Objective To investigate the function of glymphatic system in patients with mild traumatic brain injury via diffusion tensor imaging analysis along the perivascular space(DTI-ALPS)index and its relationship with clinical features.Methods The clinical and imaging data from 163 patients with mild traumatic brain injury were retrospectively collected,including 31 cases with MRI-negative findings and 132 cases with MRI-positive findings.In addition,29 healthy individuals underwent physical examinations were included as a control group.The differences in DTI-ALPS index and clinical features between mild traumatic brain injury and control group,as well as among subgroups of traumatic brain injury were analyzed.Results The DTI-ALPS index in patients with mild traumatic brain injury were significantly higher than those in control group(P＜0.05).Subgroup analysis showed that DTI-ALPS index of traumatic brain injury patients with MRI-negative findings and MRI-positive findings were all significantly higher than those of control group(P=0.023 and 0.004,respectively).Compared to control group,DTI-ALPS index in mild traumatic brain injury patients gradually increased with the progression of injury,and the difference was statistically significant(P=0.008).Conclusion Patients with mild traumatic brain injury exhibit increased functional activity of glymphatic system,as indicated by increased DTI-ALPS index,which further increase with the progression of injury.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective To discuss the application of enhanced MRI-based radiomics nomogram in predicting the efficacy of initial transcatheter arterial chemoembolization(TACE)in patients with intermediate to advanced hepatocellular carcinoma(HCC).Methods A total of 195 patients with advanced HCC(CNLC Ⅱ b-Ⅲb),who received initial TACE at the Affiliated Fifth Hospital of Wenzhou Medical University(Center 1)from January 2019 to March 2024,at the Lishui Municipal People's Hospital(Center 2)from July 2021 to June 2023,and at the Rui'an Municipal People's Hospital(Center 3)from January 2022 to January 2024,were enrolled in this study.A total of 134 patients from Center 1 were randomly divided into a training set(n=94)and an internal validation set(n=40)at a 7∶3 ratio;and other 61 patients from Center 2 and Center 3 were selected as the external validation set.Based on the modified Response Evaluation Criteria in Solid Tumors(mRECIST)criteria,the early efficacy of the initial TACE procedure was evaluated.The patients were divided into an effective group and an ineffective group.The tumor contours were delineated on the arterial,portal,and equilibrium phase images of enhanced MRI,and the corresponding radiomics features were extracted.Based on reduced-dimensional features,the Logistic regression,support vector machine,lightweight gradient boosting machine,and multi-layer perceptron models were established.Univariate analysis and multivariate logistic regression analysis were used to screen independent predictive factors,and a nomogram was established in conjunction with the optimal radiomics score.The area under the receiver operating characteristic curve(AUC)was used to evaluate the performance of the model,and decision curve analysis was adopted to calculate the net benefits.Results After screening,9 key radiomics features were obtained.The lightweight gradient boosting machine model showed good prediction performance.The AUCs of the training set,internal validation set,and external validation set were 0.909,0.836 and 0.783 respectively,which was selected as the optimal radiomics model.The nomogram constructed based on AFP level,peritumoral enhancement,and optimal radiomics score could further improve its performance,with AUC values of 0.962,0.890 and 0.821 in the training set,internal validation set,and external validation set respectively.Decision curve analysis showed that this model could bring higher net benefits to patients.Conclusion The nomogram constructed based on the enhanced MRI-based radiomics combined with AFP level and peritumoral enhancement can effectively predict the efficacy of the initial TACE in patients with intermediate to advanced HCC.

