Optically tunable gold nanoparticles have been widely used in research with near-infrared light as a means to enhance laser-induced thermal therapy since it capitalizes on nanoparticles' plasmonic heating properties. There have been several studies published on numerical models replicating this therapy in such conditions. However, there are several limitations on some of the models which can render the model unfaithful to therapy simulations. In this paper, two techniques of simulating laser-induced thermal therapy with a high-absorbing localized region of interest inside a phantom are compared. To validate these models, we conducted an experiment of an agar-agar phantom with an inclusion reproducing it with both models. The phantom was optically characterized by absorption and total attenuation. The first model is based on the macroperspective solution of the radiative transfer equation given by the diffusion equation, which is then coupled with the Pennes bioheat equation to obtain the temperature. The second is a Monte Carlo model that considers a stochastic solution of the same equation and is also considered as input to the Pennes bioheat transfer equation which is then computed. The Monte Carlo is in good agreement with the experimental data having an average percentage difference of 4.5% and a correlation factor of 0.98, while the diffusion method comparison with experimental data is 61% and 0.95 respectively. The optical characterization of the phantom and its inclusion were also validated indirectly since the Monte Carlo, which used those parameters, was also validated. While knowing the temperature in all points inside a body during photothermal therapy is important, one has to be mindful of the model which fits the conditions and properties. There are several reasons to justify the discrepancy of the diffusion method: low-scattering conditions, absorption, and reduced scattering are comparable. The error bars that are normally associated when characterizing an optical phantom can justify also a part of that uncertainty. For low-size tumors in depth, one may have to increase the light dosage in photothermal therapies to have a more effective treatment.
Keywords: Diffusion approximation; Monte Carlo; Near-infrared light; Phototherapy; Photothermal therapy.