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A Numerical Investigation of Breast Compression: Lesion Modeling
MacArthur L, Lorenzo M. Smith, Neal Hall
Pages - 8 - 21     |    Revised - 01-07-2011     |    Published - 05-08-2011
Volume - 2   Issue - 1    |    Publication Date - July / August 2011  Table of Contents
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KEYWORDS
Breast, Finite Element, FE, Lesion, MRI, Biopsy
ABSTRACT
Researchers have developed finite element (FE) models from preoperative medical images to simulate intraoperative breast compression. Applications for these FE models include mammography, non-rigid image registration, and MRI guided biopsy. Efficient FE breast models have been constructed that model suspect lesions as a single element or node within the FE breast mesh. At the expense of efficiency, other researchers have modeled the actual lesion geometry within the FE breast mesh (conformal breast-lesion mesh). Modeling the actual lesion geometry provides lesion boundary spatial information, which is lost in FE breast models that model suspect lesions as a single element or node within the FE breast mesh. In this paper, we used a commercial finite element analysis (FEA) program to construct a biomechanical breast model from patient specific MR volumes. A laterally situated lesion was identified in the diagnostic MRI. We used the FE model to simulate breast compression during an MRI guided biopsy. Our objective was to investigate the efficacy of independently discretizing the breast and lesion geometries and using a kinematic constraint to associate the lesion nodes to the nodes in the breast mesh based on their isoparametric position. This study showed that it is possible to construct an accurate and efficient FE breast model that considers the actual lesion geometry. With 61 mm of breast compression, the lesion centroid was localized to within 3.8 mm of its actual position. As compared to a conformal breast-lesion FE mesh, the element count was also reduced by 53%. These findings suggest that it is possible to predict the position of a suspect lesion\'s centroid and boundary within clinical time constraints (< 30 minutes).
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Mr. MacArthur L
- United States of America
mlstewar@oakland.edu
Dr. Lorenzo M. Smith
- United States of America
Dr. Neal Hall
- United States of America
NealHall@rossmed.edu