Abstract
Patient-specific surgical predictions of Breast Conserving Therapy, through mechano-biological simulations, could inform the shared decision making process between clinicians and patients by enabling the impact of different surgical options to be visualised. We present an overview of our processing workflow that integrates MR images and three dimensional optical surface scans into a personalised model. Utilising an interactively generated surgical plan, a multi-scale open source finite element solver is employed to simulate breast deformity based on interrelated physiological and biomechanical processes that occur post surgery. Our outcome predictions, based on the pre-surgical imaging, were validated by comparing the simulated outcome with follow-up surface scans of four patients acquired 6 to 12 months post-surgery. A mean absolute surface distance of 3.3 mm between the follow-up scan and the simulation was obtained.
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Acknowledgements
The authors would like to acknowledge the financial support of the European FP7 project VPH-PICTURE (FP7-ICT-2011-9, 600948) and the Marie Curie Fellowship project iBeSuP (FP7-PEOPLE-2013-IEF, 627025). The authors are also indebted to members of the Royal Free Hospital NHS Foundation Trust for their support of this research; in particular Dominic Baxter for patient recruitment, Georgina Bartl for data administration and David Bishop, Emily Appleby, Imogen Ashby and Susan Smart for medical photography.
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Eiben, B. et al. (2016). Breast Conserving Surgery Outcome Prediction: A Patient-Specific, Integrated Multi-modal Imaging and Mechano-Biological Modelling Framework. In: Tingberg, A., Lång, K., Timberg, P. (eds) Breast Imaging. IWDM 2016. Lecture Notes in Computer Science(), vol 9699. Springer, Cham. https://doi.org/10.1007/978-3-319-41546-8_35
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DOI: https://doi.org/10.1007/978-3-319-41546-8_35
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