Loss of myocardial Hey2/Hrt2 function disrupts rightward shift of atrioventricular cushion tissue and causes tricuspid atresia.

BACKGROUND: Endocardial cushion tissue is primordia of the valves and septa of the adult heart, and its malformation causes various congenital heart diseases (CHDs). Tricuspid atresia (TA) is defined as congenital absence or agenesis of the tricuspid valve caused by endocardial cushion defects. However, little is known about what type of endocardial cushion defect causes TA. RESULTS: Using three-dimensional volume rendering image analysis, we demonstrated morphological changes of endocardial cushion tissue in developing Hey2/Hrt2 KO mouse embryos that showed malformation of the tricuspid valve, which resembled human TA at neonatal period. In control embryos, atrioventricular (AV) endocardial cushion tissues showed rightward shift to form a tricuspid valve. However, the rightward shift of endocardial cushion tissue was disrupted in Hey2/Hrt2 KO embryos, leading to the misalignment of AV cushions. We also found that muscular tissue filled up the space between the right atrium and ventricle, resulting in the absence of the tricuspid valve. Moreover, analysis using tissue-specific conditional KO mice showed that HEY2/HRT2-expressing myocardium may physically regulate the AV shift. CONCLUSION: Disruption of rightward cushion movement is an initial cue of TA phenotype, and myocardial HEY2/HRT2 is necessary for the regulation of proper alignment of AV endocardial cushion tissue.

Robust, Narrow-Band Nanorods LEDs with Luminous Efficacy > 200 lm/W: Next-Generation of Efficient Solid-State Lighting.

Energy-efficient white light-emitting diodes (LEDs) are in high demand across the society. Despite the significant advancements in the modern lighting industry based on solid-state electronics and inorganic phosphor, solid-state lighting (SSL) continues to pursue improved efficiency, saturated color performance, and longer lifetime. Here in this article, robust, narrow emission band nanorods (NRs) are disclosed with tailored wavelengths, aiming to enhance the color rendering index (CRI) and luminous efficacy (LE). The fabricated lighting device consists of NRs of configuration CdSe/ZnxCd1-xS/ZnS, which can independently tune CRI R1-R9 values and maximize the luminous efficacy. For general lighting, NRs with quantum yield (QY) up to 96% and 99% are developed, resulting in ultra-efficient LEDs reaching a record high luminous efficacy of 214 lm W-1 (certified by the National Accreditation Service). Furthermore, NRs are deployed onto mid-power (0.3 W@ 50 mA) LEDs, showing significantly enhanced long-term stability (T95 = 400 h @ 50 mA). With these astonishing properties, the proposed NRs can pave the way for efficient lighting with desired optical spectrum.

Simultaneously Realizing High Efficiency and High Color Rendering Index for Hybrid White Organic Light-Emitting Diodes by Ultra-Thin Design of Delayed Fluorescence Sensitized Phosphorescent Layers.

In consideration of energy economization and light quality, concurrently attaining high external quantum efficiency (ηext ) and high color rendering index (CRI) is of high significance for the commercialization of hybrid white organic light-emitting diodes (WOLEDs) but is challenging. Herein, a blue luminescent molecule (2PCz-XT) consisting of a xanthone acceptor and two 3,6-diphenylcarbazole donors is prepared, which exhibits strong delayed fluorescence, short delayed fluorescence lifetime, and excellent electroluminescence property, and can sensitize green, orange, and red phosphorescent emitters efficiently. By employing 2PCz-XT as sensitizer and phosphorescent emitters as dopants, efficient two-color and three-color WOLED architectures with ultra-thin phosphorescent emitting layers (EMLs) are proposed and constructed. By incorporating a thin interlayer to modulate exciton recombination zone and reduce exciton loss, high-performance three-color hybrid WOLEDs are finally achieved, providing a high ηext of 26.8% and a high CRI value 83 simultaneously. Further configuration optimization realizes a long device operational lifetime. These WOLEDs with ultra-thin phosphorescent EMLs are among the state-of-the-art hybrid WOLEDs in the literature, demonstrating the success and applicability of the proposed device design for developing robust hybrid WOLEDs with superb efficiency and color quality.

Anatomical changes of Tenebrio molitor and Tribolium castaneum during complete metamorphosis.

