Modeling breast biomechanics for multi‐modal image analysis—successes and challenges

Biomechanical modeling of the breast is a burgeoning research field that has potential uses across a wide range of healthcare applications. This review describes recent developments regarding multi‐modal breast image analysis, and outlines some of the key challenges that researchers face in introducing the models into the clinical arena. Deformable breast models have demonstrated capabilities across a wide range of breast cancer diagnoses and treatments. Specific applications include magnetic resonance (MR) image guided surgery, registration of x‐ray and MR images, and breast reduction/augmentation surgery planning. Challenges lie in improving the fidelity of these models, which are presently simplistic and use many unverified parameters. Specific challenges include characterization of individual‐specific mechanical properties of breast tissues, precise representation of loading and boundary constraints during different clinical procedures, and validation of modeling techniques used to represent key mechanical aspects such as the suspensory Cooper's ligaments. Scientists must also work towards translating their research tools into the clinical setting by developing efficient tools with user‐friendly interactivity. Widespread adoption of such techniques has the potential to significantly reduce the numbers of misdiagnosed breast cancers and enhance surgical planning for patient treatment. Copyright © 2009 John Wiley & Sons, Inc.

[1]  Eriko Tohno,et al.  Current improvements in breast ultrasound, with a special focus on elastography , 2008, Breast cancer.

[2]  D. Vanel,et al.  Normal and pathological breast, the histological basis. , 2005, European journal of radiology.

[3]  J. M. Brady,et al.  Predicting Tumour Location by Modelling the Deformation of the Breast , 2022 .

[4]  David J. Hawkes,et al.  Validation of Volume-Preserving Non-rigid Registration: Application to Contrast-Enhanced MR-Mammography , 2002, MICCAI.

[5]  Stephane Cotin,et al.  A hybrid elastic model for real-time cutting, deformations, and force feedback for surgery training and simulation , 2000, The Visual Computer.

[6]  John B Weaver,et al.  Initial in vivo experience with steady‐state subzone‐based MR elastography of the human breast , 2003, Journal of magnetic resonance imaging : JMRI.

[7]  David Gavaghan,et al.  Predicting Tumour Location by Simulating Large Deformations of the Breast Using a 3D Finite Element Model and Nonlinear Elasticity , 2004, MICCAI.

[8]  Paul Suetens,et al.  Validation of different soft tissue simulation methods for breast augmentation , 2005 .

[9]  Vijay Rajagopal,et al.  Creating individual-specific biomechanical models of the breast for medical image analysis. , 2008, Academic radiology.

[10]  V. Rajagopal,et al.  Finite Element Modelling of Breast Biomechanics: Directly Calculating the Reference State , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  Dimitris N. Metaxas,et al.  A deformable finite element model of the breast for predicting mechanical deformations under external perturbations. , 2001, Academic radiology.

[12]  W. J. Hedley,et al.  Left ventricular mass and volume: fast calculation with guide-point modeling on MR images. , 2000, Radiology.

[13]  Michael Brady,et al.  Mammographic Image Analysis , 1999, Computational Imaging and Vision.

[14]  Michael Brady,et al.  Fusion of contrast-enhanced breast MR and mammographic imaging data , 2003, Medical Image Anal..

[15]  Yasuyo Kita,et al.  Three-dimensional reconstruction of microcalcification clusters from two mammographic views , 2001, IEEE Transactions on Medical Imaging.

[16]  David Gavaghan,et al.  Predicting Tumor Location by Modeling the Deformation of the Breast , 2008, IEEE Transactions on Biomedical Engineering.

[17]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[18]  G. Adam,et al.  Menstrual-Cycle Dependence of Breast Parenchyma Elasticity: Estimation With Magnetic Resonance Elastography of Breast Tissue During the Menstrual Cycle , 2003, Investigative radiology.

[19]  David Atkinson,et al.  On modelling of anisotropic viscoelasticity for soft tissue simulation: Numerical solution and GPU execution , 2009, Medical Image Anal..

[20]  M. Nash,et al.  Determining the finite elasticity reference state from a loaded configuration , 2007 .

[21]  J. Valentin.  Basic anatomical and physiological data for use in radiological protection: reference values , 2002, Annals of the ICRP.

[22]  E. J. M. Korthagen.  Human skin in vivo : Overview of mechanical experiments and imaging techniques , 2003 .

[23]  David J Gavaghan,et al.  Non-linear modelling of breast tissue. , 2007, Mathematical medicine and biology : a journal of the IMA.

