3D Acquisition Research Articles

A Versatile MR Elastography Research Tool with a Modified Motion Signal-to-noise Ratio Approach.

This study aimed to facilitate research progress in MR elastography (MRE) by providing a versatile and convenient application for MRE reconstruction, namely the MRE research tool (MRE-rTool). It can be used for a series of MRE image analyses, including phase unwrapping, arbitrary bandpass and directional filtering, noise assessment of the wave propagation image (motion SNR), and reconstruction of the elastogram in both 2D and 3D MRE acquisitions. To reinforce the versatility of MRE-rTool, the conventional method of motion SNR was modified into a new method that reflects the effects of image filtering. MRE tests of the phantom and liver were performed using different estimation algorithms for stiffness value (algebraic inversion of the differential equation [AIDE], local frequency estimation [LFE] in MRE-rTool, and multimodel direct inversion [MMDI] in clinical reconstruction) and acquiring dimensions (2D and 3D acquisitions). This study also tested the accuracy of masking low SNR regions using modified and conventional motion SNR under various mechanical vibration powers. The stiffness values estimated using AIDE/LFE in MRE-rTool were comparable to that of MMDI (phantom, 3.71 ± 0.74, 3.60 ± 0.32, and 3.60 ± 0.54 kPa in AIDE, LFE, and MMDI; liver, 2.26 ± 0.31, 2.74 ± 0.16, and 2.21 ± 0.26 kPa in AIDE, LFE, and MMDI). The stiffness value in 3D acquisition was independent of the direction of the motion-encoding gradient and was more accurate than that of 2D acquisition. The masking of low SNR regions using the modified motion SNR worked better than that in the conventional motion SNR for each vibration power, especially when using a directional filter. The performance of MRE-rTool on test data reached the level required in clinical MRE studies. MRE-rTool has the potential to facilitate MRE research, contribute to the future development of MRE, and has been freely released online.

Three-Dimensional Leaf Edge Reconstruction Combining Two- and Three-Dimensional Approaches

Leaves, crucial for plant physiology, exhibit various morphological traits that meet diverse functional needs. Traditional leaf morphology quantification, largely 2-dimensional (2D), has not fully captured the 3-dimensional (3D) aspects of leaf function. Despite improvements in 3D data acquisition, accurately depicting leaf morphologies, particularly at the edges, is difficult. This study proposes a method for 3D leaf edge reconstruction, combining 2D image segmentation with curve-based 3D reconstruction. Utilizing deep-learning-based instance segmentation for 2D edge detection, structure from motion for estimation of camera positions and orientations, leaf correspondence identification for matching leaves among images, and curve-based 3D reconstruction for estimating 3D curve fragments, the method assembles 3D curve fragments into a leaf edge model through B-spline curve fitting. The method's performances were evaluated on both virtual and actual leaves, and the results indicated that small leaves and high camera noise pose greater challenges to reconstruction. We developed guidelines for setting a reliability threshold for curve fragments, considering factors occlusion, leaf size, the number of images, and camera error; the number of images had a lesser impact on this threshold compared to others. The method was effective for lobed leaves and leaves with fewer than 4 holes. However, challenges still existed when dealing with morphologies exhibiting highly local variations, such as serrations. This nondestructive approach to 3D leaf edge reconstruction marks an advancement in the quantitative analysis of plant morphology. It is a promising way to capture whole-plant architecture by combining 2D and 3D phenotyping approaches adapted to the target anatomical structures.

Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging.

Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time reduction is a natural requirement in neuroimaging due to detailed structures requiring high resolution imaging and often volumetric (3D) acquisitions, and numerous studies have recently attempted to harness deep learning (DL) technology in enabling scan time reduction and image quality improvement. Various DL-based image reconstruction products allow for additional scan time reduction on top of existing accelerated acquisition methods without compromising the image quality.

