Search Results (51)

Background: Ultrasound (U/S) can be used to evaluate skeletal muscle characteristics in clinical and sports settings. Handheld U/S devices have recently emerged as a cheaper and portable alternative to conventional U/S systems. However, further research is warranted on their reliability. We assessed the reliability and inter-device agreement between a handheld U/S device (Clarius L15 HD₃) and a more conventional U/S system (GE LOGIQ e) for measuring the thickness of the rectus femoris (RF) and vastus intermedius (VI). Methods: Cross-sectional images of the RF and VI muscles were obtained in 20 participants by two assessors, and on two separate occasions by one of those assessors, using the Clarius L15 HD₃ and GE LOGIQ e devices. RF and VI thickness measurements were obtained to determine the intra-rater reliability, inter-rater reliability, and inter-device agreement. Results: All intraclass correlation coefficients (ICCs) were above 0.9 for intra-rater reliability (range: 0.94 to 0.97), inter-rater reliability (ICC: 0.97), and inter-device agreement (ICC: 0.98) when comparing the two devices in assessing RF and VI thickness. For the RF, the Bland–Altman plot revealed a mean difference of 0.06 ± 0.07 cm, with limits of agreement ranging from 0.21 to −0.09, whereas for the VI, the Bland–Altman plot showed a mean difference of 0.07 ± 0.10 cm, with limits of agreement ranging from 0.27 to −0.13. Conclusions: The handheld Clarius L15 HD₃ was reliable and demonstrated high agreement with the more conventional GE LOGIQ e for assessing the thickness of the RF and VI in young, healthy adults. Full article

Background/Objectives: Two-dimensional echocardiography (2D echo) is widely used for assessing left ventricular ejection fraction (LVEF). This single-center comparative study aims to evaluate the accuracy of LVEF measurements obtained using the AI-assisted handheld ultrasound device Kosmos against cardiac magnetic resonance (CMR), the current gold standard. Methods: A total of 49 adult patients undergoing clinically indicated CMR were prospectively enrolled. AI-based LVEF measurements were compared with CMR using the Wilcoxon signed-rank test, Pearson correlation, multivariable linear regression, and Bland–Altman analysis. All analyses were performed using STATA v18.0. Results: Median LVEF was 57% (CMR) vs. 55% (AI-Echo), with no significant difference (p = 0.51). Strong correlation (r = 0.99) and minimal bias (1.1%) were observed. Conclusions: The Kosmos AI-based autoEF algorithm demonstrated excellent agreement with CMR-derived LVEF values. Its speed and automation make it promising for bedside assessment in emergency departments, intensive care units, and outpatient clinics. This study aims to fill the gap in current clinical evidence by evaluating, for the first time, the agreement between LVEF measurements obtained via Kosmos’ AI-assisted autoEF and those from cardiac MRI (CMR), the gold standard for ventricular function assessment. This comparison is critical for validating the reliability of portable AI-driven echocardiographic tools in real-world clinical practice. However, these findings derive from a selected population at a single Italian center and should be validated in larger, diverse cohorts before assuming global generalizability. Full article

Ultrasound technology has emerged as a transformative tool in modern food science, offering non-destructive, real-time assessment and enhancement of food quality attributes. This review systematically explores the fundamental mechanisms by which ultrasound interacts with food matrices, including mechanical effects such as acoustic cavitation, localized shear forces, and microstreaming, as well as thermal and acoustic attenuation phenomena. Applications of ultrasound in food texture evaluation are discussed across multiple sectors, with particular emphasis on its role in assessing moisture distribution, fat content, structural integrity, and microstructural alterations in meat, dairy, fruits, and vegetables. The versatility of ultrasound—spanning low-intensity quality assessments to high-intensity processing interventions—makes it an invaluable technology for both quality control and product innovation. Moreover, emerging innovations such as ultrasound-assisted extraction, non-thermal pasteurization, and real-time quality monitoring are highlighted, demonstrating the synergy between ultrasound and advanced technologies like AI-driven data interpretation and portable, handheld sensing devices. Despite these advances, challenges related to technical limitations in heterogeneous food systems, high initial investment costs, scalability, and the absence of standardized protocols remain critical barriers to widespread adoption. The future directions emphasize the integration of ultrasound with multi-modal approaches, the development of miniaturized and cost-effective equipment, and the establishment of global regulatory standards to facilitate its broader application. Overall, ultrasound is positioned as a key enabler for sustainable, efficient, and non-invasive quality assurance across the global food industry. Full article

