Objective To investigate the association between serum C-reactive protein (CRP) levels and the occurrence of hemorrhagic transformation (HT) after acute cerebral infarction, and to acess its potential predictive value. Methods This retrospective cohort study consecutively enrolled 458 patients with acute cerebral infarction admitted to the Department of Neurology, West China Hospital of Sichuan University from June 1st, 2023 to December 31st, 2024. Based on serum C-reactive protein (CRP) levels measured within 24 h of admission, patients were stratified into a low-CRP group (<10 mg/L, n=245) and a high-CRP group (≥10 mg/L, n=213) using a cutoff value of 10 mg/L. The primary endpoint was radiologically confirmed hemorrhagic transformation (HT) during hospitalization. Baseline characteristics, clinical characteristics, laboratory parameters, and imaging data were collected and compared between the two groups. Independent determinants of HT were identified by univariable and multivariable logistic regression, and the discriminative performance of CRP for incident HT was quantified with ROC curve analysis. Results Among 458 enrolled patients, 126 patients (27.5%) developed HT. The high-CRP group (≥10 mg/L) demonstrated a significantly higher HT incidence than the low-CRP group (38.5% vs 18.0%, P<0.001). These patients were older, had higher baseline NIHSS scores, and showed higher prevalence of atrial fibrillation, coronary disease, diabetes, and reperfusion therapy.After multivariable adjustment, elevated CRP (≥10 mg/L) remained an independent predictor for HT (OR=1.91, 95% CI: 1.16-3.14, P=0.011). Other independent risk factors included large MCA infarction (OR=3.76), atrial fibrillation (OR=2.62), and reperfusion therapy (OR=3.94).Stratified analysis revealed a significant interaction between CRP and reperfusion status (P-interaction=0.030). Elevated CRP significantly predicted HT only in patients receiving reperfusion therapy (OR=4.51, 95% CI: 1.84-11.02, P=0.001). The AUC of CRP for HT prediction was 0.642 (95% CI: 0.586-0.697). Conclusion Elevated early-stage serum CRP (≥10 mg/L) is an independent risk factor for HT in acute cerebral infarction, demonstrating significant interaction with reperfusion therapy. Routine CRP monitoring can flag high-risk individuals and refine post-admission management.

Objective To investigate the predictive value of a nomogram combining multimodal ultrasound features and serum inflammatory markers for histological grading of invasive breast cancer. Methods Multimodal ultrasound images and immune inflammatory markers were retrospectively analyzed from 174 patients with histologically confirmed invasive breast cancer admitted to Inner Mongolia Autonomous Region People's Hospital from January 2022 to June 2025. Data were randomly divided into a training set (n=121) and a validation set (n=53) at a 7:3 ratio. Independent predictors associated with breast cancer histological grade were identified via multivariate logistic regression. A regression model was established to generate a nomogram, which was validated using the validation cohort and calibration curves. Predictive performance was assessed using ROC curves and decision curve analysis (DCA). Clinical utility was evaluated through clinical impact curves (CIC). Results Multivariate logistic regression analysis revealed perfusion defects (OR=3.743, 95% CI: 1.342-10.439, P=0.012), AUC (OR=1.002, 95% CI: 1.000~1.003, P=0.043), E_max (OR=1.021, 95% CI: 1.003-1.040, P=0.023), and LMR (OR=0.721, 95% CI: 0.572-0.909, P=0.006) were predictive factors for breast cancer histological grade. A nomogram prediction model was constructed based on these four indicators. The training set AUC was 0.856 (95% CI: 0.790-0.922), with a C-index of 0.856. Calibration curves demonstrated good agreement between predicted and actual probabilities. The Hosmer-Lemeshow test showed no statistically significant differences (P=0.231), indicating good model fit. The DCA curve indicated that intervention measures yielded high clinical net benefit when the probability threshold ranged from 0% to 87%. The CIC curve demonstrated that when the probability threshold exceeded 70%, the number of breast cancer patients predicted by the nomogram to have a certain histological grade highly matched the actual patient count. The validation set achieved an AUC of 0.846 (95% CI: 0.739-0.954) and a C-index of 0.846. The calibration curve demonstrated good agreement between the nomogram's predictions and actual outcomes. Both the DCA and CIC curves indicated the model possesses significant clinical utility. Conclusion The nomogram model for predicting breast cancer histological grade, constructed based on multimodal ultrasound features combined with serum inflammatory markers, provides important reference information for clinical diagnosis, subsequent treatment, and prognosis assessment, demonstrating significant clinical application value.

