Deep X-ray Research Articles

Combining deep learning and X-ray imaging technology to assess tomato seed quality

Combining deep learning and X-ray imaging technology to assess tomato seed quality

The Obscured Fraction of Quasars at Cosmic Noon

Statistical studies of X-ray selected active galactic nuclei (AGN) indicate that the fraction of obscured AGN increases with increasing redshift, and the results suggest that a significant part of the accretion growth occurs behind obscuring material in the early universe. We investigate the obscured fraction of highly accreting X-ray AGN at around the peak epoch of supermassive black hole growth utilizing the wide and deep X-ray and optical/IR imaging data sets. A unique sample of luminous X-ray selected AGNs above z > 2 was constructed by matching the XMM-SERVS X-ray point-source catalog with a point-spread function convolved photometric catalog covering the u*–4.5 μm bands. Photometric redshift, hydrogen column density, and 2–10 keV AGN luminosity of the X-ray selected AGN candidates were estimated. Using the sample of 306 2–10 keV detected AGN at above redshift 2, we estimate the fraction of AGN with , assuming parametric X-ray luminosity and absorption functions. The results suggest that of luminous quasars () above redshift 2 are obscured. The fraction indicates an increased contribution of obscured accretion at high redshift than that in the local universe. We discuss the implications of the increasing obscured fraction with increasing redshift based on the AGN obscuration scenarios, which describe obscuration properties in the local universe. Both the obscured and unobscured z > 2 AGN show a broad range of SEDs and morphology, which may reflect the broad variety of host galaxy properties and physical processes associated with the obscuration.

Mass assembly and active galactic nucleus activity at z ≳ 1.5 in the dense environment of XDCP J0044.0–2033

Context. XDCP J0044.0−2033 is the most massive galaxy cluster known at z > 1.5 and its core shows a high density of galaxies, which are experiencing mergers and hosting nuclear activity. Aims. We present a multi-wavelength study of a region of 24 kpc × 24 kpc located ∼157 kpc from the center of the cluster, for which we have photometric and spectroscopic observations. Our main goal is to investigate the environmental effects acting on the galaxies inhabiting this high-density region. Methods. We performed source identification and a photometric analysis on high-resolution Hubble Space Telescope (HST) images in the F105W, F140W, and F160W bands and a spectroscopic analysis of the near-infrared (NIR) KMOS data in H and YJ bands. In addition, we analyzed the deep Chandra ACIS-S X-ray exposure. Results. We find that the analyzed region hosts at least nine different sources –six of them confirmed to be cluster members within a narrow redshift range 1.5728 < z < 1.5762– and is therefore denser than the very central, more massive region of the cluster previously analyzed. These sources form two different complexes (Complex M and Complex N) at a projected distance of ∼13 kpc, which are undergoing merging on an estimated timescale of 10−30 Myr. One of the sources shows the presence of a broad Hα emission line and is classified as a Type-1 active galactic nucleus (AGN). This AGN is associated to an X-ray point-like source whose emission appears moderately obscured (with intrinsic absorption NH ∼ 1022 cm−2) and hosts a relatively massive black hole (BH) with a mass of MBH ∼ 107 M⊙, which is accreting with an Eddington ratio of ∼0.2. Conclusions. We conclude that the region analyzed here is consistent with being the formation site of a secondary brightest cluster galaxy (BCG). These findings, together with an in-depth analysis of the X-ray morphology of the cluster, suggest a merging scenario for the entire cluster, with two massive halos both harboring two rapidly evolving BCGs on the verge of being assembled. Our results are also consistent with the scenario in which the AGN phase in member galaxies is triggered by gas-rich mergers and plays a relevant role in the formation of the red sequence of elliptical galaxies observed in the center of local galaxy clusters.

