Clinical value of a Logistic regression model based on multimodality ultrasound image characteristics in predicting the expression of tumor-infiltrating lymphocytes in triple negative breast cancer
Objective To investigate the clinical value of a Logistic regression model based on multimodality ultrasound[including two-dimensional ultrasound,shear wave elastography,contrast-enhanced ultrasound(CEUS)and automated breast volume scanning]image characteristics in predicting the expression of tumor-infiltrating lymphocytes(TILs)in triple-negative breast cancer(TNBC)preoperatively.Methods Ninety-nine female patients with TNBC confirmed by pathology were divided into the TILs low expression group(<20%,n=41)and the TILs high expression group(≥20%,n=58)according to the expression of TILs.The shape,orientation,margin,internal echo,posterior echo and calcifications were obtained by two-dimensional ultrasound,and the mean shear wave velocity(SWV)was obtained by shear wave elastography(SWE),the convergence sign,halo sign and catheter change were obtained by automated breast volume scanner(ABVS),and the initial enhancement time,enhancement intensity,enhancement direction,enhancement mode,perfusion defects,peripheral vascularity and extent of lesions after enhancement were obtained by CEUS.The differences in multimodality ultrasound image characteristics between the two groups were compared.Multivariate Logistic regression was applied to analyze the independent influencing factors for predicting the high expression of TILs in TNBC,and a regression model was established.Receiver operating characteristic(ROC)curve was drawn to analyze the regression model in predicting the high expression of TILs in TNBC.Results In the TILs high expression group,the proportion of regular shape,circumscribed margin,enhanced posterior echo and heterogeneous echo pattern in two-dimensional ultrasound image characteristics as well as hyperenhancement and perfusion defects in CEUS image characteristics were higher than those in the TILs low expression group,and the differences were statistically significant(all P<0.05).The differences were not statistically significant in SWV and ABVS image characteristics.Multivariate Logistic regression analysis showed that regular shape,circumscribed margin and enhanced posterior echo in two-dimensional ultrasound image characteristics and hyperenhancement and perfusion defects in CEUS image characteristics were all independent influencing factors for predicting the high expression of TILs in TNBC(OR=6.858,3.824,5.909,1.945,6.522,all P<0.05).The established prediction model was:Logit(P)=-2.989+1.925×regular shape+1.341×circumscribed margin+1.776×enhanced posterior echo+0.665×hyperenhancement+1.875×perfusion defects,and the sensitivity,specificity,accuracy and AUC for predicting the high expression of TILs in TNBC were 68.3%,27.6%,76.0%and 0.772,respectively.Conclusion Logistic regression model based on multimodality ultrasound image characteristics has certain value in predicting TILs expression in TNBC preoperatively.
Ultrasonography,multimodalityBreast cancer,triple negativeExpression of tumor-infiltrating lymphocytesLogistic regression model
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