ImageBR: A Public MRI Dataset for Planned Implant Region and Mammary Gland Segmentation in Breast Reconstruction

Breast magnetic resonance imaging (MRI) offers three-dimensional anatomical information for reconstruction-oriented analysis, but annotated public datasets targeting implant-based reconstruction are limited. ImageBR contains MRI volumes from 44 patients (26 bilateral and 18 unilateral reconstruction cases), yielding 70 breast-level samples with expert annotations of planned implant regions, mammary gland tissue, and breast regions. The planned implant region is a surgeon-defined virtual surgical target rather than a directly visible anatomical structure on MRI, and its reference annotations were established without using the final prosthesis specifications. A two-stage benchmark combines breast-region extraction with an nnU-Net 3D cascade incorporating image-derived anatomical priors and weighted loss optimization. Under patient-level three-fold cross-validation, the reported mean breast-level Dice scores were 83.0% and 74.4% for planned implant region and mammary gland segmentation, respectively. The retrospective comparison of predicted-region volume and diameter with final implanted prosthesis specifications yielded relative errors of 14.27% and 8.98%, respectively, and measures consistency rather than independent implant-selection accuracy.