Quantifying thermal-signature equivalence in infrared breast thermography using a modified Pennes bioheat model

Abstract

Infrared breast thermography provides a noninvasive measurement of skin-surface temperature, but the relation between surface thermal patterns and intratumoral physiology is limited by heat diffusion and thermal screening. Here we study a steady-state modified Pennes bioheat model in a two-dimensional multilayer breast-tissue cross-section containing a finite-sized tumor with spatially heterogeneous perfusion. We compare four idealized perfusion patterns: uniform, rim-enhanced, necrotic-core, and anisotropic perfusion. To assess how well these internal differences are preserved at the surface, we compare the full temperature-rise profiles using an $L^2$ distance and define thermal-signature equivalence through an observational tolerance. The results show that distinct perfusion patterns can generate clearly different internal temperature fields, while their surface signatures may become much more similar after propagation through the surrounding tissue. Tests with noisy surface profiles indicate that this equivalence classification is sensitive to the assumed form of profile-level uncertainty. After matching the tumor-averaged perfusion, the radially heterogeneous cases become much closer to the uniform case, whereas the anisotropic case remains more distinguishable because of its directional structure. Increasing tumor depth promotes thermal-signature equivalence, whereas increasing tumor diameter enhances surface distinguishability;a depth--diameter map shows the competition between these two effects. Fat-layer thickness and mild outer-surface deformation modify the surface profiles, but their influence is secondary over the parameter ranges considered here. These results highlight a limitation of static breast thermography: a surface thermal anomaly can be detected without uniquely identifying the underlying intratumoral perfusion structure.