Previous work has demonstrated quantitative ultrasound (QUS) analysis techniques for extracting features and texture features from ultrasound radiofrequency data which can be used to distinguish between benign and malignant breast masses. It is desirable that there be good agreement between estimates of such features acquired using different ultrasound devices. Handheld ultrasound imaging systems are of particular interest as they are compact, relatively inexpensive, and highly portable. This study investigated the agreement between QUS parameters and texture features estimated from clinical ultrasound images of breast tumors acquired using two different ultrasound scanners: a traditional cart-based system and a wireless handheld ultrasound system. The 28 patients who participated were divided into two groups (benign and malignant). The reference phantom technique was used to produce functional estimates of the normalized power spectra and backscatter coefficient for each image. Root mean square differences of feature estimates were calculated for each cohort to quantify the level of feature variation attributable to tissue heterogeneity and differences in system imaging parameters. Cross-system statistical testing using the Mann–Whitney U test was performed on benign and malignant patient cohorts to assess the level of feature estimate agreement between systems, and the Bland–Altman method was employed to assess feature sets for systematic bias introduced by differences in imaging method. The range of p-values was 1.03 × 10⁻⁴ to 0.827 for the benign cohort and 3.03 × 10⁻¹⁰ to 0.958 for the malignant cohort. For both cohorts, all five of the primary QUS features (MBF, SS, SI, ASD, AAC) were found to be in agreement at the 5% confidence level. A total of 13 of the 20 QUS texture features (65%) were determined to exhibit statistically significant differences in the sample medians of estimates between systems at the 5% confidence level, with the remaining 7 texture features being in agreement. The results showed a comparable magnitude of feature variation between tissue heterogeneity and system effects, as well as a moderate level of statistical agreement between feature sets. Full article

Background/Objectives: This study evaluated the role of a discrete multi-wavelength near-infrared spectroscopic (DMW-NIRS) imaging device for rapid breast lesion differentiation. Methods: A total of 62 women (mean age, 49.9 years) with ultrasound (US)-guided biopsy-confirmed breast lesions (37 malignant, 25 benign) were included. A handheld probe equipped with five pairs of light-emitting diodes (LEDs) and photodiodes (PDs) measured lesion-to-normal tissue (L/N) ratios of four chromophores, THC (Total Hemoglobin Concentration), StO₂, and the Tissue Optical Index (TOI: log10(THC × Water/Lipid)). Lesions were localized using US. Diagnostic performance was assessed for each L/N ratio, with subgroup analysis for BI-RADS 4A lesions. Two adaptive BI-RADS models were developed: Model 1 used TOI_L/N thresholds (Youden index), while Model 2 incorporated radiologists’ reassessments of US findings integrated with DMW-NIRS results. These models were compared to the initial BI-RADS assessments, conducted by breast-dedicated radiologists. Results: All L/N ratios significantly differentiated malignant from benign lesions (p < 0.05), with TOI_L/N achieving the highest AUC-ROC (0.901; 95% CI: 0.825–0.976). In BI-RADS 4A lesions, all L/N ratios except Lipid significantly differentiated malignancy (p < 0.05), with TOI_L/N achieving the highest AUC-ROC (0.902; 95% CI: 0.788–1.000). Model 1 and Model 2 showed superior diagnostic performance (AUC-ROCs: 0.962 and 0.922, respectively), significantly outperforming initial BI-RADS assessments (prospective AUC-ROC: 0.862; retrospective AUC-ROC: 0.866; p < 0.05). Conclusions: Integrating DMW-NIRS findings with US evaluations enhances diagnostic accuracy, particularly for BI-RADS 4A lesions. This novel device offers a rapid, non-invasive, and efficient method to reduce unnecessary biopsies and improve breast cancer diagnostics. Further validation in larger cohorts is warranted. Full article

Lung ultrasound (LUS) has become a crucial part of the investigative tools available in the management of critically ill patients, both within the intensive care unit setting and in prehospital medicine. The increase in its application, in part driven by the COVID-19 pandemic, along with the easy access and use of mobile and handheld devices, allows for immediate access to information, reducing the need for other radiological investigations. LUS allows for the rapid and accurate diagnosis and grading of respiratory pathology, optimisation of ventilation, assessment of weaning, and monitoring of the efficacy of surfactant therapies. This, however, must occur within the framework of accreditation to ensure patient safety and prevent misinterpretation and misdiagnosis. This narrative review aims to outline the current uses of LUS within the context of published protocols, associated pathologies, LUS scoring systems, and their applications, whilst exploring more novel uses. Full article

