tunan

2018-03-01

We demonstrated that different degrees of experimental traumatic brain injury (TBI) can be differentiated clearly in fresh slices of rat brain tissues using transmission-type terahertz (THz) imaging system. The high absorption region in THz images corresponded well with the injured area in visible images and magnetic resonance imaging results. The THz image and absorption characteristics of dehydrated paraffin-embedded brain slices and the hematoxylin and eosin (H&E)-stained microscopic images were investigated to account for the intrinsic differences in the THz images for the brain tissues suffered from different degrees of TBI and normal tissue aside from water. The THz absorption coefficients of rat brain tissues showed an increase in the aggravation of brain damage, particularly in the high-frequency range, whereas the cell density decreased as the order of mild, moderate, and severe TBI tissues compared with the normal tissue. Our results indicated that the different degrees of TBI were distinguishable owing to the different water contents and probable hematoma components distribution rather than intrinsic cell intensity. These promising results suggest that THz imaging has great potential as an alternative method for the fast diagnosis of TBI.

Brain extraction from normal and pathological images: A joint PCA/Image-Reconstruction approach.

PubMed

Han, Xu; Kwitt, Roland; Aylward, Stephen; Bakas, Spyridon; Menze, Bjoern; Asturias, Alexander; Vespa, Paul; Van Horn, John; Niethammer, Marc

2018-08-01

Brain extraction from 3D medical images is a common pre-processing step. A variety of approaches exist, but they are frequently only designed to perform brain extraction from images without strong pathologies. Extracting the brain from images exhibiting strong pathologies, for example, the presence of a brain tumor or of a traumatic brain injury (TBI), is challenging. In such cases, tissue appearance may substantially deviate from normal tissue appearance and hence violates algorithmic assumptions for standard approaches to brain extraction; consequently, the brain may not be correctly extracted. This paper proposes a brain extraction approach which can explicitly account for pathologies by jointly modeling normal tissue appearance and pathologies. Specifically, our model uses a three-part image decomposition: (1) normal tissue appearance is captured by principal component analysis (PCA), (2) pathologies are captured via a total variation term, and (3) the skull and surrounding tissue is captured by a sparsity term. Due to its convexity, the resulting decomposition model allows for efficient optimization. Decomposition and image registration steps are alternated to allow statistical modeling of normal tissue appearance in a fixed atlas coordinate system. As a beneficial side effect, the decomposition model allows for the identification of potentially pathological areas and the reconstruction of a quasi-normal image in atlas space. We demonstrate the effectiveness of our approach on four datasets: the publicly available IBSR and LPBA40 datasets which show normal image appearance, the BRATS dataset containing images with brain tumors, and a dataset containing clinical TBI images. We compare the performance with other popular brain extraction models: ROBEX, BEaST, MASS, BET, BSE and a recently proposed deep learning approach. Our model performs better than these competing approaches on all four datasets. Specifically, our model achieves the best median (97.11) and mean (96.88) Dice scores over all datasets. The two best performing competitors, ROBEX and MASS, achieve scores of 96.23/95.62 and 96.67/94.25 respectively. Hence, our approach is an effective method for high quality brain extraction for a wide variety of images. Copyright © 2018 Elsevier Inc. All rights reserved.

Brain regions essential for improved lexical access in an aged aphasic patient: a case report.

PubMed

Meinzer, Marcus; Flaisch, Tobias; Obleser, Jonas; Assadollahi, Ramin; Djundja, Daniela; Barthel, Gabriela; Rockstroh, Brigitte

2006-08-17

The relationship between functional recovery after brain injury and concomitant neuroplastic changes is emphasized in recent research. In the present study we aimed to delineate brain regions essential for language performance in aphasia using functional magnetic resonance imaging and acquisition in a temporal sparse sampling procedure, which allows monitoring of overt verbal responses during scanning. An 80-year old patient with chronic aphasia (2 years post-onset) was investigated before and after intensive language training using an overt picture naming task. Differential brain activation in the right inferior frontal gyrus for correct word retrieval and errors was found. Improved language performance following therapy was mirrored by increased fronto-thalamic activation while stability in more general measures of attention/concentration and working memory was assured. Three healthy age-matched control subjects did not show behavioral changes or increased activation when tested repeatedly within the same 2-week time interval. The results bear significance in that the changes in brain activation reported can unequivocally be attributed to the short-term training program and a language domain-specific plasticity process. Moreover, it further challenges the claim of a limited recovery potential in chronic aphasia, even at very old age. Delineation of brain regions essential for performance on a single case basis might have major implications for treatment using transcranial magnetic stimulation.

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.

Look again: effects of brain images and mind-brain dualism on lay evaluations of research.

PubMed

Hook, Cayce J; Farah, Martha J

2013-09-01

Brain scans have frequently been credited with uniquely seductive and persuasive qualities, leading to claims that fMRI research receives a disproportionate share of public attention and funding. It has been suggested that functional brain images are fascinating because they contradict dualist beliefs regarding the relationship between the body and the mind. Although previous research has indicated that brain images can increase judgments of an article's scientific reasoning, the hypotheses that brain scans make research appear more interesting, surprising, or worthy of funding have not been tested. Neither has the relation between the allure of brain imaging and dualism. In the following three studies, laypersons rated both fictional research descriptions and real science news articles accompanied by brain scans, bar charts, or photographs. Across 988 participants, we found little evidence of neuroimaging's seductive allure or of its relation to self-professed dualistic beliefs. These results, taken together with other recent null findings, suggest that brain images are less powerful than has been argued.

Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

PubMed

Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

2014-01-01

The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

Time-of-day differences and short-term stability of the neural response to monetary reward: a pilot study.

PubMed

Hasler, Brant P; Forbes, Erika E; Franzen, Peter L

2014-10-30

Human and animal studies indicate that reward function is modulated by the circadian clock that governs our daily sleep/wake rhythm. For example, a robust circadian rhythm exists in positive affect, which is lower in the morning hours and peaks in the afternoon. A handful of functional neuroimaging studies suggest that systematic diurnal variation exists in brain activity related to other functions, but no published human studies have examined daily variation in the neural processing of reward. In the present study, we attempt to advance this literature by using functional neuroimaging methods to examine time-of-day changes in the responsivity of the reward circuit. Using a within-person design and a functional magnetic resonance imaging (fMRI) monetary reward task, we compared morning and afternoon reward-related brain activation in a sample of healthy young adults within 24h. Region of interest analyses focused on the striatum, and we hypothesized greater reward activation in the afternoon, concordant with the circadian peak in positive affect. Results were consistent with our hypothesis. In addition, we counterbalanced the order of morning and afternoon scans in order to explore the short-term stability of the neural response. Whole-brain analyses showed a markedly higher reactivity to reward throughout the brain in the first scan relative to the second scan, consistent with habituation to the monetary reward stimuli. However, these effects did not appear to explain the time-of-day findings. In summary, we report the first preliminary evidence of circadian variation in the neural processing of reward. These findings have both methodological and theoretical implications. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Validation of an arterial tortuosity measure with application to hypertension collection of clinical hypertensive patients

PubMed Central

2011-01-01

Background Hypertension may increase tortuosity or twistedness of arteries. We applied a centerline extraction algorithm and tortuosity metric to magnetic resonance angiography (MRA) brain images to quantitatively measure the tortuosity of arterial vessel centerlines. The most commonly used arterial tortuosity measure is the distance factor metric (DFM). This study tested a DFM based measurement’s ability to detect increases in arterial tortuosity of hypertensives using existing images. Existing images presented challenges such as different resolutions which may affect the tortuosity measurement, different depths of the area imaged, and different artifacts of imaging that require filtering. Methods The stability and accuracy of alternative centerline algorithms was validated in numerically generated models and test brain MRA data. Existing images were gathered from previous studies and clinical medical systems by manually reading electronic medical records to identify hypertensives and negatives. Images of different resolutions were interpolated to similar resolutions. Arterial tortuosity in MRA images was measured from a DFM curve and tested on numerically generated models as well as MRA images from two hypertensive and three negative control populations. Comparisons were made between different resolutions, different filters, hypertensives versus negatives, and different negative controls. Results In tests using numerical models of a simple helix, the measured tortuosity increased as expected with more tightly coiled helices. Interpolation reduced resolution-dependent differences in measured tortuosity. The Korean hypertensive population had significantly higher arterial tortuosity than its corresponding negative control population across multiple arteries. In addition one negative control population of different ethnicity had significantly less arterial tortuosity than the other two. Conclusions Tortuosity can be compared between images of different resolutions by interpolating from lower to higher resolutions. Use of a universal negative control was not possible in this study. The method described here detected elevated arterial tortuosity in a hypertensive population compared to the negative control population and can be used to study this relation in other populations. PMID:22166145

Validation of an arterial tortuosity measure with application to hypertension collection of clinical hypertensive patients.

PubMed

Diedrich, Karl T; Roberts, John A; Schmidt, Richard H; Kang, Chang-Ki; Cho, Zang-Hee; Parker, Dennis L

2011-10-18

Hypertension may increase tortuosity or twistedness of arteries. We applied a centerline extraction algorithm and tortuosity metric to magnetic resonance angiography (MRA) brain images to quantitatively measure the tortuosity of arterial vessel centerlines. The most commonly used arterial tortuosity measure is the distance factor metric (DFM). This study tested a DFM based measurement's ability to detect increases in arterial tortuosity of hypertensives using existing images. Existing images presented challenges such as different resolutions which may affect the tortuosity measurement, different depths of the area imaged, and different artifacts of imaging that require filtering. The stability and accuracy of alternative centerline algorithms was validated in numerically generated models and test brain MRA data. Existing images were gathered from previous studies and clinical medical systems by manually reading electronic medical records to identify hypertensives and negatives. Images of different resolutions were interpolated to similar resolutions. Arterial tortuosity in MRA images was measured from a DFM curve and tested on numerically generated models as well as MRA images from two hypertensive and three negative control populations. Comparisons were made between different resolutions, different filters, hypertensives versus negatives, and different negative controls. In tests using numerical models of a simple helix, the measured tortuosity increased as expected with more tightly coiled helices. Interpolation reduced resolution-dependent differences in measured tortuosity. The Korean hypertensive population had significantly higher arterial tortuosity than its corresponding negative control population across multiple arteries. In addition one negative control population of different ethnicity had significantly less arterial tortuosity than the other two. Tortuosity can be compared between images of different resolutions by interpolating from lower to higher resolutions. Use of a universal negative control was not possible in this study. The method described here detected elevated arterial tortuosity in a hypertensive population compared to the negative control population and can be used to study this relation in other populations.

Use of Propofol for Induction and Maintenance of Anesthesia in a King Penguin ( Aptenodytes patagonicus ) Undergoing Magnetic Resonance Imaging.

PubMed

Bigby, Sarah E; Carter, Jennifer E; Bauquier, Sébastien; Beths, Thierry

2016-09-01

Anesthesia protocols for patients with intracranial lesions need to provide hemodynamic stability, preserve cerebrovascular autoregulation, avoid increases in intracranial pressure, and facilitate a rapid recovery. Propofol total intravenous anesthesia (TIVA) maintains cerebral blood flow autoregulation and is considered superior to inhalant agents as an anesthetic protocol for patients with intracranial lesions. A propofol-based TIVA subsequent to premedication with medetomidine and diazepam was used in a king penguin ( Aptenodytes patagonicus ) undergoing magnetic resonance imaging of the brain after a new onset of seizures. This protocol provided a rapid and smooth induction and calm recovery in the penguin. When ventilation control is possible, propofol TIVA may be a superior choice to inhalant agents for anesthesia of birds with potential intracranial lesions.

Automatic segmentation of brain MRI in high-dimensional local and non-local feature space based on sparse representation.

PubMed

Khalilzadeh, Mohammad Mahdi; Fatemizadeh, Emad; Behnam, Hamid

2013-06-01

Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods whose results have been improved. Copyright © 2013 Elsevier Inc. All rights reserved.

Hummingbirds control hovering flight by stabilizing visual motion.

PubMed

Goller, Benjamin; Altshuler, Douglas L

2014-12-23

Relatively little is known about how sensory information is used for controlling flight in birds. A powerful method is to immerse an animal in a dynamic virtual reality environment to examine behavioral responses. Here, we investigated the role of vision during free-flight hovering in hummingbirds to determine how optic flow--image movement across the retina--is used to control body position. We filmed hummingbirds hovering in front of a projection screen with the prediction that projecting moving patterns would disrupt hovering stability but stationary patterns would allow the hummingbird to stabilize position. When hovering in the presence of moving gratings and spirals, hummingbirds lost positional stability and responded to the specific orientation of the moving visual stimulus. There was no loss of stability with stationary versions of the same stimulus patterns. When exposed to a single stimulus many times or to a weakened stimulus that combined a moving spiral with a stationary checkerboard, the response to looming motion declined. However, even minimal visual motion was sufficient to cause a loss of positional stability despite prominent stationary features. Collectively, these experiments demonstrate that hummingbirds control hovering position by stabilizing motions in their visual field. The high sensitivity and persistence of this disruptive response is surprising, given that the hummingbird brain is highly specialized for sensory processing and spatial mapping, providing other potential mechanisms for controlling position.

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

PubMed

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

2015-08-01

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

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Seidler, R. D.; Feiveson, A.; Oddsson, L.; Zanello, S.; Oman, C. M.; Ploutz-Snyder, L.; Peters, B.; Cohen, H. S.; Reschke, M.;

Brain lesions in septic shock: a magnetic resonance imaging study.

PubMed

Sharshar, Tarek; Carlier, Robert; Bernard, Francis; Guidoux, Céline; Brouland, Jean-Philippe; Nardi, Olivier; de la Grandmaison, Geoffroy Lorin; Aboab, Jérôme; Gray, Françoise; Menon, David; Annane, Djillali

2007-05-01

Understanding of sepsis-induced brain dysfunction remains poor, and relies mainly on data from animals or post-mortem studies in patients. The current study provided findings from magnetic resonance imaging of the brain in septic shock. Nine patients with septic shock and brain dysfunction [7 women, median age 63 years (interquartile range 61-79 years), SAPS II: 48 (44-56), SOFA: 8 (6-10)] underwent brain magnetic resonance imaging including gradient echo T1-weighted, fluid-attenuated inversion recovery (FLAIR), T2-weighted and diffusion isotropic images, and mapping of apparent diffusion coefficient. Brain imaging was normal in two patients, showed multiple ischaemic strokes in two patients, and in the remaining patients showed white matter lesions at the level of the centrum semiovale, predominating around Virchow-Robin spaces, ranging from small multiple areas to diffuse lesions, and characterised by hyperintensity on FLAIR images. The main lesions were also characterised by reduced signal on diffusion isotropic images and increased apparent diffusion coefficient. The lesions of the white matter worsened with increasing duration of shock and were correlated with Glasgow Outcome Score. This preliminary study showed that sepsis-induced brain lesions can be documented by magnetic resonance imaging. These lesions predominated in the white matter, suggesting increased blood-brain barrier permeability, and were associated with poor outcome.

Dorsal brain stem syndrome: MR imaging location of brain stem tegmental lesions in neonates with oral motor dysfunction.

PubMed

Quattrocchi, C C; Longo, D; Delfino, L N; Cilio, M R; Piersigilli, F; Capua, M D; Seganti, G; Danhaive, O; Fariello, G

2010-09-01

The anatomic extent of brain stem damage may provide information about clinical outcome and prognosis in children with hypoxic-ischemic encephalopathy and oral motor dysfunction. The aim of this study was to retrospectively characterize the location and extent of brain stem lesions in children with oral motor dysfunction. From January 2005 to August 2009, 43 infants hospitalized at our institution were included in the study because of a history of hypoxic-ischemic events. Of this group, 14 patients showed oral motor dysfunction and brain stem tegmental lesions detected at MR imaging. MR imaging showed hypoxic-ischemic lesions in supra- and infratentorial areas. Six of 14 patients revealed only infratentorial lesions. Focal symmetric lesions of the tegmental brain stem were always present. The lesions appeared hyperintense on T2-weighted images and hypointense on IR images. We found a strong association (P < .0001) between oral motor dysfunction and infratentorial lesions on MR imaging. Oral motor dysfunction was associated with brain stem tegmental lesions in posthypoxic-ischemic infants. The MR imaging examination should be directed to the brain stem, especially when a condition of prolonged gavage feeding is necessary in infants.

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

PubMed

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

Torres Hoyos, F.; Martín-Landrove, M.

2012-02-01

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

On the use of water phantom images to calibrate and correct eddy current induced artefacts in MR diffusion tensor imaging.

PubMed

Bastin, M E; Armitage, P A

2000-07-01

The accurate determination of absolute measures of diffusion anisotropy in vivo using single-shot, echo-planar imaging techniques requires the acquisition of a set of high signal-to-noise ratio, diffusion-weighted images that are free from eddy current induced image distortions. Such geometric distortions can be characterized and corrected in brain imaging data using magnification (M), translation (T), and shear (S) distortion parameters derived from separate water phantom calibration experiments. Here we examine the practicalities of using separate phantom calibration data to correct high b-value diffusion tensor imaging data by investigating the stability of these distortion parameters, and hence the eddy currents, with time. It is found that M, T, and S vary only slowly with time (i.e., on the order of weeks), so that calibration scans need not be performed after every patient examination. This not only minimises the scan time required to collect the calibration data, but also the computational time needed to characterize these eddy current induced distortions. Examples of how measurements of diffusion anisotropy are improved using this post-processing scheme are also presented.

Image Restoration Using Functional and Anatomical Information Fusion with Application to SPECT-MRI Images

PubMed Central

Benameur, S.; Mignotte, M.; Meunier, J.; Soucy, J. -P.

2009-01-01

Image restoration is usually viewed as an ill-posed problem in image processing, since there is no unique solution associated with it. The quality of restored image closely depends on the constraints imposed of the characteristics of the solution. In this paper, we propose an original extension of the NAS-RIF restoration technique by using information fusion as prior information with application in SPECT medical imaging. That extension allows the restoration process to be constrained by efficiently incorporating, within the NAS-RIF method, a regularization term which stabilizes the inverse solution. Our restoration method is constrained by anatomical information extracted from a high resolution anatomical procedure such as magnetic resonance imaging (MRI). This structural anatomy-based regularization term uses the result of an unsupervised Markovian segmentation obtained after a preliminary registration step between the MRI and SPECT data volumes from each patient. This method was successfully tested on 30 pairs of brain MRI and SPECT acquisitions from different subjects and on Hoffman and Jaszczak SPECT phantoms. The experiments demonstrated that the method performs better, in terms of signal-to-noise ratio, than a classical supervised restoration approach using a Metz filter. PMID:19812704

Effects of agmatine on blood-brain barrier stabilization assessed by permeability MRI in a rat model of transient cerebral ischemia.

PubMed

Ahn, S S; Kim, S H; Lee, J E; Ahn, K J; Kim, D J; Choi, H S; Kim, J; Shin, N-Y; Lee, S-K

2015-02-01

BBB disruption after acute ischemic stroke and subsequent permeability increase may be enhanced by reperfusion. Agmatine has been reported to attenuate BBB disruption. Our aim was to evaluate the effects of agmatine on BBB stabilization in a rat model of transient cerebral ischemia by using permeability dynamic contrast-enhanced MR imaging at early stages and subsequently to demonstrate the feasibility of dynamic contrast-enhanced MR imaging for the investigation of new therapies. Thirty-four male Sprague-Dawley rats were subjected to transient MCA occlusion for 90 minutes. Immediately after reperfusion, agmatine (100 mg/kg) or normal saline was injected intraperitoneally into the agmatine-treated group (n = 17) or the control group, respectively. MR imaging was performed after reperfusion. For quantitative analysis, regions of interest were defined within the infarct area, and values for volume transfer constant, rate transfer coefficient, volume fraction of extravascular extracellular space, and volume fraction of blood plasma were obtained. Infarct volume, infarct growth, quantitative imaging parameters, and numbers of factor VIII-positive cells after immunohistochemical staining were compared between control and agmatine-treated groups. Among the permeability parameters, volume transfer constant and volume fraction of extravascular extracellular space were significantly lower in the agmatine-treated group compared with the control group (0.05 ± 0.02 minutes(-1) versus 0.08 ± 0.03 minute(-1), P = .012, for volume transfer constant and 0.12 ± 0.06 versus 0.22 ± 0.15, P = .02 for volume fraction of extravascular extracellular space). Other permeability parameters were not significantly different between the groups. The number of factor VIII-positive cells was less in the agmatine-treated group than in the control group (3-fold versus 4-fold, P = .037). In ischemic stroke, agmatine protects the BBB, which can be monitored in vivo by quantification of permeability by using dynamic contrast-enhanced MR imaging. Therefore, dynamic contrast-enhanced MR imaging may serve as a potential imaging biomarker for assessing the BBB stabilization properties of pharmacologic agents. © 2015 by American Journal of Neuroradiology.

Causal Inference for Spatial Constancy across Saccades

PubMed Central

Atsma, Jeroen; Maij, Femke; Koppen, Mathieu; Irwin, David E.; Medendorp, W. Pieter

2016-01-01

Our ability to interact with the environment hinges on creating a stable visual world despite the continuous changes in retinal input. To achieve visual stability, the brain must distinguish the retinal image shifts caused by eye movements and shifts due to movements of the visual scene. This process appears not to be flawless: during saccades, we often fail to detect whether visual objects remain stable or move, which is called saccadic suppression of displacement (SSD). How does the brain evaluate the memorized information of the presaccadic scene and the actual visual feedback of the postsaccadic visual scene in the computations for visual stability? Using a SSD task, we test how participants localize the presaccadic position of the fixation target, the saccade target or a peripheral non-foveated target that was displaced parallel or orthogonal during a horizontal saccade, and subsequently viewed for three different durations. Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. We modeled the data through a Bayesian causal inference mechanism, in which at the trial level an optimal mixing of two possible strategies, integration vs. separation of the presaccadic memory and the postsaccadic sensory signals, is applied. Fits of this model generally outperformed other plausible decision strategies for producing SSD. Our findings suggest that humans exploit a Bayesian inference process with two causal structures to mediate visual stability. PMID:26967730

Some Problems for Representations of Brain Organization Based on Activation in Functional Imaging

ERIC Educational Resources Information Center

Sidtis, John J.

2007-01-01

Functional brain imaging has overshadowed traditional lesion studies in becoming the dominant approach to the study of brain-behavior relationships. The proponents of functional imaging studies frequently argue that this approach provides an advantage over lesion studies by observing normal brain activity in vivo without the disruptive effects of…

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; DeDios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Seidler, R. D.; Oddsson, L.; Zanello, S.; Clarke, T.;

Robust generative asymmetric GMM for brain MR image segmentation.

PubMed

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM algorithm is proposed which can simply and efficiently incorporate spatial constraints into an EM framework to simultaneously segment brain MR images and estimate the intensity inhomogeneity. The proposed algorithm is flexible to fit the data shapes, and can simultaneously overcome the influence of noise and intensity inhomogeneity, and hence is capable of improving over 5% segmentation accuracy comparing with several state-of-the-art algorithms. Copyright © 2017 Elsevier B.V. All rights reserved.

Non-invasive imaging of the levels and effects of glutathione on the redox status of mouse brain using electron paramagnetic resonance imaging

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

Emoto, Miho C.; Department of Neurology, Sapporo Medical University School of Medicine, Sapporo, Hokkaido 060-8556; Matsuoka, Yuta

Glutathione (GSH) is the most abundant non-protein thiol that buffers reactive oxygen species in the brain. GSH does not reduce nitroxides directly, but in the presence of ascorbates, addition of GSH increases ascorbate-induced reduction of nitroxides. In this study, we used electron paramagnetic resonance (EPR) imaging and the nitroxide imaging probe, 3-methoxycarbonyl-2,2,5,5-tetramethyl-piperidine-1-oxyl (MCP), to non-invasively obtain spatially resolved redox data from mouse brains depleted of GSH with diethyl maleate compared to control. Based on the pharmacokinetics of the reduction reaction of MCP in the mouse heads, the pixel-based rate constant of its reduction reaction was calculated as an index ofmore » the redox status in vivo and mapped as a “redox map”. The obtained redox maps from control and GSH-depleted mouse brains showed a clear change in the brain redox status, which was due to the decreased levels of GSH in brains as measured by a biochemical assay. We observed a linear relationship between the reduction rate constant of MCP and the level of GSH for both control and GSH-depleted mouse brains. Using this relationship, the GSH level in the brain can be estimated from the redox map obtained with EPR imaging. - Highlights: • Redox status of glutathione-depleted mouse brain was examined with EPR imaging. • Redox status of mouse brain changed depending on glutathione (GSH) levels in brains. • Linear relationship between GSH levels and redox status in brains was found. • Using this relation, estimation of GSH levels in brains is possible from EPR images.« less

Imaging of brain metastases.

PubMed

Fink, Kathleen R; Fink, James R

2013-01-01

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

Test-Retest Reliability of fMRI Brain Activity during Memory Encoding

PubMed Central

Brandt, David J.; Sommer, Jens; Krach, Sören; Bedenbender, Johannes; Kircher, Tilo; Paulus, Frieder M.; Jansen, Andreas

2013-01-01

The mechanisms underlying hemispheric specialization of memory are not completely understood. Functional magnetic resonance imaging (fMRI) can be used to develop and test models of hemispheric specialization. In particular for memory tasks however, the interpretation of fMRI results is often hampered by the low reliability of the data. In the present study we therefore analyzed the test-retest reliability of fMRI brain activation related to an implicit memory encoding task, with a particular focus on brain activity of the medial temporal lobe (MTL). Fifteen healthy subjects were scanned with fMRI on two sessions (average retest interval 35 days) using a commonly applied novelty encoding paradigm contrasting known and unknown stimuli. To assess brain lateralization, we used three different stimuli classes that differed in their verbalizability (words, scenes, fractals). Test-retest reliability of fMRI brain activation was assessed by an intraclass-correlation coefficient (ICC), describing the stability of inter-individual differences in the brain activation magnitude over time. We found as expected a left-lateralized brain activation network for the words paradigm, a bilateral network for the scenes paradigm, and predominantly right-hemispheric brain activation for the fractals paradigm. Although these networks were consistently activated in both sessions on the group level, across-subject reliabilities were only poor to fair (ICCs ≤ 0.45). Overall, the highest ICC values were obtained for the scenes paradigm, but only in strongly activated brain regions. In particular the reliability of brain activity of the MTL was poor for all paradigms. In conclusion, for novelty encoding paradigms the interpretation of fMRI results on a single subject level is hampered by its low reliability. More studies are needed to optimize the retest reliability of fMRI activation for memory tasks. PMID:24367338

In vivo rat deep brain imaging using photoacoustic computed tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lin, Li; Li, Lei; Zhu, Liren; Hu, Peng; Wang, Lihong V.

2017-03-01

The brain has been likened to a great stretch of unknown territory consisting of a number of unexplored continents. Small animal brain imaging plays an important role charting that territory. By using 1064 nm illumination from the side, we imaged the full coronal depth of rat brains in vivo. The experiment was performed using a real-time full-ring-array photoacoustic computed tomography (PACT) imaging system, which achieved an imaging depth of 11 mm and a 100 μm radial resolution. Because of the fast imaging speed of the full-ring-array PACT system, no animal motion artifact was induced. The frame rate of the system was limited by the laser repetition rate (50 Hz). In addition to anatomical imaging of the blood vessels in the brain, we continuously monitored correlations between the two brain hemispheres in one of the coronal planes. The resting states in the coronal plane were measured before and after stroke ligation surgery at a neck artery.

Registration of 3D fetal neurosonography and MRI☆

PubMed Central

Kuklisova-Murgasova, Maria; Cifor, Amalia; Napolitano, Raffaele; Papageorghiou, Aris; Quaghebeur, Gerardine; Rutherford, Mary A.; Hajnal, Joseph V.; Noble, J. Alison; Schnabel, Julia A.

2013-01-01

We propose a method for registration of 3D fetal brain ultrasound with a reconstructed magnetic resonance fetal brain volume. This method, for the first time, allows the alignment of models of the fetal brain built from magnetic resonance images with 3D fetal brain ultrasound, opening possibilities to develop new, prior information based image analysis methods for 3D fetal neurosonography. The reconstructed magnetic resonance volume is first segmented using a probabilistic atlas and a pseudo ultrasound image volume is simulated from the segmentation. This pseudo ultrasound image is then affinely aligned with clinical ultrasound fetal brain volumes using a robust block-matching approach that can deal with intensity artefacts and missing features in the ultrasound images. A qualitative and quantitative evaluation demonstrates good performance of the method for our application, in comparison with other tested approaches. The intensity average of 27 ultrasound images co-aligned with the pseudo ultrasound template shows good correlation with anatomy of the fetal brain as seen in the reconstructed magnetic resonance image. PMID:23969169

Advantages in functional imaging of the brain.

PubMed

Mier, Walter; Mier, Daniela

2015-01-01

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

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.

Conductive carbon tape used for support and mounting of both whole animal and fragile heat-treated tissue sections for MALDI MS imaging and quantitation.

PubMed

Goodwin, Richard J A; Nilsson, Anna; Borg, Daniel; Langridge-Smith, Pat R R; Harrison, David J; Mackay, C Logan; Iverson, Suzanne L; Andrén, Per E

2012-08-30

Analysis of whole animal tissue sections by MALDI MS imaging (MSI) requires effective sample collection and transfer methods to allow the highest quality of in situ analysis of small or hard to dissect tissues. We report on the use of double-sided adhesive conductive carbon tape during whole adult rat tissue sectioning of carboxymethyl cellulose (CMC) embedded animals, with samples mounted onto large format conductive glass and conductive plastic MALDI targets, enabling MSI analysis to be performed on both TOF and FT-ICR MALDI mass spectrometers. We show that mounting does not unduly affect small molecule MSI detection by analyzing tiotropium abundance and distribution in rat lung tissues, with direct on-tissue quantitation achieved. Significantly, we use the adhesive tape to provide support to embedded delicate heat-stabilized tissues, enabling sectioning and mounting to be performed that maintained tissue integrity on samples that had previously been impossible to adequately prepare section for MSI analysis. The mapping of larger peptidomic molecules was not hindered by tape mounting samples and we demonstrate this by mapping the distribution of PEP-19 in both native and heat-stabilized rat brains. Furthermore, we show that without heat stabilization PEP-19 degradation fragments can detected and identified directly by MALDI MSI analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

The surface topography of the choroid plexus. Environmental, low and high vacuum scanning electron microscopy.

PubMed

Mestres, Pedro; Pütz, Norbert; Garcia Gómez de Las Heras, Soledad; García Poblete, Eduardo; Morguet, Andrea; Laue, Michael

2011-05-01

Environmental scanning electron microscopy (ESEM) allows the examination of hydrated and dried specimens without a conductive metal coating which could be advantageous in the imaging of biological and medical objects. The aim of this study was to assess the performance and benefits of wet-mode and low vacuum ESEM in comparison to high vacuum scanning electron microscopy (SEM) using the choroid plexus of chicken embryos as a model, an organ of the brain involved in the formation of cerebrospinal fluid in vertebrates. Specimens were fixed with or without heavy metals and examined directly or after critical point drying with or without metal coating. For wet mode ESEM freshly excised specimens without any pre-treatment were also examined. Conventional high vacuum SEM revealed the characteristic morphology of the choroid plexus cells at a high resolution and served as reference. With low vacuum ESEM of dried but uncoated samples the structure appeared well preserved but charging was a problem. It could be reduced by a short beam dwell time and averaging of images or by using the backscattered electron detector instead of the gaseous secondary electron detector. However, resolution was lower than with conventional SEM. Wet mode imaging was only possible with tissue that had been stabilized by fixation. Not all surface details (e.g. microvilli) could be visualized and other structures, like the cilia, were deformed. In summary, ESEM is an additional option for the imaging of bio-medical samples but it is problematic with regard to resolution and sample stability during imaging. Copyright © 2011 Elsevier GmbH. All rights reserved.

Development and genetics of brain temporal stability related to attention problems in adolescent twins.

PubMed

Smit, Dirk J A; Anokhin, Andrey P

2017-05-01

The brain continuously develops and reorganizes to support an expanding repertoire of behaviors and increasingly complex cognition. These processes may, however, also result in the appearance or disappearance of specific neurodevelopmental disorders such as attention problems. To investigate whether brain activity changed during adolescence, how genetics shape this change, and how these changes were related to attention problems, we measured EEG activity in 759 twins and siblings, assessed longitudinally in four waves (12, 14, 16, and 18years of age). Attention problems were assessed with the SWAN at waves 12, 14, and 16. To characterize functional brain development, we used a measure of temporal stability (TS) of brain oscillations over the recording time of 5min reflecting the tendency of a brain to maintain the same oscillatory state for longer or shorter periods. Increased TS may reflect the brain's tendency to maintain stability, achieve focused attention, and thus reduce "mind wandering" and attention problems. The results indicate that brain TS is increased across the scalp from 12 to 18. TS showed large individual differences that were heritable. Change in TS (alpha oscillations) was heritable between 12 and 14 and between 14 and 16 for the frontal brain areas. Absolute levels of brain TS at each wave were positively correlated with attention problems but not significantly. High and low attention problems subjects showed different developmental trajectories in TS, which was significant in a cluster of frontal leads. These results indicate that trajectories in brain TS development are a biomarker for the developing brain. TS in brain oscillations is highly heritable, and age-related change in TS is also heritable in selected brain areas. These results suggest that high and low attention problems subjects are at different stages of brain development. Copyright © 2016. Published by Elsevier B.V.

A PRESTO-SENSE sequence with alternating partial-Fourier encoding for rapid susceptibility-weighted 3D MRI time series.

PubMed

Klarhöfer, Markus; Dilharreguy, Bixente; van Gelderen, Peter; Moonen, Chrit T W

2003-10-01

A 3D sequence for dynamic susceptibility imaging is proposed which combines echo-shifting principles (such as PRESTO), sensitivity encoding (SENSE), and partial-Fourier acquisition. The method uses a moderate SENSE factor of 2 and takes advantage of an alternating partial k-space acquisition in the "slow" phase encode direction allowing an iterative reconstruction using high-resolution phase estimates. Offering an isotropic spatial resolution of 4 x 4 x 4 mm(3), the novel sequence covers the whole brain including parts of the cerebellum in 0.5 sec. Its temporal signal stability is comparable to that of a full-Fourier, full-FOV EPI sequence having the same dynamic scan time but much less brain coverage. Initial functional MRI experiments showed consistent activation in the motor cortex with an average signal change slightly less than that of EPI. Copyright 2003 Wiley-Liss, Inc.

Subacute sclerosing panencephalitis and chronic viral encephalitis.

PubMed

Anlar, Banu

2013-01-01

Subacute sclerosing panencephalitis (SSPE) is a chronic infection of the central nervous system associated with the presence of mutant measles virus in the brain. It presents as a progressive, usually fatal disease. The diagnosis is based on clinical criteria and an elevated titer of measles antibodies in the cerebrospinal fluid (CSF). Electroencephalography and imaging studies provide supportive laboratory data. A brain biopsy is indicated only when CSF serology is negative or equivocal in a suspected case to assess the presence of inclusion bodies, measles virus antigens, or viral RNA. Among many drugs and methods tried in the treatment, the highest rate of stabilization or improvement was obtained with intraventricular human lymphoblastoid interferon-α and oral inosiplex. Further research for more available and efficient therapeutic regimens is warranted. Measles and SSPE are preventable by maintenance of high rates of immunization in the population. Copyright © 2013 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

The blood-brain barrier as a target in traumatic brain injury treatment.

PubMed

Thal, Serge C; Neuhaus, Winfried

2014-11-01

Traumatic brain injury (TBI) is one of the most frequent causes of death in the young population. Several clinical trials have unsuccessfully focused on direct neuroprotective therapies. Recently immunotherapeutic strategies shifted into focus of translational research in acute CNS diseases. Cross-talk between activated microglia and blood-brain barrier (BBB) could initiate opening of the BBB and subsequent recruitment of systemic immune cells and mediators into the brain. Stabilization of the BBB after TBI could be a promising strategy to limit neuronal inflammation, secondary brain damage and acute neurodegeneration. This review provides an overview on the pathophysiology of TBI and brain edema formation including definitions and classification of TBI, current clinical treatment strategies, as well as current understanding on the underlying cellular processes. A summary of in vivo and in vitro models to study different aspects of TBI is presented. Three mechanisms proposed for stabilization of the BBB, myosin light chain kinases, glucocorticoid receptors and peroxisome proliferator-activated receptors are reviewed for their influence on barrier-integrity and outcome after TBI. In conclusion, the BBB is recommended as a promising target for the treatment of traumatic brain injury, and it is suggested that a combination of BBB stabilization and neuroprotectants may improve therapeutic success. Copyright © 2015 IMSS. Published by Elsevier Inc. All rights reserved.

[First clinical experience with extended planning and navigation in an interventional MRI unit].

PubMed

Moche, M; Schmitgen, A; Schneider, J P; Bublat, M; Schulz, T; Voerkel, C; Trantakis, C; Bennek, J; Kahn, T; Busse, H

2004-07-01

To present an advanced concept for patient-based navigation and to report on our first clinical experience with interventions in the cranium, of soft-tissue structures (breast, liver) and in the musculoskeletal system. A PC-based navigation system was integrated into an existing interventional MRI environment. Intraoperatively acquired 3D data were used for interventional planning. The information content of these reference data was increased by integration of additional image modalities (e. g., fMRI, CT) and by color display of areas with early contrast media enhancement. Within 18 months, the system was used in 123 patients undergoing interventions in different anatomic regions (brain: 64, paranasal sinus: 9, breast: 20, liver: 17, bone: 9, muscle: 4). The mean duration of 64 brain interventions was compared with that of 36 procedures using the scanner's standard navigation. In contrast with the continuous scanning mode of the MR system (0.25 fps), the higher quality as well as the real time display (4 fps) of the MR images reconstructed from the 3D reference data allowed adequate hand-eye coordination. With our system, patient movement and tissue shifts could be immediately detected intraoperatively, and, in contrast to the standard procedure, navigation safely resumed after updating the reference data. The navigation system was characterized by good stability, efficient system integration and easy usability. Despite additional working steps still to be optimized, the duration of the image-guided brain tumor resections was not significantly longer. The presented system combines the advantage of intraoperative MRI with established visualization, planning, and real time capabilities of neuronavigation and can be efficiently applied in a broad range of non-neurosurgical interventions.

