Optimization of skin cooling by computational modeling for early thermographic detection of breast cancer

Abstract The purpose of this study is to enhance the early detection of breast cancer using dynamic infrared (IR) imaging by optimizing thermostimulation with cooling stress to improve thermal contrast. A 2D hemispherical breast model was built to compute steady-state and transient surface temperature profiles for tumors of different size (10–30 mm), depth (6.6–26.6 mm) and location (15°–90°). Larger tumors and tumors closer to the skin surface leave sufficiently large thermal signatures (∼0.6 °C) to be detected by steady state IR imaging. Smaller and deeper tumors in the middle and bottom portion of the gland, with thermal contrasts below 0.1 °C, require dynamic imaging with thermostimulation (cooling) to achieve satisfactory thermal contrast for IR detection. In this paper, we consider cooling times of 15–25 min and cooling temperatures of 5–15 °C to optimize thermal contrast. Cooling penetration depths during the cooling phase for constant temperature cooling at 5 °C, 10 °C and 15 °C were analyzed. To achieve the maximum thermal contrast for deeper and smaller tumors, the tissue should be cooled 5–15 min, and in the maximum thermal contrast of the thermal recovery phase appears after 20–45 min. Effects of tumor size and depth on maximum thermal contrast were analyzed systematically to provide recommendations and guidelines for clinical applications. Thermal signatures computed in this study provide valuable data for inverse reconstruction algorithms that allow the measurement of tumor properties, such as the metabolic heat generation rate.