Uncovering the Effects of Symbiosis and Temperature on Coral Calcification.

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.

Computerized Texture Analysis of Optical Coherence Tomography Angiography of Choriocapillaris in Normal Eyes of Young and Healthy Subjects.

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.

Comparison of sinogram- and image-domain penalized-likelihood image reconstruction estimators.

PURPOSE: In recent years, the authors and others have been exploring the use of penalized-likelihood sinogram-domain smoothing and restoration approaches for emission and transmission tomography. The motivation for this strategy was initially pragmatic: to provide a more computationally feasible alternative to fully iterative penalized-likelihood image reconstruction involving expensive backprojections and reprojections, while still obtaining some of the benefits of the statistical modeling employed in penalized-likelihood approaches. In this work, the authors seek to compare the two approaches in greater detail. METHODS: The sinogram-domain strategy entails estimating the "ideal" line integrals needed for reconstruction of an activity or attenuation distribution from the set of noisy, potentially degraded tomographic measurements by maximizing a penalized-likelihood objective function. The objective function models the data statistics as well as any degradation that can be represented in the sinogram domain. The estimated line integrals can then be input to analytic reconstruction algorithms such as filtered backprojection (FBP). The authors compare this to fully iterative approaches maximizing similar objective functions. RESULTS: The authors present mathematical analyses based on so-called equivalent optimization problems that establish that the approaches can be made precisely equivalent under certain restrictive conditions. More significantly, by use of resolution-variance tradeoff studies, the authors show that they can yield very similar performance under more relaxed, realistic conditions. CONCLUSIONS: The sinogram- and image-domain approaches are equivalent under certain restrictive conditions and can perform very similarly under more relaxed conditions. The match is particularly good for fully sampled, high-resolution CT geometries. One limitation of the sinogram-domain approach relative to the image-domain approach is the difficulty of imposing additional constraints, such as image non-negativity.

Region of interest reconstruction in x-ray fluorescence computed tomography for negligible attenuation.

X-ray fluorescence computed tomography (XFCT) is a synchrotron-based imaging modality employed for mapping the distribution of elements within slices or volumes of intact specimens. A pencil beam of external radiation is used to stimulate emission of characteristic X-rays from within a sample, which is scanned and rotated through the pencil beam in a first-generation tomographic geometry. One limitation of XFCT is the long image acquisition time required to acquire a complete set of line integrals one-by-one. Typically, even if only a portion of a slice through the object is of interest, measurement lines are acquired spanning the entire object at every projection view over 180 degrees to avoid reconstructing images with so-called truncation artifacts. In this work, we show that when attenuation is negligible, recent developments in tomographic reconstruction theory can be used to reduce the scanning effort required to reconstruct regions of interest within the slice. The new theory provides explicit guidance as to which line integrals must be measured for a given ROI and also provides a backprojection-filtration reconstruction algorithm that averts the truncation artifacts that typically plague filtered backprojection reconstructions from truncated data. This is demonstrated through simulation studies and with real synchrotron-based XFCT data.

Computational 3D histological phenotyping of whole zebrafish by X-ray histotomography.

Organismal phenotypes frequently involve multiple organ systems. Histology is a powerful way to detect cellular and tissue phenotypes, but is largely descriptive and subjective. To determine how synchrotron-based X-ray micro-tomography (micro-CT) can yield 3-dimensional whole-organism images suitable for quantitative histological phenotyping, we scanned whole zebrafish, a small vertebrate model with diverse tissues, at ~1 micron voxel resolutions. Micro-CT optimized for cellular characterization (histotomography) allows brain nuclei to be computationally segmented and assigned to brain regions, and cell shapes and volumes to be computed for motor neurons and red blood cells. Striking individual phenotypic variation was apparent from color maps of computed densities of brain nuclei. Unlike histology, the histotomography also allows the study of 3-dimensional structures of millimeter scale that cross multiple tissue planes. We expect the computational and visual insights into 3D cell and tissue architecture provided by histotomography to be useful for reference atlases, hypothesis generation, comprehensive organismal screens, and diagnostics.

Penalized-likelihood sinogram restoration for computed tomography.

We formulate computed tomography (CT) sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. CT measurement data are degraded by a number of factors-including beam hardening and off-focal radiation-that produce artifacts in reconstructed images unless properly corrected. Currently, such effects are addressed by a sequence of sinogram-preprocessing steps, including deconvolution corrections for off-focal radiation, that have the potential to amplify noise. Noise itself is generally mitigated through apodization of the reconstruction kernel, which effectively ignores the measurement statistics, although in high-noise situations adaptive filtering methods that loosely model data statistics are sometimes applied. As an alternative, we present a general imaging model relating the degraded measurements to the sinogram of ideal line integrals and propose to estimate these line integrals by iteratively optimizing a statistically based objective function. We consider three different strategies for estimating the set of ideal line integrals, one based on direct estimation of ideal "monochromatic" line integrals that have been corrected for single-material beam hardening, one based on estimation of ideal "polychromatic" line integrals that can be readily mapped to monochromatic line integrals, and one based on estimation of ideal transmitted intensities, from which ideal, monochromatic line integrals can be readily estimated. The first two approaches involve maximization of a penalized Poisson-likelihood objective function while the third involves minimization of a quadratic penalized weighted least squares (PWLS) objective applied in the transmitted intensity domain. We find that at low exposure levels typical of those being considered for screening CT, the Poisson-likelihood based approaches outperform the PWLS objective as well as a standard approach based on adaptive filtering followed by deconvolution. At higher exposure levels, the approaches all perform similarly.

Monotonic penalized-likelihood image reconstruction for X-ray fluorescence computed tomography.