Design and realization of the digital protection platform of traditional intangible cultural heritage based on virtual reality technology

Abstract Using new design concepts and design methods to effectively strengthen the digital protection of traditional non-heritage culture is an important measure to promote the development of conventional non-heritage culture. In this paper, the digital protection needs of traditional non-heritage culture are sorted out, including the purpose of digital protection of non-heritage, the design level, and the feasibility of the application of virtual reality technology in the digital protection of non-heritage culture. A platform for the digital protection of non-heritage culture is constructed with the model of PHP technology + MySQL database + Apache server combined with virtual reality technology, and the immersion experience and display dissemination model is designed in this platform. In order to obtain accurate digital images of traditional non-heritage culture, this paper utilizes 3D laser point cloud acquisition technology to reconstruct non-heritage culture in 3D. It combines the ICP algorithm to enhance the point cloud alignment accuracy of digital images of non-heritage culture. Evaluation of the effectiveness of the traditional non-heritage culture digital protection platform proposed in this paper was done through performance tests and application practice. The results show that the number of concurrent users of the platform in this paper can reach the maximum throughput of about 94,300 per second in 2000, the point cloud alignment accuracy of the ICP algorithm has an error of only 0.304mm, and the SUS usability evaluation of the platform scores 80.4 points. The construction of a digital protection platform for non-heritage culture using virtual reality technology can provide users with immersive experience scenes.

Dual Kernel Support Vector-based Crossover Red Fox Algorithm: Advancements in Assistive Technology for Hearing-impaired Individuals

Individuals with hearing impairment face several challenges, including difficulties in communication, social interactions, and accessibility to information on various auditory abilities. Innovations range from hearing aids to advanced communication devices and mobile apps. Designing solutions that prioritize user feedback ensures a more inclusive and empowering experience for people with hearing impairment. Assistive technology (AT) endeavors to enhance the daily lives of individuals, fostering greater connectivity, and also plays a crucial role in addressing these challenges. Therefore, an attention dual kernel support vector-based crossover red fox (ADKS-CRF) algorithm is developed for superior performance. This research study proposes a model combining a dual kernel support vector machine with an attention mechanism to implicitly operate in a high-dimensional feature space without computing the transformed vector features. The crossover strategy is incorporated with the red fox optimization algorithm, and the integrated formation of CRF fine-tunes the parameters of the ADKS model, removing the complexity of local optima. This work conducted experiments using raw data from an effective 3D ear acquisition system dataset. Experimental validation is conducted using various evaluation measures to assess effectiveness. The proposed hybrid approach achieves a sensitivity of 97.8%, an F1-score of 97.1%, a specificity of 96.3%, an accuracy of 98.4%, a false alarm rate of 90.8%, and a Matthews correlation coefficient of 97.3%. The comparative analysis evaluates the efficacy of the ADKS-CRF method with various baseline approaches for the development of ATs for hearing-impaired people.

MLGCN: an ultra efficient graph convolutional neural model for 3D point cloud analysis.

With the rapid advancement of 3D acquisition technologies, 3D sensors such as LiDARs, 3D scanners, and RGB-D cameras have become increasingly accessible and cost-effective. These sensors generate 3D point cloud data that require efficient algorithms for tasks such as 3D model classification and segmentation. While deep learning techniques have proven effective in these areas, existing models often rely on complex architectures, leading to high computational costs that are impractical for real-time applications like augmented reality and robotics. In this work, we propose the Multi-level Graph Convolutional Neural Network (MLGCN), an ultra-efficient model for 3D point cloud analysis. The MLGCN model utilizes shallow Graph Neural Network (GNN) blocks to extract features at various spatial locality levels, leveraging precomputed KNN graphs shared across GCN blocks. This approach significantly reduces computational overhead and memory usage, making the model well-suited for deployment on low-memory and low-CPU devices. Despite its efficiency, MLGCN achieves competitive performance in object classification and part segmentation tasks, demonstrating results comparable to state-of-the-art models while requiring up to a thousand times fewer floating-point operations and significantly less storage. The contributions of this paper include the introduction of a lightweight, multi-branch graph-based network for 3D shape analysis, the demonstration of the model's efficiency in both computation and storage, and a thorough theoretical and experimental evaluation of the model's performance. We also conduct ablation studies to assess the impact of different branches within the model, providing valuable insights into the role of specific components.

