A finite element model of the breast for predicting mechanical deformations during biopsy procedures

Azar, Fred S.; Metaxas, Dimitris N.; Schnall, M.

doi:10.1109/mmbia.2000.852358

Cited by 69 publications

(73 citation statements)

References 19 publications

(21 reference statements)

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“…1) show that all of the average displacement errors per node between the two simulations are under 1mm, and that using a small strain approximation [2] instead of the Lagrangian finite strain expression, in our finite element algorithm does not introduce a significant error in simulations of large deformation. …”

Section: Silicone Phantom Experimentsmentioning

confidence: 81%

“…We had presented in [2] an initial attempt to model a patient breast by developing a preliminary FE model of the breast. We extend that methodology to allow clinical use of the model by : 1.…”

Section: Methodsmentioning

confidence: 99%

“…A new meshing algorithm is used to allow variable meshing density in the model, in which the mesh density is increased around the point of interest, and decreased away from it. A new material model for fatty tissue is introduced following the rationale presented in [2]. The non-linear elastic modulus of fatty tissue E fat is a function of the strain ε fat :…”

Section: Methodsmentioning

confidence: 99%

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Methods for Modeling and Predicting Mechanical Deformations of the Breast Under External Perturbations

Azar

Metaxas

Schnall

2001

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001

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Abstract. Currently, High Field (1.5T) Superconducting MR imaging does not allow live guidance during needle breast procedures, which allow only to calculate approximately the location of a cancerous tumor in the 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 in a total time of less than a half-hour.

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Section: Silicone Phantom Experimentsmentioning

confidence: 81%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Methods for Modeling and Predicting Mechanical Deformations of the Breast Under External Perturbations

Azar

Metaxas

Schnall

2001

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001

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“…22,23 Several studies have tracked landmarks to within 5 mm. 15,24 Other studies have also included the effects of gravity.…”

Section: B Finite-element (Fe) Breast Modelsmentioning

confidence: 99%

Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation

Sturgeon

Kiarashi

et al. 2016

Med. Phys.

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Purpose: The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging. Methods: This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast. Results: The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts. Conclusions: The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging modalities that involve different positioning and compression of the breast. C 2016 American Association of Physicists in Medicine. [http://dx

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“…Applications included predicting mechanical deformations during biopsy procedures [2]; modelling compressions similar to X-ray mammography [21], [32], [52]; registration of magnetic resonance (MR) and X-ray mammograms [29]; validating a nonrigid registration of contrast-enhanced MR mammograms [35]; testing reconstruction algorithms in elastography [31], [38], [47]; and forward modelling for elastography [48].…”

Section: A Mr Derived Fe Model Of Breast Compressionmentioning

confidence: 99%

A New Validation Method for X-ray Mammogram Registration Algorithms Using a Projection Model of Breast X-ray Compression

Hipwell

Tanner

Crum

et al. 2007

IEEE Trans. Med. Imaging

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Abstract-Establishing spatial correspondence between features visible in X-ray mammograms obtained at different times has great potential to aid assessment and quantitation of change in the breast indicative of malignancy. The literature contains numerous nonrigid registration algorithms developed for this purpose, but existing approaches are flawed by the assumption of inappropriate 2-D transformation models and quantitative estimation of registration accuracy is limited. In this paper, we describe a novel validation method which simulates plausible mammographic compressions of the breast using a magnetic resonance imaging (MRI) derived finite element model. By projecting the resulting known 3-D displacements into 2-D and generating pseudo-mammograms from these same compressed magnetic resonance (MR) volumes, we can generate convincing images with known 2-D displacements with which to validate a registration algorithm. We illustrate this approach by computing the accuracy for two conventional nonrigid 2-D registration algorithms applied to mammographic test images generated from three patient MR datasets. We show that the accuracy of these algorithms is close to the best achievable using a 2-D one-to-one correspondence model but that new algorithms incorporating more representative transformation models are required to achieve sufficiently accurate registrations for this application.

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A finite element model of the breast for predicting mechanical deformations during biopsy procedures

Cited by 69 publications

References 19 publications

Methods for Modeling and Predicting Mechanical Deformations of the Breast Under External Perturbations

Methods for Modeling and Predicting Mechanical Deformations of the Breast Under External Perturbations

Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation

A New Validation Method for X-ray Mammogram Registration Algorithms Using a Projection Model of Breast X-ray Compression

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