Objective:To investigate the value of CT radiomic model based on analysis of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in differentiating stage T1-2 from stage T3-4 gastric cancer.Methods:This study was a case-control study. Totally 465 patients with gastric cancer treated in Affiliated People′s Hospital of Jiangsu University from December 2011 to December 2019 were retrospectively collected. According to postoperative pathology, they were divided into 2 groups, one with 150 cases of T1-2 tumors and another with 315 cases of T3-4 tumors. The cases were divided into a training set (326 cases) and a test set (139 cases) by stratified sampling method at 7∶3. There were 104 cases of T1-2 stage and 222 cases of T3-4 stage in the training set, 46 cases of T1-2 stage and 93 cases of T3-4 stage in the test set. The axial CT images in the venous phase during one week before surgery were selected to delineate the region of interest (ROI) at the primary lesion and the extramural gastric adipose tissue adjacent to the cancer areas. The radiomic features of the ROIs were extracted by Pyradiomics software. The least absolute shrinkage and selection operator was used to screen features related to T stage to establish the radiomic models of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer. Independent sample t test or χ2 test were used to compare the differences in clinical features between T1-2 and T3-4 patients in the training set, and the features with statistical significance were combined to establish a clinical model. Two radiomic signatures and clinical features were combined to construct a clinical-radiomics model and generate a nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate the efficacy of each model in differentiating stage T1-2 from stage T3-4 gastric cancer. The calibration curve was used to evaluate the consistency between the T stage predicted by the nomogram and the actual T stage of gastric cancer. And the decision curve analysis was used to evaluate the clinical net benefit of treatment guided by the nomogram and by the clinical model. Results:There were significant differences in CT-T stage and CT-N stage between T1-2 and T3-4 patients in the training set ( χ2=10.59, 15.92, P=0.014, 0.001) and the clinical model was established. After screening and dimensionality reduction, the 5 features from primary gastric cancer and the 6 features from the adipose tissue outside the gastric wall beside cancer established the radiomic models respectively. In the training set and the test set, the AUC values of the primary gastric cancer radiomic model were 0.864 (95% CI 0.820-0.908) and 0.836 (95% CI 0.762-0.910), and the adipose tissue outside the gastric wall beside cancer radiomic model were 0.782 (95% CI 0.731-0.833) and 0.784 (95% CI 0.702-0.866). The AUC values of the clinical model were 0.761 (95% CI 0.705-0.817) and 0.758 (95% CI 0.671-0.845), and the nomogram were 0.876 (95% CI 0.835-0.917) and 0.851 (95% CI 0.781-0.921). The calibration curve reflected that there was a high consistency between the T stage predicted by the nomogram and the actual T stage in the training set ( χ2=1.70, P=0.989). And the decision curve showed that at the risk threshold 0.01-0.74, a higher clinical net benefit could be obtained by using a nomogram to guide treatment. Conclusions:The CT radiomics features of primary gastric cancer lesions and the adipose tissue outside the gastric wall beside cancer can effectively distinguish T1-2 from T3-4 gastric cancer, and the combination of CT radiomic features and clinical features can further improve the prediction accuracy.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective: To describe the current status of the prevalence of co-morbid myopia and obesity among 7-18 years students in the Inner Mongolia Autonomous Region in 2021 and to analyze the moderating effect of lifestyle in this association ，so as to provide scientific basis for the establishment of the mechanism of Co-morbidity，Shared Etiology，and Shared Prevention of common diseases in children and adolescents. Methods: A total of 139 630 primary and secondary school students aged 7-18 years from Inner Mongolia Autonomous Region were selected by stratified random cluster sampling method in September,2021. Myopia was determined using distance visual acuity examination and refractive error examination, and obesity was determined according to the BMI classification criteria for overweight, obesity screening of Chinese school age children and adolescents. Used a questionnaire, healthy lifestyles were determined according to the American Heart Association s Healthy Lifestyle Score by totaling the six scores for smoking, alcohol consumption, diet, exercise, screen time, and sleep duration.The χ 2 test was used to compare the association between group differences in the co-morbidity rate of myopia and obesity. The multivariable Logistic regression model was used to explore the influencing factors of the co-morbidity of myopia and obesity, and the stratified analysis was used to analyze the moderating effect of lifestyles on the prevalence of the co-morbidity. Results: The prevalence of myopia and obesity co-morbidity among students aged 7-18 years old in the Inner Mongolia Autonmous Region in 2021 was 13.7%, higher among boys than girls ( 15.5 % vs. 11.8%), higher among those aged 10-12 years old than 7-9,13-15,and 16-18 years old (14.7%,13.7%, 13.3%, 12.0%), higher among other ethnic minorities than Han Chinese and Mongolians (15.3%, 14.0%, 12.5%), higher in urban areas than that in suburban areas(15.3%, 13.0%), and middle economic level tracts were higher than poor and good tracts (14.8%, 12.9 %, 12.6%) ( χ 2=392.37，115.73，62.80，119.02，121.60, P <0.05). Multivariable Logistic regression modeling showed that unhealthy lifestyles ( OR=1.24, 95%CI=1.19-1.29 ) and middle level of lifestyle score ( OR=1.15, 95%CI=1.10-1.19 ) students had higher prevalence of co-morbidity, and the results were statistically significant among both boys and girls, the age groups of 10- 12, 13-15, and 16-18 years old, as well as the Han and Mongolian ethnic groups (all P <0.05). Conclusion In 2021, the current situation of myopia and obesity co-morbidity and unhealthy lifestyles among primary and secondary school students in the Inner Mongolia Autonomous Region are not optimistic.

