Objective To explore the feasibility of radiomics nomogram based on magnetic resonance diffusion weighted imaging for predicting the expression of Ki-67 in breast cancer.Methods A retrospective study was conducted on patients with breast cancer confirmed by surgery and pathology in the Second Affiliated Hospital of Guangdong Medical University.All patients were detected by Ki-67 expression staining,and then divided into group A(n=28,low-level expression of Ki-67)and group B(n=73,high-level expression of Ki-67).The apparent diffusion coefficient(ADC)graph was generated from diffusion weighted images,and the two groups were compared for radiomics features of ADC images and clinical data.The expression level of Ki-67 in breast cancer was predicted using the features of LASSO after dimensionality reduction,and a nomogram model was established,whose diagnostic efficiency was analyzed with receiver operating characteristic curve.Results No significant difference was observed in ADC value,age,carbohydrate antigen 199,carbohydrate antigen 153,carbohydrate antigen 125 and carcinoembryonic antigen between two groups(P>0.05).LASSO regression identified two radiomics features as predictors for the expression level of Ki-67 in breast cancer.The best tuning Lambda of LASSO was-0.125 690 135 478 682,and the included radiomics features for nomogram establishment were MinIntensity and Quantile95.The established nomogram had an area under ROC curve of 0.917,achieving a sensitivity of 91.7%and a specificity of 83.3%.Conclusion The expression of Ki-67 in breast cancer can be predicted based on the radiomics features of ADC images,which can provide a noninvasive detection method for evaluating the proliferation degree and treatment prognosis of breast cancer.

Objective To explore the risk factors for obstetric septic shock.Methods The clinical data of 122 obstetric sepsis patients from Jan.2013 to Apr.2025 were retrospectively analyzed.The patients were assigned to shock group(n=26)or non-shock group(n=96)based on whether they progressed to septic shock.Variables including age,body mass index,multiple pregnancy,sequential organ failure assessment(SOFA)score,organ dysfunction status,white blood cell count(WBC),neutrophil count(NEU),neutrophil ratio,platelet count,procalcitonin,C-reactive protein,lactate(Lac),and D-dimer were recorded.Multivariate logistic regression analysis was used to identify the independent risk factors for obstetric septic shock.The predictive efficacy of these factors was evaluated using receiver operating characteristic(ROC)curve analysis.Results The proportions of patients aged≥35 years,and those with respiratory,cardiac,or central nervous system dysfunction,were significantly higher in the shock group than in the non-shock group,and the SOFA score,WBC,NEU,neutrophil ratio and Lac level were significantly higher in the shock group(all P＜0.05).Multivariate logistic regression analysis showed that increased NEU(odds ratio[OR]=1.093,95%confidence interval[CI]1.022-1.169,P=0.010)and age≥35 years(OR=3.433,95%CI 1.112-10.602,P=0.032)were independent risk factors for obstetric septic shock.ROC curve analysis showed that NEU had predictive value for obstetric septic shock(area under curve=0.741,95%CI 0.634-0.848),with an optimal cut-offvalue of 17.17×109/L.Conclusion Increased NEU and age≥35 years are independent risk factors for obstetric septic shock.NEU has predictive value for the development of obstetric septic shock and may serve as an important indicator for clinical assessment and timely treatment.

Objective To explore the feasibility of radiomics nomogram based on magnetic resonance diffusion weighted imaging for predicting the expression of Ki-67 in breast cancer.Methods A retrospective study was conducted on patients with breast cancer confirmed by surgery and pathology in the Second Affiliated Hospital of Guangdong Medical University.All patients were detected by Ki-67 expression staining,and then divided into group A(n=28,low-level expression of Ki-67)and group B(n=73,high-level expression of Ki-67).The apparent diffusion coefficient(ADC)graph was generated from diffusion weighted images,and the two groups were compared for radiomics features of ADC images and clinical data.The expression level of Ki-67 in breast cancer was predicted using the features of LASSO after dimensionality reduction,and a nomogram model was established,whose diagnostic efficiency was analyzed with receiver operating characteristic curve.Results No significant difference was observed in ADC value,age,carbohydrate antigen 199,carbohydrate antigen 153,carbohydrate antigen 125 and carcinoembryonic antigen between two groups(P>0.05).LASSO regression identified two radiomics features as predictors for the expression level of Ki-67 in breast cancer.The best tuning Lambda of LASSO was-0.125 690 135 478 682,and the included radiomics features for nomogram establishment were MinIntensity and Quantile95.The established nomogram had an area under ROC curve of 0.917,achieving a sensitivity of 91.7%and a specificity of 83.3%.Conclusion The expression of Ki-67 in breast cancer can be predicted based on the radiomics features of ADC images,which can provide a noninvasive detection method for evaluating the proliferation degree and treatment prognosis of breast cancer.