Background and Objective: Ultrasound has become more popular and useful over the last few years in improving healthcare. While handheld devices offer portability and convenience, their diagnostic accuracy and clinical utility require further scrutiny. This study attempted to evaluate the non-inferiority of handheld portable ultrasound devices compared to standard ultrasound devices for common lung pathologies. Materials and Methods: Videos of various common lung pathologies from 20 patients were recorded by a single operator using both portable handheld and standard ultrasound devices in a single setting. These videos were then assessed via online questionnaires by clinicians of various levels of experience from respiratory and non-respiratory departments. A Likert scale was used, ranging from strongly disagree to strongly agree (ranging from 1 to 5) in terms of overall image quality, clear anatomical visualization, similar clinical interpretations/decisions, and the perception of non-inferiority. Median values with interquartile ranges were reported; a rating of 3 or above was defined as indicating non-inferiority. Results: Thirty participants completed the questionnaires, of which the majority were at trainee level (n = 20, 73%) and from a respiratory department (n = 20, 67%). The participants had mixed levels of experience in terms of the years and frequency of use of the ultrasound. Overall median ratings were 4.0 for overall image quality, clear anatomical visualization, and similar clinical interpretations/decisions, with slight variations in interquartile ranges. No significant differences were observed between subgroups. The portable ultrasound device was rated similarly for the overall perception of non-inferiority, but clinicians from respiratory departments and clinicians with less experience showed statistically significant variability in their assessments. Conclusions: The portable handheld device demonstrated potential as a reliable alternative to standard models in standard clinical settings without compromising clinical decision. Further evaluation is needed that includes a direct comparison of various types of handheld ultrasound devices, across different operators’ levels of experience, to further solidify their suitability in patient care. Full article

Breast cancer remains a leading cause of cancer-related deaths among women, emphasizing the critical need for early detection and monitoring techniques. Conventional imaging modalities such as mammography, MRI, and ultrasound have face sensitivity, specificity, cost, and patient comfort limitations. This study introduces a handheld Near-Infrared Diffuse Optical Tomography (NIR DOT) probe for breast cancer imaging. The NIRscan probe utilizes multi-wavelength light-emitting diodes (LEDs) and a linear charge-coupled device (CCD) sensor to acquire real-time optical data, reconstructing cross-sectional images of breast tissue based on scattering and absorption coefficients. With wavelengths optimized for the differential optical properties of tissue components, the probe enables functional imaging, distinguishing between healthy and malignant tissues. Clinical evaluations have demonstrated its potential for precise tumor localization and monitoring therapeutic responses, achieving a sensitivity of 94.7% and specificity of 84.2%. By incorporating machine learning algorithms and a modified diffusion equation (MDE), the system enhances the accuracy and speed of image reconstruction, supporting rapid, non-invasive diagnostics. This development represents a significant step forward in portable, cost-effective solutions for breast cancer detection, with potential applications in low-resource settings and diverse clinical environments. Full article

Point-of-care ultrasound (POCUS) has increasingly become an integral part of clinical practice, particularly in nephrology, where its use extends beyond renal assessment to include multi-organ evaluations. Despite challenges such as limited ultrasound training and equipment access, especially in low- and middle-income countries, the adoption of POCUS is steadily rising. This narrative review explores the growing role of multi-organ POCUS in nephrology, with applications ranging from the assessment of congestion phenotypes, cardiorenal syndrome, and hemodynamic acute kidney injury (AKI) to the evaluation of arteriovenous fistulas and electrolyte disorders. In nephrology, POCUS enhances clinical decision making by enabling rapid, bedside evaluations of fluid status, cardiac function, and arteriovenous access. Studies have demonstrated its utility in diagnosing and managing complications such as heart failure, cirrhosis, and volume overload in end-stage renal disease. Additionally, POCUS has proven valuable in assessing hemodynamic alterations that contribute to AKI, particularly in patients with heart failure, cirrhosis, and systemic congestion. This review highlights how integrating ultrasound techniques, including lung ultrasound, venous Doppler, and focused cardiac ultrasound, can guide fluid management and improve patient outcomes. With advancements in ultrasound technology, particularly affordable handheld devices, and the expansion of targeted training programs, the potential for POCUS to become a global standard tool in nephrology continues to grow, enabling improved care in diverse clinical settings. Full article

