Tumor parameter estimation by steady-state and transient thermal analysis of semi-circular breast model with four density compositions

Abstract

Breast thermography is an adjunct screening tool to mammography in early cancer detection due to its non-invasiveness. The sensitivity of static and dynamic thermography for different breast compositions can be improved by performing Pennes' Bioheat Transfer based simulation. This study shows the effectiveness of numerical simulation in measuring the thermal profile of small-sized and deep tumors in the 2D breast model. Thickness/Dimensions in six tissue layers are inversely calculated for four density compositions, extremely dense (ED), heterogeneously dense (HD), scattered fibro glandular (SF) and predominantly fatty (PF). Steady state and transient studies are performed by varying tumor depth and radius of tumor from 20 mm to 60 mm and 2.5mm to 7.5 mm, respectively. Simulation results show that breast densities play a crucial role in static and dynamic thermography based cancer diagnosis. Transient analysis is performed by measuring surface temperature distribution during cooling and thermal recovery as a function of time.