Search Results (574)

Carotid artery disease has traditionally been assessed according to luminal stenosis, although plaques with similar narrowing may differ substantially in biological activity and clinical risk. Intraplaque neovascularization is a key feature of plaque vulnerability, reflecting microvascular proliferation and its association with inflammation, hemorrhage, and structural destabilization. Dynamic contrast-enhanced ultrasound (DCE-US) offers a real-time, radiation-free method for evaluating intraplaque enhancement kinetics using strictly intravascular microbubble agents. However, its broader use in carotid plaque imaging remains limited by variability in acquisition protocols, contrast administration, signal processing, curve fitting, and parameter interpretation. This technical review clarifies the main analytical approaches used in carotid DCE-US, distinguishing bolus-based wash-in/wash-out analysis from destruction–replenishment modeling. Bolus analysis describes first-pass microbubble transit through the plaque microvasculature and commonly provides parameters such as peak intensity, wash-in slope, area under the curve, and time to peak. Destruction–replenishment analysis evaluates post-destruction refill under stable or quasi-stable contrast conditions and relies on model-based estimation of plateau intensity and the replenishment rate. Because these approaches interrogate different kinetic regimes, their outputs should not be considered interchangeable, even when similar terms are used across studies. Particular emphasis is placed on the operational meaning of quantitative and semi-quantitative parameters, the assumptions underlying curve modeling, and the methodological consequences of ROI placement, motion correction, acoustic settings, and fitting constraints. Rather than proposing a universal acquisition protocol, this article provides practical principles for acquisition, analysis, and reporting, helping radiologists, neuroradiologists, neurologists, and vascular imaging specialists understand the processing steps, algorithmic assumptions, and model-dependent choices underlying software-derived curves and parameters. By making this analytical layer more explicit, the review seeks to support a transparent, reproducible, and biologically coherent approach to quantitative carotid plaque characterization. Full article

Finite element models of the mitral valve can be useful tools for physicians as a predictive tool for surgical planning, teaching, or observation. In order to seamlessly implement these tools in a clinical setting, the process for the creation of the models needs to take into account the diagnostic procedures and tools available to physicians. In this study, a rapid patient-specific model for clinical applications is developed, creating a parametric geometry from measurements routinely taken during the diagnostic process and maintaining a low computational cost through simplifications in material and boundary conditions. The healthy valve model is then validated against ultrasound images from peak diastole to peak systole, finding a good conformity despite simplifications. These results can serve as a stepping stone towards the development of a clinical digital twin of the mitral valve that combines engineering knowledge and medical process. Full article

The ultrasound-guided erector spinae plane (ESP) block is a locoregional anesthesia technique primarily aimed at providing analgesia to structures innervated by the dorsal branches of the spinal nerves (DBSN). While this block has been widely studied in dogs, evidence in cats is limited, and only a few cadaveric studies have addressed the lumbar region. The aim of this study was to compare the injectate distribution and staining of the DBSN following ultrasound-guided lumbar ESP blocks performed using either a longitudinal or transverse approach in feline cadavers. A total of 15 feline cadavers were included, with 3 used for anatomical dissection and 12 for ultrasound-guided injections (24 sides). Injections were performed at the level of the third lumbar vertebra (L3) using a mixture of methylene blue, lidocaine, and iopromide (0.4 mL kg⁻¹ per side). Needle placement and injectate spread were guided and confirmed by ultrasonography, followed by computed tomography (CT) and anatomical dissection to evaluate contrast and dye distribution. CT images revealed longitudinal spread of the contrast in all injections, with the transverse approach producing exclusively longitudinal distribution and the longitudinal approach showing occasional ventral spread beneath the transverse processes (25% of sides). Dissections demonstrated staining of a median of 2 DBSN per side for both approaches, predominantly L2–L3, with rare partial staining of ventral branches (VBSN) observed only with the longitudinal approach. The sympathetic trunk was not stained in any injection. No statistically significant differences were observed between approaches, except for L1 DBSN staining, which was identified significantly more frequently with the transverse approach (p = 0.033). These findings indicate that ultrasound-guided lumbar ESP block is anatomically feasible in feline cadavers and that both longitudinal and transverse approaches can result in injectate distribution to the DBSN. Full article

