The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
24 Related JoVE Articles!
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo
. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls.
DTI data analysis is performed in a variate fashion, i.e.
voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e.
differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
Probe-based Confocal Laser Endomicroscopy of the Urinary Tract: The Technique
Institutions: Stanford University School of Medicine , Veterans Affairs Palo Alto Health Care System.
Probe-based confocal laser endomicroscopy (CLE) is an emerging optical imaging technology that enables real-time in vivo
microscopy of mucosal surfaces during standard endoscopy. With applications currently in the respiratory1
and gastrointestinal tracts,2-6
CLE has also been explored in the urinary tract for bladder cancer diagnosis.7-10
Cellular morphology and tissue microarchitecture can be resolved with micron scale resolution in real time, in addition to dynamic imaging of the normal and pathological vasculature.7
The probe-based CLE system (Cellvizio, Mauna Kea Technologies, France) consists of a reusable fiberoptic imaging probe coupled to a 488 nm laser scanning unit. The imaging probe is inserted in the working channels of standard flexible and rigid endoscopes. An endoscope-based CLE system (Optiscan, Australia), in which the confocal endomicroscopy functionality is integrated onto the endoscope, is also used in the gastrointestinal tract. Given the larger scope diameter, however, application in the urinary tract is currently limited to ex vivo
Confocal image acquisition is done through direct contact of the imaging probe with the target tissue and recorded as video sequences. As in the gastrointestinal tract, endomicroscopy of the urinary tract requires an exogenenous contrast agent—most commonly fluorescein, which can be administered intravenously or intravesically. Intravesical administration is a well-established method to introduce pharmacological agents locally with minimal systemic toxicity that is unique to the urinary tract. Fluorescein rapidly stains the extracellular matrix and has an established safety profile.12
Imaging probes of various diameters enable compatibility with different caliber endoscopes. To date, 1.4 and 2.6 mm probes have been evaluated with flexible and rigid cystoscopy.10
Recent availability of a < 1 mm imaging probe13
opens up the possibility of CLE in the upper urinary tract during ureteroscopy. Fluorescence cystoscopy (i.e.
photodynamic diagnosis) and narrow band imaging are additional endoscope-based optical imaging modalities14
that can be combined with CLE to achieve multimodal imaging of the urinary tract. In the future, CLE may be coupled with molecular contrast agents such as fluorescently labeled peptides15
and antibodies for endoscopic imaging of disease processes with molecular specificity.
Medicine, Issue 71, Anatomy, Physiology, Cancer Biology, Surgery, Basic Protocols, Confocal laser endomicroscopy, microscopy, endoscopy, cystoscopy, human bladder, bladder cancer, urology, minimally invasive, cellular imaging
Detection of Neuritic Plaques in Alzheimer's Disease Mouse Model
Institutions: The University of British Columbia.
Alzheimer's disease (AD) is the most common neurodegenerative disorder leading to dementia. Neuritic plaque formation is one of the pathological hallmarks of Alzheimer's disease. The central component of neuritic plaques is a small filamentous protein called amyloid β protein (Aβ)1
, which is derived from sequential proteolytic cleavage of the beta-amyloid precursor protein (APP) by β-secretase and γ-secretase. The amyloid hypothesis entails that Aγ-containing plaques as the underlying toxic mechanism in AD pathology2
. The postmortem analysis of the presence of neuritic plaque confirms the diagnosis of AD. To further our understanding of Aγ neurobiology in AD pathogenesis, various mouse strains expressing AD-related mutations in the human APP genes were generated. Depending on the severity of the disease, these mice will develop neuritic plaques at different ages. These mice serve as invaluable tools for studying the pathogenesis and drug development that could affect the APP processing pathway and neuritic plaque formation. In this protocol, we employ an immunohistochemical method for specific detection of neuritic plaques in AD model mice. We will specifically discuss the preparation from extracting the half brain, paraformaldehyde fixation, cryosectioning, and two methods to detect neurotic plaques in AD transgenic mice: immunohistochemical detection using the ABC and DAB method and fluorescent detection using thiofalvin S staining method.
Neuroscience, Issue 53, Alzheimer’s disease, neuritic plaques, Amyloid β protein, APP, transgenic mouse
A Dual Tracer PET-MRI Protocol for the Quantitative Measure of Regional Brain Energy Substrates Uptake in the Rat
Institutions: Université de Sherbrooke, Université de Sherbrooke, Université de Sherbrooke, Université de Sherbrooke.