COVID-19 Disease Detection using Pre-Trained Deep Convolutional Neural Network (GoogleNet) on Cloud Platform

Background and Purpose: The COVID -19 epidemics are causing the main rash in more than 151 countries around the whole world.Covid-19 has a bad effect on human life worldwide. One of the critical steps in fighting COVID-19 is finding the contaminated patients early enough and putting these infected people under special care. Our main aim is to separate COVID-19 patients from other patients. Materials and Methods:In this research article, we used GoogleNet as a learning network. GoogleNet is a deep convolutional neural network of 22 layers deep. We have used a pre-trained version of the GoogleNet trained on ImageNet. The pre-trained GoogleNet image input size is 224 x 224.GoogleNet; the deep convolutional neural network model cananalyze X-ray images to classify the patient’s condition of the affected disease. Result:Experiments and evaluation of the GoogleNet have been effectively done based on 80% of X-ray pictures for training and 20% of X-ray pictures for testing phases respectively. GoogleNet shows a good result for disease classification with 91.40% of accuracy in 2.49 minutes. Conclusion:In this research paper, we have usedthe deep CNN model to classify COVID-19 disease using X-ray images based on the projected GoogleNet. Scientific studies will be the next goal of this research article

Development of Deep Learning Chest X-Ray Model for Cardiac Dose Prediction in Left-Sided Breast Cancer Radiotherapy

<h3>Purpose/Objective(s)</h3> Deep inspiration breath-hold (DIBH) is widely used to reduce the cardiac dose in left-sided breast cancer radiotherapy. This study aimed to develop a deep learning chest X-ray model for cardiac dose prediction to select patients with a potentially high risk of cardiac irradiation and need for DIBH radiotherapy. <h3>Materials/Methods</h3> We used 103 pairs of anteroposterior and lateral chest X-ray data of left-sided breast cancer patients (training cohort: n = 59, validation cohort: n=19, test cohort: n = 25). All patients underwent breast-conserving surgery followed by DIBH radiotherapy: the treatment plan consisted of two opposing tangential radiation fields. The prescription dose of the planning target volume was 42.56 Gy in 16 fractions. A convolutional neural network-based regression model was developed to predict the mean heart dose (∆MHD) reduction between free-breathing (MHD_FB) and DIBH. The model performance is evaluated as a binary classifier by setting the cutoff value of ∆MHD >1 Gy. <h3>Results</h3> The patient characteristics were as follows: the median (IQR) age was 52 (47–61) years, MHD_FB was 1.75 (1.14–2.47) Gy, and ∆MHD was 1.00 (0.52–1.64) Gy. The classification performance of the developed model showed a sensitivity of 85.7%, specificity of 90.9%, a positive predictive value of 92.3%, a negative predictive value of 83.3%, and a diagnostic accuracy of 88.0%. The AUC value of the ROC curve was 0.864. <h3>Conclusion</h3> The proposed model could predict ∆MHD in breast radiotherapy, suggesting the potential of a classifier in which patients are more desirable for DIBH.

Supermassive black holes at high redshift are expected to be obscured by their massive host galaxies’ interstellar medium

We combine results from deep ALMA observations of massive (M* &gt; 1010 M⊙) galaxies at different redshifts to show that the column density of their interstellar medium (ISM) rapidly increases toward early cosmic epochs. Our analysis includes objects from the ASPECS and ALPINE large programs, as well as individual observations ofz ∼ 6 quasar hosts. When accounting for non-detections and correcting for selection effects, we find that the median surface density of the ISM of the massive galaxy population evolves as ∼(1 + z)3.3. This means that the ISM column density toward the nucleus of az &gt; 3 galaxy is typically &gt; 100 times larger than locally, and it may reach values as high as Compton-thick atz ≳ 6. Remarkably, the median ISM column density is on the same order of what is measured from X-ray observations of large active galactic nucleus (AGN) samples already atz ≳ 2. We have developed a simple analytic model for the spatial distribution of ISM clouds within galaxies, and estimate the total covering factor toward active nuclei when obscuration by ISM clouds on the host scale is added to that of parsec-scale circumnuclear material (the so-called torus). The model includes clouds with a distribution of sizes, masses, and surface densities, and also allows for an evolution of the characteristic cloud surface density with redshift, Σc, * ∝ (1 + z)γ. We show that, forγ = 2, such a model successfully reproduces the increase in the obscured AGN fraction with redshift that is commonly observed in deep X-ray surveys, both when different absorption thresholds and AGN luminosities are considered. Our results suggest that 80–90% of supermassive black holes in the early Universe (z &gt; 6 − 8) are hidden to our view, primarily by the ISM in their hosts. We finally discuss the implications of our results and how they can be tested observationally with current and forthcoming facilities (e.g., VLT, E-ELT, ALMA, and JWST) and with next-generation X-ray imaging satellites. By extrapolating the observed X-ray nebulae around local AGN to the environments of supermassive black holes at high redshifts, we find ≲1″ nebulae impose stringent design constraints on the spatial resolution of any future X-ray imaging Great Observatory in the coming decades.

