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Evaluation of non-local means based denoising filters for diffusion kurtosis imaging using a new phantom.
PUBLISHED: 02-03-2015
Image denoising has a profound impact on the precision of estimated parameters in diffusion kurtosis imaging (DKI). This work first proposes an approach to constructing a DKI phantom that can be used to evaluate the performance of denoising algorithms in regard to their abilities of improving the reliability of DKI parameter estimation. The phantom was constructed from a real DKI dataset of a human brain, and the pipeline used to construct the phantom consists of diffusion-weighted (DW) image filtering, diffusion and kurtosis tensor regularization, and DW image reconstruction. The phantom preserves the image structure while minimizing image noise, and thus can be used as ground truth in the evaluation. Second, we used the phantom to evaluate three representative algorithms of non-local means (NLM). Results showed that one scheme of vector-based NLM, which uses DWI data with redundant information acquired at different b-values, produced the most reliable estimation of DKI parameters in terms of Mean Square Error (MSE), Bias and standard deviation (Std). The result of the comparison based on the phantom was consistent with those based on real datasets.
Authors: Kan N. Hor, Rolf Baumann, Gianni Pedrizzetti, Gianni Tonti, William M. Gottliebson, Michael Taylor, D. Woodrow Benson, Wojciech Mazur.
Published: 02-12-2011
Purpose: An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that strain is a more sensitive and earlier marker for contractile dysfunction than the frequently used parameter EF. Current technologies for CMR are time consuming and difficult to implement in clinical practice. Feature tracking is a technology that can lead to more automization and robustness of quantitative analysis of medical images with less time consumption than comparable methods. Methods: An automatic or manual input in a single phase serves as an initialization from which the system starts to track the displacement of individual patterns representing anatomical structures over time. The specialty of this method is that the images do not need to be manipulated in any way beforehand like e.g. tagging of CMR images. Results: The method is very well suited for tracking muscular tissue and with this allowing quantitative elaboration of myocardium and also blood flow. Conclusions: This new method offers a robust and time saving procedure to quantify myocardial tissue and blood with displacement, velocity and deformation parameters on regular sequences of CMR imaging. It therefore can be implemented in clinical practice.
17 Related JoVE Articles!
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Diffusion Imaging in the Rat Cervical Spinal Cord
Authors: Elizabeth Zakszewski, Brian Schmit, Shekar Kurpad, Matthew D. Budde.
Institutions: Medical College of Wisconsin, Marquette University.
Magnetic resonance imaging (MRI) is the state of the art approach for assessing the status of the spinal cord noninvasively, and can be used as a diagnostic and prognostic tool in cases of disease or injury. Diffusion weighted imaging (DWI), is sensitive to the thermal motion of water molecules and allows for inferences of tissue microstructure. This report describes a protocol to acquire and analyze DWI of the rat cervical spinal cord on a small-bore animal system. It demonstrates an imaging setup for the live anesthetized animal and recommends a DWI acquisition protocol for high-quality imaging, which includes stabilization of the cord and control of respiratory motion. Measurements with diffusion weighting along different directions and magnitudes (b-values) are used. Finally, several mathematical models of the resulting signal are used to derive maps of the diffusion processes within the spinal cord tissue that provide insight into the normal cord and can be used to monitor injury or disease processes noninvasively.
Neurobiology, Issue 98, spinal cord, magnetic resonance imaging, diffusion tensor imaging, respiratory gating, diffusion kurtosis imaging, rat, spine
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Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
Authors: Yongsook C. Lee, Gary D. Fullerton, Beth A. Goins.
Institutions: University of Kansas School of Medicine, University of Texas Health Science Center at San Antonio.
