Search Results (124)

Atrial fibrillation (AF) is a prevalent heart arrhythmia, characterized by an irregularly irregular rhythm and the absence of identifiable P waves on ECG. Given the loss of effective atrial contraction, AF carries a risk of serious complications. If untreated, AF can promote thrombogenesis, leading to stroke, systemic embolism (e.g., limb or organ ischemia), and myocardial infarction. These serious complications highlight the importance of understanding AF and assessing stroke risk to guide optimal management of this chronic arrhythmia. Congruent with recent technological developments, advanced imaging has emerged as a modality to better understand AF. This review highlights advanced imaging techniques and their advantages, with a focus on 4D flow MRI, a novel modality that enables visualization of blood flow patterns in three dimensions and provides unique insights into cardiac hemodynamics. It also synthesizes the current literature on key hemodynamic markers identified by 4D flow MRI, including blood flow stasis, wall shear stress, and vorticity. Quantifying these markers has improved predictive accuracy of future stroke risk in AF patients, allowing clinicians to risk stratifying their patients and optimize management. Finally, the review discusses potential future markers that may further refine our understanding of AF and inform patient care. Full article

Recent advances in cardiovascular imaging have revolutionized the assessment and management of abdominal aortic aneurysm (AAA) through the integration of sophisticated haemodynamic biomarkers. This comprehensive review evaluates the clinical utility and mechanistic significance of multiple biomarkers in AAA pathogenesis, progression, and treatment outcomes. Advanced cardiac imaging modalities, including four-dimensional magnetic resonance imaging (4D MRI), computational fluid dynamics (CFD), and specialized echocardiography, enable precise quantification of critical haemodynamic parameters. Wall shear stress (WSS) emerges as a fundamental biomarker, with values below 0.4 Pa indicating pathological conditions and increased risk for aneurysm progression. Time-averaged wall shear stress (TAWSS), typically maintaining values above 1.5 Pa in healthy arterial segments, provides crucial information about sustained haemodynamic forces affecting the vessel wall. The oscillatory shear index (OSI), ranging from 0 (unidirectional flow) to 0.5 (purely oscillatory flow), quantifies directional changes in WSS during cardiac cycles. In AAA, elevated OSI values between 0.3 and 0.4 correlate with disturbed flow patterns and accelerated disease progression. The relative residence time (RRT), combining TAWSS and OSI, identifies regions prone to thrombosis, with values exceeding 2–3 Pa⁻¹ indicating increased risk. The endothelial cell activation potential (ECAP), calculated as OSI/TAWSS, serves as an integrated metric for endothelial dysfunction risk, with values above 0.2–0.3 Pa⁻¹ suggesting increased inflammatory activity. Additional biomarkers include the volumetric perivascular characterization index (VPCI), which assesses vessel wall inflammation through perivascular tissue analysis, and pulse wave velocity (PWV), measuring arterial stiffness. Central aortic systolic pressure and the aortic augmentation index provide essential information about cardiovascular load and arterial compliance. Novel parameters such as particle residence time, flow stagnation, and recirculation zones offer detailed insights into local haemodynamics and potential complications. Implementation challenges include the need for specialized equipment, standardized protocols, and expertise in data interpretation. However, the potential for improved patient outcomes through more precise risk stratification and personalized treatment planning justifies continued development and validation of these advanced assessment tools. Full article

This study investigated the effect of the number of sensors (8, 12, 16, and 20) on the measurement results of stress wave velocity in two-dimensional acoustic tomography of Hoop pine (Araucaria cunninghamii Sweet) trees and evaluated the method’s accuracy and operational efficiency in tree health diagnostics. Tests were conducted on five sample trees, two of which were confirmed to have internal damage using the drilling resistance method. The results showed that increasing the number of sensors improved image resolution and information completeness. However, differences in the average stress wave velocities among sensor configurations were not statistically significant (p ≥ 0.05), indicating limited overall velocity variation. In healthy trees, stress wave velocities measured with different sensor quantities (e.g., eight vs. twenty) exhibited weak linear correlations (R² = 0.06–0.58), reflecting a relatively uniform internal structure. In contrast, damaged trees showed strong consistency in velocity results (R² = 0.82–0.91, p < 0.01), with both minimum and average velocities being significantly lower than those in healthy trees. These findings demonstrate that acoustic tomography can effectively identify internal tree defects. Notably, even with only eight sensors, decay and cavities can still be accurately detected, which significantly enhances field inspection efficiency and reduces costs, thereby showing strong potential for practical applications. Full article

