Objective To construct a prediction model of epidermal growth factor receptor(EGFR)gene mutation in patients with non-small cell lung cancer(NSCLC)based on spectral CT parameters,lymphocyte to monocyte ratio(LMR)and systemic inflam-mation response index(SIRI).Methods The spectral CT parameters,LMR and SIRI of EGFR mutant and wild types NSCLC patients were compared,respectively.The influencing factors of EGFR gene mutation were analyzed and a risk prediction model was estab-lished.Results The LMR,70 keV CT value in arterial phase and venous phase,normalized iodine concentration(NIC),slope of spectral curve(λHU)and venous phase ΔCT value in EGFR mutant type patients were significantly higher than those in EGFR wild type patients,while SIRI,arterial phase and venous phase normalized water concentration(NWC)were significantly lower than those in EGFR wild type patients(P<0.05).Female,adenocarcinoma,no smoking history,LMR,increased NIC,λHU,and ΔCT value in venous phase were the risk factors for EGFR gene mutation,and increased SIRI was a protective factor(P<0.05).The decision curve showed that when the risk threshold was 0.2-0.6,the prediction model had a good risk-benefit ratio.The P value of Hosmer-Lemeshow goodness of fit test was 0.519,and the area under the curve for predicting EGFR gene mutation in NSCLC patients was 0.911.Conclusion Spectral CT parameters,LMR and SIRI may be associated with EGFR gene mutation in NSCLC patients,the model constructed based on the above indicators has a high predictive efficacy for EGFR gene mutation.

Objective To construct radiomics-semantic models to predict the treatment resistance of chemoradiotherapy in brain gliomas based on MRI and clinical data of multicenter patients.Methods Among 2 108 brain gliomas patients from five medical institutions,132 patients had residual gliomas after surgery.The clinical risk factors and multimodal MRI were collected.All patients were divided into training set(n=95)and validation set(n=37).The treatment response of gliomas after standardized chemoradiotherapy were divided into resistant and non-resistant types.The semantic features of MRI were evaluated by two radiologists.Three different segmentation regions of interest(ROI)were delineated to extract radiomics features.And that three groups of radiomics models were con-structed based on different sequence MRIs.The radiomics model with the best predictive efficacy in each group was selected and combined with MRI semantic features,three radiomics-semantic models(combined models)were established.Finally,a MRI semantic model,three groups of radiomics models and three combined models were developed.Results Comparisons between the different models showed that the radiomics-semantic model based on pre-operative T2-fluid attenuated inversion recovery(FLAIR)sequence,had the best predictive efficacy,the area under the curve(AUC)in the training and validation sets were 0.866[95％confidence interval(CI)0.790-0.942]and 0.810(95％CI 0.667-0.952),respectively.The radiomics-semantic model based on postoperative T1 WI sequence performed the second best,with the AUC of the training and validation sets being 0.812(95％CI 0.726-0.898)and 0.711(95％CI 0.541-0.881),respectively.Conclusion The combined models based on MRI radiomics and semantic features are able to predict the treatment resistance of chemoradiotherapy in brain gliomas patients,and may be used as an important basis for optimizing treatment.

Objective To construct radiomics-semantic models to predict the treatment resistance of chemoradiotherapy in brain gliomas based on MRI and clinical data of multicenter patients.Methods Among 2 108 brain gliomas patients from five medical institutions,132 patients had residual gliomas after surgery.The clinical risk factors and multimodal MRI were collected.All patients were divided into training set(n=95)and validation set(n=37).The treatment response of gliomas after standardized chemoradiotherapy were divided into resistant and non-resistant types.The semantic features of MRI were evaluated by two radiologists.Three different segmentation regions of interest(ROI)were delineated to extract radiomics features.And that three groups of radiomics models were con-structed based on different sequence MRIs.The radiomics model with the best predictive efficacy in each group was selected and combined with MRI semantic features,three radiomics-semantic models(combined models)were established.Finally,a MRI semantic model,three groups of radiomics models and three combined models were developed.Results Comparisons between the different models showed that the radiomics-semantic model based on pre-operative T2-fluid attenuated inversion recovery(FLAIR)sequence,had the best predictive efficacy,the area under the curve(AUC)in the training and validation sets were 0.866[95％confidence interval(CI)0.790-0.942]and 0.810(95％CI 0.667-0.952),respectively.The radiomics-semantic model based on postoperative T1 WI sequence performed the second best,with the AUC of the training and validation sets being 0.812(95％CI 0.726-0.898)and 0.711(95％CI 0.541-0.881),respectively.Conclusion The combined models based on MRI radiomics and semantic features are able to predict the treatment resistance of chemoradiotherapy in brain gliomas patients,and may be used as an important basis for optimizing treatment.

