Ultrasound estimation of breast tissue biomechanical properties using a similarity-based non-linear optimization approach

Abstract

The in vivo estimation of tissue elasticity parameters is important for realistic tissue deformation modelling and diagnosis tasks such as cancer mass detection and characterization. Elastography (strain imaging) provides non-quantitative information about tissue stiffness and is becoming well established clinically. Acoustic radiation force imaging, supersonic shear wave imaging and (Young's) modulus imaging are all evolving as quantitative methods. This paper concerns the latter. The established approach to Young's modulus reconstruction involves solving the so-called inverse elasticity problem of recovering elastic parameters by comparing the displacement field from the measurements and the theoretical tissue deformation modelling. In this paper, a new modulus imaging pathway is proposed in which the inverse problem of elasticity reconstruction has been converted into a global optimization problem involving an image similarity measure. This approach is applied to ultrasound images and the tissue elasticity distribution is recovered by adaptively adding new regions based on the local mismatch of the images using a multiscaled split-and-merge approach. For this experimental evaluation of the performance of the proposed method, first synthetic images are used with different Gaussian noise levels. The reconstructed elasticity shows good agreement with the ground-truth. A comparison of the proposed method with a conventional displacement-based method is made using a gelatine phantom. The results using both methods agree remarkably well with the theoretical prediction. A further in vivo study on 19 breast cancer masses was performed. The present method estimated an elasticity contrast of 6.41 ¡ 0.98 between cancerous tissue and normal tissue, which is consistent with values reported elsewhere in the literature.

Near-Infrared Optical Mammography for Breast Cancer Detection with Intrinsic Contrast

“…Breast cancer is also typically stiffer than normal tissue; Young’s modulus values of ~3 kPa for normal breast tissue and 10–42 kPa for different breast cancers have been measured ex vivo , 44 and a cancer-to-normal tissue elasticity contrast of ~6.4 has been reported in vivo . 33 This contrast in the IFP and in the mechanical properties of cancerous tissue can affect cancer hemodynamics both at baseline and in response to physiological challenges or externally applied mechanical perturbations to the tissue.…”

Anisotropic behaviour of human gallbladder walls

“…Young's modulus (Guo et al 2010) or a general linear elasticity tensor (Raghupathy and Barocas 2010), can be determined directly from the force equilibrium equation iteratively (Moulton et al 1995;Govindjee and Mihalic 1998;Kauer et al 2002;Seshaiyer and Humphrey 2003;Bosisio et al 2007;Lei and Szeri 2007;Samani and Plewes 2007;Gokhale et al 2008;Karimi et al 2008;Li et al 2009;Balocco et al 2010;Kroon 2010). …”

Development of an Anthropomorphic Breast Phantom for Combined PET, B-Mode Ultrasound and Elastographic Imaging

“…This is due to the shadow of the hard tissue above it. This is shows in static elastography that the strain seems to be higher between two hard lesions, but in fact it is caused by mechanical artifact by former studies [26], [29]. In (c) and (d), the white arrow indicates a small lesion can be easily found by static elastography, while in B-mode image it is hardly to be found.…”

“…7(b) points to a bright, high-strain region between two hard tumours. This seems to indicate the presence of very soft material, while in fact it is a mechanical artifact [26], [29] when compared with Fig. 7(a).…”