Quantitative and semantic information about medical images are vital parts of a radiological report. However, current image viewing systems do not record it in a format that permits machine interpretation. The ePAD tool can generate machine-computable image annotations on 2D images as part of a radiologist's routine workflow. The tool has been evaluated in image studies with good results. Since ePAD currently only provides 2D visualization and annotation of images, we developed a plugin to ePAD for the visualization of volumetric image datasets, using the three planes: axial, frontal and sagittal. A study with 6 radiologists was carried out to determine the best interface for also marking 3D ROIs. Video prototypes were created for 3 options: join pixels based on intensity similarity, detect borders around image features, and paint ROIs using a spheric 3D cursor. The 3D cursor was the preferred option. We present these results and also show the final 3D cursor implementation.