In holometabolous insects, extensive reorganisation of tissues and cells occurs at the pupal stage. The remodelling of the external exoskeleton and internal organs that intervenes during metamorphosis has been traditionally studied in many insect species based on histological or ultrastructural methods. This study demonstrates the use of synchrotron X-ray phase-contrast micro-computed tomography as a powerful, non-destructive tool for in situ morphological observation of anatomical structures at the pupal stage in two Tenebrionid beetles, i.e. Tribolium castaneum and Tenebrio molitor, known as important pests, as well as emerging and promising models in experimental biology. Virtual sections and three-dimensional reconstructions were performed on both males and females at early, intermediate, and late pupal stage. The dataset allowed us to observe the remodelling of the gut and nervous system as well as the shaping of the female and male reproductive system at different pupal ages in both mealworm and red flour beetles. Moreover, we observed that the timing and duration pattern of organ development varied between the species analysed, likely related to the species-specific adaptations of the pre-imaginal stages to environmental conditions, which ultimately affect their life cycle. This research provides new knowledge on the morphological modifications that occur during the pupal stage of holometabolous insects and provides a baseline set of information on beetle metamorphosis that may support future research in forensics, physiology, and ecology as well as an image atlas for educational purposes.

Craniofacial phenotyping with fetal MRI: a feasibility study of 3D visualisation, segmentation, surface-rendered and physical models.

This study explores the potential of 3D Slice-to-Volume Registration (SVR) motion-corrected fetal MRI for craniofacial assessment, traditionally used only for fetal brain analysis. In addition, we present the first description of an automated pipeline based on 3D Attention UNet trained for 3D fetal MRI craniofacial segmentation, followed by surface refinement. Results of 3D printing of selected models are also presented.Qualitative analysis of multiplanar volumes, based on the SVR output and surface segmentations outputs, were assessed with computer and printed models, using standardised protocols that we developed for evaluating image quality and visibility of diagnostic craniofacial features. A test set of 25, postnatally confirmed, Trisomy 21 fetal cases (24-36 weeks gestational age), revealed that 3D reconstructed T2 SVR images provided 66-100% visibility of relevant craniofacial and head structures in the SVR output, and 20-100% and 60-90% anatomical visibility was seen for the baseline and refined 3D computer surface model outputs respectively. Furthermore, 12 of 25 cases, 48%, of refined surface models demonstrated good or excellent overall quality with a further 9 cases, 36%, demonstrating moderate quality to include facial, scalp and external ears. Additional 3D printing of 12 physical real-size models (20-36 weeks gestational age) revealed good/excellent overall quality in all cases and distinguishable features between healthy control cases and cases with confirmed anomalies, with only minor manual adjustments required before 3D printing.Despite varying image quality and data heterogeneity, 3D T2w SVR reconstructions and models provided sufficient resolution for the subjective characterisation of subtle craniofacial features. We also contributed a publicly accessible online 3D T2w MRI atlas of the fetal head, validated for accurate representation of normal fetal anatomy.Future research will focus on quantitative analysis, optimizing the pipeline, and exploring diagnostic, counselling, and educational applications in fetal craniofacial assessment.

Intense green light emission in Sr2 ZnGe2 O7 :Mn2+ phosphors by the design of high symmetry melilite structure.

A green phosphor Sr2 ZnGe2 O7 :Mn2+ with a melilite structure was prepared using a high-temperature solid-state reaction. When the 535 nm emission was monitored, the excitation spectrum of the Sr2 ZnGe2 O7 :Mn2+ was found to contain two excitation bands in the ultraviolet (UV) region. When excited by UV light, the sample shows bright green emission at 535 nm, which corresponds to the distinctive transition of Mn2+ (4 T1 →6 A1 ). Moreover, the quantum efficiency of Sr2 ZnGe2 O7 :Mn2+ could reach 67.6%. Finally, a high-performance white-light-emitting diode (WLED) with a low correlated colour temperature of 4632 K and a high colour rendering index (CRI) of 92.3 were packaged by coating commercial blue and red phosphors with an optimized Sr2 ZnGe2 O7 :Mn2+ sample on a 310 nm UV chip. This indicated that Sr2 ZnGe2 O7 :Mn2+ has the potential application as a green component in the WLED lighting field.

Virtual reality modelling in a child after multiple interventions for hypoplastic aortic arch and coarctation.

We present the benefits of advanced multimodality imaging and virtual reality modelling in the diagnosis and treatment planning of a child with aneurysms after numerous interventions for treatment of a hypoplastic aortic arch and coarctation.

Enhancing View Synthesis with Depth-Guided Neural Radiance Fields and Improved Depth Completion.