World Health Organization (WHO) and the Response Evaluation Criteria in Solid Tumors (RECIST) working groups advocated standardized criteria for radiologic assessment of solid tumors in response to anti-tumor drug therapy in the 1980s and 1990s, respectively. WHO criteria measure solid tumors in two-dimensions, whereas RECIST measurements use only one-dimension which is considered to be more reproducible 1, 2, 3,4,5. These criteria have been widely used as the only imaging biomarker approved by the United States Food and Drug Administration (FDA) 6. In order to measure tumor response to anti-tumor drugs on images with accuracy, therefore, a robust quality assurance (QA) procedures and corresponding QA phantom are needed. To address this need, the authors constructed a preclinical multimodality (for ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI)) phantom using tissue-mimicking (TM) materials based on the limited number of target lesions required by RECIST by revising a Gammex US commercial phantom 7. The Appendix in Lee et al. demonstrates the procedures of phantom fabrication 7. In this article, all protocols are introduced in a step-by-step fashion beginning with procedures for preparing the silicone molds for casting tumor-simulating test objects in the phantom, followed by preparation of TM materials for multimodality imaging, and finally construction of the preclinical multimodality QA phantom. The primary purpose of this paper is to provide the protocols to allow anyone interested in independently constructing a phantom for their own projects. QA procedures for tumor size measurement, and RECIST, WHO and volume measurement results of test objects made at multiple institutions using this QA phantom are shown in detail in Lee et al. 8.
Biomedical Engineering, Issue 77, Bioengineering, Medicine, Anatomy, Physiology, Cancer Biology, Molecular Biology, Genetics, Therapeutics, Chemistry and Materials (General), Composite Materials, Quality Assurance and Reliability, Physics (General), Tissue-mimicking materials, Preclinical, Multimodality, Quality assurance, Phantom, Tumor size measurement, Cancer, Imaging
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Preparation and Using Phantom Lesions to Practice Fine Needle Aspiration Biopsies
Authors: Vinod B. Shidham, George M. Varsegi, Krista D'Amore, Anjani Shidham.
Institutions: University of Wisconsin - Milwaukee, BioInnovation LLC.
Currently, health workers including residents and fellows do not have a suitable phantom model to practice the fine- needle aspiration biopsy (FNAB) procedure. In the past, we standardized a model consisting of latex glove containing fresh cattle liver for practicing FNAB. However, this model is difficult to organize and prepare on short notice, with the procurement of fresh cattle liver being the most challenging aspect. Handling of liver with contamination-related problems is also a significant draw back. In addition, the glove material leaks after a few needle passes, with resulting mess. We have established a novel simple method of embedding a small piece of sausage or banana in a commercially available silicone rubber caulk. This model allows the retention of vacuum seal and aspiration of material from the embedded specimen, resembling an actual FNAB procedure on clinical mass lesions. The aspirated material in the needle hub can be processed similar to the specimens procured during an actual FNAB procedure, facilitating additional proficiency in smear preparation and staining.
Medicine, Issue 31, FNA, FNAB, Fine Needle Aspiration Biopsy, Proficiency, procedure, Cytopathology, cytology
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
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
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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
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Tissue-simulating Phantoms for Assessing Potential Near-infrared Fluorescence Imaging Applications in Breast Cancer Surgery
Authors: Rick Pleijhuis, Arwin Timmermans, Johannes De Jong, Esther De Boer, Vasilis Ntziachristos, Gooitzen Van Dam.
Institutions: University Medical Center Groningen, Technical University of Munich.
Inaccuracies in intraoperative tumor localization and evaluation of surgical margin status result in suboptimal outcome of breast-conserving surgery (BCS). Optical imaging, in particular near-infrared fluorescence (NIRF) imaging, might reduce the frequency of positive surgical margins following BCS by providing the surgeon with a tool for pre- and intraoperative tumor localization in real-time. In the current study, the potential of NIRF-guided BCS is evaluated using tissue-simulating breast phantoms for reasons of standardization and training purposes. Breast phantoms with optical characteristics comparable to those of normal breast tissue were used to simulate breast conserving surgery. Tumor-simulating inclusions containing the fluorescent dye indocyanine green (ICG) were incorporated in the phantoms at predefined locations and imaged for pre- and intraoperative tumor localization, real-time NIRF-guided tumor resection, NIRF-guided evaluation on the extent of surgery, and postoperative assessment of surgical margins. A customized NIRF camera was used as a clinical prototype for imaging purposes. Breast phantoms containing tumor-simulating inclusions offer a simple, inexpensive, and versatile tool to simulate and evaluate intraoperative tumor imaging. The gelatinous phantoms have elastic properties similar to human tissue and can be cut using conventional surgical instruments. Moreover, the phantoms contain hemoglobin and intralipid for mimicking absorption and scattering of photons, respectively, creating uniform optical properties similar to human breast tissue. The main drawback of NIRF imaging is the limited penetration depth of photons when propagating through tissue, which hinders (noninvasive) imaging of deep-seated tumors with epi-illumination strategies.
