Search Results (1,116)

An adult female bottlenose dolphin (Tursiops truncatus) housed at a public oceanarium presented with acute anorexia and lethargy. A blood analysis demonstrated mild leukocytosis, marked azotemia, hyperkalemia, and hyperphosphatemia suggestive of acute kidney injury or renal insufficiency. Ultrasound examination of the dolphin revealed ascites, pleural effusion, bilateral nephrolithiasis, mild hydronephrosis, and bilateral hydroureter consistent with bilateral post-renal obstruction. Initial treatment consisted of antibiotics, oral fluids, and anti-inflammatory treatment. Further imaging diagnosed bilateral obstructing ureteroliths at both ureteral orifice junctions of the urinary bladder. The dolphin’s azotemia and hyperkalemia were nonresponsive to traditional medical management; therefore, peritoneal dialysis was performed for emergent clinical stabilization. Peritoneal dialysis was conducted over 3 days and facilitated the patient to undergo laser lithotripsy of the offending ureteral obstruction. The dolphin made a full recovery following months of intensive medical treatment for complications from peritoneal dialysis and secondary peritonitis. This is the first documented case of successful, though complicated, peritoneal dialysis in a cetacean. Full article

Breast cancer is the leading cause of cancer-related mortality among women world-wide, and early screening is critical for improving patient survival. Medical imaging plays a central role in breast cancer screening, diagnosis, and treatment monitoring. However, conventional imaging modalities—including mammography, ultrasound, and magnetic resonance imaging—face limitations such as low diagnostic specificity, relatively slow imaging speed, ionizing radiation exposure, and dependence on exogenous contrast agents. Photoacoustic imaging (PAI), a novel hybrid imaging technique that combines optical contrast with ultrasonic spatial resolution, has shown great promise in addressing these challenges. By revealing anatomical, functional, and molecular features of the breast tumor microenvironment, PAI offers high spatial resolution, rapid imaging, and minimal operator dependence. This review outlines the fundamental principles of PAI and systematically examines recent advances in its application to breast cancer screening, diagnosis, and therapeutic evaluation. Furthermore, we discuss the translational potential of PAI as an emerging breast imaging modality, complementing existing clinical techniques. Full article

Background: Point-of-care ultrasound (POCUS) is gaining recognition as a valuable diagnostic tool in various fields of medicine, including pediatrics. Its application at the point of care enables real-time clinical decision-making, which is particularly advantageous in pediatric settings. Although global interest in POCUS is growing, many European countries—including Poland—still lack formal training programs for POCUS at both the undergraduate and postgraduate levels. Nevertheless, the number of pediatricians incorporating POCUS into their daily clinical practice in Poland is increasing. However, the extent of its use and perceived value among pediatricians remains largely unknown. This study aimed to evaluate the current level of POCUS utilization in pediatric care in Poland, focusing on pediatricians’ self-assessed competencies, perceptions of its clinical utility, and key barriers to its implementation in daily practice. Methods: This cross-sectional study was conducted between July and August 2024 using an anonymous online survey distributed to pediatricians throughout Poland via national professional networks, with a response rate of 7.3%. Categorical variables were analyzed using the chi-square test of independence to assess the associations between key variables. Quantitative data were analyzed using descriptive statistics, and qualitative data from open-ended responses were subjected to a thematic analysis. Results: A total of 210 pediatricians responded. Among them, 149 (71%) reported access to ultrasound equipment at their workplace, and 89 (42.4%) reported having participated in some form of POCUS training. Only 46 respondents (21.9%) reported frequently using POCUS in their clinical routine. The self-assessed POCUS competence was rated as low or very low by 136 respondents (64.8%). While POCUS was generally perceived as a helpful tool in facilitating and accelerating clinical decisions, the main barriers to implementation were a lack of formal training and limited institutional support. Conclusions: Although POCUS is perceived as clinically valuable by the surveyed pediatricians in Poland, its routine use remains limited due to training and systemic barriers. Future efforts should prioritize the development of a validated, competency-based training framework and the implementation of a larger, representative national study to guide the structured integration of POCUS into pediatric care. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease. It has known multifactorial pathophysiology, but the impact of social determinants of health (SDOH) on the rising prevalence of MASLD is poorly understood. We conducted a retrospective cross-sectional study to examine the influence of SDOH on MASLD using nationwide data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES) study. Methods: We identified participants with MASLD based on liver ultrasound-based controlled attenuation parameter measurements consistent with diagnostic guidelines. We then used logistic regression models to examine associations between SDOH variables and MASLD, with a pre-specified focus on education and income, sequentially adjusting for sociodemographic factors, medical comorbidities, and other SDOH. Results: Our study found that higher education (odds ratio [OR] 0.77, 95% confidence interval [CI] 0.62–0.97, p = 0.024) but not higher income (OR 1.12, 95% CI 0.91–1.37, p = 0.3) was associated with lower odds of MASLD in multivariable adjusted models. We also identified a significant interaction between education level and food security, as well as interactions between food security and other significant SDOH. In the stratified analyses, higher education was significantly associated with lower odds of MASLD among participants with food security (OR 0.71, 95% CI 0.55–0.91, p = 0.007) but not among those with food insecurity (OR 1.26, 95% CI 0.76–2.11, p = 0.4). Conclusions: Our findings identify the potential impact of SDOH on odds of MASLD and suggest increased importance of food security relative to other SDOH. Full article