Objective To evaluate the application of exponential apparent diffusion coefficient (eADC)value in differentiating benign from malignant thyroid nodules.Methods Routine MR sequences and axial diffusion weighted imaging (DWI)sequences with different b-values(0, 300,500,800 s/mm2)were performed in 46 patients with 51 histopathologically confirmed thyroid nodules,including 35 malignant nodules and 1 6 benign nodules.The eADC values of each thyroid nodules’solid component with different b-values were measured and assessed by independent samples t test.Receiver operating characteristic (ROC)curves were drawn and used to determine the diagnostic threshold and assess the screen test.Results The eADC values of the malignant nodules were higher than that of benign nodules (P<0.05)in all of the three different b-values.The eADC values of the malignant nodules and the benign nodules were 0.618±0.080 and 0.492±0.071 (b=300 s/mm2),0.520±0.104 and 0.371±0.077 (b=500 s/mm2)and 0.407±0.114 and 0.286±0.097 (b=800 s/mm2)respectively. According to the ROC curve,the area under the curve(AUC)was 0.883,0.890 and 0.824 when the b-value was set as 300,500 and 800 s/mm2respectively.When the b-value was set as 500 s/mm2and the diagnostic threshold was 0.454,the sensitivity,specificity, positive predictive value,negative predictive value and Youden index were 74.3%,93.8%,96.3%,60.9% and 0.68,respectively.Conclusion The eADC value is helpful in differentiating benign from malignant thyroid nodules,and the best result can be obtained by using DWI with b-value of 500 s/mm2.

Objective To observe the value of MRI in evaluation on the morphology and function of iliococcygeal muscles in fertile and nulliparous women.Methods Totally 50 healthy fertile women (fertile group,further divided into cesarean section subgroup and spontaneous delivery subgroup according to the mode of delivery) and 17 nulliparous healthy women (nulliparous group) underwent MR scanning in both natural and increased abdominal pressure state.Iliococcygeus thickness (ICT),coronal iliococcygeal angle (cICA) and sagittal iliococcygeal angle (sICA) of different states were measured and compared between the groups.Results In the natural state,the right and bilateral average sICA in the fertile group were larger than those in nulliparous group (both P＜0.05),while no statistical difference of ICT,right,left and bilateral average cICA and left sICA were found between two groups (all P＞0.05);the bilateral average sICA in spontaneous delivery subgroup was larger than that in cesarean section subgroup (P＜0.05).In increased abdominal pressure state,left,right sICA and bilateral average sICA in fertile group were larger than those in nulliparous group (all P＜0.05),while there was no statistical difference of ICT and cICA between two groups (all P＞0.05);no statistical difference of ICT,cICA nor sICA was found between spontaneous delivery subgroup and cesarean section subgroup (all P＞0.05).Conclusion MRI can accurately evaluate morphological and functional changes of iliococcygeal muscle in females.

Objective To analyze CT findings of nasal NK/T-cell lymphoma.Methods The CT findings of 11 nasal NK/T-cell lymphomas, 134 nasal polyps and 24 nasal inverted papillomas were analyzed retrospectively.Fisher exact test was used to compare the differences of the three nasal lesions.Results Compared with the nasal polyps, nasal NK/T-cell lymphoma had a higher occurrence in the unilateral nasal cavity, more presented as nodular mass or mold growth,and more easily to invade nasal vestibule,nasal ala,nasal mucosal,nasopharyngeal wall and causebone destruction.Compared with the inverted papilloma,nasal NK/T-cell lymphoma had a higher incidence of tumor invasion to nasal vestibule, nasal ala, nasopharyngeal cavity, nasal mucosal.Conclusion Nasal NK/T-cell lymphoma is a homogenous tumor and often occurres in the unilateral nasal cavity, which creeps along the lateral wall of the nasal cavity, and causes the damage of nasal mucosal and surrounding soft tissue and slight destruction of bone in the early satge.

