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CT image segmentation using FEM with optimized boundary condition.
The authors propose a CT image segmentation method using structural analysis that is useful for objects with structural dynamic characteristics. Motivation of our research is from the area of genetic activity. In order to reveal the roles of genes, it is necessary to create mutant mice and measure differences among them by scanning their skeletons with an X-ray CT scanner. The CT image needs to be manually segmented into pieces of the bones. It is a very time consuming to manually segment many mutant mouse models in order to reveal the roles of genes. It is desirable to make this segmentation procedure automatic. Although numerous papers in the past have proposed segmentation techniques, no general segmentation method for skeletons of living creatures has been established. Against this background, the authors propose a segmentation method based on the concept of destruction analogy. To realize this concept, structural analysis is performed using the finite element method (FEM), as structurally weak areas can be expected to break under conditions of stress. The contribution of the method is its novelty, as no studies have so far used structural analysis for image segmentation. The methods implementation involves three steps. First, finite elements are created directly from the pixels of a CT image, and then candidates are also selected in areas where segmentation is thought to be appropriate. The second step involves destruction analogy to find a single candidate with high strain chosen as the segmentation target. The boundary conditions for FEM are also set automatically. Then, destruction analogy is implemented by replacing pixels with high strain as background ones, and this process is iterated until object is decomposed into two parts. Here, CT image segmentation is demonstrated using various types of CT imagery.
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Published: 08-13-2014
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
19 Related JoVE Articles!
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3D Printing of Preclinical X-ray Computed Tomographic Data Sets
Authors: Evan Doney, Lauren A. Krumdick, Justin M. Diener, Connor A. Wathen, Sarah E. Chapman, Brian Stamile, Jeremiah E. Scott, Matthew J. Ravosa, Tony Van Avermaete, W. Matthew Leevy.
Institutions: University of Notre Dame , University of Notre Dame, University of Notre Dame , University of Notre Dame , MakerBot Industries LLC, University of Notre Dame , University of Notre Dame .
Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing. Traditional, mold-injection methods to create models or parts have several limitations, the most important of which is a difficulty in making highly complex products in a timely, cost-effective manner.1 However, gradual improvements in three-dimensional printing technology have resulted in both high-end and economy instruments that are now available for the facile production of customized models.2 These printers have the ability to extrude high-resolution objects with enough detail to accurately represent in vivo images generated from a preclinical X-ray CT scanner. With proper data collection, surface rendering, and stereolithographic editing, it is now possible and inexpensive to rapidly produce detailed skeletal and soft tissue structures from X-ray CT data. Even in the early stages of development, the anatomical models produced by three-dimensional printing appeal to both educators and researchers who can utilize the technology to improve visualization proficiency. 3, 4 The real benefits of this method result from the tangible experience a researcher can have with data that cannot be adequately conveyed through a computer screen. The translation of pre-clinical 3D data to a physical object that is an exact copy of the test subject is a powerful tool for visualization and communication, especially for relating imaging research to students, or those in other fields. Here, we provide a detailed method for printing plastic models of bone and organ structures derived from X-ray CT scans utilizing an Albira X-ray CT system in conjunction with PMOD, ImageJ, Meshlab, Netfabb, and ReplicatorG software packages.
Medicine, Issue 73, Anatomy, Physiology, Molecular Biology, Biomedical Engineering, Bioengineering, Chemistry, Biochemistry, Materials Science, Engineering, Manufactured Materials, Technology, Animal Structures, Life Sciences (General), 3D printing, X-ray Computed Tomography, CT, CT scans, data extrusion, additive printing, in vivo imaging, clinical techniques, imaging
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High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately
Authors: Wenjin Chen, Chung Wong, Evan Vosburgh, Arnold J. Levine, David J. Foran, Eugenia Y. Xu.
Institutions: Raymond and Beverly Sackler Foundation, New Jersey, Rutgers University, Rutgers University, Institute for Advanced Study, New Jersey.
The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application – SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary “Manual Initialize” and “Hand Draw” tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.
