Recent advancements in medical imaging have greatly enhanced our understanding of tissue structure and disease mechanisms. Habitat imaging, which segments imaging data into distinct spatial subregions or "habitats," offers valuable insights into the heterogeneous nature of tumors, challenging traditional treatment strategies and supporting precision medicine. Super-resolution ultrasound (SRUS) has emerged as a promising tool for habitat imaging by exceeding the diffraction limits of conventional ultrasound, thus enabling visualization of microcirculation at the micron scale. Unlike MRI, CT, and PET, SRUS offers superior resolution in depicting microvascular structures, providing complementary information that enhances our understanding of tissue perfusion and microcirculatory heterogeneity. SRUS-based habitat imaging can delineate vascular habitats with high precision, supporting dynamic analysis and offering potential benefits in oncology, such as assessing tumor aggressiveness and monitoring therapeutic responses. As SRUS technology continues to mature, it is poised to become an integral part of personalized medicine, with future studies focusing on standardizing protocols and validating biomarkers to integrate SRUS into routine clinical practice.

Cervical cancer is a common gynecologic malignancy worldwide, ranking fourth for both incidence and mortality. Imaging and pathology assessments are incorporated in the revised 2018 International Federation of Gynecology and Obstetrics staging system for cervical cancer. The use of imaging techniques for pre-operative evaluation of cervical cancer has been increasing. Among imaging modalities for evaluating cervical cancer, ultrasound is more easily accessible, faster and more widely available than other options such as computed tomography or magnetic resonance imaging. Advanced technique in ultrasound, such as three-dimension ultrasound and contrast-enhanced ultrasound, have improved the clinical application of ultrasound in cervical cancer. Ultrasound may provide highly accurate information on detecting tumor presence and assessing local extent if performed by well-trained sonographers, as the experience level of readers is also critical for correct pre-operative staging and evaluation of treatment response. In the future, ultrasound imaging with the assistance of artificial intelligence will play an even greater role in management. This review aims to present the most updated applications of ultrasound in the pre-operative evaluation of cervical cancer.

The incidence rate of follicular thyroid carcinoma ranks second among thyroid malignancies. Compared to papillary thyroid carcinoma, it has higher rates of recurrence and metastasis, making it a threat to a patient's health. Unfortunately, accurately diagnosing follicular tumors before surgery remains an unresolved issue, as this type of disease is a gray area of fine-needle aspiration biopsy and can be challenging to differentiate clinically from benign thyroid follicular tumors. There are many studies have focused on the preoperative diagnosis of follicular tumors, and much progress has been made. However, according to current research, postoperative biopsies are still the only definitive ways to diagnose follicular thyroid carcinoma, providing evidence of capsule and vascular infiltration. We must emphasize the importance of early detection and diagnosis of follicular thyroid carcinoma to ensure effective treatment and recovery. This review provides a comprehensive summary of the literature on follicular thyroid carcinoma, including its epidemiology, clinical features, imaging diagnosis, genetic and molecular testing of thyroid follicular carcinoma, and a detailed description of the preoperative diagnosis of follicular thyroid carcinoma. We urge medical professionals to use this information to improve their understanding of this disease and enhance their ability to accurately diagnose and treat it.

Infectious complications are common postoperative issues after thermal ablation of liver tumors, including liver abscess, biliary tract infection, sepsis, which can significantly impact patient prognosis. Common pathogens associated with these infections include Escherichia coli, Enterococcus, Klebsiella pneumoniae, Staphylococcus aureus. Diagnosing infectious complications after ablation requires an integrated approach, combining clinical manifestations, laboratory tests, and imaging examinations. Notably, specific imaging findings may help identify liver abscess, biliary tract infection and infection secondary to gastrointestinal perforation. Risk factors for post-ablation infection include a history of biliary interventions or dysfunction of the sphincter of Oddi, prior arterial chemoembolization or transarterial radioembolization, and ablation performed at anatomically challenging sites. For high-risk patients, appropriate preventive measures should be implemented. Treatment typically involves antibiotics and catheter drainage, with commonly used antibiotics including penicillins, cephalosporins, quinolones, metronidazole. Understanding the diagnosis, risk factors, prevention, and treatment strategies for post-ablation infections is critical for optimizing patient outcomes. This review aims to summarize the current literature on infections after thermal ablation of liver tumors, detailing the common infection sites, pathogens, diagnostic approaches, prevention strategies, and treatment methods. Additionally, it explores the potential mechanisms underlying infection development after ablation.

Stroke significantly impacts national health due to its high incidence, disability, mortality, and recurrence rates, resulting in a substantial economic burden. Risk prediction models for ischemic stroke help identify high-risk populations for early prevention, diagnosis, and treatment. Various risk-scoring models have been developed for primary and secondary prevention of ischemic stroke, estimating the probability of cardiovascular events over a specified timeframe based on the presence of known risk factors. However, these risk-scoring models often lack precision for cardiovascular disease risk assessments across diverse baseline risk conditions. Integrating image-based biomarkers into existing risk-prediction models may enhance risk stratification accuracy. This review presents the most used models for ischemic stroke prediction and underscores the clinical utility of biomarkers in the management of ischemic stroke.

Heart transplantation (HT) is a definitive treatment for end-stage heart failure, significantly improving both the quality of life and survival rates of HT recipients (HTx). Speckle tracking echocardiography (STE), a key non-invasive diagnostic method, has become indispensable for providing an in-depth analysis of myocardial mechanics and function. This review focuses on the clinical utility of STE in both pre- and post-transplant settings. The ability of STE to identify subtle cardiac abnormalities and predict post-transplant outcomes underscores its critical role in the clinical management of HTx.