Objective To systematically evaluate alterations in the structural covariance networks (SCNs) of primary dysmenorrhea (PDM) patients using structural magnetic resonance imaging and graph theory analysis. Methods A total of 31 PDM patients and 30 healthy controls (HCs) were recruited from Shaanxi University of Chinese Medicine from September 2021 to September 2022. High-resolution T1-weighted imaging was conducted on days 1-3 of the menstrual cycle. Structural images were preprocessed using SPM8. Gray matter SCNs were reconstructed utilizing the graph analysis toolbox (GAT), and global and local network metrics were computed and compared between groups based on graph theory. Results Compared to the HC group, PDM patients exhibited trends of decreased clustering coefficient (Cp), local efficiency, and transitivity, alongside increased assortativity in global network metrics. However, these differences were not statistically significant when compared against the null distribution derived from permutation tests (P>0.05). The area under the curve (AUC) results for global metrics also indicated no significant intergroup differences (P>0.05), suggesting the overall architecture of the brain network remains relatively intact in PDM patients. At the local nodal level, under the minimum density threshold, PDM patients showed significantly altered nodal metrics prior to FDR correction (P<0.05): decreased nodal degree was observed in the left cuneus, left superior occipital gyrus, and right postcentral gyrus; increased nodal degree was found in the bilateral middle cingulate gyrus and right middle frontal gyrus; betweenness centrality was decreased in the left frontal inferior operculum and increased in the left cerebellum, cingulate gyrus, and olfactory cortex; Cp was decreased in the left cerebellum and increased in the left postcentral gyrus. These differences were no longer statistically significant after FDR correction (P>0.05). AUC analysis of standardized nodal metrics revealed that PDM patients had increased nodal degree in the bilateral cingulate gyrus, left olfactory cortex, and right parahippocampal gyrus; decreased nodal degree in the left cuneus, left middle occipital gyrus, left superior occipital gyrus, and right postcentral gyrus; increased betweenness centrality in the left middle cingulate gyrus, left olfactory cortex, right parahippocampal gyrus, and right precentral gyrus; decreased betweenness centrality in the left orbital inferior frontal gyrus, right orbital middle frontal gyrus, and right insula; increased Cp in the right orbital middle frontal gyrus; and decreased Cp in the left middle occipital gyrus and right superior occipital gyrus. Local efficiency was significantly higher in the right orbital middle frontal gyrus and lower in the right superior occipital gyrus in the PDM group (P<0.05). Analyses using both targeted and random network attacks demonstrated no significant differences in the size of the largest component of the residual network between the two groups (P>0.05). AUC results for network attack metrics also showed no significant differences (P>0.05). Conclusion Alterations in both global and nodal metrics of SCNs were observed in PDM patients, primarily involving brain regions associated with pain processing and emotion regulation, which may contribute to the manifestation of dysmenorrhea symptoms. Although the overall stability of the brain network appears largely preserved, these topological changes provide important neuroimaging evidence for the central mechanisms underlying PDM. The findings could aid in identifying potential central markers for PDM in clinical diagnosis (e.g., local efficiency in the right orbital middle frontal gyrus) and inform the development of novel neuroregulatory treatment strategies targeting pain-related brain regions.

Objective To integrate artificial intelligence with prenatal ultrasound imaging by developing a deep-learning multi-task model that simultaneously identifies standard fetal cardiac planes and performs precise instance segmentation of key anatomical structures. Methods A total of 3312 fetal cardiac ultrasound images were collected from 1300 singleton pregnancies at 18-24 weeks of gestation in the Second Affiliated Hospital of Fujian Medical University from January 2021 to July 2023, and all images were jointly annotated by three associate chief sonographers. The dataset covers five standard cardiac planes, apical four-chamber (4CH), three-vessel (3VV), three-vessel-and-trachea (3VT), right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT), together with ten critical structures, including the left/right ventricles, left/right atria, pulmonary artery, main pulmonary artery, ascending aorta, aorta, trachea and superior vena cava. YOLOv11 was adopted as the backbone network for instance segmentation. An additional classification branch was attached to the detection head to realize joint learning of plane recognition and structure segmentation. Results The proposed model achieved an AUC of 0.976 for plane recognition and an mAP of 0.937 for instance segmentation. Compared with single-task models performing only classification or segmentation, the multi-task framework demonstrated superior overall performance. Conclusion The YOLOv11-based multi-task learning model accurately recognizes standard fetal cardiac planes and delineates key anatomical structures, offering considerable potential to enhance the efficiency and accuracy of prenatal screening for congenital heart anomalies.