Necrotizing enterocolitis (NEC) remains one of the most serious gastrointestinal emergencies in preterm infants, and imaging plays a central role in diagnosis and clinical management. Historically, evaluation has relied primarily on abdominal radiography, which remains widely available and embedded in established diagnostic frameworks. However, the hallmark radiographic signs of NEC (i.e., pneumatosis intestinalis, portal venous gas, and free air) reflect relatively advanced manifestations of intestinal injury that indicate established mucosal disruption or transmural necrosis. Bowel ultrasound has increasingly complemented radiography by enabling real-time assessment of bowel wall integrity, perfusion, motility, and intra-abdominal fluid, providing physiologic information that may refine clinical interpretation and monitoring of disease progression. Expanding use of neonatologist-performed bowel ultrasound may further improve access to bedside intestinal imaging and facilitate more timely evaluation in neonatal intensive care settings. In parallel, emerging imaging technologies seek to extend the capabilities of conventional imaging by interrogating biologic processes that underlie intestinal injury. Modalities such as contrast-enhanced ultrasound, ultra-high-frequency ultrasound, and photoacoustic imaging offer the potential to characterize bowel microvascular perfusion, tissue oxygenation, and microstructural changes that may precede overt radiographic abnormalities. Complementary physiologic monitoring approaches are also being explored to identify infants at risk before clinical disease develops. Techniques including superior mesenteric artery Doppler, near-infrared spectroscopy, bowel acoustic monitoring, and electrogastrography aim to detect early alterations in intestinal perfusion, oxygenation, and motility. In addition, artificial intelligence applied to imaging and physiologic data may enhance pattern recognition, risk stratification, and clinical decision support. Together, these advances suggest that NEC evaluation is evolving from a paradigm focused on detecting late structural injury toward integrated approaches capable of identifying intestinal vulnerability earlier and monitoring disease more precisely. Full article

Coronary artery calcification (CAC) represents a clear sign of advanced atherosclerosis and a strong indicator of coronary artery disease burden and cardiovascular risk. Beyond its established prognostic value, CAC significantly influences plaque biology, lesion morphology, and the technical complexity of percutaneous coronary intervention (PCI). This review summarizes current knowledge on the mechanisms of vascular calcification, its clinical determinants, diagnostic assessment, and therapeutic implications. Vascular calcification is now understood as an active, regulated process involving osteogenic transdifferentiation of vascular smooth muscle cells, inflammatory signaling pathways, extracellular vesicle release, and disturbances in mineral metabolism. Distinct calcification phenotypes exert different effects on plaque stability: micro- and spotty calcifications are frequently linked to plaque vulnerability, whereas dense, sheet-like calcification is more typical of stable fibrocalcific lesions. The prevalence of CAC increases with age and differs between sexes, while cardiometabolic risk factors, chronic kidney disease, systemic inflammation, and genetic predisposition further contribute to its development. Noninvasive computed tomography remains the cornerstone for CAC detection and quantification, enabling reliable cardiovascular risk stratification. Intravascular imaging techniques, particularly intravascular ultrasound and optical coherence tomography, provide detailed characterization of calcified plaque morphology and support optimal procedural planning. In patients with heavily calcified lesions, intravascular imaging-guided lesion preparation and stent optimization represent the most effective strategy for improving PCI outcomes. Full article

