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PURPOSE: To evaluate effectiveness of pulmonary arteriovenous malformation (PAVM) embolization using dual-energy computed tomography (CT) and spectral curve analysis by characterizing contrast enhancement and vascular perfusion as a surrogate of the degree of vascular occlusion after embolotherapy. MATERIALS AND METHODS: Nine consecutive adult patients underwent embolization for 21 PAVMs (size range, 0.4-2.0 cm; 15/21 simple angioarchitecture) and subsequent postembolization chest dual-energy CT angiography. Twelve PAVMs were treated with vascular plugs with or without coils, whereas 9 PAVMs were treated with coils alone. Virtual spectral curves were generated using dual-energy image postprocessing in order to measure embolization effectiveness. RESULTS: Complete occlusion of target PAVM was achieved in all cases on digital subtraction angiography (DSA) at the end of the embolization procedure. With a median follow-up of 12.7 months, the vascular plug group demonstrated significantly less vascular opacification compared with the coils-only group, as measured by opacification between upstream feeding artery and different downstream vasculature locations (Δslope1: median 79.1 vs 28.6; P = .003; Δslope2: 76.4 vs 28.6; P = .0197; Δslope3: 78.9 vs 28.6; P = .004). Persistence occurred in 3 PAVMs based on size criteria, which demonstrated higher vascular opacification by dual-energy CT (Δslope1: 72 vs 28.6; P = .253; Δslope2: 65.1 vs 32.7; P = .326; Δslope3: 72.9 vs 53.5; P = .733), although statistical significance was not reached. CONCLUSIONS: Similar to emerging literature, dual-energy CT showed improved occlusion in PAVMs treated with vascular plugs compared with those treated with coils alone.
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Purpose: Single-energy computed tomography (CT) often suffers from poor contrast yet remains critical for effective radiotherapy treatment. Modern therapy systems are often equipped with both megavoltage (MV) and kilovoltage (kV) X-ray sources and thus already possess hardware for dual-energy (DE) CT. There is unexplored potential for enhanced image contrast using MV-kV DE-CT in radiotherapy contexts. Approach: A single-line integral toy model was designed for computing basis material signal-to-noise ratio (SNR) using estimation theory. Five dose-matched spectra (3 kV, 2 MV) and three variables were considered: spectral combination, spectral dose allocation, and object material composition. The single-line model was extended to a simulated CT acquisition of an anthropomorphic phantom with and without a metal implant. Basis material sinograms were computed and synthesized into virtual monoenergetic images (VMIs). MV-kV and kV-kV VMIs were compared with single-energy images. Results: The 80 kV-140 kV pair typically yielded the best SNRs, but for bone thicknesses >8 cm, the detunedMV-80 kV pair surpassed it. Peak MV-kV SNR was achieved with â¼90% dose allocated to the MV spectrum. In CT simulations of the pelvis with a steel implant, MV-kV VMIs yielded a higher contrast-to-noise ratio (CNR) than single-energy CT and kV-kV DE-CT. Without steel, the MV-kV VMIs produced higher contrast but lower CNR than single-energy CT. Conclusions: This work analyzes MV-kV DE-CT imaging and assesses its potential advantages. The technique may be used for metal artifact correction and generation of VMIs with higher native contrast than single-energy CT. Improved denoising is generally necessary for greater CNR without metal.
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Purpose: A geometric simulation of a possible two-plane detector was developed to test the abilities of the detector to generate high-resolution images of the Great Pyramid using muon tomography. Methods and Materials: Trajectory range, angular resolution, and acceptance of the detector were calculated with a simulation. Trajectories and the corresponding sinogram space covered were simulated first with one detector in one location, and then two moving detectors on adjacent sides of the pyramid. The resolution at the center slice of the pyramid was calculated using the angular resolution of the detector. Results: The simulation returned trajectory range encompassing the pyramid and peak angular resolution of .0004sr. Sinogram space covered by one position was inadequate, however two moving detectors on adjacent sides of the pyramid cover a significant portion. Resolution at the center of the pyramid is roughly 3m. Conclusions: The simulation provides a way to calculate the detector positions needed to cover an adequate amount of sinogram space for high-resolution cosmic-ray tomographic reconstruction of the Great Pyramids.
