Avanços no tratamento do Glioblastoma Multiforme via Tumor Treating Fields: desenvolvimento de um banco de dados otimizado de simulações usando o SimNIB

Abstract

The Glioblastoma Multiforme (GBM) is an aggressive brain cancer with a low survival rate. Non-invasive brain stimulation is a promising approach for treating GBM, but there is still much to be learned about its effectiveness and safety. Based on research from the early 2000s on the application of electromagnetic fields in the treatment of GBM, this dissertation proposes the development of an optimized database of simulations using SimNIBS. SimNIBS was designed to simulate electrical stimulation in the brain and can generate simulations using code in the Python language. The research explored the effectiveness of Transcranial Electrical Direct Current Stimulation (tDCS) and Alternating Current Stimulation (tACS), the latter focused on the treatment of GBM. The results highlight the influence of electrode configuration on the distribution of electrical stimulation and the penetration of the electric field into brain tissue. The data obtained indicates the need for adjustments in the current applied in tDCS and recommends specific electrode configurations to optimize GBM treatment. Ultimately, this analysis is expected to contribute to a better understanding of neuromodulation in the context of GBM. The results suggest that tACS may be an effective option for treating GBM, but additional research is needed to validate the results and determine the long-term safety of the therapy.