Cancer Biology, Issue 89, computer programming, high-throughput, image analysis, tumor spheroids, 3D, software application, cancer therapy, drug screen, neuroendocrine tumor cell line, BON-1, cancer research
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In vivo Imaging of Tumor Angiogenesis using Fluorescence Confocal Videomicroscopy
Authors: Victor Fitoussi, Nathalie Faye, Foucauld Chamming's, Olivier Clement, Charles-Andre Cuenod, Laure S. Fournier.
Institutions: Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Hôpital Européen Georges Pompidou, Service de Radiologie.
Fibered confocal fluorescence in vivo imaging with a fiber optic bundle uses the same principle as fluorescent confocal microscopy. It can excite fluorescent in situ elements through the optical fibers, and then record some of the emitted photons, via the same optical fibers. The light source is a laser that sends the exciting light through an element within the fiber bundle and as it scans over the sample, recreates an image pixel by pixel. As this scan is very fast, by combining it with dedicated image processing software, images in real time with a frequency of 12 frames/sec can be obtained. We developed a technique to quantitatively characterize capillary morphology and function, using a confocal fluorescence videomicroscopy device. The first step in our experiment was to record 5 sec movies in the four quadrants of the tumor to visualize the capillary network. All movies were processed using software (ImageCell, Mauna Kea Technology, Paris France) that performs an automated segmentation of vessels around a chosen diameter (10 μm in our case). Thus, we could quantify the 'functional capillary density', which is the ratio between the total vessel area and the total area of the image. This parameter was a surrogate marker for microvascular density, usually measured using pathology tools. The second step was to record movies of the tumor over 20 min to quantify leakage of the macromolecular contrast agent through the capillary wall into the interstitium. By measuring the ratio of signal intensity in the interstitium over that in the vessels, an 'index leakage' was obtained, acting as a surrogate marker for capillary permeability.
Medicine, Issue 79, Cancer, Biological, Microcirculation, optical imaging devices (design and techniques), Confocal videomicroscopy, microcirculation, capillary leakage, FITC-Dextran, angiogenesis
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Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization
Authors: Vania Tacher, MingDe Lin, Nikhil Bhagat, Nadine Abi Jaoudeh, Alessandro Radaelli, Niels Noordhoek, Bart Carelsen, Bradford J. Wood, Jean-François Geschwind.
Institutions: The Johns Hopkins Hospital, Philips Research North America, National Institutes of Health, Philips Healthcare.
The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 dimensional (3D) diagnostic imaging in the interventional suite and can enhance minimally-invasive therapy beyond the limitations of 2D angiography alone. The role of CBCT has been recognized in transarterial chemo-embolization (TACE) treatment of hepatocellular carcinoma (HCC). The recent introduction of a CBCT technique: dual-phase CBCT (DP-CBCT) improves intra-arterial HCC treatment with drug-eluting beads (DEB-TACE). DP-CBCT can be used to localize liver tumors with the diagnostic accuracy of multi-phasic multidetector computed tomography (M-MDCT) and contrast enhanced magnetic resonance imaging (CE-MRI) (See the tumor), to guide intra-arterially guidewire and microcatheter to the desired location for selective therapy (Reach the tumor), and to evaluate treatment success during the procedure (Treat the tumor). The purpose of this manuscript is to illustrate how DP-CBCT is used in DEB-TACE to see, reach, and treat HCC.
Medicine, Issue 82, Carcinoma, Hepatocellular, Tomography, X-Ray Computed, Surgical Procedures, Minimally Invasive, Digestive System Diseases, Diagnosis, Therapeutics, Surgical Procedures, Operative, Equipment and Supplies, Transarterial chemo-embolization, Hepatocellular carcinoma, Dual-phase cone-beam computed tomography, 3D roadmap, Drug-Eluting Beads
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Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth
Authors: Sabrina Lin, Shawn Fonteno, Shruthi Satish, Bir Bhanu, Prue Talbot.
Institutions: University of California, University of California, University of California, University of California.
Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion.
Cellular Biology, Issue 39, hESC, matrigel, stem cells, video bioinformatics, colony, growth
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Analysis of Nephron Composition and Function in the Adult Zebrafish Kidney
Authors: Kristen K. McCampbell, Kristin N. Springer, Rebecca A. Wingert.
