Objective To investigate the value of inferior vena cava blood flow parameters by ultrasound detection combined with matrix metalloproteinase (MMP)-2 and vascular endothelial growth factor (VEGF) in predicting the curative effect of radiofrequency ablation (RFA) in varicose vein of lower extremity (VVLE). Methods A retrospective analysis was performed on the clinical data of eighty-two patients with VVLE who underwent RFA from October 2022 to October 2024 at The Second Affiliated Hospital of Xi'an Jiaotong University. After 3 months of postoperative follow-up, patients were divided into effective group (n=70) and ineffective group (n=12) according to the curative effect. The differences in inferior vena cava blood flow parameters (mean diameter, reflux time, mean reflux velocity, blood flow volume), MMP-2 and VEGF between the two groups were compared, and predictive value of combined detection with the above indexes for curative effect was analyzed by ROC curves. Results Age, proportion of diabetes mellitus, mean diameter, reflux time, mean reflux velocity, blood flow volume, positive expressions of MMP-2 and VEGF in ineffective group were higher than those in effective group (P<0.05). ROC curves analysis showed that AUC values of mean diameter, reflux time, mean reflux velocity, blood flow volume and combined detection were 0.827, 0.837, 0.848, 0.821, and 0.915, respectively (P<0.05). The sensitivity, specificity and accuracy of inferior vena cava ultrasound blood flow parameters combined with MMP-2 and VEGF for predicting curative effect of RFA were 100.00%, 90.00% and 91.46%, higher than those of single index. The results of multivariate Logistic regression analysis showed that age, diabetes mellitus, inferior vena cava dysfunction (any ultrasound blood flow parameter≥cut-off value), positive MMP-2 and positive VEGF were all risk factors affecting curative effect of RFA (P<0.05). Conclusion Predictive value of inferior vena cava ultrasound blood flow parameters combined with MMP-2 and VEGF is high for curative effect of RFA in VVLE patients.

Objective To explore the predictive value of ¹⁸F-FDG PET/CT delayed imaging for lesion growth rate in patients with hepatic alveolar echinococcosis (HAE) who were unresponsive to drug therapy. Methods The patients with HAE who underwent dual phase (early phase+delayed phase) ¹⁸F-FDG PET/CT in the Department of Nuclear Medicine,the First Affiliated Hospital of Xinjiang Medical University from January 2014 to April 2024 were retrospectively collected. A total of 32 patients who did not undergo surgery and regularly took albendazole tablets (10 mg·kg^-1·d^-1) orally for a long time were analysed. The maximum standard uptake value (SUV_max), tumor to background ratios (TBR), infiltration zone width (W value) and maximum diameter of HAE lesions in 32 patients were compared before and after treatment. For these 32 patients, univariate and multivariate analyses were conducted using pre-treatment factors such as age, gender, lesion location, delayed-phase ¹⁸F-FDG PET/CT SUV_max, TBR, W value, maximum diameter as independent variables, with the annual growth rate of the lesion maximum diameter as the dependent variable. Results PET showed that the HAE lesions of 32 patients before and after drug treatment all exhibit ring-shaped hypermetabolism. After treatment, the SUV_max, TBR, and maximum lesion diameter in the delayed phase of PET/CT were greater than those before treatment (P<0.01); However, no significant differences were found in the overall distribution of W values before and after treatment (P>0.05). Among these 32 patients, The SUV_max, TBR and W value of infiltration zone before treatment were correlated with the annual growth rate of maximum diameter (P<0.001). SUV_max and TBR were highly positively correlated (P＜0.001), Thus, the SUV_max value and W value before treatment were included to predict the annual growth rate of maximum diameter of HAE. Both variables included in the model significantly influenced the annual growth rate of the HAE lesion maximum diameter (P<0.05). Conclusion Pre-treatment delayed-phase PET/CT SUV_max and W values are found to be predictive of the annual growth rate of lesions in patients with ineffective HAE drug treatment.