Objective To investigate the association between MRI-based multifidus muscle fat infiltration degree and other clinical features and postoperative recurrence of lumbar disc herniation (LDH). Methods The medical records of 743 patients with LDH who received lumbar minimally invasive surgery in Shanxi Provincial People's Hospital from April 2023 to April 2024 were retrospectively collected. The fat infiltration degree and lesion features were obtained from MRI. According to the recurrence status of LDH within 12 months after surgery, the above patients were classified into recurrence group (n=74) and non-recurrence group (n=669). Potential predictors were screened by univariate analysis. Multivariate logisticregression analysis was applied to determine the independent risk factors for postoperative recurrence of LDH. ROC curve was drawn and the area under the curve (AUC) was calculated to evaluate the predictive efficiency of the model. Results There were no statistical differences in gender, age, diabetes mellitus, hypertension and protrusion segment between the two groups of patients (P>0.05). The disease course, body mass index, Pfirrmann grading and multifidus muscle fat infiltration degree in recurrence group were higher than those in non-recurrence group (P<0.05). Regression analysis results showed that long course of disease, high body mass index, high degree of multifidus muscle fat infiltration and high Pfirrmann grade were independent risk factors for postoperative recurrence of LDH (P<0.05). The combined prediction model equation was manifested as y=2.030×disease course+0.216×body mass index+0.660×multifidus muscle fat infiltration degree+0.931×Pfirrmann grading assignment, and the AUC, sensitivity and specificity of the model were 0.991, 96.43% and 94.63% respectively. Conclusion MRI sign of multifidus muscle fat infiltration is a key independent risk factor for predicting postoperative recurrence of LDH, and its combined application with clinical features can significantly enhance the predictive efficiency.

Objective To investigate the predictive value of the left atrioventricular coupling index (LACI) combined with left atrial strain parameters-reservoir strain (LASr), conduit strain (LAScd), and contractile strain (LASct)-for recurrence of atrial fibrillation (AF) after radiofrequency catheter ablation (RFCA). Methods A total of 154 patients with AF who underwent RFCA at the Eighth Affiliated Hospital of Southern Medical University from October 2022 and December 2024 were enrolled. Based on recurrence within 6 months post-procedure, patients were divided into a recurrence group (n=38) and a non-recurrence group (n=116). Baseline data and echocardiographic parameters were compared between the two groups. Changes in LACI, LASr, LAScd, and LASct were assessed before and one month after RFCA. Generalized estimating equations and Cox regression models were used to analyze their influence on recurrence. ROC curves were employed to evaluate predictive performance, and Kaplan-Meier curves were plotted to analyze recurrence rates. Results The recurrence group had larger left atrial diameters and higher E/e' ratios (P<0.05). At one-month post-ablation, the non-recurrence group showed a more pronounced decrease in LACI and greater improvement in LASr, LASct, and LAScd (P<0.05). LACI and the left atrial strain parameters were identified as independent predictors of recurrence. ROC curve analysis demonstrated that the combined model of the four indicators yielded a higher area under the curve (AUC=0.836) than any individual parameter: LASr (AUC=0.735), LASct (AUC=0.754), LAScd (AUC=0.703), or LACI (AUC=0.776). Kaplan-Meier analysis indicated that patients with LACI ≤33.91%, LASr >25.86%, LASct >|-11.83%|, and LAScd >|-14.46%| had significantly lower recurrence rates (P<0.05). Conclusion LACI, LASr, LASct, and LAScd serve as valuable predictors of AF recurrence after RFCA. Their combined assessment improves predictive accuracy and aids in individualized postoperative risk management.

Objective To investigate the value of an interpretable machine learning model integrating intratumoral and peritumoral ultrasound radiomics with clinical sonographic features in evaluating Ki-67 expression levels in breast cancer, and to analyze the impact of different peritumoral region widths on predictive performance. Methods A retrospective analysis was performed on 185 breast cancer patients who underwent surgical treatment at our institution. Based on postoperative pathology, patients were stratified into high and low Ki-67 expression groups. Tumor regions of interest (ROIs) were delineated, with peritumoral regions automatically expanded outward (1, 3, 5 mm). Radiomics features were extracted and screened to construct four radiomics models: intratumoral, peritumoral-1mm, peritumoral-3mm, and peritumoral-5mm. The optimal peritumoral model (3 mm) was combined with the intratumoral model to establish the optimal radiomics signature, and a radiomics score was calculated. Clinically significant ultrasound features were selected to develop a clinical model. A nomogram was then constructed by integrating the optimal radiomics model and clinical model. Model performance was evaluated using ROC curves, decision curve analysis, and calibration curves. To enhance interpretability, SHapley Additive exPlanations analysis was employed to assess feature importance. Results The peritumoral-3mm model demonstrated superior predictive performance compared to other peritumoral models. Maximum lesion diameter, presence of microcalcifications, and sonographically abnormal axillary lymph nodes were incorporated into the clinical model. The nomogram combining the optimal radiomics model and clinical model exhibited strong predictive performance in both training (AUC=0.923) and validation (AUC=0.883) cohorts, with favorable clinical utility and calibration. Conclusion The combination of intratumoral and peritumoral-3 mm radiomics features with clinical ultrasound characteristics provides reliable assessment of Ki-67 expression in breast cancer, offering potential clinical decision-making support.

