Characterization of a new low-dose and low-energy Gafchromic film LD-V1.

PURPOSE: To characterize the dose-response, energy dependence, postexposure changes, orientation dependence, and spatial capabilities of LD-V1, a new low-dose Gafchromic film for low-energy x-ray dosimetry. METHODS: A single sheet of LD-V1 Gafchromic film was cut into 15 × 20 mm2 rectangles with a notch to track orientation. Eight different doses between 5 and 320 mGy were delivered by an MXR-160/22 x-ray tube using x-ray beams of 90, 100, and 120 kVp filtered with 3 mm of Al and 2 mm of Ti. The 120 kVp films were scanned at 1, 1.5, 2, 3, 12, 24, 48, 72, and 168 h postexposure in portrait orientation and additionally scanned in landscape orientation at 24 h. The 90 and 100 kVp films were scanned at 24 h postexposure in portrait orientation. Lastly, a 20 × 200 mm2 strip of film was irradiated using a thin-slit imaging collimator and scanned 24 h postexposure to test the film performance in an x-ray imaging application. RESULTS: Of the three color channels, the red channel was found to produce a dose-response curve with a large range of net optical density (netOD) values across the considered dose range. A prominent energy dependence was discovered, resulting in dose discrepancies on the scale of 17 mGy between 90 and 120 kVp for a dose of 80 mGy. The measured postexposure changes suggest that the calibration irradiation-to-scan time should be longer than 12 h with a ± 4 h scanning time window for dose errors of <0.5%. An average dose difference of 3.4% was found between the two scanning orientations. Lastly, noise of 4% was measured in the thin slit collimator film for a dose of 30 mGy. CONCLUSIONS: We have characterized the LD-V1 film for low-energy, low-dose x-ray dosimetry. Energy, scan-time, and orientation dependencies should be considered when using this film.

Measurement of coherent vibrational dynamics with X-ray Transient Absorption Spectroscopy simultaneously at the Carbon K- and Chlorine L2,3- edges.

X-ray Transient Absorption Spectroscopy (XTAS) is a powerful probe for ultrafast molecular dynamics. The evolution of XTAS signal is controlled by the shapes of potential energy surfaces of the associated core-excited states, which are difficult to directly measure. Here, we study the vibrational dynamics of Raman activated CCl4 with XTAS targeting the C 1s and Cl 2p electrons. The totally symmetric stretching mode leads to concerted elongation or contraction in bond lengths, which in turn induce an experimentally measurable red or blue shift in the X-ray absorption energies associated with inner-shell electron excitations to the valence antibonding levels. The ratios between slopes of different core-excited potential energy surfaces (CEPESs) thereby extracted agree very well with Restricted Open-Shell Kohn-Sham calculations. The other, asymmetric, modes do not measurably contribute to the XTAS signal. The results highlight the ability of XTAS to reveal coherent nuclear dynamics involving  < 0.01 Å atomic displacements and also provide direct measurement of forces on CEPESs.

X-ray ghost imaging with a specially developed beam splitter.

X-ray ghost imaging with a crystal beam splitter has advantages in highly efficient imaging due to the simultaneous acquisition of signals from both the object beam and reference beam. However, beam splitting with a large field of view, uniform distribution and high correlation has been a great challenge up to now. Therefore, a dedicated beam splitter has been developed by optimizing the optical layout of a synchrotron radiation beamline and the fabrication process of a Laue crystal. A large field of view, consistent size, uniform intensity distribution and high correlation were obtained simultaneously for the two split beams. Modulated by a piece of copper foam upstream of the splitter, a correlation of 92% between the speckle fields of the object and reference beam and a Glauber function of 1.25 were achieved. Taking advantage of synthetic aperture X-ray ghost imaging (SAXGI), a circuit board of size 880 × 330 pixels was successfully imaged with high fidelity. In addition, even though 16 measurements corresponding to a sampling rate of 1% in SAXGI were used for image reconstruction, the skeleton structure of the circuit board can still be determined. In conclusion, the specially developed beam splitter is applicable for the efficient implementation of X-ray ghost imaging.

Artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer: an evidence synthesis early value assessment.

Background: Lung cancer is one of the most common types of cancer in the United Kingdom. It is often diagnosed late. The 5-year survival rate for lung cancer is below 10%. Early diagnosis may improve survival. Software that has an artificial intelligence-developed algorithm might be useful in assisting with the identification of suspected lung cancer. Objectives: This review sought to identify evidence on adjunct artificial intelligence software for analysing chest X-rays for suspected lung cancer, and to develop a conceptual cost-effectiveness model to inform discussion of what would be required to develop a fully executable cost-effectiveness model for future economic evaluation. Data sources: The data sources were MEDLINE All, EMBASE, Cochrane Database of Systematic Reviews, Cochrane CENTRAL, Epistemonikos, ACM Digital Library, World Health Organization International Clinical Trials Registry Platform, clinical experts, Tufts Cost-Effectiveness Analysis Registry, company submissions and clinical experts. Searches were conducted from 25 November 2022 to 18 January 2023. Methods: Rapid evidence synthesis methods were employed. Data from companies were scrutinised. The eligibility criteria were (1) primary care populations referred for chest X-ray due to symptoms suggestive of lung cancer or reasons unrelated to lung cancer; (2) study designs that compared radiology specialist assessing chest X-ray with adjunct artificial intelligence software versus radiology specialists alone and (3) outcomes relating to test accuracy, practical implications of using artificial intelligence software and patient-related outcomes. A conceptual decision-analytic model was developed to inform a potential full cost-effectiveness evaluation of adjunct artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer. Results: None of the studies identified in the searches or submitted by the companies met the inclusion criteria of the review. Contextual information from six studies that did not meet the inclusion criteria provided some evidence that sensitivity for lung cancer detection (but not nodule detection) might be higher when chest X-rays are interpreted by radiology specialists in combination with artificial intelligence software than when they are interpreted by radiology specialists alone. No significant differences were observed for specificity, positive predictive value or number of cancers detected. None of the six studies provided evidence on the clinical effectiveness of adjunct artificial intelligence software. The conceptual model highlighted a paucity of input data along the course of the diagnostic pathway and identified key assumptions required for evidence linkage. Limitations: This review employed rapid evidence synthesis methods. This included only one reviewer conducting all elements of the review, and targeted searches that were conducted in English only. No eligible studies were identified. Conclusions: There is currently no evidence applicable to this review on the use of adjunct artificial intelligence software for the detection of suspected lung cancer on chest X-ray in either people referred from primary care with symptoms of lung cancer or people referred from primary care for other reasons. Future work: Future research is required to understand the accuracy of adjunct artificial intelligence software to detect lung nodules and cancers, as well as its impact on clinical decision-making and patient outcomes. Research generating key input parameters for the conceptual model will enable refinement of the model structure, and conversion to a full working model, to analyse the cost-effectiveness of artificial intelligence software for this indication. Study registration: This study is registered as PROSPERO CRD42023384164. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135755) and is published in full in Health Technology Assessment; Vol. 28, No. 50. See the NIHR Funding and Awards website for further award information.

Lung cancer is one of the most common types of cancer in the United Kingdom. Early diagnosis may improve survival, as lung cancer is often diagnosed late. Chest X-rays can be used to identify features of lung cancer. There can be delays in getting X-rays, and sometimes features of lung cancer are not seen on them. Artificial intelligence software may help by finding features of cancer on chest X-rays and highlighting them. A radiologist will look at the X-rays and information from the software. There is a lack of information about how lung cancer diagnosis could change if artificial intelligence software is used and what the costs may be to the National Health Service. This project looked at the use of artificial intelligence software in the detection of lung cancer in people referred from primary care. Software companies were invited to provide evidence. There were no studies that looked at this topic among people from primary care. We summarised the closest evidence we could find instead. All of this had flaws, so we could not tell if the results were accurate or helpful to this review. It was not clear if artificial intelligence helped to find cancers or improve people's health. We made a theoretical model to discuss the best way to assess if artificial intelligence software might be cost-effective in detecting lung cancer and what evidence would be needed to do this in a fully working model. Costs and alternative pricing models provided by five companies were used to calculate the cost of adding artificial intelligence software to review chest X-rays in people referred from their general practitioner, for the first 5 years, based on one National Health Service trust. Future studies are needed to identify the impact of adjunct artificial intelligence on test accuracy, clinical decision-making and patient outcomes (e.g. mortality and morbidity).