In this paper, we derive a monotonic penalized-likelihood algorithm for image reconstruction in X-ray fluorescence computed tomography (XFCT) when the attenuation maps at the energies of the fluorescence X-rays are unknown. In XFCT, a sample is irradiated with pencil beams of monochromatic synchrotron radiation that stimulate the emission of fluorescence X-rays from atoms of elements whose K- or L-edges lie below the energy of the stimulating beam. Scanning and rotating the object through the beam allows for acquisition of a tomographic dataset that can be used to reconstruct images of the distribution of the elements in question. XFCT is a stimulated emission tomography modality, and it is thus necessary to correct for attenuation of the incident and fluorescence photons. The attenuation map is, however, generally known only at the stimulating beam energy and not at the energies of the various fluorescence X-rays of interest. We have developed a penalized-likelihood image reconstruction strategy for this problem. The approach alternates between updating the distribution of a given element and updating the attenuation map for that element's fluorescence X-rays. The approach is guaranteed to increase the penalized likelihood at each iteration. Because the joint objective function is not necessarily concave, the approach may drive the solution to a local maximum. To encourage the algorithm to seek out a reasonable local maximum, we include in the objective function a prior that encourages a relationship, based on physical considerations, between the fluorescence attenuation map and the distribution of the element being reconstructed.

Material identification in x-ray microscopy and micro CT using multi-layer, multi-color scintillation detectors.

We demonstrate that a dual-layer, dual-color scintillator construct for microscopic CT, originally proposed to increase sensitivity in synchrotron imaging, can also be used to perform material quantification and classification when coupled with polychromatic illumination. We consider two different approaches to data handling: (1) a data-domain material decomposition whose estimation performance can be characterized by the Cramer-Rao lower bound formalism but which requires careful calibration and (2) an image-domain material classification approach that is more robust to calibration errors. The data-domain analysis indicates that useful levels of SNR (>5) could be achieved in one second or less at typical bending magnet fluxes for relatively large amounts of contrast (several mm path length, such as in a fluid flow experiment) and at typical undulator fluxes for small amount of contrast (tens of microns path length, such as an angiography experiment). The tools introduced could of course be used to study and optimize parameters for a wider range of potential applications. The image domain approach was analyzed in terms of its ability to distinguish different elemental stains by characterizing the angle between the lines traced out in a two-dimensional space of effective attenuation coefficient in the front and back layer images. This approach was implemented at a synchrotron and the results were consistent with simulation predictions.

Experimental demonstration of novel imaging geometries for x-ray fluorescence computed tomography.

PURPOSE: X-ray fluorescence computed tomography (XFCT) is an emerging imaging modality that maps the three-dimensional distribution of elements, generally metals, in ex vivo specimens and potentially in living animals and humans. At present, it is generally performed at synchrotrons, taking advantage of the high flux of monochromatic x rays, but recent work has demonstrated the feasibility of using laboratory-based x-ray tube sources. In this paper, the authors report the development and experimental implementation of two novel imaging geometries for mapping of trace metals in biological samples with ∼50-500 µm spatial resolution. METHODS: One of the new imaging approaches involves illuminating and scanning a single slice of the object and imaging each slice's x-ray fluorescent emissions using a position-sensitive detector and a pinhole collimator. The other involves illuminating a single line through the object and imaging the emissions using a position-sensitive detector and a slit collimator. They have implemented both of these using synchrotron radiation at the Advanced Photon Source. RESULTS: The authors show that it is possible to achieve 250 eV energy resolution using an electron multiplying CCD operating in a quasiphoton-counting mode. Doing so allowed them to generate elemental images using both of the novel geometries for imaging of phantoms and, for the second geometry, an osmium-stained zebrafish. CONCLUSIONS: The authors have demonstrated the feasibility of these two novel approaches to XFCT imaging. While they use synchrotron radiation in this demonstration, the geometries could readily be translated to laboratory systems based on tube sources.

Correction for resolution nonuniformities caused by anode angulation in computed tomography.

Most X-ray tubes comprise a rotating anode that is bombarded with electrons to produce X-rays. A substantial amount of heat is generated, and to increase the area of the anode exposed to the electrons, without increasing the apparent size of the focal spot, the focal track of the anode is generally beveled with a very shallow angle (typically 5 degrees-7 degrees in a computed tomography (CT) tube). Due to the line focus principle, this allows a fairly large area of the focal track to be exposed to electrons while retaining a fairly small effective projected focal spot. One side effect of anode angulation is that the focal spot appears different from different positions in the detector array; the effective focal spot size at a constant distance from the tube will be larger for a peripheral detector channel than for a central one. These differences in the effective size of the focal spot across the field-of-view lead to worse resolution in the periphery than in the center of reconstructed images. In this work we describe a method for achieving more uniform resolution in fanbeam CT images by correcting for these focal spot angulation effects. We do so by modeling the effects as a series of local blurrings in the space of transmitted CT intensities and determining the effective coefficients of the corresponding discrete convolutions. The effect of these blurrings can then be compensated for in the sinogram domain through the use of a penalized-likelihood sinogram restoration model we have recently developed.

Comparison of quadratic- and median-based roughness penalties for penalized-likelihood sinogram restoration in computed tomography.

We have compared the performance of two different penalty choices for a penalized-likelihood sinogram-restoration strategy we have been developing. One is a quadratic penalty we have employed previously and the other is a new median-based penalty. We compared the approaches to a noniterative adaptive filter that loosely but not explicitly models data statistics. We found that the two approaches produced similar resolution-variance tradeoffs to each other and that they outperformed the adaptive filter in the low-dose regime, which suggests that the particular choice of penalty in our approach may be less important than the fact that we are explicitly modeling data statistics at all. Since the quadratic penalty allows for derivation of an algorithm that is guaranteed to monotonically increase the penalized-likelihood objective function, we find it to be preferable to the median-based penalty.