Automatic Quantification of Enlarged Perivascular Space in Patients With Traumatic Brain Injury Using Super-Resolution of T2-Weighted Images.

The perivascular space (PVS) is important to brain waste clearance and brain metabolic homeostasis. Enlarged PVS (ePVS) becomes visible on magnetic resonance imaging (MRI) and is best appreciated on T2-weighted (T2w) images. However, quantification of ePVS is challenging because standard-of-care T1-weighted (T1w) and T2w images are often obtained via two-dimensional (2D) acquisition, whereas accurate quantification of ePVS normally requires high-resolution volumetric three-dimensional (3D) T1w and T2w images. The purpose of this study was to investigate the use of a deep-learning-based super-resolution (SR) technique to improve ePVS quantification from 2D T2w images for application in patients with traumatic brain injury (TBI). We prospectively recruited 26 volunteers (age: 31 ± 12 years, 12 male/14 female) where both 2D T2w and 3D T2w images were acquired along with 3D T1w images to validate the ePVS quantification using SR T2w images. We then applied the SR method to retrospectively acquired 2D T2w images in 41 patients with chronic TBI (age: 41 ± 16 years, 32 male/9 female). ePVS volumes were automatically quantified within the whole-brain white matter and major brain lobes (temporal, parietal, frontal, occipital) in all subjects. Pittsburgh Sleep Quality Index (PSQI) scores were obtained on all patients with TBI. Compared with the silver standard (3D T2w), in the validation study, the SR T2w provided similar whole-brain white matter ePVS volume (r = 0.98, p < 0.0001), and similar age-related ePVS burden increase (r = 0.80, p < 0.0001). In the patient study, patients with TBI with poor sleep showed a higher age-related ePVS burden increase than those with good sleep. Sleep status is a significant interaction factor in the whole brain (p = 0.047) and the frontal lobe (p = 0.027). We demonstrate that images produced by SR of 2D T2w images can be automatically analyzed to produce results comparable to those obtained by 3D T2 volumes. Reliable age-related ePVS burden across the whole-brain white matter was observed in all subjects. Poor sleep, affecting the glymphatic function, may contribute to the accelerated increase of ePVS burden following TBI.

DEVELOPING COMPLETE URBAN DIGITAL TWINS IN BUSY ENVIRONMENTS: A FRAMEWORK FOR FACILITATING 3D MODEL GENERATION FROM MULTI-SOURCE POINT CLOUD DATA

Abstract. The proliferation of affordable LiDAR technology and photogrammetry sensors has revolutionized 3D data acquisition in built environments, enabling comprehensive data capture from citywide scales to interior structures. This data can be transformed into digital twins, providing valuable resources for city planners, architects, engineers, and decision-makers. However, current studies often overlook the limitations of real-world point cloud datasets derived from LiDAR systems, which are voluminous, noisy, incomplete, and lacking information, which hinders monitoring, interpretation, and automated analysis. To address these challenges, methods are required to prepare point cloud data, ensuring accurate and reliable 3D representations. This research proposes a detailed framework for point cloud data preparation in busy urban environments. It includes precise algorithms, software, and parameter guidelines, allowing for the creation of comprehensive point cloud datasets. The framework has been successfully implemented on datasets acquired in Toronto, converting point cloud data from various platforms and parameters into an integrated dataset. Results demonstrate the framework's effectiveness in producing accurate and complete point cloud datasets for applications such as classification, information extraction, 3D model generation, and smart cities' monitoring and management.

INVESTIGATION OF THE RADIOMETRIC BEHAVIOUR OF A LOW-COST AUTOMOTIVE LIDAR SENSOR

Abstract. Terrestrial LiDAR is an established method for 3D data acquisition in close-range applications. A new category of low-cost LiDAR sensors for autonomous driving has become available with similar specifications. However, these new sensors lack the guarantee of survey-grade performance. Initial experiments have broadly confirmed the specification of one such low-cost sensor but have also raised issues with the radiometric behaviour. This study investigates through practical experiments how the intensity information of the Livox-Mid40 laser scanner is influenced by time, reflectance, distance and angle of incidence. The quantitative analysis of the experiments shows an expected relationship between surface reflectance and recorded intensity. However, the result indicate that intensity can significantly influence the distance measurement at very close ranges.