We present a method for comparing the uptake of the brain's two key energy substrates: glucose and ketones (acetoacetate [AcAc] in this case) in the rat. The developed method is a small-animal positron emission tomography (PET) protocol, in which 11
C-AcAc and 18
F-FDG) are injected sequentially in each animal. This dual tracer PET acquisition is possible because of the short half-life of 11
C (20.4 min). The rats also undergo a magnetic resonance imaging (MRI) acquisition seven days before the PET protocol. Prior to image analysis, PET and MRI images are coregistered to allow the measurement of regional cerebral uptake (cortex, hippocampus, striatum, and cerebellum). A quantitative measure of 11
C-AcAc and 18
F-FDG brain uptake (cerebral metabolic rate; μmol/100 g/min) is determined by kinetic modeling using the image-derived input function (IDIF) method. Our new dual tracer PET protocol is robust and flexible; the two tracers used can be replaced by different radiotracers to evaluate other processes in the brain. Moreover, our protocol is applicable to the study of brain fuel supply in multiple conditions such as normal aging and neurodegenerative pathologies such as Alzheimer's and Parkinson's diseases.
Neuroscience, Issue 82, positron emission tomography (PET), 18F-fluorodeoxyglucose, 11C-acetoacetate, magnetic resonance imaging (MRI), kinetic modeling, cerebral metabolic rate, rat
MRI and PET in Mouse Models of Myocardial Infarction
Institutions: Unversity of Cambridge, University of Cambridge, University of Cambridge.
Myocardial infarction is one of the leading causes of death in the Western world. The similarity of the mouse heart to the human heart has made it an ideal model for testing novel therapeutic strategies.
magnetic resonance imaging (MRI) gives excellent views of the heart noninvasively with clear anatomical detail, which can be used for accurate functional assessment. Contrast agents can provide basic measures of tissue viability but these are nonspecific. Positron emission tomography (PET) is a complementary technique that is highly specific for molecular imaging, but lacks the anatomical detail of MRI. Used together, these techniques offer a sensitive, specific and quantitative tool for the assessment of the heart in disease and recovery following treatment.
In this paper we explain how these methods are carried out in mouse models of acute myocardial infarction. The procedures described here were designed for the assessment of putative protective drug treatments. We used MRI to measure systolic function and infarct size with late gadolinium enhancement, and PET with fluorodeoxyglucose (FDG) to assess metabolic function in the infarcted region. The paper focuses on practical aspects such as slice planning, accurate gating, drug delivery, segmentation of images, and multimodal coregistration. The methods presented here achieve good repeatability and accuracy maintaining a high throughput.
Medicine, Issue 82, anatomy, Late Gadolinium Enhancement (LGE), MRI, FDG PET, MRI/PET imaging, myocardial infarction, mouse model, contrast agents, coregistration
Cerenkov Luminescence Imaging of Interscapular Brown Adipose Tissue
Institutions: Massachusetts General Hospital/Harvard Medical School, China Pharmaceutical University, Perkin Elmer.
Brown adipose tissue (BAT), widely known as a “good fat” plays pivotal roles for thermogenesis in mammals. This special tissue is closely related to metabolism and energy expenditure, and its dysfunction is one important contributor for obesity and diabetes. Contrary to previous belief, recent PET/CT imaging studies indicated the BAT depots are still present in human adults. PET imaging clearly shows that BAT has considerably high uptake of 18
F-FDG under certain conditions. In this video report, we demonstrate that Cerenkov luminescence imaging (CLI) with 18
F-FDG can be used to optically image BAT in small animals. BAT activation is observed after intraperitoneal injection of norepinephrine (NE) and cold treatment, and depression of BAT is induced by long anesthesia. Using multiple-filter Cerenkov luminescence imaging, spectral unmixing and 3D imaging reconstruction are demonstrated. Our results suggest that CLI with 18
F-FDG is a practical technique for imaging BAT in small animals, and this technique can be used as a cheap, fast, and alternative imaging tool for BAT research.
Medicine, Issue 92, Cerenkov luminescence imaging, brown adipose tissue, 18F-FDG, optical imaging, in vivo imaging, spectral unmixing
Quantification of Atherosclerotic Plaque Activity and Vascular Inflammation using [18-F] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT)
Institutions: University of Pennsylvania, Perelman School of Medicine, University of Pennsylvania, Perelman School of Medicine, University of Pennsylvania, Perelman School of Medicine.
