Researchers and clinicians have called for early pregnancy biomarkers of pre-term delivery, especially in the uterine cervix, a crucial player in delivery timing. The goal of this study was to develop practical biomarkers that can help predict the timing of delivery using ultrasound images. Here we investigated first-order speckle statistics as a lens into the remodeling microstructure of the cervix throughout gestation.

By using lung ultrasound and Venous Excess Ultrasound Grading System (VExUS) to assess fluid tolerance, four congestion types can be identified: fluid tolerant (no congestion), pulmonary congestion, systemic congestion and both pulmonary and systemic congestion. The primary aim is to describe the epidemiology of these congestions types.

Ultrasound Targeted Microbubble Destruction (UTMD) technology enhances microvascular blood perfusion, with adenosine triphosphate (ATP) release from red blood cells (RBCs) playing a crucial role. However, the precise mechanisms remain unclear. This study aimed to investigate the role of Piezo1 in regulating ATP release from RBCs by UTMD.

This study aimed to evaluate the feasibility, safety, and preliminary efficacy of high-intensity focused ultrasound (HIFU) ablation for treating soft tissue tumors (STTs) located in challenging anatomical regions (e.g. adjacent to critical nerves, blood vessels, joint areas, or recurrent tumors).

The quantity and quality of pelvic floor ultrasound (US) samples directly affect the accuracy of computer-assisted diagnosis of pelvic floor dysfunction. To address issues such as blurred texture and insufficient richness in existing US image-generation methods, we constructed a Cross-Perceptual Guided Generative Adversarial Network (CPG-GAN) to obtain sufficient and high-quality pelvic floor US images.

To assess the diagnostic efficacy of the contrast-enhanced ultrasound (CEUS) features combined with serum tumor biomarkers for the diagnosis of hepatocellular carcinoma (HCC).

Thyroid nodules are one of the most common thyroid disorders and can be categorized into benign and malignant thyroid nodules. Currently, the initial diagnosis is made clinically by ultrasonography, and the determination of thyroid nodules is highly dependent on the operating experience and maneuvers of the physician, resulting in fluctuating diagnostic accuracy. Recent studies have shown that using deep learning-based automated diagnostic tools can assist in the segmentation of individual nodules in thyroid ultrasound images. However, in reality, a single frame typically contains multiple nodules.

Ultrasound imaging, known for its affordability, portability and real-time capabilities, has become a crucial diagnostic tool worldwide. However, the limited field of view in 2-D ultrasound and reduced anatomical coverage in current 3-D systems have prompted the development of volumetric compounding. This review aims to outline the techniques and technologies used in mosaicking ultrasound volumes to overcome these challenges and enhance clinical imaging capabilities. This review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A search was conducted in four bibliographic databases and grey literature to identify articles that utilised 3-D ultrasound transducers for the registration or compounding of ultrasound volumes. Review selection and characterisation were performed by two independent reviewers. The search identified 72 papers published from 2013 to 2024, with most studies focused on cardiovascular applications (54.2%). The primary goal of these studies was to improve the visualisation of structures (45.8%) and extend the field of view (30.6%). Automation was a significant focus, with 46.6% of studies using automated methods for improved efficiency and accuracy. However, a larger proportion of semi-automated methods indicates that certain tasks still require human intervention. While significant progress has been made in enhancing image quality, future research should focus on refining these methods, exploring under-represented clinical applications, and leveraging state-of-the-art artificial intelligence methods to improve efficiency, accuracy and clinical integration.

The delivery of large molecules to the pathological brain is one of the main obstacles in the development of disease-modifying drugs. This is partly due to the presence of the blood-brain barrier (BBB), which blocks the free passage of lipophobic molecules and those larger than 400 Da. One strategy to bypass this natural barrier is to use low-intensity pulsed ultrasound to oscillate circulating micro-sized microbubbles, which then exert mechanical stress on the vessel walls. This procedure allows for temporary disruption of the BBB and enhanced local delivery of therapeutics from the blood to the brain parenchyma. In this study, the effect of repeated BBB opening on neuroinflammation in a healthy mouse model was first explored, followed by the effect of repeated opening on amyloid-beta (Aβ) pathology in an Alzheimer's disease model.

