Breast carcinoma is the most common neoplasm found among women in the Western world. Mammography (MM) is the most widely used diagnostic imaging method for screening and diagnosing breast cancer. However, despite technical improvements in recent years, MM has known diagnostic limits; consequently not all breast carcinomas are identified on mammograms, especially if the breast is dense, there is a breast prosthesis or the patient has previously undergone radiation, surgery or biopsy. In addition, the mammographic images of benign and malignant lesions can be similar. Therefore, abnormalities detected on MM frequently result in negative biopsies. Scintimammography (SM) is the functional imaging study of the breast using primarily the radiopharmaceuticals (99m)Tc-sestamibi and (99m)Tc-tetrofosmin. The main advantage of SM is that its functional basis makes this technique a useful complement to MM. SM resolves some of the main limitations of MM as it is not affected by changes in breast morphology. Several single-site and multi-centre studies have demonstrated that SM has an improved specificity compared with MM, because it is better able to distinguish malignant from benign breast lesions. Interestingly, except in smaller lesions, a higher sensitivity has been recorded for SM than for MM in most of these studies as well. Adjunctive use of SM when MM is equivocal can reduce the number of unnecessary breast biopsies and identify previously unexpected sites of breast cancer. SM appears unaffected by the anatomical changes seen following chemotherapy and radiotherapy, and so this technique can be particularly useful in monitoring the treatment of breast cancer patients, especially when breast-conserving treatment is given. The main limitation to SM has been the sub-optimal resolution of the standard Anger gamma camera, which makes it difficult to detect lesions of less than 10 mm; however, the development of high-resolution breast-dedicated gamma cameras may offer improvements in this respect. This review will look at the evidence for SM and show how it can become part of the clinical care algorithm in breast cancer.