Patient-specific simulations of heart (dys)function aimed at personalizing cardiac therapy are hampered by the absence of in vivo imaging technology for clinically acquiring myocardial fiber orientations. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4 °. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.The new insights obtained from the project will pave the way for the development of patient-specific models of the heart that can aid physicians in personalized diagnosis and decisions regarding electrophysiological interventions.
17 Related JoVE Articles!
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
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Institutions: Weizmann Institute of Science, Weizmann Institute of Science, Meir Medical Center, Meir Medical Center.
Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI).
The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices.
The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.
Medicine, Issue 94, Magnetic Resonance Imaging, breast, breast cancer, diagnosis, water diffusion, diffusion tensor imaging
Assessment of Cardiac Function and Myocardial Morphology Using Small Animal Look-locker Inversion Recovery (SALLI) MRI in Rats
Institutions: German Heart Institute Berlin, German Heart Institute Berlin, Hamburg, Germany.
Small animal magnetic resonance imaging is an important tool to study cardiac function and changes in myocardial tissue. The high heart rates of small animals (200 to 600 beats/min) have previously limited the role of CMR imaging. Small animal Look-Locker inversion recovery (SALLI) is a T1 mapping sequence for small animals to overcome this problem 1
. T1 maps provide quantitative information about tissue alterations and contrast agent kinetics. It is also possible to detect diffuse myocardial processes such as interstitial fibrosis or edema 1-6
. Furthermore, from a single set of image data, it is possible to examine heart function and myocardial scarring by generating cine and inversion recovery-prepared late gadolinium enhancement-type MR images 1
The presented video shows step-by-step the procedures to perform small animal CMR imaging. Here it is presented with a healthy Sprague-Dawley rat, however naturally it can be extended to different cardiac small animal models.
Medicine, Issue 77, Biomedical Engineering, Anatomy, Physiology, Cardiology, Heart Diseases, Cardiomyopathies, Heart Failure, Diagnostic Imaging, Cardiac Imaging Techniques, Magnetic Resonance Imaging, MRI, Cardiovascular Diseases, small animal imaging, T1 mapping, heart disease, cardiac function, myocardium, rat, animal model
Determination of Protein-ligand Interactions Using Differential Scanning Fluorimetry
Institutions: University of Exeter.
A wide range of methods are currently available for determining the dissociation constant between a protein and interacting small molecules. However, most of these require access to specialist equipment, and often require a degree of expertise to effectively establish reliable experiments and analyze data. Differential scanning fluorimetry (DSF) is being increasingly used as a robust method for initial screening of proteins for interacting small molecules, either for identifying physiological partners or for hit discovery. This technique has the advantage that it requires only a PCR machine suitable for quantitative PCR, and so suitable instrumentation is available in most institutions; an excellent range of protocols are already available; and there are strong precedents in the literature for multiple uses of the method. Past work has proposed several means of calculating dissociation constants from DSF data, but these are mathematically demanding. Here, we demonstrate a method for estimating dissociation constants from a moderate amount of DSF experimental data. These data can typically be collected and analyzed within a single day. We demonstrate how different models can be used to fit data collected from simple binding events, and where cooperative binding or independent binding sites are present. Finally, we present an example of data analysis in a case where standard models do not apply. These methods are illustrated with data collected on commercially available control proteins, and two proteins from our research program. Overall, our method provides a straightforward way for researchers to rapidly gain further insight into protein-ligand interactions using DSF.
Biophysics, Issue 91, differential scanning fluorimetry, dissociation constant, protein-ligand interactions, StepOne, cooperativity, WcbI.
Noninvasive In Vivo Small Animal MRI and MRS: Basic Experimental Procedures
Institutions: University of Washington, University of Washington.
Small animal Magnetic Resonance (MR) research has emerged as an important element of modern biomedical research due to its non-invasive nature and the richness of biological information it provides. MR does not require any ionizing radiation and can noninvasively provide higher resolution and better signal-to-noise ratio in comparison to other tomographic or spectroscopic modalities. In this protocol, we will focus on small animal MR imaging and MR spectroscopy (MRI/MRS) to noninvasively acquire relaxation weighted 1
H images of mouse and to obtain 31
P spectra of mouse muscle. This work does not attempt to cover every aspect of small animal MRI/MRS but rather introduces basic procedures of mouse MRI/MRS experiments. The main goal of this work is to inform researchers of the basic procedures for in vivo
MR experiments on small animals. The goal is to provide a better understanding of basic experimental procedures to allow researchers new to the MR field to better plan for non-MR components of their studies so that both MR and non-MR procedures are seamlessly integrated.
