Objective To observe the value of clinical and CT radiomics features for predicting microsatellite instability-high(MSI-H)status of gastric cancer.Methods Totally 150 gastric cancer patients including 30 cases of MSI-H positive and 120 cases of MSI-H negative were enrolled and divided into training set(n=105)or validation set(n=45)at the ratio of 7∶3.Based on abdominal vein phase enhanced CT images,lesions radiomics features were extracted and screened,and radiomics scores(Radscore)was calculated.Clinical data and Radscores were compared between MSI-H positive and negative patients in training set and validation set.Based on clinical factors and Radscores being significant different between MSI-H positive and negative ones,clinical model,CT radiomics model and clinical-CT radiomics combination model were constructed,and their predictive value for MSI-H status of gastric cancer were observed.Results Significant differences of tumor location and Radscore were found between MSI-H positive and negative patients in both training and validation sets(all P＜0.05).The area under the curve(AUC)of clinical model,CT radiomics model and combination model for evaluating MSI-H status of gastric cancer in training set was 0.760,0.799 and 0.864,respectively,of that in validation set was 0.735,0.812 and 0.849,respectively.AUC of clinical-CT radiomics combination model was greater than that of the other 2 single models(all P＜0.05).Conclusion Clinical-CT radiomics combination model based on tumor location and Radscore could effectively predict MSI-H status of gastric cancer.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To investigate the value of CT quantitative parameters of tumor and spleen in predicting the clinical stage of gastric cancer (Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage).Methods:This study was a case-control study. The data of 145 patients with gastric cancer confirmed by pathology in the First Affiliated Hospital of Zhengzhou University from February 2019 to June 2021 were retrospectively collected, including 70 cases of Ⅰ/Ⅱ stage and 75 cases of Ⅲ/Ⅳ stage. On the baseline CT images, the tumor related parameters, including tumor thickness, length of tumor, CT attenuation of tumor unenhanced phase, CT attenuation of tumor arterial phase, CT attenuation of tumor venous phase were measured. The spleen related parameters, including splenic thickness, CT attenuation of splenic unenhanced phase, CT attenuation of splenic arterial phase, CT attenuation of splenic venous phase, and standard deviation of CT attenuation (CTsd) in splenic unenhanced phase were also measured. The independent sample t test or Mann-Whitney U test was used to compare the parameters between the Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage patients. The multi-factor logistic regression analysis was used to find the independent predictors of gastric cancer clinical stage, and establish the combined parameters. The efficiency to the diagnosis of gastric cancer stage of single and combined parameters was evaluated using the operating characteristic curve, and the DeLong test was used to compare the differences of area under the curve (AUC). Results:There were significant differences in tumor thickness, length of tumor, CT attenuation of tumor venous phase, CT attenuation of splenic unenhanced phase, CT attenuation of splenic venous phase, CTsd in splenic unenhanced phase between the Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage of gastric cancer ( P<0.05). Multivariate analysis showed that tumor thickness ( OR=1.073, 95% CI 1.026-1.123, P=0.002), CT attenuation of splenic venous phase ( OR=1.040, 95% CI 1.011-1.070, P=0.006) and CTsd in splenic unenhanced phase ( OR=1.625, 95% CI 1.330-1.987, P<0.001) were independent risk factors for the clinical stage of gastric cancer and the combined parameters were established. The AUC values of tumor thickness, CT attenuation of splenic venous phase, CTsd in splenic unenhanced phase and combined parameters were 0.655, 0.614, 0.749 and 0.806, respectively. The AUC of combined parameters was higher than those of tumor thickness and CT attenuation of splenic venous phase, and the differences were statistically significant ( Z=3.37, 3.82, both P<0.001). Conclusion:Tumor thickness, CT attenuation of splenic venous phase and CTsd in splenic unenhanced phase are independent risk factors for the clinical stage of gastric cancer, and combined parameters can improve the diagnostic efficiency.

