MRI与X线联合评估乳腺非肿块样病变恶性风险的Logistic回归模型建立及应用评价OA北大核心CSTPCD

Objective:To develop,verify and test a predictive model for the malignant risk of breast non-mass-like le-sions(NML)based on magnetic resonance imaging(MRI)and mammography features,in order to improve the accuracy of malig-nant diagnosis and provide evidence for clinical decision-making.Methods:This was a retrospective study,which included the radiologic data of 150 cases that met the inclusion criteria from July 2021 to April 2023.Logistic regression was con-ducted to obtain the malignant risk prediction model of breast NML,as well as the nomogram.The accuracy of this model was evaluated by the calibration curve.The diagnostic performance was evaluated by the receiver operating characteristic(ROC)curve.Results:There were multiple factors related to the malignant risk of NML,including clustered ring enhancement,type of time-intensity curve(TIC),apparent diffusion coefficient(ADC)value,and linear or segmental calcification distribution.The model based on MRI features had an area under the ROC curve(AUC)of 0.941,a sensitivity of 88.7%,and a specificity of 86.6%.The model based on the combination of MRI and mammography features had an AUC of 0.951,a sensitivity of 91.5%,and a specificity of 91.4%.The calibration curve indicated good predictive accuracy.Conclusion:The model for the diagnosis of malignant risk of breast NML based on the combination of MRI and mammography features demonstrated high di-agnostic performance and had potential applications.