Hard X-ray imaging and tomography at the Biomedical Imaging and Therapy beamlines of Canadian Light Source.

The Biomedical Imaging and Therapy facility of the Canadian Light Source comprises two beamlines, which together cover a wide X-ray energy range from 13 keV up to 140 keV. The beamlines were designed with a focus on synchrotron applications in preclinical imaging and veterinary science as well as microbeam radiation therapy. While these remain a major part of the activities of both beamlines, a number of recent upgrades have enhanced the versatility and performance of the beamlines, particularly for high-resolution microtomography experiments. As a result, the user community has been quickly expanding to include researchers in advanced materials, batteries, fuel cells, agriculture, and environmental studies. This article summarizes the beam properties, describes the endstations together with the detector pool, and presents several application cases of the various X-ray imaging techniques available to users.

Urgent health concerns: Clinical issues associated with accidental ingestion of new metal-blade-containing sticks for heated tobacco products.

INTRODUCTION: Recently, a concerning pattern has emerged in clinical settings, drawing attention to the potential health risks associated with the accidental ingestion, mostly by children, of a new Heated Tobacco Product (HTP) stick, which contains a sharp metal blade inside. METHODS: Following a webinar of the Joint Action on Tobacco Control 2 project, where data on adverse health incidents related to novel tobacco and nicotine products from EU Member States were presented, the Milan Poison Control Center (PCC) conducted a case series study on the accidental ingestion of blade-containing HTP sticks in Italy, between July 2023 and February 2024. The data in the medical records were analyzed to identify the age distribution, clinical presentation symptoms, performed diagnostic procedures, and medical management. RESULTS: Overall, 40 cases of accidental ingestion of HTP sticks were identified and are described. A total of 33 (82.5%) children (infants and toddlers, mean age 12.3 ± 3.3 months) were hospitalized. Of these, 29 underwent abdominal X-rays, two children underwent esophagogastroduodenoscopy, and one child suffered from cut injuries to the tonsillar pillar and genian mucosa, requiring anesthesia for fibroscopy. The observed clinical cases associated with new HTP sticks containing a metal blade occurred over just eight months. This issue required the immediate implementation of corrective measures to mitigate health risks. The Ministry of Health issued an alert regarding the dangers related to the accidental ingestion of the stick and imposed more visible warnings on the package. CONCLUSIONS: It is of the utmost importance to raise awareness among both the general public and medical practitioners to prevent further cases of accidental ingestion of HTP sticks by infants and toddlers, and ensure a prompt and informed response in emergency situations.

Deep learning prediction of survival in patients with heart failure using chest radiographs.

Heart failure (HF) is associated with high rates of morbidity and mortality. The value of deep learning survival prediction models using chest radiographs in patients with heart failure is currently unclear. The aim of our study is to develop and validate a deep learning survival prediction model using chest X-ray (DLSPCXR) in patients with HF. The study retrospectively enrolled a cohort of 353 patients with HF who underwent chest X-ray (CXR) at our institution between March 2012 and March 2017. The dataset was randomly divided into training (n = 247) and validation (n = 106) datasets. Univariate and multivariate Cox analysis were conducted on the training dataset to develop clinical and imaging survival prediction models. The DLSPCXR was trained and the selected clinical parameters were incorporated into DLSPCXR to establish a new model called DLSPinteg. Discrimination performance was evaluated using the time-dependent area under the receiver operating characteristic curves (TD AUC) at 1, 3, and 5-years survival. Delong's test was employed for the comparison of differences between two AUCs of different models. The risk-discrimination capability of the optimal model was evaluated by the Kaplan-Meier curve. In multivariable Cox analysis, older age, higher N-terminal pro-B-type natriuretic peptide (NT-ProBNP), systolic pulmonary artery pressure (sPAP) > 50 mmHg, New York Heart Association (NYHA) functional class III-IV and cardiothoracic ratio (CTR) ≥ 0.62 in CXR were independent predictors of poor prognosis in patients with HF. Based on the receiver operating characteristic (ROC) curve analysis, DLSPCXR had better performance at predicting 5-year survival than the imaging Cox model in the validation cohort (AUC: 0.757 vs. 0.561, P = 0.01). DLSPinteg as the optimal model outperforms the clinical Cox model (AUC: 0.826 vs. 0.633, P = 0.03), imaging Cox model (AUC: 0.826 vs. 0.555, P < 0.001), and DLSPCXR (AUC: 0.826 vs. 0.767, P = 0.06). Deep learning models using chest radiographs can predict survival in patients with heart failure with acceptable accuracy.