Objective To compare the differences in Ki-67 expression levels among newly diagnosed hepatocellular carcinoma (HCC) patients using machine learning methods and to investigate their role in preoperative prediction of immunohistochemical characteristics. Methods This dual-center study collected MRI data and immunohistochemical Ki-67 expression profiles from 59 newly diagnosed HCC patients at the 910th Hospital of Joint Logistics Support Force and Quanzhou First Hospital from November 2023 to October 2024. The cohort included 52 males and 7 females [age 32-55 (44.71±6.639) years], stratified into high-expression (Ki-67≥20%, n=37) and low-expression (Ki-67<20%, n=22) groups based on a 20% threshold. All patients underwent preoperative contrast-enhanced MRI (3.0T scanners: Siemens Skyra and GE Discovery 750) with T2WI. Tumor regions of interest were manually delineated using 3D Slicer, and 1,198 radiomic features (shape, first-order statistics, texture, and wavelet transforms) were extracted via the OnekeyAI platform. Synthetic minority oversampling technique addressed class imbalance, followed by rigorous preprocessing (missing value imputation, outlier detection, and data standardization). Eight machine learning models, including logistic regression, support vector machine, K-nearest neighbors, Random forest, extremely randomized trees (ERT), XGBoost, LightGBM, and multilayer perceptron, were implemented for Ki-67 classification. Results Random forest, ERT and XGBoost demonstrated superior performance during training, with XGBoost achieving the highest AUC (0.914), followed by Random forest (0.911) and ERT (0.833). In testing, these models maintained robust generalization capabilities, yielding AUCs of 0.741 (Random forest), 0.750 (ERT), and 0.777 (XGBoost), respectively. Conclusion This study demonstrates that a small-sample-based integration of T2WI radiomic features with machine learning algorithms enables effective preoperative prediction of Ki-67 proliferation index in HCC patients.

Objective To investigate the efficacy of preoperative prediction model for CD34 expression in hepatocellular carcinoma integrating contrast-enhanced ultrasound liver imaging reporting and data system (CEUS LI-RADS) and gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-DTPA-MRI) and explore the clinical value. Methods A retrospective cohort of 111 patients of HCC who underwent radical resection at the Affiliated Tumor Hospital of Guangxi Medical University from September 2021 to August 2024. Based on the postoperative pathological and immunohistochemical results, the patients were divided into CD34-positive group (n=76) and CD34-negative group (n=35). All the patients underwent CEUS and Gd-EOB-MRI examinations before operation. Comparison of imaging characteristics between CD34-positive and CD34-negative groups, including CEUS LI-RADS categories, CEUS LI-RADS major imaging features, LI-RADS M major imaging features, non-LI-RADS imaging features and Gd-EOB-MRI features. Independent predictors of CD34 positive expression identified by multivariate logistic regression analysis and the establishment of predictive model. Results In the multivariate analysis, the imaging characteristics of LI-RADS M major imaging features (early washout), non-LI-RADS imaging features (tumor capsule, Adler blood blow grade, tumor edge morphology) and Gd-EOB-MRI imaging features (peritumor enhancement) were independent predictors of CD34. The predictive model constructed by combining the above three imaging characteristics demonstrated excellent performance, with the area under the ROC curve of 0.914, sensitivity of 0.943, and specificity of 0.789, indicating optimal predictive efficacy. Conclusion The predictive model based on CEUS LI-RADS combined with Gd-EOB-MRI demonstrates significant value in predicting CD34 expression and clinical prognosis in patients with HCC.

Objective To evaluate the application and value of MRI and US in the diagnosis of proximal humerus fracture combined with rotator cuff injury. Methods Taken the results of surgical exploration as the "gold standard", 121 patients with suspected rotator cuff injury and proximal humerus fracture admitted to hospital from February 2022 to February 2025 were examined by MRI and US respectively, and the effects of different scanning methods on the detection of different tendon injuries, rotator cuff injuries and diagnostic indicators were compared. Results There was no significant difference in the incidence of supraspinatus tendon injury, infraspinatus tendon injury, subscapularis tendon injury, and teres minor tendon injury between the two scanning methods (P>0.05). However, there was a significant difference in the incidence of no rotator cuff injury (3.31% vs 4.13%, P<0.05), with a Kappa consistency coefficient of 0.130. There was no significant difference in the incidence of full-thickness tear, ligament injury, bone injury, and partial tear (P>0.05), but there was a significant difference in the total number (96.69% vs 94.21%, P<0.05), with a Kappa consistency coefficient of 0.622. Meanwhile, the diagnostic accuracy rate (0.9528), sensitivity (0.9600), negative predictive value (0.1667), and Youden index (0.9600) of US for diagnosing rotator cuff injury were lower than those of MRI (0.9603, 0.9677, 0.2000, 0.9677 respectively); the missed diagnosis rate of US for rotator cuff injury (0.0400) was higher than that of MRI (0.0323); the specificity (1), positive predictive value (0.9917), and misdiagnosis rate (0.00) of US for rotator cuff injury were consistent with those of MRI. Conclusion The two examination modalities have their own advantages and disadvantages, and the appropriate examination method should be selected according to the patient's specific situation in the clinic.