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Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs. Here we introduce a rapid, sensitive, and robust wavefront sensing scheme based on phase diversity, a method successfully deployed in astronomy but underused in microscopy. Our method enables accurate wavefront sensing to less than λ/35 root mean square (RMS) error with few measurements, and AO with no additional hardware besides a corrective element. After validating the method with simulations, we demonstrate calibration of a deformable mirror > 100-fold faster than comparable methods (corresponding to wavefront sensing on the ~100 ms scale), and sensing and subsequent correction of severe aberrations (RMS wavefront distortion exceeding λ/2), restoring diffraction-limited imaging on extended biological samples.
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Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics into the imaging path. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations to show that applying the trained 'de-aberration' networks outperforms alternative methods, and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.
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Reduced angular sampling is a key strategy for increasing scanning efficiency of micron-scale computed tomography (micro-CT). Despite boosting throughput, this strategy introduces noise and extrapolation artifacts due to undersampling. In this work, we present a solution to this issue, by proposing a novel Dense Residual Hierarchical Transformer (DRHT) network to recover high-quality sinograms from 2×, 4× and 8× undersampled scans. DRHT is trained to utilize limited information available from sparsely angular sampled scans and once trained, it can be applied to recover higher-resolution sinograms from shorter scan sessions. Our proposed DRHT model aggregates the benefits of a hierarchical- multi-scale structure along with the combination of local and global feature extraction through dense residual convolutional blocks and non-overlapping window transformer blocks respectively. We also propose a novel noise-aware loss function named KL-L1 to improve sinogram restoration to full resolution. KL-L1, a weighted combination of pixel-level and distribution-level cost functions, leverages inconsistencies in noise distribution and uses learnable spatial weight maps to improve the training of the DRHT model. We present ablation studies and evaluations of our method against other state-of-the-art (SOTA) models over multiple datasets. Our proposed DRHT network achieves an average increase in peak signal to noise ratio (PSNR) of 17.73 dB and a structural similarity index (SSIM) of 0.161, for 8× upsampling, across the three diverse datasets, compared to their respective Bicubic interpolated versions. This novel approach can be utilized to decrease radiation exposure to patients and reduce imaging time for large-scale CT imaging projects.
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Artefatos , Conscientização , Humanos , Microtomografia por Raio-X , Radiografia , Razão Sinal-Ruído , Atenção , Processamento de Imagem Assistida por Computador , AlgoritmosRESUMO
Tissue phenotyping is foundational to understanding and assessing the cellular aspects of disease in organismal context and an important adjunct to molecular studies in the dissection of gene function, chemical effects, and disease. As a first step toward computational tissue phenotyping, we explore the potential of cellular phenotyping from 3-Dimensional (3D), 0.74 µm isotropic voxel resolution, whole zebrafish larval images derived from X-ray histotomography, a form of micro-CT customized for histopathology. As proof of principle towards computational tissue phenotyping of cells, we created a semi-automated mechanism for the segmentation of blood cells in the vascular spaces of zebrafish larvae, followed by modeling and extraction of quantitative geometric parameters. Manually segmented cells were used to train a random forest classifier for blood cells, enabling the use of a generalized cellular segmentation algorithm for the accurate segmentation of blood cells. These models were used to create an automated data segmentation and analysis pipeline to guide the steps in a 3D workflow including blood cell region prediction, cell boundary extraction, and statistical characterization of 3D geometric and cytological features. We were able to distinguish blood cells at two stages in development (4- and 5-days-post-fertilization) and wild-type vs. polA2 huli hutu ( hht ) mutants. The application of geometric modeling across cell types to and across organisms and sample types may comprise a valuable foundation for computational phenotyping that is more open, informative, rapid, objective, and reproducible.
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X-ray fluorescence emission tomography (XFET) is an emerging imaging modality that images the spatial distribution of metal without requiring biochemical modification or radioactivity. This work investigates the joint estimation of metal and attenuation maps with a pencil-beam XFET system that allows for direct metal measurement in the absence of attenuation. Using singular value decomposition on a simplified imaging model, we show that reconstructing metal and attenuation voxels far from the detector is an ill-conditioned problem. Using simulated data, we develop and compare two image reconstruction methods for joint estimation. The first method alternates between updating the attenuation map with a separable paraboloidal surrogates algorithm and updating the metal map with a closed-form solution. The second method performs simultaneous joint estimation with conjugate gradients based on a linearized imaging model. The alternating approach outperforms the linearized approach for iron and gold numerical phantom reconstructions. Reconstructing an (8 cm)3 object containing gold concentrations of 5 mg/cm3 and an unknown beam attenuation map using the alternating approach yields an accurate gold map (NRMSE = 0.19) and attenuation map (NRMSE = 0.14). This simulation demonstrates an accurate joint reconstruction of metal and attenuation maps, from emission data, without previous knowledge of any attenuation map.