An advanced multisystem histiocytic sarcoma in a pregnant woman: A case report.

Histiocytic sarcoma is an extremely rare disease that's hard to diagnose and treat, often leading to a poor prognosis. Here, we present a case report detailing a rare occurrence of HS in a 37-year-old pregnant woman who first presented with left shoulder pain, palpitations, and a productive cough at 20 weeks of gestation. Her diagnostic evaluations were performed, including different imaging modalities such as chest X-rays, CT scans, and MRI. Imaging revealed a large mediastinal mass with extensive involvement of the adrenal glands, lungs, and lymph nodes. The definitive diagnosis of HS is based on pathological and morphological features, and the immunohistochemistry report plays a key role. In our case, the diagnosis of HS was confirmed through pathological evaluation and immunohistochemistry, with a positive CD68 result obtained from a supraclavicular lymph node biopsy. A hospital committee comprising medical specialists like hematologists-oncologists, pathologists, pulmonologists, and obstetricians was brought together to assess the case collectively. The patient received chemotherapy, which alleviated her symptoms and maintained her condition. Based on the committee's recommendations, despite a healthy fetus and normal obstetric sonograms, the decision was made to terminate the pregnancy with the consent of the patient and her family. Despite initial improvement postchemotherapy, the patient's condition worsened, necessitating intubation. Tragically, two months after the initial admission, the patient passed away due to severe complications. In this case report, we provide a literature review and review of the patient's imaging reports. Since the patient is pregnant and HS is uncommon, it's important to highlight that this case is unique and worth sharing.

Development of Lead-Free Materials for Radiation Shielding in Medical Settings: A Review.

Radiation protection is an essential issue in diagnostic radiology to ensure the safety of patients, healthcare professionals, and the general public. Lead has traditionally been used as a shielding material due to its high atomic number, high density, and effectiveness in attenuating radiation. However, some concerns related to the long-term health effects of toxicity, environmental disease as well as heavy weight of lead have led to the search for alternative lead-free shielding materials. Leadfree multilayered polymer composites and non-lead nano-composite shields have been suggested as effective shielding materials to replace conventional lead-based and single metal shields. Using several elements with high density and atomic number, such as bismuth, barium, gadolinium, and tungsten, offer significant enhancements in the shielding ability of composites. This review focuses on the development and use of lead-free materials for radiation shielding in medical settings. It discusses the drawbacks of traditional lead shielding, such as toxicity, weight, and recycling challenges, and highlights the benefits of lead-free alternatives.

Substantial variability in what is considered important in the radiological report for anterior shoulder instability: a Delphi study with Dutch musculoskeletal radiologists and orthopedic surgeons.

Background: Standardized consensus-based radiological reports for shoulder instability may improve clinical quality, reduce heterogeneity, and reduce workload. Therefore, the aim of this study was to determine important elements for the x-ray, magnetic resonance imaging (MRI) arthrography (MRA), and computed tomography (CT) report, the extent of variability, and important MRI views and settings. Methods: An expert panel of musculoskeletal radiologists and orthopedic surgeons was recruited in a three-round Delphi design. Important elements were identified for the x-ray, MRA, and CT report and important MRI views and setting. These were rated on a 0-9 Likert scale. High variability was defined as at least one score between 1-3 and 7-9. Consensus was reached when ≥80% scored an element 1-3 or 7-9. Results: The expert panel consisted of 21 musculoskeletal radiologists and 15 orthopedic surgeons. The number of elements identified in the first round was seventeen for the x-ray report, 52 for MRA, 21 for CT, and 23 for the MRI protocol. The number of elements that reached consensus was five for x-ray, twenty for MRA, nine for CT, and two for the MRI protocol. High variability was observed in 76.5% (n = 13) x-ray elements, 85.0% (n = 45) MRA, 76.2% (n = 16) CT, and 85.7% (n = 18) MRI protocol. Conclusion: Substantial variability was observed in the scoring of important elements in the radiological for the evaluation of anterior shoulder instability, regardless of modality. Consensus was reached for five elements in the x-ray report, twenty in the MRA report, and nine in the CT report. Finally, consensus was reached on two elements regarding MRA views and settings.