Varicocele is a common, potentially correctable condition associated with impaired male fertility. Despite being frequently encountered in clinical andrology, its pathophysiological mechanisms, diagnostic criteria, and therapeutic approaches remain areas of active investigation and debate. The authors conducted a comprehensive literature search, using the PubMed database, covering clinical studies, systematic reviews, meta-analyses, and current international guidelines from the past ten years. Emphasis was placed on studies investigating novel diagnostic modalities, therapeutic innovations, and prognostic markers. Emerging evidence supports the multifactorial pathophysiology of varicocele, involving oxidative stress, hypoxia, inflammatory pathways, and potential genetic predisposition. Biomarkers, including microRNAs, antisperm antibodies, and sperm DNA fragmentation, offer diagnostic and prognostic utility, though their routine clinical implementation requires further validation. Advances in imaging, such as shear wave elastography, may improve diagnostic accuracy. While microsurgical subinguinal varicocelectomy remains the gold standard, technological refinements and non-surgical alternatives are being explored. Indications for treatment have expanded to include selected cases of non-obstructive azoospermia, hypogonadism, and optimization for assisted reproduction, though high-level evidence is limited. Full article

This study aims to characterize short-wave infrared (SWIR) reflectance spectra at cranial (at the scalp overlying the frontal cortex and the temporal bone window) and extracranial (biceps and triceps) sites in patients with multiple sclerosis (MS) and age-/sex-matched controls. We sought to identify the diagnostic accuracy of wavelength-specific patterns in distinguishing MS from normal controls and spectral markers associated with disability (e.g., Expanded Disability Status Scale scores). To achieve these objectives, we employed a multi-site SWIR spectroscopy acquisition protocol that included measurements from traditional cranial locations as well as extracranial reference sites. Advanced spectral analysis techniques, including wavelength-dependent absorption modeling and machine learning-based classification, were applied to differentiate MS-related hemodynamic changes from normal physiological variability. Classification models achieved perfect performance (accuracy = 1.00), and cortical site regression models showed strong predictive power (EDSS: R²_CV = 0.980; FSS: R²_CV = 0.939). Variable Importance in Projection (VIP) analysis highlighted key wavelengths as potential spectral biomarkers. This approach allowed us to explore novel biomarkers of neural and systemic impairment in MS, paving the way for potential clinical applications of SWIR spectroscopy in disease monitoring and management. In conclusion, spectral analysis revealed distinct wavelength-specific patterns collected from cranial and extracranial sites reflecting biochemical and structural differences between patients with MS and normal subjects. These differences are driven by underlying physiological changes, including myelin integrity, neuronal density, oxidative stress, and water content fluctuations in the brain or muscles. This study shows that portable spectral devices may contribute to bedside individuation and monitoring of neural diseases, offering a cost-effective alternative to repeated imaging. Full article

The pull-back method for determining dynamic tensile strength assumes one-dimensional stress wave propagation and material homogeneity. This study validates these assumptions for unidirectional reinforced concrete (UDRC) through experiments and numerical simulations. Split Hopkinson pressure bar tests were conducted on plain concrete, plain UDRC, and deformed UDRC specimens containing a central 6 mm steel bar. Ultra-high-speed digital image correlation at 500,000 fps enabled precise local strain rate measurements (3 s⁻¹ to 55 s⁻¹) at fracture locations. Finite element simulations revealed that while reinforcement induces localized multi-axial stresses near the steel–concrete interface, the bulk concrete maintains predominantly uniaxial stress conditions. Experimental results showed less than 1% variation in pull-back velocity between specimen types. Statistical analysis confirmed a unified strain rate-strength relationship: ${\sigma }_{\mathrm{spall}}=4.1+4.7{log}_{10}\left(\dot{\epsilon }\right)$$\mathrm{M}\mathrm{Pa}$, independent of reinforcement configuration (ANCOVA: $p=0.2182$ for interaction term). The dynamic tensile strength is governed by concrete matrix properties rather than reinforcement type. These findings are the first to experimentally and numerically validate the pull-back method’s applicability to UDRC systems, establishing that dynamic tensile failure is matrix-dominated and enabling simplified one-dimensional analysis for reinforced concrete under impact. Full article