Introduction: Chronic wounds and pathologic scars remain a persistent challenge in plastic surgery. Conventional treatments can be costly and inconsistent, prompting interest in regenerative approaches that utilize autologous tissue. Emulsified fat produces nanofat through mechanical processing and contains adipose-derived stem cells, stromal vascular fractions, extracellular matrix proteins, cytokines and growth factors. The purpose of this systematic review is to evaluate the use of autologous nanofat for wound healing and scar management, with emphasis on preparation techniques, treatment indications, and outcomes. Methods: A comprehensive PubMed search with no date restrictions was conducted in January 2026 using MeSH terms and keywords related to nanofat and wound-healing applications. Studies were screened independently by two reviewers using the Rayyan platform. Eligible studies evaluated nanofat for wound healing in human or animal subjects; non-English articles, studies not involving nanofat, editorials, and conference abstracts were excluded. The extracted data included study characteristics, participant numbers, treatment details, indications, adjunct therapies, follow-up duration, outcomes, and complications. Studies were grouped by clinical application, with individual reports included in multiple categories when relevant. Results: The search identified 53 records, of which 22 studies met the inclusion criteria after screening. These included 20 human and two animal studies spanning randomized controlled trials (n = 3), prospective trials (n = 6), retrospective analyses (n = 6), case series (n = 4), and case reports (n = 3). Mechanical emulsification was the predominant autologous nanofat preparation method (91%), often combined with filtration or centrifugation. Clinical indications in human studies were diverse, most commonly including scar treatment (n = 14) (acne, burns, depressed, and post-surgical), followed by chronic wounds (n = 3) and reconstructive applications (n = 3). Nanofat was administered via injection in 86% of studies (n = 19), typically using fine-gauge needles or microcannulas with intradermal or subdermal placement, while three studies used non-injection approaches such as topical, membrane, or dressing-based delivery. Scar or aesthetic parameters, measured using VSS, POSAS, physician grading, photography, pigmentation analysis, or clinical appearance, were evaluated in 73% of studies (n = 16), and all reported improvement in variables such as pigmentation, pliability, thickness, texture, or overall appearance. Wound-healing endpoints were assessed in 36% (n = 8), with 100% (n = 8) demonstrating accelerated healing, improved epithelialization, or defect closure. Patient-reported outcomes, including satisfaction or quality of life, were measured in 32% (n = 7), and all showed improvement. Objective imaging modalities (e.g., 3D imaging, ultrasound, angiography, digital analysis) were used in 23% (n = 5), each confirming structural or physiologic improvement. Histologic or biomolecular analyses were performed in 27% (n = 6) and uniformly demonstrated regenerative changes, such as increased angiogenesis, collagen remodeling, or growth factor expression. Treatment was well tolerated, with 77% of studies (n = 17) reporting minimal or no complications and only transient mild adverse effects, including mild pain, bruising, erythema, and edema. Conclusions: Current evidence suggests that autologous nanofat is a promising regenerative therapy for wound healing and scar modulation. Across diverse clinical applications, nanofat has been associated with improved tissue quality, enhanced healing, and favorable patient-reported outcomes, with minimal complications. The mechanical processing of autologous tissue may also involve fewer regulatory concerns compared with more extensively manipulated cellular products. Full article

Understanding the dynamics of gas bubbles in viscoelastic media is crucial for applications involving stable cavitation under ultrasound, such as drug delivery, materials processing, and biomedical imaging. The Rayleigh-Plesset equation formulated in terms of bubble volume variation, incorporating viscoelastic effects via the linear Kelvin–Voigt model, is extended here to a fourth-order approximation. This formulation allows a more accurate description of nonlinear bubble dynamics at finite acoustic amplitudes. The resulting equation is solved numerically under various acoustic conditions, with particular emphasis on driving frequencies near the bubble’s resonance and differences between Newtonian and viscoelastic media. To identify the physical conditions under which higher-order nonlinearities become necessary, a decision-tree classification analysis is performed. The results show that the proximity to resonance and the excitation amplitude are the primary determinants of higher-order nonlinear effects, while rheological properties act as modulators, with viscosity exerting a stronger influence than elasticity within the explored ranges. This work provides a physically interpretable criterion for selecting the appropriate model order, improving the prediction and control of nonlinear bubble oscillations under ultrasound excitation in viscoelastic media. Full article