Hypoplastic or absent fetal nasal bone (NB) is a significant soft marker in the risk assessment for aneuploidies. This study aimed to evaluate prenatal findings and perinatal outcomes in fetuses with absent or hypoplastic NB managed at our center. This retrospective analysis was conducted at the Department of Obstetrics at the Medical University of Vienna and including all cases with an absent or hypoplastic fetal NB between 2004 and 2022. Clinical data were extracted and analyzed using descriptive statistics. A total of 149 cases were included. Of these, 51% had chromosomal abnormalities, with trisomy 21 present in 30.9%. Malformations were identified in 55% of cases, most commonly congenital heart defects (34.9%) and facial dysmorphism (28.9%). Eighteen fetuses (12.1%) had structural anomalies without genetic disorders. In 32.9% (n = 49), the NB anomaly was isolated. Our findings show that only half of the cases had chromosomal abnormalities, and over half of the pregnancies resulted in live births with generally favorable perinatal outcomes. However, the presence of additional ultrasound abnormalities significantly increased the risk of adverse outcomes. Therefore, detection of a fetal NB anomaly should prompt comprehensive ultrasound evaluation and genetic testing. Full article

Background: The relationship between spleen and bone marrow stiffness, and other features of abnormal myeloproliferation has long been described. However, the scientific knowledge in this area remains very superficial. This review evaluated the diagnostic effectiveness of various ultrasound (US) methods in the assessment of neoplastic myeloproliferation using spleen stiffness measurement (SSM). Aim: To explore the diagnostic accuracy of US techniques in assessing spleen stiffness, determining which of them may be suitable for the diagnosis of myeloproliferative diseases in adults. Methods: The review included original retrospective or prospective studies published in the last five years (2019–2024) in peer-reviewed medical journals that reported receiver operating characteristics (ROCs) for SSM and the articles concerning the relation between SSM values and neoplastic myeloproliferation. The studies were identified through PubMed searches on 1 July and 1 December 2024. Quality was assessed using the QUADAS-2 tool. Results were tabulated according to the diagnostic method separately for myeloproliferative neoplasms (MNs) and for other clinical findings. Results: The review included 52 studies providing ROCs for SSM or compatibility between operators, and five studies covering the relation between SSM values and MNs. Conclusions: Acoustic radiation force impulse (ARFI), two-dimensional shear wave elastography (2D-SWE), transient elastography (TE), and point shear wave elastography (p-SWE) are promising methods for measuring SSM that can be incorporated into the diagnosis, screening, and monitoring system in MNs. Full article

