Objective To analyze the efficacy of different needle insertion paths for ultrasound-guided small needle knife treatment of carpal tunnel syndrome (CTS). Methods A total of 204 patients with CTS admitted to Sichuan Orthopedic Hospital were included from February 2021 to May 2023. According to the random number table method, 204 patients were equally divided into 4 groups (each n=51). All the four groups were treated with carpal tunnel corticosteroid injection under ultrasound guidance. On this basis, group A underwent small needle knife release through ulnar lateral approach of palmaris longus tendon, and group B received small needle knife treatment through wrist transverse crease-metacarpal bone specific fixed-point approach, and group C underwent small needle knife treatment through four attachment point release approach of transverse carpal ligament, and group D received carpal tunnel corticosteroid injection as routine control group. The changes of pain degree [Visual Analogue Scale (VAS)], disease symptoms [Boston Carpal Tunnel Questionnaire (BCTQ)], neuroelectrophysiological parameters [median nerve motor conduction velocity (MCV), distal motor latency (DML), sensory conduction velocity (SCV)] and joint function [wrist range of motion (ROM), grip strength] before and after treatment, treatment duration, treatment cost and occurrence of adverse reactions during treatment were compared among the four groups of patients. Results At 1, 3 and 6 months after treatment, the VAS, SSS and FSS scores and DML in all four groups were reduced compared to before treatment, and groups A, B and C showed lower values than group D (P<0.05). MCV, SCV, wrist ROM values in all directions and grip strength were increased compared with those before treatment, with groups A, B and C exhibiting higher values than group D (P<0.05). The treatment duration, treatment cost and overall incidence rate of adverse reactions were comparable among all four groups, without statistical differences (P>0.05). At 6 months, 9 months and 1 year after surgery, the recurrence rates of patients were the highest in group D and were the lowest in group C (P<0.05). Conclusion Ultrasound-guided different needle insertion paths are safe and effective in the treatment of CTS. The four attachment point release (group C) exhibits a potential advantage in reducing the long-term recurrence rate. Clinically, individualized path should be selected based on ultrasound imaging characteristics and the patient's wrist anatomy to balance precision with long-term efficacy.

Objective To systematically evaluate the efficacy and safety of ultrasound-guided sphenopalatine ganglion block for the treatment of allergic rhinitis (AR), with a focus on its short-term, cumulative, and long-term clinical improvements in young AR patients with high disease prevalence and frequent healthcare-seeking behavior, and elucidate the underlying neuromodulatory mechanisms. Methods A retrospective analysis was conducted on 50 AR patients who underwent ultrasound-guided bilateral sphenopalatine ganglion block at the Department of Ultrasound Medicine, Affiliated Hospital of Shaanxi University of Chinese Medicine, from November 2024 to September 2025. Each patient received four treatment sessions (one course). Efficacy and safety were assessed using the Visual Analog Scale (VAS) and the Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ). Symptom and quality-of-life scores were recorded at baseline and at 10 min, 30 min, 24 h, and 7 days post-treatment, as well as at 6 months after completion of the full course. Individual efficacy was evaluated based on the improvement rate of symptom scores. Results Twenty-seven patients completed the full treatment course; the remaining patients were evaluated based on data from individual treatment sessions. A total of 256 block procedures were performed, with 6 failures, yielding a puncture success rate of 97.7%. At each time point following the first, third, and fourth treatments, as well as at the 6 month follow-up, both the VAS scores and the RQLQ domain scores (including nasal congestion, rhinorrhea, nasal itching, sleep disturbance, and emotional problems) were significantly decreased compared with baseline (P<0.05), with both scales showing a similar downward trajectory. At 30 min after the first treatment, the effective rates for nasal congestion and rhinorrhea were 34% and 62%, respectively, rising to 81% and 89% after the full course. At the 6-month follow-up after the full course, 55% of patients achieved sustained symptom relief, with scores for nasal congestion, rhinorrhea, sleep, and emotions decreasing to 3.2 (2.2, 4.3), 4.3 (2.9, 5.3), 4.0 (3.0, 5.0), and 5.0 (4.0, 7.0), respectively, all significantly below the baseline values of 5.3 (3.7, 6.9), 6.8 (5.3, 8.0), 6.0 (4.0, 7.5), and 7.0 (4.0, 12.0). Four adverse events were reported during the treatment period, with an incidence of 3.1%, and no serious adverse events occurred. Conclusion Ultrasound-guided sphenopalatine ganglion block demonstrates good short-term and cumulative clinical benefit in the treatment of allergic rhinitis in young patients with elevated disease prevalence and frequent clinic visits. It provides rapid relief of nasal congestion and rhinorrhea, leads to sustained improvement in quality of life after the full course.