Medicine, Issue 91, Breast cancer, tissue-simulating phantoms, NIRF imaging, tumor-simulating inclusions, fluorescence, intraoperative imaging
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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Authors: Noam Nissan, Edna Furman-Haran, Myra Feinberg-Shapiro, Dov Grobgeld, Erez Eyal, Tania Zehavi, Hadassa Degani.
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
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Biofunctionalized Prussian Blue Nanoparticles for Multimodal Molecular Imaging Applications
Authors: Jennifer M. Vojtech, Juliana Cano-Mejia, Matthieu F. Dumont, Raymond W. Sze, Rohan Fernandes.
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 and T2-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
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Image-guided Convection-enhanced Delivery into Agarose Gel Models of the Brain
Authors: Karl A. Sillay, S. Gray McClatchy, Brandon A. Shepherd, Garrett T. Venable, Tyler S. Fuehrer.
Institutions: University of Tennessee Health Science Center, Semmes-Murphey Clinic, University of Arkansas for Medical Sciences, Restorative Neurosciences Foundation.
Convection-enhanced delivery (CED) has been proposed as a treatment option for a wide range of neurological diseases. Neuroinfusion catheter CED allows for positive pressure bulk flow to deliver greater quantities of therapeutics to an intracranial target than traditional drug delivery methods. The clinical utility of real time MRI guided CED (rCED) lies in the ability to accurately target, monitor therapy, and identify complications. With training, rCED is efficient and complications may be minimized. The agarose gel model of the brain provides an accessible tool for CED testing, research, and training. Simulated brain rCED allows practice of the mock surgery while also providing visual feedback of the infusion. Analysis of infusion allows for calculation of the distribution fraction (Vd/Vi) allowing the trainee to verify the similarity of the model as compared to human brain tissue. This article describes our agarose gel brain phantom and outlines important metrics during a CED infusion and analysis protocols while addressing common pitfalls faced during CED infusion for the treatment of neurological disease.
Medicine, Issue 87, Convection-enhanced delivery, agarose gel, volumes of distribution, gel infusion, Vd/Vi, MRI, Neurosurgery
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
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
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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Authors: Fijoy Vadakkumpadan, Hermenegild Arevalo, Natalia A. Trayanova.
Institutions: Johns Hopkins University.
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.
Bioengineering, Issue 71, Biomedical Engineering, Medicine, Anatomy, Physiology, Cardiology, Myocytes, Cardiac, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, MRI, Diffusion Magnetic Resonance Imaging, Cardiac Electrophysiology, computerized simulation (general), mathematical modeling (systems analysis), Cardiomyocyte, biomedical image processing, patient-specific modeling, Electrophysiology, simulation
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
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Adaptation of a Haptic Robot in a 3T fMRI
Authors: Joseph Snider, Markus Plank, Larry May, Thomas T. Liu, Howard Poizner.
Institutions: University of California, University of California, University of California.
Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal 1 with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data 2, and nearly real-time analyses 3. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot 4 allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1). The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments 5, 6, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ˜380 to ˜330, and ˜250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (˜2.6 lbs) but extremely stiff 3/4" graphite and well balanced on the 3DoF joint in the middle. The end result is an fMRI compatible, haptic system with about 1 cubic foot of working space, and, when combined with virtual reality, it allows for a new set of experiments to be performed in the fMRI environment including naturalistic reaching, passive displacement of the limb and haptic perception, adaptation learning in varying force fields, or texture identification 5, 6.
Bioengineering, Issue 56, neuroscience, haptic robot, fMRI, MRI, pointing
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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
Authors: Steve Burion, Tobias Funk.
Institutions: Triple Ring Technologies.