Objective To investigate the application value of magnetic resonance diffusion weighted imaging (MRI-DWI) combined with dynamic contrast enhanced MRI (DCE-MRI) in the diagnosis of prostate cancer (PCa). Methods A total of 106 patients with highly suspected PCa after clinical and laboratory examination were selected from the Department of Urology, Maanshan People's Hospital from January 2020 to December 2023. The patients were divided into PCa group (n=38) and benign group (n=68) according to the results of pathological examination. All patients underwent conventional MRI, DWI and DCE-MRI examinations, and multi-parameter image data were collected. The apparent diffusion coefficient (ADC), volume transfer constant (K^trans), interstitium-to-plasma rate constant (K_ep) and extravascular extracellular space volume fraction (V_e) were compared between the two groups. Multivariate logistic regression and ROC curve were used to analyze the diagnostic efficacy of each parameter for PCa. Results On the DWI sequence, most of the lesions in the PCa group showed high signal, and the ADC value was lower than that in the benign group (P<0.05). In DCE-MRI, the levels of K^trans and K_ep in PCa group were higher than those in benign group (P<0.05). There was no significant difference in V_e level between the two groups (P>0.05). Multivariate Logistic regression analysis showed that ADC value (OR=0.641), K^trans (OR=1.948) and K_ep (OR=1.790) were independent predictors of PCa (P<0.05). ROC curve analysis showed that the AUC of combined diagnosis of PCa was 0.944, compared with single detection (ADC: AUC=0.876; K^trans: AUC=0.802; K_ep: AUC=0.749), the difference was statistically significant (P<0.05). Conclusion MRI-DWI combined with DCE has high application value in the diagnosis of PCa, which can provide effective imaging support and reliable quantitative parameters for the early detection of lesions.

Objective To investigate the application value of magnetic resonance diffusion weighted imaging (MRI-DWI) combined with dynamic contrast enhanced MRI (DCE-MRI) in the diagnosis of prostate cancer (PCa). Methods A total of 106 patients with highly suspected PCa after clinical and laboratory examination were selected from the Department of Urology, Maanshan People's Hospital from January 2020 to December 2023. The patients were divided into PCa group (n=38) and benign group (n=68) according to the results of pathological examination. All patients underwent conventional MRI, DWI and DCE-MRI examinations, and multi-parameter image data were collected. The apparent diffusion coefficient (ADC), volume transfer constant (K^trans), interstitium-to-plasma rate constant (K_ep) and extravascular extracellular space volume fraction (V_e) were compared between the two groups. Multivariate logistic regression and ROC curve were used to analyze the diagnostic efficacy of each parameter for PCa. Results On the DWI sequence, most of the lesions in the PCa group showed high signal, and the ADC value was lower than that in the benign group (P<0.05). In DCE-MRI, the levels of K^trans and K_ep in PCa group were higher than those in benign group (P<0.05). There was no significant difference in V_e level between the two groups (P>0.05). Multivariate Logistic regression analysis showed that ADC value (OR=0.641), K^trans (OR=1.948) and K_ep (OR=1.790) were independent predictors of PCa (P<0.05). ROC curve analysis showed that the AUC of combined diagnosis of PCa was 0.944, compared with single detection (ADC: AUC=0.876; K^trans: AUC=0.802; K_ep: AUC=0.749), the difference was statistically significant (P<0.05). Conclusion MRI-DWI combined with DCE has high application value in the diagnosis of PCa, which can provide effective imaging support and reliable quantitative parameters for the early detection of lesions.