A challenge of studying mammalian cardiac embryogenesis is the limited ability to perform experimental manipulations in animal models. The avian embryo is widely accepted as a model for mammalian heart developmental studies. In this study, we establish the methodology and protocols for studying the Japanese quail (Coturnix japonica) heart at embryonic day 10 (HH38) using the FUJIFILM VisualSonics Vevo 3100 ultrasound system equipped with a MX550D small animal cardiology transducer. These protocols were designed to measure right ventricular wall thickness, pulmonary artery diameter, and the outflow velocities of the right ventricular outflow tract (RVOT) and the pulmonary artery (PA), thereby establishing baseline parameters of the normally developing quail morphology. Quail embryos are an ideal model for cardiovascular research due to their short incubation period (16–17 days), experimental accessibility, and strong similarities to mammalian heart development. These developmental similarities include, but are not limited to, looping, chamber septation, and the development of a true four-chamber heart. High-resolution imaging modalities, including ultrasound and optical coherence tomography, enable noninvasive, real-time visualization of cardiac morphology and function throughout development. Echocardiography allows for quantitative and qualitative assessments of myocardial structure and cardiac hemodynamics. The similarity to the mammalian heart, combined with rapid embryogenesis, makes quail embryos a valuable model for investigating congenital heart defects, genetic modifications, and fundamental cardiac developmental processes. In this study, we describe reproducible incubation protocols and baseline echocardiographic parameters used to evaluate morphological and physiological changes in the developing embryonic quail heart on embryonic day 10. Full article

Cryptorchidism is the most prevalent congenital anomaly of the male genitourinary tract, with an incidence of approximately 1 to 9 percent in full-term male infants, decreasing with age due to spontaneous descent. It encompasses testes that fail to descend into the scrotum, which may be intra-abdominal, inguinal, or ectopic, and can be associated with syndromic, genetic, or environmental factors. The descent process occurs in two phases: intra-abdominal, driven by gubernacular development and androgen-independent mechanisms, and inguinoscrotal, regulated by hormonal and mechanical factors including androgens and the gubernaculum. Clinically, cryptorchidism manifests as absent or hypoplastic scrotal testes, often with inguinal fullness. Palpation and physical examination are primary diagnostic tools, with imaging such as ultrasound or MRI reserved for specific cases. Surgical exploration remains the definitive diagnostic modality, especially for nonpalpable testes. Early referral, ideally before 12 months of age, is essential for timely orchidopexy, which aims to position the testes within the scrotum to reduce risks of torsion, trauma, subfertility, and malignancy. Hormonal therapy shows limited efficacy and is generally not recommended as a primary treatment modality. Long-term outcomes indicate that early orchidopexy improves spermatogenic potential and fertility. Men with a history of cryptorchidism exhibit elevated risks of subfertility and testicular germ cell tumors, with the risk being higher if surgical correction is delayed or if testes remain intra-abdominal. The increased malignancy risk persists even after orchidopexy, underscoring the importance of vigilant surveillance. Management strategies emphasize a multidisciplinary approach, combining surgical intervention with ongoing monitoring, to optimize functional and oncological outcomes. Early diagnosis, appropriate surgical treatment, and patient education are critical components in minimizing long-term complications associated with cryptorchidism. Full article

Monolithic zirconia restorations are frequently affected by the unnoticed growth of subcritical cracks, a failure process that is not captured by traditional imaging methods like radiographs and ultrasounds in sophisticated dental architectures. To address this evaluative inadequacy, this research introduces a hierarchical deep learning framework for microcrack detection and spatial localization. We promote a hierarchical deep learning system that integrates Acoustic Emission (AE) detection alongside signal processing. Raw AE signals utilized during dynamic loading are enhanced via Kalman filtering and Continuous Wavelet Transform (CWT) to construct high-fidelity time–frequency scalograms. The diagnostic pipeline operates in two stages: first, a hybrid CNN–BiGRU network with temporal attention fulfills zirconia component-level classification; second, a ResNet-18 backbone integrated with Bidirectional LSTM and Multi-Head Attention precisely localizes defects across five anatomical crown regions. This hierarchical design effectively captures the non-stationary, transient nature of fracture-induced stress waves. The framework achieved an F1-score of 99.00% and an AUC of 0.994, significantly outperforming conventional convolutional networks. By enabling predictive maintenance through early, non-invasive damage localization, this study demonstrates a promising laboratory framework for AE-based crack detection in zirconia dental structures and prosthetics and toward enhanced clinical reliability in digital dentistry. Full article