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The axial resolution of three-dimensional structured illumination microscopy (3D SIM) is limited to â¼300 nm. Here we present two distinct, complementary methods to improve axial resolution in 3D SIM with minimal or no modification to the optical system. We show that placing a mirror directly opposite the sample enables four-beam interference with higher spatial frequency content than 3D SIM illumination, offering near-isotropic imaging with â¼120-nm lateral and 160-nm axial resolution. We also developed a deep learning method achieving â¼120-nm isotropic resolution. This method can be combined with denoising to facilitate volumetric imaging spanning dozens of timepoints. We demonstrate the potential of these advances by imaging a variety of cellular samples, delineating the nanoscale distribution of vimentin and microtubule filaments, observing the relative positions of caveolar coat proteins and lysosomal markers and visualizing cytoskeletal dynamics within T cells in the early stages of immune synapse formation.
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Imageamento Tridimensional , Iluminação , Microscopia de Fluorescência/métodos , Imageamento Tridimensional/métodos , Citoesqueleto , LisossomosRESUMO
Computerized texture analysis uses higher-order mathematics to identify patterns beyond what the naked eye can recognize. We tested its feasibility in optical coherence tomography angiography imaging of choriocapillaris. Our objective was to determine sets of parameters that provide coherent and consistent output when applied to a homogeneous, healthy group of patients. This observational cross-sectional study involved 19 eyes of 10 young and healthy Caucasian subjects. En-face macular optical coherence tomography angiography of superficial choriocapillaris was obtained by the RTVue-XR Avanti system. Various algorithms were used to extract texture features. The mean and standard deviation were used to assess the distribution and dispersion of data points in each metric among eyes, which included: average gray level, gray level yielding 70% threshold and 30% threshold, balance, skewness, energy, entropy, contrast, edge mean gradient, root-mean-square variation, and first moment of power spectrum, which was compared between images, showing a highly concordant homology between all eyes of participants. We conclude that computerized texture analysis for en-face optical coherence tomography angiography images of choriocapillaris is feasible and provides values that are coherent and tightly distributed around the mean in a homogenous, healthy group of patients. Homology of blob size among subjects may represent a "repeat pattern" in signal density and thus a perfusion in the superficial choriocapillaris of healthy young individuals of the same ethnic background.
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Capilares , Tomografia de Coerência Óptica , Corioide/diagnóstico por imagem , Angiofluoresceinografia/métodos , Voluntários Saudáveis , Humanos , Tomografia de Coerência Óptica/métodosRESUMO
AbstractWe tested the impact of temperature and symbiont state on calcification in corals, using the facultatively symbiotic coral Astrangia poculata as a model system. Symbiotic and aposymbiotic colonies of A. poculata were reared in 15, 20, and 27 °C conditions. We used scanning electron microscopy to quantify how these physiological and environmental conditions impact skeletal structure. Buoyant weight data over time revealed that temperature significantly affects calcification rates. Scanning electron microscopy of A. poculata skeletons showed that aposymbiotic colonies appear to have a lower density of calcium carbonate in actively growing septal spines. We describe a novel approach to analyze the roughness and texture of scanning electron microscopy images. Quantitative analysis of the roughness of septal spines revealed that aposymbiotic colonies have a rougher surface than symbiotic colonies in tropical conditions (27 °C). This trend reversed at 15 °C, a temperature at which the symbionts of A. poculata may exhibit parasitic properties. Analysis of surface texture patterns showed that temperature impacts the spatial variance of crystals on the spine surface. Few published studies have examined the skeleton of A. poculata by using scanning electron microscopy. Our approach provides a way to study detailed changes in skeletal microstructure in response to environmental parameters and can serve as a proxy for more expensive and time-consuming analyses. Utilizing a facultatively symbiotic coral that is native to both temperate and tropical regions provides new insights into the impact of both symbiosis and temperature on calcification in corals.