Background: Artificial intelligence (AI) and machine learning (ML) have been reshaping maternal, fetal, neonatal, and reproductive healthcare by enhancing risk prediction, diagnostic accuracy, and operational efficiency across the perinatal continuum. However, no comprehensive synthesis has yet been published. Objective: To conduct a scoping review of reviews of AI/ML applications spanning reproductive, prenatal, postpartum, neonatal, and early child-development care. Methods: We searched PubMed, Embase, the Cochrane Library, Web of Science, and Scopus through April 2025. Two reviewers independently screened records, extracted data, and assessed methodological quality using AMSTAR 2 for systematic reviews, ROBIS for bias assessment, SANRA for narrative reviews, and JBI guidance for scoping reviews. Results: Thirty-nine reviews met our inclusion criteria. In preconception and fertility treatment, convolutional neural network-based platforms can identify viable embryos and key sperm parameters with over 90 percent accuracy, and machine-learning models can personalize follicle-stimulating hormone regimens to boost mature oocyte yield while reducing overall medication use. Digital sexual-health chatbots have enhanced patient education, pre-exposure prophylaxis adherence, and safer sexual behaviors, although data-privacy safeguards and bias mitigation remain priorities. During pregnancy, advanced deep-learning models can segment fetal anatomy on ultrasound images with more than 90 percent overlap compared to expert annotations and can detect anomalies with sensitivity exceeding 93 percent. Predictive biometric tools can estimate gestational age within one week with accuracy and fetal weight within approximately 190 g. In the postpartum period, AI-driven decision-support systems and conversational agents can facilitate early screening for depression and can guide follow-up care. Wearable sensors enable remote monitoring of maternal blood pressure and heart rate to support timely clinical intervention. Within neonatal care, the Heart Rate Observation (HeRO) system has reduced mortality among very low-birth-weight infants by roughly 20 percent, and additional AI models can predict neonatal sepsis, retinopathy of prematurity, and necrotizing enterocolitis with area-under-the-curve values above 0.80. From an operational standpoint, automated ultrasound workflows deliver biometric measurements at about 14 milliseconds per frame, and dynamic scheduling in IVF laboratories lowers staff workload and per-cycle costs. Home-monitoring platforms for pregnant women are associated with 7–11 percent reductions in maternal mortality and preeclampsia incidence. Despite these advances, most evidence derives from retrospective, single-center studies with limited external validation. Low-resource settings, especially in Sub-Saharan Africa, remain under-represented, and few AI solutions are fully embedded in electronic health records. Conclusions: AI holds transformative promise for perinatal care but will require prospective multicenter validation, equity-centered design, robust governance, transparent fairness audits, and seamless electronic health record integration to translate these innovations into routine practice and improve maternal and neonatal outcomes. Full article

Objectives: This study introduces an automated classification system for noisy kidney ultrasound images using an ensemble of deep neural networks (DNNs) with transfer learning. Methods: The method was tested using a dataset with two categories: normal kidney images and kidney images with stones. The dataset contains 1821 normal kidney images and 2592 kidney images with stones. Noisy images involve various types of noises, including salt and pepper noise, speckle noise, Poisson noise, and Gaussian noise. The ensemble-based method is benchmarked with state-of-the-art techniques and evaluated on ultrasound images with varying quality and noise levels. Results: Our proposed method demonstrated a maximum classification accuracy of 99.43% on high-quality images (the original dataset images) and 99.21% on the dataset images with added noise. Conclusions: The experimental results confirm that the ensemble of DNNs accurately classifies most images, achieving a high classification performance compared to conventional and individual DNN-based methods. Additionally, our method outperforms the highest-achieving method by more than 1% in accuracy. Furthermore, our analysis using Gradient-weighted Class Activation Mapping indicated that our proposed deep learning model is capable of prediction using clinically relevant features. Full article

Background and Clinical Significance: Serratus Anterior Muscle Pain Syndrome (SAMPS) is an underdiagnosed cause of anterior chest wall pain, often attributed to myofascial trigger points of the serratus anterior muscle (SAM) or dysfunction of the Long Thoracic Nerve (LTN), leading to significant disability and affecting ipsilateral upper limb movement and quality of life. Current diagnosis relies on exclusion and physical examination, with limited treatment options beyond conservative approaches. This case report presents a novel approach to chronic SAMPS, successfully diagnosed using Sonoguided Digital Palpation (SDP) and treated with ultrasound-guided hydrodissection of the LTN using 5% dextrose in water (D5W) without local anesthetic (LA), in a patient where conventional treatments had failed. Case Presentation: A 72-year-old male presented with a three-year history of persistent left chest pain radiating to the upper back, exacerbated by activity and mimicking cardiac pain. His medical history included two percutaneous coronary interventions. Physical examination revealed tenderness along the anterior axillary line and a positive hyperirritable spot at the mid axillary line at the 5th rib level. SDP was used to visualize the serratus anterior fascia (SAF) and LTN, and to reproduce the patient’s concordant pain by palpating the LTN. Ultrasound-guided hydrodissection of the LTN was then performed using 20–30cc of D5W without LA to separate the nerve from the surrounding tissues, employing a “fascial unzipping” technique. The patient reported immediate pain relief post-procedure, with the pain reducing from 9/10 to 1/10 on the Numeric Rating Scale (NRS), and sustained relief and functional improvement at the 12-month follow-up. Conclusions: Sonoguided Digital Palpation (SDP) of the LTN can serve as a valuable diagnostic adjunct for visualizing and diagnosing SAMPS. Ultrasound-guided hydrodissection of the LTN with D5W without LA may provide a promising and safe treatment option for patients with chronic SAMPS refractory to conservative management, resulting in rapid and sustained pain relief. Further research, including controlled trials, is warranted to evaluate the long-term efficacy and generalizability of these findings and to compare D5W to other injectates. Full article