Objective To observe the reproducibility of radiomics feature(RF)extracted from virtual monoenergetic image(VMI)of rabbit VX2 hepatoma models obtained with 3 different dual-energy CT(DECT)systems,and to explore relationship of reproducibility and diagnostic performance of RF.Methods Fifteen rabbits with VX2 hepatoma were randomly divided into 3 groups(each n=5).Contrast-enhanced abdominal CT scanning under volume CT dose index(CTDIvol)levels of 6,9 and 12 mGy were performed with dual-source DECT(dsDECT),rapid kV switching DECT(rsDECT)and dual-layer detector DECT(dlDECT),respectively.VMI were reconstructed at 10 keV increments from 40 to 140 keV.RF were extracted from VMI,the reproducibility was assessed using intra-class correlation coefficient(ICC),and those with ICC≥0.8 were considered as reproducible RF.The percentage of reproducible features(denoted by R)were compared among different scanner pairings and different CTDIvol levels.Within each CTDIvol group,the reconstruction energy levels yielding the maximum number(denoted by N)of common RF across different scanner pairings were identified.The receiver operating characteristic(ROC)curve was drawn,the area under the curve(AUC)was calculated,and the diagnostic efficacies of reproducible RF and other RF were compared under optimal reproducible conditions.Spearman correlation coefficient between ICC and the corresponding AUC of RF were calculated.Results RrsDECT-dsDECT(6.45％,95％CI[2.36％,8.87％])was higher than RdlDECT-dsDECT(0.72％,95％CI[0.15％,1.79％])and RrsDECT-dlDECT(1.43％,95％CI[0.60％,4.06％])(all adjusted P＜0.05),R9mGy(3.70％,95％CI[1.31％,5.73％])and R12mGy(2.63％,95％CI[0.60％,6.69％])were higher than R6mGy(1.31％,95％CI[0.12％,1.55％])(all adjusted P＜0.05).The optimal reproducible reconstruction energy levels of RF under CTDIvol of 6,9 and 12 mGy concentrated at 50-70 keV.AUC of reproducible RFs were higher than of other RF(all adjusted P＜0.05)and had certain correlation with the reproducibility(rs=0.102-0.516,P＜0.05).Conclusion The reproducibility of RF extracted from contrast-enhanced VMI CT images of rabbit VX2 hepatoma models associated with DECT scanner,CTDIvol level and reconstruction energy level.RF with higher reproducibility might have better diagnostic performance.

Objective To observe the value of clinical data combined with CT radiomics features for evaluating programmed cell death-ligand 1(PD-L1)status in gastric cancer.Methods Totally 277 gastric cancer patients were retrospectively enrolled and randomly divided into training set(n=195)and validation set(n=82)at the ratio of 7:3.There were 88 cases in PD-L1 positive subgroup and 107 cases in negative subgroup of training set,while 37 and 45 cases of validation set,respectively.The clinical and conventional CT features were compared between subgroups in both sets,the independent influencing factors of PD-L1 status in gastric cancer were analyzed,and radiomic features were screened based on CT data.Then clinical model,radiomics model and clinical-radiomics model were established,and the efficacy of each model for evaluating PD-L1 status in gastric cancer was observed.Results In training set,Borrmann type,cN stage,cM stage,clinical stage,maximum diameter and thickness were significant difference between subgroups(all P＜0.05).Borrmann type,clinical stage and the thickness were all independent influencing factors of PD-L1 positivity(all P＜0.05).The area under the curve(AUC)of clinical model,radiomic model and clinical-radiomics model for evaluating PD-L1 status in gastric cancer in training set was 0.748,0.832 and 0.841,respectively,and was 0.657,0.801 and 0.789 in validation set,respectively.AUC of clinical model was lower than the other models(all P＜0.05).Conclusion Clinical data combined with CT radiomics features was helpful for evaluating PD-L1 status in gastric cancer.