This study aims to develop an AI-based framework for automatic endometrial thickness (ET) measurement in transvaginal ultrasound (TVUS) based on a large dataset and evaluate its performance from various clinical perspectives.

Perioperative hemodynamic monitoring plays a crucial role in reducing complications during coronary artery bypass graft (CABG) surgery. Corrected left ventricular ejection time (cLVET) is used to assess cardiac contractility but requires specialized echocardiography expertise. Corrected carotid flow time (ccFT), a non-invasive carotid Doppler-based method, could serve as an alternative, but its agreement with cLVET in CABG patients remains uncertain. This study evaluates the clinical agreement between these two measures in a real-world clinical setting.

To evaluate the indirect head of rectus femoris tendon (IHRFT) enthesis as a stable adjunct anatomical landmark for standardizing coronal plane acquisition in ultrasound detection of developmental dysplasia of the hip (DDH) and characterize its diagnostic utility.

Breast cancer remains a leading threat to women's health worldwide and reducing mortality hinges on early detection. Contrast-enhanced ultrasound (CEUS), an emerging technique for blood-pool imaging, enables assessment of microvascular perfusion in breast lesions and addresses limitations of conventional ultrasound. Although CEUS plays an increasingly important role in breast cancer diagnosis, a comprehensive bibliometric evaluation of CEUS research in breast oncology has not yet been undertaken. This study applied bibliometric analysis to delineate the developmental trajectory of CEUS in breast cancer, identify prevailing research hotspots, and anticipate future directions. Using publications retrieved from the Web of Science Core Collection (1996 to May 2025), we conducted a systematic assessment of co-authorship patterns; institutional and national collaboration networks; journal and author productivity; and keyword co-occurrence and clustering. In total, 503 publications met the inclusion criteria, with annual output accelerating notably since 2020. China and the United States were the principal contributors, both in publication volume and collaborative partnerships. Forsberg Flemming and the Journal of Ultrasound in Medicine were identified as the most prolific author and journal, respectively. Thematic cluster analysis highlighted key research domains, including optimization of microbubble agents, diagnostic performance, treatment response monitoring and integration of artificial intelligence (AI). Collectively, these trends indicate the field's progression from a primarily diagnostic modality toward predictive, therapeutic, and real-time AI-enabled applications driven by ongoing technological innovation.

Aims of this first-in-human clinical trial were to evaluate the safety and efficacy of sonodynamic therapy (SDT) using a newly developed trigger pulse high-intensity focused ultrasound (HIFU) device, MS-2, and micellar nanoparticle-encapsulated epirubicin, K-912, in patients with unresectable refractory abdominal cancers.

To investigate the diagnostic performance of standard ultrasound (US) using a US-adapted Bosnian classification for characterizing cystic renal masses (CRMs) compared with computed tomography/magnetic resonance imaging (CT/MRI) as the current standard.

Ultrasound-targeted microbubble (MB) cavitation (UTMC) is an image-guided therapeutic oligonucleotide delivery platform utilizing intravenously injected gas-filled ultrasound contrast agents, which carry the therapeutic on the MB shell. During transit of MBs in the microcirculation of target tissue, ultrasound causes MB oscillation, facilitating endocytosis-independent payload uptake within insonified cells. Here, we tested the hypothesis that UTMC-mediated miR-27a* delivery will reduce tumor growth rate and result in accumulation of miR-27a* within tumor cells and the tumor microenvironment.

High frequency ultrasound imaging has become an important tool for the study of pregnancy disorders in mouse models as it enables detailed, noninvasive characterization of in utero development. However, the need to reliably identify individual fetuses over time presents a challenge when using this approach for longitudinal assessments. Large litter sizes and frequently changing fetal positions within the abdomen across gestation have the potential to confound such measurements.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a common urinary tract disorder in males. Low-intensity pulsed ultrasound (LIPUS), a non-invasive therapeutic modality, has shown potential in alleviating inflammation associated with this condition. However, the underlying mechanisms through which LIPUS exerts its effects on CP/CPPS remain largely unknown. This study aimed to investigate the impact of LIPUS at varying intensities and durations on pain relief in a rat model of CP/CPPS.