Reliably differentiating brown adipose tissue (BAT) from other tissues using a non-invasive imaging method is an important step toward studying BAT in humans. Detecting BAT is typically confirmed by the uptake of the injected radioactive tracer 18F-Fluorodeoxyglucose (18F-FDG) into adipose tissue depots, as measured by positron emission tomography/computed tomography (PET-CT) scans after exposing the subject to cold stimulus. Fat-water separated magnetic resonance imaging (MRI) has the ability to distinguish BAT without the use of a radioactive tracer. To date, MRI of BAT in adult humans has not been co-registered with cold-activated PET-CT. Therefore, this protocol uses 18F-FDG PET-CT scans to automatically generate a BAT mask, which is then applied to co-registered MRI scans of the same subject. This approach enables measurement of quantitative MRI properties of BAT without manual segmentation. BAT masks are created from two PET-CT scans: after exposure for 2 hr to either thermoneutral (TN) (24 °C) or cold-activated (CA) (17 °C) conditions. The TN and CA PET-CT scans are registered, and the PET standardized uptake and CT Hounsfield values are used to create a mask containing only BAT. CA and TN MRI scans are also acquired on the same subject and registered to the PET-CT scans in order to establish quantitative MRI properties within the automatically defined BAT mask. An advantage of this approach is that the segmentation is completely automated and is based on widely accepted methods for identification of activated BAT (PET-CT). The quantitative MRI properties of BAT established using this protocol can serve as the basis for an MRI-only BAT examination that avoids the radiation associated with PET-CT.
15 Related JoVE Articles!
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 and Analysis of Cerebral Ischemia in Living Rats Using Positron Emission Tomography with 18F-FDG
Institutions: University of Notre Dame, University of Notre Dame, University of Notre Dame, University of Notre Dame, University of Notre Dame.
Stroke is the third leading cause of death among Americans 65 years of age or older1
. The quality of life for patients who suffer from a stroke fails to return to normal in a large majority of patients2
, which is mainly due to current lack of clinical treatment for acute stroke. This necessitates understanding the physiological effects of cerebral ischemia on brain tissue over time and is a major area of active research. Towards this end, experimental progress has been made using rats as a preclinical model for stroke, particularly, using non-invasive methods such as 18
F-fluorodeoxyglucose (FDG) coupled with Positron Emission Tomography (PET) imaging3,10,17
. Here we present a strategy for inducing cerebral ischemia in rats by middle cerebral artery occlusion (MCAO) that mimics focal cerebral ischemia in humans, and imaging its effects over 24 hr using FDG-PET coupled with X-ray computed tomography (CT) with an Albira PET-CT instrument. A VOI template atlas was subsequently fused to the cerebral rat data to enable a unbiased analysis of the brain and its sub-regions4
. In addition, a method for 3D visualization of the FDG-PET-CT time course is presented. In summary, we present a detailed protocol for initiating, quantifying, and visualizing an induced ischemic stroke event in a living Sprague-Dawley rat in three dimensions using FDG-PET.
Medicine, Issue 94, PET, Positron Emission Tomography, Stroke, Cerebral Ischemia, FDG, Brain template, brain atlas, VOI analysis
Use of Electromagnetic Navigational Transthoracic Needle Aspiration (E-TTNA) for Sampling of Lung Nodules
Institutions: Johns Hopkins University.
Lung nodule evaluation represents a clinical challenge especially in patients with intermediate risk for malignancy. Multiple technologies are presently available to sample nodules for pathological diagnosis. Those technologies can be divided into bronchoscopic and non-bronchoscopic interventions. Electromagnetic navigational bronchoscopy is being extensively used for the endobronchial approach to peripheral lung nodules but has been hindered by anatomic challenges resulting in a 70% diagnostic yield. Electromagnetic navigational guided transthoracic needle lung biopsy is novel non-bronchoscopic method that uses a percutaneous electromagnetic tip tracked needle to obtain core biopsy specimens. Electromagnetic navigational transthoracic needle aspiration complements bronchoscopic techniques potentially allowing the provider to maximize the diagnostic yield during one single procedure. This article describes a novel integrated diagnostic approach to pulmonary lung nodules. We propose the use of endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) for mediastinal staging; radial EBUS, navigational bronchoscopy and E-TTNA during one single procedure to maximize diagnostic yield and minimize the number of invasive procedures needed to obtain a diagnosis. This manuscript describes in detail how the navigation transthoracic procedure is performed. Additional clinical studies are needed to determine the clinical utility of this novel technology.
