Abstract:
Tumours generally involve high rates of metabolic
heat generation and blood perfusion. In this paper, we present an
inverse method involving the differential evolution algorithm for
predicting the blood perfusion rate from the knowledge of
transient temperature response of the skin. The interesting aspect
of this work is to demonstrate that mere prediction of blood
perfusion rate can characterize a tumorous tissue without any
prior knowledge of the rate of metabolic heat generation. This is
done by the incorporation of the initial temperature in the
governing forward method itself and eliminating the metabolic
heat generation from the pertinent expressions. Due to the nonhomogenous nature of biological tissues, the thermal relaxation
time of such systems is considerably higher than other materials.
Thus, unlike conventionally-studied Pennes bioheat transfer
model, the present study addresses a non-Fourier heat
conduction-based bioheat transfer model. The effect of random
noise is also accounted in the present study and it is finally
observed that the present work satisfactorily deciphers the
malignant melanoma and other related subsurface abnormalities
using a non-invasive inverse method aided by the skin’s transient
thermal signatures.