SCAN-TO-BIM method and analysis of measurement accuracy on the example of a historic church

Building information modeling (BIM) data for existing buildings based on scans and point clouds acquired from terrestrial laser scanning (TLS) is the basis of the Scan-to-BIM methodology and is becoming common practice. However, work on the accuracy of the resulting model is still desired. The article discusses the possibility of developing a BIM model of a historical building, based on data obtained by terrestrial laser scanning. The subject of the study was the church in Posada Rybotycka (Poland). The mapping reliability studies included PointCab and ReCap point cloud processing, 3D modeling of the object using Revit software, and analysis of the accuracy of distance measurements made by TLS with data obtained from measurements made with traditional methods: total station and laser rangefinder. Based on the conducted research, the possibility of using the BIM with TLS data in the process of reconstructing the geometry of a historic building was evaluated. The results of the study showed that the convergence of the 3D model geometry with the actual course of the structure depends on the development methodology, i.e. the accuracy of 3D data acquisition, the registration process, the filtering procedure, or the parametric structural modeling method used.

Compressed SENSE accelerated 3D single-breath-hold late gadolinium enhancement cardiovascular magnetic resonance with isotropic resolution: clinical evaluation

AimThe purpose of this study was to investigate the clinical application of Compressed SENSE accelerated single-breath-hold LGE with 3D isotropic resolution compared to conventional LGE imaging acquired in multiple breath-holds.Material &amp;amp; MethodsThis was a retrospective, single-center study including 105 examinations of 101 patients (48.2 ± 16.8 years, 47 females). All patients underwent conventional breath-hold and 3D single-breath-hold (0.96 × 0.96 × 1.1 mm3 reconstructed voxel size, Compressed SENSE factor 6.5) LGE sequences at 1.5 T in clinical routine for the evaluation of ischemic or non-ischemic cardiomyopathies. Two radiologists independently evaluated the left ventricle (LV) for the presence of hyperenhancing lesions in each sequence, including localization and transmural extent, while assessing their scar edge sharpness (SES). Confidence of LGE assessment, image quality (IQ), and artifacts were also rated. The impact of LV ejection fraction (LVEF), heart rate, body mass index (BMI), and gender as possible confounders on IQ, artifacts, and confidence of LGE assessment was evaluated employing ordinal logistic regression analysis.ResultsUsing 3D single-breath-hold LGE readers detected more hyperenhancing lesions compared to conventional breath-hold LGE (n = 246 vs. n = 216 of 1,785 analyzed segments, 13.8% vs. 12.1%; p &amp;lt; 0.0001), pronounced at subendocardial, midmyocardial, and subepicardial localizations and for 1%–50% of transmural extent. SES was rated superior in 3D single-breath-hold LGE (4.1 ± 0.8 vs. 3.3 ± 0.8; p &amp;lt; 0.001). 3D single-breath-hold LGE yielded more artifacts (3.8 ± 1.0 vs. 4.0 ± 3.8; p = 0.002) whereas IQ (4.1 ± 1.0 vs. 4.2 ± 0.9; p = 0.122) and confidence of LGE assessment (4.3 ± 0.9 vs. 4.3 ± 0.8; p = 0.374) were comparable between both techniques. Female gender negatively influenced artifacts in 3D single-breath-hold LGE (p = 0.0028) while increased heart rate led to decreased IQ in conventional breath-hold LGE (p = 0.0029).ConclusionsIn clinical routine, Compressed SENSE accelerated 3D single-breath-hold LGE yields image quality and confidence of LGE assessment comparable to conventional breath-hold LGE while providing improved delineation of smaller LGE lesions with superior scar edge sharpness. Given the fast acquisition of 3D single-breath-hold LGE, the technique holds potential to drastically reduce the examination time of CMR.