Objective To investigate the clinical value of a combined model integrating conventional CT features and radiomics features based on contrast-enhanced chest CT for predicting the invasiveness of pulmonary adenocarcinoma. Methods This retrospective study enrolled 154 patients with pathologically confirmed pulmonary nodules (classified as pre-microinvasive lesions and invasive adenocarcinoma)from the Affiliated Hospital of Liaoning University of Traditional Chinese Medicine from January 2019 to December 2025. Patients were randomly allocated into a training set (n=107) and a test set (n=47) at a 7:3 ratio. Conventional imaging features (e.g., maximum diameter, mean CT value) and 107 radiomic features were extracted from CT images. Feature selection was performed using least absolute shrinkage and selection operator (LASSO) regression coupled with logistic regression, and 2 conventional features (maximum diameter, mean CT value) and 4 key radiomic features (Shape Sphericity, First-order Root Mean Squared, GLCM Difference Entropy, NGTDM Strength) were finally identified. A conventional model, a radiomics model, and a combined conventional-radiomics model were subsequently established. Predictive performance of the three models was evaluated using ROC curves and decision curve analysis. Results The combined model achieved the optimal predictive performance in both the training and test sets, with area under the curve (AUC) values of 0.947 and 0.883, respectively, outperforming the standalone conventional model (AUC=0.888, 0.845) and the radiomics model (AUC=0.938, 0.861). Decision curve analysis confirmed that the combined model yielded greater clinical net benefit. SHAP interpretability analysis further demonstrated that mean CT value and First-order Root Mean Squared were significant positive predictors, while Shape Sphericity was a negative predictor. Conclusion The integrated conventional-radiomics combined model enables more effective non-invasive prediction of pulmonary adenocarcinoma invasiveness. Its visual nomogram provides a valuable reference for clinicians to formulate individualized surgical plans.

Objective To assess the predictive efficacy of the plasma atherogenic index (AIP) in conjunction with the Gensini score for identifying coronary functional ischemia, characterized by a computed tomography fractional flow reserve (CT-FFR) of ≤0.80. Methods A total of 215 consecutive patients with suspected coronary artery disease were recruited for this study, all of whom underwent both coronary angiography and CT-FFR evaluation at the First Affiliated Hospital of Bengbu Medical University from January 2025 to January 2026. Clinical data and lipid profiles were collected, and the AIP was determined using the formula log₁₀ (TG/HDL-C). The extent of coronary stenosis was measured using the Gensini score, while functional ischemia was defined as the lowest CT-FFR value of ≤0.80 among the three principal coronary arteries. Patients were divided into an ischemic group (CT-FFR≤0.80, n=156) and a non?ischemic group (CT-FFR>0.80, n=59). Between?group differences in clinical characteristics, AIP and Gensini scores were compared. Univariate and multivariate logistic regression analyses were performed to assess the associations of AIP and Gensini score with coronary functional ischemia. The predictive performance of AIP, Gensini score, and their combination was evaluated using ROC curves and the DeLong test; Net reclassification improvement and integrated discrimination improvement were used to assess improvements in clinical risk stratification and diagnostic accuracy. Results Compared with the non?ischemic group, the ischemic group showed significantly higher AIP and Gensini scores (P<0.05). Multivariate logistic regression identified AIP, Gensini score, and age as independent predictors of coronary functional ischemia. ROC curve analysis revealed that the AUC for AIP alone, Gensini score alone, and their combined model were 0.703, 0.705, and 0.790, respectively. The DeLong test indicated that the combined model exhibited a significantly higher AUC compared to the AIP alone (P=0.009) and the Gensini score alone (P=0.006). Additionally, analyses of the net reclassification improvement and integrated discrimination improvement further substantiated that the combined model surpassed each individual indicator in terms of risk stratification and diagnostic accuracy. Conclusion Both the AIP and Gensini score are strongly correlated with coronary functional ischemia and act as independent predictors. Their integration markedly enhances the predictive performance for coronary functional ischemia.

