Correlation of DCE-MRI Perfusion Parameters and Molecular Biology of Breast Infiltrating Ductal Carcinoma - Liu, Li; Mei, Nan; Yin, Bo; Peng, Weijun (Frontiers in Oncology, 2021)
Objective To investigate the correlation of the perfusion parameters of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with molecular biological expression of breast infiltrating ductal carcinoma (IDC) in order to guide appropriate therapeutic advice and clinical outcome prediction. Materials and Methods In a prospective analysis of 67 patients with breast IDC, preoperative DCE-MRI and routine MRI images were obtained. The double-chamber model (Extended Tofts model) was employed to calculate perfusion parameters. Postoperative pathological immunohistochemistry was examined including human epidermal growth factor receptor 2 (HER-2), estrogen receptor (ER), progesterone receptor (PR), cell nuclear associated antigen (Ki-67), cytokeratin 5/6 (CK5/6) and epidermal growth factor receptor (EGFR). Statistical analysis was applied to explore the relationship between perfusion parameters and breast cancer molecular biomarkers. Results A total of 67 lesions were included in our study. The mean maximum diameter of lesions was 4.48±1.73 cm. Perfusion parameters had no correlation with tumor diameters (p>0.05). Ktrans and kep had positive correlations with Ki-67 (p<0.05). vp had a statistical difference between CK5/6 positivity and CK5/6 negativity. MAX Slope was higher in HER-2 enriched tumors than in Luminal A or B tumors (p<0.05). kep was higher in HER-2 enriched tumors than in Luminal A tumors (p<0.05). ve was higher in triple negative tumors than in HER-2 enriched, Luminal A and Luminal B tumors (p<0.05). TTP was lower in HER-2 enriched tumors than in Luminal A and B tumors (p<0.05). MAX Conc was higher in triple negative tumors than in Luminal B tumors (p<0.05). Conclusion DCE-MRI perfusion parameters can be have as a noninvasive tool to assess molecular biological expression and molecular subtype of breast IDC. They may aid in predicting breast IDC invasiveness, metastasis and prognosis.