The diagnostic accuracy of community spine radiology for adolescent idiopathic scoliosis brace candidates.

PURPOSE: The study aims to establish the diagnostic accuracy of community spine x-rays for brace candidates. METHODS: A review of adolescent idiopathic scoliosis patients seen for initial visit at a tertiary care pediatric hospital was conducted (n = 170). The index test was the pre-referral community spine x-ray interpreted by a community radiologist. Measures of diagnostic accuracy for the index test were determined against the reference standard if images were obtained within 90 days (n = 111). The reference standard was the 3-foot standing EOS spine x-ray evaluated by spine specialists. Diagnostic criterion for a brace candidate was dichotomized by Cobb angle range (25-40°) according to Scoliosis Research Society criteria. Risser stage was not included given significant missing data in index reports. To mitigate the uncertainty around true progression, sensitivity analyses were conducted on a sub-sample of data when index test was within 60 days of the reference standard (n = 67). RESULTS: Accuracy of the community spine x-ray to detect a brace candidate was 65.8% (95% CI 56.2-74.5). Sensitivity of the index test was 65.4% with a false negative rate of 34.6%. Specificity was 66.1% with a false positive rate of 33.9%. Positive and negative predictive values were 63.0% and 68.4%, respectively. Of the total number of brace candidates (n = 52), 32.7% were missed because of underestimation in Cobb angle (95% CI 21.5-46.2). The proportion of missed brace candidates because of underestimation was unchanged with 60-day data (p = 0.37). CONCLUSIONS: Inaccuracies in community spine radiology may lead to missed opportunities for non-operative treatment.

Deep learning pneumoconiosis staging and diagnosis system based on multi-stage joint approach.

BACKGROUND: Pneumoconiosis has a significant impact on the quality of patient survival due to its difficult staging diagnosis and poor prognosis. This study aimed to develop a computer-aided diagnostic system for the screening and staging of pneumoconiosis based on a multi-stage joint deep learning approach using X-ray chest radiographs of pneumoconiosis patients. METHODS: In this study, a total of 498 medical chest radiographs were obtained from the Department of Radiology of West China Fourth Hospital. The dataset was randomly divided into a training set and a test set at a ratio of 4:1. Following histogram equalization for image enhancement, the images were segmented using the U-Net model, and staging was predicted using a convolutional neural network classification model. We first used Efficient-Net for multi-classification staging diagnosis, but the results showed that stage I/II of pneumoconiosis was difficult to diagnose. Therefore, based on clinical practice we continued to improve the model by using the Res-Net 34 Multi-stage joint method. RESULTS: Of the 498 cases collected, the classification model using the Efficient-Net achieved an accuracy of 83% with a Quadratic Weighted Kappa (QWK) score of 0.889. The classification model using the multi-stage joint approach of Res-Net 34 achieved an accuracy of 89% with an area under the curve (AUC) of 0.98 and a high QWK score of 0.94. CONCLUSIONS: In this study, the diagnostic accuracy of pneumoconiosis staging was significantly improved by an innovative combined multi-stage approach, which provided a reference for clinical application and pneumoconiosis screening.

Revolutionizing Healthcare: Qure.AI's Innovations in Medical Diagnosis and Treatment.