Objective To investigate the clinical utility of ultrafast pulse wave velocity (ufPWV) in quantitatively assessing the severity of carotid atherosclerosis for predicting the risk of ischemic stroke (IS). Methods From August 2023 to April 2025, 80 patients with IS admitted to Chongqing University Three Gorges Hospital and 80 healthy volunteers were prospectively enrolled. Carotid elastic parameters, early systolic pulse wave velocity (BS) and end-systolic pulse wave velocity (ES), were measured using ufPWV, and relevant clinical laboratory indicators were collected. Differences in BS, ES, and laboratory indicators between the two groups were compared, and factors influencing BS and ES were investigated. Results Compared to the healthy control group, the IS group exhibited significantly higher values in age, BMI, systolic blood pressure, diastolic blood pressure, white blood cell count, fasting blood glucose, total cholesterol, triglycerides, low-density lipoprotein, alanine aminotransferase, and blood urea nitrogen, while hemoglobin and high-density lipoprotein levels were significantly lower (P<0.05). The bilateral carotid intima-media thickness (IMT), BS, and ES values in the IS group were significantly higher than those in the healthy control group (P<0.05). The IS group demonstrated significantly higher IMT, BS, and ES values in bilateral carotid arteries compared to healthy controls (P<0.05). Significant differences in BS were observed among the plaque group, non-plaque group of IS patients, and healthy control group (P<0.001), with the highest BS value occurring in the plaque group. No significant difference in elastic stiffness (ES) was detected between the plaque and non-plaque groups (P=0.062), although both groups exhibited higher ES values than the healthy controls (P<0.001). Multiple linear regression analysis revealed that the influencing factors for BS included age, total cholesterol, low-density lipoprotein, and plaque formation, while those for ES included age, diastolic blood pressure, IMT, and plaque formation. In predicting IS risk using ufPWV parameters, the AUC value for BS was 0.906 (95% CI: 0.859-0.954), and that for ES was 0.916 (95% CI: 0.872-0.960). The suggested normal reference ranges were BS<6.65 m/s and ES<7.73 m/s. Conclusion ufPWV provides quantitative assessment of carotid atherosclerosis severity and shows promise for evaluating cerebral arteriosclerosis and predicting IS risk.