Objective: Simple hepatic steatosis can no longer be ignored as a "benign finding", and the management and evaluation of the clinical interventions depend on the degree of hepatic steatosis. Here, we aimed to investigate the feasibility and diagnostic performance of thermoacoustic imaging (TAI) for assessing hepatic steatosis grades in a rabbit model.

Methods: High-fat diet was used for the rabbits. To collect various degrees of hepatic steatosis, the diet duration was different (4, 8, 12, 16, 20, and 24 weeks). An in-vivo liver TAI imaging system was developed. At the end of the feed point, rabbits underwent the TAI and laparotomy for liver histopathology.

Results: We performed TAI and histopathologic examinations for 33 rabbits developing none (n = 4), mild (n = 16), moderate (n = 6), and severe (n = 7) steatosis with/without hepatic fibrosis. A strong correlation was found between the thermoacoustic fat coefficient (TAFC) derived from TAI and liver fat percentage (Pearson correlation coefficient, 0.865; P < 0.001). Besides, TAFC showed significant differences between the consecutive grades of steatosis. TAI potentially provided a good diagnostic performance, with 83% sensitivity and 100% specificity for mild steatosis, 92% sensitivity and 95% specificity for moderated steatosis, and 100% sensitivity and 92% specificity for severe steatosis. The fibrosis stage did not significantly affect the TAFC.

Conclusion: Our findings demonstrate that TAI is a promising way to evaluate hepatic steatosis grades.

Rheumatoid arthritis (RA) stands as a prevalent chronic autoimmune condition globally. Although conventional disease-modifying antirheumatic drugs (DMARDs) offer relief from systemic inflammation, they frequently entail undesirable side effects. Phototherapy, encompassing both photodynamic therapy (PDT) and sonodynamic therapy (SDT), employs light and low-frequency ultrasound irradiation to generate reactive oxygen species (ROS), thereby inducing apoptosis in RA inflammatory cells and reducing cytokine expression. This approach presents a promising alternative for RA management. Recently, a range of nanomaterials that induce PDT or SDT have been developed, yielding promising outcomes in arthritis suppression. This review outlines the latest advancements in PDT/SDT-based nanomedicine for RA treatment.

Purpose: Early diagnosis and treatment of non-alcoholic fatty pancreatic disease (NAFPD) can effectively intervene in the development of type 2 diabetes. This study aimed to evaluate the utility of an improved ultrasound method for diagnosing NAFPD.

Methods: All patients underwent abdominal ultrasonography (US) and magnetic resonance imaging (MRI) mDixon-Quant technique. Patients with a pancreatic fat fraction (PFF) > 6.2% were in the NAFPD group (NA) and the rest were in the normal group (NC). MRI mDixon-Quant technique was used to evaluate the diagnostic efficiency of NAFPD with improved ultrasound diagnosis.

Results: This study included 46 participants. The MRI mDixon-Quant had good repeatability and reproducibility in measuring PFF. The kappa value of the improved version ultrasound (IVUS) method and MRI diagnosis was 0.760 (95% confidence interval [CI] = 0.662-0.858, P < 0.001). That of traditional version ultrasound (TVUS) and MRI diagnosis was 0.497 (P < 0.001). Statistical analyses revealed that pancreatic grading based on both ultrasound evaluation methods correlated with PFF, with IVUS (R² = 0.812) superior to TVUS (R² = 0.496). Body weight, body mass index, triglyceride level, abdominal circumference, abdominal visceral fat, total abdominal fat, abdominal visceral fat area, and liver fat content were significantly higher in the NA versus NC group (P < 0.05). Fat fractions of the pancreatic head, body, and tail in the NA group were significantly higher than those in the NC group (P < 0.05).

Conclusion: IVUS more consistently predicts NAFPD and correlates better with MRI than TVUS.

Cancer, one of the leading causes of global mortality, arises from dysregulated cellular processes that create an immunosuppressive tumor microenvironment (TME), promoting immune evasion and therapeutic resistance. While immunotherapy activates the immune system to combat tumors and provide durable benefits, its efficacy is often constrained by the hostile TME. Focused ultrasound (FUS) has emerged as a non-invasive, and precise therapeutic modality capable of mechanically or thermally ablating solid tumors. This review discusses the dual mechanisms of FUS—thermal ablation (T-HIFU) and mechanical disruption (M-HIFU, e.g., histotripsy)—and their role in modulating the TME. Specifically, it examines how FUS-induced immune activation can overcome immunosuppressive barriers, promote T-cell infiltration, and synergize with immunotherapy to improve outcomes in solid tumors, while also highlighting current challenges and future directions.

Photoacoustic imaging (PAI) is a functional optical imaging modality that utilizes ultrasound as a medium. Owing to its high contrast in optical imaging and deep tissue penetration capabilities inherent in ultrasound, PAI can generate images that integrate both structural and functional information. It has emerged as a novel medical imaging tool, with ongoing research continually expanding its applications within the medical field. The integration of photoacoustic imaging with other modalities to create multimodal imaging systems allows for the synergistic advantages of various technologies, thereby providing more comprehensive diagnostic information. PAI facilitates early and precise diagnosis as well as treatment monitoring for diverse conditions such as tumors, inflammation, and skeletal muscle injuries through real-time quantitative analysis of deoxyhemoglobin levels and molecular markers. This article elucidates the principles of PAI, its various modes of operation, and clinical applications while also anticipating future developmental prospects.