Qure.AI, a leading company in artificial intelligence (AI) applied to healthcare, has developed a suite of innovative solutions to revolutionize medical diagnosis and treatment. With a plethora of FDA-approved tools for clinical use, Qure.AI continually strives for innovation in integrating AI into healthcare systems. This article delves into the efficacy of Qure.AI's chest X-ray interpretation tool, "qXR," in medicine, drawing from a comprehensive review of clinical trials conducted by various institutions. Key applications of AI in healthcare include machine learning, deep learning, and natural language processing (NLP), all of which contribute to enhanced diagnostic accuracy, efficiency, and speed. Through the analysis of vast datasets, AI algorithms assist physicians in interpreting medical data and making informed decisions, thereby improving patient care outcomes. Illustrative examples highlight AI's impact on medical imaging, particularly in the diagnosis of conditions such as breast cancer, heart failure, and pulmonary nodules. AI can significantly reduce diagnostic errors and expedite the interpretation of medical images, leading to more timely interventions and treatments. Furthermore, AI-powered predictive analytics enable early detection of diseases and facilitate personalized treatment plans, thereby reducing healthcare costs and improving patient outcomes. The efficacy of AI in healthcare is underscored by its ability to complement traditional diagnostic methods, providing physicians with valuable insights and support in clinical decision-making. As AI continues to evolve, its role in patient care and medical research is poised to expand, promising further advancements in diagnostic accuracy and treatment efficacy.

Role of Lung Ultrasonography in Acute Respiratory Distress in Pediatric Age Group: A Prospective Single-Centre Study.

Introduction Lung diseases are the most frequently encountered form of diseases primarily affecting infants under one year of age. Although the chest X-ray is the first modality of choice, ultrasonography (USG) has emerged as an alternative. Lung ultrasound (LUS) finds its application in the evaluation of several pediatric lung diseases. Objective To assess the use of LUS in acute lower respiratory infections and assess the correlation between etiological diagnosis and radiological diagnosis. Methods This was a hospital-based prospective observational study conducted with children presenting with upper respiratory infections. Around 97 children were included in the study. Clinical diagnosis was made by the pediatrician. LUS was performed by a trained radiologist, using the two-dimensional (2D) ultrasound mode and motion mode (M mode) to assess the LUS in the respective areas of the chest, thereby assessing bilateral lung fields for these patients. Results The majority of our study participants were under one year old (87%), and more than half were male (55%). Bronchiolitis and lower respiratory tract infections (LRIs) were the most commonly seen clinical diagnoses. The distribution of USG findings was statistically significant across the clinical diagnosis (p-value < 0.05). Conclusion Our study found that LUS can serve as an important tool for diagnosing several acute respiratory diseases. It also showed that LUS can replace X-rays in cases of children diagnosed with acute respiratory diseases.

Thia- and Seleno-Michael reactions for the synthesis of Carbonic anhydrases inhibitors.

Novel chalcogen-containing amides and esters bearing the benzenesulfonamide moiety have been synthesised upon nucleophilic conjugate addition of thiols and selenols to suitable electron-deficient alkenes. The activity of the synthesised compounds as Carbonic Anhydrases inhibitors has been investigated in vitro and the inhibition mechanism has been elucidated by X-rays studies.

Cardiomegaly: Navigating the uncharted territories of heart failure - A multimodal radiological journey through advanced imaging, pathophysiological landscapes, and innovative therapeutic frontiers.

Cardiomegaly is among the disorders categorized by a structural enlargement of the heart by any of the situations including pregnancy, resulting in damage to heart muscles and causing trouble in normal heart functioning. Cardiomegaly can be defined in terms of dilatation with an enlarged heart and decreased left or biventricular contraction. The genetic origin of cardiomegaly is becoming more evident due to extensive genomic research opening up new avenues to ensure the use of precision medicine. Cardiomegaly is usually assessed by using an array of radiological modalities, including computed tomography (CT) scans, chest X-rays, and MRIs. These imaging techniques have provided an important opportunity for the physiology and anatomy of the heart. This review aims to highlight the complexity of cardiomegaly, highlighting the contribution of both ecological and genetic variables to its progression. Moreover, we further highlight the worth of precise clinical diagnosis, which comprises blood biomarkers and electrocardiograms (EKG ECG), demonstrating the significance of distinguishing between numerous basic causes. Finally, the analysis highlights the extensive variation of treatment lines, such as lifestyle modifications, prescription drugs, surgery, and implantable devices, although highlighting the critical need for individualized and personalized care.

