Methods for modeling and predicting mechanical deformations of the breast under external pertubations

Fred S. Azar, Dimitris N. Metaxas, Mitchell D. Schnall

Research output: Contribution to journalArticlepeer-review

128 Scopus citations

Abstract

Currently, high field (1.5 T) superconducting MR imaging does not allow live guidance during needle breast procedures. The current procedure allows the physician only to calculate approximately the location and extent of a cancerous tumor in the compressed patient breast before inserting the needle. It can then become relatively uncertain that the tissue specimen removed during the biopsy actually belongs to the lesion of interest. A new method for guiding clinical breast biopsy is presented, based on a deformable finite element model of the breast. The geometry of the model is constructed, from MR data, and its mechanical properties are modeled using a non-linear material model. This method allows imaging the breast without or with mild compression before the procedure, then compressing the breast and using the finite element model to predict the tumor's position during the procedure. A silicon phantom containing a stiff inclusion was imaged uncompressed then compressed. A model of the phantom was constructed and compressed using custom-written software, and also using a commercial FEM simulation package. The displacement of the inclusion's corners was recorded both in the real phantom and in the two compressed models. A patient's breast was imaged uncompressed then compressed. A deformable model of the uncompressed breast was constructed, then compressed. The displacement of a cyst and of two vitamin E pills taped to the surface of the breast were recorded both in the real and in the modeled breast. The entire procedure lasted less than a half-hour, making it clinically useful. The results show that it is possible to create a deformable model of the breast based on finite elements with non-linear material properties, capable of modeling and predicting breast deformations in a clinically useful amount of time.

Original languageEnglish (US)
Pages (from-to)1-27
Number of pages27
JournalMedical Image Analysis
Volume6
Issue number1
DOIs
StatePublished - Mar 2002
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

Keywords

  • Breast cancer
  • Finite element modeling
  • MRI
  • Soft tissue modeling

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