Institutions: University of Notre Dame.
The zebrafish model has emerged as a relevant system to study kidney development, regeneration and disease. Both the embryonic and adult zebrafish kidneys are composed of functional units known as nephrons, which are highly conserved with other vertebrates, including mammals. Research in zebrafish has recently demonstrated that two distinctive phenomena transpire after adult nephrons incur damage: first, there is robust regeneration within existing nephrons that replaces the destroyed tubule epithelial cells; second, entirely new nephrons are produced from renal progenitors in a process known as neonephrogenesis. In contrast, humans and other mammals seem to have only a limited ability for nephron epithelial regeneration. To date, the mechanisms responsible for these kidney regeneration phenomena remain poorly understood. Since adult zebrafish kidneys undergo both nephron epithelial regeneration and neonephrogenesis, they provide an outstanding experimental paradigm to study these events. Further, there is a wide range of genetic and pharmacological tools available in the zebrafish model that can be used to delineate the cellular and molecular mechanisms that regulate renal regeneration. One essential aspect of such research is the evaluation of nephron structure and function. This protocol describes a set of labeling techniques that can be used to gauge renal composition and test nephron functionality in the adult zebrafish kidney. Thus, these methods are widely applicable to the future phenotypic characterization of adult zebrafish kidney injury paradigms, which include but are not limited to, nephrotoxicant exposure regimes or genetic methods of targeted cell death such as the nitroreductase mediated cell ablation technique. Further, these methods could be used to study genetic perturbations in adult kidney formation and could also be applied to assess renal status during chronic disease modeling.
Cellular Biology, Issue 90, zebrafish; kidney; nephron; nephrology; renal; regeneration; proximal tubule; distal tubule; segment; mesonephros; physiology; acute kidney injury (AKI)
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A Mouse Model for Pathogen-induced Chronic Inflammation at Local and Systemic Sites
Authors: George Papadopoulos, Carolyn D. Kramer, Connie S. Slocum, Ellen O. Weinberg, Ning Hua, Cynthia V. Gudino, James A. Hamilton, Caroline A. Genco.
Institutions: Boston University School of Medicine, Boston University School of Medicine.
Chronic inflammation is a major driver of pathological tissue damage and a unifying characteristic of many chronic diseases in humans including neoplastic, autoimmune, and chronic inflammatory diseases. Emerging evidence implicates pathogen-induced chronic inflammation in the development and progression of chronic diseases with a wide variety of clinical manifestations. Due to the complex and multifactorial etiology of chronic disease, designing experiments for proof of causality and the establishment of mechanistic links is nearly impossible in humans. An advantage of using animal models is that both genetic and environmental factors that may influence the course of a particular disease can be controlled. Thus, designing relevant animal models of infection represents a key step in identifying host and pathogen specific mechanisms that contribute to chronic inflammation. Here we describe a mouse model of pathogen-induced chronic inflammation at local and systemic sites following infection with the oral pathogen Porphyromonas gingivalis, a bacterium closely associated with human periodontal disease. Oral infection of specific-pathogen free mice induces a local inflammatory response resulting in destruction of tooth supporting alveolar bone, a hallmark of periodontal disease. In an established mouse model of atherosclerosis, infection with P. gingivalis accelerates inflammatory plaque deposition within the aortic sinus and innominate artery, accompanied by activation of the vascular endothelium, an increased immune cell infiltrate, and elevated expression of inflammatory mediators within lesions. We detail methodologies for the assessment of inflammation at local and systemic sites. The use of transgenic mice and defined bacterial mutants makes this model particularly suitable for identifying both host and microbial factors involved in the initiation, progression, and outcome of disease. Additionally, the model can be used to screen for novel therapeutic strategies, including vaccination and pharmacological intervention.