Objective To evaluate the accuracy of MSCT in the pre-operative N-staging and diagnosis of metastatic lymph nodes in each group of gastric cancer.Methods Pathological and CT data of 91 patients with gastric cancer proved by surgery and pathology were analyzed retrospectively.Three-phase dynamic enhancements were performed before surgery in a unified way of hypotonic oral water,N-stage and grouping of lymph nodes of the preoperative CT imaging were evaluated by using the established diagnostic criteria and then compared with the results of surgery and pathology,the accuracy of staging and grouping was analyzed by using Kappa test.Results The accuracy of MSCT diagnosing the N-staging as a whole was 86.3%.The accuracy for N0,N1,N2 and N3 was 83.5%,89.0%,83.5% and 89.0%,respectively.The sensitivity was 86.5%,83.3%,50% and 47.4%,respectively.The specificity was 79.5%,89.4%,89.6% and 100.0%, respectively.The sensitivity for N0 was statistically different from that for N2, N0 and N3(P≤0.007).The detected accuracy for the group of left side of the cardium (No.2), periphery of the splenic hilum (No.10), posterior of the pancreastic head (No.13) were higher than other groups on MSCT with the accuracyof 100%.The sensitivity for the group of No.2,periphery of the coeliac trunk(No.9),No.10,and No.13 was 100%.The specificity for the group of No.2,No.10,and No.13 was 98.9%.Conclusion Relatively high accuracy in the preoperative N-staging and diagnosis of metastatic lymph nodes in each group of gastric cancer can be obtained by MSCT, which provide reliable information for preoperative assessment and intraoperative lymph node dissections.

Objective To evaluate the diagnostic value of MSCT in small bowel obstruction and related complications caused by diverticulitis.Methods Clinical data and CT findings of 13 patients with diverticulitis and related complications were reviewed.The imaging findings of diverticulitis were calculated and compared with those in other 20 cases without intestinal obstruction.Results Among the 1 3 cases with diverticulitis,8 occurred in the j ej unum and other 5 in ileum.CT revealed the diverticulitis in all patients as a predominantly cylindrical expansion in communication with the adjacent small bowel.CT showed intraluminal intestinal contents and little air bubbles in 3 cases with simple diverticulitis,thickening of the appendix lumen in 2 cases with perforated diverticulitis, and annular high-density in lumen in 2 cases with diverticulitis and bezoar.CT also showed diverticulitis with volvulus in 6 cases as mesenteric swirling.The average thickness of diverticula were (3.06±0.31)mm,and the average volume of diverticula were (98.98±38.59)cm3 , exhibting statistically significant differences between diverticulitis and control groups (P value were 0.000 and 0.000).Conclusion MSCT is helpful for the diagnosis of small bowel obstruction and related complications caused by diverticulitis.

Objective To evaluate the role of 64-slice spiral CT with diphase dynamic scanning in predicting the T staging of gas-tric carcinoma in different locations and assessing the sensitivity of metastasis of lymph nodes.Methods 185 patients with gastric carcinoma proved by pathology underwent diphase 64-slice CT scan and performed a TNM staging according to UICC classification. The results were compared with surgical pathological findings.Results The detection sensitivity for earlier stage gastric carcinoma was 92.0% and 99.4% for the advanced stage gastric carcinoma,While the overall accuracy rates of T and N staging were 85.4%, 69.2% respectively.Compared with the pathologic findings,the accuracy rate of CT scan for T1,T2,T3,T4 staging was 72.0%, 69.6%,90.8% and 83.3% respectively.The differences were statistically significant between T1 and T3,T2 and T3.The accuracy rate of T staging was 86.0%,84.8% respectively when the lesions were located in cardia and in antrum and this difference was not statistically significant.When the lesions were located in the body of the stomach,the differences were also not statistically signifi-cant with the accuracy rate of T staging was 89.5%,86.4% ,87.2% respectively for the lateral wall of the lesser curvature,the posterior wall of the lesser curvature and both the lesser curvature and larger curvature involved.As for the N staging,The accuracy rate of N0,N1,N2,N3 was 54.3%,87.5%,68.1% and 53.6%.The differences were significant statistically between N0 and N1, N1 and N3.Conclusion There was a high accuracy in the preoperative TNM staging of the gastric carcinoma with 64-slice spiral CT. The accuracy rate of T staging of the gastric carcinoma is not relative to the lesion’s location.