A markless 3D human motion data acquisition method based on the binocular stereo vision and lightweight open pose algorithm

This study aimed to achieve precise 3D human motion data acquisition without the need for markers. Specifically, the proposed system utilized two affordable cameras to capture human motion from diverse angles. It developed a lightweight Open Pose algorithm to extract 2D human body joints from recorded videos. Subsequently, a stereo-matching method was applied to derive accurate 3D human body joint data. Comprehensive experiments with 10 healthy participants showcased the system's exceptional performance, demonstrating superior measurement accuracy compared to established standards like the NOKOV system (RMSE values consistently below 9°) and commonly used Microsoft Kinect devices (V2 and Azure). This innovative binocular vision system presents a new approach to motion capture, potentially offering a cost-effective and precise tool for practical applications across various scenarios (e.g., motor functional assessment, virtual avatar streaming), contributing significantly to both scientific and academic communities.

The prognostic role of left atrial strain in young patients after ST elevation myocardial infarction: a 3D echocardiographic study

Abstract Background LA volume previously demonstrated its role as significant predictor of adverse events after AMI. The prognostic value of LA strain is less studied. Left atrial strain has been used as a more accurate alternative to assessing LA performance. 3D echocardiography compared with 2D measurements better reflect the entire atrial myocardium, leading to a more accurate estimation of LA function. Purpose In this study we aimed to assess the prognostic value of LA strain parameters determined by 3D echocardiography in young patients after STEMI. Patients and methods: We enrolled 112 patients in this study - 84 young patients with a first STEMI treated by primary PCI and 28 healthy age and sex matched controls. All patients underwent standard transthoracic echocardiography. In addition to conventional echocardiographic parameters, 3D acquisitions of the left atrium were performed. 3D LA longitudinal strain parameters were determined using the automated function 4D Auto LAQ. Patients were followed up for one year after STEMI, the primary endpoint being the occurrence of MACE. Results Compared to the control group, patients with STEMI had lower values of all LA strain parameters. There were also significant differences between MACE and non-MACE groups. Patients with MACE at follow up had lower reservoir strain (15.16 ± 2.58 vs. 22.71 ± 5.25), lower conduction strain (-8.62 ± 1.77 vs. -10.97 ± 1.44) and lower pumps strain (-9.36 ± 1.51 vs. -12.73 ± 2.53), compared to those from the non-MACE group. All LA strain parameters proved to have very good predictive abilities for MACE in ROC analysis (AUC = 0.894, 95 %CI, P &amp;lt; 0.0001 for LASr 3D, AUC = 0.854, 95 %CI, P &amp;lt; 0.0001 for LASct 3D, and AUC = 0.883, 95%CI, P &amp;lt; 0.0001 for LAScd 3D). For each variable we determined a cut off value as follows: 17.5 (Sb 91.7%, Sp 86.7%) for LASr 3D, -10.5 (Sb 75% Sp 86.7%) for LASct 3D, and -9.05 (Sb 75% Sp 91.7%) for LAScd 3D. LASr 3D under 17, and LASct 3D over -10.5 determined an approximately 2-fold increase in adverse events after STEMI. Univariate COX regression analysis showed that all parameters had a significant effect on MACE, while multivariate analysis identified only reservoir and pump functions as independent predictors for adverse events. LASr 3D values showed a proportional decrease with worsening diastolic dysfunction, demonstrating significant differences between diastolic dysfunction grades. We determined LASr 3D cut-off values for discriminating between different degrees of diastolic dysfunction. Conclusion 3D LA reservoir and pump strain proved to be independent predictors for MACE at one year follow up after STEMI in young patients. Beyond its prognostic role, LASr 3D may be helpful as a complementary method to evaluate diastolic dysfunction in young STEMI patients. Further larger scale studies are needed to validate these findings.