Real-Time Ultrasound Tip Location Reduces Malposition and Radiation Exposure during Umbilical Venous Catheter Placement in Neonates: A Retrospective, Observational Study.

INTRODUCTION: The umbilical venous catheter is a vital access device in neonatal intensive care units for preterm and critically ill infants. Correct positioning is crucial, as malpositioning can lead to severe complications. According to international guidelines, the position of the umbilical venous catheter tip must be assessed in real time; traditionally, the catheter is visualized with a thoracoabdominal X-ray, but one of the most effective and safest methods is therefore real-time ultrasound. METHODS: This study compares real-time ultrasound and traditional X-ray methods for assessing umbilical venous catheter tip location in 461 cases. The rate of tip malposition was analyzed retrospectively. The secondary aim was to assess indwelling time of umbilical venous catheters and reasons of removal. RESULTS: Real-time ultrasound tip location, found to be more reliable and efficient, demonstrated a significantly lower incidence of primary malpositioning compared to X-ray assessments (9.6 vs. 75.9%). The study also highlighted the association of real-time ultrasound with reduced catheter manipulation, fewer radiographs, and higher indwelling times of umbilical venous catheter. The multiple logistic regression showed a high probability of the central safe position of the umbilical venous catheter tip using real-time ultrasound tip location (odds ratio 29.5, 95% confidence interval: 17.4-49.4). CONCLUSION: The findings support the adoption of real-time ultrasound in clinical settings to enhance umbilical venous catheter placement accuracy and minimize associated risks. A minimal training investment is needed to attain the proficiency to visualize the umbilical venous catheters, offering a substantial advantage in terms of both cost-effectiveness for the procedure and enhanced patient safety.

Mechanical properties of blood exosomes and lipoproteins after the rat whole blood irradiation with X-rays in vitro explored by atomic force microscopy.

Blood is a two-component system with two levels of hierarchy: the macrosystem of blood formed elements and the dispersed system of blood nanoparticles. Biological nanoparticles are the key participants in communication between the irradiated and non-irradiated cells and inducers of the non-targeted effects of ionizing radiation. The work aimed at studying by atomic force microscopy the structural, mechanical, and electrical properties of exosomes and lipoproteins (LDL/VLDL) isolated from rat blood after its exposure to X-rays in vitro. MATERIALS AND METHODS: The whole blood of Wistar rats fed with a high-fat diet was irradiated with X-rays (1 and 100 Gy) in vitro. The structural and mechanical properties (the elastic modulus and nonspecific adhesion force) of exosome and lipoprotein isolates from the blood by ultracentrifugation method were studied using Bruker Bioscope Resolve atomic force microscope in PF QNM mode, their electric properties (the zeta-potential) was measured by electrophoretic mobility. RESULTS: Lipoproteins isolated from non-irradiated blood were softer (Me(LQ; UQ): 7.8(4.9;12.1) MPa) compared to blood nanoparticles of its exosome fraction (34.8(22.6;44.9) MPa) containing both exosomes and non-membrane nanoparticles. X-ray blood irradiation with a dose of 1 Gy significantly weakened the elastic properties of lipoproteins. Exposure of the blood to 100 Gy X-rays made lipoproteins stiffer and their nonspecific adhesive properties stronger. The radiation effects on the mechanical parameters of exosomes and non-membrane nanoparticles in exosome fractions differed. The significant radiation-induced change in electric properties of the studied nanoparticles was detected only for lipoproteins in the blood irradiated with 1 Gy X-rays. The low-dose radiation-induced changes in zeta-potential and increase in lipoprotein size with the appearance of a soft thick surface layer indicate the formation of the modified lipoproteins covered with a corona from macromolecules of irradiated blood. CONCLUSION: Our data obtained using the nanomechanical mapping mode of AFM are the first evidence of the significant radiation-induced changes in the structural and mechanical properties of the dispersed system of blood nanoparticles after the X-ray irradiation of the blood.

Class imbalance on medical image classification: towards better evaluation practices for discrimination and calibration performance.