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

Detecting stripe artifacts in ultrasound images.

PubMed

Maciak, Adam; Kier, Christian; Seidel, Günter; Meyer-Wiethe, Karsten; Hofmann, Ulrich G

2009-10-01

Brain perfusion diseases such as acute ischemic stroke are detectable through computed tomography (CT)-/magnetic resonance imaging (MRI)-based methods. An alternative approach makes use of ultrasound imaging. In this low-cost bedside method, noise and artifacts degrade the imaging process. Especially stripe artifacts show a similar signal behavior compared to acute stroke or brain perfusion diseases. This document describes how stripe artifacts can be detected and eliminated in ultrasound images obtained through harmonic imaging (HI). On the basis of this new method, both proper identification of areas with critically reduced brain tissue perfusion and classification between brain perfusion defects and ultrasound stripe artifacts are made possible.

Novel Nanotechnologies for Brain Cancer Therapeutics and Imaging.

PubMed

Ferroni, Letizia; Gardin, Chiara; Della Puppa, Alessandro; Sivolella, Stefano; Brunello, Giulia; Scienza, Renato; Bressan, Eriberto; D'Avella, Domenico; Zavan, Barbara

2015-11-01

Despite progress in surgery, radiotherapy, and in chemotherapy, an effective curative treatment of brain cancer, specifically malignant gliomas, does not yet exist. The efficacy of current anti-cancer strategies in brain tumors is limited by the lack of specific therapies against malignant cells. Besides, the delivery of the drugs to brain tumors is limited by the presence of the blood-brain barrier. Nanotechnology today offers a unique opportunity to develop more effective brain cancer imaging and therapeutics. In particular, the development of nanocarriers that can be conjugated with several functional molecules including tumor-specific ligands, anticancer drugs, and imaging probes, can provide new devices which are able to overcome the difficulties of the classical strategies. Nanotechnology-based approaches hold great promise for revolutionizing brain cancer medical treatments, imaging, and diagnosis.

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

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

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

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.

Imaging Human Brain Perfusion with Inhaled Hyperpolarized 129Xe MR Imaging.

PubMed

Rao, Madhwesha R; Stewart, Neil J; Griffiths, Paul D; Norquay, Graham; Wild, Jim M

2018-02-01

Purpose To evaluate the feasibility of directly imaging perfusion of human brain tissue by using magnetic resonance (MR) imaging with inhaled hyperpolarized xenon 129 ( 129 Xe). Materials and Methods In vivo imaging with 129 Xe was performed in three healthy participants. The combination of a high-yield spin-exchange optical pumping 129 Xe polarizer, custom-built radiofrequency coils, and an optimized gradient-echo MR imaging protocol was used to achieve signal sensitivity sufficient to directly image hyperpolarized 129 Xe dissolved in the human brain. Conventional T1-weighted proton (hydrogen 1 [ 1 H]) images and perfusion images by using arterial spin labeling were obtained for comparison. Results Images of 129 Xe uptake were obtained with a signal-to-noise ratio of 31 ± 9 and demonstrated structural similarities to the gray matter distribution on conventional T1-weighted 1 H images and to perfusion images from arterial spin labeling. Conclusion Hyperpolarized 129 Xe MR imaging is an injection-free means of imaging the perfusion of cerebral tissue. The proposed method images the uptake of inhaled xenon gas to the extravascular brain tissue compartment across the intact blood-brain barrier. This level of sensitivity is not readily available with contemporary MR imaging methods. © RSNA, 2017.

Computer-aided diagnosis with radiogenomics: analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images.

PubMed

Kai, Chiharu; Uchiyama, Yoshikazu; Shiraishi, Junji; Fujita, Hiroshi; Doi, Kunio

2018-05-10

In the post-genome era, a novel research field, 'radiomics' has been developed to offer a new viewpoint for the use of genotypes in radiology and medicine research which have traditionally focused on the analysis of imaging phenotypes. The present study analyzed brain morphological changes related to the individual's genotype. Our data consisted of magnetic resonance (MR) images of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), as well as their apolipoprotein E (APOE) genotypes. First, statistical parametric mapping (SPM) 12 was used for three-dimensional anatomical standardization of the brain MR images. A total of 30 normal images were used to create a standard normal brain image. Z-score maps were generated to identify the differences between an abnormal image and the standard normal brain. Our experimental results revealed that cerebral atrophies, depending on genotypes, can occur in different locations and that morphological changes may differ between MCI and AD. Using a classifier to characterize cerebral atrophies related to an individual's genotype, we developed a computer-aided diagnosis (CAD) scheme to identify the disease. For the early detection of cerebral diseases, a screening system using MR images, called Brain Check-up, is widely performed in Japan. Therefore, our proposed CAD scheme would be used in Brain Check-up.

Minocycline Effects on Intracerebral Hemorrhage-Induced Iron Overload in Aged Rats: Brain Iron Quantification With Magnetic Resonance Imaging.

PubMed

Cao, Shenglong; Hua, Ya; Keep, Richard F; Chaudhary, Neeraj; Xi, Guohua

2018-04-01

Brain iron overload is a key factor causing brain injury after intracerebral hemorrhage (ICH). This study quantified brain iron levels after ICH with magnetic resonance imaging R2* mapping. The effect of minocycline on iron overload and ICH-induced brain injury in aged rats was also determined. Aged (18 months old) male Fischer 344 rats had an intracerebral injection of autologous blood or saline, and brain iron levels were measured by magnetic resonance imaging R2* mapping. Some ICH rats were treated with minocycline or vehicle. The rats were euthanized at days 7 and 28 after ICH, and brains were used for immunohistochemistry and Western blot analyses. Magnetic resonance imaging (T2-weighted, T2* gradient-echo, and R2* mapping) sequences were performed at different time points. ICH-induced brain iron overload in the perihematomal area could be quantified by R2* mapping. Minocycline treatment reduced brain iron accumulation, T2* lesion volume, iron-handling protein upregulation, neuronal cell death, and neurological deficits ( P <0.05). Magnetic resonance imaging R2* mapping is a reliable and noninvasive method, which can quantitatively measure brain iron levels after ICH. Minocycline reduced ICH-related perihematomal iron accumulation and brain injury in aged rats. © 2018 American Heart Association, Inc.

Groupwise registration of MR brain images with tumors.

PubMed

Tang, Zhenyu; Wu, Yihong; Fan, Yong

2017-08-04

A novel groupwise image registration framework is developed for registering MR brain images with tumors. Our method iteratively estimates a normal-appearance counterpart for each tumor image to be registered and constructs a directed graph (digraph) of normal-appearance images to guide the groupwise image registration. Particularly, our method maps each tumor image to its normal appearance counterpart by identifying and inpainting brain tumor regions with intensity information estimated using a low-rank plus sparse matrix decomposition based image representation technique. The estimated normal-appearance images are groupwisely registered to a group center image guided by a digraph of images so that the total length of 'image registration paths' to be the minimum, and then the original tumor images are warped to the group center image using the resulting deformation fields. We have evaluated our method based on both simulated and real MR brain tumor images. The registration results were evaluated with overlap measures of corresponding brain regions and average entropy of image intensity information, and Wilcoxon signed rank tests were adopted to compare different methods with respect to their regional overlap measures. Compared with a groupwise image registration method that is applied to normal-appearance images estimated using the traditional low-rank plus sparse matrix decomposition based image inpainting, our method achieved higher image registration accuracy with statistical significance (p  =  7.02  ×  10 -9 ).

Photoacoustic imaging for transvascular drug delivery to the rat brain

NASA Astrophysics Data System (ADS)

Watanabe, Ryota; Sato, Shunichi; Tsunoi, Yasuyuki; Kawauchi, Satoko; Takemura, Toshiya; Terakawa, Mitsuhiro

2015-03-01

Transvascular drug delivery to the brain is difficult due to the blood-brain barrier (BBB). Thus, various methods for safely opening the BBB have been investigated, for which real-time imaging methods are desired both for the blood vessels and distribution of a drug. Photoacoustic (PA) imaging, which enables depth-resolved visualization of chromophores in tissue, would be useful for this purpose. In this study, we performed in vivo PA imaging of the blood vessels and distribution of a drug in the rat brain by using an originally developed compact PA imaging system with fiber-based illumination. As a test drug, Evans blue (EB) was injected to the tail vein, and a photomechanical wave was applied to the targeted brain tissue to increase the permeability of the blood vessel walls. For PA imaging of blood vessels and EB distribution, nanosecond pulses at 532 nm and 670 nm were used, respectively. We clearly visualized blood vessels with diameters larger than 50 μm and the distribution of EB in the brain, showing spatiotemporal characteristics of EB that was transvascularly delivered to the target tissue in the brain.

Embedding and Chemical Reactivation of Green Fluorescent Protein in the Whole Mouse Brain for Optical Micro-Imaging

PubMed Central

Gang, Yadong; Zhou, Hongfu; Jia, Yao; Liu, Ling; Liu, Xiuli; Rao, Gong; Li, Longhui; Wang, Xiaojun; Lv, Xiaohua; Xiong, Hanqing; Yang, Zhongqin; Luo, Qingming; Gong, Hui; Zeng, Shaoqun

2017-01-01

Resin embedding has been widely applied to fixing biological tissues for sectioning and imaging, but has long been regarded as incompatible with green fluorescent protein (GFP) labeled sample because it reduces fluorescence. Recently, it has been reported that resin-embedded GFP-labeled brain tissue can be imaged with high resolution. In this protocol, we describe an optimized protocol for resin embedding and chemical reactivation of fluorescent protein labeled mouse brain, we have used mice as experiment model, but the protocol should be applied to other species. This method involves whole brain embedding and chemical reactivation of the fluorescent signal in resin-embedded tissue. The whole brain embedding process takes a total of 7 days. The duration of chemical reactivation is ~2 min for penetrating 4 μm below the surface in the resin-embedded brain. This protocol provides an efficient way to prepare fluorescent protein labeled sample for high-resolution optical imaging. This kind of sample was demonstrated to be imaged by various optical micro-imaging methods. Fine structures labeled with GFP across a whole brain can be detected. PMID:28352214

Correspondence of the brain's functional architecture during activation and rest.

PubMed

Smith, Stephen M; Fox, Peter T; Miller, Karla L; Glahn, David C; Fox, P Mickle; Mackay, Clare E; Filippini, Nicola; Watkins, Kate E; Toro, Roberto; Laird, Angela R; Beckmann, Christian F

2009-08-04

Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is "at rest." In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically "active" even when at "rest."

Retractor-induced brain shift compensation in image-guided neurosurgery

NASA Astrophysics Data System (ADS)

Fan, Xiaoyao; Ji, Songbai; Hartov, Alex; Roberts, David; Paulsen, Keith

2013-03-01

In image-guided neurosurgery, intraoperative brain shift significantly degrades the accuracy of neuronavigation that is solely based on preoperative magnetic resonance images (pMR). To compensate for brain deformation and to maintain the accuracy in image guidance achieved at the start of surgery, biomechanical models have been developed to simulate brain deformation and to produce model-updated MR images (uMR) to compensate for brain shift. To-date, most studies have focused on shift compensation at early stages of surgery (i.e., updated images are only produced after craniotomy and durotomy). Simulating surgical events at later stages such as retraction and tissue resection are, perhaps, clinically more relevant because of the typically much larger magnitudes of brain deformation. However, these surgical events are substantially more complex in nature, thereby posing significant challenges in model-based brain shift compensation strategies. In this study, we present results from an initial investigation to simulate retractor-induced brain deformation through a biomechanical finite element (FE) model where whole-brain deformation assimilated from intraoperative data was used produce uMR for improved accuracy in image guidance. Specifically, intensity-encoded 3D surface profiles at the exposed cortical area were reconstructed from intraoperative stereovision (iSV) images before and after tissue retraction. Retractor-induced surface displacements were then derived by coregistering the surfaces and served as sparse displacement data to drive the FE model. With one patient case, we show that our technique is able to produce uMR that agrees well with the reconstructed iSV surface after retraction. The computational cost to simulate retractor-induced brain deformation was approximately 10 min. In addition, our approach introduces minimal interruption to the surgical workflow, suggesting the potential for its clinical application.

Hemorrhage detection in MRI brain images using images features

NASA Astrophysics Data System (ADS)

Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

2013-11-01

The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

Development of PET/MRI with insertable PET for simultaneous PET and MR imaging of human brain

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

Jung, Jin Ho; Choi, Yong, E-mail: ychoi.image@gmail.com; Jung, Jiwoong

2015-05-15

Purpose: The purpose of this study was to develop a dual-modality positron emission tomography (PET)/magnetic resonance imaging (MRI) with insertable PET for simultaneous PET and MR imaging of the human brain. Methods: The PET detector block was composed of a 4 × 4 matrix of detector modules, each consisting of a 4 × 4 array LYSO coupled to a 4 × 4 Geiger-mode avalanche photodiode (GAPD) array. The PET insert consisted of 18 detector blocks, circularly mounted on a custom-made plastic base to form a ring with an inner diameter of 390 mm and axial length of 60 mm. Themore » PET gantry was shielded with gold-plated conductive fabric tapes with a thickness of 0.1 mm. The charge signals of PET detector transferred via 4 m long flat cables were fed into the position decoder circuit. The flat cables were shielded with a mesh-type aluminum sheet with a thickness of 0.24 mm. The position decoder circuit and field programmable gate array-embedded DAQ modules were enclosed in an aluminum box with a thickness of 10 mm and located at the rear of the MR bore inside the MRI room. A 3-T human MRI system with a Larmor frequency of 123.7 MHz and inner bore diameter of 60 cm was used as the PET/MRI hybrid system. A custom-made radio frequency (RF) coil with an inner diameter of 25 cm was fabricated. The PET was positioned between gradient and the RF coils. PET performance was measured outside and inside the MRI scanner using echo planar imaging, spin echo, turbo spin echo, and gradient echo sequences. MRI performance was also evaluated with and without the PET insert. The stability of the newly developed PET insert was evaluated and simultaneous PET and MR images of a brain phantom were acquired. Results: No significant degradation of the PET performance caused by MR was observed when the PET was operated using various MR imaging sequences. The signal-to-noise ratio of MR images was slightly degraded due to the PET insert installed inside the MR bore while the homogeneity was maintained. The change of gain of the 256 GAPD/scintillator elements of a detector block was <3% for 60 min, and simultaneous PET and MR images of a brain phantom were successfully acquired. Conclusions: Experimental results indicate that a compact and lightweight PET insert for hybrid PET/MRI can be developed using GAPD arrays and charge signal transmission method proposed in this study without significant interference.« less

Traumatic brain injury and vestibulo-ocular function: current challenges and future prospects

PubMed Central

Wallace, Bridgett; Lifshitz, Jonathan

2016-01-01

Normal function of the vestibulo-ocular reflex (VOR) coordinates eye movement with head movement, in order to provide clear vision during motion and maintain balance. VOR is generated within the semicircular canals of the inner ear to elicit compensatory eye movements, which maintain stability of images on the fovea during brief, rapid head motion, otherwise known as gaze stability. Normal VOR function is necessary in carrying out activities of daily living (eg, walking and riding in a car) and is of particular importance in higher demand activities (eg, sports-related activities). Disruption or damage in the VOR can result in symptoms such as movement-related dizziness, blurry vision, difficulty maintaining balance with head movements, and even nausea. Dizziness is one of the most common symptoms following traumatic brain injury (TBI) and is considered a risk factor for a prolonged recovery. Assessment of the vestibular system is of particular importance following TBI, in conjunction with oculomotor control, due to the intrinsic neural circuitry that exists between the ocular and vestibular systems. The purpose of this article is to review the physiology of the VOR and the visual-vestibular symptoms associated with TBI and to discuss assessment and treatment guidelines for TBI. Current challenges and future prospects will also be addressed. PMID:28539811

Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles.

PubMed

Barker, Jocelyn; Hoogi, Assaf; Depeursinge, Adrien; Rubin, Daniel L

2016-05-01

Computerized analysis of digital pathology images offers the potential of improving clinical care (e.g. automated diagnosis) and catalyzing research (e.g. discovering disease subtypes). There are two key challenges thwarting computerized analysis of digital pathology images: first, whole slide pathology images are massive, making computerized analysis inefficient, and second, diverse tissue regions in whole slide images that are not directly relevant to the disease may mislead computerized diagnosis algorithms. We propose a method to overcome both of these challenges that utilizes a coarse-to-fine analysis of the localized characteristics in pathology images. An initial surveying stage analyzes the diversity of coarse regions in the whole slide image. This includes extraction of spatially localized features of shape, color and texture from tiled regions covering the slide. Dimensionality reduction of the features assesses the image diversity in the tiled regions and clustering creates representative groups. A second stage provides a detailed analysis of a single representative tile from each group. An Elastic Net classifier produces a diagnostic decision value for each representative tile. A weighted voting scheme aggregates the decision values from these tiles to obtain a diagnosis at the whole slide level. We evaluated our method by automatically classifying 302 brain cancer cases into two possible diagnoses (glioblastoma multiforme (N = 182) versus lower grade glioma (N = 120)) with an accuracy of 93.1% (p < 0.001). We also evaluated our method in the dataset provided for the 2014 MICCAI Pathology Classification Challenge, in which our method, trained and tested using 5-fold cross validation, produced a classification accuracy of 100% (p < 0.001). Our method showed high stability and robustness to parameter variation, with accuracy varying between 95.5% and 100% when evaluated for a wide range of parameters. Our approach may be useful to automatically differentiate between the two cancer subtypes. Copyright © 2015 Elsevier B.V. All rights reserved.

Efficient gene transfection to the brain with ultrasound irradiation in mice using stabilized bubble lipopolyplexes prepared by the surface charge regulation method.

PubMed

Ogawa, Koki; Fuchigami, Yuki; Hagimori, Masayori; Fumoto, Shintaro; Miura, Yusuke; Kawakami, Shigeru

2018-01-01

We previously developed anionic ternary bubble lipopolyplexes, an ultrasound-responsive carrier, expecting safe and efficient gene transfection. However, bubble lipopolyplexes have a low capacity for echo gas (C 3 F 8 ) encapsulation (EGE) in nonionic solution such as 5% glucose. On the other hand, we were able to prepare bubble lipopolyplexes by inserting phosphate-buffered saline before C 3 F 8 encapsulation. Surface charge regulation (SCR) by electrolytes stabilizes liposome/plasmid DNA (pDNA) complexes by accelerated membrane fusion. Considering these facts, we hypothesized that SCR by electrolytes such as NaCl would promote C 3 F 8 encapsulation in bubble lipopolyplexes mediated by accelerated membrane fusion. We defined this hypothesis as SCR-based EGE (SCR-EGE). Bubble lipopolyplexes prepared by the SCR-EGE method (SCR-EGE bubble lipopolyplexes) are expected to facilitate the gene transfection because of the high amount of C 3 F 8 . Therefore, we applied these methods for gene delivery to the brain and evaluated the characteristics of transgene expression in the brain. First, we measured the encapsulation efficiency of C 3 F 8 in SCR-EGE bubble lipopolyplexes. Next, we applied these bubble lipopolyplexes to the mouse brain; then, we evaluated the transfection efficiency. Furthermore, three-dimensional transgene distribution was observed using multicolor deep imaging. SCR-EGE bubble lipopolyplexes had a higher C 3 F 8 content than conventional bubble lipopolyplexes. In terms of safety, SCR-EGE bubble lipopolyplexes possessed an anionic potential and showed no aggregation with erythrocytes. After applying SCR-EGE bubble lipopolyplexes to the brain, high transgene expression was observed by combining with ultrasound irradiation. As a result, transgene expression mediated by SCR-EGE bubble lipopolyplexes was observed mainly on blood vessels and partially outside of blood vessels. The SCR-EGE method may promote C 3 F 8 encapsulation in bubble lipopolyplexes, and SCR-EGE bubble lipopolyplexes may be potent carriers for efficient and safe gene transfection in the brain, especially to the blood vessels.

A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head.

PubMed

Delora, Adam; Gonzales, Aaron; Medina, Christopher S; Mitchell, Adam; Mohed, Abdul Faheem; Jacobs, Russell E; Bearer, Elaine L

2016-01-15

Magnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics. This novel timesaving automation of template-based brain extraction ("skull-stripping") is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction. This method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved. A downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement. Our new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI. Copyright © 2015 Elsevier B.V. All rights reserved.

SAXS Study of Sterically Stabilized Lipid Nanocarriers Functionalized by DNA

NASA Astrophysics Data System (ADS)

Angelov, Borislav; Angelova, Angelina; Filippov, Sergey; Karlsson, Göran; Terrill, Nick; Lesieur, Sylviane; Štěpánek, Petr

2012-03-01

The structure of novel spontaneously self-assembled plasmid DNA/lipid complexes is investigated by means of synchrotron radiation small-angle X-ray scattering (SAXS) and Cryo-TEM imaging. Liquid crystalline (LC) hydrated lipid systems are prepared using the non-ionic lipids monoolein and DOPE-PEG2000 and the cationic amphiphile CTAB. The employed plasmid DNA (pDNA) is encoding for the human protein brain-derived neurotrophic factor (BDNF). A coexistence of nanoparticulate objects with different LC inner organizations is established. A transition from bicontinuous membrane sponges, cubosome intermediates and unilamelar liposomes to multilamellar vesicles, functionalized by pDNA, is favoured upon binding and compaction of pBDNF onto the cationic PEGylated lipid nanocarriers. The obtained sterically stabilized multicompartment nanoobjects, with confined supercoiled plasmid DNA (pBDNF), are important in the context of multicompartment lipid nanocarriers of interest for gene therapy of neurodegenerative diseases.

Synchrotron radiation imaging is a powerful tool to image brain microvasculature

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

Zhang, Mengqi; Sun, Danni; Xie, Yuanyuan

2014-03-15

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

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

PubMed

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

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

[Brain imaging in autism spectrum disorders. A review].

PubMed

Dziobek, I; Köhne, S

2011-05-01

In the past two decades, an increasing number of functional and structural brain imaging studies has provided insights into the neurobiological basis of autism spectrum disorders (ASD). This article summarizes pertinent functional brain imaging studies addressing the neuronal underpinnings of ASD symptomatology (impairments in social interaction and communication, repetitive and restrictive behavior) and associated neuropsychological deficits (theory of mind, executive functions, central coherence), complemented by relevant structural imaging findings. The results of these studies show that although cognitive functions in ASD are generally mediated by the same brain regions as in typically developed individuals, the degree and especially the patterns of brain activation often differ. Therefore, a hypothesis of aberrant network connectivity has increasingly been favored over one of focal brain dysfunction.

Contrast enhancement in EIT imaging of the brain.

PubMed

Nissinen, A; Kaipio, J P; Vauhkonen, M; Kolehmainen, V

2016-01-01

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data.

A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS).

PubMed

Job, Dominic E; Dickie, David Alexander; Rodriguez, David; Robson, Andrew; Danso, Sammy; Pernet, Cyril; Bastin, Mark E; Boardman, James P; Murray, Alison D; Ahearn, Trevor; Waiter, Gordon D; Staff, Roger T; Deary, Ian J; Shenkin, Susan D; Wardlaw, Joanna M

2017-01-01

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Clinics in diagnostic imaging (153). Severe hypoxic ischaemic brain injury.

PubMed Central

Chua, Wynne; Lim, Boon Keat; Lim, Tchoyoson Choie Cheio

2014-01-01

A 58-year-old Indian woman presented with asystole after an episode of haemetemesis, with a patient downtime of 20 mins. After initial resuscitation efforts, computed tomography of the brain, obtained to evaluate neurological injury, demonstrated evidence of severe hypoxic ischaemic brain injury. The imaging features of hypoxic ischaemic brain injury and the potential pitfalls with regard to image interpretation are herein discussed. PMID:25091891

Real-time reconstruction of three-dimensional brain surface MR image using new volume-surface rendering technique

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

Watanabe, T.; Momose, T.; Oku, S.

It is essential to obtain realistic brain surface images, in which sulci and gyri are easily recognized, when examining the correlation between functional (PET or SPECT) and anatomical (MRI) brain studies. The volume rendering technique (VRT) is commonly employed to make three-dimensional (3D) brain surface images. This technique, however, takes considerable time to make only one 3D image. Therefore it has not been practical to make the brain surface images in arbitrary directions on a real-time basis using ordinary work stations or personal computers. The surface rendering technique (SRT), on the other hand, is much less computationally demanding, but themore » quality of resulting images is not satisfactory for our purpose. A new computer algorithm has been developed to make 3D brain surface MR images very quickly using a volume-surface rendering technique (VSRT), in which the quality of resulting images is comparable to that of VRT and computation time to SRT. In VSRT the process of volume rendering is done only once to the direction of the normal vector of each surface point, rather than each time a new view point is determined as in VRT. Subsequent reconstruction of the 3D image uses a similar algorithm to that of SRT. Thus we can obtain brain surface MR images of sufficient quality viewed from any direction on a real-time basis using an easily available personal computer (Macintosh Quadra 800). The calculation time to make a 3D image is less than 1 sec. in VSRT, while that is more than 15 sec. in the conventional VRT. The difference of resulting image quality between VSRT and VRT is almost imperceptible. In conclusion, our new technique for real-time reconstruction of 3D brain surface MR image is very useful and practical in the functional and anatomical correlation study.« less

The detectability of brain metastases using contrast-enhanced spin-echo or gradient-echo images: a systematic review and meta-analysis.

PubMed

Suh, Chong Hyun; Jung, Seung Chai; Kim, Kyung Won; Pyo, Junhee

2016-09-01

This study aimed to compare the detectability of brain metastases using contrast-enhanced spin-echo (SE) and gradient-echo (GRE) T1-weighted images. The Ovid-MEDLINE and EMBASE databases were searched for studies on the detectability of brain metastases using contrast-enhanced SE or GRE images. The pooled proportions for the detectability of brain metastases were assessed using random-effects modeling. Heterogeneity among studies was determined using χ (2) statistics for the pooled estimates and the inconsistency index, I (2) . To overcome heterogeneity, subgroup analyses according to slice thickness and lesion size were performed. A total of eight eligible studies, which included a sample size of 252 patients and 1413 brain metastases, were included. The detectability of brain metastases using SE images (89.2 %) was higher than using GRE images (81.6 %; adjusted 84.0 %), but this difference was not statistically significant (p = 0.2385). In subgroup analysis of studies with 1-mm-thick slices and small metastases (<5 mm in diameter), 3-dimensional (3D) SE images demonstrated a higher detectability in comparison to 3D GRE images (93.7 % vs 73.1 % in 1-mm-thick slices; 89.5 % vs 59.4 % for small metastases) (p < 0.0001). Although both SE or GRE images are acceptable for detecting brain metastases, contrast-enhanced 3D SE images using 1-mm-thick slices are preferred for detecting brain metastases, especially small lesions (<5 mm in diameter).

A Unified Framework for Brain Segmentation in MR Images

PubMed Central

Yazdani, S.; Yusof, R.; Karimian, A.; Riazi, A. H.; Bennamoun, M.

2015-01-01

Brain MRI segmentation is an important issue for discovering the brain structure and diagnosis of subtle anatomical changes in different brain diseases. However, due to several artifacts brain tissue segmentation remains a challenging task. The aim of this paper is to improve the automatic segmentation of brain into gray matter, white matter, and cerebrospinal fluid in magnetic resonance images (MRI). We proposed an automatic hybrid image segmentation method that integrates the modified statistical expectation-maximization (EM) method and the spatial information combined with support vector machine (SVM). The combined method has more accurate results than what can be achieved with its individual techniques that is demonstrated through experiments on both real data and simulated images. Experiments are carried out on both synthetic and real MRI. The results of proposed technique are evaluated against manual segmentation results and other methods based on real T1-weighted scans from Internet Brain Segmentation Repository (IBSR) and simulated images from BrainWeb. The Kappa index is calculated to assess the performance of the proposed framework relative to the ground truth and expert segmentations. The results demonstrate that the proposed combined method has satisfactory results on both simulated MRI and real brain datasets. PMID:26089978

Quantitative Imaging of Energy Expenditure in Human Brain

PubMed Central

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

The Importance of Neurogenic Inflammation in Blast-Induced Neurotrauma

DTIC Science & Technology

2013-01-01

mild/moderate BINT are imaged by magnetic resonance imaging ( MRI ) to visualize potential macrophage infiltration; blood-brain barrier (BBB) disturbance...TERMS blast, traumatic brain injury, brain, inflammation, magnetic resonance imaging , mice 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...monitoring the success of therapeutic interventions. In this annual report we have utilized current live imaging methods (i.e. magnetic resonance

Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

PubMed

Renjith, Arokia; Manjula, P; Mohan Kumar, P

2015-01-01

Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

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.

Mechanism of Chronic Pain in Rodent Brain Imaging

NASA Astrophysics Data System (ADS)

Chang, Pei-Ching

Chronic pain is a significant health problem that greatly impacts the quality of life of individuals and imparts high costs to society. Despite intense research effort in understanding of the mechanism of pain, chronic pain remains a clinical problem that has few effective therapies. The advent of human brain imaging research in recent years has changed the way that chronic pain is viewed. To further extend the use of human brain imaging techniques for better therapies, the adoption of imaging technique onto the animal pain models is essential, in which underlying brain mechanisms can be systematically studied using various combination of imaging and invasive techniques. The general goal of this thesis is to addresses how brain develops and maintains chronic pain in an animal model using fMRI. We demonstrate that nucleus accumbens, the central component of mesolimbic circuitry, is essential in development of chronic pain. To advance our imaging technique, we develop an innovative methodology to carry out fMRI in awake, conscious rat. Using this cutting-edge technique, we show that allodynia is assoicated with shift brain response toward neural circuits associated nucleus accumbens and prefrontal cortex that regulate affective and cognitive component of pain. Taken together, this thesis provides a deeper understanding of how brain mediates pain. It builds on the existing body of knowledge through maximizing the depth of insight into brain imaging of chronic pain.

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.

Brain Signal Variability Differentially Affects Cognitive Flexibility and Cognitive Stability.

PubMed

Armbruster-Genç, Diana J N; Ueltzhöffer, Kai; Fiebach, Christian J

2016-04-06

Recent research yielded the intriguing conclusion that, in healthy adults, higher levels of variability in neuronal processes are beneficial for cognitive functioning. Beneficial effects of variability in neuronal processing can also be inferred from neurocomputational theories of working memory, albeit this holds only for tasks requiring cognitive flexibility. However, cognitive stability, i.e., the ability to maintain a task goal in the face of irrelevant distractors, should suffer under high levels of brain signal variability. To directly test this prediction, we studied both behavioral and brain signal variability during cognitive flexibility (i.e., task switching) and cognitive stability (i.e., distractor inhibition) in a sample of healthy human subjects and developed an efficient and easy-to-implement analysis approach to assess BOLD-signal variability in event-related fMRI task paradigms. Results show a general positive effect of neural variability on task performance as assessed by accuracy measures. However, higher levels of BOLD-signal variability in the left inferior frontal junction area result in reduced error rate costs during task switching and thus facilitate cognitive flexibility. In contrast, variability in the same area has a detrimental effect on cognitive stability, as shown in a negative effect of variability on response time costs during distractor inhibition. This pattern was mirrored at the behavioral level, with higher behavioral variability predicting better task switching but worse distractor inhibition performance. Our data extend previous results on brain signal variability by showing a differential effect of brain signal variability that depends on task context, in line with predictions from computational theories. Recent neuroscientific research showed that the human brain signal is intrinsically variable and suggested that this variability improves performance. Computational models of prefrontal neural networks predict differential effects of variability for different behavioral situations requiring either cognitive flexibility or stability. However, this hypothesis has so far not been put to an empirical test. In this study, we assessed cognitive flexibility and cognitive stability, and, besides a generally positive effect of neural variability on accuracy measures, we show that neural variability in a prefrontal brain area at the inferior frontal junction is differentially associated with performance: higher levels of variability are beneficial for the effectiveness of task switching (cognitive flexibility) but detrimental for the efficiency of distractor inhibition (cognitive stability). Copyright © 2016 the authors 0270-6474/16/363978-10$15.00/0.

Measuring the labeling efficiency of pseudocontinuous arterial spin labeling.

PubMed

Chen, Zhensen; Zhang, Xingxing; Yuan, Chun; Zhao, Xihai; van Osch, Matthias J P

2017-05-01

Optimization and validation of a sequence for measuring the labeling efficiency of pseudocontinuous arterial spin labeling (pCASL) perfusion MRI. The proposed sequence consists of a labeling module and a single slice Look-Locker echo planar imaging readout. A model-based algorithm was used to calculate labeling efficiency from the signal acquired from the main brain-feeding arteries. Stability of the labeling efficiency measurement was evaluated with regard to the use of cardiac triggering, flow compensation and vein signal suppression. Accuracy of the measurement was assessed by comparing the measured labeling efficiency to mean brain pCASL signal intensity over a wide range of flip angles as applied in the pCASL labeling. Simulations show that the proposed algorithm can effectively calculate labeling efficiency when correcting for T1 relaxation of the blood spins. Use of cardiac triggering and vein signal suppression improved stability of the labeling efficiency measurement, while flow compensation resulted in little improvement. The measured labeling efficiency was found to be linearly (R = 0.973; P < 0.001) related to brain pCASL signal intensity over a wide range of pCASL flip angles. The optimized labeling efficiency sequence provides robust artery-specific labeling efficiency measurement within a short acquisition time (∼30 s), thereby enabling improved accuracy of pCASL CBF quantification. Magn Reson Med 77:1841-1852, 2017. © 2016 International Society for Magnetic Resonance in Medicine Magn Reson Med 77:1841-1852, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

PubMed Central

Maji, Pradipta; Roy, Shaswati

2015-01-01

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

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

PubMed

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

2018-04-29

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

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.

A combined solenoid-surface RF coil for high-resolution whole-brain rat imaging on a 3.0 Tesla clinical MR scanner.

PubMed

Underhill, Hunter R; Yuan, Chun; Hayes, Cecil E

2010-09-01

Rat brain models effectively simulate a multitude of human neurological disorders. Improvements in coil design have facilitated the wider utilization of rat brain models by enabling the utilization of clinical MR scanners for image acquisition. In this study, a novel coil design, subsequently referred to as the rat brain coil, is described that exploits and combines the strengths of both solenoids and surface coils into a simple, multichannel, receive-only coil dedicated to whole-brain rat imaging on a 3.0 T clinical MR scanner. Compared with a multiturn solenoid mouse body coil, a 3-cm surface coil, a modified Helmholtz coil, and a phased-array surface coil, the rat brain coil improved signal-to-noise ratio by approximately 72, 61, 78, and 242%, respectively. Effects of the rat brain coil on amplitudes of static field and radiofrequency field uniformity were similar to each of the other coils. In vivo, whole-brain images of an adult male rat were acquired with a T(2)-weighted spin-echo sequence using an isotropic acquisition resolution of 0.25 x 0.25 x 0.25 mm(3) in 60.6 min. Multiplanar images of the in vivo rat brain with identification of anatomic structures are presented. Improvement in signal-to-noise ratio afforded by the rat brain coil may broaden experiments that utilize clinical MR scanners for in vivo image acquisition. 2010 Wiley-Liss, Inc.

A framework for correcting brain retraction based on an eXtended Finite Element Method using a laser range scanner.

PubMed

Li, Ping; Wang, Weiwei; Song, Zhijian; An, Yong; Zhang, Chenxi

2014-07-01

Brain retraction causes great distortion that limits the accuracy of an image-guided neurosurgery system that uses preoperative images. Therefore, brain retraction correction is an important intraoperative clinical application. We used a linear elastic biomechanical model, which deforms based on the eXtended Finite Element Method (XFEM) within a framework for brain retraction correction. In particular, a laser range scanner was introduced to obtain a surface point cloud of the exposed surgical field including retractors inserted into the brain. A brain retraction surface tracking algorithm converted these point clouds into boundary conditions applied to XFEM modeling that drive brain deformation. To test the framework, we performed a brain phantom experiment involving the retraction of tissue. Pairs of the modified Hausdorff distance between Canny edges extracted from model-updated images, pre-retraction, and post-retraction CT images were compared to evaluate the morphological alignment of our framework. Furthermore, the measured displacements of beads embedded in the brain phantom and the predicted ones were compared to evaluate numerical performance. The modified Hausdorff distance of 19 pairs of images decreased from 1.10 to 0.76 mm. The forecast error of 23 stainless steel beads in the phantom was between 0 and 1.73 mm (mean 1.19 mm). The correction accuracy varied between 52.8 and 100 % (mean 81.4 %). The results demonstrate that the brain retraction compensation can be incorporated intraoperatively into the model-updating process in image-guided neurosurgery systems.

MicroCT and microMRI imaging of a prenatal mouse model of increased brain size

NASA Astrophysics Data System (ADS)

López, Elisabeth K. N.; Stock, Stuart R.; Taketo, Makoto M.; Chenn, Anjen; Ravosa, Matthew J.

2008-08-01

There are surprisingly few experimental models of neural growth and cranial integration. This and the dearth of information regarding fetal brain development detract from a mechanistic understanding of cranial integration and its relevance to the patterning of skull form, specifically the role of encephalization on basicranial flexion. To address this shortcoming, our research uses transgenic mice expressing a stabilized form of β-catenin to isolate the effects of relative brain size on craniofacial development. These mice develop highly enlarged brains due to an increase in neural precursors, and differences between transgenic and wild-type mice are predicted to result solely from variation in brain size. Comparisons of wild-type and transgenic mice at several prenatal ages were performed using microCT (Scanco Medical MicroCT 40) and microMRI (Avance 600 WB MR spectrometer). Statistical analyses show that the larger brain of the transgenic mice is associated with a larger neurocranium and an altered basicranial morphology. However, body size and postcranial ossification do not seem to be affected by the transgene. Comparisons of the rate of postcranial and cranial ossification using microCT also point to an unexpected effect of neural growth on skull development: increased fetal encephalization may result in a compensatory decrease in the level of cranial ossification. Therefore, if other life history factors are held constant, the ontogeny of a metabolically costly structure such as a brain may occur at the expense of other cranial structures. These analyses indicate the benefits of a multifactorial approach to cranial integration using a mouse model.