Conventional non-invasive imaging modalities of atherosclerosis such as coronary artery calcium (CAC)1
and carotid intimal medial thickness (C-IMT)2
provide information about the burden of disease. However, despite multiple validation studies of CAC3-5
, and C-IMT2,6
, these modalities do not accurately assess plaque characteristics7,8
, and the composition and inflammatory state of the plaque determine its stability and, therefore, the risk of clinical events9-13
F]-2-fluoro-2-deoxy-D-glucose (FDG) imaging using positron-emission tomography (PET)/computed tomography (CT) has been extensively studied in oncologic metabolism14,15
. Studies using animal models and immunohistochemistry in humans show that FDG-PET/CT is exquisitely sensitive for detecting macrophage activity16
, an important source of cellular inflammation in vessel walls. More recently, we17,18
and others have shown that FDG-PET/CT enables highly precise, novel measurements of inflammatory activity of activity of atherosclerotic plaques in large and medium-sized arteries9,16,19,20
. FDG-PET/CT studies have many advantages over other imaging modalities: 1) high contrast resolution; 2) quantification of plaque volume and metabolic activity allowing for multi-modal atherosclerotic plaque quantification; 3) dynamic, real-time, in vivo
imaging; 4) minimal operator dependence. Finally, vascular inflammation detected by FDG-PET/CT has been shown to predict cardiovascular (CV) events independent of traditional risk factors21,22
and is also highly associated with overall burden of atherosclerosis23
. Plaque activity by FDG-PET/CT is modulated by known beneficial CV interventions such as short term (12 week) statin therapy24
as well as longer term therapeutic lifestyle changes (16 months)25
The current methodology for quantification of FDG uptake in atherosclerotic plaque involves measurement of the standardized uptake value (SUV) of an artery of interest and of the venous blood pool in order to calculate a target to background ratio (TBR), which is calculated by dividing the arterial SUV by the venous blood pool SUV. This method has shown to represent a stable, reproducible phenotype over time, has a high sensitivity for detection of vascular inflammation, and also has high inter-and intra-reader reliability26
. Here we present our methodology for patient preparation, image acquisition, and quantification of atherosclerotic plaque activity and vascular inflammation using SUV, TBR, and a global parameter called the metabolic volumetric product (MVP). These approaches may be applied to assess vascular inflammation in various study samples of interest in a consistent fashion as we have shown in several prior publications.9,20,27,28
Medicine, Issue 63, FDG-PET/CT, atherosclerosis, vascular inflammation, quantitative radiology, imaging
Non-invasive Imaging of Acute Allograft Rejection after Rat Renal Transplantation Using 18F-FDG PET
Institutions: University of Münster, University of Münster, University of Münster.
The number of patients with end-stage renal disease, and the number of kidney allograft recipients continuously increases. Episodes of acute cellular allograft rejection (AR) are a negative prognostic factor for long-term allograft survival, and its timely diagnosis is crucial for allograft function 1
. At present, AR can only be definitely diagnosed by core-needle biopsy, which, as an invasive method, bares significant risk of graft injury or even loss. Moreover, biopsies are not feasible in patients taking anticoagulant drugs and the limited sampling site of this technique may result in false negative results if the AR is focal or patchy. As a consequence, this gave rise to an ongoing search for new AR detection methods, which often has to be done in animals including the use of various transplantation models.
Since the early 60s rat renal transplantation is a well-established experimental method for the examination and analysis of AR 2
. We herein present in addition small animal positron emission tomography (PET) using 18
F-fluorodeoxyglucose (FDG) to assess AR in an allogeneic uninephrectomized rat renal transplantation model and propose graft FDG-PET imaging as a new option for a non-invasive, specific and early diagnosis of AR also for the human situation 3
. Further, this method can be applied for follow-up to improve monitoring of transplant rejection 4
Medicine, Issue 74, Molecular Biology, Biomedical Engineering, Bioengineering, Cellular Biology, Anatomy, Physiology, Immunology, Surgery, Tissue Engineering, Nephrology, transplantation, rat, kidney, renal, acute rejection, allograft, imaging, histology, positron emisson tomography, PET, 18F-fluorodeoxyglucose, FDG, rat, animal model
Functional Imaging of Brown Fat in Mice with 18F-FDG micro-PET/CT
Institutions: The Methodist Hospital Research Institute, Houston, The Methodist Hospital Research Institute, Houston.
