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Final Report Summary - IBESUP (Towards the simulation of breast surgical lumpectomy and surgery planning through an isogeometric numerical analysis approach)

Breast cancer, as epitomized by Europe’s breast cancer advocacy organisation: Europadonna, is currently the most prevalent form of cancer affecting women in Europe and worldwide. The treatment of early-stage breast carcinoma involves either lumpectomy – i.e tumour and partial healthy tissue removal – or mastectomy in conjunction with chemo- or/and radiotherapy. To date, there have been numerous clinical studies about the pros and cons of each available surgical treatment: breast-conserving surgery (lumpectomy), mastectomy, lymph node dissection and breast reconstruction. However, there is a lack of robust, high-fidelity predictive tools which could be used in this context of breast cancer therapy, both for predicting the outcome of these interventions, supporting the surgical team for preoperative planning, but also towards being used as a training tool for surgeons or perfecting such surgical procedures.

Motivated by the above, the “iBeSuP” project aimed to set the foundations by developing a novel simulation and planning tool for breast cancer surgery. Thus, a three-dimensional, mathematical and computational modelling framework capable simulating breast tissue deformations and physiological tissue recovery after surgery has been developed. The modelling framework engulfs two very powerful numerical methods, widely used in the applied mechanics and biomechanics communities, namely the finite element method and the isogeometric analysis method. In brief, the mathematical and computational (in-silico) modelling framework is informed using patient-specific data (i.e. magnetic resonance images, photographic / surface scans), which subsequently can be processed – using standard image processing techniques – to construct an individualised discrete model of the patient in 3D. Then, a series of involved biomechanical simulations are carried out to predict the shape of the breast, and hence the appearance of the patient, before and after (several months of) surgery. More importantly, the validity and accuracy of the modelling framework has been assessed using patient data from prospective clinical studies in breast-conserving surgery (lumpectomy).

The research work and findings of the “iBeSuP” project have been published in several peer-reviewed international journals and conference proceedings, with two landmark research articles being published very recently at PLoS ONE (doi:10.1371/journal.pone.0159766) and PLOS Computational Biology (doi:10.1371/journ al.pcbi.1005259) respectively.

In summary, the “iBeSuP” project has achieved its goal to successfully deliver a novel, validated in-silico modelling framework, which has demonstrated the potential of being used as a simulator for breast-conserving surgery. Therefore, it could work as the foundation for future developments of other relevant surgical simulators. Also, it could prove a valuable tool for surgical decision support and for multi-disciplinary team meetings towards shared decision making in the clinical environment. Nonetheless, to reach the point of translating this technology there is substantial scope to improve and innovate. More precisely, one aspect of development for the surgical simulator would be to account for the side-effects of adjuvant therapies (e.g. radiotherapy, chemotherapy), as well as expand the modelling platform to aggregate heterogeneous patient information (e.g. dietary, proteo-/genomics).

The Marie Curie “iBeSuP” project website can be directly accessed through the link:, whereas the open-source in-silico simulation platform can be accessed downloaded (for free upon request) from the Bitbucket repository via the following link:

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