A visual analytics approach to diagnosis of breast DCE-MRI data

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast has become an important image modality for early breast cancer detection. In comparison to conventional X-ray mammography it exhibits a higher sensitivity, but only moderate specificity. To improve the speci-ficity, and therefore the distinction of benign and malignant changes, the lesion’s heterogeneity and the lesion enhancement kinetics have to be evalu-ated. We present a visual analytics approach for breast tumors in DCE-MRI data that divides a tumor in different regions with different perfusion char-acteristics by employing a region merging method. The resulting region-based representation allows for evaluation of the tumor’s heterogeneity and the region-wise qualitative and quantitative evaluation of the enhancement kinetics. The analyses are com-bined with a glyph-based representation for a fast overview of the whole lesion. We tested our ap-proach with seven well-chosen lesions and com-pared them to their histopathologic reports.