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A new approach for vascular super resolution imaging using the erythrocytes as targets (SURE imaging) is described and investigated. SURE imaging does not require fragile contrast agent bubbles, making it possible to use the maximum allowable mechanical index for ultrasound scanning for an increased penetration depth. A synthetic aperture ultrasound sequence was employed with 12 virtual sources using a 10 MHz GE L8-18i-D linear array hockey stick probe. The axial resolution was 1.20λ,(185.0µm) and the lateral resolution was 1.50λ,(231.3µm). Field IIpro simulations were conducted on 12.5 µm radius vessel pairs with varying separations. A vessel pair with a separation of 70 µm could be resolved, indicating a SURE image resolution below half a wavelength. A Verasonics research scanner was used for the in vivo experiments to scan the kidneys of Sprague-Dawley rats for up to 46 s to visualize their microvasculature by processing from 0.1 up to 45 s of data for SURE imaging, and for 46.8 s for super resolution (SR) imaging with a SonoVue contrast agent. Afterward, the renal vasculature was filled with the ex vivo micro-CT contrast agent Microfil, excised, and scanned in a micro-CT scanner at both a 22.6 µm voxel size for 11 hours, and for 20 hours in a 5 µm voxel size for validating the SURE images. Comparing the SURE and micro-CT images revealed that vessels with a diameter of 28 µm, five times smaller than the ultrasound wavelength, could be detected, and the dense grid of microvessels in the full kidney was shown for scan times between 1 to 10 s. The vessel structure in the cortex was also similar for the SURE and SR images. Fourier ring correlation indicated a resolution capability of 29 µm. SURE images are acquired in seconds rather than minutes without any patient preparation or contrast injection, making the method translatable to clinical use.
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Super resolution ultrasound imaging using the erythrocytes (SURE) has recently been introduced. The method uses erythrocytes as targets instead of fragile microbubbles (MBs). The abundance of erythrocyte scatterers makes it possible to acquire SURE data in just a few seconds compared to several minutes in ultrasound localization microscopy (ULM) using MBs. A high number of scatterers can reduce the acquisition time, however, the tracking of uncorrelated and high-density scatterers is quite challenging. This paper hypothesizes that it is possible to detect and track erythrocytes as targets to obtain vascular flow images. A SURE tracking pipeline is used with modules for beamforming, recursive synthetic aperture imaging, motion estimation, echo canceling, peak detection, and recursive nearest neighbor tracker. The SURE tracking pipeline is capable of distinguishing the flow direction and separating tubes of a simulated Field II phantom with 125 to 25 µm wall-to-wall tube distances, as well as a 3D-printed hydrogel micro-flow phantom with 100 to 60 µm wall-to-wall channel distances. The comparison of an in-vivo SURE scan of a Sprague-Dawley rat kidney with ULM and micro-CT scans with voxel sizes of 26.5µm and 5µm demonstrated consistent findings. A microvascular structure composed of 16 vessels exhibited similarities across all imaging modalities. The flow direction and velocity profiles in the SURE scan were found to be concordant with those from ULM.
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Individuals with diabetes at risk of developing diabetic kidney disease (DKD) are challenging to identify using currently available clinical methods. Prognostic accuracy and initiation of treatment could be improved by a quantification of the renal microvascular rarefaction and the increased vascular tortuosity during the development of DKD. Super-resolution ultrasound (SRUS) imaging is an in vivo technique capable of visualizing blood vessels at sizes below 75 µm. This preclinical study aimed to investigate the alterations in renal blood vessels' density and tortuosity in a type 2 diabetes rat model, Zucker diabetic fatty (ZDF) rats, as a prediction of DKD. Lean age-matched Zucker rats were used as controls. A total of 36 rats were studied, subdivided into ages of 12, 22, and 40 weeks. Measured albuminuria indicated the early stage of DKD, and the SRUS was compared with the ex vivo micro-computed tomography (µCT) of the same kidneys. Assessed using the SRUS imaging, a significantly decreased cortical vascular density was detected in the ZDF rats from 22 weeks of age compared to the healthy controls, concomitant with a significantly increased albuminuria. Already by week 12, a trend towards a decreased cortical vascular density was found prior to the increased albuminuria. The quantified vascular density in µCT corresponded with the in vivo SRUS imaging, presenting a consistently lower vascular density in the ZDF rats. Regarding vessel tortuosity, an overall trend towards an increased tortuosity was present in the ZDF rats. SRUS shows promise for becoming an additional tool for monitoring and prognosing DKD. In the future, large-scale animal studies and human trials are needed for confirmation.
