Dynamic Contrast Enhanced Breast MR Imaging (DCE BMRI) has emerged as a modality for breast cancer diagnosis. In
this modality a temporal sequence of volume images of the breasts is acquired, where a contrast agent is injected after
acquisition of the first 3D image. Since the introduction of the modality, research has been directed at the development
of computer-aided support for the diagnostic workup. This includes automatic segmentation of mass-like lesions, lesion
characterization, and lesion classification. Robustness, user-independence, and reproducibility of the results of
computerized methods are essential for such methods to be acceptable for clinical application.
A previously proposed and evaluated computerized lesion segmentation method has been further analyzed in this study.
The segmentation method uses as input a subtraction image (post-contrast - pre-contrast) and a user defined region of
interest (ROI). Previous evaluation studies investigated the robustness of the segmentation against variations in the user
selected ROI. Robustness of the method against variations in the image data itself has so far not been investigated. To fill
this gap is the purpose of this study.
In this study, the segmentation algorithm was applied to a series of subtraction images built from the pre-contrast volume
and all available post-contrast image volumes, successively. This provides set of typically 4-5 delineations per lesion,
each based on a different phase of the dynamic sequence.
Analysis of the apparent lesion volumes derived from these delineations and comparison to manual delineations showed
that computerized segmentation is more robust and reproducible than manual segmentation, even if computer
segmentations are computed on subtraction images derived from different dynamic phases of the DCE MRI study, while
all manual segmentations of a lesion are derived from one and the same dynamic phase of the study.
Furthermore, it could be shown that the rate of apparent change of lesion volume over the course of a DCE MRI study is
significantly dependent on the lesion type (benign vs. malignant).