The chemical and thermal structure of the hot atmosphere of the elliptical galaxy NGC 5813

Abstract We present a robust representation of the chemical and thermal structure in the galaxy group NGC 5813 using archival, deep X-ray observations, and employing a multi-temperature spectral model based on up to date atomic line emission databases. The selection of our target is motivated by the fact that NGC 5813 has a very relaxed morphology, making it a promising candidate for the study of the AGN feedback’s influence in the intra-group medium (IGrM). Our results showcase a prominent, extended distribution of cool gas along the group’s NE-SW direction, correlating with the direction along which the supermassive black hole in the group’s central galaxy is known to interact with the IGrM. Our analysis indicates gas being uplifted from the group’s centre as the probable origin of the cool gas, although alternative scenarios, such as in-situ cooling can not be explicitly ruled out. Regarding the chemical structure of the IGrM, and unlike previous findings in massive clusters, we find no evidence for recent metal transport by jets/lobes from the central AGN. Instead, elemental abundances remain near Solar on average across the group. The distribution of elements appears to be independent of galactocentric radius, azimuth and the thermodynamics of the gas, suggesting that the IGrM has been efficiently mixed. The large scale uniformity of the abundance distribution implies the presence of complex dynamical processes in NGC 5813, despite its overall relaxed morphology. Past events of extreme AGN feedback or sloshing could be the primary mechanisms behind this.

A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques

Background and objectiveCOVID-19 outbreak has become one of the most challenging problems for human being. It is a communicable disease caused by a new coronavirus strain, which infected over 375 million people already and caused almost 6 million deaths. This paper aims to develop and design a framework for early diagnosis and fast classification of COVID-19 symptoms using multimodal Deep Learning techniques.Methods: we collected chest X-ray and cough sample data from open source datasets, Cohen and datasets and local hospitals. The features are extracted from the chest X-ray images are extracted from chest X-ray datasets. We also used cough audio datasets from Coswara project and local hospitals. The publicly available Coughvid DetectNow and Virufy datasets are used to evaluate COVID-19 detection based on speech sounds, respiratory, and cough. The collected audio data comprises slow and fast breathing, shallow and deep coughing, spoken digits, and phonation of sustained vowels. Gender, geographical location, age, preexisting medical conditions, and current health status (COVID-19 and Non-COVID-19) are recorded. ResultsThe proposed framework uses the selection algorithm of the pre-trained network to determine the best fusion model characterized by the pre-trained chest X-ray and cough models. Third, deep chest X-ray fusion by discriminant correlation analysis is used to fuse discriminatory features from the two models. The proposed framework achieved recognition accuracy, specificity, and sensitivity of 98.91%, 96.25%, and 97.69%, respectively. With the fusion method we obtained 94.99% accuracy. ConclusionThis paper examines the effectiveness of well-known ML architectures on a joint collection of chest-X-rays and cough samples for early classification of COVID-19. It shows that existing methods can effectively used for diagnosis and suggesting that the fusion learning paradigm could be a crucial asset in diagnosing future unknown illnesses. The proposed framework supports health informatics basis on early diagnosis, clinical decision support, and accurate prediction.