Objective To evaluate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based intratumoral-peritumoral radiomics model for prediction of lymphovascular invasion (LVI) in breast cancer. Methods This retrospective study analyzed 153 pathologically confirmed breast cancer patients from Peking University Shenzhen Hospital from January 2019 to September 2024. Patients were stratified into a training set (n=107) and a validation set (n=46) via 7:3 random stratified sampling. Tumor regions of interest were manually delineated on the second post-contrast DCE-MRI phase, with four peritumoral regions (2, 4, 6, 8 mm) generated by concentric expansion. Radiomic features were extracted and filtered for stability. Using the Random Forest classifier, intratumoral and multiple peritumoral models were constructed respectively. The optimal performing peritumoral region was selected and integrated with intratumoral radiomics features to establish an intratumoral-peritumoral combined model. A clinical model was constructed using significant predictors from univariate/multivariate analyses. Finally, a comprehensive model fused radiomic and clinical features. Model performance was assessed using AUC under the ROC curve. Results The 6 mm peritumoral model outperformed other peritumoral configurations. In the training set, AUC for the intratumoral, optimal peritumoral (6 mm), intratumoral-peritumoral, and clinical models were 0.850, 0.896, 0.916, and 0.787, respectively; corresponding validation AUC were 0.785, 0.742, 0.819, 0.748. The combined model demonstrated superior performance, with AUC of 0.934 (training) and 0.827 (validation). Conclusion The DCE-MRI based intratumoral-peritumoral radiomics model effectively predicts LVI status in breast cancer, with enhanced accuracy when integrated with clinical features.

Objective To investigate the clinical efficacy and risk factors of pneumatic tourniquet in orthopedic limb surgeries and analyze their effects and related influencing factors across different surgical subtypes (e.g., trauma, arthroplasty, arthroscopy) in upper and lower limb procedures. Methods A prospective observational cohort study was conducted, enrolling 30 patients from Shenzhen People's Hospital from November to December 2024. Patients were stratified by surgical sites into an upper limb group (n=6; subtypes: 5 trauma, 1 arthroscopy) and a lower limb group (n=24; subtypes: 13 arthroplasty, 8 trauma, 3 arthroscopy). Intraoperative blood loss, surgical field quality, postoperative physiological parameters (blood pressure, limb circumference, VAS pain score), laboratory markers (hemoglobin, D-dimer, C reactive protein), and neurological recovery were recorded. Results In the upper limb group, trauma surgery patients exhibited an 83.2% increase in postoperative D-dimer levels, significantly higher than the 78.9% increase in arthroscopy patients. In the lower limb group, arthroplasty patients demonstrated the largest D-dimer elevation (237%) and had lower postoperative VAS scores (3.0±1.0) compared to trauma patients (4.1±0.8, P=0.01). All neurological abnormalities resolved by postoperative day 3. Age was correlated with the amount of lower limb blood loss (r=0.32), while BMI was correlated with the changes in limb circumference (r=0.41, P<0.05). Conclusion Pneumatic tourniquets effectively optimize the surgical field in orthopedic procedures. Additionally, patient age showed a significant correlation with intraoperative blood loss and D-dimer increase in tourniquet-assisted surgeries, while BMI correlated significantly with changes in lower limb circumference, indicating that patients with larger limb circumferences may experience higher rates of postoperative limb swelling and neurological and limb sensory abnormalities compared to those with smaller limb dimensions. Therefore, enhanced monitoring and rehabilitation exercises are necessary after surgery.