Background and Clinical Significance: Radial nerve palsy typically presents as wrist drop due to nerve compression, with conventional management often yielding prolonged recovery. We report a case where ultrasound-guided hydrodissection (HD) with 5% dextrose in water (D5W) achieved immediate functional restoration, suggesting neurapraxia as the underlying pathology. Case Presentation: A 54-year-old diabetic female presented with acute left wrist drop without trauma. Examination confirmed radial nerve palsy (MRC grade 0 wrist extension), while radiographs ruled out structural causes. Ultrasound revealed fascicular swelling at the spiral groove. Under real-time guidance, 50 mL D5W (no local anesthetic) was injected to hydrodissect the radial nerve. Immediate post-procedure assessment showed restored wrist extension (medical research council (MRC) grade 4+). At one- and three-month follow-ups, the patient maintained complete resolution of symptoms and normal function. Conclusions: This case highlights two key findings: (1) HD with D5W can serve as both a diagnostic tool (confirming reversible neurapraxia through immediate response) and therapeutic intervention, and (2) early HD may circumvent prolonged disability associated with conservative management. The absence of electrodiagnostic studies limits objective severity assessment, though ultrasound localized the lesion. While promising, these observations require validation through controlled trials comparing HD to standard care, particularly in diabetic patients with heightened compression susceptibility. Technical considerations—including optimal injectate volume and the role of adjuvant therapies—warrant further investigation. US-guided HD with D5W emerges as a minimally invasive, surgery-sparing option for acute compressive radial neuropathies, with potential to redefine treatment paradigms when applied at symptom onset. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

Assessment of the placental cord insertion (PCI) is a vital component of antenatal ultrasound examinations. PCI can be complex, particularly in cases of abnormal PCI, and requires proficient sonographer spatial perception. The current literature describes the increasing potential of three-dimensional (3D) modelling to enhance spatial awareness and understanding of complex anatomical structures. This study aimed to evaluate sonographers’ confidence in ultrasound assessment of the PCI and the potential benefit of novel 3D-printed models (3DPMs) of the PCI in ultrasound education. Sonographers employed at a large private medical imaging practice in Western Australia were invited to participate in a face-to-face presentation of two-dimensional (2D) ultrasound images, ultrasound videos, and 3DPMs of normal cord insertion (NCI), marginal cord insertion (MCI), and velamentous cord insertion (VCI). Our objective was to determine the benefit of 3DPMs in improving sonographers’ confidence and ability to spatially visualise the PCI. Thirty-three participants completed questionnaires designed to compare their confidence in assessing the PCI and their ability to spatially visualise the anatomical relationship between the placenta and PCI, before and after the presentation. There was a significant association between a participant’s year of experience and their confidence levels and spatial awareness of the PCI prior to the demonstration. The results showed the 3DPMs increased participant confidence and their spatial awareness of the PCI, with no significant association with years of experience. Additionally, participating sonographers were asked to rate the 3DPMs as an educational device. The 3DPMs were ranked as being a more useful educational tool for spatially visualising the NCI, MCI, and VCI than 2D ultrasound images and videos. Most participants responded favourably when asked whether the 3DPMs would be useful in ultrasound education, with 75.8%, 84.8%, and 97% indicating the models of NCI, MCI, and VCI, respectively, would be extremely useful. Our study has demonstrated a potential role for 3DPMs of the PCI in ultrasound education, supplementing traditional 2D educational resources. Full article