Medicine, Issue 32, Small animal, MRI, MRS, mouse, brain, skeletal muscle, tumor, ischemia
Topographical Estimation of Visual Population Receptive Fields by fMRI
Institutions: Baylor College of Medicine, Max Planck Institute for Biological Cybernetics, Bernstein Center for Computational Neuroscience.
Visual cortex is retinotopically organized so that neighboring populations of cells map to neighboring parts of the visual field. Functional magnetic resonance imaging allows us to estimate voxel-based population receptive fields (pRF), i.e.
, the part of the visual field that activates the cells within each voxel. Prior, direct, pRF estimation methods1
suffer from certain limitations: 1) the pRF model is chosen a-priori and may not fully capture the actual pRF shape, and 2) pRF centers are prone to mislocalization near the border of the stimulus space. Here a new topographical pRF estimation method2
is proposed that largely circumvents these limitations. A linear model is used to predict the Blood Oxygen Level-Dependent (BOLD) signal by convolving the linear response of the pRF to the visual stimulus with the canonical hemodynamic response function. PRF topography is represented as a weight vector whose components represent the strength of the aggregate response of voxel neurons to stimuli presented at different visual field locations. The resulting linear equations can be solved for the pRF weight vector using ridge regression3
, yielding the pRF topography. A pRF model that is matched to the estimated topography can then be chosen post-hoc, thereby improving the estimates of pRF parameters such as pRF-center location, pRF orientation, size, etc
. Having the pRF topography available also allows the visual verification of pRF parameter estimates allowing the extraction of various pRF properties without having to make a-priori assumptions about the pRF structure. This approach promises to be particularly useful for investigating the pRF organization of patients with disorders of the visual system.
Behavior, Issue 96, population receptive field, vision, functional magnetic resonance imaging, retinotopy
Biofunctionalized Prussian Blue Nanoparticles for Multimodal Molecular Imaging Applications
Institutions: Children's National Medical Center, University of Maryland, George Washington University, George Washington University.
Multimodal, molecular imaging allows the visualization of biological processes at cellular, subcellular, and molecular-level resolutions using multiple, complementary imaging techniques. These imaging agents facilitate the real-time assessment of pathways and mechanisms in vivo
, which enhance both diagnostic and therapeutic efficacy. This article presents the protocol for the synthesis of biofunctionalized Prussian blue nanoparticles (PB NPs) - a novel class of agents for use in multimodal, molecular imaging applications. The imaging modalities incorporated in the nanoparticles, fluorescence imaging and magnetic resonance imaging (MRI), have complementary features. The PB NPs possess a core-shell design where gadolinium and manganese ions incorporated within the interstitial spaces of the PB lattice generate MRI contrast, both in T1
-weighted sequences. The PB NPs are coated with fluorescent avidin using electrostatic self-assembly, which enables fluorescence imaging. The avidin-coated nanoparticles are modified with biotinylated ligands that confer molecular targeting capabilities to the nanoparticles. The stability and toxicity of the nanoparticles are measured, as well as their MRI relaxivities. The multimodal, molecular imaging capabilities of these biofunctionalized PB NPs are then demonstrated by using them for fluorescence imaging and molecular MRI in vitro
Bioengineering, Issue 98, Prussian blue, nanoparticles, multimodal imaging, molecular imaging, fluorescence, magnetic resonance imaging, gadolinium, manganese
Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model
Institutions: University of Alabama at Birmingham, University of Alabama at Birmingham, University of Alabama at Birmingham.
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been limitedly used for orthotopic pancreatic tumor xenografts due to severe respiratory motion artifact in the abdominal area. Orthotopic tumor models offer advantages over subcutaneous ones, because those can reflect the primary tumor microenvironment affecting blood supply, neovascularization, and tumor cell invasion. We have recently established a protocol of DCE-MRI of orthotopic pancreatic tumor xenografts in mouse models by securing tumors with an orthogonally bent plastic board to prevent motion transfer from the chest region during imaging. The pressure by this board was localized on the abdominal area, and has not resulted in respiratory difficulty of the animals. This article demonstrates the detailed procedure of orthotopic pancreatic tumor modeling using small animals and DCE-MRI of the tumor xenografts. Quantification method of pharmacokinetic parameters in DCE-MRI is also introduced. The procedure described in this article will assist investigators to apply DCE-MRI for orthotopic gastrointestinal cancer mouse models.