Brown adipose tissue (BAT) differs from white adipose tissue (WAT) by its discrete location and a brown-red color due to rich vascularization and high density of mitochondria. BAT plays a major role in energy expenditure and non-shivering thermogenesis in newborn mammals as well as the adults 1
. BAT-mediated thermogenesis is highly regulated by the sympathetic nervous system, predominantly via β adrenergic receptor 2, 3
. Recent studies have shown that BAT activities in human adults are negatively correlated with body mass index (BMI) and other diabetic parameters 4-6
. BAT has thus been proposed as a potential target for anti-obesity/anti-diabetes therapy focusing on modulation of energy balance 6-8
. While several cold challenge-based positron emission tomography (PET) methods are established for detecting human BAT 9-13
, there is essentially no standardized protocol for imaging and quantification of BAT in small animal models such as mice. Here we describe a robust PET/CT imaging method for functional assessment of BAT in mice. Briefly, adult C57BL/6J mice were cold treated under fasting conditions for a duration of 4 hours before they received one dose of 18
F-Fluorodeoxyglucose (FDG). The mice were remained in the cold for one additional hour post FDG injection, and then scanned with a small animal-dedicated micro-PET/CT system. The acquired PET images were co-registered with the CT images for anatomical references and analyzed for FDG uptake in the interscapular BAT area to present BAT activity. This standardized cold-treatment and imaging protocol has been validated through testing BAT activities during pharmacological interventions, for example, the suppressed BAT activation by the treatment of β-adrenoceptor antagonist propranolol 14, 15
, or the enhanced BAT activation by β3 agonist BRL37344 16
. The method described here can be applied to screen for drugs/compounds that modulate BAT activity, or to identify genes/pathways that are involved in BAT development and regulation in various preclinical and basic studies.
Molecular Biology, Issue 69, Neuroscience, Anatomy, Physiology, Medicine, Brown adipose tissue, mice, 18F-Fluorodeoxyglucose, micro-PET, PET, CT, CT scan, tomography, imaging
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Institutions: Yale University School of Medicine, NatureMost Laboratories, Bruker Preclinical Imaging.
Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of care consisting of surgical debulking and combination chemotherapy consisting of platinum and taxane compounds, almost 90% of patients recur within a few years. In these patients the development of chemoresistant disease limits the efficacy of currently available chemotherapy agents and therefore contributes to the high mortality. To discover novel therapy options that can target recurrent disease, appropriate animal models that closely mimic the clinical profile of patients with recurrent ovarian cancer are required. The challenge in monitoring intra-peritoneal (i.p.) disease limits the use of i.p. models and thus most xenografts are established subcutaneously. We have developed a sensitive optical imaging platform that allows the detection and anatomical location of i.p. tumor mass. The platform includes the use of optical reporters that extend from the visible light range to near infrared, which in combination with 2-dimensional X-ray co-registration can provide anatomical location of molecular signals. Detection is significantly improved by the use of a rotation system that drives the animal to multiple angular positions for 360 degree imaging, allowing the identification of tumors that are not visible in single orientation. This platform provides a unique model to non-invasively monitor tumor growth and evaluate the efficacy of new therapies for the prevention or treatment of recurrent ovarian cancer.
Cancer Biology, Issue 93, ovarian cancer, recurrence, in vivo imaging, tumor burden, cancer stem cells, chemotherapy
Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking
Institutions: Yale University, Yale University, Yale University, Yale University, Massachusetts General Hospital, University of California, Irvine.
We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized.
We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7
. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8
that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11
C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7
to a conventional model 9
. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.
Behavior, Issue 78, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Medicine, Anatomy, Physiology, Image Processing, Computer-Assisted, Receptors, Dopamine, Dopamine, Functional Neuroimaging, Binding, Competitive, mathematical modeling (systems analysis), Neurotransmission, transient, dopamine release, PET, modeling, linear, time-invariant, smoking, F-test, ventral-striatum, clinical techniques
Direct Imaging of ER Calcium with Targeted-Esterase Induced Dye Loading (TED)
Institutions: University of Wuerzburg, Max Planck Institute of Neurobiology, Martinsried, Ludwig-Maximilians University of Munich.