Proton- compared to X-irradiation leads to more acinar atrophy and greater hyposalivation accompanied by a differential cytokine response.

Proton therapy gives less dose to healthy tissue compared to conventional X-ray therapy, but systematic comparisons of normal tissue responses are lacking. The aim of this study was to investigate late tissue responses in the salivary glands following proton- or X-irradiation of the head and neck in mice. Moreover, we aimed at investigating molecular responses by monitoring the cytokine levels in serum and saliva. Female C57BL/6J mice underwent local fractionated irradiation with protons or X-rays to the maximally tolerated acute level. Saliva and serum were collected before and at different time points after irradiation to assess salivary gland function and cytokine expression. To study late responses in the major salivary glands, histological analyses were performed on tissues collected at day 105 after onset of irradiation. Saliva volume after proton and X-irradiation was significantly lower than for controls and remained reduced at all time points after irradiation. Protons caused reduced saliva production and fewer acinar cells in the submandibular glands compared to X-rays at day 105. X-rays induced a stronger inflammatory cytokine response in saliva compared to protons. This work supports previous preclinical findings and indicate that the relative biological effectiveness of protons in normal tissue might be higher than the commonly used value of 1.1.

Diagnosis of suspected pediatric distal forearm fractures with point-of-care-ultrasound (POCUS) by pediatric orthopedic surgeons after minimal training.

BACKGROUND: Several studies have advocated the use of ultrasound to diagnose distal forearm fractures in children. However, there is limited data on the diagnostic accuracy of ultrasound for distal forearm fractures when conducted by pediatric surgeons or trainees who manage orthopedic injuries in children. The objective of this study was to determine the diagnostic accuracy of point-of-care ultrasound (POCUS) for pediatric distal forearm fractures when conducted by pediatric surgeons and trainees after minimal training. METHODS: This diagnostic study was conducted in a tertiary hospital emergency department in Germany. Participants were children and adolescents under 15 years of age who presented to the emergency department with an acute, suspected, isolated distal forearm fracture requiring imaging. Pediatric surgeons and trainees, after minimal training for sonographic fracture diagnosis, performed 6-view distal forearm POCUS on each participant prior to X-ray imaging. All data was retrospectively collected from the hospital's routine digital patient files. The primary outcome was the diagnostic accuracy of POCUS compared to X-ray as the reference standard. RESULTS: From February to June 2021, 146 children under 15 met all inclusion and exclusion criteria, and 106 data sets were available for analysis. Regarding the presence of a fracture, X-ray and Wrist-POCUS showed the same result in 99.1%, with 83/106 (78.3%) fractures detected in both modalities and one suspected buckle fracture on POCUS not confirmed in the radiographs. Wrist-POCUS had a sensitivity of 100% (95% CI [0.956, 1]) and a specificity of 95.8% (95% CI [0.789, 0.999]) compared to radiographs. In 6 cases, there were minor differences regarding a concomitant ulnar buckle. The amount of prior ultrasound training had no influence on the accuracy of Wrist-POCUS for diagnosing distal forearm fractures. All fractures were reliably diagnosed even when captured POCUS images did not meet all quality criteria. CONCLUSION: Pediatric surgeons and trainees, after minimal training in POCUS, had excellent diagnostic accuracy for distal forearm fractures in children and adolescents using POCUS compared to X-ray.

Role of Oxidative Stress Signaling, Nrf2, on Survival and Stemness of Human Adipose-Derived Stem Cells Exposed to X-rays, Protons and Carbon Ions.