Objective To investigate the function of glymphatic system in patients with mild traumatic brain injury via diffusion tensor imaging analysis along the perivascular space(DTI-ALPS)index and its relationship with clinical features.Methods The clinical and imaging data from 163 patients with mild traumatic brain injury were retrospectively collected,including 31 cases with MRI-negative findings and 132 cases with MRI-positive findings.In addition,29 healthy individuals underwent physical examinations were included as a control group.The differences in DTI-ALPS index and clinical features between mild traumatic brain injury and control group,as well as among subgroups of traumatic brain injury were analyzed.Results The DTI-ALPS index in patients with mild traumatic brain injury were significantly higher than those in control group(P＜0.05).Subgroup analysis showed that DTI-ALPS index of traumatic brain injury patients with MRI-negative findings and MRI-positive findings were all significantly higher than those of control group(P=0.023 and 0.004,respectively).Compared to control group,DTI-ALPS index in mild traumatic brain injury patients gradually increased with the progression of injury,and the difference was statistically significant(P=0.008).Conclusion Patients with mild traumatic brain injury exhibit increased functional activity of glymphatic system,as indicated by increased DTI-ALPS index,which further increase with the progression of injury.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective To explore the application value of the nomogram based on dual-energy CT in preoperative evaluation of human epidermal growth factor receptor 2(HER-2)status in patient with breast cancer.Methods A total of 269 patients with pathologically confirmed breast cancer were retrospectively collected and randomly divided into a training cohort(n=189)and a validation cohort(n=80)at a ratio of 7︰3.The dual-energy CT parameters and clinical features of all patients were measured and collected.Varia-bles with significant difference in univariate analysis were included in the multivariate logistic analysis to obtain independent risk fac-tors related to HER-2 status,with establishing a nomogram model.Receiver operating characteristic(ROC)curves were plotted to evaluate the predictive performance of the nomogram.Results There was a significant difference in axillary lymph node enlargement between the two groups(P<0.05).The venous phase iodine concentration(IC)and normalized iodine concentration(NIC)in the HER-2 positive group were significantly higher than those in the HER-2 negative group(P<0.05).Axillary lymph node enlargement,venous phase IC,and venous phase NIC were the independent risk factors for predicting HER-2 status in breast cancer.The nomogram con-structed from the above features exhibited good predictive performance,with area under the curve(AUC)of 0.856 and 0.834 in the training and validation cohorts,respectively.Conclusion The nomogram based on dual-energy CT has a high predictive value for HER-2 status in breast cancer patients.

Objective To investigate the difference of CT features of gastrointestinal stromal tumors(GIST),neurogenic tumors,and leiomyomas in stomach.Methods A retrospective analysis was performed on clinical and CT features from 312 cases of GIST,21 cases of neurogenic tumors,and 35 cases of leiomyomas in stomach.Results GIST were most commonly found in the body of stomach and exhibited large tumor sizes and late onset.CT showed GIST predominantly showed intraluminal and mixed growth pattern with irregular or round shapes and uneven density,and cystic degeneration and calcification were frequently observed.The CT values of GIST in the arterial phase and the degree of arterial enhancement were higher,with light to moderate arterial phase enhancement and moderate to marked venous phase enhancement.Gastric leiomyomas had smaller tumor sizes and presented mainly in the cardia,gastric fundus,and lesser curvature of gastric body.CT showed the intraluminal growth pattern,primarily in round shapes with uniform density,lower incidence of cystic degeneration and calcification,both the arterial and venous phase CT values and the extent of enhancement in these phases were lower,showed no or slight enhancement during the arterial phase and light to moderate enhancement during the venous phase.Gastric neurogenic tumors were predominantly located in the gastric body and antrum.CT showed the tumors demonstrated extraluminal and mixed growth patterns,most with oval-shaped appearace,uniform density and the venous phase CT values and the degree of enhancement were higher,with light to moderate arterial enhancement and moderate to marked venous enhancement.Conclusion GIST,neurogenic tumors,and leiomyomas in stomach can be differentiated based on their distinct CT features.Accurate recognition of these features aids in the differential diagnosis of these kinds of tumors.