Objective To explore the value of dual-sequence MRI radiomics model for prediction of Ki-67 expression level in breast cancer. Methods A retrospective analysis of MRI and clinical data of 177 patients with breast cancer confirmed by postoperative pathology at the First Affiliated Hospital of Bengbu Medical University from January 2023 to August 2024. They were divided into low expression group and high expression group according to immunohistochemical results, 3D Slicer software was used to manually extract the radiomics features from dynamic enhanced phase 2 and DWI images and screen the best combination features. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of clinical and imaging data, clinical model, single-sequence radiomics model, dual-sequence radiomics model, and a combined model were established, model performance was assessed using ROC curves, while calibration curves and decision curve analysis were used to evaluate clinical utility. Results Compared with the clinical and single-sequence radiomics models, the diagnostic efficacy of the dual-sequence radiomics model was better, and the AUC values in the training group and the validation group were 0.83 and 0.74, respectively. The diagnostic efficacy of the combined model was further improved, and the AUC values in the training group and the validation group were 0.85 and 0.83, respectively. Calibration and decision curves analysis indicated good agreement and favorable clinical benefit. Conclusion The dual-sequence MRI radiomics model has good diagnostic efficiency in predicting the expression level of Ki-67 in breast cancer, which is better than the single-sequence radiomics model and clinical model, these findings indicate that it is expected to become a non-invasive tool and provide help for clinical individualized treatment decision-making.

Objective To compare the diagnostic efficiency of transvaginal color Doppler ultrasound and contrast-enhanced ultrasound (CEUS) in pelvic tuberculosis. Methods A total of 90 patients with pelvic tuberculosis admitted to Hebei Chest Hospital were enrolled as the research objects between June 2022 and December 2023. All underwent transvaginal color Doppler ultrasound and CEUS examinations. The accuracy rate of the two methods in the diagnosis of pelvic tuberculosis was evaluated, imaging characteristics of the two methods were observed. Results The diagnosis accuracy rate of transvaginal color Doppler ultrasound was lower than that of CEUS [60.00% (54/90) vs 82.22% (74/90), P<0.05]. There was no significant difference in detection accuracy rates of tuberculosis at different sites (fallopian tube, fallopian ovary, endometrium, pelvic peritoneum) between the two methods (P>0.05). In color Doppler ultrasound, main types of pelvic tuberculosis were cystic masses and solid cystic masses, which were characterized by thick and rough cyst walls, irregular masses and unclear boundary. There was tubal enlargement and sausage-like lesions (34.44%). The main type of echoes was mixed type, there were grade I-Ⅲ blood flow signals around the lesions, with maximum lesions diameter of 45.38±15.37 mm. In CEUS, main type of pelvic tuberculosis was cystic masses, which were characterized by irregular masses, uneven filling of contrast agent, unclear boundary and abundant blood flow in the uterine cavity. The main type of echoes was mixed type (80.00%), with maximum lesion diameter of 46.47±14.56 mm, the difference was not statistically significant compared with that by color Doppler ultrasound (P>0.05). Conclusion Compared with transvaginal color Doppler ultrasound, CEUS has higher accuracy rate in the diagnosis of pelvic tuberculosis, which can objectively reflect blood perfusion of lesions and echoes in surrounding tissues, and play an important role in increasing accuracy rate in the early diagnosis of pelvic tuberculosis.

Objective To compare the early efficacy of transfemoral transcatheter aortic valve implantation (TF-TAVI) with transapical transcatheter aortic valve implantation (TA-TAVI) in the treatment of pure aortic regurgitation (PAR) based on echocardiography. Methods From January 2021 to November 2024, 96 patients with PAR who received treatment at the First Affiliated Hospital of University of Science and Technology of China were retrospectively enrolled. According to the surgical approach, patients were divided into the TF-TAVI group and the TA-TAVI group. The TF-TAVI group had 46 patients, including 22 males and 24 females, with the age of 56-85(72.39±7.40) years old; the TA-TAVI group had 50 patients, with 33 males and 17 females, with the age of 55-85(71.68±8.01) years old. Preoperative clinical data, perioperative data (surgical success rate, surgical duration, Length of hospital stay), echocardiographic parameters before and after surgery, and the incidence of postoperative complications were analyzed to compare the early surgical efficacy between the two groups. Results There were no statistically significant differences in preoperative clinical data between the two groups (P>0.05). The surgery duration and hospital stay in the TF-TAVI group were both shorter than those in the TA-TAVI group (P<0.05). The sizes of the left atrium and ventricle, left ventricular volume, stroke volume, cardiac output, and pulmonary artery systolic pressure in both groups were significantly reduced compared to preoperative values (P<0.05); the left ventricular wall thickness was relatively increased compared to preoperative values (P<0.05); the preoperative and postoperative diameters of the aortic sinus and the preoperative left ventricular end-diastolic diameter (LVIDd) in the TF-TAVI group were smaller than those in the TA-TAVI group (P<0.05); however, there was no statistically significant difference in postoperative LVIDd between the two groups (P>0.05). The incidence of postoperative pericardial effusion in the TF-TAVI group was lower than that in the TA-TAVI group (P<0.05); but, the incidence of postoperative conduction block and the rate of permanent pacemaker implantation were higher in the TF-TAVI group than in the TA-TAVI group (P<0.05). Conclusion Echocardiography can effectively evaluate the structure and function of the left cardiac before and after transcatheter aortic valve implantation (TAVI), and quantitatively analyze the effectiveness of left ventricular reverse remodeling. The efficacy and perioperative safety of TF-TAVI and TA-TAVI in the treatment of pure aortic regurgitation are comparable, both are safe and effective surgical options.

