Implementation of a Breast Phantom with Acoustic Properties for Ultrasonic Thermometry

Abstract

Breast cancer remains one of the leading causes of death among women globally. Early detection is critical for improving patient outcomes, making the development of accurate and efficient detection methods essential for facilitating timely treatment and enhancing patients’ quality of life. Lesion sites are often associated with localized temperature increases, which can be identified by characterizing thermal gradients using thermometry tools. Ultrasound-based techniques are preferred for obtaining thermal patterns due to their noninvasive, non-ionizing nature and cost-effectiveness compared to methods like magnetic resonance imaging. This study focuses on developing breast tissue models with varying acoustic properties, specifically the speed of sound across temperatures ranging from 32 °C to 36 °C in increments of 0.5 °C for ultrasonic inspection and diagnostic applications. These models simulate healthy and tumorous breast tissue, including the fat, gland, and tumor layers. Signal variations were analyzed using cross-correlation methods to assess the changes in the speed of sound as a function of temperature. The proposed methodology offers a cost-effective, rapid, and precise approach to phantom production, facilitating the detection of temperature changes in 0.5 °C intervals through cross-correlation analysis of the acquired signals.