Medicine, Issue 98, Imaging, Cancer, Pancreas, Mouse, Xenograft, DCE-MRI
Cortical Source Analysis of High-Density EEG Recordings in Children
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1
. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2
, because the composition and spatial configuration of head tissues changes dramatically over development3
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials
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
The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
Institutions: University of Montréal, McGill University, University of Minnesota.
Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of neurological and psychiatric disorders such as stroke and depression. Yet, the mechanisms underlying its ability to modulate brain excitability to improve clinical symptoms remains poorly understood 33
. To help improve this understanding, proton magnetic resonance spectroscopy (1
H-MRS) can be used as it allows the in vivo
quantification of brain metabolites such as γ-aminobutyric acid (GABA) and glutamate in a region-specific manner 41
. In fact, a recent study demonstrated that 1
H-MRS is indeed a powerful means to better understand the effects of tDCS on neurotransmitter concentration 34
. This article aims to describe the complete protocol for combining tDCS (NeuroConn MR compatible stimulator) with 1
H-MRS at 3 T using a MEGA-PRESS sequence. We will describe the impact of a protocol that has shown great promise for the treatment of motor dysfunctions after stroke, which consists of bilateral stimulation of primary motor cortices 27,30,31
. Methodological factors to consider and possible modifications to the protocol are also discussed.
Neuroscience, Issue 93, proton magnetic resonance spectroscopy, transcranial direct current stimulation, primary motor cortex, GABA, glutamate, stroke
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
Labeling Stem Cells with Ferumoxytol, an FDA-Approved Iron Oxide Nanoparticle
Institutions: Molecular Imaging Program at Stanford (MIPS) , Stanford University .
Stem cell based therapies offer significant potential for the field of regenerative medicine. However, much remains to be understood regarding the in vivo
kinetics of transplanted cells. A non-invasive method to repetitively monitor transplanted stem cells in vivo
would allow investigators to directly monitor stem cell transplants and identify successful or unsuccessful engraftment outcomes.
A wide range of stem cells continues to be investigated for countless applications. This protocol focuses on 3 different stem cell populations: human embryonic kidney 293 (HEK293) cells, human mesenchymal stem cells (hMSC) and induced pluripotent stem (iPS) cells. HEK 293 cells are derived from human embryonic kidney cells grown in culture with sheared adenovirus 5 DNA. These cells are widely used in research because they are easily cultured, grow quickly and are easily transfected. hMSCs are found in adult marrow. These cells can be replicated as undifferentiated cells while maintaining multipotency or the potential to differentiate into a limited number of cell fates. hMSCs can differentiate to lineages of mesenchymal tissues, including osteoblasts, adipocytes, chondrocytes, tendon, muscle, and marrow stroma. iPS cells are genetically reprogrammed adult cells that have been modified to express genes and factors similar to defining properties of embryonic stem cells. These cells are pluripotent meaning they have the capacity to differentiate into all cell lineages 1
. Both hMSCs and iPS cells have demonstrated tissue regenerative capacity in-vivo
Magnetic resonance (MR) imaging together with the use of superparamagnetic iron oxide (SPIO) nanoparticle cell labels have proven effective for in vivo
tracking of stem cells due to the near microscopic anatomical resolution, a longer blood half-life that permits longitudinal imaging and the high sensitivity for cell detection provided by MR imaging of SPIO nanoparticles 2-4
. In addition, MR imaging with the use of SPIOs is clinically translatable. SPIOs are composed of an iron oxide core with a dextran, carboxydextran or starch surface coat that serves to contain the bioreactive iron core from plasma components. These agents create local magnetic field inhomogeneities that lead to a decreased signal on T2-weighted MR images 5
. Unfortunately, SPIOs are no longer being manufactured. Second generation, ultrasmall SPIOs (USPIO), however, offer a viable alternative. Ferumoxytol (FerahemeTM) is one USPIO composed of a non-stoichiometric magnetite core surrounded by a polyglucose sorbitol carboxymethylether coat. The colloidal, particle size of ferumoxytol is 17-30 nm as determined by light scattering. The molecular weight is 750 kDa, and the relaxivity constant at 2T MRI field is 58.609 mM-1 sec-1 strength4
. Ferumoxytol was recently FDA-approved as an iron supplement for treatment of iron deficiency in patients with renal failure 6
. Our group has applied this agent in an “off label” use for cell labeling applications. Our technique demonstrates efficient labeling of stem cells with ferumoxytol that leads to significant MR signal effects of labeled cells on MR images. This technique may be applied for non-invasive monitoring of stem cell therapies in pre-clinical and clinical settings.