Objective To evaluate and compare the clinical outcomes of endoscopic variceal ligation (EVL) and endoscopic cyanoacrylate injection (ECI) for the treatment of esophagogastric variceal bleeding (EVB) in cirrhotic patients. Methods A total of 124 patients with cirrhotic EVB who were admitted to Nanchong Central Hospital from January 2022 to January 2025 were selected and randomly divided into two groups using a random number table method: the ECI group and the EVL group, with 62 patients in each group. The two groups were evaluated for clinical efficacy, success of hemostasis, clinical indicators, early rebleeding rates, blood biochemistry, and complications. Results There were no statistically significant differences between the EVL and ECI groups in terms of overall efficacy, hemostasis success rate, bleeding cessation time, transfusion volume, hospital stay and early rebleeding rate (P>0.05). The EVL group had lower hospitalization costs compared to the ECI group (P<0.05). Biochemical indicators at 6 weeks post-treatment showed improvement in both groups compared to pre-treatment levels (P<0.05), with no significant differences between the groups (P>0.05). The incidence of postoperative complications in the EVL group was 17.74%, mainly fever and esophageal stenosis, which was lower than the 37.10% in the ECI group, mainly fever and ulcers (P<0.05). Conclusion Both ECI and EVL are effective treatments for cirrhotic EVB. However, compared with ECI, EVL treatment can reduce hospitalization costs and minimize the occurrence of complications.

Objective To develop a model integrating ultrasound radiomics features and clinical indicators for the preliminary prediction of prostate cancer bone metastasis and to explore its diagnostic value. Methods One hundred and ten patients who underwent transrectal two-dimensional prostate ultrasound, whole-body bone scan, and were pathologically confirmed to have prostate cancer (via biopsy or radical resection specimens) at the Affiliated Cancer Hospital of Xinjiang Medical University from April 2023 to April 2024 were retrospectively enrolled. Based on the presence of bone metastasis detected by whole - body bone scan, they were categorized into group A (bone metastasis-positive) and group B (bone metastasis-negative). After delineating target lesions and extracting ultrasound gray-scale features, we compared the ultrasound radiomics features and clinical indicators between the two groups. Then, we constructed three prediction models for prostate cancer bone metastasis: the ultrasound radiomics prediction model, the clinical feature prediction model, and the combined prediction model. Internal validation, calibration, and ROC curve analysis were performed to assess the models predictive efficacy. Results Clinical baseline data analysis revealed that total prostate-specific antigen was an independent risk factor for clinical manifestations (P<0.05). Nine ultrasound radiomics features were selected to build the radiomics prediction model. The AUC of the clinical model was 0.719 (95% CI: 0.656-0.855), while the combined model exhibited superior predictive performance with an AUC of 0.850 (95% CI: 0.482-0.820). The calibration curve indicated that the Nomogram had favorable predictive capability, and the DCA curve demonstrated that the combined model possessed high clinical applicability. Conclusion The nomogram integrating clinical and ultrasound features holds certain clinical value in predicting prostate cancer bone metastasis. It can provide a reference for ultrasonographers and clinicians in diagnosis and treatment decision - making.