Biocompatible near-infrared fluorescent nanoparticles for macro and microscopic in vivo functional bioimaging

PubMed Central

Chu, Liliang; Wang, Shaowei; Li, Kanghui; Xi, Wang; Zhao, Xinyuan; Qian, Jun

2014-01-01

Near-infrared (NIR) imaging technology has been widely used for biomedical research and applications, since it can achieve deep penetration in biological tissues due to less absorption and scattering of NIR light. In our research, polymer nanoparticles with NIR fluorophores doped were synthesized. The morphology, absorption/emission features and chemical stability of the fluorescent nanoparticles were characterized, separately. NIR fluorescent nanoparticles were then utilized as bright optical probes for macro in vivo imaging of mice, including sentinel lymph node (SLN) mapping, as well as distribution and excretion monitoring of nanoparticles in animal body. Furthermore, we applied the NIR fluorescent nanoparticles in in vivo microscopic bioimaging via a confocal microscope. Under the 635 nm-CW excitation, the blood vessel architecture in the ear and the brain of mice, which were administered with nanoparticles, was visualized very clearly. The imaging depth of our one-photon microscopy, which was assisted with NIR fluorescent nanoprobes, can reach as deep as 500 μm. Our experiments show that NIR fluorescent nanoparticles have great potentials in various deep-tissue imaging applications. PMID:25426331

Evaluation of five diffeomorphic image registration algorithms for mouse brain magnetic resonance microscopy.

PubMed

Fu, Zhenrong; Lin, Lan; Tian, Miao; Wang, Jingxuan; Zhang, Baiwen; Chu, Pingping; Li, Shaowu; Pathan, Muhammad Mohsin; Deng, Yulin; Wu, Shuicai

2017-11-01

The development of genetically engineered mouse models for neuronal diseases and behavioural disorders have generated a growing need for small animal imaging. High-resolution magnetic resonance microscopy (MRM) provides powerful capabilities for noninvasive studies of mouse brains, while avoiding some limits associated with the histological procedures. Quantitative comparison of structural images is a critical step in brain imaging analysis, which highly relies on the performance of image registration techniques. Nowadays, there is a mushrooming growth of human brain registration algorithms, while fine-tuning of those algorithms for mouse brain MRMs is rarely addressed. Because of their topology preservation property and outstanding performance in human studies, diffeomorphic transformations have become popular in computational anatomy. In this study, we specially tuned five diffeomorphic image registration algorithms [DARTEL, geodesic shooting, diffeo-demons, SyN (Greedy-SyN and geodesic-SyN)] for mouse brain MRMs and evaluated their performance using three measures [volume overlap percentage (VOP), residual intensity error (RIE) and surface concordance ratio (SCR)]. Geodesic-SyN performed significantly better than the other methods according to all three different measures. These findings are important for the studies on structural brain changes that may occur in wild-type and transgenic mouse brains. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

PubMed Central

Guo, Bing-bing; Zheng, Xiao-lin; Lu, Zhen-gang; Wang, Xing; Yin, Zheng-qin; Hou, Wen-sheng; Meng, Ming

2015-01-01

Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only “see” pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex (the implant area) is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine (LSVM) as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern. PMID:26692860

Deformation Invariant Attribute Vector for Deformable Registration of Longitudinal Brain MR Images

PubMed Central

Li, Gang; Guo, Lei; Liu, Tianming

2009-01-01

This paper presents a novel approach to define deformation invariant attribute vector (DIAV) for each voxel in 3D brain image for the purpose of anatomic correspondence detection. The DIAV method is validated by using synthesized deformation in 3D brain MRI images. Both theoretic analysis and experimental studies demonstrate that the proposed DIAV is invariant to general nonlinear deformation. Moreover, our experimental results show that the DIAV is able to capture rich anatomic information around the voxels and exhibit strong discriminative ability. The DIAV has been integrated into a deformable registration algorithm for longitudinal brain MR images, and the results on both simulated and real brain images are provided to demonstrate the good performance of the proposed registration algorithm based on matching of DIAVs. PMID:19369031

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

PubMed

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

2017-01-01

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

Fuzzy object models for newborn brain MR image segmentation

NASA Astrophysics Data System (ADS)

Kobashi, Syoji; Udupa, Jayaram K.

2013-03-01

Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

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

PubMed

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

2017-01-01

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

Optical Brain Imaging: A Powerful Tool for Neuroscience.

PubMed

Zhu, Xinpei; Xia, Yanfang; Wang, Xuecen; Si, Ke; Gong, Wei

2017-02-01

As the control center of organisms, the brain remains little understood due to its complexity. Taking advantage of imaging methods, scientists have found an accessible approach to unraveling the mystery of neuroscience. Among these methods, optical imaging techniques are widely used due to their high molecular specificity and single-molecule sensitivity. Here, we overview several optical imaging techniques in neuroscience of recent years, including brain clearing, the micro-optical sectioning tomography system, and deep tissue imaging.

Whole-brain background-suppressed pCASL MRI with 1D-accelerated 3D RARE Stack-Of-Spirals readout

PubMed Central

Vidorreta, Marta; Wang, Ze; Chang, Yulin V.; Wolk, David A.; Fernández-Seara, María A.; Detre, John A.

2017-01-01

Arterial Spin Labeled (ASL) perfusion MRI enables non-invasive, quantitative measurements of tissue perfusion, and has a broad range of applications including brain functional imaging. However, ASL suffers from low signal-to-noise ratio (SNR), limiting image resolution. Acquisitions using 3D readouts are optimal for background-suppression of static signals, but can be SAR intensive and typically suffer from through-plane blurring. In this study, we investigated the use of accelerated 3D readouts to obtain whole-brain, high-SNR ASL perfusion maps and reduce SAR deposition. Parallel imaging was implemented along the partition-encoding direction in a pseudo-continuous ASL sequence with background-suppression and 3D RARE Stack-Of-Spirals readout, and its performance was evaluated in three small cohorts. First, both non-accelerated and two-fold accelerated single-shot versions of the sequence were evaluated in healthy volunteers during a motor-photic task, and the performance was compared in terms of temporal SNR, GM-WM contrast, and statistical significance of the detected activation. Secondly, single-shot 1D-accelerated imaging was compared to a two-shot accelerated version to assess benefits of SNR and spatial resolution for applications in which temporal resolution is not paramount. Third, the efficacy of this approach in clinical populations was assessed by applying the single-shot 1D-accelerated version to a larger cohort of elderly volunteers. Accelerated data demonstrated the ability to detect functional activation at the subject level, including cerebellar activity, without loss in the perfusion signal temporal stability and the statistical power of the activations. The use of acceleration also resulted in increased GM-WM contrast, likely due to reduced through-plane partial volume effects, that were further attenuated with the use of two-shot readouts. In a clinical cohort, image quality remained excellent, and expected effects of age and sex on cerebral blood flow could be detected. The sequence is freely available upon request for academic use and could benefit a broad range of cognitive and clinical neuroscience research. PMID:28837640

Automatic Brain Tumor Detection in T2-weighted Magnetic Resonance Images

NASA Astrophysics Data System (ADS)

Dvořák, P.; Kropatsch, W. G.; Bartušek, K.

2013-10-01

This work focuses on fully automatic detection of brain tumors. The first aim is to determine, whether the image contains a brain with a tumor, and if it does, localize it. The goal of this work is not the exact segmentation of tumors, but the localization of their approximate position. The test database contains 203 T2-weighted images of which 131 are images of healthy brain and the remaining 72 images contain brain with pathological area. The estimation, whether the image shows an afflicted brain and where a pathological area is, is done by multi resolution symmetry analysis. The first goal was tested by five-fold cross-validation technique with 100 repetitions to avoid the result dependency on sample order. This part of the proposed method reaches the true positive rate of 87.52% and the true negative rate of 93.14% for an afflicted brain detection. The evaluation of the second part of the algorithm was carried out by comparing the estimated location to the true tumor location. The detection of the tumor location reaches the rate of 95.83% of correct anomaly detection and the rate 87.5% of correct tumor location.

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

PubMed Central

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

2014-01-01

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

Dissociations between behavioural and functional magnetic resonance imaging-based evaluations of cognitive function after brain injury

PubMed Central

Bardin, Jonathan C.; Fins, Joseph J.; Katz, Douglas I.; Hersh, Jennifer; Heier, Linda A.; Tabelow, Karsten; Dyke, Jonathan P.; Ballon, Douglas J.; Schiff, Nicholas D.

2011-01-01

Functional neuroimaging methods hold promise for the identification of cognitive function and communication capacity in some severely brain-injured patients who may not retain sufficient motor function to demonstrate their abilities. We studied seven severely brain-injured patients and a control group of 14 subjects using a novel hierarchical functional magnetic resonance imaging assessment utilizing mental imagery responses. Whereas the control group showed consistent and accurate (for communication) blood-oxygen-level-dependent responses without exception, the brain-injured subjects showed a wide variation in the correlation of blood-oxygen-level-dependent responses and overt behavioural responses. Specifically, the brain-injured subjects dissociated bedside and functional magnetic resonance imaging-based command following and communication capabilities. These observations reveal significant challenges in developing validated functional magnetic resonance imaging-based methods for clinical use and raise interesting questions about underlying brain function assayed using these methods in brain-injured subjects. PMID:21354974

Development of a High Angular Resolution Diffusion Imaging Human Brain Template

PubMed Central

Varentsova, Anna; Zhang, Shengwei; Arfanakis, Konstantinos

2014-01-01

Brain diffusion templates contain rich information about the microstructure of the brain, and are used as references in spatial normalization or in the development of brain atlases. The accuracy of diffusion templates constructed based on the diffusion tensor (DT) model is limited in regions with complex neuronal micro-architecture. High angular resolution diffusion imaging (HARDI) overcomes limitations of the DT model and is capable of resolving intravoxel heterogeneity. However, when HARDI is combined with multiple-shot sequences to minimize image artifacts, the scan time becomes inappropriate for human brain imaging. In this work, an artifact-free HARDI template of the human brain was developed from low angular resolution multiple-shot diffusion data. The resulting HARDI template was produced in ICBM-152 space based on Turboprop diffusion data, was shown to resolve complex neuronal micro-architecture in regions with intravoxel heterogeneity, and contained fiber orientation information consistent with known human brain anatomy. PMID:24440528

Generating Text from Functional Brain Images

PubMed Central

Pereira, Francisco; Detre, Greg; Botvinick, Matthew

2011-01-01

Recent work has shown that it is possible to take brain images acquired during viewing of a scene and reconstruct an approximation of the scene from those images. Here we show that it is also possible to generate text about the mental content reflected in brain images. We began with images collected as participants read names of concrete items (e.g., “Apartment’’) while also seeing line drawings of the item named. We built a model of the mental semantic representation of concrete concepts from text data and learned to map aspects of such representation to patterns of activation in the corresponding brain image. In order to validate this mapping, without accessing information about the items viewed for left-out individual brain images, we were able to generate from each one a collection of semantically pertinent words (e.g., “door,” “window” for “Apartment’’). Furthermore, we show that the ability to generate such words allows us to perform a classification task and thus validate our method quantitatively. PMID:21927602

Regional brain injury on conventional and diffusion weighted MRI is associated with outcome after pediatric cardiac arrest.

PubMed

Fink, Ericka L; Panigrahy, A; Clark, R S B; Fitz, C R; Landsittel, D; Kochanek, P M; Zuccoli, G

2013-08-01

To assess regional brain injury on magnetic resonance imaging (MRI) after pediatric cardiac arrest (CA) and to associate regional injury with patient outcome and effects of hypothermia therapy for neuroprotection. We performed a retrospective chart review with prospective imaging analysis. Children between 1 week and 17 years of age who had a brain MRI in the first 2 weeks after CA without other acute brain injury between 2002 and 2008 were included. Brain MRI (1.5 T General Electric, Milwaukee, WI, USA) images were analyzed by 2 blinded neuroradiologists with adjudication; images were visually graded. Brain lobes, basal ganglia, thalamus, brain stem, and cerebellum were analyzed using T1, T2, and diffusion-weighted images (DWI). We examined 28 subjects with median age 1.9 years (IQR 0.4-13.0) and 19 (68 %) males. Increased intensity on T2 in the basal ganglia and restricted diffusion in the brain lobes were associated with unfavorable outcome (all P < 0.05). Therapeutic hypothermia had no effect on regional brain injury. Repeat brain MRI was infrequently performed but demonstrated evolution of lesions. Children with lesions in the basal ganglia on conventional MRI and brain lobes on DWI within the first 2 weeks after CA represent a group with increased risk of poor outcome. These findings may be important for developing neuroprotective strategies based on regional brain injury and for evaluating response to therapy in interventional clinical trials.

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

PubMed

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

2017-10-01

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

If the skull fits: magnetic resonance imaging and microcomputed tomography for combined analysis of brain and skull phenotypes in the mouse

PubMed Central

Blank, Marissa C.; Roman, Brian B.; Henkelman, R. Mark; Millen, Kathleen J.

2012-01-01

The mammalian brain and skull develop concurrently in a coordinated manner, consistently producing a brain and skull that fit tightly together. It is common that abnormalities in one are associated with related abnormalities in the other. However, this is not always the case. A complete characterization of the relationship between brain and skull phenotypes is necessary to understand the mechanisms that cause them to be coordinated or divergent and to provide perspective on the potential diagnostic or prognostic significance of brain and skull phenotypes. We demonstrate the combined use of magnetic resonance imaging and microcomputed tomography for analysis of brain and skull phenotypes in the mouse. Co-registration of brain and skull images allows comparison of the relationship between phenotypes in the brain and those in the skull. We observe a close fit between the brain and skull of two genetic mouse models that both show abnormal brain and skull phenotypes. Application of these three-dimensional image analyses in a broader range of mouse mutants will provide a map of the relationships between brain and skull phenotypes generally and allow characterization of patterns of similarities and differences. PMID:22947655

New insights into action-perception coupling.

PubMed

Feldman, Anatol G

2009-03-01

According to a view that has dominated the field for over a century, the brain programs muscle commands and uses a copy of these commands [efference copy (EC)] to adjust not only resulting motor action but also ongoing perception. This view was helpful in formulating several classical problems of action and perception: (1) the posture-movement problem of how movements away from a stable posture can be made without evoking resistance of posture-stabilizing mechanisms resulting from intrinsic muscle and reflex properties; (2) the problem of kinesthesia or why our sense of limb position is good despite ambiguous positional information delivered by proprioceptive and cutaneous signals; (3) the problem of visual space constancy or why the world is perceived as stable while its retinal image shifts following changes in gaze. On closer inspection, the EC theory actually does not solve these problems in a physiologically feasible way. Here solutions to these problems are proposed based on the advanced formulation of the equilibrium-point hypothesis that suggests that action and perception are accomplished in a common spatial frame of reference selected by the brain from a set of available frames. Experimental data suggest that the brain is also able to translate or/and rotate the selected frame of reference by modifying its major attributes-the origin, metrics and orientation-and thus substantially influence action and perception. Because of this ability, such frames are called physical to distinguish them from symbolic or mathematical frames that are used to describe system behavior without influencing this behavior. Experimental data also imply that once a frame of reference is chosen, its attributes are modified in a feedforward way, thus enabling the brain to act in an anticipatory and predictive manner. This approach is extended to sense of effort, kinesthetic illusions, phantom limb and phantom body phenomena. It also addresses the question of why retinal images of objects are sensed as objects located in the external, physical world, rather than in internal representations of the brain.

Scalable Joint Segmentation and Registration Framework for Infant Brain Images.

PubMed

Dong, Pei; Wang, Li; Lin, Weili; Shen, Dinggang; Wu, Guorong

2017-03-15

The first year of life is the most dynamic and perhaps the most critical phase of postnatal brain development. The ability to accurately measure structure changes is critical in early brain development study, which highly relies on the performances of image segmentation and registration techniques. However, either infant image segmentation or registration, if deployed independently, encounters much more challenges than segmentation/registration of adult brains due to dynamic appearance change with rapid brain development. In fact, image segmentation and registration of infant images can assists each other to overcome the above challenges by using the growth trajectories (i.e., temporal correspondences) learned from a large set of training subjects with complete longitudinal data. Specifically, a one-year-old image with ground-truth tissue segmentation can be first set as the reference domain. Then, to register the infant image of a new subject at earlier age, we can estimate its tissue probability maps, i.e., with sparse patch-based multi-atlas label fusion technique, where only the training images at the respective age are considered as atlases since they have similar image appearance. Next, these probability maps can be fused as a good initialization to guide the level set segmentation. Thus, image registration between the new infant image and the reference image is free of difficulty of appearance changes, by establishing correspondences upon the reasonably segmented images. Importantly, the segmentation of new infant image can be further enhanced by propagating the much more reliable label fusion heuristics at the reference domain to the corresponding location of the new infant image via the learned growth trajectories, which brings image segmentation and registration to assist each other. It is worth noting that our joint segmentation and registration framework is also flexible to handle the registration of any two infant images even with significant age gap in the first year of life, by linking their joint segmentation and registration through the reference domain. Thus, our proposed joint segmentation and registration method is scalable to various registration tasks in early brain development studies. Promising segmentation and registration results have been achieved for infant brain MR images aged from 2-week-old to 1-year-old, indicating the applicability of our method in early brain development study.

Correspondence of the brain's functional architecture during activation and rest

PubMed Central

Smith, Stephen M.; Fox, Peter T.; Miller, Karla L.; Glahn, David C.; Fox, P. Mickle; Mackay, Clare E.; Filippini, Nicola; Watkins, Kate E.; Toro, Roberto; Laird, Angela R.; Beckmann, Christian F.

2009-01-01

Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is “at rest.” In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically “active” even when at “rest.” PMID:19620724

Magnetic resonance imaging of the pediatric brain

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

Salamon, G.; Raynaud, C.; Regis, J.

1990-01-01

The atlas presents sequences of MRI sections parallel to the orbito-meatal plane in children from birth through the age of sixteen years. Each child was studied horizontally and sagitally and three-dimensional brain images were reconstructed to facilitate accurate identification of sulci and gyri. The images show crucial aspects of brain development such as the constancy of the brain stem and primitive brain from birth onward; the development of the telencephalon, characterized by deepening of sulci and growth of the cerebral cortex surface; and the different stages of white matter myelinization.

Imaging of Traumatic Brain Injury.

PubMed

Bodanapally, Uttam K; Sours, Chandler; Zhuo, Jiachen; Shanmuganathan, Kathirkamanathan

2015-07-01

Imaging plays an important role in the management of patients with traumatic brain injury (TBI). Computed tomography (CT) is the first-line imaging technique allowing rapid detection of primary structural brain lesions that require surgical intervention. CT also detects various deleterious secondary insults allowing early medical and surgical management. Serial imaging is critical to identifying secondary injuries. MR imaging is indicated in patients with acute TBI when CT fails to explain neurologic findings. However, MR imaging is superior in patients with subacute and chronic TBI and also predicts neurocognitive outcome. Copyright © 2015 Elsevier Inc. All rights reserved.

Delivery of Nano-Tethered Therapies to Brain Metastases of Primary Breast Cancer Using a Cellular Trojan Horse

DTIC Science & Technology

2015-10-01

tomography images. The CT image densities in Hounsfield units (HU) of the brain were translated into corresponding optical properties (absorption...derived the Hounsfield units and optical properties of brain tissues such as white/gray matter. 13-15 The segmentation software generated an optical map...treatment protocol. Head CT image densities (in Hounsfield Units /HU) are segmented and translated into optical properties of the brain tissue

Post-sampling release of free fatty acids - effects of heat stabilization and methods of euthanasia.

PubMed

Jernerén, Fredrik; Söderquist, Marcus; Karlsson, Oskar

2015-01-01

The field of lipid research has made progress and it is now possible to study the lipidome of cells and organelles. A basic requirement of a successful lipid study is adequate pre-analytical sample handling, as some lipids can be unstable and postmortem changes can cause substantial accumulation of free fatty acids (FFAs). The aim of the present study was to investigate the effects of conductive heat stabilization and euthanasia methods on FFA levels in the rat brain and liver using liquid chromatography tandem mass spectrometry. The analysis of brain homogenates clearly demonstrated phospholipase activity and time-dependent post-sampling changes in the lipid pool of snap frozen non-stabilized tissue. There was a significant increase in FFAs already at 2min, which continued over time. Heat stabilization was shown to be an efficient method to reduce phospholipase activity and ex vivo lipolysis. Post-sampling effects due to tissue thawing and sample preparation induced a massive release of FFAs (up to 3700%) from non-stabilized liver and brain tissues compared to heat stabilized tissue. Furthermore, the choice of euthanasia method significantly influenced the levels of FFAs in the brain. The FFAs were decreased by 15-44% in the group of animals euthanized by pentobarbital injection compared with CO2 inhalation or decapitation. Our results highlight the importance of considering euthanasia methods and pre-analytical treatment in lipid analysis, factors which may otherwise interfere with the outcome of the experiments. Copyright © 2014 Elsevier Inc. All rights reserved.

A Pathological Brain Detection System based on Extreme Learning Machine Optimized by Bat Algorithm.

PubMed

Lu, Siyuan; Qiu, Xin; Shi, Jianping; Li, Na; Lu, Zhi-Hai; Chen, Peng; Yang, Meng-Meng; Liu, Fang-Yuan; Jia, Wen-Juan; Zhang, Yudong

2017-01-01

It is beneficial to classify brain images as healthy or pathological automatically, because 3D brain images can generate so much information which is time consuming and tedious for manual analysis. Among various 3D brain imaging techniques, magnetic resonance (MR) imaging is the most suitable for brain, and it is now widely applied in hospitals, because it is helpful in the four ways of diagnosis, prognosis, pre-surgical, and postsurgical procedures. There are automatic detection methods; however they suffer from low accuracy. Therefore, we proposed a novel approach which employed 2D discrete wavelet transform (DWT), and calculated the entropies of the subbands as features. Then, a bat algorithm optimized extreme learning machine (BA-ELM) was trained to identify pathological brains from healthy controls. A 10x10-fold cross validation was performed to evaluate the out-of-sample performance. The method achieved a sensitivity of 99.04%, a specificity of 93.89%, and an overall accuracy of 98.33% over 132 MR brain images. The experimental results suggest that the proposed approach is accurate and robust in pathological brain detection. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Mapping fetal brain development in utero using magnetic resonance imaging: the Big Bang of brain mapping.

PubMed

Studholme, Colin

2011-08-15

The development of tools to construct and investigate probabilistic maps of the adult human brain from magnetic resonance imaging (MRI) has led to advances in both basic neuroscience and clinical diagnosis. These tools are increasingly being applied to brain development in adolescence and childhood, and even to neonatal and premature neonatal imaging. Even earlier in development, parallel advances in clinical fetal MRI have led to its growing use as a tool in challenging medical conditions. This has motivated new engineering developments encompassing optimal fast MRI scans and techniques derived from computer vision, the combination of which allows full 3D imaging of the moving fetal brain in utero without sedation. These promise to provide a new and unprecedented window into early human brain growth. This article reviews the developments that have led us to this point, examines the current state of the art in the fields of fast fetal imaging and motion correction, and describes the tools to analyze dynamically changing fetal brain structure. New methods to deal with developmental tissue segmentation and the construction of spatiotemporal atlases are examined, together with techniques to map fetal brain growth patterns.

Advances in neuroimaging of traumatic brain injury and posttraumatic stress disorder

PubMed Central

Van Boven, Robert W.; Harrington, Greg S.; Hackney, David B.; Ebel, Andreas; Gauger, Grant; Bremner, J. Douglas; D’Esposito, Mark; Detre, John A.; Haacke, E. Mark; Jack, Clifford R.; Jagust, William J.; Le Bihan, Denis; Mathis, Chester A.; Mueller, Susanne; Mukherjee, Pratik; Schuff, Norbert; Chen, Anthony; Weiner, Michael W.

2011-01-01

Improved diagnosis and treatment of traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are needed for our military and veterans, their families, and society at large. Advances in brain imaging offer important biomarkers of structural, functional, and metabolic information concerning the brain. This article reviews the application of various imaging techniques to the clinical problems of TBI and PTSD. For TBI, we focus on findings and advances in neuroimaging that hold promise for better detection, characterization, and monitoring of objective brain changes in symptomatic patients with combat-related, closed-head brain injuries not readily apparent by standard computed tomography or conventional magnetic resonance imaging techniques. PMID:20104401

Seeing Is Believing: The Effect of Brain Images on Judgments of Scientific Reasoning

ERIC Educational Resources Information Center

McCabe, David P.; Castel, Alan D.

2008-01-01

Brain images are believed to have a particularly persuasive influence on the public perception of research on cognition. Three experiments are reported showing that presenting brain images with articles summarizing cognitive neuroscience research resulted in higher ratings of scientific reasoning for arguments made in those articles, as compared…

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Precursors to radiopharmaceutical agents for tissue imaging

DOEpatents

Srivastava, Prem C.; Knapp, Jr., Furn F.

1988-01-01

A class of radiolabeled compounds to be used in tissue imaging that exhibits rapid brain uptake, good brain:blood radioactivity ratios, and long retention times. The imaging agents are more specifically radioiodinated aromatic amines attached to dihydropyridine carriers, that exhibit heart as well as brain specificity. In addition to the radiolabeled compounds, classes of compounds are also described that are used as precursors and intermediates in the preparation of the imaging agents.

Pediatric Major Head Injury: Not a Minor Problem.

PubMed

Leetch, Aaron N; Wilson, Bryan

2018-05-01

Traumatic brain injury is a highly prevalent and devastating cause of morbidity and mortality in children. A rapid, stepwise approach to the traumatized child should proceed, addressing life-threatening problems first. Management focuses on preventing secondary injury from physiologic extremes such as hypoxemia, hypotension, prolonged hyperventilation, temperature extremes, and rapid changes in cerebral blood flow. Initial Glasgow Coma Score, hyperglycemia, and imaging are often prognostic of outcome. Surgically amenable lesions should be evacuated promptly. Reduction of intracranial pressure through hyperosmolar therapy, decompressive craniotomy, and seizure prophylaxis may be considered after stabilization. Nonaccidental trauma should be considered when evaluating pediatric trauma patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Induction and imaging of photothrombotic stroke in conscious and freely moving rats

NASA Astrophysics Data System (ADS)

Lu, Hongyang; Li, Yao; Yuan, Lu; Li, Hangdao; Lu, Xiaodan; Tong, Shanbao

2014-09-01

In experimental stroke research, anesthesia is common and serves as a major reason for translational failure. Real-time cerebral blood flow (CBF) monitoring during stroke onset can provide important information for the prediction of brain injury; however, this is difficult to achieve in clinical practice due to various technical problems. We created a photothrombotic focal ischemic stroke model utilizing our self-developed miniature headstage in conscious and freely moving rats. In this model, a high spatiotemporal resolution imager using laser speckle contrast imaging technology was integrated to acquire real-time two-dimensional CBF information during thrombosis. The feasibility, stability, and reliability of the system were tested in terms of CBF, behavior, and T2-weighted magnetic resonance imaging (MRI) findings. After completion of occlusion, the CBF in the targeted cortex of the stroke group was reduced to 16±9% of the baseline value. The mean infarct volume measured by MRI 24 h postmodeling was 77±11 mm3 and correlated well with CBF (R2=0.74). This rodent model of focal cerebral ischemia and real-time blood flow imaging opens the possibility of performing various fundamental and translational studies on stroke without the influence of anesthetics.

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Gupta, Anjali; Pahuja, Gunjan

2017-08-01

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

Imaging fast electrical activity in the brain with electrical impedance tomography

PubMed Central

Aristovich, Kirill Y.; Packham, Brett C.; Koo, Hwan; Santos, Gustavo Sato dos; McEvoy, Andy; Holder, David S.

2016-01-01

Imaging of neuronal depolarization in the brain is a major goal in neuroscience, but no technique currently exists that could image neural activity over milliseconds throughout the whole brain. Electrical impedance tomography (EIT) is an emerging medical imaging technique which can produce tomographic images of impedance changes with non-invasive surface electrodes. We report EIT imaging of impedance changes in rat somatosensory cerebral cortex with a resolution of 2 ms and < 200 μm during evoked potentials using epicortical arrays with 30 electrodes. Images were validated with local field potential recordings and current source-sink density analysis. Our results demonstrate that EIT can image neural activity in a volume 7 × 5 × 2 mm in somatosensory cerebral cortex with reduced invasiveness, greater resolution and imaging volume than other methods. Modeling indicates similar resolutions are feasible throughout the entire brain so this technique, uniquely, has the potential to image functional connectivity of cortical and subcortical structures. PMID:26348559

Poster — Thur Eve — 15: Improvements in the stability of the tomotherapy imaging beam

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

Belec, J

2014-08-15

Use of helical TomoTherapy based MVCT imaging for adaptive planning requires the image values (HU) to remain stable over the course of treatment. In the past, the image value stability was suboptimal, which required frequent change to the image value to density calibration curve to avoid dose errors on the order of 2–4%. The stability of the image values at our center was recently improved by stabilizing the dose rate of the machine (dose control servo) and performing daily MVCT calibration corrections. In this work, we quantify the stability of the image values over treatment time by comparing patient treatmentmore » image density derived using MVCT and KVCT. The analysis includes 1) MVCT - KVCT density difference histogram, 2) MVCT vs KVCT density spectrum, 3) multiple average profile density comparison and 4) density difference in homogeneous locations. Over two months, the imaging beam stability was compromised several times due to a combination of target wobbling, spectral calibration, target change and magnetron issues. The stability of the image values were analyzed over the same period. Results show that the impact on the patient dose calculation is 0.7% +− 0.6%.« less

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.

The ontogenesis of the forebrain commissures and the determination of brain asymmetries.

PubMed

Lent, R; Schmidt, S L

1993-02-01

We have reviewed the organization and development of the interhemispheric projections through the forebrain commissures, especially those of the CC, in connection with the development of brain asymmetries. Analyzing the available data, we conclude that the developing CC plays an important role in the ontogenesis of brain asymmetries. We have extended a previous hypothesis that the rodent CC may exert a stabilizing effect over the unstable populational asymmetries of cortical size and shape, and that it participates in the developmental stabilization of lateralized motor behaviors.

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

PubMed Central

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

2013-01-01

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

Chapter 18: the origins of functional brain imaging in humans.

PubMed

Raichle, Marcus E

2010-01-01

Functional brain imaging in humans as we presently know it began when the experimental strategies of cognitive psychology were combined with modern brain imaging techniques, first positron emission tomography (PET) and then functional magnetic resonance imaging (fMRI), to examine how brain function supports mental activities. This marriage of disciplines and techniques galvanized the field of cognitive neuroscience, which has rapidly expanded to include a broad range of the social sciences as well as basic scientists interested in the neurophysiology, cell biology and genetics of the imaging signals. While much of this work has transpired over the past couple of decades, its roots can be traced back more than a century.

Application of an enhanced fuzzy algorithm for MR brain tumor image segmentation

NASA Astrophysics Data System (ADS)

Hemanth, D. Jude; Vijila, C. Kezi Selva; Anitha, J.

2010-02-01

Image segmentation is one of the significant digital image processing techniques commonly used in the medical field. One of the specific applications is tumor detection in abnormal Magnetic Resonance (MR) brain images. Fuzzy approaches are widely preferred for tumor segmentation which generally yields superior results in terms of accuracy. But most of the fuzzy algorithms suffer from the drawback of slow convergence rate which makes the system practically non-feasible. In this work, the application of modified Fuzzy C-means (FCM) algorithm to tackle the convergence problem is explored in the context of brain image segmentation. This modified FCM algorithm employs the concept of quantization to improve the convergence rate besides yielding excellent segmentation efficiency. This algorithm is experimented on real time abnormal MR brain images collected from the radiologists. A comprehensive feature vector is extracted from these images and used for the segmentation technique. An extensive feature selection process is performed which reduces the convergence time period and improve the segmentation efficiency. After segmentation, the tumor portion is extracted from the segmented image. Comparative analysis in terms of segmentation efficiency and convergence rate is performed between the conventional FCM and the modified FCM. Experimental results show superior results for the modified FCM algorithm in terms of the performance measures. Thus, this work highlights the application of the modified algorithm for brain tumor detection in abnormal MR brain images.

Tissue Probability Map Constrained 4-D Clustering Algorithm for Increased Accuracy and Robustness in Serial MR Brain Image Segmentation

PubMed Central

Xue, Zhong; Shen, Dinggang; Li, Hai; Wong, Stephen

2010-01-01

The traditional fuzzy clustering algorithm and its extensions have been successfully applied in medical image segmentation. However, because of the variability of tissues and anatomical structures, the clustering results might be biased by the tissue population and intensity differences. For example, clustering-based algorithms tend to over-segment white matter tissues of MR brain images. To solve this problem, we introduce a tissue probability map constrained clustering algorithm and apply it to serial MR brain image segmentation, i.e., a series of 3-D MR brain images of the same subject at different time points. Using the new serial image segmentation algorithm in the framework of the CLASSIC framework, which iteratively segments the images and estimates the longitudinal deformations, we improved both accuracy and robustness for serial image computing, and at the mean time produced longitudinally consistent segmentation and stable measures. In the algorithm, the tissue probability maps consist of both the population-based and subject-specific segmentation priors. Experimental study using both simulated longitudinal MR brain data and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data confirmed that using both priors more accurate and robust segmentation results can be obtained. The proposed algorithm can be applied in longitudinal follow up studies of MR brain imaging with subtle morphological changes for neurological disorders. PMID:26566399

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.

Oscillations contribute to memory consolidation by changing criticality and stability in the brain

NASA Astrophysics Data System (ADS)

Wu, Jiaxing; Skilling, Quinton; Ognjanovski, Nicolette; Aton, Sara; Zochowski, Michal

Oscillations are a universal feature of every level of brain dynamics and have been shown to contribute to many brain functions. To investigate the fundamental mechanism underpinning oscillatory activity, the properties of heterogeneous networks are compared in situations with and without oscillations. Our results show that both network criticality and stability are changed in the presence of oscillations. Criticality describes the network state of neuronal avalanche, a cascade of bursts of action potential firing in neural network. Stability measures how stable the spike timing relationship between neuron pairs is over time. Using a detailed spiking model, we found that the branching parameter σ changes relative to oscillation and structural network properties, corresponding to transmission among different critical states. Also, analysis of functional network structures shows that the oscillation helps to stabilize neuronal representation of memory. Further, quantitatively similar results are observed in biological data recorded in vivo. In summary, we have observed that, by regulating the neuronal firing pattern, oscillations affect both criticality and stability properties of the network, and thus contribute to memory formation.

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.

A system architecture for sharing de-identified, research-ready brain scans and health information across clinical imaging centers.

PubMed

Chervenak, Ann L; van Erp, Theo G M; Kesselman, Carl; D'Arcy, Mike; Sobell, Janet; Keator, David; Dahm, Lisa; Murry, Jim; Law, Meng; Hasso, Anton; Ames, Joseph; Macciardi, Fabio; Potkin, Steven G

2012-01-01

Progress in our understanding of brain disorders increasingly relies on the costly collection of large standardized brain magnetic resonance imaging (MRI) data sets. Moreover, the clinical interpretation of brain scans benefits from compare and contrast analyses of scans from patients with similar, and sometimes rare, demographic, diagnostic, and treatment status. A solution to both needs is to acquire standardized, research-ready clinical brain scans and to build the information technology infrastructure to share such scans, along with other pertinent information, across hospitals. This paper describes the design, deployment, and operation of a federated imaging system that captures and shares standardized, de-identified clinical brain images in a federation across multiple institutions. In addition to describing innovative aspects of the system architecture and our initial testing of the deployed infrastructure, we also describe the Standardized Imaging Protocol (SIP) developed for the project and our interactions with the Institutional Review Board (IRB) regarding handling patient data in the federated environment.

A System Architecture for Sharing De-Identified, Research-Ready Brain Scans and Health Information Across Clinical Imaging Centers

PubMed Central

Chervenak, Ann L.; van Erp, Theo G.M.; Kesselman, Carl; D’Arcy, Mike; Sobell, Janet; Keator, David; Dahm, Lisa; Murry, Jim; Law, Meng; Hasso, Anton; Ames, Joseph; Macciardi, Fabio; Potkin, Steven G.

2015-01-01

Progress in our understanding of brain disorders increasingly relies on the costly collection of large standardized brain magnetic resonance imaging (MRI) data sets. Moreover, the clinical interpretation of brain scans benefits from compare and contrast analyses of scans from patients with similar, and sometimes rare, demographic, diagnostic, and treatment status. A solution to both needs is to acquire standardized, research-ready clinical brain scans and to build the information technology infrastructure to share such scans, along with other pertinent information, across hospitals. This paper describes the design, deployment, and operation of a federated imaging system that captures and shares standardized, de-identified clinical brain images in a federation across multiple institutions. In addition to describing innovative aspects of the system architecture and our initial testing of the deployed infrastructure, we also describe the Standardized Imaging Protocol (SIP) developed for the project and our interactions with the Institutional Review Board (IRB) regarding handling patient data in the federated environment. PMID:22941984

A radiologic correlation with the basic functional neuroanatomy of the brain.

PubMed

Bilicka, Z; Liska, M; Bluska, P; Bilicky, J

2014-01-01

Primary cortical areas for motor, sensory and sensitive functions are localized in certain areas of the brain cortex. In clinical practice, cross sectional imaging (computer tomography and magnetic resonance) is wildy used for diagnostics purpose, treatment planning and follow up of the patients. Accurate orientation in brain structures is necessary for the evaluation of radiological images. There are numerable landmark signs, which can be used for precise identification of important brain structures. In this review article, the mostly used anatomical landmarks are described and shown on the cross sectional images (magnetic resonance imaging) (Fig. 14, Ref. 25).