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Antozoários , Dinoflagellida , Animais , Antozoários/fisiologia , Calcificação Fisiológica , Recifes de Corais , Dinoflagellida/fisiologia , Simbiose/fisiologia , TemperaturaRESUMO
Ideal three-dimensional imaging of complex samples made up of micron-scale structures extending over mm to cm, such as biological tissues, requires both wide field of view and high resolution. For existing optics and detectors used for micro-CT (computed tomography) imaging, sub-micron pixel resolution can only be achieved for fields of view of <2â mm. This article presents a unique detector system with a 6â mm field-of-view image circle and 0.5â µm pixel size that can be used in micro-CT units utilizing both synchrotron and commercial X-ray sources. A resolution-test pattern with linear microstructures and whole adult Daphnia magna were imaged at beamline 8.3.2 of the Berkeley Advanced Light Source. Volumes of 10000â ×â 10000â ×â 7096 isotropic 0.5â µm voxels were reconstructed over a 5.0â mmâ ×â 3.5â mm field of view. Measurements in the projection domain confirmed a 0.90â µm measured spatial resolution that is largely Nyquist-limited. This unprecedented combination of field of view and resolution dramatically reduces the need for sectional scans and computational stitching for large samples, ultimately offering the means to elucidate changes in tissue and cellular morphology in the context of larger, whole, intact model organisms and specimens. This system is also anticipated to benefit micro-CT imaging in materials science, microelectronics, agricultural science and biomedical engineering.
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Imageamento Tridimensional , Síncrotrons , Imageamento Tridimensional/métodos , Microtomografia por Raio-X/métodos , Raios XRESUMO
Checkpoint blockade elicits durable responses in immunogenic cancers, but it is largely ineffective in immunologically 'cold' tumours. Here we report the design, synthesis and performance of a bismuth-based nanoscale metal-organic framework that modulates the immunological and mechanical properties of the tumour microenvironment for enhanced radiotherapy-radiodynamic therapy. In mice with non-immunogenic prostate and pancreatic tumours irradiated with low X-ray doses, the intratumoural injection of the radiosensitizer mediated potent outcomes via the repolarization of immunosuppressive M2 macrophages into immunostimulatory M1 macrophages, the reduction of the concentration of intratumoural transforming growth factor beta (TGF-ß) and of collagen density, and the inactivation of cancer-associated fibroblasts. When intravenously injected in combination with checkpoint-blockade therapy, the radiosensitizer mediated the reversal of immunosuppression in primary and distant tumours via the systemic reduction of TGF-ß levels, which led to the downregulation of collagen expression, the stimulation of T-cell infiltration in the tumours and a robust abscopal effect. Nanoscale radiosensitizers that stimulate anti-tumour immunity and T-cell infiltration may enhance the therapeutic outcomes of checkpoint blockade in other tumour types.
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Estruturas Metalorgânicas , Neoplasias , Animais , Imunidade , Imunoterapia , Masculino , Estruturas Metalorgânicas/farmacologia , Camundongos , Microambiente TumoralRESUMO
Guest editors Patrick La Riviere, Rebecca Fahrig, and Norbert Pelc introduce the JMI Special Section Celebrating X-Ray Computed Tomography at 50.
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Confocal microscopy1 remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-dependent degradation in scattering samples and volumetric bleaching2. Here we address these problems, enhancing confocal microscopy performance from the sub-micrometre to millimetre spatial scale and the millisecond to hour temporal scale, improving both lateral and axial resolution more than twofold while simultaneously reducing phototoxicity. We achieve these gains using an integrated, four-pronged approach: (1) developing compact line scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; (2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; (3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labelled, thick samples; (4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than 20 distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae and adults; myoblasts in imaginal disks of Drosophila wings; and mouse renal, oesophageal, cardiac and brain tissues.
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Aprendizado Profundo , Microscopia Confocal/métodos , Microscopia Confocal/normas , Animais , Caenorhabditis elegans/citologia , Caenorhabditis elegans/embriologia , Caenorhabditis elegans/crescimento & desenvolvimento , Linhagem Celular Tumoral , Drosophila melanogaster/citologia , Drosophila melanogaster/crescimento & desenvolvimento , Humanos , Discos Imaginais/citologia , Camundongos , Mioblastos/citologia , Especificidade de Órgãos , Análise de Célula Única , Fixação de TecidosRESUMO
Computed tomography was one of the first imaging modalities to require a computerized solution of an inverse problem to produce a useful image from the data acquired by the sensor hardware. The computerized solutions, which are known as image reconstruction algorithms, have thus been a critical component of every CT scanner ever sold. We review the history of commercially deployed CT reconstruction algorithms and consider the forces that led, at various points, both to innovation and to convergence around certain broadly useful algorithms. The forces include the emergence of new hardware capabilities, competitive pressures, the availability of computational power, and regulatory considerations. We consider four major historical periods and turning points. The original EMI scanner was developed with an iterative reconstruction algorithm, but an explosion of innovation coupled with rediscovery of an older literature led to the development of alternative algorithms throughout the early 1970s. Most CT vendors quickly converged on the use of the filtered back-projection (FBP) algorithm, albeit layered with a variety of proprietary corrections in both projection data and image domains to improve image quality. Innovations such as helical scanning and multi-row detectors were both enabled by and drove the development of additional applications of FBP in the 1990s and 2000s. Finally, the last two decades have seen a return of iterative reconstruction and the introduction of artificial intelligence approaches that benefit from increased computational power to reduce radiation dose and improve image quality.
