Incorporating heterogeneity and anisotropy for surgical applications in breast deformation modeling Journal Article


Authors: Ringel, M. J.; Richey, W. L.; Heiselman, J. S.; Meszoely, I. M.; Miga, M. I.
Article Title: Incorporating heterogeneity and anisotropy for surgical applications in breast deformation modeling
Abstract: Background: Simulating soft-tissue breast deformations is of interest for many applications including image fusion, longitudinal registration, and image-guided surgery. For the surgical use case, positional changes cause breast deformations that compromise the use of preoperative imaging to inform tumor excision. Even when acquiring imaging in the supine position, which better reflects surgical presentation, deformations still occur due to arm motion and orientation changes. A biomechanical modeling approach to simulate supine breast deformations for surgical applications must be both accurate and compatible with the clinical workflow. Methods: A supine MR breast imaging dataset from n = 11 healthy volunteers was used to simulate surgical deformations by acquiring images in arm-down and arm-up positions. Three linear-elastic modeling approaches with varying levels of complexity were used to predict deformations caused by this arm motion: a homogeneous isotropic model, a heterogeneous isotropic model, and a heterogeneous anisotropic model using a transverse-isotropic constitutive model. Findings: The average target registration errors for subsurface anatomical features were 5.4 ± 1.5 mm for the homogeneous isotropic model, 5.3 ± 1.5 mm for the heterogeneous isotropic model, and 4.7 ± 1.4 mm for the heterogeneous anisotropic model. A statistically significant improvement in target registration error was observed between the heterogeneous anisotropic model and both the homogeneous and the heterogeneous isotropic models (P < 0.01). Interpretation: While a model that fully incorporates all constitutive complexities of anatomical structure likely achieves the best accuracy, a computationally tractable heterogeneous anisotropic model provided significant improvement and may be applicable for image-guided breast surgeries. © 2023 Elsevier Ltd
Keywords: breast cancer; registration; image enhancement; medical imaging; anisotropy; lumpectomy; target registration errors; finite element method; transplantation (surgical); image fusion; modeling approach; surgical guidance; anisotropic models; arm motions; isotropic models; surgical applications; fem
Journal Title: Clinical Biomechanics
Volume: 104
ISSN: 0268-0033
Publisher: Elsevier Inc.  
Date Published: 2023-04-01
Start Page: 105927
Language: English
DOI: 10.1016/j.clinbiomech.2023.105927
PUBMED: 36890069
PROVIDER: scopus
PMCID: PMC10122703
DOI/URL:
Notes: Article -- Source: Scopus
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