Glomus tumor is a benign, subcutaneous neoplasm that typically arises in regions abundant in glomus bodies, manifesting as a painful nodule. Currently, perineal glomus tumors are rarely reported in the literature. Herein, we present a unique case of glomus tumor originating in the perineal region. Ultrasound examination revealed a heterogeneous mass within the subcutaneous soft tissue layer of the vulva, featuring a distinct boundary and peripheral blood flow signals. The ultrasound contrast imaging of this mass demonstrated rapid peripheral ring enhancement during the arterial phase, followed by a gradual inward perfusion from the periphery towards the center of the nodule-like or branching-like structure, exhibiting concentric enhancement. The internal portion of the nodule showed low enhancement, which progressively diminished during the venous and delayed phases. Subsequently, an ultrasound-guided biopsy confirmed the diagnosis of glomus tumor, and the patient underwent successful surgical treatment.

Irreversible electroporation (IRE) is an innovative non-thermal ablation technique increasingly utilized in cancer treatment due to its unique operational principles and clinical advantages. As a novel interventional ultrasound technology, IRE has undergone extensive research, development, and practical application over the years. IRE ablation, particularly in conjunction with immunotherapy, has emerged as a significant modality in cancer treatment and related fields. This article aims to present the advancements in irreversible electroporation ablation for cancer through an examination of both basic research and clinical applications.

Objective: To investigate the ultrasonographic characteristics and outcomes of fetal umbilical-portal-systemic venous shunts (UPSVS).

Methods: UPSVS cases at a single center between January 2015 and December 2022 were retrospectively investigated. The ultrasonographic features, types, and postnatal outcomes of fetal UPSVS were analyzed and the outcomes were followed up on. The study was approved by our institutional review board (Approval Number KY2021130).

Results: Forty UPSVS cases, including 4 Type I, 18 Type II, and 18 Type III (16 with IIIa and 2 with IIIb) were identified. Two Type I cases were terminated because of the complete absence of the portal venous (PV) system. Genetic assessment revealed that one patient with Type I had a q22.11 deletion in trisomy 21. Type II is characterized by structural malformations, particularly cardiovascular abnormalities. Couples opted for pregnancy termination in four cases of Type II. The most common anomaly in Type III shunts was cardiac enlargement, followed by fetal growth restriction. Pregnancy was terminated in six cases of Type IIIa as requested by the couples, one resulting from premature birth, and two because of the completely absent PV system. Genetic tests showed that trisomy X had a microduplication in one patient. The shunt spontaneously closed after birth in all Type IIIa cases.

Conclusions: Prenatal diagnosis of UPSVS using ultrasonography is feasible and valuable for perinatal management and prenatal consultation. The fetal postnatal prognosis is determined by the presence of anomalies in the PV system, genetics, or structure.

Objective: Non-alcoholic fatty liver disease (NAFLD) is a chronic liver disease with a high incidence worldwide, and its incidence is increasing year by year. Plasma atherogenic Index (AIP) is used to assess the risk of cardiovascular disease and metabolic dysfunction, and albumin to glutamyltransferase ratio (AGR) is often used to assess liver function, nutritional status, and immune system diseases. This study aimed to assess the association of AIP, AGR and non-alcoholic fatty liver disease and to establish a practical and cost-effective prediction model.

Methods: Using data from the National Health and Nutrition Examination Survey (NHANES) from March 2017 to March 2020, residents 18 years of age and older with complete demographic, laboratory, and instantaneous elastography test data were included. SPSS 27.0 and R 4.4.0 were used to analyze the data, single-factor Logistic regression analysis was applied to screen the influencing factors of NAFLD, stepwise regression was applied to screen the variables, and multi-factor Logistic regression was performed to construct the prediction model and draw the column graph.

Results: AIP (OR = 3.549, 95% CI: 1.876-6.712) was a risk factor for NAFLD, and AGR (OR = 0.782, 95% CI: 0.655-0.934) was a protective factor for NAFLD. The calibration curve of NAFLD was stable, and the ROC curve AUC was 0.859.

Conclusion: AIP is an independent risk factor for NFLAD. AGR is an independent protective factor for NAFLD

Tietze syndrome which refers to painful non-purulent inflammation of the costal cartilage or sternoclavicular joint is a rare disease that is poorly reported. We report a case of Tietze syndrome in a 52-year-old female with sternoclavicular joint pain and chest wall mass post-COVID-19 virus infection. She suffered pain and swelling in the left sternoclavicular joint, which were relieved after hot compress. This case is the first report on Tietze syndrome post-COVID-19 virus infection in China. We report this case to improve our understanding of this disease and discuss possible mechanism from the perspective of embryology and pathology.

Objective: This study investigates the correlation between early B-type natriuretic peptide (BNP) levels and ultrasound hemodynamics following liver transplantation, with the aim of evaluating short-term prognosis.

Methods: We analyzed data from 924 patients who underwent liver transplantation between December 2012 and October 2022. Ustilizing the clinical liver transplantation ultrasound imaging database software V1.0 developed by Tianjin First Central Hospital, we recorded various ultrasonic dynamic parameters, including peak systolic velocity (PSV), end-diastolic velocity (EDV), peak systolic/diastolic flow velocity (S/D), resistance index (RI), pulsatility index (PI), and portal vein velocity (PVV). Additionally, BNP values were recorded within 24 hours post-surgery. We analyzed the correlation between ultrasound blood flow parameters and BNP levels. Patients were categorized into death and survival groups based on their prognosis at 3 months, and differences in blood flow parameters were compared between these groups. Furthermore, short-term prognosis was assessed based on blood flow parameters associated with diastolic blood flow.

