Biomedical Engineering Reference
In-Depth Information
surface deformation of a body in multiple gravity loaded orientations. We have
previously shown that the combination of information from these different gravity
loaded orientations can improve the identifiability of constitutive parameters of
general soft bodies, thereby improving the ability to predict deformation [
20
].
We are now applying this methodology for identifying the in vivo mechanical
properties of the different breast tissues allowing us to identify the tissue properties
without the need for obtaining additional MR scans.
7 Conclusions
We have developed a heterogeneous 3D FE model of the breast by segmenting
prone MRI into compartments for breast tissues (the combination of fat and
fibroglandular tissues) and the pectoral muscle. The deformation observed in
these models was based solely on the loading conditions, providing the ability to
predict deformations under different gravity-loaded orientations as may be required
for clinical procedures such as biopsy. We verified the applicability of such models
for simulating the prone to supine reorientation of the breast and found that
accounting for the mechanical effects of the pectoral muscle substantially improved
the accuracy of the predicted breast deformations, particularly near the shoulder
region where a large proportion of breast cancers develop.
Acknowledgements The financial support provided by the New Zealand Government's Ministry
for Science and Innovation is gratefully acknowledged. We also thank Miss Angela Lee and Dr
Jessica Jor for their valuable contributions to this study. Martyn P. Nash and Poul M. F. Nielsen are
supported by James Cook Fellowships administered by the Royal Society of New Zealand on
behalf of the New Zealand Government.
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