Publication

Tissue deformation algorithm to estimate breast tumor location from prone-to-supine position

2020
Student project
Abstract

Nearly 15-40% of patients who undergo Breast Conserving Surgery (BCS) require a repeat procedure to ensure complete removal of the tumor resulting in increased healthcare costs and possible negative psychological impact on the patient. To ensure complete tumor resection in a single procedure there is a fundamental need in accurately localizing the tumor intraoperatively. While the location of the tumor is usually known from diagnostic Magnetic Resonance (MR) images obtained in the prone position, large deformation of the breast tissue occurs between the prone position and the surgical supine position. To accurately predict these deformations and to localize the tumor, in this work we develop a biomechanical model that accounts for the breast geometry as well as the tissue properties. A Finite Element Model (FEM) is developed using the three-dimensional geometry of the breast as reconstructed from the MR images in the prone position. The data is then segmented into different materials (i.e. air, skin, fat, mammary glands, ribs, and tumor) and the noise is reduced through a custom-written algorithm. The labels that correspond to different breast tissue are then associated to each node of a finite element mesh and material properties (i.e. elastic stiffness and density) are assigned. Finally, the numerical model applies the gravitational load to the breast as well as the displacement of the skin to simulate its configuration in the supine position. Validation is obtained by comparing results with MR images in the supine position. Such predictions can significantly simplify the clinical workflow and improve the outcome through accurate and precise guidance. Novelty—Current clinical workflow for BCS involves the placement of a needle within the breast to localize the tumor. This could be time consuming and tedious. The aim is to develop a unique solution to accurately localize the tumor in the surgical supine position using Finite Element Modeling (FEM). This, in turn, could simplify

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