Linking brain, mind and behavior.

PubMed

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

2009-08-01

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

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.

Identification of autism spectrum disorder using deep learning and the ABIDE dataset.

PubMed

Heinsfeld, Anibal Sólon; Franco, Alexandre Rosa; Craddock, R Cameron; Buchweitz, Augusto; Meneguzzi, Felipe

2018-01-01

The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the patients brain activation patterns. We investigated ASD patients brain imaging data from a world-wide multi-site database known as ABIDE (Autism Brain Imaging Data Exchange). ASD is a brain-based disorder characterized by social deficits and repetitive behaviors. According to recent Centers for Disease Control data, ASD affects one in 68 children in the United States. We investigated patterns of functional connectivity that objectively identify ASD participants from functional brain imaging data, and attempted to unveil the neural patterns that emerged from the classification. The results improved the state-of-the-art by achieving 70% accuracy in identification of ASD versus control patients in the dataset. The patterns that emerged from the classification show an anticorrelation of brain function between anterior and posterior areas of the brain; the anticorrelation corroborates current empirical evidence of anterior-posterior disruption in brain connectivity in ASD. We present the results and identify the areas of the brain that contributed most to differentiating ASD from typically developing controls as per our deep learning model.

Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognitive Functions

DTIC Science & Technology

2017-05-14

AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a.  CONTRACT NUMBER 5b.  GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Brain stress level measurement (non-invasively) in quantitative term is very helpful to correlate with various

Non invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions

DTIC Science & Technology

2017-05-14

AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a.  CONTRACT NUMBER 5b.  GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Brain stress level measurement (non-invasively) in quantitative term is very helpful to correlate with various

Automatic CT Brain Image Segmentation Using Two Level Multiresolution Mixture Model of EM

NASA Astrophysics Data System (ADS)

Jiji, G. Wiselin; Dehmeshki, Jamshid

2014-04-01

Tissue classification in computed tomography (CT) brain images is an important issue in the analysis of several brain dementias. A combination of different approaches for the segmentation of brain images is presented in this paper. A multi resolution algorithm is proposed along with scaled versions using Gaussian filter and wavelet analysis that extends expectation maximization (EM) algorithm. It is found that it is less sensitive to noise and got more accurate image segmentation than traditional EM. Moreover the algorithm has been applied on 20 sets of CT of the human brain and compared with other works. The segmentation results show the advantages of the proposed work have achieved more promising results and the results have been tested with Doctors.

Improved tumor identification using dual tracer molecular imaging in fluorescence guided brain surgery

NASA Astrophysics Data System (ADS)

Xu, Xiaochun; Torres, Veronica; Straus, David; Brey, Eric M.; Byrne, Richard W.; Tichauer, Kenneth M.

2015-03-01

Brain tumors represent a leading cause of cancer death for people under the age of 40 and the probability complete surgical resection of brain tumors remains low owing to the invasive nature of these tumors and the consequences of damaging healthy brain tissue. Molecular imaging is an emerging approach that has the potential to improve the ability for surgeons to correctly discriminate between healthy and cancerous tissue; however, conventional molecular imaging approaches in brain suffer from significant background signal in healthy tissue or an inability target more invasive sections of the tumor. This work presents initial studies investigating the ability of novel dual-tracer molecular imaging strategies to be used to overcome the major limitations of conventional "single-tracer" molecular imaging. The approach is evaluated in simulations and in an in vivo mice study with animals inoculated orthotopically using fluorescent human glioma cells. An epidermal growth factor receptor (EGFR) targeted Affibody-fluorescent marker was employed as a targeted imaging agent, and the suitability of various FDA approved untargeted fluorescent tracers (e.g. fluorescein & indocyanine green) were evaluated in terms of their ability to account for nonspecific uptake and retention of the targeted imaging agent. Signal-to-background ratio was used to measure and compare the amount of reporter in the tissue between targeted and untargeted tracer. The initial findings suggest that FDA-approved fluorescent imaging agents are ill-suited to act as untargeted imaging agents for dual-tracer fluorescent guided brain surgery as they suffer from poor delivery to the healthy brain tissue and therefore cannot be used to identify nonspecific vs. specific uptake of the targeted imaging agent where current surgery is most limited.

Potential application of a handheld confocal endomicroscope imaging system using a variety of fluorophores in experimental gliomas and normal brain.

PubMed

Martirosyan, Nikolay L; Georges, Joseph; Eschbacher, Jennifer M; Cavalcanti, Daniel D; Elhadi, Ali M; Abdelwahab, Mohammed G; Scheck, Adrienne C; Nakaji, Peter; Spetzler, Robert F; Preul, Mark C

2014-02-01

The authors sought to assess the feasibility of a handheld visible-wavelength confocal endomicroscope imaging system (Optiscan 5.1, Optiscan Pty., Ltd.) using a variety of rapid-acting fluorophores to provide histological information on gliomas, tumor margins, and normal brain in animal models. Mice (n = 25) implanted with GL261 cells were used to image fluorescein sodium (FNa), 5-aminolevulinic acid (5-ALA), acridine orange (AO), acriflavine (AF), and cresyl violet (CV). A U251 glioma xenograft model in rats (n = 5) was used to image sulforhodamine 101 (SR101). A swine (n = 3) model with AO was used to identify confocal features of normal brain. Images of normal brain, obvious tumor, and peritumoral zones were collected using the handheld confocal endomicroscope. Histological samples were acquired through biopsies from matched imaging areas. Samples were visualized with a benchtop confocal microscope. Histopathological features in corresponding confocal images and photomicrographs of H & E-stained tissues were reviewed. Fluorescence induced by FNa, 5-ALA, AO, AF, CV, and SR101 and detected with the confocal endomicroscope allowed interpretation of histological features. Confocal endomicroscopy revealed satellite tumor cells within peritumoral tissue, a definitive tumor border, and striking fluorescent cellular and subcellular structures. Fluorescence in various tumor regions correlated with standard histology and known tissue architecture. Characteristic features of different areas of normal brain were identified as well. Confocal endomicroscopy provided rapid histological information precisely related to the site of microscopic imaging with imaging characteristics of cells related to the unique labeling features of the fluorophores. Although experimental with further clinical trial validation required, these data suggest that intraoperative confocal imaging can help to distinguish normal brain from tumor and tumor margin and may have application in improving intraoperative decisions during resection of brain tumors.

A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

PubMed

Zhao, Xiaomei; Wu, Yihong; Song, Guidong; Li, Zhenye; Zhang, Yazhuo; Fan, Yong

2018-01-01

Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans. Copyright © 2017 Elsevier B.V. All rights reserved.

The Potential of Using Brain Images for Authentication

PubMed Central

Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition. PMID:25126604

The potential of using brain images for authentication.

PubMed

Chen, Fanglin; Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Evidence for early neurodegeneration in the cervical cord of patients with primary progressive multiple sclerosis.

PubMed

Abdel-Aziz, Khaled; Schneider, Torben; Solanky, Bhavana S; Yiannakas, Marios C; Altmann, Dan R; Wheeler-Kingshott, Claudia A M; Peters, Amy L; Day, Brian L; Thompson, Alan J; Ciccarelli, Olga

2015-06-01

Spinal neurodegeneration is an important determinant of disability progression in patients with primary progressive multiple sclerosis. Advanced imaging techniques, such as single-voxel (1)H-magnetic resonance spectroscopy and q-space imaging, have increased pathological specificity for neurodegeneration, but are challenging to implement in the spinal cord and have yet to be applied in early primary progressive multiple sclerosis. By combining these imaging techniques with new clinical measures, which reflect spinal cord pathology more closely than conventional clinical tests, we explored the potential for spinal magnetic resonance spectroscopy and q-space imaging to detect early spinal neurodegeneration that may be responsible for clinical disability. Data from 21 patients with primary progressive multiple sclerosis within 6 years of disease onset, and 24 control subjects were analysed. Patients were clinically assessed on grip strength, vibration perception thresholds and postural stability, in addition to the Expanded Disability Status Scale, Nine Hole Peg Test, Timed 25-Foot Walk Test, Multiple Sclerosis Walking Scale-12, and Modified Ashworth Scale. All subjects underwent magnetic resonance spectroscopy and q-space imaging of the cervical cord and conventional brain and spinal magnetic resonance imaging at 3 T. Multivariate analyses and multiple regression models were used to assess the differences in imaging measures between groups and the relationship between magnetic resonance imaging measures and clinical scores, correcting for age, gender, spinal cord cross-sectional area, brain T2 lesion volume, and brain white matter and grey matter volume fractions. Although patients did not show significant cord atrophy when compared with healthy controls, they had significantly lower total N-acetyl-aspartate (mean 4.01 versus 5.31 mmol/l, P = 0.020) and glutamate-glutamine (mean 4.65 versus 5.93 mmol/l, P = 0.043) than controls. Patients showed an increase in q-space imaging-derived indices of perpendicular diffusivity in both the whole cord and major columns compared with controls (P < 0.05 for all indices). Lower total N-acetyl-aspartate was associated with higher disability, as assessed by the Expanded Disability Status Scale (coefficient = -0.41, 0.01 < P < 0.05), Modified Ashworth Scale (coefficient = -3.78, 0.01 < P < 0.05), vibration perception thresholds (coefficient = -4.37, P = 0.021) and postural sway (P < 0.001). Lower glutamate-glutamine predicted increased postural sway (P = 0.017). Increased perpendicular diffusivity in the whole cord and columns was associated with increased scores on the Modified Ashworth Scale, vibration perception thresholds and postural sway (P < 0.05 in all cases). These imaging findings indicate reduced structural integrity of neurons, demyelination, and abnormalities in the glutamatergic pathways in the cervical cord of early primary progressive multiple sclerosis, in the absence of extensive spinal cord atrophy. The observed relationship between imaging measures and disability suggests that early spinal neurodegeneration may underlie clinical impairment, and should be targeted in future clinical trials with neuroprotective agents to prevent the development of progressive disability. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Biosensor Technologies for Augmented Brain-Computer Interfaces in the Next Decades

DTIC Science & Technology

2012-05-13

Research Triangle Park, NC 27709-2211 Augmented brain–computer interface (ABCI);biosensor; cognitive-state monitoring; electroencephalogram( EEG ); human...biosensor; cognitive-state monitoring; electroencephalogram ( EEG ); human brain imaging Manuscript received November 28, 2011; accepted December 20...magnetic reso- nance imaging (fMRI) [1], positron emission tomography (PET) [2], electroencephalograms ( EEGs ) and optical brain imaging techniques (i.e

Diffusion Tensor Imaging: Application to the Study of the Developing Brain

ERIC Educational Resources Information Center

Cascio, Carissa J.; Gerig, Guido; Piven, Joseph

2007-01-01

Objective: To provide an overview of diffusion tensor imaging (DTI) and its application to the study of white matter in the developing brain in both healthy and clinical samples. Method: The development of DTI and its application to brain imaging of white matter tracts is discussed. Forty-eight studies using DTI to examine diffusion properties of…

Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography

PubMed Central

Gray Roncal, William; Prasad, Judy A.; Fernandes, Hugo L.; Gürsoy, Doga; De Andrade, Vincent; Fezzaa, Kamel; Xiao, Xianghui; Vogelstein, Joshua T.; Jacobsen, Chris; Körding, Konrad P.

2017-01-01

Methods for resolving the three-dimensional (3D) microstructure of the brain typically start by thinly slicing and staining the brain, followed by imaging numerous individual sections with visible light photons or electrons. In contrast, X-rays can be used to image thick samples, providing a rapid approach for producing large 3D brain maps without sectioning. Here we demonstrate the use of synchrotron X-ray microtomography (µCT) for producing mesoscale (∼1 µm 3 resolution) brain maps from millimeter-scale volumes of mouse brain. We introduce a pipeline for µCT-based brain mapping that develops and integrates methods for sample preparation, imaging, and automated segmentation of cells, blood vessels, and myelinated axons, in addition to statistical analyses of these brain structures. Our results demonstrate that X-ray tomography achieves rapid quantification of large brain volumes, complementing other brain mapping and connectomics efforts. PMID:29085899

Fetal magnetic resonance imaging (MRI): a tool for a better understanding of normal and abnormal brain development.

PubMed

Saleem, Sahar N

2013-07-01

Knowledge of the anatomy of the developing fetal brain is essential to detect abnormalities and understand their pathogenesis. Capability of magnetic resonance imaging (MRI) to visualize the brain in utero and to differentiate between its various tissues makes fetal MRI a potential diagnostic and research tool for the developing brain. This article provides an approach to understand the normal and abnormal brain development through schematic interpretation of fetal brain MR images. MRI is a potential screening tool in the second trimester of pregnancies in fetuses at risk for brain anomalies and helps in describing new brain syndromes with in utero presentation. Accurate interpretation of fetal MRI can provide valuable information that helps genetic counseling, facilitates management decisions, and guides therapy. Fetal MRI can help in better understanding the pathogenesis of fetal brain malformations and can support research that could lead to disease-specific interventions.

Fiber tracking of brain white matter based on graph theory.

PubMed

Lu, Meng

2015-01-01

Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.

Assessing the feasibility of detecting a hemorrhagic type stroke using a 16 channel magnetic induction system

NASA Astrophysics Data System (ADS)

Dekdouk, B.; Ktistis, C.; Armitage, D. W.; Peyton, A. J.

2010-04-01

Magnetic induction tomography (MIT) has been proposed as a possible method for imaging stroke in the human brain. Hemorrhagic stroke is characterized by local blood accumulation in the brain and exhibits a greater change in conductivity with frequency compared to other tissues which is observed in the frequency range of interest [1-10] MHz. In this study, we investigate the feasibility of detecting hemorrhagic stroke using absolute and frequency difference imaging. For this purpose, a model of the head originally obtained from MRI and X-ray data was used, to which a large stroke (50 ml) was added. In addition, a model of a 16 channel circular array MIT system was employed. The received coil induced voltages were computed using a custom eddy current solver, based on the finite difference method. For absolute imaging, the induced voltages at the receiver coils were calculated from various coil combinations at 10 MHz frequency together with anticipated systematic errors and biases (orientation and displacement of the coils, movement of the head). The induced voltage noise due to these systematic inaccuracies was compared with the voltage change due to the stroke. In order to decrease the impact of this noise, frequency difference was also considered, whereby measurements were performed at another frequency (1MHz) and subtracted. Comparison results are presented and a realistic picture is delivered with to regard the required mechanical stability and electronics accuracy for this particular medical application

Incorporating virtual reality graphics with brain imaging for assessment of sport-related concussions.

PubMed

Slobounov, Semyon; Sebastianelli, Wayne; Newell, Karl M

2011-01-01

There is a growing concern that traditional neuropsychological (NP) testing tools are not sensitive to detecting residual brain dysfunctions in subjects suffering from mild traumatic brain injuries (MTBI). Moreover, most MTBI patients are asymptomatic based on anatomical brain imaging (CT, MRI), neurological examinations and patients' subjective reports within 10 days post-injury. Our ongoing research has documented that residual balance and visual-kinesthetic dysfunctions along with its underlying alterations of neural substrates may be detected in "asymptomatic subjects" by means of Virtual Reality (VR) graphics incorporated with brain imaging (EEG) techniques.

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

PubMed

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

2016-11-09

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

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.

Brain Lesions

MedlinePlus

... seen on a brain-imaging test, such as magnetic resonance imaging (MRI) or computerized tomography (CT). On ... A cohort study. PLOS One. 2013;8:e71467. Magnetic resonance imaging (MRI). National Multiple Sclerosis Society. http:// ...

Reference genes for reverse transcription quantitative PCR in canine brain tissue.

PubMed

Stassen, Quirine E M; Riemers, Frank M; Reijmerink, Hannah; Leegwater, Peter A J; Penning, Louis C

2015-12-09

In the last decade canine models have been used extensively to study genetic causes of neurological disorders such as epilepsy and Alzheimer's disease and unravel their pathophysiological pathways. Reverse transcription quantitative polymerase chain reaction is a sensitive and inexpensive method to study expression levels of genes involved in disease processes. Accurate normalisation with stably expressed so-called reference genes is crucial for reliable expression analysis. Following the minimum information for publication of quantitative real-time PCR experiments precise guidelines, the expression of ten frequently used reference genes, namely YWHAZ, HMBS, B2M, SDHA, GAPDH, HPRT, RPL13A, RPS5, RPS19 and GUSB was evaluated in seven brain regions (frontal lobe, parietal lobe, occipital lobe, temporal lobe, thalamus, hippocampus and cerebellum) and whole brain of healthy dogs. The stability of expression varied between different brain areas. Using the GeNorm and Normfinder software HMBS, GAPDH and HPRT were the most reliable reference genes for whole brain. Furthermore based on GeNorm calculations it was concluded that as little as two to three reference genes are sufficient to obtain reliable normalisation, irrespective the brain area. Our results amend/extend the limited previously published data on canine brain reference genes. Despite the excellent expression stability of HMBS, GAPDH and HRPT, the evaluation of expression stability of reference genes must be a standard and integral part of experimental design and subsequent data analysis.

Stability of Black-and-White Photographic Images, with Special Reference to Microfilm.

ERIC Educational Resources Information Center

Reilly, James M.; And Others

1988-01-01

Reviews the history of silver image (black-and-white photographic image) stability, and discusses the redox blemish problem and solutions. A study conducted during 1987-88 by the Image Permanence Institute of the benefits of selenium treatment of microfilm to improve its image stability is then summarized. (21 references) (MES)

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

PubMed Central

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

2017-01-01

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

The impact of verbal framing on brain activity evoked by emotional images.

PubMed

Kisley, Michael A; Campbell, Alana M; Larson, Jenna M; Naftz, Andrea E; Regnier, Jesse T; Davalos, Deana B

2011-12-01

Emotional stimuli generally command more brain processing resources than non-emotional stimuli, but the magnitude of this effect is subject to voluntary control. Cognitive reappraisal represents one type of emotion regulation that can be voluntarily employed to modulate responses to emotional stimuli. Here, the late positive potential (LPP), a specific event-related brain potential (ERP) component, was measured in response to neutral, positive and negative images while participants performed an evaluative categorization task. One experimental group adopted a "negative frame" in which images were categorized as negative or not. The other adopted a "positive frame" in which the exact same images were categorized as positive or not. Behavioral performance confirmed compliance with random group assignment, and peak LPP amplitude to negative images was affected by group membership: brain responses to negative images were significantly reduced in the "positive frame" group. This suggests that adopting a more positive appraisal frame can modulate brain activity elicited by negative stimuli in the environment.

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

NASA Astrophysics Data System (ADS)

Wang, Dezong; Wang, Jinxiang

1994-05-01

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

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.

CT Perfusion in Acute Stroke: "Black Holes" on Time-to-Peak Image Maps Indicate Unsalvageable Brain.

PubMed

Meagher, Ruairi; Shankar, Jai Jai Shiva

2016-11-01

CT perfusion is becoming important in acute stroke imaging to determine optimal patient-management strategies. The purpose of this study was to examine the predictive value of time-to-peak image maps and, specifically, a phenomenon coined a "black hole" for assessing infarcted brain tissue at the time of scan. Acute stroke patients were screened for the presence of black holes and their follow-up imaging (noncontrast CT or MR) was reviewed to assess for infarcted brain tissue. Of the 23 patients with signs of acute ischemia on CT perfusion, all had black holes. The black holes corresponded with areas of infarcted brain on follow-up imaging (specificity 100%). Black holes demonstrated significantly lower cerebral blood volumes (P < .001) and cerebral blood flow (P < .001) compared to immediately adjacent tissue. Black holes on time-to-peak image maps represent areas of unsalvageable brain. Copyright © 2016 by the American Society of Neuroimaging.

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

MR image denoising method for brain surface 3D modeling

NASA Astrophysics Data System (ADS)

Zhao, De-xin; Liu, Peng-jie; Zhang, De-gan

2014-11-01

Three-dimensional (3D) modeling of medical images is a critical part of surgical simulation. In this paper, we focus on the magnetic resonance (MR) images denoising for brain modeling reconstruction, and exploit a practical solution. We attempt to remove the noise existing in the MR imaging signal and preserve the image characteristics. A wavelet-based adaptive curve shrinkage function is presented in spherical coordinates system. The comparative experiments show that the denoising method can preserve better image details and enhance the coefficients of contours. Using these denoised images, the brain 3D visualization is given through surface triangle mesh model, which demonstrates the effectiveness of the proposed method.

Revised Recommendations of the Consortium of MS Centers Task Force for a Standardized MRI Protocol and Clinical Guidelines for the Diagnosis and Follow-Up of Multiple Sclerosis

PubMed Central

Traboulsee, A.; Simon, J.H.; Stone, L.; Fisher, E.; Jones, D.E.; Malhotra, A.; Newsome, S.D.; Oh, J.; Reich, D.S.; Richert, N.; Rammohan, K.; Khan, O.; Radue, E.-W.; Ford, C.; Halper, J.; Li, D.

2016-01-01

SUMMARY An international group of neurologists and radiologists developed revised guidelines for standardized brain and spinal cord MR imaging for the diagnosis and follow-up of MS. A brain MR imaging with gadolinium is recommended for the diagnosis of MS. A spinal cord MR imaging is recommended if the brain MR imaging is nondiagnostic or if the presenting symptoms are at the level of the spinal cord. A follow-up brain MR imaging with gadolinium is recommended to demonstrate dissemination in time and ongoing clinically silent disease activity while on treatment, to evaluate unexpected clinical worsening, to re-assess the original diagnosis, and as a new baseline before starting or modifying therapy. A routine brain MR imaging should be considered every 6 months to 2 years for all patients with relapsing MS. The brain MR imaging protocol includes 3D T1-weighted, 3D T2-FLAIR, 3D T2-weighted, post-single-dose gadolinium-enhanced T1-weighted sequences, and a DWI sequence. The progressive multifocal leukoencephalopathy surveillance protocol includes FLAIR and DWI sequences only. The spinal cord MR imaging protocol includes sagittal T1-weighted and proton attenuation, STIR or phase-sensitive inversion recovery, axial T2- or T2*-weighted imaging through suspicious lesions, and, in some cases, postcontrast gadolinium-enhanced T1-weighted imaging. The clinical question being addressed should be provided in the requisition for the MR imaging. The radiology report should be descriptive, with results referenced to previous studies. MR imaging studies should be permanently retained and available. The current revision incorporates new clinical information and imaging techniques that have become more available. PMID:26564433

Application of optical coherence tomography based microangiography for cerebral imaging

NASA Astrophysics Data System (ADS)

Baran, Utku; Wang, Ruikang K.

2016-03-01

Requirements of in vivo rodent brain imaging are hard to satisfy using traditional technologies such as magnetic resonance imaging and two-photon microscopy. Optical coherence tomography (OCT) is an emerging tool that can easily reach at high speeds and provide high resolution volumetric images with a relatively large field of view for rodent brain imaging. Here, we provide the overview of recent developments of functional OCT based imaging techniques for neuroscience applications on rodents. Moreover, a summary of OCT-based microangiography (OMAG) studies for stroke and traumatic brain injury cases on rodents are provided.

Accurate and robust brain image alignment using boundary-based registration.

PubMed

Greve, Douglas N; Fischl, Bruce

2009-10-15

The fine spatial scales of the structures in the human brain represent an enormous challenge to the successful integration of information from different images for both within- and between-subject analysis. While many algorithms to register image pairs from the same subject exist, visual inspection shows that their accuracy and robustness to be suspect, particularly when there are strong intensity gradients and/or only part of the brain is imaged. This paper introduces a new algorithm called Boundary-Based Registration, or BBR. The novelty of BBR is that it treats the two images very differently. The reference image must be of sufficient resolution and quality to extract surfaces that separate tissue types. The input image is then aligned to the reference by maximizing the intensity gradient across tissue boundaries. Several lower quality images can be aligned through their alignment with the reference. Visual inspection and fMRI results show that BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities. BBR also excels at aligning partial-brain images to whole-brain images, a domain in which existing registration algorithms frequently fail. Even in the limit of registering a single slice, we show the BBR results to be robust and accurate.

MR Imaging Applications in Mild Traumatic Brain Injury: An Imaging Update

PubMed Central

Wu, Xin; Kirov, Ivan I.; Gonen, Oded; Ge, Yulin; Grossman, Robert I.

2016-01-01

Mild traumatic brain injury (mTBI), also commonly referred to as concussion, affects millions of Americans annually. Although computed tomography is the first-line imaging technique for all traumatic brain injury, it is incapable of providing long-term prognostic information in mTBI. In the past decade, the amount of research related to magnetic resonance (MR) imaging of mTBI has grown exponentially, partly due to development of novel analytical methods, which are applied to a variety of MR techniques. Here, evidence of subtle brain changes in mTBI as revealed by these techniques, which are not demonstrable by conventional imaging, will be reviewed. These changes can be considered in three main categories of brain structure, function, and metabolism. Macrostructural and microstructural changes have been revealed with three-dimensional MR imaging, susceptibility-weighted imaging, diffusion-weighted imaging, and higher order diffusion imaging. Functional abnormalities have been described with both task-mediated and resting-state blood oxygen level–dependent functional MR imaging. Metabolic changes suggesting neuronal injury have been demonstrated with MR spectroscopy. These findings improve understanding of the true impact of mTBI and its pathogenesis. Further investigation may eventually lead to improved diagnosis, prognosis, and management of this common and costly condition. © RSNA, 2016 PMID:27183405

Proteomic analysis and comparison of the biopsy and autopsy specimen of human brain temporal lobe.

PubMed

He, Sizhi; Wang, Qingsong; He, Jintang; Pu, Hai; Yang, Wei; Ji, Jianguo

2006-09-01

The proteomic study on human temporal lobe can help us to understand the physiological function of CNS in normal as well as in pathological state. Proteomic tools are potent for the assessment of protein stability post mortem. In this pilot study, the human temporal lobe biopsy specimen with chronic pharmacoresistant temporal lobe epilepsy (TLE) and autopsy specimen in control were separated by 2-DE. Using MALDI-TOF-MS and MS/MS, 375 protein spots were identified which were the products of 267 genes. Six down-regulated and 23 up-regulated protein spots in the autopsy specimen were ascertained after the gel image analysis with the ImageMaster software. A number of proteins that include neurotransmitter metabolic and glycolytic enzymes, cytoprotective proteins and cytoskeleton were found decreased while the precursor of apolipoprotein A-I increased in the TLE brain. We tried several methods to prepare the protein samples and found that DNase and RNase treatment, ultracentrifugation and Amersham clean-up kit purification can improve gel separation quality. This work optimized the sample preparation method and constructed a primary protein database of human temporal lobe and found some proteins with remarkable level change probably involved in the post-mortem process and chronic pharmacoresistant TLE pathogenesis.

Wnt/β-catenin signaling controls development of the blood–brain barrier

PubMed Central

Liebner, Stefan; Corada, Monica; Bangsow, Thorsten; Babbage, Jane; Taddei, Andrea; Czupalla, Cathrin J.; Reis, Marco; Felici, Angelina; Wolburg, Hartwig; Fruttiger, Marcus; Taketo, Makoto M.; von Melchner, Harald; Plate, Karl Heinz; Gerhardt, Holger; Dejana, Elisabetta

2008-01-01

The blood–brain barrier (BBB) is confined to the endothelium of brain capillaries and is indispensable for fluid homeostasis and neuronal function. In this study, we show that endothelial Wnt/β-catenin (β-cat) signaling regulates induction and maintenance of BBB characteristics during embryonic and postnatal development. Endothelial specific stabilization of β-cat in vivo enhances barrier maturation, whereas inactivation of β-cat causes significant down-regulation of claudin3 (Cldn3), up-regulation of plamalemma vesicle-associated protein, and BBB breakdown. Stabilization of β-cat in primary brain endothelial cells (ECs) in vitro by N-terminal truncation or Wnt3a treatment increases Cldn3 expression, BBB-type tight junction formation, and a BBB characteristic gene signature. Loss of β-cat or inhibition of its signaling abrogates this effect. Furthermore, stabilization of β-cat also increased Cldn3 and barrier properties in nonbrain-derived ECs. These findings may open new therapeutic avenues to modulate endothelial barrier function and to limit the devastating effects of BBB breakdown. PMID:18955553

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.

Brain abnormalities in antisocial individuals: implications for the law.

PubMed

Yang, Yaling; Glenn, Andrea L; Raine, Adrian

2008-01-01

With the increasing popularity in the use of brain imaging on antisocial individuals, an increasing number of brain imaging studies have revealed structural and functional impairments in antisocial, psychopathic, and violent individuals. This review summarizes key findings from brain imaging studies on antisocial/aggressive behavior. Key regions commonly found to be impaired in antisocial populations include the prefrontal cortex (particularly orbitofrontal and dorsolateral prefrontal cortex), superior temporal gyrus, amygdala-hippocampal complex, and anterior cingulate cortex. Key functions of these regions are reviewed to provide a better understanding on how deficits in these regions may predispose to antisocial behavior. Objections to the use of imaging findings in a legal context are outlined, and alternative perspectives raised. It is argued that brain dysfunction is a risk factor for antisocial behavior and that it is likely that imaging will play an increasing (albeit limited) role in legal decision-making. (c) 2008 John Wiley & Sons, Ltd.

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

PubMed

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

2016-08-01

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

Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

PubMed

Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

2013-10-01

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

Connectome imaging for mapping human brain pathways

PubMed Central

Shi, Y; Toga, A W

2017-01-01

With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project. Characterization of the microstructural environment in the human brain is discussed from the tensor model to the general fiber orientation distribution (FOD) models that can resolve crossing fibers in each voxel of the image. Using FOD-based tractography, we describe novel methods for fiber bundle reconstruction and graph-based connectivity analysis. Building upon these novel developments, there have already been successful applications of connectome imaging techniques in reconstructing challenging brain pathways. Examples including retinofugal and brainstem pathways will be reviewed. Finally, we discuss future directions in connectome imaging and its interaction with other aspects of brain imaging research. PMID:28461700

Phosphatidylserine-Targeted Nanotheranostics for Brain Tumor Imaging and Therapeutic Potential

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Transmission in near-infrared optical windows for deep brain imaging.

PubMed

Shi, Lingyan; Sordillo, Laura A; Rodríguez-Contreras, Adrián; Alfano, Robert

2016-01-01

Near-infrared (NIR) radiation has been employed using one- and two-photon excitation of fluorescence imaging at wavelengths 650-950 nm (optical window I) for deep brain imaging; however, longer wavelengths in NIR have been overlooked due to a lack of suitable NIR-low band gap semiconductor imaging detectors and/or femtosecond laser sources. This research introduces three new optical windows in NIR and demonstrates their potential for deep brain tissue imaging. The transmittances are measured in rat brain tissue in the second (II, 1,100-1,350 nm), third (III, 1,600-1,870 nm), and fourth (IV, centered at 2,200 nm) NIR optical tissue windows. The relationship between transmission and tissue thickness is measured and compared with the theory. Due to a reduction in scattering and minimal absorption, window III is shown to be the best for deep brain imaging, and windows II and IV show similar but better potential for deep imaging than window I. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

PubMed

Banerjee, Abhirup; Maji, Pradipta

2015-12-01

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

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.

Development of a high angular resolution diffusion imaging human brain template.

PubMed

Varentsova, Anna; Zhang, Shengwei; Arfanakis, Konstantinos

2014-05-01

Brain diffusion templates contain rich information about the microstructure of the brain, and are used as references in spatial normalization or in the development of brain atlases. The accuracy of diffusion templates constructed based on the diffusion tensor (DT) model is limited in regions with complex neuronal micro-architecture. High angular resolution diffusion imaging (HARDI) overcomes limitations of the DT model and is capable of resolving intravoxel heterogeneity. However, when HARDI is combined with multiple-shot sequences to minimize image artifacts, the scan time becomes inappropriate for human brain imaging. In this work, an artifact-free HARDI template of the human brain was developed from low angular resolution multiple-shot diffusion data. The resulting HARDI template was produced in ICBM-152 space based on Turboprop diffusion data, was shown to resolve complex neuronal micro-architecture in regions with intravoxel heterogeneity, and contained fiber orientation information consistent with known human brain anatomy. Copyright © 2014 Elsevier Inc. All rights reserved.

Gabapentin’s minimal action on markers of rat brain arachidonic acid metabolism agrees with its inefficacy against bipolar disorder

PubMed Central

Reese, Edmund A.; Cheon, Yewon; Ramadan, Epolia; Kim, Hyung-Wook; Chang, Lisa; Rao, Jagadeesh S.; Rapoport, Stanley I.; Taha, Ameer Y.

2012-01-01

In rats, FDA-approved mood stabilizers used for treating bipolar disorder (BD) selectively downregulate brain markers of the arachidonic acid (AA) cascade, which are upregulated in postmortem BD brain. Phase III clinical trials show that gabapentin (GBP) is ineffective in treating BD. We hypothesized that GBP would not alter the rat brain AA cascade. Chronic GBP (10 mg/kg body weight, injected i.p. for 30 days) compared to saline vehicle did not significantly alter brain expression or activity of AA-selective cytosolic phospholipase A2 (cPLA2) IVA or secretory (s) PLA2 IIA, activity of cyclooxygenase-2, or prostaglandin or thromboxane concentrations. Plasma AA concentration was unaffected. These results, taken with evidence of an upregulated AA cascade in the BD brain and that approved mood stabilizers downregulate rat brain AA cascade, support the hypothesis that effective anti-BD drugs act by targeting the AA cascade, and suggest that the rat model might be used for drug screening PMID:22841517

Magnetic resonance characteristics and susceptibility weighted imaging of the brain in gadolinium encephalopathy.

PubMed

Samardzic, Dejan; Thamburaj, Krishnamoorthy

2015-01-01

To report the brain imaging features on magnetic resonance imaging (MRI) in inadvertent intrathecal gadolinium administration. A 67-year-old female with gadolinium encephalopathy from inadvertent high dose intrathecal gadolinium administration during an epidural steroid injection was studied with multisequence 3T MRI. T1-weighted imaging shows pseudo-T2 appearance with diffusion of gadolinium into the brain parenchyma, olivary bodies, and membranous labyrinth. Nulling of cerebrospinal fluid (CSF) signal is absent on fluid attenuation recovery (FLAIR). Susceptibility-weighted imaging (SWI) demonstrates features similar to subarachnoid hemorrhage. CT may demonstrate a pseudo-cerebral edema pattern given the high attenuation characteristics of gadolinium. Intrathecal gadolinium demonstrates characteristic imaging features on MRI of the brain and may mimic subarachnoid hemorrhage on susceptibility-weighted imaging. Identifying high dose gadolinium within the CSF spaces on MRI is essential to avoid diagnostic and therapeutic errors. Copyright © 2013 by the American Society of Neuroimaging.

Hierarchical and symmetric infant image registration by robust longitudinal-example-guided correspondence detection

PubMed Central

Wu, Yao; Wu, Guorong; Wang, Li; Munsell, Brent C.; Wang, Qian; Lin, Weili; Feng, Qianjin; Chen, Wufan; Shen, Dinggang

2015-01-01

Purpose: To investigate anatomical differences across individual subjects, or longitudinal changes in early brain development, it is important to perform accurate image registration. However, due to fast brain development and dynamic tissue appearance changes, it is very difficult to align infant brain images acquired from birth to 1-yr-old. Methods: To solve this challenging problem, a novel image registration method is proposed to align two infant brain images, regardless of age at acquisition. The main idea is to utilize the growth trajectories, or spatial-temporal correspondences, learned from a set of longitudinal training images, for guiding the registration of two different time-point images with different image appearances. Specifically, in the training stage, an intrinsic growth trajectory is first estimated for each training subject using the longitudinal images. To register two new infant images with potentially a large age gap, the corresponding images patches between each new image and its respective training images with similar age are identified. Finally, the registration between the two new images can be assisted by the learned growth trajectories from one time point to another time point that have been established in the training stage. To further improve registration accuracy, the proposed method is combined with a hierarchical and symmetric registration framework that can iteratively add new key points in both images to steer the estimation of the deformation between the two infant brain images under registration. Results: To evaluate image registration accuracy, the proposed method is used to align 24 infant subjects at five different time points (2-week-old, 3-month-old, 6-month-old, 9-month-old, and 12-month-old). Compared to the state-of-the-art methods, the proposed method demonstrated superior registration performance. Conclusions: The proposed method addresses the difficulties in the infant brain registration and produces better results compared to existing state-of-the-art registration methods. PMID:26133617

Use of High Resolution 3D Diffusion Tensor Imaging to Study Brain White Matter Development in Live Neonatal Rats

PubMed Central

Cai, Yu; McMurray, Matthew S.; Oguz, Ipek; Yuan, Hong; Styner, Martin A.; Lin, Weili; Johns, Josephine M.; An, Hongyu

2011-01-01

High resolution diffusion tensor imaging (DTI) can provide important information on brain development, yet it is challenging in live neonatal rats due to the small size of neonatal brain and motion-sensitive nature of DTI. Imaging in live neonatal rats has clear advantages over fixed brain scans, as longitudinal and functional studies would be feasible to understand neuro-developmental abnormalities. In this study, we developed imaging strategies that can be used to obtain high resolution 3D DTI images in live neonatal rats at postnatal day 5 (PND5) and PND14, using only 3 h of imaging acquisition time. An optimized 3D DTI pulse sequence and appropriate animal setup to minimize physiological motion artifacts are the keys to successful high resolution 3D DTI imaging. Thus, a 3D rapid acquisition relaxation enhancement DTI sequence with twin navigator echoes was implemented to accelerate imaging acquisition time and minimize motion artifacts. It has been suggested that neonatal mammals possess a unique ability to tolerate mild-to-moderate hypothermia and hypoxia without long term impact. Thus, we additionally utilized this ability to minimize motion artifacts in magnetic resonance images by carefully suppressing the respiratory rate to around 15/min for PND5 and 30/min for PND14 using mild-to-moderate hypothermia. These imaging strategies have been successfully implemented to study how the effect of cocaine exposure in dams might affect brain development in their rat pups. Image quality resulting from this in vivo DTI study was comparable to ex vivo scans. fractional anisotropy values were also similar between the live and fixed brain scans. The capability of acquiring high quality in vivo DTI imaging offers a valuable opportunity to study many neurological disorders in brain development in an authentic living environment. PMID:22013426

Combining Segmented Grey and White Matter Images Improves Voxel-based Morphometry for the Case of Dilated Lateral Ventricles.

