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 11C-AcAc and 18F-fluorodeoxyglucose (18F-FDG) are injected sequentially in each animal. This dual tracer PET acquisition is possible because of the short half-life of 11C (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 11C-AcAc and 18F-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.
13 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
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
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
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
Using the BLT Humanized Mouse as a Stem Cell based Gene Therapy Tumor Model
Institutions: David Geffen School of Medicine at UCLA, UCLA AIDS Institute, Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research at UCLA, David Geffen School of Medicine at UCLA, David Geffen School of Medicine at UCLA.
Small animal models such as mice have been extensively used to study human disease and to develop new therapeutic interventions. Despite the wealth of information gained from these studies, the unique characteristics of mouse immunity as well as the species specificity of viral diseases such as human immunodeficiency virus (HIV) infection led to the development of humanized mouse models. The earlier models involved the use of C. B 17 scid/scid mice and the transplantation of human fetal thymus and fetal liver termed thy/liv (SCID-hu) 1, 2
or the adoptive transfer of human peripheral blood leukocytes (SCID-huPBL) 3
. Both models were mainly utilized for the study of HIV infection.
One of the main limitations of both of these models was the lack of stable reconstitution of human immune cells in the periphery to make them a more physiologically relevant model to study HIV disease. To this end, the BLT humanized mouse model was developed. BLT stands for bone marrow/liver/thymus. In this model, 6 to 8 week old NOD.Cg-Prkdcscid Il2rgtm1Wjl
/SzJ (NSG) immunocompromised mice receive the thy/liv implant as in the SCID-hu mouse model only to be followed by a second human hematopoietic stem cell transplant 4
. The advantage of this system is the full reconstitution of the human immune system in the periphery. This model has been used to study HIV infection and latency 5-8
We have generated a modified version of this model in which we use genetically modified human hematopoietic stem cells (hHSC) to construct the thy/liv implant followed by injection of transduced autologous hHSC 7, 9
. This approach results in the generation of genetically modified lineages. More importantly, we adapted this system to examine the potential of generating functional cytotoxic T cells (CTL) expressing a melanoma specific T cell receptor. Using this model we were able to assess the functionality of our transgenic CTL utilizing live positron emission tomography (PET) imaging to determine tumor regression (9).
The goal of this protocol is to describe the process of generating these transgenic mice and assessing in vivo
efficacy using live PET imaging. As a note, since we use human tissues and lentiviral vectors, our facilities conform to CDC NIH guidelines for Biosafety Level 2 (BSL2) with special precautions (BSL2+). In addition, the NSG mice are severely immunocompromised thus, their housing and maintenance must conform to the highest health standards (https://jaxmice.jax.org/research/immunology/005557-housing.html).
Cancer Biology, Issue 70, Stem Cell Biology, Immunology, Biomedical Engineering, Medicine, Bioengineering, Genetics, Oncology, Humanized mice, stem cell transplantation, stem cells, in vivo animal imaging, T cells, cancer, animal model
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
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
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
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
Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization
Institutions: The Johns Hopkins Hospital, Philips Research North America, National Institutes of Health, Philips Healthcare.
The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 dimensional (3D) diagnostic imaging in the interventional suite and can enhance minimally-invasive therapy beyond the limitations of 2D angiography alone. The role of CBCT has been recognized in transarterial chemo-embolization (TACE) treatment of hepatocellular carcinoma (HCC). The recent introduction of a CBCT technique: dual-phase CBCT (DP-CBCT) improves intra-arterial HCC treatment with drug-eluting beads (DEB-TACE). DP-CBCT can be used to localize liver tumors with the diagnostic accuracy of multi-phasic multidetector computed tomography (M-MDCT) and contrast enhanced magnetic resonance imaging (CE-MRI) (See the tumor), to guide intra-arterially guidewire and microcatheter to the desired location for selective therapy (Reach the tumor), and to evaluate treatment success during the procedure (Treat the tumor). The purpose of this manuscript is to illustrate how DP-CBCT is used in DEB-TACE to see, reach, and treat HCC.
Medicine, Issue 82, Carcinoma, Hepatocellular, Tomography, X-Ray Computed, Surgical Procedures, Minimally Invasive, Digestive System Diseases, Diagnosis, Therapeutics, Surgical Procedures, Operative, Equipment and Supplies, Transarterial chemo-embolization, Hepatocellular carcinoma, Dual-phase cone-beam computed tomography, 3D roadmap, Drug-Eluting Beads
Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo
human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g.
Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2
. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs.
LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors.
While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
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