Medicine, Issue 99, Lung nodule, Electromagnetic navigational bronchoscopy, Transthoracic needle aspiration.
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
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
Cerenkov Luminescence Imaging (CLI) for Cancer Therapy Monitoring
Institutions: Stanford University .
In molecular imaging, positron emission tomography (PET) and optical imaging (OI) are two of the most important and thus most widely used modalities1-3
. PET is characterized by its excellent sensitivity and quantification ability while OI is notable for non-radiation, relative low cost, short scanning time, high throughput, and wide availability to basic researchers. However, both modalities have their shortcomings as well. PET suffers from poor spatial resolution and high cost, while OI is mostly limited to preclinical applications because of its limited tissue penetration along with prominent scattering optical signals through the thickness of living tissues.
Recently a bridge between PET and OI has emerged with the discovery of Cerenkov Luminescence Imaging (CLI)4-6
. CLI is a new imaging modality that harnesses Cerenkov Radiation (CR) to image radionuclides with OI instruments. Russian Nobel laureate Alekseyevich Cerenkov and his colleagues originally discovered CR in 1934. It is a form of electromagnetic radiation emitted when a charged particle travels at a superluminal speed in a dielectric medium7,8
. The charged particle, whether positron or electron, perturbs the electromagnetic field of the medium by displacing the electrons in its atoms. After passing of the disruption photons are emitted as the displaced electrons return to the ground state. For instance, one 18
F decay was estimated to produce an average of 3 photons in water5
Since its emergence, CLI has been investigated for its use in a variety of preclinical applications including in vivo
tumor imaging, reporter gene imaging, radiotracer development, multimodality imaging, among others4,5,9,10,11
. The most important reason why CLI has enjoyed much success so far is that this new technology takes advantage of the low cost and wide availability of OI to image radionuclides, which used to be imaged only by more expensive and less available nuclear imaging modalities such as PET.
Here, we present the method of using CLI to monitor cancer drug therapy. Our group has recently investigated this new application and validated its feasibility by a proof-of-concept study12
. We demonstrated that CLI and PET exhibited excellent correlations across different tumor xenografts and imaging probes. This is consistent with the overarching principle of CR that CLI essentially visualizes the same radionuclides as PET. We selected Bevacizumab (Avastin; Genentech/Roche) as our therapeutic agent because it is a well-known angiogenesis inhibitor13,14
. Maturation of this technology in the near future can be envisioned to have a significant impact on preclinical drug development, screening, as well as therapy monitoring of patients receiving treatments.
Cancer Biology, Issue 69, Medicine, Molecular Biology, Cerenkov Luminescence Imaging, CLI, cancer therapy monitoring, optical imaging, PET, radionuclides, Avastin, imaging
RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells
Institutions: Children's Mercy Hospital and Clinics, School of Medicine, University of Missouri-Kansas City.
The characterization of gene expression in cells via measurement of mRNA levels is a useful tool in determining how the transcriptional machinery of the cell is affected by external signals (e.g.
drug treatment), or how cells differ between a healthy state and a diseased state. With the advent and continuous refinement of next-generation DNA sequencing technology, RNA-sequencing (RNA-seq) has become an increasingly popular method of transcriptome analysis to catalog all species of transcripts, to determine the transcriptional structure of all expressed genes and to quantify the changing expression levels of the total set of transcripts in a given cell, tissue or organism1,2
. RNA-seq is gradually replacing DNA microarrays as a preferred method for transcriptome analysis because it has the advantages of profiling a complete transcriptome, providing a digital type datum (copy number of any transcript) and not relying on any known genomic sequence3
Here, we present a complete and detailed protocol to apply RNA-seq to profile transcriptomes in human pulmonary microvascular endothelial cells with or without thrombin treatment. This protocol is based on our recent published study entitled "RNA-seq Reveals Novel Transcriptome of Genes and Their Isoforms in Human Pulmonary Microvascular Endothelial Cells Treated with Thrombin,"4
in which we successfully performed the first complete transcriptome analysis of human pulmonary microvascular endothelial cells treated with thrombin using RNA-seq. It yielded unprecedented resources for further experimentation to gain insights into molecular mechanisms underlying thrombin-mediated endothelial dysfunction in the pathogenesis of inflammatory conditions, cancer, diabetes, and coronary heart disease, and provides potential new leads for therapeutic targets to those diseases.