PubMed

Goto, Masami; Abe, Osamu; Aoki, Shigeki; Kamagata, Koji; Hori, Masaaki; Miyati, Tosiaki; Gomi, Tsutomu; Takeda, Tohoru

2018-01-18

To evaluate the error in segmented tissue images and to show the usefulness of the brain image in voxel-based morphometry (VBM) using Statistical Parametric Mapping (SPM) 12 software and 3D T 1 -weighted magnetic resonance images (3D-T 1 WIs) processed to simulate idiopathic normal pressure hydrocephalus (iNPH). VBM analysis was performed on sagittal 3D-T 1 WIs obtained in 22 healthy volunteers using a 1.5T MR scanner. Regions of interest for the lateral ventricles of all subjects were carefully outlined on the original 3D-T 1 WIs, and two types of simulated 3D-T 1 WI were also prepared (non-dilated 3D-T 1 WI as normal control and dilated 3D-T 1 WI to simulate iNPH). All simulated 3D-T 1 WIs were segmented into gray matter, white matter, and cerebrospinal fluid images, and normalized to standard space. A brain image was made by adding the gray and white matter images. After smoothing with a 6-mm isotropic Gaussian kernel, group comparisons (dilated vs non-dilated) were made for gray and white matter, cerebrospinal fluid, and brain images using a paired t-test. In evaluation of tissue volume, estimation error was larger using gray or white matter images than using the brain image, and estimation errors in gray and white matter volume change were found for the brain surface. To our knowledge, this is the first VBM study to show the possibility that VBM of gray and white matter volume on the brain surface may be more affected by individual differences in the level of dilation of the lateral ventricles than by individual differences in gray and white matter volumes. We recommend that VBM evaluation in patients with iNPH should be performed using the brain image rather than the gray and white matter images.

Anatomical Brain Magnetic Resonance Imaging of Typically Developing Children and Adolescents

ERIC Educational Resources Information Center

Giedd, Jay N.; Lalonde, Francois M.; Celano, Mark J.; White, Samantha L.; Wallace, Gregory L.; Lee, Nancy R.; Lenroot, Rhoshel K.

2009-01-01

Methodological issues relevant to magnetic resonance imaging studies of brain anatomy are discussed along with the findings on the neuroanatomic changes during childhood and adolescence. The development of the brain is also discussed.

Brain white matter fiber estimation and tractography using Q-ball imaging and Bayesian MODEL.

PubMed

Lu, Meng

2015-01-01

Diffusion tensor imaging allows for the non-invasive in vivo mapping of the brain tractography. However, fiber bundles have complex structures such as fiber crossings, fiber branchings and fibers with large curvatures that tensor imaging (DTI) cannot accurately handle. This study presents a novel brain white matter tractography method using Q-ball imaging as the data source instead of DTI, because QBI can provide accurate information about multiple fiber crossings and branchings in a single voxel using an orientation distribution function (ODF). The presented method also uses graph theory to construct the Bayesian model-based graph, so that the fiber tracking between two voxels can be represented as the shortest path in a graph. Our experiment showed that our new method can accurately handle brain white matter fiber crossings and branchings, and reconstruct brain tractograhpy both in phantom data and real brain data.

Effect of fish oils containing different amounts of EPA, DHA, and antioxidants on plasma and brain fatty acids and brain nitric oxide synthase activity in rats

PubMed Central

Engström, Karin; Saldeen, Ann-Sofie; Yang, Baichun; Mehta, Jawahar L.

2009-01-01

Background The interest in n-3 polyunsaturated fatty acids (PUFAs) has expanded significantly in the last few years, due to their many positive effects described. Consequently, the interest in fish oil supplementation has also increased, and many different types of fish oil supplements can be found on the market. Also, it is well known that these types of fatty acids are very easily oxidized, and that stability among supplements varies greatly. Aims of the study In this pilot study we investigated the effects of two different types of natural fish oils containing different amounts of the n-3 PUFAs eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and antioxidants on plasma and brain fatty acids, blood lipids, vitamin E, and in vivo lipid peroxidation, as well as brain nitric oxide synthase (NOS) activity, an enzyme which has been shown to be important for memory and learning ability. Methods Sprague-Dawley rats were divided into four groups and fed regular rat chow pellets enriched with 5% (w/w) of butter (control group), a natural fish oil (17.4% EPA and 11.7% DHA, referred to as EPA-rich), and a natural fish oil rich in DHA (7.7% EPA and 28.0% DHA, referred to as DHA-rich). Both of the fish oils were stabilized by a commercial antioxidant protection system (Pufanox®) at production. The fourth group received the same DHA-rich oil, but without Pufanox® stabilization (referred to as unstable). As an index of stability of the oils, their peroxide values were repeatedly measured during 9 weeks. The dietary treatments continued until sacrifice, after 10 days. Results Stability of the oils varied greatly. It took the two stabilized oils 9 weeks to reach the same peroxide value as the unstable oil reached after only a few days. Both the stabilized EPA- and DHA-rich diets lowered the triacylglycerols and total cholesterol compared to control (-45%, P < 0.05 and -54%, P < 0.001; -31%, P < 0.05 and -25%, P < 0.01) and so did the unstable oil, but less efficiently. Only the unstable oil increased in vivo lipid peroxidation significantly compared to control (+40%, P < 0.001). Most of the fatty acids in the plasma phospholipids were significantly affected by both the EPA- and DHA-rich diets compared to control, reflecting their specific fatty acid pattern. The unstable oil diet resulted in smaller changes, especially in n-3 PUFAs. In the brain phospholipids the changes were less pronounced, and only the diet enriched with the stabilized DHA-rich oil resulted in a significantly greater incorporation of DHA (+13%, P < 0.01), as well as total n-3 PUFAs (+13%, P < 0.01) compared to control. Only the stabilized DHA-rich oil increased the brain NOS activity (+33%, P < 0.01). Conclusions Both the EPA- and DHA-rich diets affected the blood lipids in a similarly positive manner, and they both had a large impact on plasma phospholipid fatty acids. It was only the unstable oil that increased in vivo lipid peroxidation. However, the intake of DHA was more important than that of EPA for brain phospholipid DHA enrichment and brain NOS activity, and the stability of the fish oil was also important for these effects. PMID:19961266

Effect of fish oils containing different amounts of EPA, DHA, and antioxidants on plasma and brain fatty acids and brain nitric oxide synthase activity in rats.

PubMed

Engström, Karin; Saldeen, Ann-Sofie; Yang, Baichun; Mehta, Jawahar L; Saldeen, Tom

2009-01-01

The interest in n-3 polyunsaturated fatty acids (PUFAs) has expanded significantly in the last few years, due to their many positive effects described. Consequently, the interest in fish oil supplementation has also increased, and many different types of fish oil supplements can be found on the market. Also, it is well known that these types of fatty acids are very easily oxidized, and that stability among supplements varies greatly. In this pilot study we investigated the effects of two different types of natural fish oils containing different amounts of the n-3 PUFAs eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and antioxidants on plasma and brain fatty acids, blood lipids, vitamin E, and in vivo lipid peroxidation, as well as brain nitric oxide synthase (NOS) activity, an enzyme which has been shown to be important for memory and learning ability. Sprague-Dawley rats were divided into four groups and fed regular rat chow pellets enriched with 5% (w/w) of butter (control group), a natural fish oil (17.4% EPA and 11.7% DHA, referred to as EPA-rich), and a natural fish oil rich in DHA (7.7% EPA and 28.0% DHA, referred to as DHA-rich). Both of the fish oils were stabilized by a commercial antioxidant protection system (Pufanox) at production. The fourth group received the same DHA-rich oil, but without Pufanox stabilization (referred to as unstable). As an index of stability of the oils, their peroxide values were repeatedly measured during 9 weeks. The dietary treatments continued until sacrifice, after 10 days. Stability of the oils varied greatly. It took the two stabilized oils 9 weeks to reach the same peroxide value as the unstable oil reached after only a few days. Both the stabilized EPA- and DHA-rich diets lowered the triacylglycerols and total cholesterol compared to control (-45%, P < 0.05 and -54%, P < 0.001; -31%, P < 0.05 and -25%, P < 0.01) and so did the unstable oil, but less efficiently. Only the unstable oil increased in vivo lipid peroxidation significantly compared to control (+40%, P < 0.001). Most of the fatty acids in the plasma phospholipids were significantly affected by both the EPA- and DHA-rich diets compared to control, reflecting their specific fatty acid pattern. The unstable oil diet resulted in smaller changes, especially in n-3 PUFAs. In the brain phospholipids the changes were less pronounced, and only the diet enriched with the stabilized DHA-rich oil resulted in a significantly greater incorporation of DHA (+13%, P < 0.01), as well as total n-3 PUFAs (+13%, P < 0.01) compared to control. Only the stabilized DHA-rich oil increased the brain NOS activity (+33%, P < 0.01). Both the EPA- and DHA-rich diets affected the blood lipids in a similarly positive manner, and they both had a large impact on plasma phospholipid fatty acids. It was only the unstable oil that increased in vivo lipid peroxidation. However, the intake of DHA was more important than that of EPA for brain phospholipid DHA enrichment and brain NOS activity, and the stability of the fish oil was also important for these effects.

Digital atlas of fetal brain MRI.

PubMed

Chapman, Teresa; Matesan, Manuela; Weinberger, Ed; Bulas, Dorothy I

2010-02-01

Fetal MRI can be performed in the second and third trimesters. During this time, the fetal brain undergoes profound structural changes. Interpretation of appropriate development might require comparison with normal age-based models. Consultation of a hard-copy atlas is limited by the inability to compare multiple ages simultaneously. To provide images of normal fetal brains from weeks 18 through 37 in a digital format that can be reviewed interactively. This will facilitate recognition of abnormal brain development. T2-W images for the atlas were obtained from fetal MR studies of normal brains scanned for other indications from 2005 to 2007. Images were oriented in standard axial, coronal and sagittal projections, with laterality established by situs. Gestational age was determined by last menstrual period, earliest US measurements and sonogram performed on the same day as the MR. The software program used for viewing the atlas, written in C#, permits linked scrolling and resizing the images. Simultaneous comparison of varying gestational ages is permissible. Fetal brain images across gestational ages 18 to 37 weeks are provided as an interactive digital atlas and are available for free download from http://radiology.seattlechildrens.org/teaching/fetal_brain . Improved interpretation of fetal brain abnormalities can be facilitated by the use of digital atlas cataloging of the normal changes throughout fetal development. Here we provide a description of the atlas and a discussion of normal fetal brain development.

Preprocessing film-copied MRI for studying morphological brain changes.

PubMed

Pham, Tuan D; Eisenblätter, Uwe; Baune, Bernhard T; Berger, Klaus

2009-06-15

The magnetic resonance imaging (MRI) of the brain is one of the important data items for studying memory and morbidity in elderly as these images can provide useful information through the quantitative measures of various regions of interest of the brain. As an effort to fully automate the biomedical analysis of the brain that can be combined with the genetic data of the same human population and where the records of the original MRI data are missing, this paper presents two effective methods for addressing this imaging problem. The first method handles the restoration of the film-copied MRI. The second method involves the segmentation of the image data. Experimental results and comparisons with other methods suggest the usefulness of the proposed image analysis methodology.

Neonatal brain resting-state functional connectivity imaging modalities.

PubMed

Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza

2018-06-01

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

3D surface rendered MR images of the brain and its vasculature.

PubMed

Cline, H E; Lorensen, W E; Souza, S P; Jolesz, F A; Kikinis, R; Gerig, G; Kennedy, T E

1991-01-01

Both time-of-flight and phase contrast magnetic resonance angiography images are combined with stationary tissue images to provide data depicting two contrast relationships yielding intrinsic discrimination of brain matter and flowing blood. A computer analysis is based on nearest neighbor segmentation and the connection between anatomical structures to partition the images into different tissue categories: from which, high resolution brain parenchymal and vascular surfaces are constructed and rendered in juxtaposition, aiding in surgical planning.

Neuromolecular imaging, a nanobiotechnology for Parkinson's disease: advancing pharmacotherapy for personalized medicine.

PubMed

Broderick, P A; Wenning, L; Li, Y-S

2017-01-01

Evaluating each patient and animal as its own control achieves personalized medicine, which honors the hippocratic philosophy, explaining that "it is far more important to know what person has the disease than what disease the person has." Similarly, individualizing molecular signaling directly from the patient's brain in real time is essential for providing prompt, patient-based treatment as dictated by the point of care. Fortunately, nanotechnology effectively treats many neurodegenerative diseases. In particular, the new medicinal frontier for the discovery of therapy for Parkinson's disease is nanotechnology and nanobiotechnology. Indeed, the unique nanotechnology of neuromolecular imaging combined with the series of nanobiosensors enables continuous videotracking of molecular neurotransmitters in both the normal physiologic and disease states with long-term electrochemical operational stability. This nanobiotechnology is able to track a signal in real time with excellent temporal and spatial resolution directly from each patient's brain to a computer as subjects are behaving during movement, normal and/or dysfunctional including prion-like Parkinson's behavioral biometrics. Moreover, the molecular signaling performed by these nanobiosensors live streams directly online and originates from precise neuroanatomic brain sites such as, in this case, the dorsal striatum in basal ganglia. Thus, the nanobiotechnology studies discussed herein imaged neuromolecules with and without L-3,4-dihydroxyphenylalanine (L-DOPA) in dorsal striatal basal ganglia neurons. Parkinsonian and non-Parkinsonian animals were video-tracked, and images were readily seen on a laptop via a potentiostat using a semiderivative electrical circuit. Administered L-DOPA doses were 50 and 100 mg/kg intraperitoneally (ip); the same experimental paradigm was used to image and then contrast data. Results showed that the baseline release of biogenic amine molecules was significantly above detection limits in non-Parkinsonian animals. After administration of L-DOPA, biogenic amines significantly increased in these non-Parkinson's animals. Nevertheless, it is intriguing to see that L-DOPA could not enable synaptic dopamine release in Parkinson's animals, thereby demonstrating that biogenic amines are biomarkers for Parkinson's disease. Biomarkers are biochemical, genetic, or molecular measures of biological reactions. Importantly, there were other significant biomarkers present in Parkinsonian animals and absent in non-Parkinsonian animals; these were peptide neurotransmitters that include dynorphin and somatostatin in the brain with detection limits of 40 nM for dynorphin and 37 nM for somatostatin (see Table 1). Furthermore, L-DOPA significantly increased these peptide biomarkers, dynorphin and somatostatin, in Parkinson's animals. Targeting biomarkers enables new diagnostic devices and treatments for Parkinson's disease through nanotechnology and nanobiotechnology.

A combination of lipidomics, MS imaging, and PET scan imaging reveals differences in cerebral activity in rat pups according to the lipid quality of infant formulas.

PubMed

Aidoud, Nacima; Delplanque, Bernadette; Baudry, Charlotte; Garcia, Cyrielle; Moyon, Anais; Balasse, Laure; Guillet, Benjamin; Antona, Claudine; Darmaun, Dominique; Fraser, Karl; Ndiaye, Sega; Leruyet, Pascale; Martin, Jean-Charles

2018-03-22

We evaluated the effect of adding docosahexaenoic:arachidonic acids (3:2) (DHA+ARA) to 2 representative commercial infant formulas on brain activity and brain and eye lipids in an artificially reared rat pup model. The formula lipid background was either a pure plant oil blend, or dairy fat with a plant oil blend (1:1). Results at weaning were compared to breast milk-fed pups. Brain functional activity was determined by positron emission tomography scan imaging, the brain and eye fatty acid and lipid composition by targeted and untargeted lipidomics, and DHA brain regional location by mass-spectrometry imaging. The brain functional activity was normalized to controls with DHA+ARA added to the formulas. DHA in both brain and eyes was influenced by formula intake, but more than two-thirds of tissue DHA-glycerolipids remained insensitive to the dietary challenge. However, the DHA lipidome correlated better with brain function than sole DHA content ( r = 0.70 vs. r = 0.48; P < 0.05). Brain DHA regional distribution was more affected by the formula lipid background than the provision of PUFAs. Adding DHA+ARA to formulas alters the DHA content and lipidome of nervous tissue in the neonate, making it closer to dam milk-fed controls, and normalizes brain functional activity.-Aidoud, N., Delplanque, B., Baudry, C., Garcia, C., Moyon, A., Balasse, L., Guillet, B., Antona, C., Darmaun, D., Fraser, K., Ndiaye, S., Leruyet, P., Martin, J.-C. A combination of lipidomics, MS imaging, and PET scan imaging reveals differences in cerebral activity in rat pups according to the lipid quality of infant formulas.

Added Value of Including Entire Brain on Body Imaging With FDG PET/MRI.

PubMed

Franceschi, Ana M; Matthews, Robert; Bangiyev, Lev; Relan, Nand; Chaudhry, Ammar; Franceschi, Dinko

2018-05-24

FDG PET/MRI examination of the body is routinely performed from the skull base to the mid thigh. Many types of brain abnormalities potentially could be detected on PET/MRI if the head was included. The objective of this study was therefore to identify and characterize brain findings incidentally detected on PET/MRI of the body with the head included. We retrospectively identified 269 patients with FDG PET/MRI whole-body scans that included the head. PET/MR images of the brain were reviewed by a nuclear medicine physician and neuroradiologist, first individually and then concurrently. Both PET and MRI findings were identified, including abnormal FDG uptake, standardized uptake value, lesion size, and MRI signal characteristics. For each patient, relevant medical history and prior imaging were reviewed. Of the 269 subjects, 173 were women and 96 were men (mean age, 57.4 years). Only the initial PET/MR image of each patient was reviewed. A total of 37 of the 269 patients (13.8%) had abnormal brain findings noted on the PET/MRI whole-body scan. Sixteen patients (5.9%) had vascular disease, nine patients (3.3%) had posttherapy changes, and two (0.7%) had benign cystic lesions in the brain. Twelve patients (4.5%) had serious nonvascular brain abnormalities, including cerebral metastasis in five patients and pituitary adenomas in two patients. Only nine subjects (3.3%) had a new neurologic or cognitive symptom suggestive of a brain abnormality. Routine body imaging with FDG PET/MRI of the area from the skull base to the mid thigh may miss important brain abnormalities when the head is not included. The additional brain abnormalities identified on whole-body imaging may provide added clinical value to the management of oncology patients.

Robust Transient Dynamics and Brain Functions

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo

2011-01-01

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

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

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

NASA Astrophysics Data System (ADS)

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

2013-07-01

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

Real-time simulation and visualization of volumetric brain deformation for image-guided neurosurgery

NASA Astrophysics Data System (ADS)

Ferrant, Matthieu; Nabavi, Arya; Macq, Benoit M. M.; Kikinis, Ron; Warfield, Simon K.

2001-05-01

During neurosurgery, the challenge for the neurosurgeon is to remove as much as possible of a tumor without destroying healthy tissue. This can be difficult because healthy and diseased tissue can have the same visual appearance. To this aim, and because the surgeon cannot see underneath the brain surface, image-guided neurosurgery systems are being increasingly used. However, during surgery, deformation of the brain occurs (due to brain shift and tumor resection), therefore causing errors in the surgical planning with respect to preoperative imaging. In our previous work, we developed software for capturing the deformation of the brain during neurosurgery. The software also allows preoperative data to be updated according to the intraoperative imaging so as to reflect the shape changes of the brain during surgery. Our goal in this paper was to rapidly visualize and characterize this deformation over the course of surgery with appropriate tools. Therefore, we developed tools allowing the doctor to visualize (in 2D and 3D) deformations, as well as the stress tensors characterizing the deformation along with the updated preoperative and intraoperative imaging during the course of surgery. Such tools significantly add to the value of intraoperative imaging and hence could improve surgical outcomes.

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Mesoscale brain explorer, a flexible python-based image analysis and visualization tool.

PubMed

Haupt, Dirk; Vanni, Matthieu P; Bolanos, Federico; Mitelut, Catalin; LeDue, Jeffrey M; Murphy, Tim H

2017-07-01

Imaging of mesoscale brain activity is used to map interactions between brain regions. This work has benefited from the pioneering studies of Grinvald et al., who employed optical methods to image brain function by exploiting the properties of intrinsic optical signals and small molecule voltage-sensitive dyes. Mesoscale interareal brain imaging techniques have been advanced by cell targeted and selective recombinant indicators of neuronal activity. Spontaneous resting state activity is often collected during mesoscale imaging to provide the basis for mapping of connectivity relationships using correlation. However, the information content of mesoscale datasets is vast and is only superficially presented in manuscripts given the need to constrain measurements to a fixed set of frequencies, regions of interest, and other parameters. We describe a new open source tool written in python, termed mesoscale brain explorer (MBE), which provides an interface to process and explore these large datasets. The platform supports automated image processing pipelines with the ability to assess multiple trials and combine data from different animals. The tool provides functions for temporal filtering, averaging, and visualization of functional connectivity relations using time-dependent correlation. Here, we describe the tool and show applications, where previously published datasets were reanalyzed using MBE.

Functional connectivity in the mouse brain imaged by B-mode photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xing, Wenxin; Xia, Jun; Wang, Lihong V.

2014-03-01

The increasing use of mouse models for human brain disease studies, coupled with the fact that existing functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing acoustic-resolution photoacoustic microscopy (AR-PAM), we imaged spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images were acquired noninvasively in B-scan mode with a fast frame rate, a large field of view, and a high spatial resolution. At a location relative to the bregma 0, correlations were investigated inter-hemispherically between bilaterally homologous regions, as well as intra-hemispherically within the same functional regions. The functional connectivity in different functional regions was studied. The locations of these regions agreed well with the Paxinos mouse brain atlas. The functional connectivity map obtained in this study can then be used in the investigation of brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy. Our experiments show that photoacoustic microscopy is capable to detect connectivities between different functional regions in B-scan mode, promising a powerful functional imaging modality for future brain research.

Functional Imaging and Migraine: New Connections?

PubMed Central

Schwedt, Todd J.; Chong, Catherine D.

2015-01-01

Purpose of Review Over the last several years, a growing number of brain functional imaging studies have provided insights into mechanisms underlying migraine. This manuscript reviews the recent migraine functional neuroimaging literature and provides recommendations for future studies that will help fill knowledge gaps. Recent Findings Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have identified brain regions that might be responsible for mediating the onset of a migraine attack and those associated with migraine symptoms. Enhanced activation of brain regions that facilitate processing of sensory stimuli suggests a mechanism by which migraineurs are hypersensitive to visual, olfactory, and cutaneous stimuli. Resting state functional connectivity MRI studies have identified numerous brain regions and functional networks with atypical functional connectivity in migraineurs, suggesting that migraine is associated with aberrant brain functional organization. Summary fMRI and PET studies that have identified brain regions and brain networks that are atypical in migraine have helped to describe the neurofunctional basis for migraine symptoms. Future studies should compare functional imaging findings in migraine to other headache and pain disorders and should explore the utility of functional imaging data as biomarkers for diagnostic and treatment purposes. PMID:25887764

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.

Image guided constitutive modeling of the silicone brain phantom

NASA Astrophysics Data System (ADS)

Puzrin, Alexander; Skrinjar, Oskar; Ozan, Cem; Kim, Sihyun; Mukundan, Srinivasan

2005-04-01

The goal of this work is to develop reliable constitutive models of the mechanical behavior of the in-vivo human brain tissue for applications in neurosurgery. We propose to define the mechanical properties of the brain tissue in-vivo, by taking the global MR or CT images of a brain response to ventriculostomy - the relief of the elevated intracranial pressure. 3D image analysis translates these images into displacement fields, which by using inverse analysis allow for the constitutive models of the brain tissue to be developed. We term this approach Image Guided Constitutive Modeling (IGCM). The presented paper demonstrates performance of the IGCM in the controlled environment: on the silicone brain phantoms closely simulating the in-vivo brain geometry, mechanical properties and boundary conditions. The phantom of the left hemisphere of human brain was cast using silicon gel. An inflatable rubber membrane was placed inside the phantom to model the lateral ventricle. The experiments were carried out in a specially designed setup in a CT scanner with submillimeter isotropic voxels. The non-communicative hydrocephalus and ventriculostomy were simulated by consequently inflating and deflating the internal rubber membrane. The obtained images were analyzed to derive displacement fields, meshed, and incorporated into ABAQUS. The subsequent Inverse Finite Element Analysis (based on Levenberg-Marquardt algorithm) allowed for optimization of the parameters of the Mooney-Rivlin non-linear elastic model for the phantom material. The calculated mechanical properties were consistent with those obtained from the element tests, providing justification for the future application of the IGCM to in-vivo brain tissue.

Reformatted images improve the detection rate of acute traumatic subdural hematomas on brain CT compared with axial images alone.

PubMed

Amrhein, Timothy J; Mostertz, William; Matheus, Maria Gisele; Maass-Bolles, Genevieve; Sharma, Komal; Collins, Heather R; Kranz, Peter G

2017-02-01

Subdural hematomas (SDHs) comprise a significant percentage of missed intracranial hemorrhage on axial brain CT. SDH detection rates could be improved with the addition of reformatted images. Though performed at some centers, the potential additional diagnostic sensitivity of reformatted images has not yet been investigated. The purpose of our study is to determine if the addition of coronal and sagittal reformatted images to an axial brain CT increases the sensitivity and specificity for detection of acute traumatic SDH. We retrospectively reviewed consecutive brain CTs acquired for acute trauma that contained new SDHs. An equivalent number of normal brain CTs served as control. Paired sets of images were created for each case: (1) axial images only ("axial only") and (2) axial, coronal, sagittal images ("reformat added"). Three readers interpreted both the axial only and companion reformat added for each case, separated by 1 month. Reading times and SDH detection rates were compared. One hundred SDH and 100 negative examinations were collected. Sensitivity and specificity for the axial-only scans were 75.7 and 94.3 %, respectively, compared with 88.3 and 98.3 % for reformat added. There was a 24.3 % false negative (missed SDH) rate with axial-only scans versus 11.7 % with reformat added (p = <0.001). Median reader interpretation times were longer with the addition of reformatted images (125 versus 89 s), but this difference was not significant (p = 0.23). The addition of coronal and sagittal images in trauma brain CT resulted in improved sensitivity and specificity as well as a reduction in SDH false negatives by greater than 50 %. Reformatted images substantially reduce the number of missed SDHs compared with axial images alone.

Image Statistics and the Representation of Material Properties in the Visual Cortex

PubMed Central

Baumgartner, Elisabeth; Gegenfurtner, Karl R.

2016-01-01

We explored perceived material properties (roughness, texturedness, and hardness) with a novel approach that compares perception, image statistics and brain activation, as measured with fMRI. We initially asked participants to rate 84 material images with respect to the above mentioned properties, and then scanned 15 of the participants with fMRI while they viewed the material images. The images were analyzed with a set of image statistics capturing their spatial frequency and texture properties. Linear classifiers were then applied to the image statistics as well as the voxel patterns of visually responsive voxels and early visual areas to discriminate between images with high and low perceptual ratings. Roughness and texturedness could be classified above chance level based on image statistics. Roughness and texturedness could also be classified based on the brain activation patterns in visual cortex, whereas hardness could not. Importantly, the agreement in classification based on image statistics and brain activation was also above chance level. Our results show that information about visual material properties is to a large degree contained in low-level image statistics, and that these image statistics are also partially reflected in brain activity patterns induced by the perception of material images. PMID:27582714

Image Statistics and the Representation of Material Properties in the Visual Cortex.

PubMed

Baumgartner, Elisabeth; Gegenfurtner, Karl R

2016-01-01

We explored perceived material properties (roughness, texturedness, and hardness) with a novel approach that compares perception, image statistics and brain activation, as measured with fMRI. We initially asked participants to rate 84 material images with respect to the above mentioned properties, and then scanned 15 of the participants with fMRI while they viewed the material images. The images were analyzed with a set of image statistics capturing their spatial frequency and texture properties. Linear classifiers were then applied to the image statistics as well as the voxel patterns of visually responsive voxels and early visual areas to discriminate between images with high and low perceptual ratings. Roughness and texturedness could be classified above chance level based on image statistics. Roughness and texturedness could also be classified based on the brain activation patterns in visual cortex, whereas hardness could not. Importantly, the agreement in classification based on image statistics and brain activation was also above chance level. Our results show that information about visual material properties is to a large degree contained in low-level image statistics, and that these image statistics are also partially reflected in brain activity patterns induced by the perception of material images.

Preclinical Characterization of 18F-MK-6240, a Promising PET Tracer for In Vivo Quantification of Human Neurofibrillary Tangles.

PubMed

Hostetler, Eric D; Walji, Abbas M; Zeng, Zhizhen; Miller, Patricia; Bennacef, Idriss; Salinas, Cristian; Connolly, Brett; Gantert, Liza; Haley, Hyking; Holahan, Marie; Purcell, Mona; Riffel, Kerry; Lohith, Talakad G; Coleman, Paul; Soriano, Aileen; Ogawa, Aimie; Xu, Serena; Zhang, Xiaoping; Joshi, Elizabeth; Della Rocca, Joseph; Hesk, David; Schenk, David J; Evelhoch, Jeffrey L

2016-10-01

A PET tracer is desired to help guide the discovery and development of disease-modifying therapeutics for neurodegenerative diseases characterized by neurofibrillary tangles (NFTs), the predominant tau pathology in Alzheimer disease (AD). We describe the preclinical characterization of the NFT PET tracer 18 F-MK-6240. In vitro binding studies were conducted with 3 H-MK-6240 in tissue slices and homogenates from cognitively normal and AD human brain donors to evaluate tracer affinity and selectivity for NFTs. Immunohistochemistry for phosphorylated tau was performed on human brain slices for comparison with 3 H-MK-6240 binding patterns on adjacent brain slices. PET studies were performed with 18 F-MK-6240 in monkeys to evaluate tracer kinetics and distribution in the brain. 18 F-MK-6240 monkey PET studies were conducted after dosing with unlabeled MK-6240 to evaluate tracer binding selectivity in vivo. The 3 H-MK-6240 binding pattern was consistent with the distribution of phosphorylated tau in human AD brain slices. 3 H-MK-6240 bound with high affinity to human AD brain cortex homogenates containing abundant NFTs but bound poorly to amyloid plaque-rich, NFT-poor AD brain homogenates. 3 H-MK-6240 showed no displaceable binding in the subcortical regions of human AD brain slices and in the hippocampus/entorhinal cortex of non-AD human brain homogenates. In monkey PET studies, 18 F-MK-6240 displayed rapid and homogeneous distribution in the brain. The 18 F-MK-6240 volume of distribution stabilized rapidly, indicating favorable tracer kinetics. No displaceable binding was observed in self-block studies in rhesus monkeys, which do not natively express NFTs. Moderate defluorination was observed as skull uptake. 18 F-MK-6240 is a promising PET tracer for the in vivo quantification of NFTs in AD patients. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

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.

Fiber optic in vivo imaging in the mammalian nervous system

PubMed Central

Mehta, Amit D; Jung, Juergen C; Flusberg, Benjamin A; Schnitzer, Mark J

2010-01-01

The compact size, mechanical flexibility, and growing functionality of optical fiber and fiber optic devices are enabling several new modalities for imaging the mammalian nervous system in vivo. Fluorescence microendoscopy is a minimally invasive fiber modality that provides cellular resolution in deep brain areas. Diffuse optical tomography is a non-invasive modality that uses assemblies of fiber optic emitters and detectors on the cranium for volumetric imaging of brain activation. Optical coherence tomography is a sensitive interferometric imaging technique that can be implemented in a variety of fiber based formats and that might allow intrinsic optical detection of brain activity at a high resolution. Miniaturized fiber optic microscopy permits cellular level imaging in the brains of behaving animals. Together, these modalities will enable new uses of imaging in the intact nervous system for both research and clinical applications. PMID:15464896

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.

Dynamic subcellular imaging of cancer cell mitosis in the brain of live mice.

PubMed

Momiyama, Masashi; Suetsugu, Atsushi; Kimura, Hiroaki; Chishima, Takashi; Bouvet, Michael; Endo, Itaru; Hoffman, Robert M

2013-04-01

The ability to visualize cancer cell mitosis and apoptosis in the brain in real time would be of great utility in testing novel therapies. In order to achieve this goal, the cancer cells were labeled with green fluorescent protein (GFP) in the nucleus and red fluorescent protein (RFP) in the cytoplasm, such that mitosis and apoptosis could be clearly imaged. A craniotomy open window was made in athymic nude mice for real-time fluorescence imaging of implanted cancer cells growing in the brain. The craniotomy window was reversibly closed with a skin flap. Mitosis of the individual cancer cells were imaged dynamically in real time through the craniotomy-open window. This model can be used to evaluate brain metastasis and brain cancer at the subcellular level.

Improving Brain Magnetic Resonance Image (MRI) Segmentation via a Novel Algorithm based on Genetic and Regional Growth

PubMed Central

A., Javadpour; A., Mohammadi

2016-01-01

Background Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regional growth. Methods Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer’s disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation. Results By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively. Conclusion The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases. PMID:27672629

Mapping whole-brain activity with cellular resolution by light-sheet microscopy and high-throughput image analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Silvestri, Ludovico; Rudinskiy, Nikita; Paciscopi, Marco; Müllenbroich, Marie Caroline; Costantini, Irene; Sacconi, Leonardo; Frasconi, Paolo; Hyman, Bradley T.; Pavone, Francesco S.

2016-03-01

Mapping neuronal activity patterns across the whole brain with cellular resolution is a challenging task for state-of-the-art imaging methods. Indeed, despite a number of technological efforts, quantitative cellular-resolution activation maps of the whole brain have not yet been obtained. Many techniques are limited by coarse resolution or by a narrow field of view. High-throughput imaging methods, such as light sheet microscopy, can be used to image large specimens with high resolution and in reasonable times. However, the bottleneck is then moved from image acquisition to image analysis, since many TeraBytes of data have to be processed to extract meaningful information. Here, we present a full experimental pipeline to quantify neuronal activity in the entire mouse brain with cellular resolution, based on a combination of genetics, optics and computer science. We used a transgenic mouse strain (Arc-dVenus mouse) in which neurons which have been active in the last hours before brain fixation are fluorescently labelled. Samples were cleared with CLARITY and imaged with a custom-made confocal light sheet microscope. To perform an automatic localization of fluorescent cells on the large images produced, we used a novel computational approach called semantic deconvolution. The combined approach presented here allows quantifying the amount of Arc-expressing neurons throughout the whole mouse brain. When applied to cohorts of mice subject to different stimuli and/or environmental conditions, this method helps finding correlations in activity between different neuronal populations, opening the possibility to infer a sort of brain-wide 'functional connectivity' with cellular resolution.

Using normalization 3D model for automatic clinical brain quantative analysis and evaluation

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Yao, Wei-Jen; Hwang, Wen-Ju; Chung, Being-Tau; Lin, Kang-Ping

2003-05-01

Functional medical imaging, such as PET or SPECT, is capable of revealing physiological functions of the brain, and has been broadly used in diagnosing brain disorders by clinically quantitative analysis for many years. In routine procedures, physicians manually select desired ROIs from structural MR images and then obtain physiological information from correspondent functional PET or SPECT images. The accuracy of quantitative analysis thus relies on that of the subjectively selected ROIs. Therefore, standardizing the analysis procedure is fundamental and important in improving the analysis outcome. In this paper, we propose and evaluate a normalization procedure with a standard 3D-brain model to achieve precise quantitative analysis. In the normalization process, the mutual information registration technique was applied for realigning functional medical images to standard structural medical images. Then, the standard 3D-brain model that shows well-defined brain regions was used, replacing the manual ROIs in the objective clinical analysis. To validate the performance, twenty cases of I-123 IBZM SPECT images were used in practical clinical evaluation. The results show that the quantitative analysis outcomes obtained from this automated method are in agreement with the clinical diagnosis evaluation score with less than 3% error in average. To sum up, the method takes advantage of obtaining precise VOIs, information automatically by well-defined standard 3-D brain model, sparing manually drawn ROIs slice by slice from structural medical images in traditional procedure. That is, the method not only can provide precise analysis results, but also improve the process rate for mass medical images in clinical.

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

Antisense imaging of gene expression in the brain in vivo

NASA Astrophysics Data System (ADS)

Shi, Ningya; Boado, Ruben J.; Pardridge, William M.

2000-12-01

Antisense radiopharmaceuticals could be used to image gene expression in the brain in vivo, should these polar molecules be made transportable through the blood-brain barrier. The present studies describe an antisense imaging agent comprised of an iodinated peptide nucleic acid (PNA) conjugated to a monoclonal antibody to the rat transferrin receptor by using avidin-biotin technology. The PNA was a 16-mer antisense to the sequence around the methionine initiation codon of the luciferase mRNA. C6 rat glioma cells were permanently transfected with a luciferase expression plasmid, and C6 experimental brain tumors were developed in adult rats. The expression of the luciferase transgene in the tumors in vivo was confirmed by measurement of luciferase enzyme activity in the tumor extract. The [125I]PNA conjugate was injected intravenously in anesthetized animals with brain tumors and killed 2 h later for frozen sectioning of brain and film autoradiography. No image of the luciferase gene expression was obtained after the administration of either the unconjugated antiluciferase PNA or a PNA conjugate that was antisense to the mRNA of a viral transcript. In contrast, tumors were imaged in all rats administered the [125I]PNA that was antisense to the luciferase sequence and was conjugated to the targeting antibody. In conclusion, these studies demonstrate gene expression in the brain in vivo can be imaged with antisense radiopharmaceuticals that are conjugated to a brain drug-targeting system.

