Tomosynthesis was developed for mammography, especially breast cancer detection. However, its limited-angular range scan and resultant data incompleteness causes strong image artifacts and distortions. To address this problem, a hybrid imaging method was proposed in our previous work, which combines tomosynthesis and low-resolution CT into a single system to produce fewer artifacts and distortions at a similar dose level. The purpose of this paper is to evaluate the images reconstructed using the proposed method as compared with that using the conventional tomosynthesis method (ML-convex). For that purpose, the projection datasets are acquired in both numerical simulation and phantom experiments on our breast imaging platform. Three kinds of phantoms are used in our work, including a numerical phantom, a physical phantom and 8 in vitro phantoms made of breast specimens. In addition to visual comparison of the reconstructed images, we employ spatial resolution, image contrast, reconstruction error, and convergence rate to evaluate the results quantitatively. It is observed that the results from our method can achieve significantly higher spatial resolution, higher contrast, smaller reconstruction error and faster convergence rate. Besides, a reader study using 8 in vitro phantoms of breast specimens demonstrates the clinical potential of our method, which significantly outperforms the conventional tomosynthesis. © 2008 - IOS Press and the authors. All rights reserved.