Obstructive sleep apnea (OSA) is a widely known sleep disorder that leads to serious health problems and complications. The standard diagnosis method of OSA is polysomnography. However, the process is time-intensive, expensive, and not readily accessible. Machine learning (ML) has been increasingly applied in various medical imaging modalities; however, there is still a lack of research on applying ML to ultrasound imaging for OSA classification. Previous studies on ML applications in medical imaging adopt X-rays, Computed Tomography, and Magnetic Resonance Imaging, leaving ultrasound as an underexplored area. Using the You-Only-Look-Once version 8 algorithm and static tongue ultrasound images, we classified OSA severity: normal, mild, moderate, and severe. A total of 280 ultrasound images were augmented to 838 images using brightness scaling, which enhanced the training process of the model. The system was tested on 60 images, achieving an overall classification accuracy of 85%. The results demonstrate the possibility and potential of using machine learning and ultrasound imaging for classifying the severity of OSA, suggesting potential assistance to clinicians in diagnosing and intervening in this condition. Full article

Heart disease remains a leading cause of mortality worldwide, and timely and accurate diagnosis is crucial for improving patient outcomes. Medical imaging plays a pivotal role in this process, yet traditional diagnostic methods often suffer from limitations, including dependency on manual interpretation, susceptibility to observer variability, and inefficiency in handling large-scale data. Deep learning has emerged as an innovative technology in medical imaging, providing unparalleled advancements in feature extraction, segmentation, classification, and prediction tasks. Despite its proven potential, comprehensive reviews of deep learning methods specifically targeted at cardiac imaging remain scarce. This review paper seeks to bridge this gap by analyzing the state-of-the-art deep learning applications for heart disease diagnosis, covering the period from 2015 to 2025. Employing a well-structured methodology, this review categorizes and examines studies based on imaging modalities: Ultrasound (US), Magnetic Resonance Imaging (MRI), X-ray, Computed Tomography (CT), and Electrocardiography (ECG). For each modality, the analysis focuses on utilized datasets, processing techniques (e.g., extraction, segmentation and classification), and paradigms (e.g., transfer learning, federated learning, explainability, interpretability, and uncertainty quantification). Additionally, the types of heart disease addressed and prediction accuracy metrics are also scrutinized. These findings point toward future opportunities, including the study of data quality, optimization, transfer learning, uncertainty quantification and model explainability or interpretability. Furthermore, exploring advanced techniques such as recurrent expansion, transformers, and other architectures may unlock new pathways in cardiac imaging research. This review is a critical synthesis offering a roadmap for researchers and practitioners to advance the application of deep learning in heart disease diagnosis. Full article

This is a narrative conceptual paper, not a systematic review. Ultrasound-guided fascial hydrorelease (FHR) has been reported to provide sustained pain relief in patients with chronic musculoskeletal pain; however, its underlying biological mechanisms remain incompletely understood. In this paper, we propose the “Fascial Memory Reset Hypothesis” as an integrative framework linking mechanobiology, extracellular matrix (ECM) remodeling, peripheral nociception, microcirculatory dynamics, and ultrasound imaging findings. Mechanobiological research has demonstrated that increased tissue stiffness activates YAP/TAZ signaling, promoting fibroblast activation, ECM deposition, and mechano-epigenetic regulation. These mechanically driven processes can stabilize pathological tissue phenotypes without DNA sequence alterations. The “Fascial Memory Reset Hypothesis” proposes that targeted mechanical interventions such as FHR may partially reverse these mechanically maintained states by restoring tissue mobility and modifying stiffness-dependent mechanotransduction. We propose that “stacking fascia” (observed as layered hyperechoic bands on ultrasound) represents the macroscopic structural phenotype of mechano-epigenetic memory formed through sustained mechanical stress. Integrating molecular mechanotransduction pathways, mechano-epigenetic mechanisms, neural sensitization, and vascular factors, we propose that FHR may hypothetically partially normalize pathological fascial states by mechanically restoring tissue mobility and modifying stiffness-dependent signaling. Although direct molecular evidence of the effect of FHR in human fascia remains limited, this hypothesis provides a biologically plausible link between mechanical stress, ultrasound-visible structural alterations, and sustained clinical improvement. Full article