Results: Negative correlations were observed between BNP and the resistance index (RI) and pulsatility index (PI) on the first day after surgery (r = -0.473, r = -0.602, both P < 0.05). Similar correlations were found on the fifth day post-surgery (r = -0.406, r = -0.518, both P < 0.05). Additionally, peak systolic velocity (PSV), end diastolic velocity (EDV), and BNP levels were significantly higher in the death group compared to the survival group on both the first and fifth days after surgery (all P < 0.05), while RI and PI were lower in the death group (both P < 0.05). The systolic/diastolic (S/D) ratio in the death group was also lower than that in the survival group on the first and fifth days post-surgery (both P = 0.001). Furthermore, the presence of early diastolic blood flow after surgery was not associated with short-term prognosis in either group (both P > 0.05).

Conclusion: Early BNP levels correlate with ultrasound blood flow parameters following liver transplantation, providing a foundation for evaluating cirrhotic cardiomyopathy. Patients with a poor short-term prognosis exhibit elevated BNP levels, altered dynamic circulation, and low-resistance blood flow

Biomedical ultrasound imaging, as one of the most common, safe, and cost-effective modalities in clinical diagnosis, witnesses remarkable progress with the integration of artificial intelligence (AI). Early studies based on traditional machine learning (ML) rely on handcrafted features and classical classifiers to achieve automatic recognition and quantitative analysis of ultrasound images. However, such methods are limited in feature representation capacity and generalizability. With the advent of deep learning (DL), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and attention-based architectures are widely applied to tasks such as segmentation, detection, and lesion classification, significantly improving diagnostic accuracy and robustness. More recently, large language models (LLMs) and multimodal foundation models open new avenues for intelligent ultrasound analysis. These models not only integrate imaging and textual information to support automated report generation and cross-modal reasoning but also offer enhanced interpretability and greater potential for clinical adoption. In this review, we provide a systematic review of the evolution of AI in ultrasound image analysis, spanning from traditional ML to deep learning and LLMs, outlining a complete trajectory of methodological advances.

Ultrasound medicine is an interdisciplinary field that integrates ultrasonics and medicine, encompassing the applications of ultrasound in medical diagnosis, therapy, and basic research. While classical acoustic theories and technologies have reached a developmental bottleneck, their convergence with physics, artificial intelligence (AI), and related advanced technologies has spawned a dynamic research landscape defined by ultra-microscale precision and extreme interdisciplinarity. This paper presents a comprehensive systematic review of sound field modulation theories and their cutting-edge advances in ultra-microscale and highly interdisciplinary biological research. Leveraging acoustic metamaterials, microbubble dynamics, and acoustic streaming coupling effects, breakthroughs have been achieved in deep subwavelength diffraction imaging and precise nanoscale/microscale manipulation at extreme deep subwavelength resolutions. These innovations are fueling biophysical revolutions—including mechanical loading of biomolecules and regulation of ion channel proteins—while enabling breakthroughs in emerging technologies such as sonogenetics and non-invasive ultrasound-based brain-computer interfaces (BCIs). In the future, acoustics is poised to generate disruptive technologies in areas such as artificial structures and devices, non-invasive BCIs, cell and molecular regulation, micro- and nano-imaging/manipulation, and targeted drug delivery. Its unique characteristics—wavelength tunability and cross-scale integration—will continue to drive the deep fusion of physics, biology, and information science, fostering unexploited interdisciplinary synergy.

Ultrasound is one of the most commonly used imaging modalities for the screening and diagnosis of liver nodules. However, its diagnostic accuracy is highly dependent on operator expertise, and atypical or small lesions are prone to missed diagnosis or misdiagnosis. In recent years, artificial intelligence (AI) has achieved remarkable progress in medical image analysis, offering novel solutions to improve the objectivity, accuracy, and efficiency of liver ultrasound diagnosis. This review systematically summarizes the current status and advances of AI in the ultrasound diagnosis of liver nodules, with a focus on B-mode and contrast-enhanced ultrasound (CEUS). We detail AI applications in automatic nodule detection and localization, benign–malignant differentiation, multi-class classification (e.g., hepatocellular carcinoma [HCC], cholangiocarcinoma [CCA], hemangioma [HH], metastasis [HM]), and prediction of key pathological biomarkers (e.g., microvascular invasion [MVI], pathological grading, Ki-67, vessels encapsulating tumor clusters [VETC]), analyzes the current research status and summarizes the main limitations of existing studies. By reviewing methodological characteristics such as cohort size, validation strategies, and machine learning algorithms, this paper provides insights into future research directions and promotes the development of clinically translatable AI models, with the ultimate goal of advancing standardization and broad clinical adoption of AI-assisted diagnosis in liver ultrasound.