Objective To assess right ventricular systolic function in patients with acute pulmonary embolism (APE) by using fully automated three-dimensional echocardiography right ventricular quantitative software (3DAutoRV) and to investigate the correlations between its parameters and prognosis. Methods A total of 31 patients diagnosed with APE from January 2024 to July 2025 at the The Tenth Affiliated Hospital of Southern Medical University (Dongguan People's Hospital) were enrolled in this study. According to the occurrence of adverse clinical events during hospitalization, the patients were divided into two groups: the group with adverse clinical events (A group, n=15) and the group without adverse clinical events (B group, n=16). Meanwhile, 18 healthy people were selected as control group (C group). Record 3DAutoRV parameters including right ventricular end-diastolic volume (RVEDV), right ventricular end-systolic volume (RVESV), right ventricular stroke volume (RVSV), right ventricular ejection fraction (RVEF), fractional area change (FAC), tricuspid annular plane systolic excursion (TAPSE), right ventricular free wall longitudinal strainand [RVLS(F)] and right ventricular septal longitudinal strain [RVLS(S)] for all participants.The F-test was used to compare the differences in these 3DAutoRV parameters among the three groups.Pearson correlation analysis was used to evaluate the correlation between 3DAutoRV parameters and clinical adverse events.The indicators with statistically significant differences were included in the binary logistic regression analysis. The ROC curve was applied to evaluate the predictive value of the indicators for occurring clinical adverse events in patients with APE. Results Compared to C group, A group and B group showed a significantly lower RVEF, TAPSE and FAC, while showed a significantly higher RVLS(F) and RVLS(S) (P<0.01). Compared to B group, A group showed a significantly lower RVEF, TAPSE and FAC and showed a significantly higher RVLS(F) (P<0.01),whereas no significant difference was found in RVLS(S) between the two groups (P>0.05). RVEF, TAPSE and FAC were negatively correlated with clinical adverse events (P<0.01). RVLS(F) was positively correlated with clinical adverse events (P<0.05), while RVLS(S) showed no significant correlation with clinical adverse events (P>0.05). RVEF, TAPSE, FAC and RVLS(F) were incorporated into Binary logistic regression analysis, and the results showed that only RVEF was correlated with the occurrence of clinical adverse events in APE patients (P<0.05), suggesting that RVEF was an independent influencing factor for the occurrence of clinical adverse events.The ROC curve showed the cutoff value of RVEF for predicting clinical adverse events was 42.05% (AUC=0.913, sensitivity=0.938, specificity=0.733). Conclusion 3D RVEF was correlated with the occurrence of clinical adverse events in APE patients, served as an independent influencing factor for the occurrence of clinical adverse events, and could be used to evaluate the short-term prognosis of APE patients. It is expected to provide a reference basis for clinical diagnosis and treatment.

Cervical cancer, endometrial cancer, ovarian cancer, gestational trophoblastic neoplasia, vulvar cancer and vaginal cancer are common gynecological malignancies that seriously threaten women's health. Conventional imaging modalities such as ultrasound, CT and MRI have limitations in assessing early invasion, lymph node metastasis, peritoneal dissemination and post-treatment recurrence. Moreover, they are unable to provide critical biological information including tumor metabolic activity, proliferative status, receptor expression and molecular heterogeneity, thus their specificity and sensitivity in precise staging, treatment response prediction and recurrence monitoring remain to be improved. Molecular imaging, by integrating specific molecular probes with high-sensitivity imaging techniques, enables in vivo visualization of molecular pathological processes of tumor cells, offering novel approaches for early diagnosis, precise staging, individualized treatment decision-making and efficacy evaluation of gynecological malignancies. This review aims to systematically summarize the latest progress in the application of nuclear medicine imaging (PET/CT, PET/MRI), magnetic resonance molecular imaging, fluorescence imaging and ultrasound molecular imaging in the diagnosis of cervical cancer, endometrial cancer, ovarian cancer, gestational trophoblastic neoplasia, vulvar cancer and vaginal cancer, so as to provide a theoretical foundation for further in-depth research and clinical translation.

The incidence of thyroid cancer has been steadily increasing in recent years. Fine?needle aspiration cytology (FNAC) remains the gold standard for preoperative diagnosis, yet conventional manual interpretation suffers from low efficiency, high subjectivity, and an increased workload for pathologists. The rapid advances in deep learning over the past few years have provided a new avenue to overcome these limitations. This review systematically summarizes the current status and future perspectives of artificial intelligence (AI)?based image analysis in thyroid FNAC. It highlights the technical principles of mainstream models such as U?Net and Transformer, outlines the supportive role of publicly available datasets (e.g., the PTC Dataset), and synthesizes the progress made by both domestic and international research teams in cell classification, benign?malignant differentiation, and computer?aided diagnosis. Existing studies demonstrate that AI-based models attain a diagnostic accuracy of over 96% in differentiating benign cells from TBSRTC V+ categories (comprising suspicious for papillary thyroid carcinoma and malignant). Moreover, the diagnostic performance of these models has been shown to be comparable to that of senior pathologists, with a marked improvement in inter-observer agreement among less experienced cytopathologists. Nevertheless, current research still faces challenges including lightweight model deployment, multi?center generalizability, and the determination of legal liability. With ongoing model optimization and the refinement of regulatory frameworks, AI is expected to become an indispensable adjunctive tool in thyroid FNAC diagnosis, although its complete replacement of human cytopathologists will require cautious further exploration.