Quantitative Machine Learning Analysis of Brain MRI Morphology throughout Aging.

PubMed

Shamir, Lior; Long, Joe

2016-01-01

While cognition is clearly affected by aging, it is unclear whether the process of brain aging is driven solely by accumulation of environmental damage, or involves biological pathways. We applied quantitative image analysis to profile the alteration of brain tissues during aging. A dataset of 463 brain MRI images taken from a cohort of 416 subjects was analyzed using a large set of low-level numerical image content descriptors computed from the entire brain MRI images. The correlation between the numerical image content descriptors and the age was computed, and the alterations of the brain tissues during aging were quantified and profiled using machine learning. The comprehensive set of global image content descriptors provides high Pearson correlation of ~0.9822 with the chronological age, indicating that the machine learning analysis of global features is sensitive to the age of the subjects. Profiling of the predicted age shows several periods of mild changes, separated by shorter periods of more rapid alterations. The periods with the most rapid changes were around the age of 55, and around the age of 65. The results show that the process of brain aging of is not linear, and exhibit short periods of rapid aging separated by periods of milder change. These results are in agreement with patterns observed in cognitive decline, mental health status, and general human aging, suggesting that brain aging might not be driven solely by accumulation of environmental damage. Code and data used in the experiments are publicly available.

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.

Volumetric spiral chemical shift imaging of hyperpolarized [2-(13) c]pyruvate in a rat c6 glioma model.

PubMed

Park, Jae Mo; Josan, Sonal; Jang, Taichang; Merchant, Milton; Watkins, Ron; Hurd, Ralph E; Recht, Lawrence D; Mayer, Dirk; Spielman, Daniel M

2016-03-01

MRS of hyperpolarized [2-(13)C]pyruvate can be used to assess multiple metabolic pathways within mitochondria as the (13)C label is not lost with the conversion of pyruvate to acetyl-CoA. This study presents the first MR spectroscopic imaging of hyperpolarized [2-(13)C]pyruvate in glioma-bearing brain. Spiral chemical shift imaging with spectrally undersampling scheme (1042 Hz) and a hard-pulse excitation was exploited to simultaneously image [2-(13)C]pyruvate, [2-(13)C]lactate, and [5-(13)C]glutamate, the metabolites known to be produced in brain after an injection of hyperpolarized [2-(13)C]pyruvate, without chemical shift displacement artifacts. A separate undersampling scheme (890 Hz) was also used to image [1-(13)C]acetyl-carnitine. Healthy and C6 glioma-implanted rat brains were imaged at baseline and after dichloroacetate administration, a drug that modulates pyruvate dehydrogenase kinase activity. The baseline metabolite maps showed higher lactate and lower glutamate in tumor as compared to normal-appearing brain. Dichloroacetate led to an increase in glutamate in both tumor and normal-appearing brain. Dichloroacetate-induced %-decrease of lactate/glutamate was comparable to the lactate/bicarbonate decrease from hyperpolarized [1-(13)C]pyruvate studies. Acetyl-carnitine was observed in the muscle/fat tissue surrounding the brain. Robust volumetric imaging with hyperpolarized [2-(13)C]pyruvate and downstream products was performed in glioma-bearing rat brains, demonstrating changes in mitochondrial metabolism with dichloroacetate. © 2015 Wiley Periodicals, Inc.

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.

Novel region of interest interrogation technique for diffusion tensor imaging analysis in the canine brain.

PubMed

Li, Jonathan Y; Middleton, Dana M; Chen, Steven; White, Leonard; Ellinwood, N Matthew; Dickson, Patricia; Vite, Charles; Bradbury, Allison; Provenzale, James M

2017-08-01

Purpose We describe a novel technique for measuring diffusion tensor imaging metrics in the canine brain. We hypothesized that a standard method for region of interest placement could be developed that is highly reproducible, with less than 10% difference in measurements between raters. Methods Two sets of canine brains (three seven-week-old full-brains and two 17-week-old single hemispheres) were scanned ex-vivo on a 7T small-animal magnetic resonance imaging system. Strict region of interest placement criteria were developed and then used by two raters to independently measure diffusion tensor imaging metrics within four different white-matter regions within each specimen. Average values of fractional anisotropy, radial diffusivity, and the three eigenvalues (λ1, λ2, and λ3) within each region in each specimen overall and within each individual image slice were compared between raters by calculating the percentage difference between raters for each metric. Results The mean percentage difference between raters for all diffusion tensor imaging metrics when pooled by each region and specimen was 1.44% (range: 0.01-5.17%). The mean percentage difference between raters for all diffusion tensor imaging metrics when compared by individual image slice was 2.23% (range: 0.75-4.58%) per hemisphere. Conclusion Our results indicate that the technique described is highly reproducible, even when applied to canine specimens of differing age, morphology, and image resolution. We propose this technique for future studies of diffusion tensor imaging analysis in canine brains and for cross-sectional and longitudinal studies of canine brain models of human central nervous system disease.

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

NASA Astrophysics Data System (ADS)

Bumstead, Jonathan R.

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

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

PubMed Central

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

[(18)F]-fluorodeoxyglucose positron emission tomography of the cat brain: A feasibility study to investigate osteoarthritis-associated pain.

PubMed

Guillot, Martin; Chartrand, Gabriel; Chav, Ramnada; Rousseau, Jacques; Beaudoin, Jean-François; Martel-Pelletier, Johanne; Pelletier, Jean-Pierre; Lecomte, Roger; de Guise, Jacques A; Troncy, Eric

2015-06-01

The objective of this pilot study was to investigate central nervous system (CNS) changes related to osteoarthritis (OA)-associated chronic pain in cats using [(18)F]-fluorodeoxyglucose ((18)FDG) positron emission tomography (PET) imaging. The brains of five normal, healthy (non-OA) cats and seven cats with pain associated with naturally occurring OA were imaged using (18)FDG-PET during a standardized mild anesthesia protocol. The PET images were co-registered over a magnetic resonance image of a cat brain segmented into several regions of interest. Brain metabolism was assessed in these regions using standardized uptake values. The brain metabolism in the secondary somatosensory cortex, thalamus and periaqueductal gray matter was increased significantly (P ≤ 0.005) in OA cats compared with non-OA cats. This study indicates that (18)FDG-PET brain imaging in cats is feasible to investigate CNS changes related to chronic pain. The results also suggest that OA is associated with sustained nociceptive inputs and increased activity of the descending modulatory pathways. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fluorescence laminar optical tomography for brain imaging: system implementation and performance evaluation.

PubMed

Azimipour, Mehdi; Sheikhzadeh, Mahya; Baumgartner, Ryan; Cullen, Patrick K; Helmstetter, Fred J; Chang, Woo-Jin; Pashaie, Ramin

2017-01-01

We present our effort in implementing a fluorescence laminar optical tomography scanner which is specifically designed for noninvasive three-dimensional imaging of fluorescence proteins in the brains of small rodents. A laser beam, after passing through a cylindrical lens, scans the brain tissue from the surface while the emission signal is captured by the epi-fluorescence optics and is recorded using an electron multiplication CCD sensor. Image reconstruction algorithms are developed based on Monte Carlo simulation to model light–tissue interaction and generate the sensitivity matrices. To solve the inverse problem, we used the iterative simultaneous algebraic reconstruction technique. The performance of the developed system was evaluated by imaging microfabricated silicon microchannels embedded inside a substrate with optical properties close to the brain as a tissue phantom and ultimately by scanning brain tissue in vivo. Details of the hardware design and reconstruction algorithms are discussed and several experimental results are presented. The developed system can specifically facilitate neuroscience experiments where fluorescence imaging and molecular genetic methods are used to study the dynamics of the brain circuitries.

Evaluation of 177Lu[Lu]-CHX-A″-DTPA-6A10 Fab as a radioimmunotherapy agent targeting carbonic anhydrase XII.

PubMed

Fiedler, L; Kellner, M; Gosewisch, A; Oos, R; Böning, G; Lindner, S; Albert, N; Bartenstein, P; Reulen, H-J; Zeidler, R; Gildehaus, F J

2018-05-01

Due to their infiltrative growth behavior, gliomas have, even after surgical resection, a high recurrence tendency. The approach of intracavitary radioimmunotherapy (RIT) is aimed at inhibiting tumor re-growth by directly administering drugs into the resection cavity (RC). Direct application of the radioconjugate into the RC has the advantage of bypassing the blood-brain barrier, which allows the administration of higher radiation doses than systemic application. Carbonic anhydrase XII (CA XII) is highly expressed on glioma cells while being absent from normal brain and thus an attractive target molecule for RIT. We evaluated a CA XII-specific 6A10 Fab (fragment antigen binding) labelled with 177 Lu as an agent for RIT. 6A10 Fab fragment was modified and radiolabelled with 177 Lu and characterized by MALDI-TOF, flow cytometry and radio-TLC. In vitro stability was determined under physiological conditions. Biodistribution studies, autoradiography tumor examinations and planar scintigraphy imaging were performed on SCID-mice bearing human glioma xenografts. The in vitro CA XII binding capacity of the modified Fab was confirmed. Radiochemical purity was determined to be >90% after 72 h of incubation under physiological conditions. Autoradiography experiments proved the specific binding of the Fab to CA XII on tumor cells. Biodistribution studies revealed a tumor uptake of 3.0%ID/g after 6 h and no detectable brain uptake. The tumor-to-contralateral ratio of 10/1 was confirmed by quantitative planar scintigraphy. The radiochemical stability in combination with a successful in vivo tumor uptake shows the potential suitability for future RIT applications with the 6A10 Fab. Copyright © 2018 Elsevier Inc. All rights reserved.

Brain Structure and Executive Functions in Children with Cerebral Palsy: A Systematic Review

ERIC Educational Resources Information Center

Weierink, Lonneke; Vermeulen, R. Jeroen; Boyd, Roslyn N.

2013-01-01

This systematic review aimed to establish the current knowledge about brain structure and executive function (EF) in children with cerebral palsy (CP). Five databases were searched (up till July 2012). Six articles met the inclusion criteria, all included structural brain imaging though no functional brain imaging. Study quality was assessed using…

Full-frame video stabilization with motion inpainting.

PubMed

Matsushita, Yasuyuki; Ofek, Eyal; Ge, Weina; Tang, Xiaoou; Shum, Heung-Yeung

2006-07-01

Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. We propose a practical and robust approach of video stabilization that produces full-frame stabilized videos with good visual quality. While most previous methods end up with producing smaller size stabilized videos, our completion method can produce full-frame videos by naturally filling in missing image parts by locally aligning image data of neighboring frames. To achieve this, motion inpainting is proposed to enforce spatial and temporal consistency of the completion in both static and dynamic image areas. In addition, image quality in the stabilized video is enhanced with a new practical deblurring algorithm. Instead of estimating point spread functions, our method transfers and interpolates sharper image pixels of neighboring frames to increase the sharpness of the frame. The proposed video completion and deblurring methods enabled us to develop a complete video stabilizer which can naturally keep the original image quality in the stabilized videos. The effectiveness of our method is confirmed by extensive experiments over a wide variety of videos.

Diagnostic imaging of traumatic brain injury.

PubMed

Furlow, Bryant

2006-01-01

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

Investigating MALDI MSI parameters (Part 2) - On the use of a mechanically shuttered trigger system for improved laser energy stability.

PubMed

Steven, Rory T; Dexter, Alex; Bunch, Josephine

2016-07-15

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is now widely used to desorb, ionize and detect molecules from complex samples and tissue sections. The detected ion intensity within MALDI MS and MSI is intimately linked to the laser energy per pulse incident upon the sample during analysis. Laser energy/power stability can be significantly affected by the manner in which the laser is operated. High-repetition rate diode-pumped solid-state (DPSS) lasers are being increasingly adopted to enable high-throughput MALDI MSI analysis. Within this work two different laser-triggering setups are used to demonstrate the effect of laser energy instabilities due to spiking and thermal control phenomena and a setup with a shutter to remove these effects. The effect of non-equilibrium laser operation on MALDI MSI data versus the more stable laser pulse energy of the shutter-triggered system is demonstrated in thin films of α-cyano-4-hydroxycinnamic acid (CHCA) and for imaging of murine brain tissue sections. Significant unwanted variations in absolute and relative detected ion intensity are shown where energy variation is introduced by these phenomena, which return to equilibrium within the setup employed here over timescales relevant to MALDI MS analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Medical aspects of pediatric rehabilitation after moderate to severe traumatic brain injury.

PubMed

Cantore, Lisa; Norwood, Kenneth; Patrick, Peter

2012-01-01

Recovery from severe traumatic brain injury (TBI) is prolonged, complicated and challenging. Medical rehabilitation is the bridge from acute medical care and stabilization to community reintegration. The process of caring for the recovering brain introduces unknown challenges of neural plasticity with demands to restore and to also move the child and family back to the developmental trajectory they once knew. While the ongoing focus is to maintain and advance medical stability, co- morbid conditions are addressed, and a plan for ongoing health is established. While no one manuscript can cover all of the medical aspects, this article will present in a "systems review" manner the most challenging and demanding medical conditions that children may confront following severe brain injury.

Magnetic resonance imaging of blood-brain barrier permeability in ischemic stroke using diffusion-weighted arterial spin labeling in rats.

PubMed

Tiwari, Yash V; Lu, Jianfei; Shen, Qiang; Cerqueira, Bianca; Duong, Timothy Q

2017-08-01

Diffusion-weighted arterial spin labeling magnetic resonance imaging has recently been proposed to quantify the rate of water exchange (K w ) across the blood-brain barrier in humans. This study aimed to evaluate the blood-brain barrier disruption in transient (60 min) ischemic stroke using K w magnetic resonance imaging with cross-validation by dynamic contrast-enhanced magnetic resonance imaging and Evans blue histology in the same rats. The major findings were: (i) at 90 min after stroke (30 min after reperfusion), group K w magnetic resonance imaging data showed no significant blood-brain barrier permeability changes, although a few animals showed slightly abnormal K w . Dynamic contrast-enhanced magnetic resonance imaging confirmed this finding in the same animals. (ii) At two days after stroke, K w magnetic resonance imaging revealed significant blood-brain barrier disruption. Regions with abnormal K w showed substantial overlap with regions of hyperintense T 2 (vasogenic edema) and hyperperfusion. Dynamic contrast-enhanced magnetic resonance imaging and Evans blue histology confirmed these findings in the same animals. The K w values in the normal contralesional hemisphere and the ipsilesional ischemic core two days after stroke were: 363 ± 17 and 261 ± 18 min -1 , respectively (P < 0.05, n = 9). K w magnetic resonance imaging is sensitive to blood-brain barrier permeability changes in stroke, consistent with dynamic contrast-enhanced magnetic resonance imaging and Evans blue extravasation. K w magnetic resonance imaging offers advantages over existing techniques because contrast agent is not needed and repeated measurements can be made for longitudinal monitoring or averaging.

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

PubMed

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

2009-08-01

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

Wireless image-data transmission from an implanted image sensor through a living mouse brain by intra body communication

NASA Astrophysics Data System (ADS)

Hayami, Hajime; Takehara, Hiroaki; Nagata, Kengo; Haruta, Makito; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Ohta, Jun

2016-04-01

Intra body communication technology allows the fabrication of compact implantable biomedical sensors compared with RF wireless technology. In this paper, we report the fabrication of an implantable image sensor of 625 µm width and 830 µm length and the demonstration of wireless image-data transmission through a brain tissue of a living mouse. The sensor was designed to transmit output signals of pixel values by pulse width modulation (PWM). The PWM signals from the sensor transmitted through a brain tissue were detected by a receiver electrode. Wireless data transmission of a two-dimensional image was successfully demonstrated in a living mouse brain. The technique reported here is expected to provide useful methods of data transmission using micro sized implantable biomedical sensors.

New Clinically Feasible 3T MRI Protocol to Discriminate Internal Brain Stem Anatomy.

PubMed

Hoch, M J; Chung, S; Ben-Eliezer, N; Bruno, M T; Fatterpekar, G M; Shepherd, T M

2016-06-01

Two new 3T MR imaging contrast methods, track density imaging and echo modulation curve T2 mapping, were combined with simultaneous multisection acquisition to reveal exquisite anatomic detail at 7 canonical levels of the brain stem. Compared with conventional MR imaging contrasts, many individual brain stem tracts and nuclear groups were directly visualized for the first time at 3T. This new approach is clinically practical and feasible (total scan time = 20 minutes), allowing better brain stem anatomic localization and characterization. © 2016 by American Journal of Neuroradiology.

Region specific optimization of continuous linear attenuation coefficients based on UTE (RESOLUTE): application to PET/MR brain imaging

NASA Astrophysics Data System (ADS)

Ladefoged, Claes N.; Benoit, Didier; Law, Ian; Holm, Søren; Kjær, Andreas; Højgaard, Liselotte; Hansen, Adam E.; Andersen, Flemming L.

2015-10-01

The reconstruction of PET brain data in a PET/MR hybrid scanner is challenging in the absence of transmission sources, where MR images are used for MR-based attenuation correction (MR-AC). The main challenge of MR-AC is to separate bone and air, as neither have a signal in traditional MR images, and to assign the correct linear attenuation coefficient to bone. The ultra-short echo time (UTE) MR sequence was proposed as a basis for MR-AC as this sequence shows a small signal in bone. The purpose of this study was to develop a new clinically feasible MR-AC method with patient specific continuous-valued linear attenuation coefficients in bone that provides accurate reconstructed PET image data. A total of 164 [18F]FDG PET/MR patients were included in this study, of which 10 were used for training. MR-AC was based on either standard CT (reference), UTE or our method (RESOLUTE). The reconstructed PET images were evaluated in the whole brain, as well as regionally in the brain using a ROI-based analysis. Our method segments air, brain, cerebral spinal fluid, and soft tissue voxels on the unprocessed UTE TE images, and uses a mapping of R2* values to CT Hounsfield Units (HU) to measure the density in bone voxels. The average error of our method in the brain was 0.1% and less than 1.2% in any region of the brain. On average 95% of the brain was within  ±10% of PETCT, compared to 72% when using UTE. The proposed method is clinically feasible, reducing both the global and local errors on the reconstructed PET images, as well as limiting the number and extent of the outliers.

Ethanol fixed brain imaging by phase-contrast X-ray technique

NASA Astrophysics Data System (ADS)

Takeda, Tohoru; Thet-Thet-Lwin; Kunii, Takuya; Sirai, Ryota; Ohizumi, Takahito; Maruyama, Hiroko; Hyodo, Kazuyuki; Yoneyama, Akio; Ueda, Kazuhiro

2013-03-01

The two-crystal phase-contrast X-ray imaging technique using an X-ray crystal interferometer can depict the fine structures of rat's brain such as cerebral cortex, white matter, and basal ganglia. Image quality and contrast by ethanol fixed brain showed significantly better than those by usually used formalin fixation at 35 keV X-ray energy. Image contrast of cortex by ethanol fixation was more than 3-times higher than that by formalin fixation. Thus, the technique of ethanol fixation might be better suited to image cerebral structural detail at 35 keV X-ray energy.

Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration

PubMed Central

Blinowska, Katarzyna; Müller-Putz, Gernot; Kaiser, Vera; Astolfi, Laura; Vanderperren, Katrien; Van Huffel, Sabine; Lemieux, Louis

2009-01-01

Until relatively recently the vast majority of imaging and electrophysiological studies of human brain activity have relied on single-modality measurements usually correlated with readily observable or experimentally modified behavioural or brain state patterns. Multi-modal imaging is the concept of bringing together observations or measurements from different instruments. We discuss the aims of multi-modal imaging and the ways in which it can be accomplished using representative applications. Given the importance of haemodynamic and electrophysiological signals in current multi-modal imaging applications, we also review some of the basic physiology relevant to understanding their relationship. PMID:19547657

Image registration of naval IR images

NASA Astrophysics Data System (ADS)

Rodland, Arne J.

1996-06-01

In a real world application an image from a stabilized sensor on a moving platform will not be 100 percent stabilized. There will always be a small unknown error in the stabilization due to factors such as dynamic deformations in the structure between sensor and reference Inertial Navigation Unit, servo inaccuracies, etc. For a high resolution imaging sensor this stabilization error causes the image to move several pixels in unknown direction between frames. TO be able to detect and track small moving objects from such a sensor, this unknown movement of the sensor image must be estimated. An algorithm that searches for land contours in the image has been evaluated. The algorithm searches for high contrast points distributed over the whole image. As long as moving objects in the scene only cover a small area of the scene, most of the points are located on solid ground. By matching the list of points from frame to frame, the movement of the image due to stabilization errors can be estimated and compensated. The point list is searched for points with diverging movement from the estimated stabilization error. These points are then assumed to be located on moving objects. Points assumed to be located on moving objects are gradually exchanged with new points located in the same area. Most of the processing is performed on the list of points and not on the complete image. The algorithm is therefore very fast and well suited for real time implementation. The algorithm has been tested on images from an experimental IR scanner. Stabilization errors were added artificially to the image such that the output from the algorithm could be compared with the artificially added stabilization errors.

Loss of Consciousness Is Associated with Stabilization of Cortical Activity

PubMed Central

Solovey, Guillermo; Alonso, Leandro M.; Yanagawa, Toru; Fujii, Naotaka; Magnasco, Marcelo O.; Cecchi, Guillermo A.

2015-01-01

What aspects of neuronal activity distinguish the conscious from the unconscious brain? This has been a subject of intense interest and debate since the early days of neurophysiology. However, as any practicing anesthesiologist can attest, it is currently not possible to reliably distinguish a conscious state from an unconscious one on the basis of brain activity. Here we approach this problem from the perspective of dynamical systems theory. We argue that the brain, as a dynamical system, is self-regulated at the boundary between stable and unstable regimes, allowing it in particular to maintain high susceptibility to stimuli. To test this hypothesis, we performed stability analysis of high-density electrocorticography recordings covering an entire cerebral hemisphere in monkeys during reversible loss of consciousness. We show that, during loss of consciousness, the number of eigenmodes at the edge of instability decreases smoothly, independently of the type of anesthetic and specific features of brain activity. The eigenmodes drift back toward the unstable line during recovery of consciousness. Furthermore, we show that stability is an emergent phenomenon dependent on the correlations among activity in different cortical regions rather than signals taken in isolation. These findings support the conclusion that dynamics at the edge of instability are essential for maintaining consciousness and provide a novel and principled measure that distinguishes between the conscious and the unconscious brain. SIGNIFICANCE STATEMENT What distinguishes brain activity during consciousness from that observed during unconsciousness? Answering this question has proven difficult because neither consciousness nor lack thereof have universal signatures in terms of most specific features of brain activity. For instance, different anesthetics induce different patterns of brain activity. We demonstrate that loss of consciousness is universally and reliably associated with stabilization of cortical dynamics regardless of the specific activity characteristics. To give an analogy, our analysis suggests that loss of consciousness is akin to depressing the damper pedal on the piano, which makes the sounds dissipate quicker regardless of the specific melody being played. This approach may prove useful in detecting consciousness on the basis of brain activity under anesthesia and other settings. PMID:26224868

Loss of Consciousness Is Associated with Stabilization of Cortical Activity.

PubMed

Solovey, Guillermo; Alonso, Leandro M; Yanagawa, Toru; Fujii, Naotaka; Magnasco, Marcelo O; Cecchi, Guillermo A; Proekt, Alex

2015-07-29

What aspects of neuronal activity distinguish the conscious from the unconscious brain? This has been a subject of intense interest and debate since the early days of neurophysiology. However, as any practicing anesthesiologist can attest, it is currently not possible to reliably distinguish a conscious state from an unconscious one on the basis of brain activity. Here we approach this problem from the perspective of dynamical systems theory. We argue that the brain, as a dynamical system, is self-regulated at the boundary between stable and unstable regimes, allowing it in particular to maintain high susceptibility to stimuli. To test this hypothesis, we performed stability analysis of high-density electrocorticography recordings covering an entire cerebral hemisphere in monkeys during reversible loss of consciousness. We show that, during loss of consciousness, the number of eigenmodes at the edge of instability decreases smoothly, independently of the type of anesthetic and specific features of brain activity. The eigenmodes drift back toward the unstable line during recovery of consciousness. Furthermore, we show that stability is an emergent phenomenon dependent on the correlations among activity in different cortical regions rather than signals taken in isolation. These findings support the conclusion that dynamics at the edge of instability are essential for maintaining consciousness and provide a novel and principled measure that distinguishes between the conscious and the unconscious brain. What distinguishes brain activity during consciousness from that observed during unconsciousness? Answering this question has proven difficult because neither consciousness nor lack thereof have universal signatures in terms of most specific features of brain activity. For instance, different anesthetics induce different patterns of brain activity. We demonstrate that loss of consciousness is universally and reliably associated with stabilization of cortical dynamics regardless of the specific activity characteristics. To give an analogy, our analysis suggests that loss of consciousness is akin to depressing the damper pedal on the piano, which makes the sounds dissipate quicker regardless of the specific melody being played. This approach may prove useful in detecting consciousness on the basis of brain activity under anesthesia and other settings. Copyright © 2015 the authors 0270-6474/15/3510866-12$15.00/0.

Functional Magnetic Resonance Imaging and Spectroscopic Imaging of the Brain: Application of fMRI and fMRS to Reading Disabilities and Education.

ERIC Educational Resources Information Center

Richards, Todd L.

2001-01-01

This tutorial/review covers functional brain-imaging methods and results used to study language and reading disabilities. Although the emphasis is on magnetic resonance imaging and functional magnetic resonance spectroscopy, other imaging techniques are also discussed including positron emission tomography, electroencephalography,…

Magnetic resonance imaging spectrum of perinatal hypoxic-ischemic brain injury

PubMed Central

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

2016-01-01

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

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.

Diattenuation of brain tissue and its impact on 3D polarized light imaging

PubMed Central

Menzel, Miriam; Reckfort, Julia; Weigand, Daniel; Köse, Hasan; Amunts, Katrin; Axer, Markus

2017-01-01

3D-polarized light imaging (3D-PLI) reconstructs nerve fibers in histological brain sections by measuring their birefringence. This study investigates another effect caused by the optical anisotropy of brain tissue – diattenuation. Based on numerical and experimental studies and a complete analytical description of the optical system, the diattenuation was determined to be below 4 % in rat brain tissue. It was demonstrated that the diattenuation effect has negligible impact on the fiber orientations derived by 3D-PLI. The diattenuation signal, however, was found to highlight different anatomical structures that cannot be distinguished with current imaging techniques, which makes Diattenuation Imaging a promising extension to 3D-PLI. PMID:28717561

Childhood neglect predicts disorganization in schizophrenia through grey matter decrease in dorsolateral prefrontal cortex.

PubMed

Cancel, A; Comte, M; Truillet, R; Boukezzi, S; Rousseau, P-F; Zendjidjian, X Y; Sage, T; Lazerges, P-E; Guedj, E; Khalfa, S; Azorin, J-M; Blin, O; Fakra, E

2015-10-01

Psychosocial trauma during childhood is associated with schizophrenia vulnerability. The pattern of grey matter decrease is similar to brain alterations seen in schizophrenia. Our objective was to explore the links between childhood trauma, brain morphology and schizophrenia symptoms. Twenty-one patients with schizophrenia stabilized with atypical antipsychotic monotherapy and 30 healthy control subjects completed the study. Anatomical MRI images were analysed using optimized voxel-based morphometry (VBM). Childhood trauma was assessed with the Childhood Trauma Questionnaire, and symptoms were rated on the Scale for the Assessment of Negative Symptoms (SANS) and Scale for the Assessment of Positive Symptoms (SAPS) (disorganization, positive and negative symptoms). In the schizophrenia group, we used structural equation modelling in a path analysis. Total grey matter volume was negatively associated with emotional neglect (EN) in patients with schizophrenia. Whole-brain VBM analyses of grey matter in the schizophrenia group revealed a specific inversed association between EN and the right dorsolateral prefrontal cortex (DLPFC). Path analyses identified a well-fitted model in which EN predicted grey matter density in DLPFC, which in turn predicted the disorganization score. Our findings suggest that EN during childhood could have an impact on psychopathology in schizophrenia, which would be mediated by developmental effects on brain regions such as the DLPFC. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Cortical Enhanced Tissue Segmentation of Neonatal Brain MR Images Acquired by a Dedicated Phased Array Coil

PubMed Central

Shi, Feng; Yap, Pew-Thian; Fan, Yong; Cheng, Jie-Zhi; Wald, Lawrence L.; Gerig, Guido; Lin, Weili; Shen, Dinggang

2010-01-01

The acquisition of high quality MR images of neonatal brains is largely hampered by their characteristically small head size and low tissue contrast. As a result, subsequent image processing and analysis, especially for brain tissue segmentation, are often hindered. To overcome this problem, a dedicated phased array neonatal head coil is utilized to improve MR image quality by effectively combing images obtained from 8 coil elements without lengthening data acquisition time. In addition, a subject-specific atlas based tissue segmentation algorithm is specifically developed for the delineation of fine structures in the acquired neonatal brain MR images. The proposed tissue segmentation method first enhances the sheet-like cortical gray matter (GM) structures in neonatal images with a Hessian filter for generation of cortical GM prior. Then, the prior is combined with our neonatal population atlas to form a cortical enhanced hybrid atlas, which we refer to as the subject-specific atlas. Various experiments are conducted to compare the proposed method with manual segmentation results, as well as with additional two population atlas based segmentation methods. Results show that the proposed method is capable of segmenting the neonatal brain with the highest accuracy, compared to other two methods. PMID:20862268

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

Missouri University Multi-Plane Imager (MUMPI): A high sensitivity rapid dynamic ECT brain imager

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

Logan, K.W.; Holmes, R.A.

1984-01-01

The authors have designed a unique ECT imaging device that can record rapid dynamic images of brain perfusion. The Missouri University Multi-Plane Imager (MUMPI) uses a single crystal detector that produces four orthogonal two-dimensional images simultaneously. Multiple slice images are reconstructed from counts recorded from stepwise or continuous collimator rotation. Four simultaneous 2-d image fields may also be recorded and reviewed. The cylindrical sodium iodide crystal and the rotating collimator concentrically surround the source volume being imaged with the collimator the only moving part. The design and function parameters of MUMPI have been compared to other competitive tomographic head imagingmore » devices. MUMPI's principal advantages are: 1) simultaneous direct acquisition of four two-dimensional images; 2) extremely rapid project set acquisition for ECT reconstruction; and 3) instrument practicality and economy due to single detector design and the absence of heavy mechanical moving components (only collimator rotation is required). MUMPI should be ideal for imaging neutral lipophilic chelates such as Tc-99m-PnAO which passively diffuses across the intact blood-brain-barrier and rapidly clears from brain tissue.« less

Multiresolution MR elastography using nonlinear inversion

PubMed Central

McGarry, M. D. J.; Van Houten, E. E. W.; Johnson, C. L.; Georgiadis, J. G.; Sutton, B. P.; Weaver, J. B.; Paulsen, K. D.

2012-01-01

Purpose: Nonlinear inversion (NLI) in MR elastography requires discretization of the displacement field for a finite element (FE) solution of the “forward problem”, and discretization of the unknown mechanical property field for the iterative solution of the “inverse problem”. The resolution requirements for these two discretizations are different: the forward problem requires sufficient resolution of the displacement FE mesh to ensure convergence, whereas lowering the mechanical property resolution in the inverse problem stabilizes the mechanical property estimates in the presence of measurement noise. Previous NLI implementations use the same FE mesh to support the displacement and property fields, requiring a trade-off between the competing resolution requirements. Methods: This work implements and evaluates multiresolution FE meshes for NLI elastography, allowing independent discretizations of the displacements and each mechanical property parameter to be estimated. The displacement resolution can then be selected to ensure mesh convergence, and the resolution of the property meshes can be independently manipulated to control the stability of the inversion. Results: Phantom experiments indicate that eight nodes per wavelength (NPW) are sufficient for accurate mechanical property recovery, whereas mechanical property estimation from 50 Hz in vivo brain data stabilizes once the displacement resolution reaches 1.7 mm (approximately 19 NPW). Viscoelastic mechanical property estimates of in vivo brain tissue show that subsampling the loss modulus while holding the storage modulus resolution constant does not substantially alter the storage modulus images. Controlling the ratio of the number of measurements to unknown mechanical properties by subsampling the mechanical property distributions (relative to the data resolution) improves the repeatability of the property estimates, at a cost of modestly decreased spatial resolution. Conclusions: Multiresolution NLI elastography provides a more flexible framework for mechanical property estimation compared to previous single mesh implementations. PMID:23039674

Image Registration for Stability Testing of MEMS

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; LeMoigne, Jacqueline; Blake, Peter N.; Morey, Peter A.; Landsman, Wayne B.; Chambers, Victor J.; Moseley, Samuel H.

2011-01-01

Image registration, or alignment of two or more images covering the same scenes or objects, is of great interest in many disciplines such as remote sensing, medical imaging. astronomy, and computer vision. In this paper, we introduce a new application of image registration algorithms. We demonstrate how through a wavelet based image registration algorithm, engineers can evaluate stability of Micro-Electro-Mechanical Systems (MEMS). In particular, we applied image registration algorithms to assess alignment stability of the MicroShutters Subsystem (MSS) of the Near Infrared Spectrograph (NIRSpec) instrument of the James Webb Space Telescope (JWST). This work introduces a new methodology for evaluating stability of MEMS devices to engineers as well as a new application of image registration algorithms to computer scientists.

MRI-Based Measurement of Brain Stem Cross-Sectional Area in Relapsing-Remitting Multiple Sclerosis.

PubMed

Chivers, Tomos R; Constantinescu, Cris S; Tench, Christopher R

2015-01-01

To determine if patients with relapsing-remitting multiple sclerosis (RRMS) have a reduced brain stem cross-sectional area (CSA) compared to age- and sex-matched controls. The brain stem is a common site of involvement in MS. However, relatively few imaging studies have investigated brain stem atrophy. Brain magnetic resonance imaging (MRI) was performed on patients and controls using a 1.5T MRI scanner with a quadrature head coil. Three-dimensional magnetization-prepared rapid acquisition gradient-echo (MPRAGE) images with 128 contiguous slices, covering the whole brain and brain stem and a T2-weighted image with 3 mm transverse contiguous images were acquired. We measured the brain stem CSA at three sites, the midbrain, the pons, and the medulla oblongata in 35 RRMS patients and 35 controls using a semiautomated algorithm. CSA readings were normalized using the total external cranial volume to reduce normal population variance and increase statistical power. A significant CSA reduction was found in the midbrain (P ≤ .001), pons (P ≤ .001), and the medulla oblongata (P = .047) postnormalization. A CSA reduction of 9.3% was found in the midbrain, 8.7% in the pons, and 6.5% in the medulla oblongata. A significantly reduced, normalized brain stem CSA was detected in all areas of the brain stem of the RRMS patients, when compared to age- and gender-matched controls. Lack of detectable upper cervical cord atrophy in the same patients suggests some independence of the MS pathology in these regions. Copyright © 2015 by the American Society of Neuroimaging.

Fetal brain disruption sequence versus fetal brain arrest: A distinct autosomal recessive developmental brain malformation phenotype.

PubMed

Abdel-Salam, Ghada M H; Abdel-Hamid, Mohamed S; El-Khayat, Hamed A; Eid, Ola M; Saba, Soliman; Farag, Mona K; Saleem, Sahar N; Gaber, Khaled R

2015-05-01

The term fetal brain disruption sequence (FBDS) was coined to describe a number of sporadic conditions caused by numerous external disruptive events presenting with variable imaging findings. However, rare familial occurrences have been reported. We describe five patients (two sib pairs and one sporadic) with congenital severe microcephaly, seizures, and profound intellectual disability. Brain magnetic resonance imaging (MRI) revealed unique and uniform picture of underdeveloped cerebral hemispheres with increased extraxial CSF, abnormal gyral pattern (polymicrogyria-like lesions in two sibs and lissencephaly in the others), loss of white matter, dysplastic ventricles, hypogenesis of corpus callosum, and hypoplasia of the brainstem, but hypoplastic cerebellum in one. Fetal magnetic resonance imaging (FMRI) of two patients showed the same developmental brain malformations in utero. These imaging findings are in accordance with arrested brain development rather than disruption. Molecular analysis excluded mutations in potentially related genes such as NDE1, MKL2, OCLN, and JAM3. These unique clinical and imaging findings were described before among familial reports with FBDS. However, our patients represent a recognizable phenotype of developmental brain malformations, that is, apparently distinguishable from either familial microhydranencephaly or microlissencephaly that were collectively termed FBDS. Thus, the use of the umbrella term FBDS is no longer helpful. Accordingly, we propose the term fetal brain arrest to distinguish them from other familial patients diagnosed as FBDS. The presence of five affected patients from three unrelated consanguineous families suggests an autosomal-recessive mode of inheritance. The spectrum of fetal brain disruption sequence is reviewed. © 2015 Wiley Periodicals, Inc.

Population differences in brain morphology: Need for population specific brain template.

PubMed

Rao, Naren P; Jeelani, Haris; Achalia, Rashmin; Achalia, Garima; Jacob, Arpitha; Bharath, Rose Dawn; Varambally, Shivarama; Venkatasubramanian, Ganesan; K Yalavarthy, Phaneendra

2017-07-30

Brain templates provide a standard anatomical platform for population based morphometric assessments. Typically, standard brain templates for such assessments are created using Caucasian brains, which may not be ideal to analyze brains from other ethnicities. To effectively demonstrate this, we compared brain morphometric differences between T1 weighted structural MRI images of 27 healthy Indian and Caucasian subjects of similar age and same sex ratio. Furthermore, a population specific brain template was created from MRI images of healthy Indian subjects and compared with standard Montreal Neurological Institute (MNI-152) template. We also examined the accuracy of registration of by acquiring a different T1 weighted MRI data set and registering them to newly created Indian template and MNI-152 template. The statistical analysis indicates significant difference in global brain measures and regional brain structures of Indian and Caucasian subjects. Specifically, the global brain measurements of the Indian brain template were smaller than that of the MNI template. Also, Indian brain images were better realigned to the newly created template than to the MNI-152 template. The notable variations in Indian and Caucasian brains convey the need to build a population specific Indian brain template and atlas. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

The early development of brain white matter: a review of imaging studies in fetuses, newborns and infants.

