Effects of skin surface roughness on the passive and active thermographic detection of melanoma: A numerical analysis

Abstract

Infrared thermography, while promising as a non-invasive melanoma detection has not been adopted clinically. This is because the thermal signal induced by early stage melanoma is of the same magnitude as those induced by skin surface roughness. This causes the apparent skin temperature variation that can diminish the tumour signal. To investigate this, computational models of the human skin with four different surface roughness, $R_a$ = 0, 5.0 ± 0.1, 10.3 ± 0.2 and 15.6$\pm 0.3\mu m$, were constructed. Heat transfer across the skin was described using bioheat transfer. Simulations were carried out for passive thermography (PT) and dynamic thermal imaging (DT). Numerical results indicated that both PT and DT were capable of detecting the presence of T1 to T4 melanoma if the skin surface roughness within the field-of-view (FOV) of the thermal camera is uniform. However, if differences in surface roughness exist within the FOV, the roughness-induced thermal fluctuations were 2 and 1.33 times larger than those induced by T1 and T2 melanoma, respectively. With DT, the parameters quantifying the difference in the thermal recovery curves (TRCs) between two healthy regions of interest with different surface roughness were significantly greater than those caused by the presence of T1 and T2 melanoma. The results suggest that skin surface roughness can diminish the thermal signal from T1 and T2 melanoma during infrared thermography, leading to false-negative detection. Future studies should explore incorporating surface roughness identification as part of the protocol for thermographic melanoma detection.