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Synchrotron X-ray computed tomography (SXCT) allows 3D imaging of tissue with a very large field of view and an excellent micron resolution and enables the investigation of muscle fiber atrophy in 3D. The study aimed to explore the 3D micro-architecture of healthy skeletal muscle fibers and muscle fibers at different stages of atrophy (stroke sample = muscle atrophy; spinal cord injury (SCI) sample = severe muscle atrophy). Three muscle samples: a healthy control sample; a stroke sample (atrophic sample), and an SCI sample (severe atrophic sample) were imaged using SXCT, and muscle fiber populations were segmented and quantified for microarchitecture and morphology differences. The volume fraction of muscle fibers was 74.7%, 70.2%, and 35.3% in the healthy, stroke (atrophic), and SCI (severe atrophic) muscle fiber population samples respectively. In the SCI (severe atrophic sample), 3D image analysis revealed fiber splitting and fiber swelling. In the stroke sample (atrophic sample) muscle fiber buckling was observed but was only visible in the 3D analysis. 3D muscle fiber population analysis revealed new insights into the different stages of muscle fiber atrophy not to be observed nor quantified with a 2D histological analysis including fiber buckling, loss of fibers and fiber splitting.
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Traumatismos da Medula Espinal , Acidente Vascular Cerebral , Humanos , Fibras Musculares Esqueléticas/patologia , Músculo Esquelético/diagnóstico por imagem , Músculo Esquelético/patologia , Atrofia Muscular/diagnóstico por imagem , Atrofia Muscular/patologia , Medula Espinal/patologia , Traumatismos da Medula Espinal/diagnóstico por imagem , Traumatismos da Medula Espinal/patologia , Acidente Vascular Cerebral/diagnóstico por imagem , Acidente Vascular Cerebral/patologia , SíncrotronsRESUMO
Noninvasive estimation of axon diameter with diffusion MRI holds the potential to investigate the dynamic properties of the brain network and pathology of neurodegenerative diseases. Recent studies use powder averaging to account for complex white matter architectures, but these have not been validated for real axonal geometries from regions that contain fibre crossings. Here, we present 120-304µm long segmented axons from X-ray nano-holotomography volumes of a splenium and crossing fibre region of a vervet monkey brain. We show that the axons in the complex crossing fibre region, which contains callosal, association, and corticospinal connections, exhibit a wider diameter distribution than those of the splenium region. To accurately estimate the axon diameter in these regions, therefore, sensitivity to a wide range of diameters is required. We demonstrate how the q-value, b-value, signal-to-noise ratio and the assumed intra-axonal parallel diffusivity influence the range of measurable diameters with powder average approaches. Furthermore, we show how Gaussian distributed noise results in a wider range of measurable diameter at high b-values than Rician distributed noise, even at high signal-to-noise ratios of 100. The number of gradient directions is also shown to impose a lower bound on measurable diameter. Our results indicate that axon diameter estimation can be performed with only few b-shells, and that additional shells do not improve the accuracy of the estimate. For strong gradients available on human Connectom and preclinical scanners, Monte Carlo simulations of diffusion confirm that powder averaging techniques succeed in providing accurate estimates of axon diameter across a range of diameters, sequence parameters and diffusion times, even in complex white matter architectures. At relatively low b-values, the diameter estimate becomes sensitive to axonal microdispersion and the intra-axonal parallel diffusivity shows time dependency at both in vivo and ex vivo intrinsic diffusivities.