Immunology, Issue 90, Pathogen-Induced Chronic Inflammation; Porphyromonas gingivalis; Oral Bone Loss; Periodontal Disease; Atherosclerosis; Chronic Inflammation; Host-Pathogen Interaction; microCT; MRI
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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
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Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
Authors: Rushin Shojaii, Stephanie Bacopulos, Wenyi Yang, Tigran Karavardanyan, Demetri Spyropoulos, Afshin Raouf, Anne Martel, Arun Seth.
Institutions: University of Toronto, Sunnybrook Research Institute, University of Toronto, Sunnybrook Research Institute, Medical University of South Carolina, University of Manitoba.
Histology volume reconstruction facilitates the study of 3D shape and volume change of an organ at the level of macrostructures made up of cells. It can also be used to investigate and validate novel techniques and algorithms in volumetric medical imaging and therapies. Creating 3D high-resolution atlases of different organs1,2,3 is another application of histology volume reconstruction. This provides a resource for investigating tissue structures and the spatial relationship between various cellular features. We present an image registration approach for histology volume reconstruction, which uses a set of optical blockface images. The reconstructed histology volume represents a reliable shape of the processed specimen with no propagated post-processing registration error. The Hematoxylin and Eosin (H&E) stained sections of two mouse mammary glands were registered to their corresponding blockface images using boundary points extracted from the edges of the specimen in histology and blockface images. The accuracy of the registration was visually evaluated. The alignment of the macrostructures of the mammary glands was also visually assessed at high resolution. This study delineates the different steps of this image registration pipeline, ranging from excision of the mammary gland through to 3D histology volume reconstruction. While 2D histology images reveal the structural differences between pairs of sections, 3D histology volume provides the ability to visualize the differences in shape and volume of the mammary glands.
Bioengineering, Issue 89, Histology Volume Reconstruction, Transgenic Mouse Model, Image Registration, Digital Histology, Image Processing, Mouse Mammary Gland
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Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS
Authors: Christopher J. Zopf, Narendra Maheshri.
Institutions: Massachusetts Institute of Technology.
Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies depicting the temporal dependence of gene expression provide insight into the dynamics of its regulation; however, there are many technical challenges to obtaining and analyzing fluorescence movies of single cells. We describe here a simple protocol using a commercially available microfluidic culture device to generate such data, and a MATLAB-based, graphical user interface (GUI) -based software package to quantify the fluorescence images. The software segments and tracks cells, enables the user to visually curate errors in the data, and automatically assigns lineage and division times. The GUI further analyzes the time series to produce whole cell traces as well as their first and second time derivatives. While the software was designed for S. cerevisiae, its modularity and versatility should allow it to serve as a platform for studying other cell types with few modifications.
Microbiology, Issue 77, Cellular Biology, Molecular Biology, Genetics, Biophysics, Saccharomyces cerevisiae, Microscopy, Fluorescence, Cell Biology, microscopy/fluorescence and time-lapse, budding yeast, gene expression dynamics, segmentation, lineage tracking, image tracking, software, yeast, cells, imaging
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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Authors: Joel Ramirez, Christopher J.M. Scott, Alicia A. McNeely, Courtney Berezuk, Fuqiang Gao, Gregory M. Szilagyi, Sandra E. Black.
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g. Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs. LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors. While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
Authors: Matthew Moore, Yifan Hu, Sarah Woo, Dylan O'Hearn, Alexandru D. Iordan, Sanda Dolcos, Florin Dolcos.
Institutions: University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign.
The present paper describes a comprehensive protocol for manual tracing of the set of brain regions comprising the medial temporal lobe (MTL): amygdala, hippocampus, and the associated parahippocampal regions (perirhinal, entorhinal, and parahippocampal proper). Unlike most other tracing protocols available, typically focusing on certain MTL areas (e.g., amygdala and/or hippocampus), the integrative perspective adopted by the present tracing guidelines allows for clear localization of all MTL subregions. By integrating information from a variety of sources, including extant tracing protocols separately targeting various MTL structures, histological reports, and brain atlases, and with the complement of illustrative visual materials, the present protocol provides an accurate, intuitive, and convenient guide for understanding the MTL anatomy. The need for such tracing guidelines is also emphasized by illustrating possible differences between automatic and manual segmentation protocols. This knowledge can be applied toward research involving not only structural MRI investigations but also structural-functional colocalization and fMRI signal extraction from anatomically defined ROIs, in healthy and clinical groups alike.