The black hole X-ray binary MAXI J1348–630 in quiescence

ABSTRACT The properties of the disc/jet coupling in quiescent black hole low mass X-ray binaries (BH LMXBs) are still largely unknown. In this paper, we present the first quasi-simultaneous radio and X-ray detection in quiescence of the BH LMXB MAXI J1348–630, which is known to display a hybrid disc/jet connection that depends on the accretion rate. We performed deep X-ray and radio observations using the Chandra X-ray Observatory and the Australia Telescope Compact Array. MAXI J1348–630 is detected for the first time in quiescence at an X-ray luminosity LX = (7.5 ± 2.9) × 1030(D/2.2 kpc)2 erg s−1: one of the lowest X-ray luminosities observed for a quiescent BH LMXB, possibly implying a short orbital period for the system. MAXI J1348–630 is also detected in radio at LR = (4.3 ± 0.9) × 1026(D/2.2 kpc)2 erg s−1. These detections allow us to constrain the location of MAXI J1348–630 on the radio/X-ray diagram in quiescence, finding that the source belongs to the standard (radio-loud) track in this phase. This provides a strong confirmation that hybrid-correlation sources follow the standard track at low luminosities and down to quiescence, thus improving our knowledge of the disc/jet connection in BH LMXBs.

A Hidden Population of Massive Black Holes in Simulated Dwarf Galaxies

We explore the characteristics of actively accreting massive black holes (MBHs) within dwarf galaxies in the Romulus25 cosmological hydrodynamic simulation. We examine the MBH occupation fraction, X-ray active fractions, and active galactic nucleus (AGN) scaling relations within dwarf galaxies of stellar mass 108 M ⊙ < M star < 1010 M ⊙ out to redshift z = 2. In the local universe, the MBH occupation fraction is consistent with observed constraints, dropping below unity at M star < 3 × 1010 M ⊙, M 200 < 3 × 1011 M ⊙. Local dwarf AGN in Romulus25 follow observed scaling relations between AGN X-ray luminosity, stellar mass, and star formation rate, though they exhibit slightly higher active fractions and number densities than comparable X-ray observations. Since z = 2, the MBH occupation fraction has decreased, the population of dwarf AGN has become overall less luminous, and as a result the overall number density of dwarf AGN has diminished. We predict the existence of a large population of MBHs in the local universe with low X-ray luminosities and high contamination from X-ray binaries and the hot interstellar medium that are undetectable by current X-ray surveys. These hidden MBHs make up 76% of all MBHs in local dwarf galaxies and include many MBHs that are undermassive relative to their host galaxy’s stellar mass. Their detection relies on not only greater instrument sensitivity but also better modeling of X-ray contaminants or multiwavelength surveys. Our results indicate that dwarf AGN were substantially more active in the past, despite having low luminosity today, and that future deep X-ray surveys may uncover many hidden MBHs in dwarf galaxies out to at least z = 2.

The supernova remnant SN 1006 as a Galactic particle accelerator

The origin of cosmic rays is a pivotal open issue of high-energy astrophysics. Supernova remnants are strong candidates to be the Galactic factory of cosmic rays, their blast waves being powerful particle accelerators. However, supernova remnants can power the observed flux of cosmic rays only if they transfer a significant fraction of their kinetic energy to the accelerated particles, but conclusive evidence for such efficient acceleration is still lacking. In this scenario, the shock energy channeled to cosmic rays should induce a higher post-shock density than that predicted by standard shock conditions. Here we show this effect, and probe its dependence on the orientation of the ambient magnetic field, by analyzing deep X-ray observations of the Galactic remnant of SN 1006. By comparing our results with state-of-the-art models, we conclude that SN 1006 is an efficient source of cosmic rays and obtain an observational support for the quasi-parallel acceleration mechanism.

Development of deep learning chest X-ray model for cardiac dose prediction in left-sided breast cancer radiotherapy

Deep inspiration breath-hold (DIBH) is widely used to reduce the cardiac dose in left-sided breast cancer radiotherapy. This study aimed to develop a deep learning chest X-ray model for cardiac dose prediction to select patients with a potentially high risk of cardiac irradiation and need for DIBH radiotherapy. We used 103 pairs of anteroposterior and lateral chest X-ray data of left-sided breast cancer patients (training cohort: n = 59, validation cohort: n = 19, test cohort: n = 25). All patients underwent breast-conserving surgery followed by DIBH radiotherapy: the treatment plan consisted of three-dimensional, two opposing tangential radiation fields. The prescription dose of the planning target volume was 42.56 Gy in 16 fractions. A convolutional neural network-based regression model was developed to predict the mean heart dose (∆MHD) reduction between free-breathing (MHDFB) and DIBH. The model performance is evaluated as a binary classifier by setting the cutoff value of ∆MHD > 1 Gy. The patient characteristics were as follows: the median (IQR) age was 52 (47–61) years, MHDFB was 1.75 (1.14–2.47) Gy, and ∆MHD was 1.00 (0.52–1.64) Gy. The classification performance of the developed model showed a sensitivity of 85.7%, specificity of 90.9%, a positive predictive value of 92.3%, a negative predictive value of 83.3%, and a diagnostic accuracy of 88.0%. The AUC value of the ROC curve was 0.864. The proposed model could predict ∆MHD in breast radiotherapy, suggesting the potential of a classifier in which patients are more desirable for DIBH.