Objective It is always a clinical challenge to identify neonatal pulmonary hypertension (NPH). Although the diagnostic gold standard of pulmonary hypertension (PH) is the true measurement of resting pulmonary arterial pressure (PAP) through cardiac catheterization, it is inappropriate for delicate newborns. Hence, echocardiography examination has become the most common inspection tool for NPH despite its limitations.
Methods After outlining the conventional echocardiographic parameters for detecting NPH and their drawbacks in newborns, this review mainly discussed the roles of two-dimensional speckle tracking echocardiography, including RV global longitudinal strain and segmental longitudinal strain, in the evaluation of NPH, hoping to provide more information for detecting NPH.
Results When combined with conventional echocardiographic parameters, RV longitudinal strain would be a great help for the evaluation of NPH. Furthermore, based on the preliminary research, our finding revealed that the magnitude of the apical segmental strain of RVFW was significantly lower, and the basal-to-apical strain ratio (Ratio bas/api) of RVFW was remarkably higher in infants with PH than those without PH.
Conclusion Based on the particularity of newborns, neonatal echocardiography is the preferred inspection method for NPH. It provides hemodynamic, morphological and functional information for evaluating NPH. RV longitudinal strain is sensitive to subtle changes of RV function and closely related to PH. It could be considered not only as the key factor affecting the prognosis of NPH but also as a potential index to detect and identify NPH.

In the last twenty years, there were less than 10 cases of umbilical arteriovenous malformations have been reported, which usually had single complication, included mild cardiac dilatation, pulmonary hypertension, hemorrhagic shock, and hepatic damage. Unlike previous cases, we report a case of neonate multiple organ failure caused by umbilical arteriovenous malformation complicated with portosystemic shunt, which was diagnosed by ultrasound and arteriography. We provide a new insight that umbilical arteriovenous malformation and portosystemic shunt should be considered in neonates with unexplained multiple organ failure, for researching the cause of neonate multiple organ failure, especially in those with right heart overload, hyperammonemia, and liver dysfunction. A targeted and comprehensive Dopler ultrasound can make a definitive diagnosis as soon as possible.

Pulsed field ablation (PFA), a non-thermal ablation technique that induces cell death via irreversible electroporation, has emerged as a promising therapeutic strategy for treating tumors located in anatomically complex regions. This review comprehensively examines recent developments in PFA, including its mechanisms foundations, established clinical applications in pancreatic, prostate and liver cancer, and expanding utility with other tumors, etc. Furthermore, we discuss synergistic approaches combining PFA with chemotherapy, immunotherapy, surgery and radiotherapy to augment therapeutic outcomes. In addition, technological innovations—such as robotic assistance, magnetic anchoring, and artificial intelligence—that improve precision and reproducibility are also explored. Despite encouraging clinical results, broader implementation of PFA necessitates higher-quality evidence from large-scale randomized trials and standardized treatment protocols. This review highlights the transformative potential of PFA in oncology while addressing contemporary challenges and future research directions to facilitate clinical translation.

Recent advancements in artificial intelligence (AI) have generated novel opportunities and challenges in ultrasound imaging. Deep learning algorithms exhibit significant potential in analyzing echocardiographic images, encompassing tasks such as view classification, quantification of cardiac function, and the diagnosis and risk assessment of cardiac diseases. The “black box” nature of AI models limits their clinical applications. Adopting explainable artificial intelligence (XAI) methods is crucial for improving the transparency and understanding of model predictions. This paper reviews the progress of AI applications in echocardiography, with a particular emphasis on XAI as a technical solution to enhance the transparency of model decision-making and its benefits compared to traditional AI models. This review outlines recent advancements in XAI applications for echocardiography and their clinical implications.

This pictorial review summarizes the Contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) Treatment Response Algorithm (LR-TR, v2024) for response assessment after nonradiation locoregional therapies (NLT). The NLT covered by LR-TR v2024 includes embolization procedures such as conventional transarterial chemoembolization (cTACE), drug-eluting bead TACE (DEB-TACE), and bland transarterial embolization (TAE), as well as ablation techniques such as radiofrequency ablation (RFA), microwave ablation (MWA), and percutaneous ethanol injection (PEI). The algorithm independently evaluates intralesional and perilesional viability, using arterial-phase enhancement as the dominant criteria for intralesional evaluation and multiphasic enhancement (arterial, portal, and late phases) for perilesional evaluation. The results are then integrated into three standardized response categories, including LR-TR Viable, Equivocal, or Nonviable. Evidence from multicenter studies in hepatocellular carcinoma (HCC) indicates that CEUS LR-TR v2024 provides high reliability and strong reproducibility in detecting residual viable tumor following NLT. This review provides representative imaging features and interpretation tips to familiarize physicians with CEUS LR-TR v2024, aiming to improve accuracy in treatment response assessment (TRA) in HCC and facilitate timely therapeutic adjustments that ultimately benefits patients.

Multimodal ultrasound, including B-mode imaging, contrast-enhanced ultrasound (CEUS), and ultrasound-based elastography, has demonstrated significant value in evaluating both diffuse liver diseases such as fibrosis and steatosis, and focal liver lesions such as hepatocellular carcinoma (HCC). Radiomics, including both handcrafted radiomics and deep learning approaches, has emerged as a promising strategy to enhance ultrasound-based liver disease assessment. Recent studies have applied radiomics across multimodal ultrasound, achieving notable success in grading fatty liver disease, staging fibrosis, and improving diagnosis, risk stratification, and prognostic prediction in HCC. Multimodal ultrasound provides complementary information on liver morphology, perfusion, and stiffness, while fusion strategies further enhance diagnostic accuracy and robustness. Future efforts should focus on standardized, large-scale multicenter validation, methodological improvements in multimodal integration, and the incorporation of explainable artificial intelligence to support clinical translation. Ultimately, despite ongoing challenges related to data heterogeneity, reproducibility, interpretability, and clinical validation, multimodal ultrasound radiomics holds strong promise for noninvasive, individualized, and clinically meaningful liver disease management.

