Objective To explore the efficacy of single and combined parameters from 4 non-Gaussian diffusion models for differentiating breast imaging reporting and data system(BI-RADS)MRI category 4 benign and malignant breast tumors.Methods A total of 161 BI-RADS MRI category 4 breast lesions from 159 patients were retrospectively enrolled.Based on pathological results,the lesions were divided into malignant group(n=132)and benign group(n=29).The apparent diffusion coefficient(ADC)values were calculated from diffusion weighted imaging(DWI)sequences.Multi-b-value diffusion imaging data were acquired and fitted using 4 non-Gaussian models to obtain respective parameters,including diffusion kurtosis imaging(DKI),stretched exponential model(SEM),continuous-time random walk(CTRW)and fractional order calculus(FROC)model.Univariable and multivariable logistic regression analyses were employed to identify the diffusion quantitative indicators useful for differentiating benign and malignant BI-RADS MRI category 4 breast tumors.Receiver operating characteristic(ROC)curves were drawn,and the optimal threshold was determined using Youden index.The differentiating performance of ADC value,single parameter and their combination from non-Gaussian diffusion models were assessed and compared according to the area under the curve(AUC)of ROC curves,as well as the sensitivity,specificity and accuracy under the optimal thresholds.Results In malignant group,αCTRW,KDKI and μFROC values were higher,while ADC,DCTRW,DFROC,DDCSEM,αSEM and DDKI values were lower than those in benign group(all P＜0.05).Multivariable logistic regression analysis identified DCTRW and αCTRW values as independent factors for differentiating benign and malignant BI-RADS MRI category 4 breast tumors(both P＜0.05),and a combined model was then constructed.The AUC of the combined model was higher than that of each single parameter including ADC,DCTRW and αCTRW values(all P＜0.05).Conclusion The combined model of DCTRW and αCTRW had better efficacy than each single parameter for differentiating benign and malignant BI-RADS MRI category 4 breast tumors.

Objective To explore the efficacy of single and combined parameters from 4 non-Gaussian diffusion models for differentiating breast imaging reporting and data system(BI-RADS)MRI category 4 benign and malignant breast tumors.Methods A total of 161 BI-RADS MRI category 4 breast lesions from 159 patients were retrospectively enrolled.Based on pathological results,the lesions were divided into malignant group(n=132)and benign group(n=29).The apparent diffusion coefficient(ADC)values were calculated from diffusion weighted imaging(DWI)sequences.Multi-b-value diffusion imaging data were acquired and fitted using 4 non-Gaussian models to obtain respective parameters,including diffusion kurtosis imaging(DKI),stretched exponential model(SEM),continuous-time random walk(CTRW)and fractional order calculus(FROC)model.Univariable and multivariable logistic regression analyses were employed to identify the diffusion quantitative indicators useful for differentiating benign and malignant BI-RADS MRI category 4 breast tumors.Receiver operating characteristic(ROC)curves were drawn,and the optimal threshold was determined using Youden index.The differentiating performance of ADC value,single parameter and their combination from non-Gaussian diffusion models were assessed and compared according to the area under the curve(AUC)of ROC curves,as well as the sensitivity,specificity and accuracy under the optimal thresholds.Results In malignant group,αCTRW,KDKI and μFROC values were higher,while ADC,DCTRW,DFROC,DDCSEM,αSEM and DDKI values were lower than those in benign group(all P＜0.05).Multivariable logistic regression analysis identified DCTRW and αCTRW values as independent factors for differentiating benign and malignant BI-RADS MRI category 4 breast tumors(both P＜0.05),and a combined model was then constructed.The AUC of the combined model was higher than that of each single parameter including ADC,DCTRW and αCTRW values(all P＜0.05).Conclusion The combined model of DCTRW and αCTRW had better efficacy than each single parameter for differentiating benign and malignant BI-RADS MRI category 4 breast tumors.

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.