Some cancers have a poor prognosis and often lead to local recurrence because they are resistant to available treatments, e.g., glioblastoma. Attempts have been made to increase the sensitivity of resistant tumors by targeting pathways involved in the resistance and combining it, for example, with radiotherapy (RT). We have previously reported that treating glioblastoma stem cells with an Nrf2 inhibitor increases their radiosensitivity. Unfortunately, the application of drugs can also affect normal cells. In the present study, we aim to investigate the role of the Nrf2 pathway in the survival and differentiation of normal human adipose-derived stem cells (ADSCs) exposed to radiation. We treated ADSCs with an Nrf2 inhibitor and then exposed them to X-rays, protons or carbon ions. All three radiation qualities are used to treat cancer. The survival and differentiation abilities of the surviving ADSCs were studied. We found that the enhancing effect of Nrf2 inhibition on cell survival levels was radiation-quality-dependent (X-rays > proton > carbon ions). Furthermore, our results indicate that Nrf2 inhibition reduces stem cell differentiation by 35% and 28% for adipogenesis and osteogenesis, respectively, using all applied radiation qualities. Interestingly, the results show that the cells that survive proton and carbon ion irradiations have an increased ability, compared with X-rays, to differentiate into osteogenesis and adipogenesis lineages. Therefore, we can conclude that the use of carbon ions or protons can affect the stemness of irradiated ADSCs at lower levels than X-rays and is thus more beneficial for long-time cancer survivors, such as pediatric patients.

Ion Leakage Current Control for Polycrystalline Metal Halide Perovskite Direct X-ray Detectors.

Metal halide perovskites have emerged as promising materials for X-ray detection due to their high X-ray attenuation coefficients, defect tolerance, and suitability for large-area, low-temperature fabrication. However, the intrinsic high ion conductivity of these materials presents challenges, such as high dark current density and current drift, which impair the stability and sensitivity of perovskite X-ray detectors. This study introduces an approach to mitigating these issues by incorporating 2,2,3,3,3-pentafluoropropylamine hydrochloride (PFH) into polycrystalline MAPbI3-xClx films using a one-step blade-coating method. PFH aggregates at grain boundaries, raising local vacuum energy levels and passivating surface defects, thereby reducing ion conductivity without affecting electron conductivity. As a result, this approach significantly reduces the dark current and enhances sensitivity, achieving a low detection limit of 14.7 nGyair/s. Additionally, it improves signal stability, consistency, and response speed of the detector. These findings suggest that PFH is a promising additive for advancing the performance and practical application of polycrystalline metal halide perovskite-based X-ray detectors.

Prognostic Value of Murray Law-Based QFR (µQFR)-Guided Virtual PCI in Patients With Physiological Ischemia.

BACKGROUND: Quantitative flow ratio (QFR)-based virtual percutaneous coronary intervention (PCI) is associated with improved post-PCI physiological results. Murray law-based QFR (µQFR) is a new method for physiological assessment that has higher feasibility and efficiency. The purpose of this study was to investigate the performance of µQFR-guided virtual PCI in improving post-PCI outcomes. METHODS: The QUITE RIGHT study (Quantitative Flow Ratio Virtual Stenting and Angiography Guided Percutaneous Coronary Intervention) is a prospective, multicenter, blinded, randomized, controlled superiority study. Eligible patients were randomized 1:1 to either the µQFR-guided virtual PCI group or the angiography-guided PCI group. The primary end point was the proportion of the target vessels with a post-PCI µQFR ≥0.90, accepted as an optimal post-PCI physiological outcome. RESULTS: A total of 622 patients with 666 vessels were enrolled. The optimal physiological outcome was reached more often in the µQFR-guided virtual PCI group (absolute difference, 9.1% [95% CI, 4.53-13.76]; P<0.001). The µQFR-guided virtual PCI group had a better QFR value, a lower contrast agent dose and x-ray dose, and a more appropriate stent length than the angiography-guided group. CONCLUSIONS: The QUITE RIGHT study showed that the µQFR-guided virtual PCI strategy is superior to angiography-guided PCI in terms of physiological outcomes. The µQFR-guided virtual PCI strategy is associated with lower contrast and x-ray doses and a more appropriate stent length. REGISTRATION: URL: https://www.chictr.org.cn/; Unique identifier: ChiCTR2100045452.