Objective To improve infant outcomes and guide treatment decisions, early and accurate diagnosis of congenital abnormalities during pregnancy is crucial. Despite its excellent accuracy, chorionic villus sampling (CVS) has procedural dangers; sonography offers a non-invasive, safer substitute. With an emphasis on clinical value, safety, and diagnostic accuracy, this evaluation assesses how well sonography performs in identifying congenital diseases prior to 12 weeks of gestation when compared to CVS.
Methods A comprehensive review of the literature was conducted using databases such as Web of Science, PubMed, and Scopus. Studies published between 2015 and 2024 that examined the diagnostic sensitivity, specificity, and accuracy of sonography and CVS for congenital illness identification were included.
Results With a sensitivity of 85-90%, sonography shows excellent accuracy in identifying anatomical abnormalities such organ malformations and nuchal translucency. Although CVS has a 0.5-1% chance of miscarriage, it is still the gold standard for identifying chromosomal abnormalities with an accuracy of around 99%. Combining the two modalities reduces hazards while improving diagnostic accuracy.
Conclusion For low-risk populations in particular, sonography provides a dependable, non-invasive screening method for congenital abnormalities prior to 12 weeks. For high-risk instances that need genetic investigation, CVS is advised. Integration of both approaches could optimize prenatal diagnostic protocols.

Ultrasound localization microscopy (ULM) is an ultrasound technique capable of overcoming the acoustic diffraction limit to achieve super resolution imaging of microvasculature, simultaneously balancing imaging depth and resolution. Abdominal organs are rich in microvasculature, and pathological processes in these organs are often accompanied by microvascular alterations, such as in tumors, chronic liver and kidney diseases, and allograft. Therefore, for abdominal organs, ULM represents a promising tool for aiding disease diagnosis and monitoring. Currently, an increasing number of studies are exploring the preclinical and clinical applications of ULM in both healthy and diseased abdominal organs. This paper aims to provide a systematic review of ULM applications in abdominal organs, while briefly discussing its limitations and future prospects.

Objective To compare fetal cardiac morphology and function between small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) fetuses using two-dimensional speckle-tracking echocardiography (2D-STE), and to evaluate global longitudinal strain (GLS), global sphericity index (GSI), and fractional area change (FAC) in both ventricles with FetalHQ software.
Methods This cross-sectional observational study included 101 pregnant women, comprising 36 with SGA and 65 with AGA fetuses. Five- to fifteen-second four-chamber view (4CV) cine loops of the fetal heart were acquired and analysed using fetal heart quantification and speckle tracking (FetalHQ) software. GLS, GSI, and FAC of both left ventricle (LV) and right ventricle (RV) were measured.
Results SGA fetuses demonstrated significantly lower GSI values, consistent with a more globular cardiac shape. LV-FAC and RV-FAC were significantly lower in SGA compared with AGA fetuses, reflecting impaired systolic function. Both LV-GLS and RV-GLS values were significantly higher (less negative) in the SGA group, indicating early biventricular systolic dysfunction. These findings align with previously reported adaptive responses of the fetal myocardium to chronic hypoxia.
Conclusion The study highlights distinct alterations in fetal cardiac morphology and function between SGA and AGA groups. FetalHQ-based deformation analysis may potentially detect subclinical biventricular dysfunction in SGA fetuses before Doppler abnormalities become apparent, offering potential for earlier clinical intervention and closer monitoring.

Recent advancements in ultrasound technology have revolutionized both medical imaging and therapeutic applications. Among these, volumetric imaging using two-dimensional (2D) array ultrasound transducers has emerged as a powerful tool, enabling real-time three-dimensional (3D) visualization, which is also referred to as four-dimensional (4D) imaging. 4D ultrasound imaging represents the most advanced diagnostic technique in ultrasound and is considered one of the most essential tools for medical diagnostics, particularly for assessing blood flow in micro-sized blood vessels. Due to its real-time and volumetric imaging capabilities, 4D imaging offers a unique advantage for the early diagnosis of cardiovascular and cerebrovascular diseases. The row-column-addressed (RCA) array is a novel 2D ultrasound transducer designed for ultrafast 3D ultrasonic imaging. Compared to traditional fully-sampled 2D matrix arrays, RCA transducers reduce the number of electronic channels from M×N to M+N, thereby significantly lowering hardware costs and manufacturing complexity. This review explores the design, fabrication, and clinical applications of 2D arrays, including both fully-sampled 2D arrays and RCA arrays. We discuss their roles in cardiology, brain imaging, and interventional procedures, while also addressing current challenges and future developments in the field.

Early detection of hepatocellular carcinoma (HCC) is crucial, as patient outcomes depend largely on clinical stage and treatment options at diagnosis. Currently most clinical guidelines emphasize non-invasive cross-sectional imaging for HCC diagnosis and evaluation, yet the full potential of ultrasound is often underexplored. With the development of emerging ultrasound techniques and diagnostic algorithms in recent years, the diagnostic ability of ultrasound for HCC smaller than 3 cm has been substantially improved and is increasingly emphasized in the management of small HCC. Following sequential clinical scenarios, this review discusses the state-of-the-art of ultrasound-related techniques and algorithms for preoperative screening and diagnosis, intraoperative guidance and monitoring as well as posttreatment efficacy evaluation of small HCC. By highlighting how advanced ultrasound complements and enhances standard practices, this review aims to promote ultrasound as an indispensable, versatile, and dynamic tool in the precision management of small HCC.