Steel lazy wave risers (SLWRs) are critical in offshore hydrocarbon transport for linking subsea wells to floating production facilities in deep-water environments. The incorporation of buoyancy modules reduces curvature-induced stress concentrations in the touchdown zone (TDZ); however, extended operational exposure under cyclic environmental and operational loads results in repeated seabed contact. This repeated interaction modifies the seabed soil over time, gradually forming a trench and altering the riser configuration, which significantly impacts stress patterns and contributes to fatigue degradation. Accurately reconstructing the riser’s evolving profile in the TDZ is essential for reliable fatigue life estimation and structural integrity evaluation. This study proposes a simulation-based framework for the autonomous tracking of SLWRs using a fin-actuated autonomous underwater vehicle (AUV) equipped with a monocular camera and multibeam echosounder. By fusing visual and acoustic data, the system continuously estimates the AUV’s relative position concerning the riser. A dedicated image processing pipeline, comprising bilateral filtering, edge detection, Hough transform, and K-means clustering, facilitates the extraction of the riser’s centerline and measures its displacement from nearby objects and seabed variations. The framework was developed and validated in the underwater unmanned vehicle (UUV) Simulator, a high-fidelity underwater robotics and pipeline inspection environment. Simulated scenarios included the riser’s dynamic lateral and vertical oscillations, in which the system demonstrated robust performance in capturing complex three-dimensional trajectories. The resulting riser profiles can be integrated into numerical models incorporating riser–soil interaction and non-linear hysteretic behavior, ultimately enhancing fatigue prediction accuracy and informing long-term infrastructure maintenance strategies. Full article

Acoustic tomography is a non-destructive technique used in the internal assessment of standing trees. Various researchers have focused on developing analytical tools using this technique, demonstrating that they can detect internal biodeterioration in cross-sections with good accuracy. This study evaluates the use of two ultrasonic wave devices with different frequencies (USLab and Sylvatest Duo) and a stress wave device (Microsecond Timer) to generate acoustic tomography using ImageWood VC1 software. The tests were carried out on 12 cross-sections of urban trees in the city of Madrid of the species Robinia pseudoacacia L., Platanus × hybrida Brot., Ulmus pumila L., and Populus alba L. Velocity measurements were made, forming a diffraction mesh in both standing trees and logs after cutting them down. An inspection was carried out with a perforation resistance drill (IML RESI F-400S) in the radial direction in each section, which allowed for more precise identification of defects and differentiating between holes and cracks. The various defects were determined with greater accuracy in the tomographic images taken with the higher-frequency equipment (45 kHz), and the combination of ultrasonic tomography and the use of the inspection drill can provide a more accurate representation of the defects. Full article

The Dynamic response of two cavities, an elliptical inclusion and a linear crack near anisotropic bi-material interface, was explored analytically by incident out-plane waves in the current work. Firstly, the media is divided into two half spaces (an elastic anisotropic half space with a circular cavity and a linear crack, and an elastic isotropic half space containing an elliptical cavity and an elliptical inclusion). With the help of the image principle, the complex function method is then used to derive the wave fields in each half space. Combined with Green’s functions approach, the relevant Green’s functions developed in the “crack creation” and “conjunction of two half spaces” procedures are derived sequentially. Subsequently, based on the “conjunction” technique, undetermined anti-plane forces are applied to the horizontal surfaces of two half spaces to maintain the continuity criteria of the interface. A series of Fredholm integral equations isobtained and then solved by utilizing the direct discrete technique. Dynamic stress concentration of two elliptical cavities and an elliptical inclusion is mainly considered graphically to discuss the interaction between two half spaces. Finally, a parametric study on the dynamic stress concentration factor (DSCF) was given to show the influence of different parameters on the interaction. Full article