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Diffusion MRI tractography is the only noninvasive method to measure the structural connectome in humans. However, recent validation studies have revealed limitations of modern tractography approaches, which lead to significant mistracking caused in part by local uncertainties in fiber orientations that accumulate to produce larger errors for longer streamlines. Characterizing the role of this length bias in tractography is complicated by the true underlying contribution of spatial embedding to brain topology. In this work, we compare graphs constructed with ex vivo tractography data in mice and neural tracer data from the Allen Mouse Brain Connectivity Atlas to random geometric surrogate graphs which preserve the low-order distance effects from each modality in order to quantify the role of geometry in various network properties. We find that geometry plays a substantially larger role in determining the topology of graphs produced by tractography than graphs produced by tracers. Tractography underestimates weights at long distances compared to neural tracers, which leads tractography to place network hubs close to the geometric center of the brain, as do corresponding tractography-derived random geometric surrogates, while tracer graphs place hubs further into peripheral areas of the cortex. We also explore the role of spatial embedding in modular structure, network efficiency and other topological measures in both modalities. Throughout, we compare the use of two different tractography streamline node assignment strategies and find that the overall differences between tractography approaches are small relative to the differences between tractography- and tracer-derived graphs. These analyses help quantify geometric biases inherent to tractography and promote the use of geometric benchmarking in future tractography validation efforts.
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Encéfalo/diagnóstico por imagem , Imagem de Tensor de Difusão/métodos , Animais , Córtex Cerebral/diagnóstico por imagem , Conectoma , CamundongosRESUMO
Mammalian neurons operate at length scales spanning six orders of magnitude; they project millimeters to centimeters across brain regions, are composed of micrometer-scale-diameter myelinated axons, and ultimately form nanometer scale synapses. Capturing these anatomical features across that breadth of scale has required imaging samples with multiple independent imaging modalities. Translating between the different modalities, however, requires imaging the same brain with each. Here, we imaged the same postmortem mouse brain over five orders of spatial resolution using MRI, whole brain micrometer-scale synchrotron x-ray tomography (µCT), and large volume automated serial electron microscopy. Using this pipeline, we can track individual myelinated axons previously relegated to axon bundles in diffusion tensor MRI or arbitrarily trace neurons and their processes brain-wide and identify individual synapses on them. This pipeline provides both an unprecedented look across a single brain's multi-scaled organization as well as a vehicle for studying the brain's multi-scale pathologies.
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Encéfalo/diagnóstico por imagem , Imagem Multimodal/métodos , Animais , Conectoma , Imageamento por Ressonância Magnética , Camundongos , Microscopia Eletrônica , Tomografia Computadorizada por Raios XRESUMO
PURPOSE: To introduce synchrotron X-ray microcomputed tomography (microCT) and demonstrate its use as a natively isotropic, nondestructive, 3D validation modality for diffusion MRI in whole, fixed mouse brain. METHODS: Postmortem diffusion MRI and microCT data were acquired of the same whole mouse brain. Diffusion data were processed using constrained spherical deconvolution. Synchrotron data were acquired at an isotropic voxel size of 1.17 µm. Structure tensor analysis was used to calculate fiber orientation distribution functions from the microCT data. A pipeline was developed to spatially register the 2 datasets in order to perform qualitative comparisons of fiber geometries represented by fiber orientation distribution functions. Fiber orientations from both modalities were used to perform whole-brain deterministic tractography to demonstrate validation of long-range white matter pathways. RESULTS: Fiber orientation distribution functions were able to be extracted throughout the entire microCT dataset, with spatial registration to diffusion MRI simplified due to the whole brain extent of the microCT data. Fiber orientations and tract pathways showed good agreement between modalities. CONCLUSION: Synchrotron microCT is a potentially valuable new tool for future multi-scale diffusion MRI validation studies, providing comparable value to optical histology validation methods while addressing some key limitations in data acquisition and ease of processing.