Objective To investigate the differential diagnostic value of energy spectrum CT imaging combined with tumor markers on lung adenocarcinoma and squamous cell carcinoma. Methods The medical records of patients who visit to Guangyuan Central Hospital from May 2022 to May 2024 with suspected lung space-occupying lesions who needed to be confirmed by enhanced CT scan were retrospectively analyzed. The patients were pathologically confirmed as lung adenocarcinoma (n=78) and lung squamous cell carcinoma (n=30). energy spectrum CT imaging examination (GE Discovery 750 gemstone energy spectrum 64-slice CT scanner) and serum tumor marker detection were conducted on all patients. The energy spectrum CT imaging was compared between groups of patients. The levels of serum tumor markers were measured, and the diagnostic value of energy spectrum CT imaging combined with serum tumor markers on lung adenocarcinoma and squamous cell carcinoma was analyzed by ROC curve. Delong test was adopted to compare the difference in the area under the curve (AUC) between each single index and combined model. Results Compared with lung squamous cell carcinoma group, the proportions of peripheral type distribution, ground glass nodule and pleural depression in lung adenocarcinoma group were higher (P<0.05) while the proportions of vascular convergence sign and mediastinum invasion were lower (P<0.05). Serum tumor markers levels in lung adenocarcinoma group were lower than those in lung squamous cell carcinoma group (P<0.05). The AUC of combined detection of enhanced arterial phase CT value, venous phase CT value, carcinoembryonic antigen, neuron-specific enolase, cytokeratin 19 soluble fragment 21-1 and squamous cell carcinoma antigen was higher than that of single detection, and the above AUCs were 0.92 (0.854-0.965), 0.87 (0.787-0.924), 0.70 (0.834-0.953), 0.91 (0.834-0.953), 0.93 (0.859-0.968), 0.93 (0.859-0.968), 0.76 (0.668-0.837) and 0.98 (0.966-1.000) respectively, and the sensitivity and specificity of combined detection (0.97, 0.96) were higher than those of single detection (0.80, 0.80, 0.96, 0.90, 0.90, 0.96; 0.90, 0.83, 0.77, 0.87, 0.87, 0.57). Conclusion Energy spectrum CT imaging combined with tumor markers has differential diagnostic significance in the diagnosis of lung adenocarcinoma and lung squamous cell carcinoma.

Objective To explore the diagnostic value of non-contrast dual-layer spectral detector CT with multiple parameters in acute pulmonary embolism. Methods Fifty-two patients (86 lesions) with acute pulmonary embolism who underwent non-contrast and CT pulmonary angiography (CTPA) using dual-layer spectral detector CT at the Second People's hospital of Hefei (Hefei Hospital Affiliated to Anhui Medical University) from January 2022 to October 2023 were retrospectively analyzed. Taking CTPA as the gold standard, subjective visual evaluation was performed on four sets of images including conventional 120 kVp polyenergetic images (PI), effective atomic number maps (Z_eff), Electron density maps (EDM), and EDM- Z_eff fusion maps, and the detection rate of pulmonary embolism was calculated for each set of images.A pulmonary embolism group and a control group were set up according to the presence or absence of emboli in the blood vessels.CT_PI, CT_{40 keV}, CT_{70 keV}, CT_{100 keV}, ED values and Z_eff values were measured and recorded between the two groups, then compare the differences and perform multivariate logistic regression to construct a regression model. ROC curve was applied to evaluate the diagnostic efficiency of each parameter and logistic regression model. Delong test was used to compare the AUCs. Results The detection rates of APE on PI, Z_eff, EDM, EDM and Z_eff map fusion images were 10.47%, 1.16%, 54.65%, 69.77%, respectively. The subjective scoring Kappa values of the four sets of images were 0.73, 0.79, 0.81, and 0.84, respectively. Except for Z_eff values, CT_PI, CT_{40 keV}, CT_{70 keV}, CT_{100 keV}, ED values in pulmonary embolism group were statistically higher than those in control group (P<0.05).Among all the parameters,the logistic regression model has the highest diagnostic efficiency (AUC=0.76), with a threshold of 0.56, sensitivity and specificity in diagnosing APE were 58.1% and 87.2%, respectively. Delong test showed that the AUC of CT_40keV was lower than CT_{70 keV}, CT_{100 keV}, logistic groups (P<0.05), and the AUC of CT_PI was lower than CT_100keV、Logistic groups (P<0.05), then there was no significant difference in the AUC of other parameters (P>0.05). Conclusion The combination of non-contrast images of dual-layer spectral detector CT PI, VMI, EDM have important diagnostic value for acute pulmonary embolism.

