Value of combining multimodal ultrasound features with machine learning to predict high expression of Ki-67 in breast infiltrating ductal carcinoma
Objective To investigate the value of multi-modal ultrasound features combined with machine learning in predicting high expression of Ki-67 in breast invasive ductal carcinoma.Methods A retrospective analysis was conducted in 155 patients with invasive ductal carcinoma and 155 lesions confirmed by pathology.Preoperative conventional ultrasound and acoustic radiation force impulse were performed,immunohistochemical staining was used to record the expression of Ki-67,and the patients were divided into overexpression groups(n=105)and low expression groups(n=50).Logistic regression analysis was used to analyze the differential indicators to obtain independent risk factors,and random forest and Logistic regression models were used for prediction.Results Univariate analysis showed that there were significant differences in the expression of Ki-67 and the maximum diameter,boundary,axillary lymph node status,resistance index,virtual touch tissue imaging and virtual touch tissue quantification of the lesion(P<0.05).Multivariate analysis showed that the maximum diameter,boundary,virtual touch tissue quantification and resistance index were independent risk factors for Ki-67 expression.The random forest model showed that the influencing factors for Ki-67 expression were ranked in order of importance as the maximum diameter,virtual touch tissue quantification,resistance index and boundary.The areas under the curve of the random forest and logistic regression models in predicting high expression of Ki-67 in breast invasive ductal carcinoma were 0.871 and 0.866,respectively.There was a positive correlation between the expression level of Ki-67 and the diameter of the lesion(r=0.319,P<0.001).Conclusion Multi-modal ultrasound features combined with machine learning can be used to predict the level of Ki-67 expression in invasive ductal carcinoma,providing reference value for clinical diagnosis and treatment.
breast infiltrating ductal carcinomaKi-67acoustic radiation force pulse imagingshear wave velocitymachine learning
万方数据
维普