Expansion of beam width in exposure and crystal structure beamline (BL09) of SAGA-LS and applications using expanded beams

In this study, for high-efficiency experiments of deep X-ray lithography, radiation mutation breeding, and X-ray topography, we expanded the beam width in the exposure and crystal structure beamline (BL09) using a synchrotron beam at the SAGA Light Source facility. BL09 was divided into a straight A-line for hard X-rays and a branch B-line for soft X-rays; however, we reconstructed the new BL09 as a single straight-line by unifying the A and B-lines. Vacuum components, such as a large beam shutter, large beryllium window, acoustic delay line, and monochromator chamber were newly located in the reconstructed BL09. A white (or monochromatic) beam can be switched by removing (or inserting) the monochromator into the beam path as needed. After the reconstruction, the widths of the white and monochromatic beams at the terminal of BL09 were expanded from 110 to 395 mm and from 70 to 128 mm, respectively. The expanded white beam has the width of the world-class in synchrotron radiation facilities. Furthermore, we demonstrated the effect of the expanded beams and improvement in the experimental efficiency through deep X-ray lithography, radiation mutation breeding, and X-ray topography. The use of expanded beams is also expected to lead to the fabrication of practicable fine-structures and provide a deeper understanding of defect structures.

X-ray focusing to 62keV by compound refractive lenses for high-pressure x-ray diffraction.

This study describes high-energy x-ray focusing optics using compound refractive lenses (CRLs) for high-pressure x-ray diffraction (XRD) with a monochromatic x-ray beam. A CRL-based x-ray transfocator was upgraded and installed in the optics hutch at the BL10XU beamline of SPring-8. The instrument can be equipped with two types of CRLs in parallel: a newly designed aluminum (Al) CRL for x-ray energies of 40-62keV and an existing glassy carbon CRL for those up to 40keV. In only the Al-CRL-based x-ray transfocator, a 62keV monochromatic x-ray beam with horizontal (H) and vertical (V) focused spots, whose sizes were 189 and 10.5 µm, respectively, and a flux of 1.32 × 1011 phs/s were generated. A polymer SU-8 CRL fabricated via deep x-ray lithography was installed to further reduce the x-ray beam size. The Al-CRL and the SU-8 CRL were combined to generate a smaller spot size of 12.5 (H) × 11.0 (V) μm2 with a flux of 3 × 1010 phs/s at 62keV. A two-step optical configuration combining an x-ray transfocator and SU-8 CRL provides a valuable method for high-pressure XRD using a high-energy x-ray focused beam. The optical design and performance of the Al-CRL-based x-ray transfocator, its combination with the SU-8 CRL, and the first results of the focusing optics commissioning are presented here.

Response of Patients with Acromegaly to Long-acting Octreotide with regard to Regression of Pituitary Adenoma, Growth Hormone and Insulin-like Growth Factor-1