X-ray fluoroscopy is widely used for image guidance during cardiac intervention. However, radiation dose in these procedures can be high, and this is a significant concern, particularly in pediatric applications. Pediatrics procedures are in general much more complex than those performed on adults and thus are on average four to eight times longer1. Furthermore, children can undergo up to 10 fluoroscopic procedures by the age of 10, and have been shown to have a three-fold higher risk of developing fatal cancer throughout their life than the general population2,3. We have shown that radiation dose can be significantly reduced in adult cardiac procedures by using our scanning beam digital x-ray (SBDX) system4-- a fluoroscopic imaging system that employs an inverse imaging geometry5,6 (Figure 1, Movie 1 and Figure 2). Instead of a single focal spot and an extended detector as used in conventional systems, our approach utilizes an extended X-ray source with multiple focal spots focused on a small detector. Our X-ray source consists of a scanning electron beam sequentially illuminating up to 9,000 focal spot positions. Each focal spot projects a small portion of the imaging volume onto the detector. In contrast to a conventional system where the final image is directly projected onto the detector, the SBDX uses a dedicated algorithm to reconstruct the final image from the 9,000 detector images. For pediatric applications, dose savings with the SBDX system are expected to be smaller than in adult procedures. However, the SBDX system allows for additional dose savings by implementing an electronic adaptive exposure technique. Key to this method is the multi-beam scanning technique of the SBDX system: rather than exposing every part of the image with the same radiation dose, we can dynamically vary the exposure depending on the opacity of the region exposed. Therefore, we can significantly reduce exposure in radiolucent areas and maintain exposure in more opaque regions. In our current implementation, the adaptive exposure requires user interaction (Figure 3). However, in the future, the adaptive exposure will be real time and fully automatic. We have performed experiments with an anthropomorphic phantom and compared measured radiation dose with and without adaptive exposure using a dose area product (DAP) meter. In the experiment presented here, we find a dose reduction of 30%.
Bioengineering, Issue 55, Scanning digital X-ray, fluoroscopy, pediatrics, interventional cardiology, adaptive exposure, dose savings
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High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT
Authors: Amnon Sharir, Gregory Ramniceanu, Vlad Brumfeld.
Institutions: Weizmann Institute of Science, Weizmann Institute of Science, Weizmann Institute of Science.
Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized tomography (μCT). High resolution μCT is a very versatile yet accurate (1-2 microns of resolution) technique for 3D examination of ex-vivo biological samples1, 2. As opposed to electron tomography, the μCT allows the examination of up to 4 cm thick samples. This technique requires only few hours of measurement as compared to weeks in histology. In addition, μCT does not rely on 2D stereologic models, thus it may complement and in some cases can even replace histological methods3, 4, which are both time consuming and destructive. Sample conditioning and positioning in μCT is straightforward and does not require high vacuum or low temperatures, which may adversely affect the structure. The sample is positioned and rotated 180° or 360°between a microfocused x-ray source and a detector, which includes a scintillator and an accurate CCD camera, For each angle a 2D image is taken, and then the entire volume is reconstructed using one of the different available algorithms5-7. The 3D resolution increases with the decrease of the rotation step. The present video protocol shows the main steps in preparation, immobilization and positioning of the sample followed by imaging at high resolution.
Bioengineering, Issue 52, 3D imaging, tomography, x-ray, non invasive, ex-vivo
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Hybrid µCT-FMT imaging and image analysis
Authors: Felix Gremse, Dennis Doleschel, Sara Zafarnia, Anne Babler, Willi Jahnen-Dechent, Twan Lammers, Wiltrud Lederle, Fabian Kiessling.
Institutions: RWTH Aachen University, RWTH Aachen University, Utrecht University.
Fluorescence-mediated tomography (FMT) enables longitudinal and quantitative determination of the fluorescence distribution in vivo and can be used to assess the biodistribution of novel probes and to assess disease progression using established molecular probes or reporter genes. The combination with an anatomical modality, e.g., micro computed tomography (µCT), is beneficial for image analysis and for fluorescence reconstruction. We describe a protocol for multimodal µCT-FMT imaging including the image processing steps necessary to extract quantitative measurements. After preparing the mice and performing the imaging, the multimodal data sets are registered. Subsequently, an improved fluorescence reconstruction is performed, which takes into account the shape of the mouse. For quantitative analysis, organ segmentations are generated based on the anatomical data using our interactive segmentation tool. Finally, the biodistribution curves are generated using a batch-processing feature. We show the applicability of the method by assessing the biodistribution of a well-known probe that binds to bones and joints.
Bioengineering, Issue 100, Fluorescence-mediated Tomography, Computed Tomography, Image Segmentation, Multimodal Imaging, Image Analysis, Hybrid Imaging, Biodistribution, Diffuse Optical Tomography
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.