Medical imaging plays a pivotal role in diagnostic medicine with technologies like Magnetic Resonance Imagining (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), and ultrasound scans being widely used to assist radiologists and medical experts in reaching concrete diagnosis. Given the recent massive uplift in the storage and processing capabilities of computers, and the publicly available big data, Artificial Intelligence (AI) has also started contributing to improving diagnostic radiology. Edge computing devices and handheld gadgets can serve as useful tools to process medical data in remote areas with limited network and computational resources. In this research, the capabilities of multiple platforms are evaluated for the real-time deployment of diagnostic tools. MRI classification and segmentation applications developed in previous studies are used for testing the performance using different hardware and software configurations. Cost–benefit analysis is carried out using a workstation with a NVIDIA Graphics Processing Unit (GPU), Jetson Xavier NX, Raspberry Pi 4B, and Android phone, using MATLAB, Python, and Android Studio. The mean computational times for the classification app on the PC, Jetson Xavier NX, and Raspberry Pi are 1.2074, 3.7627, and 3.4747 s, respectively. On the low-cost Android phone, this time is observed to be 0.1068 s using the Dynamic Range Quantized TFLite version of the baseline model, with slight degradation in accuracy. For the segmentation app, the times are 1.8241, 5.2641, 6.2162, and 3.2023 s, respectively, when using JPEG inputs. The Jetson Xavier NX and Android phone stand out as the best platforms due to their compact size, fast inference times, and affordability. Full article

Background: Timely detection and aggressive management of interstitial lung disease (ILD) in systemic sclerosis (SSc) are essential to improving outcomes and reducing risks of irreversible lung injury. Objective: to explore the usefulness of an ultraportable ultrasound device for the management of SSc-related ILD and to compare it with clinical and instrumental data. Methods: A total of 19 consecutive SSc patients underwent a comprehensive pulmonary evaluation: clinical, pulmonary function tests (PFTs) (spirometry, DLCO), lung CT (1.5 mm slice thickness reconstruction; HRCT), and lung ultrasound (LUS). A total score was calculated based on the number of color-coded B-lines recorded for each lung sliding. B-lines were analyzed against dyspnea, cough, Velcro, CT imaging (Warrick’s score), and PFTs. Global and subgroup analysis were performed (diffuse versus limited cutaneous SSc, Warrick’s < 7 versus >7). Results: Symptomatic lung involvement with varying degrees of dyspnea was reported in about 74% of cases (functional NYHA > 2 in more than half), chronic dry cough in one-third, Velcro rales in 42%. A total of 84.24% were classified as SSc with ILD on CT imaging. Statistically significant mild-to-moderate correlations between B-lines and clinical manifestations were demonstrated, as well as PFTs and Warrick’s scores (more B-lines, lower pulmonary function, but higher extent and severity on CT) (p < 0.05); there were differences between SSc patients without and with ILD in terms of the number and distribution of B-lines (p < 0.05), as well as different B-lines patterns and numbers in diffuse versus limited SSc (p < 0.05). Conclusions: Ultraportable handheld LUS is a promising method suitable for the management (screening, early detection, and evaluation) of SSc patients. Full article

(1) Background: Ocular emergencies account for 1.5–3% of emergency department (ED) visits and require urgent diagnosis to prevent serious complications. Ultrasonography is a crucial, non-invasive diagnostic tool for these conditions but traditionally lacks portability and integration with modern electronic smart devices. The purpose of this study was to assess the accuracy and performance of a new handheld ultrasound device in comparison to a conventional cart-based sonographic machine in patients attending to the ED for vitreo-retinal diseases. (2) Methods: three specialists in ophthalmology, with at least 4-year experience in vitreo-retinal diseases and eye ultrasound, evaluated images of 50 eyes with both portable and traditional ultrasound probes. Each specialist made the diagnosis based on the images captured with both probes and then rated their overall image quality and confidence of diagnosis with a five-point Likert scale. The concordance of diagnosis between the two probes was evaluated. (3) Results: The sample comprised 42 patients. Twenty (40%) healthy eyes and thirty eyes with the following vitreo-retinal interface conditions were examined: 12 retinal detachment (24%), 8 vitreous hemorrhage (16%), and 10 posterior vitreous detachment (20%). The overall accuracy of the two devices appeared to be comparable (70.7% vs. 69.3%). The Butterfly iQ+ probe showed similar sensitivity in retinal detachment diagnosis (91.7% vs. 94.4% of the Accutome B-scan Pro), while it showed poor performance in diagnosing posterior vitreous detachment (sensitivity = 27.2%); (4) Conclusions: The Butterfly iQ+ device demonstrated high sensitivity in the diagnosis of retinal detachment. Significant adjustments are still needed to improve the resolution of the vitreous body. Full article

