Purpose To investigate the value of intratumoral and peritumoral radiomics features based on multi-parametric MRI for preoperative prediction of lymphovascular invasion(LVI)in clinical lymph node-negative(cN0)breast cancer.Materials and Methods This retrospective study included 280 patients with pathologically confirmed breast cancer who underwent preoperative MRI at Henan Provincial People's Hospital from January 2017 to May 2021.Patients were randomly divided into a training cohort and a testing cohort.After Z-score normalization,feature selection was performed using Select K Best and least absolute shrinkage and selection operator regression.Random forest algorithms were used to construct intratumoral,peritumoral,and combined intratumoral-peritumoral radiomics models for LVI prediction.Model performance and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration curves and decision curve analysis.Results High Ki-67 expression(≥20%),axillary lymph node metastasis and positive diffusion weighted imaging(DWI)margin sign were more common in the LVI-positive group(χ2=5.959,18.316,20.554,all P<0.05).In the testing cohort,the AUC values of the dynamic contrast-enhanced(DCE)-Intra and DCE-Com models for predicting LVI status were higher than those of the DWI sequence,whereas the AUC value of the DWI-Peri model was higher than that of the DCE sequence.The DWI-DCE-Com model achieved AUCs of 0.836 and 0.818 in the training and testing cohorts,respectively,which surpassed the predictive performance of single-sequence intratumoral-peritumoral radiomics models(DWI-Com,DCE-Com).Decision curve analysis showed that the DWI-DCE-Com model provided greater net clinical benefit across a reasonable range of threshold probabilities.Conclusion Radiomics models based on multiparametric MRI features from intratumoral and peritumoral regions can effectively predict LVI status in cN0 breast cancer,offering valuable support for preoperative individualized treatment decision-making.

Purpose To investigate the value of intratumoral and peritumoral radiomics features based on multi-parametric MRI for preoperative prediction of lymphovascular invasion(LVI)in clinical lymph node-negative(cN0)breast cancer.Materials and Methods This retrospective study included 280 patients with pathologically confirmed breast cancer who underwent preoperative MRI at Henan Provincial People's Hospital from January 2017 to May 2021.Patients were randomly divided into a training cohort and a testing cohort.After Z-score normalization,feature selection was performed using Select K Best and least absolute shrinkage and selection operator regression.Random forest algorithms were used to construct intratumoral,peritumoral,and combined intratumoral-peritumoral radiomics models for LVI prediction.Model performance and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration curves and decision curve analysis.Results High Ki-67 expression(≥20%),axillary lymph node metastasis and positive diffusion weighted imaging(DWI)margin sign were more common in the LVI-positive group(χ2=5.959,18.316,20.554,all P<0.05).In the testing cohort,the AUC values of the dynamic contrast-enhanced(DCE)-Intra and DCE-Com models for predicting LVI status were higher than those of the DWI sequence,whereas the AUC value of the DWI-Peri model was higher than that of the DCE sequence.The DWI-DCE-Com model achieved AUCs of 0.836 and 0.818 in the training and testing cohorts,respectively,which surpassed the predictive performance of single-sequence intratumoral-peritumoral radiomics models(DWI-Com,DCE-Com).Decision curve analysis showed that the DWI-DCE-Com model provided greater net clinical benefit across a reasonable range of threshold probabilities.Conclusion Radiomics models based on multiparametric MRI features from intratumoral and peritumoral regions can effectively predict LVI status in cN0 breast cancer,offering valuable support for preoperative individualized treatment decision-making.

Objective To observe the value of intratumoral and peritumoral radiomics based on diffusion weighted imaging(DWI)for predicting histological grade of breast cancer.Methods Preoperative DWI data of 700 patients with single breast cancer diagnosed by pathology were retrospectively analyzed.The patients were divided into training set(n= 560,including 381 of grade Ⅰ+Ⅱ and 179 of grade Ⅲ)and test set(n=140,including 95 of grade Ⅰ+Ⅱ and 45 of grade Ⅲ)at the ratio of 8∶2.Intratumoral ROI(ROIintra)was manually delineated on DWI,which was automatically expanded by 3 mm and 5 mm to decline peritumoral ROI(ROIperi,including ROI3 mm and ROI5 mm),then intratumoral-peritumoral ROI(ROIintra+3 mm,ROIintra+5 mm)were obtained.The optimal radiomics features were extracted and screened,and the radiomics model(RM)for predicting the histological grade of breast cancer were constructed.Receiver operating characteristic curves were drawn,and the areas under the curve(AUC)were calculated to evaluate the predictive efficacy of each model.Calibration curve method was used to evaluate the calibration degree,while decision curve analysis(DCA)was performed to explore the clinical practicability of each model.Results AUC of RMintra,RM+3 mm,RM+5mm,RMintra+3 mm and RMintra+5 mm was 0.750,0.724,0.749,0.833 and 0.807 in training set,while was 0.723,0.718,0.736,0.759 and 0.782 in test set,respectively.In training set,significant differences of AUC was found(all P＜0.01),while in test set,no significant difference of AUC was found among models(all P＞0.05).The calibrations of models were all high.DCA showed that taken 0.02-0.88 as the threshold,the clinical net benefit of RMintra+per were greater in training set,while taken 0.40-0.72 as the threshold,the clinical net benefit of RMintra+per was greater in test set.Conclusion Both DWI intratumoral and peritumoral radiomics could effectively predict histological grade of breast cancer.Combination of intratumoral and peritumoral radiomics was more effective.

Recombinase polymerase amplification (RPA) is a novel technology for nucleic acid isothermal amplification. It can achieve the rapid amplification and detection of a target gene under 37-42 ℃. This amplification method is highly sensitive, more specific and less instrument-dependent than other existing methods, and it can also integrate multiple detection modes. Therefore, it is especially suitable for applying in low-resource settings and conducting point-of-care tests. Starting from the reaction principles and the experimental design of RPA, this article pointed out some key points when using RPA in a clinical setting. The current development and related problems of RPA were concluded and the various future uses of this method were also prospected.