Objective To construct a prediction model of epidermal growth factor receptor(EGFR)gene mutation in patients with non-small cell lung cancer(NSCLC)based on spectral CT parameters,lymphocyte to monocyte ratio(LMR)and systemic inflam-mation response index(SIRI).Methods The spectral CT parameters,LMR and SIRI of EGFR mutant and wild types NSCLC patients were compared,respectively.The influencing factors of EGFR gene mutation were analyzed and a risk prediction model was estab-lished.Results The LMR,70 keV CT value in arterial phase and venous phase,normalized iodine concentration(NIC),slope of spectral curve(λHU)and venous phase ΔCT value in EGFR mutant type patients were significantly higher than those in EGFR wild type patients,while SIRI,arterial phase and venous phase normalized water concentration(NWC)were significantly lower than those in EGFR wild type patients(P<0.05).Female,adenocarcinoma,no smoking history,LMR,increased NIC,λHU,and ΔCT value in venous phase were the risk factors for EGFR gene mutation,and increased SIRI was a protective factor(P<0.05).The decision curve showed that when the risk threshold was 0.2-0.6,the prediction model had a good risk-benefit ratio.The P value of Hosmer-Lemeshow goodness of fit test was 0.519,and the area under the curve for predicting EGFR gene mutation in NSCLC patients was 0.911.Conclusion Spectral CT parameters,LMR and SIRI may be associated with EGFR gene mutation in NSCLC patients,the model constructed based on the above indicators has a high predictive efficacy for EGFR gene mutation.

With completing a baseline survey of a large natural population cohort, conducting regular follow-up has become a key factor in further improving the quality of cohort construction and ensuring its sustainable development. Typical cohort follow-up methods include repeat surveys, routine monitoring, and community-oriented surveillance. However, in practical applications, there are often issues such as high costs, difficulty, and high error rates. Telephone follow-up is an important supplementary method to the methods mentioned above, as it has the characteristics of low cost, fast response, and high quality. However, the with difficult organization, quality control is challenging, response rates are low, and management levels vary widely, which limits its widespread use in large-scale population cohort studies. Given the above problems, this study draws on customer relationship management based on the actual needs of the China Northwest Cohort follow-up. It relies on the REDCap electronic data collection platform to build a telephone follow-up management and quality control system. Targeted solutions are provided for key issues in telephone follow-up implementation, including organizational structure, project management, data collection, and process quality control, to improve the quality control level of telephone follow-up comprehensively and thereby enhance the quality and efficiency of follow-up. We hope to provide standardized follow-up programs and efficient quality control tools for newly established and existing cohort studies.

Objective:In order to scientifically promote the selection of appropriate technology of traditional non-pharmacologi-cal,the value evaluation index system of traditional non-pharmacological technology was constructed in line with the characteristics of TCM based on the theory of health technology assessment and multi-criteria decision analysis.Methods:The evaluation index pool was initially formed through literature research,and then those indicators were further improved through semi-structured inter-views and Delphi method.Results:The value evaluation index was constructed with seven dimensions,including quality standard,safety,effectiveness,economy,inheritance and innovation,suitability and accessibility,which were subordinated by 17 second-level indicators and 33 third-level indicators.The questionnaire response rate was 100%.The group authority coefficient of 17 experts was 0.87,and the concentration and coordination degree of expert opinions of the first-level indicators were high.Conclusion:The index pool constructed in this study has high expert authority,good concentration and coordination of expert opinions,which needs to be verified by practical experience,which is of great significance for the value evaluation of traditional non-pharmacological technology.

Objective To explore the application of diffusion tensor imaging (DTI)in crossed cerebellar diaschisis (CCD)of cerebral gliomas. Methods MR images of 17 patients with high grade gliomas and 20 patients with low grade gliomas confirmed by postoperative pathology and 18 normal controls were analyzed retrospectively.The fractional anisotropy (FA)of cerebellar hemisphere was quantitatively measured with DTI technique.The asymmetry index (AI)of cerebellar hemispheric was calculated and compared in patients.The correlation between CCD phenomenon and histological grade of cerebral gliomas was also analyzed.Results Compared with ipsilateral cerebellar hemisphere of cerebral high grade gliomas,the FA value of contralateral cerebellar hemisphere significantly reduced (t=3.42,P<0.05).But there were no significant differences of FA values between contralateral cerebellar hemisphere and ipsilateral cerebellar hemisphere in cerebral low grade gliomas patients (t=0.80,P>0.05).The AI values of cerebellar hemisphere in high grade gliomas increased compared with low grade gliomas and normal controls (t=4.15,P<0.05;t=4.68,P<0.05),but there were no significant differences in the AI values of cerebellar hemisphere between low grade gliomas patients and normal controls (t=0.79,P>0.05).Conclusion CCD phenomenon is associated with the histological grade of cerebral gliomas.High grade gliomas can cause CCD phenomenon,but there is no evident CCD phenomenon in low grade gliomas.DTI technique is able to quantitatively assess CCD noninvasively by FA parameter.