Introduction: Acromegaly is a rare endocrine disease; its treatment is surgical (Hypophysectomy). However, somatostatin analogs represent another modality of therapy in addition to deep X-ray therapy as a third, option. The aim of the study is to find out the response of patients with acromegaly to octreotide as reflected on regression of adenoma size, insulin-like growth factor (IGF), and growth hormone (GH) by studying the medical records of many patients with acromegaly. Method: A total of 80 patients with acromegaly are enrolled in the study from July/2019 to April/2020. Their age range (20–72 years). They are 47 men and 33 women. Their selection was based on their visits to NDC on the basis of prescheduled appointments to be given their monthly injections of long-acting octreotide (LAR) and to be examined clinically plus conducting various types of hormonal studies and biochemical workups to assess their response to treatment on the following parameters: Adenoma size, IGF-1 and GH and its correlation with octreotide dose. Results: It is a cross-sectional comparative clinical trial study of 80 patients with acromegaly. Mean of age was 46.7 ± 12.4 years’, and their age range (20–72 year) minimum and maximum-year-old. Mean duration of taking drug was 8 ± 6.7 years. The mean of total LRA injection was (1073.6 ± 666.2 mg). 58.75% of patients were male while 41.25% were female. 46.25% of patients do not have transsphenoidal direct surgery, but 46.25% undergo one surgery, 7.5% undergo two transsphenoidal hypophysectomies. 87.5% of patients have no gamma knife while 12.5% have gamma knife radiosurgery. Conclusion: Acromegaly is a multi systemic disease that should be diagnosed and treated as early as possible to prevent complications and improve mortality rates.

The gravitational field of X-COP galaxy clusters

The mass profiles of massive dark matter halos are highly sensitive to the nature of dark matter and potential modifications of the theory of gravity on large scales. The Λ cold dark matter (CDM) paradigm makes strong predictions on the shape of dark matter halos and on the dependence of the shape parameters on halo mass, such that any deviation from the predicted universal shape would have important implications for the fundamental properties of dark matter. Here we use a set of 12 galaxy clusters with available deep X-ray and Sunyaev–Zel’dovich data to constrain the shape of the gravitational field with an unprecedented level of precision over two decades in radius. We introduce a nonparametric framework to reconstruct the shape of the gravitational field under the assumption of hydrostatic equilibrium and compare the resulting mass profiles to the expectations of Navarro–Frenk–White (NFW) and Einasto parametric mass profiles. On average, we find that the NFW profile provides an excellent description of the recovered mass profiles, with deviations of less than 10% over a wide radial range. However, there appears to be more diversity in the shape of individual profiles than can be captured by the NFW model. The average NFW concentration and its scatter agree very well with the prediction of the ΛCDM framework. For a subset of systems, we disentangle the gravitational field into the contribution of baryonic components (gas, brightest cluster galaxy, and satellite galaxies) and that of dark matter. The stellar content dominates the gravitational field inside ∼0.02R500 but is responsible for only 1–2% of the total gravitational field inside R200. The total baryon fraction reaches the cosmic value at R200 and slightly exceeds it beyond this point, possibly indicating a mild level of nonthermal pressure support (10 − 20%) in cluster outskirts. Finally, the relation between observed and baryonic acceleration exhibits a complex shape that strongly departs from the radial acceleration relation in spiral galaxies, which shows that the aforementioned relation does not hold at the galaxy-cluster scale.

Deep learning-based X-ray computed tomography image reconstruction and prediction of compression behavior of 3D printed lattice structures

Complex thermal processing during laser powder bed fusion ( L -PBF) inevitably induces heterogenous and anisotropic defects, which can affect the macromechanical response of components. The initial morphological features of L -PBF printed samples can be reconstructed with X-ray micro-computed tomography (μCT) scans and the effects of defects on the mechanical properties of the sample can be predicted using image-based finite element modeling. However, due to balling phenomena, several powder particles adhere to the surface of the lattice structure and the mechanical properties of these particles differ from that of the parent material. The predicted modulus and strength of the direct reconstructed models are much higher than the experimental values because of overestimated particle effect. Therefore, these particles should be removed from the CT images before high-fidelity numerical simulation. This paper proposes a new image segmentation method based on a U-Net convolutional neural network to remove adhered particles on the L -PBF manufactured lattice structure from μCT slices. High-fidelity image-based finite element models were constructed with and without the deep learning-based image preprocessing. The results were compared with those obtained from simulations using an ideal CAD model and experimental results. The proposed deep learning-based preprocessing method enables high-precision reconstruction and efficient finite element simulation prediction of additive manufactured lattice structures.

