Purpose: Previously we reported the development of anthropomorphic tissue-equivalent scatter phantoms of the human breast. Here we present the first results from the scatter imaging of the tissue equivalent breast phantoms for breast cancer diagnosis. Methods: A breast phantom was designed to assess the capability of coded aperture coherent x-ray scatter imaging to classify different types of breast tissue (adipose, fibroglandular, tumor). The phantom geometry was obtained from a prone breast geometry scanned on a dedicated breast CT system. The phantom was 3D printed using the segmented DICOM breast CT data. The 3D breast phantom was filled with lard (as a surrogate for adipose tissue) and scanned in different geometries alongside excised human breast tissues (obtained from lumpectomy and mastectomy procedures). The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor (i.e., momentum transfer (q) spectrum) of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: Our scatter imaging system was able to define the location and composition of the various materials and tissues within the phantom. Cancerous breast tissue was detected and classified through automated spectral matching and an 86% correlation threshold. The total scan time for the sample was approximately 10 minutes and approaches workflow times for clinical use in intra-operative or other diagnostic tasks. Conclusion: This work demonstrates the first results from an anthropomorphic tissue equivalent scatter phantom to characterize a coherent scatter imaging system. The functionality of the system shows promise in applications such as intra-operative margin detection or virtual biopsy in the diagnosis of breast cancer. Future work includes using additional patient-derived tissues (e.g., human fat), and modeling additional organs (e.g., lung).