Deep learning in Cobb angle automated measurement on X-rays: a systematic review and meta-analysis.

PURPOSE: This study aims to provide an overview of different deep learning algorithms (DLAs), identify the limitations, and summarize potential solutions to improve the performance of DLAs. METHODS: We reviewed eligible studies on DLAs for automated Cobb angle estimation on X-rays and conducted a meta-analysis. A systematic literature search was conducted in six databases up until September 2023. Our meta-analysis included an evaluation of reported circular mean absolute error (CMAE) from the studies, as well as a subgroup analysis of implementation strategies. Risk of bias was assessed using the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). This study was registered in PROSPERO prior to initiation (CRD42023403057). RESULTS: We identified 120 articles from our systematic search (n = 3022), eventually including 50 studies in the systematic review and 17 studies in the meta-analysis. The overall estimate for CMAE was 2.99 (95% CI 2.61-3.38), with high heterogeneity (94%, p < 0.01). Segmentation-based methods showed greater accuracy (p < 0.01), with a CMAE of 2.40 (95% CI 1.85-2.95), compared to landmark-based methods, which had a CMAE of 3.31 (95% CI 2.89-3.72). CONCLUSIONS: According to our limited meta-analysis results, DLAs have shown relatively high accuracy for automated Cobb angle measurement. In terms of CMAE, segmentation-based methods may perform better than landmark-based methods. We also summarized potential ways to improve model design in future studies. It is important to follow quality guidelines when reporting on DLAs.

Demonstration of full polarization control of soft X-ray pulses with Apple X undulators at SwissFEL using recoil ion momentum spectroscopy.

The ability to freely control the polarization of X-rays enables measurement techniques relying on circular or linear dichroism, which have become indispensable tools for characterizing the properties of chiral molecules or magnetic structures. Therefore, the demand for polarization control in X-ray free-electron lasers is increasing to enable polarization-sensitive dynamical studies on ultrafast time scales. The soft X-ray branch Athos of SwissFEL was designed with the aim of providing freely adjustable and arbitrary polarization by building its undulator solely from modules of the novel Apple X type. In this paper, the magnetic model of the linear inclined and circular Apple X polarization schemes are studied. The polarization is characterized by measuring the angular electron emission distributions of helium for various polarizations using cold target recoil ion momentum spectroscopy. The generation of fully linear polarized light of arbitrary angle, as well as elliptical polarizations of varying degree, are demonstrated.

Scatter radiation levels in X-ray rooms during chest radiography.

This research focused on the determination of scatter radiation levels in x-ray rooms during chest radiography. 108 patients were examined. Four x-ray machines (A, B, C, and D) were used during the research from three centers. Three positions were considered in this study; position Q just beside the (Bucky stand), position R, which is 150 cm from the left of the Bucky stand towards the door and position T, 200 cm from the Bucky stand to the radiographer's protective screen respectively. Two machines (A and B) from center 1 and one machine from center 2 (C) and one machine from center 3 (D). The body mass index (BMI) of the participants ranged from 20 to 25 kgm-2 with mean value of 23.97 kgm-2. The background radiation level was read using Radalert 100 m before any exposure, and the mean background level was 0.298 mR/h. The mean of the scatter radiation doses obtained from positions Q with respect to the four machines A, B, C, and D, were 0.109, 0.201, 0.204, 0.200 mR/h (9.166, 16.903, 17.156, 16.819 mSv/yr) and their standard deviations were ±0.052, ±0.053, ±0.064, and ±0.081 respectively. The results were comparable with previous studies. The study recommends staff education and training in determination of radiation levels for enhanced work safety.

Clinical and radiological response of Maffucci related enchondromas to mutant IDH1 inhibitor Ivosidenib.