This paper presents the PRONOBIS project, an ultrasound-only, robotically assisted, deep learning-based system for prostate scanning and biopsy treatment planning. The proposed system addresses the challenges of precise prostate segmentation, reconstruction and inter-operator variability by performing fully automated prostate scanning, real-time CNN-transformer-based image processing, 3D prostate reconstruction, and biopsy needle position planning. Fully automated prostate scanning is achieved by using a robotic arm equipped with an ultrasound system. Real-time ultrasound image processing utilizes state-of-the-art deep learning algorithms with intelligent post-processing techniques for precise prostate segmentation. To create a high-quality prostate segmentation dataset, this paper proposes a deep learning-based medical annotation platform, MedAP. For precise segmentation of the entire prostate sweep, DAF3D and MicroSegNet models are evaluated, and additional image post-processing methods are proposed. Three-dimensional visualization and prostate reconstruction are performed by utilizing the segmentation results and robotic positional data, enabling robust, user-friendly biopsy treatment planning. The real-time sweep scanning and segmentation operate at 30 Hz, which enable complete scan in 15 to 20 s, depending on the size of the prostate. The system is evaluated on prostate phantoms by reconstructing the sweep and by performing dimensional analysis, which indicates 92% and 98% volumetric accuracy on the tested phantoms. Three-dimansional prostate reconstruction takes approximately 3 s and enables fast and detailed insight for precise biopsy needle position planning. Full article

Background/Objectives: Otolaryngologists are increasingly using head and neck ultrasound (HNUS). Determining whether a practitioner of HNUS has achieved adequate theoretical knowledge remains a challenge. This study assesses the performance of two large language models (LLMs) in generating multiple-choice questions (MCQs) for head and neck ultrasound, compared with MCQs generated by physicians. Methods: Physicians and LLMs (ChatGPT, GPT4o, and Google Gemini, Gemini Advanced) created a total of 90 MCQs that covered the topics of lymph nodes, thyroid, and salivary glands. Experts in HNUS additionally evaluated all physician-drafted MCQs using a Delphi-like process. The MCQs were assessed by an international panel of experts in HNUS, who were blinded to the source of the questions. Using a Likert scale, the evaluation was based on an overall assessment including six assessment criteria: clarity, relevance, suitability, quality of distractors, adequate rationale of the answer, and an assessment of the level of difficulty. Results: Four experts in the clinical field of HNUS assessed the 90 MCQs. No significant differences were observed between the two LLMs. Physician-drafted questions (n = 30) had significant differences with Google Gemini in terms of relevance, suitability, and adequate rationale of the answer, but only significant differences in terms of suitability compared with ChatGPT. Compared to MCQ items (n = 16) validated by medical experts, LLM-constructed MCQ items scored significantly lower across all criteria. The difficulty level of the MCQs was the same. Conclusions: Our study demonstrates that both LLMs could be used to generate MCQ items with a quality comparable to drafts from physicians. However, the quality of LLM-generated MCQ items was still significantly lower than MCQs validated by ultrasound experts. LLMs are therefore cost-effective to generate a quick draft for MCQ items that afterward should be validated by experts before being used for assessment purposes. In this way, the value of LLM is not the elimination of humans, but rather vastly superior time management. Full article

Objective: To assess the long-term effects of Dienogest on clinical complaints and nodule sizes in women affected by recto-sigmoid deep endometriosis (DE). Methods: This was a single-center longitudinal prospective observational study comprising a consecutive series of women affected by recto-sigmoid DE, who underwent medical treatment with Dienogest (2 mg daily continuous). All women underwent clinical visits and transvaginal sonography (TVS) with bowel preparation prior to starting therapy and at 3–6-month intervals for at least 12 months. Clinical complaints such as dysmenorrhea, dyspareunia and dyschezia were assessed using a visual analog scale (VAS). The DE recto-sigmoid lesion was measured in the three orthogonal planes. The lesion’s volume was estimated using the prolate ellipsoid formula. The maximum diameter and lesion volume were used for analysis. Patients’ complaints and lesion sizes before starting the treatment and at final follow-up were compared. Results: From January 2017 to July 2020, 125 patients were consecutively recruited (mean age: 37 years, ranging from 20 to 50 years). The median follow-up period was 47.8 months (range: 12–74 months). We did not observe a significant correlation between the severity of the symptoms and the lesion size prior to starting therapy. Clinical complaints improved significantly during treatment (88% of women were symptomatic at initial visit, versus 53% at final follow-up, p < 0.001). The median lesion volume significantly decreased (median initial volume vs. final volume: 1.1 mL vs. 0.9 mL, p = 0.017). However, the median maximum lesion diameter did not change significantly (26.0 mm vs. 25.0 mm, p = 0.779). Conclusions: Long-term Dienogest therapy significantly relieves clinical symptoms related to recto-sigmoid DE. This is accompanied by a significant reduction in the lesion volume but not the maximum lesion diameter. Full article