PURPOSE: This work aims to assess standard evaluation practices used by the research community for evaluating medical imaging classifiers, with a specific focus on the implications of class imbalance. The analysis is performed on chest X-rays as a case study and encompasses a comprehensive model performance definition, considering both discriminative capabilities and model calibration. MATERIALS AND METHODS: We conduct a concise literature review to examine prevailing scientific practices used when evaluating X-ray classifiers. Then, we perform a systematic experiment on two major chest X-ray datasets to showcase a didactic example of the behavior of several performance metrics under different class ratios and highlight how widely adopted metrics can conceal performance in the minority class. RESULTS: Our literature study confirms that: (1) even when dealing with highly imbalanced datasets, the community tends to use metrics that are dominated by the majority class; and (2) it is still uncommon to include calibration studies for chest X-ray classifiers, albeit its importance in the context of healthcare. Moreover, our systematic experiments confirm that current evaluation practices may not reflect model performance in real clinical scenarios and suggest complementary metrics to better reflect the performance of the system in such scenarios. CONCLUSION: Our analysis underscores the need for enhanced evaluation practices, particularly in the context of class-imbalanced chest X-ray classifiers. We recommend the inclusion of complementary metrics such as the area under the precision-recall curve (AUC-PR), adjusted AUC-PR, and balanced Brier score, to offer a more accurate depiction of system performance in real clinical scenarios, considering metrics that reflect both, discrimination and calibration performance. CLINICAL RELEVANCE STATEMENT: This study underscores the critical need for refined evaluation metrics in medical imaging classifiers, emphasizing that prevalent metrics may mask poor performance in minority classes, potentially impacting clinical diagnoses and healthcare outcomes. KEY POINTS: Common scientific practices in papers dealing with X-ray computer-assisted diagnosis (CAD) systems may be misleading. We highlight limitations in reporting of evaluation metrics for X-ray CAD systems in highly imbalanced scenarios. We propose adopting alternative metrics based on experimental evaluation on large-scale datasets.

First report of X-ray induced somatic mutation by Muller's department chair fails to support Muller's linearity hypothesis.

This paper reevaluates the first report of X-ray-induced somatic gene mutations. It was undertaken by John Patterson, Department Chair of Hermann Muller, using the same biological model, methods and equipment of Muller. Patterson reported X-ray induced mutation frequencies for X-chromosome-linked (sex-linked) recessive gene mutations in somatic cells of Drosophila melanogaster that resulted in color changes in the ommatidia of the eyes. Results were based on color changes detected in both male and female offspring irradiated while in egg, larval or pupal stages and for unirradiated controls. Patterson claimed that the observed dose response displayed linearity, with a clear implication that the linear response extended to background exposure levels of unirradiated controls. This reanalysis disputes Patterson's interpretation, showing that the dose response in the low-dose zone strongly supported a threshold model. The doses in the experiment, which were not clearly presented, were so high that it would preclude the assumption that the experiment provided any information of relevance to radiation exposures of humans at low doses, or even at high doses delivered at low-dose rates. Induced phenotypical changes that occurred at the higher doses, especially in female offspring, overwhelmingly resulted from X-ray-induced chromosome breaks instead of point mutations as initially expected by Patterson. The Patterson findings and linearity interpretations were an important contributory factor in the acceptance of the linear non-threshold (LNT) model during the formative time of concept consolidation. It is rather shocking now to see that the actual data provided no support for the LNT model.

Hard X-ray operation of X-ray gas monitors at the European XFEL.

X-ray gas monitors (XGMs) are operated at the European XFEL for non-invasive single-shot pulse energy measurements and average beam-position monitoring. The underlying measurement principle is the photo-ionization of rare gas atoms at low gas pressures and the detection of the photo-ions and photo-electrons created. These are essential for tuning and sustaining self-amplified spontaneous emission (SASE) operation, machine radiation safety, and sorting single-shot experimental data according to pulse energy. In this paper, the first results from XGM operation at photon energies up to 30 keV are presented, which are far beyond the original specification of this device. Here, the Huge Aperture MultiPlier (HAMP) is used for single-shot pulse energy measurements since the standard X-ray gas monitor detectors (XGMDs) do not provide a sufficient signal-to-noise ratio, even at the highest operating gas pressures. A single-shot correlation coefficient of 0.98 is measured between consecutive XGMs operated with HAMP, which is as good as measuring with the standard XGMD detectors. An intra-train non-linearity of the HAMP signal is discovered, and operation parameters to mitigate this effect are studied. The upper repetition rate limit of HAMP operation at 2.25 MHz is also determined. Finally, the possibilities and limits for future XGM operation at photon energies up to 50 keV are discussed.

