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

2012 ◽  
Vol 44 (15) ◽  
pp. 778-785 ◽  
Author(s):  
Jacqueline A. Gleave ◽  
Michael D. Wong ◽  
Jun Dazai ◽  
Maliha Altaf ◽  
R. Mark Henkelman ◽  
...  
Keyword(s):  
Optical Imaging ◽  
Mouse Brain ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Brain Structures ◽  
Small Scale ◽  
Specimen Preparation ◽  
Normal Brain ◽  
Autofluorescence Imaging ◽  
The Brain

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.

scholarly journals Optical Imaging of Beta-Amyloid Plaques in Alzheimer’s Disease

Biosensors ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 255
Author(s):  
Ziyi Luo ◽  
Hao Xu ◽  
Liwei Liu ◽  
Tymish Y. Ohulchanskyy ◽  
Junle Qu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Optical Imaging ◽  
Imaging Techniques ◽  
High Sensitivity ◽  
Pathological Feature ◽  
Promising Tool ◽  
Abnormal Accumulation ◽  
Accumulation Mechanism ◽  
The Brain

Alzheimer’s disease (AD) is a multifactorial, irreversible, and incurable neurodegenerative disease. The main pathological feature of AD is the deposition of misfolded β-amyloid protein (Aβ) plaques in the brain. The abnormal accumulation of Aβ plaques leads to the loss of some neuron functions, further causing the neuron entanglement and the corresponding functional damage, which has a great impact on memory and cognitive functions. Hence, studying the accumulation mechanism of Aβ in the brain and its effect on other tissues is of great significance for the early diagnosis of AD. The current clinical studies of Aβ accumulation mainly rely on medical imaging techniques, which have some deficiencies in sensitivity and specificity. Optical imaging has recently become a research hotspot in the medical field and clinical applications, manifesting noninvasiveness, high sensitivity, absence of ionizing radiation, high contrast, and spatial resolution. Moreover, it is now emerging as a promising tool for the diagnosis and study of Aβ buildup. This review focuses on the application of the optical imaging technique for the determination of Aβ plaques in AD research. In addition, recent advances and key operational applications are discussed.

scholarly journals A novel technique for fence-post tube placement in glioma using the robot-guided frameless neuronavigation technique under exoscope surgery: patient series

2021 ◽  
Vol 2 (24) ◽  
Keyword(s):  
High Resolution ◽  
Memory Function ◽  
Three Dimensional ◽  
Needle Insertion ◽  
Tube Placement ◽  
Normal Brain ◽  
Puncture Needle ◽  
Surgery Patient ◽  
Fence Post ◽  
The Brain

BACKGROUND Robotic technology is increasingly used in neurosurgery. The authors reported a new technique for fence-post tube placement using robot-guided frameless stereotaxic technology with neuronavigation in patients with glioma. OBSERVATIONS Surgery was performed using the StealthStation S8 linked to the Stealth Autoguide cranial robotic guidance platform and a high-resolution three-dimensional (3D) surgical microscope. A surgical plan was created to determine the removal area using fence-post tube placement at the tumor and normal brain tissue boundary. Using this surgical plan, the robotic system allowed quick and accurate fence-post tube positioning, automatic alignment of the needle insertion and measurement positions in the brain, and quick and accurate puncture needle insertion into the brain tumor. Use of a ventricular drainage tube for the outer needle cylinder allowed placement of the puncture needle in a single operation. Furthermore, use of a high-resolution 3D exoscope allowed the surgeon to simultaneously view the surgical field image and the navigation screen with minimal line-of-sight movement, which improved operative safety. The position memory function of the 3D exoscope allowed easy switching between the exoscope and the microscope and optimal field of view adjustment. LESSONS Fence-post tube placement using robot-guided frameless stereotaxic technology, neuronavigation, and an exoscope allows precise glioma resection.

scholarly journals Quantifying solute spreading and mixing in reservoir rocks using 3-D PET imaging

2016 ◽  
Vol 796 ◽  
pp. 558-587 ◽  
Author(s):  
Ronny Pini ◽  
Nicholas T. Vandehey ◽  
Jennifer Druhan ◽  
James P. O’Neil ◽  
Sally M. Benson
Keyword(s):  
Imaging Techniques ◽  
Three Dimensional ◽  
Tracer Tests ◽  
Spatial Arrangement ◽  
Small Scale ◽  
Local Dispersion ◽  
Advection Dispersion ◽  
Driving Mechanisms ◽  
Positron Emission ◽  
Longitudinal Dispersivity