Objective To investigate the articular clinical features and ultrasonographic changes in patients with acute Chikungunya fever (CHIKF). Methods This prospective study included 26 patients with CHIKF confirmed by nucleic acid testing and admitted to our hospital from August 8th to 31st, 2025. All patients underwent musculoskeletal ultrasound examination of the limb joints and surrounding soft tissues The examination included small joints of the hands and feet, as well as the wrists, elbows, shoulders, ankles, knees, and hips, covering 52 joint sites in total. Results Ultrasonographic abnormalities were observed as follows: effusion in the small joints of the feet (100%, 52/52) and synovitis (42.3%, 22/52); effusion in the small joints of the hands (100%, 52/52) and synovitis (38.5%, 20/52); ankle joint effusion (34.6%, 18/52) and synovitis (25%, 13/52); wrist joint effusion (30.8%, 16/52) and synovitis (25%, 13/52); knee joint effusion (13.5%, 7/52) and synovitis (7.7%, 4/52); elbow joint effusion (19.2%, 10/52) and synovitis (3.8%, 2/52). No significant effusion or synovial hyperplasia was detected in the shoulder or hip joints. Additionally, the following findings were noted: finger tenosynovitis (3.8%, 2/52), medial calf panniculitis (38.5%, 20/52), soleus myositis in one case (1.9%, 1/52), axillary lymphadenopathy (65.4%, 34/52), and inguinal lymphadenopathy (86.5%, 45/52). Conclusion Musculoskeletal ultrasound is effective in detecting joint alterations caused by CHIKF and can clearly visualize pathological changes in periarticular soft tissues, providing an objective and reliable basis for the diagnosis of articular involvement during the acute CHIKF.

Objective To investigate the effect of low-dose scanning on the image quality of head and neck computed tomography angiography (CTA). Methods Sixty patients who underwent head and neck CTA at the First Affiliated Hospital of Bengbu Medical University from February 2022 to January 2025 were selected as the research subjects. The patients were randomly divided into a study group and a control group, with 30 cases in each group.The study group underwent dual low-dose scanning (tube current: 80 mA, contrast agent: 40 mL). The control group underwent conventional-dose scanning (tube current: 100 mA, contrast agent: 50 mL). All scans were performed in the standard position using a standard scanning protocol, and a dual-barrel high-pressure injection system was used for contrast agent bolus injection. After scanning, the data of both groups need to undergo multimodal three-dimensional post-processing.Statistical analysis was performed to compare the differences in noise, radiation dose, and image quality of various parts between the two groups, so as to analyze the effect of low-dose scanning on the image quality of head and neck CTA. Results There were no statistically significant differences in the signal-to-noise ratio and contrast-to-noise ratio of various parts (aortic arch, left common carotid artery, right common carotid artery, left internal carotid artery, right internal carotid artery, left middle cerebral artery, right middle cerebral artery) between the two groups (P>0.05). The volume CT dose index, dose-length product, effective dose, and iodine load in the study group were all lower than those in the control group (P<0.05).There was no statistically significant difference in the image quality score between the two groups (P>0.05). Conclusion Compared with conventional-dose head and neck CTA scanning, low-dose head and neck CTA scanning shows no significant difference in image quality.And low-dose head and neck CTA scanning can reduce the patient's radiation dose.

Objective To explore the value of machine learning models based on multi-parameter MRI biomarkers in the preoperative differentiation between skull base chordoma and skull base chondrosarcoma. Methods A total of 180 patients with pathologically confirmed skull base tumors (136 cases of chordoma and 44 cases of chondrosarcoma) were retrospectively included. Their clinical characteristics were collected. The tumor regions were segmented using the nnUNet framework and MRI radiomics features were extracted. Three subsets consisting of clinical characteristics, radiomics features, and fusion features were constructed and preprocessed. Then, 11 machine learning models were trained with the pathological results as labels, and the optimal model was selected based on indicators such as the area under the ROC curve (AUC) and accuracy. Results In the integrated feature model, the logistic regression model performed the best, with an AUC of 0.92 (95% CI: 0.86-0.98) and an accuracy rate of 87%. Baseline analysis revealed that tumor diameter, calcification, fibrous septum, and enhancement degree were statistically significant for discrimination (P<0.05). Decision curve analysis indicated that the integrated model had a higher net benefit rate within the clinical risk threshold range of 6%-91%. Conclusion The fusion model based on multi-parameter MRI imaging histology and clinical features can effectively distinguish between skull base chordoma and skull base chondrosarcoma, providing a reference for precise preoperative diagnosis and treatment.