Ollier Disease (OD) and Maffucci syndrome (MS) is a rare bone disorder that affects the growth and development of the bones, with an estimated prevalence of 1 in 100,000 people. It is associated with somatic mosaicism of isocitrate dehydrogenase-1 (IDH1) or 2 (IDH2) pathogenic variants. Ivosidenib is indicated for the treatment of acute myeloid leukemia and locally advanced or metastatic cholangiocarcinoma and is currently investigated in low-grade glioma with a susceptible isocitrate dehydrogenase-1 (IDH1) pathogenic variant, but its effects in patients with OD or MS are unknown. We here report the first case of a patient with MS who was treated with Ivosidenib for recurrent IDH-1 mutated glioma. Besides the stabilization of the tumor size, the patient observed significant improvement in his enchondromas that became stiffer, with reduced pain, and significant modification of the mineralization of the enchondromas observed on X-rays. This first case report provides hope for the medical management of patients suffering because of OD or MS. Future clinical research is urgently needed to evaluate long-term benefit risk profile of IDH inhibitors in these rare diseases.

Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.

BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combining chest X-ray (CXR) and electronic health record (EHR) data to screen patients with abnormal N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in emergency departments. METHODS: Using the open-source dataset MIMIC-IV and MIMICCXR, the study population consisted of 1,432 patients and 1,833 pairs of CXRs and EHRs. We processed the CXRs, extracted relevant features through lung-heart masks, and combined these with the vital signs at triage to predict corresponding NT-proBNP levels. RESULTS: The proposed method achieved a 0.89 area under the receiver operating characteristic curve by fusing predictions from single-modality models of heart size ratio, radiomic features, CXR, and the region of interest in the CXR. The model can accurately predict dyspneic patients with abnormal NT-proBNP concentrations, allowing physicians to reduce the risks associated with inappropriate treatment. CONCLUSION: The study provided new image features related to AHF and offered insights into future research directions. Overall, these models have great potential to improve patient outcomes and reduce risks in emergency departments.

Design, Construction, and Test of Compact, Distributed-Charge, X-Band Accelerator Systems that Enable Image-Guided, VHEE FLASH Radiotherapy.

The design and optimization of laser-Compton x-ray systems based on compact distributed charge accelerator structures can enable micron-scale imaging of disease and the concomitant production of beams of Very High Energy Electrons (VHEEs) capable of producing FLASH-relevant dose rates. The physics of laser-Compton x-ray scattering ensures that the scattered x-rays follow exactly the trajectory of the incident electrons, thus providing a route to image-guided, VHEE FLASH radiotherapy. The keys to a compact architecture capable of producing both laser-Compton x-rays and VHEEs are the use of X-band RF accelerator structures which have been demonstrated to operate with over 100 MeV/m acceleration gradients. The operation of these structures in a distributed charge mode in which each radiofrequency (RF) cycle of the drive RF pulse is filled with a low-charge, high-brightness electron bunch is enabled by the illumination of a high-brightness photogun with a train of UV laser pulses synchronized to the frequency of the underlying accelerator system. The UV pulse trains are created by a patented pulse synthesis approach which utilizes the RF clock of the accelerator to phase and amplitude modulate a narrow band continuous wave (CW) seed laser. In this way it is possible to produce up to 10 µA of average beam current from the accelerator. Such high current from a compact accelerator enables production of sufficient x-rays via laser-Compton scattering for clinical imaging and does so from a machine of "clinical" footprint. At the same time, the production of 1000 or greater individual micro-bunches per RF pulse enables > 10 nC of charge to be produced in a macrobunch of < 100 ns. The design, construction, and test of the 100-MeV class prototype system in Irvine, CA is also presented.

Evaluation of the usefulness of non-weight-bearing tunnel view using X-ray in the short term after medial meniscus posterior root tear onset: a retrospective study.