We report results of an experimental investigation into the effects of small-scale (mm–cm) heterogeneities on solute spreading and mixing in a Berea sandstone core. Pulse-tracer tests have been carried out in the Péclet number regime $Pe=6{-}40$ and are supplemented by a unique combination of two imaging techniques. X-ray computed tomography (CT) is used to quantify subcore-scale heterogeneities in terms of permeability contrasts at a spatial resolution of approximately $10~\text{mm}^{3}$, while [11C] positron emission tomography (PET) is applied to image the spatial and temporal evolution of the full tracer plume non-invasively. To account for both advective spreading and local (Fickian) mixing as driving mechanisms for solute transport, a streamtube model is applied that is based on the one-dimensional advection–dispersion equation. We refer to our modelling approach as semideterministic, because the spatial arrangement of the streamtubes and the corresponding solute travel times are known from the measured rock’s permeability map, which required only small adjustments to match the measured tracer breakthrough curve. The model reproduces the three-dimensional PET measurements accurately by capturing the larger-scale tracer plume deformation as well as subcore-scale mixing, while confirming negligible transverse dispersion over the scale of the experiment. We suggest that the obtained longitudinal dispersivity ($0.10\pm 0.02$  cm) is rock rather than sample specific, because of the ability of the model to decouple subcore-scale permeability heterogeneity effects from those of local dispersion. As such, the approach presented here proves to be very valuable, if not necessary, in the context of reservoir core analyses, because rock samples can rarely be regarded as ‘uniformly heterogeneous’.

scholarly journals Measurement of three-dimensional displacement field in piled embankments using synchrotron X-ray tomography

2019 ◽  
Vol 56 (6) ◽  
pp. 885-892 ◽  
Author(s):  
Louis King ◽  
Abdelmalek Bouazza ◽  
Anton Maksimenko ◽  
Will P. Gates ◽  
Stephen Dubsky
Keyword(s):  
High Resolution ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Physical Models ◽  
Scale Model ◽  
Small Scale ◽  
Full Field ◽  
X Ray ◽  
Wide Range ◽  
Piled Embankments

The measurement of displacement fields by nondestructive imaging techniques opens up the potential to study the pre-failure mechanisms of a wide range of geotechnical problems within physical models. With the advancement of imaging technologies, it has become possible to achieve high-resolution three-dimensional computed tomography volumes of relatively large samples, which may have previously resulted in excessively long scan times or significant imaging artefacts. Imaging of small-scale model piled embankments (142 mm diameter) comprising sand was undertaken using the imaging and medical beamline at the Australian Synchrotron. The monochromatic X-ray beam produced high-resolution reconstructed volumes with a fine texture due to the size and mineralogy of the sand grains as well as the phase contrast enhancement achieved by the monochromatic X-ray beam. The reconstructed volumes were well suited to the application of digital volume correlation, which utilizes cross-correlation techniques to estimate three-dimensional full-field displacement vectors. The output provides insight into the strain localizations that develop within piled embankments and an example of how advanced imaging techniques can be utilized to study the kinematics of physical models.

scholarly journals Three-dimensional visualization of protein expression in mouse brain structures using imaging mass spectrometry

2005 ◽  
Vol 16 (7) ◽  
pp. 1093-1099 ◽  
Author(s):  
Anna C. Crecelius ◽  
D. Shannon Cornett ◽  
Richard M. Caprioli ◽  
Betsy Williams ◽  
Benoit M. Dawant ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Expression ◽  
Mouse Brain ◽  
Imaging Mass Spectrometry ◽  
Three Dimensional ◽  
Brain Structures

scholarly journals Optical imaging and modulation of neurovascular responses

2018 ◽  
Vol 38 (12) ◽  
pp. 2057-2072 ◽  
Author(s):  
Kazuto Masamoto ◽  
Alberto Vazquez
Keyword(s):  
Optical Imaging ◽  
Vascular Function ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Brain Regions ◽  
Transgenic Animal ◽  
Optical Methods ◽  
Vascular Networks ◽  
Temporal Properties ◽  
Dimensional Reconstruction

The cerebral microvasculature consists of pial vascular networks, parenchymal descending arterioles, ascending venules and parenchymal capillaries. This vascular compartmentalization is vital to precisely deliver blood to balance continuously varying neural demands in multiple brain regions. Optical imaging techniques have facilitated the investigation of dynamic spatial and temporal properties of microvascular functions in real time. Their combination with transgenic animal models encoding specific genetic targets have further strengthened the importance of optical methods for neurovascular research by allowing for the modulation and monitoring of neuro vascular function. Image analysis methods with three-dimensional reconstruction are also helping to understand the complexity of microscopic observations. Here, we review the compartmentalized cerebral microvascular responses to global perturbations as well as regional changes in response to neural activity to highlight the differences in vascular action sites. In addition, microvascular responses elicited by optical modulation of different cell-type targets are summarized with emphasis on variable spatiotemporal dynamics of microvascular responses. Finally, long-term changes in microvascular compartmentalization are discussed to help understand potential relationships between CBF disturbances and the development of neurodegenerative diseases and cognitive decline.

scholarly journals A Review of Publicly Available Automatic Brain Segmentation Methodologies, Machine Learning Models, Recent Advancements, and Their Comparison

2021 ◽  
pp. 097275312199017
Author(s):  
Mahender Kumar Singh ◽  
Krishna Kumar Singh
Keyword(s):  
Machine Learning ◽  
Automatic Segmentation ◽  
Three Dimensional ◽  
Brain Structures ◽  
Magnetic Resonance Images ◽  
Learning Models ◽  
Convolutional Network ◽  
Research Perspective ◽  
The Brain ◽  
Machine Learning Models