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Axônios/ultraestrutura , Imagem de Difusão por Ressonância Magnética/métodos , Imageamento Tridimensional , Animais , Chlorocebus aethiops , Método de Monte Carlo , Distribuição Normal , Razão Sinal-RuídoRESUMO
BACKGROUND: Understanding the diversity of eyes is crucial to unravel how different animals use vision to interact with their respective environments. To date, comparative studies of eye anatomy are scarce because they often involve time-consuming or inefficient methods. X-ray micro-tomography (micro-CT) is a promising high-throughput imaging technique that enables to reconstruct the 3D anatomy of eyes, but powerful tools are needed to perform fast conversions of anatomical reconstructions into functional eye models. RESULTS: We developed a computing method named InSegtCone to automatically segment the crystalline cones in the apposition compound eyes of arthropods. Here, we describe the full auto-segmentation process, showcase its application to three different insect compound eyes and evaluate its performance. The auto-segmentation could successfully label the full individual shapes of 60-80% of the crystalline cones and is about as accurate and 250 times faster than manual labelling of the individual cones. CONCLUSIONS: We believe that InSegtCone can be an important tool for peer scientists to measure the orientation, size and dynamics of crystalline cones, leading to the accurate optical modelling of the diversity of arthropod eyes with micro-CT.
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Super-resolution ultrasound imaging (SRUS) enables in vivo microvascular imaging of deeper-lying tissues and organs, such as the kidneys or liver. The technique allows new insights into microvascular anatomy and physiology and the development of disease-related microvascular abnormalities. However, the microvascular anatomy is intricate and challenging to depict with the currently available imaging techniques, and validation of the microvascular structures of deeper-lying organs obtained with SRUS remains difficult. Our study aimed to directly compare the vascular anatomy in two in vivo 2D SRUS images of a Sprague-Dawley rat kidney with ex vivo µCT of the same kidney. Co-registering the SRUS images to the µCT volume revealed visually very similar vascular features of vessels ranging from ~ 100 to 1300 µm in diameter and illustrated a high level of vessel branching complexity captured in the 2D SRUS images. Additionally, it was shown that it is difficult to use µCT data of a whole rat kidney specimen to validate the super-resolution capability of our ultrasound scans, i.e., validating the actual microvasculature of the rat kidney. Lastly, by comparing the two imaging modalities, fundamental challenges for 2D SRUS were demonstrated, including the complexity of projecting a 3D vessel network into 2D. These challenges should be considered when interpreting clinical or preclinical SRUS data in future studies.
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Imageamento Tridimensional/métodos , Rim/irrigação sanguínea , Rim/diagnóstico por imagem , Ultrassonografia/métodos , Microtomografia por Raio-X/métodos , Animais , Masculino , Microvasos , Ratos , Ratos Sprague-DawleyRESUMO
Axonal conduction velocity, which ensures efficient function of the brain network, is related to axon diameter. Noninvasive, in vivo axon diameter estimates can be made with diffusion magnetic resonance imaging, but the technique requires three-dimensional (3D) validation. Here, high-resolution, 3D synchrotron X-ray nano-holotomography images of white matter samples from the corpus callosum of a monkey brain reveal that blood vessels, cells, and vacuoles affect axonal diameter and trajectory. Within single axons, we find that the variation in diameter and conduction velocity correlates with the mean diameter, contesting the value of precise diameter determination in larger axons. These complex 3D axon morphologies drive previously reported 2D trends in axon diameter and g-ratio. Furthermore, we find that these morphologies bias the estimates of axon diameter with diffusion magnetic resonance imaging and, ultimately, impact the investigation and formulation of the axon structure-function relationship.