Medicine, Issue 57, USPIO, cell labeling, MR imaging, MRI, molecular imaging, iron oxides, ferumoxytol, cellular imaging, nanoparticles
How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
Institutions: University of Geneva School of Medicine, École Polytechnique Fédérale de Lausanne, University Hospital Center and University of Lausanne, Massachusetts General Hospital.
Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2
, several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry3
. These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface4
. The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index5
, a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name l
ocal Gyrification Index (l
), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion6
, our method was specifically designed to identify early defects of cortical development.
In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer
Software (https://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer
provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the l
GI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study1
. This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues7
, where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.
Medicine, Issue 59, neuroimaging, brain, cortical complexity, cortical development
An in vivo Rodent Model of Contraction-induced Injury and Non-invasive Monitoring of Recovery
Institutions: University of Maryland School of Medicine, University of Maryland School of Medicine, University of Maryland School of Medicine.
Muscle strains are one of the most common complaints treated by physicians. A muscle injury is typically diagnosed from the patient history and physical exam alone, however the clinical presentation can vary greatly depending on the extent of injury, the patient's pain tolerance, etc. In patients with muscle injury or muscle disease, assessment of muscle damage is typically limited to clinical signs, such as tenderness, strength, range of motion, and more recently, imaging studies. Biological markers, such as serum creatine kinase levels, are typically elevated with muscle injury, but their levels do not always correlate with the loss of force production. This is even true of histological findings from animals, which provide a "direct measure" of damage, but do not account for all the loss of function. Some have argued that the most comprehensive measure of the overall health of the muscle in contractile force. Because muscle injury is a random event that occurs under a variety of biomechanical conditions, it is difficult to study. Here, we describe an in vivo
animal model to measure torque and to produce a reliable muscle injury. We also describe our model for measurement of force from an isolated muscle in situ
. Furthermore, we describe our small animal MRI procedure.
Medicine, Issue 51, Skeletal muscle, lengthening contraction, injury, regeneration, contractile function, torque
An Investigation of the Effects of Sports-related Concussion in Youth Using Functional Magnetic Resonance Imaging and the Head Impact Telemetry System
Institutions: University of Toronto, University of Toronto, University of Toronto, Bloorview Kids Rehab, Toronto Rehab, Sunnybrook Health Sciences Centre, University of Toronto.
One of the most commonly reported injuries in children who participate in sports is concussion or mild traumatic brain injury (mTBI)1
. Children and youth involved in organized sports such as competitive hockey are nearly six times more likely to suffer a severe concussion compared to children involved in other leisure physical activities2
. While the most common cognitive sequelae of mTBI appear similar for children and adults, the recovery profile and breadth of consequences in children remains largely unknown2
, as does the influence of pre-injury characteristics (e.g. gender) and injury details (e.g. magnitude and direction of impact) on long-term outcomes. Competitive sports, such as hockey, allow the rare opportunity to utilize a pre-post design to obtain pre-injury data before concussion occurs on youth characteristics and functioning and to relate this to outcome following injury. Our primary goals are to refine pediatric concussion diagnosis and management based on research evidence that is specific to children and youth. To do this we use new, multi-modal and integrative approaches that will:
1.Evaluate the immediate effects of head trauma in youth
2.Monitor the resolution of post-concussion symptoms (PCS) and cognitive performance during recovery
3.Utilize new methods to verify brain injury and recovery
To achieve our goals, we have implemented the Head Impact Telemetry (HIT) System. (Simbex; Lebanon, NH, USA). This system equips commercially available Easton S9 hockey helmets (Easton-Bell Sports; Van Nuys, CA, USA) with single-axis accelerometers designed to measure real-time head accelerations during contact sport participation 3 - 5
. By using telemetric technology, the magnitude of acceleration and location of all head impacts during sport participation can be objectively detected and recorded. We also use functional magnetic resonance imaging (fMRI) to localize and assess changes in neural activity specifically in the medial temporal and frontal lobes during the performance of cognitive tasks, since those are the cerebral regions most sensitive to concussive head injury 6
. Finally, we are acquiring structural imaging data sensitive to damage in brain white matter.
Medicine, Issue 47, Mild traumatic brain injury, concussion, fMRI, youth, Head Impact Telemetry System
Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Institutions: San Diego State University, San Diego State University, San Diego State University, San Diego State University, San Diego State University, Argonne National Laboratory, Broad Institute.
Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.
Immunology, Issue 100, phenomics, phage, viral metagenome, Multi-phenotype Assay Plates (MAPs), continuous culture, metabolomics