Neural radiance fields (NeRFs) leverage a neural representation to encode scenes, obtaining photorealistic rendering of novel views. However, NeRF has notable limitations. A significant drawback is that it does not capture surface geometry and only renders the object surface colors. Furthermore, the training of NeRF is exceedingly time-consuming. We propose Depth-NeRF as a solution to these issues. Specifically, our approach employs a fast depth completion algorithm to denoise and complete the depth maps generated by RGB-D cameras. These improved depth maps guide the sampling points of NeRF to be distributed closer to the scene's surface, benefiting from dense depth information. Furthermore, we have optimized the network structure of NeRF and integrated depth information to constrain the optimization process, ensuring that the termination distribution of the ray is consistent with the scene's geometry. Compared to NeRF, our method accelerates the training speed by 18%, and the rendered images achieve a higher PSNR than those obtained by mainstream methods. Additionally, there is a significant reduction in RMSE between the rendered scene depth and the ground truth depth, which indicates that our method can better capture the geometric information of the scene. With these improvements, we can train the NeRF model more efficiently and achieve more accurate rendering results.

Expanded experience with cardiovascular black blood cinematic rendering.

Black blood cinematic rendering (BBCR) is a newly described preset for cinematic rendering, which creates photorealistic displays from volumetric data sets with the contrast-enhanced blood pool displayed as dark and transparent. That set of features potentially provides for enhanced visualization of endomyocardial and intraluminal pathology, as well as cardiac devices. The similarity of the images to black-blood magnetic resonance imaging (MRI) may allow for expansion of the evaluation of certain types of pathology into patient populations unable to undergo MRI. In the emergency setting, the rapid acquisition time and reasonable post-processing time make this technique clinically feasible. In this expanded experience, we demonstrate an expanded clinical experience with the BBCR technique, highlighting the applications for intraluminal cardiovascular evaluation, especially focused on current and potential emergency radiology applications.

The role of 3D cinematic rendering in the evaluation of upper extremity trauma.

Traumatic upper extremity injuries are a common cause of emergency department visits, comprising between 10-30% of traumatic injury visits. Timely and accurate evaluation is important to prevent severe complications such as permanent deformities, ischemia, or even death. Computed tomography (CT) and CT angiography (CTA) are the favored non-invasive imaging techniques for assessing upper extremity trauma, playing a crucial role in both the treatment planning and decision-making processes for such injuries. In CT postprocessing, a novel 3D rendering method, cinematic rendering (CR), employs sophisticated lighting models that simulate the interaction of multiple photons with the volumetric dataset. This technique produces images with realistic shadows and improved surface detail, surpassing the capabilities of volume rendering (VR) or maximal intensity projection (MIP). Considering the benefits of CR, we demonstrate its use and ability to achieve photorealistic anatomic visualization in a series of 11 cases where patients presented with traumatic upper extremity injuries, including bone, vascular, and skin/soft tissue injuries, adding to diagnostic confidence and intervention planning.

Flank pain, hypertension, and hematuria: CT and 3D cinematic rendering in the evaluation of renal artery emergencies-a pictorial essay.

Non-traumatic acute renal artery emergencies encompass a spectrum of etiologies, including renal artery stenosis, arteriovenous malformations, aneurysms and pseudoaneurysms, dissections, thrombosis, and vasculitis. Prompt and accurate diagnosis in the emergency setting is crucial due to the potential for significant morbidity and mortality. Computed tomography (CT) and CT angiography (CTA) are the mainstay imaging modalities, offering rapid acquisition and high diagnostic accuracy. The integration of 3D postprocessing techniques, such as 3D cinematic rendering (CR), improves the diagnostic workflow by providing photorealistic and anatomically accurate visualizations. This pictorial essay illustrates the diagnostic utility of CT and CTA, supplemented by 3D CR, through a series of 10 cases of non-traumatic renal artery emergencies. The added value of 3D CR in improving diagnostic confidence, surgical planning, and understanding of complex vascular anatomy is emphasized.

Enhancing Deep Learning-Based Segmentation Accuracy through Intensity Rendering and 3D Point Interpolation Techniques to Mitigate Sensor Variability.

In the context of LiDAR sensor-based autonomous vehicles, segmentation networks play a crucial role in accurately identifying and classifying objects. However, discrepancies between the types of LiDAR sensors used for training the network and those deployed in real-world driving environments can lead to performance degradation due to differences in the input tensor attributes, such as x, y, and z coordinates, and intensity. To address this issue, we propose novel intensity rendering and data interpolation techniques. Our study evaluates the effectiveness of these methods by applying them to object tracking in real-world scenarios. The proposed solutions aim to harmonize the differences between sensor data, thereby enhancing the performance and reliability of deep learning networks for autonomous vehicle perception systems. Additionally, our algorithms prevent performance degradation, even when different types of sensors are used for the training data and real-world applications. This approach allows for the use of publicly available open datasets without the need to spend extensive time on dataset construction and annotation using the actual sensors deployed, thus significantly saving time and resources. When applying the proposed methods, we observed an approximate 20% improvement in mIoU performance compared to scenarios without these enhancements.