In recent years, dermatological ultrasound has made significant breakthroughs in the research and application of dermatology by virtue of its advantages of non-invasive, real-time imaging and high resolution. The increase of ultrasonic probe frequency makes it possible to visualize the skin structure. Different frequencies of high frequency or ultra-high-frequency ultrasound can realize different degrees of presentation of the fine structure of epidermis, dermis and subcutaneous layer. The wide range of application of shear wave elastography provides a new ultrasonic evaluation index for skin diseases represented by scleroderma. This review provides a detailed summary of the latest application progress and research frontiers of ultrasound in different skin diseases. It includes the diagnosis and efficacy evaluation of scleroderma, the diagnosis and activity evaluation of psoriasis, the diagnosis and follow-up of nevus punctatum, the differentiation of benign and malignant skin tumors, the evaluation of pathological scar, the application in the field of aesthetic medicine, and the evaluation of other common skin diseases. In the future, dermatological ultrasound is expected to play a more important role in accurate classification of diseases and prognosis prediction with the further innovation of equipment and the deep exploration of skin diseases.

Objective Plantar fascia (PF) is a thick connective tissue on the plantar surface of the foot that plays a crucial role in maintaining the longitudinal arch. Plantar fasciitis, characterized by inflammation of the medial tuberosity of the calcaneus, is one of the most common causes of heel pain. Imaging is essential for accurate diagnosis, with ultrasonography widely applied to evaluate PF thickness, monitor therapeutic outcomes, and guide interventions. However, its application is limited by operator dependency. This study aimed to investigate the inter- and intra-rater reliability of musculoskeletal ultrasound in measuring PF thickness in patients with plantar fasciitis.
Methods In this cross-sectional analytical study, 40 participants were enrolled, including 26 females and 14 males. The reliability of PF measurements on different sides was assessed using Cronbach’s alpha and intraclass correlation coefficients (ICC).
Results A total of 40 participants (age range: 20-60 years) were included in the study. PF thickness in patients with plantar fasciitis measured by Observer 1 ranged from 3.8-6.9 mm (left) and 3.2-6.0 mm (right), whereas measurements by Observer 2 ranged from 2.9-7.1 mm (left) and 3.2-6.0 mm (right). Intra-rater reliability showed ICCs ranging from 0.618-0.857 for Observer 1 and 0.76-0.92 for Observer 2, indicating moderate (> 0.60) to excellent reliability.
Conclusion PF is a deep structure, and its visualization may be influenced by operator technique. Ultrasound measurement of tendon thickness shows good reliability in patients with established plantar fasciitis.

Objectives Conventional ultrasound (US) elastography lacks specificity in distinguishing benign from malignant breast lesions. This study employed US to assess breast tissue viscosity and elasticity. The primary objective was to evaluate the diagnostic performance of US-derived viscoelasticity parameters. Secondary objectives included investigating the consistency of parameters in the mechanical properties of breast tissue.
Materials and methods Two doctors independently measured the viscosity and elasticity of specific positions in the breasts of 20 health females for consistency assessment. Then the doctors selected region of interest (ROI) to measure viscoelasticity. ROI-1, ROI-2, and ROI-3 represent the tumor, peritumoral, and peripheral areas, respectively. The viscosity modulus and elasticity modulus of 3 ROIs were analyzed. The viscosity and elasticity parameters with the highest area under the curve (AUC) were selected as the optimal ones. Finally, elasticity and viscosity parameters were combined to assess their diagnostic performance in differentiating breast lesions.
Results US viscoelasticity parameters can be measured with high consistency. Among conventional US elasticity parameters, 1-Emax demonstrated the highest AUC (0.746) for differentiating benign and malignant breast lesions. In US viscoelasticity parameters, 2-Emax achieved the highest AUC of 0.801, while 2-Vmax showed the highest AUC of 0.835. The highest specificity (0.903) was observed when both 2-Emax and 2-Vmax exceeded their respective cutoff values (P < 0.05 for all).
Conclusion Quantitative ultrasound viscoelasticity parameters play a crucial role in breast cancer diagnosis, with tumor boundary parameters being particularly significant for cancer screening and prevention strategies.

Objective Uterine and ovarian development is influenced by both age and hormonal milieu. Sonographic assessment of normal pubertal and pre-puberty girls provides critical insights into the physiological trajectory of female gonadal maturation and its potential pathological deviations.
Methods This was a cross-sectional study conducted at Gilani Ultrasound Center, Lahore, Pakistan. The duration of the study was 9 months. Uterus length, width, height, volume, right/left ovary volume and Fundo/Cervical ratio were measured.
Results A total of 384 subjects were included in our study, categorizing them into pre-puberty (age 2-6 years), early puberty (age 7-11 years), and late puberty (age 12-18 years) groups. In the pre-puberty group (n = 111, mean age 4.29 ± 1.20 years), uterine measurements revealed a mean length of 2.95 cm, height of 0.97 cm, width of 1.41 cm, and volume of 4.82 cm³. The mean volumes of the right and left ovaries were 1.24 cm³ and 1.10 cm³, respectively, with a mean F/C ratio of 1.33. For the early puberty group (n = 99, mean age 9.15 ± 1.45 years), uterine measurements included a mean length of 4.03 cm, height of 1.22 cm, width of 1.80 cm, and volume of 12.37 cm³. In the late puberty group (n = 31, mean age 12.63 ± 1.21 years), uterine measurements showed a mean length of 5.29 cm, height of 1.82 cm, width of 2.65 cm, and volume of 31.11 cm³. The mean volumes of the right and left ovaries were 4.70 cm³ and 5.26 cm³, respectively, with a mean F/C ratio of 1.26.
Conclusion Uterine and ovarian dimensions, including volumes, correlate directly with age and pubertal status, except for the (Fundus/Cervical) ratio, which shows individual variability. This normative data could serve as a basis for the evaluation of Uterine and ovarian dimensions and volume in the local population.

