Title :
A Numerical Investigation of Breast Compression: A Computer-Aided Design Approach for Prescribing Boundary Conditions
Author :
Stewart, M.L. ; Smith, Laura M. ; Hall, Nicholas
Author_Institution :
Oakland Univ., Rochester, MI, USA
Abstract :
Prior to performing an MRI-guided breast biopsy, the radiologist has to locate the suspect lesion with the breast compressed between rigid plates. However, the suspect lesion is typically identified from a diagnostic MRI exam with the breast hanging freely under the force of gravity. There are several challenges associated with localizing suspect lesions including, patient positioning, the visibility of the lesion may fade after contrast injection, menstrual cycles, and lesion deformation. Researchers have developed finite element analysis (FEA) methodologies that simulate breast compression with the intent of reducing these challenges. In this paper, we constructed a patient-specific finite element (FE) breast model from diagnostic MR images. In addition, we constructed surfaces corresponding to the biopsy MR volume and used them to deform the FE breast mesh. The predicted results suggest that the FE breast model, in its uncompressed configuration, can be compressed to replicate the perimeter of the biopsy MR volume. The simulated lesion displacement was within 3 mm of its actual position.
Keywords :
biomedical MRI; data compression; medical image processing; mesh generation; tumours; MRI-guided breast biopsy; breast compression; computer-aided design approach; contrast injection; finite element analysis; force-of-gravity; lesion; lesion deformation; menstrual cycles; numerical investigation; patient positioning; uncompressed configuration; Breast tissue; Finite element methods; Geometry; Lesions; Materials; Numerical models; Breast boundary conditions; MRI-guided breast biopsy; breast compression; breast finite element model; finite element lesion model; Algorithms; Biopsy; Breast; Breast Neoplasms; Computer Simulation; Female; Finite Element Analysis; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Models, Biological;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2011.2162063