Objective:To evaluate the value of preoperative prediction of vessel invasion (VI) of locally advanced gastric cancer by machine learning model based on the venous phase enhanced CT radiomics features.Methods:A retrospective analysis of 296 patients with locally advanced gastric cancer confirmed by pathology in the First Affiliated Hospital of Zhengzhou University from July 2011 to December 2020 was performed. The patients were divided into VI positive group ( n=213) and VI negative group ( n=83) based on pathological results. The data were divided into training set ( n=207) and test set ( n=89) according to the ratio of 7∶3 with stratification sampling. The clinical characteristics of patients were recorded, and the independent risk factors of gastric cancer VI were screened by multivariate logistic regression. Pyradiomics software was used to extract radiomic features from the venous phase enhanced CT images, and the minimum absolute shrinkage and selection algorithm (LASSO) was used to screen the features, obtain the optimal feature subset, and establish the radiomics signature. Four machine learning algorithms, including extreme gradient boosting (XGBoost), logistic, naive Bayes (GNB), and support vector machine (SVM) models, were used to build prediction models for the radiomics signature and the screened clinical independent risk factors. The efficacy of the model in predicting gastric cancer VI was evaluated by the receiver operating characteristic curve. Results:The degree of differentiation (OR=13.651, 95%CI 7.265-25.650, P=0.003), Lauren′s classification (OR=1.349, 95%CI 1.011-1.799, P=0.042) and CA199 (OR=1.796, 95%CI 1.406-2.186, P=0.044) were independent risk factors for predicting the VI of locally advanced gastric cancer. Based on the venous phase enhanced CT images, 864 quantitative features were extracted, and 18 best constructed radiomics signature were selected by LASSO. In the training set, the area under the curve (AUC) of XGBoost, logistic, GNB and SVM models for predicting gastric cancer VI were 0.914 (95%CI 0.875-0.953), 0.897 (95%CI 0.853-0.940), 0.880 (95%CI 0.832-0.928) and 0.814 (95%CI 0.755-0.873), respectively, and in the test set were 0.870 (95%CI 0.769-0.971), 0.877 (95%CI 0.788-0.964), 0.859 (95%CI 0.755-0.961) and 0.773 (95%CI 0.647-0.898). The logistic model had the largest AUC in the test set. Conclusions:The machine learning model based on the venous phase enhanced CT radiomics features has high efficacy in predicting the VI of locally advanced gastric cancer before the operation, and the logistic model demonstrates the best diagnostic efficacy.

Objective:To explore the value of multiphasic CT-based radiomics signature in predicting the invasive behavior of pancreatic solid pseudopapillary neoplasm (pSPN).Methods:The multiphasic CT images of patients with pSPN confirmed by postoperative pathology in the First Affiliated Hospital of Zhengzhou University from January 2012 to January 2021 were analyzed retrospectively. There were 23 cases of invasiveness and 59 cases of non-invasiveness. The region of interest(ROI) was artificially delineated layer by layer in the plain scan, arterial-phase and venous-phase images, respectively. The 1 316 image features were extracted from each ROI. The data set was divided into training and validation sets with a ratio of 7∶3 by stratified random sampling, and synthetic minority oversampling technique (SMOTE) algorithm was used for oversampling in the training set to generate invasive and non-invasive balanced data for building the training model. The constructed model was validated in the validation set. The receiver operating characteristic(ROC) analysis was used to evaluate model performance and the Delong′s test was applied to compare the area under the ROC curve (AUC) of different predict models. The improvement for classification efficiency of each independent model or their combinations were also assessed by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices.Results:After feature extraction, 2, 6 and 3 features were retained to construct plain-scanned model, arterial-phase and venous-phase models, respectively. Seven independent-phase and combined-phase models were established. Except the plain-scanned model, the AUC values of other models were greater than 0.800. The arterial-phase model had the best efficiency for classification among all independent-phase models. The AUC values of arterial-phase model in the SMOTE training and validation sets were 0.913 and 0.873, respectively. By combining the radiomics signature of the arterial-phase and venous-phase models, the AUC values of training and validation sets increased to 0.934 and 0.913 respectively. There were no significant differences of the AUC values between the scan-arterial venous-phase model and arterial venous-phase model in both training and validation sets (both P>0.05). The NRI and IDI indexes showed that the combined form of plain-scan model and arterial-venous-phase model could not significantly improve the classification efficiency in the validation set (both NRI and IDI<0). Conclusions:The arterial-phase CT-based radiomics model has a good predictive performance in the invasive behavior of pSPN, and the combination with a venous-phase radiomics model can further improve the model performance.

