| Objective:This study aims to investigate the correlation between the features of calcified breast cancer in full-field digital mammography and the expression of estrogen rec-eptor (ER),progesterone receptor (PR),human epidermal growth factor related ge-nes(C-erbB-2) and Ki-67,and to estimate the biological behavior of malignant cal-cified breast cancer from the radiolocal imaging manifestations.for providing a the-oretical basis for clinical treatment and prognosis estimation.Methods:Seventy-seven patients with nonpalpable breast calcified lesion diagnosed as breast cancer by pathological examination underweng full-field digital mammogr-aphy before operation and then operated by3D guide wire stereotactic or vacuum assisted biopsy.Immunohistochemical SP staining was used to detect the expressi-on of ER, PR, C-erbB-2and ki-67.Using Statistical analysis.Results:1.the expression of ER was positively correlated with calcification in breast cancer (r=0.280,p=0.014),and there was no significant correlation between cal-cification and PR (p=0.735)。2.The expression of C-erbB-2was positively correlated with calcification in breast cancer (r=0.245,p=0.032).3.There was no significant correlation between calcification and the expres-sion of Ki-67(p=0.007)。4.The positive expression rate of ER and C-erbB-2in non-simple calcified b-reast cancer group was higher than that in the pure calcified breast cancer group (Both p<0.05).Conclusion: 1. Full-field digital mammography can clearly show the micro calcification, clinical and inaccessible small nodules, local glands dense and structural disorder in breast cancer.2. There is a certain correlation with the X-ray manifestation of calcification breast cancer and positive expression of ER andC-erbB-2,which state the endocr-ine therapy effect,the malignant degree of lesions and the recurrence rate are ass-ociateed with the existence of calcification lesions.3.Full-field digital mammography could reflect the molecular biology beha-vior of breast cancer cells,and then it could provide valuable message for clinical treatment and prognosis estimation in patients with breast cancer. |