The aforementioned applications have in common the use of biomechanical models to predict deformations that, due to some inherent limitations, is not the most suitable approach to include in a tool designed to be used in the daily clinical practice. First, the computational process for most algorithms might take hours, days or even almost a week, depending on the complexity of the models. As a principle aim, to ease the patient/physician communications during their consultations, the planning tool must provide the solution in an expected short time. However, the biomechanical models demand high-end requirements which are not accessible in all clinics. Considering the common computation power of the available machines in clinics, the biomechanical models might take days to provide the required planning, which is too late to satisfy the aforesaid aim. Therefore, faster methodologies should be considered instead of faster machines. Second, most models are simple representations of the breast biomechanics, using unverified parameters, posing fidelity concerns on the predictions. Third, the characterization of individual-specific parameters to create personalized models of the breast, alongside with precise representation of loading and boundary constraints during different clinical procedures, is still an unsolved challenge . The aforesaid applications are intended to provide patient-specific treatment solutions. Thus, the model parameters should be easily personalized with respect to patient and tumor characterizations during the consultations. Alternative strategies to model breast deformations encompass the fitting of parametric models , physical equations to describe known breast deformations , user-intuitive parameters to change breast shape  or dataset of known cases to simulate breast surgery outcomes . These strategies model the breast with limited number of parameters and produce results in a timely manner more adequate to clinical practice, but the modelling of breast deformations has still to be improved for clinical surgery planning applications.