Ultrasonic Measurement of Temperature Rise in Breast Cyst and in Neighbouring Tissues as a Method of Tissue Differentiation

Abstract

Texture of ultrasound images contain information about the properties of examined tissues. The analysis of statistical properties of backscattered ultrasonic echoes has been recently successfully applied to differentiate healthy breast tissue from the benign and malignant lesions. We propose a novel procedure of tissue characterization based on acquiring backscattered echoes from the heated breast. We have proved that the temperature increase inside the breast modifies the intensity, spectrum of the backscattered signals and the probability density function of envelope samples. We discuss the differences in probability density functions in two types of tissue regions, e.g. cysts and the surrounding glandular tissue regions. Independently, Pennes bioheat equation in heterogeneous breast tissue was used to describe the heating process. We applied the finite element method to solve this equation. Results have been compared with the ultrasonic predictions of the temperature distribution. The results confirm the possibility of distinguishing the differences in thermal and acoustical properties of breast cyst and surrounding glandular tissues.

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“…The parameters of the : Specific heat of blood Although the Pennes equation is not perfect (Weinbaum et al, 1984), due to its compatibility with analytical implementation, it is widely preferred and used for thermal model of living tissue. Due to the imperfect Pennes equation, new methods of tissue characterization have been investigated (Gambin et al, 2016), one of which is based on backscattered echoes of heated breast and integrated with statistical analysis techniques. It has been demonstrated that an increase in breast temperature modifies three parameters of the samples: "the intensity, the spectrum of echo signals and the probability density functions" (Gambin et al, 2016).…”

“…Due to the imperfect Pennes equation, new methods of tissue characterization have been investigated (Gambin et al, 2016), one of which is based on backscattered echoes of heated breast and integrated with statistical analysis techniques. It has been demonstrated that an increase in breast temperature modifies three parameters of the samples: "the intensity, the spectrum of echo signals and the probability density functions" (Gambin et al, 2016).…”

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“…Existing models of ultrasound scattering allow obtaining numerical parameters describing the number of scatterers and their spatial distribution from the information contained in the characteristics of the enveloping echo signal. The work [17] describes the characteristics of the most commonly used mod els of ultrasound scattering. The simplest scattering model is a discrete model, in which a wave propagates in a homogeneous medium with inclusions whose properties depend on the properties of this medium.…”

“…The Kdistribution models the case when the number of scatterers is itself a random variable, which is modeled as a Poisson distribution, the local mean of which is a gamma dis tribution [20]. The Kdistribution is formed by joining two separate probability distributions [17]. The model used to rep resent the observed intensity X involves the union of two gam ma distributions.…”

“…The shape parameters of the Kdistribution and the Na kagami distribution are directly related to the effective num ber of scatterers. The shape parameter of the gamma distri bution also depends on the density of scatterers, but not lin early [17].…”