Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images

Tzu Ching Shih, Jeon Hor Chen, Dongxu Liu, Ke Nie, Lizhi Sun, Muqing Lin, Daniel Chang, Orhan Nalcioglu, Min Ying Su

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo® 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc® software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities - such as MRI, mammography, whole breast ultrasound and molecular imaging - that are performed using different body positions and under different compression conditions.

Original languageEnglish (US)
Pages (from-to)4153-4168
Number of pages16
JournalPhysics in Medicine and Biology
Issue number14
StatePublished - Jul 21 2010

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging


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