Breast modeling and simulation

Breast modeling and simulation for a better cancer treatment

Context

About 1 in 8 U.S women will develop invasive breast cancer over the course of her lifetime (www.breast cancer.org) depending on her age, genetic, relatives, etc… About 80 % of breast cancers are Invasive Ductal Caricnomas (IDC), invasive means that the cancer has spread to the surrounding breast tissues. Ductal means that the cancer began in the milk ducts, which are the pipes that carry milk from the milk producing lobules to the nipple. Carcinoma refers to any cancer that begins in the skin or other tissues that cover internal organs.

index

Breast anatomy (Original author: Patrick J. Lynch)

 

There are several ways to get rid of these tumours but two procedures are mainly used. The total ablation of the breast if the tumour is too big (mastectomy) or the removal of the tumour and some surrounding tissues (lumpectomy). In this study, we will be more interested in the lumpectomy because less traumatic for the patient, this procedure requires more precision and the surgery can be improved thanks to simulation.

Problematic

The lumpectomy is divided into two principal operations. First, a MRI in prone position (face to the ground) in order to localize the tumour in the position where the breast is the most expended. Then, the day before the surgery, a radioactive marker or a hook is placed on the patient tumour in order to be able to remove it during the surgery. The next day, the surgery will be effectuated in supine position (the back of the patient is facing the ground easier for the surgeon) and thanks to the previous marker, the surgeon is able to remove the tumour.

Using these kind of markers is on one hand dangerous for the patient (radioactivity or infection risk) and on the other hand inaccurate during the surgery. Indeed, even if a marker is placed, detect radioactivity areas precisely or cut exactly the right amount of tumour around a hook is impossible for the moment. To overcome this problem surgeons usually cut more healthy tissues to be sure to completely remove the growth.

Aims

Breast simulations would allow the tracking of the tumour based on MRI images to fit patient specific data. Several difficulties and challenges sur round this kind of simulation: unknown material properties of the patient breast (depending on a large set of parameters), specific anatomy of each patient, unknown unloaded configuration of the breast, etc. . .

Methods

This thesis is part of the RAINBOW project financed by The Marie Sklodowska-Curie European Training Network and also the H2020-EU.1.3.1. – Fostering new skills by means of excellent initial training of researchers . The project involves 2 main actors : The University of Luxembourg (UL) and a french company Anatoscope.

Anatoscope is a young start-up specialized in patient specific modelling and also real-time multi-physics simulation by using the open source simulator SOFA. So a first work is to propose a model fitting patient specific data in collaboration with Anatoscope.

Then with the University of Luxembourg, Faculty of Science, Technology and Communication (FSTC), Doctoral Programme in Computer Science and Computer Engineering (DSSE) in Professor Bordas’ team specialized in mechanical simulations. We will use inverse methods to find mechanical properties of the breast based on tumor’s displacement. And set patient-specific simulation models that are rapidly set for a particular patient, easy-to-use by clinical experts and do not require assistance from a technical team.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 764644.

References

[1] B. Eiben, V. Vavourakis, J. H. Hipwell, S. Kabus, C. Lorenz, T. Buelow, and D. J. Hawkes. Breast deformation modelling: comparison of methods to obtain a patient specific unloaded configuration. page 903615.
[2] T. Hopp, A. Stromboni, N. Duric, and N. V. Ruiter. Evaluation of breast tissue characterization by ultrasound computer tomography using a 2d/3d image registration with mammograms. In 2013 IEEE International Ultrasonics Symposium (IUS), pages 647–650. IEEE.
[3] A. L. Kellner, T. R. Nelson, L. I. Cervino, and J. M. Boone. Simulation of mechanical compression of breast tissue. 54(10):1885–1891.
[4] H. Khatam, G. P. Reece, M. C. Fingeret, M. K. Markey, and K. Ravi Chandar. In-vivo quantification of human breast deformation associated with the position change from supine to upright. 37(1):13–22.
[5] A. Mîra, A.-K. Carton, S. Muller, and Y. Payan. aUniv. grenoble alpes, CNRS, grenoble INP, VetAgro sup, TIMC-IMAG, 38000 grenoble, france. page 21.
[6] N. G. Ramião, P. S. Martins, R. Rynkevic, A. A. Fernandes, M. Barroso, and D. C. Santos. Biomechanical properties of breast tissue, a state-of-the-art review. 15(5):1307–1323.
[7] T.-C. Shih, J.-H. Chen, D. Liu, K. Nie, L. Sun, M. Lin, D. Chang, O. Nalcioglu, and M.-Y. Su. Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images. 55(14):4153–4168.
[8] G. M. Sturgeon, N. Kiarashi, J. Y. Lo, E. Samei, and W. P. Segars. Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation: FE compression for population of breast phantoms. 43(5):2207–2217.
[9] C. Wessel, J. A. Schnabel, and M. Brady. Realistic biomechanical model of a cancerous breast for the registration of prone to supine deformations. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 7249–7252. IEEE.