Parameters of dynamic contrast-enhanced MRI as imaging markers for angiogenesis and proliferation in human breast...

Breast cancer is the most common malignancy and the leading cause of cancer death in women worldwide; however, early diagnosis has been difficult due to its complex pathological structure. This study evaluated the value of morphological examination in conjunction with dynamic contrast-enhanced MRI (DCE-MRI) for more precise diagnosis of breast cancer, as well as their correlation with angiogenesis and proliferation biomarkers.

DCE-MRI parameters (including Ktrans: volume transfer coefficient reflecting vascular permeability, Kep: flux rate constant, Ve: extracellular volume ratio reflecting vascular permeability, and ADC: apparent diffusion coefficient) were obtained from 124 patients with breast cancer (124 lesions). Microvessel density (MVD) was evaluated by the immunohistochemical analysis of tumor vessels for CD31 and CD105 expression. The proliferation was assessed by analyzing Ki67.

Ktrans values were in the order of: malignant lesions>benign lesions>normal glands. Similar results were observed for Kep. The opposite changes were seen with Ve. Ktrans and Kep values were significantly higher in invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) than in mammary ductal dysplasia (MDD; ANOVA followed by Dunnett's test). In sharp contrast, ADC values were lower in IDC and DCIS than in MDD, and Ve was not significantly different among the three groups. The data from MIP (maximum intensity projection) showed that benign breast lesions had no or only one blood vessel, whereas malignant lesions had two or more blood vessels. In addition, expression of CD105 and Ki67, the commonly recognized markers for angiogenesis and proliferation, respectively, were closely correlated with MRI parameters as revealed by Pearson analysis.

Determination of Ktrans, Kep and ADC values permits estimation of tumor angiogenesis and proliferation in breast cancer and DCE-MRI parameters can be used as imaging biomarkers to predict patient prognosis and the biologic aggressiveness of the tumor.