[24]  Stanislav Emelianov,et al.  Biophysical Bases of Elasticity Imaging , 1995 .

[25]  Martyn P. Nash,et al.  Modelling the skin-breast tissue interface , 2006 .

[26]  Stephane Cotin,et al.  A hybrid elastic model for real-time cutting, deformations, and force feedback for surgery training and simulation , 1999, Proceedings Computer Animation 1999.

[27]  Abbas Samani,et al.  Measurement of the hyperelastic properties of tissue slices with tumour inclusion. , 2008, Physics in medicine and biology.

[28]  Kristina Bliznakova,et al.  A novel simulation algorithm for soft tissue compression , 2007, Medical & Biological Engineering & Computing.

[29]  R Marks,et al.  Evaluation of biomechanical properties of human skin. , 1995, Clinics in dermatology.

[30]  M. Doblaré,et al.  A finite element model to accurately predict real deformations of the breast. , 2008, Medical engineering & physics.

[31]  W. Kaiser,et al.  Model-based registration of X-ray mammograms and MR images of the female breast , 2006, IEEE Transactions on Nuclear Science.

[32]  Radhika Sivaramakrishna.  3D Breast Image Registration — A Review , 2005, Technology in cancer research & treatment.

[33]  Alistair A. Young,et al.  Model tags: direct three-dimensional tracking of heart wall motion from tagged magnetic resonance images , 1999, Medical Image Anal..

[34]  David J. Hawkes,et al.  MR Navigated Breast Surgery: Method and Initial Clinical Experience , 2008, MICCAI.

[35]  David J. Hawkes,et al.  Statistical Deformation Models of Breast Compressions from Biomechanical Simulations , 2008, Digital Mammography / IWDM.

[36]  A. Gefen,et al.  Mechanics of the normal woman's breast. , 2007, Technology and health care : official journal of the European Society for Engineering and Medicine.

[37]  D. Plewes,et al.  Elastic moduli of normal and pathological human breast tissues: an inversion-technique-based investigation of 169 samples , 2007, Physics in medicine and biology.

[38]  C. Berman,et al.  Recent advances in breast-specific imaging. , 2007, Cancer control : journal of the Moffitt Cancer Center.

[39]  Abbas Samani,et al.  A method to measure the hyperelastic parameters of ex vivo breast tissue samples. , 2004, Physics in medicine and biology.

[40]  Paul Suetens,et al.  Simulation of Soft-Tissue Deformations for Breast Augmentation Planning , 2006, ISBMS.

[41]  Paul Suetens,et al.  Biomechanically Based Elastic Breast Registration Using Mass Tensor Simulation , 2006, MICCAI.

[42]  S. Wurdinger,et al.  Comparison of written reports of mammography, sonography and magnetic resonance mammography for preoperative evaluation of breast lesions, with special emphasis on magnetic resonance mammography , 2000, Breast Cancer Research.

[43]  Michael Burcher,et al.  A novel ultrasound indentation system for measuring biomechanical properties of in vivo soft tissue. , 2003, Ultrasound in medicine & biology.

[44]  R. Howe,et al.  Breast Tissue Stiffness in Compression is Correlated to Histological Diagnosis , 1999 .

[45]  Martyn P. Nash,et al.  Modelling Mammographic Compression of the Breast , 2008, MICCAI.

[46]  T. Krouskop,et al.  Elastic Moduli of Breast and Prostate Tissues under Compression , 1998, Ultrasonic imaging.

[47]  Michael Brady,et al.  A CAD System for 3D Locating of Lesions in Mammogram , 2001, MICCAI.

[48]  Martin J. Yaffe,et al.  Biomechanical 3-D finite element modeling of the human breast using MRI data , 2001, IEEE Transactions on Medical Imaging.

[49]  Torsten Rohlfing,et al.  Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint , 2003, IEEE Transactions on Medical Imaging.

[50]  Dmitry B. Goldgof,et al.  3D Finite Element Modeling of Nonrigid Breast Deformation for Feature Registration in -ray and MR Images , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).

[51]  Ralph Highnam,et al.  The Breast Biomechanics Reference State for Multi-modal Image Analysis , 2008, Digital Mammography / IWDM.

[52]  J. Schnabel,et al.  Factors influencing the accuracy of biomechanical breast models. , 2006, Medical physics.

[53]  Benoit M. Dawant,et al.  Non-rigid registration of medical images: purpose and methods, a short survey , 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

[54]  Michael Brady,et al.  Correspondence between different view breast X-rays using a simulation of breast deformation , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).