Objective To evaluate differences in myocardial work impairment between anthracycline-based and targeted therapy in breast cancer patients using noninvasive left ventricular pressure-strain loop analysis. Methods Sixty-one postoperative breast cancer patients were enrolled in our hospital from October 2022 to September 2024, including 31 receiving doxorubicin/epirubicin (110 mg/m2)+cyclophosphamide+docetaxel (anthracycline group) and 30 receiving Herceptin-based regimen (targeted group). Thirty-one healthy women served as controls. Echocardiography was performed at baseline (T0) and after 4-6 chemotherapy cycles (T4). Conventional echocardiographic parameters, global longitudinal strain and myocardial work parameters were measured. The myocardial work parameters included global work efficiency (GWE), global wasted work (GWW), global constructive work (GCW), and global work index (GWI). Changes in these parameters were compared within and between groups at T0 and T4. Results No significant differences were observed in age, heart rate, diastolic blood pressure, systolic blood pressure, body mass index, body surface area, conventional echocardiographic parameters, global longitudinal strain and myocardial work parameters among the three groups (P>0.05). No statistically significant changes were found in left ventricular end-diastolic volume, left ventricular end-systolic volume, left ventricular ejection fraction, mitral inflow A-wave, E-wave, E/A ratio, average early diastolic mitral annular velocity (mean e′), or E/mean e′ ratio between T0 and T4 in either patient group (P>0.05), and inter-group comparisons also showed no significant differences (P>0.05). Global longitudinal strain did not change significantly within or between groups (P>0.05). However, at T4, GWW significantly increased, while GWE, GCW, and GWI significantly decreased in both the anthracycline and targeted therapy groups (P<0.05). There were no significant differences in these parameters between the two groups (P>0.05). Conclusion The left ventricular pressure-strain loop technique can effectively evaluate changes in myocardial work in breast cancer patients following targeted therapy or anthracycline-based chemotherapy, providing a reference for early clinical intervention.

Objective To investigate the characteristics of the gut microbiota in patients with symptomatic intracranial atherosclerotic stenosis (sICAS) complicated with obstructive sleep apnea syndrome (OSAS). Methods From April 2022 to June 2024, clinical data and fecal samples of 109 confirmed sICAS patients hospitalized in the Department of Neurology, Guangdong Sanjiu Brain Hospital were prospectively collected. According to the apnea-hypopnea index (AHI), patients were divided into four groups: non-OSAS group (control group, AHI<5), mild OSAS group (5≤AHI<15), moderate OSAS group (15≤AHI<30), and severe OSAS group (AHI≥30). Total fecal DNA was extracted following standardized procedures. The V3-V4 regions of the 16S rRNA gene were amplified and subjected to Illumina high-throughput sequencing. Bioinformatics analyses, including sequence assembly, quality control, and amplicon sequence variant (ASV/OTU) construction, were performed using QIIME2 and related platforms. α-diversity and β-diversity were calculated, and intergroup differences in gut microbiota were compared. Differential taxa were identified using linear discriminant analysis effect size (LEfSe). Functional metabolic pathway prediction and KEGG annotation were conducted using PICRUSt2. Results A total of 27 patients in the control group and 82 patients in the OSAS groups were included, comprising 30 mild, 30 moderate, and 22 severe cases. Compared with the control group, patients in the OSAS groups showed no significant differences in gut microbial α-diversity or β-diversity (P>0.05). Analysis of microbial composition revealed that, relative to controls, OSAS patients exhibited a significant decrease in the relative abundance of the butyrate-producing genus Blautia, while Lactobacillus and Acinetobacter were significantly increased. Functional prediction based on the KEGG database using PICRUSt2 indicated that the D-glutamine and D-glutamate metabolism pathway, D-alanine metabolism pathway, and secondary bile acid biosynthesis pathway were significantly upregulated in OSAS patients. Furthermore, as OSAS severity increased, pathways involved in valine, leucine, and isoleucine biosynthesis, as well as pantothenate and CoA biosynthesis, showed a decreasing trend. Conclusion Patients with sICAS complicated with severe OSAS exhibit gut microbiota dysbiosis and altered metabolic functions. Modulating gut microbiota composition may have potential benefits.