Objective:To investigate the application value of dual-energy CT in the differential diagnosis of lung metastases and benign nodules in breast cancer.Methods:The data of 96 patients with pathology-confirmed breast cancer at the Fifth Affiliated Hospital of Wenzhou Medical University from March 2017 to June 2021 were analyzed retrospectively. All patients received dual-energy chest CT scans within 2 weeks before surgery. All 96 patients were female, aged 31-84 (56±12) years. A total of 207 pulmonary nodules from 96 patients were classified into 81 lung metastases and 126 benign nodules according to pathological findings. Conventional CT features [longest diameter, boundary, location and CT value difference between arterial and venous phases (ΔCT) of nodules] and dual-energy CT parameters [standardized iodine concentration (NIC), slope of energy spectrum (λ HU) and normalized effective atomic number (nZ eff) in arterial and venous phases] were analyzed and measured. The χ 2 test, independent samples t test and Kruskal-Wallis rank-sum test were used to analyze the differences of conventional CT features and dual-energy CT parameters between lung metastases and benign nodules. First, the least shrinkage and selection operator (LASSO) regression method was used to screen conventional CT features and dual-energy CT parameters, and then logistic regression analysis was performed to screen out independent risk factors for lung metastases. Receiver operating characteristic (ROC) curves were used to evaluate the efficacy of CT parameters alone and logistic model in differentiating lung metastases from benign lung nodules. Results:There were statistically significant differences between lung metastases and benign nodules in longest diameter, ?CT, NIC, λ HU and nZ eff in arterial and venous phases (all P<0.05). LASSO regression and binary logistic regression analysis showed that the venous phase λ HU (OR=59.413, 95%CI 14.233-248.002, P<0.001) and the venous phase nZ eff (OR=4.508, 95%CI 2.787-7.290, P<0.001) were independent risk factors for predicting lung metastases. Among them, the venous phase λ HU had the highest diagnostic efficiency, with an area under curve (AUC) of 0.794 and an accuracy of 74.88%. The AUC of the logistic model constructed by combining the venous phase λ HU and the venous phase nZ eff could reach 0.958, and the accuracy was improved to 92.27%, which was significantly higher than the efficacy of the two alone ( Z=6.02, 9.54, all P<0.001). Conclusion:Dual-energy CT has great application value in the identification of lung metastases and benign nodules in patients with breast cancer, especially when combined with venous phase λ HU and venous phase nZ eff, the diagnostic efficiency is further improved.

Objective: To evaluate image quality and radiation dosage of CT cerebral perfusion (CTP) imaging of 70 kV with different tube current and scanning passes and its diagnostic value for hyperacute cerebral infarction. Methods: A total of 190 patients with suspected hyperacute cerebral infarction in Lishui Central Hospital of Zhejiang Province from December 2017 to February 2019 were selected prospectively, and all patients were divided into 4 groups according to random number table and received non-contrast CT examination and dual-source CT cerebral perfusion imaging with 70 kV protocol simultaneously within 6 hours after the onset of symptoms: group A, 120 mA, 21 scanning time points; group B, 100 mA, 21 scanning time points; group C, 100 mA, 17 scanning time points; group D, 80 mA, 21 scanning time points. The values of perfusion parameters such as cerebral blood flow (CBF), crerbral blood volume (CBV), mean transit time (MTT), time to peak (TTP) were acquired. Image quality was evaluated and effective dose (ED) was recorded. The quantitative variables of image quality and radiation dosage were compared between four groups using one-way analysis of variance test. Results: There was no differences between groups on the CBF, CBV, MTT, TTP maps for all CTP values (P>0.05), and all images could meet the diagnostic requirements. The subjective image quality score of vessel sharpness and overall image quality of both internal carotid artery and middle cerebral artery and the degree of noise of internal carotid in artery in group A was higher than that in group D (P<0.05). The score of vessel sharpness of internal carotid in artery ingroup A was higher than those in both groups B and C (P<0.05). The scores of vessel sharpness of both internal carotid artery and middle cerebral artery internal carotid in artery ingroups B and C were higher than that in group A (P<0.05). The mean EDs of non-contrast CT in group A, B, C, D were 1.10, 2.11, 1.76, 1.42, 1.40 mSv; compared to group A, ED was reduced approximately 16.6% (0.35/2.11), 32.7% (0.69/2.11) and 33.6% (0.71/2.11), respectively (P<0.05). The diagnostic accuracy of low dose dual source CTP for detecting hyperacute cerebral infarction was 93.5% (172/184), while that of non-contrast CT was 52.2% (96/184);for detecting hyperacutelacunar cerebral infarction, it was 72.1% (31/43) and 16.3% (7/43) respectively (P<0.05). Conclusion Appropriate reduction of tube current (100 mA) and scanning passes (17 scanning time points) can reduce the radiation dosage and acquire comparable image quality for 70 kV protocol CTP. Compared with non-contrast CT, low dose dual-source CTP is more sensitive to hyperacute cerebral infarction, especially hyperacute lacunar cerebral infarction.