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Axônios/fisiologia , Animais , Feminino , Haplorrinos , Imageamento Tridimensional , Imageamento por Ressonância Magnética , Bainha de Mielina/metabolismo , Relação Estrutura-Atividade , Vacúolos/metabolismo , Substância Branca/anatomia & histologiaRESUMO
Understanding the human inner ear anatomy and its internal structures is paramount to advance hearing implant technology. While the emergence of imaging devices allowed researchers to improve understanding of intracochlear structures, the difficulties to collect appropriate data has resulted in studies conducted with few samples. To assist the cochlear research community, a large collection of human temporal bone images is being made available. This data descriptor, therefore, describes a rich set of image volumes acquired using cone beam computed tomography and micro-CT modalities, accompanied by manual delineations of the cochlea and sub-compartments, a statistical shape model encoding its anatomical variability, and data for electrode insertion and electrical simulations. This data makes an important asset for future studies in need of high-resolution data and related statistical data objects of the cochlea used to leverage scientific hypotheses. It is of relevance to anatomists, audiologists, computer scientists in the different domains of image analysis, computer simulations, imaging formation, and for biomedical engineers designing new strategies for cochlear implantations, electrode design, and others.
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Orelha Interna/diagnóstico por imagem , Humanos , Processamento de Imagem Assistida por ComputadorRESUMO
PURPOSE: Cochlear implantation is a safe and effective surgical procedure to restore hearing in deaf patients. However, the level of restoration achieved may vary due to differences in anatomy, implant type and surgical access. In order to reduce the variability of the surgical outcomes, we previously proposed the use of a high-resolution model built from [Formula: see text] images and then adapted to patient-specific clinical CT scans. As the accuracy of the model is dependent on the precision of the original segmentation, it is extremely important to have accurate [Formula: see text] segmentation algorithms. METHODS: We propose a new framework for cochlea segmentation in ex vivo [Formula: see text] images using random walks where a distance-based shape prior is combined with a region term estimated by a Gaussian mixture model. The prior is also weighted by a confidence map to adjust its influence according to the strength of the image contour. Random walks is performed iteratively, and the prior mask is aligned in every iteration. RESULTS: We tested the proposed approach in ten [Formula: see text] data sets and compared it with other random walks-based segmentation techniques such as guided random walks (Eslami et al. in Med Image Anal 17(2):236-253, 2013) and constrained random walks (Li et al. in Advances in image and video technology. Springer, Berlin, pp 215-226, 2012). Our approach demonstrated higher accuracy results due to the probability density model constituted by the region term and shape prior information weighed by a confidence map. CONCLUSION: The weighted combination of the distance-based shape prior with a region term into random walks provides accurate segmentations of the cochlea. The experiments suggest that the proposed approach is robust for cochlea segmentation.
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Algoritmos , Cóclea/cirurgia , Implante Coclear/métodos , Tomografia Computadorizada por Raios X/métodos , Cóclea/diagnóstico por imagem , Humanos , Reprodutibilidade dos TestesRESUMO
Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical µCT images. Then, by fitting the statistical model to a patient's CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns constitutive parameters to all components of the finite element model. This model can then be used to study in silico the effects of the electrical stimulation of the cochlear implant. Results are shown on a total of 25 models of patients. In all cases, a final mesh suitable for finite element simulations was obtained, in an average time of 94 s. The framework has proven to be fast and robust, and is promising for a detailed prognosis of the cochlear implantation surgery.
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Implante Coclear , Implantes Cocleares , Simulação por Computador , Perda Auditiva Neurossensorial , Modelos Neurológicos , Feminino , Análise de Elementos Finitos , Perda Auditiva Neurossensorial/diagnóstico por imagem , Perda Auditiva Neurossensorial/fisiopatologia , Perda Auditiva Neurossensorial/terapia , Humanos , Masculino , Microtomografia por Raio-XRESUMO
We present a framework for patient specific electrical stimulation of the cochlea, that allows to perform in-silico analysis of implant placement and function before surgery. A Statistical Shape Model (SSM) is created from high-resolution human µCT data to capture important anatomical details. A Finite Element Model (FEM) is built and adapted to the patient using the results of the SSM. Electrical simulations based on Maxwell's equations for the electromagnetic field are performed on this personalized model. The model includes implanted electrodes and nerve fibers. We present the results for the bipolar stimulation protocol and predict the voltage spread and the locations of nerve excitation.