Objective To explore the predictive value of magnetic resonance-diffusion weighted imaging (MRI-DWI) and fluid-attenuated inversion recovery (FLAIR) sequences in acute stroke combined with cerebral edema. Methods A total of 150 patients with acute stroke admitted to the First People's Hospital of Guangyuan were retrospectively enrolled from June 2020 to June 2025. According to presence or absence of cerebral edema, they were divided into simple acute stroke group (non-combination group, 92 cases) and cerebral edema group (combination group, 58 cases). All patients underwent cranial MRI examinations within 24 h after admission, including T1WI, T2WI, DWI and FLAIR sequences. The apparent diffusion coefficient (ADC) and lesions volume in DWI sequence, signal intensity ratio (SIR) of lesion-normal brain tissue in FLAIR sequence and grading of FLAIR vascular hyperintensity (FVH) were obtained. The differences in the above imaging indexes and clinical data between the two groups were compared. The independent risk factors of acute stroke combined with cerebral edema were analyzed by multivariate Logistic regression analysis. The predictive efficiency of single index and combined detection for cerebral edema was evaluated by ROC curves. Results There were significant differences in age, NIHSS score at admission, interval from onset to admission and stroke types between non-combination group and combination group (P<0.05). ADC in non-combination group was greater than that in combination group, lesion volume on DWI, SIR and proportion of FVH grading at grade 2-3 were lower than those in non-combination group, and the differences were statistically significant (P<0.05). Multivariate Logistic regression analysis showed that increased NIHSS score at admission, lesion volume on DWI and SIR, FVH grading at grade 2-3 and decreased ADC were all independent risk factors of acute stroke combined with cerebral edema (P<0.05). The results of ROC curves analysis showed that area under the curve (AUC) values of ADC, lesion volume on DWI, SIR, FVH grading and combined detection for predicting cerebral edema were 0.728 (95% CI: 0.648-0.808), 0.741 (95% CI:. 0.656-0.826), 0.714 (95% CI: 0.624-0.804), 0.704 (95% CI: 0.632-0.777) and 0.837 (95% CI: 0.770-0.904), respectively (P<0.05). Conclusion MRI-DWI sequence parameters (ADC, lesion volume) and FLAIR sequence characteristics (SIR, FVH grading) are all independent high-risk factors of cerebral edema after acute stroke, which have significant predictive value in cerebral edema.

Objective To investigate the value of renal resistive index (RRI) and power Doppler ultrasound (PDU) score in predicting sepsis-associated acute kidney injury (SA-AKI) in ICU patients and to analyze their correlations with infection and inflammatory markers. Methods A total of 70 sepsis patients admitted to the Department of Critical Care Medicine, The Second People's Hospital of Foshan from April to December 2023 were included. General clinical data, vital signs at ICU admission, Acute Physiology and Chronic Health Evaluation II (APACHE-II) score, and ultrasonic renal perfusion indices including RRI and PDU score were recorded. Venous blood samples were collected to measure renal function markers as serum creatinine (SCr), blood urea nitrogen (BUN), infection marker as procalcitonin (PCT), and inflammatory marker as interleukin-6 (IL-6). Patients were classified into two cohorts: Based on the severest degree of AKI within 48 h, they were divided into a normal renal function control group, AKI stage 1, stage 2, and stage 3 groups; According to renal function recovery within 3 days, they were categorized into transient AKI and persistent AKI groups. Early indices were retrospectively reviewed, and inter-group differences were compared. ROC curves were used to assess the predictive efficacy of RRI and PDU score for AKI, while correlations between PCT, IL-6 and RRI, PDU score were analyzed. Results Among the 70 patients, 17 patients were in the non-AKI control group, 19 patients in AKI stage 1, 15 patients in AKI stage 2, and 19 patients in AKI stage 3. Patients with AKI stage 2 and 3 had significantly higher RRI (P<0.001) and lower PDU score (P<0.001) compared with those in the non-AKI group or AKI stage 1. Additionally, patients in the persistent AKI group had a significantly higher RRI (P<0.001) and a significantly lower PDU (P<0.001) compared with those in the transient AKI group. ROC curve analysis demonstrated that both RRI and PDU score were reliable predictors of AKI. Additionally, PCT and IL-6 levels were significantly elevated in patients with AKI stage 2 and 3, and were significantly correlated with RRI and PDU score. Conclusion Ultrasonic renal perfusion indices as RRI and PDU score hold significant value in predicting AKI development in sepsis patients. They are correlated with infection and inflammatory markers, providing a non-invasive, dynamic imaging approach for the early identification of high-risk patients in clinical practice.

