Algoritmo de controle do dano ao tecido saudável no tratamento de câncer por hipertermia

Abstract

According to the World Health Organization, cancer is a global health concern. The high mortality rate drives the scientific community to study new treatments, among which we can mention hyperthermia by magnetic nanoparticles. This treatment involves subjecting the target region to a low-frequency magnetic field, causing the nanoparticles to increase the temperature above 43◦C, considered the target temperature to damage the tissue and induce cell necrosis. This work uses the three-dimensional in silico model of Pennes, described by a partial differential equation (PDE), to estimate the percentage of tissue damage due to hyperthermia treatment. Differential evolution is used to optimize the treatment, suggesting the best locations for injecting magnetic nanoparticles to maximize the damage to tumor cells and minimize harm to healthy tissue. Tests were performed considering two- and three-dimensional domains, and for each one, three scenarios were considered to evaluate the suggestions obtained by the optimization method. The results indicate that the proposed technique is promising: a reduction in the percentage of damage to healthy tissue while keeping the complete damage to the tumor tissue were observed. Considering the three-dimensional domain in its most complex scenario, the optimization process was responsible for reducing the damage to healthy tissue by 59% when the nanoparticle injections are positioned in a non-intuitive location, i.e., different from the center of the tumors. The numerical solution of the PDE combined with differential evolution increases the computational effort required for algorithm execution. Due to this factor, a parallel strategy using CUDA architecture was implemented to solve the PDE at a lower cost using NVIDIA GPUs. Comparing the parallel version of the code with its sequential version executed in a single CPU, an 84.4-fold performance gain was observed.