Photoacoustic-ultrasound (PA/US) fusion imaging is an emerging dual-modality technique that integrates the high optical contrast of photoacoustic imaging (PAI, also referred to as optoacoustic imaging or photoacoustic tomography) with the anatomical resolution of US. This review summarizes the principles, technical advances, and clinical applications of PA/US in breast cancer diagnosis and therapy. Recent studies demonstrate that PA/US markedly improves diagnostic specificity while maintaining high sensitivity, particularly in differentiating benign from malignant lesions, predicting molecular subtypes, and monitoring therapeutic response. Radiomics and artificial intelligence further enhance the interpretive power of PA/US, enabling functional phenotyping, Ki-67 expression prediction, and axillary lymph node (ALN) metastasis risk assessment. Moreover, multicenter clinical trials, such as the PIONEER study, have validated the clinical feasibility of PA/US, reducing unnecessary biopsies and refining BI-RADS categorization. Despite challenges in system standardization, quantitative accuracy, and large-scale validation, PA/US holds promise as the “fourth major breast imaging modality,” complementing mammography, US, and MRI. With continued progress in AI integration, standardized protocols, and policy recognition, PA/US is expected to achieve routine clinical implementation in the next 5-10 years, supporting individualized breast cancer diagnosis and precision oncology.

Objective Aortic stenosis (AS), a prevalent valvular disease, demands accurate diagnosis. Current methods, notably Doppler echocardiography, face limitations like dynamic image challenges and reliance on cardiologist experience. To assess aortic stenosis, measuring the LVOT diameter is critical, as a 1 mm difference can result in a 10% variation in stroke volume. Accurate Doppler beam alignment and LVOT VTI measurement are also essential to avoid errors. Our study, utilizing the TMED 2 dataset, introduces a novel artificial intelligence program for precise aortic stenosis diagnosis. By leveraging AI, we aim to overcome existing constraints and significantly enhance diagnostic accuracy.
Methods a novel method that involves using convolutional neural networks (CNNs), were used to grade AS based on various views of transthoracic echocardiography (TTE) images from the TMED 2 dataset. This innovative method aimed to take advantage of CNN’s abilities to recognize detailed patterns in echocardiographic data, making AS diagnosis more accurate. We evaluated the performance of our CNN models using confusion metrics and the area under the receiver operator curve (AUROC).
Results Our CNN networks were trained on a dataset comprising view_and_diagnosis_labeled_set, which included 599 studies from 577 unique patients (some with multiple studies on distinct days). For classification, we chose three classes: no aortic stenosis, aortic stenosis, and mild aortic stenosis. The detection of aortic stenosis achieved an accuracy of 85.74%. External validation using three views (PLAX, PSAX, and A4C) of outpatient transthoracic echocardiograms demonstrated effective screening for AS, yielding respective AUROCs of 0.81, 0.88, and 0.48.
Conclusion Our novel CNN-based approach achieved an 85,74% accuracy in AS detection using diverse views from the TMED 2 dataset. External validation on outpatient echocardiograms demonstrated robust screening capabilities, with AUROCs of 0.81, 0.88, and 0.48 for PLAX, PSAX, and A4C views, respectively. These promising results suggest the potential of AI in improving AS diagnosis for clinical applications. Moving forward, our future endeavors will focus on addressing data imbalances and detecting the view of images, in addition to assessing the severity of aortic stenosis, to further refine and optimize our diagnostic approach.

Artificial Intelligence (AI) technology has made remarkable progress in fetal ultrasound examinations, particularly excelling in fetal growth monitoring, organ function assessment, and early disease diagnosis. By automating the analysis of fetal ultrasound images, AI can accurately measure fetal biometric parameters and assist in diagnosing issues such as fetal growth restriction and organ developmental abnormalities. It demonstrates significant application potential in evaluating multiple organ systems including the fetal lungs, nervous system, cardiovascular system, and placenta, substantially enhancing the efficiency and accuracy of prenatal screening. This paper aims to review the current status of AI applications in obstetric ultrasound, while also exploring its limitations and future prospects.

Gastroparesis (GP) is a gastric motility disorder characterized by delayed gastric emptying in the absence of mechanical obstruction. This expert consensus covers aspects of GP etiology (diabetes, surgery, drug-induced, idiopathic, scleroderma, etc.), symptomatology, diagnosis (scintigraphic imaging, ultrasound contrast meal assessment, and radiopaque marker gastric motility testing), and treatment (pharmacological therapy, nutritional support, traditional Chinese medicine, and interventions targeting the pylorus, such as endoscopic surgery and surgical procedures). GP significantly impacts patients' psychological well-being and quality of life, potentially leading to psychological disorders such as anxiety and depression, and also imposes a heavy economic burden on patients and society. Therefore, this expert consensus advocates for the establishment of a multidisciplinary team diagnosis and treatment model, which will further standardize and optimize the diagnosis and treatment process of GP in our country and is crucial for improving patients' therapeutic outcomes and quality of life.