This review paper provides a comprehensive examination of millimeter-wave radar technologies in automotive systems, reviewing their advancements through signal processing innovations. The evolution of radar systems, from conventional platforms to mmWave technologies, has significantly enhanced capabilities such as high-resolution imaging, real-time tracking, and multi-object detection. Signal processing advancements, including constant false alarm rate detection, multiple-input–multiple-output systems, and machine learning-based techniques, are explored for their roles in improving radar performance under dynamic and challenging environments. The integration of mmWave radar with complementary sensing technologies such as LiDAR and cameras facilitates robust environmental perception essential for advanced driver-assistance systems and autonomous vehicles. This review also calls attention to key challenges, including environmental interference, material penetration, and sensor fusion, while addressing innovative solutions such as adaptive signal processing and sensor integration. Emerging applications of joint communication–radar systems further presents the potential of mmWave radar in autonomous driving and vehicle-to-everything communications. By synthesizing recent developments and identifying future directions, this review stresses the critical role of mmWave radar in advancing vehicular safety, efficiency, and autonomy. Full article

Stress urinary incontinence (SUI) results from complex anatomical and functional interactions, including urethral mobility, muscle activity, and pelvic floor support. Despite advancements in imaging and electrophysiology, a comprehensive model remains elusive. This study employed shear wave elastography (SWE), incorporating sound touch elastography (STE) and sound touch quantification (STQ) with acoustic radiation force impulse (ARFI) technology, to assess urethral elasticity and bladder neck descent (BND) in women with SUI and continent controls. Between October 2024 and January 2025, 30 women (15 with SUI, 15 controls) underwent transperineal and intravaginal ultrasonography at IRCCS San Gerardo. Statistical analysis, conducted using JMP 17, revealed significantly greater BND in the SUI group (21.8 ± 7.8 mm vs. 10.5 ± 5 mm) and increased urethral stiffness (Young’s modulus: middle urethra, 57.8 ± 15.6 kPa vs. 30.7 ± 6.4 kPa; p < 0.0001). Mean urethral pressure was the strongest predictor of SUI (p < 0.0001). Findings emphasize the role of urethral support and connective tissue integrity in continence. By demonstrating SWE’s diagnostic utility, this study provides a foundation for personalized, evidence-based approaches to SUI assessment and management. Full article

Background/Objectives: This study investigates the association between mild first-wave COVID-19 infection and subclinical abnormalities in echocardiographic strain parameters and myocardial perfusion using single-photon emission computed tomography (SPECT). Methods: We conducted a retrospective analysis of patients from June 2020 to March 2021 with a history of mild first-wave COVID-19 infection, presenting with nonspecific cardiac symptoms and referred for SPECT myocardial perfusion stress testing. Patients had no obstructive coronary artery disease (CAD) on follow-up invasive angiography or cardiac computed tomography angiography (CCTA) and had transthoracic echocardiographic images of sufficient quality for strain analysis using AutoSTRAIN (TOMTEC^®). Results: Fifteen patients met the inclusion criteria. SPECT and echocardiography were reviewed for perfusion and strain defects, respectively, in the inferior, anterior, lateral, and septal myocardial segments. All patients had at least one perfusion abnormality on SPECT: 2/15 (13%) had a fixed defect in one segment, 3/15 (20%) in two, 3/15 (20%) in three, and 7/15 (47%) in four. While 13/15 (87%) patients had normal qualitative findings on traditional echocardiography, 12/15 (80%) had abnormal global longitudinal strain (GLS) (>−18%) and transregional wall strain abnormality in at least one segment. Abnormalities on SPECT and strain echocardiography demonstrated a moderate but significant 60% concordance, with an intraclass correlation coefficient (ICC) of 0.486 (p = 0.028). Conclusions: Patients with ‘mild’ COVID-19 infection demonstrated a high frequency of abnormalities on SPECT myocardial perfusion imaging (even in the absence of obstructive CAD) which appeared to be concordant with abnormal strain parameters on echocardiography, suggesting possible subclinical effects on myocardial tissue. Full article

