|
The purpose of this study was to develop and evaluate computer-extracted features for characterizing mammographic
mass margins according to BI-RADS spiculated and circumscribed categories. The mass was automatically segmented
using an active contour model. A spiculation measure for a pixel on the mass boundary was defined by using the angular
difference between the image gradient vector and the normal to the mass, averaged over pixels in a spiculation search
region. For the circumscribed margin feature, the angular difference between the principal eigenvector of the Hessian
matrix and the normal to the mass was estimated in a band of pixels centered at each point on the boundary, and the
feature was extracted from the resulting profile along the boundary. Three MQSA radiologists provided BI-RADS
margin ratings for a data set of 198 regions of interest containing breast masses. The features were evaluated with
respect to the individual radiologists' characterization using receiver operating characteristic (ROC) analysis, as well as
with respect to that from the majority rule, in which a mass was labeled as spiculated (circumscribed) if it was
characterized as such by 2 or 3 radiologists, and non-spiculated (non-circumscribed) otherwise. We also investigated the
performance of the features for consensus masses, defined as those labeled as spiculated (circumscribed) or nonspiculated
(non-circumscribed) by all three radiologists. When masses were labeled according to radiologists R1, R2,
and R3 individually, the spiculation feature had an area Az under the ROC curve of 0.90±0.04, 0.90±0.03, 0.88±0.03,
respectively, while the circumscribed margin feature had an Az value of 0.77±0.04, 0.74±0.04, and 0.80±0.03,
respectively. When masses were labeled according to the majority rule, the Az values for the spiculation and the
circumscribed margin features were 0.92±0.03 and 0.80±±0.03, respectively. When only the consensus masses were
considered, the Az values for the spiculation and the circumscribed margin features were 0.96±0.04 and 0.87±0.04,
respectively. We conclude that the newly developed features had high accuracy for characterizing mass margins
according to BI-RADS descriptors.
|