Background: The noninvasive study of the structure and functions of the brain using neuroimaging techniques is increasingly being used for its clinical and research perspective. The morphological and volumetric changes in several regions and structures of brains are associated with the prognosis of neurological disorders such as Alzheimer’s disease, epilepsy, schizophrenia, etc. and the early identification of such changes can have huge clinical significance. The accurate segmentation of three-dimensional brain magnetic resonance images into tissue types (i.e., grey matter, white matter, cerebrospinal fluid) and brain structures, thus, has huge importance as they can act as early biomarkers. The manual segmentation though considered the “gold standard” is time-consuming, subjective, and not suitable for bigger neuroimaging studies. Several automatic segmentation tools and algorithms have been developed over the years; the machine learning models particularly those using deep convolutional neural network (CNN) architecture are increasingly being applied to improve the accuracy of automatic methods. Purpose: The purpose of the study is to understand the current and emerging state of automatic segmentation tools, their comparison, machine learning models, their reliability, and shortcomings with an intent to focus on the development of improved methods and algorithms. Methods: The study focuses on the review of publicly available neuroimaging tools, their comparison, and emerging machine learning models particularly those based on CNN architecture developed and published during the last five years. Conclusion: Several software tools developed by various research groups and made publicly available for automatic segmentation of the brain show variability in their results in several comparison studies and have not attained the level of reliability required for clinical studies. The machine learning models particularly three dimensional fully convolutional network models can provide a robust and efficient alternative with relation to publicly available tools but perform poorly on unseen datasets. The challenges related to training, computation cost, reproducibility, and validation across distinct scanning modalities for machine learning models need to be addressed.

scholarly journals A MATLAB-based program for three-dimensional quantitative analysis of micronuclei reveals that neuroinflammation induces micronuclei formation in the brain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sarasa Yano ◽  
Kaito Akiyama ◽  
Rio Tsuchiya ◽  
Hikari Kubotani ◽  
Tomoki Chiba ◽  
...  
Keyword(s):  
Imaging Techniques ◽  
Three Dimensional ◽  
Innate Immune ◽  
The Other ◽  
Primary Neurons ◽  
Immune Response Pathway ◽  
The Brain ◽  
Quantitative Procedure

AbstractThe micronucleus is known to be a biomarker for genomic instability, which is a hallmark of tumors and aging. Normally, micronuclei are produced by segregation errors and mechanical stresses arising from dividing or migrating cells, leading to activation of the innate immune response pathway. Although micronuclei often emerge in damaged tissues, the quantitative procedure for analyzing micronuclei accurately has been problematic. Here, we introduce a novel MATLAB-based program for quantifying micronuclei (CAMDi: calculating automatic micronuclei distinction) in vitro and in vivo. CAMDi is adaptable to various experimental imaging techniques and is useful for obtaining reproducible data. CAMDi enables us to measure the accurate size of micronuclei from the three-dimensional images. Using CAMDi, we revealed a novel link between the emergence of micronuclei and neuroinflammation. We found that inflammatory stimulation does not increase the number of micronuclei in primary neurons. On the other hand, the administration of lipopolysaccharide into mice slightly increases micronuclei formation in neurons of the hippocampus region. These findings demonstrate that neuronal micronuclei formations are induced by an inflammatory response in a non-cell-autonomous manner. We provide a novel tool, CAMDi, to quantify micronuclei and demonstrate that neuronal micronuclei are produced not only by the cell-autonomous process but also by the intercellular communication associated with neuroinflammation in vivo.

scholarly journals Illuminating the Brain With X-Rays: Contributions and Future Perspectives of High-Resolution Microtomography to Neuroscience

2021 ◽  
Vol 15 ◽  
Author(s):  
Paulla Vieira Rodrigues ◽  
Katiane Tostes ◽  
Beatriz Pelegrini Bosque ◽  
João Vitor Pereira de Godoy ◽  
Dionisio Pedro Amorim Neto ◽  
...  
Keyword(s):  
Imaging Techniques ◽  
Three Dimensional ◽  
X Rays ◽  
Future Perspectives ◽  
Resonance Imaging ◽  
X Ray ◽  
Cellular Resolution ◽  
Magnetic Resonance Imaging Mri ◽  
Non Destructive ◽  
The Brain

The assessment of three-dimensional (3D) brain cytoarchitecture at a cellular resolution remains a great challenge in the field of neuroscience and constant development of imaging techniques has become crucial, particularly when it comes to offering direct and clear obtention of data from macro to nano scales. Magnetic resonance imaging (MRI) and electron or optical microscopy, although valuable, still face some issues such as the lack of contrast and extensive sample preparation protocols. In this context, x-ray microtomography (μCT) has become a promising non-destructive tool for imaging a broad range of samples, from dense materials to soft biological specimens. It is a new supplemental method to be explored for deciphering the cytoarchitecture and connectivity of the brain. This review aims to bring together published works using x-ray μCT in neurobiology in order to discuss the achievements made so far and the future of this technique for neuroscience.

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