PubMed

Dubois, J; Dehaene-Lambertz, G; Kulikova, S; Poupon, C; Hüppi, P S; Hertz-Pannier, L

2014-09-12

Studying how the healthy human brain develops is important to understand early pathological mechanisms and to assess the influence of fetal or perinatal events on later life. Brain development relies on complex and intermingled mechanisms especially during gestation and first post-natal months, with intense interactions between genetic, epigenetic and environmental factors. Although the baby's brain is organized early on, it is not a miniature adult brain: regional brain changes are asynchronous and protracted, i.e. sensory-motor regions develop early and quickly, whereas associative regions develop later and slowly over decades. Concurrently, the infant/child gradually achieves new performances, but how brain maturation relates to changes in behavior is poorly understood, requiring non-invasive in vivo imaging studies such as magnetic resonance imaging (MRI). Two main processes of early white matter development are reviewed: (1) establishment of connections between brain regions within functional networks, leading to adult-like organization during the last trimester of gestation, (2) maturation (myelination) of these connections during infancy to provide efficient transfers of information. Current knowledge from post-mortem descriptions and in vivo MRI studies is summed up, focusing on T1- and T2-weighted imaging, diffusion tensor imaging, and quantitative mapping of T1/T2 relaxation times, myelin water fraction and magnetization transfer ratio. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Non-invasive imaging of the levels and effects of glutathione on the redox status of mouse brain using electron paramagnetic resonance imaging.

PubMed

Emoto, Miho C; Matsuoka, Yuta; Yamada, Ken-Ichi; Sato-Akaba, Hideo; Fujii, Hirotada G

2017-04-15

Glutathione (GSH) is the most abundant non-protein thiol that buffers reactive oxygen species in the brain. GSH does not reduce nitroxides directly, but in the presence of ascorbates, addition of GSH increases ascorbate-induced reduction of nitroxides. In this study, we used electron paramagnetic resonance (EPR) imaging and the nitroxide imaging probe, 3-methoxycarbonyl-2,2,5,5-tetramethyl-piperidine-1-oxyl (MCP), to non-invasively obtain spatially resolved redox data from mouse brains depleted of GSH with diethyl maleate compared to control. Based on the pharmacokinetics of the reduction reaction of MCP in the mouse heads, the pixel-based rate constant of its reduction reaction was calculated as an index of the redox status in vivo and mapped as a "redox map". The obtained redox maps from control and GSH-depleted mouse brains showed a clear change in the brain redox status, which was due to the decreased levels of GSH in brains as measured by a biochemical assay. We observed a linear relationship between the reduction rate constant of MCP and the level of GSH for both control and GSH-depleted mouse brains. Using this relationship, the GSH level in the brain can be estimated from the redox map obtained with EPR imaging. Copyright © 2017 Elsevier Inc. All rights reserved.

Imaging of cerebral blood flow in patients with severe traumatic brain injury in the neurointensive care.

PubMed

Rostami, Elham; Engquist, Henrik; Enblad, Per

2014-01-01

Ischemia is a common and deleterious secondary injury following traumatic brain injury (TBI). A great challenge for the treatment of TBI patients in the neurointensive care unit (NICU) is to detect early signs of ischemia in order to prevent further advancement and deterioration of the brain tissue. Today, several imaging techniques are available to monitor cerebral blood flow (CBF) in the injured brain such as positron emission tomography (PET), single-photon emission computed tomography, xenon computed tomography (Xenon-CT), perfusion-weighted magnetic resonance imaging (MRI), and CT perfusion scan. An ideal imaging technique would enable continuous non-invasive measurement of blood flow and metabolism across the whole brain. Unfortunately, no current imaging method meets all these criteria. These techniques offer snapshots of the CBF. MRI may also provide some information about the metabolic state of the brain. PET provides images with high resolution and quantitative measurements of CBF and metabolism; however, it is a complex and costly method limited to few TBI centers. All of these methods except mobile Xenon-CT require transfer of TBI patients to the radiological department. Mobile Xenon-CT emerges as a feasible technique to monitor CBF in the NICU, with lower risk of adverse effects. Promising results have been demonstrated with Xenon-CT in predicting outcome in TBI patients. This review covers available imaging methods used to monitor CBF in patients with severe TBI.

Imaging of Cerebral Blood Flow in Patients with Severe Traumatic Brain Injury in the Neurointensive Care

PubMed Central

Rostami, Elham; Engquist, Henrik; Enblad, Per

2014-01-01

Ischemia is a common and deleterious secondary injury following traumatic brain injury (TBI). A great challenge for the treatment of TBI patients in the neurointensive care unit (NICU) is to detect early signs of ischemia in order to prevent further advancement and deterioration of the brain tissue. Today, several imaging techniques are available to monitor cerebral blood flow (CBF) in the injured brain such as positron emission tomography (PET), single-photon emission computed tomography, xenon computed tomography (Xenon-CT), perfusion-weighted magnetic resonance imaging (MRI), and CT perfusion scan. An ideal imaging technique would enable continuous non-invasive measurement of blood flow and metabolism across the whole brain. Unfortunately, no current imaging method meets all these criteria. These techniques offer snapshots of the CBF. MRI may also provide some information about the metabolic state of the brain. PET provides images with high resolution and quantitative measurements of CBF and metabolism; however, it is a complex and costly method limited to few TBI centers. All of these methods except mobile Xenon-CT require transfer of TBI patients to the radiological department. Mobile Xenon-CT emerges as a feasible technique to monitor CBF in the NICU, with lower risk of adverse effects. Promising results have been demonstrated with Xenon-CT in predicting outcome in TBI patients. This review covers available imaging methods used to monitor CBF in patients with severe TBI. PMID:25071702

Magnetic resonance imaging of the kinked fetal brain stem: a sign of severe dysgenesis.

PubMed

Stroustrup Smith, Annemarie; Levine, Deborah; Barnes, Patrick D; Robertson, Richard L

2005-12-01

Magnetic resonance imaging (MRI) allows visualization of the fetal brain stem in a manner not previously possible. A "kinked" brain stem is a sign of severe neurodysgenesis. The purpose of this series was to describe cases of a kinked brain stem detected on prenatal MRI and to discuss the possible genetic and syndromic etiologies. Seven cases of a kinked brain stem on fetal MRI (gestational age range, 18-34 weeks) were reviewed and correlated with other clinical, genetic, imaging, and autopsy findings. In all cases, there was associated cerebellar hypogenesis. Additional findings were ventriculomegaly (4 cases), cerebral hypogenesis (3 cases), microcephaly (4 cases), schizencephaly (1 case), cephalocele (1 case), hypogenesis of the corpus callosum (1 case), and hydrocephalus (1 case). In 2 cases, prenatal sonography misidentified the kinked brain stem as the cerebellum. A kinked brain stem is an indicator of severe neurodysgenesis arising early in gestation. Magnetic resonance imaging provides the necessary resolution to detect this sign and delineate any associated anomalies in utero to assist with further genetic evaluation, management, and counseling.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level

PubMed Central

Gong, Hui; Xu, Dongli; Yuan, Jing; Li, Xiangning; Guo, Congdi; Peng, Jie; Li, Yuxin; Schwarz, Lindsay A.; Li, Anan; Hu, Bihe; Xiong, Benyi; Sun, Qingtao; Zhang, Yalun; Liu, Jiepeng; Zhong, Qiuyuan; Xu, Tonghui; Zeng, Shaoqun; Luo, Qingming

2016-01-01

The precise annotation and accurate identification of neural structures are prerequisites for studying mammalian brain function. The orientation of neurons and neural circuits is usually determined by mapping brain images to coarse axial-sampling planar reference atlases. However, individual differences at the cellular level likely lead to position errors and an inability to orient neural projections at single-cell resolution. Here, we present a high-throughput precision imaging method that can acquire a co-localized brain-wide data set of both fluorescent-labelled neurons and counterstained cell bodies at a voxel size of 0.32 × 0.32 × 2.0 μm in 3 days for a single mouse brain. We acquire mouse whole-brain imaging data sets of multiple types of neurons and projections with anatomical annotation at single-neuron resolution. The results show that the simultaneous acquisition of labelled neural structures and cytoarchitecture reference in the same brain greatly facilitates precise tracing of long-range projections and accurate locating of nuclei. PMID:27374071

Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play

PubMed Central

Savitz, J B; Rauch, S L; Drevets, W C

2013-01-01

In response to queries about whether brain imaging technology has reached the point where it is useful for making a clinical diagnosis and for helping to guide treatment selection, the American Psychiatric Association (APA) has recently written a position paper on the Clinical Application of Brain Imaging in Psychiatry. The following perspective piece is based on our contribution to this APA position paper, which specifically emphasized the application of neuroimaging in mood disorders. We present an introductory overview of the challenges faced by researchers in developing valid and reliable biomarkers for psychiatric disorders, followed by a synopsis of the extant neuroimaging findings in mood disorders, and an evidence-based review of the current research on brain imaging biomarkers in adult mood disorders. Although there are a number of promising results, by the standards proposed below, we argue that there are currently no brain imaging biomarkers that are clinically useful for establishing diagnosis or predicting treatment outcome in mood disorders. PMID:23546169

Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play.

PubMed

Savitz, J B; Rauch, S L; Drevets, W C

2013-05-01

In response to queries about whether brain imaging technology has reached the point where it is useful for making a clinical diagnosis and for helping to guide treatment selection, the American Psychiatric Association (APA) has recently written a position paper on the Clinical Application of Brain Imaging in Psychiatry. The following perspective piece is based on our contribution to this APA position paper, which specifically emphasized the application of neuroimaging in mood disorders. We present an introductory overview of the challenges faced by researchers in developing valid and reliable biomarkers for psychiatric disorders, followed by a synopsis of the extant neuroimaging findings in mood disorders, and an evidence-based review of the current research on brain imaging biomarkers in adult mood disorders. Although there are a number of promising results, by the standards proposed below, we argue that there are currently no brain imaging biomarkers that are clinically useful for establishing diagnosis or predicting treatment outcome in mood disorders.

From Disabled Students to Disabled Brains: The Medicalizing Power of Rhetorical Images in the Israeli Learning Disabilities Field.

PubMed

Katchergin, Ofer

2017-09-01

The neurocentric worldview that identifies the essence of the human being with the material brain has become a central paradigm in current academic discourse. Israeli researchers also seek to understand educational principles and processes via neuroscientific models. On this background, the article uncovers the central role that visual brain images play in the learning-disabilities field in Israel. It examines the place brain images have in the professional imagination of didactic-diagnosticians as well as their influence on the diagnosticians' clinical attitudes. It relies on two theoretical fields: sociology and anthropology of the body and sociology of neuromedical knowledge. The research consists of three methodologies: ethnographic observations, in-depth interviews, and rhetorical analysis of visual and verbal texts. It uncovers the various rhetorical and ideological functions of brain images in the field. It also charts the repertoire of rhetorical devices which are utilized to strengthen the neuroreducionist messages contained in the images.

High-resolution anatomy of the human brain stem using 7-T MRI: improved detection of inner structures and nerves?

PubMed

Gizewski, Elke R; Maderwald, Stefan; Linn, Jennifer; Dassinger, Benjamin; Bochmann, Katja; Forsting, Michael; Ladd, Mark E

2014-03-01

The purpose of this paper is to assess the value of 7 Tesla (7 T) MRI for the depiction of brain stem and cranial nerve (CN) anatomy. Six volunteers were examined at 7 T using high-resolution SWI, MPRAGE, MP2RAGE, 3D SPACE T2, T2, and PD images to establish scanning parameters targeted at optimizing spatial resolution. Direct comparisons between 3 and 7 T were performed in two additional subjects using the finalized sequences (3 T: T2, PD, MPRAGE, SWAN; 7 T: 3D T2, MPRAGE, SWI, MP2RAGE). Artifacts and the depiction of structures were evaluated by two neuroradiologists using a standardized score sheet. Sequences could be established for high-resolution 7 T imaging even in caudal cranial areas. High in-plane resolution T2, PD, and SWI images provided depiction of inner brain stem structures such as pons fibers, raphe, reticular formation, nerve roots, and periaqueductal gray. MPRAGE and MP2RAGE provided clear depiction of the CNs. 3D T2 images improved depiction of inner brain structure in comparison to T2 images at 3 T. Although the 7-T SWI sequence provided improved contrast to some inner structures, extended areas were influenced by artifacts due to image disturbances from susceptibility differences. Seven-tesla imaging of basal brain areas is feasible and might have significant impact on detection and diagnosis in patients with specific diseases, e.g., trigeminal pain related to affection of the nerve root. Some inner brain stem structures can be depicted at 3 T, but certain sequences at 7 T, in particular 3D SPACE T2, are superior in producing anatomical in vivo images of deep brain stem structures.

Brain early infarct detection using gamma correction extreme-level eliminating with weighting distribution.

PubMed

Teh, V; Sim, K S; Wong, E K

2016-11-01

According to the statistic from World Health Organization (WHO), stroke is one of the major causes of death globally. Computed tomography (CT) scan is one of the main medical diagnosis system used for diagnosis of ischemic stroke. CT scan provides brain images in Digital Imaging and Communication in Medicine (DICOM) format. The presentation of CT brain images is mainly relied on the window setting (window center and window width), which converts an image from DICOM format into normal grayscale format. Nevertheless, the ordinary window parameter could not deliver a proper contrast on CT brain images for ischemic stroke detection. In this paper, a new proposed method namely gamma correction extreme-level eliminating with weighting distribution (GCELEWD) is implemented to improve the contrast on CT brain images. GCELEWD is capable of highlighting the hypodense region for diagnosis of ischemic stroke. The performance of this new proposed technique, GCELEWD, is compared with four of the existing contrast enhancement technique such as brightness preserving bi-histogram equalization (BBHE), dualistic sub-image histogram equalization (DSIHE), extreme-level eliminating histogram equalization (ELEHE), and adaptive gamma correction with weighting distribution (AGCWD). GCELEWD shows better visualization for ischemic stroke detection and higher values with image quality assessment (IQA) module. SCANNING 38:842-856, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

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

Leveraging Clinical Imaging Archives for Radiomics: Reliability of Automated Methods for Brain Volume Measurement.

PubMed

Adduru, Viraj R; Michael, Andrew M; Helguera, Maria; Baum, Stefi A; Moore, Gregory J

2017-09-01

Purpose To validate the use of thick-section clinically acquired magnetic resonance (MR) imaging data for estimating total brain volume (TBV), gray matter (GM) volume (GMV), and white matter (WM) volume (WMV) by using three widely used automated toolboxes: SPM ( www.fil.ion.ucl.ac.uk/spm/ ), FreeSurfer ( surfer.nmr.mgh.harvard.edu ), and FSL (FMRIB software library; Oxford Centre for Functional MR Imaging of the Brain, Oxford, England, https://fsl.fmrib.ox.ac.uk/fsl ). Materials and Methods MR images from a clinical archive were used and data were deidentified. The three methods were applied to estimate brain volumes from thin-section research-quality brain MR images and routine thick-section clinical MR images acquired from the same 38 patients (age range, 1-71 years; mean age, 22 years; 11 women). By using these automated methods, TBV, GMV, and WMV were estimated. Thin- versus thick-section volume comparisons were made for each method by using intraclass correlation coefficients (ICCs). Results SPM exhibited excellent ICCs (0.97, 0.85, and 0.83 for TBV, GMV, and WMV, respectively). FSL exhibited ICCs of 0.69, 0.51, and 0.60 for TBV, GMV, and WMV, respectively, but they were lower than with SPM. FreeSurfer exhibited excellent ICC of 0.63 only for TBV. Application of SPM's voxel-based morphometry on the modulated images of thin-section images and interpolated thick-section images showed fair to excellent ICCs (0.37-0.98) for the majority of brain regions (88.47% [306924 of 346916 voxels] of WM and 80.35% [377 282 of 469 502 voxels] of GM). Conclusion Thick-section clinical-quality MR images can be reliably used for computing quantitative brain metrics such as TBV, GMV, and WMV by using SPM. © RSNA, 2017 Online supplemental material is available for this article.

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

PubMed

Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y

2018-04-01

Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping; they were worse on preconditioned quantitative susceptibility mapping. Preconditioned quantitative susceptibility mapping MR imaging can bring the benefits of quantitative susceptibility mapping imaging to clinical practice without the limitations of mask-based quantitative susceptibility mapping, especially for evaluating cerebral microhemorrhage-associated pathologies, such as traumatic brain injury. © 2018 by American Journal of Neuroradiology.

In vivo multiphoton tomography and fluorescence lifetime imaging of human brain tumor tissue.

PubMed

Kantelhardt, Sven R; Kalasauskas, Darius; König, Karsten; Kim, Ella; Weinigel, Martin; Uchugonova, Aisada; Giese, Alf

2016-05-01

High resolution multiphoton tomography and fluorescence lifetime imaging differentiates glioma from adjacent brain in native tissue samples ex vivo. Presently, multiphoton tomography is applied in clinical dermatology and experimentally. We here present the first application of multiphoton and fluorescence lifetime imaging for in vivo imaging on humans during a neurosurgical procedure. We used a MPTflex™ Multiphoton Laser Tomograph (JenLab, Germany). We examined cultured glioma cells in an orthotopic mouse tumor model and native human tissue samples. Finally the multiphoton tomograph was applied to provide optical biopsies during resection of a clinical case of glioblastoma. All tissues imaged by multiphoton tomography were sampled and processed for conventional histopathology. The multiphoton tomograph allowed fluorescence intensity- and fluorescence lifetime imaging with submicron spatial resolution and 200 picosecond temporal resolution. Morphological fluorescence intensity imaging and fluorescence lifetime imaging of tumor-bearing mouse brains and native human tissue samples clearly differentiated tumor and adjacent brain tissue. Intraoperative imaging was found to be technically feasible. Intraoperative image quality was comparable to ex vivo examinations. To our knowledge we here present the first intraoperative application of high resolution multiphoton tomography and fluorescence lifetime imaging of human brain tumors in situ. It allowed in vivo identification and determination of cell density of tumor tissue on a cellular and subcellular level within seconds. The technology shows the potential of rapid intraoperative identification of native glioma tissue without need for tissue processing or staining.

From nociception to pain perception: imaging the spinal and supraspinal pathways

PubMed Central

Brooks, Jonathan; Tracey, Irene

2005-01-01

Functional imaging techniques have allowed researchers to look within the brain, and revealed the cortical representation of pain. Initial experiments, performed in the early 1990s, revolutionized pain research, as they demonstrated that pain was not processed in a single cortical area, but in several distributed brain regions. Over the last decade, the roles of these pain centres have been investigated and a clearer picture has emerged of the medial and lateral pain system. In this brief article, we review the imaging literature to date that has allowed these advances to be made, and examine the new frontiers for pain imaging research: imaging the brainstem and other structures involved in the descending control of pain; functional and anatomical connectivity studies of pain processing brain regions; imaging models of neuropathic pain-like states; and going beyond the brain to image spinal function. The ultimate goal of such research is to take these new techniques into the clinic, to investigate and provide new remedies for chronic pain sufferers. PMID:16011543

Diagnosing Autism Spectrum Disorder through Brain Functional Magnetic Resonance Imaging

DTIC Science & Technology

2016-03-01

Diagnosing Autism Spectrum Disorder through Brain Functional Magnetic Resonance Imaging THESIS MARCH 2016 Kyle A. Palko, Second Lieutenant, USAF AFIT...declared a work of the U.S. Government and is not subject to copyright protection in the United States. AFIT-ENC-MS-16-M-123 DIAGNOSING AUTISM SPECTRUM...PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENC-MS-16-M-123 DIAGNOSING AUTISM SPECTRUM DISORDER THROUGH BRAIN FUNCTIONAL MAGNETIC RESONANCE IMAGING Kyle

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

PubMed Central

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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.

Imaging the Working Brain.

ERIC Educational Resources Information Center

Swithenby, S. J.

1996-01-01

Very sensitive SQUID (superconducting quantum interference device) detectors are used in the technique known as magnetoencephalography to provide dynamic images of the brain. This can help our fundamental understanding of the way the brain works and may be of particular use in treating disorders such as epilepsy. (Author/MKR)

A new head phantom with realistic shape and spatially varying skull resistivity distribution.

PubMed

Li, Jian-Bo; Tang, Chi; Dai, Meng; Liu, Geng; Shi, Xue-Tao; Yang, Bin; Xu, Can-Hua; Fu, Feng; You, Fu-Sheng; Tang, Meng-Xing; Dong, Xiu-Zhen

2014-02-01

Brain electrical impedance tomography (EIT) is an emerging method for monitoring brain injuries. To effectively evaluate brain EIT systems and reconstruction algorithms, we have developed a novel head phantom that features realistic anatomy and spatially varying skull resistivity. The head phantom was created with three layers, representing scalp, skull, and brain tissues. The fabrication process entailed 3-D printing of the anatomical geometry for mold creation followed by casting to ensure high geometrical precision and accuracy of the resistivity distribution. We evaluated the accuracy and stability of the phantom. Results showed that the head phantom achieved high geometric accuracy, accurate skull resistivity values, and good stability over time and in the frequency domain. Experimental impedance reconstructions performed using the head phantom and computer simulations were found to be consistent for the same perturbation object. In conclusion, this new phantom could provide a more accurate test platform for brain EIT research.

Identifying Degenerative Brain Disease Using Rough Set Classifier Based on Wavelet Packet Method.

PubMed

Cheng, Ching-Hsue; Liu, Wei-Xiang

2018-05-28

Population aging has become a worldwide phenomenon, which causes many serious problems. The medical issues related to degenerative brain disease have gradually become a concern. Magnetic Resonance Imaging is one of the most advanced methods for medical imaging and is especially suitable for brain scans. From the literature, although the automatic segmentation method is less laborious and time-consuming, it is restricted in several specific types of images. In addition, hybrid techniques segmentation improves the shortcomings of the single segmentation method. Therefore, this study proposed a hybrid segmentation combined with rough set classifier and wavelet packet method to identify degenerative brain disease. The proposed method is a three-stage image process method to enhance accuracy of brain disease classification. In the first stage, this study used the proposed hybrid segmentation algorithms to segment the brain ROI (region of interest). In the second stage, wavelet packet was used to conduct the image decomposition and calculate the feature values. In the final stage, the rough set classifier was utilized to identify the degenerative brain disease. In verification and comparison, two experiments were employed to verify the effectiveness of the proposed method and compare with the TV-seg (total variation segmentation) algorithm, Discrete Cosine Transform, and the listing classifiers. Overall, the results indicated that the proposed method outperforms the listing methods.

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

[Initial diagnosis of Parkinson's disease - neuroradiological diagnosis].

PubMed

Orimo, Satoshi

2013-01-01

Brain MRI is essential for differentiating Parkinson's disease (PD) from other parkinsonian syndromes. The purpose of performing brain MRI is not to make a diagnosis of PD but is to exclude other parkinsonian syndromes. Recently, several new MRI techniques such as voxel based morphometry, relaxometry, magnetization transfer, spectroscopy, tractography, and functional MRI have been introduced in the diagnosis of PD. Neuromelanin imaging is one of the new techniques and can be useful to make an initial diagnosis of PD. MIBG myocardial scintigraphy is a sensitive imaging tool to differentiate PD from other parkinsonian syndromes and is one of the good tools to make an initial diagnosis of PD. Brain perfusion imaging is sometimes useful to make an initial diagnosis of PD, because reduced brain perfusion area can be detected before brain MRI detects morphological changes of the brain. Dopamine transporter imaging, not available in Japan, is a sensitive tool to detect very early parkinsonism and is useful to make an initial diagnosis of PD. However, it is difficult to differentiate PD from other parkinsonian syndromes.

A Proposal of New Reference System for the Standard Axial, Sagittal, Coronal Planes of Brain Based on the Serially-Sectioned Images

PubMed Central

Park, Jin Seo; Park, Hyo Seok; Shin, Dong Sun; Har, Dong-Hwan; Cho, Zang-Hee; Kim, Young-Bo; Han, Jae-Yong; Chi, Je-Geun

2010-01-01

Sectional anatomy of human brain is useful to examine the diseased brain as well as normal brain. However, intracerebral reference points for the axial, sagittal, and coronal planes of brain have not been standardized in anatomical sections or radiological images. We made 2,343 serially-sectioned images of a cadaver head with 0.1 mm intervals, 0.1 mm pixel size, and 48 bit color and obtained axial, sagittal, and coronal images based on the proposed reference system. This reference system consists of one principal reference point and two ancillary reference points. The two ancillary reference points are the anterior commissure and the posterior commissure. And the principal reference point is the midpoint of two ancillary reference points. It resides in the center of whole brain. From the principal reference point, Cartesian coordinate of x, y, z could be made to be the standard axial, sagittal, and coronal planes. PMID:20052359

Gold nanoparticle imaging and radiotherapy of brain tumors in mice

PubMed Central

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

2013-01-01

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

Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.

PubMed

Bricq, S; Collet, Ch; Armspach, J P

2008-12-01

In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. Here-proposed method takes into account neighborhood information using a Hidden Markov Chain (HMC) model. Due to the limited resolution of imaging devices, voxels may be composed of a mixture of different tissue types, this partial volume effect is included to achieve an accurate segmentation of brain tissues. Instead of assigning each voxel to a single tissue class (i.e., hard classification), we compute the relative amount of each pure tissue class in each voxel (mixture estimation). Further, a bias field estimation step is added to the proposed algorithm to correct intensity inhomogeneities. Furthermore, atlas priors were incorporated using probabilistic brain atlas containing prior expectations about the spatial localization of different tissue classes. This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.

The preprocessed connectomes project repository of manually corrected skull-stripped T1-weighted anatomical MRI data.

PubMed

Puccio, Benjamin; Pooley, James P; Pellman, John S; Taverna, Elise C; Craddock, R Cameron

2016-10-25

Skull-stripping is the procedure of removing non-brain tissue from anatomical MRI data. This procedure can be useful for calculating brain volume and for improving the quality of other image processing steps. Developing new skull-stripping algorithms and evaluating their performance requires gold standard data from a variety of different scanners and acquisition methods. We complement existing repositories with manually corrected brain masks for 125 T1-weighted anatomical scans from the Nathan Kline Institute Enhanced Rockland Sample Neurofeedback Study. Skull-stripped images were obtained using a semi-automated procedure that involved skull-stripping the data using the brain extraction based on nonlocal segmentation technique (BEaST) software, and manually correcting the worst results. Corrected brain masks were added into the BEaST library and the procedure was repeated until acceptable brain masks were available for all images. In total, 85 of the skull-stripped images were hand-edited and 40 were deemed to not need editing. The results are brain masks for the 125 images along with a BEaST library for automatically skull-stripping other data. Skull-stripped anatomical images from the Neurofeedback sample are available for download from the Preprocessed Connectomes Project. The resulting brain masks can be used by researchers to improve preprocessing of the Neurofeedback data, as training and testing data for developing new skull-stripping algorithms, and for evaluating the impact on other aspects of MRI preprocessing. We have illustrated the utility of these data as a reference for comparing various automatic methods and evaluated the performance of the newly created library on independent data.

Medical diagnosis imaging systems: image and signal processing applications aided by fuzzy logic

NASA Astrophysics Data System (ADS)

Hata, Yutaka

2010-04-01

First, we describe an automated procedure for segmenting an MR image of a human brain based on fuzzy logic for diagnosing Alzheimer's disease. The intensity thresholds for segmenting the whole brain of a subject are automatically determined by finding the peaks of the intensity histogram. After these thresholds are evaluated in a region growing, the whole brain can be identified. Next, we describe a procedure for decomposing the obtained whole brain into the left and right cerebral hemispheres, the cerebellum and the brain stem. Our method then identified the whole brain, the left cerebral hemisphere, the right cerebral hemisphere, the cerebellum and the brain stem. Secondly, we describe a transskull sonography system that can visualize the shape of the skull and brain surface from any point to examine skull fracture and some brain diseases. We employ fuzzy signal processing to determine the skull and brain surface. The phantom model, the animal model with soft tissue, the animal model with brain tissue, and a human subjects' forehead is applied in our system. The all shapes of the skin surface, skull surface, skull bottom, and brain tissue surface are successfully determined.

Photoacoustic imaging to detect rat brain activation after cocaine hydrochloride injection

NASA Astrophysics Data System (ADS)

Jo, Janggun; Yang, Xinmai

2011-03-01

Photoacoustic imaging (PAI) was employed to detect small animal brain activation after the administration of cocaine hydrochloride. Sprague Dawley rats were injected with different concentrations (2.5, 3.0, and 5.0 mg per kg body) of cocaine hydrochloride in saline solution through tail veins. The brain functional response to the injection was monitored by photoacoustic tomography (PAT) system with horizontal scanning of cerebral cortex of rat brain. Photoacoustic microscopy (PAM) was also used for coronal view images. The modified PAT system used multiple ultrasonic detectors to reduce the scanning time and maintain a good signal-to-noise ratio (SNR). The measured photoacoustic signal changes confirmed that cocaine hydrochloride injection excited high blood volume in brain. This result shows PAI can be used to monitor drug abuse-induced brain activation.

Brain MRI Characteristics of Patients with Anti-N-Methyl-D-Aspartate Receptor Encephalitis and Their Associations with 2-Year Clinical Outcome.

PubMed

Zhang, T; Duan, Y; Ye, J; Xu, W; Shu, N; Wang, C; Li, K; Liu, Y

2018-05-01

Anti- N -methyl-D-aspertate receptor encephalitis is an autoimmune-mediated disease without specific brain MRI features. Our aim was to investigate the brain MR imaging characteristics of anti- N -methyl-D-aspartate receptor encephalitis and their associations with clinical outcome at a 2-year follow-up. We enrolled 53 patients with anti- N -methyl-D-aspartate receptor encephalitis and performed 2-year follow-up. Brain MRIs were acquired for all patients at the onset phase. The brain MR imaging manifestations were classified into 4 types: type 1: normal MR imaging findings; type 2: only hippocampal lesions; type 3: lesions not involving the hippocampus; and type 4: lesions in both the hippocampus and other brain areas. The modified Rankin Scale score at 2-year follow-up was assessed, and the association between the mRS and onset brain MR imaging characteristics was evaluated. Twenty-eight (28/53, 53%) patients had normal MR imaging findings (type 1), and the others (25/53, 47%) had abnormal MRI findings: type 2: 7 patients (13%); type 3: seven patients (13%); and type 4: eleven patients (21%). Normal brain MRI findings were more common in female patients ( P = .02). Psychiatric and behavioral abnormalities were more common in adults ( P = .015), and autonomic symptoms ( P = .025) were more common in pediatric patients. The presence of hippocampal lesions ( P = .008, OR = 9.584; 95% CI, 1.803-50.931) and relapse ( P = .043, OR = 0.111; 95% CI, 0.013-0.930) was associated with poor outcome. Normal brain MRI findings were observed in half of the patients. Lesions in the hippocampus were the most common MR imaging abnormal finding. The presence of hippocampal lesions is the main MR imaging predictor for poor prognosis in patients with anti- N -methyl-D-aspartate receptor encephalitis. © 2018 by American Journal of Neuroradiology.

Diffusion tensor imaging using multiple coils for mouse brain connectomics.

PubMed

Nouls, John C; Badea, Alexandra; Anderson, Robert B J; Cofer, Gary P; Allan Johnson, G

2018-06-01

The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal-to-noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil-dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two-coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade-offs between imaging throughput and connectivity matrix integrity, studies may seek to clarify how measurement variability, post-processing techniques and biological variability impact mouse brain connectomics. Copyright © 2018 John Wiley & Sons, Ltd.

Development of optical neuroimaging to detect drug-induced brain functional changes in vivo

NASA Astrophysics Data System (ADS)

Du, Congwu; Pan, Yingtian

2014-03-01

Deficits in prefrontal function play a crucial role in compulsive cocaine use, which is a hallmark of addiction. Dysfunction of the prefrontal cortex might result from effects of cocaine on neurons as well as from disruption of cerebral blood vessels. However, the mechanisms underlying cocaine's neurotoxic effects are not fully understood, partially due to technical limitations of current imaging techniques (e.g., PET, fMRI) to differentiate vascular from neuronal effects at sufficiently high temporal and spatial resolutions. We have recently developed a multimodal imaging platform which can simultaneously characterize the changes in cerebrovascular hemodynamics, hemoglobin oxygenation and intracellular calcium fluorescence for monitoring the effects of cocaine on the brain. Such a multimodality imaging technique (OFI) provides several uniquely important merits, including: 1) a large field-of-view, 2) high spatiotemporal resolutions, 3) quantitative 3D imaging of the cerebral blood flow (CBF) networks, 4) label-free imaging of hemodynamic changes, 5) separation of vascular compartments (e.g., arterial and venous vessels) and monitoring of cortical brain metabolic changes, 6) discrimination of cellular (neuronal) from vascular responses. These imaging features have been further advanced in combination with microprobes to form micro-OFI that allows quantification of drug effects on subcortical brain. In addition, our ultrahigh-resolution ODT (μODT) enables 3D microangiography and quantitative imaging of capillary CBF networks. These optical strategies have been used to investigate the effects of cocaine on brain physiology to facilitate the studies of brain functional changes induced by addictive substance to provide new insights into neurobiological effects of the drug on the brain.

Cerenkov and radioluminescence imaging of brain tumor specimens during neurosurgery

NASA Astrophysics Data System (ADS)

Spinelli, Antonello Enrico; Schiariti, Marco P.; Grana, Chiara M.; Ferrari, Mahila; Cremonesi, Marta; Boschi, Federico

2016-05-01

We presented the first example of Cerenkov luminescence imaging (CLI) and radioluminescence imaging (RLI) of human tumor specimens. A patient with a brain meningioma localized in the left parietal region was injected with 166 MBq of Y90-DOTATOC the day before neurosurgery. The specimens of the tumor removed during surgery were imaged using both CLI and RLI using an optical imager prototype developed in our laboratory. The system is based on a cooled electron multiplied charge coupled device coupled with an f/0.95 17-mm C-mount lens. We showed for the first time the possibility of obtaining CLI and RLI images of fresh human brain tumor specimens removed during neurosurgery.

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.

Amplitude-integrated EEG in newborns with critical congenital heart disease predicts preoperative brain magnetic resonance imaging findings.

PubMed

Mulkey, Sarah B; Yap, Vivien L; Bai, Shasha; Ramakrishnaiah, Raghu H; Glasier, Charles M; Bornemeier, Renee A; Schmitz, Michael L; Bhutta, Adnan T

2015-06-01

The study aims are to evaluate cerebral background patterns using amplitude-integrated electroencephalography in newborns with critical congenital heart disease, determine if amplitude-integrated electroencephalography is predictive of preoperative brain injury, and assess the incidence of preoperative seizures. We hypothesize that amplitude-integrated electroencephalography will show abnormal background patterns in the early preoperative period in infants with congenital heart disease that have preoperative brain injury on magnetic resonance imaging. Twenty-four newborns with congenital heart disease requiring surgery at younger than 30 days of age were prospectively enrolled within the first 3 days of age at a tertiary care pediatric hospital. Infants had amplitude-integrated electroencephalography for 24 hours beginning close to birth and preoperative brain magnetic resonance imaging. The amplitude-integrated electroencephalographies were read to determine if the background pattern was normal, mildly abnormal, or severely abnormal. The presence of seizures and sleep-wake cycling were noted. The preoperative brain magnetic resonance imaging scans were used for brain injury and brain atrophy assessment. Fifteen of 24 infants had abnormal amplitude-integrated electroencephalography at 0.71 (0-2) (mean [range]) days of age. In five infants, the background pattern was severely abnormal. (burst suppression and/or continuous low voltage). Of the 15 infants with abnormal amplitude-integrated electroencephalography, 9 (60%) had brain injury. One infant with brain injury had a seizure on amplitude-integrated electroencephalography. A severely abnormal background pattern on amplitude-integrated electroencephalography was associated with brain atrophy (P = 0.03) and absent sleep-wake cycling (P = 0.022). Background cerebral activity is abnormal on amplitude-integrated electroencephalography following birth in newborns with congenital heart disease who have findings of brain injury and/or brain atrophy on preoperative brain magnetic resonance imaging. Copyright © 2015 Elsevier Inc. All rights reserved.

FROM SELECTIVE VULNERABILITY TO CONNECTIVITY: INSIGHTS FROM NEWBORN BRAIN IMAGING

PubMed Central

Miller, Steven P.; Ferriero, Donna M

2009-01-01

The ability to image the newborn brain during development has provided new information regarding the effects of injury on brain development at different vulnerable time periods. Studies in animal models of brain injury correlate beautifully with what is now observed in the human newborn. We now know that injury at term results in a predilection for gray matter injury while injury in the premature brain results in a white matter predominant pattern although recent evidence suggests a blurring of this distinction. These injuries affect how the brain matures subsequently and again, imaging has led to new insights that allow us to match function and structure. This review will focus on these patterns of injury that are so critically determined by age at insult. In addition, this review will highlight how the brain responds to these insults with changes in connectivity that have profound functional consequences. PMID:19712981

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

NASA Astrophysics Data System (ADS)

Moualhi, Wafa; Ezzeddine, Zagrouba

2015-02-01

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

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

PubMed Central

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-01-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159

Enhancement of brain tumor MR images based on intuitionistic fuzzy sets

NASA Astrophysics Data System (ADS)

Deng, Wankai; Deng, He; Cheng, Lifang

2015-12-01

Brain tumor is one of the most fatal cancers, especially high-grade gliomas are among the most deadly. However, brain tumor MR images usually have the disadvantages of low resolution and contrast when compared with the optical images. Consequently, we present a novel adaptive intuitionistic fuzzy enhancement scheme by combining a nonlinear fuzzy filtering operation with fusion operators, for the enhancement of brain tumor MR images in this paper. The presented scheme consists of the following six steps: Firstly, the image is divided into several sub-images. Secondly, for each sub-image, object and background areas are separated by a simple threshold. Thirdly, respective intuitionistic fuzzy generators of object and background areas are constructed based on the modified restricted equivalence function. Fourthly, different suitable operations are performed on respective membership functions of object and background areas. Fifthly, the membership plane is inversely transformed into the image plane. Finally, an enhanced image is obtained through fusion operators. The comparison and evaluation of enhancement performance demonstrate that the presented scheme is helpful to determine the abnormal functional areas, guide the operation, judge the prognosis, and plan the radiotherapy by enhancing the fine detail of MR images.