The diagnostic accuracy of handheld ultrasound (HHUS) devices operated by newly certified operators for pneumonia is unknown. This multicenter diagnostic accuracy study included patients prospectively suspected of pneumonia from February 2021 to February 2022 in four emergency departments. The index test was a 14-zone focused lung ultrasound (FLUS) examination, with consolidation with air bronchograms as diagnostic criteria for pneumonia. FLUS examinations were performed by newly certified operators using HHUS. The reference standard was computed tomography (CT) and expert diagnosis using all medical records. The sensitivity and specificity of FLUS and chest X-ray (CXR) were compared using McNemar’s test. Of the 324 scanned patients, 212 (65%) had pneumonia, according to the expert diagnosis. FLUS had a sensitivity of 31% (95% CI 26–36) and a specificity of 82% (95% CI 78–86) compared with the experts’ diagnosis. Compared with CT, FLUS had a sensitivity of 32% (95% CI 27–37) and specificity of 81% (95% CI 77–85). CXR had a sensitivity of 66% (95% CI 61–72) and a specificity of 76% (95% CI 71–81) compared with the experts’ diagnosis. Compared with CT, CXR had a sensitivity of 69% (95% CI 63–74) and a specificity of 68% (95% CI 62–72). Compared with the experts’ diagnosis and CT diagnosis, FLUS performed by newly certified operators using HHUS devices had a significantly lower sensitivity for pneumonia when compared to CXR (p < 0.001). FLUS had a significantly higher specificity than CXR using CT diagnosis as a reference standard (p = 0.02). HHUS exhibited low sensitivity for pneumonia when used by newly certified operators. Full article

Background: The HHUS market is very complex due to a multitude of equipment variants and several different device manufacturers. Only a few studies have compared different HHUS devices under clinical conditions. We conducted a comprehensive prospective observer study with a direct comparison of nine different HHUS devices in terms of B-scan quality, device handling, and software features under abdominal imaging conditions. Methods: Nine different HHUS devices (Butterfly iQ+, Clarius C3HD3, D5CL Microvue, Philips Lumify, SonoEye Chison, SonoSite iViz, Mindray TE Air, GE Vscan Air, and Youkey Q7) were used in a prospective setting by a total of 12 experienced examiners on the same subjects in each case and then assessed using a detailed questionnaire regarding B-scan quality, handling, and usability of the software. The evaluation was carried out using a point scale (5 points: very good; 1 point: insufficient). Results: In the overall evaluation, Vscan Air and SonoEye Chison achieved the best ratings. They achieved nominal ratings between “good” (4 points) and “very good” (5 points). Both devices differed significantly (p < 0.01) from the other seven devices tested. Among the HHUS devices, Clarius C3HD3 and Vscan Air achieved the best results for B-mode quality, D5CL Microvue achieved the best results for device handling, and SonoEye Chison and Vscan Air achieved the best results for software. Conclusions: This is the first comprehensive study to directly compare different HHUS devices in a head-to-head manner. While the majority of the tested devices demonstrated satisfactory performance, notable discrepancies were observed between them. In particular, the B-scan quality exhibited considerable variation, which may have implications for the clinical application of HHUS. The findings of this study can assist in the selection of an appropriate HHUS device for specific applications, considering the clinical objectives and acknowledging the inherent limitations. Full article

The popularity of handheld devices for point-of-care ultrasound (POCUS) has increased in recent years due to their portability and cost-effectiveness. However, POCUS has the drawback of lower imaging quality compared to conventional ultrasound because of hardware limitations. Improving the quality of POCUS through post-image processing would therefore be beneficial, with deep learning approaches showing promise in this regard. This review investigates the state-of-the-art progress of image enhancement using deep learning suitable for POCUS applications. A systematic search was conducted from January 2024 to February 2024 on PubMed and Scopus. From the 457 articles that were found, the full text was retrieved for 69 articles. From this selection, 15 articles were identified addressing multiple quality enhancement aspects. A disparity in the baseline performance of the low-quality input images was seen across these studies, ranging between 8.65 and 29.24 dB for the Peak Signal-to-Noise Ratio (PSNR) and between 0.03 an 0.71 for the Structural Similarity Index Measure (SSIM). In six studies, where both the PSNR and the SSIM metrics were reported for the baseline and the generated images, mean differences of 6.60 (SD ± 2.99) and 0.28 (SD ± 0.15) were observed for the PSNR and SSIM, respectively. The reported performance outcomes demonstrate the potential of deep learning-based image enhancement for POCUS. However, variability in the extent of the performance gain across datasets and articles was notable, and the heterogeneity across articles makes quantifying the exact improvements challenging. Full article