Ultrawideband (UWB) Microwave Imaging is an emerging technology for breast cancer detection which is based on the dielectric contrast between normal and cancerous tissues at microwave frequencies. The breast is illuminated by a UWB pulse and reflected signals are used to determine the presence and location of significant dielectric scatterers, which may be representative of cancerous tissue within the breast. Beamformers are used to spatially focus the reflected signals and to compensate for path dependent attenuation and phase effects. These beamfonners can be divided into two distinct categories: Data-Independent and Data-Adaptive beamformers. Data-Independent beamformers typically use an assumed channel model to compensate for path-dependent propagation effects. Conversely, Data-Adaptive beamformers attempt to directly estimate the actual channel based on signals reflected from the breast. Recent studies by Lazebnik et al. indicate that the range of dielectric properties of normal breast tissue is much greater than reported previously. This presents a much more difficult imaging problem due to dielectric heterogeneity. Difficulties encountered by data-independent beamformers in locating tumors within dielectrically heterogeneous breasts have been documented previously. In this paper, the effects of heterogeneity on data-adaptive beamformers is investigated. 2D MRI-derived breast models with varying levels of dielectric heterogeneity are used to evaluate the data-adaptive beamformers.