3D Cinematic rendering for evaluating femoral pseudoaneurysms in injection drug users.

The inguinal region, specifically the femoral vasculature, is a commonly used site of injection for intravenous drug users (IVDU). Repeated puncture of the vessel wall results in breakdown and subsequent arterial pseudoaneurysm- dilatations or outpouching of blood vessels, which, if left untreated, can result in fatal complications such as rupture with hemorrhage, sepsis, or even limb loss. The current modalities for arterial pseudoaneurysms include Doppler ultrasound and computed tomography (CT) angiography, both of which play important roles in management and surgical planning. However, 3D cinematic rendering (CR), a novel CT post-processing technique, offers timely, highly detailed photorealistic images that more clearly display the relation of anatomical structures, allowing for greater diagnostic confidence and precise surgical planning, particularly useful in the emergency setting. In this pictorial review, we demonstrate role of 3D CR in diagnosis and management of femoral pseudoaneurysms in IVDU through 9 illustrative cases.

Res-NeuS: Deep Residuals and Neural Implicit Surface Learning for Multi-View Reconstruction.

Surface reconstruction using neural networks has proven effective in reconstructing dense 3D surfaces through image-based neural rendering. Nevertheless, current methods are challenging when dealing with the intricate details of large-scale scenes. The high-fidelity reconstruction performance of neural rendering is constrained by the view sparsity and structural complexity of such scenes. In this paper, we present Res-NeuS, a method combining ResNet-50 and neural surface rendering for dense 3D reconstruction. Specifically, we present appearance embeddings: ResNet-50 is used to extract the appearance depth features of an image to further capture more scene details. We interpolate points near the surface and optimize their weights for the accurate localization of 3D surfaces. We introduce photometric consistency and geometric constraints to optimize 3D surfaces and eliminate geometric ambiguity existing in current methods. Finally, we design a 3D geometry automatic sampling to filter out uninteresting areas and reconstruct complex surface details in a coarse-to-fine manner. Comprehensive experiments demonstrate Res-NeuS's superior capability in the reconstruction of 3D surfaces in complex, large-scale scenes, and the harmful distance of the reconstructed 3D model is 0.4 times that of general neural rendering 3D reconstruction methods and 0.6 times that of traditional 3D reconstruction methods.

Synthetic Training Data in AI-Driven Quality Inspection: The Significance of Camera, Lighting, and Noise Parameters.

Industrial-quality inspections, particularly those leveraging AI, require significant amounts of training data. In fields like injection molding, producing a multitude of defective parts for such data poses environmental and financial challenges. Synthetic training data emerge as a potential solution to address these concerns. Although the creation of realistic synthetic 2D images from 3D models of injection-molded parts involves numerous rendering parameters, the current literature on the generation and application of synthetic data in industrial-quality inspection scarcely addresses the impact of these parameters on AI efficacy. In this study, we delve into some of these key parameters, such as camera position, lighting, and computational noise, to gauge their effect on AI performance. By utilizing Blender software, we procedurally introduced the "flash" defect on a 3D model sourced from a CAD file of an injection-molded part. Subsequently, with Blender's Cycles rendering engine, we produced datasets for each parameter variation. These datasets were then used to train a pre-trained EfficientNet-V2 for the binary classification of the "flash" defect. Our results indicate that while noise is less critical, using a range of noise levels in training can benefit model adaptability and efficiency. Variability in camera positioning and lighting conditions was found to be more significant, enhancing model performance even when real-world conditions mirror the controlled synthetic environment. These findings suggest that incorporating diverse lighting and camera dynamics is beneficial for AI applications, regardless of the consistency in real-world operational settings.

Cinematic rendering of non-traumatic thoracic aorta emergencies: a new look at an old problem.

Non-traumatic thoracic aorta emergencies are acute conditions associated with substantial morbidity and mortality. In the emergency setting, timely detection of aortic injury through radiological imaging is crucial for prompt treatment planning and favorable patient outcomes. 3D cinematic rendering (CR), a novel rendering algorithm for computed tomography (CT) image processing, allows for life-like visualization of spatial details and contours of highly complex anatomic structures such as the thoracic aorta and its vessels, generating a photorealistic view that not just adds to diagnostic confidence, but is especially useful for non-radiologists, including surgeons and emergency medicine physicians. In this pictorial review, we demonstrate the utility of CR in the setting of non-traumatic thoracic aorta emergencies through 10 cases that were processed at a standalone 3D CR station at the time of presentation, including its role in diagnosis and management.