BACKGROUND: This study aimed to examine whether the non-weight-bearing tunnel view X-ray is effective for short-term evaluation of medial meniscus posterior root tear (MMPRT) by assessing the X-ray characteristics at the initial and follow-up visits. METHODS: This was a retrospective longitudinal study of 26 enrolled knees diagnosed with MMPRT on magnetic resonance imaging. The distance between the medial tibial eminence and medial femoral condyle (MTE-MFC distance) and medial tibiofemoral joint (MTFJ) width were measured by obtaining non-weight-bearing tunnel view and frontal view X-ray radiographs. The initial and follow-up values at a median interval of 17 days were compared. Additionally, the correlations between the MTE-MFC distance increase rate and body mass index (BMI), age, femorotibial angle (FTA), and posterior tibial slope (PTS) were evaluated using linear regression analysis. RESULTS: The tunnel view images of the initial and follow-up X-rays showed a significant increase in the MTE-MFC distance and a significant decrease in the MTFJ width. Furthermore, a moderate correlation was observed between the change in the MTE-MFC distance and the time interval between X-rays. However, no substantial correlation was observed for the change in the MTFJ width over time. Moreover, no significant correlation was observed between the change in the MTE-MFC distance in the non-weight-bearing tunnel view and BMI, age, FTA, and PTS. CONCLUSIONS: The non-weight-bearing tunnel view is highly beneficial for evaluating MMPRT progression in the short term.

Ectopically expressed rhodopsin is not sensitive to X-rays.

Visual perception of X-radiation is a well-documented, but poorly understood phenomenon. Scotopic rod cells and rhodopsin have been implicated in visual responses to X-rays, however, some evidence suggests that X-rays excite the retina via a different mechanism than visible light. While rhodopsin's role in X-ray perception is unclear, the possibility that it could function as an X-ray receptor has led to speculation that it could act as a transgenically expressed X-ray receptor. If so, it could be used to transduce transcranial X-ray signals and control the activity of genetically targeted populations of neurons in a less invasive version of optogenetics, X-genetics. Here we investigate whether human rhodopsin (hRho) is capable of transducing X-ray signals when expressed outside of the retinal environment. We use a live-cell cAMP GloSensor luminescence assay to measure cAMP decreases in hRho-expressing HEK293 cells in response to visible light and X-ray stimulation. We show that cAMP GloSensor luminescence decreases are not observed in hRho-expressing HEK293 cells in response to X-ray stimulation, despite the presence of robust responses to visible light. Additionally, irradiation had no significant effect on cAMP GloSensor responses to subsequent visible light stimulation. These results suggest that ectopically expressed rhodopsin does not function as an X-ray receptor and is not capable of transducing transcranial X-ray signals into neural activity for X-ray mediated, genetically targeted neuromodulation.

Quality improvement project aiming to reduce inappropriate use of abdominal x-rays in the ED.

BACKGROUND: There is compelling evidence that AXRs have limited clinical value in the acute setting. Despite this, they are frequently used in many EDs. This quality improvement project (QIP) aimed to reduce unnecessary AXR use in a single-centre ED. METHOD: All consecutive AXRs conducted on patients aged 16 years and above in a District General Hospital ED in England between 2 August 2021 and 5 June 2022 were included. This period of time was divided into a pre-intervention and intervention period, during which iterative plan-do-study-act cycles were undertaken to implement a wide range of educational and system level interventions. RESULTS: 501 AXRs were performed during the QIP. The average number of AXRs per fortnight fell from 27.5 during the preintervention period to 17.6 during the intervention period and met criteria for special cause variation. No special cause variation in CT usage was observed, with an average number of 70.7 and 74 CT abdomen-pelvis scans during the preintervention and intervention periods, respectively. 119 (23.8%) AXRs showed acute and clinically significant findings, and of this group 118/119 (99.2%) underwent further imaging. In contrast, 382 (76.2%) AXRs had no acute or clinically significant findings, and of this group 344/382 (90.1%) proceeded to further imaging. CONCLUSION: In this single-centre QIP, coordinated multidisciplinary interventions were effective in reducing unnecessary AXR usage without resulting in excess CTs. The methods and interventions described are easily reproducible at minimal expense and may be of interest to other departments undertaking quality improvement work in this area.

