This study demonstrated that MK derived from DKI was performed better than MD, ADC, Ve, Kep and Ktrans for differentiating between benign and malignant BLs. Also, MK has great potentialities in predict histological grades, lymph node status and Ki-67 expression of BCs. Finally, a XGboost model was constructed by combining MD, MK, age, shape and menstrual status, which exhibited superior diagnostic performance for BC characterization and an improved assessment of BLs. The findings of current study will aid the development of a novel noninvasive approach for BC screening and clinical diagnosis, therefore reducing unnecessary biopsies and patient`s anxiety.
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