Abstract 19141: Carotid Artery Plaque Rim Sign on Computed Tomography Angiography is Associated With Intraplaque Hemorrhage and Inflammatory Microenvironment

Introduction: The carotid artery rim sign on CTA is characterized by soft-plaque components surrounded by a rind of thin, adventitial calcification and its role in plaque instability is not established yet. Intraplaque hemorrhage (IPH) and the inflammatory microenvironment in carotid atheroma are considered features of atherosclerotic plaque vulnerability leading to cerebrovascular events. Hypothesis: The association between rim sign on CTA and carotid IPH and inflammation remains scantly investigated. In this study, we aimed to determine whether rim sign is associated with IPH on MRA and with the extent of IPH and inflammation on histology. We hypothesized that rim sign may be a radiological predictor of carotid IPH and inflammation. Methods: We retrospectively enrolled 100 consecutive patients who underwent carotid endarterectomy (CEA) and neck CTA before CEA. On CTA, the ipsilateral rim sign was defined as the presence of adventitial calcifications with internal soft-tissue plaque of ≥2 mm in maximum thickness. Of the included patients, 25 had MRA with 3D magnetization-prepared rapid acquisition with gradient echo (MPRAGE) sequence. Carotid plaque specimens were collected and stained with H&amp;E to quantify IPH (%). Histologically, we defined IPH as an area of carotid plaque with blood elements, and inflammatory microenvironment as the presence of lymphocytes and plasma cells (chronic inflammation) and foam cells. Results: The rim sign on CTA was present in 56 (56%) of patients. IPH on MRA was present in 11 (44%) patients. The rim sign was significantly associated with the presence of IPH on MRA [9 (81.8%) vs 2 (14.3%); p=0.003]. On histology, the rim sign was associated with a higher extent of IPH [5.0 % (IQR 2.0-25.0) vs 5.0% (IQR 0.0-10.0); p=0.017], with chronic inflammation [44 (78.6%) vs 12 (21.4%); p=0.003], and foam cells [51 (91.1%) vs 5 (8.9%); p&lt;0.001]. Conclusions: These findings suggest that rim sign on CTA may be proposed as a potential imaging marker of IPH as well as a histologic predictor of IPH extent and carotid plaque inflammatory microenvironment.

A survey on weakly supervised 3D point cloud semantic segmentation

AbstractWith the popularity and advancement of 3D point cloud data acquisition technologies and sensors, research into 3D point clouds has made considerable strides based on deep learning. The semantic segmentation of point clouds, a crucial step in comprehending 3D scenes, has drawn much attention. The accuracy and effectiveness of fully supervised semantic segmentation tasks have greatly improved with the increase in the number of accessible datasets. However, these achievements rely on time‐consuming and expensive full labelling. In solve of these existential issues, research on weakly supervised learning has recently exploded. These methods train neural networks to tackle 3D semantic segmentation tasks with fewer point labels. In addition to providing a thorough overview of the history and current state of the art in weakly supervised semantic segmentation of 3D point clouds, a detailed description of the most widely used data acquisition sensors, a list of publicly accessible benchmark datasets, and a look ahead to potential future development directions is provided.

Integrated methodology to link geochemical and geophysical-lab data in a geophysical investigation of a slag heap for resource quantification

The increasing need to find alternative stocks of critical raw materials drives to revisit the residues generated during the former production of mineral and metallic raw materials. Geophysical methods contribute to the sustainable characterization of metallurgical residues inferring on their composition, zonation and volume(s) estimation. Nevertheless, more quantitative approaches are needed to link geochemical or mineralogical analyses with the geophysical data. In this contribution, we describe a methodology that integrates geochemical and geophysical laboratory measurements to interpret geophysical field data solving a classification problem. The final aim is to estimate volume(s) of different types of materials to assess the potential resource recovery. We illustrate this methodology with a slag heap composed of residues from a former iron and steel factory. First, we carried out a 3D field acquisition using electrical resistivity tomography (ERT) and induced polarization (IP), based on which, a sampling survey was designed. We conducted laboratory measurements of ERT, IP, spectral induced polarization (SIP), and X-ray fluorescence analysis, based on which, 4 groups of different chemical composition were identified. Then we carried out a 3D probabilistic classification of the field data, based on 2D kernel density estimators (for each group) fitted to the inverted data collocated with the samples. The estimated volumes based on the classification model were: 4.17 × 103 m3 ± 12 %, 1.888 × 105 m3 ± 12 %, 59.4 × 103 m3 ± 19 %, and 2.30 × 104 m3 ± 21% for the groups ordered with an increasing metallic content. The uncertainty ranges were derived from comparing the volumes with and without considering the probabilities associated to the classification. We found that a representative sampling and the definition of the KDE bandwidths are defining elements in the classification and ultimately the estimation of volumes. This methodology is suitable to quantitatively interpret geophysical data in terms of the geochemical composition of the materials, integrating uncertainties both in the classification and the estimation of volumes. Furthermore, several crucial elements in the investigation of metallurgical residues could be applied in a real case study, e.g., geophysical field acquisition, sampling and lab measurements.

