Dynamic MR imaging of invasive breast cancer: correlation with tumour grade and other histological factors

Abstract

The purpose of this study was to explore the association between dynamic MR enhancement characteristics and histopathological prognostic factors of invasive breast cancer. 53 women with primary invasive breast cancer underwent dynamic contrast enhanced breast MRI. Region of interest (ROI) analysis was performed on synthetic images obtained by kinetic modelling of the dynamic data. Operator-defined, large ROIs and computer-defined, 9-pixel ROIs were selected for each tumour. The relative increase in mean ROI pixel intensity was expressed in the form of enhancement ratios. Univariate and multivariate analyses were performed to explore the association of these ratios with standard histological factors, including tumour size, histopathological classification, histological grade, the presence of extensive in situ component and lymphovascular invasion, multifocal disease, and axillary lymph node status. All enhancement ratios showed significant differences between node-positive and node-negative tumours (max. p = 0.002). However, automated ROI ratios showed less overlap between node-positive and node-negative carcinomas than did large ROI ratios. A strongly significant association was observed between all automated ROI enhancement ratios and histological tumour grade (max. p = 0.001). Based on stepwise multiple regression analysis, node status and histological grade were the only histopathological factors with a significant independent effect on the enhancement characteristics. In summary, there is a strong association between dynamic MR characteristics and two important prognostic markers of invasive breast cancer, namely axillary node status and histological grade. This may allow MRI to be used in pre-operative predictions of tumour behaviour and biological activity.