Visualization of calcium dynamics is important to understand the role of calcium in cell physiology. To examine calcium dynamics, synthetic fluorescent Ca2+
indictors have become popular. Here we demonstrate TED (= targeted-esterase induced dye loading), a method to improve the release of Ca2+
indicator dyes in the ER lumen of different cell types. To date, TED was used in cell lines, glial cells, and neurons in vitro
. TED bases on efficient, recombinant targeting of a high carboxylesterase activity to the ER lumen using vector-constructs that express Carboxylesterases (CES). The latest TED vectors contain a core element of CES2 fused to a red fluorescent protein, thus enabling simultaneous two-color imaging. The dynamics of free calcium in the ER are imaged in one color, while the corresponding ER structure appears in red. At the beginning of the procedure, cells are transduced with a lentivirus. Subsequently, the infected cells are seeded on coverslips to finally enable live cell imaging. Then, living cells are incubated with the acetoxymethyl ester (AM-ester) form of low-affinity Ca2+
indicators, for instance Fluo5N-AM, Mag-Fluo4-AM, or Mag-Fura2-AM. The esterase activity in the ER cleaves off hydrophobic side chains from the AM form of the Ca2+
indicator and a hydrophilic fluorescent dye/Ca2+
complex is formed and trapped in the ER lumen. After dye loading, the cells are analyzed at an inverted confocal laser scanning microscope. Cells are continuously perfused with Ringer-like solutions and the ER calcium dynamics are directly visualized by time-lapse imaging. Calcium release from the ER is identified by a decrease in fluorescence intensity in regions of interest, whereas the refilling of the ER calcium store produces an increase in fluorescence intensity. Finally, the change in fluorescent intensity over time is determined by calculation of ΔF/F0
Cellular Biology, Issue 75, Neurobiology, Neuroscience, Molecular Biology, Biochemistry, Biomedical Engineering, Bioengineering, Virology, Medicine, Anatomy, Physiology, Surgery, Endoplasmic Reticulum, ER, Calcium Signaling, calcium store, calcium imaging, calcium indicator, metabotropic signaling, Ca2+, neurons, cells, mouse, animal model, cell culture, targeted esterase induced dye loading, imaging
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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
) (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
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
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.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
Consensus Brain-derived Protein, Extraction Protocol for the Study of Human and Murine Brain Proteome Using Both 2D-DIGE and Mini 2DE Immunoblotting
Institutions: Inserm UMR 837, CHRU-Lille, Faculté de Médecine - Pôle Recherche, CHRU-Lille.
Two-dimensional gel electrophoresis (2DE) is a powerful tool to uncover proteome modifications potentially related to different physiological or pathological conditions. Basically, this technique is based on the separation of proteins according to their isoelectric point in a first step, and secondly according to their molecular weights by SDS polyacrylamide gel electrophoresis (SDS-PAGE). In this report an optimized sample preparation protocol for little amount of human post-mortem and mouse brain tissue is described. This method enables to perform both two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) and mini 2DE immunoblotting. The combination of these approaches allows one to not only find new proteins and/or protein modifications in their expression thanks to its compatibility with mass spectrometry detection, but also a new insight into markers validation. Thus, mini-2DE coupled to western blotting permits to identify and validate post-translational modifications, proteins catabolism and provides a qualitative comparison among different conditions and/or treatments. Herein, we provide a method to study components of protein aggregates found in AD and Lewy body dementia such as the amyloid-beta peptide and the alpha-synuclein. Our method can thus be adapted for the analysis of the proteome and insoluble proteins extract from human brain tissue and mice models too. In parallel, it may provide useful information for the study of molecular and cellular pathways involved in neurodegenerative diseases as well as potential novel biomarkers and therapeutic targets.
Neuroscience, Issue 86, proteomics, neurodegeneration, 2DE, human and mice brain tissue, fluorescence, immunoblotting.
Abbreviations: 2DE (two-dimensional gel electrophoresis), 2D-DIGE (two-dimensional fluorescence difference gel electrophoresis), mini-2DE (mini 2DE immunoblotting),IPG (Immobilized pH Gradients), IEF (isoelectrofocusing), AD (Alzheimer´s disease)
Modeling Astrocytoma Pathogenesis In Vitro and In Vivo Using Cortical Astrocytes or Neural Stem Cells from Conditional, Genetically Engineered Mice
Institutions: University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, Emory University School of Medicine, University of North Carolina School of Medicine.
Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro
using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro
. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo
. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo
tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro
and in vivo
and may be useful in preclinical drug development for these devastating diseases.