Extracellular vesicles from subjects with COPD modulate cancer initiating cells phenotype through HIF-1α shuttling

Chronic obstructive pulmonary disease (COPD) is a risk factor for lung cancer development. COPD induces activation of hypoxia-induced signaling, causing remodeling of surrounding microenvironmental cells also modulating the release and cargo of their extracellular vesicles (EVs). We aimed to evaluate the potential role of circulating EVs from COPD subjects in lung cancer onset. Plasma-EVs were isolated by ultracentrifugation from heavy smoker volunteers with (COPD-EVs) or without (heavy smoker-EVs, HS-EV) COPD and characterized following MISEV guidelines. Immortalized human bronchial epithelial cells (CDK4, hTERT-HBEC3-KT), genetically modified with different oncogenic alterations commonly found in lung cancer (sh-p53, KRASV12), were used to test plasma-EVs pro-tumorigenic activity in vitro. COPD-EVs mainly derived from immune and endothelial cells. COPD-EVs selectively increased the subset of CD133+CXCR4+ metastasis initiating cells (MICs) in HBEC-sh-p53-KRASV12high cells and stimulated 3D growth, migration/invasion, and acquisition of mesenchymal traits. These effects were not observed in HBEC cells bearing single oncogenic mutation (sh-p53 or KRASV12). Mechanistically, hypoxia-inducible factor 1-alpha (HIF-1α) transferred from COPD-EVs triggers CXCR4 pathway activation that in turn mediates MICs expansion and acquisition of pro-tumorigenic effects. Indeed, HIF-1α inhibition or CXCR4 silencing prevented the acquisition of malignant traits induced by COPD-EVs alone. Hypoxia recapitulates the effects observed with COPD-EVs in HBEC-sh-p53-KRASV12high cells. Notably, higher levels of HIF-1α were observed in EVs from COPD subjects who subsequently developed cancer compared to those who remained cancer-free. Our findings support a role of COPD-EVs to promote the expansion of MICs in premalignant epithelial cells through HIF-1α-CXCR4 axis activation thereby potentially sustaining lung cancer progression.

Novel 3D versus traditional transesophageal echocardiography techniques: Defining differences in the diagnosis of infective endocarditis.

Despite the availability of current antibiotic and surgical treatment options, infective endocarditis (IE) remains associated with a high mortality rate. Even though two-dimensional (2D) transesophageal echocardiography (TOE) is a major criteria in the diagnosis of IE, it is constrained by the single-plane orientation. Since three-dimensional (3D) TOE provides a comprehensive understanding of the cardiac architecture by allowing for a realistic visualization of the underlying structures in 3D space, it has attracted considerable interest in recent years. The purpose of this narrative review is to discuss the advantages and pitfalls of 3D TOE in patients with IE, as well as to address emerging photo-realistic 3D techniques that have the potential to enhance the visualization of cardiac structures in this setting. According to recent research, 3D TOE acquisitions outperform 2D acquisitions in terms of vegetation identification accuracy and embolism risk assessment. By reporting a variety of findings that are missed with 2D TOE, but which are validated by surgical examination, 3D TOE further improves the ability to identify endocarditis complications on both native and prosthetic valves. In addition to conventional 3D TOE, future developments in 3D technology led to the development of transillumination and tissue-transparency rendering, which may improve anatomical understanding and depth perception. Due to the use of both conventional and novel 3D techniques, there are more patients who require surgical intervention, indicating that 3D TOE may have a clinical relevance on the surgical management. 3D TOE might fill the gaps left by 2D TOE in the diagnosis of IE.