Investigation on the mechanical interface stability of curved high aspect ratio x-ray gratings made by deep x-ray lithography

We describe the rationale for selecting graphite as a substrate material suitable for manufacturing curved high-aspect ratio metallic x-ray gratings and experimentally validate that its properties satisfy requirements relevant for clinical phase-contrast and dark-field x-ray imaging. Selection criteria applied to two candidate materials graphite and polyimide were compliance to bending, mechanical tenacity of the attachment of the lamellar grating structure to the substrate, the substrate material’s x-ray robustness, and the compatibility with the x-ray LIGA process used to manufacture the grating structures. In contrast to other standard materials such as silicon wafers with titanium layer, graphite wafers could be bent to smaller radii and are natively electrically conductive. While polyimide wafers allowed for even smaller bending radii, we found their high risk of grating structure detachment to be a strong detractor. Minimum achievable bending radii were 55 and 70 mm for pure graphite wafers and graphite wafers with mounted grating structure, respectively. Electron microscopy of graphite surface and cross-sections revealed a fine porous structure conducting to a very stable metal–wafer interface. Grating structures with heights of more than 200 μm were bonded to graphite wafers and their integrity confirmed in flat as well as in bent state using microfocus x-ray imaging. We conclude that graphite is a very well-suited substrate material for manufacturing curved x-ray gratings.

Diagnostic accuracy of a commercially available, deep learning-based chest X-ray interpretation software for detecting culture-confirmed pulmonary tuberculosis

Few evaluations of computer-aided detection (CAD) software for analyzing chest radiographs for tuberculosis have used mycobacterial culture as the reference standard. Using data from a prospective study of symptomatic adults and household contacts of persons with tuberculosis who were seeking care in Karachi, we evaluated the accuracy of LUNIT INSIGHT version 3.1.0.0 (LUNIT, South Korea) for detecting pulmonary tuberculosis in the triage use case. The reference standard was liquid culture. We estimated the diagnostic accuracy using three developer-recommended threshold scores for tuberculosis: 15, 30, and 45. A total 269 of 2190 (12%) participants had culture-confirmed pulmonary tuberculosis. LUNIT-reported abnormalities of nodule, consolidation, fibrosis, and pleural effusion were more common with culture-confirmed tuberculosis. At the tuberculosis threshold score of 30, sensitivity and specificity were, respectively, 87.7% [95% CI: 83.2-91.4%] and 64.3% [62.1-66.4%]. Sensitivity was similar at scores of 15, 88.1% [95% CI: 83.6-91.7%] and 45, 86.6% [82.0 - 90.5%]; and specificity was 57.9% [55.7-60.2%] and 69.9% [67.8-71.9%], respectively. Sensitivity was lower for smear-negative disease, and specificity was lower with increasing age, previous tuberculosis, and decreasing body mass index. Diabetes and tobacco smoking did not modify accuracy. In a population where most tuberculosis was smear-positive, LUNIT-reported radiographic abnormalities were associated with culture-confirmed disease. Manufacturer-recommended threshold scores had limited sensitivity.

Fast and Inexpensive Separation of Bright Phosphor Particles from Commercial Sources by Gravitational and Centrifugal Sedimentation for Deep Tissue X-ray Luminescence Imaging

X-ray luminescence tomography (XLT) detects X-ray scintillators contrast agents using a focused or collimated X-ray beam to provide high spatial resolution excitation through thick tissue. The approach requires bright nanophosphors that are either synthesized or purchased. However, currently available commercial nanophosphors are mostly composed of a polydisperse mixture of several micro- to nano-sized particles that are unsuitable for biomedical imaging applications because of their size and aggregated form. Here, we demonstrate a fast and robust method to obtain uniform nano to submicron phosphor particles from a commercial source of polydisperse Eu- and Tb-doped Gd2O2S particles by separating the smaller particles present using gravitational and centrifugal sedimentation. In contrast to ball milling for 15–60 min, which drastically degraded the particles’ brightness while reducing their size, our sedimentation method enabled the extraction of comparatively bright nanophosphors (≈100–300 nm in size) with a luminescence intensity of ≈10–20% of the several micron particles in the sample. Moreover, if scale up for higher yielding is required, the sedimentation process can be accelerated using fixed-angle and/or swinging bucket rotating centrifugation. Finally, after separation and characterization, nano and submicron phosphors were suspended and imaged through 5 mm thick porcine tissue using our in-house-built scanning X-ray induced luminescence chemical imaging (XELCI) system.