Objective: To investigate the sleep status among primary and middle school students in Zhoushan City, Zhejiang Province, so as to provide insights into improving the sleep quality among primary and middle school students. Methods: A district and a county was selected using the cluster random sampling method from Zhoushan City in October, 2019, and grades 4 to 6 primary school students, junior high school and high school students were sampled as the study subjects. Students' gender, grade, residing in schools, duration of homework and duration of extracurricular classes were collected using the questionnaires of the 2019 national program for common diseases and health risk factors surveillance and intervention program among Chinese students. According to the Plan for the Comprehensive Prevention and Control of Myopia among Children and Adolescents, daily sleep duration of 10 h and longer among primary school students, 9 h and longer among junior high school students and 8 h and longer among high school students were defined as adequate sleep, and the proportion of adequate sleep was estimated among primary and middle school students. Results: Totally 3 042 students were enrolled, including 1 587 boys (52.17%) and 1 455 girls (47.83%), 996 primary school students (32.74%), 1 030 junior high school students (33.86%), 758 ordinary high school students (24.92%) and 258 vocational high school students (8.48%). The mean sleep duration was (9.23±1.10) h among primary school students, (8.09±1.05) h among junior high school students, (7.20±1.26) h among ordinary high school students and (7.97±1.03) h among vocational high school students, respectively, and the proportion of adequate sleep was 26.31% among primary school students, 22.82% among junior high school students, 22.56% among ordinary high school students and 66.67% among vocational high school students, respectively. A relatively higher proportion of adequate sleep was seen among primary school students in Grade 4 (33.63%) and with homework duration of less than 1 h (34.53%); among junior high school students in Grade 1 (37.76%), residing in schools (40.00%), studying in county schools (30.87%), with homework duration of less than 1 h (34.69%) and less than 1 h duration of extracurricular classes (33.33%); among male ordinary high school students (28.03%), and ordinary high school students in Grade 1 (28.30%), residing in schools (26.18%) and studying in district schools (25.83%); among male vocational high school students (69.06%) and vocational high school students residing in schools (73.14%). Conclusion The proportion of adequate sleep is low among primary and middle school students in Zhoushan City. The homework duration and duration of extracurricular classes are recommended to be reduced to ensure adequate sleep among primary and middle school students.

Acute Disease ; Fatty Liver/diagnosis* ; Female ; Humans ; Liver ; Pregnancy ; Pregnancy Complications/diagnosis*

Objective:To investigate the predictive value of visceral adipose tissue (VAT) in occult peritoneal metastasis (OPM) of gastric cancer.Methods:A total of 93 patients with gastric cancer admitted to the First Affiliated Hospital of Zhengzhou University from October 2018 to October 2021 were retrospectively collected. None of the patients had typical peritoneal metastasis on CT. Patients were divided into OPM group (31 cases) and non-OPM group (62 cases) according to laparoscopic exploration. The clinical, pathological and CT features were recorded. The parameters related to adipose tissue (VAT and subcutaneous adipose tissue) within the range of 15 mm and 25 mm below the largest layer of gastric cancer lesions in preoperative CT images were measured, including the volume, average CT attenuation and standard deviation. The independent-sample t test, Wilcoxon rank-sum test, χ 2 test or Fisher′s exact probability were used to compare the clinical, pathological and CT imaging parameters between OPM and non-OPM groups. Multivariate logistic regression analysis was used to explore the independent risk factors for OPM of gastric cancer and establish a combined model. The receiver operating characteristic curve was used to evaluate the efficacy of each indicator and the combined model in predicting OPM of gastric cancer. Results:There were statistically significant differences in age, pathological type, CA125, ascites, cT stage, the thickest diameter of lesion, average CT attenuation of 15 mm VAT and 25 mm VAT between the OPM group and the non-OPM group ( P<0.05). Multivariate analysis showed that ascites, cT stage and average CT attenuation of 25 mm VAT were independent risk factors for OPM of gastric cancer, with the OR (95%CI) of 4.940 (1.287-18.967), 4.284 (1.270-14.455), and 1.149 (1.013-1.303), respectively. A combined model was established. The area under the curve (AUC) of ascites, cT stage, average CT attenuation of 25 mm VAT, average CT attenuation of 15 mm VAT and combined model were 0.685, 0.718, 0.703, 0.674 and 0.813, respectively. There were statistically significant differences in AUC between the combined model and each four single indicators above ( Z=2.98, 2.63, 2.09, 2.54, P=0.003, 0.009, 0.037, 0.011). Conclusions:The ascites, cT stage and average CT attenuation of 25 mm VAT are independent risk factors for OPM in gastric cancer. The combined model based on the above three indicators has the best performance in predicting OPM in gastric cancer.