High-throughput and high-resolution powder X-ray diffractometer consisting of six sets of 2D CdTe detectors with variable sample-to-detector distance and innovative automation system.

The demand for powder X-ray diffraction analysis continues to increase in a variety of scientific fields, as the excellent beam quality of high-brightness synchrotron light sources enables the acquisition of high-quality measurement data with high intensity and angular resolution. Synchrotron powder diffraction has enabled the rapid measurement of many samples and various in situ/operando experiments in nonambient sample environments. To meet the demands for even higher throughput measurements using high-energy X-rays at SPring-8, a high-throughput and high-resolution powder diffraction system has been developed. This system is combined with six sets of two-dimensional (2D) CdTe detectors for high-energy X-rays, and various automation systems, including a system for automatic switching among large sample environmental equipment, have been developed in the third experimental hutch of the insertion device beamline BL13XU at SPring-8. In this diffractometer system, high-brilliance and high-energy X-rays ranging from 16 to 72 keV are available. The powder diffraction data measured under ambient and various nonambient conditions can be analysed using Rietveld refinement and the pair distribution function. Using the 2D CdTe detectors with variable sample-to-detector distance, three types of scan modes have been established: standard, single-step and high-resolution. A major feature is the ability to measure a whole powder pattern with millisecond resolution. Equally important, this system can measure powder diffraction data with high Q exceeding 30 Å-1 within several tens of seconds. This capability is expected to contribute significantly to new research avenues using machine learning and artificial intelligence by utilizing the large amount of data obtained from high-throughput measurements.

L3-edge X-ray spectroscopy of rhodium and palladium compounds.

L3-edge high-energy-resolution fluorescence-detection X-ray absorption near-edge structure (XANES) spectra for palladium and rhodium compounds are presented, with focus on their electronic structures. The data are compared with transmission XANES spectra recorded at the K-edge. A correlation between the absorption edge energy and the metal ion oxidation state is not observed. Despite the different filling of the 4d orbitals and different local coordination, the Rh and Pd compounds show remarkably similar spectral shapes. Calculation of the density of states and of the L3-XANES data reproduce the experimental results.

CAFES: Chest X-ray Analysis using Federated Self-supervised Learning for Pediatric COVID-19 Detection.

Chest X-rays (CXRs) play a pivotal role in cost-effective clinical assessment of various heart and lung related conditions. The urgency of COVID-19 diagnosis prompted their use in identifying conditions like lung opacity, pneumonia, and acute respiratory distress syndrome in pediatric patients. We propose an AI-driven solution for binary COVID-19 versus non-COVID-19 classification in pediatric CXRs. We present a Federated Self-Supervised Learning (FSSL) framework to enhance Vision Transformer (ViT) performance for COVID-19 detection in pediatric CXRs. ViT's prowess in vision-related binary classification tasks, combined with self-supervised pre-training on adult CXR data, forms the basis of the FSSL approach. We implement our strategy on the Rhino Health Federated Computing Platform (FCP), which ensures privacy and scalability for distributed data. The chest X-ray analysis using the federated SSL (CAFES) model, utilizes the FSSL-pre-trained ViT weights and demonstrated gains in accurately detecting COVID-19 when compared with a fully supervised model. Our FSSL-pre-trained ViT showed an area under the precision-recall curve (AUPR) of 0.952, which is 0.231 points higher than the fully supervised model for COVID-19 diagnosis using pediatric data. Our contributions include leveraging vision transformers for effective COVID-19 diagnosis from pediatric CXRs, employing distributed federated learning-based self-supervised pre-training on adult data, and improving pediatric COVID-19 diagnosis performance. This privacy-conscious approach aligns with HIPAA guidelines, paving the way for broader medical imaging applications.