Ms. Liesbet Roose Profile

Liesbet Roose

at KU Leuven

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Proceedings Article | 10 March 2006 Paper

Pre-operative simulation and post-operative validation of soft-tissue deformations for breast implantation planning

Liesbet Roose, Wim De Maerteleire, Wouter Mollemans, Frederik Maes, Paul Suetens

Proceedings Volume 6141, 61410Z (2006) https://doi.org/10.1117/12.648426

KEYWORDS: Breast, Tissues, Skin, Natural surfaces, Surgery, 3D modeling, Finite element methods, Computer simulations, 3D image processing, Visualization

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Virtual surgery simulation plays an increasingly important role as a planning aid for the surgeon. A reliable simulation method to predict the surgical outcome of breast reconstruction and breast augmentation procedures does not yet exist. However, a method to pre-operatively assess the result of the procedure would be useful to ensure a symmetrical and naturally looking result, and could be a practical means of communication with the patient. In this paper, we present a basic framework to simulate a subglandular breast implantation. First, we propose a method to build a model of the patient's anatomy, based on a 3D picture of the skin surface in combination with thickness estimates of the soft tissue surrounding the breast. This approach is cheap, fast and the picture can be taken while the patient is standing upright, which makes it advantageous compared to conventional CTor MR-based methods. Second, a set of boundary conditions is defined to mimic the effect of the implant. Finally, we compute the new equilibrium geometry using the iterative FEM-based Mass Tensor Method, which is computationally more effcient than the traditional FEM approach since sufficient precision can be achieved with a limited number of iterations. We illustrate our approach with a preliminary validation study on 4 patients. We obtain promising results with a mean error between the simulated and the true post-operative breast geometry below 4 mm and maximal error below 10 mm, which is found to be sufficiently accurate for visual assessment in clinical practice.

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