Neuroscience, Issue 90, astrocytoma, cortical astrocytes, genetically engineered mice, glioblastoma, neural stem cells, orthotopic allograft
Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
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
Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples
Institutions: Institute for Hepatitis and Virus Research, Thomas Jefferson University , Drexel University College of Medicine, Van Andel Research Institute, Serome Biosciences Inc..
In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed.
Glycosylation of protein, which is the most ubiquitous post-translational modification on proteins, modifies the physical, chemical, and biological properties of a protein, and plays a fundamental role in various biological processes1-6
. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases 7-12
. In fact, most current cancer biomarkers, such as the L3 fraction of α-1 fetoprotein (AFP) for hepatocellular carcinoma 13-15
, and CA199 for pancreatic cancer 16, 17
are all aberrant glycan moieties on glycoproteins. However, methods to study protein glycosylation have been complicated, and not suitable for routine laboratory and clinical settings. Chen et al.
has recently invented a chemically blocked antibody microarray with a glycan-binding protein (GBP) detection method for high-throughput and multiplexed profile glycosylation of native glycoproteins in a complex sample 18
. In this affinity based microarray method, multiple immobilized glycoprotein-specific antibodies capture and isolate glycoproteins from the complex mixture directly on the microarray slide, and the glycans on each individual captured protein are measured by GBPs. Because all normal antibodies contain N-glycans which could be recognized by most GBPs, the critical step of this method is to chemically block the glycans on the antibodies from binding to GBP. In the procedure, the cis
-diol groups of the glycans on the antibodies were first oxidized to aldehyde groups by using NaIO4
in sodium acetate buffer avoiding light. The aldehyde groups were then conjugated to the hydrazide group of a cross-linker, 4-(4-N-MaleimidoPhenyl)butyric acid Hydrazide HCl (MPBH), followed by the conjugation of a dipeptide, Cys-Gly, to the maleimide group of the MPBH. Thus, the cis-diol groups on glycans of antibodies were converted into bulky none hydroxyl groups, which hindered the lectins and other GBPs bindings to the capture antibodies. This blocking procedure makes the GBPs and lectins bind only to the glycans of captured proteins. After this chemically blocking, serum samples were incubated with the antibody microarray, followed by the glycans detection by using different biotinylated lectins and GBPs, and visualized with Cy3-streptavidin. The parallel use of an antibody panel and multiple lectin probing provides discrete glycosylation profiles of multiple proteins in a given sample 18-20
. This method has been used successfully in multiple different labs 1, 7, 13, 19-31
. However, stability of MPBH and Cys-Gly, complicated and extended procedure in this method affect the reproducibility, effectiveness and efficiency of the method. In this new protocol, we replaced both MPBH and Cys-Gly with one much more stable reagent glutamic acid hydrazide (Glu-hydrazide), which significantly improved the reproducibility of the method, simplified and shorten the whole procedure so that the it can be completed within one working day. In this new protocol, we describe the detailed procedure of the protocol which can be readily adopted by normal labs for routine protein glycosylation study and techniques which are necessary to obtain reproducible and repeatable results.
Molecular Biology, Issue 63, Glycoproteins, glycan-binding protein, specific protein glycosylation, multiplexed high-throughput glycan blocked antibody microarray
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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
Reaggregate Thymus Cultures
Institutions: University of Birmingham .
Stromal cells within lymphoid tissues are organized into three-dimensional structures that provide a scaffold that is thought to control the migration and development of haemopoeitic cells. Importantly, the maintenance of this three-dimensional organization appears to be critical for normal stromal cell function, with two-dimensional monolayer cultures often being shown to be capable of supporting only individual fragments of lymphoid tissue function. In the thymus, complex networks of cortical and medullary epithelial cells act as a framework that controls the recruitment, proliferation, differentiation and survival of lymphoid progenitors as they undergo the multi-stage process of intrathymic T-cell development. Understanding the functional role of individual stromal compartments in the thymus is essential in determining how the thymus imposes self/non-self discrimination. Here we describe a technique in which we exploit the plasticity of fetal tissues to re-associate into intact three-dimensional structures in vitro
, following their enzymatic disaggregation. The dissociation of fetal thymus lobes into heterogeneous cellular mixtures, followed by their separation into individual cellular components, is then combined with the in vitro
re-association of these desired cell types into three-dimensional reaggregate structures at defined ratios, thereby providing an opportunity to investigate particular aspects of T-cell development under defined cellular conditions. (This article is based on work first reported Methods in Molecular Biology 2007, Vol. 380 pages 185-196).