The descriptive text of this protocol is divided into four parts. The first part describes the treatment of human pulmonary microvascular endothelial cells with thrombin and RNA isolation, quality analysis and quantification. The second part describes library construction and sequencing. The third part describes the data analysis. The fourth part describes an RT-PCR validation assay. Representative results of several key steps are displayed. Useful tips or precautions to boost success in key steps are provided in the Discussion section. Although this protocol uses human pulmonary microvascular endothelial cells treated with thrombin, it can be generalized to profile transcriptomes in both mammalian and non-mammalian cells and in tissues treated with different stimuli or inhibitors, or to compare transcriptomes in cells or tissues between a healthy state and a disease state.
Genetics, Issue 72, Molecular Biology, Immunology, Medicine, Genomics, Proteins, RNA-seq, Next Generation DNA Sequencing, Transcriptome, Transcription, Thrombin, Endothelial cells, high-throughput, DNA, genomic DNA, RT-PCR, PCR
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
Stereotactic Radiosurgery for Gynecologic Cancer
Institutions: University Hospitals Case Medical Center and Case Western Reserve University School of Medicine, University Hospitals Case Medical Center and Case Western Reserve University School of Medicine.
Stereotactic body radiotherapy (SBRT) distinguishes itself by necessitating more rigid patient immobilization, accounting for respiratory motion, intricate treatment planning, on-board imaging, and reduced number of ablative radiation doses to cancer targets usually refractory to chemotherapy and conventional radiation. Steep SBRT radiation dose drop-off permits narrow 'pencil beam' treatment fields to be used for ablative radiation treatment condensed into 1 to 3 treatments.
Treating physicians must appreciate that SBRT comes at a bigger danger of normal tissue injury and chance of geographic tumor miss. Both must be tackled by immobilization of cancer targets and by high-precision treatment delivery. Cancer target immobilization has been achieved through use of indexed customized Styrofoam casts, evacuated bean bags, or body-fix molds with patient-independent abdominal compression.1-3
Intrafraction motion of cancer targets due to breathing now can be reduced by patient-responsive breath hold techniques,4
patient mouthpiece active breathing coordination,5
respiration-correlated computed tomography,6
or image-guided tracking of fiducials implanted within and around a moving tumor.7-9
The Cyberknife system (Accuray [Sunnyvale, CA]) utilizes a radiation linear accelerator mounted on a industrial robotic arm that accurately follows patient respiratory motion by a camera-tracked set of light-emitting diodes (LED) impregnated on a vest fitted to a patient.10
Substantial reductions in radiation therapy margins can be achieved by motion tracking, ultimately rendering a smaller planning target volumes that are irradiated with submillimeter accuracy.11-13
Cancer targets treated by SBRT are irradiated by converging, tightly collimated beams. Resultant radiation dose to cancer target volume histograms have a more pronounced radiation "shoulder" indicating high percentage target coverage and a small high-dose radiation "tail." Thus, increased target conformality comes at the expense of decreased dose uniformity in the SBRT cancer target. This may have implications for both subsequent tumor control in the SBRT target and normal tissue tolerance of organs at-risk. Due to the sharp dose falloff in SBRT, the possibility of occult disease escaping ablative radiation dose occurs when cancer targets are not fully recognized and inadequate SBRT dose margins are applied. Clinical target volume (CTV) expansion by 0.5 cm, resulting in a larger planning target volume (PTV), is associated with increased target control without undue normal tissue injury.7,8
Further reduction in the probability of geographic miss may be achieved by incorporation of 2-[18
F-FDG) positron emission tomography (PET).8
Use of 18
F-FDG PET/CT in SBRT treatment planning is only the beginning of attempts to discover new imaging target molecular signatures for gynecologic cancers.
Medicine, Issue 62, radiosurgery, Cyberknife stereotactic radiosurgery, radiation, ovarian cancer, cervix cancer
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
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Institutions: The Feinstein Institute for Medical Research.
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.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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
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
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
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