Background/Objectives: This study proposes CMT-BUSNet, a hybrid architecture integrating CNN, Mamba, and Transformer branches for breast ultrasound tumor segmentation with built-in explainability. Methods: CMT-BUSNet employs a CNN-anchored hierarchical parallel encoder where Mamba and Transformer branches process CNN-derived features in parallel, fused through an Adaptive Feature Fusion Module (AFFM) with Dense Nested Decoder and Boundary-Aware Composite Loss. Five-fold cross-validation on BUS-BRA (N = 1875) compared nine architectures under identical protocols, plus nnU-Net v2 trained with its default self-configuring protocol as a benchmark. External evaluation used the BUSI dataset (N = 647). Results: CMT-BUSNet achieved DSC = 0.9037 ± 0.0047 on BUS-BRA with higher boundary delineation metrics than nnU-Net v2, which was trained under a different self-configuring protocol (B-IoU: 0.611 vs. 0.557; HD95: 10.07 vs. 13.54 pixels), despite nnU-Net’s marginally higher DSC (0.9108). On BUSI, CMT-BUSNet (DSC = 0.6709) yielded higher scores than nnU-Net (0.5579) across all metrics under zero-shot transfer, though the two methods were trained under different protocols. Training-based ablation confirmed each component’s contribution, and quantitative XAI validation demonstrated attribution faithfulness (nEAR = 2.82×) and uncertainty–error correlation (r = 0.39). Conclusions: CMT-BUSNet achieves competitive accuracy with higher boundary metrics, preliminary cross-dataset transferability, and built-in interpretability relative to nnU-Net (noting different training protocols). Internal validation folds are image-disjoint but not guaranteed to be patient-disjoint, which should be considered when interpreting the reported metrics. Multicenter validation is required before clinical deployment. Full article

Introduction/Aims: Quantitative analysis of nerve echogenicity can support the diagnosis of mono- and polyneuropathies, for instance by distinguishing inflammatory-demyelinating from axonal damage. However, echogenicity is mainly assessed qualitatively and examiner-dependently. This study aimed to establish quantitative reference data for grayscale values of peripheral nerves in the upper and lower extremities of healthy children and adolescents to provide a clinical benchmark. Methods: We retrospectively analyzed ultrasound data from 211 healthy children aged two to seventeen years who had undergone standardized examinations of 15 peripheral nerve sites. Grayscale analysis (0–255 levels per pixel) was performed within manually defined regions of interest (ROIs) using ImageJ (version 1.52). Echogenicity values were correlated with age, weight, height, and body mass index (BMI). Results: Echogenicity showed no significant overall association with biometric parameters. Mean grayscale values ranged from 85.23 ± 2.16 for the tibial nerve at the medial malleolus to 134.62 ± 2.69 for the sural nerve. Gain settings below 60 resulted in significantly lower grayscale values, whereas measurements with gain ≥ 60 were stable and comparable. Discussion: We propose reference grayscale ranges for peripheral nerves in healthy children and adolescents as a practical benchmark for clinical use and future studies. Due to technical constraints—particularly retrospective image processing and non-lossless data export—each laboratory should establish its own reference dataset, or multicentric parameters should be established. As our sample consisted predominantly of Caucasian participants, ethnic differences should be considered when applying these values to other populations. Full article