Immunology, Issue 18, Springer Protocols, Thymus, 2-dGuo, Thymus Organ Cultures, Immune Tolerance, Positive and Negative Selection, Lymphoid Development
A New Single Chamber Implantable Defibrillator with Atrial Sensing: A Practical Demonstration of Sensing and Ease of Implantation
Institutions: University Hospital of Rostock, Germany.
Implantable cardioverter-defibrillators (ICDs) terminate ventricular tachycardia (VT) and ventricular fibrillation (VF) with high efficacy and can protect patients from sudden cardiac death (SCD). However, inappropriate shocks may occur if tachycardias are misdiagnosed. Inappropriate shocks are harmful and impair patient quality of life. The risk of inappropriate therapy increases with lower detection rates programmed in the ICD. Single-chamber detection poses greater risks for misdiagnosis when compared with dual-chamber devices that have the benefit of additional atrial information. However, using a dual-chamber device merely for the sake of detection is generally not accepted, since the risks associated with the second electrode may outweigh the benefits of detection. Therefore, BIOTRONIK developed a ventricular lead called the LinoxSMART
S DX, which allows for the detection of atrial signals from two electrodes positioned at the atrial part of the ventricular electrode. This device contains two ring electrodes; one that contacts the atrial wall at the junction of the superior vena cava (SVC) and one positioned at the free floating part of the electrode in the atrium. The excellent signal quality can only be achieved by a special filter setting in the ICD (Lumax 540 and 740 VR-T DX, BIOTRONIK). Here, the ease of implantation of the system will be demonstrated.
Medicine, Issue 60, Implantable defibrillator, dual chamber, single chamber, tachycardia detection
Basics of Multivariate Analysis in Neuroimaging Data
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9
. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
Institutions: The Johns Hopkins University.
In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death 1
. To date, the only effective treatment for melanoma remains surgical excision, therefore, the key to extended survival is early detection 2,3
. Considering the large numbers of patients diagnosed every year and the limitations in accessing specialized care quickly, the development of objective in vivo
diagnostic instruments to aid the diagnosis is essential. New techniques to detect skin cancer, especially non-invasive diagnostic tools, are being explored in numerous laboratories. Along with the surgical methods, techniques such as digital photography, dermoscopy, multispectral imaging systems (MelaFind), laser-based systems (confocal scanning laser microscopy, laser doppler perfusion imaging, optical coherence tomography), ultrasound, magnetic resonance imaging, are being tested. Each technique offers unique advantages and disadvantages, many of which pose a compromise between effectiveness and accuracy versus ease of use and cost considerations. Details about these techniques and comparisons are available in the literature 4
Infrared (IR) imaging was shown to be a useful method to diagnose the signs of certain diseases by measuring the local skin temperature. There is a large body of evidence showing that disease or deviation from normal functioning are accompanied by changes of the temperature of the body, which again affect the temperature of the skin 5,6
. Accurate data about the temperature of the human body and skin can provide a wealth of information on the processes responsible for heat generation and thermoregulation, in particular the deviation from normal conditions, often caused by disease. However, IR imaging has not been widely recognized in medicine due to the premature use of the technology 7,8
several decades ago, when temperature measurement accuracy and the spatial resolution were inadequate and sophisticated image processing tools were unavailable. This situation changed dramatically in the late 1990s-2000s. Advances in IR instrumentation, implementation of digital image processing algorithms and dynamic IR imaging, which enables scientists to analyze not only the spatial, but also the temporal thermal behavior of the skin 9
, allowed breakthroughs in the field.
In our research, we explore the feasibility of IR imaging, combined with theoretical and experimental studies, as a cost effective, non-invasive, in vivo optical measurement technique for tumor detection, with emphasis on the screening and early detection of melanoma 10-13
. In this study, we show data obtained in a patient study in which patients that possess a pigmented lesion with a clinical indication for biopsy are selected for imaging. We compared the difference in thermal responses between healthy and malignant tissue and compared our data with biopsy results. We concluded that the increased metabolic activity of the melanoma lesion can be detected by dynamic infrared imaging.
Medicine, Issue 51, Infrared imaging, quantitative thermal analysis, image processing, skin cancer, melanoma, transient thermal response, skin thermal models, skin phantom experiment, patient study