Alzheimer's disease (AD), as an irreversible chronic neurodegenerative disorder, early diagnosis and intervention are crucial for delaying the disease progression. Diffusion tensor imaging (DTI), an important branch of MRI, can non-invasively assess the microstructural changes of brain tissue, providing unique value for the early diagnosis and pathological mechanism research of AD. This study will review several aspects including the pathological mechanism of AD, the principle and parameters of DTI, the changes of DTI parameters during the pathological process of AD, and the correlation between DTI parameters and the pathological development of AD, in order to explore the feasibility of using DTI parameters as clinical diagnostic indicators and their correspondence with disease stages, aiming to provide references for the early diagnosis and pathological mechanism research of AD.

The accurate diagnosis and treatment of coronary artery disease rely on the evaluation of myocardial microcirculation and function. However, the traditional myocardial computed tomographic perfusion (CTP) has limited its clinical application due to the high radiation dose (15-25 mSv). In recent years, through the integration of the third-generation dual-source CT, dynamic stress protocols and deep learning techniques, the radiation dose of CTP has been significantly reduced to 3.26 mSv (a 78% reduction), while the diagnostic specificity has been increased to 92%. Dynamic CTP combined with computed tomography angiography can simultaneously assess the coronary artery anatomy and myocardial perfusion function, achieving a "one-stop" diagnosis and avoiding 30%-50% of unnecessary invasive examinations. Artificial intelligence further optimizes the diagnostic process by automatically quantifying perfusion defects and predicting prognosis; multimodal integration (such as CTP+PET) increases the diagnostic sensitivity and specificity to 95% and 92% respectively. This article systematically reviews the technological progress, clinical application value and future directions of low-dose CTP, providing an evidence-based basis for optimizing the accurate diagnosis and treatment of coronary artery disease.

Glioma is the most common primary malignant brain tumor, and its treatment and prognosis are closely related to the tumor microenvironment, individualized diagnosis and treatment of Pathogenesisma is of great significance. The tumor microenvironment of glioma consists of tumor cells and surrounding components, which has an important impact on the behavior of the tumor. A better understanding of the tumor microenvironment of glioma will contribute to more effective treatment of the tumor and improvement of prognosis. Magnetic resonance has been widely used in the clinical evaluation of glioma, but it still has certain limitations in evaluating the tumor microenvironment of glioma. Radiomics can extract information with high throughput from images of various modalities and has been widely used in the diagnosis and treatment of glioma in recent years. However, there has been no research to systematically summarize the studies on radiomics in predicting the microenvironment of glioma. This paper comprehensively reviews the advancements in the application of MRI-based radiomics for predicting the tumor microenvironment of glioma.

Ulcerative colitis (UC), as a chronic non-specific inflammatory bowel disease, requires long-term medical treatment for patients. With the popularization of biological agents, the progression of the disease can be effectively delayed. However, there are individual differences in treatment response among patients. Improper use may lead to therapeutic non-response or even aggravation of the condition. If effective efficacy assessment can be conducted in the early stage of UC treatment, the drug regimen can be timely adjusted to avoid adverse reactions of drug therapy. This article reviews the application of ultrasound in the assessment of UC activity and efficacy, as well as the progress in the application of new ultrasound technologies in UC.

Renal cell carcinoma (RCC) is a common malignant tumor of the urinary system. CT remains the primary imaging modality for renal tumor diagnosis. Radiomics, a computer-based imaging analysis approach, has demonstrated remarkable performance in distinguishing benign from malignant tumors, predicting pathological grading, and analyzing genetic mutations by extracting high-throughput quantitative features from CT images and integrating statistical methods with machine learning models. In recent years, the continuous advancements in radiomics and artificial intelligence have highlighted its potential in personalized diagnosis and treatment of RCC, driving the evolution of precision medicine. This review summarizes recent advances in CT-based radiomics for diagnosis, subtype classification, pathological grading, molecular prediction, and personalized treatment strategies in renal cell carcinoma. Furthermore, it explores future directions to optimize its clinical translation and application.