Recent Advances in Preparing Transparent Phosphor Ceramics for High-Index Color Rendering and High-Power Lighting.

In recent years, high-power white light-emitting diode (wLED)/laser diode (wLD) lighting sources based on transparent phosphor ceramic (TPC) materials have attracted increasing application interest in automotive headlights, projection displays, and space navigation lighting due to their superior brightness, lighting distance, compactness, lifespan, and environmental resistance compared with the widely used phosphor-converted wLEDs. However, preparing TPC-converted wLEDs/wLDs with high color rendering index (CRI) remains a huge challenge, which limits their widespread application. In this review, we summarize the recently adopted strategies for constructing TPCs to develop high-power wLEDs/wLDs with high CRI values (>75). The construction protocols were categorized into four groups: host regulation, red-emitter doping, host regulation/red-emitter doping combination, and composite structure design. A comprehensive discussion was conducted on the design principles, photoluminescent properties, and device performances for each strategy. The challenges and future trends of high-power and high-CRI wLEDs/wLDs based on TPCs are also discussed toward the end of this review.

CT and MRI of Gastrointestinal Stromal Tumors: New Trends and Perspectives.

Gastrointestinal stromal tumors (GISTs) are defined as mesenchymal tumors of the gastrointestinal tract that express positivity for CD117, which is a c-KIT proto-oncogene antigen. Expression of the c-KIT protein, a tyrosine kinase growth factor receptor, allows the distinction between GISTs and other mesenchymal tumors such as leiomyoma, leiomyosarcoma, schwannoma and neurofibroma. GISTs can develop anywhere in the gastrointestinal tract, as well as in the mesentery and omentum. Over the years, the management of GISTs has improved due to a better knowledge of their behaviors and risk or recurrence, the identification of specific mutations and the use of targeted therapies. This has resulted in a better prognosis for patients with GISTs. In parallel, imaging of GISTs has been revolutionized by tremendous progress in the field of detection, characterization, survival prediction and monitoring during therapy. Recently, a particular attention has been given to radiomics for the characterization of GISTs using analysis of quantitative imaging features. In addition, radiomics has currently many applications that are developed in conjunction with artificial intelligence with the aim of better characterizing GISTs and providing a more precise assessment of tumor burden. This article sums up recent advances in computed tomography and magnetic resonance imaging of GISTs in the field of image/data acquisition, tumor detection, tumor characterization, treatment response evaluation, and preoperative planning.

Cinematic Rendering of Pancreatic Neuroendocrine Tumours: Opportunities for Clinical Implementation: Part 2: Preoperative Planning and Evaluation of Metastatic Disease.

Pancreatic neuroendocrine tumours (PNETs) are a rare subset of pancreatic tumours that have historically comprised up to 3% of all clinically detected pancreatic tumours. In recent decades, however, advancements in imaging have led to an increased incidental detection rate of PNETs and imaging has played an increasingly central role in the initial diagnostics and surgical planning of these tumours. Cinematic rendering (CR) is a 3D post-processing technique that generates highly photorealistic images through more realistically modelling the path of photons through the imaged volume. This allows for more comprehensive visualization, description, and interpretation of anatomical structures. In this 2-part review article, we present the first description of the various CR appearances of PNETs in the reported literature while providing commentary on the unique clinical opportunities afforded by the adjunctive utilization of CR in the workup of these rare tumours. This second instalment focuses on the applications of CR in optimizing preoperative planning of PNETs.

Cinematic Rendering of Pancreatic Neuroendocrine Tumours: Opportunities for Clinical Implementation: Part 1: Tumour Detection and Characterization.

Pancreatic neuroendocrine tumours (PNETs) are a rare subset of pancreatic tumours that have historically comprised up to 3% of all clinically detected pancreatic tumours. In recent decades, however, advancements in imaging have led to an increased incidental detection rate of PNETs and imaging has played an increasingly central role in the initial diagnostics and surgical planning of these tumours. Cinematic rendering (CR) is a 3D post-processing technique that generates highly photorealistic images through more realistically modelling the path of photons through the imaged volume. This allows for more comprehensive visualization, description, and interpretation of anatomical structures. In this 2-part review article, we present the first description of the various CR appearances of PNETs in the reported literature while providing commentary on the unique clinical opportunities afforded by the adjunctive utilization of CR in the workup of these rare tumours. The first of these 2 instalments highlights the utility of CR in optimizing PNET detection and characterization.