We conducted a user-centred design of a clinical decision-support system for breast cancer screening, diagnosis, and reporting based on stroke gestures. We combined knowledge elicitation interviews, scenario-focused questionnaires and paper mock-ups to understand user needs. Multi-fidelity (low and high) prototypes were designed and compared first in vitro in a usability laboratory, then in vivo in the real world. The resulting user interface provides radiologists with a platform that integrates domain-oriented tools for the visualisation of mammograms, the manual, and the semi-automatic annotation of breast cancer findings based on stroke gestures. The contribution of this work lies in that, to the best of our knowledge, stroke gestures have not yet been applied to the annotation of mammograms. On the one hand, although there is a substantial amount of research done in stroke-based interaction, none focuses especially on the domain of breast cancer annotation. On the other hand, typical gestures in breast cancer annotation tools are those with a keyboard and a mouse.