Phase-contrast visualization of human tissues using superimposed wavefront imaging of diffraction-enhanced x-rays.

BACKGROUND: Phase-contrast computed tomography (CT) using high-brilliance, synchrotron-generated x-rays enable three-dimensional (3D) visualization of microanatomical structures within biological specimens, offering exceptionally high-contrast images of soft tissues. Traditional methods for phase-contrast CT; however, necessitate a gap between the subject and the x-ray camera, compromising spatial resolution due to penumbral blurring. Our newly developed technique, Superimposed Wavefront Imaging of Diffraction-enhanced x-rays (SWIDeX), leverages a Laue-case Si angle analyzer affixed to a scintillator to convert x-rays to visible light, capturing second-order differential phase contrast images and effectively eliminating the distance to the x-ray camera. This innovation achieves superior spatial resolution over conventional methods. PURPOSE: In this paper, the imaging principle and CT reconstruction algorithm based on SWIDeX are presented in detail and compared with conventional analyzer-based imaging (ABI). It also shows the physical setup of SWIDeX that provides the resolution preserving second-order differential images for reconstruction. We compare the spatial resolution and the sensitivity of SWIDeX to conventional ABI. METHODS: To demonstrate high-spatial resolution achievable by SWIDeX, the internal structures of four human tissues-ductal carcinoma in situ, normal stomach, normal pancreas, and intraductal papillary mucinous neoplasm of the pancreas-were visualized using an imaging system configured at the Photon Factory's BL14B beamline under the High Energy Accelerator Research Organization (KEK). Each tissue was thinly sliced after imaging, stained with hematoxylin and eosin (H&E) for conventional microscope-based pathology. RESULTS: A comparison of SWIDeX-CT and pathological images visually demonstrates the effectiveness of SWIDeX-CT for biological tissue imaging. SWIDeX could generate clearer 3D images than existing analyzer-based phase-contrast methods and accurately delineate tissue structures, as validated against histopathological images. CONCLUSIONS: SWIDeX can visualize important 3D structures in biological soft tissue with high spatial resolution and can be an important tool for providing information between the disparate scales of clinical and pathological imaging.

Classification of Pneumonia via a Hybrid ZFNet-Quantum Neural Network Using a Chest X-ray Dataset.

INTRODUCTION: Deep neural networks (DNNs) have made significant contributions to diagnosing pneumonia from chest X-ray imaging. However, certain aspects of diagnosis and planning can be further enhanced through the implementation of a quantum deep neural network (QDNN). Therefore, we introduced a technique that integrates neural networks with quantum algorithms named the ZFNet-quantum neural network for detecting pneumonia using 5863 X-ray scans with binary cases. METHODS: The hybrid model efficiently pre-processes complex and high-dimensional data by extracting significant features from the ZFNet model. These significant features are given to the quantum circuit algorithm and further embedded into a quantum device. The parameterized quantum circuit algorithm using qubits, superposition theorem, and entanglement phenomena generates 4 features from 4098 features extracted from images via a deep transfer learning model. Moreover, to validate the outcome measures of the proposed technique, we used various PennyLane quantum devices to detect pneumonia and normal control images. By using the Adam optimizer, which exploits an adaptive learning rate that is fixed to 10-6 and six layers of a quantum circuit composed of quantum gates, the proposed model achieves an accuracy of 96.5%, corresponding to 25 epochs. RESULTS: The integrated ZFNet-quantum learning network outperforms the deep transfer learning network in terms of testing accuracy, as the accuracy gained by the convolutional neural network (CNN) is 94%. Therefore, we use a hybrid classical-quantum model to detect pneumonia in which a variational quantum algorithm enhances the outcomes of a ZFNet transfer learning method. CONCLUSION: This approach is an efficient and automated method for detecting pneumonia and could significantly enhance outcome measures related to the speed and accuracy of the network in the clinical and healthcare sectors.