Objective To investigate the hepatobiliary phase manifestations and pathological basis of gadoxetic acid disodium-enhanced MRI (Gd-EOB-DTPA-enhanced MRI) in focal liver lesions, and to provide more reference information for the differential diagnosis of focal liver lesions. Methods A retrospective analysis was performed on the clinical and Gd-EOB-DTPA-enhanced MRI data of 110 patients with surgically and pathologically confirmed focal liver lesions in Meizhou People's Hospital from January 2016 to May 2019. Pathological confirmation revealed 66 cases of hepatocellular carcinoma (HCC), 12 cases of intrahepatic cholangiocarcinoma (ICC), 3 cases of combined hepatocellular-cholangiocarcinoma (cHCC-CC), 17 cases of metastases, 1 case of primary hepatic squamous cell carcinoma, 1 case of primary hepatic lymphoma, 1 case of hepatic focal nodular hyperplasia (FNH), 3 cases of hepatic regenerative nodules, 1 case of hepatic adenoma, 4 cases of hepatic cavernous hemangioma, and 1 case of hepatic angiomyolipoma, and the relationship between hepatobiliary phase manifestations and pathological basis was analyzed. Results On the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRI: 13 cases (13/66, 20%) of HCC showed isointense to hyperintense signals, and 53 cases (53/66, 80%) of HCC showed obviously hypointense signals. Nine cases (9/12, 75%) of ICC presented hypointense signals with flocculent slightly hyperintense foci. Nine cases (9/17, 52%) of metastatic liver cancer showed hypointense signals with central hyperintense signals. The 3 cases of cHCC-CC showed hypointense signals with central cloud-like hyperintense signals, central cloud-like hyperintense signals with peripheral hyperintense signals, and peripheral hyperintense signals with central hypointense signals, respectively. Among the 3 cirrhotic regenerative nodules, 2 cases showed hypointense signals and 1 case showed hyperintense signals. The 4 cases of cavernous hemangioma presented hypointense signals. The 1 case of FNH showed ring-shaped hyperintense signals with a central "target sign" of slightly hyperintense signals. The 1 case of primary lymphoma showed hypointense signals with central dendritic hyperintense signals. The 1 case of hepatic angiomyolipoma, 1 case of hepatic adenoma, and 1 case of primary squamous cell carcinoma all showed hypointense signals. The hepatobiliary phase manifestations of focal liver lesions varied according to the pathological conditions within the lesions. Conclusion Fully understanding the hepatobiliary phase manifestations of Gd-EOB-DTPA-enhanced MRI and their pathological basis is helpful for the differential diagnosis of focal liver lesions and has important clinical application value.

Objective To analyze the influencing factors and independent risk factors of postoperative communicating hydrocephalus in children with posterior cranial fossa tumors, and construct a predictive model to provide a basis for preoperative risk assessment and postoperative management. Methods A retrospective analysis was conducted on the clinical data and imaging information of 113 children with posterior cranial fossa tumors in the Department of Neurosurgery of Women and Children's Medical Center, Affiliated to Guangzhou Medical University from December 2021 to December 2024. Cross-tabulation analysis and chi-square test were performed on all categorical variables and whether secondary communicating hydrocephalus occurred to evaluate the correlation between each categorical variable factor and the outcome. Binary Logistic regression analysis was used to predict independent risk factors. Results The body weight of the children, GCS score at admission, preoperative obstruction, tumor location, intraoperative blood loss, operation time, tumor pathology, postoperative infection, and peak red blood cells in cerebrospinal fluid were significantly correlated with the occurrence of secondary communicating hydrocephalus after surgery (P<0.05). Among them, postoperative intracranial infection was an independent risk factor for secondary communicating hydrocephalus after posterior cranial fossa tumor surgery. Conclusion Postoperative intracranial infection is an independent risk factor for secondary hydrocephalus, so the risk of infection should be reduced as much as possible, and targeted treatment should be provided in a timely manner.

Objective To identify the optimal scanning sequence and parameters for prostate MR diffusion imaging, by comparing the effects of different b values in two diffusion imaging sequences: EPI-DWI and RESOLVE-DWI on the prostate image quality on 3.0 tesla magnetic resonance imaging (3T MRI). Methods A retrospective analysis was conducted on 70 prostate cancer patients who met the enrollment ranking standards at Hanzhong people's hospital from January 2023 to December 2024. All patients underwent both scans of EPI-DWI and RESOLVE-DWI with b values of 50, 800, 1400, 2000 and 3000 s/mm². The scanning parameters for EPI-DWI were as follows: TR 6800 ms, TE 59 ms, ETL 114, Bandwidth 1566 Hz/Px,and for RESOLVE-DWI are as follows: TR 5870 ms,TE 58 ms, ETL 79, Bandwidth 1078 Hz/Px. The readout was divided into 5 segments. The quality of the prostate images was compared. Results RESOLVE-DWI group showed higher overall subjective image quality scores compared to EPI-DWI group (P<0.05). RESOLVE-DWI group exhibited higher overall SNR (P<0.05). For both sequences, SNR peaked at b=50, with no statistical difference between b=50 and b=800 (P>0.05). Similarly, RESOLVE-DWI group showed superior CNR (P<0.05). Both sequences peak of CNR values were observed at b=800 and 1400 s/mm², with no significant difference between b=800 and b=1400 s/mm² (P>0.05). Conclusion RESOLVE-DWI is the preferred sequence for prostate 3T magnetic resonance diffusion imaging. Selecting b values of 50, 800 and 1400 s/mm² provides optimal SNR and CNR, offering reliable imaging support for the diagnosis of prostate cancer.