Chronic wounds are characterized by prolonged healing duration, high recurrence rates, and substantial treatment costs. The healing process is influenced by multiple factors, including tissue perfusion, inflammatory responses, and the local microenvironment. Accurate and timely wound assessment is essential for optimizing therapeutic strategies and improving patient outcomes. Traditional evaluation methods primarily rely on scoring systems and clinical experience, which often fall short in detecting deep tissue changes, microcirculatory abnormalities, and early risk signals. This review summarizes the applications of three-dimensional photogrammetry, near-infrared imaging, infrared thermography, fluorescence imaging, and laser speckle contrast imaging in chronic wound assessment. It compares their assessment dimensions, clinical scenarios, and implementation limitations, and examines technological complementarity and the roles of artificial intelligence in data standardization, longitudinal prediction, and smart nursing, providing a basis for objective assessment, risk identification, and continuous management.

With the advancement of artificial intelligence (AI) technology, its applications in ultrasound medicine have gradually expanded from image analysis to multiple clinical stages, including image acquisition, quality control, lesion detection, and interventional navigation, demonstrating potential value in improving diagnostic efficiency and reducing variability among operators. At the same time, ethical concerns are becoming increasingly prominent, such as opaque algorithmic decision-making processes, data privacy risks, health equity issues arising from model biases, and unclear accountability. These challenges are particularly evident in ultrasound medicine, a field highly dependent on operator experience and dynamic image interpretation. Based on an overview of typical AI applications and current research developments, this article provides a comprehensive analysis of these ethical challenges and explores possible solutions from perspectives including model optimization, clinical application standards, medical education, and governance mechanisms. Overall, AI is currently better suited as an auxiliary tool in clinical decision-making, and its effective implementation depends on improved model interpretability, refined multi-party responsibility frameworks, and continuous enhancement of physicians' professional competence. Moving forward, it is essential to advance technological innovation and ethical governance in tandem to further enhance the safety, transparency, and applicability of AI systems, thereby promoting their standardized use in ultrasound medicine.

Pancreatic solid pseudopapillary neoplasm (pSPN) is a rare low-grade malignant pancreatic tumor. Surgical resection is currently the preferred treatment method. Although the overall prognosis is good, 2.6%-15% of patients will still experience recurrence or metastasis. Imaging is not only used for early diagnosis of pSPN, but also plays an important role in assessing tumor biological behavior, predicting prognosis, and guiding treatment decisions and follow-up. This article systematically explains the application progress of commonly used imaging technologies in the prognosis diagnosis and treatment evaluation of pSPN, and explores the correlation between multi-modal imaging features and clinical prognosis, providing directions for future research.

Cerebral small vessel disease (CSVD) is an important cause of vascular cognitive impairment and vascular dementia. CSVD-related cognitive impairment has an insidious onset, making early diagnosis and intervention challenging. Conventional assessment relies mainly on MRI markers, which have limited ability to reflect early pathological alterations and individual cognitive risk. Diffusion tensor imaging (DTI) is sensitive to white matter microstructural changes and can provide quantitative information. This review summarizes the associations of conventional MRI markers with cognitive impairment and their limitations, as well as advances in conventional and derived DTI metrics, with emphasis on the distinct information, potential complementarity, and evidence limitations of the diffusion tensor image analysis along the perivascular space (DTI-ALPS) index and peak width of skeletonized mean diffusivity. Current evidence suggests that DTI metrics may provide complementary information for the early assessment of CSVD-related cognitive impairment; however, further standardization and validation in multicenter studies are required before clinical application.