The accurate and efficient simulation of seismic wave energy dissipation and phase dispersion during propagation in subsurface media due to inelastic attenuation is critical for the hydrocarbon-bearing distinction and improving the quality of seismic imaging in strongly attenuating geological media. The fractional viscoelastic equation, which quantifies frequency-independent anelastic effects, has recently become a focal point in seismic exploration. We have developed a novel hybrid staggered-grid Grünwald–Letnikov (HSGGL) finite difference method for solving the fractional viscoelastic equation in the time domain. The proposed method achieves accurate and computationally efficient solutions by using a staggered grid to discretize the first-order partial derivatives of the velocity–stress equations, combined with Grünwald–Letnikov finite difference discretization for the fractional-order terms. To improve the computational efficiency, we employ a preset accuracy to truncate the difference stencil, resulting in a compact fractional-order difference scheme. A stability analysis using the eigenvalue method reveals that the proposed method confers a relaxed stability condition, providing greater flexibility in the selection of sampling intervals. The numerical experiments indicate that the HSGGL method achieves a maximum relative error of no more than 0.17% compared to the reference solution (on a finely meshed domain) while being significantly faster than the conventional global FD method (GFD). In a 500 × 500 computational domain, the computation times for the proposed methods, which meet the specified accuracy levels used, are only approximately 4.67%, 4.47%, 4.44%, and 4.42% of that of the GFD method. This indicates that the novel HSGGL method has the potential as an effective forward modeling tool for understanding complex subsurface structures by employing a fractional viscoelastic equation. Full article

Repeatable and reliable assessment of corneal biomechanics with spatial resolution remains a challenge. Vibrational Optical Computerized Tomography (V-OCT), based on sound-wave elastography, has made it possible to investigate the natural resonant modes of the cornea and obtain the elastic moduli non-invasively. This pilot study presents a characterization of four corneal vibrational modes from aberrometric, geometrical, and biomechanical approaches in the living human cornea of five healthy volunteers by combining a corneal sound-wave generator, dual Placido–Scheimpflug corneal imaging, and the Ocular Response Analyzer (ORA) devices. Sound-induced corneal wavefront aberration maps were reconstructed as a function of sound frequency and isolated from the natural state. While maps of low-order aberrations (LOA) revealed symmetric geometrical patterns, those corresponding to high-order aberrations (HOA) showed complex non-symmetric patterns. Corneal geometry was evaluated by reconstructing corneal elevation maps through biconical fitting, and the elastic and viscous components were calculated by applying the standard linear solid model to the ORA measurements. The results showed that sound-wave modulation can increase high-order corneal aberrations significantly. Two frequencies rendered the corneal shape more prolate (50 Hz) and oblate (150 Hz) with respect to the baseline, respectively. Finally, both the elastic and viscous properties are sensitive to sound-induced vibrational modes, which can also modulate the corneal stress-strain response. The cornea exhibits natural resonant modes influenced by its optical, structural, and biomechanical properties. Full article

Laver (Pyropia spp.) is a major seaweed that is cultivated and consumed globally. Although quality standards for laver products have been established, traditional physicochemical analyses and sensory evaluations have notable drawbacks regarding rapid-quality inspection. Not all relevant physicochemical quality indices, such as texture, are typically evaluated. Therefore, in this study, we investigated the use of hyperspectral imaging to rapidly, accurately, and objectively determine the quality of dried laver. Hyperspectral images of 25 dried laver samples were captured in the short-wave infrared range from 980 to 2576 nm to assess their moisture, protein content, cutting stress, and other key quality indicators. Spectral signatures were analyzed using partial least-squares discriminant analysis (PLS-DA) to correlate the spectral data with three primary quality index values. The performance of PLS-DA was compared with that of the variable importance in projection score and nonlinear regression analysis methods. The comprehensive quality grading model demonstrated accuracies ranging from 96 to 100%, R² values from 75 to 92%, and root-mean-square errors from 0.14 to 0.25. These results suggest that the PLS-DA regression model shows great potential for the multivariate analysis of hyperspectral images, serving as an effective quality grading system for dried laver. Full article