Objective To analyze the diagnostic value of three-dimensional ultrasound combined with shear wave elastography (SWE) for stress urinary incontinence (SUI) in primiparas. Methods A total of 112 primiparas who underwent pelvic floor examination at 6-12 weeks after delivery from January 2024 to December 2024 were selected as study subjects. According to the clinical symptoms and urine pad test results, they were divided into SUI group (n=48) and non-SUI group (n=64). All study subjects underwent transperineal pelvic floor ultrasound examination. The area, anteroposterior diameter, left-right diameter of levator hiatus (LHA) in resting state and maximum Valsalva maneuver and thickness of levator ani muscle (LAM) were measured by 3D ultrasound. The mean Young' s modulus (E_mean) of bilateral puborectalis (PR) in resting state and Valsalva maneuver was measured by SWE technique. The differences in parameters between the two groups were compared. Binary logistic regression analysis was used to analyze the independent risk factors of SUI. ROC curve was used to evaluate the efficiency of each parameter and combined diagnosis of SUI. Results The LHA area, anteroposterior diameter and left-right diameter in resting and Valsalva states in SUI group were larger than those in non-SUI group, and the LAM thickness was thinner than that in non-SUI group (P<0.001). The bilateral PR E_mean values in resting and Valsalva states in SUI group were lower than those in non-SUI group (P<0.001). Binary Logistic regression analysis showed that LHA area in Valsalva state (OR=1.402, 95% CI: 1.150-1.709) and PR E_mean in Valsalva state (OR=0.946, 95%C I: 0.918-0.974) were independent influencing factors of postpartum SUI in primiparas (P<0.05). ROC curve analysis showed that the area under the curve (AUC) of LHA area in Valsalva state was 0.892, and the AUC of PR E_mean was 0.875, and the AUC of combined diagnosis was 0.945, with sensitivity of 93.75% and specificity of 81.25%. Conclusion Three-dimensional ultrasound combined with SWE can objectively and quantitatively evaluate the changes of postpartum pelvic floor structure and function in primiparas from two dimensions of morphology and biomechanics. LHA area and PR E_mean in Valsalva state are effective indicators for the diagnosis of SUI. The combined detection of the two can significantly enhance the diagnostic efficiency.

Nonalcoholic fatty liver disease is one of the most common chronic liver diseases globally, with a prevalence of approximately 32.16%, and this rate is on the rise. Early diagnosis and intervention are crucial for reducing the risk of complications such as cirrhosis, hepatocellular carcinoma, and other serious sequelae. Ultrasound attenuation imaging is an emerging non-invasive imaging tool that can quantitatively assess hepatic steatosis by measuring the attenuation coefficient. It has been shown to have a high correlation with magnetic resonance proton density fat fraction and histological biopsy results (with a correlation coefficient as high as 0.85). This technique also demonstrates high accuracy in the diagnosis of different grades of fatty liver, especially in obese patients. As a convenient and non-invasive imaging modality, ultrasound attenuation imaging has shown significant value in the early diagnosis and disease progression assessment of nonalcoholic fatty liver disease, and it holds great potential for clinical application.

Hepatic fibrosis is a common pathological process in various chronic liver diseases, and its early diagnosis and accurate assessment are crucial for treatment and prognosis. Traditional liver biopsy has limitations such as invasiveness and sampling errors, while the development of non-invasive imaging techniques has provided new means for the diagnosis of hepatic fibrosis. This article reviews the principles, advantages and disadvantages, and clinical applications of non-invasive imaging methods such as elastography, dynamic contrast-enhanced imaging, and molecular imaging. It also explores technological innovations such as AI-driven analytical methods and multimodal data fusion, as well as emerging technologies and future development directions. These new technologies are expected to improve the diagnostic accuracy of hepatic fibrosis, reduce equipment costs, simplify operational procedures, and promote the development of personalized medicine.