Neuroscience, Issue 89, Anatomy, Segmentation, Medial Temporal Lobe, MRI, Manual Tracing, Amygdala, Hippocampus, Perirhinal Cortex, Entorhinal Cortex, Parahippocampal Cortex
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Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
Authors: Todd A. Sasser, Sarah E. Chapman, Shengting Li, Caroline Hudson, Sean P. Orton, Justin M. Diener, Seth T. Gammon, Carlos Correcher, W. Matthew Leevy.
Institutions: Carestream Molecular Imaging , University of Notre Dame , University of Notre Dame , Oncovision, GEM-Imaging S.A..
Obesity is associated with increased morbidity and mortality as well as reduced metrics in quality of life.1 Both environmental and genetic factors are associated with obesity, though the precise underlying mechanisms that contribute to the disease are currently being delineated.2,3 Several small animal models of obesity have been developed and are employed in a variety of studies.4 A critical component to these experiments involves the collection of regional and/or total animal fat content data under varied conditions. Traditional experimental methods available for measuring fat content in small animal models of obesity include invasive (e.g. ex vivo measurement of fat deposits) and non-invasive (e.g. Dual Energy X-ray Absorptiometry (DEXA), or Magnetic Resonance (MR)) protocols, each of which presents relative trade-offs. Current invasive methods for measuring fat content may provide details for organ and region specific fat distribution, but sacrificing the subjects will preclude longitudinal assessments. Conversely, current non-invasive strategies provide limited details for organ and region specific fat distribution, but enable valuable longitudinal assessment. With the advent of dedicated small animal X-ray computed tomography (CT) systems and customized analytical procedures, both organ and region specific analysis of fat distribution and longitudinal profiling may be possible. Recent reports have validated the use of CT for in vivo longitudinal imaging of adiposity in living mice.5,6 Here we provide a modified method that allows for fat/total volume measurement, analysis and visualization utilizing the Carestream Molecular Imaging Albira CT system in conjunction with PMOD and Volview software packages.
Medicine, Issue 62, X-ray computed tomography (CT), image analysis, in vivo, obesity, metabolic disorders
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High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
Authors: Sucharit Katyal, Clint A. Greene, David Ress.
Institutions: The University of Texas at Austin.
Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures. High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1. Since, T2* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE ~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume. In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4. Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization. In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.
Neuroscience, Issue 63, fMRI, midbrain, brainstem, colliculus, BOLD, brain, Magentic Resonance Imaging, MRI
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
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Monitoring Tumor Metastases and Osteolytic Lesions with Bioluminescence and Micro CT Imaging
Authors: Ed Lim, Kshitij Modi, Anna Christensen, Jeff Meganck, Stephen Oldfield, Ning Zhang.
Institutions: Caliper Life Sciences.
Following intracardiac delivery of MDA-MB-231-luc-D3H2LN cells to Nu/Nu mice, systemic metastases developed in the injected animals. Bioluminescence imaging using IVIS Spectrum was employed to monitor the distribution and development of the tumor cells following the delivery procedure including DLIT reconstruction to measure the tumor signal and its location. Development of metastatic lesions to the bone tissues triggers osteolytic activity and lesions to tibia and femur were evaluated longitudinally using micro CT. Imaging was performed using a Quantum FX micro CT system with fast imaging and low X-ray dose. The low radiation dose allows multiple imaging sessions to be performed with a cumulative X-ray dosage far below LD50. A mouse imaging shuttle device was used to sequentially image the mice with both IVIS Spectrum and Quantum FX achieving accurate animal positioning in both the bioluminescence and CT images. The optical and CT data sets were co-registered in 3-dimentions using the Living Image 4.1 software. This multi-mode approach allows close monitoring of tumor growth and development simultaneously with osteolytic activity.
Medicine, Issue 50, osteolytic lesions, micro CT, tumor, bioluminescence, in vivo, imaging, IVIS, luciferase, low dose, co-registration, 3D reconstruction
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