A Deformable Finite Element Model of the Breast for Predicting Mechanical Deformations under External Perturbations

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

doi:10.1016/s1076-6332(03)80640-2

Cited by 126 publications

(107 citation statements)

References 14 publications

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“…Previous work on soft tissue modelling has been applied to the breast [5][6][7][8][9], the heart [10][11][12] and the liver [18]. All of these authors use the finite element method to solve the governing equations although, as full details of the scheme used are sometimes not given, it is not always possible to comment on the suitability of the scheme used.…”

Section: Numerical Methods For Soft Tissue Modellingmentioning

confidence: 99%

“…Schnabel et al [9] used linear elasticity to approximate the displacement of breast tissue. Azar et al [5,13] model the whole displacement as consisting of a large number of tiny displacements that are computed using linear elasticity, this approach allows an exponential stress -strain relationship to be built into the model. Samani et al [6] and Liu et al [7] used non-linear elasticity when computing displacements, allowing more general stress -strain relationships to be built into the model.…”

Section: Numerical Methods For Soft Tissue Modellingmentioning

confidence: 99%

See 1 more Smart Citation

The Solution of Inverse Non‐Linear Elasticity Problems That Arise When Locating Breast Tumours

Whiteley

2005

Computational and Mathematical Methods in Medicine

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Non-linear elasticity theory may be used to calculate the coordinates of a deformed body when the coordinates of the undeformed, stress-free body are known. In some situations, such as one of the steps in the location of tumours in a breast, the coordinates of the deformed body are known and the coordinates of the undeformed body are to be calculated, i.e. we require the solution of the inverse problem. Other than for situations where classical linear elasticity theory may be applied, the simple approach for solving the inverse problem of reversing the direction of gravity and modelling the deformed body as an undeformed body does not give the correct solution. In this study, we derive equations that may be used to solve inverse problems. The solution of these equations may be used for a wide range of inverse problems in non-linear elasticity.

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Section: Numerical Methods For Soft Tissue Modellingmentioning

confidence: 99%

Section: Numerical Methods For Soft Tissue Modellingmentioning

confidence: 99%

The Solution of Inverse Non‐Linear Elasticity Problems That Arise When Locating Breast Tumours

Whiteley

2005

Computational and Mathematical Methods in Medicine

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“…A detailed description of the derivation of this equation can be found in [3]. Finally, a faster time-convergence algorithm employing an Euler method with adaptive step sizing is used.…”

Section: Methodsmentioning

confidence: 99%

“…We tracked the displacement of a small cyst and of two vitamin E pills taped to the superior and inferior parts of the breast. We also tested the model through a convergence analysis and a sensitivity analysis (in which the material parameters were varied over a physiologically relevant range, within two standard deviations of their experimentally derived average value) [3].…”

Section: Testing the Model And Its Performance On A Patientmentioning

confidence: 99%

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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“…However, sensorless planning based on preoperatively predicting the effects of tissue deformations must be used when real-time sensor data is not available or unreliable. In [5], a piece-wise nonlinear FEM model was used to track the position of a tumor during breast compression before a breast cancer biopsy. However, we are not aware of past work explicitly simulating needle insertion and the resulting tissue deformations to plan needle procedures without real-time sensor input.…”

Section: Related Workmentioning

confidence: 99%

Sensorless planning for medical needle insertion procedures

Alterovitz¹,

Goldberg²,

Pouliot

et al.

Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453)

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− Medical procedures such as seed implantation, biopsies, and treatment injections require inserting a needle tip to a specific target location inside the human body. This is difficult because (1) needle insertion causes soft tissues to displace and deform, and (2) it is often difficult or impossible to obtain precise imaging data during insertion. We are developing a sensorless planning system for needle insertion that incorporates numerical optimization with a soft tissue simulation based on a dynamic FEM formulation that models the effects of needle tip and frictional forces using a 2D mesh. In this paper we describe a sensorless planning algorithm for radioactive seed implantation that computes needle insertion offsets that compensate for tissue deformations. We apply the method to seed implantation during permanent seed prostate brachytherapy to minimize seed placement error in simulation without relying on real-time imaging.

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A Deformable Finite Element Model of the Breast for Predicting Mechanical Deformations under External Perturbations

Cited by 126 publications

References 14 publications

The Solution of Inverse Non‐Linear Elasticity Problems That Arise When Locating Breast Tumours

The Solution of Inverse Non‐Linear Elasticity Problems That Arise When Locating Breast Tumours

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

Sensorless planning for medical needle insertion procedures

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