Correcting gradient chain induced fat quantification errors in radial multi-echo Dixon imaging using a gradient modulation transfer function

Purpose: Multi-echo Stack-of-stars (SoS) radial k-space trajectories with golden angle ordering are becoming popular for free-breathing abdominal Dixon imaging and proton density fat fraction (PDFF) mapping. Gradient chain imperfections including eddy currents and system delays are known to affect the image quality of radial imaging and to confound the estimation of PDFF mapping. This work proposes a retrospective trajectory correction method based on a simple gradient modulation transfer function (GMTF) measurement to predict and correct gradient chain induced k-space trajectory errors.Methods: The GMTF was measured using the standard hardware of a 3 Tesla scanner on a phantom using the thin slice method and was applied to a 3D radial SoS Dixon imaging sequence. The impact of the GMTF-based correction on image reconstruction and PDFF quantification was investigated using numerical simulations and validated on experimental phantom data as well as on in vivo leg and liver data of healthy volunteers.Results: Correcting the k-space trajectories with the measured GMTF during image reconstruction reduced PDFF quantification errors for phantom and in vivo acquisitions. A Bland-Altman comparison of the measured PDFF phantom and reference data confirmed that the GMTF correction narrowed down the limits of agreement (LoA) from 1.3% ± 8.1% (uncorrected) to 1.9% ± 5.4% (GMTF-corrected) over the full PDFF range (0%–100%) and from −0.26% ± 2.8% (uncorrected) to 0.12% ± 1.5% (GMTF-corrected) within the 0%–50% PDFF range. Liver PDFF estimation was improved by reducing the standard deviation of the mean liver PDFF and the bias of the mean liver PDFF for all subjects.Conclusion: The proposed GMTF-based k-space trajectory correction is a fast alternative method for avoiding PDFF quantitation errors caused by gradient-system induced k-space trajectory errors in 3D radial multi-echo gradient-echo acquisitions.

Radial Planes in Hip Magnetic Resonance Imaging: Techniques, Applications, and Perspectives.

The hip cartilage and labrum, as the main targets of femoroacetabular impingement, sports-related or traumatic damage, as well as congenital and developmental abnormalities, have attracted increasing attention with the development of magnetic resonance imaging (MRI) and hip arthroscopy. MRI is a commonly used imaging modality to noninvasively visualize the hip cartilage and labral lesions. However, conventional orthogonal MRI planes encounter unique challenges given the ball-and-socket configuration of the hip joint, its anatomically abducted and anteverted orientation, and the thin, closely apposed cartilage enveloping the femoral head and acetabulum. Advancements in hip MRI's radial plane, which is acquired through the center of the hip joint, offer a solution. This technology provides true cross-sectional images of the cartilage and labrum perpendicular to the curvature of the joint, thereby mitigating the partial-volume-averaging effects. The integration of 3.0-Tesla high field strength and three-dimensional (3D) acquisition techniques further enhances the capabilities of the radial plane. This combination yields a high signal-to-noise ratio, high spatial resolution, high contrast between intraarticular structures, while minimizing partial-volume-averaging effects. Such improvements potentially facilitate the comprehensive detection of even minor chondral and labral lesions. The capability for multiplanar reconstruction from a single 3D volumetric acquisition further strengthens the usefulness of the radial plane by aiding in precise localization of hip cartilage and labral lesions, in line with hip arthroscopy findings. These advancements have the potential to standardize MRI evaluations and radiographic reporting systems for hip cartilage and labrum, offering precise guidance for hip arthroscopy. This article presents a comprehensive review of radial plane technology applied to the hip MRI, and discusses the morphological assessment and localization of hip cartilage and labral lesions utilizing this advanced imaging technique. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.