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

PubMed

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images

NASA Astrophysics Data System (ADS)

Deng, He; Deng, Wankai; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2016-10-01

Image enhancement techniques are able to improve the contrast and visual quality of magnetic resonance (MR) images. However, conventional methods cannot make up some deficiencies encountered by respective brain tumor MR imaging modes. In this paper, we propose an adaptive intuitionistic fuzzy sets-based scheme, called as AIFE, which takes information provided from different MR acquisitions and tries to enhance the normal and abnormal structural regions of the brain while displaying the enhanced results as a single image. The AIFE scheme firstly separates an input image into several sub images, then divides each sub image into object and background areas. After that, different novel fuzzification, hyperbolization and defuzzification operations are implemented on each object/background area, and finally an enhanced result is achieved via nonlinear fusion operators. The fuzzy implementations can be processed in parallel. Real data experiments demonstrate that the AIFE scheme is not only effectively useful to have information from images acquired with different MR sequences fused in a single image, but also has better enhancement performance when compared to conventional baseline algorithms. This indicates that the proposed AIFE scheme has potential for improving the detection and diagnosis of brain tumors.

Common Sense Beliefs about the Central Self, Moral Character, and the Brain

PubMed Central

Fernandez-Duque, Diego; Schwartz, Barry

2016-01-01

To assess lay beliefs about self and brain, we probed people's opinions about the central self, in relation to morality, willful control, and brain relevance. In study 1, 172 participants compared the central self to the peripheral self. The central self, construed at this abstract level, was seen as more brain-based than the peripheral self, less changeable through willful control, and yet more indicative of moral character. In study 2, 210 participants described 18 specific personality traits on 6 dimensions: centrality to self, moral relevance, willful control, brain dependence, temporal stability, and desirability. Consistent with Study 1, centrality to the self, construed at this more concrete level, was positively correlated to brain dependence. Centrality to the self was also correlated to desirability and temporal stability, but not to morality or willful control. We discuss differences and similarities between abstract (Study 1) and concrete (Study 2) levels of construal of the central self, and conclude that in contemporary American society people readily embrace the brain as the underlying substrate of who they truly are. PMID:26793140

Common Sense Beliefs about the Central Self, Moral Character, and the Brain.

PubMed

Fernandez-Duque, Diego; Schwartz, Barry

2015-01-01

To assess lay beliefs about self and brain, we probed people's opinions about the central self, in relation to morality, willful control, and brain relevance. In study 1, 172 participants compared the central self to the peripheral self. The central self, construed at this abstract level, was seen as more brain-based than the peripheral self, less changeable through willful control, and yet more indicative of moral character. In study 2, 210 participants described 18 specific personality traits on 6 dimensions: centrality to self, moral relevance, willful control, brain dependence, temporal stability, and desirability. Consistent with Study 1, centrality to the self, construed at this more concrete level, was positively correlated to brain dependence. Centrality to the self was also correlated to desirability and temporal stability, but not to morality or willful control. We discuss differences and similarities between abstract (Study 1) and concrete (Study 2) levels of construal of the central self, and conclude that in contemporary American society people readily embrace the brain as the underlying substrate of who they truly are.

Towards ultrahigh resting-state functional connectivity in the mouse brain using photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Hariri, Ali; Bely, Nicholas; Chen, Chen; Nasiriavanaki, Mohammadreza

2016-03-01

The increasing use of mouse models for human brain disease studies, coupled with the fact that existing high-resolution functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing both mechanical and optical scanning in the photoacoustic microscopy, we can image spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images is going to be acquired noninvasively with a fast frame rate, a large field of view, and a high spatial resolution. We developed an optical resolution photoacoustic microscopy (OR-PAM) with diode laser. Laser light was raster scanned due to XY-stage movement. Images from ultra-high OR-PAM can then be used to study brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy.

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.

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.

Quantification of amyloid deposits and oxygen extraction fraction in the brain with multispectral optoacoustic imaging in arcAβ mouse model of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Ni, Ruiqing; Vaas, Markus; Rudin, Markus; Klohs, Jan

2018-02-01

Beta-amyloid (Aβ) deposition and vascular dysfunction are important contributors to the pathogenesis in Alzheimer's disease (AD). However, the spatio-temporal relationship between an altered oxygen metabolism and Aβ deposition in the brain remains elusive. Here we provide novel in-vivo estimates of brain Aβ load with Aβ-binding probe CRANAD-2 and measures of brain oxygen saturation by using multi-spectral optoacoustic imaging (MSOT) and perfusion imaging with magnetic resonance imaging (MRI) in arcAβ mouse models of AD. We demonstrated a decreased cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) in the cortical region of the arcAβ mice compared to wildtype littermates at 24 months. In addition, we showed proof-of-concept for the detection of cerebral Aβ deposits in brain from arcAβ mice compared to wild-type littermates.

Swept-source optical coherence tomography powered by a 1.3-μm vertical cavity surface emitting laser enables 2.3-mm-deep brain imaging in mice in vivo

NASA Astrophysics Data System (ADS)

Choi, Woo June; Wang, Ruikang K.

2015-10-01

We report noninvasive, in vivo optical imaging deep within a mouse brain by swept-source optical coherence tomography (SS-OCT), enabled by a 1.3-μm vertical cavity surface emitting laser (VCSEL). VCSEL SS-OCT offers a constant signal sensitivity of 105 dB throughout an entire depth of 4.25 mm in air, ensuring an extended usable imaging depth range of more than 2 mm in turbid biological tissue. Using this approach, we show deep brain imaging in mice with an open-skull cranial window preparation, revealing intact mouse brain anatomy from the superficial cerebral cortex to the deep hippocampus. VCSEL SS-OCT would be applicable to small animal studies for the investigation of deep tissue compartments in living brains where diseases such as dementia and tumor can take their toll.

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.

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.

Magnetic Resonance Imaging with laser polarized 129Xe

NASA Astrophysics Data System (ADS)

Swanson, Scott D.; Rosen, Matthew S.; Agranoff, Bernard W.; Coulter, Kevin P.; Welsh, Robert C.; Chupp, Timothy E.

1998-01-01

Magnetic Resonance Imaging with laser-polarized 129Xe can be utilized to trace blood flow and perfusion in tissue for a variety of biomedical applications. Polarized xenon gas introduced in to the lungs dissolves in the blood and is transported to organs such as the brain where it accumulates in the tissue. Spectroscopic studies combined with imaging have been used to produce brain images of 129Xe in the rat head. This work establishes that nuclear polarization produced in the gas phases survives transport to the brain where it may be imaged. Increases in polarization and delivered volume of 129Xe will allow clinical measurements of regional blood flow.

An architecture for a brain-image database

NASA Technical Reports Server (NTRS)

Herskovits, E. H.

2000-01-01

The widespread availability of methods for noninvasive assessment of brain structure has enabled researchers to investigate neuroimaging correlates of normal aging, cerebrovascular disease, and other processes; we designate such studies as image-based clinical trials (IBCTs). We propose an architecture for a brain-image database, which integrates image processing and statistical operators, and thus supports the implementation and analysis of IBCTs. The implementation of this architecture is described and results from the analysis of image and clinical data from two IBCTs are presented. We expect that systems such as this will play a central role in the management and analysis of complex research data sets.

Rapid whole brain imaging of neural activity in freely behaving larval zebrafish (Danio rerio)

PubMed Central

Shang, Chunfeng; Yang, Wenbin; Bai, Lu; Du, Jiulin

2017-01-01

The internal brain dynamics that link sensation and action are arguably better studied during natural animal behaviors. Here, we report on a novel volume imaging and 3D tracking technique that monitors whole brain neural activity in freely swimming larval zebrafish (Danio rerio). We demonstrated the capability of our system through functional imaging of neural activity during visually evoked and prey capture behaviors in larval zebrafish. PMID:28930070

Brain Basics: Know Your Brain

MedlinePlus

... free mailed brochure Table of Contents Introduction The Architecture of the Brain The Geography of Thought The ... brain is diseased or dysfunctional. Image 1 The Architecture of the Brain The brain is like a ...

Normal feline brain: clinical anatomy using magnetic resonance imaging.

PubMed

Mogicato, G; Conchou, F; Layssol-Lamour, C; Raharison, F; Sautet, J

2012-04-01

The purpose of this study was to provide a clinical anatomy atlas of the feline brain using magnetic resonance imaging (MRI). Brains of twelve normal cats were imaged using a 1.5 T magnetic resonance unit and an inversion/recovery sequence (T1). Fourteen relevant MRI sections were chosen in transverse, dorsal, median and sagittal planes. Anatomic structures were identified and labelled using anatomical texts and Nomina Anatomica Veterinaria, sectioned specimen heads, and previously published articles. The MRI sections were stained according to the major embryological and anatomical subdivisions of the brain. The relevant anatomical structures seen on MRI will assist clinicians to better understand MR images and to relate this neuro-anatomy to clinical signs. © 2011 Blackwell Verlag GmbH.

Deep two-photon microscopic imaging through brain tissue using the second singlet state from fluorescent agent chlorophyll α in spinach leaf

NASA Astrophysics Data System (ADS)

Shi, Lingyan; Rodríguez-Contreras, Adrián; Budansky, Yury; Pu, Yang; An Nguyen, Thien; Alfano, Robert R.

2014-06-01

Two-photon (2P) excitation of the second singlet (S) state was studied to achieve deep optical microscopic imaging in brain tissue when both the excitation (800 nm) and emission (685 nm) wavelengths lie in the "tissue optical window" (650 to 950 nm). S2 state technique was used to investigate chlorophyll α (Chl α) fluorescence inside a spinach leaf under a thick layer of freshly sliced rat brain tissue in combination with 2P microscopic imaging. Strong emission at the peak wavelength of 685 nm under the 2P S state of Chl α enabled the imaging depth up to 450 μm through rat brain tissue.

Functional photoacoustic imaging to observe regional brain activation induced by cocaine hydrochloride

NASA Astrophysics Data System (ADS)

Jo, Janggun; Yang, Xinmai

2011-09-01

Photoacoustic microscopy (PAM) was used to detect small animal brain activation in response to drug abuse. Cocaine hydrochloride in saline solution was injected into the blood stream of Sprague Dawley rats through tail veins. The rat brain functional change in response to the injection of drug was then monitored by the PAM technique. Images in the coronal view of the rat brain at the locations of 1.2 and 3.4 mm posterior to bregma were obtained. The resulted photoacoustic (PA) images showed the regional changes in the blood volume. Additionally, the regional changes in blood oxygenation were also presented. The results demonstrated that PA imaging is capable of monitoring regional hemodynamic changes induced by drug abuse.

Deep two-photon microscopic imaging through brain tissue using the second singlet state from fluorescent agent chlorophyll α in spinach leaf.

PubMed

Shi, Lingyan; Rodríguez-Contreras, Adrián; Budansky, Yury; Pu, Yang; Nguyen, Thien An; Alfano, Robert R

2014-06-01

Two-photon (2P) excitation of the second singlet (S₂) state was studied to achieve deep optical microscopic imaging in brain tissue when both the excitation (800 nm) and emission (685 nm) wavelengths lie in the "tissue optical window" (650 to 950 nm). S₂ state technique was used to investigate chlorophyll α (Chl α) fluorescence inside a spinach leaf under a thick layer of freshly sliced rat brain tissue in combination with 2P microscopic imaging. Strong emission at the peak wavelength of 685 nm under the 2P S₂ state of Chl α enabled the imaging depth up to 450 μm through rat brain tissue.

78 FR 734 - Medical Imaging Drugs Advisory Committee; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-04

..., LLC. The proposed indication (use) for this product is for magnetic resonance imaging in brain...) to detect and visualize areas with disruption of the blood brain barrier (specialized tissues that help protect the brain) and/or abnormal vascularity (abnormal blood circulation). FDA intends to make...

Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Voos, Avery; Pelphrey, Kevin

2013-01-01

Functional magnetic resonance imaging (fMRI), with its excellent spatial resolution and ability to visualize networks of neuroanatomical structures involved in complex information processing, has become the dominant technique for the study of brain function and its development. The accessibility of in-vivo pediatric brain-imaging techniques…

High-resolution imaging of the large non-human primate brain using microPET: a feasibility study

NASA Astrophysics Data System (ADS)

Naidoo-Variawa, S.; Hey-Cunningham, A. J.; Lehnert, W.; Kench, P. L.; Kassiou, M.; Banati, R.; Meikle, S. R.

2007-11-01

The neuroanatomy and physiology of the baboon brain closely resembles that of the human brain and is well suited for evaluating promising new radioligands in non-human primates by PET and SPECT prior to their use in humans. These studies are commonly performed on clinical scanners with 5 mm spatial resolution at best, resulting in sub-optimal images for quantitative analysis. This study assessed the feasibility of using a microPET animal scanner to image the brains of large non-human primates, i.e. papio hamadryas (baboon) at high resolution. Factors affecting image accuracy, including scatter, attenuation and spatial resolution, were measured under conditions approximating a baboon brain and using different reconstruction strategies. Scatter fraction measured 32% at the centre of a 10 cm diameter phantom. Scatter correction increased image contrast by up to 21% but reduced the signal-to-noise ratio. Volume resolution was superior and more uniform using maximum a posteriori (MAP) reconstructed images (3.2-3.6 mm3 FWHM from centre to 4 cm offset) compared to both 3D ordered subsets expectation maximization (OSEM) (5.6-8.3 mm3) and 3D reprojection (3DRP) (5.9-9.1 mm3). A pilot 18F-2-fluoro-2-deoxy-d-glucose ([18F]FDG) scan was performed on a healthy female adult baboon. The pilot study demonstrated the ability to adequately resolve cortical and sub-cortical grey matter structures in the baboon brain and improved contrast when images were corrected for attenuation and scatter and reconstructed by MAP. We conclude that high resolution imaging of the baboon brain with microPET is feasible with appropriate choices of reconstruction strategy and corrections for degrading physical effects. Further work to develop suitable correction algorithms for high-resolution large primate imaging is warranted.

Correlation between 99Tcm-HMPAO-SPECT brain image and a history of decompression illness or extent of diving experience in commercial divers.

PubMed Central

Shields, T G; Duff, P M; Evans, S A; Gemmell, H G; Sharp, P F; Smith, F W; Staff, R T; Wilcock, S E

1997-01-01

OBJECTIVES: To explore the use of 99technetiumm-hexamethyl propylene amine oxime single photon computed tomography (HMPAO-SPECT) of the brain as a means of detecting nervous tissue damage in divers and to determine if there is any correlation between brain image and a diver's history of diving or decompression illness (DCI). METHODS: 28 commercial divers with a history of DCI, 26 divers with no history of DCI, and 19 non-diving controls were examined with brain HMPAO-SPECT. Results were classified by observer assessment as normal (I) or as a pattern variants (II-V). The brain images of a subgroup of these divers (n = 44) and the controls (n = 17) were further analysed with a first order texture analysis technique based on a grey level histogram. RESULTS: 15 of 54 commercial divers (28%) were visually assessed as having HMPAO-SPECT images outside normal limits compared with 15.8% in appropriately identified non-diver control subjects. 18% of divers with a history of DCI were classified as having a pattern different from the normal image compared with 38% with no history of DCI. No association was established between the presence of a pattern variant from the normal image and history of DCI, diving, or other previous possible neurological insult. On texture analysis of the brain images, divers had a significantly lower mean grey level (MGL) than non-divers. Divers with a history of DCI (n = 22) had a significantly lower MGL when compared with divers with no history of DCI (n = 22). Divers with > 14 years professional diving or > 100 decompression days a year had a significantly lower MGL value. CONCLUSIONS: Observer assessment of HMPAO-SPECT brain images can lead to disparity in results. Texture analysis of the brain images supplies both an objective and consistent method of measurement. A significant correlation was found between a low measure of MGL and a history of DCI. There was also an indication that diving itself had an effect on texture measurement, implying that it had caused subclinical nervous tissue damage. PMID:9166130

Bundle Adjustment-Based Stability Analysis Method with a Case Study of a Dual Fluoroscopy Imaging System

NASA Astrophysics Data System (ADS)

Al-Durgham, K.; Lichti, D. D.; Detchev, I.; Kuntze, G.; Ronsky, J. L.

2018-05-01

A fundamental task in photogrammetry is the temporal stability analysis of a camera/imaging-system's calibration parameters. This is essential to validate the repeatability of the parameters' estimation, to detect any behavioural changes in the camera/imaging system and to ensure precise photogrammetric products. Many stability analysis methods exist in the photogrammetric literature; each one has different methodological bases, and advantages and disadvantages. This paper presents a simple and rigorous stability analysis method that can be straightforwardly implemented for a single camera or an imaging system with multiple cameras. The basic collinearity model is used to capture differences between two calibration datasets, and to establish the stability analysis methodology. Geometric simulation is used as a tool to derive image and object space scenarios. Experiments were performed on real calibration datasets from a dual fluoroscopy (DF; X-ray-based) imaging system. The calibration data consisted of hundreds of images and thousands of image observations from six temporal points over a two-day period for a precise evaluation of the DF system stability. The stability of the DF system - for a single camera analysis - was found to be within a range of 0.01 to 0.66 mm in terms of 3D coordinates root-mean-square-error (RMSE), and 0.07 to 0.19 mm for dual cameras analysis. It is to the authors' best knowledge that this work is the first to address the topic of DF stability analysis.

The lucky image-motion prediction for simple scene observation based soft-sensor technology

NASA Astrophysics Data System (ADS)

Li, Yan; Su, Yun; Hu, Bin

2015-08-01

High resolution is important to earth remote sensors, while the vibration of the platforms of the remote sensors is a major factor restricting high resolution imaging. The image-motion prediction and real-time compensation are key technologies to solve this problem. For the reason that the traditional autocorrelation image algorithm cannot meet the demand for the simple scene image stabilization, this paper proposes to utilize soft-sensor technology in image-motion prediction, and focus on the research of algorithm optimization in imaging image-motion prediction. Simulations results indicate that the improving lucky image-motion stabilization algorithm combining the Back Propagation Network (BP NN) and support vector machine (SVM) is the most suitable for the simple scene image stabilization. The relative error of the image-motion prediction based the soft-sensor technology is below 5%, the training computing speed of the mathematical predication model is as fast as the real-time image stabilization in aerial photography.

Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.

PubMed

Somasundaram, Karuppanagounder; Ezhilarasan, Kamalanathan

2015-01-01

To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. The proposed method is based on gray scale transformation and morphological operations. The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.

A prototype MR insertable brain PET using tileable GAPD arrays.

PubMed

Hong, Key Jo; Choi, Yong; Jung, Jin Ho; Kang, Jihoon; Hu, Wei; Lim, Hyun Keong; Huh, Yoonsuk; Kim, Sangsu; Jung, Ji Woong; Kim, Kyu Bom; Song, Myung Sung; Park, Hyun-Wook

2013-04-01

The aim of this study was to develop a prototype magnetic resonance (MR)-compatible positron emission tomography (PET) that can be inserted into a MR imager and that allows simultaneous PET and MR imaging of the human brain. This paper reports the initial results of the authors' prototype brain PET system operating within a 3-T magnetic resonance imaging (MRI) system using newly developed Geiger-mode avalanche photodiode (GAPD)-based PET detectors, long flexible flat cables, position decoder circuit with high multiplexing ratio, and digital signal processing with field programmable gate array-based analog to digital converter boards. A brain PET with 72 detector modules arranged in a ring was constructed and mounted in a 3-T MRI. Each PET module was composed of cerium-doped lutetium yttrium orthosilicate (LYSO) crystals coupled to a tileable GAPD. The GAPD output charge signals were transferred to preamplifiers using 3 m long flat cables. The LYSO and GAPD were located inside the MR bore and all electronics were positioned outside the MR bore. The PET detector performance was investigated both outside and inside the MRI, and MR image quality was evaluated with and without the PET system. The performance of the PET detector when operated inside the MRI during MR image acquisition showed no significant change in energy resolution and count rates, except for a slight degradation in timing resolution with an increase from 4.2 to 4.6 ns. Simultaneous PET/MR images of a hot-rod and Hoffman brain phantom were acquired in a 3-T MRI. Rods down to a diameter of 3.5 mm were resolved in the hot-rod PET image. The activity distribution patterns between the white and gray matter in the Hoffman brain phantom were well imaged. The hot-rod and Hoffman brain phantoms on the simultaneously acquired MR images obtained with standard sequences were observed without any noticeable artifacts, although MR image quality requires some improvement. These results demonstrate that the simultaneous acquisition of PET and MR images is feasible using the MR insertable PET developed in this study.

Learning-based deformable image registration for infant MR images in the first year of life.

PubMed

Hu, Shunbo; Wei, Lifang; Gao, Yaozong; Guo, Yanrong; Wu, Guorong; Shen, Dinggang

2017-01-01

Many brain development studies have been devoted to investigate dynamic structural and functional changes in the first year of life. To quantitatively measure brain development in such a dynamic period, accurate image registration for different infant subjects with possible large age gap is of high demand. Although many state-of-the-art image registration methods have been proposed for young and elderly brain images, very few registration methods work for infant brain images acquired in the first year of life, because of (a) large anatomical changes due to fast brain development and (b) dynamic appearance changes due to white-matter myelination. To address these two difficulties, we propose a learning-based registration method to not only align the anatomical structures but also alleviate the appearance differences between two arbitrary infant MR images (with large age gap) by leveraging the regression forest to predict both the initial displacement vector and appearance changes. Specifically, in the training stage, two regression models are trained separately, with (a) one model learning the relationship between local image appearance (of one development phase) and its displacement toward the template (of another development phase) and (b) another model learning the local appearance changes between the two brain development phases. Then, in the testing stage, to register a new infant image to the template, we first predict both its voxel-wise displacement and appearance changes by the two learned regression models. Since such initializations can alleviate significant appearance and shape differences between new infant image and the template, it is easy to just use a conventional registration method to refine the remaining registration. We apply our proposed registration method to align 24 infant subjects at five different time points (i.e., 2-week-old, 3-month-old, 6-month-old, 9-month-old, and 12-month-old), and achieve more accurate and robust registration results, compared to the state-of-the-art registration methods. The proposed learning-based registration method addresses the challenging task of registering infant brain images and achieves higher registration accuracy compared with other counterpart registration methods. © 2016 American Association of Physicists in Medicine.

Considerations for opto-mechanical vs. digital stabilization in surveillance systems

NASA Astrophysics Data System (ADS)

Kowal, David

2015-05-01

Electro-optical surveillance and reconnaissance systems are frequently mounted on unstable or vibrating platforms such as ships, vehicles, aircraft and masts. Mechanical coupling between the platform and the cameras leads to angular vibration of the line of sight. Image motion during detector and eye integration times leads to image smear and a resulting loss of resolution. Additional effects are wavy images for detectors based on a rolling shutter mechanism and annoying movement of the image at low frequencies. A good stabilization system should yield sub-pixel stabilization errors and meet cost and size requirements. There are two main families of LOS stabilization methods: opto-mechanical stabilization and electronic stabilization. Each family, or a combination of both, can be implemented by a number of different techniques of varying complexity, size and cost leading to different levels of stabilization. Opto-mechanical stabilization is typically based on gyro readings, whereas electronic stabilization is typically based on gyro readings or image registration calculations. A few common stabilization techniques, as well as options for different gimbal arrangements will be described and analyzed. The relative merits and drawbacks of the different techniques and their applicability to specific systems and environments will be discussed. Over the years Controp has developed a large number of stabilized electro-optical payloads. A few examples of payloads with unique stabilization mechanisms will be described.

Imaging Taurine in the Central Nervous System Using Chemically Specific X-ray Fluorescence Imaging at the Sulfur K-Edge

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

Hackett, Mark J.; Paterson, Phyllis G.; Pickering, Ingrid J.

A method to image taurine distributions within the central nervous system and other organs has long been sought. Since taurine is small and mobile, it cannot be chemically “tagged” and imaged using conventional immuno-histochemistry methods. Combining numerous indirect measurements, taurine is known to play critical roles in brain function during health and disease and is proposed to act as a neuro-osmolyte, neuro-modulator, and possibly a neuro-transmitter. Elucidation of taurine’s neurochemical roles and importance would be substantially enhanced by a direct method to visualize alterations, due to physiological and pathological events in the brain, in the local concentration of taurine atmore » or near cellular spatial resolution in vivo or in situ in tissue sections. We thus have developed chemically specific X-ray fluorescence imaging (XFI) at the sulfur K-edge to image the sulfonate group in taurine in situ in ex vivo tissue sections. To our knowledge, this represents the first undistorted imaging of taurine distribution in brain at 20 μm resolution. We report quantitative technique validation by imaging taurine in the cerebellum and hippocampus regions of the rat brain. Further, we apply the technique to image taurine loss from the vulnerable CA1 (cornus ammonis 1) sector of the rat hippocampus following global brain ischemia. The location-specific loss of taurine from CA1 but not CA3 neurons following ischemia reveals osmotic stress may be a key factor in delayed neurodegeneration after a cerebral ischemic insult and highlights the significant potential of chemically specific XFI to study the role of taurine in brain disease.« less

Optimized magnetic resonance diffusion protocol for ex-vivo whole human brain imaging with a clinical scanner

NASA Astrophysics Data System (ADS)

Scherrer, Benoit; Afacan, Onur; Stamm, Aymeric; Singh, Jolene; Warfield, Simon K.

2015-03-01

Diffusion-weighted magnetic resonance imaging (DW-MRI) provides a novel insight into the brain to facilitate our understanding of the brain connectivity and microstructure. While in-vivo DW-MRI enables imaging of living patients and longitudinal studies of brain changes, post-mortem ex-vivo DW-MRI has numerous advantages. Ex-vivo imaging benefits from greater resolution and sensitivity due to the lack of imaging time constraints; the use of tighter fitting coils; and the lack of movement artifacts. This allows characterization of normal and abnormal tissues with unprecedented resolution and sensitivity, facilitating our ability to investigate anatomical structures that are inaccessible in-vivo. This also offers the opportunity to develop today novel imaging biomarkers that will, with tomorrow's MR technology, enable improved in-vivo assessment of the risk of disease in an individual. Post-mortem studies, however, generally rely on the fixation of specimen to inhibit tissue decay which starts as soon as tissue is deprived from its blood supply. Unfortunately, fixation of tissues substantially alters tissue diffusivity profiles. In addition, ex-vivo DW-MRI requires particular care when packaging the specimen because the presence of microscopic air bubbles gives rise to geometric and intensity image distortion. In this work, we considered the specific requirements of post-mortem imaging and designed an optimized protocol for ex-vivo whole brain DW-MRI using a human clinical 3T scanner. Human clinical 3T scanners are available to a large number of researchers and, unlike most animal scanners, have a bore diameter large enough to image a whole human brain. Our optimized protocol will facilitate widespread ex-vivo investigations of large specimen.

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.

Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics.

PubMed

Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek

2013-01-01

Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.

In vivo imaging of scattering and absorption properties of exposed brain using a digital red-green-blue camera

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Yoshida, Keiichiro; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu

2014-03-01

We investigate a method to estimate the spectral images of reduced scattering coefficients and the absorption coefficients of in vivo exposed brain tissues in the range from visible to near-infrared wavelength (500-760 nm) based on diffuse reflectance spectroscopy using a digital RGB camera. In the proposed method, the multi-spectral reflectance images of in vivo exposed brain are reconstructed from the digital red, green blue images using the Wiener estimation algorithm. The Monte Carlo simulation-based multiple regression analysis for the absorbance spectra is then used to specify the absorption and scattering parameters of brain tissue. In this analysis, the concentration of oxygenated hemoglobin and that of deoxygenated hemoglobin are estimated as the absorption parameters whereas the scattering amplitude a and the scattering power b in the expression of μs'=aλ-b as the scattering parameters, respectively. The spectra of absorption and reduced scattering coefficients are reconstructed from the absorption and scattering parameters, and finally, the spectral images of absorption and reduced scattering coefficients are estimated. The estimated images of absorption coefficients were dominated by the spectral characteristics of hemoglobin. The estimated spectral images of reduced scattering coefficients showed a broad scattering spectrum, exhibiting larger magnitude at shorter wavelengths, corresponding to the typical spectrum of brain tissue published in the literature. In vivo experiments with exposed brain of rats during CSD confirmed the possibility of the method to evaluate both hemodynamics and changes in tissue morphology due to electrical depolarization.

Development of a Human Brain Diffusion Tensor Template

PubMed Central

Peng, Huiling; Orlichenko, Anton; Dawe, Robert J.; Agam, Gady; Zhang, Shengwei; Arfanakis, Konstantinos

2009-01-01

The development of a brain template for diffusion tensor imaging (DTI) is crucial for comparisons of neuronal structural integrity and brain connectivity across populations, as well as for the development of a white matter atlas. Previous efforts to produce a DTI brain template have been compromised by factors related to image quality, the effectiveness of the image registration approach, the appropriateness of subject inclusion criteria, the completeness and accuracy of the information summarized in the final template. The purpose of this work was to develop a DTI human brain template using techniques that address the shortcomings of previous efforts. Therefore, data containing minimal artifacts were first obtained on 67 healthy human subjects selected from an age-group with relatively similar diffusion characteristics (20–40 years of age), using an appropriate DTI acquisition protocol. Non-linear image registration based on mean diffusion-weighted and fractional anisotropy images was employed. DTI brain templates containing median and mean tensors were produced in ICBM-152 space and made publicly available. The resulting set of DTI templates is characterized by higher image sharpness, provides the ability to distinguish smaller white matter fiber structures, contains fewer image artifacts, than previously developed templates, and to our knowledge, is one of only two templates produced based on a relatively large number of subjects. Furthermore, median tensors were shown to better preserve the diffusion characteristics at the group level than mean tensors. Finally, white matter fiber tractography was applied on the template and several fiber-bundles were traced. PMID:19341801

Development of a human brain diffusion tensor template.

PubMed

Peng, Huiling; Orlichenko, Anton; Dawe, Robert J; Agam, Gady; Zhang, Shengwei; Arfanakis, Konstantinos

2009-07-15

The development of a brain template for diffusion tensor imaging (DTI) is crucial for comparisons of neuronal structural integrity and brain connectivity across populations, as well as for the development of a white matter atlas. Previous efforts to produce a DTI brain template have been compromised by factors related to image quality, the effectiveness of the image registration approach, the appropriateness of subject inclusion criteria, and the completeness and accuracy of the information summarized in the final template. The purpose of this work was to develop a DTI human brain template using techniques that address the shortcomings of previous efforts. Therefore, data containing minimal artifacts were first obtained on 67 healthy human subjects selected from an age-group with relatively similar diffusion characteristics (20-40 years of age), using an appropriate DTI acquisition protocol. Non-linear image registration based on mean diffusion-weighted and fractional anisotropy images was employed. DTI brain templates containing median and mean tensors were produced in ICBM-152 space and made publicly available. The resulting set of DTI templates is characterized by higher image sharpness, provides the ability to distinguish smaller white matter fiber structures, contains fewer image artifacts, than previously developed templates, and to our knowledge, is one of only two templates produced based on a relatively large number of subjects. Furthermore, median tensors were shown to better preserve the diffusion characteristics at the group level than mean tensors. Finally, white matter fiber tractography was applied on the template and several fiber-bundles were traced.

Imaging human brain cyto- and myelo-architecture with quantitative OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Boas, David A.; Wang, Hui; Konukoglu, Ender; Fischl, Bruce; Sakadzic, Sava; Magnain, Caroline V.

2017-02-01

No current imaging technology allows us to directly and without significant distortion visualize the microscopic and defining anatomical features of the human brain. Ex vivo histological techniques can yield exquisite planar images, but the cutting, mounting and staining that are required components of this type of imaging induce distortions that are different for each slice, introducing cross-slice differences that prohibit true 3D analysis. We are overcoming this issue by utilizing Optical Coherence Tomography (OCT) with the goal to image whole human brain cytoarchitectural and laminar properties with potentially 3.5 µm resolution in block-face without the need for exogenous staining. From the intrinsic scattering contrast of the brain tissue, OCT gives us images that are comparable to Nissl stains, but without the distortions introduced in standard histology as the OCT images are acquired from the block face prior to slicing and thus without the need for subsequent staining and mounting. We have shown that laminar and cytoarchitectural properties of the brain can be characterized with OCT just as well as with Nissl staining. We will present our recent advances to improve the axial resolution while maintaining contrast; improvements afforded by speckle reduction procedures; and efforts to obtain quantitative maps of the optical scattering coefficient, an intrinsic property of the tissue.

Liposome-based glioma targeted drug delivery enabled by stable peptide ligands.

PubMed

Wei, Xiaoli; Gao, Jie; Zhan, Changyou; Xie, Cao; Chai, Zhilan; Ran, Danni; Ying, Man; Zheng, Ping; Lu, Weiyue

2015-11-28

The treatment of glioma is one of the most challenging tasks in clinic. As an intracranial tumor, glioma exhibits many distinctive characteristics from other tumors. In particular, various barriers including enzymatic barriers in the blood and brain capillary endothelial cells, blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB) rigorously prevent drug and drug delivery systems from reaching the tumor site. To tackle this dilemma, we developed a liposomal formulation to circumvent multiple-barriers by modifying the liposome surface with proteolytically stable peptides, (D)CDX and c(RGDyK). (D)CDX is a D-peptide ligand of nicotine acetylcholine receptors (nAChRs) on the BBB, and c(RGDyK) is a ligand of integrin highly expressed on the BBTB and glioma cells. Lysosomal compartments of brain capillary endothelial cells are implicated in the transcytosis of those liposomes. However, both peptide ligands displayed exceptional stability in lysosomal homogenate, ensuring that intact ligands could exert subsequent exocytosis from brain capillary endothelial cells and glioma targeting. In the cellular uptake studies, dually labeled liposomes could target both brain capillary endothelial cells and tumor cells, effectively traversing the BBB and BBTB monolayers, overcoming enzymatic barrier and targeting three-dimensional tumor spheroids. Its targeting ability to intracranial glioma was further verified in vivo by ex vivo imaging and histological studies. As a result, doxorubicin liposomes modified with both (D)CDX and c(RGDyK) presented better anti-glioma effect with prolonged median survival of nude mice bearing glioma than did unmodified liposomes and liposomes modified with individual peptide ligand. In conclusion, the liposome suggested in the present study could effectively overcome multi-barriers and accomplish glioma targeted drug delivery, validating its potential value in improving the therapeutic efficacy of doxorubicin for glioma. Copyright © 2015 Elsevier B.V. All rights reserved.

High-resolution single photon planar and spect imaging of brain and neck employing a system of two co-registered opposed gamma imaging heads

DOEpatents

Majewski, Stanislaw [Yorktown, VA; Proffitt, James [Newport News, VA

2011-12-06

A compact, mobile, dedicated SPECT brain imager that can be easily moved to the patient to provide in-situ imaging, especially when the patient cannot be moved to the Nuclear Medicine imaging center. As a result of the widespread availability of single photon labeled biomarkers, the SPECT brain imager can be used in many locations, including remote locations away from medical centers. The SPECT imager improves the detection of gamma emission from the patient's head and neck area with a large field of view. Two identical lightweight gamma imaging detector heads are mounted to a rotating gantry and precisely mechanically co-registered to each other at 180 degrees. A unique imaging algorithm combines the co-registered images from the detector heads and provides several SPECT tomographic reconstructions of the imaged object thereby improving the diagnostic quality especially in the case of imaging requiring higher spatial resolution and sensitivity at the same time.

Neuroanatomy of the killer whale (Orcinus orca) from magnetic resonance images.

PubMed

Marino, Lori; Sherwood, Chet C; Delman, Bradley N; Tang, Cheuk Y; Naidich, Thomas P; Hof, Patrick R

2004-12-01

This article presents the first series of MRI-based anatomically labeled sectioned images of the brain of the killer whale (Orcinus orca). Magnetic resonance images of the brain of an adult killer whale were acquired in the coronal and axial planes. The gross morphology of the killer whale brain is comparable in some respects to that of other odontocete brains, including the unusual spatial arrangement of midbrain structures. There are also intriguing differences. Cerebral hemispheres appear extremely convoluted and, in contrast to smaller cetacean species, the killer whale brain possesses an exceptional degree of cortical elaboration in the insular cortex, temporal operculum, and the cortical limbic lobe. The functional and evolutionary implications of these features are discussed. (c) 2004 Wiley-Liss, Inc.

Demyelinating and ischemic brain diseases: detection algorithm through regular magnetic resonance images

NASA Astrophysics Data System (ADS)

Castillo, D.; Samaniego, René; Jiménez, Y.; Cuenca, L.; Vivanco, O.; Rodríguez-Álvarez, M. J.

2017-09-01

This work presents the advance to development of an algorithm for automatic detection of demyelinating lesions and cerebral ischemia through magnetic resonance images, which have contributed in paramount importance in the diagnosis of brain diseases. The sequences of images to be used are T1, T2, and FLAIR. Brain demyelination lesions occur due to damage of the myelin layer of nerve fibers; and therefore this deterioration is the cause of serious pathologies such as multiple sclerosis (MS), leukodystrophy, disseminated acute encephalomyelitis. Cerebral or cerebrovascular ischemia is the interruption of the blood supply to the brain, thus interrupting; the flow of oxygen and nutrients needed to maintain the functioning of brain cells. The algorithm allows the differentiation between these lesions.