A constrained reconstruction technique of hyperelasticity parameters for breast cancer assessment

Abstract

In breast elastography, breast tissue usually undergoes large compression resulting in significant geometric and structural changes. This implies that breast elastography is associated with tissue nonlinear behavior. In this study, an elastography technique is presented and an inverse problem formulation is proposed to reconstruct parameters characterizing tissue hyperelasticity. Such parameters can potentially be used for tumor classification. This technique can also have other important clinical applications such as measuring normal tissue hyperelastic parameters in vivo. Such parameters are essential in planning and conducting computer-aided interventional procedures. The proposed parameter reconstruction technique uses a constrained iterative inversion; it can be viewed as an inverse problem. To solve this problem, we used a nonlinear finite element model corresponding to its forward problem. In this research, we applied Veronda-Westmann, Yeoh and polynomial models to model tissue hyperelasticity. To validate the proposed technique, we conducted studies involving numerical and tissue-mimicking phantoms. The numerical phantom consisted of a hemisphere connected to a cylinder, while we constructed the tissue-mimicking phantom from polyvinyl alcohol with freeze-thaw cycles that exhibits nonlinear mechanical behavior. Both phantoms consisted of three types of soft tissues which mimic adipose, fibroglandular tissue and a tumor. The results of the simulations and experiments show feasibility of accurate reconstruction of tumor tissue hyperelastic parameters using the proposed method. In the numerical phantom, all hyperelastic parameters corresponding to the three models were reconstructed with less than 2% error. With the tissue-mimicking phantom, we were able to reconstruct the ratio of the hyperelastic parameters reasonably accurately. Compared to the uniaxial test results, the average error of the ratios of the parameters reconstructed for inclusion to the middle and external layers were 13% and 9.6%, respectively. Given that the parameter ratios of the abnormal tissues to the normal ones range from three times to more than ten times, this accuracy is sufficient for tumor classification.

Development of array piezoelectric fingers towards in vivo breast tumor detection

“…45 as well as in this study (not shown). In addition, these choices were consistent with the E values of normal breast tissues and those of breast tumors reported in the literature, which were 3-33 kPa and 6-107 kPa, respectively [35][36][37][62][63][64] as shown in Table SI in the supplementary material. The diameters of model tumors were 11.5 ± 0.3 mm, 10.3 ± 0.3 mm, 7.8 ± 0.2 mm, and 6.2 ± 0.2 mm, respectively.…”

Automated palpation for breast tissue discrimination based on viscoelastic biomechanical properties

“…Since the 2000s, this focus has shifted to parameters that express the nonlinear material behavior of biological tissues, such as nonlinear elasticity, hyperelasticity and viscoelasticity. Some researchers [6], including Hall et al [7] and Mehrabian et al [8,9], have applied ultrasound and finite element inverse analysis to determine the elastic nonlinearity under large strains (around 10 % axial strain). Additionally, many researchers have reported dynamic multifrequency elastography for viscoelastic imaging using MRI and external oscillation devices [10][11][12].…”

A New Energy Inversion for Parameter Identification in Saddle Point Problems with an Application to the Elasticity Imaging Inverse Problem of Predicting Tumor Location

“…By separating these scales, they reported a local and precise reconstruction. For other interesting aspects of the problem, see also [1,4,7,11,23,27,32]. All the above works, deal with the static approach.…”

“…is a sequence of solutions to the discrete optimization problem (32). Then every subsequence of * h has a convergent subsequence with limit point as a solution to the minimization problem (30).…”